Building Change Detection Network Based on Multilevel Geometric Representation Optimization Using Frame Fields by Fachuan He, Hao Chen, Shuting Yang, Zhixiang Guo

“…Furthermore, a discriminative loss function is constructed through multi-task learning to optimize the polygonal structured information of the building targets. …”
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Shape Optimization of Multi-chamber Acoustical Plenums Using the BEM, Neural Networks, and the GA Method by Ying-Chun CHANG, Ho-Chih CHENG, Min-Chie CHIU, Yuan-Hung CHIEN

“…In order to speed up the assessment of optimal plenums hybridized with multiple partitioned baffles, a simplified objective function (OBJ) is established by linking the boundary element model (BEM, developed using SYSNOISE) with a polynomial neural network fit with a series of real data – input design data (baffle dimensions) and output data approximated by BEM data in advance. …”
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Explicitly Constrained Black-Box Optimization With Disconnected Feasible Domains Using Deep Generative Models by Naoki Sakamoto, Rei Sato, Kazuto Fukuchi, Jun Sakuma, Youhei Akimoto

“…To stabilize the training of the deep generative model as the decoder, we propose decomposing the decoder into sub-models, introducing skip connections to each sub-model, and training the sub-models sequentially with separate loss functions. Numerical experiments using a test problem and a topology optimization problem show that the proposed method can find feasible domains with better objective function values and higher probability than both conventional decoder-based constraint-handling methods and non-decoder-based constraint-handling methods.…”
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Optimal Configuration of ESS in Distribution Network Considering Generation of PV-Load Time Series Scenarios by Xiaolong Xiao, Mingming Shi, Fan Wu, Yukai Wei, Bo Zhao, Fang Zhang

“…A distribution network ESS configuration model is constructed with the objectives of minimizing voltage fluctuation indicator, line loss rate, and minimizing ESS investment cost. To solve the high-dimensional multi-objective functions in the model, an non-dominated sorting genetic algorithm-III (NSGA-III) was employed, and the optimal solution is selected by using the entropy weight method (EWM). …”
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Optimal Autonomous Control for Distribution Transformer Area With High Photovoltaic Penetration Based on CSBO-LSTM by Yukai Wei, Chun He, Zhuo Chen, Yinyuan Guo, Zongyuan Li

“…The model takes maximizing PV power consumption as the core objective, while considering voltage stability regulation and minimum network loss, to construct a multi-objective optimization function. …”
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Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

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GWO and WOA variable step MPPT algorithms-based PV system output power optimization by Abderrahim Zemmit, Abdelouadoud Loukriz, Khaled Belhouchet, Yahya Z. Alharthi, Muhannad Alshareef, Prabhu Paramasivam, Sherif S. M. Ghoneim

“…It also minimized power loss to 0.56 W in simulation and 0.39 W in real data, demonstrating its optimization capabilities under fluctuating conditions. …”
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MRI-Driven Alzheimer’s Disease Diagnosis Using Deep Network Fusion and Optimal Selection of Feature by Muhammad Umair Ali, Shaik Javeed Hussain, Majdi Khalid, Majed Farrash, Hassan Fareed M. Lahza, Amad Zafar

“…Alzheimer’s disease (AD) is a degenerative neurological condition characterized by cognitive decline, memory loss, and reduced everyday function, which eventually causes dementia. …”
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Feature Extraction and Classification of Power Quality Disturbances Using Optimized Tunable-Q Wavelet Transform and Incremental Support Vector Machine by Indu Sekhar Samanta, Pravat Kumar Rout, Kunjabihari Swain, Satyasis Mishra, Murthy Cherukuri

“…However, the utilization of default decomposition parameters to address nonstationary PQ signals may lead to information loss and reduced performance of the system. To avoid this limitation, an OTQWT as an enhanced technique to TQWT based on an Adaptive Particle Swarm Optimization (APSO) is suggested. …”
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Curvature-Adaptive Learning Rate Optimizer: Theoretical Insights and Empirical Evaluation on Neural Network Training by Kehelwala Dewage Gayan Maduranga

“…Furthermore, CALR demonstrates superior performance on neural network training tasks using MNIST and CIFAR-10 datasets, achieving faster convergence, lower loss, and better generalization compared to traditional optimizers. …”
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PTCDet: advanced UAV imagery target detection by Jia Su, Yichang Qin, Ze Jia, Yanli Hou

