A Student-Centric Evaluation Survey to Explore the Impact of LLMs on UML Modeling by Bilal Al-Ahmad, Anas Alsobeh, Omar Meqdadi, Nazimuddin Shaikh

“…We developed a novel rule-based prompt-engineering framework that transforms domain scenarios into optimized prompts for LLM processing. The generated diagrams were then synthesized using PlantUML and evaluated through a rigorous survey involving 121 computer science and software engineering students across three U.S. universities. …”
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Efficient vision transformers with edge enhancement for robust small target detection in drone-based remote sensing by Xuguang Zhu, Zhizhao Zhang

“…Small object detection in UAV remote sensing imagery faces significant challenges due to scale variations, background clutter, and real-time processing requirements. This study proposes a lightweight transformer-based detector, MLD-DETR, which enhances detection performance in complex scenarios through multi-scale edge enhancement and hierarchical attention mechanisms. …”
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Efficient Limb Range of Motion Analysis from a Monocular Camera for Edge Devices by Xuke Yan, Linxi Zhang, Bo Liu, Guangzhi Qu

“…Furthermore, the proposed model is optimized for deployment on resource-constrained edge devices, balancing accuracy and the benefits of edge computing like cost-effectiveness and localized data processing. …”
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Jointly Achieving Smart Homes Security and Privacy through Bidirectional Trust by Osman Abul, Melike Burakgazi Bilgen

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Control system for noise-resistant electronic speed controller of a brushless electric motor for an unmanned aerial vehicle by M. V. Parinov, A. N. Yurov, Ya. V. Skitskiy

“…Methods of algorithmization, expert assessments, linear computational processes and experimental studies were used.Results. …”
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Parallel Excitatory and Inhibitory Neural Circuit Pathways Underlie Reward-Based Phasic Neural Responses by Huanyuan Zhou, KongFatt Wong-Lin, Da-Hui Wang

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Development banks in the digital economy on the example of the asian development bank by S. Matveevskiy

“…The essence of the digital economy as a complex of cloud computing technologies, big data and their analysis, artificial intelligence (AI), which ensures the production of fundamentally new products and services is revealed. …”
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Feature Selection Using Pearson Correlation for Ultra-Wideband Ranging Classification by Gita Indah Hapsari, Rendy Munadi, Bayu Erfianto, Indrarini Dyah Irawati

“…The Random Forest and Gradient Boosting models exhibit superior performance, maintaining classification accuracy above 90%. The reduction in computational overhead makes the proposed approach highly suitable for real-time applications, particularly in edge-computing environments where processing efficiency is critical. …”
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PlantNet: Scalable Convolutional Neural Network for Image-Based Plant Disease Detection by Sinha Anupa, Kumaraswamy Balasubramaniam

“…By leveraging deep learning techniques, PlantNet processes large-scale image datasets to detect disease symptoms with high precision. …”
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RepVGG-MEM: A Lightweight Model for Garbage Classification Achieving a Balance Between Accuracy and Speed by Qiuxin Si, Sang Ik Han

“…This performance reflects a commendable balance between accuracy and processing speed. Furthermore, the model’s redundancy is minimized through pruning techniques, which significantly reduce both complexity and computational overhead. …”
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Short packet communication in IoT networks: performance analysis by Dinh-Tung Vo, Thu Ha Thi-Pham, Minh Tran, Byung-Seo Kim, Rupak Kharel, Miroslav Voznak

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Improved Road Extraction Models through Semi-Supervised Learning with ACCT by Hao Yu, Shihong Du, Zhenshan Tan, Xiuyuan Zhang, Zhijiang Li

“…Labeled and unlabeled images are processed by both models to generate road maps from different perspectives. …”
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Design and analysis of a small satellite design hosting lidar sensor for data acquisition aimed at environmental protection by Paschalidis Maria, Kolios Stavros

“…The study also addresses advanced data analysis techniques for Lidar sensor data, focusing on signal processing, object detection, and feature extraction. …”
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Damage Detection Method for Road Ancillary Facilities Integrating Attention Mechanism by Shuang Yang, Huiqin Wang, Ke Wang, Nan Guo

“…The model first introduces the D-GhostNet V3Conv module, replacing the standard convolutional layers, significantly enhancing feature extraction capabilities while reducing computational costs. Additionally, the improved AR-BiFormer attention mechanism is integrated into the backbone network, enabling adaptive weight adjustment of feature maps through parallel processing of contextual information, thereby effectively improving the detection of small targets in complex scenes. …”
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A novel federated learning approach for IoT botnet intrusion detection using SHAP-based knowledge distillation by Md. Alamgir Hossain, Sadman Saif, Md. Saiful Islam

“…Our framework leverages SHAP (Shapley Additive Explanations), a technique for computing feature importance, to provide interpretable insights while maintaining data privacy. …”
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Beyond binary: multi-class skin lesion classification with AlexNet transfer learning-towards enhanced dermatological diagnosis by Abida Noaman, Reyaz Ahmad, Muhammad Farhan Khan, Abdul Salam Mohammed, Muhammad Farooq, Khan Muhammad Adnan

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Prediction and optimization of WEDM parameters for machining of NiTi-shape memory alloy using ANFIS-PSO approach by Lokesh Kumar, Ashish Goyal, Vimal Kumar Pathak

“…The findings recommended optimal operating settings to maximize dimensional accuracy and minimize both processing time and cost. Real-time monitoring was performed using a vibration device to assess the frequency of motion of the wire electrode during the cutting interaction with the workpiece. …”
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Effective DDoS attack detection in software-defined vehicular networks using statistical flow analysis and machine learning. by Himanshi Babbar, Shalli Rani, Maha Driss

“…The ML models, especially complex ones like Random Forest, require substantial processing power, which necessitates efficient data handling and possibly leveraging edge computing resources to reduce latency. …”
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Rate-Adaptive LiDAR Point Cloud Streaming Over LEO Satellite Networks by Dominic Laniewski, Nils Aschenbruck

“…Many agricultural robots are equipped with Light Detection and Ranging (LiDAR) sensors, which generate large, three-dimensional point clouds that are often offloaded to dedicated cloud-based computing centers for complex processing tasks. However, the produced data rates can reach hundreds of Mbit/s, overwhelming the uplink of current LEO satellite networks of approximately 20Mbit/s, making a real-time transmission challenging. …”
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Golf swing classification with multiple deep convolutional neural networks by Libin Jiao, Rongfang Bie, Hao Wu, Yu Wei, Jixin Ma, Anton Umek, Anton Kos

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