Transfer Learning for Induction Motor Health Monitoring: A Brief Review by Prashant Kumar

“…These sophisticated deep learning algorithms have been widely used for induction motor health monitoring due to their autonomous feature extraction abilities and end-to-end learning capabilities. …”
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Determinants of depressive symptoms in multinational middle-aged and older adults by Can Lu, Shenwei Wan, Zhiyong Liu

“…Abstract This study harnesses machine learning to dissect the complex socioeconomic determinants of depression risk among older adults across five international cohorts (HRS, ELSA, SHARE, CHARLS, MHAS). Evaluating six predictive algorithms, XGBoost demonstrated superior performance in four cohorts (AUC 0.7677–0.8771), while LightGBM excelled in ELSA (AUC 0.9011). …”
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Teaching deep networks to see shape: Lessons from a simplified visual world. by Christian Jarvers, Heiko Neumann

“…This suggests that different learning algorithms with sparser, more local weight changes are required to make networks more sensitive to shape and improve their capability to describe human vision.…”
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The influence of eye model parameter variations on simulated eye-tracking outcomes by Joshua Fischer, David van den Heever, Johan van der Merwe

“…The outcomes showed that variations in anterior corneal asphericity significantly influence simulated eye-tracking outcomes of both interpolation and model-based gaze estimation algorithms. Other, more commonly varied parameters such as the corneal radius of curvature and foveal offset angle had little influence on simulated outcomes.  …”
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Symmetrifying Smart Home by Sungyong Ahn

“…It describes a smart home as a topological continuum that could unfold lots of functional spaces—those optimized for a variety of predictable user behaviors and intentions, such as going to bed, working out, and energy-saving—according to how software applications redeploy its embedded sensors and actuators into certain algorithmic orders. …”
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Probabilistic Operation of the Microgrids Including Active Loads and Distributed Generation Constrained to Flexibility and Reliability Indices by Hosein Hasan Shahi, Mehdi Nafar, Mohsen Simab

“…The ant-lion and crow search algorithms are merged to solve the problem and find a reliable optimal solution. …”
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Neural mechanisms for the attention-mediated propagation of conceptual information in the human brain. by David Acunzo, Damiano Grignolio, Clayton Hickey

“…However, neuroscientific investigation has focused closely on the identification of the systems and algorithms that support attentional control or that instantiate the effect of attention on sensation and perception. …”
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Genetic and bioinformatics analysis of an individual with Am phenotype due to variant of A-glycosyltransferase enzyme gene by ZHANG Xu, ZHOU Zhuren, HUANG Xuying, LI Lichun, LI Xiaofeng, LI Jianping

“…The c.912C>A mutation was predicted to be “probably damaging” and “deleterious” by PolyPhen2 and PROVEAN algorithms, respectively. …”
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Integrated bioinformatics analysis to develop diagnostic models for malignant transformation of chronic proliferative diseases by Hua Liu, Sheng Lin, Pei-Xuan Chen, Juan Min, Xia-Yang Liu, Ting Guan, Chao-Ying Yang, Xiao-Juan Xiao, De-Hui Xiong, Sheng-Jie Sun, Ling Nie, Han Gong, Xu-Sheng Wu, Xiao-Feng He, Jing Liu

“…Lactoferrin (LTF) and G protein-coupled receptor 65 (GPR65) were integrated into a nomogram with a robust predictive power. The predicted drug vemurafenib inhibited proliferation and increased apoptosis in PV and AML cells. …”
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Artificial Intelligence and Ethical Dimensions of Automated Traffic Enforcement: Implications for Public Health, Healthcare Equity, and Social Justice by Patricia Haley

“…The analysis reveals how machine learning and predictive analytics in automated enforcement create disproportionate burdens on marginalized populations through three specific mechanisms: (1) biased algorithmic design that targets low-income neighborhoods more intensively, (2) punitive traffic fine structures that impose greater relative financial hardship on economically disadvantaged families, and (3) opaque implementation practices that limit community understanding and participation. …”
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The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis by Gujun Cong, Jingjing Shao, Feng Xiao, Haixia Zhu, Peipei Kang

“…A diagnostic model was then constructed and validated using a combination of 108 machine learning algorithms. The XGBoost and Random Forest algorithms highlighted the significant role of COL1A1, and we further analyzed the expression and correlation of COL1A1, AR, and EGFR through multiplex immunofluorescence staining. …”
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SOME TYPES OF METASUBJECT RESULTS WHEN TEACHING MATHEMATICS by V. A. Testov

“…Among of metasubject results of studying mathematics, the following types of mathematical schemes of thinking are identified: logical, algorithmic, combinatory, figurative-geometrical, stochastic. …”
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Prospects for Legal Regulation of Quantum Communication by A. Minbaleev, S. Zenin, K. Evsikov

“…The authors note that their predictions about the cryptographic strength of encryption algorithms are based solely on modern knowledge about the capabilities of quantum computing and do not take into account its hidden potential, for example, in terms of cryptanalysis information systems based on a machine learning model generated by a quantum computer. …”
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The effects of limb position and grasped load on hand gesture classification using electromyography, force myography, and their combination. by Peyton R Young, Kihun Hong, Eden J Winslow, Giancarlo K Sagastume, Marcus A Battraw, Richard S Whittle, Jonathon S Schofield

“…An emerging alternative control technique is force myography (FMG) which uses pattern recognition algorithms to predict hand gestures from the axial forces present at the skin's surface created by contractions of the underlying muscles. …”
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Acoustic-Based Machine Main State Monitoring for High-Speed CNC Drilling by Pimolkan Piankitrungreang, Kantawatchr Chaiprabha, Worathris Chungsangsatiporn, Chanat Ratanasumawong, Peemdej Chancharoen, Ratchatin Chancharoen

“…By integrating big data concepts and intelligent algorithms, the system supports continuous monitoring, anomaly detection, and process optimization. …”
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Model Selection Methods for Model-Bridge Simulation Calibration by Bojan Batalo, Lincon S. Souza, Keisuke Yamazaki

“…Often, manual calibration is time-consuming, error-prone, and dependent on expert knowledge. Therefore, many algorithmic approaches have been explored, from heuristic-based and Bayesian methods to search and genetic algorithms. …”
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Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players by Ui-jae Hwang, Kyu Sung Chung, Sung-min Ha

“…Supervised learning models achieved high performance in classifying EOA status, with Random Forest, gradient boosting, and decision tree algorithms achieving 100% classification accuracy (AUC = 1.000) on the test dataset. …”
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Identifying the NEAT1/miR-26b-5p/S100A2 axis as a regulator in Parkinson's disease based on the ferroptosis-related genes. by Taole Li, Jifeng Guo

“…According to the five machine algorithms, 4 features (S100A2, GNGT1, NEUROD4, FCN2) were screened and used to create a PD diagnostic model. …”
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Gated recurrent deep learning approaches to revolutionizing English language learning for personalized instruction and effective instruction by Bo Sun

“…The GRNN-ELL model dynamically adapts to the learner’s progress using powerful sequence modelling and language processing algorithms. The training and evaluation architecture and dataset are detailed with an emphasis on optimization techniques. …”
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Parallel region growing of half-tone images based on selected average brightness of the area along the growth route by V. Yu. Tsviatkou

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