Model predictive control for energy efficient AC motor drives: An overview by Muhammad Bilal Shahid, Weidong Jin, Muhammad Abbas Abbasi, Abdul Rashid Bin Husain, Hafiz Mudassir Munir, Mannan Hassan, Aymen Flah, Ahmed Saad Eddine Souissi, Thamer A. H. Alghamdi

“…Abstract State‐of‐the‐art model‐based predictive control techniques for AC motor drives are reviewed in this paper. A plethora of MPC algorithms with vast number of complex ideas has emerged in the last decade and this work makes an attempt to present those concepts in an intuitive, comprehensive and hierarchical manner. …”
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Deciphering the role of cuproptosis in the development of intimal hyperplasia in rat carotid arteries using single cell analysis and machine learning techniques by Miao He, Hui Chen, Zhengli Liu, Boxiang Zhao, Xu He, Qiujin Mao, Jianping Gu, Jie Kong

“…After identifying relevant genes, we verified CAGs expression in IH and control groups using a rat model of carotid balloon strain. …”
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Integration of AI with artificial sensory systems for multidimensional intelligent augmentation by Changyu Tian, Youngwook Cho, Youngho Song, Seongcheol Park, Inho Kim, Soo-Yeon Cho

“…We introduce specialized AI algorithms and raw data processing methods for each function, designed to enhance and optimize sensing performance. …”
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Target repositioning using multi-layer networks and machine learning: The case of prostate cancer by Milan Picard, Marie-Pier Scott-Boyer, Antoine Bodein, Mickaël Leclercq, Julien Prunier, Olivier Périn, Arnaud Droit

“…Second, by extracting relevant features from the network using several approaches including proximity to disease-associated genes, but also unbiased approaches such as propagation-based methods, topological metrics, and module detection algorithms. …”
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Delirium in tetanus patients: a review of clinical features, pathophysiology, and integrated management strategies by Yanwei Rao, Xinzao Xu, Lijing Chen, Di Wang, Lin Liu, Tingting Jiang, Yang Chen, Yongjie Wang

“…Large-scale prospective studies are essential to validate proposed management algorithms and refine evidence-based treatment protocols. …”
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Advancements in deep learning for early diagnosis of Alzheimer’s disease using multimodal neuroimaging: challenges and future directions by Muhammad Liaquat Raza, Muhammad Liaquat Raza, Muhammad Liaquat Raza, Syed Tawassul Hassan, Subia Jamil, Noorulain Hyder, Kinza Batool, Sajidah Walji, Muhammad Khizar Abbas

“…These models can effectively process structural and functional imaging modalities, extracting relevant features and patterns associated with Alzheimer’s pathology. …”
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Predictive modeling for rework detection in sustainable building projects by AbdulLateef Olanrewaju, Kafayat Shobowale

“…The results revealed that Random Forest and AdaBoost outperformed the other algorithms. The Adaboost achieved an accuracy of 90%, with a precision of 0.80, a recall of 0.76, and an F1-score of 0.77. …”
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Identification and experimental validation of BMX as a crucial PANoptosis‑related gene for immune response in Spinal Cord Injury. by Tianbao Feng, Jiating Hu, Mi Xie, Guodong Shi, Qi Wang, Jingyuan Yao, Xiaoqin Liu

“…Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and 8 machine learning algorithms were used to narrowed down hub genes. BMX and CASP5 were consistently identified across all algorithms. …”
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Identification of anoikis-related genes in heart failure: bioinformatics and experimental validation by Lina Zhang, Jianjun Gu, Yan Jiang, Juan Xue, Ye Zhu

“…Subsequently, two machine learning (ML) algorithms were employed to identify hub DEARGs: least absolute shrinkage and selection operator (LASSO) and random forest (RF). …”
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Efficient Explainable Models for Alzheimer’s Disease Classification with Feature Selection and Data Balancing Approach Using Ensemble Learning by Yogita Dubey, Aditya Bhongade, Prachi Palsodkar, Punit Fulzele

“…<b>Results:</b> This approach results in a robust, interpretable, and clinically relevant framework for Alzheimer’s disease diagnosis. …”
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Analysis of the Results of a Questionnaire Survey of Doctors and Clinical Psychologists on Somatovegetative Symptoms of Stress by Anna A. Kuzyukova, Natalia A. Levchenko, Larisa A. Marchenkova

“…The high prevalence of stress conditions among the Russian population contributes to the development of a large number of psychosomatic disorders associated with them, which cause frequent referral of these functional conditions to somatic medical institutions, along with the difficulty of timely diagnosis, which keeps the search and development of diagnostic algorithms aimed at their verification relevant. The National Medical Research Center for Rehabilitation and Balneology is working on the creation of a questionnaire “Comprehensive assessment of the physiological symptoms of stress”, in which a preliminary survey of specialists was conducted. …”
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Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer Diagnostics by Jihan Wang, Zhengxiang Zhang, Yangyang Wang

“…Feature selection methods—such as filter, wrapper, and embedded techniques—play a critical role in enhancing the precision of cancer diagnostics by identifying relevant biomarkers. The integration of multi-omics data and ML algorithms facilitates a more comprehensive understanding of tumor heterogeneity, advancing both diagnostics and personalized therapies. …”
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Innovative Educational Scenarios in Game Based Teaching and Learning by Ion Smeureanu, Narcisa Isăilă

“…Game based on demonstration (using simulation, modelling or visualization) coordinates users to obtain relevant information; the multiple representations of knowledge are so used and compared through a multitude of examples.…”
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Legal Analysis of AI-Generated Creations: Copyright Law Perspectives by Praja Chrisna Bagus Edhita, Hakim Hary Abdul, Basri, Kurniaty Yulia, Sari Elvira Purnama

“…Legal analysis shows that AI is just a computer programming tool that performs tasks based on human commands. AI uses algorithms and computer training for recognition, prediction, and decision-making. …”
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Generative design for architectural spatial layouts: a review of technical approaches by Shurui Yan, Chen Wu, Yixin Zhang

“…Additionally, improving computational efficiency makes knowledge-driven methods, such as heuristic algorithms, more user-friendly. Furthermore, the study suggests that an intelligent combination of these two approaches at different phases of generative design yields a promising research direction. …”
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Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping by Alexander Gresch, Martin Kliesch

“…In particular, efficient energy estimation may be crucial in achieving a quantum advantage for a practically relevant problem. For instance, the measurement effort poses a critical bottleneck for variational quantum algorithms. …”
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Pertinence of contact duration as edge feature for epidemic spread analysis by Ramya D. Shetty, Shrutilipi Bhattacharjee

“…Existing studies consider the edges mostly equally while designing the algorithms for the unweighted contact networks, where each connection explicitly shows whether the individuals are in contact or not. …”
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Analysis and Evaluation of Competence of Information Sources in Problems of Intellectual Data Processing by Krisilov V. A., Komleva N. O.

“…., using data mining algorithms and a statistical approach. The aim of the work is to formalize the description and analysis of the source data as a means of improving the quality of solving intellectual problems. …”
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Artificial Intellect and Methodology of Economic Science by M. V. Dubovik, S. G. Dmitriev

“…Apart from that, the issue of public trust to applying algorithms and elaboration of evidence-based policy become hardly attainable without relevant interpretation of model functioning, in spite of hypothetic accuracy of forecasts made with their help. …”
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A Systematic Review of Gen-AI Applications in Education: Rewards, Challenges and Future Prospects by Everleen Nekesa Wanyonyi, Millicent Kathambi Murithi

“…The widespread use of AI systems has sparked debates on how to effectively train future-relevant competencies while maintaining learning integrity. …”
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