Fast Physical Random Bit Generation Based on a Broadband Chaotic Entropy Source Originated From a Filtered Feedback WRC-FPLD by Xi Tang, Guang-Qiong Xia, Can Ran, Tao Deng, Xiao-Dong Lin, Li Fan, Zi-Ye Gao, Gong-Ru Lin, Zheng-Mao Wu

“…Finally, by utilizing multi-bit post-processing method, PRBs is generated at a rate up to 240 Gbits/s, which can pass all the 15 NIST statistics tests and meet the strict criteria of the statistical bias and the serial correlation coefficient.…”
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Research on the optimal operation of a prosumer micro energy network centred on data centres by Yuanshi Zhang, Yiwu Ge, Shunjiang Wang, Weiqi Pan, Yiwen Feng, Peng Qiu

“…By considering data interaction and power sharing among multiple micro‐energy networks, the alternating direction method of multipliers algorithm is used to solve the system‐distributed optimization problem in two stages. …”
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Designing the optimal number of active branches in a multi-branch buck-boost converter by I. Kovacova, D. Kovac

“…The novelty of the proposed work consists in the development of a precise method for determining the optimal number of branches in a multi-branch buck-boost converter for a specified output power. …”
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Coverage Optimization Technology of Power Pipe Gallery Based on Improved Gray Wolf Algorithm by Cheng ZHONG, Di ZHAI, Yang LU, Xiaobo LIU, Xinru WANG, Xiongwen ZHAO

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An incremental data-driven approach for carbon emission prediction and optimization of heat treatment processes by Qian Yi, Xin Wu, Junkang Zhuo, Congbo Li, Chuanjiang Li, Huajun Cao

“…In manufacturing enterprises, the variety of heat treatment processes, insufficient data in the early stages of production, and the continuous increase of samples over time make it difficult to predict and optimize carbon emissions dynamically. Therefore, this paper proposes a low-carbon optimization method for heat treatment processes based on incremental data-driven approaches. …”
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Optimization Of Shell And Tube Cycle Recuperator Design In Organic Rankine Geothermal Power Plant by Muhammad Rifqi Dwi Septian

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A new approach for monitoring spatial and temporal changes in forest types in subtropical regions with sample migration and multi-source remote sensing data by Pengfei Zheng, Dongyang Han, Jiang Liu, Bin Xu, Panfei Fang, Shaodong Huang, Wendou Liu, Shaozhi Chen

“…We then conducted a change detection analysis using a post-classification comparison method. We propose a novel workflow for processing ground survey data to generate stable reference samples, which are then used with a transfer learning approach to construct a multi-year sample library. …”
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Integrating optimal terrain representations from public DEMs using spaceborne LiDAR by Xingang Zhang, Shanchuan Guo, Haowei Mu, Bo Yuan, Zilong Xia, Xiaoquan Pan, Hong Fang, Pengfei Tang, Peijun Du

“…Due to differences in data sources and processing methods, the accuracy of Digital Elevation Models (DEMs) varies greatly in different regions, which poses challenges for users in data selection. …”
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Generalizable Solar Irradiance Prediction for Battery Operation Optimization in IoT-Based Microgrid Environments by Ray Colucci, Imad Mahgoub

“…A shift towards renewable energy sources, particularly solar power, is underway, though these sources face challenges due to their inherent intermittency. …”
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Sunflower-based butterfly optimization algorithm with enhanced RNN for the harmonics elimination in multilevel inverter by V. Mohan, G. Krithiga, M. Thamil Alagan, V. Sathya

“…In this paper, the Sunflower based– Butterfly Optimization Algorithm (SF-BOA) is presented as a method for evaluating transcendental nonlinear equations using an MLI in a SHE approaches. …”
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Ensemble Learning-Based Wine Quality Prediction Using Optimized Feature Selection and XGBoost by Sonam Tyagi, Ishwari Singh Rajput, Bhawnesh Kumar, Harendra Singh Negi

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Optimizing surfactin yield in Bacillus velezensis BN to enhance biocontrol efficacy and rhizosphere colonization by Tongshu Liu, Yanli Zheng, Litao Wang, Xu Wang, Haiyan Wang, Yongqiang Tian

