Stress-Responsive Spatial Voronoi Optimization for Lightweight Architectural Shell Structures by Haining Zhou, Xinyu Shi, Da Wan, Weijiu Cui, Kang Bi, Wenxuan Zhao, Rong Jiao, Hiroatsu Fukuda

“…Finite Element Analysis (FEA) demonstrates that the optimized Voronoi-driven GPS achieves notable improvements, revealing up to 79.7% material volume reduction and significant improvement in structural efficiency, achieving a stiffness-to-weight ratio (SWR) exceeding 2200 in optimized configurations. …”
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Coordinated Optimization Method for Distributed Energy Storage and Dynamic Reconfiguration to Enhance the Economy and Reliability of Distribution Network by Caihong Zhao, Qing Duan, Junda Lu, Haoqing Wang, Guanglin Sha, Jiaoxin Jia, Qi Zhou

“…First, a scenario-generation method is developed based on Latin hypercube sampling and Kantorovich distance synchronous back-substitution reduction is used to obtain the typical scenario of wind and solar output. …”
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Open-Circuit Fault Diagnosis Method of Energy Storage Converter Based on MFCC Feature Set by Bin YU, Xingrong SONG, Ting ZHOU, Linbo LUO, Hui LI, Liang CHE

“…Then, through kernel principal component analysis (KPCA), the dimension reduction screening of nonlinear fault features under charge and discharge conditions is realized. …”
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Unsupervised detection of high-frequency oscillations in intracranial electroencephalogram: promoting a valuable automated diagnostic tool for epilepsy by Wenjing Chen, Tongzhou Kang, Md Belal Bin Heyat, Jamal E. Fatima, Yuanning Xu, Dakun Lai

“…The CVAE model is trained for dimensionality reduction and feature reconstruction, followed by clustering of the reconstructed maps using the K-means algorithm for automated HFOs detection.ResultsEvaluation of the proposed unsupervised method on clinical iEEG data demonstrates its superior performance compared to traditional supervised models. …”
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Recurrent Neural-Based Vehicle Demand Forecasting and Relocation Optimization for Car-Sharing System: A Real Use Case in Thailand by Peerapon Vateekul, Panyawut Sri-iesaranusorn, Pawit Aiemvaravutigul, Adsadawut Chanakitkarnchok, Kultida Rojviboonchai

“…It achieved a 3% opportunity loss reduction and 3% less relocation trips, reducing human effort by 17 man-hours/week.…”
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Early Detection of Surface Mildew in Maize Kernels Using Machine Vision Coupled with Improved YOLOv5 Deep Learning Model by Yu Xia, Ao Shen, Tianci Che, Wenbo Liu, Jie Kang, Wei Tang

“…This resulted in a notable reduction in the model parameters and calculation amount while simultaneously enhancing model precision. …”
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Battery Sizing Method for Microgrids—A Colombian Application Case by Andres Felipe Zamora-Muñoz, Martha Lucia Orozco-Gutierrez, Dany Mauricio Lopez-Santiago, Jhoan Alejandro Montenegro-Oviedo, Carlos Andres Ramos-Paja

“…Mixed integer linear programming (MILP) is used as optimization algorithm to size BESS, which is applied to an isolated community in Colombia located at Isla Múcura. …”
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Enhanced Defect Detection in Additive Manufacturing via Virtual Polarization Filtering and Deep Learning Optimization by Xu Su, Xing Peng, Xingyu Zhou, Hongbing Cao, Chong Shan, Shiqing Li, Shuo Qiao, Feng Shi

“…Experiments show a 40.3% reduction in loss, a 10.8% improvement in precision, a 10.3% improvement in recall, and a 13.7% improvement in mAP compared to the original YOLO V5 model. …”
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Performance of M-QAM MIMO PNC Based on MRC and ZR Techniques by Alaa A. Yassin, Ebtihal H. G. Yousif, Rashid A. Saeed, Hashim Elshafie, Abdullah Alenizi, Hesham Alhumyani

“…The system model is based on denoise-and-forward (DNF) relaying along with the Latin Square (LS) mapping algorithm at the relay node and square M-ary Quadrature Amplitude Modulation (M-QAM) at all nodes. …”
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Torque capability enhancement of commercial interior permanent magnet motors using t-shaped notching and merged barrier rotor topology by H.N. Lin, P. Seangwong, N. Fernando, A. Siritaratiwat, P. Khunkitti

