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7th Mathematics, Science, and computer Science Education International Seminar, MSCEIS 2019

作者： Kasim, Anita Ahmad Bakri, Muhammad Septiarini, Anindita Departemen of Information Technology Tadulako University Palu Indonesia Department of Architecture Tadulako University Palu Indonesia Department of Computer Science Mulawarman University Samarinda Indonesia

ISBN: (纸本)9781631902567

This study aims to utilize artificial neural networks to distinguish batik motifs and non-batik fabric motifs. Several important steps are needed, namely the process of acquiring batik and non-batik images, pre-transforming batik and non-batik images to gray scale forms, texture feature extraction in gray scale images and detection of motifs using networks artificial nerve. Image acquisition is done by collecting batik and not batik images from several different motifs. Processing data sets is divided into 70% as training data and 30% as testing data. Artificial neural network models used in this research use the Backpropagation learning algorithm by comparing the Scaled conjugate gradient algorithm (trainscg) training method and the Levenberg-Marquardt algorithm (trainlm) training method. The results obtained for the accuracy using the Scaled conjugate gradient algorithm (trainscg) training method were higher with an accuracy value of 84.12%, compared to the Levenberg-Marquardt algorithm (trainlm) method by 86.11%. © 2020 EAI.

关键词： Neural networks

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Intrusion Detection System Through Deep Learning in Routing MANET Networks

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Intelligent Automation & Soft Computing 2023年第7期37卷 269-281页

作者： Zainab Ali Abbood DoguÇagdaşAtilla Çagatay Aydin Department Electrical and Computer Engineering Altinbas UniversityIstanbulTurkey Department Computer Technology Engineering Al-Esraa UniversityBaghdadIraq Electric Autonomous and Unmanned Vehicles Application and Research CentreAltinbas UniversityIstanbulTurkey Faculty of Engineering and Architecture Altinbas UniversityIstanbulTurkey Department Electrical and Electronics Engineering Ege UniversityIzmirTurkey

Deep learning(DL)is a subdivision of machine learning(ML)that employs numerous algorithms,each of which provides various explanations of the data it consumes;mobile ad-hoc networks(MANET)are growing in *** reasons including node mobility,due to MANET’s potential to provide small-cost solutions for real-world contact challenges,decentralized management,and restricted bandwidth,MANETs are more vulnerable to security *** protecting MANETs from attack,encryption and authentication schemes have their ***,deep learning(DL)approaches in intrusion detection sys-tems(IDS)can adapt to the changing environment of MANETs and allow a sys-tem to make intrusion decisions while learning about its mobility in the *** are a secondary deﬁance system for mobile ad-hoc networks *** since they monitor network trafﬁc and report anything ***,many scientists have employed deep neural networks(DNNs)to address intrusion detection *** paper used MANET to recognize com-plex patterns by focusing on security standards through efﬁciency determination and identifying malicious nodes,and mitigating network attacks using the three algorithms presented Cascading Back Propagation Neural Network(CBPNN),Feedforward-Neural-Network(FNN),and Cascading-Back-Propagation-Neural-Network(CBPNN)(FFNN).In addition to Convolutional-Neural-Network(CNN),these primary forms of deep neural network(DNN)building designs are widely used to improve the performance of intrusion detection systems(IDS)and the use of IDS in conjunction with machine learning(ML).Further-more,machine learning(ML)techniques than their statistical and logical methods provide MANET network learning capabilities and encourage adaptation to differ-ent *** with another current model,The proposed model has better average receiving packet(ARP)and end-to-end(E2E)*** results have been obtained from CBP,FFNN and CNN 74%,82%and 85%,respectively,by the ti

关键词： ARP CBPNN CNN DNN DL E2E FFNN IDS ML MANET security

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Formalising ODRL semantics using web ontologies

Formalising ODRL semantics using web ontologies

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2nd International Workshop on Open Digital Rights Language, ODRL 2005

作者： García, Roberto Gil, Rosa Gallego, Isabel Delgado, Jaime Technology Department Universitat Pomeu Fabra Barcelona E-08003 Spain Computer Architecture Department Universitat Politecnica de Catalunya Barcelona E-08034 Spain

ISBN: (纸本)1740645014

In order to move Digital Rights Management to the Internet, a common rights expression language is needed. ODRL (Open Digital Rights Language) is one of the proposed solutions. It is based on a XML language and thus it just formalises the language syntax, while language semantics are specified informally. Actually, ODRL seems quite complete and generic enough to cope with such a complex domain. However, the problem is that it has such a rich structure that it is difficult to implement. In our opinion, it lacks formal semantics that would help ODRL applications development. As the application context is the Web, our approach to formalise ODRL semantics is based on semantic web ontologies. Firstly, ORDL has been moved to the Semantic Web space using XML Schema to OWL and XML to RDF tools. This provides some simple semantics. In order to refine them, the resulting ODRL ontologies have been connected to IPROnto, a result of previous research. IPROnto, Intellectual Property Rights Ontology, models the IPR core concepts for creation, intellectual property rights and the basic kinds of actions that operate on intellectual property. It enables semantics-aware IPR applications that benefit from semantic queries, in contrast to the difficulties that emerge from the use of syntactic queries when the information space is as complicated as in the IPR field. Moreover, specialised reasoners can be used for license checking and retrieval. All these advantages have been propagated to ODRL thanks to this mapping.

