Mapping Landslide Sensitivity Based on Machine Learning: A Case Study in Ankang City, Shaanxi Province, China by Baoxin Zhao, Jingzhong Zhu, Youbiao Hu, Qimeng Liu, Yu Liu

“…The main purpose of this research is to apply the logistic regression (LR) model, the support vector machine (SVM) model based on radial basis function, the random forest (RF) model, and the coupled model of the whale optimization algorithm (WOA) and genetic algorithm (GA) with RF, to make landslide susceptibility mapping for the Ankang City of Shaanxi Province, China. …”
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Cyber threat intelligence for smart grids using knowledge graphs, digital twins, and hybrid machine learning in SCADA networks by Nabeel Al-Qirim, Munir Majdalawieh, Anoud Bani-hani, Hussam Al Hamadi

“…This study presents a novel “Digital-twin and Machine Learning-based SCADA Cyber Threat Intelligence (DT-ML-SCADA-CTI)” approach, which utilizes an innovative algorithm to visualize and predict the effects of cyber-attacks, including FDIA, RTCI, and SRA, on SCADA systems. …”
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Deep learning object detection-based early detection of lung cancer by Kuo-Yang Huang, Kuo-Yang Huang, Kuo-Yang Huang, Che-Liang Chung, Che-Liang Chung, Che-Liang Chung, Jia-Lang Xu

“…The performance of the You Only Look Once (YOLO) series of models in the lung CT image object detection task is compared in terms of algorithms, and different versions of YOLOv5, YOLOv8, YOLOv9, YOLOv10, and YOLOv11 are examined for lung cancer detection and classification. …”
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Local Entropy Optimization–Adaptive Demodulation Reassignment Transform for Advanced Analysis of Non-Stationary Mechanical Signals by Yuli Niu, Zhongchao Liang, Hengshan Wu, Jianxin Tan, Tianyang Wang, Fulei Chu

“…This method provides strong support for mechanical fault diagnosis, condition monitoring, and predictive maintenance, making it particularly suitable for real-time analysis of multi-component and cross-frequency signals.…”
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Artificial Intelligence in IVF Laboratories: Elevating Outcomes Through Precision and Efficiency by Yaling Hew, Duygu Kutuk, Tuba Duzcu, Yagmur Ergun, Murat Basar

“…AI’s data analysis and pattern recognition capabilities offer valuable predictive insights, enhancing personalized treatment plans and increasing success rates in fertility treatments. …”
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Fuzzy logic-based particle swarm optimization for integrated energy management system considering battery storage degradation by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Ahmed Tijjani Dahiru, Wen Yao Low, Mohd Herwan Sulaiman, Temitope Ibrahim Amosa

“…Overall, the FLB-PSO algorithm outperforms traditional PSO in terms of robustness to system dynamics, convergence rate, operational cost reduction, and improved energy efficiency.…”
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Signature of pre-pregnancy microbiome in infertile women undergoing frozen embryo transfer with gestational diabetes mellitus by Wenzheng Guan, Tian Zhou, Jiao Jiao, Liwen Xiao, Zhen Wang, Siyuan Liu, Fujie Yan, Fangqing Zhao, Xiuxia Wang

“…Algorithms on the basis of marker species and biochemical parameters can be used as effective tools for GDM risk evaluation before pregnancy.…”
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Dynamics of striatal action selection and reinforcement learning by Jack W Lindsey, Jeffrey Markowitz, Winthrop F Gillis, Sandeep R Datta, Ashok Litwin-Kumar

“…In our model, learning and action selection signals can be multiplexed without interference, enabling learning algorithms beyond those of standard temporal difference models.…”
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Improving the Classification Accuracy for Near-Infrared Spectroscopy of Chinese Salvia miltiorrhiza Using Local Variable Selection by Lianqing Zhu, Haitao Chang, Qun Zhou, Zhongyu Wang

“…Combining the strengths of the local algorithm and interval partial least squares, the spectra data have firstly been divided into several pairs of classes in sample direction and equidistant subintervals in variable direction. …”
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Oxidative stability of biodiesel in the presence of leaves and fruit extracts by Isadora Guilherme Branco, Erica Signori Romagnoli, José Gonçales Filho, Ana Carolina Gomes Mantovani, Dionisio Borsato