“…The optimized motor achieves a 3.86 % increase in back-EMF, a 6.2 % reduction in total harmonic distortion, and a 6.58 % decrease in cogging torque under no-load conditions. …”
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Classification of Chicken Carcass Breast Blood-Related Defects Using Hyperspectral Imaging Combined with Convolutional Neural Networks by Liukui Duan, Juanfang Bao, Hao Yang, Liuqian Gao, Xu Zhang, Shengjie Li, Huihui Wang

“…To process hyperspectral data, the Improved Firefly Band Selection Algorithm was constructed with the 1-D CNN CBD classification model as the objective function, achieving a reduction in the dimensionality of hyperspectral data. …”
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Calculation Model of Multi-roll Straightening Process Based on Bilinear Hardening and Power Hardening by ZHU Xiaoyu, CHENG Zixing, WANG Xiaogang, HAN Peisheng

“…The results show that with increasing reduction, the error between hardened and ideal models increases. …”
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The effect of using Naive Bayes to detect spam email by Sun Zehui

“…This paper focuses on the spam detection method based on the plain Bayesian algorithm. The plain Bayesian algorithm is particularly suitable for spam detection due to its high detection accuracy and its wide application in text classification tasks. …”
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New State Identification Method for Rotating Machinery under Variable Load Conditions Based on Hybrid Entropy Features and Joint Distribution Adaptation by Xiaoming Xue, Nan Zhang, Suqun Cao, Wei Jiang, Jianzhong Zhou, Liyan Liu

“…As for the training and testing set under different load conditions, all data was mapped into a reproducing space by joint distribution adaptation to reduce the distribution discrepancies between datasets, where the pseudolabels of the testing set and the final diagnostic results were obtained by the k-nearest neighbor algorithm. Finally, five cases with the training and testing set under variable load conditions were used to demonstrate the performance of the proposed method, and comparisons with some other diagnosis models combined with the same features and other dimensionality reduction methods were also discussed. …”
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Dynamic Coal Flow-Based Energy Consumption Optimization of Scraper Conveyor by Qi Lu, Yonghao Chen, Xiangang Cao, Tao Xie, Qinghua Mao, Jiewu Leng

“…The multi-objective optimization model for energy consumption is solved using the NSGA-II-ARSBX algorithm, yielding a 33.7% reduction in energy consumption, while the lump coal area is reduced by 27.7%, indicating a trade-off between energy efficiency and coal fragmentation. …”
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Smart Packet Delivery in Mobile Underwater Sensors Networks (M-CTSP) by Abdul Khan, Miguel-Angel Luque-Nieto, Ali Akbar Siddique

“…This results in a 40% rise in energy use reduction, 15% improvement in packet delivery with a 30% increase in network lifetime when compared to normal clustering-based protocols: LEACH and EECBP-FOA. …”
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Collaborative Optimization of Model Pruning and Knowledge Distillation for Efficient and Lightweight Multi-Behavior Recognition in Piglets by Yizhi Luo, Kai Lin, Zixuan Xiao, Yuankai Chen, Chen Yang, Deqin Xiao

“…In the first stage, the LAMP pruning algorithm is used to prune and optimize redundant channels, resulting in the lightweight YOLOv8-Prune. …”
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Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection by Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Oscal Tzyh-Chiang Chen, Oscal Tzyh-Chiang Chen

“…These findings demonstrate notable improvements in accuracy and complexity reduction, making it suitable for detecting strawberry diseases in diverse conditions.…”
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Energy Efficiency Optimization Design for Cycle Position Servo PMSM Based on Operating Energy Consumption Model by Bin Yuan, Hui Li, Xuewei Xiang, Hao Zhou

“…The optimal design scheme after global optimization is quickly solved by the evolutionary algorithm. Finally, the effectiveness of the proposed method is verified through simulation and prototype experiments.…”
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Multi-Hazard Vibration Control of Transmission Infrastructure: A Pounding Tuned Mass Damper Approach with Lifelong Reliability Analysis by Zhuoqun Zhang, Lizhong Qi, Jingguo Rong, Yaping Zhang, Peijie Li, Ziguang Jia

“…Specifically, the PTMD reduced the vibration reduction ratio by 10% to 30% under wind loads and by 20% to 80% under seismic actions, with more pronounced effects at higher wind speeds and peak ground accelerations (PGAs). …”
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