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value="clinpract" > Clinics and Practice </option> <option value="clockssleep" > Clocks & Sleep </option> <option value="coasts" > Coasts </option> <option value="coatings" > Coatings </option> <option value="colloids" > Colloids and Interfaces </option> <option value="colorants" > Colorants </option> <option value="commodities" > Commodities </option> <option value="complications" > Complications </option> <option value="compounds" > Compounds </option> <option value="computation" > Computation </option> <option value="csmf" > Computer Sciences & Mathematics Forum </option> <option value="computers" > Computers </option> <option value="condensedmatter" > Condensed Matter </option> <option value="conservation" > Conservation </option> <option value="constrmater" > Construction Materials </option> <option value="cmd" > Corrosion and Materials Degradation (CMD) </option> <option value="cosmetics" > Cosmetics </option> <option value="covid" > COVID </option> <option value="crops" > Crops </option> <option value="cryo" > Cryo </option> <option value="cryptography" > Cryptography </option> <option value="crystals" > Crystals </option> <option value="cimb" > Current Issues in Molecular Biology (CIMB) </option> <option value="curroncol" > Current Oncology </option> <option value="dairy" > Dairy </option> <option value="data" > Data </option> <option value="dentistry" > Dentistry Journal </option> <option value="dermato" > Dermato </option> <option value="dermatopathology" > Dermatopathology </option> <option value="designs" > Designs </option> <option value="diabetology" > Diabetology </option> <option value="diagnostics" > Diagnostics </option> <option value="dietetics" > Dietetics </option> <option value="digital" > Digital </option> <option value="disabilities" > Disabilities </option> <option value="diseases" > Diseases </option> <option value="diversity" > Diversity </option> <option value="dna" > DNA </option> <option value="drones" > Drones </option> <option value="ddc" > Drugs and Drug Candidates (DDC) </option> <option value="dynamics" > Dynamics </option> <option value="earth" > Earth </option> <option value="ecologies" > Ecologies </option> <option value="econometrics" > Econometrics </option> <option value="economies" > Economies </option> <option value="education" > Education Sciences </option> <option value="electricity" > Electricity </option> <option value="electrochem" > Electrochem </option> <option value="electronicmat" > Electronic Materials </option> <option value="electronics" > Electronics </option> <option value="ecm" > Emergency Care and Medicine </option> <option value="encyclopedia" > Encyclopedia </option> <option value="endocrines" > Endocrines </option> <option value="energies" > Energies </option> <option value="esa" > Energy Storage and Applications (ESA) </option> <option value="eng" > Eng </option> <option value="engproc" > Engineering Proceedings </option> <option value="entropy" > Entropy </option> <option value="environsciproc" > Environmental Sciences Proceedings </option> <option value="environments" > Environments </option> <option value="epidemiologia" > Epidemiologia </option> <option value="epigenomes" > Epigenomes </option> <option value="ebj" > European Burn Journal (EBJ) </option> <option value="ejihpe" > European Journal of Investigation in Health, Psychology and Education (EJIHPE) </option> <option value="fermentation" > Fermentation </option> <option value="fibers" > Fibers </option> <option value="fintech" > FinTech </option> <option value="fire" > Fire </option> <option value="fishes" > Fishes </option> <option value="fluids" > Fluids </option> <option value="foods" > Foods </option> <option value="forecasting" > Forecasting </option> <option value="forensicsci" > Forensic Sciences </option> <option value="forests" > Forests </option> <option value="fossstud" > Fossil Studies </option> <option value="foundations" > Foundations </option> <option value="fractalfract" > Fractal and Fractional (Fractal Fract) </option> <option value="fuels" > Fuels </option> <option value="future" > Future </option> <option value="futureinternet" > Future Internet </option> <option value="futurepharmacol" > Future Pharmacology </option> <option value="futuretransp" > Future Transportation </option> <option value="galaxies" > Galaxies </option> <option value="games" > Games </option> <option value="gases" > Gases </option> <option value="gastroent" > Gastroenterology Insights </option> <option value="gastrointestdisord" > Gastrointestinal Disorders </option> <option value="gastronomy" > Gastronomy </option> <option value="gels" > Gels </option> <option value="genealogy" > Genealogy </option> <option value="genes" > Genes </option> <option value="geographies" > Geographies </option> <option value="geohazards" > GeoHazards </option> <option value="geomatics" > Geomatics </option> <option value="geometry" > Geometry </option> <option value="geosciences" > Geosciences </option> <option value="geotechnics" > Geotechnics </option> <option value="geriatrics" > Geriatrics </option> <option value="glacies" > Glacies </option> <option value="gucdd" > Gout, Urate, and Crystal Deposition Disease (GUCDD) </option> <option value="grasses" > Grasses </option> <option value="hardware" > Hardware </option> <option value="healthcare" > Healthcare </option> <option value="hearts" > Hearts </option> <option value="hemato" > Hemato </option> <option value="hematolrep" > Hematology Reports </option> <option value="heritage" > Heritage </option> <option value="histories" > Histories </option> <option value="horticulturae" > Horticulturae </option> <option value="hospitals" > Hospitals </option> <option value="humanities" > Humanities </option> <option value="humans" > Humans </option> <option value="hydrobiology" > Hydrobiology </option> <option value="hydrogen" > Hydrogen </option> <option value="hydrology" > Hydrology </option> <option value="hygiene" > Hygiene </option> <option value="immuno" > Immuno </option> <option value="idr" > Infectious Disease Reports </option> <option value="informatics" > Informatics </option> <option value="information" > Information </option> <option value="infrastructures" > Infrastructures </option> <option value="inorganics" > Inorganics </option> <option value="insects" > Insects </option> <option value="instruments" > Instruments </option> <option value="iic" > Intelligent Infrastructure and Construction </option> <option value="ijerph" > International Journal of Environmental Research and Public Health (IJERPH) </option> <option value="ijfs" > International Journal of Financial Studies (IJFS) </option> <option value="ijms" > International Journal of Molecular Sciences (IJMS) </option> <option value="IJNS" > International Journal of Neonatal Screening (IJNS) </option> <option value="ijpb" > International Journal of Plant Biology (IJPB) </option> <option value="ijt" > International Journal of Topology 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Compos. Sci.) </option> <option value="jcp" > Journal of Cybersecurity and Privacy (JCP) </option> <option value="jdad" > Journal of Dementia and Alzheimer's Disease (JDAD) </option> <option value="jdb" > Journal of Developmental Biology (JDB) </option> <option value="jeta" > Journal of Experimental and Theoretical Analyses (JETA) </option> <option value="jfb" > Journal of Functional Biomaterials (JFB) </option> <option value="jfmk" > Journal of Functional Morphology and Kinesiology (JFMK) </option> <option value="jof" > Journal of Fungi (JoF) </option> <option value="jimaging" > Journal of Imaging (J. Imaging) </option> <option value="jintelligence" > Journal of Intelligence (J. Intell.) </option> <option value="jlpea" > Journal of Low Power Electronics and Applications (JLPEA) </option> <option value="jmmp" > Journal of Manufacturing and Materials Processing (JMMP) </option> <option value="jmse" > Journal of Marine Science and Engineering (JMSE) </option> <option value="jmahp" > Journal of Market Access & Health Policy (JMAHP) </option> <option value="jmp" > Journal of Molecular Pathology (JMP) </option> <option value="jnt" > Journal of Nanotheranostics (JNT) </option> <option value="jne" > Journal of Nuclear Engineering (JNE) </option> <option value="ohbm" > Journal of Otorhinolaryngology, Hearing and Balance Medicine (JOHBM) </option> <option value="jop" > Journal of Parks </option> <option value="jpm" > Journal of Personalized Medicine (JPM) </option> <option value="jpbi" > Journal of Pharmaceutical and BioTech Industry (JPBI) </option> <option value="jor" > Journal of Respiration (JoR) </option> <option value="jrfm" > Journal of Risk and Financial Management (JRFM) </option> <option value="jsan" > Journal of Sensor and Actuator Networks (JSAN) </option> <option value="joma" > Journal of the Oman Medical Association (JOMA) </option> <option value="jtaer" > Journal of Theoretical and Applied Electronic Commerce Research (JTAER) </option> <option value="jvd" > Journal of Vascular Diseases (JVD) </option> <option value="jox" > Journal of Xenobiotics (JoX) </option> <option value="jzbg" > Journal of Zoological and Botanical Gardens (JZBG) </option> <option value="journalmedia" > Journalism and Media </option> <option value="kidneydial" > Kidney and Dialysis </option> <option value="kinasesphosphatases" > Kinases and Phosphatases </option> <option value="knowledge" > Knowledge </option> <option value="labmed" > LabMed </option> <option value="laboratories" > Laboratories </option> <option value="land" > Land </option> <option value="languages" > Languages </option> <option value="laws" > Laws </option> <option value="life" > Life 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Med.) </option> <option value="resources" > Resources </option> <option value="rheumato" > Rheumato </option> <option value="risks" > Risks </option> <option value="robotics" > Robotics </option> <option value="ruminants" > Ruminants </option> <option value="safety" > Safety </option> <option value="sci" > Sci </option> <option value="scipharm" > Scientia Pharmaceutica (Sci. Pharm.) </option> <option value="sclerosis" > Sclerosis </option> <option value="seeds" > Seeds </option> <option value="sensors" > Sensors </option> <option value="separations" > Separations </option> <option value="sexes" > Sexes </option> <option value="signals" > Signals </option> <option value="sinusitis" > Sinusitis </option> <option value="smartcities" > Smart Cities </option> <option value="socsci" > Social Sciences </option> <option value="siuj" > Société Internationale d’Urologie Journal (SIUJ) </option> <option value="societies" > Societies </option> <option value="software" > Software </option> <option value="soilsystems" > Soil Systems </option> <option value="solar" > Solar </option> <option value="solids" > Solids </option> <option value="spectroscj" > Spectroscopy Journal </option> <option value="sports" > Sports </option> <option value="standards" > Standards </option> <option value="stats" > Stats </option> <option value="stresses" > Stresses </option> <option value="surfaces" > Surfaces </option> <option value="surgeries" > Surgeries </option> <option value="std" > Surgical Techniques Development </option> <option value="sustainability" > Sustainability </option> <option value="suschem" > Sustainable Chemistry </option> <option value="symmetry" > Symmetry </option> <option value="synbio" > SynBio </option> <option value="systems" > Systems </option> <option value="targets" > Targets </option> <option value="taxonomy" > Taxonomy </option> <option value="technologies" > Technologies </option> <option value="telecom" > Telecom </option> <option value="textiles" > Textiles </option> <option value="thalassrep" > Thalassemia Reports </option> <option value="therapeutics" > Therapeutics </option> <option value="thermo" > Thermo </option> <option value="timespace" > Time and Space </option> <option value="tomography" > Tomography </option> <option value="tourismhosp" > Tourism and Hospitality </option> <option value="toxics" > Toxics </option> 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value="women" > Women </option> <option value="world" > World </option> <option value="wevj" > World Electric Vehicle Journal (WEVJ) </option> <option value="youth" > Youth </option> <option value="zoonoticdis" > Zoonotic Diseases </option> </select> </div> <div class="large-2 medium-2 small-6 columns "> <div class=""> <div class="search-input-label">Article Type</div> </div> <select id="article_type" tabindex="4" name="article_type" class="chosen-select"> <option value="">All Article Types</option> <option value="research-article">Article</option> <option value="review-article">Review</option> <option value="rapid-communication">Communication</option> <option value="editorial">Editorial</option> <option value="abstract">Abstract</option> <option value="book-review">Book Review</option> <option value="brief-communication">Brief Communication</option> <option value="brief-report">Brief Report</option> <option value="case-report">Case Report</option> <option 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data-filterid="refine_subjects_engineering"> <i class="material-icons">remove_circle_outline</i> </a> <label> Engineering </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_computer-math"> <i class="material-icons">remove_circle_outline</i> </a> <label> Computer Science & Mathematics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_environment"> <i class="material-icons">remove_circle_outline</i> </a> <label> Environmental & Earth Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_chem-materials"> <i class="material-icons">remove_circle_outline</i> </a> <label> Chemistry & Materials Science </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_physics-astronomy"> <i class="material-icons">remove_circle_outline</i> </a> <label> Physical Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_bio-life"> <i class="material-icons">remove_circle_outline</i> </a> <label> Biology & Life Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_health"> <i class="material-icons">remove_circle_outline</i> </a> <label> Public Health & Healthcare </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_business-econ"> <i class="material-icons">remove_circle_outline</i> </a> <label> Business & Economics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_arts-humanity"> <i class="material-icons">remove_circle_outline</i> </a> <label> Social Sciences, Arts and Humanities </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_subjects_med-pharma"> <i class="material-icons">remove_circle_outline</i> </a> <label> Medicine & Pharmacology </label> </div/> </div> <div class="filter-actions-container filter-actions-container--filled filter-actions-container--hidden"> <a class="js-refine-filter" data-reveal-id="refine-modal-subjects" data-filter="subjects"><strong>Add Subjects</strong></a> <a href="#" class="remove-refines link--red right" data-refineid="subjects"><strong>Reset</strong></a> </div> <div class="filter-actions-container filter-actions-container--empty "> <a class="button button--color button--full-width js-refine-filter" href="#" data-reveal-id="refine-modal-subjects" data-filter="subjects" class="all">Select Subjects</a> </div> <div style="clear:both;"></div> <div id="refine-modal-subjects" class="reveal-modal reveal-modal-new" data-reveal aria-labelledby="modalTitle" aria-hidden="true" role="dialog"> <div class="row"> <div class="small-12 columns"> <h2>Filter Subjects</h2> <input class="js-filter" type="text" form="temp" placeholder="Search for Subjects" style="width: 100%; max-width: 300px;" /> <p class="reveal-modal-new__description"> Select subjects you want to add to your filter. </p> </div> <div class="js-refinement-values-container"> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="engineering" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_engineering" value="engineering"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_engineering">Engineering (342)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="computer science & mathematics" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_computer-math" value="computer-math"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_computer-math">Computer Science & Mathematics (322)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="environmental & earth sciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_environment" value="environment"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_environment">Environmental & Earth Sciences (278)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="chemistry & materials science" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_chem-materials" value="chem-materials"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_chem-materials">Chemistry & Materials Science (226)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="physical sciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_physics-astronomy" value="physics-astronomy"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_physics-astronomy">Physical Sciences (169)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="biology & life sciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_bio-life" value="bio-life"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_bio-life">Biology & Life Sciences (155)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="public health & healthcare" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_health" value="health"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_health">Public Health & Healthcare (54)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="business & economics" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_business-econ" value="business-econ"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_business-econ">Business & Economics (38)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="social sciences, arts and humanities" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_arts-humanity" value="arts-humanity"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_arts-humanity">Social Sciences, Arts and Humanities (37)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="medicine & pharmacology" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_subjects" id="refine_subjects_med-pharma" value="med-pharma"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_subjects_med-pharma">Medicine & Pharmacology (23)</label> </div> </div> </div> </div> <div class="row"> <div class="small-12 columns"> <a class="button button--color js-filter-close" data-itemid="subjects" onclick="$('#refine-modal-subjects').foundation('reveal', 'close'); return false;">Add to Filter</a> <a class="button button--grey" onclick="$(this).closest('.reveal-modal').find('.close-reveal-modal').click(); return false;">Cancel</a> </div> </div> <input type="hidden" name="subjects" id="refine_subjects_field"> <a class="close-reveal-modal" aria-label="Close"> <i class="material-icons">clear</i> </a> </div></div> <div class="generic-item refind-item-wrap filter-container filter-container-journals" style=""> <h3>Journals</h3> <div class="js-refinement-selections-container"> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_applsci"> <i class="material-icons">remove_circle_outline</i> </a> <label> Applied Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_sensors"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sensors </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_electronics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Electronics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_sustainability"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sustainability </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_information"> <i class="material-icons">remove_circle_outline</i> </a> <label> Information </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_mathematics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mathematics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_remotesensing"> <i class="material-icons">remove_circle_outline</i> </a> <label> Remote Sensing </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijgi"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJGI </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_symmetry"> <i