RPN-Toolbox : uma ferramenta para o desenvolvimento de estruturas de controle

A literatura disponível na área de controle de processos químicos tem dado pouca atenção para o problema da seleção de estruturas de controle, entretanto a correta escolha das variáveis controladas e manipuladas, assim como os seus pareamentos, é tão ou mesmo mais importante que o projeto do controlador propriamente dito, pois esta etapa define o desempenho alcançável para o sistema em malha fechada. Esta dissertação explora vários aspectos genéricos do controle de processos com o objetivo de introduzir os principais pontos da metodologia RPN, um método sistemático que, através de índices baseados em sólidos fundamentos matemáticos, permite avaliar o projeto de controle como um todo. O índice RPN (Número de Desempenho Robusto) indica quão potencialmente difícil é, para um dado sistema, alcançar o desempenho desejado. O produto final desse trabalho é o RPN-Toolbox, a implementação das rotinas da metodologia RPN em ambiente MATLAB® com o intuito de torná-la acessível a qualquer profissional da área de controle de processos. O RPN-Toolbox permite que todas as rotinas necessárias para proceder a análise RPN de controlabilidade sejam executadas através de comandos de linha ou utilizando uma interface gráfica. Além do desenvolvimento das rotinas para o toolbox, foi realizado um estudo do problema de controle denominado processo Tennessee-Eastman. Foi desenvolvida uma estrutura de controle para a unidade e esta foi comparada, de modo sistemático, através da metodologia RPN e de simulações dinâmicas, com outras soluções apresentadas na literatura. A partir do índice concluiu-se que a estrutura proposta é tão boa quanto a melhor das estruturas da literatura e a partir de simulações dinâmicas do processo frente a diversos distúrbios, a estrutura proposta foi a que apresentou melhores resultados.

The executive toolbox: building legislative support in a multiparty presidential regime

How do presidents win legislative support under conditions of extreme multipartism? Comparative presidential research has offered two parallel answers, one relying on distributive politics and the other claiming that legislative success is a function of coalition formation. We merge these insights in an integrated approach to executive-legislative relations, also adding contextual factors related to dynamism and bargaining conditions. We find that the two presidential “tools” – pork and coalition goods – are substitutable resources, with pork functioning as a fine-tuning instrument that interacts reciprocally with legislative support. Pork expenditures also depend upon a president’s bargaining leverage and the distribution of legislative seats.

Introdução à identificação de sistemas utilizando o System Identification Toolbox do MATLAB em conjunto com o Arduino para o laboratório de controle linear

The education designed and planned in a clear and objective manner is of paramount importance for universities to prepare competent professionals for the labor market, and above all can serve the population with an efficient work. Specifically, in relation to engineering, conducting classes in the laboratories it is very important for the application of theory and development of the practical part of the student. The planning and preparation of laboratories, as well as laboratory equipment and activities should be developed in a succinct and clear way, showing to students how to apply in practice what has been learned in theory and often shows them why and where it can be used when they become engineers. This work uses the MATLAB together with the System Identification Toolbox and Arduino for the identification of linear systems in Linear Control Lab. MATLAB is a widely used program in the engineering area for numerical computation, signal processing, graphing, system identification, among other functions. Thus the introduction to MATLAB and consequently the identification of systems using the System Identification Toolbox becomes relevant in the formation of students to thereafter when necessary to identify a system the base and the concept has been seen. For this procedure the open source platform Arduino was used as a data acquisition board being the same also introduced to the student, offering them a range of software and hardware for learning, giving you every day more luggage to their training

Introdução à identificação de sistemas utilizando o System Identification Toolbox do MATLAB em conjunto com o Arduino para o laboratório de controle linear

The education designed and planned in a clear and objective manner is of paramount importance for universities to prepare competent professionals for the labor market, and above all can serve the population with an efficient work. Specifically, in relation to engineering, conducting classes in the laboratories it is very important for the application of theory and development of the practical part of the student. The planning and preparation of laboratories, as well as laboratory equipment and activities should be developed in a succinct and clear way, showing to students how to apply in practice what has been learned in theory and often shows them why and where it can be used when they become engineers. This work uses the MATLAB together with the System Identification Toolbox and Arduino for the identification of linear systems in Linear Control Lab. MATLAB is a widely used program in the engineering area for numerical computation, signal processing, graphing, system identification, among other functions. Thus the introduction to MATLAB and consequently the identification of systems using the System Identification Toolbox becomes relevant in the formation of students to thereafter when necessary to identify a system the base and the concept has been seen. For this procedure the open source platform Arduino was used as a data acquisition board being the same also introduced to the student, offering them a range of software and hardware for learning, giving you every day more luggage to their training

