UNION: A Trust Model Distinguishing Intentional and Unintentional Misbehavior in Inter-UAV Communication by Ezedin Barka, Chaker Abdelaziz Kerrache, Nasreddine Lagraa, Abderrahmane Lakas, Carlos T. Calafate, Juan-Carlos Cano

“…Simulations conducted using NS2.35 evidence the efficiency of our proposal, called UNION, at ensuring high detection ratios > 87% and high accuracy with reduced end-to-end delay, clearly outperforming previous proposals known as RPM, T-CLAIDS, and CATrust.…”
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Leveraging Neural Trojan Side-Channels for Output Exfiltration by Vincent Meyers, Michael Hefenbrock, Dennis Gnad, Mehdi Tahoori

“…To achieve low latency and high efficiency, field-programmable gate arrays (FPGAs) are increasingly being employed as accelerators for neural network inference in cloud and edge devices. …”
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Investigating Single-Molecule Molecular Inversion Probes for Medium-Scale Targeted DNA Methylation Analysis by Roy B. Simons, Hieab H. H. Adams, Manfred Kayser, Athina Vidaki

“…Conclusions: The observed low specificity and uniformity indicate that smMIPs in their current form are not compatible with the lowered complexity of bisulfite-converted DNA.…”
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Enhancing chronic wound assessment through agreement analysis and tissue segmentation by Ana C. Morgado, Rafaela Carvalho, Ana Filipa Sampaio, Maria J. M. Vasconcelos

“…Moreover, the obtained inter-rater agreement scores still emphasize the inherent complexity of the task, as even experienced healthcare professionals may differ in delineating tissue boundaries. …”
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A framework for the simulation of individual glycan coordinates to analyze spatial relationships within the glycocalyx by Sarah Fritsche, Sarah Fritsche, Leonhard Möckl, Leonhard Möckl, Leonhard Möckl, Leonhard Möckl

“…Importantly, we include various experimental considerations, such as labeling and detection efficiency. This approach may contribute to establishing a new standard of connection between geometrical and molecular-resolution data in service of advancing our understanding of the functional role of the glycocalyx in biology as well as its clinical potential.…”
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Deep Learning with Dual-Channel Feature Fusion for Epileptic EEG Signal Classification by Bingbing Yu, Mingliang Zuo, Li Sui

“…While deep learning methods have shown promise, many current models suffer from limitations such as excessive complexity, high computational demands, and insufficient generalizability. …”
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Slope Stability Monitoring Methods and Technologies for Open-Pit Mining: A Systematic Review by Rohan Le Roux, Mohammadali Sepehri, Siavash Khaksar, Iain Murray

“…Slope failures in open-pit mining pose significant operational and safety issues, underscoring the importance of implementing effective stability monitoring frameworks for early hazard detection to allow for timely intervention and risk mitigation. …”
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Multijunction solar cell parameter estimation based on metaheuristic algorithms by Marwa M. Elzalabani, Doaa M. Atia, Aref Y. Eliwa, Belal A. Abou Zalam, Mahmoud S. AbouOmar

“…Several mathematical models exist for MJSC parameter estimation— Single Diode Model (SDM), Double Diode Model (DDM), and Triple Diode Model (TDM)—each offering a trade-off between complexity and accuracy, improved efficiency, and reliable operation. …”
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Automated Arrhythmia Classification System: Proof-of-Concept With Lightweight Model on an Ultra-Edge Device by Namho Kim, Seongjae Lee, Seungmin Kim, Sung-Min Park

“…The efficiency of the lightweight model and edge-computing system was evaluated regarding arrhythmia classification performance and computational complexity. …”
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A Node Generation and Refinement Algorithm in Meshless RPIM for Electromagnetic Analysis of Sensors by Zihao Li, Siguang An, Guoping Zou, Jianqiang Han

