Analisis Visual dan Machine Learning untuk Mengukur Validitas Dokumen Akademik Perpustakaan: Studi pada Data Turnitin by Hesti Ari Wardani, Imam Yuadi

“…Additionally, a logistic regression algorithm is applied to classify documents based on Turnitin scores. …”
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Examining the role of social media in fostering responsible consumption: Insights from Bitcoin Adoption trends (2015–2023) by Yu Ge, Haochuan Wang, Kenny Soon Lee Cheah, Azni Zarina Binti Taha

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MAPPING GENERATIVE AI'S ETHICAL ISSUES IN HIGHER EDUCATION: A FELT-GUIDED SYSTEMATIC REVIEW [PEMETAAN ISU ETIKA GENERATIVE AI DI PENDIDIKAN TINGGI: TINJAUAN SISTEMATIS BERPANDUAN... by okky barus, Achmad Nizar Hidayanto, Imairi Eitiveni

“…The SLR revealed seven prominent ethical concerns: (1) academic integrity and plagiarism, highlighting issues of unauthorized assistance and false authorship; (2) bias and fairness, manifested through algorithmic and linguistic biases; (3) data privacy and security, concerning unauthorized access and re-identification risks; (4) impact on critical thinking and learning outcomes, fostering over-reliance; (5) authorship, intellectual property, and copyright ambiguities; (6) misinformation, hallucinations, and deepfakes, eroding trust; and (7) broader environmental and labor impacts. …”
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Enhancing emergency response efficiency through advanced urban logistics: The role of driver psychophysiology and vehicle dynamics in mitigating socio-economic impacts by Yurii Davidich, Dávid Földes, Andrii Galkin

“…This work lays a foundation for future research aimed at integrating real-time data analytics and sophisticated routing algorithms to further refine emergency response mechanisms in urban environments.…”
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Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach by Yueyi Li, Xiaodong Zhang

“…Furthermore, an improved adaptive large neighborhood search (ALNS) algorithm is developed to enhance computational efficiency and solution quality. …”
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Enhance differential privacy mechanisms for clinical data analysis using CNNs and reinforcement learning by Rakesh Batchala, Priyank Jain, Manasi Gyanchandani, Sanyam Shukla, Rajesh Wadhvani

“…We investigated the synergy between Convolutional Neural Networks (CNNs) and two reinforcement learning algorithms: the value-based Deep Q-Network (DQN) and the policy-based Advantage Actor-Critic (A2C). …”
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Reverse Logistics Network Optimization for Retired BIPV Panels in Smart City Energy Systems by Cimeng Zhou, Shilong Li

“…Through the energy conversion of building skins, building-integrated photovoltaic (BIPV) technology, the core carrier of the smart city energy system, encourages the conversion of buildings into energy-generating units. …”
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Spatiotemporal Analysis of Eco-Geological Environment Using the RAGA-PP Model in Zigui County, China by Xueling Wu, Jiaxin Lu, Chaojie Lv, Liuting Qin, Rongrui Liu, Yanjuan Zheng

“…Focusing on Zigui County, this study developed a 16-indicator evaluation system integrating geological, ecological, and socioeconomic factors. …”
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Machine learning in predicting firm performance: a systematic review by Yaseen Hezam, Hoa Luong, Lilian Anthonysamy

“…It reveals a predominance of classification methods in ML, with neural networks, logistic regression, and decision trees being the most frequently employed algorithms. These findings underscore the potential of ML techniques to provide a more nuanced and accurate prediction of firm performance by integrating diverse data sources and attributes. …”
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Mission Sequence Model and Deep Reinforcement Learning-Based Replanning Method for Multi-Satellite Observation by Peiyan Li, Peixing Cui, Huiquan Wang

“…We propose a framework that integrates stochastic master-satellite mission allocation with single-satellite replanning, supported by reactive scheduling policies trained via deep reinforcement learning. …”
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Assessing the Guidelines on the Use of Generative Artificial Intelligence Tools in Universities: A Survey of the World’s Top 50 Universities by Midrar Ullah, Salman Bin Naeem, Maged N. Kamel Boulos

