967 resultados para Multilevel Systems Model
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This paper describes a communication model to integrate repositories of programming problems with other e-Learning software components. The motivation for this work comes from the EduJudge project that aims to connect an existing repository of programming problems to learning management systems. When trying to use the existing repositories of learning objects we realized that they are mainly specialized search engines and lack features for integration with other e-Learning systems. With this model we intend to clarify the main features of a programming problem repository, in order to enable the design and development of software components that use it. The two main points of this model are the definition of programming problems as learning objects and the definition of the core functions exposed by the repository. In both cases, this model follows the existing specifications of the IMS standard and proposes extensions to deal with the special requirements of automatic evaluation and grading of programming exercises. In the definition of programming problems as learning objects we introduced a new schema for meta-data. This schema is used to represent meta-data related to automatic evaluation that cannot be conveniently represented using the standard: the type of automatic evaluation; the requirements of the evaluation engine; or the roles of different assets - tests cases, program solutions, etc. In the definition of the core functions we used two different web services flavours - SOAP and REST - and described each function as an operation for each type of interface. We describe also the data types of the arguments of each operation. These data types consist mainly on learning objects and their identifications, but include also usage reports and queries using XQuery.
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Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação Geográfica
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In recent years emerged several initiatives promoted by educational organizations to adapt Service Oriented Architectures (SOA) to e-learning. These initiatives commonly named eLearning Frameworks share a common goal: to create flexible learning environments by integrating heterogeneous systems already available in many educational institutions. However, these frameworks were designed for integration of systems participating in business like processes rather than on complex pedagogical processes as those related to automatic evaluation. Consequently, their knowledge bases lack some fundamental components that are needed to model pedagogical processes. The objective of the research described in this paper is to study the applicability of eLearning frameworks for modelling a network of heterogeneous eLearning systems, using the automatic evaluation of programming exercises as a case study. The paper surveys the existing eLearning frameworks to justify the selection of the e-Framework. This framework is described in detail and identified the necessary components missing from its knowledge base, more precisely, a service genre, expression and usage model for an evaluation service. The extensibility of the framework is tested with the definition of this service. A concrete model for evaluation of programming exercises is presented as a validation of the proposed approach.
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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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Hydraulic systems are dynamically susceptible in the presence of entrapped air pockets, leading to amplified transient reactions. In order to model the dynamic action of an entrapped air pocket in a confined system, a heuristic mathematical formulation based on a conceptual analogy to a mechanical spring-damper system is proposed. The formulation is based on the polytropic relationship of an ideal gas and includes an additional term, which encompasses the combined damping effects associated with the thermodynamic deviations from the theoretical transformation, as well as those arising from the transient vorticity developed in both fluid domains (air and water). These effects represent the key factors that account for flow energy dissipation and pressure damping. Model validation was completed via numerical simulation of experimental measurements.
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Dynamic and distributed environments are hard to model since they suffer from unexpected changes, incomplete knowledge, and conflicting perspectives and, thus, call for appropriate knowledge representation and reasoning (KRR) systems. Such KRR systems must handle sets of dynamic beliefs, be sensitive to communicated and perceived changes in the environment and, consequently, may have to drop current beliefs in face of new findings or disregard any new data that conflicts with stronger convictions held by the system. Not only do they need to represent and reason with beliefs, but also they must perform belief revision to maintain the overall consistency of the knowledge base. One way of developing such systems is to use reason maintenance systems (RMS). In this paper we provide an overview of the most representative types of RMS, which are also known as truth maintenance systems (TMS), which are computational instances of the foundations-based theory of belief revision. An RMS module works together with a problem solver. The latter feeds the RMS with assumptions (core beliefs) and conclusions (derived beliefs), which are accompanied by their respective foundations. The role of the RMS module is to store the beliefs, associate with each belief (core or derived belief) the corresponding set of supporting foundations and maintain the consistency of the overall reasoning by keeping, for each represented belief, the current supporting justifications. Two major approaches are used to reason maintenance: single-and multiple-context reasoning systems. Although in the single-context systems, each belief is associated to the beliefs that directly generated it—the justification-based TMS (JTMS) or the logic-based TMS (LTMS), in the multiple context counterparts, each belief is associated with the minimal set of assumptions from which it can be inferred—the assumption-based TMS (ATMS) or the multiple belief reasoner (MBR).
