H2FPEF and HFA‐PEFF scores for heart failure risk stratification in hypertrophic cardiomyopathy patients by Yi‐Peng Gao, Hong‐Yun Liu, Xiao‐Jun Bi, Jie Sun, Ying Zhu, Wei Zhou, Ya‐Ting Fan, Xue‐Qing Cheng, Pei‐Na Huang, Ya‐Ni Liu, You‐Bin Deng

“…Future studies should develop and validate a new algorithm integrating both scores.…”
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CoMSeC: A Comparative Analysis of Various Service Classification Techniques by Malabika Das, Ansh Sarkar, Sujata Swain

“…The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has significantly impacted Web Service Classification, a critical task for service discovery, composition, and selection in various applications. …”
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An Efficient Universal Generating Function-Based Analyzing Approach for Multistate System with Imperfect Coverage Failure by Zheng Li, Jinlei Qin

“…During the computation of the system’s UGF, an algorithm based on matrix (ABM) is developed to reduce the computational complexity. …”
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Bearing fault diagnosis for high-speed train based on improved VMD and APSO-SVM by ZHANG Qingsong, ZHANG Bing, QIN Yi

“…Therefore, APSO algorithm was used to optimize the core parameters of the SVM, which further improved the recognition accuracy of cage fault and realized the effective identification for the fault bearings of high-speed train.…”
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Object detection and tracking in video sequences: formalization, metrics and results by R. P. Bohush, S. V. Ablameyko

“…Based on the considered generalization, an algorithm for tracking people has been developed that uses the tracking through detection method and convolutional neural networks to detect people and form features. …”
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基于Shannon熵的LCD-SVM方法在齿轮故障分类中的研究 by 李鹏宇, 邵忍平, 汪亚运

“…Local feature scale decomposition（Local characteristic scale decomposition,LCD）is a new adaptive time-frequency analysis method,which can adaptively decompose a complex signal into a number of ISC（Intrinsic scale component,ISC）components.SVM（support vector machine,SVM）is a kind of intelligent classification methods of machine learning,Shannon entropy is a nonlinear statistical learning methods.The LCD and SVM are introduced to the fault classification of mechanical transmission system.The Hilbert demodulation algorithm is used to strike the envelope signal of ISC components,through which the Shannon entropy is structured.After an in-depth analysis on the basis,it is combined with SVM in good relationship.The result is input vectors of SVM classifier,the trained SVM is used to determine the fault location,the type or degree of the test sample.Through the experimental analysis and verification,using this combining method,the recognition rate of four operating states which contains the normal state,the root crack of tooth,the wear of tooth surface,the composite fault is up to 97.5%.…”
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Prospects of phytopreparations based on Calendula officinalis in complex treatment of chemical burn of the esophagus by M. L. Voskresenskaya, A. N. Plekhanov, B. D. Dorzhiev, S. V. Tsyrempilov

“…The lack of standardized approach in treatment of local changes in chemical burns of the esophagus, severe and unsatisfactory results of using medication algorithms inspire a search for alternative methods of treatment and drug development. …”
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Survey on Collaborative Task Assignment for Heterogeneous UAVs Based on Artificial Intelligence Methods by Mengzhen Li, Na Li, Xiaoyu Shao, Jiahe Wang, Dachuan Xu

“…We provide a comprehensive review of artificial intelligence algorithms applied in UAV swarm mission planning, analyzing their strengths and weaknesses in multi-UAV cooperative environments. …”
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Improving the accuracy and metrological support of power meters in the frequency range from 37.5 to 178.6 GHz by A. V. Gusinsky, M. M. Kasperovich, V. A. Bogush

“…This paper presents the composition, diagram andgeneral principle of the device. …”
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Computational intelligence investigations on evaluation of salicylic acid solubility in various solvents at different temperatures by Adel Alhowyan, Wael A. Mahdi, Ahmad J. Obaidullah

“…Abstract This research shows the utilization of various tree-based machine learning algorithms with a specific focus on predicting Salicylic acid solubility values in 13 solvents. …”
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Multi-agent system of a network enterprise based on the Industrie 4.0 digital platform by V. А. Kazakov, Yu. F. Telnov

“…The main results of the article are the construction of the component composition diagram of the digital platform conceptual model, algorithms for generating a request to produce product components and its assessment by software agents of the digital platform in the form of UML sequence diagrams. …”
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Interval price prediction of livestock product based on fuzzy mathematics and improved LSTM. by Weimin Ma, Lingling Peng, Hu Chen, Haisheng Yan

“…An empirical study was conducted on the weekly price data of pork, beef, and mutton in China from 2009 to 2023, incorporating discussions on different embedding dimensions, prediction step, fuzzy granulation window sizes, decomposition techniques, and prediction algorithms. The results indicate that the proposed interval prediction model can not only achieve high accuracy in point prediction, but also better capture price change intervals.…”
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Successive Cohorts of Twitter Users Show Increasing Activity and Shrinking Content Horizons by Frederik Wolf, Sune Lehmann, Philipp Lorenz-Spreen

“… The global public sphere has changed dramatically over the past decades: A significant part of public discourse now takes place on algorithmically driven platforms. Despite its growing importance, there is scant large-scale academic research on the long-term evolution of user behaviour on these platforms. …”
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Retinal revelations: Seeing beyond the eye with artificial intelligence by John Davis Akkara

“…Additionally, AI can estimate age, sex, body composition, and other health parameters from eye images. …”
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Equilibrium Analysis of Electricity Market with Multi-Agents Considering Uncertainty by Zhonghai Sun, Runyi Pi, Junjie Yang, Chao Yang, Xin Chen

“…The proposed architecture comprises two interdependent layers: The upper-layer Stackelberg game coordinates strategic interactions among EVA, LA, and CESSO to mitigate bidding uncertainties through cooperative mechanisms. The lower-layer non-cooperative Nash game models competition patterns to determine market equilibria under multi-agent participation. …”
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A Survey of Localization in Wireless Sensor Network by Long Cheng, Chengdong Wu, Yunzhou Zhang, Hao Wu, Mengxin Li, Carsten Maple

“…In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. …”
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A comprehensive multi-agent deep reinforcement learning framework with adaptive interaction strategies for contention window optimization in IEEE 802.11 Wireless LANs by Yi-Hao Tu, Yi-Wei Ma

“…This study introduces the Multi-Agent, Multi-Parameter, Interaction-Driven Contention Window Optimization (M2I-CWO) algorithm, a novel Multi-Agent Deep Reinforcement Learning (MADRL) framework designed to optimize multiple CW parameters in IEEE 802.11 Wireless LANs. …”
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Joint Latency-Energy Minimization for Fog-Assisted Wireless IoT Networks by Farshad Shams, Vincenzo Lottici, Zhi Tian

“…Numerical results obtained using realistic models are presented to corroborate the effectiveness of the proposed algorithm.…”
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Secrecy-Oriented Transmitter Optimization for Visible Light Communication Systems by Hong Shen, Yuqin Deng, Wei Xu, Chunming Zhao

“…Despite the fact that the corresponding optimization problem has a nonconvex fractional form, we are able to determine its locally optimal solution via Charnes–Cooper transformation and minorization-maximization algorithm. …”
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A Uniform Clustering Mechanism for Wireless Sensor Networks by Rabia Noor Enam, Rehan Qureshi, Syed Misbahuddin

“…For example, for a cooperative data aggregation, it necessitates variable or large sized packets while the aggregations, based on spatial correlation of sensor nodes, cannot be exploited easily. …”
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