Mises à distances. Ethnographie des places publiques centrales de Cluj-« Napoca » (Roumanie) dans le postsocialisme

Cette recherche porte sur le changement social dans la période postsocialiste à Cluj-« Napoca », une ville transylvaine de Roumanie. En mobilisant une approche en termes de rapports sociaux à l’espace, l’étude explore les principes de différenciation tant spatialement que socialement. Les concepts d’« espace public » et de « lieu » ont permis une analyse aux multiples facettes menée selon quatre axes : matérialité et la visibilité des espaces, sphère publique-politique, vie sociale publique, investissements et appropriations individuelles. La thèse examine ainsi les activités qui se déroulent dans les places publiques centrales, les investissements spatiaux, les rituels quotidiens et les manifestations contestataires, les multiples attachements ethniques et religieux des habitants. L’ethnographie des places publiques centrales de Cluj-« Napoca » a mis en évidence une « faible classification des espaces » centraux de la ville, traduite par une grande diversité sociale. Les marques ethnicisantes parsemées à Cluj-« Napoca » renvoient aux groupes ethniques, mais aussi à d’autres enjeux qui relèvent du processus de restructuration du champ politique dans le postsocialisme. Dans le même registre, les stratégies de type ethnique sont mobilisées pour désigner de nouveaux critères de différenciation sociale et pour redéfinir d’anciennes catégories sociales. Oublis, silences et exigences d’esthétisation reflètent des demandes implicites des habitants pour redéfinir les cadres de la politique. Finalement, la thèse montre comment l’espace public à Cluj-« Napoca » pendant la période postsocialiste relève d’un processus continuel de diversification sociale et d’invention des Autres par d’incessantes mises à distance. L’espace public n’est pas la recherche de ce que pourrait constituer le vivre ensemble, mais la quête de ce qui nous menace et qu’il faut mettre à distance.

A Vector Signal Processing Approach to Color

Surface (Lambertain) color is a useful visual cue for analyzing material composition of scenes. This thesis adopts a signal processing approach to color vision. It represents color images as fields of 3D vectors, from which we extract region and boundary information. The first problem we face is one of secondary imaging effects that makes image color different from surface color. We demonstrate a simple but effective polarization based technique that corrects for these effects. We then propose a systematic approach of scalarizing color, that allows us to augment classical image processing tools and concepts for multi-dimensional color signals.

Los conceptos de salud financiera, riesgo y epidemiología en los estados financieros de las compañías del sector de extracción de petróleo crudo y gas natural en Colombia

El presente proyecto tiene como objeto identificar cuáles son los conceptos de salud, enfermedad, epidemiología y riesgo aplicables a las empresas del sector de extracción de petróleo y gas natural en Colombia. Dado, el bajo nivel de predicción de los análisis financieros tradicionales y su insuficiencia, en términos de inversión y toma de decisiones a largo plazo, además de no considerar variables como el riesgo y las expectativas de futuro, surge la necesidad de abordar diferentes perspectivas y modelos integradores. Esta apreciación es pertinente dentro del sector de extracción de petróleo y gas natural, debido a la creciente inversión extranjera que ha reportado, US$2.862 millones en el 2010, cifra mayor a diez veces su valor en el año 2003. Así pues, se podrían desarrollar modelos multi-dimensional, con base en los conceptos de salud financiera, epidemiológicos y estadísticos. El termino de salud y su adopción en el sector empresarial, resulta útil y mantiene una coherencia conceptual, evidenciando una presencia de diferentes subsistemas o factores interactuantes e interconectados. Es necesario mencionar también, que un modelo multidimensional (multi-stage) debe tener en cuenta el riesgo y el análisis epidemiológico ha demostrado ser útil al momento de determinarlo e integrarlo en el sistema junto a otros conceptos, como la razón de riesgo y riesgo relativo. Esto se analizará mediante un estudio teórico-conceptual, que complementa un estudio previo, para contribuir al proyecto de finanzas corporativas de la línea de investigación en Gerencia.

