Factor Analysis of a Large DSGE Model

We study the workings of the factor analysis of high-dimensional data using artificial series generated from a large, multi-sector dynamic stochastic general equilibrium (DSGE) model. The objective is to use the DSGE model as a laboratory that allow us to shed some light on the practical benefits and limitations of using factor analysis techniques on economic data. We explain in what sense the artificial data can be thought of having a factor structure, study the theoretical and finite sample properties of the principal components estimates of the factor space, investigate the substantive reason(s) for the good performance of di¤usion index forecasts, and assess the quality of the factor analysis of highly dissagregated data. In all our exercises, we explain the precise relationship between the factors and the basic macroeconomic shocks postulated by the model.

Génération efficace de graphes d’appels dynamiques complets

Analyser le code permet de vérifier ses fonctionnalités, détecter des bogues ou améliorer sa performance. L’analyse du code peut être statique ou dynamique. Des approches combinants les deux analyses sont plus appropriées pour les applications de taille industrielle où l’utilisation individuelle de chaque approche ne peut fournir les résultats souhaités. Les approches combinées appliquent l’analyse dynamique pour déterminer les portions à problèmes dans le code et effectuent par la suite une analyse statique concentrée sur les parties identifiées. Toutefois les outils d’analyse dynamique existants génèrent des données imprécises ou incomplètes, ou aboutissent en un ralentissement inacceptable du temps d’exécution. Lors de ce travail, nous nous intéressons à la génération de graphes d’appels dynamiques complets ainsi que d’autres informations nécessaires à la détection des portions à problèmes dans le code. Pour ceci, nous faisons usage de la technique d’instrumentation dynamique du bytecode Java pour extraire l’information sur les sites d’appels, les sites de création d’objets et construire le graphe d’appel dynamique du programme. Nous démontrons qu’il est possible de profiler dynamiquement une exécution complète d’une application à temps d’exécution non triviale, et d’extraire la totalité de l’information à un coup raisonnable. Des mesures de performance de notre profileur sur trois séries de benchmarks à charges de travail diverses nous ont permis de constater que la moyenne du coût de profilage se situe entre 2.01 et 6.42. Notre outil de génération de graphes dynamiques complets, nommé dyko, constitue également une plateforme extensible pour l’ajout de nouvelles approches d’instrumentation. Nous avons testé une nouvelle technique d’instrumentation des sites de création d’objets qui consiste à adapter les modifications apportées par l’instrumentation au bytecode de chaque méthode. Nous avons aussi testé l’impact de la résolution des sites d’appels sur la performance générale du profileur.

Median filtering: structure analysis and application

Median filtering is a simple digital non—linear signal smoothing operation in which median of the samples in a sliding window replaces the sample at the middle of the window. The resulting filtered sequence tends to follow polynomial trends in the original sample sequence. Median filter preserves signal edges while filtering out impulses. Due to this property, median filtering is finding applications in many areas of image and speech processing. Though median filtering is simple to realise digitally, its properties are not easily analysed with standard analysis techniques,

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

Development of a Fully Automated Image Analysis Method for High Density cDNA and array CGH Microarray Based Genomic Studies

In this thesis, different techniques for image analysis of high density microarrays have been investigated. Most of the existing image analysis techniques require prior knowledge of image specific parameters and direct user intervention for microarray image quantification. The objective of this research work was to develop of a fully automated image analysis method capable of accurately quantifying the intensity information from high density microarrays images. The method should be robust against noise and contaminations that commonly occur in different stages of microarray development.

Conceptual knowledge discovery and data analysis

In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin.

Semantic network analysis of ontologies

A key argument for modeling knowledge in ontologies is the easy re-use and re-engineering of the knowledge. However, beside consistency checking, current ontology engineering tools provide only basic functionalities for analyzing ontologies. Since ontologies can be considered as (labeled, directed) graphs, graph analysis techniques are a suitable answer for this need. Graph analysis has been performed by sociologists for over 60 years, and resulted in the vivid research area of Social Network Analysis (SNA). While social network structures in general currently receive high attention in the Semantic Web community, there are only very few SNA applications up to now, and virtually none for analyzing the structure of ontologies. We illustrate in this paper the benefits of applying SNA to ontologies and the Semantic Web, and discuss which research topics arise on the edge between the two areas. In particular, we discuss how different notions of centrality describe the core content and structure of an ontology. From the rather simple notion of degree centrality over betweenness centrality to the more complex eigenvector centrality based on Hermitian matrices, we illustrate the insights these measures provide on two ontologies, which are different in purpose, scope, and size.

