Adaptive Autoencoder-Based Intrusion Detection System with Single Threshold for CAN Networks by Donghyeon Kim, Hyungchul Im, Seongsoo Lee

“…A portion of the attack data was utilized to determine the optimal detection threshold using a Gaussian kernel density estimation function, while the frame count was selected based on error rate analysis. …”
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Performance evaluation of structural variation detection using DNBSEQ whole-genome sequencing by Junhua Rao, Huijuan Luo, Dan An, Xinming Liang, Lihua Peng, Fang Chen

“…We found that these two SV sets were highly consistent of SV sites and genomic characteristics, including repetitive regions, GC distribution, difficult-to-sequence regions, and gene features, indicating the robustness of our comparative analysis and highlights the value of both platforms in understanding the genomic context of SVs. …”
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A Survey on Android Malware Detection Techniques Using Supervised Machine Learning by Safa J. Altaha, Ahmed Aljughaiman, Sonia Gul

“…Machine learning (ML) plays a significant role in malware analysis and detection because it can process huge amounts of data, identify complex patterns, and adjust to changing threats. …”
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Tracing truth: dynamic temporal networks for multi-modal fake news detection by Jiaen Hu, Juan Zhang, Zichen Li

“…Further analysis demonstrates that the proposed DTN model exhibits high accuracy and effectiveness in multi-modal fake news detection.…”
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DCW-YOLO: An Improved Method for Surface Damage Detection of Wind Turbine Blades by Li Zou, Anqi Chen, Chunzi Li, Xinhua Yang, Yibo Sun

“…In light of these challenges, a novel model named DCW-YOLO for surface damage detection of WTBs is proposed in this research, which leverages image data collected by unmanned aerial vehicles (UAVs) and the YOLOv8 algorithm for image analysis. …”
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Artificial intelligence and 3D subsurface interpretation for bright spot and channel detections by Yasir Bashir, Muhammad Afiq Aiman Bin Zahari, Abdullah Karaman, Doğa Doğan, Zeynep Döner, Ali Mohammadi, Syed Haroon Ali

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Detection of weeds in vegetables using image classification neural networks and image processing by Huiping Jin, Kang Han, Kang Han, Hongting Xia, Bo Xu, Xiaojun Jin

“…Image classification neural networks were utilized to identify the grid cells containing vegetables and exclude them from further analysis. Finally, image processing technology was employed to segment the non-vegetable grid images based on their color features. …”
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UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions by Charles Buchanan, Gogulan Karunanithy, Olga Tkachenko, Michael Barber, Michael T. Marty, Timothy J. Nott, Christina Redfield, Andrew J. Baldwin

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IoT and cloud-based non-invasive diabetes detection system from photoplethysmogram by Nusrat Jahan Papri, Ajmal Ahmed, Aditta Chowdhury

“…With the rapid advancements of the Internet of Things (IoT) and cloud computing, healthcare is evolving for early disease detection and personalized treatment solutions. The aim of this research is to develop a system based on the Internet of Things (IoT) for non-invasive diabetes detection using Photoplethysmography (PPG) signals. …”
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The Main Arboviruses and Virus Detection Methods in Vectors: Current Approaches and Future Perspectives by Amanda Montezano Cintra, Nathália Mayumi Noda-Nicolau, Milena Leite de Oliveira Soman, Pedro Henrique de Andrade Affonso, Guilherme Targino Valente, Rejane Maria Tommasini Grotto

“…In addition, this work provides a comparative analysis of diverse laboratory methodologies for viral detection in vectors. …”
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Multimodal Detection of Agitation in People With Dementia in Clinical Settings: Observational Pilot Study by Abeer Badawi, Somayya Elmoghazy, Samira Choudhury, Sara Elgazzar, Khalid Elgazzar, Amer M Burhan

“…The system combines digital biomarkers collected from the EmbracePlus (Empatica Inc) wristband with video-based behavioral monitoring. Facial features in video frames were anonymized using a masking tool, and a deep learning model was used for AA detection. …”
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MAGECODE: Machine-Generated Code Detection Method Using Large Language Models by Hung Pham, Huyen Ha, van Tong, Dung Hoang, Duc Tran, Tuyen Ngoc Le