class="material-icons">remove_circle_outline</i> </a> <label> Symmetry </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_futureinternet"> <i class="material-icons">remove_circle_outline</i> </a> <label> Future Internet </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_BDCC"> <i class="material-icons">remove_circle_outline</i> </a> <label> BDCC </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_algorithms"> <i class="material-icons">remove_circle_outline</i> </a> <label> Algorithms </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_water"> <i class="material-icons">remove_circle_outline</i> </a> <label> Water </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_energies"> <i class="material-icons">remove_circle_outline</i> </a> <label> Energies </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_machines"> <i class="material-icons">remove_circle_outline</i> </a> <label> Machines </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_buildings"> <i class="material-icons">remove_circle_outline</i> </a> <label> Buildings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_entropy"> <i class="material-icons">remove_circle_outline</i> </a> <label> Entropy </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_computers"> <i class="material-icons">remove_circle_outline</i> </a> <label> Computers </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_informatics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Informatics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijerph"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJERPH </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_diagnostics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Diagnostics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_education"> <i class="material-icons">remove_circle_outline</i> </a> <label> Education Sciences </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_systems"> <i class="material-icons">remove_circle_outline</i> </a> <label> Systems </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_processes"> <i class="material-icons">remove_circle_outline</i> </a> <label> Processes </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_drones"> <i class="material-icons">remove_circle_outline</i> </a> <label> Drones </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_wevj"> <i class="material-icons">remove_circle_outline</i> </a> <label> WEVJ </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_engproc"> <i class="material-icons">remove_circle_outline</i> </a> <label> Engineering Proceedings </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_ijms"> <i class="material-icons">remove_circle_outline</i> </a> <label> IJMS </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_nutrients"> <i class="material-icons">remove_circle_outline</i> </a> <label> Nutrients </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_micromachines"> <i class="material-icons">remove_circle_outline</i> </a> <label> Micromachines </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_genes"> <i class="material-icons">remove_circle_outline</i> </a> <label> Genes </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_animals"> <i class="material-icons">remove_circle_outline</i> </a> <label> Animals </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_jmse"> <i class="material-icons">remove_circle_outline</i> </a> <label> JMSE </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_robotics"> <i class="material-icons">remove_circle_outline</i> </a> <label> Robotics </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_journals_technologies"> <i class="material-icons">remove_circle_outline</i> 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type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_make" value="make"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_make">MAKE (2)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="jtaer" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_jtaer" value="jtaer"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_jtaer">JTAER (2)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="viruses" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_viruses" value="viruses"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_viruses">Viruses (1)</label> </div> </div> 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class="refine_checkbox refine_journals" id="refine_journals_polymers" value="polymers"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_polymers">Polymers (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="cells" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_cells" value="cells"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_cells">Cells (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="land" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_land" value="land"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_land">Land (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="axioms" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_axioms" value="axioms"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_axioms">Axioms (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="life" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_life" value="life"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_life">Life (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="insects" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_insects" value="insects"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_insects">Insects (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="jpm" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_jpm" value="jpm"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_jpm">JPM (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="geosciences" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_geosciences" value="geosciences"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_geosciences">Geosciences (1)</label> </div> </div> <div class="large-6 medium-6 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class="refine_checkbox refine_journals" id="refine_journals_computation" value="computation"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_computation">Computation (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="aerospace" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_aerospace" value="aerospace"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_aerospace">Aerospace (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="children" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_children" value="children"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_children">Children (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="risks" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_risks" value="risks"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_risks">Risks (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="publications" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_publications" value="publications"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_publications">Publications (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="foods" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_foods" value="foods"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_foods">Foods (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="bioengineering" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_bioengineering" value="bioengineering"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_bioengineering">Bioengineering (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="fluids" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_fluids" value="fluids"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_fluids">Fluids (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="horticulturae" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_horticulturae" value="horticulturae"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_horticulturae">Horticulturae (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="batteries" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_batteries" value="batteries"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_batteries">Batteries (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="condensed matter" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_condensedmatter" value="condensedmatter"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_condensedmatter">Condensed Matter (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="designs" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_designs" value="designs"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_designs">Designs (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="mti" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_mti" value="mti"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_mti">MTI (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="mca" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_mca" value="mca"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_mca">MCA (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="asi" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_asi" value="asi"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_asi">ASI (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="world" 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data-filter="physical sciences forum" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_journals" id="refine_journals_psf" value="psf"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_journals_psf">Physical Sciences Forum (1)</label> </div> </div> </div> </div> <div class="row"> <div class="small-12 columns"> <a class="button button--color js-filter-close" data-itemid="journals" onclick="$('#refine-modal-journals').foundation('reveal', 'close'); return false;">Add to Filter</a> <a class="button button--grey" onclick="$(this).closest('.reveal-modal').find('.close-reveal-modal').click(); return false;">Cancel</a> </div> </div> <input type="hidden" name="journals" id="refine_journals_field"> <a class="close-reveal-modal" aria-label="Close"> <i class="material-icons">clear</i> </a> </div></div> <div class="generic-item refind-item-wrap filter-container filter-container-article_types" style=""> <h3>Article Types</h3> <div class="js-refinement-selections-container"> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_research-article"> <i class="material-icons">remove_circle_outline</i> </a> <label> Article </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_review-article"> <i class="material-icons">remove_circle_outline</i> </a> <label> Review </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_systematic_review"> <i class="material-icons">remove_circle_outline</i> </a> <label> Systematic Review </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_proceedings"> <i class="material-icons">remove_circle_outline</i> </a> <label> Proceeding Paper </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_editorial"> <i class="material-icons">remove_circle_outline</i> </a> <label> Editorial </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_rapid-communication"> <i class="material-icons">remove_circle_outline</i> </a> <label> Communication </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_project-report"> <i class="material-icons">remove_circle_outline</i> </a> <label> Project Report </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_article_types_extended-abstract"> <i class="material-icons">remove_circle_outline</i> </a> <label> Extended Abstract </label> </div/> </div> <div class="filter-actions-container filter-actions-container--filled filter-actions-container--hidden"> <a class="js-refine-filter" data-reveal-id="refine-modal-article_types" data-filter="article_types"><strong>Add Article Types</strong></a> <a href="#" class="remove-refines link--red right" data-refineid="article_types"><strong>Reset</strong></a> </div> <div class="filter-actions-container filter-actions-container--empty "> <a class="button button--color button--full-width js-refine-filter" href="#" data-reveal-id="refine-modal-article_types" data-filter="article_types" class="all">Select Article Types</a> </div> <div style="clear:both;"></div> <div id="refine-modal-article_types" class="reveal-modal reveal-modal-new" data-reveal aria-labelledby="modalTitle" aria-hidden="true" role="dialog"> <div class="row"> <div class="small-12 columns"> <h2>Filter Article Types</h2> <input class="js-filter" type="text" form="temp" placeholder="Search for Article Types" style="width: 100%; max-width: 300px;" /> <p class="reveal-modal-new__description"> Select article types you want to add to your filter. </p> </div> <div class="js-refinement-values-container"> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="article" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_research-article" value="research-article"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_research-article">Article (462)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="review" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_review-article" value="review-article"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_review-article">Review (35)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="systematic review" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_systematic_review" value="systematic_review"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_systematic_review">Systematic Review (6)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="proceeding paper" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" 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for="refine_article_types_rapid-communication">Communication (2)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="project report" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_project-report" value="project-report"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_project-report">Project Report (1)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="extended abstract" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_article_types" id="refine_article_types_extended-abstract" value="extended-abstract"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_article_types_extended-abstract">Extended Abstract (1)</label> </div> </div> </div> </div> <div class="row"> <div class="small-12 columns"> <a class="button button--color js-filter-close" data-itemid="article_types" onclick="$('#refine-modal-article_types').foundation('reveal', 'close'); return false;">Add to Filter</a> <a class="button button--grey" onclick="$(this).closest('.reveal-modal').find('.close-reveal-modal').click(); return false;">Cancel</a> </div> </div> <input type="hidden" name="article_types" id="refine_article_types_field"> <a class="close-reveal-modal" aria-label="Close"> <i class="material-icons">clear</i> </a> </div></div> <div class="generic-item refind-item-wrap filter-container filter-container-countries" style=""> <h3>Countries / Regions</h3> <div class="js-refinement-selections-container"> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CHINA"> <i class="material-icons">remove_circle_outline</i> </a> <label> China </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KOREA_REPUBLIC_OF"> <i class="material-icons">remove_circle_outline</i> </a> <label> Republic of Korea </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SPAIN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Spain </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UNITED_STATES"> <i class="material-icons">remove_circle_outline</i> </a> <label> USA </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_INDIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> India </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UNITED_KINGDOM"> <i class="material-icons">remove_circle_outline</i> </a> <label> UK </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GREECE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Greece </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SAUDI_ARABIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Saudi Arabia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ITALY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Italy </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_AUSTRALIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Australia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CANADA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Canada </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TAIWAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Taiwan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_EGYPT"> <i class="material-icons">remove_circle_outline</i> </a> <label> Egypt </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_JAPAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Japan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PAKISTAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Pakistan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_POLAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Poland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BRAZIL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Brazil </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GERMANY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Germany </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MALAYSIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Malaysia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TURKEY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Turkey (Türkiye) </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_VIETNAM"> <i class="material-icons">remove_circle_outline</i> </a> <label> Vietnam </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_COLOMBIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Colombia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_FRANCE"> <i class="material-icons">remove_circle_outline</i> </a> <label> France </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_FINLAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Finland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_INDONESIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Indonesia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MOROCCO"> <i class="material-icons">remove_circle_outline</i> </a> <label> Morocco </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PORTUGAL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Portugal </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SWITZERLAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Switzerland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MEXICO"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mexico </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NETHERLANDS"> <i class="material-icons">remove_circle_outline</i> </a> <label> The Netherlands </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NORWAY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Norway </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SWEDEN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sweden </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_IRAN_ISLAMIC_REPUBLIC_OF"> <i class="material-icons">remove_circle_outline</i> </a> <label> Iran </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BANGLADESH"> <i class="material-icons">remove_circle_outline</i> </a> <label> Bangladesh </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_THAILAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Thailand </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UNITED_ARAB_EMIRATES"> <i class="material-icons">remove_circle_outline</i> </a> <label> United Arab Emirates </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_IRAQ"> <i class="material-icons">remove_circle_outline</i> </a> <label> Iraq </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_JORDAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Jordan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ROMANIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Romania </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ALGERIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Algeria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ARGENTINA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Argentina </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_AUSTRIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Austria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_BELGIUM"> <i class="material-icons">remove_circle_outline</i> </a> <label> Belgium </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CHILE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Chile </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CYPRUS"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cyprus </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CZECH_REPUBLIC"> <i class="material-icons">remove_circle_outline</i> </a> <label> Czech Republic </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GHANA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ghana </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ISRAEL"> <i class="material-icons">remove_circle_outline</i> </a> <label> Israel </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_LEBANON"> <i class="material-icons">remove_circle_outline</i> </a> <label> Lebanon </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NEW_ZEALAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> New Zealand </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_NIGERIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Nigeria </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SLOVENIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Slovenia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SOUTH_AFRICA"> <i class="material-icons">remove_circle_outline</i> </a> <label> South Africa </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_TUNISIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Tunisia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UKRAINE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ukraine </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_RUSSIAN_FEDERATION"> <i class="material-icons">remove_circle_outline</i> </a> <label> Russia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CAMEROON"> <i class="material-icons">remove_circle_outline</i> </a> <label> Cameroon </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_CROATIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Croatia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_DENMARK"> <i class="material-icons">remove_circle_outline</i> </a> <label> Denmark </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ECUADOR"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ecuador </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_ETHIOPIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ethiopia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_GEORGIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Georgia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_HUNGARY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Hungary </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_IRELAND"> <i class="material-icons">remove_circle_outline</i> </a> <label> Ireland </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_JAMAICA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Jamaica </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_KUWAIT"> <i class="material-icons">remove_circle_outline</i> </a> <label> Kuwait </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_MOZAMBIQUE"> <i class="material-icons">remove_circle_outline</i> </a> <label> Mozambique </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_PHILIPPINES"> <i class="material-icons">remove_circle_outline</i> </a> <label> Philippines </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_QATAR"> <i class="material-icons">remove_circle_outline</i> </a> <label> Qatar </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SLOVAKIA"> <i class="material-icons">remove_circle_outline</i> </a> <label> Slovakia </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_SUDAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Sudan </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_URUGUAY"> <i class="material-icons">remove_circle_outline</i> </a> <label> Uruguay </label> </div/> <div class="remove-filter-container remove-filter-container--hidden"> <a href="#" class="remove-filter-link link--red " data-filterid="refine_countries_UZBEKISTAN"> <i class="material-icons">remove_circle_outline</i> </a> <label> Uzbekistan </label> </div/> </div> <div class="filter-actions-container filter-actions-container--filled filter-actions-container--hidden"> <a class="js-refine-filter" data-reveal-id="refine-modal-countries" data-filter="countries"><strong>Add Countries / Regions</strong></a> <a href="#" class="remove-refines link--red right" data-refineid="countries"><strong>Reset</strong></a> </div> <div class="filter-actions-container filter-actions-container--empty "> <a class="button button--color button--full-width js-refine-filter" href="#" data-reveal-id="refine-modal-countries" data-filter="countries" class="all">Select Countries / Regions</a> </div> <div style="clear:both;"></div> <div id="refine-modal-countries" class="reveal-modal reveal-modal-new" data-reveal aria-labelledby="modalTitle" aria-hidden="true" role="dialog"> <div class="row"> <div class="small-12 columns"> <h2>Filter Countries / Regions</h2> <input class="js-filter" type="text" form="temp" placeholder="Search for Countries / Regions" style="width: 100%; max-width: 300px;" /> <p class="reveal-modal-new__description"> Select countries / regions you want to add to your filter. </p> </div> <div class="js-refinement-values-container"> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="china" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_CHINA" value="CHINA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_CHINA">China (213)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="republic of korea" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_KOREA_REPUBLIC_OF" value="KOREA_REPUBLIC_OF"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_KOREA_REPUBLIC_OF">Republic of Korea (55)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="spain" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SPAIN" value="SPAIN"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SPAIN">Spain (47)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="usa" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_UNITED_STATES" value="UNITED_STATES"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_UNITED_STATES">USA (47)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="india" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_INDIA" value="INDIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_INDIA">India (26)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="uk" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_UNITED_KINGDOM" value="UNITED_KINGDOM"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_UNITED_KINGDOM">UK (22)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="greece" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_GREECE" value="GREECE"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_GREECE">Greece (21)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="saudi arabia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_SAUDI_ARABIA" value="SAUDI_ARABIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_SAUDI_ARABIA">Saudi Arabia (16)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="italy" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_ITALY" value="ITALY"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_ITALY">Italy (13)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="australia" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" class="refine_checkbox refine_countries" id="refine_countries_AUSTRALIA" value="AUSTRALIA"> <label class="search_refine_label" style="margin-bottom: 10px;" for="refine_countries_AUSTRALIA">Australia (12)</label> </div> </div> <div class="large-6 medium-6 small-12 columns end js-data-filter" data-filter="canada" style="padding-top: 0px; padding-bottom: 0px; margin-top: 0;" > <div> <input type="checkbox" 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href="/1424-8220/24/22/7400/pdf?version=1732115709" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Pressure Control of Multi-Mode Variable Structure Electro–Hydraulic Load Simulation System" data-journal="sensors"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1424-8220/24/22/7400">Pressure Control of Multi-Mode Variable Structure Electro–Hydraulic Load Simulation System</a> <div class="authors"> by <span class="inlineblock "><strong>He Hao</strong>, </span><span class="inlineblock "><strong>Hao Yan</strong>, </span><span class="inlineblock "><strong>Qi Zhang</strong> and </span><span class="inlineblock "><strong>Haoyu Li</strong></span> </div> <div class="color-grey-dark"> <em>Sensors</em> <b>2024</b>, <em>24</em>(22), 7400; <a href="https://doi.org/10.3390/s24227400">https://doi.org/10.3390/s24227400</a> - 20 Nov 2024 </div> Viewed by 312 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> During the loading process, significant external position disturbances occur in the electro–hydraulic load simulation system. To address these position disturbances and effectively mitigate the impact of uncertainty on system performance, this paper first treats model parameter uncertainty and external disturbances as lumped disturbances. <a href="#" data-counterslink = "https://www.mdpi.com/1424-8220/24/22/7400/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> During the loading process, significant external position disturbances occur in the electro–hydraulic load simulation system. To address these position disturbances and effectively mitigate the impact of uncertainty on system performance, this paper first treats model parameter uncertainty and external disturbances as lumped disturbances. The various states of the servo valve and the pressures within the hydraulic cylinder chambers are then examined. Building on this foundation, the paper proposes a nonlinear multi-mode variable structure independent load port electro–hydraulic load simulation system that is tailored for specific loading conditions. Secondly, in light of the significant motion disturbances present, this paper proposes an integral sliding mode active disturbance rejection composite control strategy that is based on fixed-time convergence. Based on the structure of the active disturbance rejection control framework, the fixed-time integral sliding mode and active disturbance rejection control algorithms are integrated. An extended state observer is designed to accurately estimate the lumped disturbance, effectively compensating for it to achieve precise loading of the independent load port electro–hydraulic load simulation system. The stability of the designed controller is also demonstrated. The results of the simulation research indicate that when the command input is a step signal, the pressure control accuracy under the composite control strategy is 99.94%, 99.86%, and 99.76% for disturbance frequencies of 1 Hz, 3 Hz, and 5 Hz, respectively. Conversely, when the command input is a sinusoidal signal, the pressure control accuracy remains high, measuring 99.94%, 99.8%, and 99.6% under the same disturbance frequencies. Furthermore, the simulation demonstrates that the influence of sensor random noise on the system remains within acceptable limits, highlighting the effective filtering capabilities of the extended state observer. This research establishes a solid foundation for the collaborative control of load ports and the engineering application of the independent load port electro–hydraulic load simulation system. <a href="/1424-8220/24/22/7400">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/sensors/sections/electronic_sensors">Electronic Sensors</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1424-8220/24/22/7400/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1525431"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1525431"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1525431" data-cycle-prev="#prev1525431" 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data-imgindex='20' data-target='article-1525431-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g021-550.jpg?1732115833'><p>Figure 21</p></div> --- <div class='openpopupgallery' data-imgindex='21' data-target='article-1525431-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g022-550.jpg?1732115834'><p>Figure 22</p></div></script></div></div><div id="article-1525431-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g001-550.jpg?1732115817" title=" <strong>Figure 1</strong><br/> <p>Schematic view of independent load port electro–hydraulic load simulation system model (1—tank, 2—hydraulic pump, 3—relief valve, 4—electro–hydraulic servo valve, 5—independent load port electro–hydraulic load simulation system controller, 6—pressure sensor, 7—hydraulic cylinder, 8—displacement sensor, 9—linear actuator, 10—linear actuator controller).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g002-550.jpg?1732115818" title=" <strong>Figure 2</strong><br/> <p>Block diagram of fixed-time integral sliding mode active disturbance rejection composite control.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g003-550.jpg?1732115819" title=" <strong>Figure 3</strong><br/> <p>Closed-loop pressure with a disturbance frequency of 1 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g004-550.jpg?1732115820" title=" <strong>Figure 4</strong><br/> <p>Closed-loop pressure error with a disturbance frequency of 1 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g005-550.jpg?1732115821" title=" <strong>Figure 5</strong><br/> <p>Controller output with a disturbance frequency of 1 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g006-550.jpg?1732115821" title=" <strong>Figure 6</strong><br/> <p>Closed-loop pressure with a disturbance frequency of 3 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g007-550.jpg?1732115822" title=" <strong>Figure 7</strong><br/> <p>Closed-loop pressure error with a disturbance frequency of 3 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g008-550.jpg?1732115823" title=" <strong>Figure 8</strong><br/> <p>Controller output with a disturbance frequency of 3 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g009-550.jpg?1732115823" title=" <strong>Figure 9</strong><br/> <p>Closed-loop pressure with a disturbance frequency of 5 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g010-550.jpg?1732115824" title=" <strong>Figure 10</strong><br/> <p>Closed-loop pressure error with a disturbance frequency of 5 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g011-550.jpg?1732115825" title=" <strong>Figure 11</strong><br/> <p>Controller output with a disturbance frequency of 5Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g012-550.jpg?1732115826" title=" <strong>Figure 12</strong><br/> <p>Closed-loop pressure with a disturbance frequency of 1 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g013-550.jpg?1732115827" title=" <strong>Figure 13</strong><br/> <p>Closed-loop pressure error with a disturbance frequency of 1 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g014-550.jpg?1732115827" title=" <strong>Figure 14</strong><br/> <p>Controller output with a disturbance frequency of 1 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g015-550.jpg?1732115828" title=" <strong>Figure 15</strong><br/> <p>Closed-loop pressure with a disturbance frequency of 3 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g016-550.jpg?1732115829" title=" <strong>Figure 16</strong><br/> <p>Closed-loop pressure error with disturbance frequency of 3 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g017-550.jpg?1732115830" title=" <strong>Figure 17</strong><br/> <p>Controller output with a disturbance frequency of 3 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g018-550.jpg?1732115831" title=" <strong>Figure 18</strong><br/> <p>Closed-loop pressure with a disturbance frequency of 5 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g019-550.jpg?1732115831" title=" <strong>Figure 19</strong><br/> <p>Closed-loop pressure error with a disturbance frequency of 5 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g020-550.jpg?1732115832" title=" <strong>Figure 20</strong><br/> <p>Controller output with a disturbance frequency of 5 Hz.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g021-550.jpg?1732115833" title=" <strong>Figure 21</strong><br/> <p>Pressure curve under random noise of 50 mV.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sensors/sensors-24-07400/article_deploy/html/images/sensors-24-07400-g022-550.jpg?1732115834" title=" <strong>Figure 22</strong><br/> <p>Pressure curve under random noise of 100 mV.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1424-8220/24/22/7400'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1524798" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 1057 KiB   </span> <a href="/2304-8158/13/22/3697/pdf?version=1732088650" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Food Public Opinion Prevention and Control Model Based on Sentiment Analysis" data-journal="foods"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2304-8158/13/22/3697">Food Public Opinion Prevention and Control Model Based on Sentiment Analysis</a> <div class="authors"> by <span class="inlineblock "><strong>Leiyang Chen</strong>, </span><span class="inlineblock "><strong>Xiangzhen Peng</strong>, </span><span class="inlineblock "><strong>Liang Dong</strong>, </span><span class="inlineblock "><strong>Zhenyu Wang</strong>, </span><span class="inlineblock "><strong>Zhidong Shen</strong> and </span><span class="inlineblock "><strong>Xiaohui Cui</strong></span> </div> <div class="color-grey-dark"> <em>Foods</em> <b>2024</b>, <em>13</em>(22), 3697; <a href="https://doi.org/10.3390/foods13223697">https://doi.org/10.3390/foods13223697</a> - 20 Nov 2024 </div> Viewed by 288 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Food public opinion is characterized by its low ignition point, high diffusibility, persistence, and strong negativity, which significantly impact food safety and consumer trust. This paper introduces the Food Public Opinion Prevention and Control (FPOPC) model driven by deep learning and personalized recommendation <a href="#" data-counterslink = "https://www.mdpi.com/2304-8158/13/22/3697/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Food public opinion is characterized by its low ignition point, high diffusibility, persistence, and strong negativity, which significantly impact food safety and consumer trust. This paper introduces the Food Public Opinion Prevention and Control (FPOPC) model driven by deep learning and personalized recommendation algorithms, rigorously tested and analyzed through experimentation. Initially, based on an analysis of food public opinion development, a comprehensive FPOPC framework addressing all stages of food public opinion was established. Subsequently, a sentiment prediction model for food news based on user comments was developed using a Stacked Autoencoder (SAE), enabling predictions about consumer sentiments toward food news. The sentiment values of the food news were then quantified, and improvements were made in allocating Pearson correlation coefficient weights, leading to the design of a collaborative filtering-based personalized food news recommendation mechanism. Furthermore, an enhanced Bloom filter integrated with HDFS technology devised a rapid recommendation mechanism for food public opinion. Finally, the designed FPOPC model and its associated mechanisms were validated through experimental verification and simulation analysis. The results demonstrate that the FPOPC model can accurately predict and control the development of food public opinion and the entire food supply chain, providing regulatory agencies with effective tools for managing food public sentiment. <a href="/2304-8158/13/22/3697">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/foods/special_issues/LN10DS77KZ ">Food Security and Structural Transformation of the Food Industry—Volume II</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2304-8158/13/22/3697/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1524798"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1524798"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1524798" data-cycle-prev="#prev1524798" data-cycle-progressive="#images1524798" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1524798-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g001-550.jpg?1732088746" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1524798" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1524798-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g002-550.jpg?1732088748'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1524798-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g003-550.jpg?1732088749'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1524798-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g004-550.jpg?1732088750'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1524798-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g005-550.jpg?1732088751'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1524798-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g006-550.jpg?1732088753'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1524798-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g007-550.jpg?1732088754'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1524798-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g008-550.jpg?1732088756'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1524798-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g009-550.jpg?1732088757'><p>Figure 9</p></div></script></div></div><div id="article-1524798-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g001-550.jpg?1732088746" title=" <strong>Figure 1</strong><br/> <p>Diagram of food public sentiment development.