Research on Adaptive Identification Technology for Rolling Bearing Performance Degradation Based on Vibration–Temperature Fusion by Zhenghui Li, Lixia Ying, Liwei Zhan, Shi Zhuo, Hui Li, Xiaofeng Bai

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Technical note: Evolution of convective boundary layer height estimated by Ka-band continuous millimeter wave radar at Wuhan in central China by Z. Zhang, Z. Zhang, Z. Zhang, K. Huang, K. Huang, K. Huang, F. Yi, F. Yi, F. Yi, W. Cheng, F. Liu, F. Liu, F. Liu, J. Zhang, Y. Jia

“…Although these algorithms are based on different dynamic and thermodynamic effects, the diurnal evolution of the CBLH from MMCR is generally consistent with that from lidar, except for a few hours post-sunrise and pre-sunset due to the influence of the aerosol residual layer on the lidar RCS. …”
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Multi-parametric quantitative MRI reveals three different white matter subtypes. by Jack R Foucher, Olivier Mainberger, Julien Lamy, Mathieu D Santin, Alexandre Vignaud, Mathilde M Roser, Paulo L de Sousa

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Significance of EEG-electrode combinations while calculating filters with common spatial patterns by Wetzel, Dominik, Jacobs, Paul-Philipp, Winkler, Dirk, Grunert, Ronny

“…It is crucial to reduce the amount of features especially in cases where few data is available. Therefore, different approaches to reduce the amount of electrodes used for CSP calculation are tried in this research.Methods: Freely available EEG datasets are used for the evaluation. …”
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The Artificial Intelligence and the dispute for different ways in its predictive use in the criminal process by Rodrigo Régnier Chemim Guimarães

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A bi-subpopulation coevolutionary immune algorithm for multi-objective combinatorial optimization in multi-UAV task allocation by Xi Chen, Yu Wan, Jingtao Qi, Zipeng Zhao, Yirun Ruan, Jun Tang

“…Therefore, this paper constructs a Multi-objective Combinatorial Optimization in Multi-UAV Task Allocation Problem (MCOTAP) model, and proposes a Bi-subpopulation Coevolutionary Immune Algorithm (BCIA). The two coevolutionary mechanisms improve the lower limit of population diversity, and the evolutionary strategy pool integrating multiple strategies and the adaptive strategy selection mechanism enhance the local search ability in the late evolution. …”
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Evaluation and optimization of carbon emission for federal edge intelligence network by Peng ZHANG, Yong XIAO, Jiwei HU, Liang LIAO, Jianxin LYU, Zegang BAI

“…In recent years, the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks, the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI), based on edge computing and distributed federated machine learning, has been widely acknowledged as one of the key pathway for implementing network native intelligence.However, evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue, a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently, three carbon emission optimization schemes for FEI networks were presented, including dynamic energy trading (DET), dynamic task allocation (DTA), and dynamic energy trading and task allocation (DETA).Finally, by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets, FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.…”
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APPROACH OF PROCESSING, CLASSIFICATION AND DETECTION OF NEW CLASSES AND ANOMALIES IN HETEROGENIOUS AND DIFFERENT STREAMS OF DATA by R. A. Bagutdinov

“…The level of false positives in the developed algorithm is rather low and can be considered insignificant. …”
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An Adaptive Parameter Evolutionary Marine Predators Algorithm for Joint Resource Scheduling of Cooperative Jamming Networked Radar Systems by Dejiang Lu, Siyi Cheng, You Chen, Xi Zhang, Haoyang Li, Tianjian Yang

“…Considering the scene constraints, an Improved Adaptive Parameter Evolution Marine Predators Algorithm is designed as an optimizer and embedded in the proposed framework to jointly optimize the platform beam allocation and jamming mode selection. …”
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Evaluating the Performance of SVM, Isolation Forest, and DBSCAN for Anomaly Detection by Lu Haowen

“…This study evaluates the suitability of three algorithms—Support Vector Machine (SVM), Isolation Forest, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) by comparing their accuracy and time efficiency in detecting outliers in different types of datasets. …”
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A modified TOPSIS algorithm for the assessment of sports quality in higher education using circular pythagorean fuzzy information by Jiapeng Li, Yitong Zhang

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A Machine Learning Approach to Evaluate the Performance of Rural Bank by Jun Wei, Tao Ye, Zhe Zhang

“…This paper empirically uses data from rural banks in 30 provinces in China to classify the different characteristics of rural banks’ performance in order to better evaluate their performance.…”
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Evolutionary Artificial Intelligence Algorithm for Optimizing Step Phase Detection Based on Foot-Mounted Triaxial Accelerometer Data by P. A. Khmarskiy

“…The aim of this study was to develop and experimentally validate an algorithm for automatic selection of filter frequency characteristics and detection threshold in order to enhance the accuracy and reliability of gait phase detection. …”
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RESULTS OF INTRODUCTING THE PRINCIPLES OF INFECTION CONTROL INTO THE PRACTICE OF THE BELARUS REPUBLICAN TUBERCULOSIS SERVICE by G. L. Gurevich, A. P. Astrovko, E. M. Skryagina, D. A. Klimuk, O. M. Kalechits, A. E. Skryagin

“…The health protection in healthcare workers and patients in different healthcare organizations may be compared on the basis of qualitative and quantitative evaluation of the efficiency of tuberculosis IC measures. …”
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On modeling random data to evaluate the performance of statistical tests in cryptography by U. Y. Palukha, M. A. Prokharchyk, Yu. S. Kharin

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A Power Control Algorithm for V2V Communication Networks Based on Dynamic Multi-Objective Optimization by Mengyu Ma, Zihao Gu, Chao Wang, Zuxing Li, Jianyao Hu, Fuqiang Liu

“…We propose a prediction-based dynamic multi-objective optimization evolutionary algorithm (DMOEA) that facilitates the evolution of the solution population by predicting the centroid of the power allocation decision set in a new environment, so that transmission decisions can be made to adapt to the highly dynamic environment. …”
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Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm by Fatemeh Hataminia, Anahita Azinfar

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Prediction of Work-relatedness of Shoulder Musculoskeletal Disorders as by Using Machine Learning by Saemi Jung, Bogeum Kim, Yoon-Ji Kim, Eun-Soo Lee, Dongmug Kang, Youngki Kim

“…Background: This study aimed to develop prediction models for the work-relatedness of shoulder diseases through machine learning algorithms. Methods: The dataset comprised 7,270 cases of 8,302 individuals who applied for occupational diseases and received the final approval decision from the Korea Workers' Compensation and Welfare Service's Disease Evaluation Committee, which is related to shoulder musculoskeletal disorders between January 2020 and December 2021. …”
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Impact of a crop insurance mechanism on credit obtained by smallholders: evidence from “Proagro Mais” in Paraná by Carlos Oñate-Paredes, Vitor Augusto Ozaki

“…The methodology incorporates the propensity score matching (PSM) at the endline year, employing three distinct matching algorithms, and PSM at the baseline, coupled with the difference-in-differences method. …”
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Efficient Rollout Algorithms for Resource-Constrained Project Scheduling with a Flexible Project Structure and Uncertain Activity Durations by Chunlai Yu, Xiaoming Wang, Qingxin Chen

“…In addition, rollout algorithms perform more stably than other methods under different problem characteristics.…”
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