Rapid deployment method of integrated localization and communication network for high dynamic emergency scenarios by XU Lianming, ZHU Wendi, WANG Li, LIU Zhenyu, ZHANG Yuhao

“…Additionally, to mitigate severe fading effects of NLoS links caused by obstacles such as mountains, a virtual attractive force modelling method for NLoS link avoidance was proposed, improving the service quality of the emergency network by eliminating severe fading links. …”
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Autonomous Driving of Trackless Transport Vehicles: A Case Study in Underground Mines by Yunjie Sun, Linxin Zhang, Junhong Liu, Yonghe Xu, Xiaoquan Li

“…The introduction of autonomous vehicles in underground mine trackless transportation systems can significantly reduce safety risks for personnel in production operations and improve transportation efficiency. Current autonomous mining vehicle technology is characterized by complex algorithms and high deployment costs, which limit its widespread application in underground mines. …”
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CNN-LSTM optimized with SWATS for accurate state-of-charge estimation in lithium-ion batteries considering internal resistance by Zhaowei Zhang, Chen Liu, Tianyu Li, Tian Wang, Yaoyao Cui, Pengcheng Zhao

“…To solve these problems, this paper describes a battery test bench for producing an effective lithium-ion battery dataset containing current, voltage, temperature, and more importantly, internal resistance measurements. To improve the estimated SOC performance, the internal resistance is considered in the construction of a data-driven model. …”
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Optimization of transportation efficiency through fuzzy logic and LINGO software by Zahoor Ahmad Ganie, Zahid Gulzar Khaki, Tanveer Ahmad Tarray, Gazala Salam, Eid Sadun Alotaibi

“…Intuitionistic fuzzy programming and randomized response techniques have been adapted in this proposed methodology to overcome data privacy, cost-effectiveness, and minimization of variation within strata problems. The model was confirmed to be able to lower standard errors, maintain data integrity, and improve transportation management in computational tests. …”
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Machine learning allows robust classification of lung neoplasm tissue using an electronic biopsy through minimally-invasive electrical impedance spectroscopy by Georgina Company-Se, Virginia Pajares, Albert Rafecas-Codern, Pere J. Riu, Javier Rosell-Ferrer, Ramon Bragós, Lexa Nescolarde

“…This study aims to use classification algorithms with minimally invasive electrical impedance spectroscopy to improve neoplastic lung tissue identification during biopsies. …”
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Numerical Investigation on Influential Factors for Quality of Smooth Blasting in Rock Tunnels by Baoping Zou, Zhipeng Xu, Jianxiu Wang, Zhanyou Luo, Lisheng Hu

“…Proposed 3-dimensional blasting modelling was based on LS-DYNA to simulate the occurrence of smooth blasting in rock masses, and the erosion algorithm was also employed to determine the fracturing of jointed rocks. …”
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Machine learning based adaptive traffic prediction and control using edge impulse platform by Manoj Tolani, G. E. Saathwik, Ayush Roy, L. A. Ameeth, Dhanush Bharadwaj Rao, Ambar Bajpai, Arun Balodi

“…The model is rigorously tested and validated to ensure its reliability and accuracy in real-world traffic scenarios.…”
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Time-Triggered Task Offloading Scheduling in TSN-Based Edge Computing Power Networks by Hongrui Nie, Yang Wu, Weifeng Zhu, Jinzuo Zhong, Hang Yang, Yu Zhou

“…Subsequently, we establish the correlation between tasks using Directed Acyclic Graph (DAG) and design a matching and load balancing-based task offloading algorithm (MLB-TOA). Moreover, we propose an efficient routing algorithm for task generation streams (TGS-RA) and an incremental task generation stream injection time planning algorithm (TGS-ITP) in time-sensitive networking. …”
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Planning Flexible Bus Service as an Alternative to Suspended Bicycle-Sharing Service: A Data-Driven Approach by Yujia Wang, Yuan Tian, Binyu Yang, Jian Wang, Xiaowei Hu, Shi An

“…Firstly, an FFBS trip path reconstruction algorithm consists of fine-grained road network modelling and trajectory matching is proposed. …”
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Features of the Development Strategy Customer Relationship Management by I. M. Gurova

