In this paper, noise reduction performance of the Generalized Side-lobe Canceller (GSC) algorithm and its performance degradation under reverberant environments are briefly reviewed. An acoustic echo canceller (AEC) is employed as a pre-processor for GSC noise reduction algorithm in order to improve the noise reduction performance of the GSC especially in highly reverberant environments where GSC alone fails to work properly. The proposed AEC-GSC algorithm consists of an AEC pre-processor, which includes Segment Variable Stepsize Proportionate Normalized Least Mean Square (SVS-PNLMS) algorithm recently proposed, and the GSC noise reduction algorithm. The performance of both AEC-GSC and GSC alone is evaluated through computer simulations, using real speech recordings in reverberant room environment. Through different computer simulations it is demonstrated that the proposed AEC-GSC structure performs better than GSC alone in terms of speech distortion parameters and ERLE. It also presents a better tracking behavior between the pause intervals during a speech signal due to using the SVS-PNLMS algorithm in its AEC section.

Input-Queued switch architecture has become attractive for implementing high performance routers because the switching fabric and the buffer need not run at a multiple of input link's rate. It is challenging to provide a scheduling technique that is both highly efficient and fair in resource allocation. We propose an iterative Cell- based Fair scheduling (iCFS) scheme, based on SLIP that support fair bandwidth distribution among flows and achieves asymptotically 100 percent throughput.

Many definitive and approximate methods have been so far proposed for the construction of an optimal binary search tree. One such method is the use of evolutionary algorithms with satisfactorily improved cost efficiencies. This paper will propose a new genetic algorithm for constructing a near optimal binary search tree. In this algorithm, a new greedy method is used for the crossover of chromosomes while a new way is also developed for inducing mutation in them. Practical results show a rapid and desirable convergence towards the near optimal solution. The use of a heuristic to create not so costly chromosomes as the first offspring, the greediness of the crossover, and the application of elitism in the selection of future generation chromosomes are the most important factors leading to near optimal solutions by the algorithm at desirably high speeds. Due to the practical results, increasing problem size does not cause any considerable difference between the solution obtained from the algorithm and exact solution. Task parallelism causes an improving effect on proposed algorithm.

This research addresses computer network routing based on recursive modeling method (RMM). In our proposed method, each router as an intelligent agent uses RMM tree-like structure to make a rational and intelligent decision on transmitting packages. This decision is made based on the models of other routers in the network and its belief about them. However, as the network conditions vary with time, the needs of updating each routers belief about others can not be neglected. To achieve this goal, Bayesian law is used to update routers belief about others. To validate the proposed method, we test it as a computer simulation. The results show that this method increases the network performance by decreasing the network overhead arising from routers packages. Additionally, as the network dynamics increases, employing Bayesian law helps the routers to quickly adapt to the new conditions.

This research addresses a new iterative geometrical noise cancellation method for closed-form camera pose estimation based on collinearity theory. We first explain how to estimate camera position and it’s orientation by employing extra nonsingular point of the edge line of the landmark’s corner through a closed-form geometrical pose estimation algorithm. Then, we propose a new iterative noise cancellation algorithm to reduce the estimation error of camera transaction matrix, which has the most portion in camera pose estimation errors. To validate our proposed method, we test it as a computer simulation. The results show that this method is efficient, accurate and robustness. But the drawback is that the camera rotation matrix, which used in noise cancellation algorithm, may not always be inverseable.

Considerable speed of process engineering improvement and the consequent impact on workflow management systems has brought up a new wave of researches in reconsidering current solutions for workflow systems and proposing more brilliant ideas for such type of software systems. Agent technology as a semi-matured methodology of software design, has introduced itself as a promising approach in building complex software systems. In this paper we presented a simple ready for use agent architecture which can be deployed in many types of workflow automations.

