Search results for "GME"

showing 10 items of 5956 documents

Implementing structured document production to support enterprise content management

2017

Within enterprise content management (ECM), the major goal is to develop and deploy systematic solutions for managing documents and other content items. ECM implementation concerns the development and deployment of new content management solutions and practices in an organization. Extensible Markup Language (XML) offers a standardized format for documents supporting the management and preservation of documents as structured documents. However, the deployment of XML may require a demanding standardization process, changes in work practices, and new tools for document management. Consequently, this research explores the implementation of structured document production environments. The focus …

sähköiset asiakirjatECMenterprise content managementmetadataComputingMethodologies_DOCUMENTANDTEXTPROCESSINGtiedonhallintasisällönhallintatiedonhallintajärjestelmätXMLstructured documentsrakenteiset dokumentitasiakirjahallinto
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A novel heuristic memetic clustering algorithm

2013

In this paper we introduce a novel clustering algorithm based on the Memetic Algorithm meta-heuristic wherein clusters are iteratively evolved using a novel single operator employing a combination of heuristics. Several heuristics are described and employed for the three types of selections used in the operator. The algorithm was exhaustively tested on three benchmark problems and compared to a classical clustering algorithm (k-Medoids) using the same performance metrics. The results show that our clustering algorithm consistently provides better clustering solutions with less computational effort.

ta113Determining the number of clusters in a data setBiclusteringClustering high-dimensional dataDBSCANComputingMethodologies_PATTERNRECOGNITIONTheoretical computer scienceCURE data clustering algorithmCorrelation clusteringCanopy clustering algorithmCluster analysisAlgorithmMathematics2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP)
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Collaborative EA Information Elicitation Method : The IEM for Business Architecture

2015

This study contributes to the enterprise architecture (EA) methodologies by suggesting a method for eliciting architecture requirements: gathering both the current architecture information, and the development needs and requirements for the business architecture (BA) dimension in EA planning. Most of all EA dimensions, the developing of the BA requires collaboration with various non-IT stakeholders. It presents thus challenges to the IT department, or the consultancy involved in EA related efforts. The contribution of the various stakeholder groups as informants is, however, crucial to well founded EA design decisions. The suggested method takes related IS development fields as starting poi…

ta113EngineeringKnowledge managementRequirements engineeringbusiness.industryrequirements elicitationComputingMethodologies_MISCELLANEOUSStakeholderEnterprise architectureInformation technologyRequirements elicitationpublic administrationBusiness process modelingKnowledge acquisitionmethodsmenetelmätenterprise architectureBusiness architecturejulkinen hallintokokonaisarkkitehtuuribusiness
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Interface Detection Using a Quenched-Noise Version of the Edwards-Wilkinson Equation

2015

We report here a multipurpose dynamic-interface-based segmentation tool, suitable for segmenting planar, cylindrical, and spherical surfaces in 3D. The method is fast enough to be used conveniently even for large images. Its implementation is straightforward and can be easily realized in many environments. Its memory consumption is low, and the set of parameters is small and easy to understand. The method is based on the Edwards-Wilkinson equation, which is traditionally used to model the equilibrium fluctuations of a propagating interface under the influence of temporally and spatially varying noise. We report here an adaptation of this equation into multidimensional image segmentation, an…

ta113Image segmentationta114DiscretizationInterface (Java)Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONobject detectionimage edge detectionImage segmentationComputer Graphics and Computer-Aided DesignGrayscaleGray-scaleObject detectionSurface topographyNoiseMathematical modelThree-dimensional displaysSegmentationTomography3D image processingNoiseSurface morphologyAlgorithmSoftwareIEEE Transactions on Image Processing
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A New Augmented Lagrangian Approach for $L^1$-mean Curvature Image Denoising

2015

Variational methods are commonly used to solve noise removal problems. In this paper, we present an augmented Lagrangian-based approach that uses a discrete form of the L1-norm of the mean curvature of the graph of the image as a regularizer, discretization being achieved via a finite element method. When a particular alternating direction method of multipliers is applied to the solution of the resulting saddle-point problem, this solution reduces to an iterative sequential solution of four subproblems. These subproblems are solved using Newton’s method, the conjugate gradient method, and a partial solution variant of the cyclic reduction method. The approach considered here differs from ex…

ta113Mean curvatureDiscretizationimage denoisingAugmented Lagrangian methodApplied MathematicsGeneral Mathematicsmean curvaturekuvankäsittelyTopologyFinite element methodimage processingsymbols.namesakeLagrangian relaxationLagrange multiplierConjugate gradient methodsymbolsApplied mathematicsaugmented Lagrangian methodalternating direction methods of multipliersvariational modelMathematicsCyclic reductionSIAM Journal on Imaging Sciences
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Support vector machine integrated with game-theoretic approach and genetic algorithm for the detection and classification of malware

