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 obtained research results indicate the advantages of using a combination of machine learning algorithms to ensure the reliable protection of smart networks from cyberattacks taking into account the nature of the electrical load.…”
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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

“…Six machine learning algorithms are utilized: support vector machine (SVM), backpropagation (BP) neural network, gaussian process regression (GPR), extreme gradient boosting (XGBoost), K-nearest neighbor (KNN), and random forest (RF). …”
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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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The Heart of Transformation: Exploring Artificial Intelligence in Cardiovascular Disease by Mohammed A. Chowdhury, Rodrigue Rizk, Conroy Chiu, Jing J. Zhang, Jamie L. Scholl, Taylor J. Bosch, Arun Singh, Lee A. Baugh, Jeffrey S. McGough, KC Santosh, William C.W. Chen

“…We analyze and discuss commonly used AI and ML models, algorithms, and methodologies, highlighting their roles in improving clinical outcomes while addressing current limitations and future clinical applications. …”
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Remote Sensing Image Segmentation Using Vision Mamba and Multi-Scale Multi-Frequency Feature Fusion by Yice Cao, Chenchen Liu, Zhenhua Wu, Lei Zhang, Lixia Yang

“…Although segmentation algorithms based on convolutional neural networks (CNNs) or Transformers have achieved significant performance improvements, the trade-off between segmentation precision and computational complexity remains a key limitation for practical applications. …”
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An Exceptional Responder to Nivolumab in Metastatic Non-Small-Cell Lung Cancer: A Case Report and Literature Review of Long-Term Survivors by Babak Baseri, Bachar Samra, Eric Tam, Edwin Chiu, Andrea Leaf

“…Studying the clinical course of exceptional responders can help identify potential predictors of response to immunotherapy and further fine-tune our management algorithms in the absence of standard of care in challenging scenarios. …”
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A DSP–FPGA Heterogeneous Accelerator for On-Board Pose Estimation of Non-Cooperative Targets by Qiuyu Song, Kai Liu, Shangrong Li, Mengyuan Wang, Junyi Wang

“…Instruction-level control supports model generalization, while a weight concatenation strategy improves resource utilization during convolution. …”
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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

“…However, persistent challenges include data scarcity in developing regions (only 12% of Sub-Saharan African monitoring stations provide real-time data), algorithmic bias (65% sensitivity loss in cross-regional models), and regulatory skepticism toward "black-box" systems. …”
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Inflow Prediction for Agricultural Reservoirs Using Disaster Prevention Measurement Data: A Comparison of TANK Model and Machine Learning by Bong-Kuk Lee, Joonyoung Choi, Kyoung Jae Lim, Jeongho Han

“…The results of this study demonstrate the potential of machine learning techniques for inflow prediction in agricultural reservoirs and suggest the need for further research on model improvement using various algorithms and input variables.…”
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Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study by Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi

“…Through this method, six optimal clusters were selected with a silhouette score of 0.2831, which is a relatively higher value compared to other clustering algorithms. …”
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Optimisation of the adaptive neuro-fuzzy inference system for adjusting low-cost sensors PM concentrations by Martina Casari, Piotr A. Kowalski, Laura Po

“…Notably, incorporating only PM2.5, relative humidity and temperature as features yields optimal performance while mitigating overfitting issues. …”
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