YOLOv5-DTW: Gesture recognition based on YOLOv5 and dynamic time warping for digital media design by Lu Zhao, Jing Yu

“…In the recognition stage, firstly, the background and sensor thermal noise are used to enhance the classification data set, and the background optimization preprocessing algorithm is designed to improve the adaptability of the model to the complex background. …”
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METHOD FOR MODIFYING PROFILE OF CYCLOIDAL WHEEL CONSIDERING COMPENSATION FOR ELASTIC DEFORMATION by QIN ZhengZheng, WANG Quan, ZHAO DaXing, WANG Jun, ZENG LiLei

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Bayesian Time-Domain Ringing Suppression Approach in Impulse Ultrawideband Synthetic Aperture Radar by Xinhao Xu, Wenjie Li, Haibo Tang, Longyong Chen, Chengwei Zhang, Tao Jiang, Jie Liu, Xingdong Liang

“…This study systematically analyzes the mechanisms of ringing generation, including its physical origins and mathematical modeling in SAR systems. Building on this analysis, we propose a Bayesian ringing suppression algorithm based on sparse optimization. …”
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Machine learning-based prediction method for open-pit mining truck speed distribution in manned operation by Changyou XU, Gang CHEN, Qiuxia ZHANG, Bo WANG, Hongwang ZHANG, Hongrui LI, Weiwei QIN, Muyang LI

“…Among these models, the Random Forest-based model exhibited lower mean squared error and a higher coefficient of determination, outperforming the XGBoost-based model. …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Despite their success, machine learning methods face fundamental limitations in optimizing complex high-dimensional energy landscapes, which motivates research into new methods to improve the robustness and performance of optimization algorithms. …”
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Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models by Mohamed Salah Benkhalfallah, Sofia Kouah, Saad Harous

“…By evaluating performance of several regression algorithms using various metrics, this study identifies the most effective method for analyzing sectoral energy consumption. …”
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Threat analysis model to control IoT network routing attacks through deep learning approach by K. Janani, S. Ramamoorthy

“…A deep learning hybrid model based on a Long-Short-Term Memory (LSTM) network and adaptive Mayfly Optimization Algorithm (LAMOA) was presented for the classification of IoT attacks. …”
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Enhancing Fault Detection in AUV-Integrated Navigation Systems: Analytical Models and Deep Learning Methods by Huibao Yang, Bangshuai Li, Xiujing Gao, Bo Xiao, Hongwu Huang

“…Specifically, the particle swarm optimization (PSO) algorithm was employed to optimize the hyperparameters of a long short-term memory (LSTM) neural network, leading to the development of a PSO-LSTM fault detection model. …”
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Aerodynamic model identification of supersonic aircraft using Bayesian approach-based Box–Jenkins structure by Muhammad Fawad Mazhar, Muhammad Wasim, Manzar Abbas, Imran Shafi, Jamshed Riaz, Tae-hoon Kim, Imran Ashraf

“…Box–Jenkins (BJ) structure with Bayesian approach, named as Box–Jenkins–Bayesian–Estimation (BJBE). BJ model utilizes a nonlinear least square estimator for parameter identification, which has been improved by the Levenberg–Marquardt algorithm for parameter error minimization, and further refinement is accomplished through Bayes’ theorem using its maximum-a-posteriori characteristics. …”
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Research on Abstraction-Based Search Space Partitioning and Solving Satisfiability Problems by Yuexin Huang, Qinzhou Niu, Yanfang Song

“…Solving satisfiability problems is central to many areas of computer science, including artificial intelligence and optimization. Efficiently solving satisfiability problems requires exploring vast search spaces, where search space partitioning plays a key role in improving solving efficiency. …”
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Enhanced Conformer-Based Speech Recognition via Model Fusion and Adaptive Decoding with Dynamic Rescoring by Junhao Geng, Dongyao Jia, Zihao He, Nengkai Wu, Ziqi Li

