Coordinated Jamming and Poisoning Attack Detection and Mitigation in Wireless Federated Learning Networks by Sofia Barkatsa, Maria Diamanti, Panagiotis Charatsaris, Stefanos Voikos, Eirini Eleni Tsiropoulou, Symeon Papavassiliou

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Advancements in Onboard Processing of Synthetic Aperture Radar (SAR) Data: Enhancing Efficiency and Real-Time Capabilities by Laura Parra Garcia, Gianluca Furano, Max Ghiglione, Valentina Zancan, Ernesto Imbembo, Christos Ilioudis, Carmine Clemente, Paolo Trucco

“…This article discusses various onboard processing techniques employed in SAR systems and explores their challenges, like computational constraints, architectural impacts, power consumption, and algorithm optimization. Furthermore, it examines the potential future developments in onboard processing, such as the integration of artificial intelligence and machine learning techniques to enhance data analysis and decision-making capabilities. …”
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Resource Control in IRS Assisted Multi-Access Edge Computing for Sustainable 6G IIoT Networks by Ashu Taneja, Shalli Rani, Wadii Boulila

“…Additionally, we propose a resource control algorithm that assigns cell-edge user clusters to specific IRSs based on optimal IRS phase shift and channel correlation criteria. …”
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ALCS-PP: Adaptive Latency Control Scheme for Packet Pacing in Self-Clocked Congestion Control by Haider Dhia Zubaydi, Ahmed Samir Jagmagji, Sandor Molnar

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THEORETICAL AND METHODOLOGICAL ASPECTS OF USING INFORMATION ANDCOGNITIVE TECHNOLOGIES IN THE TRAINING OF TRANSPORT SPECIALISTS by Lavrentieva Olena, Krupskyi Oleksandr

“…Additionally, the use of multimedia technologies, scribing, virtual and augmented reality, project technologies based on networking, gamification, interactive technologies, primarily group work technologies, open, distance, and blended learning technologies, and also the Internet of Things, Blockchain, Big Data, expert systems, SMART technologies, and artificial intelligence significantly enhances the quality of training students in proficiency transport area. …”
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Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…Lastly, the feature importance plot shows that QoS is the collective effect of service performance and not a function QoS metrics only that determines the degree of satisfaction of a user of the service. This Artificial Intelligence (AI) powered system promotes a more transparent and efficient MBB experience for all stakeholders in Nigeria's fast evolving digital landscape.…”
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The value of multi-phase CT based intratumor and peritumoral radiomics models for evaluating capsular characteristics of parotid pleomorphic adenoma by Qian Shen, Cong Xiang, Yongliang Han, Yongmei Li, Kui Huang

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An Enhanced and Lightweight YOLOv8-Based Model for Accurate Rice Pest Detection by Guisuo Liu, Juxing Di, Qing Wang, Yan Zhao, Yang Yang

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AI and Primary Care: Scoping Review by Gellert Katonai, Nora Arvai, Bertalan Mesko

“…Inclusion criteria were empirical, peer-reviewed studies published in English between January 2010 and April 2024, involving direct stakeholder interaction (general practitioners, nurses, or patients) in real-world PHC settings, evaluating AI applications (eg, diagnostics, workflow optimization, and documentation). Exclusions included algorithm-only validations, pediatric populations, secondary or tertiary care contexts not explicitly addressing PHC workflows, nonempirical research (eg, editorials or protocols), and non-English studies. …”
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RST-YOLOv8: An Improved Chip Surface Defect Detection Model Based on YOLOv8 by Wenjie Tang, Yangjun Deng, Xu Luo

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Line-Structured Light-Based Three-Dimensional Reconstruction Measurement System with an Improved Scanning-Direction Calibration Method by Jia Chen, Shantao Ping, Xiaowei Liang, Xulong Ma, Shiyan Pang, Ying He

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Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images:... by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue, Zeyu Zhang

