Prediction and Impact Analysis of Soil Nitrogen and Salinity Under Reclaimed Water Irrigation: A Case Study by Zeyu Liu, Kai Fang, Xiaoqin Sun, Yandong Wang, Zhuo Tian, Jing Liu, Liying Bai, Qilin He

“…Understanding these impacts is crucial for developing sustainable practices that optimize resource use while ensuring the long-term health and viability of agricultural and agroforestry systems. …”
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Optimization of agricultural planting structure in major grain-producing areas based on supply and demand and water resources: A case study of Hebei Province by Wenxue Xia, Jiankang Dong, Bing Zhang, Jingyan Han

“…Given the rigid constraints on water resources, addressing how to optimize crop planting structures in Hebei Province while considering multiple objectives remains a critical challenge. …”
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Toward sustainable machining of hardened SKD11: Machine learning-based evaluation and optimization of surface roughness, tool wear, and CO2 emissions by Van-Canh Nguyen, Dung Hoang Tien, Van-Hung Pham, Thinh-Viet Nguyen, Thuy-Duong Nguyen

“…Consequently, the multi-objective optimization problem focused on minimizing Ra and CE, implemented through the NSGA-III algorithm. …”
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Byzantine fault-tolerant distributed access control mechanism for the Internet of things by CHAI Rong, AI Liping, YANG Ningyu, LIANG Chengchao

“…In the proposed algorithm, the main cluster nodes execute an improved Paxos algorithm, while the sub-cluster nodes execute the Hotstuff algorithm. …”
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Photovoltaic Module Fault Detection Technology Based on Remote Sensing Technology and Deeplabv3+ Model by Xiaowei Xu, Mingxian Liu, Yongjie Nie, Ke Wang, Wenhua Xu

“…The research results indicated that bilateral filtering and gamma filtering algorithms showed superior performance in testing, with the highest indicator evaluation results. …”
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Optimized multi-unit coordinated scheduling based on improved IGDT: Low-carbon scheduling research for the electric-heat-oxygen integrated energy system by Zhe Yin, Zhifan Zhang, Ruijin Zhu, Yifan Zhang, Jiyuan Wang, Wenxing Tang

“…In contrast, under the RSS, total cost decreased by 19.98 %, while carbon trading cost significantly dropped by 321.90 %.…”
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3E multi-objective optimization of Organic Rankine Cycle configurations for a geothermal off-grid system: Power, DHW, and hydrogen production by A. Mokhtari, M. Jalalvand

“…The optimization process utilized the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), aiming to maximize energy and exergy efficiency, hydrogen production, and minimize levelized costs of electricity (LCOE) and hydrogen (LCOH), while ensuring that electrical and DHW demands are met. …”
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An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance by Abhijeet Das

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Machine Learning Inspired Design of Complex-Shaped GaN Subwavelength Grating Reflectors by Onoriode N. Ogidi-Ekoko, Wen Liang, Haotian Xue, Nelson Tansu

“…We present the machine learning inspired design of two types of GaN zero contrast subwavelength gratings (SWGs): a polynomial-shaped grating and, for reference, a conventional rectangular grating, using the differential evolution algorithm to optimize the designs for high broadband reflectivity and separately for large fabrication tolerance. …”
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Efficient Real-Time Cost Management in Renewable Energy-Powered Microgrid with Integrated Electric Vehicle Charging/Discharging Control by Swati Sharma, Ikbal Ali

“…Our multi-level control strategy ensures both immediate response to disturbances and long-term optimization, maintaining microgrid stability. Through meticulous real-time monitoring and control, our hybrid PSO-GWO algorithm delivers superior performance, slashing costs by $152.47 for medium scale microgrid while reducing execution time by 0.81 seconds as compared to other metaheuristic algorithms. …”
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Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction by Jingjing Chen, Dan Zhang, Chengxiu Zhu, Lin Lin, Kejun Ye, Ying Hua, Mengjia Peng

