217 research outputs found

    Application of Model-driven engineering to multi-agent systems: a language to model behaviors of reactive agents

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    Many users of multi-agent systems (MAS) are very commonly disinclined to model and simulate using current MAS platforms. More specifically, modeling the dynamics of a system (in particular the agents' behaviors) is very often a challenge to MAS users. This issue is more often observed in the domain of socio-ecological systems (SES), because SES domain experts are rarely programmers. Indeed, the majority of MAS platforms were not conceived taking into consideration domain-experts who are non-programmers. Most current MAS tools are not dedicated to SES, or nor do they possess an easily understandable formalism to represent the behaviors of agents. Moreover, because it is platform-dependent, a model realized in a given MAS platform cannot be properly used on another platform due to incompatibility between MAS platforms. To overcome these limitations, we propose a domain-specific language (DSL) to describe the behaviors of reactive agents, regardless of the MAS platform used for simulation. To achieve this result, we used model-driven engineering (MDE), an approach that provides tools to develop DSLs from a meta-model (abstract syntax), textual editors with syntax highlighting (for the concrete syntax) and code generation capabilities (for source-code generation of a model). As a result, we implemented a language and a textual editor that allow SES domain experts to describe behaviors in three different ways that are close to their natural expression: as equations when they are familiar with these, as a sequence of activities close to natural language or as an activity diagram to represent decisions and a sequence of behaviors using a graphic formalism. To demonstrate interoperability, we also developed code generators targeting two different MAS platforms (Cormas and Netlogo). We tested the code generators by implementing two SES models with the developed DSL. The generated code was targeted to both MAS platforms (Cormas and Netlogo), and successfully simulated in one of them. We conclude that the MDE approach provides adequate tools to develop DSL and code generators to facilitate MAS modeling and simulation by non-programmers. Concerning the DSL developed, although the behavioral aspect of MAS simulation is part of the complexity of modeling in MAS, there are still other essential aspects of model and simulation of MAS that are yet to be explored, such as model initialization and points of view on the model simulated worl

    Current Challenges in Modeling Cellular Metabolism

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    Mathematical and computational models play an essential role in understanding the cellular metabolism. They are used as platforms to integrate current knowledge on a biological system and to systematically test and predict the effect of manipulations to such systems. The recent advances in genome sequencing techniques have facilitated the reconstruction of genome-scale metabolic networks for a wide variety of organisms from microbes to human cells. These models have been successfully used in multiple biotechnological applications. Despite these advancements, modeling cellular metabolism still presents many challenges. The aim of this Research Topic is not only to expose and consolidate the state-of-the-art in metabolic modeling approaches, but also to push this frontier beyond the current edge through the introduction of innovative solutions. The articles presented in this e-book address some of the main challenges in the field, including the integration of different modeling formalisms, the integration of heterogeneous data sources into metabolic models, explicit representation of other biological processes during phenotype simulation, and standardization efforts in the representation of metabolic models and simulation results

    Computational tools for pathway optimization towards metabolic engineering applications

