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products</title> <meta name="description" content="Search results for: personalized products"> <meta name="keywords" content="personalized products"> <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 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="personalized products"> <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> 4670</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: personalized products</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">4670</span> Optimal Decisions for Personalized Products with Demand Information Updating and Limited Capacity </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Meimei%20Zheng">Meimei Zheng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Product personalization could not only bring new profits to companies but also provide the direction of long-term development for companies. However, the characteristics of personalized product cause some new problems. This paper investigates how companies make decisions on the supply of personalized products when facing different customer attitudes to personalized product and service, constraints due to limited capacity and updates of personalized demand information. This study will provide optimal decisions for companies to develop personalized markets, resulting in promoting business transformation and improving business competitiveness. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=demand%20forecast%20updating" title="demand forecast updating">demand forecast updating</a>, <a href="https://publications.waset.org/abstracts/search?q=limited%20capacity" title=" limited capacity"> limited capacity</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20products" title=" personalized products"> personalized products</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a> </p> <a href="https://publications.waset.org/abstracts/66358/optimal-decisions-for-personalized-products-with-demand-information-updating-and-limited-capacity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/66358.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">262</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">4669</span> User Modeling from the Perspective of Improvement in Search Results: A Survey of the State of the Art</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samira%20Karimi-Mansoub">Samira Karimi-Mansoub</a>, <a href="https://publications.waset.org/abstracts/search?q=Rahem%20Abri"> Rahem Abri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Currently, users expect high quality and personalized information from search results. To satisfy user’s needs, personalized approaches to web search have been proposed. These approaches can provide the most appropriate answer for user’s needs by using user context and incorporating information about query provided by combining search technologies. To carry out personalized web search, there is a need to make different techniques on whole of user search process. There are the number of possible deployment of personalized approaches such as personalized web search, personalized recommendation, personalized summarization and filtering systems and etc. but the common feature of all approaches in various domains is that user modeling is utilized to provide personalized information from the Web. So the most important work in personalized approaches is user model mining. User modeling applications and technologies can be used in various domains depending on how the user collected information may be extracted. In addition to, the used techniques to create user model is also different in each of these applications. Since in the previous studies, there was not a complete survey in this field, our purpose is to present a survey on applications and techniques of user modeling from the viewpoint of improvement in search results by considering the existing literature and researches. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=filtering%20systems" title="filtering systems">filtering systems</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20web%20search" title=" personalized web search"> personalized web search</a>, <a href="https://publications.waset.org/abstracts/search?q=user%20modeling" title=" user modeling"> user modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=user%20search%20behavior" title=" user search behavior"> user search behavior</a> </p> <a href="https://publications.waset.org/abstracts/73551/user-modeling-from-the-perspective-of-improvement-in-search-results-a-survey-of-the-state-of-the-art" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/73551.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">280</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">4668</span> Acoustic Performance and Application of Three Personalized Sound-Absorbing Materials</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fangying%20Wang">Fangying Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhang%20Sanming"> Zhang Sanming</a>, <a href="https://publications.waset.org/abstracts/search?q=Ni%20Qian"> Ni Qian</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In recent years, more and more personalized sound absorbing materials have entered the Chinese room acoustical decoration market. The acoustic performance of three kinds of personalized sound-absorbing materials: Flame-retardant Flax Fiber Sound-absorbing Cotton, Eco-Friendly Sand Acoustic Panel and Transparent Micro-perforated Panel (Film) are tested by Reverberation Room Method. The sound absorption characteristic curves show that their performance match for or even exceed the traditional sound absorbing material. Through the application in the actual projects, these personalized sound-absorbing materials also proved their sound absorption ability and unique decorative effect. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acoustic%20performance" title="acoustic performance">acoustic performance</a>, <a href="https://publications.waset.org/abstracts/search?q=application%20prospect%20personalized%20sound-absorbing%20materials" title=" application prospect personalized sound-absorbing materials"> application prospect personalized sound-absorbing materials</a> </p> <a href="https://publications.waset.org/abstracts/88980/acoustic-performance-and-application-of-three-personalized-sound-absorbing-materials" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88980.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">190</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">4667</span> VR/AR Applications in Personalized Learning</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Andy%20Wang">Andy Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Personalized learning refers to an educational approach that tailors instruction to meet the unique needs, interests, and abilities of each learner. This method of learning aims at providing students with a customized learning experience that is more engaging, interactive, and relevant to their personal lives. With generative AI technology, the author has developed a Personal Tutoring Bot (PTB) that supports personalized learning. The author is currently testing PTB in his EE 499 – Microelectronics Metrology course. Virtual Reality (VR) and Augmented Reality (AR) provide interactive and immersive learning environments that can engage student in online learning. This paper presents the rationale of integrating VR/AR tools in PTB and discusses challenges and solutions of incorporating VA/AR into the Personal Tutoring Bot (PTB). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=personalized%20learning" title="personalized learning">personalized learning</a>, <a href="https://publications.waset.org/abstracts/search?q=online%20education" title=" online education"> online education</a>, <a href="https://publications.waset.org/abstracts/search?q=hands-on%20practice" title=" hands-on practice"> hands-on practice</a>, <a href="https://publications.waset.org/abstracts/search?q=VR%2FAR%20tools" title=" VR/AR tools"> VR/AR tools</a> </p> <a href="https://publications.waset.org/abstracts/175539/vrar-applications-in-personalized-learning" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/175539.