Percepción de residentes de medicina de urgencias en Colombia del ambiente educativo en los servicios de urgencias

Introducción: La atención de calidad en urgencias sólo es posible si los médicos han recibido una enseñanza de alta calidad. La escala PHEEM (Postgraduate Hospital Educational Environment Measure) es un instrumento válido y fiable, utilizado internacionalmente para medir el entorno educativo, en la formación médica de posgrado. Materiales y métodos: Estudio de corte trasversal que utilizó la escala PHEEM versión en español para conocer el entorno educativo de los programas de urgencias. El coeficiente alfa de Cronbach se calculó para determinar la consistencia interna. Se aplicó estadística descriptiva a nivel global, por categorías e ítems de la escala PHEEM y se compararon resultados por sexo, año de residencia y programa. Resultados: 94 (94%) residentes llenaron el cuestionario. La puntuación media de la escala PHEEM fue 93,91 ± 23,71 (58,1% de la puntuación máxima) que se considera un ambiente educativo más positivo que negativo, pero con margen de mejora. Hubo una diferencia estadísticamente significativa en la percepción del ambiente educativo entre los programas de residencia (p =0,01). El instrumento es altamente confiable (alfa de Cronbach = 0,952). La barrera más frecuente en la enseñanza fue el hacinamiento y la evaluación fue percibida con el propósito de cumplir normas. Discusión: Los resultados de este estudio aportaron evidencia sobre la validez interna de la escala PHEEM en el contexto colombiano. Este estudio demostró cómo la medición del ambiente educativo en una especialidad médico-quirúrgica, con el uso de una herramienta cuantitativa, puede proporcionar información en relación a las fortalezas y debilidades de los programas.

Fast training of self organizing maps for the visual exploration of molecular compounds

Visual exploration of scientific data in life science area is a growing research field due to the large amount of available data. The Kohonen’s Self Organizing Map (SOM) is a widely used tool for visualization of multidimensional data. In this paper we present a fast learning algorithm for SOMs that uses a simulated annealing method to adapt the learning parameters. The algorithm has been adopted in a data analysis framework for the generation of similarity maps. Such maps provide an effective tool for the visual exploration of large and multi-dimensional input spaces. The approach has been applied to data generated during the High Throughput Screening of molecular compounds; the generated maps allow a visual exploration of molecules with similar topological properties. The experimental analysis on real world data from the National Cancer Institute shows the speed up of the proposed SOM training process in comparison to a traditional approach. The resulting visual landscape groups molecules with similar chemical properties in densely connected regions.

Effectiveness of landmark analysis for establishing locality in p2p networks

Locality to other nodes on a peer-to-peer overlay network can be established by means of a set of landmarks shared among the participating nodes. Each node independently collects a set of latency measures to landmark nodes, which are used as a multi-dimensional feature vector. Each peer node uses the feature vector to generate a unique scalar index which is correlated to its topological locality. A popular dimensionality reduction technique is the space filling Hilbert’s curve, as it possesses good locality preserving properties. However, there exists little comparison between Hilbert’s curve and other techniques for dimensionality reduction. This work carries out a quantitative analysis of their properties. Linear and non-linear techniques for scaling the landmark vectors to a single dimension are investigated. Hilbert’s curve, Sammon’s mapping and Principal Component Analysis have been used to generate a 1d space with locality preserving properties. This work provides empirical evidence to support the use of Hilbert’s curve in the context of locality preservation when generating peer identifiers by means of landmark vector analysis. A comparative analysis is carried out with an artificial 2d network model and with a realistic network topology model with a typical power-law distribution of node connectivity in the Internet. Nearest neighbour analysis confirms Hilbert’s curve to be very effective in both artificial and realistic network topologies. Nevertheless, the results in the realistic network model show that there is scope for improvements and better techniques to preserve locality information are required.

Ecology of sponge assemblages (Porifera) in the Wakatobi region, south-east Sulawesi, Indonesia: richness and abundance

