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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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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Adaptive multi-agent reinforcement learning for dynamic pricing and distributed energy management in virtual power plant networks by Jian-Dong Yao, Wen-Bin Hao, Zhi-Gao Meng, Bo Xie, Jian-Hua Chen, Jia-Qi Wei

“…Extensive simulations across diverse scenarios demonstrate that our approach consistently outperforms baseline methods, including Stackelberg game models and model predictive control, achieving an 18.73% reduction in costs and a 22.46% increase in VPP profits. …”
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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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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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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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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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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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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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An Efficient and Cost-Effective Vehicle Detection and Tracking System for Collision Avoidance in Foggy Weather by Naeem Raza, Muhammad Asif Habib, H. M. Sajid Imran, Abdul Qayum, Sajida Perveen, Sohail Jabbar, Shahzad Sarwar, Mudassar Ahmad

“…The optimized deep-SORT outperforms pre-processing, inference, NMS post-processing, and update time, achieving higher FPS on foggy and the BDD100K dataset video sequences compared to the baseline deep-SORT and strong-SORT vehicle tracking algorithms. …”
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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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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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Medical Device Failure Predictions Through AI-Driven Analysis of Multimodal Maintenance Records by Noorul Husna Abd Rahman, Khairunnisa Hasikin, Nasrul Anuar Abd Razak, Ayman Khallel Al-Ani, D. Jerline Sheebha Anni, Prabu Mohandas

“…Then, four machine learning algorithms and three deep learning networks are evaluated to determine the best predictive model. …”
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Accelerating RRT* convergence with novel nonuniform and uniform sampling approach by Sivasankar Ganesan, Mohanraj Thangamuthu, Balakrishnan Ramalingam, Madan Mohan Rayguru, Sethu Narayanan Tamilselvan

“…Due to its asymptotic optimality, the optimal rapidly-exploring random tree (RRT*) algorithm is the most widely used among these. …”
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Complex Large-Deformation Multimodality Image Registration Network for Image-Guided Radiotherapy of Cervical Cancer by Ping Jiang, Sijia Wu, Wenjian Qin, Yaoqin Xie

“…The DSC index of the MTEF algorithm is 5.64% higher than that of the TransMorph algorithm. …”
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Digital Land Suitability Assessment for Irrigated Cultivation of Some Agricultural Crops Using Machine Learning Approaches (Case Study: Qazvin-Abyek) by F. Jannati, F. Sarmadian

“…The utilization of modern mapping techniques such as digital soil mapping and machine learning algorithms can significantly improve the accuracy of land suitability assessment and crop performance prediction. …”
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Reduction of Multiplicative Noise in Radar Images by A. A. Tuzova, V. A. Pavlov, A. A. Belov

“…The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. …”
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