Java multimedia telecollaboration

Using Java-based tools in multimedia collaborative environments accessed over the Internet can increase an application's client base. Most operating systems support Java, and its "compile once-run everywhere" architecture is easy to maintain and update. The Java-based tools presented here let users share Internet resources, including resources originally designed for single use.     

Extending the Kernighan/Lin Heuristic for Hardware and Software Functional Partitioning

The Kernighan/Lin graph partitioning heuristic, also known as min-cut or group migration, has been extended over several decades very successfully for circuit partitioning. Those extensions customized the heuristic and its associated data structure to rapidly compute the minimum-cut metric central to circuit partitioning; as such, those extensions are not directly applicable to other problems. In this paper, we extend the heuristic for functional partitioning, which in turn can solve the much investigated codesign problem of partitioning a system's coarse-grained functions among hardware and software components. The key extension customizes the heuristic and data structure to rapidly compute execution-time and communication metrics, crucial to hardware and software partitioning, and leads to near-linear time-complexity and excellent resulting quality. Another extension uses a new criteria for terminating the heuristic, eliminating time-consuming and unnecessary fine-tuning of a partition. Our experiments demonstrate extremely fast execution times (just a few seconds) with results matched only by the slower simulated annealing heuristic, meaning that the extended Kernighan/Lin heuristic will likely prove hard to beat for hardware and software functional partitioning.     

A complete VARMA modelling methodology based on scalar components

Abstract. This article proposes an extension to scalar component methodology for the identification and estimation of VARMA models. The complete methodology determines the exact positions of all free parameters in any VARMA model with a predetermined embedded scalar component structure. This leads to an exactly identified system of equations that is estimated using full information maximum likelihood.     

Classification and trend analysis of UML books (1997–2009)

Technical books of each subject area denote the level of maturity and knowledge demand in that area. According to the Google Books database, about 208 Unified Modeling Language (UML) books have been published from its inception in 1997 until 2009. While various book reviews are frequently published in various sources (e.g., IEEE Software Bookshelf), there are no studies to classify UML books into meaningful categories. Such a classification can help researchers in the area to identify trends and also reveal the level of activity in each sub-area of UML. The statistical survey reported in this article intends to be a first step in classification and trend analysis of the UML books published from 1997 to 2009. The study also sheds light on the quantity of books published in different focus areas (e.g., UML’s core concepts, patterns, tool support, Object Constraint Language and Model-Driven Architecture) and also on different application domains (e.g., database modeling, web applications, and real-time systems). The trends of book publications in each sub-area of UML are also used to track the level of maturity, to identify possible Hype cycles and also to measure knowledge demand in each area.     

An H∞non‐fragile observer‐based adaptive sliding mode controller design for uncertain fractional‐order nonlinear systems with time delay and input nonlinearity

In this paper the problem of non‐fragile adaptive sliding mode observer design is addressed for a class of nonlinear fractional‐order time‐delay systems with uncertainties, external disturbance, exogenous noise, and input nonlinearity. An H_∞ observer‐based adaptive sliding mode control considering the non‐fragility of the observer is proposed for this system. The sufficient asymptotic stability conditions are derived in the form of linear matrix inequalities. It is proven that the sliding surface is reachable in finite time. An illustrative example is provided which corroborates the effectiveness of the theoretical results.     

Conceptual aspects of geometric quantum computation

Geometric quantum computation is the idea that geometric phases can be used to implement quantum gates, i.e., the basic elements of the Boolean network that forms a quantum computer. Although originally thought to be limited to adiabatic evolution, controlled by slowly changing parameters, this form of quantum computation can as well be realized at high speed by using nonadiabatic schemes. Recent advances in quantum gate technology have allowed for experimental demonstrations of different types of geometric gates in adiabatic and nonadiabatic evolution. Here, we address some conceptual issues that arise in the realizations of geometric gates. We examine the appearance of dynamical phases in quantum evolution and point out that not all dynamical phases need to be compensated for in geometric quantum computation. We delineate the relation between Abelian and non-Abelian geometric gates and find an explicit physical example where the two types of gates coincide. We identify differences and similarities between adiabatic and nonadiabatic realizations of quantum computation based on non-Abelian geometric phases.     