GEDI: a user-friendly toolbox for analysis of large-scale gene expression data

Abstract Background Several mathematical and statistical methods have been proposed in the last few years to analyze microarray data. Most of those methods involve complicated formulas, and software implementations that require advanced computer programming skills. Researchers from other areas may experience difficulties when they attempting to use those methods in their research. Here we present an user-friendly toolbox which allows large-scale gene expression analysis to be carried out by biomedical researchers with limited programming skills. Results Here, we introduce an user-friendly toolbox called GEDI (Gene Expression Data Interpreter), an extensible, open-source, and freely-available tool that we believe will be useful to a wide range of laboratories, and to researchers with no background in Mathematics and Computer Science, allowing them to analyze their own data by applying both classical and advanced approaches developed and recently published by Fujita et al. Conclusion GEDI is an integrated user-friendly viewer that combines the state of the art SVR, DVAR and SVAR algorithms, previously developed by us. It facilitates the application of SVR, DVAR and SVAR, further than the mathematical formulas present in the corresponding publications, and allows one to better understand the results by means of available visualizations. Both running the statistical methods and visualizing the results are carried out within the graphical user interface, rendering these algorithms accessible to the broad community of researchers in Molecular Biology.

SNA--a toolbox for the stoichiometric analysis of metabolic networks

BACKGROUND: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. RESULTS: SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: http://bioinformatics.org/project/?group_id=546. CONCLUSION: Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results.

Loss estimation for landslides in mountain areas – An integrated toolbox for vulnerability assessment and damage documentation

Global environmental change includes changes in a wide range of global scale phenomena, which are expected to affect a number of physical processes, as well as the vulnerability of the communities that will experience their impact. Decision-makers are in need of tools that will enable them to assess the loss of such processes under different future scenarios and to design risk reduction strategies. In this paper, a tool is presented that can be used by a range of end-users (e.g. local authorities, decision makers, etc.) for the assessment of the monetary loss from future landslide events, with a particular focus on torrential processes. The toolbox includes three functions: a) enhancement of the post-event damage data collection process, b) assessment of monetary loss of future events and c) continuous updating and improvement of an existing vulnerability curve by adding data of recent events. All functions of the tool are demonstrated through examples of its application.

«Toolbox Assessment» - ein hochschuldidaktischer Service im virtuellen Raum

Zeitgemäße Hochschullehre verlangt nach zeitgemäßen Prüfungsformen. Mit «Assessment», wie es hier verstanden wird, ist jedoch nicht nur die abschließende Lernerfolgskontrolle gemeint. Im Ideal der kompetenzorientierten Hochschullehre erhalten die Studierenden auch auf dem Weg zur angestrebten Handlungskompetenz immer wieder Gelegenheit zur Standortbestimmung. Eine Benotung ist dabei nicht zwingend, informierendes Feedback jedoch schon. Mit der «Toolbox Assessment» erhalten Lehrende dazu nun ein attraktives Hilfsmittel buchstäblich in die Hand.

Digital repository implementation: a toolbox for streamlined success

Purpose – The purpose of this paper is to describe the tools and strategies that were employed by C/W MARS to successfully develop and implement the Digital Treasures digital repository. Design/methodology/approach – This paper outlines the planning and subsequent technical issues that arise when implementing a digitization project on the scale of the large, multi-type, automated library network. Workflow solutions addressed include synchronous online metadata record submissions from multiple library sources and the delivery of collection-level use statistics to participating library administrators. The importance of standards-based descriptive metadata and the role of project collaboration are also discussed. Findings – From the time of its initial planning, the Digital Treasures repository was fully implemented in six months. The discernable and statistically quantified online discovery and access of actual digital objects greatly assisted libraries unsure of their own staffing costs/benefits to join the repository. Originality/value – This case study may serve as a possible example of initial planning, workflow and final implementation strategies for new repositories in both the general and library consortium environment. Keywords – Digital repositories, Library networks, Data management. Paper type – Case study

The SUGAR Toolbox

The SUGAR Toolbox contains scripts coded in MATLAB for calculating various thermodynamic, kinetic, and geologic properties of substances occurring in the marine environment, particularly gas hydrate and seep systems. Brief descriptions of the toolbox scripts and some notes on the underlying basic theory as well as tables of additional property values can be found in the accompanying documentation.

