Construction of reliable QSPR models for predicting the impact sensitivity of nitroenergetic compounds using correlation weights of the fragments of molecular structures by Shahram Lotfi, Shahin Ahmadi, Alla P. Toropova, Andrey A. Toropov

“…This study aimed to develop a QSPR model for predicting the impact sensitivity of 404 nitro compounds using the Monte Carlo algorithm implemented in CORAL-2023 software. The Simplified Molecular Input Line Entry System (SMILES) was employed to represent the molecular structures, while correlation weight descriptors were computed. …”
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Practical DU-CU Placement in an Enhanced Mobile BroadBand Request During 5G Traffic by Ange Joel Nounga Njanda, Joao Filipe Muchanga, Hojjat Baghban, Karcius Day R. Assis

“…The objective is to identify the optimal candidate sites for deploying the DU and CU functions to ensure a continuous service path from the RU to the DC. …”
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Prediction Model of Household Carbon Emission in Old Residential Areas in Drought and Cold Regions Based on Gene Expression Programming by Shiao Chen, Yaohui Gao, Zhaonian Dai, Wen Ren

“…., electricity usage and heating energy consumption) were selected using Pearson correlation analysis and the Random Forest (RF) algorithm. Subsequently, a hybrid prediction model was constructed, with its parameters optimized by minimizing the root mean square error (RMSE) as the fitness function. …”
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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

“…Most traditional test suite optimization methods treat test cases as atomic units, without analyzing the utility of individual instructions. …”
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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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I-YOLOv11n: A Lightweight and Efficient Small Target Detection Framework for UAV Aerial Images by Yukai Ma, Caiping Xi, Ting Ma, Han Sun, Huiyang Lu, Xiang Xu, Chen Xu

“…However, existing detection algorithms still have weak small target representation ability, extensive computational resource overhead, and poor deployment adaptability. …”
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Implementing Blockchain Technology for Secure Data Transactions in Cloud Computing Environments Challenges and Solutions by Dandu Varalakshmi, N Shirisha, K Suresh, Saidhbi Shaik, V Venkatesh, C F Theresa Cenate

“…In this paper, we design an optimized, cloud-based blockchain-enabled security framework for real-world scalability, performance, and regulatory constraints. …”
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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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