Spatiotemporal tensor analysis for effective information mining of hydraulic structures considering environmental excitation and vibration response by Hui Li, Zhang Han, Tengfei Bao, Xiaohan Duan, Guang Yang, Xianyu Xiong, Yibo Ouyang, Jiankang Lou

“…The time-weighted modified dynamic time warping theory and curvature smoothing algorithm were combined to construct the optimal filter model with a balancing factor to extract the effective information from vibration response. …”
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Online variational Gaussian process for time series data by Weidong Wang, Mian Muhammad Yasir Khalil, Leta Yobsan Bayisa

“…Unlike traditional methods that rely on a fixed number of inducing points, OLVGP adaptively adjusts the number of inducing points as new data arrives and optimizes them from the model, ensuring that the model remains computationally efficient while maintaining high predictive accuracy. …”
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Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes by T. V. Zolotova, D. A. Volkova

“…The practical implementation of the methods for detecting and eliminating outliers used in this work can be a tool for calculating more accurate indicators in any area, for example, to improve forecasting the stock price. As part of further work, it is possible to consider the optimization of the parameters used in the methods of detecting and correcting outliers to study their effect on the results of the models.…”
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An Approach for Detecting Faulty Lines in a Small-Current, Grounded System Using Learning Spiking Neural P Systems with NLMS by Yangheng Hu, Yijin Wu, Qiang Yang, Yang Liu, Shunli Wang, Jianping Dong, Xiaohua Zeng, Dapeng Zhang

“…An adaptive learning mechanism was introduced to optimize the convergence and precision of the detection model. …”
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Bagging Vs. Boosting in Ensemble Machine Learning? An Integrated Application to Fraud Risk Analysis in the Insurance Sector by Ruixing Ming, Osama Mohamad, Nisreen Innab, Mohamed Hanafy

“…Addressing the pressing challenge of insurance fraud, which significantly impacts financial losses and trust within the insurance industry, this study introduces an innovative automated detection system utilizing ensemble machine learning (EML) algorithms. The approach encompasses four strategic phases: 1) Tackling data imbalance through diverse re-sampling methods (Over-sampling, Under-sampling, and Hybrid); 2) Optimizing feature selection (Filtering, Wrapping, and Embedding) to enhance model accuracy; 3) employing binary classification techniques (Bagging and Boosting) for effective fraud identification; and 4) applying explanatory model analysis (Shapley Additive Explanations, Break-down plot, and variable-importance Measure) to evaluate the influence of individual features on model performance. …”
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A Lightweight Method for Road Defect Detection in UAV Remote Sensing Images with Complex Backgrounds and Cross-Scale Fusion by Wenya Zhang, Xiang Li, Lina Wang, Danfei Zhang, Pengfei Lu, Lei Wang, Chuanxiang Cheng

“…Experimental findings indicate that the CSGEH-YOLO algorithm surpasses the baseline YOLOv8s, achieving a 3.1% improvement in mAP. …”
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Estimation of the Number of Active Sweat Glands Through Discrete Sweat Sensing by Jelte R. Haakma, Elisabetta Peri, Simona Turco, Eduard Pelssers, Jaap M. J. den Toonder, Massimo Mischi

“…Based on our findings, we provide recommendations for optimal device layouts to improve accuracy in estimating active sweat glands. …”
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CareNexus: Integrated solutions for Healthcare Communication by Alexandru Ioan BULZAN

“…A secure authentication based on multiple factors and the use of encryption algorithms, an interface based on different user roles and a prediction system based on model training had been implemented. …”
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Sparse Convolution FPGA Accelerator Based on Multi-Bank Hash Selection by Jia Xu, Han Pu, Dong Wang

“…However, many computing devices that claim high computational power still struggle to execute neural network algorithms with optimal efficiency, low latency, and minimal power consumption. …”
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Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation by Liang Liu, Xige Zhang, Jiahui Zhou, Kai Niu, Zixuan Guo, Yawen Zhao, Meng Zhang

“…Additionally, by analyzing the relationship between performance and reliability, we proposed optimization methods to improve reliability while ensuring a high performance was maintained. …”
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A data driven approach to urban area delineation using multi source geospatial data by Chenyu Fang, Lin Zhou, Xinyue Gu, Xing Liu, Martin Werner

