A Novel Active RFID and TinyML based system for livestock Localization in Pakistan by Syed Atir Raza Shirazi, Maham Fatima, Abdul Wahab, Sadaf Ali

“…To realize the full potential of this unique Active RFID and TinyML-based livestock localization system in Pakistan, further research should focus on optimizing localization algorithms, enhancing TinyML models, and exploring interaction with upcoming technologies …”
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Biometric Authentication Using Chest Wall Displacement Recorded by VHF-Band Loop Antenna by Shun Hinatsu, Saki Wada

“…We then applied non-fiducial techniques and classification algorithms to the signals under both intra- and inter-recording states. …”
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Leveraging Agent-Based Modeling and IoT for Enhanced E-Commerce Strategies by Mohamed Shili, Sajid Anwar

“…The paper provides a comprehensive overview of the system’s framework, design principles, and algorithms, highlighting the robustness and flexibility of the proposed structure. …”
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An efficient video slice encryption scheme and its application by Qinyou Huang, Luping Wang, Jie Chen

“…To address this issue, we propose a novel video security encryption scheme that optimally balances encryption speed and security. We introduce a scheme for video fragmentation, design corresponding sorting and merging algorithms, and construct a video transmission framework compatible with this scheme. …”
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Applications of Machine Learning in Human Factors and Ergonomics: A Comprehensive Review of Research From the Past Decade by Erman Cakit, Waldemar Karwowski

“…KNN, when optimized for k-values, yielded accuracy rates exceeding 90% in ergonomic applications. …”
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A Strategy-Driven Semantic Framework for Precision Decision Support in Targeted Medical Fields by Sivan Albagli-Kim, Dizza Beimel

“…Strategies integrate domain-specific knowledge and algorithms, refining decision making while maintaining the iterative nature of expert–patient interactions. …”
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Future horizons in diabetes: integrating AI and personalized care by Kaiqi Zhang, Yun Qi, Wenjun Wang, Xinyi Tian, Jiahui Wang, Lili Xu, Xu Zhai

“…Future horizons in diabetes care must focus on overcoming challenges in data privacy, algorithmic bias, device interoperability, and equity in AI-driven care while integrating these innovations into healthcare systems to improve patient outcomes and quality of life.…”
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AI-Driven Wearable Bioelectronics in Digital Healthcare by Guangqi Huang, Xiaofeng Chen, Caizhi Liao

“…We highlight how these technologies could democratize healthcare through remote patient monitoring and resource optimization while emphasizing the imperative of interdisciplinary collaboration to ensure equitable, secure, and clinically impactful deployment. …”
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A machine learning-powered energy consumption prediction system with API by Toyeeb Adekunle Abd’Azeez, Lanre Olatomiwa

“…After comparing different statistical models, including RandomForestRegressor, ExtraTreesRegressor, SupportVectorRegressor, and XGBRegressor algorithms, ExtraTreesRegressor emerged as the optimal model, with an R2 score of 0.7441 and a MAPE of 16.27%. …”
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Tracking Secondary Raw Material Operational Framework—DataOps Case Study by Gabriel Pestana, Marisa Almeida, Nelson Martins

“…It enhances supply chain transparency through digital traceability, promotes predictive material sourcing, and streamlines logistics via algorithmic optimization. Challenges such as regulatory gaps and quality standards are addressed through standardized processes, open data governance, and innovative algorithms. …”
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Multi-Agent Reinforcement Learning in Games: Research and Applications by Haiyang Li, Ping Yang, Weidong Liu, Shaoqiang Yan, Xinyi Zhang, Donglin Zhu

“…The findings reveal core principles governing how groups make optimal choices in complex environments while mapping the technological development pathways created by blending cross-disciplinary methods to enhance multi-agent systems.…”
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Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement by Kaustab C. Sahu, Slawomir Koziel, Anna Pietrenko-Dabrowska

“…The proposed procedure ensures building models of outstanding predictive power while using small training datasets, which is beyond the capabilities of benchmark algorithms.…”
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Hydrogen Enhancement in Syngas Through Biomass Steam Gasification: Assessment with Machine Learning Models by Yunye Shi, Diego Mauricio Yepes Maya, Electo Silva Lora, Albert Ratner

“…These algorithms outperform traditional models by accurately handling complex, high-dimensional data more efficiently and cost-effectively. …”
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A Comprehensive Survey on Machine and Deep Learning for Optical Communications by Mohammad Ali Amirabadi, S. Alireza Nezamalhosseini, Mohammad Hossein Kahaei, Lawrence R. Chen

“…Specific emphasis is placed on identifying how these algorithms enhance system performance and optimization. …”
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Scalable earthquake magnitude prediction using spatio-temporal data and model versioning by Rahul Singh, Bholanath Roy

“…The results reveal that Gradient Boosting performs optimally on smaller datasets, while LightGBM demonstrates superior accuracy with larger datasets, showcasing the pipeline’s flexibility and scalability. …”
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Increasing the noise immunity of radio receiving paths with automatic sensitivity control by Р. V. Zayats, I. Y. Malevich

“…The considered structural solutions and algorithms make it possible to optimize the technical appearance of RRPs for radar, radio navigation and radio communication with increased noise immunity and to adapt their characteristics to the conditions of nonstationary electromagnetic environment.…”
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Single-cell and multi-omics analysis reveals the role of stem cells in prognosis and immunotherapy of lung adenocarcinoma patients by Jianan Zheng, Haoran Lin, Wei Ye, Mingjun Du, Chenjun Huang, Jun Fan

“…Multiple machine learning algorithms were systematically compared in order to develop an optimal prognostic model. …”
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Using machine learning to predict anesthetic dose in fish: a case study using nutmeg oil by Mert Minaz, Cem Alparslan, Akif Er

“…Each model was trained using different activation functions (purelin, tansig, logsig) and optimization algorithms (traingda, trainrp, trains), and the optimal network architecture was selected based on prediction performance for each output variable. …”
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Deep Learning in Power Systems: A Bibliometric Analysis and Future Trends by Seyed Mahdi Miraftabzadeh, Andrea Di Martino, Michela Longo, Dario Zaninelli

“…Keyword trends show traditional deep learning techniques like LSTMs and CNNs are widely used in power systems, while newer methods like advanced reinforcement learning, graph neural networks, and physics-informed neural networks are emerging, promising advancements in optimal power flow, V2G integrations, and grid resilience. …”
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Data stewardship and curation practices in AI-based genomics and automated microscopy image analysis for high-throughput screening studies: promoting robust and ethical AI applicat... by Asefa Adimasu Taddese, Assefa Chekole Addis, Bjorn T. Tam

“…The study also examined specific AI considerations, such as algorithmic bias, model explainability, and the application of advanced cryptographic techniques. …”
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