Mixed methodology to analyze the relationship between maturity of environmental management and the adoption of green supply chain management in Brazil

The aim of this research is to verify the relationship between the maturity levels of environmental management and the adoption of green supply chain management (GSCM) practices by electro-electronic companies in Brazil. In this work a two-phase research was conducted, with one quantitative and the other qualitative. The quantitative phase aimed to test whether a relationship between the maturity levels of environmental management and GSCM exists, while the qualitative phase tried to detail the characteristics of this relationship. The quantitative phase was conducted through a survey with 100 Brazilian electro-electronic companies and the collected data were processed using Structural Equation Modeling. For the qualitative phase, a multiple case study was conducted with three companies located in Brazil. The results indicate that: (1) The main hypothesis was confirmed and considered statistically valid, indicating that, indeed, the maturity level of environmental management influences the adoption of GSCM practices; (2) a coevolution tends to occur between the environmental maturity and the GSCM practices; that is, the more developed is the company's environmental management, more complex GSCM practices are adopted; and (3) the GSCM internal practices tend to present a greater relative adoption than the external practices; these external practices of GSCM tend to be adopted when the company is inserted in a higher environmental stage and/or operates under a scenario of stronger normative environmental pressure. By the way, this is the first research mixing survey and case studies on GSCM in Brazil. (C) 2014 Elsevier B.V. All rights reserved.

Bias na Representação de Assunto: Uma Discussão de Oposições Binárias nos Functional Requirements for Subject Authority Data (FRSAD)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Os efeitos do Game Design no processo de criação de jogos digitais utilizados no ensino de Química e Ciências: o que devemos considerar?

Pós-graduação em Educação para a Ciência - FC

Jornalismo da Multidão: estudo sobre as formas de financiamento coletivo da Agência Pública

Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

A methodology and a tool to design of mixed-signal technology

This paper presents a tool box developed to read files describing a SIMULINK® model and translates it into a structural VHDL-AMS description. In translation process, all files and directory structures to simulate the translated model on SystemVision™ environment is generate. The tool box named MS2SV was tested by three models of commercially available digital-to-analogue converters. All models use the R2R ladder network to conversion, but the functionality of these three components is different. The methodology of conversion of the model is presents together with sort theory about R-2R ladder network. In the evaluation of the translated models, we used a sine waveform input signal and the waveform generated by D/A conversion process was compared by FFT analysis. The results show the viability of this type of approach. This work considers some of challenges set by the electronic industry for the further development of simulation methodologies and tools in the field of mixed-signal technology. © 2007 IEEE.

Bayesian longitudinal data analysis with mixed models and thick-tailed distributions using MCMC

Linear mixed effects models are frequently used to analyse longitudinal data, due to their flexibility in modelling the covariance structure between and within observations. Further, it is easy to deal with unbalanced data, either with respect to the number of observations per subject or per time period, and with varying time intervals between observations. In most applications of mixed models to biological sciences, a normal distribution is assumed both for the random effects and for the residuals. This, however, makes inferences vulnerable to the presence of outliers. Here, linear mixed models employing thick-tailed distributions for robust inferences in longitudinal data analysis are described. Specific distributions discussed include the Student-t, the slash and the contaminated normal. A Bayesian framework is adopted, and the Gibbs sampler and the Metropolis-Hastings algorithms are used to carry out the posterior analyses. An example with data on orthodontic distance growth in children is discussed to illustrate the methodology. Analyses based on either the Student-t distribution or on the usual Gaussian assumption are contrasted. The thick-tailed distributions provide an appealing robust alternative to the Gaussian process for modelling distributions of the random effects and of residuals in linear mixed models, and the MCMC implementation allows the computations to be performed in a flexible manner.

Selection of alfalfa cultivars adapted for tropical environments with repeated measures using PROC MIXED of SAS (R) System

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Methodology analysis of a computational tool used in electronic circuit design

This paper considers the importance of using a top-down methodology and suitable CAD tools in the development of electronic circuits. The paper presents an evaluation of the methodology used in a computational tool created to support the synthesis of digital to analog converter models by translating between different tools used in a wide variety of applications. This tool is named MS 2SV and works directly with the following two commercial tools: MATLAB/Simulink and SystemVision. Model translation of an electronic circuit is achieved by translating a mixed-signal block diagram developed in Simulink into a lower level of abstraction in VHDL-AMS and the simulation project support structure in SystemVision. The method validation was performed by analyzing the power spectral of the signal obtained by the discrete Fourier transform of a digital to analog converter simulation model. © 2011 IEEE.

A mixed-integer LP model for the reconfiguration of radial electric distribution systems considering distributed generation

The problem of reconfiguration of distribution systems considering the presence of distributed generation is modeled as a mixed-integer linear programming (MILP) problem in this paper. The demands of the electric distribution system are modeled through linear approximations in terms of real and imaginary parts of the voltage, taking into account typical operating conditions of the electric distribution system. The use of an MILP formulation has the following benefits: (a) a robust mathematical model that is equivalent to the mixed-integer non-linear programming model; (b) an efficient computational behavior with exiting MILP solvers; and (c) guarantees convergence to optimality using classical optimization techniques. Results from one test system and two real systems show the excellent performance of the proposed methodology compared with conventional methods. © 2012 Published by Elsevier B.V. All rights reserved.