Search results for " Network"

showing 10 items of 6428 documents

A sliding mode approach to H∞ synchronization of master–slave time-delay systems with Markovian jumping parameters and nonlinear uncertainties

2012

Author's version of an article published in the journal: Journal of the Franklin Institute. Also available from the publisher at: http://dx.doi.org/10.1016/j.jfranklin.2011.09.015 In this paper, a sliding-mode approach is proposed for exponential H∞ synchronization problem of a class of masterslave time-delay systems with both discrete and distributed time-delays, norm-bounded nonlinear uncertainties and Markovian switching parameters. Using an appropriate LyapunovKrasovskii functional, some delay-dependent sufficient conditions and a synchronization law, which include the masterslave parameters are established for designing a delay-dependent mode-dependent sliding mode exponential H∞ synch…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Computer Networks and CommunicationsComputer scienceApplied Mathematicssynchronization master-slave systems sliding mode delay H∞ performance nonlinear uncertaintiesVDP::Technology: 500::Mechanical engineering: 570Mode (statistics)Control engineeringMaster/slaveNonlinear systemControl and Systems EngineeringControl theorySignal ProcessingSynchronization (computer science)Markovian jumpingJournal of the Franklin Institute
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Investigation of vehicle crash modeling techniques: theory and application

2013

Published version of an article in the journal: The International Journal of Advanced Manufacturing Technology. Also available from the publisher at: http://dx.doi.org/10.1007/s00170-013-5320-3 Creating a mathematical model of a vehicle crash is a task which involves considerations and analysis of different areas which need to be addressed because of the mathematical complexity of a crash event representation. Therefore, to simplify the analysis and enhance the modeling process, in this work, a brief overview of different vehicle crash modeling methodologies is proposed. The acceleration of a colliding vehicle is measured in its center of gravity—this crash pulse contains detailed informati…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Feedforward neural network; Lumped parameter models; Multiresolution analysis; Vehicle crash modeling; Control and Systems Engineering; Software; Mechanical Engineering; Computer Science Applications1707 Computer Vision and Pattern Recognition; Industrial and Manufacturing EngineeringEvent (computing)Computer scienceReliability (computer networking)Mechanical Engineeringvehicle crash modelingVDP::Technology: 500::Mechanical engineering: 570lumped parameter modelsCrashControl engineeringComputer Science Applications1707 Computer Vision and Pattern RecognitionCollisionIndustrial and Manufacturing EngineeringComputer Science Applicationsmultiresolution analysisAutoregressive modelControl and Systems Engineeringfeedforward neural networkRepresentation (mathematics)SimulationSoftwareMotor vehicle crash
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Application of Wavelet Networks to Adaptive Control of Robotic Manipulators

2011

Published version of a chapter in the book: Intelligent Robotics and Applications. Also available from the publisher at; http://dx.doi.org/10.1007/978-3-642-25489-5_39 In this paper, a wavelet-based adaptive control is proposed for a class of robotic manipulators, which consist of nonlinearities for friction effects and uncertain terms as disturbances. The controller is calculated by using a mixed of feedback linearization technique, supervisory control and H∞ control. In addition, the parameter adaptive laws of the wavelet network are developed using a Lyapunov-based design. It is also shown that both system tracking stability and convergence of the error estimation can be guaranteed in th…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Lyapunov functionEngineeringAdaptive controlbusiness.industryVDP::Technology: 500::Mechanical engineering: 570Stability (learning theory)Control engineeringwavelet networks robotic maniplulators adaptive controlsymbols.namesakeWaveletSupervisory controlControl theoryConvergence (routing)symbolsFeedback linearizationbusiness
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Modeling and Performance Analysis of Energy Efficiency Binary Power Control in MIMO-OFDM Wireless Communication Systems

2011

Published version of an article in the journal:International Journal of Distributed Sensor Networks. Also available from Hindawi Publishing: http://dx.doi.org/10.1155/2011/946258 The energy efficiency optimization of the binary power control scheme for MIMO-OFDM wireless communication systems is formulated, and then a global optimization solution of power allocation is derived. Furthermore, a new energy efficiency binary power control (EEBPC) algorithm is designed to improve the energy efficiency of MIMO-OFDM wireless communication systems. Simulation results show that the EEBPC algorithm has better energy efficiency and spectrum efficiency than the average power control algorithm in MIMO-O…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Scheme (programming language)Theoretical computer scienceArticle SubjectComputer Networks and CommunicationsComputer scienceBinary numberData_CODINGANDINFORMATIONTHEORY02 engineering and technologylcsh:QA75.5-76.950203 mechanical engineeringVDP::Technology: 500::Information and communication technology: 550::Telecommunication: 552Computer Science::Networking and Internet Architecture0202 electrical engineering electronic engineering information engineeringElectronic engineeringGlobal optimizationComputer Science::Information Theorycomputer.programming_languageComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKSGeneral Engineering020206 networking & telecommunications020302 automobile design & engineeringSpectral efficiencyMIMO-OFDMPower (physics)lcsh:Electronic computers. Computer sciencecomputerPower controlEfficient energy useInternational Journal of Distributed Sensor Networks
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Tracking the Preferences of Users Using Weak Estimators

