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Journal articles on the topic 'Personalized Feed'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

García, Víctor Manuel Álvarez, María del Puerto Paule Ruiz, Remko van Dort, and Juan Ramón Pérez Pérez. "RSS-Based Learning Using Audio." International Journal of Human Capital and Information Technology Professionals 1, no. 4 (2010): 76–87. http://dx.doi.org/10.4018/jhcitp.2010100105.

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Specifications such as RSS feeds are opening a new channel of communication for Internet-based learning, which gives a decentralized view of web resources while maintaining the privacy of teachers and students who are consulting the information. This philosophy can be used to create personalized learning tools in which users can take control of resources they want to have access to. In this regard, RSS is XML-based, which makes it easy to complement visual access with audio interfaces, adapting the feeds to different educational contexts and learning styles. This paper discusses the use of fee

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Srujana, Sri, E. Padmalatha Dr., and Tanvi Mareddy. "Review on Personalized Activity Notification and Feedback." Engineering and Technology Journal 10, no. 04 (2025): 4386–91. https://doi.org/10.5281/zenodo.15141775.

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News Aggregator is a real-time, personalized news and placement update service specifically tailored for students. It will be extremely difficult to keep up with in this age of information with information relevant to employment opportunities and pertinent information without the precise solutions in a timely manner. It caters to an application required by a centralized system that offers educational and professional content, well-curated towards individual academic or career interests. The system uses the application of ML and NLP for behavior and preference analysis regarding individuals. Re

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Soler Costa, Rebeca, Qing Tan, Frédérique Pivot, Xiaokun Zhang, and Harris Wang. "Personalized and adaptive learning." Texto Livre: Linguagem e Tecnologia 14, no. 3 (2021): e33445. http://dx.doi.org/10.35699/1983-3652.2021.33445.

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Education Technology advances many aspects of learning. More and more learning is taking place online. Learners’ learning behaviors, style, and performance can be easily profiled through learning analytics which collects their online learning footage. It enables and encourages educational research, learning software application development, and online education practices towards personalized and adaptive learning. As we continue to see personalized and adaptive learning progress, we must also pay attention to the negative impacts that feed into our research. In this paper, we will present our

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Manoharan, Saravanapriya, and Radha Senthilkumar. "An Intelligent Fuzzy Rule-Based Personalized News Recommendation Using Social Media Mining." Computational Intelligence and Neuroscience 2020 (May 31, 2020): 1–10. http://dx.doi.org/10.1155/2020/3791541.

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Recommendation of a relevant and suitable news article is an essential but a challenging task due to changes in the user interest categories over time. Moreover, the Internet technology provides abundant news articles from a huge amount of resources. Meanwhile, nowadays, many people are confronted with viral news articles through social media cost-free without considering the news sites. Therefore, mining of social media for addressing such viral news articles has become another key challenge. To overcome the above challenges, this paper proposes fuzzy logic approach for predicting users’ dive

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Navya, Vattikonda Anuj Kumar Gupta Achuthananda Reddy Polu Bhumeka Narra and Dheeraj Varun Kumar Reddy Buddula. "Leveraging Deep Learning for Personalized Fashion Recommendations Using Fashion MNIST." International Journal of Multidisciplinary Research in Science and Business 1, no. 7 (2025): 54–77. https://doi.org/10.5281/zenodo.15349661.

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People are particularly conscious of their clothing choices since fashion has a biginfluence on daily life. Large populations are usually recommended fashion goodsand trends by specialists via a manual, curated process. On the other hand, ecommerce websites greatly benefit from automatic, personalized recommendationsystems, which are becoming more popular. This study introduces a deep learningbased framework for personalized fashion recommendation, utilizing the FashionMNIST dataset as the primary data source. The dataset was divided into trainingand testing sets in a 70:30 ratio to ensure rob

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Zheng, Xiao, Fumi Wu, Weizhang Chen, Elham Naghizade, and Kourosh Khoshelham. "Show Me a Safer Way: Detecting Anomalous Driving Behavior Using Online Traffic Footage." Infrastructures 4, no. 2 (2019): 22. http://dx.doi.org/10.3390/infrastructures4020022.

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Real-time traffic monitoring is essential in many novel applications, from traffic management to smart navigation systems. The large number of traffic cameras being integrated into urban infrastructures has enabled efficient traffic monitoring as an intervention in reducing traffic accidents and related casualties. In this paper, we focus on the problem of the automatic detection of anomalous driving behaviors, e.g., speeding or stopping on a bike lane, by using the traffic-camera feed that is available online. This can play an important role in personalized route-planning applications where,

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Yongjun Zhang. "A Recommender System for Personalized Reading Recommendations and Literature Discovery utilizing the HGRNN-EOO technique." Journal of Electrical Systems 20, no. 3s (2024): 2283–96. http://dx.doi.org/10.52783/jes.3053.

