Reinforcement Learning-Based Resource Allocation Scheme of NR-V2X Sidelink for Joint Communication and Sensing by Zihan Li, Ping Wang, Yamin Shen, Song Li

“…Joint communication and sensing (JCS) is becoming an important trend in 6G, owing to its efficient utilization of spectrums and hardware resources. Utilizing echoes of the same signal can achieve the object location sensing function, in addition to the V2X communication function. …”
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LE-YOLO: A Lightweight and Enhanced Algorithm for Detecting Surface Defects on Particleboard by Chao He, Yongkang Kang, Anning Ding, Wei Jia, Huaqiong Duo

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RpiBeh offers a versatile open source solution for rodent behavior tracking and closed loop interventions by Yiqi Sun, Jie Zhang, Qianyun Wang, Jianguang Ni

“…Existing commercial systems are costly and inflexible for customization, while current open-source tools are often lack of real-time functionality and suffer from steep learning curve. …”
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Assessment of the Integrated Communicable Disease Surveillance and Response System in Thamar Governorate, Yemen by Basem F. Abdel-Aziz, Saddam A.H. Al-Nahari, Ali A. Al-Waleedi, Shymaa M. Elshoura

“…The questionnaire included two sections: assessment of core activities of the IDSR system (structure, case confirmation, data reporting, data analysis, outbreak investigation, epidemic preparedness, epidemic responses, feedback) and assessment of support functions of the IDSR system (supervision, training, coordination, logistics and resources). …”

YOLO-PEL: The Efficient and Lightweight Vehicle Detection Method Based on YOLO Algorithm by Zhi Wang, Kaiyu Zhang, Fei Wu, Hongxiang Lv

“…YOLOv8-PEL shows outstanding performance in detection accuracy, computational efficiency, and generalization capability, making it suitable for real-time and resource-constrained applications. …”
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A Self-Adaptive Particle Swarm Optimization Based Multiple Source Localization Algorithm in Binary Sensor Networks by Long Cheng, Yan Wang, Shuai Li

“…Then the maximum likelihood estimator is employed to establish the objective function which is used to estimate the location of sources. …”
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Fast detection method for radionuclides based on Sequential Bayesian approach by WAN Linjian, ZHANG Xuan, ZHANG Chunlei, HUANG Jianwei, LIU Jiacheng, ZHANG Xiaole, LI Dehong, YANG Zhijun

“…Finally, experimental verifications were conducted on the feasibility, detection performance, and universality of the method by placing a set of standard point sources at different distances from the front of a LaBr3(Ce) detection system in both low and natural radiation background environments. …”
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Joint Multifractal Analysis and Source Testing of River Level Records Based on Multifractal Detrended Cross-Correlation Analysis by Liang Wu, Manling Wang, Tongzhou Zhao

“…It is important for the detection of change in multifractality in space. Besides, the cross-correlations in two analyzed series make the analysis of sources of joint multifractality difficult. …”
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Distribution and functional significance of KLF15 in mouse cerebellum by Dan Li, Shuijing Cao, Yanrong Chen, Yueyan Liu, Kugeng Huo, Zhuangqi Shi, Shuxin Han, Liecheng Wang

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Research on intrusion detection model based on improved MLP algorithm by Qihao Zhao, Fuwei Wang, Weimin Wang, Tianxin Zhang, Haodong Wu, Weijun Ning

“…These patterns can be effectively captured through MLP’s multiple nonlinear transformations, such as ReLU and Sigmoid activation functions, which are especially beneficial for intrusion detection. …”
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Code vulnerability detection method based on graph neural network by Hao CHEN, Ping YI