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    Dissertação de mestrado em Engenharia InformáticaMetabolic Engineering targets the microorganism's cellular metabolism to design new strains with an industrial purpose. Applications of these metabolic manipulations in Biotechnological derive from the need of enhanced production of valuable compounds. The development of in silico metabolic models proposes a quantifiable approach for the manipulation these microorganisms. In this context, constraint based modelling is one of the major approaches to predict cellular behaviour. It allows to prune the feasible space of possibilities describing possible phenotype outcomes in terms of metabolic fluxes. Under these conditions, cellular metabolism can be represented as an algebraic system constrained by the laws of mass balance and thermodynamics. These systems are prone to be represented as networks, taking advantage of different graph-based paradigms, including bipartite graphs, hypergraphs and process graphs. This thesis explores these representations and underlying algorithms for metabolic network topological analysis. The main aim will be to identify potential pathways towards the optimized biochemical production of selected compounds. Related to this task, algorithms will also be designed aiming to complement networks of specific organisms, taking as input larger metabolic databases, inserting new reactions making them able to produce a new compound of interest. To address these problems, and also related tasks of data pre-processing and evaluation of the solutions, a complete computational framework was developed. It integrates a number of previously proposed algorithms from distinct authors, together with a number of improvements that were necessary to cope with large-scale metabolic networks. These are the result of problems identi ed in the previous algorithms regarding their scalability. A case study in synthetic metabolic engineering was selected from the literature to validate the algorithms and test the capabilities of the implemented framework. It allowed to compare the performance of the implemented algorithms and validate the proposed improvements.A Engenharia Metabólica visa a alteração do metabolismo celular dos microorganismos com vista ao desenho de novas estirpes com fins industriais. As aplicações destas modificações genéticas na Biotecnologia derivam da necessidade de produzir de forma otimizada compostos de alto valor. O desenvolvimento de modelos computacionais propõe uma abordagem quantitativa para a manipulação destes organismos. Neste contexto, a modelação baseada em restrições constitui uma das abordagens mais usadas para a previsão do comportamento celular. Esta permite reduzir o espaço de soluções viáveis descrevendo o fenótipo celular a partir dos fluxos metabólicos. Nestas condições, o metabolismo celular pode ser representado como um sistema algébrico restringido pelas leis da conservação de massa e termodinâmica. Estes sistemas podem ser representados como redes, tirando partido de diferentes paradigmas baseados em grafos, incluindo os grafos bipartidos, os hipergrafos e os grafos de processos. Esta tese explora estas representações e os respetivos algoritmos para a análise topológica de redes metabólicas. O objetivo principal será o de identificar potenciais vias metabólicas para a optimização da produção de compostos selecionados. Relacionado com esta tarefa, serão desenhados algoritmos com o objetivo de complementar redes de organismos específicos, tomando como entradas bases de dados metabólicas de maior dimensão, inserindo novas reações de forma a torná-los capazes da produção de novos compostos de interesse. Para abordar estes problemas, bem como tarefas relacionadas ao nível do pré-processamento e avaliação das soluções, foi desenvolvida uma plataforma computacional completa. Esta integra um conjunto de algoritmos previamente propostos por diversos autores, em conjunto com melhorias significativas que foram necessárias para que estes pudessem lidar com redes metabólicas de grande escala. Estas melhorias resultam da identificação de problemas nos algoritmos no que diz respeito à sua escalabilidade. Um caso de estudo na Engenharia Metabólica sintética foi selecionado da literatura para validar os algoritmos e testar as capacidades da plataforma implementada. Este permitiu comparar o desempenho dos algoritmos implementados e validar as melhorias propostas

    The effectiveness of IF-MADM (intuitionistic-fuzzy multi-attribute decision-making) for group decisions: methods and an empirical assessment for the selection of a senior centre

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    This study determines the effectiveness of intuitionistic-fuzzy multi-attribute decision-making (IF-MADM) for making group decisions in practice. The effectiveness of the method is measured in terms of four dimensions: applicability, efficacy, efficiency and informativeness. To measure the efficacy, an IF-MADM model that has been recently proposed, AHP and the TOPSIS approach, which are compensatory models for group MADM, are used to model and solve the same collective decision. Using non-parametric statistical tests for data analytics, a ‘similarity confirmation method’ is proposed for a pair-wise test. This is to determine whether the score vectors are similar. Score vectors are used to determine the final ordinal ranks and whose scales differ greatly for different MADM methods. Since the latter two MADM models are both trustworthy with a known range of applications, any similarity in the results verifies the efficacy of IF-MADM. Using this process, the applicability of IF-MADM modelling is demonstrated. The efficiency and informativeness are also benchmarked and justified in terms of the model’s ability to produce a more informed decision. These results are of interest to practitioners for the selection and application of MADM models. Finally, the selection of a senior centre, which is a real group decision problem, is used to illustrate these. This extends the empirical application of IF-MADM, as relatively few studies practically compare issues for IF-MADM with those for other MADM models. The study also supports a rarely studied non-clinical healthcare decision that is relevant because there are many aging societies

