A DSP–FPGA Heterogeneous Accelerator for On-Board Pose Estimation of Non-Cooperative Targets by Qiuyu Song, Kai Liu, Shangrong Li, Mengyuan Wang, Junyi Wang

“…Experimental results show that the optimized model achieves a peak throughput of 399.16 GOP/s with less than 1% accuracy loss. …”
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Countermeasuring Anti-Ship Missiles for Surface Naval Platforms: A Machine Learning Approach With Explainable Artificial Intelligence by Murat Ertop, Ali Oter, Ali Kara

“…The authors believe that the proposed model can be further improved and integrated with existing countermeasure techniques.…”
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Hierarchically Federated Learning in Wireless Networks: D2D Consensus and Inter-Cell Aggregation by Jie Zhang, Li Chen, Yunfei Chen, Xiaohui Chen, Guo Wei

“…Based on the convergence analysis, we characterize the network topology of each cell, the communication interval of intra-cell consensus and inter-cell aggregation on the training performance. To further improve the performance of HDFL, we optimize the computation capacity selection and bandwidth allocation to minimize the training latency and energy overhead. …”
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rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask by Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun

“…The SVM achieved 84.3% accuracy for sound data classification, while the Lion algorithm−optimized SVM achieved an even higher accuracy of 93.6%. …”
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Vehicle detection in drone aerial views based on lightweight OSD-YOLOv10 by Yang Zhang, Xiaobing Chen, Su Sun, Hongfeng You, Yuanyuan Wang, Jianchu Lin, Jiacheng Wang

“…Abstract To address the challenges of low performance in vehicle image detection from UAV aerial imagery, difficulties in small target feature extraction, and the large parameter size of existing models, we propose the OSD-YOLOv10 algorithm, an enhanced version based on YOLOv10n. …”
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Evolutionary game-based cooperative strategy for effective capacity of multiple-input-multiple-output communications by Jianhua Liu, Jiadi Yu, Minglu Li, Luqun Li, Dazhi Li, Shigen Shen

“…Numerical results show that the proposed algorithm can effectively improve the quality of service for mobile two-dimensional multiple-input-multiple-output communication networks.…”
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DrugBERT: a BERT-based approach integrating LDA topic embedding and efficacy-aware mechanism for predicting anti-tumor drug efficacy by Weiwei Zhu, Xiaodong Jiang, Lei Zhang, Peng Zhou, Xinping Xie, Hongqiang Wang

“…These findings highlight its potential for optimizing personalized therapeutic strategies through language model.…”
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Module Partition of Mechatronic Products Based on Core Part Hierarchical Clustering and Non-Core Part Association Analysis by Shuai Wang, Yi-Fei Song, Guang-Yu Zou, Jia-Xiang Man

“…Then, based on the core parts, the corresponding product design structural matrix (DSM) model is established. Secondly, the hierarchical clustering algorithm is used to obtain the module division scheme of different levels of mechatronic products, and the optimal modular scheme is obtained through an evaluation of modularity and a rationality analysis of module structure. …”
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GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…Secondly, we integrated the SimAM attention module to optimize the collaborative learning of feature map dimensions and to reduce reliance on hyperparameter tuning through precise weight allocation, thereby improving the model’s rapid response capability to fires. …”
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“Bias Correction Method” for Regional Correction Experiment of Warm Season Rainstorm in Zhejiang by Chengyan Mao, Xin Pan, Haowen Li, Weibiao Li, Haoya Liu

“…The corrected forecasts are subsequently evaluated against the original model outputs. The key findings include: (1) Zhejiang Province is optimally divided into four regions characterized by similar precipitation patterns, which exhibit distinct regional features closely linked to the province’s topography and geomorphology. …”
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Predicting hospital outpatient volume using XGBoost: a machine learning approach by Lingling Zhou, Qin Zhu, Qian Chen, Ping Wang, Hao Huang

“…Accurate prediction of outpatient demand can significantly enhance operational efficiency and optimize the allocation of medical resources. This study aims to develop a predictive model for daily hospital outpatient volume using the XGBoost algorithm. …”
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Fully-Gated Denoising Auto-Encoder for Artifact Reduction in ECG Signals by Ahmed Shaheen, Liang Ye, Chrishni Karunaratne, Tapio Seppänen

“…While our model performs best compared with other models tested in this study, more improvements are needed for optimal morphological preservation, especially in the presence of electrode motion artifacts.…”
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MED-AGNeT: An attention-guided network of customized augmentation of samples based on conditional diffusion for textile defect detection by Jun Liu, Haolin Li, Hao Liu, Jiuzhen Liang

“…Ultimately, AGNet’s true positive rate (TPR), positive predictive value (PPV), and f-measure exceed those of the state-of-the-art (SOTA) algorithms by 1.88%, 0.05%, and 0.77%, respectively, and with a consistent model architecture, its parameter quantity is reduced by 56%.…”
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Comprehensive Review of Robotics Operating System-Based Reinforcement Learning in Robotics by Mohammed Aljamal, Sarosh Patel, Ausif Mahmood

“…To improve decision making, robots need a dependable framework to facilitate communication between different modules and the optimal action for real-world applications. …”
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Decoding Depression from Different Brain Regions Using Hybrid Machine Learning Methods by Qi Sang, Chen Chen, Zeguo Shao

“…To clarify the impact of brain region segmentation on the detection accuracy of moderate-to-severe major depressive disorder (MDD) and identify the optimal brain region for detecting MDD using electroencephalography (EEG), this study compared eight traditional single-machine learning algorithms with a hybrid machine learning model based on a stacking ensemble technique. …”
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An abnormal traffic detection method for chain information management system network based on convolutional neural network by Chao Liu, Chunxiang Liu, Changrong Liu

“…Finally, the conditional random field (CRF) determines the optimal label sequence based on the conditional probability distribution and applies the Viterbi algorithm to complete the sequence labeling of network traffic in chain information management system. …”
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Short-Term Power Prediction for Wind Farm and Solar Plant Clusters Based on Machine Learning Method by Yang CUI, Zhenghong CHEN, Peihua XU

“…Firstly, the machine learning-based Bisecting K-Means(BKM) clustering algorithm is used to reasonably divide the wind farms and PV stations in the region into clusters; Secondly, based on the correlation between of the historical power data of each power station and the total historical power data in the region, a representative power station is selected for each region; Thirdly, after optimizing and correcting the NWP(numerical weather prediction) model of each representative power station, a short-term power prediction framework model is established using BP neural network based on the cluster division of wind farms and PV power plants. …”
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GPU Assisted Brute Force Cryptanalysis of GPRS, GSM, RFID, and TETRA by Cihangir Tezcan, Gregor Leander

“…In this work we provide optimized implementations of several widely used algorithms on GPUs, leading to interesting insights on the cost of brute force attacks on several real-word applications. …”
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To accurately predict lymph node metastasis in patients with mass-forming intrahepatic cholangiocarcinoma by using CT radiomics features of tumor habitat subregions by Pengyu Chen, Zhenwei Yang, Peigang Ning, Hao Yuan, Zuochao Qi, Qingshan Li, Bo Meng, Xianzhou Zhang, Haibo Yu

“…This model is expected to provide personalized decision support to clinicians and help to optimize treatment plans and improve patient outcomes.…”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…This approach effectively captures both structured features and non-linear patterns, making it suitable for datasets with complex dependencies. The second model pairs eXtreme Gradient Boosting (XGBoost), a highly efficient boosting algorithm for tabular data, with an Artificial Neural Network (ANN). …”
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