Privacy-Preserving Hierarchical Reinforcement Learning Framework for Task Offloading in Low-Altitude Vehicular Fog Computing by Zhiwei Wei, Jingxin Mao, Bing Li, Rongqing Zhang

“…At the local DRL level, we design an Attention-enhanced Federated Proximal Policy Optimization (AFedPPO) algorithm to enable decentralized training and execution (DTDE) for task offloading, which is privacy-preserving, effective, and scalable for the low-altitude VFC systems. …”
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Thyroid nodule classification in ultrasound imaging using deep transfer learning by Yan Xu, Mingmin Xu, Zhe Geng, Jie Liu, Bin Meng

“…Following model fusion, the AUC improved to 0.783 (95% CI: 0.724–0.841). …”
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The Analysis of the Possibility to Conduct Orbital Manoeuvres of Nanosatellites in the Context of the Maximisation of a Specific Operational Task by Magdalena Lewinska, Michal Kedzierski

“…It is suggested that future research should develop towards more advanced optimisation techniques, such as artificial intelligence algorithms that may additionally improve the precision and efficiency of planning orbital trajectories.…”
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Breeding of Solanaceous Crops Using AI: Machine Learning and Deep Learning Approaches—A Critical Review by Maria Gerakari, Anastasios Katsileros, Konstantina Kleftogianni, Eleni Tani, Penelope J. Bebeli, Vasileios Papasotiropoulos

“…Through advanced algorithms and predictive models, ML and DL facilitate the identification and optimization of key traits, including higher yield, improved quality, pest resistance, and tolerance to extreme climatic conditions. …”
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Distributed Beamforming for Relay Assisted Multiuser Machine-to-Machine Networks by Chen Chen, Lin Bai, Meiping Feng, Minhua Huang, Tian Tian

“…Numerical simulations for the proposed algorithms are presented showing the performance of the proposed schemes is close to that of the optimal scheme with global CSI in terms of bit error rate (BER) criterion.…”
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Foreign object detection for mining conveyor belts based on YOLOv5n-CND by SUN Aoran, ZHAO Peipei, YANG Di, ZHANG Junyi, YU Hongjian

“…The mAP@0.5 and mAP@0.5:0.95 of YOLOv5n-CND were 2.6% and 3.4% higher than YOLOv5n, and 1.7% and 3.8% higher than YOLOv5s-CBAM, respectively. Although the model’s parameter count slightly increased compared to the YOLOv5n model, it was still lower than that of other models. …”
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Convergence of nanotechnology and artificial intelligence in the fight against liver cancer: a comprehensive review by Manjusha Bhange, Darshan Telange

“…We highlight how AI-powered algorithms can optimize nanocarrier design, facilitate real-time monitoring of treatment efficacy, and enhance clinical decision-making. …”
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A Novel Time Series Prediction Approach Based on a Hybridization of Least Squares Support Vector Regression and Swarm Intelligence by Nhat-Duc Hoang, Anh-Duc Pham, Minh-Tu Cao

“…In order to optimize the LS-SVR’s tuning parameters, the FLSVRTSP incorporates the firefly algorithm (FA) as the search engine. …”
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A plug and play fuzzy mask extraction module for single image deraining by Mingdi Hu, Yao Song, Songxin Zhang, Zejian Xie, Bingyi Jing

“…Comprehensive experiments show that combining the rain removal network with our proposed model not only improves the rain removal effect of the algorithm, but also gives clearer background details of the image. …”
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Eco-assessment of meat raw materials: A convolutional neural network approach to sustainable quality control by Verezubova Natalia, Sakovich Natalia, Yukovleva Olga, Chekulaev Artur, Verezubova Irina

“…Genetic algorithms are employed to optimize hyperparameters, which significantly improve model performance. …”
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A Bluetooth Indoor Positioning System Based on Deep Learning with RSSI and AoA by Yongjie Yang, Hao Yang, Fandi Meng