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">4666</span> AI-Powered Personalized Teacher Training for Enhancing Language Teaching Competence</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ororho%20Maureen%20Ekpelezie">Ororho Maureen Ekpelezie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study investigates language educators' perceptions and experiences regarding AI-driven personalized teacher training modules in Awka South, Anambra State, Nigeria. Utilizing a stratified random sampling technique, 25 schools across various educational levels were selected to ensure a representative sample. A total of 1000 questionnaires were distributed among language teachers in these schools, focusing on assessing their perceptions and experiences related to AI-driven personalized teacher training. With an impressive response rate of 99.1%, the study garnered valuable insights into language teachers' attitudes towards AI-driven personalized teacher training and its effectiveness in enhancing language teaching competence. The quantitative analysis revealed predominantly positive perceptions towards AI-driven personalized training modules, indicating their efficacy in addressing individual learning needs. However, challenges were identified in the long-term retention and transfer of AI-enhanced skills, underscoring the necessity for further refinement of personalized training approaches. Recommendations stemming from these findings emphasize the need for continued refinement of training methodologies and the development of tailored professional development programs to alleviate educators' concerns. Overall, this research enriches discussions on the integration of AI technology in teacher training and professional development, with the aim of bolstering language teaching competence and effectiveness in educational settings. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=language%20teacher%20training" title="language teacher training">language teacher training</a>, <a href="https://publications.waset.org/abstracts/search?q=AI-driven%20personalized%20learning" title=" AI-driven personalized learning"> AI-driven personalized learning</a>, <a href="https://publications.waset.org/abstracts/search?q=professional%20development" title=" professional development"> professional development</a>, <a href="https://publications.waset.org/abstracts/search?q=language%20teaching%20competence" title=" language teaching competence"> language teaching competence</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20teacher%20training" title=" personalized teacher training"> personalized teacher training</a> </p> <a href="https://publications.waset.org/abstracts/186990/ai-powered-personalized-teacher-training-for-enhancing-language-teaching-competence" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186990.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">39</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">4665</span> D3Advert: Data-Driven Decision Making for Ad Personalization through Personality Analysis Using BiLSTM Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sandesh%20Achar">Sandesh Achar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=personalized%20advertisement" title="personalized advertisement">personalized advertisement</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20Learning" title=" deep Learning"> deep Learning</a>, <a href="https://publications.waset.org/abstracts/search?q=MBTI%20dataset" title=" MBTI dataset"> MBTI dataset</a>, <a href="https://publications.waset.org/abstracts/search?q=BiLSTM%20network" title=" BiLSTM network"> BiLSTM network</a>, <a href="https://publications.waset.org/abstracts/search?q=NLP." title=" NLP."> NLP.</a> </p> <a href="https://publications.waset.org/abstracts/184326/d3advert-data-driven-decision-making-for-ad-personalization-through-personality-analysis-using-bilstm-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184326.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">44</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">4664</span> A Framework for Internet Education: Personalised Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zoe%20Wong">Zoe Wong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this paper is to develop a framework for internet education. This framework uses the personalized learning approach for everyone who can freely develop their qualifications & careers. The key components of the framework includes students, teachers, assessments and infrastructure. It allows remove the challenges and limitations of the current educational system and allows learners' to cope with progressing learning materials. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=internet%20education" title="internet education">internet education</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20approach" title=" personalized approach"> personalized approach</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20technology" title=" information technology"> information technology</a>, <a href="https://publications.waset.org/abstracts/search?q=framework" title=" framework"> framework</a> </p> <a href="https://publications.waset.org/abstracts/47256/a-framework-for-internet-education-personalised-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47256.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">358</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">4663</span> Morphology of Cartographic Words: A Perspective from Chinese Characters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xinyu%20Gong">Xinyu Gong</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhilin%20Li"> Zhilin Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Xintao%20Liu"> Xintao Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Maps are a means of communication. Cartographic language involves established theories of natural language for understanding maps. “Cartographic words’, or “map symbols”, are crucial elements of cartographic language. Personalized mapping is increasingly popular, with growing demands for customized map-making by the general public. Automated symbol-making and customization play a key role in personalized mapping. However, formal representations for the automated construction of map symbols are still lacking. In natural language, the process of word and sentence construction can be formalized. Through the analogy between natural language and graphical language, formal representations of natural language construction can be used as a reference for constructing cartographic language. We selected Chinese character structures (i.e., S <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=personalized%20mapping" title="personalized mapping">personalized mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=Chinese%20character" title=" Chinese character"> Chinese character</a>, <a href="https://publications.waset.org/abstracts/search?q=cartographic%20language" title=" cartographic language"> cartographic language</a>, <a href="https://publications.waset.org/abstracts/search?q=map%20symbols" title=" map symbols"> map symbols</a> </p> <a href="https://publications.waset.org/abstracts/131340/morphology-of-cartographic-words-a-perspective-from-chinese-characters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131340.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">176</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">4662</span> Patent Protection for AI Innovations in Pharmaceutical Products</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nerella%20Srinivas">Nerella Srinivas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study explores the significance of patent protection for artificial intelligence (AI) innovations in the pharmaceutical sector, emphasizing applications in drug discovery, personalized medicine, and clinical trial optimization. The challenges of patenting AI-driven inventions are outlined, focusing on the classification of algorithms as abstract ideas, meeting the non-obviousness standard, and issues around defining inventorship. The methodology includes examining case studies and existing patents, with an emphasis on how companies like Benevolent AI and Insilico Medicine have successfully secured patent rights. Findings demonstrate that a strategic approach to patent protection is essential, with particular attention to showcasing AI’s technical contributions to pharmaceutical advancements. Conclusively, the study underscores the critical role of understanding patent law and innovation strategies in leveraging intellectual property rights in the rapidly advancing field of AI-driven pharmaceuticals. