Traffic and Obstacle-Aware UAV Positioning in Urban Environments Using Reinforcement Learning by Kamran Shafafi, Manuel Ricardo, Rui Campos

“…Unmanned Aerial Vehicles (UAVs) are suited as cost-effective and adaptable platforms for carrying Wi-Fi Access Points (APs) and cellular Base Stations (BSs). …”
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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

“…The dataset was preprocessed using the Standard Scaler to standardize it, ensuring each feature has a mean of zero and a standard deviation of one, followed by outlier detection with Cook’s distance. Hyperparameter optimization made using the Differential Evolution (DE) method improved the performance of models. …”
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Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction by Diqing Fan, Chenjiang Yu, Ling Sha, Haifeng Zhang, Xintian Liu

“…Laser-welded automotive brake joints are subjected to weld defect detection and classification, and image processing algorithms are optimized to improve the accuracy of detection and failure analysis by utilizing the high efficiency, low cost, flexibility, and automation advantages of machine vision technology. …”
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Comprehensive Analysis of Phenotypic Traits in Chinese Cabbage Using 3D Point Cloud Technology by Chongchong Yang, Lei Sun, Jun Zhang, Xiaofei Fan, Dongfang Zhang, Tianyi Ren, Minggeng Liu, Zhiming Zhang, Wei Ma

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Research on Unmanned Aerial Vehicle Path Planning for Carbon Emission Monitoring of Land-Side Heavy Vehicles in Ports by Xincong Wu, Zhanzhu Li, Xiaohua Cao

“…Lastly, this paper focuses on the initial path planning problem of drone monitoring and proposes an improved A* algorithm (IEHA). The algorithm improves the search method of child nodes by eliminating nodes that collide with obstacles, thereby reducing the threat of path collisions. …”
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Research on Dynamic Performance of Autonomous-rail Rapid Tram by ZHONG Hanwen, LI Xiaoguang, XIAO Lei, YANG Yong, ZHANG Chenlin, HUANG Ruipeng, YUAN Xiwen

“…Through detailed Simpack dynamic model, the simulation research was carried out to provide guidance for optimization and improvement of vehicle dynamic performance. …”
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Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model by WANG Ding1, PAN Miao2, WU Ying1

“…Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model,the maximum likelihood method（MLM） for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM,an improved alternative projection iteration algorithm,which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound（CRB） for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.…”
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Pig behavior recognition and disease warning based on compressed sensing and long-short term memory network by Ren Wang, Mingdong Zhao

“…By means of ellipse fitting based on the minimum cost function and target tracking based on the shortest distance matching, we design four motion information detection algorithms including motion displacement, motion velocity, motion acceleration and motion angular velocity. …”
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Rapid Detection of Key Phenotypic Parameters in Wheat Grains Using Linear Array Camera by Wenjing Zhu, Kaiwen Duan, Xiao Li, Kai Yu, Changfeng Shao

“…The errors estimating the comprehensive grain length of five wheat varieties using the extraction algorithm developed in this study, the determination coefficient and root mean square error indices, were 0.986 and 0.0887, respectively, compared with manual measurements. …”
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Integrating artificial intelligence into thermodynamics: A new paradigm for sustainable future by Marwan Al-Raeei

“…In addition, we examine the application of AI-driven optimization techniques, such as genetic algorithms and reinforcement learning, which have proven essential for improving energy efficiency and reliability across various industries. …”
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Maglev Derived Systems: An Interoperable Freight Vehicle Application Focused on Minimal Modifications to the Rail Infrastructure and Vehicles by Jesus Felez, Miguel A. Vaquero-Serrano, William Z. Liu, Carlos Casanueva, Michael Schultz-Wildelau, Gerard Coquery, Pietro Proietti

“…Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. …”
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Maximum likelihood self-calibration for direction-dependent gain-phase errors with carry-on instrumental sensors:case of deterministic signal model by WANG Ding1, PAN Miao2, WU Ying1

“…Aim at the self-calibration of direction-dependent gain-phase errors in case of deterministic signal model,the maximum likelihood method（MLM） for calibrating the direction-dependent gain-phase errors with carry-on instrumental sensors was presented.In order to maximize the high-dimensional nonlinear cost function appearing in the MLM,an improved alternative projection iteration algorithm,which could optimize the azimuths and direction-dependent gain-phase errors was proposed.The closed-form expressions of the Cramér-Rao bound（CRB） for azimuths and gain-phase errors were derived.Simulation experiments show the effectiveness and advantage of the novel method.…”
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GRU-based multi-scenario gait authentication for smartphones by Qi JIANG, Ru FENG, Ruijie ZHANG, Jinhua WANG, Ting CHEN, Fushan WEI

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Nitrous oxide prediction through machine learning and field-based experimentation: A novel strategy for data-driven insights by Muhammad Hassan, Khabat Khosravi, Travis J. Esau, Gurjit S. Randhawa, Aitazaz A. Farooque, Seyyed Ebrahim Hashemi Garmdareh, Yulin Hu, Nauman Yaqoob, Asad T. Jappa

“…Feature selection and optimization of input scenarios were achieved using a combination of particle swarm optimization (PSO) and manual methods. …”
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Research on Behavior Recognition and Online Monitoring System for Liaoning Cashmere Goats Based on Deep Learning by Geng Chen, Zhiyu Yuan, Xinhui Luo, Jinxin Liang, Chunxin Wang

“…YOLOv8n demonstrated superior performance, converging within 50 epochs with an average accuracy of 95.31%, making it a baseline for further improvements. We improved YOLOv8n through dataset expansion, algorithm lightweighting, attention mechanism integration, and loss function optimization. …”
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A review on agrowaste based activated carbons for pollutant removal in wastewater systems by Karinate Valentine Okiy, Joseph Nwabanne Tagbo, Walter Peter Echeng

“…The deployment of mathematical and machine learning approaches (ANN and novel GMDH algorithms) in optimization of batch and continuous adsorption processes are also highlighted. …”
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Promoting mental health in the age of new digital tools: balancing challenges and opportunities of social media, chatbots, and wearables by Julien Coelho, Julien Coelho, Florian Pécune, Jean-Arthur Micoulaud-Franchi, Jean-Arthur Micoulaud-Franchi, Bernard Bioulac, Pierre Philip, Pierre Philip

“…Although stigma and discrimination hinder progress, these conditions are often preventable or manageable at minimal cost. The adoption of digital tools in mental health promotion, including telemedicine, online therapy, social media, and wearables, offers promising new avenues to address these issues. …”
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Multi-Level Spectral Attention Network for Hyperspectral BRDF Reconstruction from Multi-Angle Multi-Spectral Images by Liyao Song, Haiwei Li

“…For the multi-level Transformer spectral dimension enhancement algorithm, we added spectral response loss constraints to improve BRDF accuracy. …”
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The Air Transportation System as a Subsystem of Modern Communication Space: Analysis Based on Transfer Entropy Graphs by Sagit Valeev, Natalya Kondratyeva

“…New technologies in aviation improve the flight performance of airliners and reduce the costs of transporting passengers. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…This optimization ensures improved accuracy, faster convergence, and better generalization to unseen data. …”
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