    Soft Computing

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    Soft computing is used where a complex problem is not adequately specified for the use of conventional math and computer techniques. Soft computing has numerous real-world applications in domestic, commercial and industrial situations. This book elaborates on the most recent applications in various fields of engineering

    Utilização de métodos de sobreclassificação para apoio na tomada de decisão em gestão de projetos

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    Monografia (graduação)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia de Produção, 2015.Este trabalho aborda, através da metodologia fundamentada na pesquisa bibliográfica e análise de conteúdo, a tomada de decisão no ambiente de gerenciamento de projetos envolvendo diferentes aspectos do seu ciclo de vida. Estas decisões são, por vezes, complexas e de difícil escolha, o que implica na necessidade do uso de métodos de apoio. Neste contexto, os métodos multicritério de apoio à decisão (Multi Criteria Decision Analysis - MCDA) podem auxiliar o decisor na estruturação e solução destes problemas. Dentre os métodos MCDA existentes, os métodos de sobreclassificação têm sido aplicados à gestão de projetos com bons resultados. Desta forma, é proposta uma análise destes métodos a fim de observar as características que levam a escolha de um determinado método de sobreclassificação para problemas específicos de gestão de projetos. Esta análise resultou na identificação de um padrão de utilização dos métodos de sobreclassificação para apoio na tomada de decisão de problemas relacionados à priorização de projeto, seleção de portfólio, seleção de fornecedores e priorização de atividades. ________________________________________________________________________________ ABSTRACTThis paper deals with decision making in the project management environment, involving different aspects of their life cycle through the methodology based on bibliographic research and content analysis. These decisions are sometimes complex and hard to choice, which implies the need to use methods of support. In this context, multi-criteria decision support methods (Multi Criteria Decision Analysis - MCDA) can help the decision maker in the structuring and solving these problems. Among the existing MCDA methods, outranking methods have been applied to the management of projects with good results. Thus, it is proposed an analysis of these methods in order to observe the characteristics that lead to choice of a particular outranking method for specific project management problems. This analysis resulted in the identification of a pattern of use of outranking methods to support the decision making of problems related to project prioritization, portfolio selection, vendor selection and prioritization of activitie

    Best Practices for Children and Youth with Autism Spectrum Disorder: A Resource Guide for Community Partners

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    Students with Autism Spectrum Disorder (ASD) present a unique challenge, and learning opportunity for professionals. The purpose of this study was to create a comprehensive and accessible handbook to empower those who work with children and youth with ASD in a community setting. The best practices and effective intervention programs for students with ASD were researched and evaluated. Four individuals from various community agencies voluntarily participated in a Needs Assessment Questionnaire and, based on their information, a Handbook on Best Practices for Children with ASD, including a resource section was created. The theoretical framework examined for this project was based on social-cognitive theory, specifically Bandura's (1986) theory of triadic reciprocity and reciprocal determinism. This theory places emphasis on the fact that behaviour must be evaluated in the course of normal development, and that what may be appropriate for an individual at one age or point in time, may not be at another. Once the handbook was complete, an Evaluative Questionnaire was circulated to determine its effectiveness and overall benefits in practice for community partners in the field. The results of this questionnaire contributed to a final copy of the handbook. Implications for future research were considered and the limitations of this study were examined

    Soft Computing

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    Soft computing is used where a complex problem is not adequately specified for the use of conventional math and computer techniques. Soft computing has numerous real-world applications in domestic, commercial and industrial situations. This book elaborates on the most recent applications in various fields of engineering

    Connecting higher education institutions with small and medium-sized enterprises

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    The aim of this monograph is to foster, enhance, encourage and maintain a productive dialogue between universities and businesses. Collaboration between universities and businesses is necessary for skills development (education and training), the generation, acquisition and adoption of knowledge and for the promotion of entrepreneurship as well as for expanding the relevance of research carried out at HEI. We believe that companies lacking close relationship with the academic community are likely to advance slower. On the other hand, universities not offering state-of-the-art lectures, valuable knowledge and groundbreaking methodologies and who do not implement research in the real world are most likely to lose their customers. In addition, universities have an important role in helping students understand the opportunities that are available in the business sector or in self-employment
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