An Intelligent Method for C++ Test Case Synthesis Based on a Q-Learning Agent by Serhii Semenov, Oleksii Kolomiitsev, Mykhailo Hulevych, Patryk Mazurek, Olena Chernyk

“…An explicit synthesis algorithm constructs new test cases by selecting API calls from a learned policy encoded in a Q-table. …”
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Reconstruction for Scanning LiDAR with Array GM-APD on Mobile Platform by Di Liu, Jianfeng Sun, Wei Lu, Sining Li, Xin Zhou

“…This method avoids the need for field-of-view registration, improves data utilization, and reduces the complexity of the algorithm while eliminating the effect of LiDAR motion. …”
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Towards Intelligent Unmanned Adversarial Games: A Reinforcement Learning Framework with the PHP-ROW Method by Guoqing Shi, Yi Cao, Dinghan Wang, Qiming Yang, Jiandong Zhang, Zhuoyong Shi

“…The superiority of the PHP-ROW method is showcased by contrasting it against the conventional proximal policy optimization (PPO) algorithm. Conclusively, the utility and efficacy of the presented framework are corroborated through human–machine adversarial game simulations in a hyper-realistic environment. …”
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Intelligent Robot in Unknown Environments: Walk Path Using Q-Learning and Deep Q-Learning by Mouna El Wafi, My Abdelkader Youssefi, Rachid Dakir, Mohamed Bakir

“…This eliminates the need for manually fixed parameters and enables the learning algorithm to automatically determine optimal values, ensuring adaptability to diverse environments rather than being constrained to specific cases. …”
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Heuristic Binary Search for Modulated Predictive Control by Rafael FIgueiredo, Igor Oliani, Angelo Lunardi, Alfeu J. Sguarezi Filho

“…This paper introduces the Heuristic Binary Search, an intelligent search algorithm that efficiently explores the solution space, accommodating arbitrary cost function constraints similar to Finite Control Set, while maintaining a fixed switching frequency. …”
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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

“…Nodule detection was done using the Retina-UNet model, while the features were classified using a Support Vector Machine (SVM). …”
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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 proposed algorithm presented promising results, it is shown that the model can predict building heights for ridge and eave to a mean absolute error of 0.70 m, and in the occluded area was approximately 1.0 m. …”
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Balancing Precision and Speed: Introducing the Performance Efficiency Evaluation Ratio (PEER) in Visual Odometry by Cem Atilgan, Muharrem Mercimek

“…PEER incorporates a tunable weighting parameter to prioritize performance, speed, or a balanced trade-off, and employs normalization techniques to ensure comparability across different algorithms and systems. We evaluated PEER using the KITTI dataset with various feature extraction algorithms (SIFT, ORB, BRISK, KAZE, AKAZE) and matching algorithms (BF, FLANN). …”
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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

“…Notably, approximately half of the reviewed studies employ publicly available AI systems for instructional purposes (n = 32), while the other half develop proprietary AI-based learning tools (n = 31). 26 studies use AI techniques to generate and deliver multimodal learning materials. …”
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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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