Technology roles and paths of influence in an ecosystem model of technology evolution

We propose a new conceptual model for understanding technology evolution that highlights dynamic and highly interdependent relationships among multiple technologies. We argue that, instead of considering technologies in isolation, technology evolution is best viewed as a dynamic system or ecosystem that includes a variety of interrelated technologies. By considering the interdependent nature of technology evolution, we identify three roles that technologies play within a technology ecosystem. These roles are components, products and applications, and support and infrastructure. Technologies within an ecosystem interact through these roles and impact each others’ evolution. We also classify types of interactions between technology roles, which we term paths of influence. We demonstrate the use of our proposed model through examples of wireless networking (Wi-Fi) technologies and a business mini-case on the digital music industry.

Design-code traceability recovery: selecting the basic linkage properties

Traceability ensures that software artifacts of subsequent phases of the development cycle are consistent. Few works have so far addressed the problem of automatically recovering traceability links between object-oriented (OO) design and code entities. Such a recovery process is required whenever there is no explicit support of traceability from the development process. The recovered information can drive the evolution of the available design so that it corresponds to the code, thus providing a still useful and updated high-level view of the system.

Automatic recovery of traceability links can be achieved by determining the similarity of paired elements from design and code. The choice of the properties involved in the similarity computation is crucial for the success of the recovery process. In fact, design and code objects are complex artifacts with several properties attached. The basic anchors of the recovered traceability links should be chosen as those properties (or property combinations) which are expected to be maintained during the transformation of design into code. This may depend on specific practices and/or the development environment, which should therefore be properly accounted for.

In this paper different categories of basic properties of design and code entities will be analyzed with respect to the contribution they give to traceability recovery. Several industrial software components will be employed as a benchmark on which the performances of the alternatives are measured.     

The Future of Enterprise System-Enabled Organizations

Companies are beginning to expect to gain strategic value from the implementation and operation of enterprise systems (ES). Currently dominating trends in business are sense-and-respond business models, globalization, corporate realignment, virtual organizations and accelerated product life-cycles. Available and evolving features of enterprise systems are summarized in a framework, concluding that present capabilities of enterprise systems correspond only to some extend to the new practices required to respond to these corporate challenges, and that ERP vendors strive to fill the gap. By integrating higher management functions enterprise systems will also impact on the practice of executives. The future work of an executive is illustrated by a fictitious example.     

Noise analysis compact differential evolution

This article proposes a compact algorithm for optimisation in noisy environments. This algorithm has a compact structure and employs differential evolution search logic. Since it is a compact algorithm, it does not store a population of solutions but a probabilistic representation of the population. This kind of algorithmic structure can be implemented in those real-world problems characterized by memory limitations. The degree of randomization contained in the compact structure allows a robust behaviour in the presence of noise. In addition the proposed algorithm employs the noise analysis survivor selection scheme. This scheme performs an analysis of the noise and automatically performs a re-sampling of the solutions in order to ensure both reliable pairwise comparisons and a minimal cost in terms of fitness evaluations. The noise analysis component can be reliably used in noise environments affected by Gaussian noise which allow an a priori analysis of the noise features. This situation is typical of problems where the fitness is computed by means of measurement devices. An extensive comparative analysis including four different noise levels has been included. Numerical results show that the proposed algorithm displays a very good performance since it regularly succeeds at handling diverse fitness landscapes characterized by diverse noise amplitudes.     

梨树断陷西丁家地区沙河子组—营城组沉积体系及演化过程研究

根据岩心、测录井、地震以及分析化验资料,运用沉积学原理和方法,对西丁家地区沙河子组—营城组时期沉积相和沉积体系进行综合研究。研究表明该区域在早白垩世主要发育湖泊、辫状河三角洲相等四大类沉积相及其亚相和微相。结合研究区＂西断东超＂型箕状断陷的构造演化特征,在沉积相认识的基础上组合出两大类沉积体系：从沙河子组沉积期至营城组沉积期,北部斜坡带由扇三角洲—水下扇沉积体系演化为辫状河三角洲—湖泊沉积体系;西部断阶带主要发育扇三角洲—水下扇沉积体系。     

