Search results for "cluster analysis."

showing 10 items of 805 documents

Normalised compression distance and evolutionary distance of genomic sequences: comparison of clustering results

2009

Genomic sequences are usually compared using evolutionary distance, a procedure that implies the alignment of the sequences. Alignment of long sequences is a time consuming procedure and the obtained dissimilarity results is not a metric. Recently, the normalised compression distance was introduced as a method to calculate the distance between two generic digital objects and it seems a suitable way to compare genomic strings. In this paper, the clustering and the non-linear mapping obtained using the evolutionary distance and the compression distance are compared, in order to understand if the two distances sets are similar.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryCompression (functional analysis)Metric (mathematics)Normalized compression distanceuniversal similarity metric USM clustering DNA sequences normalised compression distance evolutionary distance genomic sequences nonlinear mapping bioinformaticsPattern recognitionArtificial intelligenceCluster analysisbusinessDistance matrices in phylogenyMathematics
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Fuzzy Smoothed Composition of Local Mapping Transformations for Non-rigid Image Registration

2009

This paper presents a novel method for medical image regis- tration. The global transformation is obtained by composing affine trans- formations, which are recovered locally from given landmarks. Transfor- mations of adjacent regions are smoothed to avoid blocking artifacts, so that a unique continuous and differentiable global function is obtained. Such composition is operated using a technique derived from fuzzy C- means clustering. The method was successfully tested on several datasets; results, both qualitative and quantitative, are shown. Comparisons with other methods are reported. Final considerations on the efficiency of the technique are explained.

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industryImage registrationPattern recognitionComposition (combinatorics)Blocking (statistics)Fuzzy logicfree form deformation image registration fuzzy clustering function interpolation.Global transformationComputer visionDifferentiable functionArtificial intelligenceAffine transformationbusinessCluster analysisMathematics
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The Switch to Online Learning during the COVID-19 Pandemic: The Interplay between Personality and Mental Health on University Students

2023

The switching from traditional to online learning during the COVID-19 pandemic was challenging for students, determining an increase in physical and mental health problems. The current paper applied a two-step cluster analysis in a large sample of n = 1028 university students (Mage = 21.10 years, SD = 2.45 years; range: 18–30 years; 78.4% females). Participants responded to an online survey exploring neuroticism, trait/state anxiety, general self-efficacy, academic motivation, fear of COVID-19, the impact of the COVID-19 pandemic on physical and mental health, and the help requests. Results showed two significant clusters of students having a Maladaptive Academic Profile (n = 456; 44.4%) or…

Settore M-PSI/01 - Psicologia GeneraleHealth Toxicology and Mutagenesisonline learningPublic Health Environmental and Occupational HealthCOVID-19anxietySettore M-PSI/04 - Psicologia Dello Sviluppo E Psicologia Dell'Educazionemotivationpersonalitymental health; online learning; motivation; personality; self-efficacy; COVID-19; anxiety; neuroticism; cluster analysisneuroticismself-efficacymental healthcluster analysis
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The relation between emotional support, self-concept, and social functioning among school-aged children

2013

The study examined the relations between perceived emotional support from parents and peers, self-concept and social functioning among a sample of school-aged children. The study had three main purposes. Firstly, the study was aimed at evaluating the association between emotional support perceived from parents and peers, and self concept. Secondly, the study was aimed at inquiring the existence of different children’s profiles on the basis of the level of perceived emotional support from parents and peers, and their self-concept. Finally, the study was aimed at exploring any difference that could have emerged in their social functioning. The participants were 270 children (F = 137, M = 133)…

Settore M-PSI/04 - Psicologia Dello Sviluppo E Psicologia Dell'EducazioneEMOTIONAL SUPPORT SELF-CONCEPT CLUSTER ANALYSIS PEER RELATIONSHIPSettore M-PSI/03 - Psicometria
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Soft Topographic Map for Clustering and Classification of Bacteria

2007

In this work a new method for clustering and building a topographic representation of a bacteria taxonomy is presented. The method is based on the analysis of stable parts of the genome, the so-called “housekeeping genes”. The proposed method generates topographic maps of the bacteria taxonomy, where relations among different type strains can be visually inspected and verified. Two well known DNA alignement algorithms are applied to the genomic sequences. Topographic maps are optimized to represent the similarity among the sequences according to their evolutionary distances. The experimental analysis is carried out on 147 type strains of the Gammaprotebacteria class by means of the 16S rRNA…

Settore MED/07 - Microbiologia E Microbiologia Clinicatopographic mapComputer scienceClass (philosophy)GenomeAlgorithmsDatabase systemsDNAGenesTaxonomiestaxonomySimilarity (network science)Computer visionbacteriaCluster analysisGeneBioinformatichousekeeping geneSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniSettore INF/01 - Informaticabusiness.industryBacterial taxonomyPattern recognitionGenomic Sequence ClusteringTopographic mapHousekeeping geneSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaArtificial intelligencebusinessclustering
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The routes of Southern Italy university students: an explorative analysis

2022

The neoclassical migration approach postulates that different conditions in labour markets among territories are the driving forces behind migration. On the other hand, exponents of the new economics of migration argue that the decision to move is not made at the individual level. Considering migration as the result of a decision taken within a social network helps to explain the so-called chain migration. In this paper, we pay attention to the migratory chain of university students. This work introduces a statistical technique to “classify” migratory chains of students living in Sicily, Sardinia or Apulia, and enrolled in some centre-north regions from 2008 to 2017.

