Typhus: epidemiological evolution and features of a clinical case in Novosibirsk by E. I. Krasnova, Yu. V. Kazakova, V. G. Kuznetsova, V. V. Provorova, L. L. Pozdnyakova, E. N. Usolkina, L. M. Panasenko, E. A. Gaiduk, P. R. Dmitrieva

“…In the period 2019-2022 in the Novosibirsk Region cases of typhoid fever were not detected. The article reflects the epidemiological features of typhoid fever for the period 2014-2023. …”
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Features of a new Coronavirus infection in children of different ages by M. A. Shakmaeva, T. M. Chernova, V. N. Timchenko, T. A. Nachinkina, K. V. Tetyushin, T. A. Kaplina, M. D. Subbotina, O. V. Bulina, O. I. Afanasyeva

“…The new coronavirus infection (COVID-1 9) is a socially significant problem around the world. According to available statistics, complications are less common among children, asymptomatic or mild forms of the disease prevail more often.This article presents the features of the viral landscape of the upper respiratory tract in children with ARVI in a pandemic, the clinical and laboratory features of the course of COVID-1 9 in children of different ages.It was found that SARS-CoV-2 is detected only in a third (32.9%) of hospitalized patients with respiratory symptoms, in 4.3% of cases — in combination with seasonal CoV-OC43 / CoV-229E, in 1 1.6% — with other respiratory viruses. …”
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The current state and problems of studying the biological effects of THz irradiation by E. A. Butikova, I. A. Razumov, O. V. Poveshchenko, V. V. Kanygin

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FEATURES OF CYTOKINE REGULATION IN PATIENTS WITH MECHANICAL JAUNDICE OF MALIGNANT GENESIS by O. V. Smirnova, V. V. Tsukanov, N. M. Titova, B. G. Gubanov

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Features of conducting a forensic commodity examination of furniture products by M. V. Hаrbuz, L. Yu. Ulybіnа

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A survey of face recognition techniques under occlusion by Dan Zeng, Raymond Veldhuis, Luuk Spreeuwers

“…Second the authors analyse how the existing face recognition methods cope with the occlusion problem and classify them into three categories, which are given as: 1) occlusion robust feature extraction approaches, 2) occlusion aware face recognition approaches, and 3) occlusion recovery based face recognition approaches. …”
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Protocol-Based Deep Intrusion Detection for DoS and DDoS Attacks Using UNSW-NB15 and Bot-IoT Data-Sets by Muhammad Zeeshan, Qaiser Riaz, Muhammad Ahmad Bilal, Muhammad K. Shahzad, Hajira Jabeen, Syed Ali Haider, Azizur Rahim

“…In this paper, we propose a Protocol Based Deep Intrusion Detection (PB-DID) architecture, in which we created a data-set of packets from IoT traffic by comparing features from the UNSWNB15 and Bot-IoT data-sets based on flow and Transmission Control Protocol (TCP). …”
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Speaker verification method based on cross-domain attentive feature fusion by Zhen YANG, Tianlang WANG, Haiyan GUO, Tingting WANG

“…Aiming at the problem that the lack of structure information among speech signal sample in the front-end acoustic features of speaker verification system, a speaker verification method based on cross-domain attentive feature fusion was proposed.Firstly, a feature extraction method based on the graph signal processing (GSP) was proposed to extract the structural information of speech signals, each sample point in a speech signal frame was regarded as a graph node to construct the speech graph signal and the graph frequency information of the speech signal was extracted through the graph Fourier transform and filter banks.Then, an attentive feature fusion network with the residual neural network and the squeeze-and- excitation block was proposed to fuse the features in the traditional time-frequency domain and those in the graph frequency domain to promote the speaker verification system performance.Finally, the experiment was carried out on the VoxCeleb, SITW, and CN-Celeb datasets.The experimental results show that the proposed method performs better than the baseline ECAPA-TDNN model in terms of equal error rate (EER) and minimum detection cost function (min-DCF).…”
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Speaker verification method based on cross-domain attentive feature fusion by Zhen YANG, Tianlang WANG, Haiyan GUO, Tingting WANG