“…By designing a texture-aware data prior algorithm, a high-quality training dataset with geological rationality is generated. …”
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Evaluating the value of machine learning models for predicting hematoma expansion in acute spontaneous intracerebral hemorrhage based on CT imaging features of hematomas and surrou... by Tianyu Yang, Tianyu Yang, Zhen Zhao, Yan Gu, Shengkai Yang, Yonggang Zhang, Lei Li, Ting Wang, Zhongchang Miao

“…ObjectiveThis study evaluates the utility of artificial intelligence (AI) for automated segmentation of intracranial hematomas and surrounding oedema in non-contrast computed tomography (CT) images. …”
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Morphological Estimation of Primary Branch Inclination Angles in Jujube Trees Based on Improved PointNet++ by Linyuan Shang, Fenfen Yan, Tianxin Teng, Junzhang Pan, Lei Zhou, Chao Xia, Chenlin Li, Mingdeng Shi, Chunjing Si, Rong Niu

“…The segmentation of jujube tree branches and the estimation of primary branch inclination angles (IAs) are crucial for achieving intelligent pruning. This study presents a primary branch IA estimation algorithm for jujube trees based on an improved PointNet++ network. …”
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Deep reinforcement learning agents for dynamic spectrum access in television whitespace cognitive radio networks by Udeme C. Ukpong, Olabode Idowu-Bismark, Emmanuel Adetiba, Jules R. Kala, Emmanuel Owolabi, Oluwadamilola Oshin, Abdultaofeek Abayomi, Oluwatobi E. Dare

“…Reinforcement Learning (RL) in CRs helps predict spectral changes and identify optimal transmission frequencies. This work presents the development of Deep RL (DRL) models for enhanced DSA in TV Whitespace (TVWS) cognitive radio networks using Deep Q-Networks (DQN) and Quantile-Regression (QR-DQN) algorithms. …”
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Soft sensor modeling method for Pichia pastoris fermentation process based on substructure domain transfer learning by Bo Wang, Jun Wei, Le Zhang, Hui Jiang, Cheng Jin, Shaowen Huang

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Evaluation of a Machine Learning Model Based on Laboratory Parameters for the Prediction of Influenza A and B in Chongqing, China: Multicenter Model Development and Validation Stud... by Weiwei Hu, Yulong Liu, Jian Dong, Xuelian Peng, Chunyan Yang, Honglin Wang, Yong Chen, Shan Shi, Jin Li

“…The CatBoost (CATB) algorithm was optimized via 5-fold cross-validation and random grid search using 24 routine blood parameters. …”
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Characterizing Optimum N Rate in Waterlogged Maize (<i>Zea mays</i> L.) with Unmanned Aerial Vehicle (UAV) Remote Sensing by Bhawana Acharya, Syam Dodla, Brenda Tubana, Thanos Gentimis, Fagner Rontani, Rejina Adhikari, Dulis Duron, Giulia Bortolon, Tri Setiyono

“…The experiment was performed using a split plot design with four replications, with soil moisture conditions as main plots and different N rates as sub-plots. The artificial intelligence SciPy (version 1.5.2) optimization algorithm and spherical function were used to estimate the economically optimum N rate under the different treatments. …”
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Research and implementation of text classification method for customer service orders based on multi-model fusion by Liang ZHANG, Xiaoju DAI, Rong ZHENG, Tongze He

“…Due to the large amount of order categories and their hierarchical associations, traditional manual order classification method of customer service in telecom call center has the problems of long archiving time, low efficiency and unsustainable accuracy.To solve this problem, a novel text classification algorithm based on multi-model fusion was proposed, which intelligently classify orders with multiple models based on data characteristics and their hierarchical associations, the effectiveness of this method was verified.The current manual operation process was optimized and operation efficiency was enhanced, which support the intelligent transformation and upgradation of existing customer service system.…”
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Energy-Efficient Sleep Mode Schemes for Cell-Less RAN in 5G and Beyond 5G Networks by Farinaz Kooshki, Ana Garcia Armada, Md. Munjure Mowla, Adam Flizikowski, Slawomir Pietrzyk

“…., certain phase and conditional phase) through the intelligent interference management for temporarily switching access points (APs) to sleep, optimizing the network energy efficiency (EE) in highly loaded scenarios, as well as in scenarios with lower load. …”
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