Settore SECS-S/05 - Statistica SocialeStudent mobility chain migration cluster analysis university students
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Implementing Immersive Clustering with VR Juggler

2005

Continuous, rapid improvements in commodity hardware have allowed users of immersive visualization to employ high-quality graphics hardware, high-speed processors, and significant amounts of memory for much lower costs than would be possible with high-end, shared memory computers traditionally used for such purposes. Mimicking the features of a single shared memory computer requires that the commodity computers act in concert—namely, as a tightly synchronized cluster. In this paper, we describe the clustering infrastructure of VR Juggler that enables the use of distributed and clustered computers for the display of immersive virtual environments. We discuss each of the potential ways to syn…

Shared memoryComputer scienceHuman–computer interactionGraphics hardwareOperating systemScene graphGraphicsVirtual realityCluster analysiscomputer.software_genrecomputerVisualization
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COMPARISON OF TWO SIMPLIFICATION METHODS FOR SHORELINE EXTRACTION FROM DIGITAL ORTHOPHOTO IMAGES

2018

Abstract. The coastal ecosystems are very sensitive to external influences. Coastal resources such as sand dunes, coral reefs and mangroves has vital importance to prevent coastal erosion. Human based effects also threats the coastal areas. Therefore, the change of coastal areas should be monitored. Up-to-date, accurate shoreline information is indispensable for coastal managers and decision makers. Remote sensing and image processing techniques give a big opportunity to obtain reliable shoreline information. In the presented study, NIR bands of seven 1:5000 scaled digital orthophoto images of Riga Bay-Latvia have been used. The Object-oriented Simple Linear Clustering method has been utili…

Shorelcsh:Applied optics. Photonicsgeographygeography.geographical_feature_category010504 meteorology & atmospheric scienceslcsh:TReference data (financial markets)Orthophotolcsh:TA1501-1820Image processingImage segmentation010502 geochemistry & geophysics01 natural scienceslcsh:TechnologySand dune stabilizationCoastal erosionlcsh:TA1-2040Cluster analysislcsh:Engineering (General). Civil engineering (General)CartographyGeology0105 earth and related environmental sciencesRemote sensingISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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An enhanced random walk algorithm for delineation of head and neck cancers in PET studies

2017

An algorithm for delineating complex head and neck cancers in positron emission tomography (PET) images is presented in this article. An enhanced random walk (RW) algorithm with automatic seed detection is proposed and used to make the segmentation process feasible in the event of inhomogeneous lesions with bifurcations. In addition, an adaptive probability threshold and a k-means based clustering technique have been integrated in the proposed enhanced RW algorithm. The new threshold is capable of following the intensity changes between adjacent slices along the whole cancer volume, leading to an operator-independent algorithm. Validation experiments were first conducted on phantom studies:…

Similarity (geometry)Computer sciencePET imagingBiomedical EngineeringRandom walk030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicinemedicineImage Processing Computer-AssistedHumansSegmentationComputer visionCluster analysisEvent (probability theory)Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionimedicine.diagnostic_testbusiness.industryPhantoms ImagingBiological target volume; Head and neck cancer segmentation; PET imaging; Random walksComputer Science ApplicationPattern recognitionRandom walkComputer Science ApplicationsBiological target volumeHausdorff distancePositron emission tomographyHead and Neck Neoplasms030220 oncology & carcinogenesisPositron-Emission TomographyArtificial intelligenceHead and neck cancer segmentationComputer Vision and Pattern RecognitionbusinessAlgorithmsBiological target volume Head and neck cancer segmentation PET imaging Random walks Algorithms Head and Neck Neoplasms Humans Image Processing Computer-Assisted Phantoms Imaging Positron-Emission TomographyVolume (compression)
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Trademarks recognition based on local regions similarities

2010

This paper deals with content based image retrieval. We propose a logo recognition algorithm based on local regions, where the trademark (or logo) image is segmented by the clustering of points of interest obtained by Harris corners detector. The minimum rectangle surrounding each cluster is detected forming the regions of interest. Global features such as Hu moments and histograms of each local region are combined to find similar logos in the database. Similarity is measured based on the integrated minimum average distance of the individual components. The results obtained demonstrate tolerance to logos distortions such as rotation, occlusion and noise.

Similarity (geometry)business.industryComputer scienceMathematics::History and OverviewComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCorner detectionPattern recognitionImage segmentationContent-based image retrievalEdge detectionComputingMethodologies_PATTERNRECOGNITIONComputer Science::Computer Vision and Pattern RecognitionPattern recognition (psychology)Computer visionArtificial intelligencebusinessCluster analysisImage retrieval10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010)
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