A survey on the applications of transfer learning to enhance the performance of large language models in healthcare systems by Anmol Rahujo, Daniya Atif, Syed Azeem Inam, Abdullah Ayub Khan, Sajid Ullah

“…Abstract The healthcare field experiences significant developments through transfer learning and large language models that boost medical diagnosis accuracy while improving patient services and clinical process automation. …”
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Energy Management and Edge-Driven Trading in Fractal-Structured Microgrids: A Machine Learning Approach by Mostafa Pasandideh, Jason Kurz, Mark Apperley

“…The integration of renewable energy into residential microgrids presents significant challenges due to solar generation intermittency and variability in household electricity demand. …”
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A New Serious Game (<i>e-SoundWay</i>) for Learning English Phonetics by Alfonso Lago-Ferreiro, María Ángeles Gómez-González, José Carlos López-Ardao

“…This paper presents the design and evaluation of <i>e-SoundWay</i>, a cross-platform serious game developed to improve English phonetic competence through a multimodal and narrative-driven approach. …”
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A Combined Windowing and Deep Learning Model for the Classification of Brain Disorders Based on Electroencephalogram Signals by Dina Abooelzahab, Nawal Zaher, Abdel Hamid Soliman, Claude Chibelushi

“…Objective: This study presents a deep learning-based model designed to classify EEG data with better accuracy compared to existing approaches. …”
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Predicting OCD severity from religiosity and personality: A machine learning and neural network approach by Brian A. Zaboski, Alixandra Wilens, Joseph P.H. McNamara, Gregory N. Muller

“…We applied advanced machine and deep learning techniques to identify key predictors of OCD severity, uncovering nuanced relationships and unexpected findings. …”
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The Teacher's Challenges of the Implementation of Problem-Based Learning in Teaching English at SMKN 1 Toraja Utara by Yanti Inna Pagampa, Viktor Siumarlata, Judith Ratu Tandi Arrang

“… The urgency of this research lies in addressing the practical challenges faced by teachers in implementing Project-Based Learning (PBL) within English instruction at SMKN 1 Toraja Utara, particularly under the Merdeka Belajar Curriculum. …”
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A Cross-sectional Study on Attitude, Practices and Perception of Medical Undergraduates towards E-learning by B. M. Sindhu, B. M. Rashmi, Abhinandan S. Kumbar, Shivakumar Manmathayya

“…It equips students with the competencies needed to thrive in the field of rapidly evolving medical education. The present study was conducted to assess the attitudes and practices regarding ‘e-learning’ amongst undergraduate students and interns of a medical college. …”
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Faces of different socio-cultural identities impact emotional meaning learning for L2 words by Beixian Gu, Xiaobing Sun, David Beltrán, Manuel de Vega

“…Abstract This study investigated how exposure to Caucasian and Chinese faces influences native Mandarin-Chinese speakers’ learning of emotional meanings for English L2 words. …”
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Interactive Learning: The Use of Multimedia with Hybrid Models in Balinese Language Subjects for Grade VII Students by I Gede Ardi Suryadharma, I Nyoman Jampel, I Komang Sudarma

“…The results of the validity of interactive multimedia development will be presented in five main points which include: subject matter experts, learning design experts, learning media experts, individual trials, and small group trials. …”
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Comparative analysis of the performance of regression machine learning models for indoor visible light positioning systems by Mohamed Hussien Moharam

“…Abstract This paper presents an Indoor Visible Light Positioning (VLP) system designed for deployment in enclosed environments, using four ceiling-mounted Light Emitting Diodes (LEDs) to serve both illumination and positioning functions. …”
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Leveraging Collaborative Strategic Reading (CSR) on Project-Based Learning (PjBL): Text Types by Frida Unsiah, Pratnyawati Nuridi Suwarso, Wahyu Diny Sujannah, Sugeng Susilo Adi, Siti Maftuhah Damio

