A survey of evolutionary algorithms for decision-tree induction

This paper presents a survey of evolutionary algorithms that are designed for decision-tree induction. In this context, most of the paper focuses on approaches that evolve decision trees as an alternate heuristics to the traditional top-down divide-and-conquer approach. Additionally, we present some alternative methods that make use of evolutionary algorithms to improve particular components of decision-tree classifiers. The paper's original contributions are the following. First, it provides an up-to-date overview that is fully focused on evolutionary algorithms and decision trees and does not concentrate on any specific evolutionary approach. Second, it provides a taxonomy, which addresses works that evolve decision trees and works that design decision-tree components by the use of evolutionary algorithms. Finally, a number of references are provided that describe applications of evolutionary algorithms for decision-tree induction in different domains. At the end of this paper, we address some important issues and open questions that can be the subject of future research.

THE DEVELOPMENT AND EVALUATION OF SOFTWARE TO VERIFY DIAGNOSTIC ACCURACY

This article describes the development and evaluation of software that verifies the accuracy of diagnoses made by nursing students. The software was based on a model that uses fuzzy logic concepts, including PERL, the MySQL database for Internet accessibility, and the NANDA-I 2007-2008 classification system. The software was evaluated in terms of its technical quality and usability through specific instruments. The activity proposed in the software involves four stages in which students establish the relationship values between nursing diagnoses, defining characteristics/risk factors and clinical cases. The relationship values determined by students are compared to those of specialists, generating performance scores for the students. In the evaluation, the software demonstrated satisfactory outcomes regarding the technical quality and, according to the students, helped in their learning and may become an educational tool to teach the process of nursing diagnosis.

Trial of Experimental Toothpastes Regarding Quality for Cleaning Dentures

The aim of this study was to evaluate the efficacy of experimental toothpastes for removing denture biofilm by means of a randomized crossover trial. Thirty volunteers brushed their dentures using a brush and four pastes: (1) Corega refreshing mint (control), (2)0.2% chloramine T, (3)1.0% chloramine T, and (4) 0.01% fluorosurfactant. Each paste was used for 7 days, and participants were randomized to use them according to one of four sequences. Biofilm was disclosed (neutral red) after each period, photographed, and quantified by means of a software program. All experimental toothpastes were similar to the control in terms of posttreatment biofilm coverage. Int J Prosthodont 2012;25:157-159.

Assessment of physiological potential of cucumber seeds using the software Seedling Vigor Imaging System® (SVIS®)

The software Seed Vigor Imaging System (SVIS®), has been successfully used to evaluate seed physiological potential by automated analyses of scanned seedlings. In this research, the efficiency of this system was compared to other tests accepted for assessing cucumber (Cucumis sativus L.) seed vigor of distinct seed lots of Supremo and Safira cultivars. Seeds were subjected to germination, traditional and saturated salt accelerated aging, seedling emergence, seedling length and SVIS analyses (determination of vigor indices and seedling growth uniformity, lengths of primary root, hypocotyl and whole seedlings). It was also determined whether the definition of seedling growth/uniformity ratios affects the sensitivity of the SVIS®. Results showed that analyses SVIS have provided consistent identification of seed lots performance, and have produced information comparable to those from recommended seed vigor tests, thus demonstrating a suitable sensitivity for a rapid and objective evaluation of physiological potential of cucumber seeds. Analyses of four-days-old cucumber seedlings using the SVIS® are more accurate and growth/uniformity does not affect the precision of results.