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2304-8158/13/22/3697'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g002-550.jpg?1732088748" title=" <strong>Figure 2</strong><br/> <p>Diagram of the food public sentiment prevention and control framework.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2304-8158/13/22/3697'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g003-550.jpg?1732088749" title=" <strong>Figure 3</strong><br/> <p>The structure of SAE.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2304-8158/13/22/3697'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g004-550.jpg?1732088750" title=" <strong>Figure 4</strong><br/> <p>Structure of the food public opinion prediction model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2304-8158/13/22/3697'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g005-550.jpg?1732088751" title=" <strong>Figure 5</strong><br/> <p>Diagram of the personalized recommendation algorithm based on collaborative filtering.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2304-8158/13/22/3697'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g006-550.jpg?1732088753" title=" <strong>Figure 6</strong><br/> <p>Fast recommendation mechanism based on Bloom filter.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2304-8158/13/22/3697'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g007-550.jpg?1732088754" title=" <strong>Figure 7</strong><br/> <p>Comparison of MAE and RMSE for LSTM, GRU, and SAEs (Positive Sentiment).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2304-8158/13/22/3697'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g008-550.jpg?1732088756" title=" <strong>Figure 8</strong><br/> <p>Comparison of MAE and RMSE for LSTM, GRU, and SAEs (Negative Sentiment).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2304-8158/13/22/3697'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/foods/foods-13-03697/article_deploy/html/images/foods-13-03697-g009-550.jpg?1732088757" title=" <strong>Figure 9</strong><br/> <p>Recall rate of the designed recommendation model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2304-8158/13/22/3697'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1517488" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 31 pages, 753 KiB   </span> <a href="/2075-1680/13/11/776/pdf?version=1731562693" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Divergence and Similarity Characteristics for Two Fuzzy Measures Based on Associated Probabilities" data-journal="axioms"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2075-1680/13/11/776">Divergence and Similarity Characteristics for Two Fuzzy Measures Based on Associated Probabilities</a> <div class="authors"> by <span class="inlineblock "><strong>Gia Sirbiladze</strong>, </span><span class="inlineblock "><strong>Bidzina Midodashvili</strong> and </span><span class="inlineblock "><strong>Teimuraz Manjafarashvili</strong></span> </div> <div class="color-grey-dark"> <em>Axioms</em> <b>2024</b>, <em>13</em>(11), 776; <a href="https://doi.org/10.3390/axioms13110776">https://doi.org/10.3390/axioms13110776</a> - 9 Nov 2024 </div> Viewed by 538 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The article deals with the definitions of the distance, divergence, and similarity characteristics between two finite fuzzy measures, which are generalizations of the same definitions between two finite probability distributions. As is known, a fuzzy measure can be uniquely represented by the so-called <a href="#" data-counterslink = "https://www.mdpi.com/2075-1680/13/11/776/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The article deals with the definitions of the distance, divergence, and similarity characteristics between two finite fuzzy measures, which are generalizations of the same definitions between two finite probability distributions. As is known, a fuzzy measure can be uniquely represented by the so-called its associated probability class (APC). The idea of generalization is that new definitions of distance, divergence, and similarity between fuzzy measures are reduced to the definitions of distance, divergence, and similarity between the APCs of fuzzy measures. These definitions are based on the concept of distance generator. The proof of the correctness of generalizations is provided. Constructed distance, similarity, and divergence relations can be used in such applied problems as: determining the difference between Dempster-Shafer belief structures; Constructions of collaborative filtering similarity relations; non-additive and interactive parameters of machine learning in phase space metrics definition, object clustering, classification and other tasks. In this work, a new concept is used in the fuzzy measure identification problem for a certain multi-attribute decision-making (MADM) environment. For this, a conditional optimization problem with one objective function representing the distance, divergence or similarity index is formulated. Numerical examples are discussed and a comparative analysis of the obtained results is presented. <a href="/2075-1680/13/11/776">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/axioms/special_issues/I8A7IXN97T ">New Perspectives in Fuzzy Sets and Their Applications</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2075-1680/13/11/776/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="absgraph cycle-slideshow"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1517488-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/axioms/axioms-13-00776/article_deploy/html/images/axioms-13-00776-g001-550.jpg?1731562782" alt="" style="border: 0;"><p>Figure 1</p></div></div></div><div id="article-1517488-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/axioms/axioms-13-00776/article_deploy/html/images/axioms-13-00776-g001-550.jpg?1731562782" title=" <strong>Figure 1</strong><br/> <p>Fuzzy terms of similarity of two fuzzy measures. <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mn>1</mn> </msub> </mrow> </semantics></math> = “very low similarity”, <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mn>2</mn> </msub> </mrow> </semantics></math> = “low similarity”, <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mn>3</mn> </msub> </mrow> </semantics></math> = “medium similarity”, <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mn>4</mn> </msub> </mrow> </semantics></math> = “high similarity”, <math display="inline"><semantics> <mrow> <msub> <mi>Q</mi> <mn>5</mn> </msub> </mrow> </semantics></math> = “very high similarity”.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2075-1680/13/11/776'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1515726" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 1246 KiB   </span> <a href="/2076-3417/14/22/10220/pdf?version=1730965988" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Artificial Intelligence-Powered Recommender Systems for Promoting Healthy Habits and Active Aging: A Systematic Review" data-journal="applsci"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2076-3417/14/22/10220">Artificial Intelligence-Powered Recommender Systems for Promoting Healthy Habits and Active Aging: A Systematic Review</a> <div class="authors"> by <span class="inlineblock "><strong>Juan Lopez-Barreiro</strong>, </span><span class="inlineblock "><strong>Jose Luis Garcia-Soidan</strong>, </span><span class="inlineblock "><strong>Luis Alvarez-Sabucedo</strong> and </span><span class="inlineblock "><strong>Juan M. Santos-Gago</strong></span> </div> <div class="color-grey-dark"> <em>Appl. Sci.</em> <b>2024</b>, <em>14</em>(22), 10220; <a href="https://doi.org/10.3390/app142210220">https://doi.org/10.3390/app142210220</a> - 7 Nov 2024 </div> Viewed by 652 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> (1) Background: Increasing life expectancy allows for more age-related health issues. Enhancing physical, cognitive, mental, and social health is crucial. Promoting healthy habits combats stress and diseases. Recommendation systems, like collaborative filtering, tailor suggestions but face challenges. Techniques such as artificial intelligence and <a href="#" data-counterslink = "https://www.mdpi.com/2076-3417/14/22/10220/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> (1) Background: Increasing life expectancy allows for more age-related health issues. Enhancing physical, cognitive, mental, and social health is crucial. Promoting healthy habits combats stress and diseases. Recommendation systems, like collaborative filtering, tailor suggestions but face challenges. Techniques such as artificial intelligence and machine learning are vital. Personalized health recommendations improve lifestyles and mitigate issues. (2) Methods: A systematic review adhering to the general principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses was conducted with the aim of identifying articles on innovative research about using recommendation algorithms, machine learning, or artificial intelligence to promote healthy habits and active aging. (3) Results: A total of 34 articles were included in this work. They address the topic of recommendation systems that use machine learning or artificial intelligence in the promotion of healthy habits. (4) Conclusions: This article reviews health-related activity recommendation techniques for the general population. With rising life expectancy and common health issues, effective recommendations are crucial for future public health. Limitations include excluding simpler models. Despite many proposals, systematic adherence mechanisms are lacking. Developing traceable, verifiable systems for healthy activity recommendations is vital for aging populations in developed countries. <a href="/2076-3417/14/22/10220">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/applsci/special_issues/WFXM2FW402 ">Applications of Data Science and Artificial Intelligence</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2076-3417/14/22/10220/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1515726"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1515726"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1515726" data-cycle-prev="#prev1515726" data-cycle-progressive="#images1515726" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1515726-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/applsci/applsci-14-10220/article_deploy/html/images/applsci-14-10220-g001-550.jpg?1730966079" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1515726" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1515726-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10220/article_deploy/html/images/applsci-14-10220-g002-550.jpg?1730966082'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1515726-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/applsci/applsci-14-10220/article_deploy/html/images/applsci-14-10220-g003-550.jpg?1730966083'><p>Figure 3</p></div></script></div></div><div id="article-1515726-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/applsci/applsci-14-10220/article_deploy/html/images/applsci-14-10220-g001-550.jpg?1730966079" title=" <strong>Figure 1</strong><br/> <p>Mahesh classification of ML algorithms [<a href="#B13-applsci-14-10220" class="html-bibr">13</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/22/10220'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10220/article_deploy/html/images/applsci-14-10220-g002-550.jpg?1730966082" title=" <strong>Figure 2</strong><br/> <p>Flow diagram of the systematic review according to PRISMA guidelines.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/22/10220'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/applsci/applsci-14-10220/article_deploy/html/images/applsci-14-10220-g003-550.jpg?1730966083" title=" <strong>Figure 3</strong><br/> <p>Evolution of the publication year of the included studies.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2076-3417/14/22/10220'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1514114" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 32 pages, 7967 KiB   </span> <a href="/2071-1050/16/22/9618/pdf?version=1730792347" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="A Bibliometric Review of Indoor Environment Quality Research and Its Effects on Occupant Productivity (2011–2023)" data-journal="sustainability"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2071-1050/16/22/9618">A Bibliometric Review of Indoor Environment Quality Research and Its Effects on Occupant Productivity (2011–2023)</a> <div class="authors"> by <span class="inlineblock "><strong>Mustafa Shetaw</strong>, </span><span class="inlineblock "><strong>Louis Gyoh</strong>, </span><span class="inlineblock "><strong>Michael Gerges</strong> and </span><span class="inlineblock "><strong>Nenpin Dimka</strong></span> </div> <div class="color-grey-dark"> <em>Sustainability</em> <b>2024</b>, <em>16</em>(22), 9618; <a href="https://doi.org/10.3390/su16229618">https://doi.org/10.3390/su16229618</a> - 5 Nov 2024 </div> Viewed by 707 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Over the past decade, there has been a growing recognition of the importance of indoor environmental quality (IEQ) in influencing occupant productivity. Researchers have studied various buildings, including offices, schools, hospitals, and residential settings, to understand the relationship between IEQ and productivity outcomes. <a href="#" data-counterslink = "https://www.mdpi.com/2071-1050/16/22/9618/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Over the past decade, there has been a growing recognition of the importance of indoor environmental quality (IEQ) in influencing occupant productivity. Researchers have studied various buildings, including offices, schools, hospitals, and residential settings, to understand the relationship between IEQ and productivity outcomes. Studies have taken a multifactorial approach, considering multiple aspects of IEQ. Evidence from the literature review suggests that the quality of the indoor environment is an essential factor that affects the productivity of building occupants, and it is one of the fundamental issues in the development of societies. This area of research requires the responsible participation of researchers at all levels, as there is significant scope to contribute to knowledge. Therefore, this study aims to conduct a bibliometric analysis of the published literature on indoor environmental quality and its impact on building occupant productivity through the scientific literature available from one of the largest and most famous academic databases, Scopus; the study was determined in 2011 to 2023. The search used differential thresholds for IEQ keywords affecting building occupant productivity. Three discrete queries were performed, resulting in approximately 3861 publications. These were filtered by reducing false positives and excluding publications irrelevant to the research topic. The final results were 72 publications. This study also used Excel and VOS viewer to analyse and create graphs and network visualisation maps to show the growth of publications and their types, active countries and institutions for recovered publications, international collaboration, author keywords, active journals, and citation analysis. This study can significantly advance our understanding of building occupant productivity and enhance quality of life and work. Evaluating the research outputs is essential for highlighting contributions to knowledge and global collaboration in this research area. The potential impact of this study is not just theoretical. It can shape the future of our built environments and the lives of those occupying them. <a href="/2071-1050/16/22/9618">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2071-1050/16/22/9618/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1514114"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1514114"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1514114" data-cycle-prev="#prev1514114" data-cycle-progressive="#images1514114" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1514114-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g001-550.jpg?1730792541" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1514114" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g002-550.jpg?1730792542'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g003-550.jpg?1730792544'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g004-550.jpg?1730792545'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g005-550.jpg?1730792546'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g006-550.jpg?1730792547'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g007-550.jpg?1730792548'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g008-550.jpg?1730792550'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g009-550.jpg?1730792552'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g010-550.jpg?1730792553'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g011-550.jpg?1730792554'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g012-550.jpg?1730792555'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g013-550.jpg?1730792556'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g014-550.jpg?1730792558'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g015-550.jpg?1730792559'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g016-550.jpg?1730792560'><p>Figure 16</p></div> --- <div class='openpopupgallery' data-imgindex='16' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g017-550.jpg?1730792561'><p>Figure 17</p></div> --- <div class='openpopupgallery' data-imgindex='17' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g018-550.jpg?1730792562'><p>Figure 18</p></div> --- <div class='openpopupgallery' data-imgindex='18' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g019-550.jpg?1730792563'><p>Figure 19</p></div> --- <div class='openpopupgallery' data-imgindex='19' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g020-550.jpg?1730792565'><p>Figure 20</p></div> --- <div class='openpopupgallery' data-imgindex='20' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g021-550.jpg?1730792568'><p>Figure 21</p></div> --- <div class='openpopupgallery' data-imgindex='21' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g022-550.jpg?1730792570'><p>Figure 22</p></div> --- <div class='openpopupgallery' data-imgindex='22' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g023-550.jpg?1730792572'><p>Figure 23</p></div> --- <div class='openpopupgallery' data-imgindex='23' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g024-550.jpg?1730792575'><p>Figure 24</p></div> --- <div class='openpopupgallery' data-imgindex='24' data-target='article-1514114-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g025-550.jpg?1730792577'><p>Figure 25</p></div></script></div></div><div id="article-1514114-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g001-550.jpg?1730792541" title=" <strong>Figure 1</strong><br/> <p>Annual growth of publications in the first query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g002-550.jpg?1730792542" title=" <strong>Figure 2</strong><br/> <p>Percentage of document types published in the first query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g003-550.jpg?1730792544" title=" <strong>Figure 3</strong><br/> <p>Top 5 active countries in indoor environmental quality and occupant productivity.