“…One popular method for electromagnetic field computation is the meshless radial point interpolation method (RPIM), where the number and distribution of nodes are critical to ensuring both accuracy and efficiency. However, traditional RPIM methods often face challenges in achieving stable and precise results, particularly in complex electromagnetic environments. …”
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Improving and simulating urban landscape image recognition using combination optimization and fuzzy K-means algorithm by Lihua Yang, Yuhui Zheng

“…The FKM allows for the clustering of mixed-use urban zones with greater accuracy, identifying complex patterns, and relationships that earlier research methods often overlook. …”
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Addressing data scarcity in speech emotion recognition: A comprehensive review by Samuel Kakuba, Dong Seog Han

“…These signals encode complex relationships between features at multiple time scales, effectively reflecting a speaker’s emotional state. …”
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Texture Analysis and Classification using Local Binary Patterns and Statistical Features by Hasan Maher

“…To demonstrate the efficiency of the proposed hybrid method, several experiments are performed on several texture databases. …”
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Well Testing of Fracture Corridors in Naturally Fractured Reservoirs for an Improved Recovery Strategy by Yingying Guo, Andrew Wojtanowicz

“…Among them, corridor-type NFRs, characterized by discrete fracture corridors, exhibit complex flow behavior that challenges conventional development strategies and reduces recovery efficiency. …”
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Prevention of Bankruptcy of Industrial Enterprises and Organizations with State Participation by E. V. Gavrilin, S. V. Khetagurov

“…There had been used the formal legal method in the paper, methods of complex and interdisciplinary analysis, as well as General scientific methods, including the dialectical method and the method of system analysis. …”
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A YOLO11-Based Method for Segmenting Secondary Phases in Cu-Fe Alloy Microstructures by Qingxiu Jing, Ruiyang Wu, Zhicong Zhang, Yong Li, Qiqi Chang, Weihui Liu, Xiaodong Huang

“…Experimental results on the Cu-Fe alloy metallographic image dataset demonstrate that YOLO11 outperforms mainstream semantic segmentation models such as U-Net and DeepLabV3+ in terms of mAP (85.5%), inference speed (208 FPS), and model complexity (10.2 GFLOPs). The improved YOLO11 model achieves an mAP of 89.0%, a precision of 84.6%, and a recall of 81.0% on this dataset, showing significant performance improvements while effectively balancing inference speed and model complexity. …”
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Insights and Recommendations for the Assessment and Design of Fault Diagnosis Methods Applied to Modern Distribution Systems by Talita M. O. A. Cunha, Gabriela N. Lopes, Leonardo S. Lessa, Moises J. B. B. Davi, Mario Oleskovicz, Jose C. M. Vieira

“…The growing integration of Distributed Generation (DG) and the complexity of modern distribution networks present new challenges in fault diagnosis. …”
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Discrimination of the Skin Cells from Cellular-Resolution Optical Coherence Tomography by Deep Learning by Jui-Yun Yi, Sheng-Lung Huang, Shiun Li, Yu-You Yen, Chun-Yeh Chen

“…Deep learning algorithms (particularly convolutional neural networks, CNN) that extract features from images efficiently process the OCT’s complex images. We used four models to classify the images of five types of 2D-OCT skin cells. …”
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Identification of Rare Multiple Core‐Mantle Boundary Reflections PmKP Up To P7KP With Deep Learning by Sheng Dong, Yulin Chen, Baolong Zhang, Sidao Ni, Xiaofei Chen, Yi Wang

“…Our approach significantly improves the efficiency of PmKP phase identification and holds the capability to detect other weak core phases, such as PKiKP.…”
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Enhancing augmented reality with machine learning for hands-on origami training by Mikołaj Łysakowski, Jakub Gapsa, Chenxu Lyu, Thomas Bohné, Sławomir Konrad Tadeja, Piotr Skrzypczyński, Piotr Skrzypczyński

“…These findings suggest that while ML-supported AR systems can enhance the user experience, further optimization is required to streamline the feedback process and improve efficiency in complex manual tasks.…”
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