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arXiv 2022年

作者： Kostinakis, Konstantinos Morfidis, Konstantinos Demertzis, Konstantinos Iliadis, Lazaros Department of Civil Engineering Aristotle University Thessaloniki Aristotle University Campus Thessaloniki54124 Greece Terma Dasylliou Thessaloniki55535 Greece Laboratory of Complex Systems Department of Physics Faculty of Sciences International Hellenic University Kavala Campus St. Loukas 65404 Greece School of Engineering Department of Civil Engineering Faculty of Mathematics Programming and General Courses Democritus University of Thrace Xanthi Kimmeria Greece

Developing a rapid, but also reliable and efficient, method for classifying the seismic damage potential of buildings constructed in countries with regions of high seismicity is always at the forefront of modern scientific research. Such a technique would be essential for estimating the pre-seismic vulnerability of the buildings, so that the authorities will be able to develop earthquake safety plans for seismic rehabilitation of the highly earthquake-susceptible structures. In the last decades, several researchers have proposed such procedures, some of which were adopted by seismic code guidelines. These procedures usually utilize methods based either on simple calculations or on the application of statistics theory. Recently, the increase of the computers' power has led to the development of modern statistical methods based on the adoption of Machine Learning algorithms. These methods have been shown to be useful for predicting seismic performance and classifying structural damage level by means of extracting patterns from data collected via various sources. The present paper attempts to compare and evaluate the capability of various Machine Learning methods to adequately classify the seismic damage potential of R/C buildings. A large training dataset is used for the implementation of the classification algorithms. To this end, 90 3D R/C buildings with three different masonry infills' distributions are analysed utilizing Nonlinear Time History Analysis method for 65 real seismic records. The level of the seismic damage is expressed in terms of the Maximum Interstory Drift Ratio. A large number of Machine Learning algorithms is utilized in order to estimate the buildings' damage response. The most significant conclusion which is extracted is that the Machine Learning methods that are mathematically well-established and their operations that are clearly interpretable step by step can be used to solve some of the most sophisticated real-world problems in consideratio

关键词： Classification (of information)

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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

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

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International Conference on Soft Computing and Measurements (SCM)

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

ISBN: (数字)9781728196923

ISBN: (纸本)9781728196930

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.

关键词： Consumer behavior Mobile applications Sociology Statistics Logistics Analytical models Software

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Polynomial spline collocation method for solving weakly regular Volterra integral equations of the first kind

arXiv

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arXiv 2021年

作者： Tynda, Aleksandr Noeiaghdam, Samad Sidorov, Denis Higher and Applied Mathematics Department Penza State University Penza440026 Russia Industrial Mathematics Laboratory Baikal School of BRICS Irkutsk National Research Technical University Irkutsk664074 Russia Department of Applied Mathematics and Programming South Ural State University Lenin prospect 76 Chelyabinsk454080 Russia Energy Systems Institute Siberian Branch of Russian Academy of Science Irkutsk664033 Russia Institute of Mathematics and Information Technologies Irkutsk State University Irkutsk664025 Russia

The polynomial spline collocation method is proposed for solution of Volterra integral equations of the first kind with special piecewise continuous kernels. The Gauss-type quadrature formula is used to approximate integrals during the discretization of the proposed projection method. The estimate of accuracy of approximate solution is obtained. Stochastic arithmetics is also used based on the Contrôle et Estimation Stochastique des Arrondis de Calculs (CESTAC) method and the Control of Accuracy and Debugging for Numerical Applications (CADNA) library. Applying this approach it is possible to find optimal parameters of the projective method. The numerical examples are included to illustrate the efficiency of proposed novel collocation *** Codes 45H05, 65R20 © 2021, CC BY.

关键词： Integral equations

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Darknet traffic big-data analysis and network management to real-time automating the malicious intent detection process by a weight agnostic neural networks framework

arXiv

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arXiv 2021年

作者： Demertzis, Konstantinos Tsiknas, Konstantinos Takezis, Dimitrios Skianis, Charalabos Iliadis, Lazaros Laboratory of Complex Systems Department of Physics Faculty of Sciences International Hellenic University Kavala Campus St. Loukas65404 Greece Department of Electrical and Computer Engineering Democritus University of Thrace Vas. Sofias 12 Xanthi67100 Greece Hellenic National Defence General Staff Stratopedo Papagou Mesogeion 227-231 Athens15561 Greece University of Aegean Karlovassi Samos83200 Greece School of Engineering Department of Civil Engineering Faculty of Mathematics Programming and General courses Democritus University of Thrace Kimmeria Xanthi Greece

