Temporal Community Detection and Analysis with Network Embeddings by Limengzi Yuan, Xuanming Zhang, Yuxian Ke, Zhexuan Lu, Xiaoming Li, Changzheng Liu

“…By establishing coherent relationships between node representations and community structures, we optimize both the Convex-NMF-based representation learning model and the evolutionary clustering-based TCD model within a unified framework. …”
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Digital Land Suitability Assessment for Irrigated Cultivation of Some Agricultural Crops Using Machine Learning Approaches (Case Study: Qazvin-Abyek) by F. Jannati, F. Sarmadian

“…The utilization of modern mapping techniques such as digital soil mapping and machine learning algorithms can significantly improve the accuracy of land suitability assessment and crop performance prediction. …”
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Complex Large-Deformation Multimodality Image Registration Network for Image-Guided Radiotherapy of Cervical Cancer by Ping Jiang, Sijia Wu, Wenjian Qin, Yaoqin Xie

“…The DSC index of the MTEF algorithm is 5.64% higher than that of the TransMorph algorithm. …”
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Reduction of Multiplicative Noise in Radar Images by A. A. Tuzova, V. A. Pavlov, A. A. Belov

“…The proposed algorithm allowed optimal parameters for several speckle noise filters to be determined. …”
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A Rice-Mapping Method with Integrated Automatic Generation of Training Samples and Random Forest Classification Using Google Earth Engine by Yuqing Fan, Debao Yuan, Liuya Zhang, Maochen Zhao, Renxu Yang

“…The spatial distribution characteristics of rice cultivation extracted by the LR algorithm were accurate and the performance was optimal. …”
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Early Warning of Axillary Lymph Node Metastasis in Breast Cancer Patients Using Multi-Omics Signature: A Machine Learning-Based Retrospective Study by Ke Z, Shen L, Shao J

“…The AUC of GLRM was 0.818 (95% CI: 0.757~0.879), significantly lower than that of RFM’s AUC 0.893 (95% CI: 0.836~0.950).Conclusion: The prediction models based on machine learning (ML) algorithms and multiomics have shown good performance in predicting ALN metastasis, and RFM shows greater advantages compared to traditional GLRM. …”
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Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review by Habiba Njeri Ngugi, Andronicus A. Akinyelu, Absalom E. Ezugwu

“…Preprocessing methods like K-means clustering, Fuzzy C-Means, and PCA, along with ensemble approaches, further improved model accuracy. Lastly, the study underscores that high-quality, well-labeled datasets, stakeholder involvement, and comprehensive evaluation metrics such as F1 score and precision are crucial for optimizing ML and DL models, making them more effective for real-world applications in sustainable agriculture.…”
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Research on a Hierarchical Control Strategy for Anti-Lock Braking Systems Based on Active Disturbance Rejection Control (ADRC) by Shi Luo, Bing Zhang, Jiantao Ma, Xinyue Zheng

“…Firstly, a vehicle dynamics model and an ABS model based on the EMB system are established; secondly, a speed observer based on the dilated state observer is used in the upper layer to design a pavement recognition algorithm, which recognizes the current pavement and outputs the optimal slip rate; then, an ABS controller based on the ADRC algorithm is designed for the lower layer to track the optimal slip rate. …”
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Frailty in older adults patients: a prospective observational cohort study on subtype identification by Zhikai Yang, Chen Ji, Ting Wang, Wei He, Yuhao Wan, Min Zeng, Di Guo, Lingling Cui, Hua Wang

“…This study applied the K-means clustering algorithm to analyze 27 variables, determining the optimal cluster number using the Elbow method and Silhouette coefficient. …”
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Mechanism for data recovery as a result of data corruption, infection and/or unauthorized modification by L. V. Cherkesova, V. A. Savelyev, E. A. Revyakina, A. R. Polulyakh, M. A. Sementsov

