Towards precision agriculture: metaheuristic model compression for enhanced pest recognition by Sana Parez, Norah Saleh Alghamdi, Tahir Mahmood, Waseem Ullah, Muhammad Attique Khan, Taha Houda, Naqqash Dilshad

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A robust deep learning framework for multiclass skin cancer classification by Burhanettin Ozdemir, Ishak Pacal

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Revolutionizing Management Accounting: The Role of Artificial Intelligence in Predictive Analytics, Automated Reporting, and Decision-Making by Milos Pavlovic, Cedomir Gligoric, Filip Zdravkovic, Danijela Pavlovic

“…AI-powered automated reporting improves efficiency and minimizes errors, while AI-based decision support systems deliver real-time insights and detect complex patterns, resulting in more effective strategic decisions. …”
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MalGEA: A malware analysis framework via matrix factorization based node embedding and graph external attention by Ruisheng Li, Qilong Zhang, Huimin Shen

“…Experimental results demonstrate that our method significantly outperforms existing node embedding approaches in terms of computational efficiency, while also achieving high accuracy in malware detection and family classification tasks.…”
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Gradient Boosting Feature Selection for Integrated Fault Diagnosis in Series-Compensated Transmission Lines by Rab Nawaz, Abdul Wadood, Khawaja Khalid Mehmood, Syed Basit Ali Bukhari, Hani Albalawi, Aadel Mohammed Alatwi, Muhammad Sajid

“…The integration of feature extraction with efficient gradient-boosting feature selection ensures high accuracy, speed, and computational efficiency, thus outperforming techniques that require heavy preprocessing. …”
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Thermo-Optic Nanomaterial Fiber Hydrogen Sensor by Xuhui Zhang, Liang Guo, Xinran Wei, Qiang Liu, Yuzhang Liang, Junsheng Wang, Wei Peng

“…However, the widespread use of hydrogen is also accompanied by safety hazards, and how to detect hydrogen safely and efficiently has become a research focus. …”
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HFC-YOLO11: A Lightweight Model for the Accurate Recognition of Tiny Remote Sensing Targets by Jinyin Bai, Wei Zhu, Zongzhe Nie, Xin Yang, Qinglin Xu, Dong Li

“…Ablation studies validate the balanced performance of the hierarchical feature compensation strategy in the preservation of resolution and computational efficiency. Visualization results confirm an enhanced robustness against complex background interference. …”
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Steel Wire Rope Damage Width Identification Method Based on Residual Networks and Multi-Channel Feature Fusion by Yan Peng, Junde Liu, Junjie He, Yongjun Qiu, Xie Liu, Le Chen, Fengfeng Yang, Bulong Chen, Bin Tang, Yuhan Wang

“…In order to ensure the safety of steel wire rope in various application scenarios, it is particularly important to quantitatively detect the defects of wire rope. Complex detection conditions affect the detection efficiency of wire rope. …”
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Intelligent identification of Cenozoic spore and pollen fossils in Bohai Sea area by Leilei SHUI, Kunqi QIU, Huan WAN, Shengli GONG, Wenkai LU, Wenyan WEI, Yonghao WANG, Yongzhao YU

“…By utilizing techniques such as deep learning for object detection and label smoothing, the efficiency of fossil screening and spore and pollen fossil classification was significantly enhanced. …”
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Multi-Source, Fault-Tolerant, and Robust Navigation Method for Tightly Coupled GNSS/5G/IMU System by Zhongliang Deng, Zhichao Zhang, Zhenke Ding, Bingxun Liu

“…However, frequent multi-sensor faults, including missing alarm thresholds, uncontrolled error accumulation, and delayed warnings, hinder the adaptability of navigation systems to the dynamic multi-source information of complex scenarios. This study introduces an advanced, tightly coupled GNSS/5G/IMU integration framework designed for distributed PNT systems, providing all-source fault detection with weighted, robust adaptive filtering. …”
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Evaluation criteria of centralization options in the architecture of multicomputer systems with traps and baits by Antonina Kashtalian, Sergii Lysenko, Anatoliy Sachenko, Bohdan Savenko, Oleg Savenko, Andrii Nicheporuk

