Research on Migration Strategy of Mobile Agent in Wireless Sensor Networks by Dai Ting, Huang Haiping, Lu Yang, Wang Ruchuan, Pan Xinxing

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To the 110 anniversary since the birth of professor E.A.Vasyukova by Alexandr Sergeevich Ametov, Elena Valerievna Doskina, Irina Ivanovna Kochergina, Olga Mikhailovna Smirnova, Ekaterina Evgenyevna Mishina

“…Ekaterina Alekseevna had long and difficult career path - from research assistant to the director of the All-Russian Institute of Experimental Endocrinology(now Endocrinology Research Centre), was head of it for 10 years, a long time was head of the Department of Endocrinology at the Central Institute of Advanced Medical Ministry of Health (now the Academy of Postgraduate Education). She had more than 200 publications, including 14 monographs, collections and algorithms in endocrinology. …”
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Analysis of Blockchain-Technology by Danylo Dvorchuk, Iryna Shpinareva

“…The research highlights recent advancements, such as AI-assisted transaction validation and adaptive consensus algorithms, as promising directions for blockchain scalability and security. …”
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A Review of Modeling and Control Techniques for Unmanned Aerial Vehicles by Elisabeth Andarge Gedefaw, Nardos Belay Abera, Chala Merga Abdissa

“…The findings highlight that hybrid control strategies incorporating adaptive mechanisms, learning‐based algorithms, and quaternion‐based modeling offer significant potential for enhancing autonomy and control. …”
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Using the Remote Sensing Method to Simulate the Land Change in the Year 2030 by Burcu Degerli, Mehmet Çetin

“…Spatial and temporal variability properties of LU/LC were determined using MLC algorithm, controlled classification approach. The predictive values of the LU/LC change that will occur in 2030, calculated with the MLP‑ANN model based on Machine Learning algorithms and mapped with the QGIS 3.16 program. …”
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High-Frequency Cryptocurrency Price Forecasting Using Machine Learning Models: A Comparative Study by Fátima Rodrigues, Miguel Machado

“…We compare various machine learning models, including recurrent neural networks (RNNs), time series analysis (ARIMA), and conventional regression algorithms, using minute-step Bitcoin price data over a 30-day period to predict prices 60 min ahead. …”
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Electromyography based Gesture Recognition: An Implementation of Hand Gesture Analysis Using Sensors by Talha Khan, Shaheer Ahmed, Syed Safdar Ali Rizvi, Sadique Ahmad, Nitasha Khan

“…Moreover, Artificial Intelligence (AI) based predictive or classification algorithms may be applied for the best optimal results.   …”
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LED-Based Optical Wireless Power Transmission for Automatic Tracking and Powering Mobile Object in Real Time by Mingzhi Zhao, Tomoyuki Miyamoto

“…By integrating machine vision and predictive control algorithms, the system ensures accurate tracking and stable power delivery under dynamic operating conditions. …”
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Applications of Machine Learning Technologies for Feedstock Yield Estimation of Ethanol Production by Hyeongjun Lim, Sojung Kim

“…As a result, this study will help researchers and engineers predict feedstock yields using various machine learning techniques, and contribute to efficient and stable biofuel production and supply chain design based on accurate predictions of feedstocks.…”
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Optimizing Wheat Yields: AI and IoT Techniques for Continuous Agricultural Monitoring by Nandy Manish, Afzal Md

“…This data is analyzed using AI algorithms developed predictive models and actionable insights. …”
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Pioneering machine learning techniques to estimate thermal conductivity of carbon-based phase change materials: A comprehensive modeling framework by Raouf Hassan, Alireza Baghban

“…A dataset of 482 samples, incorporating various nanoparticle types, concentrations, PCM types, and operating temperatures, was curated and refined using the Monte Carlo Outlier Detection algorithm. Extensive machine learning algorithms were explored; however, CatBoost, XGBoost, ANN, Random Forest, and Gradient Boosting emerged as the most accurate models. …”
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Analysis of signals from air conditioner compressors with ordinal patterns and machine learning by Keila Barbosa, Alejandro C Frery, George DC Cavalcanti

“…Integrating machine learning methods with a symbolic transformation offers a robust approach for the early and accurate diagnosis of potential failures, enhancing the predictive maintenance of air conditioning equipment.…”
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Stroke Risk Classification Using the Ensemble Learning Method of XGBoost and Random Forest by Gullam Almuzadid, Egia Rosi Subhiyakto

“…This study proposes a stroke risk classification model using ensemble learning that combines Random Forest and XGBoost algorithms. A Kaggle dataset with 5110 samples (249 stroke, 4861 non-stroke) presented significant class imbalance. …”
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ML-Based Materials Evaluation in 3D Printing by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Jakub Kopowski

“…Machine learning (ML) is transforming the evaluation of 3D printing materials, enabling more efficient and accurate assessment of material properties, including their sustainable life cycle. ML algorithms can analyze vast amounts of data from previous printing processes to predict the performance of different materials (including those used in multi-material printing) under different conditions. …”
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Artificial intelligence in soil science: Where do we go now? by Jose Pablo Castro, Caley K. Gasch, Paulo Flores

“…Core Ideas Artificial intelligence (AI) is changing soil science with advanced analytic and predictive modeling tools. Ethical AI in soil science should focus on data integrity, privacy, and transparent research. …”
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Performance-Enhancing Market Risk Calculation Through Gaussian Process Regression and Multi-Fidelity Modeling by N. Lehdili, P. Oswald, H. D. Nguyen

“…More precisely, multi-fidelity modeling combines models of different fidelity levels, defined as the degree of detail and precision offered by a predictive model or simulation, to achieve rapid yet precise prediction. …”
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A Comprehensive Survey on AI in Counter-Terrorism and Cybersecurity: Challenges and Ethical Dimensions by Ioannis Syllaidopoulos, Klimis S. Ntalianis, Ioannis Salmon

“…This paper provides a comprehensive overview of AI methodologies, such as predictive analytics, Natural Language Processing (NLP), and machine learning architectures (e.g., Support Vector Machines – SVM and Long Short-Term Memory – LSTM), and optimization algorithms (e.g., Particle Swarm Optimization – PSO), assessing their effectiveness in security applications. …”
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Supervised filters for EEG signal in naturally occurring epilepsy forecasting. by Francisco Javier Muñoz-Almaraz, Francisco Zamora-Martínez, Paloma Botella-Rocamora, Juan Pardo

“…Such filters have been employed in a machine learning algorithm, such as the K-Nearest Neighbor (KNN), to improve the prediction of seizures. …”
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Potentialities and development of groundwater resources applying machine learning models in the extended section of Manbhum-Singhbhum Plateau, India by Arijit Ghosh, Biswajit Bera

“…XGBoost indicates the highest predictive capacity (AUC 0.97). The innovation of this study lies in the combination of hydrological, topographical and geological datasets into machine learning platform. …”
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Advancements in Chemical Materials: Exploring Smart Storage Equipment and Protection Systems (Review) by Samah Kamil, Mohammed Al-Turfi, Riyadh Almukhtar

“…Results showed breakthroughs in sensor technologies, systems integration, and AI algorithms for real-time storage facility monitoring, danger identification, and predictive analytics. …”
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