“…However, our study found that only a small number of the retrieved guidelines offered instructions on the AI algorithm (understanding how it works), the documentation of prompts and outputs, AI detection tools, and mechanisms for reporting misconduct. …”
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Large Language Models in Medical Chatbots: Opportunities, Challenges, and the Need to Address AI Risks by James C. L. Chow, Kay Li

“…These include hallucinations (the generation of factually incorrect or misleading content by an AI model), algorithmic biases, privacy risks, and a lack of regulatory clarity. …”
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Bridging the Gap: A Review of Machine Learning in Water Quality Control by Herlina Abdul Rahim, Nur Athirah Syafiqah Noramli, Indrabayu

“…This review critically examines the integration of machine learning (ML) with conventional water quality monitoring and treatment methods, presenting a systematic comparison of their capabilities, limitations, and synergies. …”
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BRIDGING THE GAP: OPPORTUNITIES, CHALLENGES AND STRATEGIES FOR AI DEPLOYMENT IN PUBLIC SERVICE DELIVERY by Richard Douglas Kamara

“…Additionally, building public trust by implementing transparent policies and actively involving citizens in the adoption process is vital for the successful integration of AI. …”
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High-flow nasal cannula therapy versus continuous positive airway pressure for non-invasive respiratory support in paediatric critical care: the FIRST-ABC RCTs by Padmanabhan Ramnarayan, Alvin Richards-Belle, Karen Thomas, Laura Drikite, Zia Sadique, Silvia Moler Zapata, Robert Darnell, Carly Au, Peter J Davis, Izabella Orzechowska, Julie Lester, Kevin Morris, Millie Parke, Mark Peters, Sam Peters, Michelle Saull, Lyvonne Tume, Richard G Feltbower, Richard Grieve, Paul R Mouncey, David Harrison, Kathryn Rowan

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Machine Learning-Assisted Sustainable Mix Design of Waste Glass Powder Concrete with Strength–Cost–CO₂ Emissions Trade-Offs by Yuzhuo Zhang, Jiale Peng, Zi Wang, Meng Xi, Jinlong Liu, Lei Xu

“…To address this gap, this study proposes an AI-assisted framework integrating machine learning (ML) and Multi-Objective Optimization (MOO) to achieve a sustainable GPC design. …”
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Remote sensing-based assessment of four decades of land use/land cover change in the Sigi River Watershed, East Usambara Mountains, Tanzania by Simon Chidodo, Simon Chidodo, Lulu Zhang, Azin Zarei, Karl-Heinz Feger

“…These spatial patterns reflect the influence of population pressure, socio-economic transformations, government land policies, and the establishment of protected areas in the uplands. …”
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On the Synergy of IoMT Devices and Ceiling-Mounted Systems for Advanced Medical Data Analytics by Andreas Andreou, Constandinos X. Mavromoustakis, Evangelos K. Markakis, Athina Bourdena, George Mastorakis

“…Specifically, Twin-Delayed Deep Deterministic Policy Gradients (TD3) and Soft Actor-Critic (SAC) algorithms are adopted to optimize task scheduling and system decisions in dynamic, resource-constrained settings. …”
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An End-to-End Solution for Large-Scale Multi-UAV Mission Path Planning by Jiazhan Gao, Liruizhi Jia, Minchi Kuang, Heng Shi, Jihong Zhu

“…The MHA module effectively models global spatial-task dependencies among nodes, enhancing solution quality. Additionally, we integrate a Multi-Start Greedy Rollout Baseline to evaluate diverse trajectories via parallelized greedy searches, thereby reducing policy gradient variance and improving training stability. …”
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Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model by Jingjing Sun, Xin Guan, Xiaojun Sun, Xiaojing Cao, Yepei Tan, Jiarong Liao

“…The work first establishes a Random Forest Regression (RFR) model. The RFR algorithm integrates Bagging ensemble learning and random subspace theory to construct multiple decision trees and aggregate their predictions, thereby enhancing the model’s prediction accuracy and stability. …”
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