A Robust Enhanced Ensemble Learning Method for Breast Cancer Data Diagnosis on Imbalanced Data by Zhenzhen Wang, Junde Xie, Jia Zhang

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Artificial intelligence in educational technology and transformative approaches to English language using fuzzy framework with CRITIC-TOPSIS method by Jingdan Liu, Xujie Bao, Liji Chen

“…Furthermore, a comprehensive comparative study is conducted to assess the compatibility of the proposed optimization techniques in the CRITIC-TOPSIS method with existing optimization approaches. …”
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Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems by Jevgenijs Telicko, Andris Krumins, Agris Nikitenko

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Efficient Parallel Video Processing Techniques on GPU: From Framework to Implementation by Huayou Su, Mei Wen, Nan Wu, Ju Ren, Chunyuan Zhang

“…Through the analysis to the kernels, we found that speedup ratios of the compute intensive algorithms are proportional with the computation power of the GPU. …”
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Physics-Based AI-Driven Surrogate Modeling for Structural Displacement Prediction in Mechanical Systems With Limited Sensor Data by Ali Hashemi, Javad Beheshti, Mahdieh Mohammadi

“…The methodology significantly reduces sensor requirements and computational overhead, offering a practical, scalable solution for structural health monitoring (SHM) in complex mechanical systems. …”
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Investigating Internet of Things and Artificial Intelligence-Based Approaches to Smart Irrigation System Optimisation for Agricultural Water Resource Management by Balassem Zaid Ajzan, Alkhafaij Mahdi Abdulkhudur, Raju Nadimpalli Venkata Ganapathi

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Enhancing 4G/LTE Network Path Loss Prediction with PSO-GWO Hybrid Approach by Messaoud Garah, Nabil Boukhennoufa

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A Statistical Analysis Based Probabilistic Routing for Resource-Constrained Delay Tolerant Networks by Jixing Xu, Jianbo Li, Shan Jiang, Chenqu Dai, Lei You

“…Based on statistical analysis, we compute and update the expected intermeeting times between nodes. …”
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Numerical-analytical modeling of oil extraction from oil fields with a gas cap using horizontal wells with automatic history matching by D. V. Shevchenko, A. A. Salamatin, A. D. Yarullin, S. A. Usmanov, V. V. Saveliev, V. A. Sudakov, A. P. Roschektaev, E. V. Yudin, D. S. Vorobyov, V. V. Sorokina, A. A. Sveshnikova

“…The average calculation time of one iteration being less than 10 seconds allows for multiple model run scenarios using optimization algorithms for automatic calibration to actual production data. …”
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Novel channel attention-based filter pruning methods for low-complexity semantic segmentation models by Md. Bipul Hossain, Na Gong, Mohamed Shaban

“…While the aforementioned models have been deemed very successful in segmenting medical targets including organs and diseases in high resolution images, the computational complexity represents a burden for the real-time application of the algorithms or the deployment of the models on resource-constrained platforms. …”
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A novel method for asynchronous source localisation based on time of arrival measurements by Huijie Zhu, Sheng Liu, Zhiqiang Yao, Moses Chukwuka Okonkwo, Zheng Peng

“…Comparative analysis with state-of-the-art semidefinite programming and min–max criterion-based algorithms are conducted. Simulations show that the proposed method is superior in terms of localisation accuracy and computational complexity, and can reach the optimality benchmark of Cramér–Rao Lower Bound even in high signal-to-noise ratio environments.…”
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Deep Learning-Based Sound Source Localization: A Review by Kunbo Xu, Zekai Zong, Dongjun Liu, Ran Wang, Liang Yu

“…Future research should prioritize physics-informed modeling to embed acoustic propagation mechanisms, unsupervised domain adaptation to reduce reliance on labeled data, and sensor-algorithm co-design to optimize hardware-software synergy. …”
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Artificial Intelligence for Unstructured Data Processing by Yohanes Bowo Widodo, Febrianti Widyahastuti, Mohammad Narji, Sondang Sibuea

“…By using deep learning models and advanced algorithms, AI can identify patterns and relationships in complex data, thereby providing deeper insights for better decision making. …”
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Application of the Endurance Time Method in the Seismic Assessment of Moment-Resisting Reinforced Concrete Frames with Setbacks by Mehdi Izadpanah

“…In this method, acceleration functions are generated using optimization algorithms, reducing the need for excessive use of accelerograms. …”
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Regulation of the functional state of locomotive crew drivers using biofeedback training: factor analysis of experimental data by N. V. Shcherbina

“…Biofeedback based on electrodermal activity of the skin is used as a method for optimizing the functional state of drivers and assistant drivers of locomotive crews. …”
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Effect of Low-Dose MDCT and Iterative Reconstruction on Trabecular Bone Microstructure Assessment. by Felix K Kopp, Konstantin Holzapfel, Thomas Baum, Radin A Nasirudin, Kai Mei, Eduardo G Garcia, Rainer Burgkart, Ernst J Rummeny, Jan S Kirschke, Peter B Noël

“…We investigated the effects of low-dose multi detector computed tomography (MDCT) in combination with statistical iterative reconstruction algorithms on trabecular bone microstructure parameters. …”
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AI-Driven Gamification and Biotechnical Systems in Cardiovascular Monitoring of Cyclic Sport Athletes by Shukurova Sayyora, Pulatova Mavlyuda, Adilbekov Taxir

“…The paper attempts to move forward research in biotechnical systems and gamification from traditional sports medicine, athlete conditioning, and exercise physiology contexts to emerging AI-enhanced frameworks that address current cardiovascular health challenges.In proposing such a novel approach, the authors reason why AHP-regression-based studies may be particularly suited for the iterative assessment, validation, and optimization of findings in the form of decision-making models such as personalized AI-driven training algorithms. …”
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A fast calculation approach for thermal distribution of aircraft piston pumps based on finite difference method by Jiming MA, Haolun NING

“…The principal advantage of this methodology resides in its substantially enhanced computational efficiency. Compared with conventional finite element approaches, the proposed method reduces the simulation duration to approximately 10 % of that required by traditional algorithms under identical operational conditions.The developed methodology enables efficient and accurate simulation of critical heat generation mechanisms in piston pumps, including frictional heating and fluid leakage phenomena, while simultaneously providing comprehensive temperature distributions across pump components. …”
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swPHoToNs: Toward trillion‐body‐scale cosmological N‐body simulations on Sunway TaihuLight supercomputer by Zhao Liu, Qiao Wang, Xiaojing Lv, Xu Liu, Hongsong Meng, Guanghui Zhu, Liang Gao, Haohuan Fu, Guangwen Yang

“…The scale of the problem naturally leads to extreme scenarios with billions or even trillions of particles, thus demanding massive computational power and highly efficient algorithms. …”
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Multidepot Recycling Vehicle Routing Problem with Resource Sharing and Time Window Assignment by Yong Wang, Xiuwen Wang, Xiangyang Guan, Jinjun Tang

“…The 3D k-means clustering algorithm groups customers into clusters on the basis of their spatial and temporal distances to reduce the computational complexity in optimizing the multidepot logistics networks. …”
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