Efficient tuna detection and counting with improved YOLOv8 and ByteTrack in pelagic fisheries by Yuanchen Cheng, Zichen Zhang, Yuqing Liu, Jie Li, Zhou Fu

“…This paper proposes an automatic tuna counting method based on the YOLOv8n-DMTNet target detection algorithm combined with the improved ByteTrack tracking algorithm. …”
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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

“…To address these issues, we propose TCDA-NE, a novel TCD algorithm that combines evolutionary clustering with convex non-negative matrix factorization (Convex-NMF). …”
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Enhancing Automated Maneuvering Decisions in UCAV Air Combat Games Using Homotopy-Based Reinforcement Learning by Yiwen Zhu, Yuan Zheng, Wenya Wei, Zhou Fang

“…While algorithms enhanced with densely distributed artificial rewards show potential, they risk deviating from the primary objectives. …”
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Adaptive Fast Refocusing for Ship Targets With Complex Motion in SAR Images by Xinqi Xu, Xiangguang Leng, Zhongzhen Sun, Xiangdong Tan, Kefeng Ji, Gangyao Kuang

“…This algorithm can adaptively adjust algorithm parameters based on SAR images from different SAR platforms, thereby more accurately determining the optimal rotation interval (ORI), reducing computational cost, and achieving adaptive fast refocusing. …”
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Dual-hybrid intrusion detection system to detect False Data Injection in smart grids. by Saad Hammood Mohammed, Mandeep S Jit Singh, Abdulmajeed Al-Jumaily, Mohammad Tariqul Islam, Md Shabiul Islam, Abdulmajeed M Alenezi, Mohamed S Soliman

“…Future research should focus on integrating real-world smart grid data for validation, developing adaptive learning mechanisms, exploring other bio-inspired optimization algorithms, and addressing real-time processing and scalability challenges in large-scale deployments.…”
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PP-QADMM: A Dual-Driven Perturbation and Quantized ADMM for Privacy Preserving and Communication-Efficient Federated Learning by Anis Elgabli

“…We provide a rigorous theoretical proof of convergence, showing that PP-QADMM converges to the optimal solution for convex problems while achieving a convergence rate comparable to standard ADMM, but with significantly lower communication and energy costs, and robust privacy protection. …”
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TA-RRT*: Adaptive Sampling-Based Path Planning Using Terrain Analysis by Taegeun Oh, Yun-Jae Won, Sungjin Lee

“…While existing RRT*-based algorithms perform node sampling and tree expansion in various ways to optimize path planning, they may still generate inefficient paths in complex terrain environments. …”
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RFID-Based Real-Time Salt Concentration Monitoring with Adaptive EKF by Renhai Feng, Xinyi Lin

“…The concentration dynamics are modeled as a hidden Markov process and tracked using an adaptive extended Kalman filter (AEKF). The AEKF algorithm avoids computationally expensive inversion of complex observation equations while automatically adjusting noise covariance matrices via innovation sequence. …”
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Graph attention networks based multi-agent path finding via temporal-spatial information aggregation. by Qingling Zhang, Peng Wang, Cui Ni, Xianchang Liu

“…An effective Multi-Agent Path Finding (MAPF) algorithm must efficiently plan paths for multiple agents while adhering to constraints, ensuring safe navigation from start to goal. …”
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Short-term results of treatment of non-epithelial gastro-intestinal tumors complicated by bleeding by S. G. Shapovalyants, A. I. Mikhalev, Ye. D. Fedorov, R. V. Plakhov, L. M. Mikhaleva, Z. V. Galkova, Ye. V. Ivanova, A. E. Sergeyenko

“…According to suggested diagnostic algorithm detailed characteristic of patients with bleeding tumor was given, the optimal method of surgical intervention was chosen. …”
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THE USE OF CORRELATION ANALYSIS OF TWO-DIMENSION STOCHASTIC PROCESS FOR HELICOPTER MAINTENANCE WORKABILITY ESTIMATION by Y. M. Chinyuchin, A. S. Solov’ev

