METHOD OF IMAGE PROCESSING IN THE PROBLEM OF DETECTING MOVING OBJECTS IN OPTICAL-ELECTRONIC SURVEILLANCE SYSTEMS OF THERMAL IMAGING TYPE by E. I. Mikhnionok

“…Moving objects on the observed scene are subject to investigation, so it is advisable to use algorithms based on background subtraction methods to solve the detection problem. …”
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Counting workflow satisfiability with exclusion constraints based on backtracking tree-decomposition by Zhinian ZHAI, Weixiang WANG, Yahui LU, Mingwei WU, Zhijun ZHENG, Fahong YU

“…Experiments show that, the proposed optimized algorithm declined in running time, and has well synthetical performance for workflows with low-density constraints compared to the existing #WS（≠）algorithms.…”
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The association between cystatin C and hypertension risk in diabetes patients: A multi-cohort cross-sectional study by Ye Kuang, Jia Wang, Yang Wang, Chuanmei Peng, Pei He, Yong Ji, Jinrong Tian, Yong Yuan, Lei Feng

“…Analyzing 5210 DM patients from three cohorts, this study identified serum cystatin C (CysC) as an independent risk factor for DM + HTN through univariate and multivariate logistic regression. A risk prediction model incorporating CysC concentration was developed and adjusted for age, sex, race, education, body mass index, smoking status, and drinking status. …”
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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…These performance gains are driven by real-time analytics, predictive modelling, and adaptive resource modulation. …”
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Optimizing flood resilience in China’s mountainous areas: Design flood estimation using advanced machine learning techniques by Xuemei Wang, Ronghua Liu, Chaoxing Sun, Xiaoyan Zhai, Liuqian Ding, Xiao Liu, Xiaolei Zhang

“…Notably, catchments with areas > 100 km² demonstrated higher estimation accuracy, with an average 60 % reduction in MQE and a 30 % increase in QR compared to catchments of all sizes. …”
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The Value of MRI and Radiomics for the Diagnostic Evaluation of Thyroid-Associated Ophthalmopathy by Weiyi Zhou, Yan Song, Jufeng Shi, Tuo Li

“…The early diagnosis and prediction of these refractory and relapsed patients is essential. …”
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Outdoor Clothing Design for Traffic Safety Based on Big Data and Artificial Intelligence by Ya Zhou, Yun Shi

“…The first experiment is to test the accuracy of various machine learning algorithms for clothing size measurement. The results obtained are as follows: the predicted value of the DBN neural network is the closest to the actual value, the average prediction accuracy of DBN for the cuff size is 90%, and the average prediction accuracy for the neck circumference is 91.5%. …”
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Modelling Tyre-Road Noise with Data Mining Techniques by Elisabete Fraga FREITAS, Joaquim TINOCO, Francisco SOARES, Jocilene COSTA, Paulo CORTEZ, Paulo PEREIRA

“…The data modelling took into account three learning algorithms and three metrics to define the best predictive model. …”
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Design of the Urban Lighting Control System Based on Optical Multisensor Technology and the GM Model by Weili Wu, Xiang Tang

“…The results of the evaluations show that the fresh method is successful in dimming, prediction, and control. This conclusively demonstrates the efficacy of the paper’s proposed design solution, which integrates optical multisensor technology with sophisticated control algorithms and data analysis to improve the quality of life in urban areas by boosting the efficiency and sustainability of the urban lighting system.…”
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Detection of the Pin Defects of Power Transmission Lines Based on Improved TPH-MobileNetv3 by Mengxuan Li, Jingshan Han, Zhi Yang, Bin Zhao, Peng Liu

“…Moreover, compared with the mainstream algorithms with the same detection accuracy, this algorithm not only reduces the model size and significantly enhances detection efficiency but also satisfies the requirement of edge image processing of power inspection.…”
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Application of Particle Filter to On-Board Life Estimation of LED Lights by Fazludeen Ruknudeen, Sundararajan Asokan

“…Life prediction methods based on reliability analysis and filtering algorithms proposed in the past were predominantly based on accelerated life tests and cannot be readily implemented for on-board diagnosis. …”
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Modeling of settlement of shallow-founded rocking structures using explainable physics-guided machine learning by Sivapalan Gajan, Christopher Kantor

“…SHAP analysis reveals that the PGML model predictions and their dependency on input features are consistent with the existing domain knowledge, and that the inclusion of physics in PGML models help improve the prediction accuracy, especially in cases where other input features fail to capture the combined complex interaction among the variables involved.…”
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Ai-powered digital twin in the industrial IoT by Željko Bolbotinović, Saša D. Milić, Žarko Janda, Dragan Vukmirović

“…Special attention is devoted to developing a novel multivariate-time-series prediction method. This method should enable parameter prediction which cannot be directly measured. …”
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A privacy preserving machine learning framework for medical image analysis using quantized fully connected neural networks with TFHE based inference by Sadhana Selvakumar, B. Senthilkumar

“…Abstract Medical image analysis using deep learning algorithms has become a basis of modern healthcare, enabling early detection, diagnosis, treatment planning, and disease monitoring. …”
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Advanced Supply Chain Management Using Adaptive Serial Cascaded Autoencoder with LSTM and Multi-Layered Perceptron Framework by Aniruddha Deka, Parag Jyoti Das, Manob Jyoti Saikia

“…The SGSO-ASCALSMLP model is highly efficient in predicting financial risks, outperforming conventional prediction techniques and heuristic algorithms, making it a promising approach for enhancing financial risk management in supply chain networks.…”
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Demographic forecast modelling using SSA-XGBoost for smart population management based on multi-sources data. by Jin Wang, Shihan Ma, Qing Lv, Qiang Li

“…Population prediction could provide effective data support for social and economic planning and decision-making, especially for the sub-national population forecasting accurately. …”
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A Data Decomposition and End-to-End Optimization-Based Monthly Carbon Emission Intensity of Electricity Forecasting Method by Yue Yan, Haoran Feng, Jinwei Song, Shixu Zhang, Shize Zhang, Qi He

“…Case studies conducted using actual data from Guangdong Province, China, demonstrate that the proposed method can effectively enhance monthly data, thereby improving prediction accuracy.…”
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Entry point of machine learning in axial spondyloarthritis by Tiantian Sun, Qing Yu, Yuening Chen, Hongxiao Liu, Xinning Qu

“…This enables the diagnosis, stratification, therapeutic efficacy prediction and prognostic evaluation of axSpA, positioning it as an emerging research topic. …”
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Harnessing Digital Twin Technology for Detailed Simulation and Analysis of Climate Impact on Agricultural Systems by Hassan Muntather Muhsin, Ramadan Ghazi Mohamad, Karthikeyan R.

“…The model incorporates real time data collection and well developed, yet still new, algorithms like random forest to enable real time analysis, as well as realistic prediction using system simulation models to yield highly useful and actionable insights. …”
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Intelligent policy framework: Natural resource conservation, knowledge and big data analytics by Nina Xiao, Xianhe Qu

“…This approach integrates prior information and observational data to ensure the continuity and accuracy of predictions. The weighted SVM algorithm based on grey relational analysis improves the accuracy of the predictive model by identifying key factors within multi-dimensional data and assigning appropriate weights to different features to address the challenges posed by incomplete or noisy data. …”
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