91 resultados para PLC and SCADA programming


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Finding the optimal value for a problem is usual in many areas of knowledge where in many cases it is needed to solve Nonlinear Optimization Problems. For some of those problems it is not possible to determine the expression for its objective function and/or its constraints, they are the result of experimental procedures, might be non-smooth, among other reasons. To solve such problems it was implemented an API contained methods to solve both constrained and unconstrained problems. This API was developed to be used either locally on the computer where the application is being executed or remotely on a server. To obtain the maximum flexibility both from the programmers’ and users’ points of view, problems can be defined as a Java class (because this API was developed in Java) or as a simple text input that is sent to the API. For this last one to be possible it was also implemented on the API an expression evaluator. One of the drawbacks of this expression evaluator is that it is slower than the Java native code. In this paper it is presented a solution that combines both options: the problem can be expressed at run-time as a string of chars that are converted to Java code, compiled and loaded dynamically. To wide the target audience of the API, this new expression evaluator is also compatible with the AMPL format.

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Nonlinear Optimization Problems are usual in many engineering fields. Due to its characteristics the objective function of some problems might not be differentiable or its derivatives have complex expressions. There are even cases where an analytical expression of the objective function might not be possible to determine either due to its complexity or its cost (monetary, computational, time, ...). In these cases Nonlinear Optimization methods must be used. An API, including several methods and algorithms to solve constrained and unconstrained optimization problems was implemented. This API can be accessed not only as traditionally, by installing it on the developer and/or user computer, but it can also be accessed remotely using Web Services. As long as there is a network connection to the server where the API is installed, applications always access to the latest API version. Also an Web-based application, using the proposed API, was developed. This application is to be used by users that do not want to integrate methods in applications, and simply want to have a tool to solve Nonlinear Optimization Problems.

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Within the pedagogical community, Serious Games have arisen as a viable alternative to traditional course-based learning materials. Until now, they have been based strictly on software solutions. Meanwhile, research into Remote Laboratories has shown that they are a viable, low-cost solution for experimentation in an engineering context, providing uninterrupted access, low-maintenance requirements, and a heightened sense of reality when compared to simulations. This paper will propose a solution where both approaches are combined to deliver a Remote Laboratory-based Serious Game for use in engineering and school education. The platform for this system is the WebLab-Deusto Framework, already well-tested within the remote laboratory context, and based on open standards. The laboratory allows users to control a mobile robot in a labyrinth environment and take part in an interactive game where they must locate and correctly answer several questions, the subject of which can be adapted to educators' needs. It also integrates the Google Blockly graphical programming language, allowing students to learn basic programming and logic principles without needing to understand complex syntax.

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Standards for learning objects focus primarily on content presentation. They were already extended to support automatic evaluation but it is limited to exercises with a predefined set of answers. The existing standards lack the metadata required by specialized evaluators to handle types of exercises with an indefinite set of solutions. To address this issue we extended existing learning object standards to the particular requirements of a specialized domain. We present a definition of programming problems as learning objects that is compatible both with Learning Management Systems and with systems performing automatic evaluation of programs. The proposed definition includes metadata that cannot be conveniently represented using existing standards, such as: the type of automatic evaluation; the requirements of the valuation engine; and the roles of different assets - tests cases, program solutions, etc. We present also the EduJudge project and its main services as a case study on the use of the proposed definition of programming problems as learning objects.

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This work is a contribution to the e-Framework, arguably the most prominent e-learning framework today, and consists of the definition of a service for the automatic evaluation of programming exercises. This evaluation domain differs from trivial evaluations modelled by languages such as the IMS Question & Test Interoperability (QTI) specification. Complex evaluation domains justify the development of specialized evaluators that participate in several business processes. These business processes can combine other type of systems such as Programming Contest Management Systems, Learning Management Systems, Integrated Development Environments and Learning Object Repositories where programming exercises are stored as Learning Objects. This contribution describes the implementation approaches used, more precisely, behaviours & requests, use & interactions, applicable standards, interface definition and usage scenarios.

