UAV With the Ability to Control with Sign Language and Hand by Image Processing by Hediyeh Hojaji, Alireza Delisnav, Mohammad Hossein Ghafouri Moghaddam, Fariba Ghorbani, Shadi Shafaghi, Masoud Shafaghi

“…Data collection involved capturing various hand gestures under various environmental conditions to train and validate our recognition algorithms, including implementing YOLO V5 alongside Python libraries with OpenCV. …”
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Experimental 5G Network Performance Analysis in a Semi-Anechoic and Semi-Reverberation Chamber by Felix Delgado-Ferro, Alejandro Ramirez-Arroyo, Jorge Navarro-Ortiz, Juan F. Valenzuela-Valdes

“…This dataset has been analyzed using statistical algorithms such as Principal Component Analysis and SHapley Additive ExPlanations. …”
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Texas rural land market integration: A causal analysis using machine learning applications by Tian Su, Senarath Dharmasena, David Leatham, Charles Gilliland

“…Moreover, lenders may also benefit from the information to manage collateral and thus maintain the stability of their operation.…”
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Real-time Data Sharing Platform Technology for Rail Transit Management Systems by LIU Chao, LI Shen, SU Cheng, WANG Wei, HUANG Qing

“…［Objective］ With the development of the rail transit industry and advancements in sensing and positioning technologies, numerous low-cost data collection devices are now connected to the internet, which enables access to abundant operational data but also poses challenges in data management due to information overload. …”
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Leveraging Large Language Models for Integrated Satellite-Aerial-Terrestrial Networks: Recent Advances and Future Directions by Shumaila Javaid, Ruhul Amin Khalil, Nasir Saeed, Bin He, Mohamed-Slim Alouini

“…We outline the current architecture of ISATNs and highlight the significant role LLMs can play in optimizing data flow, signal processing, and network management to advance 5G/6G communication technologies through advanced predictive algorithms and real-time decision-making. A comprehensive analysis of ISATN components is conducted, assessing how LLMs can effectively address traditional data transmission and processing bottlenecks. …”
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Enhancing Operational Efficacy of Smart Parking Facilities through Intelligent License Plate Recognition by Nikta Shamsmohammadi, Sina Shaffiee Haghshenas, Giuseppe Guido, Vittorio Astarita

“…Similarly, the Super-Resolution Convolutional Neural Network (SRCNN) model, also utilizing a kernel regularizer, demonstrated a commendable accuracy of 0.85. …”
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Investigating Potential Anti-Bacterial Natural Products Based on Ayurvedic Formulae Using Supervised Network Analysis and Machine Learning Approaches by Pei Gao, Ahmad Kamal Nasution, Naoaki Ono, Shigehiko Kanaya, Md. Altaf-Ul-Amin

“…The initial approach utilizes a supervised network analysis, which involves the application of distance measurement algorithms to scrutinize the interconnectivity and relational patterns within the network derived from Ayurvedic formulae. …”
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Integrating Multimodal Deep Learning with Multipoint Statistics for 3D Crustal Modeling: A Case Study of the South China Sea by Hengguang Liu, Shaohong Xia, Chaoyan Fan, Changrong Zhang

“…The flexibility of our approach also suggests its applicability to other regions and geological attributes, paving the way for more comprehensive and data-driven investigations of Earth’s subsurface.…”
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Monitoring and modeling hydrologic conditions in Ukraine for hydropower generation by Matthew J. McCarthy, Jesus D. Gomez-Velez, David Hughes, Shannon Meade

“…New hydrological insights for the region: We ran new algorithms on 144 WorldView-2 and WorldView-3 satellite images to map rivers and extract width, one of which was validated against river gauge data located along the same river but in a neighboring country. …”
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A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles by Jie Chen, Ruochen Wang, Wei Liu, Dong Sun, Yu Jiang, Renkai Ding

“…Their stability control strategies must also account for terrain irregularities, real-time load shifts, and extreme slopes, validated through scaled-model tests and field trials. …”
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Cybersecurity and Major Cyber Threats of Smart Meters: A Systematic Mapping Review by Jones Márcio Nambundo, Otávio de Souza Martins Gomes, Adler Diniz de Souza, Raphael Carlos Santos Machado

