Automatic GPR detection of grouting defects behind the tunnel shield segments based on wavelet coherence analysis combined with modified Res-RCNN by Dengyi Wang, Ming Peng, Liu Liu, Xiongyao Xie, Zhenming Shi, Yaoying Liang, Jian Shen, Qiyu Wu

“…Then, a modified Res-RCNN is applied to automatically extract the defect features from the wavelet coherence images. Finally, the post-processing and visualization automatically give an intuitive clear feature map that shows the location and probability of the grouting defects along the tunnel. …”
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Analysis of the ion mobility spectra of chloroacetophenone, tris(2-chloroethyl)amine, and methanethiol by D. A. Aleksandrova, T. B. Melamed, E. P. Baberkina, E. S. Osinova, L. A. Luzenina, A. A. Kaplin, R. V. Yakushin, A. E. Kovalenko, G. V. Tsaplin, Yu. B. Sinkevich, A. A. Fenin, J. R. Shaltaeva, V. V. Belyakov, A. O. Shablya, A. G. Sazonov

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Epidemiological and clinical characteristics of bacterial co-detection in respiratory syncytial virus-positive children in Wenzhou, China, 2021 to 2023 by Xiaoxiao Qu, Xuanmei Ye, Jian Yu, Feifei Zheng, Yatian Tang, Fangling Yuan, Qipeng Xie

“…Predictive features were selected via the Boruta algorithm and modeled using XGBoost, with SHAP applied for interpretability. …”
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GlassBoost: A Lightweight and Explainable Classification Framework for Tabular Datasets by Ehsan Namjoo, Alison N. O’Connor, Jim Buckley, Conor Ryan

“…To evaluate the system, we apply it to an anomaly detection task in the context of intrusion detection systems (IDSs), using a dataset containing traffic features from both malicious and normal activities. …”
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Clinical features of fatigue in amyotrophic lateral sclerosis by E. V. Pervushina, M. A. Kutlubaev

“…The independent predictors of the severity of fatigue were calculated using linear regression analysis.Results. Fatigue was detected in 27 (64 %) patients. …”
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Attention-driven hybrid deep learning and SVM model for early Alzheimer’s diagnosis using neuroimaging fusion by Arjun Kidavunil Paduvilan, Godlin Atlas Lawrence Livingston, Sampath Kumar Kuppuchamy, Rajesh Kumar Dhanaraj, Muthuvel Subramanian, Amal Al-Rasheed, Masresha Getahun, Ben Othman Soufiene

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Features of the intestinal microbiota in children with intestinal parasitosis by O. V. Kovaleva, L. A. Lityaeva

“…The aim of the research is to study the features of the intestinal microbiota in children with parasitic invasions.Clinical and microbiological examination of 40 children aged from 9 months to 1 0 years with functional disorders of the intestine was carried out, in 20 of whom intestinal parasitoses were detected (15 of them — ascariasis, 5 — intestinal lambliosis) — the main group. …”
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FEATURES OF OTOGENIC INTRACRANIAL COMPLICATIONS AT THE PRESENT STAGE by A. A. Krivopalov, Yu. K. Yanov, S. V. Astashchenko, A. Yu. Shcherbuk, S. A. Artyushkin, S. G. Vakhrushev, I. S. Piskunov, V. S. Piskunov, N. A. Tuzikov

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Features of infective endocarditis in injection drug users by I. V. Demko, L. I. Pelinovskaya, M. V. Mankhayeva, O. P. Ishchenko, V. A. Mosina, A. Yu. Kraposhina, E. E. Ivanitskaya

“…An association of infective endocarditis with HIV infection (72,5%) and hepatitis C was detected in 97,5% of patients.Conclusion. Knowing of the infective endocarditis features in drug addicts makes it possible to improve the approaches to the diagnostics in earlier periods of its progression and thus makes the treatment of these patients more promising.…”
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Empirical Evaluation and Analysis of YOLO Models in Smart Transportation by Lan Anh Nguyen, Manh Dat Tran, Yongseok Son

