Cooperation, interaction and learning in local production systems: Evidence in Brazilian firms

In a local production system (LPS), besides external economies, the interaction, cooperation, and learning are indicated by the literature as complementary ways of enhancing the LPS's competitiveness and gains. In Brazil, the greater part of LPSs, mostly composed by small enterprises, displays incipient relationships and low levels of interaction and cooperation among their actors. The size of the participating enterprises itself for specificities that engender organizational constraints, which, in turn, can have a considerable impact on their relationships and learning dynamics. For that reason, it is the purpose of this article to present an analysis of interaction, cooperation, and learning relationships among several types of actors pertaining to an LPS in the farming equipment and machinery sector, bearing in mind the specificities of small enterprises. To this end, the fieldwork carried out in this study aimed at: (i) investigating external and internal knowledge sources conducive to learning and (ii) identifying and analyzing motivating and inhibiting factors related to specificities of small enterprises in order to bring the LPS members closer together and increase their cooperation and interaction. Empirical evidence shows that internal aspects of the enterprises, related to management and infrastructure, can have a strong bearing on their joint actions, interaction and learning processes.

Influence of the technological innovation degree on knowledge creation: Evidence from a Brazilian firm

The aim of this paper is to analyze the process of knowledge creation when developing high technology products in projects having various innovation degrees. The main contribution to the literature is the systematization of an approach to analyze knowledge creation during the product innovation process. Three innovation projects developed by a company specialized in industrial automation systems were investigated using case studies. The knowledge creation processes, which took place in these three projects, were analyzed comparatively. As a distinctive result of this paper, the main features of the knowledge creation processes influenced by a degree of technological innovation are identified.

The BRAzilian Seismographic Integrated Systems (BRASIS): infrastructure and data management

In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of Sao Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation.

Restricted-Range Fishes and the Conservation of Brazilian Freshwaters

Background: Freshwaters are the most threatened ecosystems on earth. Although recent assessments provide data on global priority regions for freshwater conservation, local scale priorities remain unknown. Refining the scale of global biodiversity assessments (both at terrestrial and freshwater realms) and translating these into conservation priorities on the ground remains a major challenge to biodiversity science, and depends directly on species occurrence data of high taxonomic and geographic resolution. Brazil harbors the richest freshwater ichthyofauna in the world, but knowledge on endemic areas and conservation in Brazilian rivers is still scarce. Methodology/Principal Findings: Using data on environmental threats and revised species distribution data we detect and delineate 540 small watershed areas harboring 819 restricted-range fishes in Brazil. Many of these areas are already highly threatened, as 159 (29%) watersheds have lost more than 70% of their original vegetation cover, and only 141 (26%) show significant overlap with formally protected areas or indigenous lands. We detected 220 (40%) critical watersheds overlapping hydroelectric dams or showing both poor formal protection and widespread habitat loss; these sites harbor 344 endemic fish species that may face extinction if no conservation action is in place in the near future. Conclusions/Significance: We provide the first analysis of site-scale conservation priorities in the richest freshwater ecosystems of the globe. Our results corroborate the hypothesis that freshwater biodiversity has been neglected in former conservation assessments. The study provides a simple and straightforward method for detecting freshwater priority areas based on endemism and threat, and represents a starting point for integrating freshwater and terrestrial conservation in representative and biogeographically consistent site-scale conservation strategies, that may be scaled-up following naturally linked drainage systems. Proper management (e. g. forestry code enforcement, landscape planning) and conservation (e. g. formal protection) of the 540 watersheds detected herein will be decisive in avoiding species extinction in the richest aquatic ecosystems on the planet.

Expert system for the assessment of power transformer insulation condition based on type-2 fuzzy logic systems

An efficient expert system for the power transformer condition assessment is presented in this paper. Through the application of Duval`s triangle and the method of the gas ratios a first assessment of the transformer condition is obtained in the form of a dissolved gas analysis (DGA) diagnosis according IEC 60599. As a second step, a knowledge mining procedure is performed, by conducting surveys whose results are fed into a first Type-2 Fuzzy Logic System (T2-FLS), in order to initially evaluate the condition of the equipment taking only the results of dissolved gas analysis into account. The output of this first T2-FLS is used as the input of a second T2-FLS, which additionally weighs up the condition of the paper-oil system. The output of this last T2-FLS is given in terms of words easily understandable by the maintenance personnel. The proposed assessing methodology has been validated for several cases of transformers in service. (C) 2010 Elsevier Ltd. All rights reserved.

