Supplier's selection model based on an empirical study

The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, there were identified five broad selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. After the identification criteria, a survey was elaborated and companies were contacted in order to understand which factors have more weight in their decisions to choose the partners. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Value Analysis. The goal of the paper it's to supply a selection reference model that can represent an orientation/pattern for a decision making on the suppliers/partners selection process

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.

Analysis of the domain of applicability of an algorithm for a resources system selection problem for Distributed/Agile/Virtual Enterprises integration

The process of resources systems selection takes an important part in Distributed/Agile/Virtual Enterprises (D/A/V Es) integration. However, the resources systems selection is still a difficult matter to solve in a D/A/VE, as it is pointed out in this paper. Globally, we can say that the selection problem has been equated from different aspects, originating different kinds of models/algorithms to solve it. In order to assist the development of a web prototype tool (broker tool), intelligent and flexible, that integrates all the selection model activities and tools, and with the capacity to adequate to each D/A/V E project or instance (this is the major goal of our final project), we intend in this paper to show: a formulation of a kind of resources selection problem and the limitations of the algorithms proposed to solve it. We formulate a particular case of the problem as an integer programming, which is solved using simplex and branch and bound algorithms, and identify their performance limitations (in terms of processing time) based on simulation results. These limitations depend on the number of processing tasks and on the number of pre-selected resources per processing tasks, defining the domain of applicability of the algorithms for the problem studied. The limitations detected open the necessity of the application of other kind of algorithms (approximate solution algorithms) outside the domain of applicability founded for the algorithms simulated. However, for a broker tool it is very important the knowledge of algorithms limitations, in order to, based on problem features, develop and select the most suitable algorithm that guarantees a good performance.

Cervical cancer screening coverage in a high-incidence region

OBJECTIVE To analyze the coverage of a cervical cancer screening program in a city with a high incidence of the disease in addition to the factors associated with non-adherence to the current preventive program.METHODS A cross-sectional study based on household surveys was conducted. The sample was composed of women between 25 and 59 years of age of the city of Boa Vista, RR, Northern Brazil who were covered by the cervical cancer screening program. The cluster sampling method was used. The dependent variable was participation in a women’s health program, defined as undergoing at least one Pap smear in the 36 months prior to the interview; the explanatory variables were extracted from individual data. A generalized linear model was used.RESULTS 603 women were analyzed, with an mean age of 38.2 years (SD = 10.2). Five hundred and seventeen women underwent the screening test, and the prevalence of adherence in the last three years was up to 85.7% (95%CI 82.5;88.5). A high per capita household income and recent medical consultation were associated with the lower rate of not being tested in multivariate analysis. Disease ignorance, causes, and prevention methods were correlated with chances of non-adherence to the screening system; 20.0% of the women were reported to have undergone opportunistic and non-routine screening.CONCLUSIONS The informed level of coverage is high, exceeding the level recommended for the control of cervical cancer. The preventive program appears to be opportunistic in nature, particularly for the most vulnerable women (with low income and little information on the disease). Studies on the diagnostic quality of cervicovaginal cytology and therapeutic schedules for positive cases are necessary for understanding the barriers to the control of cervical cancer.

Determinants of the use of health care services: multilevel analysis in the Metropolitan Region of Sao Paulo

OBJECTIVE To evaluate the individual and contextual determinants of the use of health care services in the metropolitan region of Sao Paulo.METHODS Data from the Sao Paulo Megacity study – the Brazilian version of the World Mental Health Survey multicenter study – were used. A total of 3,588 adults living in 69 neighborhoods in the metropolitan region of Sao Paulo, SP, Southeastern Brazil, including 38 municipalities and 31 neighboring districts, were selected using multistratified sampling of the non-institutionalized population. Multilevel Bayesian logistic models were adjusted to identify the individual and contextual determinants of the use of health care services in the past 12 months and presence of a regular physician for routine care.RESULTS The contextual characteristics of the place of residence (income inequality, violence, and median income) showed no significant correlation (p > 0.05) with the use of health care services or with the presence of a regular physician for routine care. The only exception was the negative correlation between living in areas with high income inequality and presence of a regular physician (OR: 0.77; 95%CI 0.60;0.99) after controlling for individual characteristics. The study revealed a strong and consistent correlation between individual characteristics (mainly education and possession of health insurance), use of health care services, and presence of a regular physician. Presence of chronic and mental illnesses was strongly correlated with the use of health care services in the past year (regardless of the individual characteristics) but not with the presence of a regular physician.CONCLUSIONS Individual characteristics including higher education and possession of health insurance were important determinants of the use of health care services in the metropolitan area of Sao Paulo. A better understanding of these determinants is essential for the development of public policies that promote equitable use of health care services.

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion. © 2014 Springer-Verlag Berlin Heidelberg.

Spectral and weak polynomial completeness for the porduct of nonsingular matrices

Let F be a field with at least four elements. In this paper, we identify all the pairs (A, B) of n x n nonsingular matrices over F , satisfying the following property: for every monic polynomial f(x) = xn + an-1xn-1 + … +a1x + aο over F, with a root in F and aο = (-1)n det(AB), there are nonsingular matrices X, Y ϵ Fnxn such that X A X-1 Y BY-1 has characteristic polynomial f (x). © 2014 © 2014 Taylor & Francis.