Due to the rapid growth of electronic environments (such as internet) much research is currently being performed on autonomous trading mechanisms. Also in the last few years there has been an increasing interest from the agent community in the use of techniques from decision theory and game theory. Our paper connects theses two fields. In real world, when two agents negotiate, it seems rational that they emphasize on their highest priorities first. We give a strategy based on the 7 types presented by Raymund J. Lin and Seng-cho T. Chou [7] in which an agent can gain more profit by sacrificing or delaying some high priority tasks. The focus of this paper is on negotiation of self interest agents.

Prediction of reliability in early phases of software development is one of the discussions which has been attracting more and more attentions during the recent three decades. Techniques and models are mostly used at the test phase; there are only a few models that are employed at early phase of software development. Early prediction, however, is very important for better prognosis and management of risks. In this paper we propose an approach for software reliability early prediction based on software behavior. The major difference between our approach and those of others is the fact that we use a formal method, called Viewcharts [1], to specify the behavior of software systems.

The goal of network topological design is to find a minimum cost configuration of network components. Design of access network is discussed here. The objective is minimizing the access network cost by means of finding optimal number and location of concentrators. The network cost consists of the concentrators cost and cost of access links, that connecting terminals to the concentrators. Here, contrary to most of other methods, which use candidate locations for concentrators, the search space is continuous. Solution to the problem is improved in this article. The problem is solved using a type of self organizing neural network called Growing Neural Network. In this method, terminal locations are used as input of neural network and self organizing feature leads to optimal solution. Furthermore, an improved version of the COM algorithm is proposed. Improvement is achieved by means of applying cost constraint in cluster merging phase. The simulation results for different networks with various cost parameters show the new methods achieve the better performance than that of previous methods.

The Anticipatory Classifier System (ACS) employs the learning classifier system framework and the learning theory of anticipation behavioral control. The resulting evolutionary system can build an internal environmental model and then applies reinforcement learning techniques to develop an optimal set of classifiers. XCSF is another novel version of learning classifier systems (LCS) which introduced the concept of computable classifier prediction and successfully applied to function-approximation problems. In this paper, we apply ACS to function approximation. ACSF is a new version of ACS introduced to develop more accurate approximations.

In this paper, we propose a method that uses domain engineering concepts to design components in a minimizedextendable manner and to provide required platform to implement these components, we propose a component model called AECM that uses aspect-oriented method besides other techniques to improve component reusability. AECM proposes a component definition language to define component specifications that component behaviors can be minimized or extended through the language. In addition, AECM proposes an assembly definition language to wire components; these two languages make software architecture. In this component model, aspects are some kind of component and all component concepts are applicable to them. AECM categorizes aspects of a component to two categories: 1) built-in and extension aspects, 2) inter-components aspects and intra-component aspects, and supports them in different ways to control applicable changing to the component. AECM supports definition of weave time and runtime aspect application rules in a way that any changes of the rules will not affect the component implementation.

A SRLG is a group of network links that share a common physical resource whose failure will cause the failure of all links of the group. To protect a logical connection in a network from a single SRLG failure, two different paths are usually assigned to the connection. The two paths must be disjoint to avoid synchronous failure. In this paper, we extend a high-performance link-disjoint routing algorithm called CoLE to SRLG-disjoint routing. The analysis and the simulation results demonstrate improvement over the previous algorithms.

We report on our work on improving the performance of collective operations in MPICH on clusters connected by switched networks. For each collective operation, we use multiple algorithms depending on the message size, with the goal of minimizing latency for short messages and minimizing bandwidth usage for long messages. Although we have implemented new algorithms for all MPI collective operations, because of limited space we describe only the algorithms for allgather, broadcast,reduce-scatter, and reduce. We present performance results using the SKaMPI benchmark on a Myrinet-connected Linux cluster and an IBM . In all cases, the new algorithms significantly outperform the old algorithms used in MPICH on the Myrinet cluster, and, in many cases, they outperform the algorithms used in IBM’s MPI .