“…To develop the software module, a reversible incremental backup algorithm was chosen as the most suitable for the developed algorithm and more convenient to use.Conclusion. …”
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High-Resolution Computed Tomography of Single Breast Cancer Microcalcifications in Vivo by Kazumasa Inoue, Fangbing Liu, Jack Hoppin, Elaine P. Lunsford, Christian Lackas, Jacob Hesterman, Robert E. Lenkinski, Hirofumi Fujii, John V. Frangioni

“…At an optimal detector sampling frequency, the ECBA provided a 28 μm (21%) FWHM improvement in resolution over the FCBA. …”
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Composing problem solvers for simulation experimentation: a case study on steady state estimation. by Stefan Leye, Roland Ewald, Adelinde M Uhrmacher

“…To support those users, we propose a general scheme to aggregate such algorithms to so-called synthetic problem solvers, which exploit algorithm differences to improve overall performance. …”
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A PSO weighted ensemble framework with SMOTE balancing for student dropout prediction in smart education systems by Achin Jain, Arun Kumar Dubey, Shakir Khan, Arvind Panwar, Mohammad Alkhatib, Abdulaziz M Alshahrani

“…This methodology balances the dataset using SMOTE, optimizes model hyperparameters, and fine-tunes ensemble weights through PSO to improve predictive performance. …”
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Efficient Task Scheduling and Load Balancing in Fog Computing for Crucial Healthcare Through Deep Reinforcement Learning by Prashanth Choppara, Bommareddy Lokesh

“…The foundation of this approach is the DRL model, which is designed to dynamically optimize the partition of computational tasks across fog nodes to improve both data throughput and operational response times. …”
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Spatiotemporal-Dependent Vehicle Routing Problem Considering Carbon Emissions by Ziqi Liu, Yeping Chen, Jian Li, Dongqing Zhang

“…In the algorithm, a neighborhood search operator is employed to optimize elite individuals so that the algorithm can stimulate the intensification and avoid falling into a local optimum. …”
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Enhancing BVR Air Combat Agent Development With Attention-Driven Reinforcement Learning by Andre R. Kuroswiski, Annie S. Wu, Angelo Passaro

“…We propose a novel approach that introduces a task-based layer, leveraging domain expertise to optimize decision-making and training efficiency. By integrating multi-head attention mechanisms into the policy model and employing an improved DQN algorithm, agents dynamically select context-aware tasks, enabling the learning of efficient emergent behaviors for variable engagement conditions. …”
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A novel re-entrant circular star-shaped auxetic honeycomb with enhanced energy absorption and anisotropic Poisson’s ratio by Danrong Shi, Zhuangzhuang Wang, Yongwei Li, Ruyuan Huo, Jin Zhang, Jianguo Cai

“…A multi-objective optimisation strategy was used by a Kriging surrogate model and NSGA-II algorithm to identify an optimal configuration with improved crashworthiness. …”
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A Blur-Score-Guided Region Selection Method for Airborne Aircraft Detection in Remote Sensing Images by Yujian Wang, Yi Hou, Yuting Xie, Ruofan Wang, Shilin Zhou

“…Our approach includes an improved tenengrad gradient algorithm to extract motion blur information and construct a Blur-Score map. …”
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MATE-ViT: A multi-channel contrast-limited adaptive time-frequency enhancement and vision transformer framework for bearing fault diagnosis by Jiangdong Zhao, Jiao Yu, Wenming Wang, Ji Huang, Xiaolu Ma

“…First, an improved CLAHE algorithm is used to independently enhance the multi-channel time-frequency images, effectively improving the local contrast and detail expression of the images, thereby enhancing the recognizability of fault features. …”
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A data driven approach to urban area delineation using multi source geospatial data by Chenyu Fang, Lin Zhou, Xinyue Gu, Xing Liu, Martin Werner

“…Abstract This study introduces a data-driven, bottom-up approach to urban delineation, integrating feature engineering with the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, which represents a significant improvement in precision and methodology compared to traditional approaches that rely on simplistic OpenStreetMap (OSM) road node data aggregations. …”
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