The case for mesodata: An empirical investigation of an evolving database system

Database evolution can be considered a combination of schema evolution, in which the structure evolves with the addition and deletion of attributes and relations, together with domain evolution in which an attribute’s specification, semantics and/or range of allowable values changes. We present the results of an empirical investigation of the evolution of a commercial database system that measures and delineates between changes to the database that are (a) structural and (b) attribute domain related. We also estimate the impact that modelling using the mesodata approach would have on the evolving system.     

Affine invariant scale-space

A newaffine invariant scale-space for planar curves is presented in this work. The scale-space is obtained from the solution of a novel nonlinear curve evolution equation which admits affine invariant solutions. This flow was proved to be the affine analogue of the well knownEuclidean shortening flow. The evolution also satisfies properties such ascausality, which makes it useful in defining a scale-space. Using an efficient numerical algorithm for curve evolution, this continuous affine flow is implemented, and examples are presented. The affine-invariant progressive smoothing property of the evolution equation is demonstrated as well.     

软件体系结构动态演化的元胞自动机模型研究

目前软件体系结构动态演化的元胞自动机模型存在描述单一、元胞间关系不明确、没有详细阐述动态演化过程应用约束条件的缺点。针对这些不足进行相关的研究,重新定义了软件体系结构动态演化的扩展元胞自动机模型,基于扩展元胞自动机模型结合演化应用约束条件,分析了软件体系结构的动态演化过程,运用元胞间控制约束条件和行为相关约束条件来正确地指导SA动态演化。提出了动点稳态转移的概念,对演化程度和一致性进行定义分析,此方法比以往的元胞自动机模型更能准确指导SA动态演化,促进SA动态演化的进一步研究。通过案例验证了该方法的应用价值和可行性,可以更全面地应用于软件体系结构的动态演化。     

决策演化集的三支博弈

决策演化集是处理决策规则在时间序列上的演化问题的理论。决策演化集将着眼点从静态的决策信息系统转移到动态的时间序列上,研究决策信息系统在随着时间变化时的演化规律,是一种新的决策研究方法。目前,在决策演化集的标准结构下存在着一些问题,例如预测得到的属性较少,预测夹角偏大等问题。决策演化集的三支结构在提高预测准确度方面是一个有效的方法,但其阈值α和β是固定的。然而,在时间序列下数据是不停变化的,固定的α和β并不能很好地适应这种变化。利用博弈论的方法来调整修改α和β使其适应决策信息系统在时间序列下的变化,并通过实例来演示这种调整。     

Convexity Rule for Shape Decomposition Based on Discrete Contour Evolution

We concentrate here on decomposition of 2D objects into meaningfulparts of visual form, orvisual parts. It is a simple observation that convex parts of objects determine visual parts. However, the problem is that many significant visual parts are not convex, since a visual part may have concavities. We solve this problem by identifying convex parts at different stages of a proposed contour evolution method in which significant visual parts will become convex object parts at higher stages of the evolution. We obtain a novel rule for decomposition of 2D objects into visual parts, called the hierarchical convexity rule, which states that visual parts are enclosed by maximal convex (with respect to the object) boundary arcs at different stages of the contour evolution. This rule determines not only parts of boundary curves but directly the visual parts of objects. Moreover, the stages of the evolution hierarchy induce a hierarchical structure of the visual parts. The more advanced the stage of contour evolution, the more significant is the shape contribution of the obtained visual parts.     

The pervasiveness of evolution in GRUMPS software

This paper describes the evolution of the design and implementation of a distributed run‐time system that itself is designed to support the evolution of the topology and implementation of an executing, distributed system. The three different versions of the run‐time architecture that have been designed and implemented are presented, together with how each architecture addresses the problems of topological and functional evolution. In addition, the reasons for the rapid evolution of the design and implementation of the architecture are also described. From the lessons learned in both evolving the design of the architecture and in trying to provide a run‐time system that can support run‐time evolution, this paper discusses two generally applicable observations: evolution happens all the time, and it is not possible to anticipate how systems will evolve as designs; and large, run‐time systems do not follow a predictable path. In addition to this, rapid prototyping has proved to be extremely useful in the production of the three architectures; this kind of prototyping has been made much easier by designing the core set of Java abstractions in terms of interfaces; and building an architecture that allows as many decisions as possible to be made at run‐time which has produced a support system that is more responsive to the user as well as the distributed environment in which it is executing. Copyright © 2003 John Wiley & Sons, Ltd.     

Architectural evolution of FamiWare using cardinality-based feature models

ContextAmbient Intelligence systems domain is an outstanding example of modern systems that are in permanent evolution, as new devices, technologies or facilities are continuously appearing. This means it would be desirable to have a mechanism that helps with the propagation of evolution changes in deployed systems.ObjectiveWe present a software product line engineering process to manage the evolution of FamiWare, a family of middleware for ambient intelligence environments. This process drives the evolution of FamiWare middleware configurations using cardinality-based feature models, which are especially well suited to express the structural variability of ambient intelligence systems.MethodFamiWare uses cardinality-based feature models and clonable features to model the structural variability present in ambient intelligence systems, composed of a large variety of heterogeneous devices. Since the management evolution of configurations with clonable features is manually untreatable due to the high number of features, our process automates it and propagates changes made at feature level to the architectural components of the FamiWare middleware. This is a model driven development process as the evolution management, the propagation of evolution changes and the code generation are performed using some kind of model mappings and transformations. Concretely we present a variability modelling language to map the selection of features to the corresponding FamiWare middleware architectural components.ResultsOur process is able to manage the evolution of cardinality-based feature models with thousands of features, something which is not possible to tackle manually. Thanks to the use of the variability language and the automatic code generation it is possible to propagate and maintain a correspondence between the FamiWare architectural model and the code. The process is then able to calculate the architectural differences between the evolved configuration and the previous one. Checking these differences, our process helps to calculate the effort needed to perform the evolution changes in the customized products. To perform those tasks we have defined two operators, one to calculate the differences between two feature model configurations and another to create a new configuration from a previous one.ConclusionOur process automatically propagates the evolution changes of the middleware family into the existing configurations where the middleware is already deployed and also helps us to calculate the effort in performing the changes in every configuration. Finally, we validated our approach, demonstrating the functioning of the defined operators and showing that by using our tool we can generate evolved configurations for FamiWare with thousands of cloned features, for several case studies.     

A generalized finite-difference time-domain quantum method for the N-body interacting Hamiltonian

The Quantum Finite-Difference Time-Domain (FDTD-Q) method is a numerical method for solving the time evolution of the Schrödinger equation. It can be applied to systems of interacting particles, allowing for realistic simulations of quantum mechanics of various experimental systems. One of the drawbacks of the method is that divergences in the numerical evolution occur rather easily in the presence of interactions, which necessitates a large number of evolution steps or imaginary time evolution. We present a generalized (GFDTD-Q) method for solving the time-dependent Schrödinger equation including interactions between the particles. The new scheme provides a more relaxed condition for stability when the finite difference approximations for spatial derivatives are employed, as compared with the original FDTD-Q scheme. We demonstrate our scheme by simulating the time evolution of a two-particle interaction Hamiltonian. Our results show that the generalized method allows for stable time evolutions, in contrast to the original FDTD-Q scheme which produces a divergent solution.