انجمن کامپیوتر ایران

Grid computing is a promising technology for future computing platforms and is expected to provide easier access to remote computational resources that are usually locally limited. Scheduling is one of the active research topics in grid environments. The goal of grid task scheduling is to achieve high system throughput and to allocate various computing resources to applications. The Complexity of scheduling problem increases with the size of the grid and becomes highly difficult to solve effectively. Many different methods have been proposed to solve this problem. Some of these methods are based on heuristic techniques that provide an optimal or near optimal solution for large grids. In this paper we introduce a new task scheduling algorithm based on Ant Colony Optimization (ACO). According to the experimental results, the proposed algorithm confidently demonstrates its competitiveness with previously proposed algorithms.

Binary Arithmetic Coding (BAC) is among the techniques used in H.264 video coding standard to improve the coding efficiency. BAC includes an iterative process of renormalization with up to seven iterations for coding each symbol. Since BAC is also a computational intensive unit in H.264 encoder, various hardware realizations have been proposed for it in the literature. In this paper, we propose a hardware implementation for BAC, which uses lookup table to avoid the iterative coding process and achieves coding rate of one symbol per clock at 260 MHz clock rate. Post synthesize simulation results indicate that the proposed architecture is a resource and speed efficient hardware for H.264 binary arithmetic encoder.

In this work, we present SIMUIINK bit-true modeling of the conjugate structure-algebraic CELP (CS-ACELP) speech coder which has been chosen as the core layer of speech coder standard ITU-T G.729.1. The optimum bit numbers of the computational blocks are defined as the minimum word-widths that maintain the quality of the output with minimum chip area and power. Such optimum bitwidth of the coefficients and the internal computations are extracted. As a result, a golden model of the codec which best suits as a reference for its hardware implementation is developed. The power and area improvements are estimated in two blocks of CSACELP speech coder.

Background modeling is one of the most important parts of visual surveillance systems. Most background models are pixel-based which extract detailed shape of moving objects, but they are so sensitive to nonstationary scenes. In many applications there is no need to detect the detailed shape of moving objects. So some researchers use block-based methods instead of pixel-based which are more insensitive to local movements. These two methods are complementary to each other. We propose an efficient hierarchical method by which the block level information is utilized intelligently to improve the efficiency and robustness of pixel level. Experimental results demonstrate the effectiveness of the algorithm when applied in different outdoor and indoor environments.

In recent years, processing the images that contain human faces has been a growing research interest because of establishment and development of automatic methods especially in security applications, compression, and perceptual user interface. In this paper, a new method has been proposed for multiple face detection and tracking in video frames. The proposed method uses skin color, edge and shape information, face detection, and dynamic movement analysis of faces for more accurate real-time multiple face detection and tracking purposes. One of the main advantages of the proposed method is its robustness against usual challenges in face tracking such as scaling, rotation, scene changes, fast movements, and partial occlusions.

Vehicle tracking is an essential requirement of any vision based Intelligent Transportation System for extracting different traffic parameters, efficiently. Handling inter-object occlusion is the most challenging part of tracking as a process of finding and following interested objects in a sequence of video frames. In this paper we present a system, based on code-book background model for motion segmentation and Kalman filter for tracking with a new approach for occlusion. This approach separates occluded vehicles based on longest common substring of chain codes. We use this tracking system to estimate some traffic parameters. Experimental results show the efficiency of the method

The existing workflow modeling languages have some limitations and drawbacks. The aim is to introduce a new workflow modeling language based on stochastic activity networks (SANs). SANs are a powerful extension of Petri nets, which have been used in a wide range of applications. SAN-based workflow modeling language (SWML) has some high-level modeling primitives for easily modeling workflow patterns. For analysis of the modeled workflow systems with SWML, we have introduced the transformation techniques from SWML models into ordinary SANs. The transformed models can be analyzed using the existing tools for SANs, such as the Möbius modeling tool. In this paper, we present definitions of SWML modeling language and its primitives and an example of SWML models.