关键词： Ontology

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Potential implementation of EVs - Features, Challenges and User perspective

Potential implementation of EVs - Features, Challenges and U...

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2021 IEEE Green Energy and Smart Systems Conference, IGESSC 2021

作者： Alotaibi, Saleh Omer, Siddig Aljarallah, Sulaiman Su, Yuehong University Of Nottingham Faculty Of Engineering Department Of Architecture And Built Environment Nottingham United Kingdom Zulfi College Of Technology Department Of Computer Science Riyadh Saudi Arabia

ISBN: (纸本)9781665434560

Sustainable transportation has become an important consideration for countries seeking to reduce carbon emissions. Electric vehicles (EVs) are seen as a cornerstone of the transformation toward sustainability within the transportation sector;however, research on large-scale EVs' implementation to aid carbon emission reduction is sparse. Doubts have been raised concerning the effectiveness of EVs in satisfying sustainability in all of its dimensions: economic, social and environmental. Since achieving balanced sustainability requires an understanding of end-users' requirements, a mixed-methods empirical study surveyed end-users' perceptions of the desirable characteristics of EVs, using Saudi Arabia as a case study. Data gathered from 1012 respondents were analyzed to examine and rank their preferences, allowing the identification of a set of key features likely to influence Saudi citizens' utilization of EVs. Quantitative findings indicate that the features perceived as most significant were availability of charging stations and EV travelling distance. Other features which are also found important include aesthetics, maintenance costs, and charging cost, whereas end-users had low concern for branding and resale value. Thematic analysis of qualitative data shows that the most significant themes were security, localization of the EVs industry, charging energy sources, and self-driving. These results may serve as a framework to replicate the study in other countries, taking relevant inherent factors into account. © 2021 IEEE.

关键词： Sustainable development

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The synergistic interplay of artificial intelligence and digital twin in environmentally planning sustainable smart cities:A comprehensive systematic review

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Environmental Science and Ecotechnology 2024年第4期20卷 79-104页

作者： Simon Elias Bibri Jeffrey Huang Senthil Kumar Jagatheesaperumal John Krogstie Swiss Federal Institute of Technology Lausanne(EPFL) Institute of Computer and Communication Sciences(IINFCOM)School of ArchitectureCivil and Environmental Engineering(ENAC)Media and Design Laboratory(LDM)1015LausanneSwitzerland Department of Electronics&Communication Engineering Mepco Schlenk Engineering CollegeSivakasi626005TamilnaduIndia Department of Computer Science Norwegian University of Science and Technology(NTNU)TrondheimNorway

The dynamic landscape of sustainable smart cities is witnessing a significant transformation due to the integration of emerging computational technologies and innovative *** advancements are reshaping data-driven planning strategies,practices,and approaches,thereby facilitating the achievement of environmental sustainability *** transformative wave signals a fundamental shift d marked by the synergistic operation of artificial intelligence(AI),artificial intelligence of things(AIoT),and urban digital twin(UDT)*** previous research has largely explored urban AI,urban AIoT,and UDT in isolation,a significant knowledge gap exists regarding their synergistic interplay,collaborative integration,and collective impact on data-driven environmental planning in the dynamic context of sustainable smart *** address this gap,this study conducts a comprehensive systematic review to uncover the intricate interactions among these interconnected technologies,models,and domains while elucidating the nuanced dynamics and untapped synergies in the complex ecosystem of sustainable smart *** to this study are four guiding research questions:*** theoretical and practical foundations underpin the convergence of AI,AIoT,UDT,data-driven planning,and environmental sustainability in sustainable smart cities,and how can these components be synthesized into a novel comprehensive framework?*** does integrating AI and AIoT reshape the landscape of datadriven planning to improve the environmental performance of sustainable smart cities?*** can AI and AIoT augment the capabilities of UDT to enhance data-driven environmental planning processes in sustainable smart cities?*** challenges and barriers arise in integrating and implementing AI,AIoT,and UDT in data-driven environmental urban planning,and what strategies can be devised to surmount or mitigate them?Methodologically,this study involves a rigorous analysis and synthesis of studies publis

关键词： Sustainable smart cities Artificial intelligence Artificial intelligence of things Urban digital twin Data-driven urban planning Environmental planning Environmental sustainability

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Synchronization of fractional-order chaotic systems based on the fractional-order sliding mode controller

Synchronization of fractional-order chaotic systems based on...

