Methodological aspects of inventory management in logistics under modern conditions by A. G. Sakharov, A. E. Trubin, O. P. Kultygin, A. Yu. Anisimov

“…The article aims to design optimal inventory management algorithms in logistics in the current environment. …”
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Reinforcement Learning-driven Mechanism Study of Ecological Compensation to Suppress Carbon Lock-in by Yongxin Zhou

“…Specifically, RL-MEC-CL, in a continuous action space, leverages an actor-critic architecture with experience replay and target networks to optimize compensation strategies adaptively, balancing carbon reduction benefits, sequestration enhancement, and policy costs. …”
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PENC: a predictive-estimative nonlinear control framework for robust target tracking of fixed-wing UAVs in complex urban environments by Shiji Hai, Xitai Na, Zhihui Feng, Jinshuo Shi, Qingbin Sun

“…This necessitates tracking algorithms capable of both target state estimation and prediction. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Further research is needed to evaluate cost-effectiveness, real-world applications, and strategies (e.g., clinician training and the integration of explainable AI) to improve trust and broaden clinical adoption.…”
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Developing advanced datadriven framework to predict the bearing capacity of piles on rock by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Fabián Danilo Reyes Silva, José Luis Allauca Palta, José Luis Llamuca Llamuca, Siva Avudaiappan

“…The developed framework provides engineers and practitioners with a powerful tool for improving pile design accuracy, reducing uncertainties, and optimizing construction practices. …”
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Convergence and Quantum Advantage of Trotterized MERA for Strongly-Correlated Systems by Qiang Miao, Thomas Barthel

“…Furthermore, we show how the convergence can be substantially improved by building up the MERA layer by layer in the initialization stage and by scanning through the phase diagram during optimization. …”
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Hierarchical Vehicle Scheduling Research on Tide Bicycle-Sharing Traffic of Autonomous Transportation Systems by Mai Hao, Ming Cai, Minghui Fang, Shuxin Jin

“…It minimizes operating costs and maximizes user satisfaction to dynamically optimize scheduling routes and required vehicles within each layered zone. …”
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THE PROBATION OFFICER AS AN AUTHORITY OF CRIMINAL ENFORCEMENT LAW. DEVELOPMENT PROSPECTS IN THE LIGHT OF MODERN TECHNOLOGIES by Tomasz Kalisz

“…Among the advantages are cost efficiency, increased work effectiveness, better prediction of recidivism risk, optimized resource use, individualized approach, and easier communication and collaboration. …”
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The Potential of Artificial Intelligence in Pharmaceutical Innovation: From Drug Discovery to Clinical Trials by Vera Malheiro, Beatriz Santos, Ana Figueiras, Filipa Mascarenhas-Melo

“…AI has revolutionized drug discovery and development by enabling rapid and effective analysis of vast volumes of biological and chemical data during the identification of new therapeutic compounds. The algorithms developed can predict the efficacy, toxicity, and possible adverse effects of new drugs, optimize the steps involved in clinical trials, reduce associated time and costs, and facilitate the implementation of innovative drugs in the market, making it easier to develop precise therapies tailored to the individual genetic profile of patients. …”
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Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…The superior performance of the neural network approach suggests significant potential for improving water resource management practices, optimizing cloud seeding interventions, and informing policy decisions. …”
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Heterogeneous Graph Attention Networks for Scheduling in Cloud Manufacturing and Logistics by Dmitrii Fomin, Ilya Makarov, Mariia Voronina, Anna Strimovskaya, Vitaliy Pozdnyakov

“…Our model minimizes both manufacturing and logistics costs, achieving significant performance improvements over greedy algorithms and comparable results to strong genetic algorithms in large-scale scenarios with up to 20 locations. …”
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Integrating Machine Learning and Material Feeding Systems for Competitive Advantage in Manufacturing by Müge Sinem Çağlayan, Aslı Aksoy

“…Material feeding systems are of pivotal importance in the optimization of productivity, with attendant improvements in quality, reduction of costs, and minimization of delivery times. …”
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Application of artificial intelligence in electrochemical diagnostics for human health by Koushlesh Ranjan, Basanti Barar, Minakshi Prasad, Gaya Prasad

“…AI also assists in optimizing sensor design, manages large datasets, and improves the performance and reliability of electrochemical diagnostics (ED) devices. …”
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Electricity nowcasting and forecasting efficiency in blockchain-integrated energy trading platforms by Ameni Boumaiza

“…Our methodology integrates real-time nowcasting algorithms and machine learning-based forecasting models to optimize electricity distribution, battery storage utilization, and cost efficiency within the marketplace. …”
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A Comprehensive Review of the Diagnostics for Pediatric Tuberculosis Based on Assay Time, Ease of Operation, and Performance by Soumya Basu, Subhra Chakraborty

“…Gaps in the existing diagnostic methods, algorithms, and operational costs were also reviewed. …”
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Predicting Subcontractor Performance Using Web-Based Evolutionary Fuzzy Neural Networks by Chien-Ho Ko

“…The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. …”
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A variable threshold ring signature scheme for privacy protection in smart city blockchain applications by Guo Hongzhi, Qin Haowen

“…We further introduce an optimized batch-verification algorithm that cuts the number of expensive pairing checks per signature from O(n) to $$O(1) + n$$ O ( 1 ) + n , dramatically improving throughput. …”
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Digital augmentation of aftercare for patients with anorexia nervosa: the TRIANGLE RCT and economic evaluation by Janet Treasure, Katie Rowlands, Valentina Cardi, Suman Ambwani, David McDaid, Jodie Lord, Danielle Clark Bryan, Pamela Macdonald, Eva Bonin, Ulrike Schmidt, Jon Arcelus, Amy Harrison, Sabine Landau

“…Statistical uncertainty was explored through bootstrapping 1000 randomly resampled pairs of costs and outcomes with cost-effectiveness planes and cost-effectiveness acceptability curves showing the likelihood of ECHOMANTRA being cost-effective at different willingness-to-pay levels generated. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…However, system heterogeneity, communication costs, and data imbalance remain critical. Oversampling techniques, model optimization, and reduced communication rounds were used to mitigate the issues. …”
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The Emergence of AI-Driven Virtual Hospitals: Redefining Patient Care Beyond Physical Boundaries by Ifrah Hameed, Hafiz Muhammad Haseeb Khaliq

“…For example, AI-based support systems offer data-driven insights that improve diagnostic accuracy and patient outcomes thus transforming healthcare delivery 3. …”
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