“…You Only Look Once (YOLO) and its variants have emerged as the most popular real-time object detection algorithms. They have been widely used in real-time smart transportation applications due to their low-latency detection and high accuracy. …”
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Neurophysiologic features in glutaric aciduria type I by Dilek Yalnizoğlu, Neriman Sari, Güzide Turanli, Turgay Coşkun, Meral Topçu

“…This finding probably indicates underlying cerebral dysfunction, and is not a specific feature. However, it suggests that these patients may develop abnormal EEG features during the course of the disease, and thus a baseline EEG may be useful for comparison over time. …”
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UNSW-MG24: A Heterogeneous Dataset for Cybersecurity Analysis in Realistic Microgrid Systems by Zhibo Zhang, Benjamin Turnbull, Shabnam Kasra Kermanshahi, Hemanshu Pota, Jiankun Hu

“…Additionally, pivoting attacks and mimicry attacks are implemented to increase this dataset's heterogeneity for intrusion detection. Comprehensive features such as network flow attributes, system call parameters, and power measurement metrics are extracted from the generated dataset. …”
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Features of the microelement status in children with acute urticaria by G. E. Yalovega, A. A. Lebedenko, S. V. Mal’tsev, T. S. Kalmykova, L. A. Averkina, A. N. Posevina, A. O. Funik, O. E. Semernik, V. M. Novikovsky, E. V. Morgul’

“…Objective: Our aim was to study the features of the microelement status in children with acute urticaria.Methods: A comparative study included patients with acute urticaria of varying severity and healthy children (I and IIA groups of health). …”
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Automated Detection of Recent Mud Extrusions Using UAV Imagery and Deep Learning: A Comparative Analysis of Traditional and CNN-Based Approaches by M. Guastella, M. Guastella, A. Pisciotta, R. Martorana, A. D’Alessandro

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Towards precision agriculture tea leaf disease detection using CNNs and image processing by Irfan Sadiq Rahat, Hritwik Ghosh, Suresh Dara, Shashi Kant

“…The GlobalAveragePooling2D layer towards the model’s end succinctly summarizes the extracted features, preparing the model for the final classification stage. …”
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Pathomorphological features of inflammatory infiltrate in colorectal cancer by S. I. Tertyshnyi, O. H. Chucha

“…Aim: to investigate the pathomorphological features and severity of inflammatory infiltration in colorectal cancers. …”
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COVID-19 biobank: features of the cytokine profile by N. N. Sushentseva, O. S. Popov, S. V. Apalko, A. Yu. Anisenkova, S. V. Azarenko, K. V. Smantserev, D. N. Khobotnikov, T. V. Gladysheva, E. V. Minina, S. V. Strelyukhina, S. P. Urazov, D. Pavlovich, S. R. Fridman, S. G. Shcherbak

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Actively protective combinatorial analysis: A scalable novel method for detecting variants that contribute to reduced disease prevalence in high-risk individuals by J Sardell, S Das, K Taylor, C Stubberfield, A Malinowski, M Strivens, S Gardner

“…We show how this can be used to identify mechanisms in the background of normal cellular biology that work to slow or stop progression of complex, chronic diseases.Actively protective combinatorial analysis identifies combinations of features that contribute to reducing risk of disease in individuals who remain healthy even though their genomic profile suggests that they have high risk of developing disease. …”
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GNSS time series analysis of the crustal movement network of China: Detecting the optimal order of the polynomial term and its effect on the deterministic model by Shuguang Wu, Hua Ouyang, Houpu Li, Zhao Li, Haiyang Li, Yuefan He

“…The latter contains some stochastic noises, which can be affected by detecting the former parameters. If there are not enough parameters assumed, modeling errors will occur and adversely affect the analysis results. …”
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An automatic acne detection, severity, and assessment framework using generative adversarial network with deep neural network by Umara Khalid, Li Chen, Abdullah Ayub Khan, Faisal Mehmood

“…In this process, consultants receive better accuracy and efficiency during the process of acne detection and severity analysis. Second, this paper utilizes deep neural networks (DNNs) as a backend process to lightning the extraction of multi-scale features through a multi-hierarchy neural net for regionalized facial features to investigate distinction and localization. …”
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