“…These gaps include design requirements, software and firmware updates, physical security, the use of big data to detect vulnerabilities, user data privacy, and inconsistencies in machine learning algorithms. Future research should focus on these aspects to improve the stability and reliability of smart meters.…”
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Explainable AI-driven intelligent system for precision forecasting in cardiovascular disease by Anas Bilal, Abdulkareem Alzahrani, Khalid Almohammadi, Muhammad Saleem, Muhammad Sajid Farooq, Raheem Sarwar

“…IntroductionCardiovascular diseases (CVDs) are complex and affect a large part of the world’s population; early accurate and timely prediction is also complicated. Typically, predicting CVDs involves using statistical models and other forms of standard machine learning. …”
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RNA m7G methylation regulators and targets significantly contribute to chronic obstructive pulmonary disease by Chenyu Zhu, Luyi Tan, Xinyu Zhang, Wenli Cheng, Min Li, Yibo Chen, Wenjuan Zhang

“…More importantly, CAT was found to be a meaningful key target gene in METTL1-CAT axis for m7G methylation in COPD. We also used the cell premature senescence model for the preliminary validation of the above biosignature analysis results. …”
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Prediction of mortality risk in patients with severe community-acquired pneumonia in the intensive care unit using machine learning by Jingjing Pan, Tao Guo, Haobo Kong, Wei Bu, Min Shao, Zhi Geng

“…Five machine learning algorithms were used to build predictive models. Models were evaluated through nested cross-validation to select the best one. …”
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Diagnosis of Pre-Tightening Force Loosening for Top Cover Bolts in Generator Sets by Chongshi Li, Songlin Xie, Xiong Shu, Yuan Wan, Pingheng Pan, Fan Mo, Weiyu Wang

“…The proposed approach utilizes stress feature analysis and intelligent algorithms to enhance the diagnostic process. The study involves a detailed analysis of the stress transfer mechanism during bolt loosening, aiming to elucidate the relationship between changes in pre-tightening force and stress distribution in the surrounding bolts. …”
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Transforming Sleep Monitoring: Review of Wearable and Remote Devices Advancing Home Polysomnography and Their Role in Predicting Neurological Disorders by Diana Vitazkova, Helena Kosnacova, Daniela Turonova, Erik Foltan, Martin Jagelka, Martin Berki, Michal Micjan, Ondrej Kokavec, Filip Gerhat, Erik Vavrinsky

“…The paper highlights the integration of hardware innovations, targeted sleep parameters, and partially advanced algorithms, illustrating how these elements converge to provide reliable sleep health information. …”
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A Survey of Matrix Completion Methods for Recommendation Systems by Andy Ramlatchan, Mengyun Yang, Quan Liu, Min Li, Jianxin Wang, Yaohang Li

“…Several applications other than the traditional user-item association prediction are also discussed.…”
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AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness by Anantaya Timtong, Atthaphon Ariyarit, Wanwanut Boongsood, Prasert Aengchuan, Attasit Wiangkham

“…These established methods are not only expensive and time-consuming but also frequently limited by the availability of data. …”
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Precision Weed Management for Straw-Mulched Maize Field: Advanced Weed Detection and Targeted Spraying Based on Enhanced YOLO v5s by Xiuhong Wang, Qingjie Wang, Yichen Qiao, Xinyue Zhang, Caiyun Lu, Chao Wang

“…These results confirm the robustness of the model and the feasibility of the targeted spraying method. This approach also promotes the application of deep learning algorithms in precision weed management within directional spraying systems.…”
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RMVAD-YOLO: A Robust Multi-View Aircraft Detection Model for Imbalanced and Similar Classes by Keda Li, Xiangyue Zheng, Jingxin Bi, Gang Zhang, Yi Cui, Tao Lei

“…Aircraft detection technology plays a vital role in civilian applications, with significant attention being devoted to research on related algorithms in recent years. However, most existing research predominantly focuses on aircraft detection from a single top–down viewpoint, which constrains the applicability of detection technology across diverse scenarios. …”
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