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EEGLAB</title> <meta name="description" content="Search results for: EEGLAB"> <meta name="keywords" content="EEGLAB"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" 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class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="EEGLAB"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 7</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: EEGLAB</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7</span> Noninvasive Brain-Machine Interface to Control Both Mecha TE Robotic Hands Using Emotiv EEG Neuroheadset</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Adrienne%20Kline">Adrienne Kline</a>, <a href="https://publications.waset.org/abstracts/search?q=Jaydip%20Desai"> Jaydip Desai</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=brain-machine%20interface" title="brain-machine interface">brain-machine interface</a>, <a href="https://publications.waset.org/abstracts/search?q=EEGLAB" title=" EEGLAB"> EEGLAB</a>, <a href="https://publications.waset.org/abstracts/search?q=emotiv%20EEG%20neuroheadset" title=" emotiv EEG neuroheadset"> emotiv EEG neuroheadset</a>, <a href="https://publications.waset.org/abstracts/search?q=OpenViBE" title=" OpenViBE"> OpenViBE</a>, <a href="https://publications.waset.org/abstracts/search?q=simulink" title=" simulink"> simulink</a> </p> <a href="https://publications.waset.org/abstracts/28333/noninvasive-brain-machine-interface-to-control-both-mecha-te-robotic-hands-using-emotiv-eeg-neuroheadset" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28333.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">502</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">6</span> Real Time Acquisition and Psychoacoustic Analysis of Brain Wave</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shweta%20Singh">Shweta Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Dipali%20Bansal"> Dipali Bansal</a>, <a href="https://publications.waset.org/abstracts/search?q=Rashima%20Mahajan"> Rashima Mahajan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Psychoacoustics has become a potential area of research due to the growing interest of both laypersons and medical and mental health professionals. Non-invasive brain computer interface like Electroencephalography (EEG) is widely being used in this field. An attempt has been made in this paper to examine the response of EEG signals to acoustic stimuli further analysing the brain electrical activity. The real time EEG is acquired for 6 participants using a cost effective and portable EMOTIV EEG neuron headset. EEG data analysis is further done using EMOTIV test bench, EDF browser and EEGLAB (MATLAB Tool) application software platforms. Spectral analysis of acquired neural signals (AF3 channel) using these software platforms are clearly indicative of increased brain activity in various bands. The inferences drawn from such an analysis have significant correlation with subject’s subjective reporting of the experiences. The results suggest that the methodology adopted can further be used to assist patients with sleeping and depressive disorders. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=OM%20chant" title="OM chant">OM chant</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20analysis" title=" spectral analysis"> spectral analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=EDF%20browser" title=" EDF browser"> EDF browser</a>, <a href="https://publications.waset.org/abstracts/search?q=EEGLAB" title=" EEGLAB"> EEGLAB</a>, <a href="https://publications.waset.org/abstracts/search?q=EMOTIV" title=" EMOTIV"> EMOTIV</a>, <a href="https://publications.waset.org/abstracts/search?q=real%20time%20acquisition" title=" real time acquisition"> real time acquisition</a> </p> <a href="https://publications.waset.org/abstracts/6427/real-time-acquisition-and-psychoacoustic-analysis-of-brain-wave" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6427.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">281</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">5</span> A Real Time Set Up for Retrieval of Emotional States from Human Neural Responses</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashima%20Mahajan">Rashima Mahajan</a>, <a href="https://publications.waset.org/abstracts/search?q=Dipali%20Bansal"> Dipali Bansal</a>, <a href="https://publications.waset.org/abstracts/search?q=Shweta%20Singh"> Shweta Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=brain%20computer%20interface" title="brain computer interface">brain computer interface</a>, <a href="https://publications.waset.org/abstracts/search?q=electroencephalogram" title=" electroencephalogram"> electroencephalogram</a>, <a href="https://publications.waset.org/abstracts/search?q=EEGLab" title=" EEGLab"> EEGLab</a>, <a href="https://publications.waset.org/abstracts/search?q=BCILab" title=" BCILab"> BCILab</a>, <a href="https://publications.waset.org/abstracts/search?q=emotive" title=" emotive"> emotive</a>, <a href="https://publications.waset.org/abstracts/search?q=emotions" title=" emotions"> emotions</a>, <a href="https://publications.waset.org/abstracts/search?q=interval%20features" title=" interval features"> interval features</a>, <a href="https://publications.waset.org/abstracts/search?q=spectral%20features" title=" spectral features"> spectral features</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20neural%20network" title=" artificial neural network"> artificial neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=control%20applications" title=" control applications"> control applications</a> </p> <a href="https://publications.waset.org/abstracts/6428/a-real-time-set-up-for-retrieval-of-emotional-states-from-human-neural-responses" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6428.