The influence of sedimentation, depth and substratum angle on sponge assemblages in the Wakatobi region, south-eastern Sulawesi, Indonesia was considered. Sponge assemblages were sampled from two reef localities. The first reef (Sampela) was highly impacted by high sedimentation rates with fine sediment particles that settle slowly, while the second (Hoga) experienced only fast settling coarse sediment with lower overall sedimentation rates. Sponge assemblages were sampled (area occupied and numbers) on the reef fiat (0 m) and at 5 (reef crest), 10 and 15 m (15 m at Hoga only). Some significant (P < 0.001) differences were observed in the area occupied and the number of sponge patches between surface angles and sites. Significantly lower (t > 4.61, df = 9, P < 0.001) sponge numbers, percentage cover and richness were associated with the reef flat at both sites compared with all other depths at each site, with the exception of abundance of sponges on the reef flat at Sampela, which was much greater than at any other depth sampled. Species richness increased with depth at both sites but differences between surface angles were only recorded at Sampela, with higher species richness being found on vertical, inclined and horizontal surfaces respectively A total of 100 sponge species (total area sampled 52.5 m(2)) was reported from the two sites, with 58 species found at Sampela and 71 species at Hoga (41% of species shared). Multi-dimensional scaling (MDS) indicated differences in assemblage structure between sites and most depth intervals, but not substratum angles. A number of biological (e.g. competition and predation) and physical (e.g. sedimentation and aerial exposure) factors were considered to control sponge abundance and richness. Unexpectedly a significant (F-1,F-169 = 148.98, P < 0.001) positive linear relationship was found between sponge density and area occupied. In areas of high sponge coverage, the number of patches was also high, possibly due to fragmentation of large sponges produced as a result of predation and physical disturbance. The MDS results were also the same whether sponge numbers or percentage cover estimates were used, suggesting that although these different approaches yield different sorts of information, the same assemblage structure can be identified.

Exact error estimates and optimal randomized algorithms for integration

Exact error estimates for evaluating multi-dimensional integrals are considered. An estimate is called exact if the rates of convergence for the low- and upper-bound estimate coincide. The algorithm with such an exact rate is called optimal. Such an algorithm has an unimprovable rate of convergence. The problem of existing exact estimates and optimal algorithms is discussed for some functional spaces that define the regularity of the integrand. Important for practical computations data classes are considered: classes of functions with bounded derivatives and Holder type conditions. The aim of the paper is to analyze the performance of two optimal classes of algorithms: deterministic and randomized for computing multidimensional integrals. It is also shown how the smoothness of the integrand can be exploited to construct better randomized algorithms.

Space partitioning for scalable K-means

K-Means is a popular clustering algorithm which adopts an iterative refinement procedure to determine data partitions and to compute their associated centres of mass, called centroids. The straightforward implementation of the algorithm is often referred to as `brute force' since it computes a proximity measure from each data point to each centroid at every iteration of the K-Means process. Efficient implementations of the K-Means algorithm have been predominantly based on multi-dimensional binary search trees (KD-Trees). A combination of an efficient data structure and geometrical constraints allow to reduce the number of distance computations required at each iteration. In this work we present a general space partitioning approach for improving the efficiency and the scalability of the K-Means algorithm. We propose to adopt approximate hierarchical clustering methods to generate binary space partitioning trees in contrast to KD-Trees. In the experimental analysis, we have tested the performance of the proposed Binary Space Partitioning K-Means (BSP-KM) when a divisive clustering algorithm is used. We have carried out extensive experimental tests to compare the proposed approach to the one based on KD-Trees (KD-KM) in a wide range of the parameters space. BSP-KM is more scalable than KDKM, while keeping the deterministic nature of the `brute force' algorithm. In particular, the proposed space partitioning approach has shown to overcome the well-known limitation of KD-Trees in high-dimensional spaces and can also be adopted to improve the efficiency of other algorithms in which KD-Trees have been used.

How do people perceive, understand, and anticipate responding to flash flood risks and warnings? Results from a public survey in Boulder, Colorado, USA

This study investigates flash flood forecast and warning communication, interpretation, and decision making, using data from a survey of 418 members of the public in Boulder, Colorado, USA. Respondents to the public survey varied in their perceptions and understandings of flash flood risks in Boulder, and some had misconceptions about flash flood risks, such as the safety of crossing fast-flowing water. About 6% of respondents indicated consistent reversals of US watch-warning alert terminology. However, more in-depth analysis illustrates the multi-dimensional, situationally dependent meanings of flash flood alerts, as well as the importance of evaluating interpretation and use of warning information along with alert terminology. Some public respondents estimated low likelihoods of flash flooding given a flash flood warning; these were associated with lower anticipated likelihood of taking protective action given a warning. Protective action intentions were also lower among respondents who had less trust in flash flood warnings, those who had not made prior preparations for flash flooding, and those who believed themselves to be safer from flash flooding. Additional analysis, using open-ended survey questions about responses to warnings, elucidates the complex, contextual nature of protective decision making during flash flood threats. These findings suggest that warnings can play an important role not only by notifying people that there is a threat and helping motivate people to take protective action, but also by helping people evaluate what actions to take given their situation.