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g004-550.jpg?1730792545" title=" <strong>Figure 4</strong><br/> <p>Network visualisation map of most frequent author’s keywords in the first query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g005-550.jpg?1730792546" title=" <strong>Figure 5</strong><br/> <p>The publication results from the first query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g006-550.jpg?1730792547" title=" <strong>Figure 6</strong><br/> <p>Annual growth of publications in the second query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g007-550.jpg?1730792548" title=" <strong>Figure 7</strong><br/> <p>Percentage of document types published in the second query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g008-550.jpg?1730792550" title=" <strong>Figure 8</strong><br/> <p>Top 5 active countries in indoor environmental quality and occupants’ productivity research extracted from the second query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g009-550.jpg?1730792552" title=" <strong>Figure 9</strong><br/> <p>Network visualisation map of most frequent authors keywords in the second query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g010-550.jpg?1730792553" title=" <strong>Figure 10</strong><br/> <p>The publication results from the second query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g011-550.jpg?1730792554" title=" <strong>Figure 11</strong><br/> <p>Annual growth of publications in the third query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g012-550.jpg?1730792555" title=" <strong>Figure 12</strong><br/> <p>Percentage of document types published in the third query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g013-550.jpg?1730792556" title=" <strong>Figure 13</strong><br/> <p>Top 5 active countries in indoor environmental quality and occupants’ productivity research extracted from the third query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g014-550.jpg?1730792558" title=" <strong>Figure 14</strong><br/> <p>Network visualisation map of most frequent author keywords in the third query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g015-550.jpg?1730792559" title=" <strong>Figure 15</strong><br/> <p>The publication results from the third query.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g016-550.jpg?1730792560" title=" <strong>Figure 16</strong><br/> <p>Annual growth of publications (resulting from the three queries).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g017-550.jpg?1730792561" title=" <strong>Figure 17</strong><br/> <p>Percentage of document types published (resulting from the three queries).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g018-550.jpg?1730792562" title=" <strong>Figure 18</strong><br/> <p>Top 5 active countries in indoor environmental quality and occupants’ productivity research extracted from the three queries.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g019-550.jpg?1730792563" title=" <strong>Figure 19</strong><br/> <p>Geographical distribution map of research published about indoor environmental quality and occupant productivity research extracted from the three inquiries (2011–2023).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g020-550.jpg?1730792565" title=" <strong>Figure 20</strong><br/> <p>Network visualisation map of the international collaboration of studies on the effect of indoor environment quality on occupants’ productivity extracted from the three queries’ results.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g021-550.jpg?1730792568" title=" <strong>Figure 21</strong><br/> <p>Network visualisation map of the institutions supports research about indoor environmental quality and occupants’ productivity (2011–2023).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g022-550.jpg?1730792570" title=" <strong>Figure 22</strong><br/> <p>Network visualisation map of most frequent author keywords, extracted from the result of the three queries.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g023-550.jpg?1730792572" title=" <strong>Figure 23</strong><br/> <p>Top 5 journals with the highest number of publications.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g024-550.jpg?1730792575" title=" <strong>Figure 24</strong><br/> <p>Network visualisation map of the authors with the most publications, extracted from the result of the three queries.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09618/article_deploy/html/images/sustainability-16-09618-g025-550.jpg?1730792577" title=" <strong>Figure 25</strong><br/> <p>Network map of the most cited publications.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/22/9618'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1513903" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 4145 KiB   </span> <a href="/1996-1073/17/21/5514/pdf?version=1730735746" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Electric Vehicle Charging Station Recommendations Considering User Charging Preferences Based on Comment Data" data-journal="energies"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/1996-1073/17/21/5514">Electric Vehicle Charging Station Recommendations Considering User Charging Preferences Based on Comment Data</a> <div class="authors"> by <span class="inlineblock "><strong>Houzhi Li</strong>, </span><span class="inlineblock "><strong>Qingwen Han</strong>, </span><span class="inlineblock "><strong>Xueyuan Bai</strong>, </span><span class="inlineblock "><strong>Li Zhang</strong>, </span><span class="inlineblock "><strong>Wen Wang</strong>, </span><span class="inlineblock "><strong>Wenjia Chen</strong> and </span><span class="inlineblock "><strong>Lin Xiang</strong></span> </div> <div class="color-grey-dark"> <em>Energies</em> <b>2024</b>, <em>17</em>(21), 5514; <a href="https://doi.org/10.3390/en17215514">https://doi.org/10.3390/en17215514</a> - 4 Nov 2024 </div> Viewed by 522 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> User preferences are important for electric vehicle charging station (EVCS) recommendations, but they have not been deeply analyzed. Therefore, in this study, user charging preferences are identified and applied to EVCS recommendations using a hybrid model that integrates LightGBM and singular value decomposition <a href="#" data-counterslink = "https://www.mdpi.com/1996-1073/17/21/5514/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> User preferences are important for electric vehicle charging station (EVCS) recommendations, but they have not been deeply analyzed. Therefore, in this study, user charging preferences are identified and applied to EVCS recommendations using a hybrid model that integrates LightGBM and singular value decomposition (SVD). In the model, LightGBM is used to predict user ratings according to users’ comments regarding charging orders, and the feature importance reported by each user is output. Then, a co-occurrence matrix between users and charging stations (EVCSs) is constructed and decomposed using SVD. Based on the decomposed results, the final evaluated scores of each user for EVCSs can be calculated. Upon ranking the EVCSs according to the scores, the EVCS recommendation results are obtained, taking into account the users’ charging preferences. The sample data consist of 28,306 orders from 508 users at 241 charging stations in Linyi, Shandong, China. The experimental results show that the proposed hybrid model outperforms the benchmark models in terms of precision, recall, and F1 score, and its F1 score can be increased by 96% compared with that of the traditional item-based collaborative filtering method with charging counts for EVCS recommendations. <a href="/1996-1073/17/21/5514">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/energies/sections/electric_vehicles">E: Electric Vehicles</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/1996-1073/17/21/5514/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1513903"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1513903"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1513903" data-cycle-prev="#prev1513903" data-cycle-progressive="#images1513903" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1513903-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g001-550.jpg?1730735835" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1513903" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g002-550.jpg?1730735837'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g003-550.jpg?1730735837'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g004-550.jpg?1730735838'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g005-550.jpg?1730735838'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g006-550.jpg?1730735839'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g007-550.jpg?1730735839'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g008-550.jpg?1730735840'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g009-550.jpg?1730735840'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g010-550.jpg?1730735841'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g011-550.jpg?1730735841'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1513903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g012-550.jpg?1730735842'><p>Figure 12</p></div></script></div></div><div id="article-1513903-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g001-550.jpg?1730735835" title=" <strong>Figure 1</strong><br/> <p>Method flow chart.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g002-550.jpg?1730735837" title=" <strong>Figure 2</strong><br/> <p>Heat map of 14 features for user charging rating prediction.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g003-550.jpg?1730735837" title=" <strong>Figure 3</strong><br/> <p>Training and testing set partition diagram.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g004-550.jpg?1730735838" title=" <strong>Figure 4</strong><br/> <p>Results of user rating prediction of models.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g005-550.jpg?1730735838" title=" <strong>Figure 5</strong><br/> <p>Performance of model user rating prediction.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g006-550.jpg?1730735839" title=" <strong>Figure 6</strong><br/> <p>Overall feature importance from LightGBM.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g007-550.jpg?1730735839" title=" <strong>Figure 7</strong><br/> <p>Example of users’ personalized charging preferences.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g008-550.jpg?1730735840" title=" <strong>Figure 8</strong><br/> <p>Model performance with different decomposition dimensions.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g009-550.jpg?1730735840" title=" <strong>Figure 9</strong><br/> <p>Model performance with different recommendation list lengths.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g010-550.jpg?1730735841" title=" <strong>Figure 10</strong><br/> <p>The accuracy, recall, and F1 score of different recommendation models.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g011-550.jpg?1730735841" title=" <strong>Figure 11</strong><br/> <p>Changes in rating prediction results (MSE, MAE, RMSE, and R<sup>2</sup>) and recommendation results (precision, recall, and F1) after data imbalance processing.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/energies/energies-17-05514/article_deploy/html/images/energies-17-05514-g012-550.jpg?1730735842" title=" <strong>Figure 12</strong><br/> <p>(<b>a</b>) Overall standard deviation of feature importance in incremental learning; (<b>b</b>) illustrations of feature importance changes for user with maximum feature importance variance.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/1996-1073/17/21/5514'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1513864" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 32 pages, 6218 KiB   </span> <a href="/2079-9292/13/21/4331/pdf?version=1730790065" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Natural Language Processing and Machine Learning-Based Solution of Cold Start Problem Using Collaborative Filtering Approach" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/21/4331">Natural Language Processing and Machine Learning-Based Solution of Cold Start Problem Using Collaborative Filtering Approach</a> <div class="authors"> by <span class="inlineblock "><strong>Kamta Nath Mishra</strong>, </span><span class="inlineblock "><strong>Alok Mishra</strong>, </span><span class="inlineblock "><strong>Paras Nath Barwal</strong> and </span><span class="inlineblock "><strong>Rajesh Kumar Lal</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(21), 4331; <a href="https://doi.org/10.3390/electronics13214331">https://doi.org/10.3390/electronics13214331</a> - 4 Nov 2024 </div> Viewed by 732 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In today’s digital era, the abundance of online services presents users with a daunting array of choices, spanning from streaming platforms to e-commerce websites, leading to decision fatigue. Recommendation algorithms play a pivotal role in aiding users in navigating this plethora of options, <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/21/4331/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In today’s digital era, the abundance of online services presents users with a daunting array of choices, spanning from streaming platforms to e-commerce websites, leading to decision fatigue. Recommendation algorithms play a pivotal role in aiding users in navigating this plethora of options, among which collaborative filtering (CF) stands out as a prevalent technique. However, CF encounters several challenges, including scalability issues, privacy implications, and the well-known cold start problem. This study endeavors to mitigate the cold start problem by harnessing the capabilities of natural language processing (NLP) applied to user-generated reviews. A unique methodology is introduced, integrating both supervised and unsupervised NLP approaches facilitated by sci-kit learn, utilizing benchmark datasets across diverse domains. This study offers scientific contributions through its <i>novel</i> approach, ensuring rigor, precision, scalability, and real-world relevance. It tackles the cold start problem in recommendation systems by combining natural language processing (NLP) with machine learning and collaborative filtering techniques, addressing data sparsity effectively. This study emphasizes reproducibility and accuracy while proposing an advanced solution that improves personalization in recommendation models. The proposed NLP-based strategy enhances the quality of user-generated content, consequently refining the accuracy of Collaborative Filtering-Based Recommender Systems (CFBRSs). The authors conducted experiments to test the performance of the proposed approach on benchmark datasets like <i>MovieLens</i>, <i>Jester</i>, <i>Book-Crossing</i>, <i>Last.fm</i>, <i>Amazon Product Reviews</i>, <i>Yelp</i>, <i>Netflix Prize</i>, <i>Goodreads</i>, <i>IMDb (Internet movie Database) Data</i>, <i>CiteULike</i>, <i>Epinions</i>, and <i>Etsy</i> to measure global accuracy, global loss, F-1 Score, and AUC (area under curve) values. Assessment through various techniques such as random forest, Naïve Bayes, and Logistic Regression on heterogeneous benchmark datasets indicates that random forest is the most effective method, achieving an accuracy rate exceeding 90%. Further, the proposed approach received a global accuracy above 95%, a global loss of 1.50%, an F-1 Score of 0.78, and an AUC value of 92%. Furthermore, the experiments conducted on distributed and global differential privacy (GDP) further optimize the system’s efficacy. <a href="/2079-9292/13/21/4331">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/9M87C9D974 ">Innovations in Artificial Intelligence, Natural Language Processing and Big Data</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/21/4331/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1513864"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1513864"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1513864" data-cycle-prev="#prev1513864" data-cycle-progressive="#images1513864" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1513864-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g001-550.jpg?1730790212" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1513864" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g002-550.jpg?1730790214'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g003-550.jpg?1730790217'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g004-550.jpg?1730790218'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g005-550.jpg?1730790219'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g006-550.jpg?1730790220'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g007-550.jpg?1730790221'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g008-550.jpg?1730790224'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g009-550.jpg?1730790228'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g010-550.jpg?1730790229'><p>Figure 10</p></div> --- <div class='openpopupgallery' data-imgindex='10' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g011-550.jpg?1730790230'><p>Figure 11</p></div> --- <div class='openpopupgallery' data-imgindex='11' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g012-550.jpg?1730790231'><p>Figure 12</p></div> --- <div class='openpopupgallery' data-imgindex='12' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g013-550.jpg?1730790233'><p>Figure 13</p></div> --- <div class='openpopupgallery' data-imgindex='13' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g014-550.jpg?1730790234'><p>Figure 14</p></div> --- <div class='openpopupgallery' data-imgindex='14' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g015-550.jpg?1730790236'><p>Figure 15</p></div> --- <div class='openpopupgallery' data-imgindex='15' data-target='article-1513864-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g016-550.jpg?1730790237'><p>Figure 16</p></div></script></div></div><div id="article-1513864-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g001-550.jpg?1730790212" title=" <strong>Figure 1</strong><br/> <p>Classification of recommender systems.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g002-550.jpg?1730790214" title=" <strong>Figure 2</strong><br/> <p>Algorithmic steps of the proposed approach.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g003-550.jpg?1730790217" title=" <strong>Figure 3</strong><br/> <p>Proposed solution to further improve the solution for the cold start problem.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g004-550.jpg?1730790218" title=" <strong>Figure 4</strong><br/> <p>Sentiment analysis from textual review.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g005-550.jpg?1730790219" title=" <strong>Figure 5</strong><br/> <p>Flow of review “Pre-processing” for ReSA.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g006-550.jpg?1730790220" title=" <strong>Figure 6</strong><br/> <p>Flow of Preprocessed User Review for ReSA.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g007-550.jpg?1730790221" title=" <strong>Figure 7</strong><br/> <p>Schematic data flow representing the recommender’s system equilibrium states.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g008-550.jpg?1730790224" title=" <strong>Figure 8</strong><br/> <p>Word cloud for the positive reviews.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g009-550.jpg?1730790228" title=" <strong>Figure 9</strong><br/> <p>Amazon review dataset.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g010-550.jpg?1730790229" title=" <strong>Figure 10</strong><br/> <p>Pie chart of positive and negative review distributions.