“…The aim of this work is to identify specific features of development of strategy of customer relationship management through the systematization of theoretical and methodological framework and a detailed consideration of the algorithm of this process. Methods: the methodology of the study is based on the application of universal scientific methods of analysis and synthesis, analogy and modeling. …”
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Enhancing Laser-Induced Breakdown Spectroscopy Quantification Through Minimum Redundancy and Maximum Relevance-Based Feature Selection by Manping Wang, Yang Lu, Man Liu, Fuhui Cui, Rongke Gao, Feifei Wang, Xiaozhe Chen, Liandong Yu

“…Our results demonstrate that the mRMR method significantly reduces the number of selected features while improving model performance. This study validates the effectiveness of the mRMR algorithm for LIBS feature extraction and highlights the potential of feature selection techniques to enhance predictive accuracy. …”
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Comparison of Machine Learning Methods for Predicting Electrical Energy Consumption by Retno Wahyusari, Sunardi Sunardi, Abdul Fadlil

“…Data pre-processing, specifically min-max normalization, is crucial for improving the accuracy of distance-based algorithms like KNN. …”
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Machine Learning-Based Seismic Damage Assessment of a Bridge Portfolio in Cohesive Soil by Burak Ozturk, Ahmed Fouad Hussein, Mohamed Hesham El Naggar

“…Results show that CatBoost and LightGBM outperform other methods in accuracy and robustness, particularly under imbalanced data conditions. Oversampling improves classification for specific targets but introduces overfitting risks in others, while undersampling generally degrades model performance. …”
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Dental bur detection system based on asymmetric double convolution and adaptive feature fusion by HongLing Hou, Ao Yang, Xiangyao Li, Kangkai Zhu, Yandi Zhao, Zhiqiang Wu

“…Abstract This study aims to improve the detection of dental burs, which are often undetected due to their minuscule size, slender profile, and substantial manufacturing output. …”
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High-Performance Real-Time Human Activity Recognition Using Machine Learning by Pardhu Thottempudi, Biswaranjan Acharya, Fernando Moreira

“…This paper presents an innovative HAR system that leverages machine-learning algorithms deployed on the B-L475E-IOT01A Discovery Kit, a highly efficient microcontroller platform designed for low-power, real-time applications. …”
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Explainable quality assessment of effective aligned skeletal representations for martial arts movements by multi-machine learning decisions by Yiqun Pang, Kaiqi Zhang, Fengmei Li

“…Firstly, the key features are extracted by the feature alignment technique, which eliminates the influence of athletes’ movement speed, rhythm and duration on the scoring, thus reflecting the athletes’ skill level more realistically. Second, to further improve the objectivity and accuracy, an adaptive weighted multi-model decision-making strategy is proposed. …”
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Rethinking Technological Investment and Cost-Benefit: A Software Requirements Dependency Extraction Case Study by Gouri Ginde, Guenther Ruhe, Chad Saunders

“…As such, our results showed that, 1) chasing model accuracy improvisation through increased annotated data does not generate expected returns in traditional ML methods. 2) For complex ML algorithms, the need for larger annotated dataset investment cost is justified by the higher returns, however, the trade-offs between accuracy and ROI become evident.…”
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Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

“…This paper addresses the data sparsity issue to improve group recommendation performance, overcoming the limitations of overlooking individual user recommendation tasks and depending on single-view modeling. …”
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Machine learning for the prediction of mortality in patients with sepsis-associated acute kidney injury: a systematic review and meta-analysis by Xiangui Lv, Daiqiang Liu, Xinwei Chen, Lvlin Chen, Xiaohui Wang, Xiaomei Xu, Lin Chen, Chao Huang

“…Results A total of 8 studies were included, with a total of 53 predictive models and 17 machine learning algorithms used. Meta-analysis using a random effects model showed that the overall C index in the training set was 0.81 (95% CI: 0.78–0.84), sensitivity was 0.39 (0.32–0.47), and specificity was 0.92 (95% CI: 0.89–0.95). …”
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An Edge Container Migration Optimization Method for Multi-service Intelligent Resource Scheduling of Distribution Networks by Shuai LI, Di XU, Xiangyu WEN, Jiaxin ZHANG

“…The simulation results demonstrate that compared with traditional algorithms, the proposed method can validly improve the data processing delay performance for distribution network.…”
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