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Development the Numerical Method to Solve the Inverse Initial Value Problem for the Thermal Conductivity Equation of Composite Materials

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Journal of Physics: Conference Series 2021年第3期1879卷

作者： H K Al-Mahdawi Department of System Programming School of Electronic Engineering and Computer Science South Ural State University Lenina 76 Chelyabinsk 454080 Russia

In this paper, the heat conduction equation for composite materials posed and solved. This problem is known as an inverse initial value problem for the heat conduction equation. In order to solve and formulate this inverse problem, the function spaces must be defined and represented. By studying and solving the direct problem for the heat equation in composite materials, it is possible to determine the function spaces and solve the inverse initial value problem. Scientific methods used: the separation of variables method used to solve the direct problem for the heat equation. It found that method separation of variables does not completely lead to the solution of the inverse initial value problem, since this method leads to a divergent series of solutions and rather massive errors. The heat conduction problem can be formulated as Fredholm integral first kind equations. The discretization algorithm applied to reformulated the problem as linear operator problem as matrix and vectors form. Then, Tikhonov's regularization inversion method has been used to find an approximation solution. Finally, as shown in the numerical example the regularized approximate solutions obtained.

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Method of Activity of Intelligent Agent for Semantic Analysis of Software Requirements

Method of Activity of Intelligent Agent for Semantic Analysi...

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IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems

作者： Olga Pavlova Tetiana Hovorushchenko Artem Boyarchuk System Programming Department of Khmelnytsky National University Computer Engineering & System Programming Department of Khmelnytsky National University Lecturer of Computer Systems Networks and Cybersecurity Department of National Aerospace University "Kharkiv Aviation Institute"

ISBN: (纸本)9781728140704

The paper deals with the development of the method of activity and the realization of the intelligent agent (IA) for semantic analysis of the natural language software requirements. This IA performs the analysis of the requirements, determines the number and percentage of missing indicators for determining the metrics of complexity and quality of software, displays which indicators are missing for each metric, and also forms the real ontology of the domain "Software engineering" (part "Quality and complexity of software. Metric analysis"). During an experiment, which is conducted with the help of the realized IA, the semantic analysis of requirements for the Internet of Things (IoT)-system was performed. Such analysis provides an increase of the volume and ensures of the sufficiency of metric information in the software requirements, which, in turn, provides an improvement in the quality of the software of IoT-system.

关键词： Natural language software requirements Semantic analysis Intelligent agent (IA) Ontology-based intelligent agent (OBIA) Internet of things (IoT)-system software requirements Intelligent agents Semantics Metronidazole activity INFORMATION ASSURANCE Metric computer software

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A flexible framework for web-based virtual reality presentation of cultural heritage

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AIP Conference Proceedings 2021年第1期2333卷

作者： Dimo Chotrov Angel Bachvarov 1Technical University Sofia Faculty of Computer Systems and Technologies Department Programming and Computer Technologies Bulgaria 2Technical University Sofia Faculty of Mechanical Engineering Department Automation of Discrete Production Engineering Bulgaria

The Virtual Reality (VR) experiences are great for an engaging presentation creating wide public awareness of cultural heritage, especially if the experience is built on a web-based technology. One of the still posing challenges is that once an application has been developed, for example for a virtual museum or a virtual tour, it usually remains fixed to an embedded in the application model. Adding new functionalities or interaction paradigms needs additional development and new deployment. In this paper, we propose a framework, which achieves the decoupling of an experience from the used models and interaction paradigms through scene and input templates and configuration files. This allows an easy way for generation of a variety of experiences even by people with no or limited programming skills.

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Using the Model of a Functional Rationalizer of Consumer Behavior in Recommendation Systems for Managing the Transport Activity of the Urban Population 23

Using the Model of a Functional Rationalizer of Consumer Beh...

