933 resultados para model driven system, semantic representation, semantic modeling, enterprise system development


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This paper provides a semantics for the UML-RSDS (Reactive System Development Support) subset of UML, using the real-time action logic (RAL) formalism. We show how this semantics can be used to resolve some ambiguities and omissions in UML semantics, and to support reasoning about specifications using the B formal method and tools. We use `semantic profiles' to provide precise semantics for different semantic variation points of UML. We also show how RAL can be used to give a semantics to notations for real-time specification in UML. Unlike other approaches to UML semantics, which concentrate on the class diagram notation, our semantic representation has behaviour as a central element, and can be used to define semantics for use cases, state machines and interactions, in addition to class diagrams.

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This paper proposes a systematic approach to management of variability modelsdriven and aspects using the mechanisms of approaches Aspect-Oriented Software Development (AOSD) and Model-Driven Development (MDD). The main goal of the approach, named CrossMDA-SPL, is to improve the management(gerência), modularization and isolation ou separation of the variability of the LPSs of architecture in a high level of abstraction (model) at the design and implementing phases of development Software Product Lines (SPLs), exploiting the synergy between AOSD and MDD. The CrossMDA-SPL approach defines some artifacts basis for advance the separation clear in between the mandatory (bounden) and optional features in the architecture of SPL. The artifacts are represented by two models named: (i) core model (base domain) - responsible for specify the common features the all members of the SPL, and (ii) variability model - responsible for represent the variables features of SPL. In addition, the CrossMDA-SPL approach is composed of: (i) guidelines for modeling and representation of variability, (ii) CrossMDA-SPL services and process, and (iii) models of the architecture of SPL or product instance of SPL. The guidelines use the advantages of AOSD and MDD to promote a better modularization of the variable features of the architecture of SPL during the creation of core and variability models of the approach. The services and sub-processes are responsible for combination automatically, through of process of transformation between the core and variability models, and the generation of new models that represent the implementation of the architecture of SPL or a instance model of SPL. Mechanisms for effective modularization of variability for architectures of SPL at model level. The concepts are described and measured with the execution of a case study of an SPL for management systems of transport electronic tickets

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Currently there are several aspect-oriented approaches that are related to different stages of software development process. These approaches often lack integration with each other and their models and artifacts are not aligned in a coherent process. The integration of Aspect-Oriented Software development (AOSD) and Model-Driven Development (MDD) enables automatic propagation of models from one phase to another, avoiding loss of important information and decisions established in each. This paper presents a model driven approach, called Marisa-AOCode, which supports the processing of detailed design artifacts to code in different Aspect-Oriented Programming languages. The approach proposed by Maris- AOCode defines transformation rules between aSideML, a modeling language for aspectoriented detailed design, and Metaspin, a generic metamodel for aspect-oriented programming languages. The instantiation of the generic metamodel (Metaspin) provided by the approach of Maris-AOCode is illustrated by the transformation of Metaspin for two languages: AspectLua and CaesarJ. We illustrate the approach with a case study based on the Health Watcher System

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Aspect-Oriented Software Development (AOSD) is a technique that complements the Object- Oriented Software Development (OOSD) modularizing several concepts that OOSD approaches do not modularize appropriately. However, the current state-of-the art on AOSD suffers with software evolution, mainly because aspect definition can stop to work correctly when base elements evolve. A promising approach to deal with that problem is the definition of model-based pointcuts, where pointcuts are defined based on a conceptual model. That strategy makes pointcut less prone to software evolution than model-base elements. Based on that strategy, this work defines a conceptual model at high abstraction level where we can specify software patterns and architectures that through Model Driven Development techniques they can be instantiated and composed in architecture description language that allows aspect modeling at architecture level. Our MDD approach allows propagate concepts in architecture level to another abstraction levels (design level, for example) through MDA transformation rules. Also, this work shows a plug-in implemented to Eclipse platform called AOADLwithCM. That plug-in was created to support our development process. The AOADLwithCM plug-in was used to describe a case study based on MobileMedia System. MobileMedia case study shows step-by-step how the Conceptual Model approach could minimize Pointcut Fragile Problems, due to software evolution. MobileMedia case study was used as input to analyses evolutions on software according to software metrics proposed by KHATCHADOURIAN, GREENWOOD and RASHID. Also, we analyze how evolution in base model could affect maintenance on aspectual model with and without Conceptual Model approaches

