Shoulder–Elbow Joint Angle Prediction Using COANN with Multi-Source Information Integration by Siyu Zong, Wei Li, Dawen Sun, Zhuoda Jia, Zhengwei Yue

“…To address the precision challenges in upper-limb joint motion prediction, this study proposes a novel artificial neural network (COANN) enhanced by the Cheetah Optimization Algorithm (COA). The model integrates surface electromyography (sEMG) signals with joint angle data through multi-source information fusion, effectively resolving the local optima issue in neural network training and improving the accuracy limitations of single sEMG predictions. …”
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Photovoltaic Power Forecasting with Weather Conditioned Attention Mechanism by Xuetao Jiang, Yuchun Gou, Meiyu Jiang, Lihui Luo, Qingguo Zhou

“…The proposed Conditional Decomposition (CD) algorithm searches for the decomposition algorithms and corresponding hyperparameters of the prediction model, aiming to achieve the optimal prediction performance. …”
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Overheating Defect Detection of Composite Insulator Based on Mask R-CNN by Yi GAO, Lianfang TIAN, Qiliang DU

“…Firstly, in order to improve the accuracy of segmentation, the Mask R-CNN network is improved according to the idea of Cascade R-CNN, and the data augmentation and transfer learning methods are used for model training to improve the network performance. …”
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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…Compared with the CRF model, LSTM-CRF model,GRU-CRF model, BiLSTM-CRF model, CNN-CRF model, and Bert-CRF model, the F1-score values of the proposed model are improved by 27.42%, 18.78%, 23.62%, 13.25%, 14.88%, and 14.46%. …”
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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…Compared with the CRF model, LSTM-CRF model,GRU-CRF model, BiLSTM-CRF model, CNN-CRF model, and Bert-CRF model, the F1-score values of the proposed model are improved by 27.42%, 18.78%, 23.62%, 13.25%, 14.88%, and 14.46%. …”
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Beyond Linearity: Uncovering the Complex Spatiotemporal Drivers of New-Type Urbanization and Eco-Environmental Resilience Coupling in China’s Chengdu–Chongqing Economic Circle with... by Caoxin Chen, Shiyi Wang, Meixi Liu, Ke Huang, Qiuyi Guo, Wei Xie, Jiangjun Wan

“…A random forest (RF) model, interpreted with Shapley Additive exPlanations (SHAP) and Partial Dependence Plot (PDP) algorithms, explores nonlinear driving mechanisms, while Geographically and Temporally Weighted Regression (GTWR) assesses drivers’ spatiotemporal heterogeneity. …”
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Detection and Prediction of Wind and Solar Photovoltaic Power Ramp Events Based on Data-Driven Methods: A Critical Review by Jie Zhang, Xinchun Zhu, Yigong Xie, Guo Chen, Shuangquan Liu

“…Our analysis reveals that while detection algorithms for ramp events have matured and the overall predictive performance of power forecasting models has improved, existing approaches often struggle to capture localized ramp phenomena, resulting in persistent deviations. …”
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Design of a dynamic trust management and defense decision system for shared vehicle data based on blockchain and deep reinforcement learning by Jinxiang Chen, Yan Li, Jiaxing Deng, Beicheng Qin, Chengcai He, Qiangsheng Huang, Jingchun Wu

“…Using the Deep Q-Network (DQN) algorithm, the system identifies optimal defensive strategies through multidimensional data interactions. …”
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A multitask framework based on CA-EfficientNetV2 for the prediction of glioma molecular biomarkers by Qian Xu, Feng Ning Liang, Ya Ru Cao, Jin Duan, Teng Cui, Teng Zhao, Hong Zhu

“…Initially, unlabeled MR images were annotated using K-means clustering to generate pseudolabels, which were subsequently refined using a Vision Transformer (ViT) network to improve labeling accuracy. Then, the Fruit Fly Optimization Algorithm (FOA) was employed to assign optimal weights to the pseudolabeled data. …”
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Neuro-fuzzy controller based adaptive control for enhancing the frequency response of two-area power system by M.S. Elborlsy, Samir A. Hamad, Fayez F.M. El-Sousy, R.M. Mostafa, H.E. Keshta, Mohamed A. Ghalib

“…FPI and PI controllers' parameters are optimally tuned using a recent optimization technique known as the Coati Optimization Algorithm (COA). …”
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Smoothing Photovoltaic Power Fluctuations for Cascade Hydro-PV-Pumped Storage Generation System Based on a Fuzzy CEEMDAN by Lei Chen, Jun Wang, Zhang Sun, Tao Huang, Fan Wu