“…The schemes of using neural networks for vulnerability detection are mostly based on traditional natural language processing ideas, processing the code as array samples and ignoring the structural features in the code, which may omit possible vulnerabilities.A code vulnerability detection method based on graph neural network was proposed, which realized function-level code vulnerability detection through the control flow graph feature of the intermediate language.Firstly, the source code was compiled into an intermediate representation, and then the control flow graph containing structural information was extracted.At the same time, the word vector embedding algorithm was used to initialize the vector of basic block to extract the code semantic information.Then both of above were spliced to generate the graph structure sample data.The multilayer graph neural network model was trained and tested on graph structure data features.The open source vulnerability sample data set was used to generate test data to evaluate the method proposed.The results show that the method effectively improves the vulnerability detection ability.…”
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Transformer-based ECG classification for early detection of cardiac arrhythmias by Sunnia Ikram, Amna Ikram, Harvinder Singh, Malik Daler Ali Awan, Sajid Naveed, Isabel De la Torre Díez, Henry Fabian Gongora, Thania Candelaria Chio Montero

“…Electrocardiogram (ECG) classification plays a critical role in early detection and trocardiogram (ECG) classification plays a critical role in early detection and monitoring cardiovascular diseases. …”
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Performance Analysis of Diabetes Detection Using Machine Learning Classifiers by Hung Huynh, Liu Hui, Ngoc Han Nguyen, Ruixuan Qiao

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Algorithms for Automatic Detection and Location of Infrasound Events in the PSDL System by Asming Vladimir Ernestovich, Fedorov Andrey Viktorovich

“…An algorithm for detecting infrasound signals by calculating the cross-correlation function between records of individual sensors in a array is described. …”
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Toward global rooftop PV detection with Deep Active Learning by Matthias Zech, Hendrik-Pieter Tetens, Joseph Ranalli

“…It is crucial to know the location of rooftop PV systems to monitor the regional progress toward sustainable societies and to ensure the integration of decentralized energy resources into the electricity grid. However, locations of PV are often unknown, which is why a large number of studies have proposed variants of Deep Learning to detect PV panels in remote sensing data using supervised Deep Learning. …”
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DWS-YOLO: A Lightweight Detector for Blood Cell Detection by Yihai Mao, Hongyi Zhang, Wanqing Wu, Xingen Gao, Zhibin Lin, Juqiang Lin

“…Improved attention, loss function, and suppression enhance detection accuracy, while lightweight C3 module reduces computation time. …”
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Detection, Parameter Estimation and Direction Finding of Periodic Pulse Signals by V. B. Manelis, I. S. Faustov, V. A. Kozmin

“…Simple-to-implement algorithms for detecting periodic pulse signals, evaluating their parameters, and direction finding of the source have been developed. …”
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Radar Detection Simulation by Digital Twins of Target and Antenna System by A. S. Grigoriev, A. A. Kazantsev, A. M. Terentyev, B. S. Stavtsev

“…The signal-to-noise dynamic dependence of the given radar system, space object, and observation scenario, presented by their digital models, was calculated. The function of detection probability density was calculated, which demonstrated an insufficient detection capacity of a radar system in the case of observation of such type of objects.Conclusion. …”
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A Lightweight Citrus Object Detection Method in Complex Environments by Qiurong Lv, Fuchun Sun, Yuechao Bian, Haorong Wu, Xiaoxiao Li, Xin Li, Jie Zhou

“…Aiming at the limitations of current citrus detection methods in complex orchard environments, especially the problems of poor model adaptability and high computational complexity under different lighting, multiple occlusions, and dense fruit conditions, this study proposes an improved citrus detection model, YOLO-PBGM, based on You Only Look Once v7 (YOLOv7). …”
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Improved CSW-YOLO Model for Bitter Melon Phenotype Detection by Haobin Xu, Xianhua Zhang, Weilin Shen, Zhiqiang Lin, Shuang Liu, Qi Jia, Honglong Li, Jingyuan Zheng, Fenglin Zhong

“…The diversity of bitter melon shapes has a direct impact on its market acceptance and consumer preferences, making precise identification of bitter melon germplasm resources crucial for breeding work. To address the limitations of time-consuming and less accurate traditional manual identification methods, there is a need to enhance the automation and intelligence of bitter melon phenotype detection. …”
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