Mask-Space Optimized Transformer for Semantic Segmentation of Lithium Battery Surface Defect Images by Daozong Sun, Jiasi Chen, Peiwen Wu, Yucheng Pan, Hongsheng Zhong, Zihao Deng, Xiuyun Xue

“…Experimental results demonstrate that our method outperforms other state-of-the-art methods in terms of mean Intersection over Union (mIoU). …”
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Optimization study of a multi-heat source coupled bathing hot water system by Yunxin Huang, Jinghui Luo, Yongchang Zhou, Xiaoxuan Wu, Nianchen Wang, Shicheng Xin, Changjian Zhang

“…Compared to conventional full-factor orthogonal methods, the Taguchi approach reduced the number of orthogonal experiments while effectively predicting the optimal parameter combinations, thereby providing a more efficient, stable, and economical design solution for the coupled system. …”
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Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation by R. T. N. Cardoso, R. H. C. Takahashi, F. R. B. Cruz

“…Instead of using the expected values of the objective function, the randomness nature of the decision variables is kept along the process, while Pareto fronts weighted by all quantiles of the objective function are determined. …”
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Autonomous deployment and energy efficiency optimization strategy of UAV based on deep reinforcement learning by Yi ZHOU, Xiaoyong MA, Fuxiao GAO, Wei LI, Nan CHENG, Ning LU

“…Utilizing a UAV to build aerial mobile small cell can provide more flexible and efficient access services for ground terminal users.Constrained by the coverage and limited energy of the UAV,it is necessary to study how to build a fast,efficient and energy-saving air-ground collaborative network.To deal with complex dynamic scenarios,the UAV needs to deploy an optimal coverage position,and meanwhile reduce both path loss and energy consumption in the deployment process.Based on the deep reinforcement learning,a strategy of autonomous UAV deployment and efficiency optimization was proposed.The coverage state set of UAV was established,and the energy efficiency was used as a reward function.Depth neural network and Q-learning were used to guide UAV to make autonomous decision and deploy the optimal position.The simulation results show that the deployment time of the proposed method can be effectively reduced by 60%,while the energy consumption can be reduced by 10%~20%.…”
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Autonomous deployment and energy efficiency optimization strategy of UAV based on deep reinforcement learning by Yi ZHOU, Xiaoyong MA, Fuxiao GAO, Wei LI, Nan CHENG, Ning LU

“…Utilizing a UAV to build aerial mobile small cell can provide more flexible and efficient access services for ground terminal users.Constrained by the coverage and limited energy of the UAV,it is necessary to study how to build a fast,efficient and energy-saving air-ground collaborative network.To deal with complex dynamic scenarios,the UAV needs to deploy an optimal coverage position,and meanwhile reduce both path loss and energy consumption in the deployment process.Based on the deep reinforcement learning,a strategy of autonomous UAV deployment and efficiency optimization was proposed.The coverage state set of UAV was established,and the energy efficiency was used as a reward function.Depth neural network and Q-learning were used to guide UAV to make autonomous decision and deploy the optimal position.The simulation results show that the deployment time of the proposed method can be effectively reduced by 60%,while the energy consumption can be reduced by 10%~20%.…”
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PRODUTION OF THE MICROBIAL GELLAN BY SPHINGOMONAS PAUCIMOBILIS BACTERIA. 1. OPTIMIZATION OF THE PHYSICAL CULTURAL CONDITIONS by N. B Jafar, M. M. Ahmad

“…The purpose of this study was to find the optimal physical cultural condition to produce the microbial exopolysaccharide, gellan, by the bacteria <em>Sphingomonas paucimobilis</em> in laboratory media using batch culture method. …”
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REDUCTION DESIGN AND OPTIMIZATION ANALYSIS FOR VEHICLE BODY BASED ON TAILOR ROLLED BLANK TECHNOLOGY by CHENG JiangHong, WANG LiJuan, CHEN ZongYu, XU MingTao, FANG ZheLin

“…Combining with the design method of body collision force transmission path and load flow reasonable distribution,optimization design and analysis of a SUV on critical parts structure was carried out based on the TRB technology,which have great effects on the vehicle body safety in side collision. …”
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Optimizing UAV Hyperspectral Imaging for Urban Tree Chlorophyll and Leaf Area Index Retrieval by Shanshan Wei, Tiangang Yin, Bo Yuan, Kim Hwa Lim, Soo Chin Liew, Andrew J. Whittle

“…Uncrewed aerial vehicle (UAV) based hyperspectral imaging offers a flexible method for monitoring urban trees. However, its effect on estimating biochemical and biophysical parameters is still unknown. …”
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Optimizing irrigation scheduling for maize based on soil moisture threshold and water consumption intensity by LIANG Xue, XUE Bing, LI Fangfang, CUI Yirui, MA Yangtao, WEI Changzhou, JIANG Yan

“…The water use efficiency of both varieties was the highest when total irrigation amount was 660 cm. The optimal irrigation scheduling for the DH618 variety was 51-70 mm in each irrigation with the total irrigation amount being 649.5 mm, while for the XY335 variety, the optimal irrigation was 39-67.5 mm in each irrigation with the total irrigation amount being 629.5 mm. …”
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Design and optimization of co-production process of natural gas liquefaction and BOG helium extraction by Rongge XIAO, Linnan PANG, Yalong LIU