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title="artificial intelligence">artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=pharmaceutical%20industry" title=" pharmaceutical industry"> pharmaceutical industry</a>, <a href="https://publications.waset.org/abstracts/search?q=patent%20protection" title=" patent protection"> patent protection</a>, <a href="https://publications.waset.org/abstracts/search?q=drug%20discovery" title=" drug discovery"> drug discovery</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20medicine" title=" personalized medicine"> personalized medicine</a>, <a href="https://publications.waset.org/abstracts/search?q=clinical%20trials" title=" clinical trials"> clinical trials</a>, <a href="https://publications.waset.org/abstracts/search?q=intellectual%20property" title=" intellectual property"> intellectual property</a>, <a href="https://publications.waset.org/abstracts/search?q=non-obviousness" title=" non-obviousness"> non-obviousness</a> </p> <a href="https://publications.waset.org/abstracts/193083/patent-protection-for-ai-innovations-in-pharmaceutical-products" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193083.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">13</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">4661</span> Personalized Learning: An Analysis Using Item Response Theory</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=A.%20Yacob">A. Yacob</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20Hj.%20Ali"> N. Hj. Ali</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20H.%20Yusoff"> M. H. Yusoff</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Y.%20MohdSaman"> M. Y. MohdSaman</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20M.%20A.%20F.%20W.%20Hamzah"> W. M. A. F. W. Hamzah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Personalized learning becomes increasingly popular which not is restricted by time, place or any other barriers. This study proposes an analysis of Personalized Learning using Item Response Theory which considers course material difficulty and learner ability. The study investigates twenty undergraduate students at TATI University College, who are taking programming subject. By using the IRT, it was found that, finding the most appropriate problem levels to each student include high and low level test items together is not a problem. Thus, the student abilities can be asses more accurately and fairly. Learners who experience more anxiety will affect a heavier cognitive load and receive lower test scores. Instructors are encouraged to provide a supportive learning environment to enhance learning effectiveness because Cognitive Load Theory concerns the limited capacity of the brain to absorb new information. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=assessment" title="assessment">assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=item%20response%20theory" title=" item response theory"> item response theory</a>, <a href="https://publications.waset.org/abstracts/search?q=cognitive%20load%20theory" title=" cognitive load theory"> cognitive load theory</a>, <a href="https://publications.waset.org/abstracts/search?q=learning" title=" learning"> learning</a>, <a href="https://publications.waset.org/abstracts/search?q=motivation" title=" motivation"> motivation</a>, <a href="https://publications.waset.org/abstracts/search?q=performance" title=" performance"> performance</a> </p> <a href="https://publications.waset.org/abstracts/7302/personalized-learning-an-analysis-using-item-response-theory" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/7302.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">4660</span> Performance Study of Classification Algorithms for Consumer Online Shopping Attitudes and Behavior Using Data Mining</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rana%20Alaa%20El-Deen%20Ahmed">Rana Alaa El-Deen Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=M.%20Elemam%20Shehab"> M. Elemam Shehab</a>, <a href="https://publications.waset.org/abstracts/search?q=Shereen%20Morsy"> Shereen Morsy</a>, <a href="https://publications.waset.org/abstracts/search?q=Nermeen%20Mekawie"> Nermeen Mekawie</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=online%20shopping" title=" online shopping"> online shopping</a>, <a href="https://publications.waset.org/abstracts/search?q=WEKA" title=" WEKA"> WEKA</a> </p> <a href="https://publications.waset.org/abstracts/25690/performance-study-of-classification-algorithms-for-consumer-online-shopping-attitudes-and-behavior-using-data-mining" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25690.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">351</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">4659</span> An Analysis of a Canadian Personalized Learning Curriculum</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ruthanne%20Tobin">Ruthanne Tobin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The shift to a personalized learning (PL) curriculum in Canada represents an innovative approach to teaching and learning that is also evident in various initiatives across the 32-nation OECD. The premise behind PL is that empowering individual learners to have more input into how they access and construct knowledge, and express their understanding of it, will result in more meaningful school experiences and academic success. In this paper presentation, the author reports on a document analysis of the new curriculum in the province of British Columbia. Three theoretical frameworks are used to analyze the new curriculum. Framework 1 focuses on five dominant aspects (FDA) of PL at the classroom level. Framework 2 focuses on conceptualizing and enacting personalized learning (CEPL) within three spheres of influence. Framework 3 focuses on the integration of three types of knowledge (content, technological, and pedagogical). Analysis is ongoing, but preliminary findings suggest that the new curriculum addresses framework 1 quite well, which identifies five areas of personalized learning: 1) assessment for learning; 2) effective teaching and learning; 3) curriculum entitlement (choice); 4) school organization; and 5) “beyond the classroom walls” (learning in the community). Framework 2 appears to be less well developed in the new curriculum. This framework speaks to the dynamics of PL within three spheres of interaction: 1) nested agency, comprised of overarching constraints [and enablers] from policy makers, school administrators and community; 2) relational agency, which refers to a capacity for professionals to develop a network of expertise to serve shared goals; and 3) students’ personalized learning experience, which integrates differentiation with self-regulation strategies. Framework 3 appears to be well executed in the new PL curriculum, as it employs the theoretical model of technological, pedagogical content knowledge (TPACK) in which there are three interdependent bodies of knowledge. Notable within this framework is the emphasis on the pairing of technologies with excellent pedagogies to significantly assist students and teachers. This work will be of high relevance to educators interested in innovative school reform. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=curriculum%20reform" title="curriculum reform">curriculum reform</a>, <a href="https://publications.waset.org/abstracts/search?q=K-12%20school%20change" title=" K-12 school change"> K-12 school change</a>, <a href="https://publications.waset.org/abstracts/search?q=innovations%20in%20education" title=" innovations in education"> innovations in education</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20learning" title=" personalized learning "> personalized learning </a> </p> <a href="https://publications.waset.org/abstracts/59474/an-analysis-of-a-canadian-personalized-learning-curriculum" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59474.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">282</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">4658</span> Personalized Email Marketing Strategy: A Reinforcement Learning Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lei%20Zhang">Lei Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Tingting%20Xu"> Tingting Xu</a>, <a href="https://publications.waset.org/abstracts/search?q=Jun%20He"> Jun He</a>, <a href="https://publications.waset.org/abstracts/search?q=Zhenyu%20Yan"> Zhenyu Yan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Email marketing is one of the most important segments of online marketing. It has been proved to be the most effective way to acquire and retain customers. The email content is vital to customers. Different customers may have different familiarity with a product, so a successful marketing strategy must personalize email content based on individual customers’ product affinity. In this study, we build our personalized email marketing strategy with three types of emails: nurture, promotion, and conversion. Each type of email has a different influence on customers. We investigate this difference by analyzing customers’ open rates, click rates and opt-out rates. Feature importance from response models is also analyzed. The goal of the marketing strategy is to improve the click rate on conversion-type emails. To build the personalized strategy, we formulate the problem as a reinforcement learning problem and adopt a Q-learning algorithm with variations. The simulation results show that our model-based strategy outperforms the current marketer’s strategy. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=email%20marketing" title="email marketing">email marketing</a>, <a href="https://publications.waset.org/abstracts/search?q=email%20content" title=" email content"> email content</a>, <a href="https://publications.waset.org/abstracts/search?q=reinforcement%20learning" title=" reinforcement learning"> reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=Q-learning" title=" Q-learning"> Q-learning</a> </p> <a href="https://publications.waset.org/abstracts/152253/personalized-email-marketing-strategy-a-reinforcement-learning-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/152253.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">194</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">4657</span> User Intention Generation with Large Language Models Using Chain-of-Thought Prompting Title</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gangmin%20Li">Gangmin Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Fan%20Yang"> Fan Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=personalized%20recommendation" title="personalized recommendation">personalized recommendation</a>, <a href="https://publications.waset.org/abstracts/search?q=generative%20user%20modelling" title=" generative user modelling"> generative user modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=user%20intention%20identification" title=" user intention identification"> user intention identification</a>, <a href="https://publications.waset.org/abstracts/search?q=large%20language%20models" title=" large language models"> large language models</a>, <a href="https://publications.waset.org/abstracts/search?q=chain-of-thought%20prompting" title=" chain-of-thought prompting"> chain-of-thought prompting</a> </p> <a href="https://publications.waset.org/abstracts/185916/user-intention-generation-with-large-language-models-using-chain-of-thought-prompting-title" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185916.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">54</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">4656</span> A Semantic E-Learning and E-Assessment System of Learners </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wiem%20Ben%20Khalifa">Wiem Ben Khalifa</a>, <a href="https://publications.waset.org/abstracts/search?q=Dalila%20Souilem"> Dalila Souilem</a>, <a href="https://publications.waset.org/abstracts/search?q=Mahmoud%20Neji"> Mahmoud Neji</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The evolutions of Social Web and Semantic Web lead us to ask ourselves about the way of supporting the personalization of learning by means of intelligent filtering of educational resources published in the digital networks. We recommend personalized courses of learning articulated around a first educational course defined upstream. Resuming the context and the stakes in the personalization, we also suggest anchoring the personalization of learning in a community of interest within a group of learners enrolled in the same training. This reflection is supported by the display of an active and semantic system of learning dedicated to the constitution of personalized to measure courses and in the due time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Semantic%20Web" title="Semantic Web">Semantic Web</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20system" title=" semantic system"> semantic system</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a>, <a href="https://publications.waset.org/abstracts/search?q=evaluation" title=" evaluation"> evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=e-learning" title=" e-learning"> e-learning</a> </p> <a href="https://publications.waset.org/abstracts/72932/a-semantic-e-learning-and-e-assessment-system-of-learners" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72932.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">335</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">4655</span> Personalize E-Learning System Based on Clustering and Sequence Pattern Mining Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=H.%20S.%20Saini">H. S. Saini</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20Vijayalakshmi"> K. Vijayalakshmi</a>, <a href="https://publications.waset.org/abstracts/search?q=Rishi%20Sayal"> Rishi Sayal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Network-based education has been growing rapidly in size and quality. Knowledge clustering becomes more important in personalized information retrieval for web-learning. A personalized-Learning service after the learners’ knowledge has been classified with clustering. Through automatic analysis of learners’ behaviors, their partition with similar data level and interests may be discovered so as to produce learners with contents that best match educational needs for collaborative learning. We present a specific mining tool and a recommender engine that we have integrated in the online learning in order to help the teacher to carry out the whole e-learning process. We propose to use sequential pattern mining algorithms to discover the most used path by the students and from this information can recommend links to the new students automatically meanwhile they browse in the course. We have Developed a specific author tool in order to help the teacher to apply all the data mining process. We tend to report on many experiments with real knowledge so as to indicate the quality of using both clustering and sequential pattern mining algorithms together for discovering personalized e-learning systems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=e-learning" title="e-learning">e-learning</a>, <a href="https://publications.waset.org/abstracts/search?q=cluster" title=" cluster"> cluster</a>, <a href="https://publications.waset.org/abstracts/search?q=personalization" title=" personalization"> personalization</a>, <a href="https://publications.waset.org/abstracts/search?q=sequence" title=" sequence"> sequence</a>, <a href="https://publications.waset.org/abstracts/search?q=pattern" title=" pattern"> pattern</a> </p> <a href="https://publications.waset.org/abstracts/33440/personalize-e-learning-system-based-on-clustering-and-sequence-pattern-mining-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33440.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">429</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">4654</span> A Paradigm Shift towards Personalized and Scalable Product Development and Lifecycle Management Systems in the Aerospace Industry</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=David%20E.%20Culler">David E. Culler</a>, <a href="https://publications.waset.org/abstracts/search?q=Noah%20D.%20Anderson"> Noah D. Anderson</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Integrated systems for product design, manufacturing, and lifecycle management are difficult to implement and customize. Commercial software vendors, including CAD/CAM and third party PDM/PLM developers, create user interfaces and functionality that allow their products to be applied across many industries. The result is that systems become overloaded with functionality, difficult to navigate, and use terminology that is unfamiliar to engineers and production personnel. For example, manufacturers of automotive, aeronautical, electronics, and household products use similar but distinct methods and processes. Furthermore, each company tends to have their own preferred tools and programs for controlling work and information flow and that connect design, planning, and manufacturing processes to business applications. This paper presents a methodology and a case study that addresses these issues and suggests that in the future more companies will develop personalized applications that fit to the natural way that their business operates. A functioning system has been implemented at a highly competitive U.S. aerospace tooling and component supplier that works with many prominent airline manufacturers around the world including The Boeing Company, Airbus, Embraer, and Bombardier Aerospace. During the last three years, the program has produced significant benefits such as the automatic creation and management of component and assembly designs (parametric models and drawings), the extensive use of lightweight 3D data, and changes to the way projects are executed from beginning to end. CATIA (CAD/CAE/CAM) and a variety of programs developed in C#, VB.Net, HTML, and SQL make up the current system. The web-based platform is facilitating collaborative work across multiple sites around the world and improving communications with customers and suppliers. This work demonstrates that the creative use of Application Programming Interface (API) utilities, libraries, and methods is a key to automating many time-consuming tasks and linking applications together. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=PDM" title="PDM">PDM</a>, <a href="https://publications.waset.org/abstracts/search?q=PLM" title=" PLM"> PLM</a>, <a href="https://publications.waset.org/abstracts/search?q=collaboration" title=" collaboration"> collaboration</a>, <a href="https://publications.waset.org/abstracts/search?q=CAD%2FCAM" title=" CAD/CAM"> CAD/CAM</a>, <a href="https://publications.waset.org/abstracts/search?q=scalable%20systems" title=" scalable systems"> scalable systems</a> </p> <a href="https://publications.waset.org/abstracts/38378/a-paradigm-shift-towards-personalized-and-scalable-product-development-and-lifecycle-management-systems-in-the-aerospace-industry" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38378.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">174</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">4653</span> A Reading Light That Can Adjust Indoor Light Intensity According to the Activity and Person for Improve Indoor Visual Comfort of Occupants and Tested using Post-occupancy Evaluation Techniques for Sri Lankan Population</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.T.P.%20De%20Silva">R.T.P. De Silva</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20K.%20Wijayasiriwardhane"> T. K. Wijayasiriwardhane</a>, <a href="https://publications.waset.org/abstracts/search?q=B.%20Jayawardena"> B. Jayawardena</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Most people nowadays spend their time indoor environment. Because of that, a quality indoor environment needs for them. This study was conducted to identify how to improve indoor visual comfort using a personalized light system. Light intensity, light color, glare, and contrast are the main facts that affect visual comfort. The light intensity which needs to perform a task is changed according to the task. Using necessary light intensity and we can improve the visual comfort of occupants. The hue can affect the emotions of occupants. The preferred light colors and intensity change according to the occupant's age and gender. The research was conducted to identify is there any relationship between personalization and visual comfort. To validate this designed an Internet of Things-based reading light. This light can work according to the standard light levels and personalized light levels. It also can measure the current light intensity of the environment and maintain continuous light levels according to the task. The test was conducted by using 25 undergraduates, and 5school students, and 5 adults. The feedbacks are gathered using Post-occupancy evaluation (POE) techniques. Feedbacks are gathered in three steps, It was done without any light control, with standard light level, and with personalized light level Users had to spend 10 minutes under each condition. After finishing each step, collected their feedbacks. According to the result gathered, 94% of participants rated a personalized light system as comfort for them. The feedbacks show stay under continuous light level help to keep their concentrate. Future research can be conducted on how the color of indoor light can affect for indoor visual comfort of occupants using a personalized light system. Further proposed IoT based can improve to change the light colors according to the user's preference. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=indoor%20environment%20quality" title="indoor environment quality">indoor environment quality</a>, <a href="https://publications.waset.org/abstracts/search?q=internet%20of%20things%20based%20light%20system" title=" internet of things based light system"> internet of things based light system</a>, <a href="https://publications.waset.org/abstracts/search?q=post%20occupancy%20evaluation" title=" post occupancy evaluation"> post occupancy evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=visual%20comfort" title=" visual comfort"> visual comfort</a> </p> <a href="https://publications.waset.org/abstracts/144243/a-reading-light-that-can-adjust-indoor-light-intensity-according-to-the-activity-and-person-for-improve-indoor-visual-comfort-of-occupants-and-tested-using-post-occupancy-evaluation-techniques-for-sri-lankan-population" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/144243.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">155</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">4652</span> Using Differentiation Instruction to Create a Personalized Experience</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Valerie%20Yocco%20Rossi">Valerie Yocco Rossi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Objective: The author will share why differentiation is necessary for all classrooms as well as strategies for differentiating content, process, and product. Through learning how to differentiate, teachers will be able to create activities and assessments to meet the abilities, readiness levels, and interests of all learners. Content and Purpose: This work will focus on how to create a learning experience for students that recognizes their different interests, abilities, and readiness levels by differentiating content, process, and product. Likewise, the best learning environments allow for choice. Choice boards allow students to select tasks based on interests. There can be challenging and basic tasks to meet the needs of various abilities. Equally, rubrics allow for personalized and differentiated assessments based on readiness levels and cognitive abilities. The principals of DI help to create a classroom where all students are learning to the best of their abilities. Outcomes: After reviewing the work, readers will be able to (1) identify the benefits of differentiated instruction; (2) convert traditional learning activities to differentiated ones; (3) differentiate, writing-based assessments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=differentiation" title="differentiation">differentiation</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20learning" title=" personalized learning"> personalized learning</a>, <a href="https://publications.waset.org/abstracts/search?q=design" title=" design"> design</a>, <a href="https://publications.waset.org/abstracts/search?q=instructional%20strategies" title=" instructional strategies"> instructional strategies</a> </p> <a href="https://publications.waset.org/abstracts/168918/using-differentiation-instruction-to-create-a-personalized-experience" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/168918.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">4651</span> MY ATBU: A Rebranding Campaign Using Promotional Products</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azeez%20Ayodele">Azeez Ayodele</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Promotional products take symbolic roles, they can become an emblem, and they can become part of a rebrand and even be a brand itself. Promotional products express both an institution’s inspirations and its aspirations; it can reflect a continuum. This stimulates the interest of the study, which is to examine the impact of rebranding Abubakar Tafawa Balewa University, Bauchi-Nigeria, using promotional products. It examines the concept of rebranding with the aim to discuss the effectiveness of the promotional products in branding higher educational sector that needs to be assessed and measured. Therefore, some measures of branding activities are proposed. Conclusion suggests that university rebranding is effective and the use of a commercial approach can be easier. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=branding" title="branding">branding</a>, <a href="https://publications.waset.org/abstracts/search?q=higher%20education" title=" higher education"> higher education</a>, <a href="https://publications.waset.org/abstracts/search?q=promotional%20products" title=" promotional products"> promotional products</a>, <a href="https://publications.waset.org/abstracts/search?q=rebranding" title=" rebranding"> rebranding</a> </p> <a href="https://publications.waset.org/abstracts/16589/my-atbu-a-rebranding-campaign-using-promotional-products" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/16589.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">262</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">4650</span> Towards the Prediction of Aesthetic Requirements for Women’s Apparel Product</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yu%20Zhao">Yu Zhao</a>, <a href="https://publications.waset.org/abstracts/search?q=Min%20Zhang"> Min Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuanqian%20Wang"> Yuanqian Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Qiuyu%20Yu"> Qiuyu Yu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The prediction of aesthetics of apparel is helpful for the development of a new type of apparel. This study is to build the quantitative relationship between the aesthetics and its design parameters. In particular, women’s pants have been preliminarily studied. This aforementioned relationship has been carried out by statistical analysis. The contributions of this study include the development of a more personalized apparel design mechanism and the provision of some empirical knowledge for the development of other products in the aspect of aesthetics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=aesthetics" title="aesthetics">aesthetics</a>, <a href="https://publications.waset.org/abstracts/search?q=crease%20line" title=" crease line"> crease line</a>, <a href="https://publications.waset.org/abstracts/search?q=cropped%20straight%20leg%20pants" title=" cropped straight leg pants"> cropped straight leg pants</a>, <a href="https://publications.waset.org/abstracts/search?q=knee%20width" title=" knee width"> knee width</a> </p> <a href="https://publications.waset.org/abstracts/110584/towards-the-prediction-of-aesthetic-requirements-for-womens-apparel-product" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110584.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">186</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">4649</span> TimeTune: Personalized Study Plans Generation with Google Calendar Integration</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chevon%20Fernando">Chevon Fernando</a>, <a href="https://publications.waset.org/abstracts/search?q=Banuka%20Athuraliya"> Banuka Athuraliya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this research is to provide a solution to the students’ time management, which usually becomes an issue because students must study and manage their personal commitments. "TimeTune," an AI-based study planner that provides an opportunity to maneuver study timeframes by incorporating modern machine learning algorithms with calendar applications, is unveiled as the ideal solution. The research is focused on the development of LSTM models that connect to the Google Calendar API in the process of developing learning paths that would be fit for a unique student's daily life experience and study history. A key finding of this research is the success in building the LSTM model to predict optimal study times, which, integrating with the real-time data of Google Calendar, will generate the timetables automatically in a personalized and customized manner. The methodology encompasses Agile development practices and Object-Oriented Analysis and Design (OOAD) principles, focusing on user-centric design and iterative development. By adopting this method, students can significantly reduce the tension associated with poor study habits and time management. In conclusion, "TimeTune" displays an advanced step in personalized education technology. The fact that its application of ML algorithms and calendar integration is quite innovative is slowly and steadily revolutionizing the lives of students. The excellence of maintaining a balanced academic and personal life is stress reduction, which the applications promise to provide for students when it comes to managing their studies. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=personalized%20learning" title="personalized learning">personalized learning</a>, <a href="https://publications.waset.org/abstracts/search?q=study%20planner" title=" study planner"> study planner</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20management" title=" time management"> time management</a>, <a href="https://publications.waset.org/abstracts/search?q=calendar%20integration" title=" calendar integration"> calendar integration</a> </p> <a href="https://publications.waset.org/abstracts/185394/timetune-personalized-study-plans-generation-with-google-calendar-integration" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/185394.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">49</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">4648</span> The Analysis of Personalized Low-Dose Computed Tomography Protocol Based on Cumulative Effective Radiation Dose and Cumulative Organ Dose for Patients with Breast Cancer with Regular Chest Computed Tomography Follow up</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Okhee%20Woo">Okhee Woo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose: The aim of this study is to evaluate 2-year cumulative effective radiation dose and cumulative organ dose on regular follow-up computed tomography (CT) scans in patients with breast cancer and to establish personalized low-dose CT protocol. Methods and Materials: A retrospective study was performed on the patients with breast cancer who were diagnosed and managed consistently on the basis of routine breast cancer follow-up protocol between 2012-01 and 2016-06. Based on ICRP (International Commission on Radiological Protection) 103, the cumulative effective radiation doses of each patient for 2-year follow-up were analyzed using the commercial radiation management software (Radimetrics, Bayer healthcare). The personalized effective doses on each organ were analyzed in detail by the software-providing Monte Carlo simulation. Results: A total of 3822 CT scans on 490 patients was evaluated (age: 52.32±10.69). The mean scan number for each patient was 7.8±4.54. Each patient was exposed 95.54±63.24 mSv of radiation for 2 years. The cumulative CT radiation dose was significantly higher in patients with lymph node metastasis (p = 0.00). The HER-2 positive patients were more exposed to radiation compared to estrogen or progesterone receptor positive patient (p = 0.00). There was no difference in the cumulative effective radiation dose with different age groups. Conclusion: To acknowledge how much radiation exposed to a patient is a starting point of management of radiation exposure for patients with long-term CT follow-up. The precise and personalized protocol, as well as iterative reconstruction, may reduce hazard from unnecessary radiation exposure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computed%20tomography" title="computed tomography">computed tomography</a>, <a href="https://publications.waset.org/abstracts/search?q=breast%20cancer" title=" breast cancer"> breast cancer</a>, <a href="https://publications.waset.org/abstracts/search?q=effective%20radiation%20dose" title=" effective radiation dose"> effective radiation dose</a>, <a href="https://publications.waset.org/abstracts/search?q=cumulative%20organ%20dose" title=" cumulative organ dose"> cumulative organ dose</a> </p> <a href="https://publications.waset.org/abstracts/92617/the-analysis-of-personalized-low-dose-computed-tomography-protocol-based-on-cumulative-effective-radiation-dose-and-cumulative-organ-dose-for-patients-with-breast-cancer-with-regular-chest-computed-tomography-follow-up" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92617.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">197</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">4647</span> Financial Products Held by University Students: An Empirical Study from the Czech Republic</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Barbora%20Chmelikova">Barbora Chmelikova</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Current financial markets offer a wide range of financial products to the consumers. However, access to the financial products is not always provided or guaranteed, particularly in less developed countries. For this reason, financial inclusion is an important component in the modern society. This paper investigates financial inclusion and what financial products are held by university students majoring in finance fields. The OECD methodology was used to examine the awareness and use of financial products. The study was conducted via online questionnaire at Masaryk University in the Czech Republic among finance students. The results show that the students use current and savings accounts more than any other financial products. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=financial%20inclusion" title="financial inclusion">financial inclusion</a>, <a href="https://publications.waset.org/abstracts/search?q=financial%20products" title=" financial products"> financial products</a>, <a href="https://publications.waset.org/abstracts/search?q=personal%20finance" title=" personal finance"> personal finance</a>, <a href="https://publications.waset.org/abstracts/search?q=university%20students" title=" university students"> university students</a> </p> <a href="https://publications.waset.org/abstracts/58766/financial-products-held-by-university-students-an-empirical-study-from-the-czech-republic" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58766.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">377</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">4646</span> Conceptualizing Personalized Learning: Review of Literature 2007-2017</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ruthanne%20Tobin">Ruthanne Tobin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As our data-driven, cloud-based, knowledge-centric lives become ever more global, mobile, and digital, educational systems everywhere are struggling to keep pace. Schools need to prepare students to become critical-thinking, tech-savvy, life-long learners who are engaged and adaptable enough to find their unique calling in a post-industrial world of work. Recognizing that no nation can afford poor achievement or high dropout rates without jeopardizing its social and economic future, the thirty-two nations of the OECD are launching initiatives to redesign schools, generally under the banner of Personalized Learning or 21st Century Learning. Their intention is to transform education by situating students as co-enquirers and co-contributors with their teachers of what, when, and how learning happens for each individual. In this focused review of the 2007-2017 literature on personalized learning, the author sought answers to two main questions: “What are the theoretical frameworks that guide personalized learning?” and “What is the conceptual understanding of the model?” Ultimately, the review reveals that, although the research area is overly theorized and under-substantiated, it does provide a significant body of knowledge about this potentially transformative educational restructuring. For example, it addresses the following questions: a) What components comprise a PL model? b) How are teachers facilitating agency (voice & choice) in their students? c) What kinds of systems, processes and procedures are being used to guide the innovation? d) How is learning organized, monitored and assessed? e) What role do inquiry based models play? f) How do teachers integrate the three types of knowledge: Content, pedagogical and technological? g) Which kinds of forces enable, and which impede, personalizing learning? h) What is the nature of the collaboration among teachers? i) How do teachers co-regulate differentiated tasks? One finding of the review shows that while technology can dramatically expand access to information, expectations of its impact on teaching and learning are often disappointing unless the technologies are paired with excellent pedagogies in order to address students’ needs, interests and aspirations. This literature review fills a significant gap in this emerging field of research, as it serves to increase conceptual clarity that has hampered both the theorizing and the classroom implementation of a personalized learning model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=curriculum%20change" title="curriculum change">curriculum change</a>, <a href="https://publications.waset.org/abstracts/search?q=educational%20innovation" title=" educational innovation"> educational innovation</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20learning" title=" personalized learning"> personalized learning</a>, <a href="https://publications.waset.org/abstracts/search?q=school%20reform" title=" school reform"> school reform</a> </p> <a href="https://publications.waset.org/abstracts/59380/conceptualizing-personalized-learning-review-of-literature-2007-2017" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59380.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">223</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">4645</span> Training AI to Be Empathetic and Determining the Psychotype of a Person During a Conversation with a Chatbot</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aliya%20Grig">Aliya Grig</a>, <a href="https://publications.waset.org/abstracts/search?q=Konstantin%20Sokolov"> Konstantin Sokolov</a>, <a href="https://publications.waset.org/abstracts/search?q=Igor%20Shatalin"> Igor Shatalin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=AI" title="AI">AI</a>, <a href="https://publications.waset.org/abstracts/search?q=empathetic" title=" empathetic"> empathetic</a>, <a href="https://publications.waset.org/abstracts/search?q=chatbot" title=" chatbot"> chatbot</a>, <a href="https://publications.waset.org/abstracts/search?q=AI%20models" title=" AI models"> AI models</a> </p> <a href="https://publications.waset.org/abstracts/164587/training-ai-to-be-empathetic-and-determining-the-psychotype-of-a-person-during-a-conversation-with-a-chatbot" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/164587.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">93</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">4644</span> An Integrative Computational Pipeline for Detection of Tumor Epitopes in Cancer Patients</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tanushree%20Jaitly">Tanushree Jaitly</a>, <a href="https://publications.waset.org/abstracts/search?q=Shailendra%20Gupta"> Shailendra Gupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Leila%20Taher"> Leila Taher</a>, <a href="https://publications.waset.org/abstracts/search?q=Gerold%20Schuler"> Gerold Schuler</a>, <a href="https://publications.waset.org/abstracts/search?q=Julio%20Vera"> Julio Vera</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cancer%20immunotherapy" title="cancer immunotherapy">cancer immunotherapy</a>, <a href="https://publications.waset.org/abstracts/search?q=epitope%20prediction" title=" epitope prediction"> epitope prediction</a>, <a href="https://publications.waset.org/abstracts/search?q=NGS%20data" title=" NGS data"> NGS data</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20medicine" title=" personalized medicine"> personalized medicine</a> </p> <a href="https://publications.waset.org/abstracts/51877/an-integrative-computational-pipeline-for-detection-of-tumor-epitopes-in-cancer-patients" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51877.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">253</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">4643</span> Surgical Planning for the Removal of Cranial Spheno-orbital Meningioma by Using Personalized Polymeric Prototypes Obtained with Additive Manufacturing Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Freddy%20Patricio%20Moncayo-Matute">Freddy Patricio Moncayo-Matute</a>, <a href="https://publications.waset.org/abstracts/search?q=Pablo%20Gerardo%20Pe%C3%B1a-Tapia"> Pablo Gerardo Peña-Tapia</a>, <a href="https://publications.waset.org/abstracts/search?q=V%C3%A1zquez-Silva%20Efr%C3%A9n"> Vázquez-Silva Efrén</a>, <a href="https://publications.waset.org/abstracts/search?q=Pa%C3%BAl%20Bol%C3%ADvar%20Torres-Jara"> Paúl Bolívar Torres-Jara</a>, <a href="https://publications.waset.org/abstracts/search?q=Diana%20Patricia%20Moya-Loaiza"> Diana Patricia Moya-Loaiza</a>, <a href="https://publications.waset.org/abstracts/search?q=Gabriela%20Abad-Farf%C3%A1n"> Gabriela Abad-Farfán</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study describes a clinical case and the results on the application of additive manufacturing for the surgical planning in the removal of a cranial spheno-orbital meningioma. It is verified that the use of personalized anatomical models and cutting guides helps to manage the cranial anomalies approach. The application of additive manufacturing technology: Fused Deposition Modeling (FDM), as a low-cost alternative, enables the printing of the test anatomical model, which in turn favors the reduction of surgery time, as well the morbidity rate reduction too. And the printing of the personalized cutting guide, which constitutes a valuable aid to the surgeon in terms of improving the intervention precision and reducing the invasive effect during the craniotomy. As part of the results, post-surgical follow-up is included as an instrument to verify the patient's recovery and the validity of the procedure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=surgical%20planning" title="surgical planning">surgical planning</a>, <a href="https://publications.waset.org/abstracts/search?q=additive%20manufacturing" title=" additive manufacturing"> additive manufacturing</a>, <a href="https://publications.waset.org/abstracts/search?q=rapid%20prototyping" title=" rapid prototyping"> rapid prototyping</a>, <a href="https://publications.waset.org/abstracts/search?q=fused%20deposition%20modeling" title=" fused deposition modeling"> fused deposition modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=custom%20anatomical%20model" title=" custom anatomical model"> custom anatomical model</a> </p> <a href="https://publications.waset.org/abstracts/163905/surgical-planning-for-the-removal-of-cranial-spheno-orbital-meningioma-by-using-personalized-polymeric-prototypes-obtained-with-additive-manufacturing-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/163905.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">100</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">4642</span> Optimizing Glycemic Control with AI-Guided Dietary Supplements: A Randomized Trial in Type 2 Diabetes</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Evgeny%20Pokushalov">Evgeny Pokushalov</a>, <a href="https://publications.waset.org/abstracts/search?q=Claire%20Garcia"> Claire Garcia</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrey%20Ponomarenko"> Andrey Ponomarenko</a>, <a href="https://publications.waset.org/abstracts/search?q=John%20Smith"> John Smith</a>, <a href="https://publications.waset.org/abstracts/search?q=Michael%20Johnson"> Michael Johnson</a>, <a href="https://publications.waset.org/abstracts/search?q=Inessa%20Pak"> Inessa Pak</a>, <a href="https://publications.waset.org/abstracts/search?q=Evgenya%20Shrainer"> Evgenya Shrainer</a>, <a href="https://publications.waset.org/abstracts/search?q=Dmitry%20Kudlay"> Dmitry Kudlay</a>, <a href="https://publications.waset.org/abstracts/search?q=Leila%20Kasimova"> Leila Kasimova</a>, <a href="https://publications.waset.org/abstracts/search?q=Richard%20Miller"> Richard Miller</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study evaluated the efficacy of an AI-guided dietary supplement regimen compared to a standard physician-guided regimen in managing Type 2 diabetes (T2D). A total of 160 patients were randomly assigned to either the AI-guided group (n=80) or the physician-guided group (n=80) and followed over 90 days. The AI-guided group received 5.3 ± 1.2 supplements per patient, while the physician-guided group received 2.7 ± 0.6 supplements per patient. The AI system personalized supplement types and dosages based on individual genetic and metabolic profiles. The AI-guided group showed a significant reduction in HbA1c levels from 7.5 ± 0.8% to 7.1 ± 0.7%, compared to a reduction from 7.6 ± 0.9% to 7.4 ± 0.8% in the physician-guided group (mean difference: -0.3%, 95% CI: -0.5% to -0.1%; p < 0.01). Secondary outcomes, including fasting plasma glucose, HOMA-IR, and insulin levels, also improved more in the AI-guided group. Subgroup analyses revealed that the AI-guided regimen was particularly effective in patients with specific genetic polymorphisms and elevated metabolic markers. Safety profiles were comparable between both groups, with no serious adverse events reported. In conclusion, the AI-guided dietary supplement regimen significantly improved glycemic control and metabolic health in T2D patients compared to the standard physician-guided approach, demonstrating the potential of personalized AI-driven interventions in diabetes management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Type%202%20diabetes" title="Type 2 diabetes">Type 2 diabetes</a>, <a href="https://publications.waset.org/abstracts/search?q=AI-guided%20supplementation" title=" AI-guided supplementation"> AI-guided supplementation</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20medicine" title=" personalized medicine"> personalized medicine</a>, <a href="https://publications.waset.org/abstracts/search?q=glycemic%20control" title=" glycemic control"> glycemic control</a>, <a href="https://publications.waset.org/abstracts/search?q=metabolic%20health" title=" metabolic health"> metabolic health</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20polymorphisms" title=" genetic polymorphisms"> genetic polymorphisms</a>, <a href="https://publications.waset.org/abstracts/search?q=dietary%20supplements" title=" dietary supplements"> dietary supplements</a>, <a href="https://publications.waset.org/abstracts/search?q=HbA1c" title=" HbA1c"> HbA1c</a>, <a href="https://publications.waset.org/abstracts/search?q=fasting%20plasma%20glucose" title=" fasting plasma glucose"> fasting plasma glucose</a>, <a href="https://publications.waset.org/abstracts/search?q=HOMA-IR" title=" HOMA-IR"> HOMA-IR</a>, <a href="https://publications.waset.org/abstracts/search?q=personalized%20nutrition" title=" personalized nutrition"> personalized nutrition</a> </p> <a href="https://publications.waset.org/abstracts/194485/optimizing-glycemic-control-with-ai-guided-dietary-supplements-a-randomized-trial-in-type-2-diabetes" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194485.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">10</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">4641</span> A Reinforcement Learning Based Method for Heating, Ventilation, and Air Conditioning Demand Response Optimization Considering Few-Shot Personalized Thermal Comfort</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xiaohua%20Zou">Xiaohua Zou</a>, <a href="https://publications.waset.org/abstracts/search?q=Yongxin%20Su"> Yongxin Su</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The reasonable operation of heating, ventilation, and air conditioning (HVAC) is of great significance in improving the security, stability, and economy of power system operation. However, the uncertainty of the operating environment, thermal comfort varies by users and rapid decision-making pose challenges for HVAC demand response optimization. In this regard, this paper proposes a reinforcement learning-based method for HVAC demand response optimization considering few-shot personalized thermal comfort (PTC). First, an HVAC DR optimization framework based on few-shot PTC model and DRL is designed, in which the output of few-shot PTC model is regarded as the input of DRL. Then, a few-shot PTC model that distinguishes between awake and asleep states is established, which has excellent engineering usability. Next, based on soft actor criticism, an HVAC DR optimization algorithm considering the user’s PTC is designed to deal with uncertainty and make decisions rapidly. Experiment results show that the proposed method can efficiently obtain use’s PTC temperature, reduce energy cost while ensuring user’s PTC, and achieve rapid decision-making under uncertainty. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=HVAC" title="HVAC">HVAC</a>, <a href="https://publications.waset.org/abstracts/search?q=few-shot%20personalized%20thermal%20comfort" title=" few-shot personalized thermal comfort"> few-shot personalized thermal comfort</a>, <a href="https://publications.waset.org/abstracts/search?q=deep%20reinforcement%20learning" title=" deep reinforcement learning"> deep reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=demand%20response" title=" demand response"> demand response</a> </p> <a href="https://publications.waset.org/abstracts/182116/a-reinforcement-learning-based-method-for-heating-ventilation-and-air-conditioning-demand-response-optimization-considering-few-shot-personalized-thermal-comfort" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/182116.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">86</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=personalized%20products&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=personalized%20products&page=3">3</a></li> <li class="page-item"><a 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