“…However, the practical application of surfactin is currently limited by its low yield in natural strains.MethodsThis study aimed to optimize the culture conditions for Bacillus velezensis BN, a strain with exceptional biocontrol properties, to enhance its surfactin yield. …”
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Federated Learning for Fall Detection With Multimodal Residual Fusion and Pareto-Optimized Client Selection by Bao-Quan Wang, Fan Yang, Yi Wang, Fan Zhao, Yun-Fei Han, Yu-Peng Ma

“…Secondly, to address variations in data modalities, distributions, and quality across clients, by considering all client factors rather than treating clients as independent, five innovative evaluation metrics are designed to assess the convergence and generalization performance of the local models. Finally, a Pareto-optimized client selection method is introduced to efficiently select reliable clients for global aggregation, ensuring both the stability and robustness of the global model. …”
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Robust Optimization for Microgrid Management With Compensator, EV, Storage, Demand Response, and Renewable Integration by Hamid Hematian, Mohamad Tolou Askari, Meysam Amir Ahmadi, Mahmood Sameemoqadam, Majid Babaei Nik

“…The model primarily addresses challenges arising from the integration of power electronics-based generation units, the unpredictable nature of demand in microgrids, and the integration of small-scale renewable energy sources. The proposed model includes detailed formulations for MG energy management, covering optimal battery usage, efficient EV energy management, compensator usage, and strategic dispatching of DG resources. …”
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Comparative analysis and application of rockburst prediction model based on secretary bird optimization algorithm by Tengjie Yang, Tengjie Yang, Xinqiang Gao, Xinqiang Gao, Lichuan Wang, Yongqing Xue, Haobo Fan, Zhengguo Zhu, Zhengguo Zhu, Jingbo Zhao, Beiyi Dong, Beiyi Dong

“…The reliability of the proposed feature selection, model optimization, and data balancing methods was verified by comparing the optimal model with other methods. …”
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METHODS OF ASSESSMENT OF THE RELATIVE BIOLOGICAL EFFECTIVENESS OF NEUTRONS IN NEUTRON THERAPY by V. A. Lisin

“…Research is conducted for neutron sources differing in the method of producing particles, energy and energy spectrum. …”
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Dam Risk Identification Method Based on EAHP-EWM-TOPSIS by ZHAN Mingqiang, CHEN Bo, TIAN Jufei, HU Zelin, PAN Xinmei

“…To address the uncertainty and fuzziness of dam risk indicators, this paper proposes a dam risk identification model based on the EAHP-EWM-TOPSIS game combination model.This is to determine the subjective and objective weights of risk evaluation indicators by extension analytic hierarchy process and entropy weight method respectively.Meanwhile, the game theory is introduced to determine the optimal combination weight, and a weighted standardized decision matrix is constructed.Then, the TOPSIS method is employed to calculate the relative proximity between each risk factor and the ideal solution as the basis for ranking risk factors to identify the main risk sources of dams.The engineering example shows that the main risk factors affecting the safe service of the dams are dam seepage and cross-bank seepage, with the relative proximity of 0.712 7 and 0.855 2 respectively.The identified main risk factors are consistent with the actual engineering situation, which verifies the model effectiveness.The differentiation degree of this model is more obvious than other models, providing an effective basis for dam reinforcement and risk management.…”
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Study on the Evaluation Method of Green Construction Based on Ontology and BIM by Zhao Xu, Xuerong Wang, Wentao Zhou, Jingfeng Yuan

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Methods for Calculating the Resistance of Grounding Devices with Backfilling Special Compositions by Drako Mikhail, Pavlovich Ivan, Baraishuk Siarhei

“…The study proposes a calculation method and shows a fairly good convergence of the results with experimental data, and defines a further direction in optimizing calculation methods GDs.…”
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A Trusted Federated Learning Method Based on Consortium Blockchain by Xiaojun Yin, Xijun Wu, Xinming Zhang

“…Federated learning (FL) has gained significant attention in distributed machine learning due to its ability to protect data privacy while enabling model training across decentralized data sources. However, traditional FL methods face challenges in ensuring trust, security, and efficiency, particularly in heterogeneous environments with varying computational capacities. …”
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