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g011-550.jpg?1730790230" title=" <strong>Figure 11</strong><br/> <p>Confusion matrices comparing the performance after the ReSA process.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g012-550.jpg?1730790231" title=" <strong>Figure 12</strong><br/> <p>Generating heat-map using Naïve Bayes classification.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g013-550.jpg?1730790233" title=" <strong>Figure 13</strong><br/> <p>Accuracy, recall, and precision Scores for random forest and Naive Baye’s models.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g014-550.jpg?1730790234" title=" <strong>Figure 14</strong><br/> <p>Generating a graph for training loss vs. epoch using the different optimizers.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g015-550.jpg?1730790236" title=" <strong>Figure 15</strong><br/> <p>Generating a graph for validation loss vs. epoch using the different optimizers.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04331/article_deploy/html/images/electronics-13-04331-g016-550.jpg?1730790237" title=" <strong>Figure 16</strong><br/> <p>Generation of area under curve (AUC) for the proposed model.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/21/4331'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1508568" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 17 pages, 2287 KiB   </span> <a href="/2227-7102/14/11/1177/pdf?version=1730277740" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Redesigning of Flexible Learning Itinerary Configurator (FLIC) for the Design of Learning Situations in Compulsory Education (FLIC-IPAFLEX)" data-journal="education"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2227-7102/14/11/1177">Redesigning of Flexible Learning Itinerary Configurator (FLIC) for the Design of Learning Situations in Compulsory Education (FLIC-IPAFLEX)</a> <div class="authors"> by <span class="inlineblock "><strong>Jacoba Munar-Garau</strong>, </span><span class="inlineblock "><strong>Juan Moreno-Garcia</strong>, </span><span class="inlineblock "><strong>Barbara De-Benito-Crosetti</strong> and </span><span class="inlineblock "><strong>Jesus Salinas</strong></span> </div> <div class="color-grey-dark"> <em>Educ. Sci.</em> <b>2024</b>, <em>14</em>(11), 1177; <a href="https://doi.org/10.3390/educsci14111177">https://doi.org/10.3390/educsci14111177</a> - 28 Oct 2024 </div> Viewed by 572 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> This paper presents the redesign process of FLIC, a web application developed for creating personal learning itineraries in higher education, now adapted for primary and secondary education as FLIC-IPAFLEX. This redesign meets the need for personalised learning through flexible pathways. It supports teachers <a href="#" data-counterslink = "https://www.mdpi.com/2227-7102/14/11/1177/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> This paper presents the redesign process of FLIC, a web application developed for creating personal learning itineraries in higher education, now adapted for primary and secondary education as FLIC-IPAFLEX. This redesign meets the need for personalised learning through flexible pathways. It supports teachers in creating learning situations (LSs) as per the criteria set forth by the new Spanish Education Law (LOMLOE). The SCRUM model, integrated into Design-Based Research (DBR), was employed, implementing several iterative cycles involving teachers to validate the tool’s utility. The platform facilitates the creation, publication, and reuse of LS by enabling the filtering of competencies, evaluation criteria, and basic knowledge, as well as integrating with Google Classroom, an application widely used by teachers. The results show a positive user evaluation, highlighting its ease of use and capacity to foster collaboration among teachers, thereby promoting the co-design of flexible and adaptive LSs. FLIC-IPAFLEX aims to contribute to the field of learning design technologies, aligning with the demands of compulsory education and supporting collaborative processes within the educational environment. <a href="/2227-7102/14/11/1177">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/education/special_issues/XFK69683B0 ">ICTs in Managing Education Environments</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2227-7102/14/11/1177/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1508568"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1508568"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1508568" data-cycle-prev="#prev1508568" data-cycle-progressive="#images1508568" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1508568-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g001-550.jpg?1730277875" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1508568" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1508568-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g002-550.jpg?1730277876'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1508568-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g003-550.jpg?1730277878'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1508568-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g004-550.jpg?1730277878'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1508568-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g0A1-550.jpg?1730277879'><p>Figure A1</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1508568-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g0A2-550.jpg?1730277879'><p>Figure A2</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1508568-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g0A3-550.jpg?1730277881'><p>Figure A3</p></div></script></div></div><div id="article-1508568-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g001-550.jpg?1730277875" title=" <strong>Figure 1</strong><br/> <p>Process of building and implementing a flexible itinerary in the original FLIC application.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7102/14/11/1177'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g002-550.jpg?1730277876" title=" <strong>Figure 2</strong><br/> <p>Phases of the FLIC-IPAFLEX application redesign process according to the SCRUM model based on the IBD methodology.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7102/14/11/1177'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g003-550.jpg?1730277878" title=" <strong>Figure 3</strong><br/> <p>Process of designing and implementing an LS with FLIC-IPAFLEX.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7102/14/11/1177'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g004-550.jpg?1730277878" title=" <strong>Figure 4</strong><br/> <p>User interface. Teacher’s personal space.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7102/14/11/1177'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g0A1-550.jpg?1730277879" title=" <strong>Figure A1</strong><br/> <p></p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7102/14/11/1177'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g0A2-550.jpg?1730277879" title=" <strong>Figure A2</strong><br/> <p></p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7102/14/11/1177'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/education/education-14-01177/article_deploy/html/images/education-14-01177-g0A3-550.jpg?1730277881" title=" <strong>Figure A3</strong><br/> <p></p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-7102/14/11/1177'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1508237" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 14 pages, 2641 KiB   </span> <a href="/2072-666X/15/11/1306/pdf?version=1730111187" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Vacuum Filtration-Coated Silver Electrodes Coupled with Stacked Conductive Multi-Walled Carbon Nanotubes/Mulberry Paper Sensing Layers for a Highly Sensitive and Wide-Range Flexible Pressure Sensor" data-journal="micromachines"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2072-666X/15/11/1306">Vacuum Filtration-Coated Silver Electrodes Coupled with Stacked Conductive Multi-Walled Carbon Nanotubes/Mulberry Paper Sensing Layers for a Highly Sensitive and Wide-Range Flexible Pressure Sensor</a> <div class="authors"> by <span class="inlineblock "><strong>Guanhai Yan</strong>, </span><span class="inlineblock "><strong>Dongrui Dang</strong>, </span><span class="inlineblock "><strong>Sheng Chang</strong>, </span><span class="inlineblock "><strong>Xuefeng Zhang</strong>, </span><span class="inlineblock "><strong>Jinhua Zhang</strong> and </span><span class="inlineblock "><strong>Zhengdong Wang</strong></span> </div> <div class="color-grey-dark"> <em>Micromachines</em> <b>2024</b>, <em>15</em>(11), 1306; <a href="https://doi.org/10.3390/mi15111306">https://doi.org/10.3390/mi15111306</a> - 28 Oct 2024 </div> Viewed by 588 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Flexible pressure sensors based on paper have attracted considerable attention owing to their good performance, low cost, and environmental friendliness. However, effectively expanding the detection range of paper-based sensors with high sensitivities is still a challenge. Herein, we present a paper-based resistive pressure <a href="#" data-counterslink = "https://www.mdpi.com/2072-666X/15/11/1306/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Flexible pressure sensors based on paper have attracted considerable attention owing to their good performance, low cost, and environmental friendliness. However, effectively expanding the detection range of paper-based sensors with high sensitivities is still a challenge. Herein, we present a paper-based resistive pressure sensor with a sandwich structure consisting of two electrodes and three sensing layers. The silver nanowires were dispersed deposited on a filter paper substrate using the vacuum filtration coating method to prepare the electrode. And the sensing layer was fabricated by coating carbon nanotubes onto a mulberry paper substrate. Waterborne polyurethane was introduced in the process of preparing the sensing layers to enhance the strength of the interface between the carbon nanotubes and the mulberry paper substrate. Therefore, the designed sensor exhibits a good sensing performance by virtue of the rational structure design and proper material selection. Specifically, the rough surfaces of the sensing layers, porous conductive network of silver nanowires on the electrodes, and the multilayer stacked structure of the sensor collaboratively increase the change in the surface contact area under a pressure load, which improves the sensitivity and extends the sensing range simultaneously. Consequently, the designed sensor exhibits a high sensitivity (up to 6.26 kPa<sup>−1</sup>), wide measurement range (1000 kPa), low detection limit (~1 Pa), and excellent stability (1000 cycles). All these advantages guarantee that the sensor has potential for applications in smart wearable devices and the Internet of Things. <a href="/2072-666X/15/11/1306">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/micromachines/special_issues/DT3R3UUSDW ">Novel Micromachine Systems Enabled Tissue Characterization and Physiological Monitoring</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2072-666X/15/11/1306/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1508237"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1508237"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1508237" data-cycle-prev="#prev1508237" data-cycle-progressive="#images1508237" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1508237-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/micromachines/micromachines-15-01306/article_deploy/html/images/micromachines-15-01306-g001-550.jpg?1730111303" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1508237" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1508237-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/micromachines/micromachines-15-01306/article_deploy/html/images/micromachines-15-01306-g002-550.jpg?1730111306'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1508237-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/micromachines/micromachines-15-01306/article_deploy/html/images/micromachines-15-01306-g003-550.jpg?1730111308'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1508237-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/micromachines/micromachines-15-01306/article_deploy/html/images/micromachines-15-01306-g004-550.jpg?1730111311'><p>Figure 4</p></div></script></div></div><div id="article-1508237-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/micromachines/micromachines-15-01306/article_deploy/html/images/micromachines-15-01306-g001-550.jpg?1730111303" title=" <strong>Figure 1</strong><br/> <p>Schematic illustration of the fabrication process and sensing mechanism of the pressure sensor. (<b>a</b>) Preparation process of a CMP sensing layer. (<b>b</b>) Preparation process of a AgNWs/FP electrode. (<b>c</b>) Schematic illustration of the proposed all-paper-based flexible pressure sensor. (<b>d</b>) Digital images of a CMP sensing layer, a AgNWs/FP electrode, and a sensor, respectively. (<b>e</b>) Sensing mechanism of the proposed all-paper-based pressure sensor.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-666X/15/11/1306'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/micromachines/micromachines-15-01306/article_deploy/html/images/micromachines-15-01306-g002-550.jpg?1730111306" title=" <strong>Figure 2</strong><br/> <p>Characterization of all-paper-based flexible pressure sensor. (<b>a</b>) SEM image of pristine mulberry paper. (<b>b</b>) Surface SEM image of a CMP sensing layer prepared by dip coating process. (<b>c</b>) An enlarged view of a CMP sensing layer SEM image. (<b>d</b>) Raman spectra of a CMP sensing layer. Characteristic peaks of MWCNTs, WPU, and mulberry paper are clearly depicted. (<b>e</b>) Cross-sectional SEM image of a AgNWs/FP electrode. (<b>f</b>) Enlarged view of figure (<b>e</b>).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-666X/15/11/1306'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/micromachines/micromachines-15-01306/article_deploy/html/images/micromachines-15-01306-g003-550.jpg?1730111308" title=" <strong>Figure 3</strong><br/> <p>Pressure sensing performance of the CMP sensors. (<b>a</b>) Current-voltage curves of the three-layer CMP pressure sensor under different pressures varying from 5 kPa to 500 kPa. (<b>b</b>) Relative current changes in pressure sensors with one, two, and three CMP sensing layers in the pressure range of 1–1000 kPa. (<b>c</b>) Relative current changes in pressure sensors with one, two, and three CMP sensing layers in the pressure range of 1–50 kPa. (<b>d</b>) Dynamic response of the sensor under repeated pressure of 0.98 Pa for 11 cycles. (<b>e</b>) Current change in the sensor under a pressure over 1000 kPa. (<b>f</b>) Dynamic response of the pressure sensor under different pressures within 10–500 kPa. (<b>g</b>) Small pressure detection under high pressure. Three weights of 500 g, 1.48 g, and 1.45 g were placed on top surface of the sensor one after another, denoted in three stages denoted as ➀, ➁, and ➂. (<b>h</b>) Performance comparison of sensors prepared by drop-coating and dip-coating process. (<b>i</b>) Comparisons of sensitivity and sensing range with previously reported paper-based pressure sensors [<a href="#B15-micromachines-15-01306" class="html-bibr">15</a>,<a href="#B41-micromachines-15-01306" class="html-bibr">41</a>,<a href="#B54-micromachines-15-01306" class="html-bibr">54</a>,<a href="#B55-micromachines-15-01306" class="html-bibr">55</a>,<a href="#B56-micromachines-15-01306" class="html-bibr">56</a>,<a href="#B57-micromachines-15-01306" class="html-bibr">57</a>,<a href="#B58-micromachines-15-01306" class="html-bibr">58</a>,<a href="#B59-micromachines-15-01306" class="html-bibr">59</a>,<a href="#B60-micromachines-15-01306" class="html-bibr">60</a>,<a href="#B61-micromachines-15-01306" class="html-bibr">61</a>,<a href="#B62-micromachines-15-01306" class="html-bibr">62</a>,<a href="#B63-micromachines-15-01306" class="html-bibr">63</a>,<a href="#B64-micromachines-15-01306" class="html-bibr">64</a>,<a href="#B65-micromachines-15-01306" class="html-bibr">65</a>,<a href="#B66-micromachines-15-01306" class="html-bibr">66</a>,<a href="#B67-micromachines-15-01306" class="html-bibr">67</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-666X/15/11/1306'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/micromachines/micromachines-15-01306/article_deploy/html/images/micromachines-15-01306-g004-550.jpg?1730111311" title=" <strong>Figure 4</strong><br/> <p>Some practical application examples of the presented CMP pressure sensors. (<b>a</b>) Measurement of tremor signals from the throat of a volunteer. (<b>b</b>) The relative change in current of the sensor caused by muscular activity of speaking. (<b>c</b>) Plantar pressure measurement achieved by a sensor fixed on an insole. (<b>d</b>) Plantar pressure signals measurement during a series of continuous squatting activities. (<b>e</b>) Real-time response of continuous mouse click. (<b>f</b>) Real-time response of continuous pressing on the top surface of a sensor.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2072-666X/15/11/1306'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1504903" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 24 pages, 5194 KiB   </span> <a href="/2504-446X/8/11/606/pdf?version=1729850731" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Decentralized Multi-Agent Search for Moving Targets Using Road Network Gaussian Process Regressions" data-journal="drones"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2504-446X/8/11/606">Decentralized Multi-Agent Search for Moving Targets Using Road Network Gaussian Process Regressions</a> <div class="authors"> by <span class="inlineblock "><strong>Brady Moon</strong>, </span><span class="inlineblock "><strong>Christine Akagi</strong> and </span><span class="inlineblock "><strong>Cameron K. Peterson</strong></span> </div> <div class="color-grey-dark"> <em>Drones</em> <b>2024</b>, <em>8</em>(11), 606; <a href="https://doi.org/10.3390/drones8110606">https://doi.org/10.3390/drones8110606</a> - 23 Oct 2024 </div> Viewed by 1732 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Unmanned aerial vehicles (UAVs) can collaborate as teams to accomplish diverse mission objectives, such as target search and tracking. This paper introduces a method that leverages accumulated target-density information over the course of a UAV mission to adapt path-planning rewards, guiding UAVs toward <a href="#" data-counterslink = "https://www.mdpi.com/2504-446X/8/11/606/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Unmanned aerial vehicles (UAVs) can collaborate as teams to accomplish diverse mission objectives, such as target search and tracking. This paper introduces a method that leverages accumulated target-density information over the course of a UAV mission to adapt path-planning rewards, guiding UAVs toward areas with a higher likelihood of target presence. The target density is modeled using a Gaussian process, which is iteratively updated as the UAVs search the environment. Unlike conventional search algorithms that prioritize unexplored regions, this approach incentivizes revisiting target-rich areas. The target-density information is shared across UAVs using decentralized consensus filters, enabling cooperative path selection that balances the exploration of uncertain regions with the exploitation of known high-density areas. The framework presented in this paper provides an adaptive cooperative search method that can quickly develop an understanding of the region’s target-dense areas, helping UAVs refine their search. Through Monte Carlo simulations, we demonstrate this method in both a 2D grid region and road networks, showing up to a 26% improvement in target density estimates. <a href="/2504-446X/8/11/606">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Topic <a href="/topics/X896Y50INK">Civil and Public Domain Applications of Unmanned Aviation</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2504-446X/8/11/606/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1504903"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1504903"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1504903" data-cycle-prev="#prev1504903" data-cycle-progressive="#images1504903" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1504903-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g001-550.jpg?1729850795" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1504903" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1504903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g002-550.jpg?1729850796'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1504903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g003-550.jpg?1729850797'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1504903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g004-550.jpg?1729850798'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1504903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g005-550.jpg?1729850799'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1504903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g006-550.jpg?1729850801'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1504903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g007-550.jpg?1729850803'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1504903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g008-550.jpg?1729850805'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1504903-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g009-550.jpg?1729850807'><p>Figure 9</p></div></script></div></div><div id="article-1504903-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g001-550.jpg?1729850795" title=" <strong>Figure 1</strong><br/> <p>This figure depicts the research objective to efficiently search for targets using UAVs by predicting the target densities along the road networks based on their history of observations.