A Novel Time Delay Nonsingular Fast Terminal Sliding Mode Control for Robot Manipulators with Input Saturation by Thanh Nguyen Truong, Anh Tuan Vo, Hee-Jun Kang

“…Manipulator systems are increasingly deployed across various industries to perform complex, repetitive, and hazardous tasks, necessitating high-precision control for optimal performance. However, the design of effective control algorithms is challenged by nonlinearities, uncertain dynamics, disturbances, and varying real-world conditions. …”
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Cybersecurity of smart grids: Comparison of machine learning approaches training for anomaly detection by S. V. Kochergin, S. V. Artemova, A. A. Bakaev, E. S. Mityakov, Zh. G. Vegera, E. A. Maksimova

“…The purpose of this work is to conduct research and analysis into the effectiveness of different machine-learning methods for identifying anomalies in decentralized smart networks, including cyberattacks and emergency modes, as well as to develop recommendations on the optimal combination of these methods for ensuring effective cybersecurity under conditions of changing electrical loads.Methods. …”
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Study of Factors Influencing Thermal Comfort at Tram Stations in Guangzhou Based on Machine Learning by Xin Chen, Huanchen Zhao, Beini Wang, Bo Xia

“…This research provides clear strategic guidance for urban planners, public transport managers, and designers to enhance thermal comfort at tram stations while offering a data-driven approach to optimizing outdoor spaces and promoting sustainable urban development.…”
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Revolutionizing Marine Stability: A Review of Cutting-Edge Gyro Stabilizer Designs and Techniques for Vessels by Wan Rahiman, Mohamad Hazwan Mohd Ghazali, Iskandar Al-Thani Mahmood

“…Despite these challenges, recent advancements in control algorithms and optimization techniques have improved gyro stabilizer adaptability under varying sea conditions. …”
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Personal health data protection and intelligent healthcare applications under generative adversarial network by Xiaoyuan Gao, Wei Mi, Xirui Feng

“…The proposed method employs a multi-generator architecture and optimizes generator parameters through gradient clipping and genetic algorithms, enhancing data privacy protection and the quality and utility of the generated data. …”
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Applications of artificial intelligence in neurosurgical education: a scoping review by Hector Julio Piñera-Castro, Christian Borges-García

“…Abstract Background Artificial intelligence (AI) has transformed medical education through optimized instruction, competency assessment, and personalized learning. …”
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End-to-End Vector Simplification for Building Contours via a Sequence Generation Model by Longfei Cui, Junkui Xu, Lin Jiang, Haizhong Qian

“…Simplifying building contours involves reducing data volume while preserving the continuity, accuracy, and essential characteristics of building shapes. …”
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State-Space Analysis and Complexity Assessment of Puzzle Games Using Colored Petri Nets by Ahmad Taghinezhad-Nia, Saeid Pashazadeh

“…By synthesizing model-checking techniques with ML-based algorithmic implementations, we develop an optimized search strategy for traversing the state space graph, enabling the derivation of quantitative complexity metrics. …”
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COMMUNICATION STRATEGIES AND TACTICS IN CRISIS SITUATIONS by Olena Danylina

“…The case-study analysis identified three overarching tactics of media behaviour: operational–informational (rapid dissemination of verified facts), analytical–interpretative (contextual explanation of cause-and-effect links), and mobilisation-oriented (stimulating collective action). Their optimal mix depends on crisis dynamics, while maximum effectiveness requires transparent sourcing, coordination with official bodies, and algorithmic content monitoring. …”
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Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models. by Al Mahmud Siam, Pankaj Bhowmik, Md Palash Uddin

“…Our framework integrates three complementary feature selection techniques: Pearson correlation, information gain (IG), and random forest importance (RFI), each optimized for the dataset's characteristics. Pearson Correlation eliminates redundancy by removing highly correlated features, while IG and RFI evaluate the relevance of the remaining features. …”
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Machine learning-based prediction of physical parameters in heterogeneous carbonate reservoirs using well log data by Fuyong Wang, Xianmu Hou

“…Application of cross-validation techniques optimized the performance of GPR, resulting in an accuracy index (ACI) value of 0.9699 for porosity prediction. …”
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Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector by Utsav Pandey, Sanjeet Singh

“…In the first stage, an output-oriented Data Envelopment Analysis is employed to model the interdependency between operational efficiency and service quality by assessing the allocation of the input resources for achieving these two objectives. While accounting for the external influences and avoiding the ‘best practice trap’ in the healthcare sector, a set of classification algorithms are used to quantify the impact of external factors on efficiency levels. …”
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Detection and Prediction of Wind and Solar Photovoltaic Power Ramp Events Based on Data-Driven Methods: A Critical Review by Jie Zhang, Xinchun Zhu, Yigong Xie, Guo Chen, Shuangquan Liu

“…This review systematically examines recent advancements in the field, focusing on three principal areas: the definition and detection of ramp event characteristics, innovations in predictive model architectures, and strategies for precision optimization. Our analysis reveals that while detection algorithms for ramp events have matured and the overall predictive performance of power forecasting models has improved, existing approaches often struggle to capture localized ramp phenomena, resulting in persistent deviations. …”
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An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change by J. D. Jakeman, M. Perego, D. T. Seidl, T. A. Hartland, T. R. Hillebrand, M. J. Hoffman, S. F. Price

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Advancing soil mapping and management using geostatistics and integrated machine learning and remote sensing techniques: a synoptic review by Sunshine A. De Caires, Chaney St Martin, Melissa A. Atwell, Fuat Kaya, Glorious A. Wuddivira, Mark N. Wuddivira

“…Hybrid approaches combining geostatistics with ML algorithms (e.g., RF, Boost, SVM, ANN) demonstrate promise in addressing spatial uncertainty, while RS data enhances covariate enrichment and near-real-time applications. …”
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The use of artificial intelligence in the HR processes of logistics companies by Adam Panek

“…Personalization of AI-based training improves employee engagement and productivity, while optimization of work schedules and accurate forecasting of staffing needs allow for better human resource management. …”
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Bioinformatic Analysis of Complex In Vitro Fertilization Data and Predictive Model Design Based on Machine Learning: The Age Paradox in Reproductive Health by Myrto A. Lantzi, Eleni Papakonstantinou, Dimitrios Vlachakis

“…This approach to the processing and utilization of clinical data demonstrates the potential for optimization and documentation of therapeutic procedures. …”
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Augmented intelligence with voice assistance and automated machine learning in Industry 5.0 by Alexandros Bousdekis, Mina Foosherian, Mattheos Fikardos, Stefan Wellsandt, Katerina Lepenioti, Enrica Bosani, Gregoris Mentzas, Klaus-Dieter Thoben

“…Augmented intelligence puts together human and artificial agents to create a socio-technological system, so that they co-evolve by learning and optimizing decisions through intuitive interfaces, such as conversational, voice-enabled interfaces. …”
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A Year of Critical Care: The Changing Face of the ICU During COVID-19 by Atiya Dhala, Deepa Gotur, Steven Huan-Ling Hsu, Aditya Uppalapati, Marco Hernandez, Jefferson Alegria, Faisal Masud

“…Houston Methodist’s incident command center team navigated this health crisis by ramping up its bed capacity, streamlining treatment algorithms, and optimizing ICU staffing while ensuring adequate supplies of personal protective equipment (PPE), ventilators, and other ICU essentials. …”
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Potential of Multi-Source Multispectral vs. Hyperspectral Remote Sensing for Winter Wheat Nitrogen Monitoring by Xiaokai Chen, Yuxin Miao, Krzysztof Kusnierek, Fenling Li, Chao Wang, Botai Shi, Fei Wu, Qingrui Chang, Kang Yu

“…Results showed that, while hyperspectral data yielded slightly higher accuracy, optimized multispectral indices, particularly from PS and S2, achieved comparable performance. …”
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