Efficient group communication for large-scale parallel clustering

Global communication requirements and load imbalance of some parallel data mining algorithms are the major obstacles to exploit the computational power of large-scale systems. This work investigates how non-uniform data distributions can be exploited to remove the global communication requirement and to reduce the communication cost in iterative parallel data mining algorithms. In particular, the analysis focuses on one of the most influential and popular data mining methods, the k-means algorithm for cluster analysis. The straightforward parallel formulation of the k-means algorithm requires a global reduction operation at each iteration step, which hinders its scalability. This work studies a different parallel formulation of the algorithm where the requirement of global communication can be relaxed while still providing the exact solution of the centralised k-means algorithm. The proposed approach exploits a non-uniform data distribution which can be either found in real world distributed applications or can be induced by means of multi-dimensional binary search trees. The approach can also be extended to accommodate an approximation error which allows a further reduction of the communication costs.

Are we there yet? Exploring empowerment at the microscale in the South African wine industry

Empowerment is a standard but ambiguous element of development rhetoric and so, through the socially complex and contested terrain of South Africa, this paper explores its potential to contribute to inclusive development. Investigating micro-level engagements with the national strategy of Broad-Based Black Economic Empowerment (B-BBEE) in the South African wine industry highlights the limitations, but also potential, of this single domain approach. However, latent paternalism, entrenched interests and a ‘dislocated blackness’ maintain a complex racial politics that shapes both power relations and the opportunities for transformation within the industry. Nonetheless, while B-BBEE may not, in reality, be broad-based its manifestations are contributing to challenging racist structures and normalising changing attitudes. This paper concludes that, to be transformative, empowerment needs to be re-embedded within South Africa as a multi-scalar, multi-dimensional dialogue and, despite the continuation of structural constraints, positions the local as a critical scale at which to initiate broader social change.

Tensor regression based on linked multiway parameter analysis

Classical regression methods take vectors as covariates and estimate the corresponding vectors of regression parameters. When addressing regression problems on covariates of more complex form such as multi-dimensional arrays (i.e. tensors), traditional computational models can be severely compromised by ultrahigh dimensionality as well as complex structure. By exploiting the special structure of tensor covariates, the tensor regression model provides a promising solution to reduce the model’s dimensionality to a manageable level, thus leading to efficient estimation. Most of the existing tensor-based methods independently estimate each individual regression problem based on tensor decomposition which allows the simultaneous projections of an input tensor to more than one direction along each mode. As a matter of fact, multi-dimensional data are collected under the same or very similar conditions, so that data share some common latent components but can also have their own independent parameters for each regression task. Therefore, it is beneficial to analyse regression parameters among all the regressions in a linked way. In this paper, we propose a tensor regression model based on Tucker Decomposition, which identifies not only the common components of parameters across all the regression tasks, but also independent factors contributing to each particular regression task simultaneously. Under this paradigm, the number of independent parameters along each mode is constrained by a sparsity-preserving regulariser. Linked multiway parameter analysis and sparsity modeling further reduce the total number of parameters, with lower memory cost than their tensor-based counterparts. The effectiveness of the new method is demonstrated on real data sets.

Large deviations of Rouse polymer chain: first passage problem

The purpose of this paper is to investigate several analytical methods of solving first passage (FP) problem for the Rouse model, a simplest model of a polymer chain. We show that this problem has to be treated as a multi-dimensional Kramers' problem, which presents rich and unexpected behavior. We first perform direct and forward-flux sampling (FFS) simulations, and measure the mean first-passage time $\tau(z)$ for the free end to reach a certain distance $z$ away from the origin. The results show that the mean FP time is getting faster if the Rouse chain is represented by more beads. Two scaling regimes of $\tau(z)$ are observed, with transition between them varying as a function of chain length. We use these simulations results to test two theoretical approaches. One is a well known asymptotic theory valid in the limit of zero temperature. We show that this limit corresponds to fully extended chain when each chain segment is stretched, which is not particularly realistic. A new theory based on the well known Freidlin-Wentzell theory is proposed, where dynamics is projected onto the minimal action path. The new theory predicts both scaling regimes correctly, but fails to get the correct numerical prefactor in the first regime. Combining our theory with the FFS simulations lead us to a simple analytical expression valid for all extensions and chain lengths. One of the applications of polymer FP problem occurs in the context of branched polymer rheology. In this paper, we consider the arm-retraction mechanism in the tube model, which maps exactly on the model we have solved. The results are compared to the Milner-McLeish theory without constraint release, which is found to overestimate FP time by a factor of 10 or more.

