Flood extent mapping in SAR images using semi-supervised approach by Girisha S, Savitha G, Sughosh P

“…The findings highlight the method's effectiveness in improving flood-zone segmentation accuracy, leading to more efficient disaster management.…”
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R-SABMNet: A YOLOv8-Based Model for Oriented SAR Ship Detection with Spatial Adaptive Aggregation by Xiaoting Li, Wei Duan, Xikai Fu, Xiaolei Lv

“…However, ships in SAR images exhibit various characteristics including complex land scattering interference, variable scales, and dense spatial arrangements. Existing algorithms are insufficient in effectively addressing these challenges. …”
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RODA-OOD: Robust Domain Adaptation from Out-of-Distribution Data by Jaekyun Jeong, Mangyu Lee, Sunguk Yun, Keejun Han, Jungeun Kim

“…To address this issue, we propose RObust Domain Adaptation from Out-Of-Distribution data (RODA-OOD), a novel method based on data-centric AI principles that focuses on improving data quality rather than refining model architecture. …”
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Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…This study presents a novel hybrid modeling framework that combines Response Surface Methodology (RSM) with machine learning (ML) algorithms– Support Vector Regression (SVR) and Gradient Boosting Regression (GBR)– to contribute to the predictive modeling and optimization of thermally-activated ZnFe-LDH based Fenton catalysis. …”
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Anchor Dragging Risk Estimation Strategy from Supervised Cost-Sensitive Learning by Sang-Lok Yoo, Shem Otoi Onyango, Joo-Sung Kim, Kwang-Il Kim

“…A combination of data-undersampling methods and cost-sensitive algorithms was used to select the model with the best recall, area under the receiver operating characteristic curve (AUC), and geometric mean (GM) scores. …”
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Bearing Fault Diagnosis Grounded in the Multi-Modal Fusion and Attention Mechanism by Jianjian Yang, Haifeng Han, Xuan Dong, Guoyong Wang, Shaocong Zhang

“…The comparative results clearly demonstrate that the proposed Fusion Attention Network for Bearing Diagnosis yields significant improvements in classification outcomes.…”
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Separable reversible data hiding by vacating room after encryption using encrypted pixel difference by Veeramuthu Venkatesh, R. Anushiadevi, Padmapriya Velupillai Meikandan, Hemalatha Mahalingam, Rengarajan Amirtharajan

“…It achieves an embedding rate of 1.2 bpp, significantly improving upon standard VRAE algorithms while allowing for lossless data extraction and image recovery. …”
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A survey on exploring the challenges and applications of wireless body area networks (WBANs) by Arun Sekar Rajasekaran, L. Sowmiya, Azees Maria, R. Kannadasan

“…At last, the advancement in WBAN is for future improvement in the area of body area networks.…”
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Low-latency neuromorphic air hockey player by Juan P Romero B, Dimitrios Korakovounis, Jens E Pedersen, Jorg Conradt

“…However, most of today’s widely used neuromorphic benchmarks focus primarily on improving accuracy metrics using pre-recorded datasets, often overlooking critical factors such as latency and power consumption. …”
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A Practical Methodology for Accuracy and Quality Evaluation of Structured Light Systems in Automotive Inspection by Antonio Lagudi, Umberto Severino, Loris Barbieri, Fabio Bruno

“…It also demonstrated the ability to quantify improvements obtained through image enhancement algorithms. …”
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Intelligent Manufacturing in Wine Barrel Production: Deep Learning-Based Wood Stave Classification by Frank A. Ricardo, Martxel Eizaguirre, Desmond K. Moru, Diego Borro

“…To enhance performance and accuracy, we employ a data augmentation strategy using cropping techniques to address intra-class variability in individual staves. (3) Results: Our approach significantly improves accuracy and reliability in classifying wood with irregular textures and heterogeneity. …”
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MODERN APPROACHES AND TECHNOLOGIES OF PSYCHOLOGICAL SUPPORT OF FAMILIES OF PARTICIPANTS (VETERANS) OF A SPECIAL MILITARY OPERATION by Roza I. Kadieva, Aizanat R. Davudova

“…This ensures more complete and effective support for children and their families, improves coordination between services, and thus enhances the quality of psychological assistance. …”
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Machine Learning Model Based on Prognostic Nutritional Index for Predicting Long‐Term Outcomes in Patients With HCC Undergoing Ablation by Nan Zhang, Ke Lin, Bin Qiao, Liwei Yan, Dongdong Jin, Daopeng Yang, Yue Yang, Xiaohua Xie, Xiaoyan Xie, Bowen Zhuang

“…Conclusion The PNI‐based Aorsf model effectively predicts long‐term survival outcomes after ablation therapy, making a significant contribution to HCC research by improving surveillance, prevention, and treatment strategies.…”
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Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly patients with cardiovascular metabolic diseases in China: a longitudinal st... by Gege Zhang, Sijie Dong, Li Wang

“…Identifying and intervening in high-risk populations is crucial for improving patients' quality of life.…”
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Features of training 3d computer modeling and visualization of future teachers of informatics by O. G. Rylova

“…Questions on three-dimensional computer modeling and visualization will pass through the content line through the content of six academic disciplines («Computer graphics and multimedia», «Computational methods and computer modeling», «Programming Technologies and Algorithmization Methods», «Information Technologies in Education», «Methods teaching informatics» and «Architecture and software of computer systems»). …”
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Fuzzy LQR-based control to ensure comfort in HVAC system with two different zones by Elif Çinar, Tayfun Abut

“…Simulation results show that the FLQR method improves comfort performance by 90.4 % for Zone-1 and 88.1 % for Zone-2 compared to conventional LQR. …”
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Voltage Control Nonlinearity in QZSDMC Fed PMSM Drive System with Grid Filtering by Przemysław Siwek, Konrad Urbanski

“…The structure and control algorithms enabling regulation of the converter’s output voltage in both step-down and step-up modes are presented. …”
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Advanced Deep Learning Based Predictive Maintenance of DC Microgrids: Correlative Analysis by M. Y. Arafat, M. J. Hossain, Li Li

“…This study can contribute to the emerging technology for predictive maintenance of MGs and provide significant insights into the modeling and performance of RNN architectures for improving fault detection in MG systems. The findings can have noteworthy implications to enhance the efficiency and resilience in MG systems, thereby evolving the renewable energy technologies in power sector and contributing to the sustainable and greener energy landscape.…”
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Advanced Technologies for Smart Fertilizer Management in Agriculture: A Review by Jian-Jun Liu, Hao Wu, Imran Riaz

“…Precision fertilization has emerged as a critical component of modern smart agriculture, providing a transformative approach to optimizing nutrient application, enhancing crop productivity, and minimizing environmental harm while improving resource use efficiency. However, key challenges hinder its widespread adoption, including regional disparities in data quality, scalability constraints in low-resource settings, regulatory inconsistencies, and the high costs of technology adoption for smallholder farmers. …”
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Deep Learning in Written Arabic Linguistic Studies: A Comprehensive Survey by Manar Almanea

“…This article presents a comprehensive survey on recent applications of deep learning (DL) algorithms to written Arabic. Despite the increasing amount of user-generated content in Arabic, linguistic studies focusing on Arabic suffer from low analytical resources. …”
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