Personalized client-edge-cloud hierarchical federated learning in mobile edge computing by Chunmei Ma, Xiangqian Li, Baogui Huang, Guangshun Li, Fengyin Li

“…Abstract Mobile edge computing aims to deploy mobile applications at the edge of wireless networks. …”
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Optimising complexity and learning for photonic reservoir computing with gain-controlled multimode fibres by Giulia Marcucci, Luana Olivieri, Juan Sebastian Totero Gongora

“…We discuss the physical origin of the optimal regions by analysing the information theory and linear algebra properties of the readout matrix, unveiling a deep connection between the computational performance of the system and the Kolmogorov algorithmic complexity of the nonlinear features generated by the reservoir. …”
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Computational modeling of visual salience alteration and its application to eye-movement data by Yoshihisa Fujita, Toshiya Murai, Jun Miyata, Jun Miyata

“…It handles diverse image-derived features, as seen in functional approximation models, while implementing center-surround competition—the core process of salience computation—via an artificial neural network, akin to neurobiological models. …”
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The utility of preoperative computed tomography-guided screw marking in thoracic spine surgery by Christopher Marvin Jesse, Aatharshan Kannathasan, Ralph T. Schär, Johannes Goldberg, Andreas Raabe, Jan Gralla, Johannes Kaesmacher, Tomas Dobrocky, Eike Immo Piechowiak

“…Data included clinical features, radiological parameters, and complications. …”
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IoT‐Based Elderly Health Monitoring System Using Firebase Cloud Computing by Adhan Efendi, Muhammad Imam Ammarullah, Indra Griha Tofik Isa, Meli Puspita Sari, Jasmine Nurul Izza, Yohanes Sinung Nugroho, Hamid Nasrullah, Denny Alfian

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Study of kinetic performance effect on wheel and rail wear using computer simulation by Nikolay V. Limarenko, Victor P. Zharov, Yury V Panov, Boris G Shapoval

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Review of Brain Computer Interface Technology in the Treatment of Motor Dysfunction after Stroke by Yulian ZHU, Sijie LIANG

“…The work flow of BCI in treating stroke patients could be roughly divided into five steps: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and control interface. …”
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A novel approach to skin disease segmentation using a visual selective state spatial model with integrated spatial constraints by Yu Bai, Hai Zhou, Hongjie Zhu, Shimin Wen, Binbin Hu, Haotian Li, Huazhang Wang, Daji Ergu, Fangyao Liu

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Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…The architecture achieves 98% classification accuracy, outperforming leading models like VGG-19, DarkNet-19, and ResNet-50. Moreover, the computational time per run (40–90 s) is significantly lower than these models, which use higher learnable parameters (5.7 million). …”
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Research on Clustering Based PWR pin-by-pin Homogenization Parameters Compression Method by LI Tianya1, 2, LUO Qi3, YAO Dong2, HE Caiyun1, CAI Yun2, WANG Dan1, DUAN Yongqiang1, LIAO Hongkuan1, XIAO Peng2

“…In the high-fidelity numerical calculation method of reactor physics, the pin-by-pin two-step method can achieve a balance between computational accuracy and computational cost, and is currently a feasible and realistic high fidelity numerical calculation method. …”

A Parameter-Free Topological Disassembly-Guided Method for Hyperspectral Target Detection by Xiaotong Sun, Lina Zhuang, Lianru Gao, Hongmin Gao, Xu Sun, Bing Zhang

“…Traditional model-driven methods often underperform due to the mismatches between model assumptions and real data, while data-driven methods face challenges such as complex training processes, parameter tuning, and high computational costs. To address these challenges, this article adopts a model-free and parameter-free design philosophy. …”
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Lightweight Sheep Face Recognition Model Combining Grouped Convolution and Parameter Fusion by Gaochao Liu, Lijun Kang, Yongqiang Dai

“…Finally, parameter fusion optimization work was carried out for the detection head, and the construction of the Parameter Fusion Detection (PFDetect) module was achieved, which significantly reduced the number of model parameters and computational complexity. …”
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Develop Approach to Predicate Software Reliability Growth Model Parameters Based on Machine learning by anfal A. Fadhil, Asmaa’ H. AL_Bayati, Ibrahim Ahmed Saleh

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Pattern recognition method for the identification of Daiqu large yellow croaker based on computer vision by YU Xinjie, WU Xiongfei, SHEN Weiliang

“…First, 24 morphological parameters of Daiqu large yellow croaker were measured for both F₂ and F₃ generations by computer vision technology. …”
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On the minimum number of radiation field parameters to specify gas cooling and heating functions by David Robinson, Camille Avestruz, Nickolay Y. Gnedin

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Parameters Identification for Photovoltaic Module Based on an Improved Artificial Fish Swarm Algorithm by Wei Han, Hong-Hua Wang, Ling Chen

“…Different from the traditional linear model, the model of PV module has the features of nonlinearity and multiparameters. Since conventional methods are incapable of identifying the parameters of PV module, an excellent optimization algorithm is required. …”
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C-parameter version of robust bounded one-class support vector classification by Junyou Ye, Zhixia Yang, Yongxing Hu, Zheng Zhang

“…This paper presents a novel C-parameter version of bounded one-class support vector classification (C-BOCSVC) to determine a unique decision boundary. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…To simulate real-world conditions， noise was added to modal parameters. Dynamic features， such as natural frequencies and mode shapes， were used for damage detection. …”
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Learned Regularizations for Multi‐Parameter Elastic Full Waveform Inversion Using Diffusion Models by Mohammad H. Taufik, Fu Wang, Tariq Alkhalifah

“…Specifically, we first train the (unsupervised) diffusion model to understand the coupling relationship of the distribution of the elastic parameters and use the trained model in the inversion process with a negligible additional computational cost. …”
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Differential Evolution with Autonomous Selection of Mutation Strategies and Control Parameters and Its Application by Zhenyu Wang, Zijian Cao, Zhiqiang Du, Haowen Jia, Binhui Han, Feng Tian, Fuxi Liu

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