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International Conference on Sciences of Electronics, Technologies of information and Telecommunications (SETIT)

作者： Anton Korshunov Information Systems Department The Institute for System Programming Russian Academy of Sciences Moscow Russia

The paper describes a method for keyterm extraction from messages of microblogs. The described approach utilizes the information obtained by the analysis of structure and content of Wikipedia. The algorithm is based on computation of “keyphraseness” measure for each term, i.e. an estimation of probability that it can be selected as a key in the text. The experimental study of the proposed technique demonstrated satisfactory results which significantly outpaces analogues. As a demonstration of possible application of the algorithm, the prototype of context-sensitive advertising system has been implemented. This system is able to obtain the descriptions of the goods relevant to the found keyterms from Amazon online store. Several suggestions are also made on how to utilize the information obtained by the analysis of Twitter messages in different auxiliary services.

关键词： Twitter Internet Blogs Encyclopedias Electronic publishing Databases

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Pattern Recognition - Applications and Methods 1

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丛书名： Advances in Intelligent systems and Computing

1000年

作者： Pedro Latorre Carmona J. Salvador Sánchez Ana L.N. Fred

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Hybrid Grey Wolf and Dipper Throated Optimization in Network Intrusion Detection systems

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Computers, Materials & Continua 2023年第2期74卷 2695-2709页

作者： Reem Alkanhel Doaa Sami Khafaga El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Rashid Amin Mostafa Abotaleb B.M.El-den Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science University of Engineering and TechnologyTaxilaPakistan Department of System Programming South Ural State UniversityChelyabinsk454080Russia

The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices *** to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing ***’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT *** imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network ***,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization *** prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE *** results showed that the proposed approach outperforms the other approaches and could boost the detection *** addition,a statistical analysis is performed to study the significance and stability of the proposed *** conducted experiments include seven different types of attack cases in the RPL-NIDS17 *** on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).

关键词： Metaheuristics grey wolf optimization dipper throated optimization dataset balancing locality sensitive hashing SMOTE

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Comparative analysis of signal processing methods secondary surveillance radar

Comparative analysis of signal processing methods secondary ...

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2018 International Conference on information and Telecommunication Technologies and Radio Electronics, UkrMiCo 2018

作者： Goriushkina, A.E. Svyd, I.V. Zavolodko, G.E. Maistrenko, G.V. National Technical University KhPI NTU KhPI Department of Computer Science and Programming Kharkiv Ukraine Kharkiv National University of Radio Electronics KNURE Dept. Radiotechnologies Information and Communication Systems Kharkiv Ukraine National Technical University KhPI NTU KhPI Department of Information Systems Kharkiv Ukraine Kharkiv National University of Radio Electronics KNURE Department of Electronic Computers Kharkiv Ukraine

ISBN: (纸本)9781538652640

In the paper, based on a comparative analysis of the methods of processing time-interval codes used as secondary surveillance radar information signals consisting of a different sequence of performing joint decoding operations, selecting signals by duration and time position, it is shown that the most effective is the signal processing method in which first the signals are decoded, then the signals are selected in accordance with the duration and in the future with the selection according to the time position, which provides the lowest probability of a false alarm of the first kind. © 2018 IEEE.

关键词： Errors

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Al-Biruni Earth Radius Optimization for COVID-19 Forecasting

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Computer systems Science & Engineering 2023年第7期46卷 883-896页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Tatiana Makarovskikh Amal H.Alharbi Doaa Sami Khafaga Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of System Programming South Ural State University454080ChelyabinskRussia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.

关键词： COVID-19 prediction meta-heuristic optimization LSTM Al-Biruni earth radius algorithm

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Dipper Throated Optimization for Detecting Black-Hole Attacks inMANETs

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Computers, Materials & Continua 2023年第1期74卷 1905-1921页

作者： Reem Alkanhel El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security and privacy,mobile ad-hoc network(MANET)continues to be in demand for additional debate and *** more MANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,MANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost MANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-MLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

关键词： Black-hole attack mobile ad-hoc network optimization dipper throated optimization

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Research into the Influence of Informative Speech Parameters on the Reliability of RNN-based Classification of Human Emotional States 26

Research into the Influence of Informative Speech Parameters...