“…In the deep learning network architecture, we propose a convolutional neural network (CNN)–multi-head attention (MHA) model. During the training process, the backpropagation (BP) algorithm is used to compute the gradient of the loss function and update the parameters of the entire network, gradually optimizing the model’s performance. …”
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A pregeneration–recognition method of detecting weak seafloor echoes for full-waveform airborne LiDAR bathymetry by Yadong Guo, Wenxue Xu, Yanxiong Liu, Fanlin Yang, Xue Ji, Yikai Feng, Qiuhua Tang

“…Finally, a back propagation neural network (BPNN) model is constructed using the points generated from surface–seafloor shots, and the seafloor points in seafloor-undefined shots are obtained by optimizing the BPNN results. …”
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Information and methodological aspects of developing platforms of spatial management of natural assets in resource limitations by V.V. Mykytenko, I.V. Dragan

“…It is planned to build, within the subsystems of functional and decision-making and development of communicative metaspace, which is included in the spatial management system, sustainable theoretical-analytical and applied models with a high degree of approximation of characteristics and comparative assessment of optimal natural assets for involvement within business ecosystems of Ukraine, available natural resources in the context of the formation of a national economy of the platform type as a result of strengthening the competitive positions of participants in sustainable management and increasing the effectiveness of spatial management. …”
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GA-BPNN Based Hybrid Steering Control Approach for Unmanned Driving Electric Vehicle with In-Wheel Motors by Yong Li, Xing Xu, Wujie Wang

“…The genetic algorithm (GA) is employed to optimize the initial weight of BPNN and search within a large range. …”
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Research and Application of a Health Management Device for the Electrical Control Cabinet of the EMU by Yongshen WU, Jian FENG, Mingshuai ZHANG, Chaoyue JU, Feihong YI

“…Specifically, the data of voltage and current of the key loops of electrical cabinets were obtained through health management device in real time with a high speed, the real-time monitoring, status assessment, logic control analysis, malfunction diagnosis and residual life prediction throughout the life cycle of electrical cabinets could be achieved based on a recognition algorithm model. Hence, the health management device can improve the self-perception and health management capability of electrical cabinets and thus make vehicles more reliable. …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

“…In this study, we developed machine learning (ML) algorithms to estimate 30-day mortality risk post-hip fracture surgery in the elderly using data from the National Surgical Quality Improvement Program (NSQIP 2012–2017, n = 62,492 patients). …”
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Conceptual Framework of Energy-and-Ecology of Indoor Plant Lighting by Sergei A. Rakut’ko

“…(Conclusions) For the first time, the author raises a question about the development of structural elements of the BAT formation algorithm in lighting horticulture in terms of energy-ecological indicators as an integrative optimality criterion of the system. …”
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Remote Sensing of Particle Absorption Coefficient of Pigments Using a Two-Stage Framework Integrating Optical Classification and Machine Learning by Xietian Xia, Shaohua Lei, Hui Lu, Zenghui Xu, Xiang Li, Xing Chen, Niancheng Hong, Jie Xu, Kun Shi, Jiacong Huang

“…Focusing on inland waters—key areas for eutrophication monitoring—we first developed an intelligent clustering method combining Kernel Principal Angle-based Component (KPAC) dimensionality reduction and Chameleon Swarm Algorithm (CSA)-optimized k-medoids to classify water bodies into four optical types based on hyperspectral reflectance features. …”
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A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…The results show that SVC and GBDT algorithms are more effective and the overall model classification accuracy reached 86.44% and 91.53%. …”
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Joint Resource Scheduling of the Time Slot, Power, and Main Lobe Direction in Directional UAV Ad Hoc Networks: A Multi-Agent Deep Reinforcement Learning Approach by Shijie Liang, Haitao Zhao, Li Zhou, Zhe Wang, Kuo Cao, Junfang Wang

“…The algorithm with the main lobe direction scheduling improves performance by 67.06% compared to the algorithm without the main lobe direction scheduling.…”
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