Clustering and diffusion in a symplectic map lattice with non-local coupling

We study a symplectic chain with a non-local form of coupling by means of a standard map lattice where the interaction strength decreases with the lattice distance as a power-law, in Such a way that one can pass continuously from a local (nearest-neighbor) to a global (mean-field) type of coupling. We investigate the formation of map clusters, or spatially coherent structures generated by the system dynamics. Such clusters are found to be related to stickiness of chaotic phase-space trajectories near periodic island remnants, and also to the behavior of the diffusion coefficient. An approximate two-dimensional map is derived to explain some of the features of this connection. (C) 2008 Elsevier Ltd. All rights reserved.

A WAVELET-BASED SPEAKER VERIFICATION ALGORITHM

This paper presents a study on wavelets and their characteristics for the specific purpose of serving as a feature extraction tool for speaker verification (SV), considering a Radial Basis Function (RBF) classifier, which is a particular type of Artificial Neural Network (ANN). Examining characteristics such as support-size, frequency and phase responses, amongst others, we show how Discrete Wavelet Transforms (DWTs), particularly the ones which derive from Finite Impulse Response (FIR) filters, can be used to extract important features from a speech signal which are useful for SV. Lastly, an SV algorithm based on the concepts presented is described.

Speaker at a New York Trade School Commencement Ceremony

An administrator from the New York Trade School speaks at the school's commencement ceremony. In front of the speaker several athletic awards are positioned on a table. Black and white photograph.

Clustering Lab value working with medical data

Data mining is a relatively new field of research that its objective is to acquire knowledge from large amounts of data. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available [27]. On the one hand, practitioners are expected to use all this data in their work but, at the same time, such a large amount of data cannot be processed by humans in a short time to make diagnosis, prognosis and treatment schedules. A major objective of this thesis is to evaluate data mining tools in medical and health care applications to develop a tool that can help make rather accurate decisions. In this thesis, the goal is finding a pattern among patients who got pneumonia by clustering of lab data values which have been recorded every day. By this pattern we can generalize it to the patients who did not have been diagnosed by this disease whose lab values shows the same trend as pneumonia patients does. There are 10 tables which have been extracted from a big data base of a hospital in Jena for my work .In ICU (intensive care unit), COPRA system which is a patient management system has been used. All the tables and data stored in German Language database.

Racial Conflict in the United States of America : A Deconstructive Perspective on Native Speaker by Changrae Lee

Written about the time of the Golden Venture incident, Chang-rae Lee’s Native Speaker makes a particular reference to that incident, whereby implying that particular immigrants, on the grounds of their racial identities, are mistreated and considered as aliens by some Americas. While some whites discriminate against immigrants, there is widespread ethnic tension between Korean Americans and African Americans. Significantly, racial conflict between Koreans and blacks and the racist attitude of some whites toward immigrants are mirrored in the relationship between the Korean-American protagonist Henry and his American wife Lelia. That is, due to their different racial identities they do not understand each other and they always argue. However, toward the end of the novel, Henry and Lelia come to understand each other. While ethnic conflict between Koreans and blacks and certain whites’ discriminatory attitudes toward immigrants is serious one, the novel suggests the unimportance of racial identity. In other words, the novel concludes that there is no discriminatory treatment of immigrants and, in fact, every one is a native Speaker in America. In the novel there is no message of how racial conflict could be resolved. However, this essay suggests that by investigating how the tension between Henry and Lelia is resolved, one could suggest a solution for the ethnicity problem in America and in real life.

Speaker at a New York Trade School Social Event

A speaker is pictured along with other important guests on the dais at a New York Trade School social event. Black and white photograph.

Speaker at a New York Trade School Commencement Ceremony

A speaker at the 1957 commencement ceremony at the New York Trade School is shown. George E. McLaughlin, superintendent of the school, can be seen amongst other administrators on the stage behind the speaker. Black and white photograph.

Speaker at a New York Trade School Commencement Ceremony

A speaker at a commencement at the New York Trade School. Other administrators can be seen on the dais behind the speaker. Photograph is black and white.

Utilizando conceitos como descritores de textos para o processo de identificação de conglomerados (clustering) de documentos

A descoberta e a análise de conglomerados textuais são processos muito importantes para a estruturação, organização e a recuperação de informações, assim como para a descoberta de conhecimento. Isto porque o ser humano coleta e armazena uma quantidade muito grande de dados textuais, que necessitam ser vasculhados, estudados, conhecidos e organizados de forma a fornecerem informações que lhe dêem o conhecimento para a execução de uma tarefa que exija a tomada de uma decisão. É justamente nesse ponto que os processos de descoberta e de análise de conglomerados (clustering) se insere, pois eles auxiliam na exploração e análise dos dados, permitindo conhecer melhor seu conteúdo e inter-relações. No entanto, esse processo, por ser aplicado em textos, está sujeito a sofrer interferências decorrentes de problemas da própria linguagem e do vocabulário utilizado nos mesmos, tais como erros ortográficos, sinonímia, homonímia, variações morfológicas e similares. Esta Tese apresenta uma solução para minimizar esses problemas, que consiste na utilização de “conceitos” (estruturas capazes de representar objetos e idéias presentes nos textos) na modelagem do conteúdo dos documentos. Para tanto, são apresentados os conceitos e as áreas relacionadas com o tema, os trabalhos correlatos (revisão bibliográfica), a metodologia proposta e alguns experimentos que permitem desenvolver determinados argumentos e comprovar algumas hipóteses sobre a proposta. As conclusões principais desta Tese indicam que a técnica de conceitos possui diversas vantagens, dentre elas a utilização de uma quantidade muito menor, porém mais representativa, de descritores para os documentos, o que torna o tempo e a complexidade do seu processamento muito menor, permitindo que uma quantidade muito maior deles seja analisada. Outra vantagem está no fato de o poder de expressão de conceitos permitir que os usuários analisem os aglomerados resultantes muito mais facilmente e compreendam melhor seu conteúdo e forma. Além do método e da metodologia proposta, esta Tese possui diversas contribuições, entre elas vários trabalhos e artigos desenvolvidos em parceria com outros pesquisadores e colegas.

Contribuições aos Processos de Clustering com Base em Métricas não-Euclidianas

In this work we present a new clustering method that groups up points of a data set in classes. The method is based in a algorithm to link auxiliary clusters that are obtained using traditional vector quantization techniques. It is described some approaches during the development of the work that are based in measures of distances or dissimilarities (divergence) between the auxiliary clusters. This new method uses only two a priori information, the number of auxiliary clusters Na and a threshold distance dt that will be used to decide about the linkage or not of the auxiliary clusters. The number os classes could be automatically found by the method, that do it based in the chosen threshold distance dt, or it is given as additional information to help in the choice of the correct threshold. Some analysis are made and the results are compared with traditional clustering methods. In this work different dissimilarities metrics are analyzed and a new one is proposed based on the concept of negentropy. Besides grouping points of a set in classes, it is proposed a method to statistical modeling the classes aiming to obtain a expression to the probability of a point to belong to one of the classes. Experiments with several values of Na e dt are made in tests sets and the results are analyzed aiming to study the robustness of the method and to consider heuristics to the choice of the correct threshold. During this work it is explored the aspects of information theory applied to the calculation of the divergences. It will be explored specifically the different measures of information and divergence using the Rényi entropy. The results using the different metrics are compared and commented. The work also has appendix where are exposed real applications using the proposed method