Attackers are perpetually modifying their tactics to avoid detection and frequently leverage legitimate credentials with trusted tools already deployed in a network environment, making it difficult for organizations to proactively identify critical security risks. Network traffic analysis products have emerged in response to attackers’ relentless innovation, offering organizations a realistic path forward for combatting creative attackers. Additionally, thanks to the widespread adoption of cloud computing, Device Operators (DevOps) processes, and the Internet of Things (IoT), maintaining effective network visibility has become a highly complex and overwhelming process. What makes network traffic analysis technology particularly meaningful is its ability to combine its core capabilities to deliver malicious intent detection. In this paper, we propose a novel darknet traffic analysis and network management framework to real-time automating the malicious intent detection process, using a weight agnostic neural networks architecture. It is an effective and accurate computational intelligent forensics tool for network traffic analysis, the demystification of malware traffic, and encrypted traffic identification in real-time. Based on Weight Agnostic Neural Networks (WANNs) methodology, we propose an automated searching neural net architectures strategy that can perform various tasks such as identify zero-day attacks. By automating the malicious intent detection process from the darknet, the advanced proposed solution is reducing the skills and effort barrier that prevents many organizations from effectively protecting their most critical assets. Copyright © 2021, The Authors. All rights reserved.

关键词： Network management

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ROLE OF SIMULATION IN RAPID PROTOTYPING FOR CONCEPT DEVELOPMENT

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NAVAL ENGINEERS JOURNAL 1991年第3期103卷 204-211页

作者： KING, JF BARTON, DE J. Fred King:is the manager of the Advanced Technology Department for Unisys in Reston Virginia. He earned his Ph.D. in mathematics from the University of Houston in 1977. He has been principal investigator of research projects in knowledge engineering pattern recognition and heuristic problem-solving. Efforts include the development of a multi-temporal multispectral classifier for identifying graincrops using LANDSAT satellite imagery data for NASA. Also as a member of the research team for a NCI study with Baylor College of Medicine and NASA he helped develop techniques for detection of carcinoma using multispectral microphotometer scans of lung tissue. He established and became technical director of the AI Laboratory for Ford Aerospace where he developed expert scheduling modeling and knowledge acquisition systems for NASA. Since joining Unisys in 1985 he has led the development of object-oriented programming environments blackboard architectures data fusion techniques using neural networks and intelligent data base systems. Douglas E. Barton:is manager of Logistics Information Systems for Unisys in Reston Virginia. He earned his B.A. degree in computer science from the College of William and Mary in 1978 and did postgraduate work in London as a Drapers Company scholar. Since joining Unisys in 1981 his work has concentrated on program management and software engineering of large scale data base management systems and design and implementation of knowledge-based systems in planning and logistics. As chairman of the Logistics Data Subcommittee of the National Security Industrial Association (NSIA) he led an industry initiative which examined concepts in knowledge-based systems in military logistics. His responsibilities also include evaluation development and tailoring of software engineering standards and procedures for data base and knowledge-based systems. He is currently program manager of the Navigation Information Management System which provides support to the Fleet Ballistic Missile Progr

A valuable technique during concept development is rapid prototyping of software for key design components. This approach is particularly useful when the optimum design approach is not readily apparent or several known alternatives need to be rapidly evaluated. A problem inherent in rapid prototyping is the lack of a "target system" with which to interface. Some alternatives are to develop test driver libraries, integrate the prototype with an existing working simulator, or build one for the specific problem. This paper presents a unique approach to concept development using rapid prototyping for concept development and scenario-based simulation for concept verification. The rapid prototyping environment, derived from artificial intelligence technology, is based on a blackboard architecture. The rapid prototype simulation capability is provided through an object-oriented modeling environment. It is shown how both simulation and blackboard technologies are used collectively to rapidly gain insight into a tenacious problem. A specific example will be discussed where this approach was used to evolve the logic of a mission controller for an autonomous underwater vehicle.

