A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.

Decision analysis for the genotype designation in low-template-DNA profiles

What genotype should the scientist specify for conducting a database search to try to find the source of a low-template-DNA (lt-DNA) trace? When the scientist answers this question, he or she makes a decision. Here, we approach this decision problem from a normative point of view by defining a decision-theoretic framework for answering this question for one locus. This framework combines the probability distribution describing the uncertainty over the trace's donor's possible genotypes with a loss function describing the scientist's preferences concerning false exclusions and false inclusions that may result from the database search. According to this approach, the scientist should choose the genotype designation that minimizes the expected loss. To illustrate the results produced by this approach, we apply it to two hypothetical cases: (1) the case of observing one peak for allele xi on a single electropherogram, and (2) the case of observing one peak for allele xi on one replicate, and a pair of peaks for alleles xi and xj, i ≠ j, on a second replicate. Given that the probabilities of allele drop-out are defined as functions of the observed peak heights, the threshold values marking the turning points when the scientist should switch from one designation to another are derived in terms of the observed peak heights. For each case, sensitivity analyses show the impact of the model's parameters on these threshold values. The results support the conclusion that the procedure should not focus on a single threshold value for making this decision for all alleles, all loci and in all laboratories.

A template for externalisation-internalisation decisions in virtual enterprises

Recognising the importance of alliance decision making in a virtual enterprise (VE), this paper proposes an analysis template to facilitate this process. The existing transaction-cost and resource-based theories in the literature are first reviewed, showing some deficiencies in both type of theories, and the potential of the resource based explanations. The paper then goes on to propose a resource-based analysis template, integrating both the motives of using certain business forms and the factors why different forms help achieve different objectives, Resource-combination effectiveness, management complexity and flexibility are identified as the three factors providing fundamental explanations of an organization's alliance making decision process. The template provides a comprehensive and generic approach for analysing alliance decisions.

'Artificial Immune Systems: A new Decision Making Paradigm for Operational Research'

Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annealing. More recently, a novel computational intelligence technique inspired by immunology has emerged, called Artificial Immune Systems (AIS). This immune system inspired technique has already been useful in solving some computational problems. In this keynote, we will very briefly describe the immune system metaphors that are relevant to AIS. We will then give some illustrative real-world problems suitable for AIS use and show a step-by-step algorithm walkthrough. A comparison of AIS to other well-known algorithms and areas for future work will round this keynote off. It should be noted that as AIS is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from the examples given here

A New Paradigm for Heuristic Decision Making, Invited Keynote Talk

Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annealing. More recently, a novel computational intelligence technique inspired by immunology has emerged, called Artificial Immune Systems (AIS). This immune system inspired technique has already been useful in solving some computational problems. In this keynote, we will very briefly describe the immune system metaphors that are relevant to AIS. We will then give some illustrative real-world problems suitable for AIS use and show a step-by-step algorithm walkthrough. A comparison of AIS to other well-known algorithms and areas for future work will round this keynote off. It should be noted that as AIS is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from the examples given here.

The Putative Leishmania Telomerase Rna (leishter) Undergoes Trans-splicing And Contains A Conserved Template Sequence.

Telomerase RNAs (TERs) are highly divergent between species, varying in size and sequence composition. Here, we identify a candidate for the telomerase RNA component of Leishmania genus, which includes species that cause leishmaniasis, a neglected tropical disease. Merging a thorough computational screening combined with RNA-seq evidence, we mapped a non-coding RNA gene localized in a syntenic locus on chromosome 25 of five Leishmania species that shares partial synteny with both Trypanosoma brucei TER locus and a putative TER candidate-containing locus of Crithidia fasciculata. Using target-driven molecular biology approaches, we detected a ∼2,100 nt transcript (LeishTER) that contains a 5' spliced leader (SL) cap, a putative 3' polyA tail and a predicted C/D box snoRNA domain. LeishTER is expressed at similar levels in the logarithmic and stationary growth phases of promastigote forms. A 5'SL capped LeishTER co-immunoprecipitated and co-localized with the telomerase protein component (TERT) in a cell cycle-dependent manner. Prediction of its secondary structure strongly suggests the existence of a bona fide single-stranded template sequence and a conserved C[U/C]GUCA motif-containing helix II, representing the template boundary element. This study paves the way for further investigations on the biogenesis of parasite TERT ribonucleoproteins (RNPs) and its role in parasite telomere biology.

Nanostructured thin films obtained by electrodeposition over a colloidal crystal template: applications in electrochemical devices

Colloidal particles have been used to template the electrosynthesis of several materials, such as semiconductors, metals and alloys. The method allows good control over the thickness of the resulting material by choosing the appropriate charge applied to the system, and it is able to produce high density deposited materials without shrinkage. These materials are a true model of the template structure and, due to the high surface areas obtained, are very promising for use in electrochemical applications. In the present work, the assembly of monodisperse polystyrene templates was conduced over gold, platinum and glassy carbon substrates in order to show the electrodeposition of an oxide, a conducting polymer and a hybrid inorganic-organic material with applications in the supercapacitor and sensor fields. The performances of the resulting nanostructured films have been compared with the analogue bulk material and the results achieved are depicted in this paper.