“…ABSTRACT This research evaluated the efficiency of ethanolic extracts from yerba mate leaves (Ilex paraguariensis), coffee leaves (coffea arabica), and jambolan pulp (Syzygium cumini Lamarck) through the application of the simplex-centroid mixture design, the super modified simplex optimization algorithm, and the functions of desirability, using the induction period (IP) and the rate constant (k) of the biodiesel oxidation reaction at 110 °C as responses. …”
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NMPC-Based 3D Path Tracking of a Bioinspired Foot-Wing Amphibious Robot by Heqiang Cao, Hailong Wang, Zhiqiang Hu

“…To this end, a nonlinear model predictive control (NMPC) algorithm is employed to compute optimal control inputs, as it effectively addresses the challenges of strong nonlinearity, coupling effects, and multi-objective optimization. …”
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Integrated Technologies for Smart Building Energy Systems Refurbishment: A Case Study in Italy by Lorenzo Villani, Martina Casciola, Davide Astiaso Garcia

“…This model enabled energy simulations using the Carrier–Pizzetti method and supported the design of a hybrid HVAC system—integrating VRF and hydronic circuits—further enhanced by a custom ML algorithm for adaptive, predictive energy management through BIM and IoT data fusion. …”
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Artificial intelligence-assisted nursing interventions in psychiatry for oral cancer patients: A concise narrative review by Abdulmalik Fareeq Saber, Sirwan Khalid Ahmed, Safin Hussein, Karzan Qurbani

“…Challenges and ethical considerations in integrating AI into healthcare include data privacy, algorithm validation, and the need for professional training.…”
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Hybrid nanofluid flow around a circular cylinder: A coupled ANN and numerical study of MHD, bioconvection, and thermal radiation by Muhammad Fawad Malik

“…This study provides significant information for researchers and engineers seeking to understand the characteristics of flow, its dynamics, and its predictive modeling.…”
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Intelligent Fault Warning Method for Wind Turbine Gear Transmission System Driven by Digital Twin and Multi-Source Data Fusion by Tiantian Xu, Xuedong Zhang, Wenlei Sun

“…A digital twin system architecture is developed, comprising a high-precision geometric model and a dynamic mechanism model, enabling real-time interaction and data fusion between the physical transmission system and its virtual model. At the algorithmic level, a CNN-LSTM-Attention fault prediction model is proposed, which innovatively integrates the spatial feature extraction capabilities of a convolutional neural network (CNN), the temporal modeling advantages of long short-term memory (LSTM), and the key information-focusing characteristics of an attention mechanism. …”
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Robust Load Frequency Control in Cyber-Vulnerable Smart Grids with Renewable Integration by Rambaboo Singh, Ramesh Kumar, Utkarsh Raj, Ravi Shankar

“…In light of these concerns, this study proposes a cyber-physical LFC framework incorporating a fuzzy linear active disturbance rejection controller (F-LADRC), wherein the controller parameters are systematically optimized using the quasi-opposition-based reptile search algorithm (QORSA). Furthermore, the proposed approach integrates a comprehensive cyberattack detection and prevention scheme, employing Haar wavelet transforms for anomaly detection and long short-term memory (LSTM) networks for predictive mitigation. …”
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AI-Powered Eye Tracking for Bias Detection in Online Course Reviews: A Udemy Case Study by Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

“…We selected Udemy courses, a platform with over 70 million learners. Predict (version 1.0.), developed by Stanford University, was used with the algorithm on the consumer neuroscience database (n = 180,000) from Tobii eye tracking (Tobii X2-30, Tobii Pro AB, Danderyd, Sweden). …”
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Optimisation of railway tamping scheduling by Mahdi Khosravi, Alireza Ahmadi, Ahmad Kasraei, Arne Nissen

“…To achieve this, we formulated the track geometry tamping scheduling problem as a mixed integer linear programming model and employed a genetic algorithm for its resolution. Key track quality indicators, including the standard deviation of the longitudinal level and single defects, were considered.We developed predictive models for the evolution of standard deviation and single defects over time, which were utilised to schedule preventive tamping activities and anticipate potential corrective actions. …”
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SorpVision: A Comprehensive Dataset for Cementitious Sorptivity Analysis Powered by Computer Vision by Hossein Kabir, Jordan Wu, Sunav Dahal, Tony Joo, Nishant Garg

“…SorpVision, combined with a cost-effective USB camera setup and a robust vision algorithm, facilitates real-time water level detection in cementitious systems. …”
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Hybrid Paddy disease classification using optimized statistical feature based transformation technique with explainable AI by M Amudha, Brindha K

“…This research proposes a machine learning strategy based on Explainable AI that can assist farmers quickly diagnose and manage rice leaf diseases. To enhance predictive performance by transforming features, an improved Owl Search Optimization (IOSO) algorithm is used. …”
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