Spatiotemporal pattern analysis of land use in Jiangsu Province based on long-term time series remote sensing images by Zhendong Ji, Lingzhi Yin, Jinhong Wang

“…Principal Component Analysis (PCA) was applied to reduce feature dimensionality, and the Random Forest classification algorithm was optimized with Bayesian Optimization and Tree-structured Parzen Estimators (TPE) for improved performance. …”
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A toolkit for quantifying individual response to herbal extracts in metabolic and inflammatory stress by Soo-yeon Park, Oran Kwon, Tim van den Broek, Jildau Bouwman, Ji Yeon Kim

“…Intervention with herbal extracts (e.g., Angelica keiskei, AK, and Capsosiphon fulvescens, CF) resulted in higher health scores in the health space, indicating improved health. This research emphasizes the quantification of phenotypic changes for personalized nutrition and health optimization. …”
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CFTformer: End-to-End Cross-Frame Multi-Object Tracking With Transformer by Abdollah Amirkhani, Seyed Alireza Khoshnevis

“…To access model’s performance in AV applications, the BDD100K dataset was utilized for training and evaluation where the proposed approach achieved a 1.9% improvement in the IDF1 compared to other transformer-based models.…”
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Obstacle Avoidance Control of Autonomous Undersea Vehicle Based on DVFH+ in Ocean Current Environment by Zhongben ZHU, Jiahao ZHANG, Yifan XUE, Hongde QIN

“…Additionally, by considering the drift angle compensation in the real ocean current environment, the obstacle avoidance algorithm was optimized to improve its robustness and adaptability. …”
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Robust fuzzy dynamic integrated environmental-economic-social scheduling considering demand response and user’s satisfaction with electricity under multiple uncertainties by Hong Zhang, Qianwei Xi, Lei Chen, Yong Min, Xiongxiong Fan, Wenjin Fang, Nan Tian, Fei Xu

“…Taking the lowest comprehensive operation cost as the economic objective, the smallest emissions of CO2 and atmospheric pollutants as environmental objective and the largest user’s comprehensive satisfaction with electricity as the social objective, based on the robust fuzzy theory, the multi-objective uncertainty optimal scheduling model is constructed, which is transformed into deterministic model and then solved by intelligent optimization algorithm. …”
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Constrained total least squares localization using angle of arrival and time difference of arrival measurements in the presence of synchronization clock bias and sensor position er... by Ruirui Liu, Ding Wang, Jiexin Yin, Ying Wu

“…Subsequently, a set of pseudo-linear equations are constructed, based on which the constrained total least squares optimization model has been formulated for target localization and the Newton iteration is applied to obtain the source position and clock bias simultaneously. …”
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Advanced Load Balancing Based on Network Flow Approach in LTE-A Heterogeneous Network by Shucong Jia, Wenyu Li, Xiang Zhang, Yu Liu, Xinyu Gu

“…Furthermore, a novel algorithm named optimal solution-based LB (OSLB) is proposed. …”
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Smart estimation of protective antioxidant enzymes’ activity in savory (Satureja rechingeri L.) under drought stress and soil amendments by Amin Taheri-Garavand, Mojgan Beiranvandi, Abdolreza Ahmadi, Nikolaos Nikoloudakis

“…The current research was carried out to develop a genetic algorithm-based artificial neural network (ΑΝΝ) model able of simulating the levels of antioxidants in savory when using soil amendments [biochar (BC) and superabsorbent (SA)] under drought. …”
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A Distributed Resilience Enhancement Strategy for Multi-microgrids Based on System of Systems Architecture by Linxinyan LIN, Junpeng ZHU, Yue YUAN

“…Firstly, the energy exchange process of the multi-microgrid systems is modeled based on the SoS architecture, and the distributed optimization algorithm is used to solve the model, which ensures the privacy of user information. …”
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Deep Reinforcement Learning with Local Attention for Single Agile Optical Satellite Scheduling Problem by Zheng Liu, Wei Xiong, Chi Han, Xiaolan Yu

“…Thus, an efficient approach is demanded to solve this problem, and this paper proposes a deep reinforcement learning algorithm with a local attention mechanism. A mathematical model is first established to describe this problem, which considers a series of complex constraints and takes the profit ratio of completed tasks as the optimization objective. …”
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UAV-Assisted Unbiased Hierarchical Federated Learning: Performance and Convergence Analysis by Ruslan Zhagypar, Nour Kouzayha, Hesham ElSawy, Hayssam Dahrouj, Tareq Y. Al-Naffouri