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.

Density-Profile Processes Describing Biological Signaling Networks: Almost Sure Convergence to Deterministic Trajectories

We introduce jump processes in R(k), called density-profile processes, to model biological signaling networks. Our modeling setup describes the macroscopic evolution of a finite-size spin-flip model with k types of spins with arbitrary number of internal states interacting through a non-reversible stochastic dynamics. We are mostly interested on the multi-dimensional empirical-magnetization vector in the thermodynamic limit, and prove that, within arbitrary finite time-intervals, its path converges almost surely to a deterministic trajectory determined by a first-order (non-linear) differential equation with explicit bounds on the distance between the stochastic and deterministic trajectories. As parameters of the spin-flip dynamics change, the associated dynamical system may go through bifurcations, associated to phase transitions in the statistical mechanical setting. We present a simple example of spin-flip stochastic model, associated to a synthetic biology model known as repressilator, which leads to a dynamical system with Hopf and pitchfork bifurcations. Depending on the parameter values, the magnetization random path can either converge to a unique stable fixed point, converge to one of a pair of stable fixed points, or asymptotically evolve close to a deterministic orbit in Rk. We also discuss a simple signaling pathway related to cancer research, called p53 module.

Aplicação de filtros de Gabor no processo de classificação de imagens digitais com base em atributos de textura

No processo de classificação de uma imagem digital, o atributo textura pode ser uma fonte importante de informações. Embora o processo de caracterização da textura em uma imagem seja mais difícil, se comparado ao processo de caracterização de atributos espectrais, sabe-se que o emprego daquele atributo pode aumentar significativamente a exatidão na classificação da imagem. O objetivo deste trabalho de pesquisa consiste em desenvolver e testar um método de classificação supervisionado em imagens digitais com base em atributos de textura. O método proposto implementa um processo de filtragem baseado nos filtros de Gabor. Inicialmente, é gerado um conjunto de filtros de Gabor adequados às freqüências espaciais associadas às diferentes classes presentes na imagem a ser classificada. Em cada caso, os parâmetros utilizados por cada filtro são estimados a partir das amostras disponíveis, empregando-se a transformada de Fourier. Cada filtro gera, então, uma imagem filtrada que quantifica a freqüência espacial definida no filtro. Este processo resulta em um certo número de imagens filtradas as quais são denominadas de "bandas texturais". Desta forma, o problema que era originalmente unidimensional passa a ser multi-dimensional, em que cada pixel passa a ser definido por um vetor cuja dimensionalidade é idêntica ao número de filtros utilizados. A imagem em várias "bandas texturais" pode ser classificada utilizando-se um método de classificação supervisionada. No presente trabalho foi utilizada a Máxima Verossimilhança Gaussiana. A metodologia proposta é então testada, utilizandose imagens sintéticas e real. Os resultados obtidos são apresentados e analisados.

A colaboração com fornecedores e clientes, e sua influência no desempenho da firma : uma análise empírica na indústria brasileira de embalagens

