An Enhanced Approach for Remaining Useful Life Prediction of Bearings Using Incomplete Lifecycle Data by Xunmeng An, Chao Zhang, Caiye Liu, Wentao Zhao

“…Accurately predicting the remaining useful life (RUL) of rolling bearings is crucial for ensuring optimal equipment operation and timely maintenance. …”
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Economic Production Quantity Model under Back Order, Rework, Imperfect Quality, Electricity Tariff, and Emission Tax by Dana Marsetiya Utama, Yolanda Dwi Asmara Putri, Shanty Kusuma Dewi

“…To solve this complex optimization problem, the Genetic Algorithm (GA) is used for its efficiency in handling non-linear and combinatorial problems. …”
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Blind super-resolution network based on local fuzzy discriminative loss for fabric data augmentation by Ning Dai, Xiaohan Hu, Kaixin Xu, Xudong Hu, Yanhong Yuan, Bo Cao, Luhong Shi

“…To address these challenges, this paper proposes a blind super-resolution algorithm for fabric defect data augmentation. The model is based on Real-ESRGAN and has been optimized specifically for the resolution degradation module to better adapt to the resolution degradation process in fabric images. …”
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A Comparative Evaluation of Machine Learning Methods for Predicting Student Outcomes in Coding Courses by Zakaria Soufiane Hafdi, Said El Kafhali

“…Educational data mining (EDM) has emerged as a pivotal AI application to transform educational environments by optimizing learning processes and identifying at-risk students. …”
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Horizontal Control System for Maglev Ruler Based on Improved Active Disturbance Rejection Controller by Gengyun Tian, Chunlin Tian, Jiyuan Sun, Shusen Diao

“…This paper is centered around the autonomous displacement of the maglev ruler system, with the core objective of optimizing the performance of its horizontal control system. …”
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A Multi-Phase DRL-Driven SDN Migration Framework Addressing Budget, Legacy Service Compatibility, and Dynamic Traffic by Kai Yuan Tan, Saw Chin Tan, Teong Chee Chuah

“…This approach can potentially lower migration costs by up to 64% while achieving network optimization objectives. …”
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Establishing an AI-based diagnostic framework for pulmonary nodules in computed tomography by Ruiting Jia, Baozhi Liu, Mohsin Ali

“…Abstract Background Pulmonary nodules seen by computed tomography (CT) can be benign or malignant, and early detection is important for optimal management. The existing manual methods of identifying nodules have limitations, such as being time-consuming and erroneous. …”
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Variation Characteristics of Mass-Loss Rate in Dynamic Seepage System of the Broken Rocks by Luzhen Wang, Hailing Kong

“…In this study, the seepage tests of the broken mudstone were carried out using the patented pumping station seepage method, and the time-varying function of the mass-loss rate was generalized. Then, the optimal coefficients in the function of mass-loss rate were computed using the genetic algorithm. …”
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LoD2 Building Reconstruction from Stereo Satellite Imagery using Deep Learning and Model-Driven Approach by Rojgar Qarani Ismael, Haval Sadeq

“…The Reconstructed model was refined by utilizing OpenStreetMap library and graph cut optimization method. The suggested methodology is tested on the GeoEye-1 satellite imagery dataset for Erbil City, which is validated with ground truth data. …”
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Balancing Precision and Speed: Introducing the Performance Efficiency Evaluation Ratio (PEER) in Visual Odometry by Cem Atilgan, Muharrem Mercimek

“…Overall, PEER provides a robust and flexible framework for optimizing visual odometry systems.…”
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Computing Non-Dominated Flexible Skylines in Vertically Distributed Datasets with No Random Access by Davide Martinenghi

“…These algorithms process data locally, thereby reducing data transfer and exposure to breaches, while at the same time improving scalability thanks to data distribution across multiple sources. …”
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Design and assessment of AI-based learning tools in higher education: a systematic review by Jihao Luo, Chenxu Zheng, Jiamin Yin, Hock Hai Teo

“…Lastly, we provide recommendations for optimizing the design and implementation of AI-based learning tools in higher education and outline promising directions for future research in this field.…”
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Adaptive robust self‐scheduling for a wind‐based GenCo equipped with power‐to‐gas system and gas turbine to participate in electricity and natural gas markets by Mojtaba Fereydani, Mohammad Amin Latify

“…A tri‐level adaptive robust optimization model is introduced for the GenCo’s short‐term operational scheduling. …”
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EdgeGuard: Decentralized Medical Resource Orchestration via Blockchain-Secured Federated Learning in IoMT Networks by Sakshi Patni, Joohyung Lee

“…We have made several technological advances, including a lightweight blockchain consensus mechanism designed for IoMT networks, an adaptive edge resource allocation method based on reinforcement learning, and a federated learning algorithm optimized for medical data with differential privacy. …”
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Spike Stall Precursor Detection in a Single-Stage Axial Compressor: A Data-Driven Dynamic Modeling Approach by Anish Thapa, Jichao Li, Marco P. Schoen

“…Reducing this margin through active control requires stall precursor detection and mitigation mechanisms. While several algorithms have shown promising results in predicting modal stalls, predicting spike stalls remains a challenge due to their rapid onset, leaving little time for corrective actions. …”
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Swarm intelligence based classification rule induction (CRI) framework for qualitative and quantitative approach: An application of bankruptcy prediction and credit risk analysis by J. Uthayakumar, T. Vengattaraman, P. Dhavachelvan

“…In this paper, a unified framework for qualitative and quantitative bankruptcy analysis using Ant Colony Optimization (ACO) based ant-miner algorithm is proposed. …”
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HIGH-EFFICIENCY INFRARED RECEIVER by A. K. Esman, V. I. Kostenko, N. I. Mukhurov, G. L. Zykov, V. A. Potachits

“…Simulation of the electromagnetic characteristics of the proposed receiver by using the software package HFSS with the basic algorithm of a finite element method which implemented to calculate the behavior of electromagnetic fields on an arbitrary geometry with a predetermined material properties have shown that when the inner parts of the electrodes of the low-barrier Schottky diode is performed in the concentric elliptical convex-concave shape, it can be reduce the reflection losses to -57.75 dB and the standing wave ratio to 1.003 while increasing the directivity up to 23 at a wavelength of 6.09 μm. …”
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Power-Yeoh: A Yeoh-Type Hyperelastic Model with Invariant I₂ for Rubber-like Materials by Subraya Krishna Bhat, Keerthan A.

“…Also, the interesting phenomenon of thin balloon expansion is investigated by applying the model to relevant experimental data on elastomeric balloons available in the literature. A genetic algorithm-based least squares optimization routine is carried out to determine the material constants while applying the reported experimental data. …”
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Effective practices in enhancing autonomous English language learning through YouTube by Ritueli Daeli, Santosa Santosa

“…This research contributes to understanding the role of digital platforms in language education, offering insights into optimizing their use for autonomous learning. …”
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A lightweight weed detection model for cotton fields based on an improved YOLOv8n by Jun Wang, Zhengyuan Qi, Yanlong Wang, Yanyang Liu

“…Secondly, the Bidirectional Feature Pyramid Network (BiFPN) is introduced to enhance the feature fusion layer, further optimizing the model’s ability to recognize weed features in complex backgrounds. …”
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