Evaluation of a UAS-based Bridge Inspection Framework with Automated Damage Candidate Suggestion and Human-in-the-loop Damage Assessment by E. T. Bartczak, M. Bassier, M. Vergauwen

“…Unmanned aerial systems have shown considerable potential to improve bridge inspection procedures by enhancing safety, efficiency, and data quality. However, developing a comprehensive system that integrates safe flight planning, data acquisition, automated damage detection, and reporting while addressing practical challenges remains complex. …”
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A Hybrid Machine Learning Model for Accurate Autism Diagnosis by Durga Prasad Kavadi, Venkata Rami Reddy Chirra, Palacharla Ravi Kumar, Sai Babu Veesam, Sagar Yeruva, Lalitha Kumari Pappala

“…Additionally, a hybrid classification approach is introduced, combining Autoencoder (AE) with the Butterfly Optimization Algorithm (BOA) to enhance detection accuracy. To manage and process large datasets effectively, the MapReduce tool is used for efficient data handling. …”
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Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…Specifically, ANN models excel at detecting subtle, complex patterns that reflect battery health and performance, crucial for accurate SOC estimation. …”
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Molecular Xenomonitoring (MX) allows real-time surveillance of West Nile and Usutu virus in mosquito populations. by Clément Bigeard, Laura Pezzi, Raphaelle Klitting, Nazli Ayhan, Grégory L'Ambert, Nicolas Gomez, Géraldine Piorkowski, Rayane Amaral, Guillaume André Durand, Agathe M G Colmant, Cynthia Giraud, Katia Ramiara, Camille Migné, Gilda Grard, Thierry Touzet, Stéphan Zientara, Rémi Charrel, Gaëlle Gonzalez, Alexandre Duvignaud, Denis Malvy, Xavier de Lamballerie, Albin Fontaine

“…West Nile Virus (WNV) and Usutu virus (USUV) circulate through complex cryptic transmission cycles involving mosquitoes as vectors, birds as amplifying hosts and several mammal species as dead-end hosts. …”
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Optimization of a Navigation System for Autonomous Charging of Intelligent Vehicles Based on the Bidirectional A* Algorithm and YOLOv11n Model by Shengkun Liao, Lei Zhang, Yunli He, Junhui Zhang, Jinxu Sun

“…The optimized YOLOv11n model achieves state-of-the-art precision (P) and mAP@0.5 compared to YOLOv5, YOLOv8n, and the baseline model, with a minor 0.9% recall (R) deficit compared to YOLOv5 but more balanced overall performance and superior capability for small-object detection. By fusing the two improved modules, the proposed system successfully realizes autonomous charging navigation, providing an efficient solution for energy management in intelligent vehicles in real-world environments.…”
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The Optical System Design of a Space-Based Wide-Field Infrared Slitless Spectrometer by Yue Chen, Liang Zhou, Peiquan Chen, Pengkai Dong, Haiyang Zhang, Wenji She

“…With the increasingly complex space environment, the operational safety of spacecraft faces severe challenges, creating an urgent need to develop efficient and reliable space target detection and identification technologies. …”
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Occlusion Vehicle Target Recognition Method Based on Component Model by Haorui Han, Hanshan Li

“…Based on the U-net codec structure, combining multi-scale detection and double constraints loss to improve the visual region segmentation under complex background (VSRS) performance. …”
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Sensing-Aided Communication Method for Distributed Radar Communication System by Xinren Wang, Sisi Xia, Zhongzheng Ding, Qin Wang, Wenchao Xia, Haitao Zhao

“…Numerical simulation results show that this scheme can achieve excellent performance in complex real-world environments. This work contributes to the development of efficient ISAC solutions and provides insights for future research into 6G technologies.…”
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Towards sustainable architecture: Enhancing green building energy consumption prediction with integrated variational autoencoders and self-attentive gated recurrent units from mult... by Qing Zeng, Fang Peng, Xiaojuan Han

“…The framework incorporates self-attention mechanisms and Multi-Task Learning (MTL) strategies to capture long-term dependencies and complex patterns in energy consumption time series data, while simultaneously optimizing prediction accuracy and anomaly detection. …”
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Community Clustering and Recommendation Toward Elderly Health Records: Probabilistic Representation Learning and Large Graph Search by Huijiong Ding

