Search results for "cluster analysis."

showing 10 items of 805 documents

Phenotypic and genotypic characterization of a new fish-virulent Vibrio vulnificus serovar that lacks potential to infect humans.

2007

Vibrio vulnificus is a bacterial species that is virulent for humans and fish. Human isolates are classified into biotypes 1 and 3 (BT1 and BT3) and fish isolates into biotype 2 (BT2). However, a few human infections caused by BT2 isolates have been reported worldwide (zoonosis). These BT2 human isolates belong to serovar E (SerE), which is also present in diseased fish. The aim of the present work was to characterize a new BT2 serovar [serovar A (SerA)], which emerged in the European fish-farming industry in 2000, by means of phenotypic, serological and genetic [plasmid profiling, ribotyping and random amplified polymorphic DNA (RAPD)] methodologies. The results confirmed that SerA constit…

SerotypeDNA BacterialLipopolysaccharidesGenotypeVirulenceVibrio vulnificusMicrobiologyRibotypingMicrobiologySerologyRibotypingFish DiseasesMiceGenotypemedicineAnimalsCluster AnalysisHumansSerum Bactericidal TestSerotypingVibrio vulnificusMice Inbred BALB CEelsbiologyVirulenceZoonosisbiology.organism_classificationmedicine.diseaseDNA FingerprintingRAPDRandom Amplified Polymorphic DNA TechniqueDisease Models AnimalPhenotypeVibrio InfectionsPlasmidsMicrobiology (Reading, England)
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Molecular Typing Reveals Frequent Clustering among Human Isolates of Listeria monocytogenes in Italy

2009

In Italy, the annual incidence of reported cases of listeriosis amounts in recent years (2004 to 2006) to 0.8 cases per million inhabitants. Our study is a subtyping analysis by serotyping, ribotyping, and pulsed-field gel electrophoresis analysis of 44 human isolates from apparently sporadic cases of infection in the Lombardy region and in the Province of Florence, Italy, in the years 1996 to 2007. Based on the results of the different subtyping methods, 10 occasions were detected when strains of L. monocytogenes with the same subtype were isolated from more than one listeriosis case. A total of 28 (66.7%) out of 44 isolates were attributed to molecular subtype clusters. Our data support t…

Serotypemedicine.medical_specialtyBiologySettore MED/42 - Igiene Generale E Applicatamedicine.disease_causeMicrobiologyMicrobiologyImmunocompromised HostRibotypingListeria monocytogenesListeria monocytogenes epidemiology human cases molecular typingMolecular geneticsGenotypemedicineCluster AnalysisHumansListeriosisTypingAgedMolecular epidemiologyListeria monocytogenesVirologySubtypingBacterial Typing TechniquesItalyFood ScienceJournal of Food Protection
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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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Spectral properties of correlation matrices for some hierarchically nested factor models

2007

We show that spectral methods, such as Principal Component Analysis and Random Matrix Theory, are unable to reveal the hierarchical (or nested) structure of a set of mutivariate data. We consider the method introduced in M. Tumminello et al., EPL 78, 30006 (2007) to associate a hierarchical factor model with a set of data by making use of clustering algorithms. This is done by proving the existence of a bijective correspondence between a hierarchical tree and a factor model.

Set (abstract data type)Discrete mathematicsTree (data structure)Multiple correspondence analysisPrincipal component analysisBijectionCluster analysisRandom matrixFactor analysisMathematics
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Correlation based hierarchical clustering in financial time series

2005

We review a correlation based clustering procedure applied to a portfolio of assets synchronously traded in a financial market. The portfolio considered consists of the set of 500 highly capitalized stocks traded at the New York Stock Exchange during the time period 1987-1998. We show that meaningful economic information can be extracted from correlation matrices.

