Identifying business components is the basis of component-based software engineering. Many approaches, including cluster analysis and concept analysis, have been proposed to identify components from business models. These approaches classify business elements into a set of components by analyzing their properties. However, most of them do not consider the difference in their properties for the business elements, which may decrease the accuracy of the identification results. Furthermore, component identification by partitioning business elements cannot reflect which features are responsible for the generation of certain results. This paper deals with a new approach for component identification from business models using fuzzy formal concept analysis. First, the membership between business elements and their properties is quantified and transformed into a fuzzy formal context, from which the concept lattice is built using a refined incremental algorithm. Then the components are selected from the concepts according to the concept dispersion and distance. Finally, the effectiveness and efficiency are validated by applying our approach in the real-life cases and experiments.

Performance and power consumption are two important design objectives for data centers consisting of thousands or tens of thousands of disks (or disk arrays). To leverage the two objectives, in this study we propose a multi-version disk array (MDA). The main idea of MDA is to exploit the I/O workload characteristics to guide the replication strategy by replicating multiple versions of the popular data blocks and simply offloading the write data to the free space of the reserved version region, thus achieving high performance in the burst period and low power consumption in the idle period. Our prototype implementation of MDA and the performance evaluations show that the performance of MDA outperforms that of traditional RAID10 by up to 34.4% and 42.3% in terms of the average response time for the online transaction processing (OLTP) application I/O and search engine I/O, respectively. Moreover, the energy efficiency of MDA outperforms that of RAID10 by up to 48.7% and 36.4%, respective to the aforementioned measures.

With the growing use of service-oriented architecture for designing next generation software systems, the service composition problem and its execution complexity have become even more important in responding to different user requests. The gravitational search algorithm is one of the latest heuristic algorithms. It has a number of distinguishing features, such as rapid convergence, lower memory usage, and the use of particular parameters, for instance, the distance between the solutions. In this paper, we propose a model for the optimization of the Web service composition problem based on qualitative measures and the gravitational search algorithm. To determine the efficacy of this proposed model we solve the problem with the particle swarm optimization algorithm for comparison. Simulation results show that the gravitational search algorithm has a high potential and substantial efficiency in finding the best combination of Web services.

In video applications, real-time image scaling techniques are often required. In this paper, an efficient implementation of a scaling engine based on 4×4 cubic convolution is proposed. The cubic convolution has a better performance than other traditional interpolation kernels and can also be realized on hardware. The engine is designed to perform arbitrary scaling ratios with an image resolution smaller than 2560×1920 pixels and can scale up or down, in horizontal or vertical direction. It is composed of four functional units and five line buffers, which makes it more competitive than conventional architectures. A strict fixed-point strategy is applied to minimize the quantization errors of hardware realization. Experimental results show that the engine provides a better image quality and a comparatively lower hardware cost than reference implementations.

We employ a multiuser detection (MUD) method using a novel genetic algorithm (GA) based on complementary error function mutation (CEFM) and a differential algorithm (DA) for ultra-wideband (UWB) systems. The proposed MUD method is termed CEFM-GA DA for short. We describe the scheme of CEFM-GA DA, analyze its algorithm, and compare its computational complexity with other MUDs. Simulation results show that a significant performance gain can be achieved by employing the proposed CEFM-GA DA, compared with successive interference cancellation (SIC), parallel interference cancellation (PIC), conventional GA, and CEFM-GA without DA, for UWB systems in lognormal fading channel. Moreover, CEFM-GA DA not only reduces computational complexity relative to conventional GA and CEFM-GA without DA, but also improves bit error rate (BER) performance.

In this paper, novel dual-band (DB) branch-line couplers (BLCs) employing a composite right/left handed transmission line (CRLH TL) and fractal geometry are presented for the first time. The CRLH TL, with specified characteristic impedance and phase shift, consists of lumped elements for the left handed (LH) part and fractal-shaped microstrip lines (MLs) for the right handed (RH) part, which can be designed separately. Two designed BLCs are involved in size reduction, one using a 3/2 fractal curve of first iteration, the other constructed based on a hybrid shape of fractal and meandered lines. A miniaturized principle for CRLH TL realization is derived and an exact design method for fractal implementation is developed. For verification, an example coupler was fabricated and measured. Consistent numerical and experimental results confirmed the design concept, showing that the BLCs obtain DB behavior centered at 0.9 GHz and 1.8 GHz respectively with good in-band performance, except for slightly larger coupled insertion loss for the hybrid-shaped BLC case. In addition, the proposed fractal- and hybrid-shaped BLCs obtained a 49.7% and 64.1% size reduction respectively relative to their conventional counterparts working in the lower band. The most important contributions of this article are the demonstration of compatibility between the fractal and CRLH TL techniques and the provision of an alternative approach and a new concept for designing devices.

A DC hybrid power source composed of photovoltaic cells as the main power source, Li-ion battery storage as the secondary power source, and power electronic interface, is modeled based on port-controlled Hamiltonian systems and Euler-Lagrange framework. Subsequently, passivity-based controllers are synthesized. Local asymptotic stability is ensured as well. In addition, a power management system is designed to manage power flow between components. Modeling and simulation of the proposed hybrid power source is accomplished using MATLAB/Simulink. Our interest is focused on the comparison of the two passivity-based control methods and their use in hybrid power systems.