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Decentralised co-operative multi-agent systems are computational systems where conflicts are frequent due to the nature of the represented knowledge. Negotiation methodologies, in this case argumentation based negotiation methodologies, were developed and applied to solve unforeseeable and, therefore, unavoidable conflicts. The supporting computational model is a distributed belief revision system where argumentation plays the decisive role of revision. The distributed belief revision system detects, isolates and solves, whenever possible, the identified conflicts. The detection and isolation of the conflicts is automatically performed by the distributed consistency mechanism and the resolution of the conflict, or belief revision, is achieved via argumentation. We propose and describe two argumentation protocols intended to solve different types of identified information conflicts: context dependent and context independent conflicts. While the protocol for context dependent conflicts generates new consensual alternatives, the latter chooses to adopt the soundest, strongest argument presented. The paper shows the suitability of using argumentation as a distributed decentralised belief revision protocol to solve unavoidable conflicts.
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This paper describes the implementation of a distributed model predictive approach for automatic generation control. Performance results are discussed by comparing classical techniques (based on integral control) with model predictive control solutions (centralized and distributed) for different operational scenarios with two interconnected networks. These scenarios include variable load levels (ranging from a small to a large unbalance generated power to power consumption ratio) and simultaneously variable distance between the interconnected networks systems. For the two networks the paper also examines the impact of load variation in an island context (a network isolated from each other).
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Dissertação apresentada na Faculdade de Ciências e Tecnologias da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores
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Task scheduling is one of the key mechanisms to ensure timeliness in embedded real-time systems. Such systems have often the need to execute not only application tasks but also some urgent routines (e.g. error-detection actions, consistency checkers, interrupt handlers) with minimum latency. Although fixed-priority schedulers such as Rate-Monotonic (RM) are in line with this need, they usually make a low processor utilization available to the system. Moreover, this availability usually decreases with the number of considered tasks. If dynamic-priority schedulers such as Earliest Deadline First (EDF) are applied instead, high system utilization can be guaranteed but the minimum latency for executing urgent routines may not be ensured. In this paper we describe a scheduling model according to which urgent routines are executed at the highest priority level and all other system tasks are scheduled by EDF. We show that the guaranteed processor utilization for the assumed scheduling model is at least as high as the one provided by RM for two tasks, namely 2(2√−1). Seven polynomial time tests for checking the system timeliness are derived and proved correct. The proposed tests are compared against each other and to an exact but exponential running time test.
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Comunicação apresentada na 17.ª conferência anual da NISPACee, realizada de 14 a 16 de Maio de 2009.
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Comunicação apresentada na 4th Annual ICPA - International Conference on Public Administration "Building bridges to the future: leadership and collaboration in public administration", na Universidade de Minnesota nos Estados Unidos, de 24 a 26 de setembro de 2008
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Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Electrotécnica, Especialidade de Sistemas Digitais, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Human mesenchymal stem/stromal cells (MSCs) have received considerable attention in the field of cell-based therapies due to their high differentiation potential and ability to modulate immune responses. However, since these cells can only be isolated in very low quantities, successful realization of these therapies requires MSCs ex-vivo expansion to achieve relevant cell doses. The metabolic activity is one of the parameters often monitored during MSCs cultivation by using expensive multi-analytical methods, some of them time-consuming. The present work evaluates the use of mid-infrared (MIR) spectroscopy, through rapid and economic high-throughput analyses associated to multivariate data analysis, to monitor three different MSCs cultivation runs conducted in spinner flasks, under xeno-free culture conditions, which differ in the type of microcarriers used and the culture feeding strategy applied. After evaluating diverse spectral preprocessing techniques, the optimized partial least square (PLS) regression models based on the MIR spectra to estimate the glucose, lactate and ammonia concentrations yielded high coefficients of determination (R2 ≥ 0.98, ≥0.98, and ≥0.94, respectively) and low prediction errors (RMSECV ≤ 4.7%, ≤4.4% and ≤5.7%, respectively). Besides PLS models valid for specific expansion protocols, a robust model simultaneously valid for the three processes was also built for predicting glucose, lactate and ammonia, yielding a R2 of 0.95, 0.97 and 0.86, and a RMSECV of 0.33, 0.57, and 0.09 mM, respectively. Therefore, MIR spectroscopy combined with multivariate data analysis represents a promising tool for both optimization and control of MSCs expansion processes.