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It is widely accepted that solving programming exercises is fundamental to learn how to program. Nevertheless, solving exercises is only effective if students receive an assessment on their work. An exercise solved wrong will consolidate a false belief, and without feedback many students will not be able to overcome their difficulties. However, creating, managing and accessing a large number of exercises, covering all the points in the curricula of a programming course, in classes with large number of students, can be a daunting task without the appropriated tools working in unison. This involves a diversity of tools, from the environments where programs are coded, to automatic program evaluators providing feedback on the attempts of students, passing through the authoring, management and sequencing of programming exercises as learning objects. We believe that the integration of these tools will have a great impact in acquiring programming skills. Our research objective is to manage and coordinate a network of eLearning systems where students can solve computer programming exercises. Networks of this kind include systems such as learning management systems (LMS), evaluation engines (EE), learning objects repositories (LOR) and exercise resolution environments (ERE). Our strategy to achieve the interoperability among these tools is based on a shared definition of programming exercise as a Learning Object (LO).

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Several standards appeared in recent years to formalize the metadata of learning objects, but they are still insufficient to fully describe a specialized domain. In particular, the programming exercise domain requires interdependent resources (e.g. test cases, solution programs, exercise description) usually processed by different services in the programming exercise life-cycle. Moreover, the manual creation of these resources is time-consuming and error-prone leading to what is an obstacle to the fast development of programming exercises of good quality. This paper focuses on the definition of an XML dialect called PExIL (Programming Exercises Interoperability Language). The aim of PExIL is to consolidate all the data required in the programming exercise life-cycle, from when it is created to when it is graded, covering also the resolution, the evaluation and the feedback. We introduce the XML Schema used to formalize the relevant data of the programming exercise life-cycle. The validation of this approach is made through the evaluation of the usefulness and expressiveness of the PExIL definition. In the former we present the tools that consume the PExIL definition to automatically generate the specialized resources. In the latter we use the PExIL definition to capture all the constraints of a set of programming exercises stored in a learning objects repository.

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Learning computer programming requires solving programming exercises. In computer programming courses teachers need to assess and give feedback to a large number of exercises. These tasks are time consuming and error-prone since there are many aspects relating to good programming that should be considered. In this context automatic assessment tools can play an important role helping teachers in grading tasks as well to assist students with automatic feedback. In spite of its usefulness, these tools lack integration mechanisms with other eLearning systems such as Learning Management Systems, Learning Objects Repositories or Integrated Development Environments. In this paper we provide a survey on programming evaluation systems. The survey gathers information on interoperability features of these systems, categorizing and comparing them regarding content and communication standardization. This work may prove useful to instructors and computer science educators when they have to choose an assessment system to be integrated in their e-Learning environment.

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Assessment plays a vital role in learning. This is certainly the case with assessment of computer programs, both in curricular and competitive learning. The lack of a standard – or at least a widely used format – creates a modern Ba- bel tower made of Learning Objects, of assessment items that cannot be shared among automatic assessment systems. These systems whose interoperability is hindered by the lack of a common format include contest management systems, evaluation engines, repositories of learning objects and authoring tools. A prag- matical approach to remedy this problem is to create a service to convert among existing formats. A kind of translation service specialized in programming prob- lems formats. To convert programming exercises on-the-fly among the most used formats is the purpose of the BabeLO – a service to cope with the existing Babel of Learning Object formats for programming exercises. BabeLO was designed as a service to act as a middleware in a network of systems typically used in auto- matic assessment of programs. It provides support for multiple exercise formats and can be used by: evaluation engines to assess exercises regardless of its format; repositories to import exercises from various sources; authoring systems to create exercises in multiple formats or based on exercises from other sources. This paper analyses several of existing formats to highlight both their differ- ences and their similar features. Based on this analysis it presents an approach to extensible format conversion. It presents also the features of PExIL, the pivotal format in which the conversion is based; and the function definitions of the proposed service – BabeLO. Details on the design and implementation of BabeLO, including the service API and the interfaces required to extend the conversion to a new format, are also provided. To evaluate the effectiveness and efficiency of this approach this paper reports on two actual uses of BabeLO: to relocate exercises to a different repository; and to use an evaluation engine in a network of heterogeneous systems.

