Evolutionary algorithms for the modeling of bioreactors

This work aims to study the application of Genetic Algorithms in anaerobic digestion modeling, in particular when using dynamical models. Along the work, different types of bioreactors are shown, such as batch, semi-batch and continuous, as well as their mathematical modeling. The work intendeds to estimate the parameter values of two biological reaction model. For that, simulated results, where only one output variable, the produced biogas, is known, are fitted to the model results. For this reason, the problems associated with reverse optimization are studied, using some graphics that provide clues to the sensitivity and identifiability associated with the problem. Particular solutions obtained by the identifiability analysis using GENSSI and DAISY softwares are also presented. Finally, the optimization is performed using genetic algorithms. During this optimization the need to improve the convergence of genetic algorithms was felt. This need has led to the development of an adaptation of the genetic algorithms, which we called Neighbored Genetic Algorithms (NGA1 and NGA2). In order to understand if this new approach overcomes the Basic Genetic Algorithms (BGA) and achieves the proposed goals, a study of 100 full optimization runs for each situation was further developed. Results show that NGA1 and NGA2 are statistically better than BGA. However, because it was not possible to obtain consistent results, the Nealder-Mead method was used, where the initial guesses were the estimated results from GA; Algoritmos Evolucionários para a Modelação de Bioreactores Resumo: Neste trabalho procura-se estudar os algoritmos genéticos com aplicação na modelação da digestão anaeróbia e, em particular, quando se utilizam modelos dinâmicos. Ao longo do mesmo, são apresentados diferentes tipos de bioreactores, como os batch, semi-batch e contínuos, bem como a modelação matemática dos mesmos. Neste trabalho procurou-se estimar o valor dos parâmetros que constam num modelo de digestão anaeróbia para o ajustar a uma situação simulada onde apenas se conhece uma variável de output, o biogas produzido. São ainda estudados os problemas associados à optimização inversa com recurso a alguns gráficos que fornecem pistas sobre a sensibilidade e identifiacabilidade associadas ao problema da modelação da digestão anaeróbia. São ainda apresentadas soluções particulares de idenficabilidade obtidas através dos softwares GENSSI e DAISY. Finalmente é realizada a optimização do modelo com recurso aos algoritmos genéticos. No decorrer dessa optimização sentiu-se a necessidade de melhorar a convergência e, portanto, desenvolveu-se ainda uma adaptação dos algoritmos genéticos a que se deu o nome de Neighboured Genetic Algorithms (NGA1 e NGA2). No sentido de se compreender se as adaptações permitiam superar os algoritmos genéticos básicos e atingir as metas propostas, foi ainda desenvolvido um estudo em que o processo de optimização foi realizado 100 vezes para cada um dos métodos, o que permitiu concluir, estatisticamente, que os BGA foram superados pelos NGA1 e NGA2. Ainda assim, porque não foi possivel obter consistência nos resultados, foi usado o método de Nealder-Mead utilizado como estimativa inicial os resultados obtidos pelos algoritmos genéticos.

Portuguese Adaptation of Students Engagement in Schools International Scale (SESIS)

The importance of student’s engagement has been recently pointed out in research. However, there has been a lack of engagement assessment instrument, pertaining psychometric qualities. Objective: This paper presents the Portuguese adaptation of the “Student’s Engagement in School International Scale” (SESIS), drawn up from a12 countries international study (Lam et al., 2012; Lam et al., in press). Method: Psychometric properties of this scale were examined with data from 685 students from different grades (6th, 7th, 9th and 10th), from both sexes, and different regions of the country. Results: Factorial analysis of the results, with varimax rotation, lead to three different factors which explain 50.88% of the variance. The scale integrates the original 33 items, and cognitive, affective and behavioural dimensions. For the external validity study, the relationship between student’s engagement in school results and other school variables — academic performance, self-concept — was considered, and significant relations were observed, as expected. Conclusion: The data presented highlights the qualities of SESIS, as well as its usefulness for research purposes. Suggestion: It is suggested the investigation of the extension of SESIS’s three-dimensionality, in future studiesKeywords: Innovation, technology, research projects, etc. [Arial 10-point, justified alignment].

Portuguese Adaptation of Students Engagement in Schools International Scale (Sesis)

The importance of student’s engagement has been recently pointed out in research. However, there has been a lack of engagement assessment instruments, showing psychometric qualities, such as reliability and validity. Objective: This paper presents the Portuguese adaptation of the “Student’s Engagement in Schools International Scale” (SESIS), drawn up from 12 countries international study (Lam et al., 2012; Lam et al., in press). Method: Psychometric properties of this scale were examined using data from 685 students, of both sexes, and from different grades (6th, 7th, 9th and 10th), and regions of the country. Results: Factorial analysis of the results, with varimax rotation, conducted to three different factors which explain 62,19% of the variance. The scale integrates the original 33 items, and cognitive, affective and behavioural dimensions. For the external validity study, the relationship between student’s engagement in school results and other school variables — academic performance, school conduct — was considered, and significant relations were observed, as expected. Conclusion: The data presented highlights the qualities of SESIS, as well as its usefulness for research purpose. Suggestion: It is suggested the investigation of the extension of SESIS’s three-dimensionality, in future studies