انجمن کامپیوتر ایران

در اين مقاله، روشي جهت استخراج ويژگيهاي پايدار از تصاوير عنبيه بر اساس تبديل ويژگي غير وابسته به مقياس جهت شناسايي هويت ارائه شده است. مزيت اين روش بر روشهاي رايج عدم حساسيت به تغييرات مقياس، حركت و چرخش در تصاوير ميباشد. همچنين نويسندگان، پايگاه داده جديد IRIRIS متشكل از تصاوير عنبيه اخذ شده در زوايا و فواصل متفاوت در شرايط نور محيطي را ايجاد نموده و روش ارائه شده را بر روي تصاوير اين پايگاه داده جهت يافتن اين ويژگيها اعمال و به نتيجه تطبيق بالايي بر اساس اين ويژگيها دست يافتند. در نهايت پارامترهاي مهم تاثير گذار بر الگوريتم استخراج نقاط كليدي مورد بررسي قرار گرفته است.

On-Demand Multicast Routing Protocol (ODMRP) is a well-known protocol for ad hoc networks. This protocol is mesh based and exhibits a high packet delivery ratio even at high mobility. In ODMRP the robustness is achieved by using the number of multiple routes which is a solution for the high speed mobility and the subsequent route breaking. The ODMRP is such designed that the number of multiple routes only depends on the number of senders and receivers, irrespective of the node speed and the traffic load. In this paper we proposed a Reduced Data Transmission ODMRP (RDTODMRP) routing algorithm that considers the network conditions e.g. mobility speed and traffic load to determine the multiple routs. This cuts down the unnecessary redundant routes and their data transmissions. Furthermore in ODMRP and RDTODMRP, flooding of Join-Request packets causes excessive control overhead, In order to solve the problem, we Limit some nodes to Flood Join-Request packets and forbid it to be a forwarding node (LF-RDTODMRP). It is shown by simulation that the RDTODMRP and LF-RDTODMRP reduce the number of data transmission, control overhead, end to end delay and improve the data packet delivery ratio.

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.

Being able to predict the coming seizure can impressively improve the quality of the patients' lives since they can be warned to avoid doing risky activities via a prediction system. Here, a locally linear neuro fuzzy model is used to predict the EEG time series. Subsequently, this model is utilized in accompany with Singular Spectrum Analysis for prediction. Afterward, an information theoretic criterion is used to select a reliable subset of input variables which contain more information about the target signal. Comparison of three mentioned methods on one hand shows that SSA enables our prediction model to extract the main patterns of the EEG signal and highly improves the prediction accuracy. On the other hand, applying the method of channel selection to the model yields more accurate prediction. It is shown that fusion of some certain signals provides more information about the target and considerably improves the prediction ability.

In this paper, we present a new measure for evaluating similarity changes in a multi agent system. The similarity measure of the agents changes during the learning process. The similarity differences are because of any composition or decomposition of some agent sets. The presented measure, defines the changes of homogeneity of agents by composition and decomposition. The utility of the metrics is demonstrated in the experimental evaluation of multi agent foraging. The results show that while the similarity difference gets a positive value, the performance grow rapidly.

In this paper, a new fuzzy fading memory (FFM) is developed in order to aid a modified input estimation (MIE) technique and enhance its performance in tracking high maneuvering targets. The MIE has been introduced recently and performs well in tracking low and medium maneuvering targets. However, due to some modeling errors, the accuracy of this tracker may be seriously degraded in presence of high maneuvers. To cope with this difficulty, an intelligent approach based on FFM is presented in this paper. Simulation results prove the efficiency of the proposed method in tracking high maneuvering targets.

With ever increasing complexity of software systems, it is now more evident than ever that a fundamental change in software engineering practices is required. In this paper we discuss the nature of change and its implications. The notion of passive autonomy is introduced as a reference to the relative autonomy of business entities, and we claim that realizing the passive autonomy in information systems would results in systems far more adaptable and aligned with business’ needs. In order to realize this autonomy, theuse of autonomous agents as representing real world autonomous entities is suggested. After pointing out the shortcomings of current agent based architectures, a new architecture is proposed, based on indirect, multilateral negotiation. The suitability of this architecture is demonstrated in a simple case of beer game and it is shown that the bullwhip effect is remedied to some extent using this new architectural approach.