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Recommender systems are used to address information overload, enhance personalization, and improve user experience by providing tailored suggestions based on individual preferences, thereby increasing engagement and facilitating content discovery. This paper proposes a hybrid approach for recommender system in personalized reading recommendation and literature discovery. The proposed hybrid approach is the combined performance of both the Hierarchal Gated Recurrent Neural Network (HGRNN) and Eurasian Oystercatcher Optimizer (EOO).Commonly it is named as HGRNN-EOO technique. The major objective

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Hui, Shuyue, and Yuanyuan Zhang. "A Virtual Reality Gearbox Experiment Platform Based on Hand Tracking and Natural Language Processing." Frontiers in Computing and Intelligent Systems 9, no. 3 (2024): 56–63. http://dx.doi.org/10.54097/kxbmxd41.

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In manufacturing engineering education, the gearbox is an essential mechanical component and a fundamental skill students must master. Recent data suggests that insufficient understanding of its load capacity and exceeding operational limits can damage internal components, potentially leading to severe consequences like fires. In order to address the challenges faced by physical laboratories and existing traditional virtual labs in the new engineering disciplines, including the lack of insufficient experimental safety, operational real-ism, insufficient personalized learning support, and the d

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A, Akshay. "Analysis of Model Progression and Parity in Personalized Modeling of Lipsync Decoder to Cater Hearing Impaired Individuals." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 03 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem29627.

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The Analysis of model progression and parity in personalized modeling of Lipsync decoder to cater hearing impaired individuals aims to enhance communication accessibility for hearing-impaired individuals by understanding flaws in and helping bring light to them translating visual cues from lip movements into intelligible speech through advancements in machine learning and computer vision. This paper delves into the analysis of model progression and parity in personalized modeling of Lipsync decoder technology to enhance communication accessibility for hearing-impaired individuals. By implement

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Papa, Venetia, and Thomas Photiadis. "Algorithmic Curation and Users’ Civic Attitudes: A Study on Facebook News Feed Results." Information 12, no. 12 (2021): 522. http://dx.doi.org/10.3390/info12120522.

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Facebook users are exposed to diverse news and political content; this means that Facebook is a significant tool for the enhancement of civic participation and engagement in politics. However, it has been argued that Facebook, through its algorithmic curation reinforces the pre-existing attitudes of individuals, rather than challenging or potentially altering them. The objective of this study is to elucidate the emotional and behavioural impact of the personalization of Facebook users’ News Feeds results, and thereby to uncover a possible link between their online and offline civic attitudes.

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Wang, Jonathan X., Delaney K. Sullivan, Alex C. Wells, and Jonathan H. Chen. "ClinicNet: machine learning for personalized clinical order set recommendations." JAMIA Open 3, no. 2 (2020): 216–24. http://dx.doi.org/10.1093/jamiaopen/ooaa021.

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Abstract Objective This study assesses whether neural networks trained on electronic health record (EHR) data can anticipate what individual clinical orders and existing institutional order set templates clinicians will use more accurately than existing decision support tools. Materials and Methods We process 57 624 patients worth of clinical event EHR data from 2008 to 2014. We train a feed-forward neural network (ClinicNet) and logistic regression applied to the traditional problem structure of predicting individual clinical items as well as our proposed workflow of predicting existing insti

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More, Anushree Deepak, Rakshita Devendra Godiyal, Hiral Gachake, and Ashwini Balaji Ghodake. "Robust Pi Surveillance Robot." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (2022): 154–58. http://dx.doi.org/10.22214/ijraset.2022.41173.

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Abstract: Remote surveillance of our house, as well as office areas, has become an important aspect. Human surveillance is achieved by moving (troop or equipment) personnel near sensitive areas to constantly monitor the area. But humans have their limitations, and deployment in inaccessible places is always impossible. We have developed a robot that can be used for video surveillance & monitoring which can be controlled through a GUI. Using this project, we put forward a surveillance robot with an Interface Board of the Raspberry Pi and Software to fulfill Real Time requirements. The Raspb

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Samuel O. Olorunkoya, Oluwatobi Fijabi, Oluseyi V. Alagbe, and Mowumi Olatinwo. "Harnessing the role of nutrigenomics for feed efficiency utilization in cattle: Opportunities and challenges." Engineering Science & Technology Journal 5, no. 7 (2024): 2139–56. http://dx.doi.org/10.51594/estj.v5i7.1308.

