2 resultados para C (Computer program language)
em Reposit
Resumo:
Introduction: Knowing the experience of abuse, contextual determinants that led to the rupture of the situation and attempts to build a more harmonious future, it is essential to work sensitivities and better understand victims of domestic violence. Objectives: To understand the suffering of women victims of violence. Methods: This is an intentional sample of 21 women who were at shelter home or in the community. The data were collected by in- Documento descargado de http://www.elsevier.es el 13-10-2016 3rd World Congress of Health Research 21 terviews, guided by a script organized into four themes. The interviews were conducted with audio record, the permission of the participants were fully passed the text and analyzed as two different corpuses, depending on the context in which they occurred. The analysis was conducted using the ALCESTE computer program. The study obtained a favorable opinion of the Committee on Health and Welfare of the University of Évora. Results: From the irst sample analysis emerged ive classes. The association of the words gave the meaning of each class that we have appointed as Class 1 - Precipitating Events; Class 2 - Experience of abuse; Class 3 - Two feet in the present and looking into the future; Class 4 - The present and learning from the experience of abuse; and Class 5 - Violence in general. From the analysis of the sample in the community four classes emerged that we have appointed as Class 1 - Violence in general; Class 2 - Precipitating Events; Class 3 - abuse of experience; and class 4 - Support in the process. Conclusions: Women who are at shelter home have this experience of violence and its entire context a lot are very focused on their experiences and the future is distant and unclear. Women in the community have a more comprehensive view of the phenomenon of violence as a whole, they can decentralize to their personal experiences and recognize the importance of support in the future construction process.
Resumo:
Apresenta·se um breve resumo histórico da evolução da amostragem por transectos lineares e desenvolve·se a sua teoria. Descrevemos a teoria de amostragem por transectos lineares, proposta por Buckland (1992), sendo apresentados os pontos mais relevantes, no que diz respeito à modelação da função de detecção. Apresentamos uma descrição do princípio CDM (Rissanen, 1978) e a sua aplicação à estimação de uma função densidade por um histograma (Kontkanen e Myllymãki, 2006), procedendo à aplicação de um exemplo prático, recorrendo a uma mistura de densidades. Procedemos à sua aplicação ao cálculo do estimador da probabilidade de detecção, no caso dos transectos lineares e desta forma estimar a densidade populacional de animais. Analisamos dois casos práticos, clássicos na amostragem por distâncias, comparando os resultados obtidos. De forma a avaliar a metodologia, simulámos vários conjuntos de observações, tendo como base o exemplo das estacas, recorrendo às funções de detecção semi-normal, taxa de risco, exponencial e uniforme com um cosseno. Os resultados foram obtidos com o programa DISTANCE (Thomas et al., in press) e um algoritmo escrito em linguagem C, cedido pelo Professor Doutor Petri Kontkanen (Departamento de Ciências da Computação, Universidade de Helsínquia). Foram desenvolvidos programas de forma a calcular intervalos de confiança recorrendo à técnica bootstrap (Efron, 1978). São discutidos os resultados finais e apresentadas sugestões de desenvolvimentos futuros. ABSTRACT; We present a brief historical note on the evolution of line transect sampling and its theoretical developments. We describe line transect sampling theory as proposed by Buckland (1992), and present the most relevant issues about modeling the detection function. We present a description of the CDM principle (Rissanen, 1978) and its application to histogram density estimation (Kontkanen and Myllymãki, 2006), with a practical example, using a mixture of densities. We proceed with the application and estimate probability of detection and animal population density in the context of line transect sampling. Two classical examples from the literature are analyzed and compared. ln order to evaluate the proposed methodology, we carry out a simulation study based on a wooden stakes example, and using as detection functions half normal, hazard rate, exponential and uniform with a cosine term. The results were obtained using program DISTANCE (Thomas et al., in press), and an algorithm written in C language, kindly offered by Professor Petri Kontkanen (Department of Computer Science, University of Helsinki). We develop some programs in order to estimate confidence intervals using the bootstrap technique (Efron, 1978). Finally, the results are presented and discussed with suggestions for future developments.