“…In this paper, we propose improvements to the model structure fusion and decoding algorithms. …”
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Physical Health Portrait and Intervention Strategy of College Students Based on Multivariate Cluster Analysis and Machine Learning by Rong Guo, Rou Dong, Ni Lu, Lin Yu, Chaoxian Chen, Yonglin Che, Jiajin Zhang, Jianke Yang

“…This study employs an improved K-means algorithm integrated with machine learning models to analyze university students’ fitness data and develop personalized health intervention strategies. …”
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A Survey on the Key Technologies of UAV Motion Planning by Yuquan Zhou, Li Yan, Yaxi Han, Hong Xie, Yinghao Zhao

“…However, achieving full autonomy remains a challenge as human intervention is still required in most scenarios. Motion planning, a cornerstone of UAV autonomous navigation, has garnered extensive attention, with numerous advanced algorithms having been proposed in recent years. …”
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Advances in Pinhole and Multi-Pinhole Collimators For Single Photon Emission Computed Tomography Imaging by Jalil Islamian, AhmadReza Azazrm, Babak Mahmoudian, Esmail Gharapapagh

“…On the other hand, recent developments in collimator optimization have heightened the need for appropriate reconstruction algorithms for pinhole SPECT imaging. …”
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Robust Adaptive Fractional-Order PID Controller Design for High-Power DC-DC Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm for... by Seyyed Morteza Ghamari, Daryoush Habibi, Asma Aziz

“…To overcome this issue, Grey Wolf Optimization (GWO) algorithm is proposed to identify the most suitable initial gains for each agent, providing faster adaptation and consistent performance during the training process. …”
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FPGA Acceleration With Hessian-Based Comprehensive Intra-Layer Mixed-Precision Quantization for Transformer Models by Woohong Byun, Jongseok Woo, Saibal Mukhopadhyay

“…It is implemented on a single Xilinx ZCU102 FPGA board, operating at 200MHz with a power consumption of 15.08W during inference on the 110-million-parameter BERT-Base and 345-million-parameter GPT-2 Medium transformer models. Coupled with the proposed algorithm and dataflow optimization, it enables on-chip storage of all necessary parameters, minimizing off-chip memory access. …”
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Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method by Rencheng Fang, Tao Zhou, Baohua Yu, Zhigang Li, Long Ma, Tao Luo, Yongcai Zhang, Xinqi Liu

“…In addition, we propose the MDBO-BP-Adaboost model to predict students' performance. Firstly, the model incorporates the good point set initialization, triangle wandering strategy and adaptive t-distribution strategy to obtain the Modified Dung Beetle Optimization Algorithm (MDBO), secondly, it uses MDBO to optimize the weights and thresholds of the BP neural network, and lastly, the optimized BP neural network is used as a weak learner for Adaboost. …”
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Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models by Hongkun Fu, Jian Lu, Jian Li, Wenlong Zou, Xuhui Tang, Xiangyu Ning, Yue Sun

“…Accurate crop yield prediction is crucial for formulating agricultural policies, guiding agricultural management, and optimizing resource allocation. This study proposes a method for predicting yields in China’s major winter wheat-producing regions using MOD13A1 data and a deep learning model which incorporates an Improved Gray Wolf Optimization (IGWO) algorithm. …”
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A systematic review on the integration of explainable artificial intelligence in intrusion detection systems to enhancing transparency and interpretability in cybersecurity by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Furthermore, the review highlights critical gaps in standardization and scalability, emphasizing the need for hybrid models and real-time explainability. The paper concludes with recommendations for future research directions, suggesting improvements in XAI techniques tailored for IDS, standardized evaluation metrics, and ethical frameworks prioritizing security and transparency. …”
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Enhancing Extreme Learning Machine Robustness via Residual-Variance-Aware Dynamic Weighting and Broyden–Fletcher–Goldfarb–Shanno Optimization: Application to Metro Crowd Flow Predi... by Lihui Wang, Jianguang Xie

“…Aiming at the robustness problem of the extreme learning machine (ELM) in noisy and nonuniform data scenarios, this paper proposes an improved algorithm (BFGS-URWELM) that integrates uniform residual weighting and Broyden–Fletcher–Goldfarb–Shanno (BFGS) quasi-Newton optimization. …”
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