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2504-446X/8/11/606'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g002-550.jpg?1729850796" title=" <strong>Figure 2</strong><br/> <p>This figure provides the functional diagram of our cooperative search algorithm. This shows that once vehicles sense information from their environment and share their local common operating picture then this information is incorporated in the road segment rewards.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2504-446X/8/11/606'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g003-550.jpg?1729850797" title=" <strong>Figure 3</strong><br/> <p>This figure illustrates the Rollout policy for path planning, which initially employs an exhaustive search before transitioning to a greedy heuristic policy once sufficient spatial diversity is achieved among the potential paths. The darker gray circles represent the states selected for expansion by the greedy heuristic policy.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2504-446X/8/11/606'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g004-550.jpg?1729850798" title=" <strong>Figure 4</strong><br/> <p>An illustration of how the length scale (<math display="inline"><semantics> <mi>λ</mi> </semantics></math>) and signal variance (<math display="inline"><semantics> <msubsup> <mi>σ</mi> <mi>f</mi> <mn>2</mn> </msubsup> </semantics></math>) influence the GP regression fit using test data generated from a noisy sine wave. (<b>a</b>) Under-fit GP regression; (<b>b</b>) Good-fit GP regression; (<b>c</b>) Over-fit GP Regression.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2504-446X/8/11/606'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g005-550.jpg?1729850799" title=" <strong>Figure 5</strong><br/> <p>This figure shows the Chatsworth simulation environment and true heat map at time <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>600</mn> </mrow> </semantics></math> s. (<b>a</b>) Target paths and road network; (<b>b</b>) True heat map.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2504-446X/8/11/606'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g006-550.jpg?1729850801" title=" <strong>Figure 6</strong><br/> <p>These figures display the heat maps and UAV paths for a single simulation run across all three search methods at time <math display="inline"><semantics> <mrow> <mi>t</mi> <mo>=</mo> <mn>600</mn> </mrow> </semantics></math> s, with two UAVs conducting searches in the Chatsworth region. (<b>a</b>) UMSR Method; (<b>b</b>) HMMSR Method; (<b>c</b>) GP Regression Method; (<b>d</b>) Heat map for UMSR; (<b>e</b>) Heat map for HMMSR; (<b>f</b>) Heat map for GP regression.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2504-446X/8/11/606'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g007-550.jpg?1729850803" title=" <strong>Figure 7</strong><br/> <p>RMS errors for the heat map averaged over 100 MC runs for 600 s using the grid cell method in the Chatsworth region.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2504-446X/8/11/606'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g008-550.jpg?1729850805" title=" <strong>Figure 8</strong><br/> <p>Chatsworth as a road network.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2504-446X/8/11/606'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/drones/drones-08-00606/article_deploy/html/images/drones-08-00606-g009-550.jpg?1729850807" title=" <strong>Figure 9</strong><br/> <p>RMS errors for the heat map averaged over 100 MC runs for 600 s using the Chatsworth road network.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2504-446X/8/11/606'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1504465" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 15 pages, 1050 KiB   </span> <a href="/2227-9067/11/11/1276/pdf?version=1730360340" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="The Otoacoustic Emissions in the Universal Neonatal Hearing Screening: An Update on the European Data (2004 to 2024)" data-journal="children"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Review</span></div> <a class="title-link" href="/2227-9067/11/11/1276">The Otoacoustic Emissions in the Universal Neonatal Hearing Screening: An Update on the European Data (2004 to 2024)</a> <div class="authors"> by <span class="inlineblock "><strong>Stavros Hatzopoulos</strong>, </span><span class="inlineblock "><strong>Ludovica Cardinali</strong>, </span><span class="inlineblock "><strong>Piotr Henryk Skarżyński</strong> and </span><span class="inlineblock "><strong>Giovanna Zimatore</strong></span> </div> <div class="color-grey-dark"> <em>Children</em> <b>2024</b>, <em>11</em>(11), 1276; <a href="https://doi.org/10.3390/children11111276">https://doi.org/10.3390/children11111276</a> - 23 Oct 2024 </div> Viewed by 634 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> <b>Background:</b> The reported data on European universal neonatal hearing screening (UNHS) practices tend to be scarce, despite the fact that the European Union project, EUScreen, collected unofficial data from 38 collaborating European institutions. The objectives of this systematic review were as follows: (a) <a href="#" data-counterslink = "https://www.mdpi.com/2227-9067/11/11/1276/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> <b>Background:</b> The reported data on European universal neonatal hearing screening (UNHS) practices tend to be scarce, despite the fact that the European Union project, EUScreen, collected unofficial data from 38 collaborating European institutions. The objectives of this systematic review were as follows: (a) to identify the most recent (in a 20-year span) literature information about UNHS programs in Europe and (b) to provide data on the procedures used to assess the population, the intervention policies, and on the estimated prevalence of congenital hearing loss with emphasis on the bilateral hearing loss cases. <b>Methods:</b> Queries were conducted via the Pubmed, Scopus and Google Scholar databases for the time period of 2004–2024. The Mesh terms used were “OAE”, “Universal Neonatal Hearing Screening”, “congenital hearing loss” and “well babies”. Only research articles and review papers of European origin were considered good candidates. The standard English language filter was not used, in order to identify information from non-English-speaking scientific communities and groups. <b>Results:</b> Very few data and reports were identified in the literature search. Eleven manuscripts were identified corresponding to eight UNHS programs. Except in Poland, most of the data refer to regional and not national programs. The screening coverage estimates of all programs exceed 90%; infants were mostly assessed by a three-stage protocol (TEOAE + TEOAE + AABR), followed by a clinical ABR test. The average prevalence (i.e., from well babies AND NICU infants) of bilateral hearing loss ranged from 0.5 to 20.94 per 1000 (Zurich sample). Infants presenting unilateral or bilateral hearing losses were first rehabilitated by hearing aids and consequently (>15 mo) by cochlear implants. <b>Conclusions:</b> Even though UNHS programs are well-established clinical practices in the European States, the amount of information in the literature about these programs is surprising low. The existing data in the timespan 2004–2024 corroborate the international UNHS data in terms of coverage and bilateral hearing loss prevalence, but there is a strong need to supplement the existing information with the latest developments, especially in the area of hearing loss rehabilitation. <a href="/2227-9067/11/11/1276">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Section <a href="/journal/children/sections/pediatric_otolaryngology">Pediatric Otolaryngology</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2227-9067/11/11/1276/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1504465"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1504465"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1504465" data-cycle-prev="#prev1504465" data-cycle-progressive="#images1504465" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1504465-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/children/children-11-01276/article_deploy/html/images/children-11-01276-g001-550.jpg?1730360428" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1504465" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1504465-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/children/children-11-01276/article_deploy/html/images/children-11-01276-g002-550.jpg?1730360430'><p>Figure 2</p></div></script></div></div><div id="article-1504465-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/children/children-11-01276/article_deploy/html/images/children-11-01276-g001-550.jpg?1730360428" title=" <strong>Figure 1</strong><br/> <p>Schematic view of the Auditory periphery, which is assessed in neonatal hearing screening. Hearing deficits can occur in all 3 compartments (i.e., external, middle, inner) as well at the level of the auditory nerve fibers, modified from [<a href="#B14-children-11-01276" class="html-bibr">14</a>]. OAEs can identify hearing loss issues up to the level of outer hair cells (the left in green, an example of a hair cell, not to scale with the rest of the illustration); AABR/ABR extend the hearing loss identification at the level of the auditory nerve fibers and the brainstem. Figure created with BioRender.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9067/11/11/1276'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/children/children-11-01276/article_deploy/html/images/children-11-01276-g002-550.jpg?1730360430" title=" <strong>Figure 2</strong><br/> <p>Flow diagram of the literature search, according to PRISMA criteria (<a href="http://www.prisma-statement.org/" target="_blank">http://www.prisma-statement.org/</a>, accessed on 31 July 2024), with the steps followed in the manuscript selection procedure. After the application of the selection criteria, the initial 244 manuscripts were reduced to 11 (see <a href="#children-11-01276-t001" class="html-table">Table 1</a> “Universal newborn hearing screening” Pubmed + Scopus).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2227-9067/11/11/1276'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1504371" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 18 pages, 3322 KiB   </span> <a href="/2073-431X/13/11/275/pdf?version=1729650961" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Enhanced Collaborative Filtering: Combining Autoencoder and Opposite User Inference to Solve Sparsity and Gray Sheep Issues" data-journal="computers"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2073-431X/13/11/275">Enhanced Collaborative Filtering: Combining Autoencoder and Opposite User Inference to Solve Sparsity and Gray Sheep Issues</a> <div class="authors"> by <span class="inlineblock "><strong>Lamyae El Youbi El Idrissi</strong>, </span><span class="inlineblock "><strong>Ismail Akharraz</strong>, </span><span class="inlineblock "><strong>Aziza El Ouaazizi</strong> and </span><span class="inlineblock "><strong>Abdelaziz Ahaitouf</strong></span> </div> <div class="color-grey-dark"> <em>Computers</em> <b>2024</b>, <em>13</em>(11), 275; <a href="https://doi.org/10.3390/computers13110275">https://doi.org/10.3390/computers13110275</a> - 23 Oct 2024 </div> Viewed by 681 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In recent years, the study of recommendation systems has become crucial, capturing the interest of scientists and academics worldwide. Music, books, movies, news, conferences, courses, and learning materials are some examples of using the recommender system. Among the various strategies employed, collaborative filtering <a href="#" data-counterslink = "https://www.mdpi.com/2073-431X/13/11/275/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In recent years, the study of recommendation systems has become crucial, capturing the interest of scientists and academics worldwide. Music, books, movies, news, conferences, courses, and learning materials are some examples of using the recommender system. Among the various strategies employed, collaborative filtering stands out as one of the most common and effective approaches. This method identifies similar active users to make item recommendations. However, collaborative filtering has two major challenges: sparsity and gray sheep. Inspired by the remarkable success of deep learning across a multitude of application areas, we have integrated deep learning techniques into our proposed method to effectively address the aforementioned challenges. In this paper, we present a new method called Enriched_AE, focused on autoencoder, a well-regarded unsupervised deep learning technique renowned for its superior ability in data dimensionality reduction, feature extraction, and data reconstruction, with an augmented rating matrix. This matrix not only includes real users but also incorporates virtual users inferred from opposing ratings given by real users. By doing so, we aim to enhance the accuracy of predictions, thus enabling more effective recommendation generation. Through experimental analysis of the MovieLens 100K dataset, we observe that our method achieves notable reductions in both RMSE (Root Mean Squared Error) and MAE (Mean Absolute Error), underscoring its superiority over the state-of-the-art collaborative filtering models. <a href="/2073-431X/13/11/275">Full article</a> </div> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2073-431X/13/11/275/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1504371"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1504371"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1504371" data-cycle-prev="#prev1504371" data-cycle-progressive="#images1504371" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1504371-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g001-550.jpg?1729651075" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1504371" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1504371-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g002-550.jpg?1729651077'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1504371-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g003-550.jpg?1729651077'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1504371-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g004-550.jpg?1729651078'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1504371-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g005-550.jpg?1729651080'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1504371-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g006-550.jpg?1729651081'><p>Figure 6</p></div> --- <div class='openpopupgallery' data-imgindex='6' data-target='article-1504371-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g007-550.jpg?1729651081'><p>Figure 7</p></div> --- <div class='openpopupgallery' data-imgindex='7' data-target='article-1504371-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g008-550.jpg?1729651083'><p>Figure 8</p></div> --- <div class='openpopupgallery' data-imgindex='8' data-target='article-1504371-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g009-550.jpg?1729651084'><p>Figure 9</p></div> --- <div class='openpopupgallery' data-imgindex='9' data-target='article-1504371-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g010-550.jpg?1729651085'><p>Figure 10</p></div></script></div></div><div id="article-1504371-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g001-550.jpg?1729651075" title=" <strong>Figure 1</strong><br/> <p>Classification of Recommender Systems in the Application Phase According to the Study of Taghavi et al. [<a href="#B7-computers-13-00275" class="html-bibr">7</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g002-550.jpg?1729651077" title=" <strong>Figure 2</strong><br/> <p>Hierarchical flow summary for tackling recommender system issues; the orange-colored boxes represent the hierarchical pathway of the research problem.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g003-550.jpg?1729651077" title=" <strong>Figure 3</strong><br/> <p>Structure of a basic AE.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g004-550.jpg?1729651078" title=" <strong>Figure 4</strong><br/> <p>Study Workflow Diagram.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g005-550.jpg?1729651080" title=" <strong>Figure 5</strong><br/> <p>User’s rating distribution of the MovieLens 100K dataset: (<b>A</b>) Distribution of the number of ratings given by each user; (<b>B</b>) Distribution of different rating values.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g006-550.jpg?1729651081" title=" <strong>Figure 6</strong><br/> <p>Model loss Enriched_AE.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g007-550.jpg?1729651081" title=" <strong>Figure 7</strong><br/> <p>Model loss AE.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g008-550.jpg?1729651083" title=" <strong>Figure 8</strong><br/> <p>Comparison between the proposed method and benchmark methods based on MAE.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g009-550.jpg?1729651084" title=" <strong>Figure 9</strong><br/> <p>Comparison of the proposed method with benchmark approaches focusing on RMSE.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/computers/computers-13-00275/article_deploy/html/images/computers-13-00275-g010-550.jpg?1729651085" title=" <strong>Figure 10</strong><br/> <p>Comparison of AE and Enriched_AE.