U-curve: A branch-and-bound optimization algorithm for U-shaped cost functions on Boolean lattices applied to the feature selection problem

This paper presents the formulation of a combinatorial optimization problem with the following characteristics: (i) the search space is the power set of a finite set structured as a Boolean lattice; (ii) the cost function forms a U-shaped curve when applied to any lattice chain. This formulation applies for feature selection in the context of pattern recognition. The known approaches for this problem are branch-and-bound algorithms and heuristics that explore partially the search space. Branch-and-bound algorithms are equivalent to the full search, while heuristics are not. This paper presents a branch-and-bound algorithm that differs from the others known by exploring the lattice structure and the U-shaped chain curves of the search space. The main contribution of this paper is the architecture of this algorithm that is based on the representation and exploration of the search space by new lattice properties proven here. Several experiments, with well known public data, indicate the superiority of the proposed method to the sequential floating forward selection (SFFS), which is a popular heuristic that gives good results in very short computational time. In all experiments, the proposed method got better or equal results in similar or even smaller computational time. (C) 2009 Elsevier Ltd. All rights reserved.

Nonstationary feature extraction techniques for automatic classification of impact acoustic signals

Condition monitoring of wooden railway sleepers applications are generallycarried out by visual inspection and if necessary some impact acoustic examination iscarried out intuitively by skilled personnel. In this work, a pattern recognition solutionhas been proposed to automate the process for the achievement of robust results. Thestudy presents a comparison of several pattern recognition techniques together withvarious nonstationary feature extraction techniques for classification of impactacoustic emissions. Pattern classifiers such as multilayer perceptron, learning cectorquantization and gaussian mixture models, are combined with nonstationary featureextraction techniques such as Short Time Fourier Transform, Continuous WaveletTransform, Discrete Wavelet Transform and Wigner-Ville Distribution. Due to thepresence of several different feature extraction and classification technqies, datafusion has been investigated. Data fusion in the current case has mainly beeninvestigated on two levels, feature level and classifier level respectively. Fusion at thefeature level demonstrated best results with an overall accuracy of 82% whencompared to the human operator.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Identification of cause of impairment in spiral drawings, using non-stationary feature extraction approach

Parkinson’s disease is a clinical syndrome manifesting with slowness and instability. As it is a progressive disease with varying symptoms, repeated assessments are necessary to determine the outcome of treatment changes in the patient. In the recent past, a computer-based method was developed to rate impairment in spiral drawings. The downside of this method is that it cannot separate the bradykinetic and dyskinetic spiral drawings. This work intends to construct the computer method which can overcome this weakness by using the Hilbert-Huang Transform (HHT) of tangential velocity. The work is done under supervised learning, so a target class is used which is acquired from a neurologist using a web interface. After reducing the dimension of HHT features by using PCA, classification is performed. C4.5 classifier is used to perform the classification. Results of the classification are close to random guessing which shows that the computer method is unsuccessful in assessing the cause of drawing impairment in spirals when evaluated against human ratings. One promising reason is that there is no difference between the two classes of spiral drawings. Displaying patients self ratings along with the spirals in the web application is another possible reason for this, as the neurologist may have relied too much on this in his own ratings.

Informatização da operação e da gestão de uma unidade de saúde de alta complexidade do sistema único de saúde (SUS): estudo de caso do instituto de medicina integral Prof. Fernando Figueira (Imip) sob o enfoque do isomorfismo institucional

O trabalho buscou identificar e avaliar a escolha do Imip à luz da teoria neoinstitucional, mediante os mecanismos isomórficos que caracterizam o campo das organizações de saúde. Trata-se de um estudo de caso, tendo o Imip como objeto de análise, voltado especificamente para dois modelos de informatização da operação e da gestão, a fim de verificar qual o mais adequado para as especificidades da instituição, incluindo o aspecto financeiro, custo/benefício. O primeiro modelo se refere a um sistema próprio de informatização; o segundo a um modelo de sistema de gestão já existente, comercializado por empresa especializada nesta tecnologia. A metodologia abrangeu pesquisas bibliográficas, documentais e de campo. O referencial teórico foi a teoria neoinstitucional e o trabalho de campo constou de uma pesquisa incluindo observação simples, visando compor variáveis dos dois modelos avaliados, e coleta de dados realizada por meio da aplicação de dois questionários: um questionário aberto, com os dirigentes do Imip, e um questionário misto, com cem colaboradores, utilizadores do sistema, escolhidos aleatoriamente, por sorteio. Entre os achados se identificou claras referências ao isomorfismo, principalmente o mimético, nas percepções dos indivíduos respondentes. Ao final da pesquisa, foi possível concluir que a contratação de um sistema de gestão hospitalar, já existente no mercado, concebido e comercializado por empresa de tecnologia especializada no segmento da saúde, justificou-se como a melhor escolha para a organização, pois, as semelhanças existentes entre os processos do Instituto e aqueles contidos no sistema eram muito mais relevantes que suas particularidades. Outro fator relevante levou em consideração os elevados custos para uma única instituição desenvolver e manter sozinha um sistema atualizado segundo as exigências normativas e técnicas necessárias às organizações de saúde e os padrões de qualidade da informação estabelecidos pelo SUS.