“…Reading is regarded as an essential activity in language learning, providing a valuable source of information, an exciting activity, a tool of communication, and a way to enhance one's knowledge. …”
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Accelerated and Energy-Efficient Galaxy Detection: Integrating Deep Learning with Tensor Methods for Astronomical Imaging by Humberto Farias, Guillermo Damke, Mauricio Solar, Marcelo Jaque Arancibia

“…As astronomical surveys continue to produce vast amounts of data, the computational and energy demands for galaxy classification have escalated, necessitating more efficient and sustainable approaches. This study presents a novel application of tensor factorization within the Faster R-CNN framework, resulting in the development of our model, T-Faster R-CNN, designed to enhance both the energy efficiency and computational performance of deep learning models used in galaxy classification. …”
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Advances in Skeleton-Based Fall Detection in RGB Videos: From Handcrafted to Deep Learning Approaches by Van-Ha Hoang, Jong Weon Lee, Md. Jalil Piran, Chun-Su Park

“…In this paper, we examine the most recent advances in skeleton-based fall detection in RGB videos, from handcrafted feature-based methods to advanced deep learning algorithms. Further, we present several skeleton-based fall detection techniques and their performance results on various benchmark datasets, along with challenges and future directions in this field.…”
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Survival analysis for sepsis patients: A machine learning approach to feature selection and predictive modeling by Kaida Cai, Xiaofang Yang, Zhengyan Wang, Wenzhi Fu, Hanwen Liu, Fatemeh Mahmoudi

“…Abstract Sepsis is a life-threatening condition that presents substantial challenges to healthcare and pharmacological management due to its high mortality rates and complex patient responses. …”
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Exploring self-regulated learning strategies to enhance English speaking skills among EFL students by Ulin Ni'mah, Mutiatun Nasihah, Farid Munfaati

“…The idea of self-regulation derived from educational psychology has recently increased researchers’ interest in second language learning. Self-Regulated Learning (SRL) is crucial since it empowers language learners to take ownership of their studies. …”
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Predicting tennis match outcomes mid-game using machine learning on psychological and physical data by Boyuan Li, Zihui Deng, Gaurav Gupta, Jinger Li, Yixuan Miao

“…The role of player performance is integral in-game analytics, impacting the interpretation and results of the analysis. Our work presents an AI for Science (AI4Sci) method to use real-time data from each game point to determine essential feature values, formulate and assess the impact of psychological momentum, and employ machine learning methodology on mid-match data for predicting the game’s victor. …”
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The effect of educational intervention based on mobile learning on the knowledge and self-efficacy of healthcare providers in vaccination by Leila Shamsi, Mojgan Janighorban, Soheila Mohamadirizi

“…BACKGROUND: The gap between the knowledge and self-efficacy of healthcare providers and their actual function in doing vaccination calls for the implementation of a program that can empower them. Thus, the present study was conducted to determine the effect of mobile learning educational intervention on the knowledge and self-efficacy of healthcare providers in conducting vaccination. …”
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Comparative Analysis of Machine learning Methods to Identify signs of suspicious Transactions of Credit Institutions and Their Clients by Yu. M. Beketnova

“…Automation of the process of identifying unscrupulous credit institutions based on machine learning methods will allow regulatory authorities to quickly identify and suppress illegal activities. …”
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Application of machine learning for real-time water quality monitoring in developing countries: A review by Samson Otieno Ooko, Laura Cheptegei, Simon M. Karume

“…The emergence of the Internet of Things (IoT) technologies and Machine Learning (ML) present opportunities that can be exploited for monitoring water quality in real-time. …”
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e-Health Strategy for Surgical Prioritization: A Methodology Based on Digital Twins and Reinforcement Learning by Fabián Silva-Aravena, Jenny Morales, Manoj Jayabalan

“…This article presents a methodological framework for elective surgery scheduling based on the integration of patient-specific Digital Twins (DTs) and reinforcement learning (RL). …”
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