Compositional data analysis of vote shares in the 2001 Australian Federal election

First application of compositional data analysis techniques to Australian election data

Simulation of interlaminar and intralaminar damage in polymer-based composites for aeronautical applications under impact loading

La aplicación de materiales compuestos de matriz polimérica reforzados mediante fibras largas (FRP, Fiber Reinforced Plastic), está en gradual crecimiento debido a las buenas propiedades específicas y a la flexibilidad en el diseño. Uno de los mayores consumidores es la industria aeroespacial, dado que la aplicación de estos materiales tiene claros beneficios económicos y medioambientales. Cuando los materiales compuestos se aplican en componentes estructurales, se inicia un programa de diseño donde se combinan ensayos reales y técnicas de análisis. El desarrollo de herramientas de análisis fiables que permiten comprender el comportamiento mecánico de la estructura, así como reemplazar muchos, pero no todos, los ensayos reales, es de claro interés. Susceptibilidad al daño debido a cargas de impacto fuera del plano es uno de los aspectos de más importancia que se tienen en cuenta durante el proceso de diseño de estructuras de material compuesto. La falta de conocimiento de los efectos del impacto en estas estructuras es un factor que limita el uso de estos materiales. Por lo tanto, el desarrollo de modelos de ensayo virtual mecánico para analizar la resistencia a impacto de una estructura es de gran interés, pero aún más, la predicción de la resistencia residual después del impacto. En este sentido, el presente trabajo abarca un amplio rango de análisis de eventos de impacto a baja velocidad en placas laminadas de material compuesto, monolíticas, planas, rectangulares, y con secuencias de apilamiento convencionales. Teniendo en cuenta que el principal objetivo del presente trabajo es la predicción de la resistencia residual a compresión, diferentes tareas se llevan a cabo para favorecer el adecuado análisis del problema. Los temas que se desarrollan son: la descripción analítica del impacto, el diseño y la realización de un plan de ensayos experimentales, la formulación e implementación de modelos constitutivos para la descripción del comportamiento del material, y el desarrollo de ensayos virtuales basados en modelos de elementos finitos en los que se usan los modelos constitutivos implementados.

Automated organizational network analysis for enterprise 2.0

Social Networking Sites have recently become a mainstream communications technology for many people around the world. Major IT vendors are releasing social software designed for use in a business/commercial context. These Enterprise 2.0 technologies have impressive collaboration and information sharing functionality, but so far they do not have any organizational network analysis (ONA) features that reveal any patterns of connectivity within business units. This paper shows the impact of organizational network analysis techniques and social networks on organizational performance, we also give an overview on current enterprise social software, and most importantly, we highlight how Enterprise 2.0 can help automate an organizational network analysis.

On the variability of the surface environment response to synoptic forcing over complex terrain: a multivariate data analysis approach

Synoptic climatology relates the atmospheric circulation with the surface environment. The aim of this study is to examine the variability of the surface meteorological patterns, which are developing under different synoptic scale categories over a suburban area with complex topography. Multivariate Data Analysis techniques were performed to a data set with surface meteorological elements. Three principal components related to the thermodynamic status of the surface environment and the two components of the wind speed were found. The variability of the surface flows was related with atmospheric circulation categories by applying Correspondence Analysis. Similar surface thermodynamic fields develop under cyclonic categories, which are contrasted with the anti-cyclonic category. A strong, steady wind flow characterized by high shear values develops under the cyclonic Closed Low and the anticyclonic H–L categories, in contrast to the variable weak flow under the anticyclonic Open Anticyclone category.

Thermal analysis and structural investigation of different dental composite resins

The structural and thermal properties of three different dental composite resins, Filtek (TM) Supreme XT, Filtek (TM) Z-250 and TPHA (R)(3) were investigated in this study. The internal structures of uncured and cured resins with blue light-emitting diodes (LEDs) were examined by Micro-Raman spectroscopy. Thermal analysis techniques as DSC, TG and DTG methods were used to investigate the temperature characteristics, as glass transition (T (g) ), degradation, and the thermal stability of the resins. The results showed that the TPHA (R)(3) and Filtek (TM) Supreme XT presented very similar T (g) values, 48 and 50A degrees C, respectively, while the Filtek (TM) Z-250 composite resin presented a higher one, 58A degrees C. AFM microscope was utilized in order to analyze the sample morphologies, which possess different fillers. The composed resin Filtek (TM) Z-250 has a well interconnected more homogeneous morphology, suggesting a better degree of conversion correlated to the glass phase transition temperature. The modes of vibration of interest in the resin were investigated using Raman spectroscopy. It was possible to observe the bands representative for the C=C (1630 cm(-1)) and C=O(1700 cm(-1)) vibrations were studied with respect to their compositions and polymerization. It was observed that the Filtek (TM) Z -250 resin presents the best result related to the thermal properties and polymerization after light curing among the other resins.