A Common-feature approach for testing present-value restrictions with financial data

It is well known that cointegration between the level of two variables (labeled Yt and yt in this paper) is a necessary condition to assess the empirical validity of a present-value model (PV and PVM, respectively, hereafter) linking them. The work on cointegration has been so prevalent that it is often overlooked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. The basis of this result is the use of rational expectations in forecasting future values of variables in the PVM. If this condition fails, the present-value equation will not be valid, since it will contain an additional term capturing the (non-zero) conditional expected value of future error terms. Our article has a few novel contributions, but two stand out. First, in testing for PVMs, we advise to split the restrictions implied by PV relationships into orthogonality conditions (or reduced rank restrictions) before additional tests on the value of parameters. We show that PV relationships entail a weak-form common feature relationship as in Hecq, Palm, and Urbain (2006) and in Athanasopoulos, Guillén, Issler and Vahid (2011) and also a polynomial serial-correlation common feature relationship as in Cubadda and Hecq (2001), which represent restrictions on dynamic models which allow several tests for the existence of PV relationships to be used. Because these relationships occur mostly with nancial data, we propose tests based on generalized method of moment (GMM) estimates, where it is straightforward to propose robust tests in the presence of heteroskedasticity. We also propose a robust Wald test developed to investigate the presence of reduced rank models. Their performance is evaluated in a Monte-Carlo exercise. Second, in the context of asset pricing, we propose applying a permanent-transitory (PT) decomposition based on Beveridge and Nelson (1981), which focus on extracting the long-run component of asset prices, a key concept in modern nancial theory as discussed in Alvarez and Jermann (2005), Hansen and Scheinkman (2009), and Nieuwerburgh, Lustig, Verdelhan (2010). Here again we can exploit the results developed in the common cycle literature to easily extract permament and transitory components under both long and also short-run restrictions. The techniques discussed herein are applied to long span annual data on long- and short-term interest rates and on price and dividend for the U.S. economy. In both applications we do not reject the existence of a common cyclical feature vector linking these two series. Extracting the long-run component shows the usefulness of our approach and highlights the presence of asset-pricing bubbles.

O direito à informação jornalística: garantias constitucionais ao direito de ser informado no sistema brasileiro.

The freedom of social communication referred to those freedoms exercised under of the media. The journalism is professional activity responsible for factual information, real, pluralistic and of the public interest, directed diffusely to social orientation. The right of the information, characterized as diffuse right or of fruition by uncertain and numerous holders, is subdivided in the right of the inform, inform yourself and right to be informed. The journalists, as occupants of a enlarged spectrum concerning of right of the inform, have responsibility for the information they disseminate, devoir that puts on the basis of the constitutional right to be informed. This duty is divided with journalistic companies, when them realized. In the research, examined the existence of constitutional guarantees the right to be informed. To answer the question, realized research to support bibliographical and documentary. The guaranty is a empirical preoccupation coated with legality, since lends itself effect concretize a right. Traced so a panel of guarantees of institutional imprint, substantive and procedural. Treating of the institutional guarantees the right to information, it would refer to true institutions (as the free press) and may begin subjective rights. In the case of substantial guarantees, we would have access to information, the confidentiality of the fonts and the incensurable feature of journalistic information. A guarantee peculiar would be constitution of bodies responsible for monitoring the quality of the vehicles of communication. Trace it also a panel strict of procedural safeguards, such as public civil action, the security s warrant, and the rights of petition and answer.

A novel algorithm for feature selection using Harmony Search and its application for non-technical losses detection

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

CENSUS HISTOGRAMS: A SIMPLE FEATURE EXTRACTION and MATCHING APPROACH FOR FACE RECOGNITION

Most face recognition approaches require a prior training where a given distribution of faces is assumed to further predict the identity of test faces. Such an approach may experience difficulty in identifying faces belonging to distributions different from the one provided during the training. A face recognition technique that performs well regardless of training is, therefore, interesting to consider as a basis of more sophisticated methods. In this work, the Census Transform is applied to describe the faces. Based on a scanning window which extracts local histograms of Census Features, we present a method that directly matches face samples. With this simple technique, 97.2% of the faces in the FERET fa/fb test were correctly recognized. Despite being an easy test set, we have found no other approaches in literature regarding straight comparisons of faces with such a performance. Also, a window for further improvement is presented. Among other techniques, we demonstrate how the use of SVMs over the Census Histogram representation can increase the recognition performance.

New Insights on Nontechnical Losses Characterization Through Evolutionary-Based Feature Selection

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

Adaptive filter feature identification for structural health monitoring in an aeronautical panel

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Feature selection through gravitational search algorithm

In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are conducted in order to asses the robustness of the proposed technique against Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and a Particle Swarm Optimization (PSO)-based algorithm for feature selection.

Observing documentary reading by verbal protocol

Verifies the applicability to research on indexers' reading strategies of the process observing technique known as Verbal Protocol or Thinking Aloud. This interpretative-qualitative data collecting technique allows the observation of different kinds of process during the progress of different kinds of tasks. Presents a theoretical investigation into reading and into formal methodological procedures to observe reading processes. Describes details of the methodological procedures adopted in five case studies with analysis of samples of data. The project adopted three kinds of parameters for data analysis: theoretical, normative, empirical (derived from observations made in the first case study). The results are compared, and important conclusions regarding documentary reading are drawn.