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Nutrigenomics, the study of the interaction between nutrition and genes, presents a transformative approach to enhancing feed efficiency in cattle. This field leverages genetic insights to optimize dietary formulations, aiming to improve nutrient utilization and overall productivity. With the global demand for meat and dairy products rising, increasing feed efficiency is critical for economic viability and environmental sustainability in the livestock industry. The role of nutrigenomics in cattle feed efficiency encompasses several key areas. Precision nutrition is one of the foremost opportun

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Rauf, Umber, Sadaqat Ali, Muhammad Sajid, et al. "Nutritional Strategies to Enhance Immunity in Poultry: A Review of Feed Additives and Dietary Formulations." Scholars Academic Journal of Biosciences 13, no. 02 (2025): 244–61. https://doi.org/10.36347/sajb.2025.v13i02.006.

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This review explores the effect of nutritional strategies on improving immunity in poultry with special emphasis on additives and diet formulations. Poultry immunity is sensitive to dietary components; nutrients such as antioxidants, essential fatty acids, probiotics, prebiotics, and phytochemicals are critical for modulating immune responses. Incorporating phytogenic feed additives and nutraceuticals into diets has quickly been perceived as a safe, natural strategy to boost poultry immunity. Finally, the emerging concept of precision nutrition, in which diets are designed specifically to the

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Patil, Swapnali, Keshav Jaiwal, Prem Shinde, Tanmay Jain, and Prof. Shobha Patil. "SheEO: Empowering Women Entrepreneurs." International Journal of Ingenious Research, Invention and Development (IJIRID) 4, no. 2 (2025): 478–84. https://doi.org/10.5281/zenodo.15449513.

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<em>The rise of digital technologies has revolutionized the business landscape, particularly in terms of accessibility and scalability for entrepreneurs. In India, the entrepreneurial ecosystem has historically been male-dominated, but recent trends indicate a significant increase in women-led startups. SheEO, a web application, is designed to support and empower women entrepreneurs by providing a comprehensive platform for mentorship, funding, and resource access. The platform leverages matchmaking algorithms to offer a personalized feed, allowing users to connect directly with mentors and in

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Xu, Shuyue. "Image-Based Fitness Guidance and Recording System." Journal of Computing and Electronic Information Management 15, no. 2 (2024): 36–40. https://doi.org/10.54097/02dy7x92.

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This study proposes a fitness guidance and recording system design based on computer vision, aiming to provide users with personalized, real-time and efficient fitness guidance and training, as well as dietary record services through advanced computer vision algorithms. The system integrates a variety of technologies such as image processing, action recognition and body analysis, which can automatically capture the movement posture of users in the process of fitness, and compare it with the standard action library, so as to accurately evaluate the accuracy of action and provide immediate feedb

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R, Selvam. "Applications Of Nutrigenomics in Livestock." Trends In Agriculture Science 2, no. 2 (2023): 130–35. https://doi.org/10.5281/zenodo.7682086.

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Nutrigenomics is a science which analyses the effects of nutrients on the expression of an individual’s genetic makeup. It includes three “omics” viz., Transcriptomics, Proteomics and Metabolomics.  It analyses how nutrition influence gene expression, metabolic pathways and disease development which implies the possibility to change the way of feeding the livestock and poultry. Nutrigenomics combines diversified fields such as nutrition, bioinformatics, molecular biology, genomics and epigenomics. The main function of nutrigenomics is to develop the feeds that can be mat

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Valerio, Andrea, Danilo Demarchi, Brendan O’Flynn, Paolo Motto Motto Ros, and Salvatore Tedesco. "Development of a Personalized Multiclass Classification Model to Detect Blood Pressure Variations Associated With Physical or Cognitive Workload." Sensors 24, no. 11 (2024): 3697. http://dx.doi.org/10.3390/s24113697.

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Comprehending the regulatory mechanisms influencing blood pressure control is pivotal for continuous monitoring of this parameter. Implementing a personalized machine learning model, utilizing data-driven features, presents an opportunity to facilitate tracking blood pressure fluctuations in various conditions. In this work, data-driven photoplethysmograph features extracted from the brachial and digital arteries of 28 healthy subjects were used to feed a random forest classifier in an attempt to develop a system capable of tracking blood pressure. We evaluated the behavior of this latter clas

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De Gregori, Manuela, Carolina Muscoli, Michael Schatman, et al. "Combining pain therapy with lifestyle: the role of personalized nutrition and nutritional supplements according to the SIMPAR Feed Your Destiny approach." Journal of Pain Research Volume 9 (December 2016): 1179–89. http://dx.doi.org/10.2147/jpr.s115068.

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Kim, Sora, Soo-Yeon Kim, and Kang Hoon Sung. "Fortune 100 companies’ Facebook strategies: corporate ability versus social responsibility." Journal of Communication Management 18, no. 4 (2014): 343–62. http://dx.doi.org/10.1108/jcom-01-2012-0006.

