Enhancing Secure Energy Efficiency of SWIPT IoT Network Considering IRS and Artificial-Noise: A Deep Learning Approach by Kimchheang Chhea, Jung-Ryun Lee

“…We first formulate a joint optimization model of IRS and AN aided secure communication, which is a non-convex optimization problem with linear and non-linear constraints. …”
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Task Offloading with LLM-Enhanced Multi-Agent Reinforcement Learning in UAV-Assisted Edge Computing by Feifan Zhu, Fei Huang, Yantao Yu, Guojin Liu, Tiancong Huang

“…This framework integrates the QTRAN algorithm with a large language model (LLM) for efficient region decomposition and employs graph convolutional networks (GCNs) combined with self-attention mechanisms to adeptly manage inter-subregion relationships. …”
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City-scale industrial tank detection using multi-source spatial data fusion by Zhibao Wang, Mingyuan Zhu, Lu Bai, Jinhua Tao, Mei Wang, Xiaoqing He, Anna Jurek-Loughrey, Liangfu Chen

“…To address this, high-resolution remote sensing images and deep learning algorithms are used to improve the accuracy of industrial storage tank detection at the city scale. …”
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Multiple UAV Swarms Collaborative Firefighting Strategy Considering Forest Fire Spread and Resource Constraints by Pei Zhu, Rui Song, Jiangao Zhang, Ziheng Xu, Yaqi Gou, Zhi Sun, Quan Shao

“…The multiple UAV swarm adaptive information-driven collaborative search (MUSAIDCS) algorithm and the resource-limited firefighting model were established. …”
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MPDP -medoids: Multiple partition differential privacy preserving -medoids clustering for data publishing in the Internet of Medical Things by Zekun Zhang, Tongtong Wu, Xiaoting Sun, Jiguo Yu

“…Based on the traditional k -medoids clustering, multiple partition differential privacy k -medoids clustering algorithm optimizes the randomness of selecting initial center points and adds Laplace noise to the clustering process to improve data availability while protecting user’s privacy information. …”
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Advancements in machine learning for estimating parameters of wastewater treatment plants by Kolyeva Natalya, Rastyagaev Alexander, Kortenko Lyudmila, Rozhkov Sergey, Sbitneva Mariia, Kuznetsov Aleksandr

“…As a result of the study, a model of the XGBoost algorithm was developed, which successfully coped with the task of optimization of calculations, providing high accuracy, and this, in turn, opens up new opportunities for improving the efficiency of design of wastewater treatment plants.…”
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Boosting skin cancer diagnosis accuracy with ensemble approach by Priya Natha, Sivarama Prasad Tera, Ravikumar Chinthaginjala, Safia Obaidur Rab, C. Venkata Narasimhulu, Tae Hoon Kim

“…Moreover, feature vectors that were optimally produced from image data by a Genetic Algorithm (GA) were given to the ML models. …”
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Anti-packet-loss joint encoding for voice-over-IP steganography by Zhan-zhan GAO, Guang-ming TANG, Wei-wei ZHANG

“…Furthermore, the influences of key parameters on the performance of joint coding were studied. The selection algorithm for optimal parameters was also given. Experimental results show that the proposed joint coding can effectively improve steganographic resistance to packet loss, and decrease the number of modifications to the voice stream.…”
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Individual Travel Knowledge Graph-Based Public Transport Commuter Identification: A Mixed Data Learning Approach by Song Hu, Jiancheng Weng, Quan Liang, Wei Zhou, Peizhao Wang

“…The results confirm that the proposed model has a better identification accuracy and viability, and the model performance will improve with the increase of the sample size.…”
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A visual positioning method for tunnel boring machines in underground coal mines based on anchor net features by Xuhui ZHANG, Yunkai CHI, Yuyang DU, Junying JIANG, Wenjuan YANG, Youjun ZHAO, Jicheng WAN, Yanqun WANG, Chenhui TIAN

“…In combination with pose graph optimization, this model enabled precise TBM positioning. …”
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PMD-Transformer: A Domain Generalization Approach for Person Re-Identification by Xingguo Jiang, Ling Yu, Guojun Lin, Yuchao Zhang

“…Finally, a new feedforward network (DRFNN) is used to enhance the mastery of spatial information and further improve the generalization performance of the model. …”
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Accelerated Benders’ Decomposition for Integrated Forward/Reverse Logistics Network Design under Uncertainty by Vahab Vahdat, Mohammad Ali Vahdatzad

“…Numerical results confirmed that the proposed solution algorithm improved the convergence of BD lower bound and the upper bound, enabling to reach an acceptable optimality gap in a convenient time.…”
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Intelligent deep learning-based dual-task approach for robust power quality event classification by Lipsa Ray, Pampa Sinha, Siddhanta Pani, Anshuman Nayak, Kaushik Paul, Chitralekha Jena, Md. Minarul Islam, Taha Selim Ustun

“…These findings underscore the model’s efficacy in real-time PQ monitoring, contributing to improved reliability and stability in evolving power systems.…”
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A Robust Hybrid MRAPID Controller Design for an Underactuated Nonlinear System With Parametric Uncertainty by Ahmed Abduljabbar Mahmood, Mohamed Abderrahim

“…This paper presents an optimal design and simulation of a novel enhanced model reference adaptive proportional–integral–derivative controller (MRAPIDC) for underactuated nonlinear systems with parametric uncertainty. …”
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Research on End-Effector Position Error Compensation of Industrial Robotic Arm Based on ECOA-BP by Wenping Xiang, Junhua Chen, Hao Li, Zhiyuan Chai, Yinghou Lou

“…To achieve error compensation, an approach based on an Enhanced Crayfish Optimization Algorithm (ECOA) optimizing a BP neural network was proposed to compensate for position errors. …”
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Enhancing the e-commerce shopping experience with IoT-enabled smart carts in smart stores by Jian Wang

“…The findings demonstrate that the proposed IoT-enabled model efficiently balances classification tasks, reduces congestion during algorithm execution, and minimizes energy waste. …”
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DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…In response to the limitations of current infrared and visible light image fusion algorithms-namely insufficient feature extraction, loss of detailed texture information, underutilization of differential and shared information, and the high number of model parameters-this paper proposes a novel multi-scale infrared and visible image fusion method with two-branch feature interaction. …”
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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

“…The preliminary application of detecting daily active state, activity pattern and behavior recognition of pigs based on motion information is further explored. The improved k-means clustering algorithm is combined with convolutional neural network and long and short term memory network to provide early warning for pig diseases. …”
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Interactive Operation Strategy for Multi-scenario County-Level Multi-microgrid Based on ADMM by Chongbiao ZHANG, Chenwen QIAN, Hongyan YU, Yanling PENG, Jinwei CHEN

“…Firstly, a scheduling model for independent microgrid operation is established to realize the optimal scheduling strategy in the day-ahead pre-scheduling plan. …”
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Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction. by Kang Xu, Bin Pan, MingXin Zhang, Xuan Zhang, XiaoYu Hou, JingXian Yu, ZhiZhu Lu, Xiao Zeng, QingQing Jia

“…Existing methods, however, have the following limitations: (1) insufficient exploration of interactions across different temporal scales, which restricts effective future flow prediction; (2) reliance on predefined graph structures in graph neural networks, making it challenging to accurately model the spatial relationships in complex road networks; and (3) end-to-end training, which often results in unclear optimization directions for model parameters, thereby limiting improvements in predictive performance. …”
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