A novel anthropometric method to accurately evaluate tissue deformation by Chongyang Ye, Xiaolu Li, Haiyan Song, Yu Shi, Ruixin Liang, Jun Zhang, Ka Po Lee, Zhaolong Chen, Beibei Zhou, Raymond Kai-Yu Tong, Kit-Lun Yick, Sun-Pui Ng, Joanne Yip

“…IntroductionBiomechanical imaging through body scanning can provide a more comprehensive understanding of the soft tissue deformation exerted by compression sportswear, which is crucial in sports science research and functional sportswear design. …”
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Extracting Knowledge From Scientific Texts on Patient-Derived Cancer Models Using Large Language Models: Algorithm Development and Validation Study by Jiarui Yao, Zinaida Perova, Tushar Mandloi, Elizabeth Lewis, Helen Parkinson, Guergana Savova

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Two Symbol Expansion Methods and Their Application to Reversible Data Hiding by Hyoung Joong Kim, Changhee Kang, Sang-Ug Kang

“…Second, a symbol domain created by concatenating two adjacent pixels was used. Both algorithms exploit the similarity between the neighboring pixels in an image, and the experimental results demonstrate an average PSNR of <inline-formula> <tex-math notation="LaTeX">$64.1dB$ </tex-math></inline-formula>, which is 11.6% higher compared to the original histogram shifting method. …”
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Artificial intelligence algorithms for the diagnosis of signs of diabetic retinopathy, diabetic macular edema, age-related macular degeneration, vitreomacular interface abnormaliti... by E.A. Katalevskaya, A.Yu. Sizov, M.I. Tyurikov, Yu.V. Vladimirova

“…For fundus images analysis algorithms accuracy, sensitivity, specificity, AUROC were calculated for the following structures: microaneurysms, intraretinal hemorrhages, hard exudates, soft exudates, retinal and optic disc neovascularization, preretinal hemorrhages, epiretinal fibrosis, laser coagulates. …”
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Discrete Multi-Objective Grey Wolf Algorithm Applied to Dynamic Distributed Flexible Job Shop Scheduling Problem with Variable Processing Times by Jiapeng Chen, Chun Wang, Binzi Xu, Sheng Liu

“…Based on the parameter sensitivity study and a comparison with four algorithms, the algorithm’s stability and effectiveness in both static and dynamic environments are demonstrated. …”
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Review of algebraic attacks on stream ciphers by ZHANG Long1, WU Wen-ling2, WEN Qiao-yan1

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Evaluation method of e-government audit information based on big data analysis by Jingui He, Hansi Ya

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Research on somatic interactive exhibition design of lacquer artwork based on multi-source data analysis by Ke Ni

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Comparative Evaluation of Reinforcement Learning Algorithms for Multi-Agent Unmanned Aerial Vehicle Path Planning in 2D and 3D Environments by Mirza Aqib Ali, Adnan Maqsood, Usama Athar, Hasan Raza Khanzada

“…In the second phase, we transition this comparison to a physics-based 3D simulation, incorporating realistic UAV (fixed wing) dynamics and checkpoint-based navigation. We compared five algorithms, namely, Proximal Policy Optimization (PPO), Soft Actor–Critic (SAC), Deep Deterministic Policy Gradient (DDPG), Trust Region Policy Optimization (TRPO), and Multi–Agent DDPG (MADDPG), in various scenarios. …”
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Blind recognition of primitive BCH code based on average cosine conformity by Zhaojun WU, Limin ZHANG, Zhaogen ZHONG, Yufeng LONG

“…In order to overcome the poor performance of existing algorithms for recognition of BCH code in low signal-to-noise ratio (SNR),a recognition algorithm based on average cosine conformity was proposed.Firstly,by traversing the possible values of code length and m-level primitive polynomial fields,the code length was identified by matching the initial code roots.Secondly,on the premise of recognizing the code length,the GF(2^m) domain was traversed under the m-level primitive polynomial and the primitive polynomial with the strongest error-correcting ability was the generator polynomial for the domain.Finally,the minimum common multiple corresponding to the minimum polynomial of code roots was obtained,and the BCH code generator polynomial was recognized.In checking matching,the statistic of average cosine conformity was introduced.The optimal threshold was solved based on the minimum error decision criterion and distribution of the statistic to realize the fast identification of the BCH.The simulation results show that the deduced statistical characteristics are consistent with the actual situation,and the proposed algorithm can achieve reliable recognition under SNR of 5 dB and code length of 511.Comparing with existing algorithms,the performance of the proposed algorithm is better than that of the existing soft-decision algorithm and 1~3.5 dB better than that of the hard-decision algorithms.…”
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Blind recognition of primitive BCH code based on average cosine conformity by Zhaojun WU, Limin ZHANG, Zhaogen ZHONG, Yufeng LONG