2013

Abstract. —In the modern world, a rapid growth of mali- cious software production has become one of the most signifi- cant threats to the network security. Unfortunately, wides pread signature-based anti-malware strategies can not help to de tect malware unseen previously nor deal with code obfuscation te ch- niques employed by malware designers. In our study, the prob lem of malware detection and classification is solved by applyin g a data-mining-based approach that relies on supervised mach ine- learning. Executable files are presented in the form of byte a nd opcode sequences and n-gram models are employed to extract essential features from these sequences. Feature vectors o btained are…

ta113Network securitybusiness.industryComputer scienceFeature vectorFeature extractionuhatBytecomputer.file_formatMachine learningcomputer.software_genrehaittaohjelmatSupport vector machineObfuscation (software)ComputingMethodologies_PATTERNRECOGNITIONnetworknetwork securityMalwareData miningArtificial intelligenceExecutabletietoturvabusinesscomputer2013 IEEE Globecom Workshops (GC Wkshps)
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A Stochastic Algorithm Based on Fast Marching for Automatic Capacitance Extraction in Non-Manhattan Geometries

2014

WOS:000346854900026 (Nº de Acesso Web of Science) We present an algorithm for two- and three-dimensional capacitance analysis on multidielectric integrated circuits of arbitrary geometry. Our algorithm is stochastic in nature and as such fully parallelizable. It is intended to extract capacitance entries directly from a pixelized representation of the integrated circuit (IC), which can be produced from a scanning electron microscopy image. Preprocessing and monitoring of the capacitance calculation are kept to a minimum, thanks to the use of distance maps automatically generated with a fast marching technique. Numerical validation of the algorithm shows that the systematic error of the algo…

ta113Parallelizable manifoldSEM image segmentationComputer scienceMatemáticasApplied MathematicsGeneral MathematicsFast marchingCapacitance extractionIntegrated circuitResolution (logic)CapacitanceImage (mathematics)law.inventionNon-Manhattan IClawFloating random walkPreprocessorRepresentation (mathematics)AlgorithmFast marching method
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Depth perception in tablet-based augmented reality at medium- and far-field distances

2013

Current augmented reality (AR) systems often fail to indicate the distance between the user and points of interest in the environment. Empirical evaluations of human depth perception in AR settings compared to real world settings are needed. Our goal in this study was to understand tablet-based AR depth perception by comparing it with real-world depth perception.

ta113Point of interestComputer sciencebusiness.industrybisectionNear and far fieldDistance perceptionhahmottaminenComputer visionAugmented realityArtificial intelligencebusinessDepth perceptionlisätty todellisuus
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Online user survey on current mobile augmented reality applications

2011

Augmented reality (AR) as an emerging technology in the mobile computing domain is becoming mature enough to engender publicly available applications for end users. Various commercial applications have recently been emerging in the mobile consumer domain at an increasing pace — Layar, Junaio, Google Goggles, and Wikitude are perhaps the most prominent ones. However, the research community lacks an understanding of how well such timely applications have been accepted, what kind of user experiences they have evoked, and what the users perceive as the weaknesses of the various applications overall. During the spring of 2011 we conducted an online survey to study the overall acceptance and user…

ta113World Wide WebUser experience designEmerging technologiesbusiness.industryComputer scienceEnd userMobile computingContext (language use)Augmented realityMobile telephonybusinessUser Research2011 10th IEEE International Symposium on Mixed and Augmented Reality
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Automatic dynamic texture segmentation using local descriptors and optical flow

2012

A dynamic texture (DT) is an extension of the texture to the temporal domain. How to segment a DT is a challenging problem. In this paper, we address the problem of segmenting a DT into disjoint regions. A DT might be different from its spatial mode (i.e., appearance) and/or temporal mode (i.e., motion field). To this end, we develop a framework based on the appearance and motion modes. For the appearance mode, we use a new local spatial texture descriptor to describe the spatial mode of the DT; for the motion mode, we use the optical flow and the local temporal texture descriptor to represent the temporal variations of the DT. In addition, for the optical flow, we use the histogram of orie…

ta113business.industrySegmentation-based object categorizationComputer scienceTexture DescriptorComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flowScale-space segmentationPattern recognitionImage segmentationComputer Graphics and Computer-Aided DesignImage textureMotion fieldRegion growingComputer Science::Computer Vision and Pattern RecognitionHistogramComputer visionSegmentationArtificial intelligencebusinessSoftwareIEEE Transactions on Image Processing
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