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Purpose – The purpose of this paper is to examine how Fortune 100 companies are using Facebook (FB) in terms of employing corporate ability (CA), corporate social responsibility (CSR), and hybrid communication strategies, meeting different stakeholders’ expectations, and incorporating interactivity components into social media. Design/methodology/approach – A quantitative content analysis was used to examine a total of 1,486 corporate FB postings. Findings –Fortune 100 companies predominantly employed a CA strategy over a CSR strategy or a hybrid strategy. They prioritize customers’ needs over

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Rahimifar, Atefeh, Karun Kaniyamattam, Jeffrey Wiegert, and Luis O. Tedeschi. "446 A stochastic, dynamic agent-based model of swine nutrient requirements for the growing finishing production phase." Journal of Animal Science 102, Supplement_3 (2024): 253–54. http://dx.doi.org/10.1093/jas/skae234.291.

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Abstract Agent-based modeling (ABM) is a powerful tool that offers the flexibility to represent the stochasticity exhibited by swine systems due to individual animal nutritional requirements. ABM can also accurately mimic the biological dynamic growth performance of pigs. Addressing and simulating the biological growth dynamics enables precision nutrition and sustainable production management. To realistically replicate the nutrient requirement and growth performance of growing-finishing pigs, we developed an ABM based on the principles and equations from the eleventh Swine Nutrient Requiremen

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Portnov, N. M., and E. N. Preobrazhenskaya. "DIET DEVELOPMENT AND SYSTEM OF MONITORING NUTRIENT STATUS." Informatics and education, no. 3 (May 10, 2019): 63–67. http://dx.doi.org/10.32517/0234-0453-2019-34-3-63-67.

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The article describes the experience of developing a standard menu for ballet students feeding, in accordance with the requirements of nutrient and natural consumption standards of SANPIN-2409 and taking into account the increased physical activity on the basis of a specialized computer program 1C:Medicine. Dietary food. A special computer system for monitoring physical development and nutrient status of those who feed according to the indicators of anthropometry, physical activity, body composition, actual nutrition, physical qualities, as well as laboratory analyses was developed to substant

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Schellewald, Andreas. "Theorizing “Stories About Algorithms” as a Mechanism in the Formation and Maintenance of Algorithmic Imaginaries." Social Media + Society 8, no. 1 (2022): 205630512210770. http://dx.doi.org/10.1177/20563051221077025.

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In this article, I report from an ethnographic investigation into young adult users of the popular short-video app TikTok. More specifically, I discuss their experience of TikTok’s algorithmic content feed, or so-called “For You Page.” Like many other personalized online environments today, the For You Page is marked by the tension of being a mechanism of digital surveillance and affective control, yet also a source of entertainment and pleasure. Focusing on people’s sense-making practices, especially in relation to stories about the TikTok algorithm, the article approaches the discursive repe

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Nicholson, Andrew A., Tomas Ros, Rakesh Jetly, and Ruth A. Lanius. "Regulating posttraumatic stress disorder symptoms with neurofeedback: Regaining control of the mind." Journal of Military, Veteran and Family Health 10, no. 4-EN (2024): 83–95. http://dx.doi.org/10.3138/jmvfh-0718-0015.

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Neurofeedback is emerging as a psychophysiological treatment where self-regulation is achieved through online feed-back of neural states. Novel personalized medicine approaches are particularly important for the treatment of posttrau-matic stress disorder (PTSD), as symptom presentation of the disorder, as well as responses to treatment, are highly het-erogeneous. Learning to achieve control of specific neural substrates through neurofeedback has been shown to display therapeutic evidence in patients with a wide variety of psychiatric disorders, including PTSD. This article outlines the neural

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Lee, Jungwoo, Cheong Kim, and Kun Chang Lee. "Investigating the Negative Effects of Emojis in Facebook Sponsored Ads for Establishing Sustainable Marketing in Social Media." Sustainability 13, no. 9 (2021): 4864. http://dx.doi.org/10.3390/su13094864.

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Emojis are prevalent in modern social media advertising. Despite this fact, little research can be found on its effects on consumer purchase intentions. This study seeks to examine purchase intentions in the context of Sponsored Ads on Facebook News Feeds, their perceived intrusiveness, and how the added factor of emoji presence can further affect consumer perception in order to suggest a pathway for establishing sustainable marketing strategies. We investigated the effect of emojis on consumers and then the extent to which ad personalization can attenuate intrusiveness to the point of influen

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D. V. S. Prabhash, T. K. Weerasinghe, R. T. K. Weerasiri, D. I. De Sliva, H. P. A. H. Piyumantha,. "Optimizing University Mobility : An Internal Navigation and Crowd Management System." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 879–88. http://dx.doi.org/10.17762/ijritcc.v11i9.8980.