BSRN Toolbox V2.0 - a tool to create quality checked output files from BSRN datasets and station-to-archive files

The BSRN Toolbox is a software package supplied by the WRMC and is freely available to all station scientists and data users. The main features of the package include a download manager for Station- to-Archive files, a tool to convert files into human readable TAB-separated ASCII-tables (similar to those output by the PANGAEA database), and a tool to check data sets for violations of the "BSRN Global Network recommended QC tests, V2.0" quality criteria. The latter tool creates quality codes, one per measured value, indicating if the data are "physically possible," "extremely rare," or if "intercomparison limits are exceeded." In addition, auxiliary data such as solar zenith angle or global calculated from diffuse and direct can be output. All output from the QC tool can be visualized using PanPlot (doi:10.1594/PANGAEA.816201).

Descripción, comparación y ejemplos de uso de las funciones de la toolbox de procesado digital de imágenes de MATLAB®

Matlab, uno de los paquetes de software matemático más utilizados actualmente en el mundo de la docencia y de la investigación, dispone de entre sus muchas herramientas una específica para el procesado digital de imágenes. Esta toolbox de procesado digital de imágenes está formada por un conjunto de funciones adicionales que amplían la capacidad del entorno numérico de Matlab y permiten realizar un gran número de operaciones de procesado digital de imágenes directamente a través del programa principal. Sin embargo, pese a que MATLAB cuenta con un buen apartado de ayuda tanto online como dentro del propio programa principal, la bibliografía disponible en castellano es muy limitada y en el caso particular de la toolbox de procesado digital de imágenes es prácticamente nula y altamente especializada, lo que requiere que los usuarios tengan una sólida formación en matemáticas y en procesado digital de imágenes. Partiendo de una labor de análisis de todas las funciones y posibilidades disponibles en la herramienta del programa, el proyecto clasificará, resumirá y explicará cada una de ellas a nivel de usuario, definiendo todas las variables de entrada y salida posibles, describiendo las tareas más habituales en las que se emplea cada función, comparando resultados y proporcionando ejemplos aclaratorios que ayuden a entender su uso y aplicación. Además, se introducirá al lector en el uso general de Matlab explicando las operaciones esenciales del programa, y se aclararán los conceptos más avanzados de la toolbox para que no sea necesaria una extensa formación previa. De este modo, cualquier alumno o profesor que se quiera iniciar en el procesado digital de imágenes con Matlab dispondrá de un documento que le servirá tanto para consultar y entender el funcionamiento de cualquier función de la toolbox como para implementar las operaciones más recurrentes dentro del procesado digital de imágenes. Matlab, one of the most used numerical computing environments in the world of research and teaching, has among its many tools a specific one for digital image processing. This digital image processing toolbox consists of a set of additional functions that extend the power of the digital environment of Matlab and allow to execute a large number of operations of digital image processing directly through the main program. However, despite the fact that MATLAB has a good help section both online and within the main program, the available bibliography is very limited in Castilian and is negligible and highly specialized in the particular case of the image processing toolbox, being necessary a strong background in mathematics and digital image processing. Starting from an analysis of all the available functions and possibilities in the program tool, the document will classify, summarize and explain each function at user level, defining all input and output variables possible, describing common tasks in which each feature is used, comparing results and providing illustrative examples to help understand its use and application. In addition, the reader will be introduced in the general use of Matlab explaining the essential operations within the program and clarifying the most advanced concepts of the toolbox so that an extensive prior formation will not be necessary. Thus, any student or teacher who wants to start digital image processing with Matlab will have a document that will serve to check and understand the operation of any function of the toolbox and also to implement the most recurrent operations in digital image processing.