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26th International Conference on Digital Signal Processing and its Applications, DSPA 2024

作者： Alimuradov, Alan K. Tychkov, Alexander Yu. Tyurin, Mikhail A. Dudnikov, Dmitry S. Tychkova, Anna N. Moiseev, Danil S. Myasnikova, Maria G. Student Research and Production Business Incubator Penza State University Penza Russia Penza State University Department of Radio Engineering and Radioelectronic Systems Penza Russia Penza State University Department of Automation and Telemechanics Penza Russia Penza State University Department of Scientific and Innovation Penza Russia Leninogorsk Oil College Department of Information Systems and Programming Leninogorsk Russia

ISBN: (纸本)9798350361728

Reliable classification of human emotional states from speech is dependent on speech signal processing algorithms and classification methods. The reliability is especially affected by the database of emotional speech informative parameters used to train classification methods. The paper is aimed at studying the influence of informative speech signal parameters on classification reliability of human emotional states based on a Recurrent Neural Network (RNN). The research is to expand the information space for emotional speech parameters through the use of an original signal representation algorithm based on Empirical Mode Decomposition (EMD), and assessing the impact on classification reliability using a five-layer RNN. The article outlines the research relevance and provides a brief overview of related academic papers. Local and global informative speech parameters relevant to human emotional states are considered in detail. The emotional speech database is described, and the speech signal representation algorithm based on modified decomposition methods is characterized. The research results on the method for classifying human emotional states based on a five-layer RNN using original and extended databases of emotional speech informative parameters are presented. Reliability assessment was performed by computing the confusion matrix for multi-class classification. The research results have evidenced an increase in classification reliability of human emotional states by an average of 2.66 % through expanding the information space for emotional speech parameters. The reliability ranges from 97.4 % to 98.3 % for the classification of emotional states, and from 95.8 % to 98.2 % for the classification of emotions. © 2024 IEEE.

关键词： Empirical mode decomposition

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Hydrogeological-Mathematical Model of Formation and Management of Resources and Quality of Fresh Underground Water of the Karakalpak Artesian Basin

Hydrogeological-Mathematical Model of Formation and Manageme...

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2021 International Conference on information Science and Communications Technologies, ICISCT 2021

作者： Seitnazarov, Kuanish Aytanov, Anvar Kojametov, Ermuhammed Asenbaev, Nurbek Nukus Branch of Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Faculty of 'Computer Engineering' Nukus Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Computer Systems Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Information Computer Technologies and Programming Tashkent Uzbekistan Nukus Branch of Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Information Security Nukus Uzbekistan

ISBN: (纸本)9781665432580

This article discusses the problems of using groundwater resources of the Karakalpak artesian basin. The task of drawing up a geological and mathematical model of the operational resources of groundwater in the Karakalpak artesian basin for the rational use of fresh groundwater in the basin is set. This article discusses the problem of lack of fresh groundwater in the territory of the Republic of Karakalpakstan. A method of hydrogeological-mathematical model of exploitable groundwater resources for the correct use of fresh groundwater is proposed. © 2021 IEEE.

关键词： Hydrogeology

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Social Engineering Attacks Detection Approach 13

Social Engineering Attacks Detection Approach

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13th International Conference on Dependable systems, Services and Technologies, DESSERT 2023

作者： Lysenko, Sergii Vorobiov, Volodymyr Bokhonko, Oleksandr Gaj, Piotr Savenko, Oleg Woloszyn, Jacek Khmelnitsky National University Department of Computer Engineering and Information Systems Khmelnitsky Ukraine Silesian University of Technology Gliwice Poland Khmelnitsky National University Department of Computer Engineering and System Programming Khmelnitsky Ukraine Kazimierz Pulaski University of Technology and Humanities in Radom Department of Informatics and Teleinformatics Radom Poland

ISBN: (纸本)9798350396119

The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits frequently capitalize on human psychology, trust, and a lack of vigilance to attain unauthorized entry to networks, systems, or data. In contrast to traditional social engineering tactics that center on psychological manipulation, technical social engineering attacks employ technological means and strategies to manipulate and beguile individuals. The paper presents an attempt to detect social engineering attacks. The approach utilized four machine learning algorithms (decision tree, random forest, K-nearest neighbor, and extreme gradient boosting). The analysis is centered on data collected from network hosts, which may serve as indicators of a potential social engineering attack. The empirical results demonstrated high detection accuracy. © 2023 IEEE.

关键词： Cybersecurity

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Analysis of Hardware and Software Tools for Implementation of Cognitive Radio Networks

Analysis of Hardware and Software Tools for Implementation o...

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2022 International Conference on information Science and Communications Technologies, ICISCT 2022

作者： Reypnazarov, Ernazar Khujamatov, Halimjon Khasanov, Doston Allamuratova, Zamira Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi The Computer Enjineering Faculty Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Data Communication Networks and Systems Tashkent Uzbekistan Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi Department of Information-Computer Technologies and Programming Tashkent Uzbekistan

ISBN: (纸本)9781665472296

This paper analyzes of the hardware and software tools for implementing a cognitive radio network. In particular, software-configurable radio modules, which are considered the main element of the cognitive network, were studied according to their main characteristics, among which the widely used ones were comparatively analyzed. As a result of the analysis, the HackRF One device was selected as the most preferred option for cognitive network research, and its working principles, structure, and characteristics were revealed in detail. It also provides information about the GNU Radio software environment and its capabilities, which are used to operate the HackRF One device. © 2022 IEEE.

关键词： Digital signal processing

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