Search results for "computer.software_genre"

showing 10 items of 3858 documents

Trust management in tactical coalition software defined networks

2018

This paper reports from ongoing efforts related to trust management in tactical Software Defined Networks (SDN) when used with mobile nodes in a coalition operation. We analyze the problem space and suggests a set of security and contructional requirements, as well as an analysis on how existing technology may contribute to a solution. The proposed architecture serves as a guide for current and future experimentation on trust management and protection in SDN. The paper also reports from experimental investigations into the utility of these technology elements for the present purpose.

Set (abstract data type)AuthenticationComputer scienceTrust management (information system)ArchitectureSoftware-defined networkingComputer securitycomputer.software_genrecomputerProblem space2018 International Conference on Military Communications and Information Systems (ICMCIS)
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PROTEIN SECONDARY STRUCTURE PREDICTION: HOW TO IMPROVE ACCURACY BY INTEGRATION

2006

In this paper a technique to improve protein secondary structure prediction is proposed. The approach is based on the idea of combining the results of a set of prediction tools, choosing the most correct parts of each prediction. The correctness of the resulting prediction is measured referring to accuracy parameters used in several editions of CASP. Experimental evaluations validating the proposed approach are also reported.

Set (abstract data type)Bioinformatics Protein PredictionCorrectnessComputer sciencebusiness.industryArtificial intelligenceData miningMachine learningcomputer.software_genreProtein secondary structure predictionbusinessCASPcomputerApplied Artificial Intelligence
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Robust refinement of initial prototypes for partitioning-based clustering algorithms

2007

Non-uniqueness of solutions and sensitivity to erroneous data are common problems to large-scale data clustering tasks. In order to avoid poor quality of solutions with partitioning-based clustering methods, robust estimates (that are highly insensitive to erroneous data values) are needed and initial cluster prototypes should be determined properly. In this paper, a robust density estimation initialization method that exploits the spatial median estimate to the prototype update is presented. Besides being insensitive to noise and outliers, the new method is also computationally comparable with other traditional methods. The methods are compared by numerical experiments on a set of syntheti…

Set (abstract data type)Computer scienceCorrelation clusteringOutlierInitializationSensitivity (control systems)Density estimationNoise (video)Data miningCluster analysiscomputer.software_genrecomputerRecent Advances in Stochastic Modeling and Data Analysis
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2020

Discriminant validity was originally presented as a set of empirical criteria that can be assessed from multitrait-multimethod (MTMM) matrices. Because datasets used by applied researchers rarely lend themselves to MTMM analysis, the need to assess discriminant validity in empirical research has led to the introduction of numerous techniques, some of which have been introduced in an ad hoc manner and without rigorous methodological support. We review various definitions of and techniques for assessing discriminant validity and provide a generalized definition of discriminant validity based on the correlation between two measures after measurement error has been considered. We then review t…

Set (abstract data type)Computer scienceManagement of Technology and InnovationStrategy and ManagementMonte Carlo methodDiscriminant validityGeneral Decision SciencesGuidelineData miningcomputer.software_genrecomputerConfirmatory factor analysisOrganizational Research Methods
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A hierarchical clustering strategy and its application to proteomic interaction data

2003

We describe a novel strategy of hierarchical clustering analysis, particularly useful to analyze proteomic interaction data. The logic behind this method is to use the information for all interactions among the elements of a set to evaluate the strength of the interaction of each pair of elements. Our procedure allows the characterization of protein complexes starting with partial data and the detection of "promiscuous" proteins that bias the results, generating false positive data. We demonstrate the usefulness of our strategy by analyzing a real case that involves 137 Saccharomyces cerevisiae proteins. Because most functional studies require the evaluation of similar data sets, our method…

Set (abstract data type)Data setRange (mathematics)Computer scienceBenchmark (computing)Data miningcomputer.software_genrecomputerHierarchical clustering
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On handling exceptions

1995

The current literature of information systems has dealt extensively with all kinds of exceptions. There are several studies defining the concept of exception and even providing classifications. However, no studies provide a method for verifying the rules in order to handle exceptions and to achieve the goals set by an organization's rules. In this paper, a model employing a set of unique input/output (UIO) sequences is presented for verifying such rules. The model originally presented for Finite State Machines (FSM) has been modified to include concepts of exception handling and will be used to form a tool usable for verifying exception handling rules in OISs.

Set (abstract data type)Finite-state machineProgramming languageComputer scienceException handlingInformation systemData miningUSablecomputer.software_genrecomputerProceedings of conference on Organizational computing systems - COCS '95
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PRIvacy LEakage Methodology (PRILE) for IDS Rules

2010

This paper introduces a methodology for evaluating PRIvacy LEakage in signature-based Network Intrusion Detection System (IDS) rules. IDS rules that expose more data than a given percentage of all data sessions are defined as privacy leaking. Furthermore, it analyses the IDS rule attack specific pattern size required in order to keep the privacy leakage below a given threshold, presuming that occurrence frequencies of the attack pattern in normal text are known. We have applied the methodology on the network intrusion detection system Snort’s rule set. The evaluation confirms that Snort in its default configuration aims at not being excessively privacy invasive. However we have identified s…

Set (abstract data type)Pattern sizeEngineeringbusiness.industryPrivacy softwareData miningNetwork intrusion detectionLeakage (economics)computer.software_genreComputer securitybusinesscomputerSignature (logic)
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<strong>New tool useful for drug discovery validated through benchmark datasets</strong>

2018

Atomic Weighted Vectors (AWVs) are vectors that contain the codified information of molecular structures, which can apply to a set of Aggregation Operators (AOs) to calculate total and local molecular descriptors (MDs). This article presents an exploratory study of a new tool useful for drug discovery using different datasets, such as DRAGON and Sutherland’s datasets, as well as their comparison with other well-known approaches. In order to evaluate the performance of the tool, several statistics and QSAR/QSPR experiments were performed. Variability analyses are used to quantify the information content of the AWVs obtained from the tool, by the way of an information theory-based algorithm. …

Set (abstract data type)Quantitative structure–activity relationshipOrthogonalityComputer scienceMolecular descriptorPrincipal component analysisGenetic algorithmBenchmark (computing)Data miningInformation theorycomputer.software_genrecomputerProceedings of MOL2NET 2018, International Conference on Multidisciplinary Sciences, 4th edition
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Features for Text Comparison

2008

The main purpose of this paper is to deliver appropriate tool to find similarities between texts. The area of interest covers comparing large amount of different texts grouped in various areas of knowledge. Similarity is defined as distance between two texts and as this the measure may be calculated as the set of parameters based on features.

Set (abstract data type)Similarity (network science)Computer sciencebusiness.industryArea of interestArtificial intelligencebusinesscomputer.software_genreMeasure (mathematics)computerNatural language processing
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Modeling musical attributes to characterize ensemble recordings using rhythmic audio features

2011

In this paper, we present the results of a pre-study on music performance analysis of ensemble music. Our aim is to implement a music classification system for the description of live recordings, for instance to help musicologist and musicians to analyze improvised ensemble performances. The main problem we deal with is the extraction of a suitable set of audio features from the recorded instrument tracks. Our approach is to extract rhythm-related audio features and to apply them for regression-based modeling of eight more general musical attributes. The model based on Partial Least-Squares Regression without preceding Principal Component Analysis performed best for all of the eight attribu…

Set (abstract data type)Sound recording and reproductionMusicologyComputer scienceSpeech recognitionFeature extractionMusicalAudio signal processingcomputer.software_genrecomputer2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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