“…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”
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Embedding Moving Baseline RTK for High-Precision Spatiotemporal Synchronization in Virtual Coupling Applications by Susu Huang, Baigen Cai, Debiao Lu, Yang Zhao, Miao Zhang, Linyu Shang

“…To further enhance synchronization performance, a decentralized distributed synchronization algorithm was introduced, reducing communication overhead and improving real-time responsiveness. …”
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Optimal Dispatch of Multi-Coupling Systems Considering Molten Salt Thermal Energy Storage Retrofit and Cost Allocation Under Rapid Load Variations by Niancheng Zhou, Zhenyu Xu, Yuan Chi, Yao Zou, Fei Xu, Xuhui Dai

“…The results demonstrate that the proposed flexibility retrofit scheme and optimization algorithm enable a more coordinated and economically efficient dispatch strategy.…”
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An adaptive search mechanism with convolutional learning networks for online social media text summarization and classification model by Reema G. AL-anazi, Muhammad Swaileh A. Alzaidi, Majdy M. Eltahir, Hassan Alkhiri, Samah Hazzaa Alajmani, Abdulbasit A. Darem, Mohammed Alshahrani, Nawaf Alhebaishi

“…Furthermore, the moth search algorithm (MSA)-based hyperparameter selection process is performed to optimize the feature extraction results of the BERT model. …”
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Enhanced Superpixel-Guided ResNet Framework with Optimized Deep-Weighted Averaging-Based Feature Fusion for Lung Cancer Detection in Histopathological Images by Karthikeyan Shanmugam, Harikumar Rajaguru

“…<b>Background/Objectives:</b> Lung cancer is a leading cause of cancer-related mortalities, with early diagnosis crucial for survival. While biopsy is the gold standard, manual histopathological analysis is time-consuming. …”
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Research on energy storage planning methods for distributed renewable energy integrated rural power distribution networks by Haoshuai Jia, Renqing Feng, Hai Jiang, Chao Gao, Yue Zhao, Rui Zhang, Ziyi Xuan

“…The optimal locations and capacities of energy storage systems are determined using YALMIP toolbox and the beetle swarm optimization (BSO) algorithm, and the proposed method is validated on a modified IEEE 33-bus system. …”
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Sustainable Self-Training Pig Detection System with Augmented Single Labeled Target Data for Solving Domain Shift Problem by Junhee Lee, Heechan Chae, Seungwook Son, Jongwoong Seo, Yooil Suh, Jonguk Lee, Yongwha Chung, Daihee Park

“…To address the degradation issue, this study proposes a self-training-based domain adaptation method that utilizes a single label on target (SLOT) sample from the target domain, a genetic algorithm (GA)-based data augmentation search (DAS) designed explicitly for SLOT data to optimize the augmentation parameters, and a super-low-threshold strategy to include low-confidence-scored pseudo-labels during self-training. …”
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Optimizing wireless dynamic charging infrastructure for electric vehicles: A predictive and adaptive framework leveraging decision-dependent uncertainties and renewable energy util... by Yanjia Wang, Xianlong Li, Mohannad Alhazmi, Da Xie, Xitian Wang

“…The rapid adoption of electric vehicles (EVs) is transforming modern transportation systems while presenting challenges related to charging infrastructure, grid integration, and renewable energy utilization. …”
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O2O-PLB: A One-to-One-Based Optimizer With Priority and Load Balancing Mechanism for Resource Allocation in Fog-Cloud Environments by V. C. Bharathi, S. Syed Abuthahir, Monelli Ayyavaraiah, G. Arunkumar, Usama Abdurrahman, Sardar Asad Ali Biabani

“…Based on the experimental results, the O2O-PLB algorithm significantly outperforms the benchmark algorithms across essential performance metrics at varying task loads. …”
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Strategic Power Flow-Stackelberg Dynamics for Minimizing Transmission Losses in Peer-to-Peer Trading by K. V. Biji Varghese, Dattatraya N. Gaonkar

“…Seller microgrids initiate the game by proposing trading prices that account for transmission losses and the amount of energy to be traded, while the buyer microgrids respond by optimizing their trading strategies based on these proposed prices. …”
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