“…In this paper, we take into account both semantic features extracted from Large Language Models (LLMs) and the applicability of metrics (e.g., Log-Likelihood, Rank, Log-rank, etc.) for source code analysis. …”
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Particle swarm optimization with YOLOv8 for improved detection performance of tomato plants by Sarah M. Ayyad, Nada M. Sallam, Samah A. Gamel, Zainab H. Ali

“…Thirdly, the proposed framework was compared with many cutting-edge object detection architectures for tomato harvesting, e.g., Convolutional neural network (CNN), Mask R-CNN and color analysis, and other models based on handcrafted features. …”
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Harnessing Aggregation‐Induced Emission‐Based Detection Toolbox for Diagnostics of Urogenital Tumors by Wenzhe Chen, Hantian Guan, Yongfeng Lu, Guohua Zeng, Di Gu, Keying Guo, Cheng Jiang, Hongxing Liu

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Multistage pig identification using a sequential ear tag detection pipeline by Martin Wutke, Damiano Debiasi, Shobhana Tomar, Jeanette Probst, Nicole Kemper, Kai Gevers, Marc-Alexander Lieboldt, Imke Traulsen

“…Consequently, synthetic features such as ear tags have become widely adopted. …”
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A Microsphere-Based Sensor for Point-of-Care and Non-Invasive Acetone Detection by Oscar Osorio Perez, Ngan Anh Nguyen, Landon Denham, Asher Hendricks, Rodrigo E. Dominguez, Eun Ju Jeong, Marcio S. Carvalho, Mateus Lima, Jarrett Eshima, Nanxi Yu, Barbara Smith, Shaopeng Wang, Doina Kulick, Erica Forzani

“…In this study, we introduce a novel colorimetric sensor designed for potential continuous acetone detection in biological fluids. The sensor features a polydimethylsiloxane (PDMS) shell that encapsulates a sensitive and specific liquid-core acetone-sensing probe. …”
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Application of a UAV-borne GPR system in the detection of water bodies and cavities by Ying WANG, Chenchen SUN, Lu ZHANG, Yifei CHEN, Song LU, Feng ZHOU

“…This led to improved identifiability of waveform features, as well as enhanced accuracy and intuitiveness of data interpretation and analysis. …”
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Diagnostic value of multi-tumor-associated autoantibody expression in esophageal squamous cell carcinoma and correlation of clinical features by Sihao Zhou, Sihao Zhou, Kejun Liu, Kejun Liu, Yuyu Yang, Chuan Yuan, Chuan Yuan, Yi Liu, Yi Liang, Wenhao Li, Jingjing Zhang, Hongyu Ye, Sheng Gong, Yingmeng Wu, Weizhao Huang

“…The diagnostic efficacy of the combined test with the remaining five antibodies (PGP9.5, SOX2, GBU4-5, MAGE-A1, and CAGE) was similar to that of the 7-TAAB combined test after eliminating the two antibodies with low expression rates. (4) Univariate analysis revealed significant differences in the positive expression rates of the 7-TAAB combination test in terms of age, hemoglobin level, albumin level, tumor location, tumor length, lymph node stage, and tumor clinical stage (P < 0.05), and multivariate analysis revealed that age and lymph node stage were independent factors affecting antibody expression.ConclusionThe multi-tumor-associated autoantibody combination test not only has a good auxiliary diagnostic value but also closely correlates with the clinical features of ESCC.…”
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A Pictorial Review of CT Angiography Imaging Features of Aortic Dissection and Its Complications: Role of Emergency Teleradiology by Reddy Muni Harika, Rao Pallavi, Kalyanpur Arjun

“…When coupled with emergency teleradiology analysis, the clinical outcomes can be significantly improved.…”
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Human Depth Sensors-Based Activity Recognition Using Spatiotemporal Features and Hidden Markov Model for Smart Environments by Ahmad Jalal, Shaharyar Kamal, Daijin Kim

“…Then, these features are processed by principal component analysis for dimension reduction and better feature representation. …”
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