O crescimento da importância de relacionamentos inter-organizacionais na pesquisa e prática nos negócios tem sido observado por diversos autores, que têm colocado a colaboração no centro das análises sobre como companhias competem (ANDERSON; NARUS, 1990; HILL, 1990; MORGAN; HUNT, 1994; WILSON, 1995; DONALDSON; O’TOOLE, 2000). Perspectivas teóricas em Marketing, em Economia, em Estratégia e em Gestão de Operações, revelam que a colaboração tem impacto positivo no desempenho das firmas. No entanto, apesar da popularidade e benefícios dos relacionamentos inter-organizacionais, nem todas as evidências são positivas (COMBS; KETCHEN, 1999; HILL, 1990; MADHOK; TALLMAN, 1998), e existem dificuldades na medição e na análise da relação entre estes construtos. Visando contribuir com resultados conclusivos através de medidas validadas sobre a relação entre colaboração e desempenho, esta pesquisa estabeleceu como foco a indústria de embalagens, tendo como unidade de análise os fabricantes de embalagens do Brasil. Ambos construtos, colaboração e desempenho, foram tratados como multi-dimensionais, com a colaboração sendo analisada em duas interfaces da empresa focal: com os clientes e com os fornecedores. A colaboração analisada em quatro dimensões (flexibilidade, troca de informações, resolução conjunta de problemas e restrição ao uso de poder) versus o desempenho, com quatro dimensões de desempenho operacional (flexibilidade, qualidade, tempo e custo) e o desempenho financeiro com duas dimensões (crescimento e lucratividade). Os resultados e testes das hipóteses evidenciaram que existe relação entre colaboração com fornecedores e clientes e desempenho, mas a natureza desta relação não é simples e universal. Quando a colaboração e desempenho são tratados com sua natureza multidimensional, os efeitos da colaboração se manifestam com intensidade diferente, nas diferentes dimensões de desempenho. Este estudo tem implicações gerenciais evidentes ao apontar para quais dimensões da colaboração em cada interface do fabricante de embalagem têm impacto sobre cada desempenho, permitindo focar nos aspectos mais relevantes do relacionamento para obter melhor retorno.

Estrutura de propriedade e valor das empresas no Brasil

Este estudo examina a relação entre estrutura de propriedade e valor das empresas, tratando a estrutura de propriedade de forma endógena e multi-dimensional. Para isso, o modelo desenvolvido por Demsetz e Villalonga (2001) é aplicado em uma amostra de 192 empresas listadas na Bovespa entre 2006 e 2008. Os resultados indicam que o valor da firma pode afetar a concentração da estrutura de propriedade, mas não vice-versa. As evidências obtidas também indicam que, no Brasil, a variável da estrutura de propriedade que influencia, de forma negativa, o valor das empresas é o potencial de expropriação dos acionistas minoritários pelos acionistas controladores, representada pelo desvio entre a concentração do direito de controle e a concentração do direito de fluxo de caixa.

The dimensions of trust in interorganizational relationships: how buyer and supplier perspectives differ?

Apesar da pesquisa em confiança interorganizacional e sua relação com performance ter sido conduzida sob as perspectivas da Teoria de Custos de Transação, Teoria das Trocas Sociais e Canais de Marketing, três importantes lacunas na literatura requerem investigação. Primeiro, está em andamento um debate conceitual sobre a multi-dimensionalidade da confiança, e como ela deve ser operacionalizada e medida, e que se divide em três correntes de pensamento - um construto multidimensional definido por dimensões não dominantes, um construto baseado em duas dimensões dominantes (afetiva e calculativa), ou um construto unidimensional. Segundo, existe ambiguidade em como as dimensões da confiança são definidas, levando a artefatos de equivalência nas escalas e resultados contraditórios. Terceiro, as diferentes percepções que compradores e fornecedores podem ter em cada dimensão da confiança e seu impacto na performance logística ainda não estão claros. Esta pesquisa empírica examina a confiança nas relações entre compradores e fornecedores no setor de logística no Brasil, através de duas amostras e estudos independentes: um examina a percepção dos compradores e o outro examina a dos fornecedores. Em seguida, os dois estudos são comparados para determinar as diferentes perspectivas da confiança e as implicações na performance logística. A análise multivariada mostrou que a confiança parece estar presente nas relações interorganizacionais, e é a percepção do comprador que possui maior relação com a performance logística. Ao mesmo tempo, compradores percebem fornecedores de forma mais negativa nas dimensões mensuráveis (competência e performance), enquanto não foram encontradas diferenças nos aspectos sociais (honestidade e benevolência), o que pode ser resultado do ambiente e cultura pesquisados. As análises mostraram que, apesar da confiança poder ser definida como um construto multidimensional, ela deve ser operacionalizada como um construto unidimensional direcionado pela competência e credibilidade. Este estudo contribui para a prática sugerindo formas de aumentar a confiança interorganizacional para aumento da performance.