关键词： Military Engineering

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CONCURRENT LARGE-SIGNAL SIMULATION OF AN ACTIVE MICROSTRIP ANTENNA

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 1995年第1期8卷 3-12页

作者： MCDOWALL, DS FUSCO, VF High Frequency Electronics Laboratory. Department of Electrical and Electronic Engineering The Queen's University of Belfast Ashby Building Stranmillis Road Belfast BT9 5AH U.K. D. Stewart McDowall was born in Dublin Republic of Ireland in 1967. He received the M. Eng. degree in Electrical and Electronic Engineering from the Queen's University of Belfast in 1990. In the same year he was presented with a Distinction Award from the Departmnet of Education of Northern Ireland and he is currently pursuing his Ph.D. in the Microwave Research Group at Q.U.B. His principal research area is the electromagnetic field mapping of microwave systems using concurrent programming. He is an Associate Member of the Institute of Electrical Engineers. Vincent F. Fusco was educated at the Queens's University of Belfast where he obtained the degree of Ph.D. in 1982. He has worked as a research engineer on short-range radar and radio telemetry systems. Currently he is a reader in Microwave Communications in the School of Electrical engineering and Computer Science the Queen's University of Belfast. His current research interests include non-linear microwave circuit simulatino and concurrent programming techniques for electromagnetic field problems with particular emphasis on EMC applications. He has published numerous research papers in these areas. He is the author of the bookMicrowave Circuits Analysis and Computer Aided Design Prentice-Hall 1987. Dr Fusco is a Chartered Electrical Engineer and a Member of the Institute of Electrical Engineers.

This paper details the use of a circuit-based EM modelling technique combined with a harmonic balance simulator used to model the radiation from the microstrip bodies comprising an active antenna circuit. The modelling approach adopted for the planar bodies in the circuit will be shown to allow the use of concurrent algorithms in order to reduce overall computational time.

关键词： Microstrip antennas

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C-3 systems LAND-BASED TESTING

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NAVAL ENGINEERS JOURNAL 1980年第6期92卷 35-42页

作者： CAMPBELL, JS THE AUTHOR was born in Porterville. Calif. in 1928 and joined the U.S. Nary in 1945 in the “Aviation Midshipman” Program. He received his designation as a Naval Aviator in 1950 and flew combat missions in Korea while still a Midshipman followed by participation in various operational and training squadrons until 1958 when he completed the Naval Test Pilot School Program. After a tour as an Engineering Test Pilot. he attended the Naval Postgraduate School Monterey. Calif. and was then assigned to the Fleet Computer Programming Center as a part of the NTDS development. Later he had operational tours as CIC Officer in the USS Enterprise and as AAW Officer on the Staff of Commander Task Force SEVENTY-SEVEN in Vietnam. During an interceding tour of duty he was the Program Manager for the TACDEW Training Facilities at San Diego Calif: and Dam Neck Va. After completing his active duty in the U.S. Navy Mr. Campbell joined Logicon Inc. and during the six years with the Tactical and Training Systems Division held various positions including Project Manager Department Head Assistant Director and Division Director prior to leaving in 1976 to join the Assistant Secretary of the Nary for R&D as Special Assistant for Weapons Systems Integration. In 1978 he joined the Staff at the Naval Ocean Systems Center as Associate Director for Command Control and Communications and Acting Head of the C3I Systems Department where he is charged with the development and operation of the C3Systems Integration Test and Evaluation Laboratory.

The increasingly important role of land-based test sites (LBTSs) in military command, control, and communications (C 3 ) is discussed, with particular reference to system integration, R&D, and testing. The LBTS at the Naval Ocean systems Center (NOSC), San Diego, is described in detail, and lessons learned from the operation of the and other LBTSe are considered in terms of both their tactical and strategic implications.

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Novel symmetric numerical methods for solving symmetric mathematical problems

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International Journal of Circuits, systems and Signal Processing 2021年 15卷 1545-1557页

作者： Ibrahimov, V.R. Mehdiyeva, G.Y.U. Yue, Xiao-Guang Kaabar, Mohammed K.A. Noeiaghdam, Samad Juraev, Davron Aslonqulovich Institute of Control Systems named after Academician A.Huseynov BakuAZ1141 Azerbaijan Computational mathematics Baku State University BakuAZ1148 Azerbaijan Department of Computer Science and Engineering School of Sciences European University Cyprus Nicosia1516 Cyprus Institute of Mathematical Sciences Faculty of Science University of Malaya Kuala Lumpur50603 Malaysia Department of Mathematics and Statistics Washington State University PullmanWA99163 United States Industrial Mathematics Laboratory Baikal School of BRICS Irkutsk National Research Technical University Irkutsk664074 Russia Department of Applied Mathematics and Programming South Ural State University Lenin Prospect 76 Chelyabinsk454080 Russia Department of Natural Science Disciplines Higher Military Aviation School of the Republic of Uzbekistan Karshi City180100 Uzbekistan