Disposable Graphite Foil Based Electrodes and Their Application in Pharmaceutical Analysis

This paper explores a new source of graphite for working electrodes, which presents advantages such as low electrical resistance, good flexibility, favorable mechanical performance, versatility to design electrodes in almost any size and very low cost. The new electrodes were investigated in batch electrochemical cells as associated with flow injection analysis systems. Cyclic voltammetry, stripping voltammetry, and amperometry associated with flow injection analysis techniques were applied for the determination of ascorbic acid, zinc and paracetamol in pharmaceutical formulations, respectively. Well-established analytical methods were applied for comparison purposes. The results herein demonstrate the potential of graphite foils as working electrodes in different electroanalytical methods, offering the possibility of producing disposable sensors for routine applications.

A cooperação trilateral brasileira em Moçambique: um estudo de caso comparado: o ProALIMENTOS e o ProSAVANA

A arquitetura do sistema de ajuda internacional passa por um processo de transformação, no qual as barreiras Norte e Sul tornam-se cada vez mais indefinidas, e a cooperação trilateral, que une as práticas opostas da cooperação Norte-Sul com a cooperação Sul-Sul, emerge como uma nova modalidade da cooperação técnica brasileira. Com o objetivo de compreender esse cenário, esta tese almeja identificar e contrastar as motivações e as práticas dos agentes da cooperação trilateral brasileira por meio de um estudo de caso comparado de dois projetos, desenvolvidos pela Agência Brasileira de Cooperação (ABC), no setor agrícola em Moçambique: o ProALIMENTOS, parceria entre a United States Agency for International Development (USAID- -Brasil) e ABC, e o ProSAVANA, parceria entre Japan International Cooperation Agency (JICA) e ABC. Para isso, a pesquisa parte dos pressupostos da actor-oriented approach para estabelecer uma análise multinível, que cria desta forma um elo entre o agente e a estrutura, a prática e a política, com um olhar sobre o contexto macro, meso e micro. A utilização da metodologia qualitativa aplicada a essa investigação combinou a técnica de participação observante com a técnica de análise documental, acrescentando à análise 59 entrevistas semiestruturadas, realizadas principalmente entre os meses de março e junho de 2013, em Moçambique. Os resultados da pesquisa indicam que, no caso do ProALIMENTOS, há ganhos em complementaridade e troca de conhecimento para as três contrapartes, porém há a sobreposição das práticas Norte-Sul de cooperação para o desenvolvimento internacional sobre as práticas da cooperação Sul-Sul. Enquanto que, no caso do ProSAVANA, não há qualquer ganho de complementariedade, uma vez que o Programa enfrenta desafios internos e externos. A falta de harmonização e coordenação técnica no âmbito interno intensificam o embate externo com os representantes da sociedade civil ao gerar constantes falhas de comunicação, o que coloca em xeque a própria continuidade do ProSAVANA. Por último, a pesquisa mostra que é necessário um maior comprometimento do governo brasileiro nos projetos de Cooperação Trilateral, uma vez que os resultados desses projetos podem impactar e afetar a credibilidade do Brasil como um novo prestador de ajuda internacional.

Ensino do processo de enfermagem: significados percepções docentes na formação do enfermeiro

The implementation of the nursing process should be experienced by all nurses during their formative years. However, the lack of implementation of the nursing process for care planning during the educational process and the existing disorder in the formation process prompted the following research questions: What is the meaning of teaching the nursing process to the nursing professors? Do nursing professors use strategies and methods that promote critical thinking in their students? The objective of the study was to analyze the meaning that teaching of the nursing process has for the nursing faculty of the bachalaureate nursing course. Qualitative descriptive study conducted with a sample of 30 faculty members that taught nursing care courses in the nursing program of the Federal University of Rio Grande do Norte (UFRN) in Natal, RN. Two instruments were used, a questionaire and an interview guide. The questionnaire was designed to obtain sociodemographic, educational and work information, of faculty activities and of the teaching of nursing care. The guide was composed of five open questions regarding the understanding and perceptions of the nursing process, its utilization in teaching, and the nursing care teaching strategies. Interview data were submitted to content analysis techniques and interpreted according to the principles of Symbolic Interactionism. Six categories related to the analytical themes were identified: the nursing process as the guide for the care actions; clinical rationality; use of the care activities; teaching relevance; teaching barreirs; teaching strategies with focus on the abilities and competencies of the clinical rationale. Faculty perceptions regarding the teaching of the nursing process; nursing care approach in the nurses‟ formation. The study indicates that the participants understand the relevance of the nursing process a work instrument and that the use of this method during the nurses‟ formation enhances the abilities and competencies for critical thinking that is essencial for care. The strategies for teaching of abilities and competencies were identified, however the nursing faculty should use codes, direction and the influence so that the students can Interact and therefore stimulate the use of the nursing process