Features of water extracts sample preparation of solar panels components for biotesting by M. Semenova, A. Smirnov, I. Vezhenkova, T. Kustov, A. Kovalevskaya

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Passive Diagnosis for WSNs Using Time Domain Features of Sensing Data by Lufeng Mo, Jinrong Li, Guoying Wang, Liping Chen

“…This paper presents a passive diagnosis method used for fault detection and fault classification based on the time domain features of sensing data (TDSD). …”
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Allgrove syndrome in endocrinology: Difficulties of diagnosis and treatment features. Case report by Uliana V. Buyvalenko, Anna R. Levshina, Anna K. Eremkina, Kseniya A. Komshilova, Nadezhda M. Platonova

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Encrypted traffic identification scheme based on sliding window and randomness features by LIU Jiachi, KUANG Boyu, SU Mang, XU Yaqian, FU Anmin

“…However, data encryption, while ensuring privacy and security, has also become a means for illegal content to evade network supervision. To achieve the detection and analysis of encrypted traffic, it has become necessary to efficiently identify encrypted traffic. …”
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Evaluating Sparse Feature Selection Methods: A Theoretical and Empirical Perspective by Monica Fira, Liviu Goras, Hariton-Nicolae Costin

“…The mathematical foundations of feature selection methods inspired by compressed detection are presented, highlighting how the principles of sparse signal recovery can be applied to identify the most relevant features. …”
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Features of inpatient treatment of patients with skin diseases and sexually transmitted infections by V. V. Korolenko, T. S. Gruzieva

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Clinical-epidemiological and pathogenetic features of viral hepatitis C in the hemodialysis departments by R. N. Akalaev, G. Z. Aripkhodzhaeva, S. A. Rashidova, A. N. Abdullaev, K. A. Khashimov

“…When analyzing the clinical examination and laboratory test results of 395 patients, the parenteral viral infection markers were detected in 181 patients (45.8%). The analysis of the overall incidence of viral hepatitis showed that chronic viral hepatitis C had the highest rates and was found in 125 patients (31.6%). …”
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Clinical and laboratory features of the course of the Crimean-Congo hemorrhagic fever in Uzbekistan by S. S. Saydaliev, R. I. Kasimova, U. Kh. Mirzaev, E. I. Musabaev

“…The results of this study are based on a retrospective analysis of all confirmed patients.Results: 81 patients with CCHF confirmed by enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) methods were examined. …”
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Insulation Condition Assessment of High-Voltage Single-Core Cables Via Zero-Crossing Frequency Analysis of Impedance Phase Angle by Fang Wang, Zeyang Tang, Zaixin Song, Enci Zhou, Mingzhen Li, Xinsong Zhang

“…An impedance spectroscopy analysis model of the frequency response of high-voltage single-core cables under different aging conditions has been established. …”
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RESEARCH ON VISUAL DETECTION METHOD OF SOUND FILM BROKEN GLUE DEFECT by Jianchun Liu, Xunjin Jiang, Chaoqi Huang, Yuquan Lin

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Trading Community Analysis of Countries’ Roll-On/Roll-Off Shipping Networks Using Fine-Grained Vessel Trajectory Data by Shichen Huang, Tengda Sun, Jing Shi, Piqiang Gong, Xue Yang, Jun Zheng, Huanshuai Zhuang, Qi Ouyang

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Detecting tropical freshly-opened swidden fields using a combined algorithm of continuous change detection and support vector machine by Ningsang Jiang, Peng Li, Zhiming Feng

“…The development of data-, information-, and knowledge-based algorithms for monitoring swidden agriculture requires integration of multi-dimensional features. The first part of the Continuous Change Detection and Classification (CCDC) algorithm holds promising potential in capturing abrupt changes. …”
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Plant disease detection with generative adversarial networks by Garam Han, Derek Kwaku Pobi Asiedu, Kwabena Ebo Bennin

“…Generative Adversarial Networks (GANs) have emerged as a promising approach for enhancing image detection and facilitating image classification. Deep learning models, which exhibit high classification accuracy, have proven advantageous over conventional approaches for Plant disease detection (PDD). …”
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Review of malware detection and classification visualization techniques by Jinwei WANG, Zhengjia CHEN, Xue XIE, Xiangyang LUO, Bin MA

“…With the rapid advancement of technology, network security faces a significant challenge due to the proliferation of malicious software and its variants.These malicious software use various technical tactics to deceive or bypass traditional detection methods, rendering conventional non-visual detection techniques inadequate.In recent years, data visualization has gained considerable attention in the academic community as a powerful approach for detecting and classifying malicious software.By visually representing the key features of malicious software, these methods greatly enhance the accuracy of malware detection and classification, opening up extensive research opportunities in the field of cyber security.An overview of traditional non-visual detection techniques and visualization-based methods were provided in the realm of malicious software detection.Traditional non-visual approaches for malicious software detection, including static analysis, dynamic analysis, and hybrid techniques, were introduced.Subsequently, a comprehensive survey and evaluation of prominent contemporary visualization-based methods for detecting malicious software were undertaken.This primarily encompasses encompassed the integration of visualization with machine learning and visualization combined with deep learning, each of which exhibits distinct advantages and characteristics within the domain of malware detection and classification.Consequently, the holistic consideration of several factors, such as dataset size, computational resources, time constraints, model accuracy, and implementation complexity, is necessary for the selection of detection and classification methods.In conclusion, the challenges currently faced by detection technologies are summarized, and a forward-looking perspective on future research directions in the field is provided.…”
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Unsupervised detection of semantic correlations in big data by Santiago Acevedo, Alex Rodriguez, Alessandro Laio

“…The proposed algorithm is largely insensitive to the so-called curse of dimensionality, and can therefore be used in big data analysis. We test this approach identifying phase transitions in model magnetic systems and we then apply it to the detection of semantic correlations of images and text inside deep neural networks.…”
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2D Object Detection: A Survey by Emanuele Malagoli, Luca Di Persio

“…This survey provides a comprehensive review of the evolution of 2D generic object detection, tracing its development from traditional methods relying on handcrafted features to modern approaches driven by deep learning. …”
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A Mobile Analytical Chemistry Workstation with a C4D Sensor for Rapid Detection of Organophosphates Under Field Conditions by Yineng Wang, Xi Cao, Walter Messina, Anna Maria Hogan, Justina Ugwah, Eric Moore

“…The system features a streamlined workflow that includes in-field sample collection, microfluidic analysis, and the wireless transmission of data to a central command centre for immediate decision-making. …”
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Complex Indoor Human Detection with You Only Look Once: An Improved Network Designed for Human Detection in Complex Indoor Scenes by Yufeng Xu, Yan Fu

“…The comprehensive case analysis and comparative evaluation highlight the superiority and effectiveness of this method in complex indoor human detection tasks.…”
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A tailored deep learning approach for early detection of oral cancer using a 19-layer CNN on clinical lip and tongue images by Pinjie Liu, Kambiz Bagi

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An approach to malignant mammary phyllodes tumors detection by Ilić Ivan, Ranđelović Pavle, Ilić Ratko, Katić Vuka, Milentijević Maja, Veličković Ljubinka, Krstić Miljan

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