Profiles of an object provide rich information about its geometry and can be used for shape reconstruction under known object movement. In this paper we propose a method to estimate the motion from space curves. The moving object is captured by two cameras during time. A robust curve stereo matching algorithm is employed to extract the precise location of convinced space curves for any sequence. By tracking of the space curves, the rigid motion estimation of object can be accomplished. So, by unifying the large number of virtual cameras, the rays constructed from silhouette are intersected to recover the fine visual hull. Because of using the curve matching scheme instead of color matching, the proposed method is less sensitive to color adjustment between cameras and illumination changes of light source. Our method is applicable also to the low-texture object.

This paper study and analyzes of effective parameters on camera pose estimation process for virtual studio. The camera pose estimation process, the process of estimating camera extrinsic parameters, is based on closedform geometrical approaches which is used the benefic of simple corners detection of 3D cubic-like virtual studio’s landmarks. Our studies include all landmarks characteristic parameters like landmark’s lengths, landmark’s corners angles and its installation position errors; and some camera parameters like lens’ focal length and CCD resolution. We study and analyze all these parameters efficiency on camera extrinsic parameters including camera rotation and position matrixes through computer simulation. We found that the camera transaction matrix is infected more than other camera extrinsic parameters by the noise of effective pose estimation parameters.

The complexity of the modern chips is rising and fundamental changes in systems design are necessary. Systemon- a-Programmable-Chip (SOPC) concept is bringing a major revolution in the design of integrated circuits, due to the flexibility it provides and complexity it caters to. Particle Swarm Optimization (PSO) is a new powerful function optimizer that is used successfully to solve problems in numerous fields. A major downside of PSO and many evolutionary algorithms is that they have essential difficulties in their huge computation time due to sequential execution in software implementation. By implementing a modified particle swarm optimizer in hardware, many of the computations can be preformed simultaneously, significantly reducing computation time compared to software. In this paper, a SOPC-based PSO framework is proposed. The obtained results indicate a speedup of up to 40 times in the elapsed computation time.

As the designs get more complex, more sophisticated verification methodologies are required. At higher levels of abstraction, design and verification methodologies are required to minimize the cost of electronic product design. In this paper we integrate an assertion-based verification methodology with our objectoriented system-level synthesis methodology. Functional and performance assertions, based on Property Specification Language (PSL) and Logic of Constrains (LOC) are written during design process. Trace checkers are automatically generated to validate particular simulation runs or to analyze their performance characteristic(s). Following the case study, we demonstrate that the assertion-based verification is highly useful for both functional and performance system-level verification.

We introduce a new tool for probabilistic model checking, GPMC, with a graphical user interface, and compare it with existing well-known tool in this scope PRISM. Some case studies are presented to show the efficiency and performance of it against PRISM. Two of these case studies are collected from several examples that were used for testing PRISM and another one is an extended simple example of a DTMC. We explain in each case study the powers and weaknesses of these tools, and find new methods for solving weaknesses.

In this paper, we present a cycle-accurate co-simulation environment developed for verification and performance evaluation of OO-ASIP in our ODYSSEY design methodology. This environment is composed of a processor Instruction Set Simulator (ISS) integrated with a hardware simulator and communicate with it through socket connections. We demonstrate the effect of our co-simulation method in increasing speed of simulation without missing cycle accuracy of results by means of two case studies.

As enterprises become increasingly information based, making improvements in their information activities is an essential priority to guarantee their continuing competitiveness. A key to achieve these improvements is developing an Enterprise Architecture (EA). EA typically encompasses an overview of the entire information system in an enterprise, including the software, hardware, and information architectures. In this paper, we aim the use of Model Driven Architecture (MDA) in Enterprise Architecture. MDA is the most recent approach which is introduced by OMG to improve software development. Our goal is to apply MDA to EA across multiple hierarchical levels ranging from business to IT. However, it is considered as an extension of the initial scope of MDA, but we show that MDA can play a pivotal role in this case. It enables various specialists to reason about and design business and IT systems that are truly integrated. The overall benefit is an increase in the project success rate.