“…Ultimately, the inner focaler IoU loss (INFL) function effectively accelerates the regression of detection bounding boxes, enhancing the generalization ability and overall detection performance of the model. …”
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Exploring optimal analgesic strategies for chronic limb-threatening ischaemia: a systematic review protocol by Patrice Forget, Caitlin Sara MacLeod, John Nagy, Thanapon Ekkunagul, Jeevan Francis

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Secoisolariciresinol Diglucoside with Antioxidant Capacity from Flaxseed: A Study on Microwave-Assisted Germination Optimization by Jinling Hu, Qingyi Zhang, Yaning Li, Qiqi Zhang, Caihua Jia, Fenghong Huang, Qianchun Deng, Cuie Tang

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Production and optimization of polyglutamic acid from Bacillus licheniformis: effect of low levels of gamma radiation by Riham M. Youssef, Reham Samir, Ola M. Gomaa, Hala N. ElHifnawi, Mohamed A. Ramadan

“…In comparison to Bacillus subtilis (ATCC6633), Bacillus licheniformis showed an over 33% inclination in PGA yield under optimal conditions. FTIR spectra demonstrated that PGA functional groups were successfully unchanged after exposure to low levels of gamma radiation similar to the doses given to cancer patients under radiotherapy. …”
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Study on the peak shaving operation of cascade hydropower stations based on the plant-wide optimal curve by Fengshuo Liu, Kui Huang, Xuanyu Shi, Longqing Zhao, Yangxin Yu, Xueshan Ai, Xiang Fu

“…This study proposes a novel method to enhance RES and hydropower utilization through: 1) Establishing a plant-wide optimal output-water level-outflow relationship curve based on the output-head-flow relationship and the flow-head loss and outflow-tailwater level relationship curves for each unit; 2) Developing a short-term peak shaving model for cascaded hydropower stations that incorporates wind and PV power which defines minimum coefficient of variation of residual load as objective functions, and improving discrete differential dynamic programming successive approximation (DDDPSA) method to solve it; 3) Analyzing the peak shaving capacity of the cascade hydropower station by varying water consumption for power generation. …”
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Optimization of thermosonication conditions for critical quality parameters of watermelon juice using response surface methodology by Makaepea M. Maoto, Daniso Beswa, Afam I. O. Jideani

“…According to the findings, thermosonication could be a viable method for preserving watermelon juice, with minimal quality loss and improved functional attributes.…”
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Process Optimization and Wear Performance of Plasma-Cladding Fe5 Coatings on Rotary Tillage Blades by Jiang Zeng, Yinggang Ma, Zhichao Fang, Mingliang Wu, Zhili Wu, Mingkai Lei

“…The following parameter combination was optimized using response surface methodology (RSM): a cladding current of 144A, a cladding speed of 23 mm/s, a powder feeding rate of 23 g/min, and a cladding distance of 12 mm. …”
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Co-Simulation Model for Determination of Optimal Active Power Filters Settings in Low-Voltage Network by Mario Primorac, Zvonimir Klaić, Heidi Adrić, Matej Žnidarec

“…This paper, along with a detailed analysis of the literature, provides an overview of different views on the problems of optimal allocation of active filters and emphasizes the importance that the problem of optimal allocation of active filters should be based on the variability of the harmonic spectrum as a function of time. …”
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Analysis of Gas Pipeline Failure Factors Based on the Novel Bayesian Network by Machine Learning Optimization by Shuangqing Chen, Shun Zhou, Zhe Xu, Yongbin Liu, Bing Guan, Xiaoyu Jiang, Wencheng Li

“…Assessing the failure of urban gas pipelines is crucial for identifying risk factors and preventing gas accidents that result in economic losses and casualties. Most previous studies on gas pipeline failure assessment are based on the basic Bayesian network (BN). …”
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Cryopreservation of Noble Scallop Mimachlamys nobilis sperm: Optimization study of cooling rate and thawing temperature by Minghao Li, Zhengyi Fu, Gang Yu, Zhenhua Ma

“…Transmission electron microscopy further revealed the impact of freezing conditions on sperm, including damage to the plasma membrane, dissolution, blurring and swelling of the acrosome and mitochondria, and cristae fragmentation and loss. This study emphasizes the importance of optimizing freezing and thawing protocols and accurately controlling cryoprotectant concentration, providing key insights for the effective long-term preservation of M.nobilis sperm. …”
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