2011

Published version of am article from the book:AI 2011: Advances in Artificial Intelligence. Also available from the publisher on SpringerLink:http://dx.doi.org/10.1007/978-3-642-25832-9_81 Since a social network, by definition, is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary, estimating a user’s interests, typically, involves non-stationary distributions. The consequent time varying nature of the distribution to be trac…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Service (systems architecture)Social networkbusiness.industryComputer scienceEstimatorRecommender systemTracking (particle physics)Machine learningcomputer.software_genreTarget distributionVDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425Targeted advertisingRange (statistics)Artificial intelligencebusinesscomputer
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An intelligent architecture for service provisioning in pervasive environments

2011

Accepted version of an article from the conference: 2011 International Symposium on Innovations in Intelligent Systems and Applications (INISTA). Definitive published version available from IEEE: http://dx.doi.org/10.1109/INISTA.2011.5946134 The vision of pervasive environments is being realized more than ever with the proliferation of services and computing resources located in our surrounding environments. Identifying those services that deserve the attention of the user is becoming an increasingly-challenging task. In this paper, we present an adaptive multi-criteria decision making mechanism for recommending relevant services to the mobile user. In this context Relevance is determined b…

VDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413Service (systems architecture)business.industrycomputer.internet_protocolComputer scienceMobile computing020206 networking & telecommunicationsContext (language use)02 engineering and technologyService-oriented architectureRecommender systemWorld Wide WebVDP::Technology: 500::Information and communication technology: 550::Telecommunication: 5520202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingRelevance (information retrieval)Mobile telephonyUser interfacebusinesscomputer
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Information diffusion model with homogeneous continuous time Markov chain on Indonesian Twitter users

2022

In this paper, a homogeneous continuous time Markov chain (CTMC) is used to model information diffusion or dissemination, also to determine influencers on Twitter dynamically. The tweeting process can be modeled with a homogeneous CTMC since the properties of Markov chains are fulfilled. In this case, the tweets that are received by followers only depend on the tweets from the previous followers. Knowledge Discovery in Database (KDD) in Data Mining is used to be research methodology including pre-processing, data mining process using homogeneous CTMC, and post-processing to get the influencers using visualization that predicts the number of affected users. We assume the number of affected u…

VDP::Samfunnsvitenskap: 200::Økonomi: 210Artificial IntelligenceComputer Networks and CommunicationsCommunicationSoftwareComputer Science ApplicationsInformation Systems
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Sustainable development goals research in higher education institutions: An interdisciplinarity assessment through an entropy-based indicator

2022

Since 2015, the United Nations has urged higher education institutions (HEIs) to adopt an interdisciplinary approach towards the Sustainable Development Goals (SDGs). In other words, universities are encouraged to transcend any single disciplinary perspective in exploring sustainable development issues. This study examines the importance of driving the scientific production of HEIs towards the SDGs as a concrete institutional contribution to sustainable development. While bibliometric tools for the SDGs are currently emerging, the existing models have not focused on interdisciplinarity or on their usefulness as decision-management tools to drive SDG-related research at a micro-scale (i.e. t…

VDP::Samfunnsvitenskap: 200::Økonomi: 210Social network analysisMarketingSustainable development goals Interdisciplinarity Social network analysis Higher education institutions Information system design theoryHigher education institutions:Samfunnsvitenskap: 200 [VDP]InterdisciplinaritySustainable development goalsInformation system design theory
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An Efficient Convolutional Neural Network with Transfer Learning for Malware Classification

2022

Rising prevalence of malicious software (malware) attacks represent a serious threat to online safety in the modern era. Malware is a threat to anyone who uses the Internet since it steals data and causes damage to computer systems. In addition, the exponential growth of malware hazards that affect many computer users, corporations, and governments has made malware detection, a popular issue in academic study. Current malware detection methods are slow and ineffectual because they rely on static and dynamic analysis of malware signatures and behavior patterns to detect unknown malware in real-time. Thus, this paper discusses the role of deep convolution neural networks in malware classifica…

VDP::Teknologi: 500Article SubjectComputer Networks and CommunicationsElectrical and Electronic EngineeringVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550VDP::Teknologi: 500::Elektrotekniske fag: 540Information SystemsWireless Communications and Mobile Computing
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Prediction of dynamic mooring responses of a floating wind turbine using an artificial neural network

2021

Abstract Numerical simulations in coupled aero-hydro-servo-elastic codes are known to be a challenge for design and analysis of offshore wind turbine systems because of the large number of design load cases involved in checking the ultimate and fatigue limit states. To alleviate the simulation burden, machine learning methods can be useful. This article investigates the effect of machine learning methods on predicting the mooring line tension of a spar floating wind turbine. The OC3 Hywind wind turbine with a spar-buoy foundation and three mooring lines is selected and simulated with SIMA. A total of 32 sea states with irregular waves are considered. Artificial neural works with different c…

VDP::Teknologi: 500Artificial neural networkComputer scienceFloating wind turbineMooringMarine engineeringIOP Conference Series: Materials Science and Engineering
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