“…Abstract This study introduces a data-driven, bottom-up approach to urban delineation, integrating feature engineering with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, which represents a significant improvement in precision and methodology compared to traditional approaches that rely on simplistic OpenStreetMap (OSM) road node data aggregations. …”
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MATE-ViT: A multi-channel contrast-limited adaptive time-frequency enhancement and vision transformer framework for bearing fault diagnosis by Jiangdong Zhao, Jiao Yu, Wenming Wang, Ji Huang, Xiaolu Ma

“…First, an improved CLAHE algorithm is used to independently enhance the multi-channel time-frequency images, effectively improving the local contrast and detail expression of the images, thereby enhancing the recognizability of fault features. …”
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Neural Network for Underwater Fish Image Segmentation Using an Enhanced Feature Pyramid Convolutional Architecture by Guang Yang, Junyi Yang, Wenyao Fan, Donghe Yang

“…The model was validated using the Fish4Knowledge dataset, and the experimental results demonstrate that the model achieves a Mean Intersection over Union (MIoU) of 95.1%, with improvements of 1.3%, 1.5%, and 1.7% in the MIoU, Mean Pixel Accuracy (PA), and F1 score, respectively, compared to traditional segmentation methods. …”
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An AIoT-Based Automated Farming Irrigation System for Farmers in Limpopo Province by Relebogile Langa, Michael Nthabiseng Moeti, Thabiso Maubane

“…A machine learning precipitation prediction algorithm optimizes water usage. The paper also describes a system with multiple sensors that detect soil parameters, and automatically irrigate land based on soil moisture by switching the motor on/off. …”
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Artificial neural networks in predicting impaired bone metabolism in diabetes mellitus by S. S. Safarova

“…Further, the obtained data were processed using the MATLAB software to develop an ANN with a training (80%) and test (20%) set. The ANN model was trained by optimizing the relationship between a set of input data (a number of clinical and laboratory parameters: gender, age, body mass index, duration of diabetes mellitus, etc.) and a set of corresponding output data (variables reflecting the state of bone metabolism: bone mineral density, markers of bone remodeling).Results. …”
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Performance of Hybrid Transmission of a D2D Communication With Energy Harvesting and Ambient Backscattering by Saranya Karattupalayam Chidambaram, Yogesh Kumar Choukiker, Abhijit Bhowmick

“…In order to improve spectrum efficiency and green energy utilization, this paper investigates a green paradigm for a relay-assisted device-to-device (D2D) communication with energy harvesting (EH) and ambient backscattering (ABSC). …”
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Predictive framework of vegetation resistance in channel flow by Fengcong Jia, Weijie Wang, Yu Han, Jiayu Du, Yue Zhang, Zihan Liu, Hairong Gao

“…This study introduces a machine learning-based framework for predicting vegetation flow resistance, incorporating nine ML methods, including SVM, XGBoost, and BP. To improve predictive performance, optimization algorithms such as PSO, WSO, and RIME were applied. …”
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Enhancing BVR Air Combat Agent Development With Attention-Driven Reinforcement Learning by Andre R. Kuroswiski, Annie S. Wu, Angelo Passaro

“…We propose a novel approach that introduces a task-based layer, leveraging domain expertise to optimize decision-making and training efficiency. By integrating multi-head attention mechanisms into the policy model and employing an improved DQN algorithm, agents dynamically select context-aware tasks, enabling the learning of efficient emergent behaviors for variable engagement conditions. …”
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Performance and emission analysis of CI engine fueled with Dunaliella salina biodiesel and TiO₂ nanoparticle additives: Experimental and ANN-based Predictive Approach by V Hariram, S Balamurugan, R Mohan, R Karthick, Nandagopal Kaliappan, K Barathiraja, J Godwin John, K Kamakshi Priya

“…An Artificial Neural Network (ANN) model was developed using the Levenberg-Marquardt algorithm, incorporating 27 datasets generated through a Response Surface Methodology (RSM)-based d-optimal design to predict engine performance and emission characteristics. …”
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Building Thermal Comfort Research Based on Energy-Saving Concept by Feiran Xue, Jingyuan Zhao

“…First of all, this article introduces the concept and application mode of energy-saving concepts in buildings and the concept of thermal comfort and the SET index of standard effective temperature, including the two-node model and the algorithm involved in the Fanger heat balance equation. …”
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