“…The new calculated program complex which main task is to find the optimal algorithm of stochastic helicopter de- sign and assembling in terms of maintenance efficiency is described. …”
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KDFE: Robust KNN-Driven Fusion Estimator for LEO-SoOP Under Multi-Beam Phased-Array Dynamics by Jiaqi Yin, Ruidan Luo, Xiao Chen, Linhui Zhao, Hong Yuan, Guang Yang

“…Global FFT processing extracts real-time Doppler-SNR parameter pairs, while a KNN-based arbiter dynamically selects the optimal estimator by: (1) Projecting parameter pairs into historical performance space, (2) Identifying the accuracy-optimal algorithm for current beam conditions, and (3) Executing real-time switching to balance accuracy and robustness. …”
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Increasing the Efficiency Factor of Solar Power Plants Due to Solar Energy Localizing by V. I. Mironchuk, A. A. Velchenko

“…The article presents an analysis of the state of development of solar energy in Europe and  the  Republic  of  Belarus  for 2020.  An algorithm for increasing the efficiency factor of  solar power plants by localizing the solar trajectory depending on the latitude and longitude of the area has been proposed. …”
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Detection Model for Cotton Picker Fire Recognition Based on Lightweight Improved YOLOv11 by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song, Yi Wu

“…The improved detection algorithm maintains high accuracy while achieving faster inference speed and fewer model parameters. …”
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OR-FCOS: an enhanced fully convolutional one-stage approach for growth stage identification of Oudemansiella raphanipes by Runze Fang, Huamao Huang, Nuoyan Guo, Haichuan Wei, Shiyi Wang, Haiying Hu, Ming Liu

“…Channel pruning further reduces the decoder’s parameters, decreasing model size and computational requirements while maintaining precision. The enhanced algorithm achieved a mean average precision (mAP) of 89.4% ( $$\hbox {mAP}_{50}$$ ) and 78.3% ( $$\hbox {mAP}_{50:95}$$ ), while the number of model parameters was reduced to 9.9 M, the model size was reduced to 40.1 MB, and the number of floating point operations per second (FLOPs) was reduced to 31.2 G. …”
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Research on the Application of Artificial Intelligence in Quantitative Investment: Implementation Scenarios, Practical Challenges, and Future Trends by Chen Boshan

“…Second, the research focuses on key AI applications in quantitative investment, including multi-factor model optimization, high-frequency market risk management, multimodal data integration, and algorithmic trading enhancement. …”
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Communication resource allocation method in vehicular networks based on federated multi-agent deep reinforcement learning by Qingli Liu, Yongjie Ma

“…The simulation results show that the system spectrum efficiency is improved by 19.1% on average compared with the centralized DDPG, MADDPG, MAPPO and FL-DuelingDQN algorithms in the Vehicle Networking scenario, while the transmission success rate of the V2V link is improved by 9.3% on average, and the total capacity of the V2I link is increased by 16.1% on average.…”
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NLP-Driven Analysis of Pneumothorax Incidence Following Central Venous Catheter Procedures: A Data-Driven Re-Evaluation of Routine Imaging in Value-Based Medicine by Martin Breitwieser, Vanessa Moore, Teresa Wiesner, Florian Wichlas, Christian Deininger

“…<b>Methods:</b> We analyzed electronic health records from four university hospitals in Salzburg, Austria, focusing on X-rays performed between 2012 and 2021 following CVC procedures. A custom-built NLP algorithm identified cases of pneumothorax from radiologists’ reports and clinician requests, while excluding cases with contraindications such as chest injuries, prior pneumothorax, or missing data. …”
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AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices by Aiswarya Baburaj, Syamini Jayadevan, Akshaya Kumar Aliyana, Naveen Kumar SK, George K Stylios

“…This review explores the synergistic potential of AI‐driven TENG systems, from optimizing materials and fabrication to embedding machine learning and deep learning algorithms for intelligent real‐time sensing. …”
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AHA: Design and Evaluation of Compute-Intensive Hardware Accelerators for AMD-Xilinx Zynq SoCs Using HLS IP Flow by David Berrazueta-Mena, Byron Navas

“…Our performance evaluation across various configurations highlights performance–resource trade-offs and demonstrates that ANN and BPNN achieve significant parallelism, while AES optimization increases resource utilization the most. …”
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