Search results for "Clustering"
showing 10 items of 446 documents
Algorithms for internal validation clustering measures in the post genomic era.
2011
Galaxy clustering: a point process
2016
El 'clustering' de galàxies és l'agregació de galàxies en l'universe produida per la força de la gravetat. Les galàxies tendeixen a formar estructures de major tamany tal com 'clusters' o filaments que formen la xarxa còsmica ('Cosmic Web'). Aquesta Estructura a Gran Escala de l'Univers es pot entendre com el resultat de la distribució de galàxies, un procés en el qual totes les galàxies estan subjectes a forces comuns i comparteixen propietats universals. L'anàlisis d'aquesta distribució es pot realitzar amb técniques de processos puntuals, l'estudi de configuracions de punts sobre un marc. En aquesta tesi fem servir aquesta branca de la estadística en tres approximacions diferents: els es…
Behavioral aspects of the European carbon market
2016
TEMA: El tema de esta tesis doctoral está basado en el campo de las finanzas del comportamiento en donde se proponen teorías basados en la psicología para explicar las anomalías del mercado de valores. Dentro de las finanzas del comportamiento, se supone que la estructura de la información y las características de los participantes del mercado influyen sistemáticamente en las decisiones de inversión de los individuos, así como en los resultados del mercado. Así pues, durante todo el estudio se analizaran ciertos comportamientos psicológicos que podrían afectar al comportamiento del mercado del carbono europeo y que de demostrarse su presencia alteraría la racionalidad de dicho mercado finan…
Inflammatory Biomarkers in Febrile Seizure: A Comprehensive Bibliometric, Review and Visualization Analysis.
2021
Background: Inflammatory markers association with many diseases is the subject of many articles and reviews. This study presents a comprehensive bibliometric review and visualization analysis of inflammatory biomarkers (IB) in the context of febrile seizure (FS) patients. Methods: The study focused on IB in FS using (1) bibliometric analysis specific indicators and maps in order to analyze and present the network of authors, journals, universities, and countries, and (2) automated literature screening and unsupervised clustering approach for filtering and topic cluster identification. Results: We conducted a literature mining search on FS research, specifically IB in the context of FS, usin…
Hierarchical structure of the Sicilian goats revealed by Bayesian analyses of microsatellite information
2010
Genetic structure and relationship amongst the main goat populations in Sicily (Girgentana, Derivata di Siria, Maltese and Messinese) were analysed using information from 19 microsatellite markers genotyped on 173 individuals. A posterior Bayesian approach implemented in the program STRUCTURE revealed a hierarchical structure with two clusters at the first level (Girgentana vs. Messinese, Derivata di Siria and Maltese), explaining 4.8% of variation (amovaФ(ST) estimate). Seven clusters nested within these first two clusters (further differentiations of Girgentana, Derivata di Siria and Maltese), explaining 8.5% of variation (amovaФ(SC) estimate). The analyses and methods applied in this stu…
Probabilistic Transition-Based Approach for Detecting Application-Layer DDoS Attacks in Encrypted Software-Defined Networks
2017
With the emergence of cloud computing, many attacks, including Distributed Denial-of-Service (DDoS) attacks, have changed their direction towards cloud environment. In particular, DDoS attacks have changed in scale, methods, and targets and become more complex by using advantages provided by cloud computing. Modern cloud computing environments can benefit from moving towards Software-Defined Networking (SDN) technology, which allows network engineers and administrators to respond quickly to the changing business requirements. In this paper, we propose an approach for detecting application-layer DDoS attacks in cloud environment with SDN. The algorithm is applied to statistics extracted from…
Classification of Chitinozoa (Llandoverian, Canada) Using Image Analysis
1996
Chitinozoa (Llandoverian, Canada) were studied using image analysis. After digitalization of the objects, shape parameters were calculated. The boundary of each fossil was then traced by a vector centred at the centroid for Fast Fourier Transform (FFT). Results of the two methods were used as variables in a hierarchical cluster analysis in order to group the samples. These results show that Chitinozoa can be significantly classified in terms of taxa using independent shape parameters obtained by image analysis.
Unsupervised clustering method for pattern recognition in IIF images
2017
Autoimmune diseases are a family of more than 80 chronic, and often disabling, illnesses that develop when underlying defects in the immune system lead the body to attack its own organs, tissues, and cells. Diagnosis of autoimmune pathologies is based on research and identification of antinuclear antibodies (ANA) through indirect immunofluorescence (IIF) method and is performed by analyzing patterns and fluorescence intensity. We propose here a method to automatically classify the centromere pattern based on the grouping of centromeres on the cells through a clustering K-means algorithm. The described method was tested on a public database (MIVIA). The results of the test showed an Accuracy…
An algorithm for earthquakes clustering based on maximum likelihood
2007
In this paper we propose a clustering technique set up to separate and find out the two main components of seismicity: the background seismicity and the triggered one. We suppose that a seismic catalogue is the realization of a non homogeneous space-time Poisson clustered process, with a different parametrization for the intensity function of the Poisson-type component and of the clustered (triggered) component. The method here proposed assigns each earthquake to the cluster of earthquakes, or to the set of independent events, according to the increment to the likelihood function, computed using the conditional intensity function estimated by maximum likelihood methods and iteratively chang…
Restricted Neighborhood Search Clustering Revisited: An Evolutionary Computation Perspective
2013
Protein-protein interaction networks have been broadly studied in the last few years, in order to understand the behavior of proteins inside the cell. Proteins interacting with each other often share common biological functions or they participate in the same biological process. Thus, discovering protein complexes made of groups of proteins strictly related, can be useful to predict protein functions. Clustering techniques have been widely employed to detect significative biological complexes. In this paper, we integrate one of the most popular network clustering techniques, namely the Restricted Neighborhood Search Clustering (RNSC), with evolutionary computation. The two cost functions in…