Um modelo categorizador intervalar n-dimensional com l-camadas baseado em tesselações

O ICTM (Interval Categorizer Tesselation Model), objeto da presente tese, é um modelo geral para análise de espaços de natureza geométrica, baseado em tesselaçoes, que é capaz de produzir uma categorização confiável de conjunto de pontos de um dado espaço, de acordo com múltiplas características dos pontos, cada característica correspondendo a uma camada do modelo. Por exemplo, na análise de terrenos geográficos, uma região geográfica pode ser analisada de acordo com a sua topografia, vegetaçao, demografia, dados econômicos etc, cada uma gerando uma subdivisão diferente da região. O modelo geral baseado em tesselações não está restrito, porém, a análise de espaços bi-dimensionais. O conjunto dos pontos analisados pode pertencer a um espaço multidimensional, determinando a característica multi-dimensional de cada camada. Um procedimento de projeção das categorizações obtidas em cada camada sobre uma camada básica leva a uma categorização confiavel mais significante, que combina em uma só classificação as análises obtidas para cada característica. Isto permite muitas análises interessantes no que tange a dependência mútua das características. A dimensão da tesselação pode ser arbitrária ou escolhida de acordo com algum critério específico estabelecido pela aplicação. Neste caso, a categorização obtida pode ser refinada, ou pela re-definição da dimensão da tesselação ou tomando cada sub-região resultante para ser analisada separadamente A formalização nos registradores pode ser facilmente recuperada apenas pela indexação dos elementos das matrizes, em qualquer momento da execução. A implementação do modelo é naturalmente paralela, uma vez que a análise é feita basicamente por regras locais. Como os dados de entrada numéricos são usualmente suscetíveis a erros, o modelo utiliza a aritmética intervalar para se ter um controle automático de erros. O modelo ICTM também suporta a extração de fatos sobre as regiões de modo qualitativo, por sentenças lógicas, ou quantitativamente, pela análise de probabilidade. Este trabalho recebe apoio nanceiro do CNPq/CTPETRO e FAPERGS.

Analog nonderivative optimizers

Analog networks for solving convex nonlinear unconstrained programming problems without using gradient information of the objective function are proposed. The one-dimensional net can be used as a building block in multi-dimensional networks for optimizing objective functions of several variables.

The contribution of biofuels to the sustainability of development in Latin America and the Caribbean

Includes bibliography

Socio-Economic Perspectives on Shifting Cultivation Landscapes in Northern Laos

Despite the rapid agricultural transition that has occurred in the past decade, shifting cultivation remains a widespread agricultural practice in the northern uplands of Lao PDR. Little information is available on the basic socio-economic situation and respective possible patterns in shifting cultivation landscapes on a regional level. On the basis of a recent approximation of the extent of shifting cultivation landscapes for two time periods and disaggregated village level census data, this paper characterizes these landscapes in terms of key socioeconomic parameters for the whole of northern Laos. Results showed that over 550,000 people live in shifting cultivation regions. The poverty rate of this population of 46.5 % is considerably higher than the national rural rate. Most shifting cultivation landscapes are located in remote locations and a high share of the population comprises ethnic minorities, pointing to multi-dimensional marginality of these areas. We discuss whether economic growth and increased market accessibility are sufficient to lift these landscapes out of poverty.

The Interplay of Power and Trust in Platform Ecosystems of the Enterprise Application Software Industry

In recent years, the formerly oligopolistic Enterprise Application Software (EAS) industry began to disintegrate into focal inter-firm networks with one huge, powerful, and multi-national plat-form vendor as the center, surrounded by hundreds or even thousands of small, niche players that act as complementors. From a theoretical point of view, these platform ecosystems may be governed by two organizing principles - trust and power. However, it is neither from a practical nor from a theoretical perspective clear, how trust and power relate to each other, i.e. whether they act as complements or substitutes. This study tries to elaborate our understanding of the relationship of trust and power by exploring their interplay using multi-dimensional conceptual-izations of trust and power, and by investigating potential dynamics in this interplay over the course of a partnership. Based on an exploratory multiple-case study of seven dyadic partner-ships between four platform vendors, and seven complementors, we find six different patterns of how trust and power interact over time. These patterns bear important implications for the suc-cessful management of partnerships between platform vendors and complementors, and clarify the theoretical debate surrounding the relationship of trust and power.