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In the evolving landscape of educational technology, the article explores the critical frontier of indoor navigation systems, focusing on universities. Traditional approaches in higher education often fall short of meeting dynamic user expectations, necessitating revolutionary solutions. This research introduces an innovative internal navigation and crowd management system that seamlessly integrates augmented reality, natural language processing, machine learning, and image processing technologies. The Android platform serves as the foundation, harnessing augmented reality's transformative cap

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Steens, Thomas, Jan-Simon Telle, Benedikt Hanke, et al. "A Forecast-Based Load Management Approach for Commercial Buildings Demonstrated on an Integration of BEV." Energies 14, no. 12 (2021): 3576. http://dx.doi.org/10.3390/en14123576.

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Load-forecasting problems have already been widely addressed with different approaches, granularities and objectives. Recent studies focused not only on deep learning methods but also on forecasting loads on single building level. This study aims to research problems and possibilities arising by using different load-forecasting techniques to manage loads. For that behavior of two neural networks, Long Short-Term Memory and Feed-Forward Neural Network as well as two statistical methods, standardized load profiles and personalized standardized load profiles are analyzed and assessed by using a s

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Liu, Chuanxin, Bangchao Liang, Yangguang Zhao, and Xiaoxiao Han. "Effects of Hot-Melt-Extrusion process parameters on the Feedability of Fused Deposition Modeling filaments." Journal of Physics: Conference Series 2355, no. 1 (2022): 012017. http://dx.doi.org/10.1088/1742-6596/2355/1/012017.

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Abstract Fused deposition modelling (FDM) has shown its advantages in the field of personalized oral medicine due to its low cost, simplicity and flexible manufacturing for on- demand doses. However, most pharmaceutical-grade polymers that can be hot-melt extruded do not have the mechanical properties for high-quality FDM feedstock, and it is considered a barrier to further development of FDM pharmaceutical applications. In this paper, the impacts of Hot- Melt Extrusion (HME) process parameters on the mechanical properties of FDM filaments is explored for the brittle polymer polyvinylpyrrolido

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G, Prabakar, Arun, L., P. Kumaravel, et al. "Advancements in Animal Nutrition an Insights from Veterinary Science." UTTAR PRADESH JOURNAL OF ZOOLOGY 45, no. 16 (2024): 139–45. http://dx.doi.org/10.56557/upjoz/2024/v45i164294.

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Animal nutrition plays a crucial role in the health, well-being, and productivity of livestock and companion animals. As advancements in science and technology continue to reshape the field of animal nutrition, veterinary professionals are at the forefront of translating research findings into practical solutions for optimizing animal health and performance. This journal article provides a comprehensive overview of recent developments and emerging trends in animal nutrition, with a focus on veterinary perspectives. Drawing upon a synthesis of recent studies and industry developments, this pape

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J, Omana, Jeipratha P. N, Devi K, Benila S, and Revathi K. "Personalized Drug Recommendation System Using Wasserstein Auto-encoders and Adverse Drug Reaction Detection with Weighted Feed Forward Neural Network (WAES-ADR) in Healthcare." Journal of Informatics and Web Engineering 4, no. 1 (2025): 332–47. https://doi.org/10.33093/jiwe.2025.4.1.24.

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In recent years, the use of deep learning approaches in healthcare has yielded promising results in a variety of fields, most notably in the detection of adverse drug reactions (ADRs) and drug recommendations. This paper promises a breakthrough in this field by using Wasserstein autoencoders (WAEs) for personalized medicine recommendation and ADR detection. WAEs' capacity to manage complex data distributions and develop meaningful latent representations makes them ideal for modeling heterogeneous healthcare data. This study intends to improvise the precision and efficiency of drug recommendati

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Dutta, Shanta, Yuying Zhang, Mingjing He, and Daniel C.W. Tsang. "Adopting a personal learning environment and network to strengthen students’ self-directed and life-long learning attributes." Journal of Educational Research and Reviews 12, no. 1 (2024): 12–24. http://dx.doi.org/10.33495/jerr_v12i1.23.138.

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This study explored the implementation of a learner-centered interactive platform termed “Personal Learning Environment and Network (PLE&N)” in fostering a connected, deep, and personalized learning environment for accommodating students' diverse and unique learning needs. Leveraging the network-based and technology-enhanced PLE&N model introduced by the course instructor, students actively engaged with peers, instructors, experts, and professionals in a collaborative learning environment. As the successful implementation of PLE&N extensively relied on the student’s contribution to

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Cenamor, Isabel, Tomás De la Rosa, and Daniel Borrajo. "OnDroad Planner: Building Tourist Plans Using Traveling Social Network Information." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 1 (November 3, 2013): 14–15. http://dx.doi.org/10.1609/hcomp.v1i1.13118.

