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

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MP-NER: Morpho-Phonological Integration Embedding for Chinese Named Entity Recognition by Pu Li, Guopeng Cheng, Guojun Deng, Shuanghong Qu, Min Huang, Guoxiang Li

“…Additionally, the lack of clear separators between Chinese characters exacerbates these challenges, leading to difficulties in boundary detection and entity category determination. Inspired by the hieroglyphic and phonetic features of Chinese characters, this study proposes a multi-feature fusion embedding model (MP-NER). …”
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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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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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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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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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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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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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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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Robustness evaluation of commercial liveness detection platform by Pengcheng WANG, Haibin ZHENG, Jianfei ZOU, Ling PANG, Hu LI, Jinyin CHEN

“…Liveness detection technology has become an important application in daily life, and it is used in scenarios including mobile phone face unlock, face payment, and remote authentication.However, if attackers use fake video generation technology to generate realistic face-swapping videos to attack the living body detection system in the above scenarios, it will pose a huge threat to the security of these scenarios.Aiming at this problem, four state-of-the-art Deepfake technologies were used to generate a large number of face-changing pictures and videos as test samples, and use these samples to test the online API interfaces of commercial live detection platforms such as Baidu and Tencent.The test results show that the detection success rate of Deepfake images is generally very low by the major commercial live detection platforms currently used, and they are more sensitive to the quality of images, and the false detection rate of real images is also high.The main reason for the analysis may be that these platforms were mainly designed for traditional living detection attack methods such as printing photo attacks, screen remake attacks, and silicone mask attacks, and did not integrate advanced face-changing detection technology into their liveness detection.In the algorithm, these platforms cannot effectively deal with Deepfake attacks.Therefore, an integrated live detection method Integranet was proposed, which was obtained by integrating four detection algorithms for different image features.It could effectively detect traditional attack methods such as printed photos and screen remakes.It could also effectively detect against advanced Deepfake attacks.The detection effect of Integranet was verified on the test data set.The results show that the detection success rate of Deepfake images by proposed Integranet detection method is at least 35% higher than that of major commercial live detection platforms.…”
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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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Selecting change image for efficient change detection by Rui Huang, Ruofei Wang, Yuxiang Zhang, Yan Xing, Wei Fan, Kai Leung Yung

“…Abstract Change detection (CD) is a fundamental problem that aims at detecting changed objects from two observations. …”
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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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Texture Analysis and Classification using Local Binary Patterns and Statistical Features by Hasan Maher

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ROCK FRACTURES NEAR FAULTS: SPECIFIC FEATURES OF STRUCTURAL‐PARAGENETIC ANALYSIS by Yu. P. Burzunova

“…The new approach to structural‐paragenetic analysis of near‐fault fractures [Seminsky, 2014, 2015] and specific features of its application are discussed. This approach was tested in studies of fracturing in West Pribaikalie and Central Mongolia. …”
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Features of management and treatment of elderly patients with type 2 diabetes mellitus by L. Yu. Morgunov, E. V. Zemskova

“…Diagnostic criteria for diabetes mellitus in elderly patients do not differ from the general population, there are several features of their management. The elderly population varies greatly in functional and cognitive abilities. …”
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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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