“…Therefore, for the purpose of energy saving, consumption reduction and full utilization of the cold energy, this study proposes an innovative co-production process combining nitrogen cyclic expansion refrigeration based natural gas liquefaction and BOG cryogenic helium extraction, This study uses the HYSYS software to simulate the nitrogen cyclic expansion refrigeration based natural gas liquefaction, the BOG cryogenic helium extraction and the co-production process, and analyzes the key parameters relating to the comprehensive energy consumption and the crude helium concentration. While maintaining the crude helium concentration at 76.8%, the co-production system, with the goal of minimizing the comprehensive energy consumption, was optimized by applying the response surface method and the genetic algorithm into the process. …”
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Optimizing Reservoir Separability in Liquid State Machines for Spatio-Temporal Classification in Neuromorphic Hardware by Oscar I. Alvarez-Canchila, Andres Espinal, Alberto Patiño-Saucedo, Horacio Rostro-Gonzalez

“…By leveraging PSO, our method fine-tunes reservoir parameters, neuron dynamics, and connectivity patterns, maximizing separability while aligning with the resource constraints typical of neuromorphic hardware. …”
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Optimizing energy and load management in island microgrids for enhancing resilience against resource interruptions by Majid Hosseina, Mahmoud Samiei Moghaddam, Amir Hassannia

“…The proposed method offers a scalable, real-time implementable solution for microgrid operators seeking to enhance resilience against renewable energy intermittency and optimize energy utilization. …”
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Energy-Saving Light Source Spectrum Optimization by Considering Object&#x0027;s Reflectance by Jingjing Zhang, Run Hu, Bin Xie, Xingjian Yu, Xiaobing Luo, Zhihua Yu, Lijun Zhang, Hong Wang, Xing Jin

“…In this study, a spectrum optimization method by means of a genetic algorithm to minimize the light energy along the absorbed wavelengths while maintaining the light quality of the light source was proposed. …”
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On the Design of Near-Optimal Generalized Block-Based Spatial Modulation With Low Detection Complexity by Yen-Ming Chen, Wei-Lun Lin, Heng Lee, Tsung-Lin Chen

“…Building on this idea, this paper first proposes a near-optimal codebook search method based on three-dimensional (3-D) mapping, applicable to both fast and slow Rayleigh fading channels. …”
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Investigation of Floating Offshore Wind Farm Layout Optimization Considering Mooring Line Constraints by Haiying Sun, Mingdan Li, Tianhui Fan, Chenzhi Cai

“…By defining constraint areas, the optimization process ensures that FOWTs are optimally positioned while avoiding interference and collisions. …”
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Topological optimization design of the front coupling rod of prosthetic knee joint based on Inspire by Xiaofei Su, Yan Zhu, Hui Dong, Jingyu Yang, Lu Wang, Zhengyu Zhao

“…This optimization process is aimed at achieving mass reduction of the prosthetic motion mechanism while improving its structural performance. …”
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Quality Measurement and Optimization Prediction of Urban Waterfront Fitness Space Based on Behavior Simulation by Chunxia YANG, Ruoyao MIN

“…Based on the multi-agent behavior simulation technology and waterfront fitness quality assessment system, this research conducts a quality measurement of nine typical waterfront public spaces along the Huangpu River, and explores the possibility of further optimizing the spatial quality of the Minsheng Wharf area, aiming to provide a systematic method for quality assessment and optimization prediction. …”
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CHARACTERIZATION OF ISOBATHS IN THE CENOMANIAN RESERVOIR OF THE MUANDA FIELD – IMPLICATIONS FOR OPTIMAL OIL RESOURCE MANAGEMENT by Marlin Agolo Monza, Franck Tondozi Keto, Raphael Matamba Jibikila, Yves Bolokole Mpehenzale, Osée Mayinga Mayinga

“…The study of isobaths characterization in the Cenomanian reservoir of the Muanda field focuses on optimizing petroleum resource management. Using geostatistical techniques and numerical analysis methods, the isobaths of the K, J, I and H layers were mapped. …”
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Setting Priorities for Optimizing Vascular Access Decision Making--An International Survey of Patients and Clinicians. by Sabine N van der Veer, Maria C Haller, Carina A C M Pittens, Jacqueline Broerse, Clare Castledine, Maurizio Gallieni, Nicholas Inston, Anna Marti Monros, Niels Peek, Wim van Biesen

“…Patients generally assigned higher priority to decisions regarding managing adverse effects of arteriovenous access and patient involvement in care, while clinicians more often prioritized decisions around sustaining patients' access options, technical aspects of access creation, and optimizing fistula maturation and patency.…”
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Bayesian optimized deep learning and ensemble classification approach for multiclass plant disease identification by Silpa Padmanabhuni, Pradeepini Gera

“…Abstract Early detection of plant diseases is crucial in smart agriculture to prevent significant crop losses and reduce reliance on chemical pesticides. While many existing methods leverage customized neural network architectures or transfer learning, they often suffer from limited accuracy, model interpretability, and dataset imbalance. …”
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