A technique to classify and compare agile methods

This manuscript describes a technique to perform comparisons on agile methods, based on a set of relevant features and attributes. This set includes attributes related to four SWEBOK Knowledge Areas (KAs) and to the Agile Manifesto principles. With this set of attributes, by analyzing the practices proposed by each method, we are able to assess (1) the coverage degree for the considered KAs and (2) the agility degree

Classification and comparison of agile methods

This manuscript describes a technique and its tool support to perform comparisons on agile methods, based on a set of relevant features and attributes. This set includes attributes related to four IEEE’s Software Engineering Body of Knowledge (SWEBOK) Knowledge Areas (KAs) and to the agile principles defined in the Agile Manifesto. With this set of attributes, by analysing the practices proposed by each method, we are able to assess (1) the coverage degree for the considered KAs and (2) the agility degree. In this manuscript, the application of the technique is exemplified in comparing eXtreme Programming (XP) and Scrum

Advocating the broad use of the decision tree method in education

Predictive studies have been widely undertaken in the field of education to provide strategic information about the extensive set of processes related to teaching and learning, as well as about what variables predict certain educational outcomes, such as academic achievement or dropout. As in any other area, there is a set of standard techniques that is usually used in predictive studies in the field education. Even though the Decision Tree Method is a well-known and standard approach in Data Mining and Machine Learning, and is broadly used in data science since the 1980's, this method is not part of the mainstream techniques used in predictive studies in the field of education. In this paper, we support a broad use of the Decision Tree Method in education. Instead of presenting formal algorithms or mathematical axioms to present the Decision Tree Method, we strictly present the method in practical terms, focusing on the rationale of the method, on how to interpret its results, and also, on the reasons why it should be broadly applied. We first show the modus operandi of the Decision Tree Method through a didactic example; afterwards, we apply the method in a classification task, in order to analyze specific educational data.(undefined)info:eu-repo/semantics/publishedVersio

Evolution signatures in genome network properties

Genomes maybe organized as networks where protein-protein association plays the role of network links. The resulting networks are far from being random and their topological properties are a consequence of the underlying mechanisms for genome evolution. Considering data on protein-protein association networks from STRING database, we present experimental evidence that degree distribution is not scale free, presenting an increased probability for high degree nodes. We also show that the degree distribution approaches a scale invariant state as the number of genes in the network increases, although real genomes still present finite size effects. Based on the experimental evidence unveiled by these data analyses, we propose a simulation model for genome evolution, where genes in a network are either acquired de novo using a preferential attachment rule, or duplicated, with a duplication probability that linearly grows with gene degree and decreases with its clustering coefficient. The results show that topological distributions are better described than in previous genome evolution models. This model correctly predicts that, in order to produce protein-protein association networks with number of links and number of nodes in the observed range, it is necessary 90% of gene duplication and 10% of de novo gene acquisition. If this scenario is true, it implies a universal mechanism for genome evolution

Milage learn+: Perspective of teachers

The development of technology has contributed to enormous changes in society, in interactions and communications. These changes are also reflected in education. MILAGE LEARN+ is an application for mobile devices that has been developed at the University of Algarve with the support of the ERAMUS+ project with partners from Portugal, Spain, Germany and Cyprus, enabling students to access educational content in and outside the classroom. The App works as a support tool for students which provides them the opportunity to solve tasks autonomously. In order to stimulate and support the implementation of the various activities proposed, MILAGE+ LEARN+ App interface incorporates gamification features and segmenting different levels of activities. The app provides detailed videos with the solution of problems and self-assessment scheme and peer review. A questionnaire was addressed to all teachers trained to use the MILAGE LEARN+ platform. This questionnaire includes thirty-one questions, of which four are open-response and twenty-seven are closed-response. In this paper we present how teachers, use this learning platform in their classroom, how often, with what intention, identify application weaknesses and identify new features to be developed

Banzeiro, rebojo

Resenha de: BRUM, Eliane. Banzeiro Òkòtó: uma viagem à Amazônia Centro do Mundo. São Paulo Companhia das Letras, 2021. 448

Banzeiro, rebojo

Review of:BRUM, Eliane. Banzeiro Òkòtó: uma viagem à Amazônia Centro do Mundo. São Paulo Companhia das Letras, 2021. 448pResenha de:BRUM, Eliane. Banzeiro Òkòtó: uma viagem à Amazônia Centro do Mundo. São Paulo Companhia das Letras, 2021. 448

Modeling and control of a nuclear power plant using AI techiniques

In pressurized water reactor (PWR) nuclear power plants (NPPs) pressure control in the primary loops is fundamental for keeping the reactor in a safety condition and improve the generation process efficiency. The main component responsible for this task is the pressurizer. The pressurizer pressure control system (PPCS) utilizes heaters and spray valves to maintain the pressure within an operating band during steady state conditions, and limits the pressure changes during transient conditions. Relief and safety valves provide overpressure protection for the reactor coolant system (RCS) to ensure system integrity. Various protective reactor trips are generated if the system parameters exceed safe bounds. Historically, a proportional-integral-derivative (PID) controller is used in PWRs to keep the pressure in the set point, during those operation conditions. The purpose of this study is to develop fuzzy controllers for the PWR pressurizer modeled by an artificial neural network (ANN) and compare their performance with conventional ones. Data from a 2785 MWth Westinghouse 3-loop PWR simulator was used to test both the conventional and the fuzzy controllers. The simulation results show that the fuzzy controllers have better performance compared with conventional ones

Fundamentos y aplicabilidad del Modelado Exploratorio de Ecuaciones Estructurales en contextos psicoeducativos

In last few years, the use of confi rmatory factor analysis (CFA) has become dominant in structural validation of psychological tests. However, the requirement of latent variables only loading on specific target items introduces some constraints on the solutions found, namely a factor solution that links some items only in one specific dimension. The most recent use of exploratory structural equation modeling (ESEM), which allows items to be predominantly related to a factor, with non-zero loadings on other factors, has been identifi ed as the one that best respects the proper functioning of the assessed psychological attributes. Method: In this study we compared the two approaches to structural validity using the answers of a sample of 2,478 fi rst-year higher education students to a multidimensional questionnaire of academic expectations. Results: The results show clear gains in information collected when combining CFA and ESEM. Conclusions: In conclusion, some implications are highlighted for research and practice of psychological assessment.En los últimos años, el uso del Análisis Factorial Confi rmatorio (AFC) se ha convertido en un tipo de análisis predominante en la validación de tests psicológicos. Sin embargo, el requisito de que las variables latentes únicamente carguen sobre algunas de las respectivas dimensiones de destino conlleva algunas restricciones a las soluciones obtenidas; es decir, una solución factorial que requiere la vinculación de ciertos ítems solo en una dimensión. El uso más reciente del Modelo Exploratorio de Ecuaciones Estructurales (ESEM), que permite que los ítems puedan ser predominantemente relacionados con un factor y con cargas diferentes a cero en otros factores, ha sido identifi cado como aquel que mejor respeta el buen funcionamiento de los atributos psicológicos evaluados. Método: en este estudio, con las respuestas de una muestra de 2.478 estudiantes de primer año de la enseñanza superior a un cuestionario multidimensional de expectativas académicas, hemos comparado los dos enfoques de validez estructural. Resultados: los resultados muestran claros benefi cios en la información recopilada al combinar el AFC y el ESEM. Conclusiones: como conclusión se señalan algunas implicaciones para la investigación y la práctica de evaluación psicológica.info:eu-repo/semantics/publishedVersio