“…New mathematical models were developed for the criteria for operational efficiency, stability, integrity and security in relation to the system center, which, unlike the known mathematical models for evaluating system centers for selecting the next options for centralization, are presented in analytical expressions that take into account the features of the types of centralization in the system architecture, indicators of operational efficiency, stability, integrity and security in relation to the system center and allow forming on their basis an objective function for evaluating options for centralization in systems, the feature of which is the hiding of components with the system center from detection by attackers. …”
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Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-... by Daoqi Han, Honghui Li, Xueliang Fu

“…However, traditional intrusion detection methods encounter several issues such as low detection efficiency and prolonged detection time when dealing with massive and high-dimensional data. …”
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Multi-Robot Cooperative Simultaneous Localization and Mapping Algorithm Based on Sub-Graph Partitioning by Wan Xu, Yanliang Chen, Shijie Liu, Ao Nie, Rupeng Chen

“…To address the challenges in multi-robot collaborative SLAM, including excessive redundant computations and low processing efficiency in candidate loop closure selection during front-end loop detection, as well as high computational complexity and long iteration times due to global pose optimization in the back-end, this paper introduces several key improvements. …”
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Rapid Diagnosis of Distributed Acoustic Sensing Vibration Signals Using Mel-Frequency Cepstral Coefficients and Liquid Neural Networks by Haitao Liu, Yunfan Xu, Yuefeng Qi, Haosong Yang, Weihong Bi

“…Distributed Acoustic Sensing (DAS) systems face increasing challenges in massive data processing and real-time fault diagnosis due to the growing complexity of industrial environments and data volume. …”
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A Decision Support System For Early Stage Parkinson's Diagnosis from EEG Data Using Symbolic Mutual Information and KAC Features by Nurhan Gürsel Özmen, Neslihan Baki

“…Therefore, in this study, an efficient PD detection method from EEG data by using a new set of features is searched. …”
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EnsembleXAI-Motor: A Lightweight Framework for Fault Classification in Electric Vehicle Drive Motors Using Feature Selection, Ensemble Learning, and Explainable AI by Md. Ehsanul Haque, Mahe Zabin, Jia Uddin

“…As electric vehicles (EVs) are growing, the fault diagnosis in their drive motor becomes more important to have optimal performance and safety. Traditional fault detection methods suffer mainly from high false positive and false negative rates, computational complexity, and lack of transparency in decision-making methods. …”
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Advanced smart assistance with enhancing social interaction and daily activities for visually impaired individuals using deep learning with modified seagull optimization by Sana Alazwari, Hussah Nasser AlEisa, Mohammed Rizwanullah, Radwa Marzouk

“…Next, the features are extracted using the Dilated Convolution Block Attention Module with EfficientNet (DCBAM-EfficientNet) module, which derives the intrinsic and complex features. …”
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GS-LinYOLOv10: A drone-based model for real-time construction site safety monitoring by Yang Song, ZhenLin Chen, Hua Yang, Jifei Liao

“…The model integrates IoT sensor data for real-time feedback, incorporates the GSConv module for lightweight feature extraction, and utilizes a Linformer-based attention mechanism to efficiently capture global context. These innovations reduce computational complexity while significantly improving detection accuracy. …”
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Vehicle-to-Infrastructure Multi-Sensor Fusion (V2I-MSF) With Reinforcement Learning Framework for Enhancing Autonomous Vehicle Perception by Daud Khan, Sawera Aslam, Kyunghi Chang

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TIAR-SAR: An Oriented SAR Ship Detector Combining a Task Interaction Head Architecture with Composite Angle Regression by Yu Gu, Minding Fang, Dongliang Peng

“…These include the inherent misalignment between regression and classification tasks and the boundary discontinuity problem in oriented object detection. These issues hinder efficient and accurate ship detection in complex scenarios. …”
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