Least squares support vector machines with tuning based on chaotic differential evolution approach applied to the identification of a thermal process

In the past decade, support vector machines (SVMs) have gained the attention of many researchers. SVMs are non-parametric supervised learning schemes that rely on statistical learning theory which enables learning machines to generalize well to unseen data. SVMs refer to kernel-based methods that have been introduced as a robust approach to classification and regression problems, lately has handled nonlinear identification problems, the so called support vector regression. In SVMs designs for nonlinear identification, a nonlinear model is represented by an expansion in terms of nonlinear mappings of the model input. The nonlinear mappings define a feature space, which may have infinite dimension. In this context, a relevant identification approach is the least squares support vector machines (LS-SVMs). Compared to the other identification method, LS-SVMs possess prominent advantages: its generalization performance (i.e. error rates on test sets) either matches or is significantly better than that of the competing methods, and more importantly, the performance does not depend on the dimensionality of the input data. Consider a constrained optimization problem of quadratic programing with a regularized cost function, the training process of LS-SVM involves the selection of kernel parameters and the regularization parameter of the objective function. A good choice of these parameters is crucial for the performance of the estimator. In this paper, the LS-SVMs design proposed is the combination of LS-SVM and a new chaotic differential evolution optimization approach based on Ikeda map (CDEK). The CDEK is adopted in tuning of regularization parameter and the radial basis function bandwith. Simulations using LS-SVMs on NARX (Nonlinear AutoRegressive with eXogenous inputs) for the identification of a thermal process show the effectiveness and practicality of the proposed CDEK algorithm when compared with the classical DE approach.     

A coevolutionary differential evolution with harmony search for reliability-redundancy optimization

Solving reliability-redundancy optimization problems via meta-heuristic algorithms has attracted increasing attention in recent years. In this paper, an effective coevolutionary differential evolution with harmony search algorithm (CDEHS) is proposed to solve the reliability-redundancy optimization problem by dividing the problem into a continuous part and an integer part. In CDEHS, two populations evolve simultaneously and cooperatively, where one population for the continuous part evolves by means of differential evolution while another population for the integer part evolves by means of harmony search. After half of the whole evolving process, the integer part stops evolving and provides the best solution to the other part for further evolving with differential evolution. Simulations results based on three typical problems and comparisons with some existing algorithms show that the proposed CDEHS is effective, efficient and robust for solving the reliability-redundancy optimization problem.     

适应度平均选择的离散差分演化算法

如何将差分演化算法用于离散领域是该领域的一个重要问题.提出一种适应度平均选择的离散差分演化算法,提出的算法中每个个体有均等的机会被选择用于引导算法的进化,这种选择方式有助于克服贪婪选择操作导致的种群多样性下降过快而使算法易陷入局部最优的问题.最后在多维背包问题上的实验结果表明提出的算法具有良好性能.     

差分进化微粒群优化算法-DEPSO

微粒群优化算法是一种新的进化计算技术,具有良好的优化性能,但是对于高维多模态函数,因进化后期微粒多样性的降低导致算法早熟收敛.文章提出的差分进化微粒群优化算法(DEPSO),拓宽了微粒信息传递的途径,增加了微粒的多样性,保证了算法的全局收敛.实验结果表明,DEPSO比PSO有更好的性能.     

Snake Mating Systems, Behavior, and Evolution: The Revisionary Implications of Recent Findings.

Sexual selection and mating systems profoundly influence the behavior and psychology of animals. Using their own studies of green anacondas (Eunectes murinus) and reviewing other recent studies, the authors conclude that incomplete data derived from a few well-studied snake species have led to general acceptance of polygyny as the dominant mating system in snakes. New data on behavior, paternity, and life history in a diverse taxonomic array of snakes support the view that polyandry is not only common in snakes but may have been the ancestral mating system. This interpretation helps to explain many seemingly paradoxical behavioral differences between lizards and snakes, such as the lack of territorial systems in most snakes and their frequent female-biased sexual size dimorphism. (PsycINFO Database Record (c) 2010 APA, all rights reserved)