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23rd International Conference on Soft Computing and Measurements, SCM 2020

作者： Seliverstov, Yaroslav A. Seliverstov, Svytoslav A. Podoprigora, Nikolay V. Starichenkov, Alexey L. Naryshkin, Roman S. Solomenko Institute of Transport Problems Russian Academy of Sciences Institute of Computer Science and Technology Peter the Great St.Petersburg Polytechnic University Laboratory of Intelligent Transport Systems St. Petersburg Russia Saint Petersburg State University of Architecture and Civil Engineering Department of Ground Transportation Technological Machines St. Petersburg Russia Saint Petersburg Electrotechnical University 'LETI' Department of Ship Control Systems St. Petersburg Russia Saint Petersburg State University Department of Programming Technology St. Petersburg Russia

ISBN: (纸本)9781728196923

An overview of existing urban software mobile applications of the transport and economic direction is given. A model of a functional rationalizer of consumer behavior is being built. The software model of the functional rationalizer of consumer behavior (SM FRCB) was developed for the first time. PMFRCB allows the user to expand the number of his preferred needs (occupations, activities) during the daily cycle through intelligent recommendations. Also, SM FRCB allows you to optimize needs (activities, activities) at the cost and rate of their use. The SM FRCB is made in Python_3 using the libraries matplotlib, collections, numpy, pyplot, mplot3d. The analysis of consumer behavior before and after using the functional rationalizer model is carried out. The graphical results of a structural analysis of the costs of old and new consumer behavior, analysis of consumer behavior within the boundaries of the theory of possibilities and the model of transport behavior of a resident before and after applying the functional rationalizer model are presented. The prospects of further improving the SM FRCB are considered. © 2020 IEEE.

关键词： Smart city

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Cyber-Typhon: An Online Multi-task Anomaly Detection Framework 15th

Cyber-Typhon: An Online Multi-task Anomaly Detection Framewo...

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15th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2019

作者： Demertzis, Konstantinos Iliadis, Lazaros Kikiras, Panayiotis Tziritas, Nikos School of Engineering Department of Civil Engineering Faculty of Mathematics Programming and General Courses Democritus University of Thrace Kimmeria Xanthi Greece School of Science Department of Computer Science University of Thessaly Lamia Greece Research Center for Cloud Computing Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9783030198220

According to the Greek mythology, Typhon was a gigantic monster with one hundred dragon heads, bigger than all mountains. His open hands were extending from East to West, his head could reach the sky and flames were coming out of his mouth. His body below the waste consisted of curled snakes. This research effort introduces the "Cyber-Typhon" (CYTY) an Online Multi-Task Anomaly Detection Framework. It aims to fully upgrade old passive infrastructure through an intelligent mechanism, using advanced Computational Intelligence (COIN) algorithms. More specifically, it proposes an intelligent Multi-Task Learning framework, which combines On-Line Sequential Extreme Learning Machines (OS-ELM) and Restricted Boltzmann Machines (RBMs) in order to control data flows. The final target of this model is the intelligent classification of Critical Infrastructures’ network flow, resulting in Anomaly Detection due to Advanced Persistent Threat (APT) attacks. © 2019, IFIP International Federation for Information Processing.

关键词： Anomaly detection

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A botnet detection approach based on the clonal selection algorithm 9

A botnet detection approach based on the clonal selection al...

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9th IEEE International Conference on Dependable Systems, Services and Technologies, DESSERT 2018

作者： Lysenko, Sergii Bobrovnikova, Kira Savenko, Oleg Department of Computer Engineering and System Programming Khmelnitsky National University Instytutska 11 Khmelnitsky Ukraine

ISBN: (纸本)9781538659038

The paper presents a new technique for the botnets' detection in the corporate area networks. It is based on the usage of the algorithms of the artificial immune systems. Proposed approach is able to distinguish benign network traffic from malicious one using the clonal selection algorithm taking into account the features of the botnet's presence in the network. An approach present the main improvements of the BotGRABBER system. It is able to detect the IRC, HTTP, DNS and P2P botnets. © 2018 IEEE.

关键词： Botnet

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DDoS botnet detection technique based on the use of the semi-supervised fuzzy C-means clustering 14

DDoS botnet detection technique based on the use of the semi...

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14th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops, ICTERI 2018

作者： Lysenko, Sergii Savenko, Oleg Bobrovnikova, Kira Department of Computer Engineering System Programming Khmelnitsky National University Instytutska 11 Khmelnitsky Ukraine

A new technique for the DDoS botnet detection based on the botnets network features analysis is proposed. It uses the semi-supervised fuzzy c-means clustering. The proposed approach includes the learning and the detection stages. Analysis is based on the extracted from the network traffic features that may indicate the presence of the DDoS botnets' presence in the network. Experimental results demonstrated that the proposed technique ensures the DDoS botnet detection at the rate at about 95%. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Botnet