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2073-431X/13/11/275'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1503782" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 25 pages, 4129 KiB   </span> <a href="/2071-1050/16/21/9144/pdf?version=1729584686" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="Navigating the Nexus of Artificial Intelligence and Renewable Energy for the Advancement of Sustainable Development Goals" data-journal="sustainability"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2071-1050/16/21/9144">Navigating the Nexus of Artificial Intelligence and Renewable Energy for the Advancement of Sustainable Development Goals</a> <div class="authors"> by <span class="inlineblock "><strong>Raghu Raman</strong>, </span><span class="inlineblock "><strong>Sangeetha Gunasekar</strong>, </span><span class="inlineblock "><strong>Deepa Kaliyaperumal</strong> and </span><span class="inlineblock "><strong>Prema Nedungadi</strong></span> </div> <div class="color-grey-dark"> <em>Sustainability</em> <b>2024</b>, <em>16</em>(21), 9144; <a href="https://doi.org/10.3390/su16219144">https://doi.org/10.3390/su16219144</a> - 22 Oct 2024 </div> Viewed by 1465 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> The integration of artificial intelligence (AI) into renewable energy and sustainability represents a transformative approach toward achieving sustainable development goals (SDGs), especially SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 13 (Climate Action). This study utilized the <a href="#" data-counterslink = "https://www.mdpi.com/2071-1050/16/21/9144/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> The integration of artificial intelligence (AI) into renewable energy and sustainability represents a transformative approach toward achieving sustainable development goals (SDGs), especially SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), and SDG 13 (Climate Action). This study utilized the PRISMA framework to conduct a systematic review, focusing on the role of AI in renewable energy and sustainable development. This research utilized Scopus’s curated AI research area, which employs text mining to refine AI concepts into unique keywords. Further refinement via the All Science Journals Classification system and SDG-mapping filters narrowed the focus to publications relevant to renewable energy and SDGs. By employing the BERTopic modeling approach, our study identifies major topics, such as enhancing wind speed forecasts, performance analysis of fuel cells, energy management in elective vehicles, solar irradiance prediction, optimizing biofuel production, and improving energy efficiency in buildings. AI-driven models offer promising solutions to address the dynamic challenges of sustainable energy. Insights from academia-industry collaborations indicate that such partnerships significantly accelerate sustainable-energy transitions, with a focus on AI-driven energy storage, grid management, and renewable-energy forecasting. A global consensus on the critical role of investing in technology-driven solutions for energy sustainability was underscored by the relationship between funding data and global R&D spending patterns. This study serves as a resource for practitioners to harness AI technologies for renewable energy, where for example, AI’s accurate wind speed predictions can increase wind farm efficiency, highlighting the necessity of innovation and collaboration for sustainable development. <a href="/2071-1050/16/21/9144">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/sustainability/special_issues/energy_economics_policy_sus ">Energy Economics and Energy Policy towards Sustainability</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2071-1050/16/21/9144/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1503782"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1503782"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1503782" data-cycle-prev="#prev1503782" data-cycle-progressive="#images1503782" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1503782-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g001-550.jpg?1729584806" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1503782" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1503782-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g002a-550.jpg?1729584809'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1503782-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g002b-550.jpg?1729584811'><p>Figure 2 Cont.</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1503782-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g003-550.jpg?1729584812'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1503782-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g004-550.jpg?1729584814'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1503782-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g005-550.jpg?1729584817'><p>Figure 5</p></div></script></div></div><div id="article-1503782-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g001-550.jpg?1729584806" title=" <strong>Figure 1</strong><br/> <p>Research design.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/21/9144'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g002a-550.jpg?1729584809" title=" <strong>Figure 2</strong><br/> <p>Evolution of major topics according to publications.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/21/9144'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g002b-550.jpg?1729584811" title=" <strong>Figure 2 Cont.</strong><br/> <p>Evolution of major topics according to publications.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/21/9144'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g003-550.jpg?1729584812" title=" <strong>Figure 3</strong><br/> <p>Thematic clusters based on keywords from the industry–academia collaboration.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/21/9144'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g004-550.jpg?1729584814" title=" <strong>Figure 4</strong><br/> <p>Mapping funders based on publications and citations. The yellow and blue lines in the quadrant chart represent thresholds for citations and publications, respectively.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/21/9144'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/sustainability/sustainability-16-09144/article_deploy/html/images/sustainability-16-09144-g005-550.jpg?1729584817" title=" <strong>Figure 5</strong><br/> <p>Future research framework.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2071-1050/16/21/9144'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1499963" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 16 pages, 2366 KiB   </span> <a href="/2079-9292/13/20/4073/pdf?version=1729135753" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="UDIS: Enhancing Collaborative Filtering with Fusion of Dimensionality Reduction and Semantic Similarity" data-journal="electronics"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2079-9292/13/20/4073">UDIS: Enhancing Collaborative Filtering with Fusion of Dimensionality Reduction and Semantic Similarity</a> <div class="authors"> by <span class="inlineblock "><strong>Hamidreza Koohi</strong>, </span><span class="inlineblock "><strong>Ziad Kobti</strong>, </span><span class="inlineblock "><strong>Tahereh Farzi</strong> and </span><span class="inlineblock "><strong>Emad Mahmodi</strong></span> </div> <div class="color-grey-dark"> <em>Electronics</em> <b>2024</b>, <em>13</em>(20), 4073; <a href="https://doi.org/10.3390/electronics13204073">https://doi.org/10.3390/electronics13204073</a> - 16 Oct 2024 </div> Viewed by 671 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> In the era of vast information, individuals are immersed in choices when purchasing goods and services. Recommender systems (RS) have emerged as vital tools to navigate these excess options. However, these systems encounter challenges like data sparsity, impairing their effectiveness. This paper proposes <a href="#" data-counterslink = "https://www.mdpi.com/2079-9292/13/20/4073/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> In the era of vast information, individuals are immersed in choices when purchasing goods and services. Recommender systems (RS) have emerged as vital tools to navigate these excess options. However, these systems encounter challenges like data sparsity, impairing their effectiveness. This paper proposes a novel approach to address this issue and enhance RS performance. By integrating user demographic data, singular value decomposition (SVD) clustering, and semantic similarity in collaborative filtering (CF), we introduce the UDIS method. This method amalgamates four prediction types—user-based CF (U), demographic-similarity-based (D), item-based CF (I), and semantic-similarity-based (S). UDIS generates separate predictions for each category and evaluates four different merging techniques—the average, max, weighted sum, and Shambour methods—to integrate these predictions. Among these, the average method proved most effective, offering a balanced approach that significantly improved precision and accuracy on the MovieLens dataset compared to alternative methods. <a href="/2079-9292/13/20/4073">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Special Issue <a href=" /journal/electronics/special_issues/50EK4W3G1P ">Knowledge Information Extraction Research</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2079-9292/13/20/4073/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1499963"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1499963"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1499963" data-cycle-prev="#prev1499963" data-cycle-progressive="#images1499963" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1499963-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g001-550.jpg?1729135846" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1499963" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1499963-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g002-550.jpg?1729135848'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1499963-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g003-550.jpg?1729135850'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1499963-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g004-550.jpg?1729135852'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1499963-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g005-550.jpg?1729135853'><p>Figure 5</p></div></script></div></div><div id="article-1499963-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g001-550.jpg?1729135846" title=" <strong>Figure 1</strong><br/> <p>Architecture of the proposed UDIS.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/20/4073'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g002-550.jpg?1729135848" title=" <strong>Figure 2</strong><br/> <p>Comparison results of four different integration methods in the accuracy measures.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/20/4073'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g003-550.jpg?1729135850" title=" <strong>Figure 3</strong><br/> <p>Comparison results of four different integration methods in precision measures.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/20/4073'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g004-550.jpg?1729135852" title=" <strong>Figure 4</strong><br/> <p>Comparison of UDIS method based on FCM clustering with k-means, SOM, and EM methods in the accuracy measure.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/20/4073'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/electronics/electronics-13-04073/article_deploy/html/images/electronics-13-04073-g005-550.jpg?1729135853" title=" <strong>Figure 5</strong><br/> <p>Comparison of UDIS method based on FCM clustering with k-means, SOM, and EM methods in the precision measure.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2079-9292/13/20/4073'>Full article</a></strong> "></a></div> </div> </div> <div class="generic-item article-item"> <input class="article-list-checkbox export-element" type="checkbox" name="articles_ids[]" value="1491435" data-select-all-name="article-listing"> <div class="article-content"> <div class="label right label__btn"> <span style="font-size: 12px; color: #1a1a1a;"> 19 pages, 1874 KiB   </span> <a href="/2673-6489/4/4/42/pdf?version=1727882336" class="UD_Listings_ArticlePDF" title="Article PDF" data-name="An AI-Based Approach for Developing a Recommendation System for Underground Mining Methods Pre-Selection" data-journal="mining"> <i class="material-icons custom-download"></i> </a> </div> <div class="article-icons"><span class="label openaccess" data-dropdown="drop-article-label-openaccess" aria-expanded="false">Open Access</span><span class="label articletype">Article</span></div> <a class="title-link" href="/2673-6489/4/4/42">An AI-Based Approach for Developing a Recommendation System for Underground Mining Methods Pre-Selection</a> <div class="authors"> by <span class="inlineblock "><strong>Elsa Pansilvania Andre Manjate</strong>, </span><span class="inlineblock "><strong>Natsuo Okada</strong>, </span><span class="inlineblock "><strong>Yoko Ohtomo</strong>, </span><span class="inlineblock "><strong>Tsuyoshi Adachi</strong>, </span><span class="inlineblock "><strong>Bernardo Miguel Bene</strong>, </span><span class="inlineblock "><strong>Takahiko Arima</strong> and </span><span class="inlineblock "><strong>Youhei Kawamura</strong></span> </div> <div class="color-grey-dark"> <em>Mining</em> <b>2024</b>, <em>4</em>(4), 747-765; <a href="https://doi.org/10.3390/mining4040042">https://doi.org/10.3390/mining4040042</a> - 2 Oct 2024 </div> Viewed by 851 <div class="abstract-div"> <a href="#" onclick="$(this).next('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> <strong>Abstract </strong> </a> <div class="abstract-cropped inline"> Selecting the most appropriate mining method to recover mineral resources is a critical decision-making task in mining project development. This study introduces an artificial intelligence-based mining methods recommendation system (AI-MMRS) for the pre-selection of underground mining methods. The study integrates and evaluates the <a href="#" data-counterslink = "https://www.mdpi.com/2673-6489/4/4/42/more" onclick="$(this).parents('.abstract-cropped').toggleClass('inline').next('.abstract-full').toggleClass('inline'); return false;"> [...] Read more.</a> </div> <div class="abstract-full "> Selecting the most appropriate mining method to recover mineral resources is a critical decision-making task in mining project development. This study introduces an artificial intelligence-based mining methods recommendation system (AI-MMRS) for the pre-selection of underground mining methods. The study integrates and evaluates the capability of two approaches for mining methods selection (MMS): the memory-based collaborative filtering (CF) approach aided by the UBC-MMS system to predict the top-3 relevant mining methods and supervised machine learning (ML) classification algorithms to enhance the effectiveness and novelty of the AI-MMRS, addressing the limitations of the CF approach. The results reveal that the memory-based CF approach achieves an accuracy ranging from 81.8% to 87.9%. Among the classification algorithms, artificial neural network (ANN) and k-nearest neighbors (KNN) classifiers perform the best, with accuracy levels of 66.7% and 63.6%, respectively. These findings demonstrate the effectiveness and viability of both approaches in MMS, acknowledging their limitations and the need for continuous training and optimization. The proposed AI-MMRS for the pre-selection stage supplemented by the direct involvement of mining professionals in later stages of MMS, has the potential to significantly aid in the MMS decision-making, providing data-driven and experience-based recommendations following the ongoing evolution of mining practices. <a href="/2673-6489/4/4/42">Full article</a> </div> </div> <div class="belongsTo" style="margin-bottom: 10px;"> (This article belongs to the Topic <a href="/topics/V3W8O5TWEY">Mining Innovation</a>)<br/> </div> <a href="#" class="abstract-figures-show" data-counterslink = "https://www.mdpi.com/2673-6489/4/4/42/show" ><span >►</span><span style=" display: none;">▼</span> Show Figures </a><div class="abstract-image-preview "><div class="arrow left-arrow" id="prev1491435"><i class="fa fa-caret-left"></i></div><div class="arrow right-arrow" id="next1491435"><i class="fa fa-caret-right"></i></div><div class="absgraph cycle-slideshow manual" data-cycle-fx="scrollHorz" data-cycle-timeout="0" data-cycle-next="#next1491435" data-cycle-prev="#prev1491435" data-cycle-progressive="#images1491435" data-cycle-slides=">div" data-cycle-log="false"><div class='openpopupgallery cycle-slide' data-imgindex='0' data-target='article-1491435-popup'><span class="helper"></span><img src="data:image/gif;base64,R0lGODlhAQABAAD/ACwAAAAAAQABAAACADs=" data-src="https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g001-550.jpg?1727882427" alt="" style="border: 0;"><p>Figure 1</p></div><script id="images1491435" type="text/cycle" data-cycle-split="---"><div class='openpopupgallery' data-imgindex='1' data-target='article-1491435-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g002-550.jpg?1727882429'><p>Figure 2</p></div> --- <div class='openpopupgallery' data-imgindex='2' data-target='article-1491435-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g003-550.jpg?1727882430'><p>Figure 3</p></div> --- <div class='openpopupgallery' data-imgindex='3' data-target='article-1491435-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g004-550.jpg?1727882433'><p>Figure 4</p></div> --- <div class='openpopupgallery' data-imgindex='4' data-target='article-1491435-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g005-550.jpg?1727882434'><p>Figure 5</p></div> --- <div class='openpopupgallery' data-imgindex='5' data-target='article-1491435-popup'><span class="helper"></span><img src='https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g006-550.jpg?1727882435'><p>Figure 6</p></div></script></div></div><div id="article-1491435-popup" class="popupgallery" style="display: inline; line-height: 200%"><a href="https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g001-550.jpg?1727882427" title=" <strong>Figure 1</strong><br/> <p>Methodology for developing the AI-MMRS (DMS: document management software: LogicalDOC Business version 8.7.3; ML: machine learning, CF: collaborative filtering, NMF: nonnegative matrix factorization) [<a href="#B10-mining-04-00042" class="html-bibr">10</a>,<a href="#B11-mining-04-00042" class="html-bibr">11</a>].</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-6489/4/4/42'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g002-550.jpg?1727882429" title=" <strong>Figure 2</strong><br/> <p>Collaborative filtering recommendation system framework based on the user–item interaction dataset <span class="html-italic">X</span> composed of u-users and i-items with ratings ranging from 1 to 5, “?” unknown or missing rating.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-6489/4/4/42'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g003-550.jpg?1727882430" title=" <strong>Figure 3</strong><br/> <p>Showing the data pre-processing: transformation of the input dataset for experiments to evaluate the proposed memory-based collaborative filtering approach.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-6489/4/4/42'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g004-550.jpg?1727882433" title=" <strong>Figure 4</strong><br/> <p>Workflow of the proposed methodology for practical experiments: the memory-based collaborative filtering approach for predicting and recommending top-N mining methods.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-6489/4/4/42'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g005-550.jpg?1727882434" title=" <strong>Figure 5</strong><br/> <p>Performance of the proposed model in predicting primary and top-3 most relevant mining methods in terms of GAR and F1-score.</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-6489/4/4/42'>Full article</a></strong> "></a><a href="https://pub.mdpi-res.com/mining/mining-04-00042/article_deploy/html/images/mining-04-00042-g006-550.jpg?1727882435" title=" <strong>Figure 6</strong><br/> <p>Confusion matrix of the artificial neural network (ANN) model showing the per-class Recall or True Positive Rate (TPR) and the True Negative Rate (TNR).</p> <strong style='display: block; margin-top: 10px; font-size: 18px;'><a style='color: #fff' href='/2673-6489/4/4/42'>Full article</a></strong> "></a></div> </div> </div> <span class="more" style="display: none;"></span> </div> <div class="row footer"> <div class="listing-select-options"> <div class="columns small-12"> <div class="select generic-item"> <a href="#" class="export-options-show export-element export-expanded"> Show export options <i class="material-icons">expand_more</i> </a> <a href="#" class="export-options-show export-element"> Show export options <i class="material-icons">expand_less</i> </a> </div> <div class="listing-export-options export-element"> <div class="export-element" style="margin-top: 10px; margin-bottom: 10px;"> <input type="checkbox" class="selector selectUnselectAll bb-checkbox" id="selectUnselectAll" data-select-all="article-listing"> <div class="indented bb-indented"> Select all </div> </div> <div class="indented1"> <span style="display: inline-block; 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