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Several standards have appeared in recent years to formalize the metadata of learning objects, but they are still insufficient to fully describe a specialized domain. In particular, the programming exercise domain requires interdependent resources (e.g. test cases, solution programs, exercise description) usually processed by different services in the programming exercise lifecycle. Moreover, the manual creation of these resources is time-consuming and error-prone, leading to an obstacle to the fast development of programming exercises of good quality. This chapter focuses on the definition of an XML dialect called PExIL (Programming Exercises Interoperability Language). The aim of PExIL is to consolidate all the data required in the programming exercise lifecycle from when it is created to when it is graded, covering also the resolution, the evaluation, and the feedback. The authors introduce the XML Schema used to formalize the relevant data of the programming exercise lifecycle. The validation of this approach is made through the evaluation of the usefulness and expressiveness of the PExIL definition. In the former, the authors present the tools that consume the PExIL definition to automatically generate the specialized resources. In the latter, they use the PExIL definition to capture all the constraints of a set of programming exercises stored in a learning objects repository.

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Volatile organic compounds are a common source of groundwater contamination that can be easily removed by air stripping in columns with random packing and using a counter-current flow between the phases. This work proposes a new methodology for the column design for any particular type of packing and contaminant avoiding the necessity of a pre-defined diameter used in the classical approach. It also renders unnecessary the employment of the graphical Eckert generalized correlation for pressure drop estimates. The hydraulic features are previously chosen as a project criterion and only afterwards the mass transfer phenomena are incorporated, in opposition to conventional approach. The design procedure was translated into a convenient algorithm using C++ as programming language. A column was built in order to test the models used either in the design or in the simulation of the column performance. The experiments were fulfilled using a solution of chloroform in distilled water. Another model was built to simulate the operational performance of the column, both in steady state and in transient conditions. It consists in a system of two partial non linear differential equations (distributed parameters). Nevertheless, when flows are steady, the system became linear, although there is not an evident solution in analytical terms. In steady state the resulting system of ODE can be solved, allowing for the calculation of the concentration profile in both phases inside the column. In transient state the system of PDE was numerically solved by finite differences, after a previous linearization.

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Applications refactorings that imply the schema evolution are common activities in programming practices. Although modern object-oriented databases provide transparent schema evolution mechanisms, those refactorings continue to be time consuming tasks for programmers. In this paper we address this problem with a novel approach based on aspect-oriented programming and orthogonal persistence paradigms, as well as our meta-model. An overview of our framework is presented. This framework, a prototype based on that approach, provides applications with aspects of persistence and database evolution. It also provides a new pointcut/advice language that enables the modularization of the instance adaptation crosscutting concern of classes, which were subject to a schema evolution. We also present an application that relies on our framework. This application was developed without any concern regarding persistence and database evolution. However, its data is recovered in each execution, as well as objects, in previous schema versions, remain available, transparently, by means of our framework.

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Generally, the evolution process of applications has impact on their underlining data models, thus becoming a time-consuming problem for programmers and database administrators. In this paper we address this problem within an aspect-oriented approach, which is based on a meta-model for orthogonal persistent programming systems. Applying reflection techniques, our meta-model aims to be simpler than its competitors. Furthermore, it enables database multi-version schemas. We also discuss two case studies in order to demonstrate the advantages of our approach.

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We consider an optimal control problem with a deterministic finite horizon and state variable dynamics given by a Markov-switching jump–diffusion stochastic differential equation. Our main results extend the dynamic programming technique to this larger family of stochastic optimal control problems. More specifically, we provide a detailed proof of Bellman’s optimality principle (or dynamic programming principle) and obtain the corresponding Hamilton–Jacobi–Belman equation, which turns out to be a partial integro-differential equation due to the extra terms arising from the Lévy process and the Markov process. As an application of our results, we study a finite horizon consumption– investment problem for a jump–diffusion financial market consisting of one risk-free asset and one risky asset whose coefficients are assumed to depend on the state of a continuous time finite state Markov process. We provide a detailed study of the optimal strategies for this problem, for the economically relevant families of power utilities and logarithmic utilities.

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We derived a framework in integer programming, based on the properties of a linear ordering of the vertices in interval graphs, that acts as an edge completion model for obtaining interval graphs. This model can be applied to problems of sequencing cutting patterns, namely the minimization of open stacks problem (MOSP). By making small modifications in the objective function and using only some of the inequalities, the MOSP model is applied to another pattern sequencing problem that aims to minimize, not only the number of stacks, but also the order spread (the minimization of the stack occupation problem), and the model is tested.