Era um sonho desde criança : a representação social da docência para os professores do município de Queimadas-PB

The objective of this work was to access and understand the teaching social representation (MOSCOVICI, 2005) for the teachers of the children education and fundamental education at Queimadas city, Paraíba. We assume that one representation that allows the teacher to name its profession and to act on it, is a derivative of regularities that are expressed by means of a habitus (BOURDIEU, 1983a), generative matrix of perception and action. This teaching habitus is originated from the experiences and the trajectories of social and professional life of the group. Therefore, from some variables, we tried to access the profile of the group of teachers studied and to get closer of their life style to understand their profession choice and the teaching social representation for this group. In this research, it was used four data sources: a) the questionnaires of characterization; b) the questionnaires of practices and meanings; c) the experience reports and; d) the interviews in depth. The analysis of the data collected was done by means of the simple statistics (frequency), the intersection of variables through cross tables and, the thematic analysis of the contents. The results show that there is a lightly homogeneous group in terms of its social origin and its life style, moreover, they conduct to an overlap between this origin/style and the professional choice. On the other hand, the teacher representation is multi-dimensional such that, all dimensions intercept and articulate with each other to provide a concise teacher representation. They are four dimensions: love and care, help and donation, teaching and learning and, sacrifice and hope. The elements of the teacher representation are substantiated in the schemes of perception and appreciation of the group, in the regularities and life experiences in the context of religion, family, gender and profession. In these regularities we find the elements that comprise the teaching habitus which drives perception and action, representation and daily practice of these teachers. The teaching social representation is still perceived as a threshold for the professional identity of the group of teachers considered. We also observed that there are signs of changes in the practices used by these professionals since they graduate from the course of pedagogy. However, it is not possible to say that these changes are isolated or they lead to a transformation in the teaching habitus or the teaching social representation

Culturally-sensitive complaints of depressions and anxieties in women

Background: Current classifications of Mental Disorders are centered on Westernized concepts and constructs. Cross-cultural sensitivity emphasizes culturally-appropriate translations of symptoms and questions, assuming that concepts and constructs are applicable.Methods: Groups and individual psychiatrists from various cultures from Asia, Latin America, North Africa and Eastern Europe prepared descriptions of main symptoms and complaints of treatment-seeking women in their cultures, which are interpreted by clinicians as a manifestation of a clinically-relevant dysphoric disorder. They also transliterated the expressions of DSM IV criteria of main dysphoric disorders in their cultures.Results: In many non-western cultures the symptoms and constructs that are interpreted and treated as dysphoric disorders are mostly somatic and are different from the Western-centered DSM or ICD systems. In many cases the DSM and ICD criteria of depression and anxieties are not even acknowledged by patients.Limitations: the descriptive approach reported here is a preliminary step which involved local but Westernized clinicians-investigators following a biomedical thinking. It should be followed by a more systematic-comprehensive surveys in each culture.Conclusions: Westernized concepts and constructs of mental order and disorders are not necessarily universally applicable. Culturallysensitive phenomena, treatments and treatment responses may be diversified. Attempts at their cross-cultural harmonization should take into consideration complex interactional multi-dimensional processes. (c) 2006 Elsevier B.V. All rights reserved.

A genômica funcional no âmbito da produção animal: estado da arte e perspectivas

Os últimos vinte anos caracterizaram-se pela proliferação de tecnologias que tornaram possível decifrar o genoma das espécies, localizar e identificar particularidades na sua seqüência, elucidar as suas funções dentro dos sistemas biológicos e, sobretudo, começar a entender os mecanismos que controlam as interações entre os genótipos e os estímulos ambientais, que são responsáveis pela diversidade fenotípica. Estes estudos sobre as bases moleculares da variabilidade fenotípica abriram uma nova abordagem científica, caracterizada pela multiplicidade das questões envolvidas, que resultou no surgimento de novas áreas de pesquisa, cujos conhecimentos estão sendo aplicados em diversos campos da biologia, inclusive na zootecnia. Tendo em vista o grande impacto que tais conhecimentos estão tendo sobre a compreensão dos fenômenos biológicos, parece ser oportuno fazer uma avaliação das potencialidades de aplicação das abordagens de Genômica Funcional em pesquisas de nutrição e alimentação de ruminantes. Nesse contexto, este artigo está focado na descrição das principais ferramentas genômicas disponíveis e na discussão sobre a viabilidade de se utilizar as informações por elas geradas em benefício da produção animal.

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