—The mathematical model for many problems is arising in different industries of natural science, basically formulated using differential, integral and integro-differential equations. The investigation of these equations is conducted with the help of numerical integration theory. It is commonly known that a class of problems can be solved by applying numerical integration. The construction of the quadrature formula has a direct relation with the computation of definite integrals. The theory of definite integrals is used in geometry, physics, mechanics and in other related subjects of science. In this work, the existence and uniqueness of the solution of above-mentioned equations are investigated. By this way, the domain has been defined in which the solution of these problems is equivalent. All proposed four problems can be solved using one and the same methods. We define some domains in which the solution of one of these problems is also the solution of the other problems. Some stable methods with the degree p © 2021, North Atlantic University Union NAUN. All rights reserved.

关键词： Integrodifferential equations

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INNOVATIONS IN COMPUTER-AIDED-DESIGN OF MARINE TURBINES USING INTERACTIVE GRAPHICS

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NAVAL ENGINEERS JOURNAL 1980年第2期92卷 207-217页

作者： GINGRICH, JK WINTER, RL Mr. John K. Gingrich joined the General Electric Company after his graduation from Lafayette College in 1948. His early assignments were with the General Engineering Laboratory and the Knolls Atomic Power Laboratory in Schenectady. N. Y. He joined the Marine Turbine and Gear Department in 1968 as Manager Engineering Administration. and assumed his present assignment as Manager Engineering Resource Planning & Administration in 1976. Mr. Gingrich was instrumental in procuring the Interactive Graphics System for the Medium Steam Department. having headed up the Study Team and is now responsible for the Interactive Graphics Systems management including new procurements. He is a member of the American Institute of Design Drafting and is currently the Chairman of the Computer-Aided Drafting Committee in that organization. Mr. Reinhold L. Winter is a graduate of the General Electric Apprentice Program and Salem State College from which he received his B.S. degree in Business Administration. He has nineteen years experience with the General Electric Company including eight years in Business Systems and Programming two years in Computer Operations Management and six years in his present position as Manager Engineering Business Systems. He was a member of the original Study Team that investigated and selected the present Applicon Interactive Graphics (IAG) equipment and currently is responsible for the management of software and hardware support for the ZAG Facility.

This paper discusses the Interactive Graphics System used by the General Electric Company, Medium Steam Turbine Department (Engineering & Manufacturing) for designing, drafting, and manufacturing applications. A brief overview of the hardware malting up the system is described, followed by a more detailed description of the actual applications. Two-dimensional applications described include a Heat Balance Analysis, Flow Diagrams, and Electrical Schematics. A more fruitful area for increased productivity gains is described in the three-dimensional or mechanical applications including turbine design & layout and bucket design. coordination of the design with manufacturing for numerical control tape generation is described through CAM and Plate Frame Cutting applications. Finally, a short review of the engineering design work using Interactive Graphics is discussed. Productivity gains of 2.6 to 1 are being realized, and the overall savings to the Medium Steam Department are outlined.

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Use of convolutional neural networks for segmenting images of roads from satellite

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IOP Conference Series: Materials Science and Engineering 2020年第5期971卷

作者： Ya A Seliverstov S A Seliverstov R S Naryshkin M N Kripak Laboratory of Intelligent Transport Systems Solomenko Institute of Transport Problems of the Russian Academy of Sciences 13 12-th Line VO 199178 Saint Petersburg Russia Department of Programming Technologies Saint-Petersburg State University Universitetsky ave. 35 Peterhof St. Petersburg 198504 Russia Automobile Transport Department Sevastopol State University 33 Universitetskaya Street Sevastopol 299053 Russia

The article developed a technique for using convolutional neural networks for automatic segmentation of roads in images obtained from satellites with a synthesized aperture. The analysis of the subject area and the relevance of this study. The development of a neural network based on U-net was carried out in Python 3x using the libraries TensorFlow, TensorBoard, Pandas, Numpy, Scipy, Matplotlib, Sklearn. The neural network was trained on a training sample of 1200 images prepared by hand marking. The accuracy of the developed model when testing on prepared samples was 68%. According to the results of the study, conclusions were drawn and prospects for further functional development of the developed tools were determined.

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