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Piquasso: A Photonic Quantum computer Simulation Software Platform

arXiv

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arXiv 2024年

作者： Kolarovszki, Zoltán Rybotycki, Tomasz Rakyta, Péter Kaposi, Ágoston Poór, Boldizsár Jóczik, Szabolcs Nagy, Dániel T.R. Varga, Henrik El-Safty, Kareem H. Morse, Gregory Oszmaniec, Michal Kozsik, Tamás Zimborás, Zoltán Quantum Computing and Quantum Information Research Group HUN-REN Wigner Research Centre for Physics Konkoly-Thege Miklós út 29-33 BudapestH-1525 Hungary Department of Programming Languages and Compilers Eötvös Loránd University Pázmány Péter sétány 1/a BudapestH-1117 Hungary Center for Theoretical Physics Polish Academy of Sciences Al. Lotników 32/46 Warszawa02-668 Poland Department of Physics of Complex Systems Eötvös Loránd University Pázmány Péter sétány 1/a BudapestH-1117 Hungary Quantinuum 17 Beaumont Street OxfordOX1 2NA United Kingdom Robert Bosch Kft. Gyömrői út 104. BudapestH-1103 Hungary Department of Computer Engineering Technical University of Munich Arcisstraße 21 München80333 Germany Algorithmiq Ltd. Kanavakatu 3C Helsinki00160 Finland

We introduce the Piquasso quantum programming framework, a full-stack open-source software platform for the simulation and programming of photonic quantum computers. Piquasso can be programmed via a high-level Python programming interface enabling users to perform efficient quantum computing with discrete and continuous variables. Via optional high-performance C++ backends, Piquasso provides state-of-the-art performance in the simulation of photonic quantum computers. The Piquasso framework is supported by an intuitive web-based graphical user interface where the users can design quantum circuits, run computations, and visualize the results. Copyright © 2024, The Authors. All rights reserved.

关键词： Quantum computers

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Structure and Functioning of Information Systems of Background Monitoring of Landscape Elements of Gorgany Nature Reserve

Structure and Functioning of Information Systems of Backgrou...

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International Conference on Advanced computer Information Technologies (ACIT)

作者： Yaroslav Nykolaychuk Yaroslav Petrashchuk Olena Slobodian Ihor Pitukh Taras Grynchyshyn Lyubov Nykolaychuk Volodymyr Hryha Department of Specialized Computer Systems Ternopil National Economic University Ternopil Ukraine Gorgany nature reserve Nadvirna Ukraine Department of Programming and Information Technologies Nadvirna College by National Transport University Nadvirna Ukraine Department of Social Communication and Law Ivano-Frankivsk National Technical University of Oil and Gas Ivano-Frankivsk Ukraine Department of Computer Engineering and Electronics Vasyl Stefanyk Precarpathian National University Ivano-Frankivsk Ukraine

ISBN: (数字)9781728167602

ISBN: (纸本)9781728167619

This paper discusses the structural organization of the background monitoring system (BMS) of the transboundary UNESCO World Heritage Site “Beech forests of the Carpathians and ancient beech forests of Germany” using actual data and information from Gorgany Nature Reserve in Ivano-Frankivsk, Ukraine. The features of the structure and functions of background monitoring of the protected natural resources, forests and wildlife of Gorgany Nature Reserve is based on modern methods of collecting and processing of digital data, implementation of the principles of Internet of Things and cloud technologies, combined with GPS-systems, sensor networks with the use of optical and fiber-optic telecommunication channels. The information technology of the background monitoring system is based on figurative cluster models of monitoring objects according to theoretical principles of statistical, correlatory, spectral, cluster, logic-statistical and entropy analysis.

关键词： Monitoring Forestry Correlation Optical fiber sensors Optical fibers Biological system modeling

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A Model of Deep Neural Network for Iris Classification With Different Activation Functions

A Model of Deep Neural Network for Iris Classification With ...

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2018 International Conference on Artificial Intelligence and Data Processing, IDAP 2018

作者： Eldem, Ayşe Eldem, Hüseyin Üstün, Deniz Department of Computer Engineering Karamanoǧlu Mehmetbey University Karaman Turkey Department of Technology and Computer Programming Karamanoǧlu Mehmetbey University Karaman Turkey

ISBN: (纸本)9781538668788

In recent years, deep neural network (DNN) has been frequently used for classification. In this study, iris flowers having 3 different types are classified by using DNN which are utilized the width and length of petal and sepal features as input. Some experiments are made for the iris dataset by using different activation functions and different epoch numbers. Then, the activation function which gives the best result is determined. The classification success of the developed model is achieved 96% for the iris dataset. © 2018 IEEE.

关键词： Deep neural networks

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