“…This approach enables more precise, efficient, and personalized healthcare interventions, wherein the key steps include: 1) Geometry-based feature selection from high-dimensional health data-This effectively reduces dimensionality while preserving discriminative health patterns. 2) Probabilistic multi-topic representations of individual health profiles-These latent space embeddings capture complex health-need interactions. 3) Graph-based community detection via shared clinical/behavioral traits-The algorithm identifies natural clusters with medical relevance. 4) Personalized intervention ranking by community relevance-This ensures tailored care plan recommendations for each subgroup. …”
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Cyborg insect factory: automatic assembly for insect-computer hybrid robot via vision-guided robotic arm manipulation of custom bipolar electrodes by Qifeng Lin, Nghia Vuong, Kewei Song, Phuoc Thanh Tran-Ngoc, Greg Angelo Gonzales Nonato, Hirotaka Sato

“…Abstract Insect–computer hybrid robots offer strong potential for navigating complex terrains. This study identified the intersegmental membrane between the pronotum and mesothorax of the Madagascar hissing cockroach as an effective site for electrical stimulation to control direction and speed. …”
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Deep Learning Model for Feature Extraction and Anomaly Recognition in High-Dimensional Energy Metering Data by Huakun Que, Zetao Jiang, Zhifeng Zhou, Yongsheng He, Xin Liu

“…Abnormal energy usage in buildings and industries, often caused by system malfunctions, leads to substantial energy waste. Detecting such anomalies is essential for cost control and efficient energy management. …”
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Two key algorithms for intelligent inspection robots in electric bicycle charging sheds by Yingjian An, Ge Wei

“…Experimental results demonstrate that the proposed MS-RRT* achieves a 100% exploration success rate in narrow channels, outperforming state-of-the-art methods in both efficiency and robustness. The improved SOLOv2 also surpasses Mask R-CNN in multi-category component recognition, ensuring reliable inspection in complex scenarios. …”
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Decoding burn trauma: biomarkers for early diagnosis of burn-induced pathologies by Fadi Khalaf, Daniella Touma, Alexandra Pappas, Lareina Hatim, Stephanie Wojtowicz-Piotrowski, Marc G. Jeschke

“…Abstract Burn injuries represent a significant global challenge due to their multifaceted nature, characterized by a complex cascade of metabolic and immune dysfunction that can result in severe complications. …”
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A Comprehensive Study of Recent Path-Planning Techniques in Dynamic Environments for Autonomous Robots by Nour AbuJabal, Mohammed Baziyad, Raouf Fareh, Brahim Brahmi, Tamer Rabie, Maamar Bettayeb

“…The review discusses the key trends, challenges, and gaps in current methods to emphasize the need for more efficient and robust algorithms that can handle complex and unpredictable dynamic environments. …”
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New Trends in the Methodologies of Determination of Benzodiazepine Residues in Biological Samples by Israel S. Ibarra, Isaí Vázquez-Garrido, Gabriela Islas, Juan F. Flores-Aguilar

“…The availability of efficient analytical methods is crucial for the determination of these drugs in a complex matrix such as biological samples in clinical settings. …”
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Environmental Applications of Mass Spectrometry for Emerging Contaminants by Anil Kumar Meher, Akli Zarouri

“…Addressing these challenges necessitates advanced analytical tools capable of detecting and quantifying trace levels of ECs in complex environmental matrices. …”
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Enhancing Privacy by Large Mask Inpainting and Fusion-Based Segmentation in Street View Imagery by Mahdi Khourishandiz, Abdollah Amirkhani

“…Our approach integrates semantic segmentation with 2D priors and multimodal data from cameras and LiDAR to achieve precise object detection in complex urban scenes. Detected regions are seamlessly filled using a large-mask inpainting technique based on fast Fourier convolutions (FFC), enabling efficient generalization to high-resolution imagery. …”
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SYSTEM AND ALGORITHM OF INTELLIGENT BIOMEDICAL SIGNAL PROCESSING AND ANALYSIS FOR HUMAN HEALTH STATUS REMOTE MONITORING SYSTEM by Nguyen Trong Tuyen, Tran Trong Huu, Nguyen Mau Thach, Zafar M. Yuldashev

“…A specific feature of such algorithms is change of the number of channels used for biomedical signal recording and processing according to the change of patient’s condition. To detect the exacerbation first symptoms by means of the patient's wearable computer, additional channels are activated for recording biomedical signals used to evaluate the expanded complex of diagnostically significant parameters of the disease and their integration when specifying the patient's condition. …”
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Analysis and Synthesis March Memory Tests by V. N. Yarmolik, V. A. Levantsevich, D. V. Demenkovets

“…Mathematical models of memory device faults and the efficiency of their detection, in particular, complex pattern sensitive faults of the PNPSFk type, based on classical march memory tests are presented. …”
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