Action taken on CDCC resolutions and resolutions of ECLAC and other United Nations bodies with implications for CDCC: resolutions and decisions of ECLAC, ECOSOC and the UN General Assembly with implications for CDCC

Revisa las acciones tomadas en relacion con las resoluciones del CDCC y aquellas de la CEPAL, ECOSOC y Asamblea General, con implicancias para el CDCC.

Rank Aggregation for Pattern Classifier Selection in Remote Sensing Images

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A path- and label-cost propagation approach to speedup the training of the optimum-path forest classifier

In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of big data classification problems. The research on this area ranges from Graphics Processing Units-based implementations to mathematical optimizations, being the main drawback of the former approaches to be dependent on the graphic video card. Here, we propose an architecture-independent optimization approach for the optimum-path forest (OPF) classifier, that is designed using a theoretical formulation that relates the minimum spanning tree with the minimum spanning forest generated by the OPF over the training dataset. The experiments have shown that the approach proposed can be faster than the traditional one in five public datasets, being also as accurate as the original OPF. (C) 2014 Elsevier B. V. All rights reserved.

A brief look at the least-squares approach as a classifier applied to restricted-vocabulary speech recognition

In this letter, a speech recognition algorithm based on the least-squares method is presented. Particularly, the intention is to exemplify how such a traditional numerical technique can be applied to solve a signal processing problem that is usually treated by using more elaborated formulations.

Multicollinearity and financial constraint in investment decisions: a bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Ultrasonic sensor signals and optimum path forest classifier for the microstructural characterization of thermally-aged inconel 625 alloy

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Two and a Half Cheers for the Midwestern Bourgeoisie: Role of the Virtues in Tempering Business Decisions

A recent book (The Bourgeois Virtues: Ethics for an Age of Commerce, D. N. McCloskey), raises the matter of the role of the virtues in business and economic choice, arguing that capitalism can indeed, be virtuous or at least better than the alternative(s). This argument is especially timely in light of the apparent excesses on Wall Street and in some banking/financial institutions. Excessive greed and often the lack of business ethics contributed in substantive ways to the financial crisis and near economic meltdown we have been experiencing. As McCloskey, (2006, pp. 1-2) argues (in setting the stage for the complex argument made in this 616-page book!): “The book … is directed toward you who are suspicious of the phrase ‘bourgeois virtues,’ pretty sure that it is a contradiction in terms. And the book is directed, with less optimism about changing their minds, toward you who think the phrase is worse: a lie. ‘Bourgeois virtues’ is neither. The claim here is that modern capitalism does not need to be offset to be good. Capitalism can on the contrary be virtuous. In a fallen world bourgeois life is not perfect. But it’s better than any available alternative. American capitalism needs to be inspirited, moralized, completed. Two and a half cheers for the Midwestern bourgeoisie (middle-class, small business owners…. yet)… Many a businessman is an ethical shell or worse. Even the virtues of the bourgeoisie, … do not lead straight to heaven.”

Analyzing ACRE: Results for 2009 and Decisions for 2010

In 2009, agricultural producers participating in federal farm programs had to decide between staying in the existing Direct and Counter-Cyclical Program (DCP), and the new Average Crop Revenue Election Program (ACRE). If producers chose to keep the DCP, their farm income safety net is strictly tied to crop prices, with a combination of marketing loans, counter-cyclical payments and direct payments. If producers chose the new ACRE program, they changed their farm income safety net to a combination of price and revenue. The new ACRE component is based on revenue and replaces the counter-cyclical payment. The other parts of the safety net for ACRE participants remain tied to price, albeit at lower levels (direct payments reduced 20 percent, marketing loan rates reduced 30 percent).

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Decisions on Temporal Sampling Protocol Influence the Detection of Ecological Patterns

Within-site variability in species detectability is a problem common to many biodiversity assessments and can strongly bias the results. Such variability can be caused by many factors, including simple counting inaccuracies, which can be solved by increasing sample size, or by temporal changes in species behavior, meaning that the way the temporal sampling protocol is designed is also very important. Here we use the example of mist-netted tropical birds to determine how design decisions in the temporal sampling protocol can alter the data collected and how these changes might affect the detection of ecological patterns, such as the species-area relationship (SAR). Using data from almost 3400 birds captured from 21,000 net-hours at 31 sites in the Brazilian Atlantic Forest, we found that the magnitude of ecological trends remained fairly stable, but the probability of detecting statistically significant ecological patterns varied depending on sampling effort, time of day and season in which sampling was conducted. For example, more species were detected in the wet season, but the SAR was strongest in the dry season. We found that the temporal distribution of sampling effort was more important than its total amount, discovering that similar ecological results could have been obtained with one-third of the total effort, as long as each site had been equally sampled over 2 yr. We discuss that projects with the same sampling effort and spatial design, but with different temporal sampling protocol are likely to report different ecological patterns, which may ultimately lead to inappropriate conservation strategies.

Work activities as a resource for work organization design and for strategic decisions?

This paper proposes a discussion about the possibilities to link strategic decisions to working activities performed by workers. In that sense contributions from activities analysis could be considered in order to design and manage production.

Management practices and influences on IT architecture decisions: a case study in a telecom company

The study aims to analyze the IT architecture management practices associated with their degree of maturity and the influence of institutional and strategic factors on the decisions involved through a case study in a large telecom organization. The case study allowed us to identify practices that led the company to its current stage of maturity and identify practices that can lead the company to the next stage. The strategic influence was mentioned by most respondents and the institutional influence was present in decisions related to innovation and those dealing with a higher level of uncertainties.