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">317</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4</span> Analysis of Matching Pursuit Features of EEG Signal for Mental Tasks Classification </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zin%20Mar%20Lwin">Zin Mar Lwin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=BCI" title="BCI">BCI</a>, <a href="https://publications.waset.org/abstracts/search?q=EEG" title=" EEG"> EEG</a>, <a href="https://publications.waset.org/abstracts/search?q=ICA" title=" ICA"> ICA</a>, <a href="https://publications.waset.org/abstracts/search?q=SVM" title=" SVM"> SVM</a> </p> <a href="https://publications.waset.org/abstracts/19307/analysis-of-matching-pursuit-features-of-eeg-signal-for-mental-tasks-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19307.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">277</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> An Analysis of the Temporal Aspects of Visual Attention Processing Using Rapid Series Visual Processing (RSVP) Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shreya%20Borthakur">Shreya Borthakur</a>, <a href="https://publications.waset.org/abstracts/search?q=Aastha%20Vartak"> Aastha Vartak</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This Electroencephalogram (EEG) project on Rapid Visual Serial Processing (RSVP) paradigm explores the temporal dynamics of visual attention processing in response to rapidly presented visual stimuli. The study builds upon previous research that used real-world images in RSVP tasks to understand the emergence of object representations in the human brain. The objectives of the research include investigating the differences in accuracy and reaction times between 5 Hz and 20 Hz presentation rates, as well as examining the prominent brain waves, particularly alpha and beta waves, associated with the attention task. The pre-processing and data analysis involves filtering EEG data, creating epochs for target stimuli, and conducting statistical tests using MATLAB, EEGLAB, Chronux toolboxes, and R. The results support the hypotheses, revealing higher accuracy at a slower presentation rate, faster reaction times for less complex targets, and the involvement of alpha and beta waves in attention and cognitive processing. This research sheds light on how short-term memory and cognitive control affect visual processing and could have practical implications in fields like education. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=RSVP" title="RSVP">RSVP</a>, <a href="https://publications.waset.org/abstracts/search?q=attention" title=" attention"> attention</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20processing" title=" visual processing"> visual processing</a>, <a href="https://publications.waset.org/abstracts/search?q=attentional%20blink" title=" attentional blink"> attentional blink</a>, <a href="https://publications.waset.org/abstracts/search?q=EEG" title=" EEG"> EEG</a> </p> <a href="https://publications.waset.org/abstracts/169655/an-analysis-of-the-temporal-aspects-of-visual-attention-processing-using-rapid-series-visual-processing-rsvp-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/169655.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">69</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> The Comparative Electroencephalogram Study: Children with Autistic Spectrum Disorder and Healthy Children Evaluate Classical Music in Different Ways</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Galina%20Portnova">Galina Portnova</a>, <a href="https://publications.waset.org/abstracts/search?q=Kseniya%20Gladun"> Kseniya Gladun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In our EEG experiment participated 27 children with ASD with the average age of 6.13 years and the average score for CARS 32.41 and 25 healthy children (of 6.35 years). Six types of musical stimulation were presented, included Gluck, Javier-Naida, Kenny G, Chopin and other classic musical compositions. Children with autism showed orientation reaction to the music and give behavioral responses to different types of music, some of them might assess stimulation by scales. The participants were instructed to remain calm. Brain electrical activity was recorded using a 19-channel EEG recording device, 'Encephalan' (Russia, Taganrog). EEG epochs lasting 150 s were analyzed using EEGLab plugin for MatLab (Mathwork Inc.). For EEG analysis we used Fast Fourier Transform (FFT), analyzed Peak alpha frequency (PAF), correlation dimension D2 and Stability of rhythms. To express the dynamics of desynchronizing of different rhythms we've calculated the envelope of the EEG signal, using the whole frequency range and a set of small narrowband filters using Hilbert transformation. Our data showed that healthy children showed similar EEG spectral changes during musical stimulation as well as described the feelings induced by musical fragments. The exception was the ‘Chopin. Prelude’ fragment (no.6). This musical fragment induced different subjective feeling, behavioral reactions and EEG spectral changes in children with ASD and healthy children. The correlation dimension D2 was significantly lower in autists compared to healthy children during musical stimulation. Hilbert envelope frequency was reduced in all group of subjects