SAFERIDES: Application of decentralized control edge-computing to ridesharing monitoring services by Samaa Elnagar, Kweku Muata Osei Bryson, Manoj Thomas

“…However, advances in deep learning enabled Internet of Things (IoTs) to onload tasks and run cognitive tasks locally. …”
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A fuzzy-optimized multi-level random forest (FOMRF) model for the classification of the impact of technostress by Gabriel James, Ifeoma, David, John, Samuel, Enefiok, Imeh Umoren, Ubong Etuk, Aloysius, Anietie, Saviour, Chikodili

“…Traditional machine learning models often struggle with the complexity and non-linearity of technostress classification. …”
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Kerja lapangan dan simulasi peradilan sebagai metode pembelajaran mata kuliah Hukum Administrasi Negara by Eny Kusdarini, Setiati Widihastuti

“…Based on the explanation above, this research has an objective to develop the field work method and the fictive justice functioned as the learning model of State Administration Law subject in Department of Civic Education and Law (PKnH) FISE UNY which applies student centered learning characteristic. …”
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Analyzing Partial Shading in PV Systems Using Wavelet Packet Transform and Empirical Mode Decomposition Techniques by Kais Abdulmawjood, Walid G. Morsi

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Multi-User Satisfaction-Driven Bi-Level Optimization of Electric Vehicle Charging Strategies by Boyin Chen, Jiangjiao Xu, Dongdong Li

“…A bi-level optimization architecture is subsequently formulated, leveraging deep reinforcement learning (DRL) to capture user-specific demand characteristics through customized reward functions and adaptive constraint structures. …”
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Gene2role: a role-based gene embedding method for comparative analysis of signed gene regulatory networks by Xin Zeng, Shu Liu, Bowen Liu, Weihang Zhang, Wanzhe Xu, Fujio Toriumi, Kenta Nakai

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A multi-modal graph-based framework for Alzheimer’s disease detection by Najmeh Mashhadi, Razvan Marinescu

“…Abstract We propose a compositional graph-based Machine Learning (ML) framework for Alzheimer’s disease (AD) detection that constructs complex ML predictors from modular components. …”
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Empirical evidence of students' systems thinking skills in ESD-oriented: A Rasch analysis approach by Ikmanisa Khairati, L. Lufri, Muhyiatul Fadilah

“… Education for Sustainable Development (ESD) serves as a key accelerator for achieving the Sustainable Development Goals (SDGs), emphasizing systems thinking as an essential competency that must be cultivated in the learning process. This study investigates students' systems thinking skills within the ESD framework through assessments on environmental change—one of the core topics in biology education. …”
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Using the optimal combined index weight ratio to improve the probability of anomaly detection in big area additive manufacturing by Monique S. McClain, Dhrubajit Chowdhury, Omar Eldaghar, Kris Villez

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Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer by Zhaohui Wu, Liuliu Cao, Jie Zhao

“…By integrating multi-omics data from public repositories and applying machine learning-driven feature selection, we identified three core biomarkers—FABP4,CDR2L,and FSTL3 that independently predicted overall survival in CRC patients with diabetes. …”
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Research on object detection and recognition in remote sensing images based on YOLOv11 by Lu-hao He, Yong-zhang Zhou, Lei Liu, Wei Cao, Jian-hua Ma

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Advancing Scholarship Management: A Blockchain-Enhanced Platform With Privacy-Secure Identities and AI-Driven Recommendations by Tu-Anh Nguyen-Hoang, Ngoc Cu Hoang, Phu Thien Hua, Mong-Thy Nguyen Thi, Thu-Thuy Ta, Thu Nguyen, Khoa Tan-Vo, Ngoc-Thanh Dinh, Hong-Tri Nguyen

“…Additionally, a machine learning model is employed to predict scholarship qualification, functioning as a recommendation system that identifies and prioritizes deserving students. …”
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DMM-YOLO: A high efficiency soil fauna detection model based on an adaptive dynamic shuffle mechanism by Jiehui Ke, Renbo Luo, Guoliang Xu, Yuna Tan, Zhifeng Wu, Liufeng Xiao

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Wearable Sensors-Based Intelligent Sensing and Application of Animal Behaviors: A Comprehensive Review by Luyu Ding, Chongxian Zhang, Yuxiao Yue, Chunxia Yao, Zhuo Li, Yating Hu, Baozhu Yang, Weihong Ma, Ligen Yu, Ronghua Gao, Qifeng Li

“…Current behavior classification relies predominantly on traditional machine learning or deep learning approaches with high-frequency data acquisition. …”
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Planning and Scheduling System for Electric Vehicle Charging by Piotr Palka, Tomasz Sliwinski, Przemyslaw Kaszynski, Marta Kuta, Bogdan Ruszczak, Marcin Malec, Piotr Saluga, Jacek Kaminski

“…The research details the functional requirements of this procedure application and its architecture. …”
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Incorporating Crowdsourced Annotator Distributions into Ensemble Modeling to Improve Classification Trustworthiness for Ancient Greek Papyri by Graham West, Matthew I. Swindall, Ben Keener, Timothy Player, Alex C. Williams, James H. Brusuelas, John F. Wallin

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Prediction of protein biophysical traits from limited data: a case study on nanobody thermostability through NanoMelt by Aubin Ramon, Mingyang Ni, Olga Predeina, Rebecca Gaffey, Patrick Kunz, Shimobi Onuoha, Pietro Sormanni

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Molecular signatures bidirectionally link myocardial infarction and lung cancer by Dhruva Nandi, Rajiv Janardhanan, Sridhar Hannenhalli, Piyush Agrawal

“…In addition, a machine learning model based on the expression of the shared genes distinguished MI patients from controls, achieving an AUROC of 0.72 and an AUPRC of 0.86. …”
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Utilizing Artificial Intelligence for Microbiome Decision-Making: Autism Spectrum Disorder in Children from Bosnia and Herzegovina by Džana Bašić-Čičak, Jasminka Hasić Telalović, Lejla Pašić

“…Additionally, we developed machine learning classifiers to differentiate between the two groups using microbial abundance and predicted functional pathways. …”
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The Impact of Brain-Based Teaching on Iranian EFL Learners' Vocabulary Retention and Recall by Davoud Amini, Mahsa Rahmani Asl, Abolfazl Ghasemzadeh

“…The brain-based learning (BBL) approach refers to a learning method which attends to the structural and functional properties of the brain when involved in learning. …”
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