22,702 research outputs found
Invertible Program Restructurings for Continuing Modular Maintenance
When one chooses a main axis of structural decompostion for a software, such
as function- or data-oriented decompositions, the other axes become secondary,
which can be harmful when one of these secondary axes becomes of main
importance. This is called the tyranny of the dominant decomposition. In the
context of modular extension, this problem is known as the Expression Problem
and has found many solutions, but few solutions have been proposed in a larger
context of modular maintenance. We solve the tyranny of the dominant
decomposition in maintenance with invertible program transformations. We
illustrate this on the typical Expression Problem example. We also report our
experiments with Java and Haskell programs and discuss the open problems with
our approach.Comment: 6 pages, Early Research Achievements Track; 16th European Conference
on Software Maintenance and Reengineering (CSMR 2012), Szeged : Hungary
(2012
Towards Consistency Management for a Business-Driven Development of SOA
The usage of the Service Oriented Architecture
(SOA) along with the Business Process Management has emerged
as a valuable solution for the complex (business process driven)
system engineering. With a Model Driven Engineering where the
business process models drive the supporting service component
architectures, less effort is gone into the Business/IT alignment
during the initial development activities, and the IT developers
can rapidly proceed with the SOA implementation. However, the
difference between the design principles of the emerging domainspecific
languages imposes serious challenges in the following
re-design phases. Moreover, enabling evolutions on the business
process models while keeping them synchronized with the underlying
software architecture models is of high relevance to the key
elements of any Business Driven Development (BDD). Given a
business process update, this paper introduces an incremental
model transformation approach that propagates this update
to the related service component configurations. It, therefore,
supports the change propagation among heterogenous domainspecific
languages, e.g., the BPMN and the SCA. As a major
contribution, our approach makes model transformation more
tractable to reconfigure system architecture without disrupting its
structural consistency. We propose a synchronizer that provides
the BPMN-to-SCA model synchronization with the help of the
conditional graph rewriting
Reconstruction of Hamiltonians from given time evolutions
In this paper we propose a systematic method to solve the inverse dynamical
problem for a quantum system governed by the von Neumann equation: to find a
class of Hamiltonians reproducing a prescribed time evolution of a pure or
mixed state of the system. Our approach exploits the equivalence between an
action of the group of evolution operators over the state space and an adjoint
action of the unitary group over Hermitian matrices. The method is illustrated
by two examples involving a pure and a mixed state.Comment: 14 page
An enhanced artificial neural network with a shuffled complex evolutionary global optimization with principal component analysis
The classical Back-Propagation (BP) scheme with gradient-based optimization in training Artificial Neural Networks (ANNs) suffers from many drawbacks, such as the premature convergence, and the tendency of being trapped in local optimums. Therefore, as an alternative for the BP and gradient-based optimization schemes, various Evolutionary Algorithms (EAs), i.e., Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Simulated Annealing (SA), and Differential Evolution (DE), have gained popularity in the field of ANN weight training. This study applied a new efficient and effective Shuffled Complex Evolutionary Global Optimization Algorithm with Principal Component Analysis – University of California Irvine (SP-UCI) to the weight training process of a three-layer feed-forward ANN. A large-scale numerical comparison is conducted among the SP-UCI-, PSO-, GA-, SA-, and DE-based ANNs on 17 benchmark, complex, and real-world datasets. Results show that SP-UCI-based ANN outperforms other EA-based ANNs in the context of convergence and generalization. Results suggest that the SP-UCI algorithm possesses good potential in support of the weight training of ANN in real-word problems. In addition, the suitability of different kinds of EAs on training ANN is discussed. The large-scale comparison experiments conducted in this paper are fundamental references for selecting proper ANN weight training algorithms in practice
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Lattice modeling of excavation damage in argillaceous clay formations: Influence of deformation and strength anisotropy
This paper presents modeling of mechanical anisotropy in argillaceous rocks using an irregular lattice modeling approach, namely the rigid-body-spring network. To represent the mechanical anisotropy, new schemes are implemented in the modeling framework. The directionality of elastic deformation is resolved by modifying the element formulation with anisotropic elastic properties. The anisotropy of strength and failure characteristics is facilitated by adopting orientation-dependent failure criteria into the failure model. The verification of the improved modeling procedures is performed against theoretical model predictions for unconfined compression tests with various bedding orientations. Furthermore, excavation damage and fracturing processes in rock formations are simulated for different geomechanical configurations, such as rock anisotropy and tectonic heterogeneity. The simulated excavation damage characteristics are realistic and comparable with the actual field observation at a tunnel located in an argillaceous clay formation. The simulation results provide insights into the excavation damage zone phenomena with an explicit representation of fracturing processes
Proposition of a PLM tool to support textile design: A case study applied to the definition of the early stages of design requirements
The current climate of economic competition forces businesses to adapt more than ever to the expectations of their customers. Faced with new challenges, practices in textile design have evolved in order to be able to manage projects in new work environments. After presenting a state of the art overview of collaborative tools used in product design and making functional comparison between PLM solutions, our paper proposes a case study for the development and testing of a collaborative platform in the textile industry, focusing on the definition of early stages of design needs. The scientific contributions presented in this paper are a state of the art of current PLM solutions and their application in the field of textile design; and a case study where we will present, define, and test the mock-up of a collaborative tool to assist the early stages, based on identified intermediary representations
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