“…Aiming at the problem that the lack of structure information among speech signal sample in the front-end acoustic features of speaker verification system, a speaker verification method based on cross-domain attentive feature fusion was proposed.Firstly, a feature extraction method based on the graph signal processing (GSP) was proposed to extract the structural information of speech signals, each sample point in a speech signal frame was regarded as a graph node to construct the speech graph signal and the graph frequency information of the speech signal was extracted through the graph Fourier transform and filter banks.Then, an attentive feature fusion network with the residual neural network and the squeeze-and- excitation block was proposed to fuse the features in the traditional time-frequency domain and those in the graph frequency domain to promote the speaker verification system performance.Finally, the experiment was carried out on the VoxCeleb, SITW, and CN-Celeb datasets.The experimental results show that the proposed method performs better than the baseline ECAPA-TDNN model in terms of equal error rate (EER) and minimum detection cost function (min-DCF).…”
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Key nodes identification in complex networks based on subnetwork feature extraction by Luyuan Gao, Xiaoyang Liu, Chao Liu, Yihao Zhang, Giacomo Fiumara, Pasquale De Meo

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Feature Coding and Graph via Transformer: Different Granularities Classification for Aircraft by Jianghao Rao, Senlin Qin, Zongyan An, Jianlin Zhang, Qiliang Bao, Zhenming Peng

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IoT intrusion detection method for unbalanced samples by ANTONG P, Wen CHEN, Lifa WU

“…In recent years, network traffic increases exponentially with the iteration of devices, while more and more attacks are launched against various applications.It is significant to identify and classify attacks at the traffic level.At the same time, with the explosion of Internet of Things (IoT) devices in recent years, attacks on IoT devices are also increasing, causing more and more damages.IoT intrusion detection is able to distinguish attack traffic from such a large volume of traffic, secure IoT devices at the traffic level, and stop the attack activity.In view of low detection accuracy of various attacks and sample imbalance at present, a random forest based intrusion detection method (Resample-RF) was proposed, which consisted of three specific methods: optimal sample selection algorithm, feature merging algorithm based on information entropy, and multi-classification greedy transformation algorithm.Aiming at the problem of unbalanced samples in the IoT environment, an optimal sample selection algorithm was proposed to increase the weight of small samples.Aiming at the low efficiency problem of random forest feature splitting, a feature merging method based on information entropy was proposed to improve the running efficiency.Aiming at the low accuracy problem of random forest multi-classification, a multi-classification greedy transformation method was proposed to further improve the accuracy.The method was evaluated on two public datasets.F1 reaches 0.99 on IoT-23 dataset and 1.0 on Kaggle dataset, both of which have good performance.The experimental results show that the proposed model can effectively identify the attack traffic from the massive traffic, better prevent the attack of hackers on the application, protect the IoT devices, and thus protect the related users.…”
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ShipYOLO: An Enhanced Model for Ship Detection by Xu Han, Lining Zhao, Yue Ning, Jingfeng Hu

“…In response to this problem, this study uses an improved YOLO-V4 detection model (ShipYOLO) to detect ships. …”
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Binocular Vision-Based Target Detection Algorithm by Huiguo Zhang

“…In the field of target detection, algorithms are challenged with multi-objective optimization problems in identifying detection targets, and it is also crucial to improve the recognition of small and insignificant targets. …”
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Customer Attrition Detection Using the LGBM Model by Huang Jie

“…To select the most suitable model for accurately detecting customer churn, this study performs preprocessing, including data cleaning, feature engineering, and feature selection. …”
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Features of the clinical course of novel coronavirus infection COVID-19 in children by T. B. Bikmetov, I. V. Zorin, R. S. Yakupova

“…Background. The problem of the clinical course and complications of a novel coronavirus infection (COVID-19) in children is given special attention in pediatrics. …”
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MODERN METHODS OF AUTOMATIC RECTANGLE OBJECTS DETECTION by E. S. Matusevich, I. E. Kheidorov

“…The algorithms were tested on the base of 1000 passports for the problem of accurate photo edges detection.…”
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An efficient fusion detector for road defect detection by Li Yang, Jingwei Deng, Hailong Duan, Chenchen Yang

“…To address this problem, an SCB-AF-Detector is proposed, which combines space-to-depth convolution with bottleneck transformer and employs enhanced asymptotic feature pyramid network to fuse features. …”
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Sparse wavelet decomposition in problems of vibration-based diagnostics of rotary equipment by Y. P. Aslamov, A. P. Aslamov, I. G. Davydov, A. V. Borsuk

“…At the present an increase in the effectiveness of vibration-based diagnostics is achieved by automating the solution of this problem and also by the use of matched sets of informative features, which causes the urgency of the development of algorithms for their detection. …”
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Immunohistochemical features of cyclooxygenase-2 expression in endometrial hyperplasia without atypia by N. Ye. Horban, T. D. Zadorozhna, I. B. Vovk, V. K. Kondratiuk, S. M. Kilichevych

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