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第三十二届中国控制会议

作者： YAN Xiaomei SHANG Ting ZHAO Xiaoguo Faculty of Automation and Information Engineering Xi'an University of Technology School of Mechanical and Electrical Engineering Xi'an University of Architecture and Technology Department of Electrical and Computer Engineering The Ohio State UniversityColumbus 43210USA

ISBN: (纸本)9789881563835

For synchronization of fractional-order chaotic systems,this paper presents a novel fractional-order sliding mode controller,in which fractional calculus is introduced to the sliding mode *** on Lyapunov stability theory and fractional-order system's stability theorem,stability analysis is *** examples are given respectively,which include synchronization of two identical fractional-order systems(Chen-Chen) and synchronization of two non-identical fractional-order systems(Chen-Liu).Numerical simulations illustrate the effectiveness of the proposed controller.

关键词： Synchronization fractional-order chaotic system sliding mode control

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A method to improve the accuracy of protein torsion angles

A method to improve the accuracy of protein torsion angles

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作者： Calvo, J.C. Ortega, J. Anguita, M. Taheri, J. Zomaya, A. Department of Computer Architecture and Computer Technology CITIC-UGR University of Granada Granada Spain School of Information Technologies University of Sydney Sydney NSW Australia

ISBN: (纸本)9789898425362

Protein structure prediction (PSP) is an open problem with many useful applications in disciplines such as Medicine, Biology and Biochemistry. As this problem presents a vast search space where the analysis of each protein structure requires a significant amount of computing time, it is necessary to propose efficient search procedures in this very large space of possible protein conformations. Thus, an important issue is to add vital information (such as rotamers) to the process to decrease its active search space -rotamers give statistical information about torsional angles and conformations. In this paper, we propose a new method to refine the torsional angles of a protein to remake/reconstruct its structures with more resemblance to its original structure. This approach could be used to improve the accuracy of the rotamer libraries and/or to extract information from the Protein Data Bank to facilitate solution of the PSP problem.

关键词： Proteins

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Graph Data Management 1

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丛书名： Data-Centric Systems and Applications

1000年

作者： George Fletcher Jan Hidders Josep Lluís Larriba-Pey

ISBN: (数字)9783319961934

ISBN: (纸本)9783319961927;9783030071516

This book presents a comprehensive overview of fundamental issues and recent advances in graph data management. Its aim is to provide beginning researchers in the area of graph data management, or in fields that require graph data management, an overview of the latest developments in this area, both in applied and in fundamental subdomains.;The topics covered range from a general introduction to graph data management, to more specialized topics like graph visualization, flexible queries of graph data, parallel processing, and benchmarking. The book will help researchers put their work in perspective and show them which types of tools, techniques and technologies are available, which ones could best suit their needs, and where there are still open issues and future research directions.;The chapters are contributed by leading experts in the relevant areas, presenting a coherent overview of the state of the art in the field. Readers should have a basic knowledge of data management techniques as they are taught in computer science MSc programs.

关键词： Database Management Math Applications in computer Science System Performance and Evaluation Models and Principles

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Designing radial basis function neural networks with meta-evolutionary algorithms: The effect of chromosome codification

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10th International Work-Conference on Artificial Neural Networks, IWANN 2009

作者： Parras-Gutierrez, Elisabet Rivas, Victor M. Del Jesus, M. Jose Merelo, Juan J. Department of Computer Sciences Campus Las Lagunillas s/n Jaen 23071 Spain Department of Computer Architecture and Technology CITIC-UGR C/Periodista Daniel Saucedo s/n Granada 18071 Spain

ISBN: (纸本)3642024807

In this paper a study of two approaches of a meta-algorithm, Meta-CHC-RBF, is presented. The main goal of this algorithm is to automatically design Radial Basis Function Networks (RBFNs) finding a suitable configuration of parameters (automatically adapted to every problem) necessary for the algorithm EvRBF, an evolutionary algorithm for the automatic design of asymmetric RBFNs. The principal difference between two proposals is the type of codification, in the fist one, the meta-algorithm uses binary codification, while in the second one, it implements real codification;affecting this influence of the codification kind in the carried out experimentation. Finally, results show that the first approach yields good marks reducing the computation time, with respect the second one. © 2009 Springer Berlin Heidelberg.

关键词： Radial basis function networks

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Parallelizing a machine translation decoder for multicore computer

Parallelizing a machine translation decoder for multicore co...

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2011 7th International Conference on Natural Computation, ICNC 2011

作者： Chen, Long Huo, Wei Mi, Haitao Zhang, Zhaoqing Feng, Xiaobing Li, Zhiyuan Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Department of Computer Science Purdue University West Lafayette IN 47907 United States

ISBN: (纸本)9781424499533

Machine translation (MT), with its broad potential use, has gained increased attention from both researchers and software vendors. To generate high quality translations, however, MT decoders can be highly computation intensive. With significant raw computing power, multi-core microprocessors have the potential to speed up MT software on desktop machines. However, retrofitting existing MT decoders is a nontrivial issue. Race conditions and atomicity issues are among those complications making parallelization difficult. In this article, we show that, to parallelize a state-of-the-art MT decoder, it is much easier to overcome such difficulties by using a process-based parallelization method, called functional task parallelism, than using conventional thread-based methods. We achieve a 7.60 times speed up on an 8-core desktop machine while making significantly less changes to the original sequential code than required by using multiple threads. © 2011 IEEE.

关键词： Machine translation

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