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One of the key challenges in automated planning is to define the sources of information that will feed the initial state and goals of each planning task. In many domains, the information comes from company's databases. In other applications, the information is harder to obtain and it is usually partial. In this paper, we will describe an application on travel planning, where the initial state and goals will be obtained by crowdsourcing. Travel planning requires the use of plenty Internet-based resources; some of them are related to human generated opinions on all kinds of matters (e.g. hotels,

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Patil, Swapnali. "ShEO: Empowering Women Entrepreneurs." International Journal for Research in Applied Science and Engineering Technology 12, no. 10 (2024): 1409–16. http://dx.doi.org/10.22214/ijraset.2024.64821.

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The rise of digital technologies has revolutionized the business landscape, particularly in terms of accessibility and scalability for entrepreneurs. In India, the entrepreneurial ecosystem has historically been male-dominated, but recent trends indicate a significant increase in women-led startups. ShEO, a Flutter-based application, is designed to support and empower women entrepreneurs by providing a comprehensive platform for mentorship, funding, and resource access. The platform leverages matchmaking algorithms to offer a personalized feed, allowing users to connect directly with mentors a

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Ilker, Yengin, Furkan Ince Ibrahim, Karahoca Adem, Karahoca Dilek, and Uzunboylu Huseyin. "The Use of Deliberates Practices on a Mobile Learning Environment." AWERProcedia Information Technology & Computer Science (Global Journal on Technology) 2, no. 1 (2012): 241–49. https://doi.org/10.5281/zenodo.834779.

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Mobile learning brings the opportunity to do practices and activities anywhere in our daily life. However learning for expertise requires more than daily activities, it requires deliberate practices. Different than daily activities and practices, deliberate practices are specific and well designed activities for gradually gaining and improving expertise with the help of teacher led feed-backs. This paper introduces the use of deliberates practices on a mobile learning environment. This paper describes the system design and applications including both teacher and student side of the mobile lear

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Zhu, Cong Rong, and Peng Yang. "The Design of Curler for Irregular Metal Lid Based on Pro/E." Applied Mechanics and Materials 741 (March 2015): 258–61. http://dx.doi.org/10.4028/www.scientific.net/amm.741.258.

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Canned foods with no preservatives are the safe alternatives to fresh and frozen foods which help to meet dietary needs. With the prevalence of canned foods, the sales grow rapidly which provides a bright prospect for metal packaging machinery. The appearance of the metal can is one of the important factors that will affect the sale. Therefore, canning companies pay special attention to the personalized metal packaging and attach great importance to the development and application of special-shaped cans, thus, square or oval cans are widely used. In view of the ubiquitous problems existing in

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Xie, Ruobing, Shaoliang Zhang, Rui Wang, Feng Xia, and Leyu Lin. "Hierarchical Reinforcement Learning for Integrated Recommendation." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 5 (2021): 4521–28. http://dx.doi.org/10.1609/aaai.v35i5.16580.

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Integrated recommendation aims to jointly recommend heterogeneous items in the main feed from different sources via multiple channels, which needs to capture user preferences on both item and channel levels. It has been widely used in practical systems by billions of users, while few works concentrate on the integrated recommendation systematically. In this work, we propose a novel Hierarchical reinforcement learning framework for integrated recommendation (HRL-Rec), which divides the integrated recommendation into two tasks to recommend channels and items sequentially. The low-level agent is

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Haghi, Mehdi, Reza Farshbaf Zinati, and Mohammad Reza Razfar. "Experimental and Modeling Study of the Turning Process of PA 6/Nano Calcium Carbonate Composite." Journal of Composites 2013 (May 27, 2013): 1–7. http://dx.doi.org/10.1155/2013/970954.

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Nowadays, polymeric nanocomposites have emerged as a new material class with rapidly growing use in industrial products because of good mechanical, thermal, and physical properties. Recently, the requirement of the direct machining of these materials has increased due to the production of the most of them by extrusion method in simple cross section and the increased demand for personalized products. In this work, the effect of turning parameters (cutting speed and feed) and nano calcium carbonate content on the machinability properties of polyamide 6/nano calcium carbonate composites was inves

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Chung, Min Hee. "Prediction model for day-ahead solar insolation using meteorological data for smart grid." E3S Web of Conferences 111 (2019): 06040. http://dx.doi.org/10.1051/e3sconf/201911106040.