“…Furthermore, in order to overcome the drawback that too frequent conversion of unit operating mode would reduce the service life and smoothing effect of the VSPSS unit, the optimization model of the base power of the VSPSS is established and solved by the grid adaptive direct search method (MADS) to obtain the control signal of the VSPSS for suppressing the short-term fluctuations of the PV output. …”
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Predicting 24-hour intraocular pressure peaks and averages with machine learning by Ranran Chen, Jinming Lei, Yujie Liao, Yiping Jin, Xue Wang, Xiaomei Li, Danping Wu, Hong Li, Yanlong Bi, Haohao Zhu

“…Specific time point combinations and the RFR algorithm were identified, which improved the accuracy of predicting 24-hour peak and average intraocular pressure. …”
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Adaptive Covariance Matrix for UAV-Based Visual–Inertial Navigation Systems Using Gaussian Formulas by Yangzi Cong, Wenbin Su, Nan Jiang, Wenpeng Zong, Long Li, Yan Xu, Tianhe Xu, Paipai Wu

“…Our algorithm has shown significantly higher accuracy compared to the famous VINS-Mono framework, outperforming it by 18.18% on average, as well as the optimization rate of RMS, which reaches 65.66% for the F1 dataset and 41.74% for F2 in the field tests outdoors.…”
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CT-TDMA:efficient TDMA protocol for underwater sensor networks by Lu HONG, Feng HONG, Zheng-bao LI, Zhong-wen GUO

“…Aimed at underwater acoustic sensor networks(UWSN),a novel sender based conflict model with the schemes of allocating continuous time was presented,including local conflict graph(LCG)and a distribute algorithm to generate LCG.Moreover,CT-TDMA,an efficient TDMA protocol based on the conflict model was also proposed,which used heuristic priority rules to allocate transmitting moments for all nodes.CT-TDMA exploits the diversity of propagation delay of different links in UWSN to decrease the idle time between packets at the same receiving node,which helps in improving the throughput.And a heuristic schedule algorithm is applied to shorten the process of allocating continuous time for each node.Simulation results show that,compared with traditional TDMA protocols such as ST-MAC,network throughput of CT-TDMA has increased 20% and end to end delay has decreased 18%;compared to the theoretically optimal scheme with global knowledge,CT-TDMA has achieved 80% network throughput and the end to end delay is only 12% longer.…”
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CT-TDMA:efficient TDMA protocol for underwater sensor networks by Lu HONG, Feng HONG, Zheng-bao LI, Zhong-wen GUO

“…Aimed at underwater acoustic sensor networks(UWSN),a novel sender based conflict model with the schemes of allocating continuous time was presented,including local conflict graph(LCG)and a distribute algorithm to generate LCG.Moreover,CT-TDMA,an efficient TDMA protocol based on the conflict model was also proposed,which used heuristic priority rules to allocate transmitting moments for all nodes.CT-TDMA exploits the diversity of propagation delay of different links in UWSN to decrease the idle time between packets at the same receiving node,which helps in improving the throughput.And a heuristic schedule algorithm is applied to shorten the process of allocating continuous time for each node.Simulation results show that,compared with traditional TDMA protocols such as ST-MAC,network throughput of CT-TDMA has increased 20% and end to end delay has decreased 18%;compared to the theoretically optimal scheme with global knowledge,CT-TDMA has achieved 80% network throughput and the end to end delay is only 12% longer.…”
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Personalised context-aware re-ranking in recommender system by Xiangyong Liu, Guojun Wang, Md Zakirul Alam Bhuiyan

“…However, contextual factors significantly affect user behaviour, especially in the Internet of Things (IoT), which brings difficulties to modelling user preferences. In this paper, we propose a personalised context-aware re-ranking algorithm (p-CAR) in IoT. …”
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Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan

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A practical guide for nephrologist peer reviewers: evaluating artificial intelligence and machine learning research in nephrology by Yanni Wang, Wisit Cheungpasitporn, Hatem Ali, Jianbo Qing, Charat Thongprayoon, Wisit Kaewput, Karim M. Soliman, Zhengxing Huang, Min Yang, Zhongheng Zhang

“…AI-driven models utilize diverse datasets—including electronic health records, imaging, and biomarkers—to improve clinical decision-making. …”
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Masks-to-Skeleton: Multi-View Mask-Based Tree Skeleton Extraction with 3D Gaussian Splatting by Xinpeng Liu, Kanyu Xu, Risa Shinoda, Hiroaki Santo, Fumio Okura

“…Furthermore, we use a minimum spanning tree (MST) algorithm during the optimization loop to regularize the graph to a tree structure. …”
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Temporal Community Detection and Analysis with Network Embeddings by Limengzi Yuan, Xuanming Zhang, Yuxian Ke, Zhexuan Lu, Xiaoming Li, Changzheng Liu

“…By establishing coherent relationships between node representations and community structures, we optimize both the Convex-NMF-based representation learning model and the evolutionary clustering-based TCD model within a unified framework. …”
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