“…While applicable to terrestrial base stations (BSs), the proposed algorithm relies on UAVs for local model aggregation thanks to their ability to enhance wireless channels with lower latency and improved coverage. …”
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Self-Adjusting Look-Ahead Distance of Precision Path Tracking for High-Clearance Sprayers in Field Navigation by Xu Wang, Bo Zhang, Xintong Du, Huailin Chen, Tianwen Zhu, Chundu Wu

“…By developing a kinematic model of the pure pursuit algorithm for agricultural machinery, an evaluation function is then employed to estimate the pose of the machinery and identify the corresponding optimal look-ahead distance within the designated area. …”
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An online tool based on the Internet of Things and intelligent blockchain technology for data privacy and security in rural and agricultural development by Krishnaprasath Vellimalaipattinam Thiruvenkatasamy, Hayder M. A. Ghanimi, Sudhakar Sengan, Meshal Ghalib Alharbi

“…Central to this model is the proposed Quantum Neural Network + Bayesian Optimization (QNN + BO), a practiced algorithm that, when combined with methods like the Elliptic Curve Cryptography (ECC) and Coyote Optimization Algorithm (COA), guarantees secure data flow, processing, and storage. …”
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The accuracy of image-based individual tree crown detection and delineation across vegetation types by N. Pucino, T. McVicar, S. Levick, A. van Dijk

“…Ultimately, these findings provide valuable insights into enhancing large-scale vegetation monitoring and improving model generalization for tree crown detection.…”
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Building construction crack detection with BCCD YOLO enhanced feature fusion and attention mechanisms by Wenhao Ren, Zuowei Zhong

“…Firstly, this model optimizes the Path Aggregation Network (PAN) by introducing lateral skips and weighted feature fusion mechanisms, improving the multi-scale fusion capability of bare concrete crack features. …”
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Privacy-Oriented Successive Approximation Image Position Follower Processing by Ying Miao, Danyang Shao, Zhimin Yan

“…The detection of human key points depends on the human pose estimation algorithm, so the research in this paper is based on the bottom-up model in the multiperson pose estimation method; firstly, all the human key points in the image are detected by feature extraction through the convolutional neural network, and then the accurate labelling of human key points is achieved by using the heat map and offset fusion optimization method in the feature point confidence map prediction, and finally, the human body detection results are obtained. …”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…This study investigates the application effectiveness of deep learning-based object detection technology in forest fire smoke recognition by using the YOLOv11x algorithm to develop an efficient fire detection model. …”
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Lithium-Ion Battery State of Health Estimation Based on Feature Reconstruction and Transformer-GRU Parallel Architecture by Bing Chen, Yongjun Zhang, Jinsong Wu, Hongyuan Yuan, Fang Guo

“…The results show that the RMSE of the state of health estimation by the proposed method is 0.0071, which is an improvement of 61.41% in the accuracy of its baseline model.…”
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Resource Scheduling with Uncertain Execution Time in Cloud Computing by LI Cheng-yan, CAO Ke-han, FENG Shi-xiang, SUN Wei

“…For the problem of cloud computing resource scheduling, based on the fuzzy programming theory, a fuzzy cloud resource scheduling model under timecost constraint was set up, the uncertain execution time of tasks is represented by the triangular fuzzy number, and the target is to minimize the average value and standard deviation of the evaluation function An improved chaotic ant colony algorithm was proposed to solve the model, the elitist strategy is introduced to optimize the pheromone updating, a chaotic mapping with infinite folding times is used for chaotic search, and the adaptive chaotic disturbance mechanism is designed to enhance the global searching ability The model and algorithm were tested on the Cloudsim platform, the reliability of the model was proved, and the experimental results showed that the proposed algorithm had better performance in convergence speed, solution ability and load balance…”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…However, the underlying machine learning strategy used to develop and refine the EGF algorithm has not yet been detailed. Here, we present how our EGF Model—trained on procedural outcomes from 199 fully anonymized retrospective patient datasets—identifies clinically significant sources of AF and how this machine learning–driven hyperparameter optimization underlies its clinical effectiveness. …”
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