Multi-region routing

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Access to childbirth care by adolescents and young people in the Northeastern region of Brazil

ABSTRACT OBJECTIVE To identify the factors that interfere with the access of adolescents and young people to childbirth care for in the Northeast region of Brazil. METHODS Cross-sectional study with 3,014 adolescents and young people admitted to the selected maternity wards to give birth in the Northeast region of Brazil. The sample design was probabilistic, in two stages: the first corresponded to the health establishments and the second to women who had recently given birth and their babies. The data was collected by means of interviews and consulting the hospital records, from pre-tested electronic form. Descriptive statistics were used for the univariate analysis, Pearson’s Chi-square test for the bivariate analysis and multiple logistic regressions for the multivariate analysis. Sociodemographic variables, obstetrical history, and birth care were analyzed. RESULTS Half of the adolescents and young people interviewed had not been given guidance on the location that they should go to when in labor, and among those who had, 23.5% did not give birth in the indicated health service. Furthermore, one third (33.3%) had to travel in search of assisted birth, and the majority (66.7%) of the postpartum women came to maternity by their own means. In the bivariate analysis, the variables marital status, paid work, health insurance, number of previous pregnancies, parity, city location, and type of health establishment showed a significant association (p < 0.20) with inadequate access to childbirth care. The multivariate analysis showed that married adolescents and young people (p < 0.015), with no health insurance (p < 0.002) and from the countryside (p < 0.001) were more likely to have inadequate access to childbirth care. CONCLUSIONS Adolescents and young women, married, without health insurance, and from the countryside are more likely to have inadequate access to birth care. The articulation between outpatient care and birth care can improve this access and, consequently, minimize the maternal and fetal risks that arise from a lack of systematic hospitalization planning.

An unsupervised approach to feature discretization and selection

Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.

Efficient feature selection filters for high-dimensional data

Feature selection is a central problem in machine learning and pattern recognition. On large datasets (in terms of dimension and/or number of instances), using search-based or wrapper techniques can be cornputationally prohibitive. Moreover, many filter methods based on relevance/redundancy assessment also take a prohibitively long time on high-dimensional. datasets. In this paper, we propose efficient unsupervised and supervised feature selection/ranking filters for high-dimensional datasets. These methods use low-complexity relevance and redundancy criteria, applicable to supervised, semi-supervised, and unsupervised learning, being able to act as pre-processors for computationally intensive methods to focus their attention on smaller subsets of promising features. The experimental results, with up to 10(5) features, show the time efficiency of our methods, with lower generalization error than state-of-the-art techniques, while being dramatically simpler and faster.

Reshaping higher education systems in the MENA region: the contribution of remote and virtual labs

Learning is not only happening in school or university; it is also an important aspect of the daily life that allows students to remain in their biological and physical environment helping to reshape it, by applying what they have learnt. Today, the higher education sector is a part of important strategies used by countries in order to foster their development. Despite its geographical location, i.e. its closeness to Europe and Asia, the MENA (Middle East and North Africa) region still needs an integrated strategy for the advancement, reform, and update of its higher educational landscape. Although some solutions have been experimented in the region in the field of higher education, they have not been able to raise the quality of education to the level comparable that observed in developed countries. In other words, many MENA higher education systems are facing problems, for which solution ought to be sought. We analyse the situation of higher education systems in the MENA countries and the factors that affect the delay in achieving the level of education existing in other world regions, e.g. Europe, especially in the higher education sector. During the discussion, the impact of new technology-enhanced tools, such as remote laboratories, in the process of development and consolidation of MENA universities, is particularly stressed.

Inquérito sorológico da prevalência de infecção chagásica no Brasil, 1975/1980

A nationwide seroepidemiologic survey of human T. cruzi infection was carried out in Brazil from 1975 to 1980 as a joint programme of the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and the Superintendência de Campanhas (SUGAM), Ministry of Health, of Brazil. Due to the marked heterogeneity of urban populations as result of wide migratory movements in the country and since triatomine transmission of the disease occurs mostly in rural areas, the survey was limited to rural populations. The survey was based on a large cluster sampling of complete households, from randomly selected localities comprised of 10 to 500 houses, or up to 200 houses in the Amazon region. Random selection of localities and houses was permitted by a detailed mapping of every locality in the country, as performed and continuously adjusted, by SUCAM. In the selected houses duplicate samples on filter paper were collected from every resistent 1 year or older. Samples were tested in one of 14 laboratories scattered in the country by the indirect anti-IgG immunofluorescence test, with reagents produced and standardized by a central laboratory located at the Instituto de Medicina Tropical de São Paulo. A continuous quality control was performed at this laboratory, which tested duplicates of 10% to 15% of all samples examined by the collaborating laboratories. Data regarding number of sera collected, patients'age, sex, place of residence, place of birth and test result were computerized at the Department of Preventive Medicine, Medical School, University of São Paulo, São Paulo, Brazil. Serologic prevalence indices were estimated for each Municipality and mapped according to States and Territories in Brazil. Since data were already available for the State of São Paulo and the Federal District, these unities were not included in the survey.

Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Testing native speakers of German and Portuguese on the understanding of topological operators-line-region relations in gvSIG

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies