RFID adoption: framework and survey in large Brazilian companies

Purpose - The purpose of this paper is to provide a framework for radio frequency identification (RFID) technology adoption considering company size and five dimensions of analysis: RFID applications, expected benefits business drivers or motivations barriers and inhibitors, and organizational factors. Design/methodology/approach - A framework for RFID adoption derived from literature and the practical experience on the subject is developed. This framework provides a conceptual basis for analyzing a survey conducted with 114 companies in Brazil. Findings - Many companies have been developing RFID initiatives in order to identify potential applications and map benefits associated with their implementation. The survey highlights the importance business drivers in the RFID implementation stage, and that companies implement RFID focusing on a few specific applications. However, there is a weak association between expected benefits and business challenges with the current level of RFID technology adoption in Brazil. Research limitations/implications - The paper is not exhaustive, since RFID adoption in Brazil is at early stages during the survey timeline. Originality/value - The main contribution of the paper is that it yields a framework for analyzing RFID technology adoption. The authors use this framework to analyze RFID adoption in Brazil, which proved to be a useful one for identifying key issues for technology adoption. The paper is useful to any researchers or practitioners who are focused on technology adoption, in particular, RFID technology.

Are supplier selection criteria going green? Case studies of companies in Brazil

Purpose - The purpose of this paper is to verify if Brazilian companies are adopting environmental requirements in the supplier selection process. Further, this paper intends to analyze whether there is a relation between the level of environmental management maturity and the inclusion of environmental criteria in the companies` selection of suppliers. Design/methodology/approach - A review of mainstream literature on environmental management, traditional criteria in the supplier selection process and the incorporation of environmental requirements in this context. The empirical study`s strategy is based on five Brazilian case studies with industrial companies. Face-to-face interviews and informal conversations are to be held, explanations made by e-mail with representatives from the purchasing, environmental management, logistics and other areas, and observation and the collection of company documents are also employed. Findings - Based on the cases, it is concluded that companies still use traditional criteria to select suppliers, such as quality and cost, and do not adopt environmental requirements in the supplier selection process in a uniform manner. Evidence found shows that the level of environmental management maturity influences the depth with which companies adopt environmental criteria when selecting suppliers. Thus, a company with more advanced environmental management adopts more formal procedures for selecting environmentally appropriate suppliers than others. Originality/value - This is the first known study to verify if Brazilian companies are adopting environmental requirements in the supplier selection process.

Barriers faced by MSEs: evidence from Mozambique

Purpose - The purpose of this research is to shed light on the main barriers faced by Mozambican micro and small enterprises (MSEs) and their implications in respect to the support policies available for these enterprises. Design/methodology/approach - A literature review was made on those barriers faced by the MSEs and on the policies and governmental instruments of assistance available for MSEs. Then, a two-step research was conducted. The first phase consisted of collecting data from 21 MSEs in Mozambique, mainly by means of interviews where the main barriers faced by those interviewed were identified and hence, this led to the second phase, which was interviewing governmental/support entities in order to know what they had done to minimize those barriers which had been identified by the entrepreneurs. Findings - The results show that financial and competitive barriers are the main barriers faced by the analyzed MSEs. These barriers vary according to the field of activity of the enterprises. Originality/value - This study serves to enrich the state of the art on the subject of smaller enterprises in Africa and will specially. help to fill the lack of academic research available about Mozambique.

A spectral clustering algorithm for manufacturing cell formation

A graph clustering algorithm constructs groups of closely related parts and machines separately. After they are matched for the least intercell moves, a refining process runs on the initial cell formation to decrease the number of intercell moves. A simple modification of this main approach can deal with some practical constraints, such as the popular constraint of bounding the maximum number of machines in a cell. Our approach makes a big improvement in the computational time. More importantly, improvement is seen in the number of intercell moves when the computational results were compared with best known solutions from the literature. (C) 2009 Elsevier Ltd. All rights reserved.

QUADRANT-SEARCHING: A NEW TECHNIQUE TO REDUCE THE SEARCH SPACE OF THE INVERSE PROBLEM OF EIT USING BEM TO THE DIRECT PROBLEM

The image reconstruction using the EIT (Electrical Impedance Tomography) technique is a nonlinear and ill-posed inverse problem which demands a powerful direct or iterative method. A typical approach for solving the problem is to minimize an error functional using an iterative method. In this case, an initial solution close enough to the global minimum is mandatory to ensure the convergence to the correct minimum in an appropriate time interval. The aim of this paper is to present a new, simple and low cost technique (quadrant-searching) to reduce the search space and consequently to obtain an initial solution of the inverse problem of EIT. This technique calculates the error functional for four different contrast distributions placing a large prospective inclusion in the four quadrants of the domain. Comparing the four values of the error functional it is possible to get conclusions about the internal electric contrast. For this purpose, initially we performed tests to assess the accuracy of the BEM (Boundary Element Method) when applied to the direct problem of the EIT and to verify the behavior of error functional surface in the search space. Finally, numerical tests have been performed to verify the new technique.

Use of the q-Gaussian mutation in evolutionary algorithms

This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.

Controllability of Volterra-Fredholm type systems in Banach spaces

We show the results in Chalishajar [Controllability of mixed Volterra-Fredholm-type integro-differential systems in Banach space, J. Franklin Inst. 344(1) (2007) 12-21] and Chang and Chalishajar [Controllability of mixed Volterra-Fredholm type integro-differential systems in Banach space, J. Franklin Inst., doi:10.1016/j. jfranklin.2008.02.002] are only valid for ordinary differential control systems. As a result the examples provided cannot be recovered as applications of the abstract results. (C) 2008 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

Decay chain differential equations: Solution through matrix algebra

A matricial method to solve the decay chain differential equations system is presented. The quantity of each nuclide in the chain at a time t may be evaluated by analytical expressions obtained in a simple way using recurrence relations. This method may be applied to problems of radioactive buildup and decay and can be easily implemented computationally. (C) 2009 Elsevier B.V. All rights reserved.