Template-based fluoroethylenepropylene piezoelectrets with tubular channels for transducer applications

We describe the concept, the fabrication, and the most relevant properties of a piezoelectric-polymer system: Two fluoroethylenepropylene (FEP) films with good electret properties are laminated around a specifically designed and prepared polytetrafluoroethylene (PTFE) template at 300 degrees C. After removing the PTFE template, a two-layer FEP film with open tubular channels is obtained. For electric charging, the two-layer FEP system is subjected to a high electric field. The resulting dielectric barrier discharges inside the tubular channels yield a ferroelectret with high piezoelectricity. d(33) coefficients of up to 160 pC/N have already been achieved on the ferroelectret films. After charging at suitable elevated temperatures, the piezoelectricity is stable at temperatures of at least 130 degrees C. Advantages of the transducer films include ease of fabrication at laboratory or industrial scales, a wide range of possible geometrical and processing parameters, straightforward control of the uniformity of the polymer system, flexibility, and versatility of the soft ferroelectrets, and a large potential for device applications e.g., in the areas of biomedicine, communications, production engineering, sensor systems, environmental monitoring, etc.

Decision theory applied to image quality control in radiology

Background: The present work aims at the application of the decision theory to radiological image quality control ( QC) in diagnostic routine. The main problem addressed in the framework of decision theory is to accept or reject a film lot of a radiology service. The probability of each decision of a determined set of variables was obtained from the selected films. Methods: Based on a radiology service routine a decision probability function was determined for each considered group of combination characteristics. These characteristics were related to the film quality control. These parameters were also framed in a set of 8 possibilities, resulting in 256 possible decision rules. In order to determine a general utility application function to access the decision risk, we have used a simple unique parameter called r. The payoffs chosen were: diagnostic's result (correct/incorrect), cost (high/low), and patient satisfaction (yes/no) resulting in eight possible combinations. Results: Depending on the value of r, more or less risk will occur related to the decision-making. The utility function was evaluated in order to determine the probability of a decision. The decision was made with patients or administrators' opinions from a radiology service center. Conclusion: The model is a formal quantitative approach to make a decision related to the medical imaging quality, providing an instrument to discriminate what is really necessary to accept or reject a film or a film lot. The method presented herein can help to access the risk level of an incorrect radiological diagnosis decision.

DECISION TREE CLASSIFIERS FOR STAR/GALAXY SEPARATION

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 <= r <= 21 (85.2%) and r >= 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 <= r <= 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (> 80%) while simultaneously achieving low contamination (similar to 2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 <= r <= 21.

On the template synthesis of nanostructured inorganic/organic hybrid films

Prussian Blue has been introduced as a mediator to achieve stable, sensitive, reproducible, and interference-free biosensors. However, Na(+), Li(+), H(+), and all group II cations are capable to block the activity of Prussian Blue and, because Na(+) can be found in most human fluids, Prussian Blue analogs have already been developed to overcome this problem. These analogs, such as copper hexacyanoferrate, have also been introduced in a conducting polypyrrole matrix to create hybrid materials (copper hexacyanoferrate/polypyrrole, CuHCNFe/Ppy) with improved mechanical and electrochemical characteristics. Nowadays, the challenges in amperometric enzymatic biosensors consist of improving the enzyme immobilization and in making the chemical signal transduction more efficient. The incorporation of nanostructured materials in biosensors can optimize both steps and a nanostructured hybrid CuHCNFe/Ppy mediator has been developed using a template of colloidal polystyrene particles. The nanostructured material has achieved sensitivities 7.6 times higher than the bulk film during H(2)O(2) detection and it has also presented better results in other analytical parameters such as time response and detection limit. Besides, the nanostructured mediator was successfully applied at glucose biosensing in electrolytes containing Prussian Blue blocking cations. (C) 2008 The Electrochemical Society.

Information from managing information systems as a fundamental element to support decision-making in hospitals

This article deals with the activity of defining information of hospital systems as fundamental for choosing the type of information systems to be used and also the organizational level to be supported. The use of hospital managing information systems improves the user`s decision -making process by allowing control report generation and following up the procedures made in the hospital as well.

Maternal decision on obtaining prenatal care: a study in Brazil

Objective: to address the social aspects of pregnancy and the views of pregnant women regarding prenatal assistance in Brazil. Design: this qualitative study was focused on describing the Social Representations of prenatal care held by pregnant women. The discourse of the collective subject (DCS) framework was used to analyse the data collected, within the theoretical background of social representations, as proposed and developed by Serge Moscovici. Participants and setting: 21 pregnant women who were users of the publicly funded Brazilian unified health-care system and resided in the area served by its family health programme in a low- to middle-income neighbourhood on the outskirts of Campo Grande, the capital of the state of Mato Grosso do Sul, in southwestern Brazil. Data were collected by conducting in-depth, face-to-face interviews from January to October 2006. Findings: all participants were married. Formal education of the participants was less than five years in four cases, between five and eight years in six cases, and greater than 11 years in 10 cases. Nine participants had informal jobs and earned up to US$ 200 per month, four paricipants had administrative jobs and earned over US$ 500 per month, and eight participants did not work. No specific racial/ethnic background predominated. Lack of adherence to prenatal care allowed for the identification of two DCS themes: `organisation of prenatal care services` and `lifestyle features`. Key conclusions: the respondents were found to have negative feelings about pregnancy which manifest as many fears, including the fear of harming their children`s health, of being punished during labour, and of being reprimanded by health-care professionals for overlooking their prenatal care, in addition to the insecurity felt towards the infant and self. Implications for practice: the findings reveal that communication between pregnant women and healthcare professionals has been ineffective and that prenatal care has not been effective for the group interviewed-features that are likely to be found among other low- to middle-income groups living elsewhere in Brazil. (C) 2009 Elsevier Ltd. All rights reserved.

Financial distress, financial constraint and investment decision: Evidence from Brazil

This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques. (C) 2010 Elsevier B.V. All rights reserved.