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In the overseas market, power generation and energy service companies have been engaged in the business of providing personalized trading services for the production of electric power through the Internet platform. This is, so that the electric power sharing system between individuals is being developed through the Internet platform. The prediction of insolation is essential for the prediction of power generation for photovoltaic systems. In this study, we present a prediction model for insolation from data observed at the Meteorological Administration. We also present basic data for the devel

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Jiang, Lei, Haotan Wei, and Ding Liu. "Research on Abnormal State Detection of CZ Silicon Single Crystal Based on Multimodal Fusion." Sensors 24, no. 21 (2024): 6819. http://dx.doi.org/10.3390/s24216819.

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The Czochralski method is the primary technique for single-crystal silicon production. However, anomalous states such as crystal loss, twisting, swinging, and squareness frequently occur during crystal growth, adversely affecting product quality and production efficiency. To address this challenge, we propose an enhanced multimodal fusion classification model for detecting and categorizing these four anomalous states. Our model initially transforms one-dimensional signals (diameter, temperature, and pulling speed) into time–frequency domain images via continuous wavelet transform. These images

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Zhao, Yan, Qianrui Guo, Yukun Zhang, et al. "Application of Deep Learning for Prediction of Alzheimer’s Disease in PET/MR Imaging." Bioengineering 10, no. 10 (2023): 1120. http://dx.doi.org/10.3390/bioengineering10101120.

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging is a promising technique that combines the advantages of PET and MR to provide both functional and structural information of the brain. Deep learning (DL) is a subfield of machine learning (ML) and artificial intelligence (AI) that focuses on developing algorithms and models inspired by the structure and function of the human brain’s neural networks. DL has been applied to various aspects of PET/MR imaging in AD, such a

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Mittinty, Manasi M., John Lee, Amanda C. de C. Williams, and Natasha Curran. "Exploring patient experiences of a pain management centre: A qualitative study." Scandinavian Journal of Pain 17, no. 1 (2017): 378–81. http://dx.doi.org/10.1016/j.sjpain.2017.09.017.

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AbstractBackground and aimsTo improve care and management of patients with chronic pain it is important to understand patients’ experiences of treatment, and of the people and the environment involved. As chronic pain patients often have long relationships with medical clinics and pain management centres, the team and team interactions with the patients could impact the treatment outcome. The aim of this study was to elicit as honest as possible an account of chronic pain patients’ experiences associated with their care and feed this information back to the clinical team as motivation for impr

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Will, Ursula M. "Abstract 7400: Prevention outpatient clinic: evidence-based, risk-stratified counseling and prevention research." Cancer Research 85, no. 8_Supplement_1 (2025): 7400. https://doi.org/10.1158/1538-7445.am2025-7400.

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Abstract The Prevention Outpatient Clinic (POC), the centerpiece of the National Cancer Prevention Center (NCPC), is being established in Heidelberg through a long-term partnership between the German Cancer Research Center and the German Cancer Aid. This initiative aims to systematically expand evidence-based, personalized cancer prevention across Germany, integrating all essential elements of prevention, from basic research and clinical trials to public counseling and the training of prevention specialists, under one roof. Inspired by the Comprehensive Cancer Centers model, the NCPC seeks to

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Henrichs, Elia, Tanja Noack, Ana María Pinzon Piedrahita, María Alejandra Salem, Johnathan Stolz, and Christian Krupitzer. "Can a Byte Improve Our Bite? An Analysis of Digital Twins in the Food Industry." Sensors 22, no. 1 (2021): 115. http://dx.doi.org/10.3390/s22010115.

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The food industry faces many challenges, including the need to feed a growing population, food loss and waste, and inefficient production systems. To cope with those challenges, digital twins that create a digital representation of physical entities by integrating real-time and real-world data seem to be a promising approach. This paper aims to provide an overview of digital twin applications in the food industry and analyze their challenges and potentials. Therefore, a literature review is executed to examine digital twin applications in the food supply chain. The applications found are class

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Wolff, Monica, and Cella Buciuman. "Bias in Personalized Social Media Content: Impact on Romanian Generation Z Decision Making." European Conference on Social Media 12, no. 1 (2025): 11–19. https://doi.org/10.34190/ecsm.12.1.3293.

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In an era dominated by personalized digital experiences, social media platforms play an increasingly influential role in shaping young adults' perceptions and decisions. With the use of algorithms that personalize social media feeds for individual users, concerns have arisen regarding the extent to which such personalization reinforces preexisting biases and influences user behavior, with a focus on how it influences biased decisions in a variety of contexts, including political opinions, lifestyle choices, and shopping habits. This study investigates the impact of personalized social media co

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Sonea, Cosmin, Raluca Aniela Gheorghe-Irimia, Dana Tapaloaga, Maria Rodica Gurau, Lavinia Udrea, and Paul-Rodian Tapaloaga. "Optimizing Animal Nutrition and Sustainability Through Precision Feeding: A Mini Review of Emerging Strategies and Technologies." Annals of "Valahia" University of Târgovişte. Agriculture 15, no. 2 (2023): 7–11. http://dx.doi.org/10.2478/agr-2023-0011.