On the Filtering Problem for Continuous-Time Markov Jump Linear Systems with no Observation of the Markov Chain

We consider in this paper the optimal stationary dynamic linear filtering problem for continuous-time linear systems subject to Markovian jumps in the parameters (LSMJP) and additive noise (Wiener process). It is assumed that only an output of the system is available and therefore the values of the jump parameter are not accessible. It is a well known fact that in this setting the optimal nonlinear filter is infinite dimensional, which makes the linear filtering a natural numerically, treatable choice. The goal is to design a dynamic linear filter such that the closed loop system is mean square stable and minimizes the stationary expected value of the mean square estimation error. It is shown that an explicit analytical solution to this optimal filtering problem is obtained from the stationary solution associated to a certain Riccati equation. It is also shown that the problem can be formulated using a linear matrix inequalities (LMI) approach, which can be extended to consider convex polytopic uncertainties on the parameters of the possible modes of operation of the system and on the transition rate matrix of the Markov process. As far as the authors are aware of this is the first time that this stationary filtering problem (exact and robust versions) for LSMJP with no knowledge of the Markov jump parameters is considered in the literature. Finally, we illustrate the results with an example.

Comparison of oxygen mass transfer coefficient in simple and extractive fermentation systems

Aeration and agitation are important variables to ensure effective oxygen transfer rate during aerobic bioprocesses: therefore, the knowledge of the volumetric mass transfer coefficient (k(L)a) is required. In view of selecting the optimum oxygen requirements for extractive fermentation in aqueous two-phase system (ATPS), the k(L)a values in a typical ATPS medium were compared in this work with those in distilled water and in a simple fermentation medium. in the absence of biomass. Aeration and agitation were selected as the independent variables using a 2(2) full factorial design. Both variables showed statistically significant effects on k(L)a, and the highest values of this parameter in both media for simple fermentation (241 s(-1)) and extractive fermentation with ATPS (70.3 s(-1)) were observed at the highest levels of aeration (5 vvm) and agitation (1200 rpm). The k(L)a values were then used to establish mathematical correlations of this response as a function of the process variables. The exponents of the power number (N(3)D(2)) and superficial gas velocity (V(s)) determined in distilled water (alpha = 0.39 and beta = 0.47, respectively) were in reasonable agreement with the ones reported in the literature for several aqueous systems and close to those determined for a simple fermentation medium (alpha=0.38 and beta=0.41). On the other hand, as expected by the increased viscosity in the presence of polyethylene glycol, their values were remarkably higher in a typical medium for extractive fermentation (alpha=0.50 and beta=1.0). A reasonable agreement was found between the experimental data of k(L)a for the three selected systems and the values predicted by the theoretical models, under a wide range of operational conditions. (C) 2009 Elsevier B.V. All rights reserved.

A Study of the Corporative Portals as a Tool of Explicit Knowledge Externalization in Universities

The corporative portals, enabled by Information Technology and Communication tools, provide the integration of heterogeneous data proceeding from internal information systems, which are available for access and sharing of the interested community. They can be considered an important instrument of explicit knowledge evaluation in the. organization, once they allow faster and,safer, information exchanges, enabling a healthful collaborative environment. In the specific case of major Brazilian universities, the corporate portals assume a basic aspect; therefore they offer an enormous variety and amount of information and knowledge, due to the multiplicity of their activities This. study aims to point out important aspects of the explicit knowledge expressed by the searched universities; by the analysis, of the content offered in their corporative portals` This is an exploratory study made through, direct observation of the existing contents in the corporative portals of two public universities as. Well as three private ones. A. comparative analysis of the existing contents in these portals was carried through;. it can be useful to evaluate its use as factor of optimization of the generated explicit knowledge in the university. As results, the existence of important differences, could be verified in the composition and in the content of the corporative portals of the public universities compared to the private institutions. The main differences are about the kind of services and the destination-of the,information that have as focus different public-target. It-could also be concluded that the searched private universities, focus, on the processes related to the attendance of the students, the support for the courses as well as the spreading of information to the public interested in joining the institution; whereas the anal public universities prioritize more specific information, directed to,the dissemination-of the research, developed internally or with institutional objectives.

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.