Fast implementation of dense stereo vision algorithms on a highly parallel SIMD architecture

In this paper, we present faster than real-time implementation of a class of dense stereo vision algorithms on a low-power massively parallel SIMD architecture, the CSX700. With two cores, each with 96 Processing Elements, this SIMD architecture provides a peak computation power of 96 GFLOPS while consuming only 9 Watts, making it an excellent candidate for embedded computing applications. Exploiting full features of this architecture, we have developed schemes for an efficient parallel implementation with minimum of overhead. For the sum of squared differences (SSD) algorithm and for VGA (640 × 480) images with disparity ranges of 16 and 32, we achieve a performance of 179 and 94 frames per second (fps), respectively. For the HDTV (1,280 × 720) images with disparity ranges of 16 and 32, we achieve a performance of 67 and 35 fps, respectively. We have also implemented more accurate, and hence more computationally expensive variants of the SSD, and for most cases, particularly for VGA images, we have achieved faster than real-time performance. Our results clearly demonstrate that, by developing careful parallelization schemes, the CSX architecture can provide excellent performance and flexibility for various embedded vision applications.     

Agent-based time delay margin in consensus of multi-agent systems by an event-triggered control method: Concept and computation

This paper deals with defining the concept of agent-based time delay margin and computing its value in multi-agent systems controlled by event-triggered based controllers. The agent-based time delay margin specifying the time delay tolerance of each agent for ensuring consensus in event-triggered controlled multi-agent systems can be considered as complementary for the concept of (network) time delay margin, which has been previously introduced in some literature. In this paper, an event-triggered control method for achieving consensus in multi-agent systems with time delay is considered. It is shown that the Zeno behavior is excluded by applying this method. Then, in a multi-agent system controlled by the considered event-triggered method, the concept of agent-based time delay margin in the presence of a fixed network delay is defined. Moreover, an algorithm for computing the value of the time delay margin for each agent is proposed. Numerical simulation results are also provided to verify the obtained theoretical results.     

Effect of High‐Energy Ball Milling on Mechanical Properties of the Mg–Nb Composites Fabricated through Powder Metallurgy Process

New biocompatible and biodegradable Mg–Nb composites used as bone implant materials are fabricated through powder metallurgy process. Mg–Nb mixture powders are prepared through mechanical milling and manual mixing. Then, the Mg–Nb composites are fabricated through cold press and sintering processes. The effect of mechanical milling and Nb particles as reinforcements on the microstructures and mechanical properties of Mg–Nb composites are investigated. The mechanical milling process is found to be effective in reducing the size of Mg and Nb particles, distributing the Nb particles uniformly in the Mg matrix and obtaining Mg–Nb composite particles. The Mg–Nb composite particles can be bound together firmly during the sintering process, result in Mg–Nb composite structures with no intermetallic formation, lower porosity, and higher mechanical properties compared to composites prepared through manual mixing. Interestingly, the mechanical properties of manually mixed Mg–Nb composites appear to be even lower than that of pure Mg.

     

Model updating of multistory shear buildings for simultaneous identification of mass,stiffness and damping matrices using two different soft-computing methods

In this research, two novel methods for simultaneous identification of mass–damping–stiffness of shear buildings are proposed. The first method presents a procedure to estimate the natural frequencies, modal damping ratios, and modal shapes of shear buildings from their forced vibration responses. To estimate the coefficient matrices of a state-space model, an auto-regressive exogenous excitation (ARX) model cooperating with a neural network concept is employed. The modal parameters of the structure are then evaluated from the eigenparameters of the coefficient matrix of the model. Finally, modal parameters are used to identify the physical/structural (i.e., mass, damping, and stiffness) matrices of the structure. In the second method, a direct strategy of physical/structural identification is developed from the dynamic responses of the structure without any eigenvalue analysis or optimization processes that are usually necessary in inverse problems. This method modifies the governing equations of motion based on relative responses of consecutive stories such that the new set of equations can be implemented in a cluster of artificial neural networks. The number of neural networks is equal to the number of degree-of-freedom of the structure. It is shown the noise effects may partially be eliminated by using high-order finite impulse response (FIR) filters in both methods. Finally, the feasibility and accuracy of the presented model updating methods are examined through numerical studies on multistory shear buildings using the simulated records with various noise levels. The excellent agreement of the obtained results with those of the finite element models shows the feasibility of the proposed methods.