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The approach Software Product Line (SPL) has become very promising these days, since it allows the production of customized systems on large scale through product families. For the modeling of these families the Features Model is being widely used, however, it is a model that has low level of detail and not may be sufficient to guide the development team of LPS. Thus, it is recommended add the Features Model to other models representing the system from other perspectives. The goals model PL-AOVgraph can assume this role complementary to the Features Model, since it has a to context oriented language of LPS's, which allows the requirements modeling in detail and identification of crosscutting concerns that may arise as result of variability. In order to insert PL-AOVgraph in development of LPS's, this paper proposes a bi-directional mapping between PL-AOVgraph and Features Model, which will be automated by tool ReqSys-MDD. This tool uses the approach of Model-Driven Development (MDD), which allows the construction of systems from high level models through successive transformations. This enables the integration of ReqSys-MDD with other tools MDD that use their output models as input to other transformations. So it is possible keep consistency among the models involved, avoiding loss of informations on transitions between stages of development

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This work presents a new three-phase transformer modeling suitable for simulations in Pspice environment, which until now represents the electrical characteristics of a real transformer. It is proposed the model comparison to a three-phase transformer modeling present in EMTP - ATP program, which includes the electrical and magnetic characteristics. In addition, a set including non-linear loads and a real three-phase transformer was prepared in order to compare and validate the results of this new proposed model. The three-phase Pspice transformer modeling, different from the conventional one using inductance coupling, is remarkable for its simplicity and ease in simulation process, since it uses available voltage and current sources present in Pspice program, enabling simulations of three-phase network system including the most common configuration, three wires in the primary side and four wires in the secondary side (three-phases and neutral). Finally, the proposed modeling becomes a powerful tool for three-phase network simulations due to its simplicity and accuracy, able to simulate and analyze harmonic flow in three-phase systems under balanced and unbalanced conditions.

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This paper presents a nonlinear model with individual representation of plants for the centralized long-term hydrothermal scheduling problem over multiple areas. In addition to common aspects of long-term scheduling, this model takes transmission constraints into account. The ability to optimize hydropower exchange among multiple areas is important because it enables further minimization of complementary thermal generation costs. Also, by considering transmission constraints for long-term scheduling, a more precise coupling with shorter horizon schedules can be expected. This is an important characteristic from both operational and economic viewpoints. The proposed model is solved by a sequential quadratic programming approach in the form of a prototype system for different case studies. An analysis of the benefits provided by the model is also presented. ©2009 IEEE.

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Modal analysis is widely approached in the classic theory of transmission line modeling. This technique is applied to model the three-phase representation of conventional electric systems taking into account their self and mutual electrical parameters. However the methodology has some particularities and inaccuracies for specific applications which are not clearly described in the basic references of this topic. This paper provides a thorough review of modal analysis theory applied to line models followed by an original and simple procedure to overcome the possible errors embedded in the modal decoupling through the three-phase system modeling. © 2012 IEEE.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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The hydroelectric power plant Hidroltuango represents a major expansion for the Colombian electrical system (with a total capacity of 2400 MW). This paper analyzes the possible interconnections and investments involved in connecting Hidroltuango, in order to strengthen the Colombian national transmission system. A Mixed Binary Linear Programming (MBLP) model was used to solve the Multistage Transmission Network Expansion Planning (MTEP) problem of the Colombian electrical system, taking the N-1 safety criterion into account. The N-1 safety criterion indicates that the transmission system must be expanded so that the system will continue to operate properly if an outage in a system element (within a pre-defined set of contingencies) occurs. The use of a MBLP model guaranteed the convergence with existing classical optimization methods and the optimal solution for the MTEP using commercial solvers. Multiple scenarios for generation and demand were used to consider uncertainties within these parameters. The model was implemented using the algebraic modeling language AMPL and solved using the commercial solver CPLEX. The proposed model was then applied to the Colombian electrical system using the planning horizon of 2018-2025. (C) 2014 Elsevier B.V. All rights reserved.

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Models are becoming increasingly important in the software development process. As a consequence, the number of models being used is increasing, and so is the need for efficient mechanisms to search them. Various existing search engines could be used for this purpose, but they lack features to properly search models, mainly because they are strongly focused on text-based search. This paper presents Moogle, a model search engine that uses metamodeling information to create richer search indexes and to allow more complex queries to be performed. The paper also presents the results of an evaluation of Moogle, which showed that the metamodel information improves the accuracy of the search.