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Abstract Precision feeding, a practice involving customized diets tailored to individual nutritional requirements, has emerged as a promising paradigm within animal production, underpinned by advanced technologies and data analytics. This mini review embarks on an exploration of the evolutionary trajectory of precision feeding and its profound ramifications on animal nutrition, environmental sustainability, and animal welfare. Prominent technological advancements, exemplified by sensors and automation, have wrought transformative change across various sectors, spanning from dairy farming to po

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Nuijten, Raoul, Pieter Van Gorp, Alireza Khanshan, et al. "Evaluating the Impact of Adaptive Personalized Goal Setting on Engagement Levels of Government Staff With a Gamified mHealth Tool: Results From a 2-Month Randomized Controlled Trial." JMIR mHealth and uHealth 10, no. 3 (2022): e28801. http://dx.doi.org/10.2196/28801.

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Background Although the health benefits of physical activity are well established, it remains challenging for people to adopt a more active lifestyle. Mobile health (mHealth) interventions can be effective tools to promote physical activity and reduce sedentary behavior. Promising results have been obtained by using gamification techniques as behavior change strategies, especially when they were tailored toward an individual’s preferences and goals; yet, it remains unclear how goals could be personalized to effectively promote health behaviors. Objective In this study, we aim to evaluate the i

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Ronquillo-Cana, Carlos Javier, Pablo Pancardo, Martha Silva, José Adán Hernández-Nolasco, and Matias Garcia-Constantino. "Fuzzy System to Assess Dangerous Driving: A Multidisciplinary Approach." Sensors 22, no. 10 (2022): 3655. http://dx.doi.org/10.3390/s22103655.

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Dangerous driving can cause accidents, injuries and loss of life. An efficient assessment helps to identify the absence or degree of dangerous driving to take the appropriate decisions while driving. Previous studies assess dangerous driving through two approaches: (i) using electronic devices or sensors that provide objective variables (acceleration, turns and speed), and (ii) analyzing responses to questionnaires from behavioral science that provide subjective variables (driving thoughts, opinions and perceptions from the driver). However, we believe that a holistic and more realistic assess

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Senturk, Niyazi, Gulten Tuncel, Berkcan Dogan, et al. "BRCA Variations Risk Assessment in Breast Cancers Using Different Artificial Intelligence Models." Genes 12, no. 11 (2021): 1774. http://dx.doi.org/10.3390/genes12111774.

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Artificial intelligence provides modelling on machines by simulating the human brain using learning and decision-making abilities. Early diagnosis is highly effective in reducing mortality in cancer. This study aimed to combine cancer-associated risk factors including genetic variations and design an artificial intelligence system for risk assessment. Data from a total of 268 breast cancer patients have been analysed for 16 different risk factors including genetic variant classifications. In total, 61 BRCA1, 128 BRCA2 and 11 both BRCA1 and BRCA2 genes associated breast cancer patients’ data we

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Teixeira, Joana, Vicente Rocha, João Oliveira, Pedro A. S. Jorge, and Nuno A. Silva. "Towards real-time identification of trapped particles with UMAP-based classifiers." Journal of Physics: Conference Series 2407, no. 1 (2022): 012043. http://dx.doi.org/10.1088/1742-6596/2407/1/012043.

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Abstract Optical trapping provides a way to isolate, manipulate, and probe a wide range of microscopic particles. Moreover, as particle dynamics are strongly affected by their shape and composition, optical tweezers can also be used to identify and classify particles, paving the way for multiple applications such as intelligent microfluidic devices for personalized medicine purposes, or integrated sensing for bioengineering. In this work, we explore the possibility of using properties of the forward scattered radiation of the optical trapping beam to analyze properties of the trapped specimen

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Ma, Yifeng, Suzhen Wang, Zhipeng Hu, et al. "StyleTalk: One-Shot Talking Head Generation with Controllable Speaking Styles." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 2 (2023): 1896–904. http://dx.doi.org/10.1609/aaai.v37i2.25280.

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Different people speak with diverse personalized speaking styles. Although existing one-shot talking head methods have made significant progress in lip sync, natural facial expressions, and stable head motions, they still cannot generate diverse speaking styles in the final talking head videos. To tackle this problem, we propose a one-shot style-controllable talking face generation framework. In a nutshell, we aim to attain a speaking style from an arbitrary reference speaking video and then drive the one-shot portrait to speak with the reference speaking style and another piece of audio. Spec

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