Set (abstract data type)FinanceCorrelationEconomic informationSeries (mathematics)Stock exchangebusiness.industryPortfoliobusinessCluster analysiseconophysichierarchical clusteringHierarchical clustering
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Detection of Anomalous HTTP Requests Based on Advanced N-gram Model and Clustering Techniques

2013

Nowadays HTTP servers and applications are some of the most popular targets for network attacks. In this research, we consider an algorithm for HTTP intrusions detection based on simple clustering algorithms and advanced processing of HTTP requests which allows the analysis of all queries at once and does not separate them by resource. The method proposed allows detection of HTTP intrusions in case of continuously updated web-applications and does not require a set of HTTP requests free of attacks to build the normal user behaviour model. The algorithm is tested using logs acquired from a large real-life web service and, as a result, all attacks from these logs are detected, while the numbe…

Set (abstract data type)n-gramResource (project management)Computer scienceServerAnomaly detectionIntrusion detection systemData miningWeb serviceCluster analysiscomputer.software_genrecomputer
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An Inquiry-Based Approach to a Pedagogical Laboratory for Primary School Teacher Education

2017

In questo articolo vengono presentati e di- scussi alcuni risultati relativi alla sperimen- tazione di due esperienze di didattica laboratoriale della fisica, una basata su me- todi di indagine scientifica e l’altra su meto- dologie didattiche più “tradizionali”, svolte durante l’A.A. 2014-15 con studenti del CdL in Scienze della Formazione Primaria del- l’Università di Palermo. I dati, analizzati tra- mite metodi quantitativi, sono stati ricavati dalla somministrazione prima, durante e do- po le attività laboratoriali, di un questionario finalizzato a comprendere gli stili di insegna- mento preferiti dagli studenti, la motivazio- ne di questi all’apprendimento/insegna- mento delle scienze …

Settore FIS/08 - Didattica E Storia Della FisicaSettore MAT/04 - Matematiche ComplementariInquiry-Based Science Educa- tion. Science Education. Cluster Analysis. Quantitative analysis.
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Multidimensional Scaling in Cluster Analysis: examples in Science and Mathematics Education

2021

Several researches in STEM education research highlight the advantages of an inte- grated approach to these disciplines that relates knowledge and know-how, design and implementation, theoretical and practical problems [5, 4, 6]. In some researches, the effectiveness of these approaches on students conceptual understanding and motivation and has been studied through the use of quantitative analysis tools such as cluster analysis (CLA) [1, 7]. Through CLA it is possible to characterize students analyzing the strategies they deploy to tackle, for example, questionnaires built so as to investigate the lines of reasoning implemented by them when they are proposed with problematic situations. In…

Settore FIS/08 - Didattica E Storia Della FisicaSettore MAT/04 - Matematiche ComplementariMultidimensional Scaling Cluster Analysis Science and Mathematics Education
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Cluster analysis of HVSR peak datasets to detect geological structures

2014

A modified centroid-based algorithm has been applied to HVSR (Horizontal to Vertical Spectral Ratio) datasets (Nakamura, 2000) acquired for studies of seismic microzoning in various urban centers of Sicilian towns also aimed to obtain detailed reconstruction of the roof of the seismic bedrock (Di Stefano et al. 2014). HVSR data were previously properly processed to extract frequency and amplitude of peaks by a code based on clustering of HVSR curves determined in sliding time windows. In centroid-based clustering, clusters are represented by a central vector, which may not necessarily be a member of the data set. After fixing the number of clusters, the algorithm find the cluster centers an…

Settore GEO/11 - Geofisica ApplicataCluster analysis HVSR geological structures
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Image Segmentation based on Genetic Algorithms Combination

2005

The paper describes a new image segmentation algorithm called Combined Genetic segmentation which is based on a genetic algorithm. Here, the segmentation is considered as a clustering of pixels and a similarity function based on spatial and intensity pixel features is used. The proposed methodology starts from the assumption that an image segmentation problem can be treated as a Global Optimization Problem. The results of the image segmentations algorithm has been compared with recent existing techniques. Several experiments, performed on real images, show good performances of our approach compared to other existing methods.

Settore INF/01 - InformaticaComputer scienceSegmentation-based object categorizationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationImage segmentationReal imageGenetic Algorithms clusteringImage textureMinimum spanning tree-based segmentationRegion growingComputer Science::Computer Vision and Pattern RecognitionSegmentationComputer visionArtificial intelligenceCluster analysisbusiness
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