“…In order to overcome the poor performance of existing algorithms for recognition of BCH code in low signal-to-noise ratio (SNR),a recognition algorithm based on average cosine conformity was proposed.Firstly,by traversing the possible values of code length and m-level primitive polynomial fields,the code length was identified by matching the initial code roots.Secondly,on the premise of recognizing the code length,the GF(2^m) domain was traversed under the m-level primitive polynomial and the primitive polynomial with the strongest error-correcting ability was the generator polynomial for the domain.Finally,the minimum common multiple corresponding to the minimum polynomial of code roots was obtained,and the BCH code generator polynomial was recognized.In checking matching,the statistic of average cosine conformity was introduced.The optimal threshold was solved based on the minimum error decision criterion and distribution of the statistic to realize the fast identification of the BCH.The simulation results show that the deduced statistical characteristics are consistent with the actual situation,and the proposed algorithm can achieve reliable recognition under SNR of 5 dB and code length of 511.Comparing with existing algorithms,the performance of the proposed algorithm is better than that of the existing soft-decision algorithm and 1~3.5 dB better than that of the hard-decision algorithms.…”
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Prediction using inelastic constitutive artificial neural networks for impact of dead-time on inverters in wireless power transfer systems by Mr. Franklin J, Dr. Pongiannan R K

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European sovereign debt control through reinforcement learning by Tato Khundadze, Willi Semmler, Willi Semmler, Willi Semmler

“…We demonstrate that the Soft Actor-Critic algorithm provides comparable or, in some cases, better solutions to multi-objective macroeconomic optimization problems, in comparison to Nonlinear Model Predictive Control (NMPC) algorithm.…”
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Adaptive-clustered image-block hierarchical DCT hybrid digital-analog wireless transmission method by Shu TANG, Peng YANG, Xianzhong XIE, Guangyi ZHOU, Jiaqing LI, Yu ZHAO

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TANS: A Tolerance-Aware Neighborhood Search Method for Workflow Scheduling with Uncertainties in Cloud Manufacturing by Haiyan Xu, Fanhao Ma, Long Chen

“…In this paper, we consider the workflow scheduling problem with soft deadlines and fuzzy time uncertainties in cloud manufacturing environments. …”
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Complete Blood Count and Monocyte Distribution Width–Based Machine Learning Algorithms for Sepsis Detection: Multicentric Development and External Validation Study by Andrea Campagner, Luisa Agnello, Anna Carobene, Andrea Padoan, Fabio Del Ben, Massimo Locatelli, Mario Plebani, Agostino Ognibene, Maria Lorubbio, Elena De Vecchi, Andrea Cortegiani, Elisa Piva, Donatella Poz, Francesco Curcio, Federico Cabitza, Marcello Ciaccio

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Semiparametric Transformation Models with a Change Point for Interval-Censored Failure Time Data by Junyao Ren, Shishun Zhao, Dianliang Deng, Tianshu You, Hui Huang

“…Model parameters are estimated via the EM algorithm, with the change point identified through a profile likelihood approach using grid search. …”
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Improved model MASW YOLO for small target detection in UAV images based on YOLOv8 by Xianghe Meng, Fei Yuan, Dexiang Zhang

“…Abstract The present paper proposes an algorithmic model, MASW-YOLO, that improves YOLOv8n. …”
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FedDyH: A Multi-Policy with GA Optimization Framework for Dynamic Heterogeneous Federated Learning by Xuhua Zhao, Yongming Zheng, Jiaxiang Wan, Yehong Li, Donglin Zhu, Zhenyu Xu, Huijuan Lu

“…Prior to this work, few studies have explored the use of optimization algorithms for hyperparameter tuning in federated learning. …”
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Treatment-prognostication-adjustment a new therapeutic idea by analyzing T cell immune checkpoint in tumor microenvironment by algorithm: A bibliometric analysis by Shiwei Ma, Xin Wu, Zhongguang Wu, Qiangqiang Zhao

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