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In electronic commerce, systems development is based on two fundamental types of models, business models and process models. A business model is concerned with value exchanges among business partners, while a process model focuses on operational and procedural aspects of business communication. Thus, a business model defines the what in an e-commerce system, while a process model defines the how. Business process design can be facilitated and improved by a method for systematically moving from a business model to a process model. Such a method would provide support for traceability, evaluation of design alternatives, and seamless transition from analysis to realization. This work proposes a unified framework that can be used as a basis to analyze, to interpret and to understand different concepts associated at different stages in e-Commerce system development. In this thesis, we illustrate how UN/CEFACT’s recommended metamodels for business and process design can be analyzed, extended and then integrated for the final solutions based on the proposed unified framework. Also, as an application of the framework, we demonstrate how process-modeling tasks can be facilitated in e-Commerce system design. The proposed methodology, called BP3 stands for Business Process Patterns Perspective. The BP3 methodology uses a question-answer interface to capture different business requirements from the designers. It is based on pre-defined process patterns, and the final solution is generated by applying the captured business requirements by means of a set of production rules to complete the inter-process communication among these patterns.

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In the last few years the resolution of numerical weather prediction (nwp) became higher and higher with the progresses of technology and knowledge. As a consequence, a great number of initial data became fundamental for a correct initialization of the models. The potential of radar observations has long been recognized for improving the initial conditions of high-resolution nwp models, while operational application becomes more frequent. The fact that many nwp centres have recently taken into operations convection-permitting forecast models, many of which assimilate radar data, emphasizes the need for an approach to providing quality information which is needed in order to avoid that radar errors degrade the model's initial conditions and, therefore, its forecasts. Environmental risks can can be related with various causes: meteorological, seismical, hydrological/hydraulic. Flash floods have horizontal dimension of 1-20 Km and can be inserted in mesoscale gamma subscale, this scale can be modeled only with nwp model with the highest resolution as the COSMO-2 model. One of the problems of modeling extreme convective events is related with the atmospheric initial conditions, in fact the scale dimension for the assimilation of atmospheric condition in an high resolution model is about 10 Km, a value too high for a correct representation of convection initial conditions. Assimilation of radar data with his resolution of about of Km every 5 or 10 minutes can be a solution for this problem. In this contribution a pragmatic and empirical approach to deriving a radar data quality description is proposed to be used in radar data assimilation and more specifically for the latent heat nudging (lhn) scheme. Later the the nvective capabilities of the cosmo-2 model are investigated through some case studies. Finally, this work shows some preliminary experiments of coupling of a high resolution meteorological model with an Hydrological one.

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This thesis investigates interactive scene reconstruction and understanding using RGB-D data only. Indeed, we believe that depth cameras will still be in the near future a cheap and low-power 3D sensing alternative suitable for mobile devices too. Therefore, our contributions build on top of state-of-the-art approaches to achieve advances in three main challenging scenarios, namely mobile mapping, large scale surface reconstruction and semantic modeling. First, we will describe an effective approach dealing with Simultaneous Localization And Mapping (SLAM) on platforms with limited resources, such as a tablet device. Unlike previous methods, dense reconstruction is achieved by reprojection of RGB-D frames, while local consistency is maintained by deploying relative bundle adjustment principles. We will show quantitative results comparing our technique to the state-of-the-art as well as detailed reconstruction of various environments ranging from rooms to small apartments. Then, we will address large scale surface modeling from depth maps exploiting parallel GPU computing. We will develop a real-time camera tracking method based on the popular KinectFusion system and an online surface alignment technique capable of counteracting drift errors and closing small loops. We will show very high quality meshes outperforming existing methods on publicly available datasets as well as on data recorded with our RGB-D camera even in complete darkness. Finally, we will move to our Semantic Bundle Adjustment framework to effectively combine object detection and SLAM in a unified system. Though the mathematical framework we will describe does not restrict to a particular sensing technology, in the experimental section we will refer, again, only to RGB-D sensing. We will discuss successful implementations of our algorithm showing the benefit of a joint object detection, camera tracking and environment mapping.