during musical compositions 1,3,5,6 compositions compared to the background. During musical fragments 2 and 4 (terrible) lower Hilbert envelope frequency was observed only in children with ASD and correlated with the severity of the disease. Alfa peak frequency was lower compared to the background during this musical composition in healthy children and conversely higher in children with ASD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electroencephalogram%20%20%28EEG%29" title="electroencephalogram (EEG)">electroencephalogram (EEG)</a>, <a href="https://publications.waset.org/abstracts/search?q=emotional%20perception" title=" emotional perception"> emotional perception</a>, <a href="https://publications.waset.org/abstracts/search?q=ASD" title=" ASD"> ASD</a>, <a href="https://publications.waset.org/abstracts/search?q=musical%20perception" title=" musical perception"> musical perception</a>, <a href="https://publications.waset.org/abstracts/search?q=childhood%20Autism%20rating%20scale%20%20%28CARS%29" title=" childhood Autism rating scale (CARS)"> childhood Autism rating scale (CARS)</a> </p> <a href="https://publications.waset.org/abstracts/62155/the-comparative-electroencephalogram-study-children-with-autistic-spectrum-disorder-and-healthy-children-evaluate-classical-music-in-different-ways" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62155.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">284</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Perception of Tactile Stimuli in Children with Autism Spectrum Disorder</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kseniya%20Gladun">Kseniya Gladun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Tactile stimulation of a dorsal side of the wrist can have a strong impact on our attitude toward physical objects such as pleasant and unpleasant impact. This study explored different aspects of tactile perception to investigate atypical touch sensitivity in children with autism spectrum disorder (ASD). This study included 40 children with ASD and 40 healthy children aged 5 to 9 years. We recorded rsEEG (sampling rate of 250 Hz) during 20 min using EEG amplifier “Encephalan” (Medicom MTD, Taganrog, Russian Federation) with 19 AgCl electrodes placed according to the International 10–20 System. The electrodes placed on the left, and right mastoids served as joint references under unipolar montage. The registration of EEG v19 assignments was carried out: frontal (Fp1-Fp2; F3-F4), temporal anterior (T3-T4), temporal posterior (T5-T6), parietal (P3-P4), occipital (O1-O2). Subjects were passively touched by 4 types of tactile stimuli on the left wrist. Our stimuli were presented with a velocity of about 3–5 cm per sec. The stimuli materials and procedure were chosen for being the most "pleasant," "rough," "prickly" and "recognizable". Type of tactile stimulation: Soft cosmetic brush - "pleasant" , Rough shoe brush - "rough", Wartenberg pin wheel roller - "prickly", and the cognitive tactile stimulation included letters by finger (most of the patient’s name ) "recognizable". To designate the moments of the stimuli onset-offset, we marked the moment when the moment of the touch began and ended; the stimulation was manual, and synchronization was not precise enough for event-related measures. EEG epochs were cleaned from eye movements by ICA-based algorithm in EEGLAB plugin for MatLab 7.11.0 (Mathwork Inc.). Muscle artifacts were cut out by manual data inspection. The response to tactile stimuli was significantly different in the group of children with ASD and healthy children, which was also depended on type of tactile stimuli and the severity of ASD. Amplitude of Alpha rhythm increased in parietal region to response for only pleasant stimulus, for another type of stimulus ("rough," "thorny", "recognizable") distinction of amplitude was not observed. Correlation dimension D2 was higher in healthy children compared to children with ASD (main effect ANOVA). In ASD group D2 was lower for pleasant and unpleasant compared to the background in the right parietal area. Hilbert transform changes in the frequency of the theta rhythm found only for a rough tactile stimulation compared with healthy participants only in the right parietal area. Children with autism spectrum disorders and healthy children were responded to tactile stimulation differently with specific frequency distribution alpha and theta band in the right parietal area. Thus, our data supports the hypothesis that rsEEG may serve as a sensitive index of altered neural activity caused by ASD. Children with autism have difficulty in distinguishing the emotional stimuli ("pleasant," "rough," "prickly" and "recognizable"). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=autism" title="autism">autism</a>, <a href="https://publications.waset.org/abstracts/search?q=tactile%20stimulation" title=" tactile stimulation"> tactile stimulation</a>, <a href="https://publications.waset.org/abstracts/search?q=Hilbert%20transform" title=" Hilbert transform"> Hilbert transform</a>, <a href="https://publications.waset.org/abstracts/search?q=pediatric%20electroencephalography" title=" pediatric electroencephalography"> pediatric electroencephalography</a> </p> <a href="https://publications.waset.org/abstracts/64445/perception-of-tactile-stimuli-in-children-with-autism-spectrum-disorder" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/64445.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">250</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); 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