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the concept of multi-hop CDMA cellular networks has received increasing attention now. It is a widely accepted assumption that using multi-hopping in cellular networks will increase the cellular throughput. There are several advantages of MCN such as the improved signal quality and higher coverage. Finding an available relaying path is a critical prerequisite for the success of the multi-hop cellular networks and has a great impact on the network throughput. Most works use signal strength, distance and power consumption as routing criteria, but the effect of interference specially intercell interference does not take into account in routing algorithms. For this reason, in this paper interference is calculated at any receiver during the uplink, and a novel routing scheme based on minimum interference and best link gain in each hop, is proposed. Simulation results indicate that the routing algorithm based on our proposed metric results in higher throughput than the other metrics under a certain constraint.

On-chip network interconnections or Network-on- Chip (NOC) is viewed as a possible solution to global wiring issues in highly integrated complex systems. In current NoCs and in order to promote system level integrity, there is a growing need to provide different traffic classes, each with a different Quality-of-Service guarantee. In synchronous NOCs guaranteed service is provided by reserving time slots. Asynchronous NOC implementation, on the other hand, eliminates the need for synchronization when crossing clock domains. In asynchronous NOCs there is no notation of time and arbitration. Any delay in arbitration or refusing requests in arbitration results in the accumulation of data in switch buffers. In this paper a novel arbitration scheme for clockless NOCs has been proposed that is able to service a connection without any halt or jitter in streaming. Consequently, links with a burst traffic pattern and guaranteed bandwidth requirement can be implemented without any large buffers. Simulation results indicate that the proposed method is able to reduce switch buffer size, and hence power consumption in any NoC platform that is providing guaranteed bandwidth requirements in applications with burst data characteristics. For instance, in an MPEG-2 decoder mapped to a 3x2 mesh with 8 guaranteed bandwidth channels in each port, the proposed arbitration scheme is able to reduce the buffer size by 25%. The improvement increases to %47 for a JPEG2000 encoder mapped to a 3x3 mesh.

Web access prediction has attracted significant attention in recent years. Web prefetching and some personalization systems use prediction algorithms. Most current applications that predict the next user web page have an offline component that does the data preparation task and an online section that provides personalized content to the users based on their current navigational activities. In this paper we present an online prediction model that does not have an offline component and fit in the memory with good prediction accuracy. Our algorithm is based on LZ78 and LZW algorithms that are adapted for modeling the user navigation in web. Our model decreases computational complexities which is a serious problem in developing online prediction systems. A performance evaluation is presented using real web logs. This evaluation shows that our model needs much less memory than PPM family of algorithms with good prediction accuracy.

Video processing techniques based on pattern recognition methods and machine vision is one of the interesting research fields which attract many researchers. In this paper, we proposed a novel method for video summarization using genetic algorithm based on information theory. Our method relies on the mutual information for video summarization. The information theory measure provides us with better results because it extracts the inter-frame information. We present that it is a suitable factor for summarizing video, which maintains its integrity.

In this paper we propose several methods for partitioning, the process of grouping members of population to different memeplexes, in a shuffled frog leaping algorithm. These proposed methods divide the population in terms of the value of cost function or the geometric position of members or quite random partitioning. The proposed methods are evaluated on several low and high dimensional benchmark functions. The obtained results on low dimensional functions demonstrate that geometric partitioning methods have the best success rate and the fastest performance. Also on high dimensional functions, however using of the geometric partitioning methods for the partitioning stage of the SFL algorithm lead to a better success rate but these methods are more time consuming than other partitioning methods.

In this paper, we proposed a new feature subset selection approach. In proposed approach first, the entire dataset are classified and the best number of clusters over it are found according to silhouette value. Then according to this value, each feature is alone classified with the same cluster number and accordingly the proposed entropy fuzzy measure is found for them. We examine our method on some traditional datasets. The results show a good performance of proposed method.

Uncertainty reasoning has been identified as an important and challenging issue in the database research. Many logic frameworks have been proposed to represent and reason about uncertainty in deductive databases. On the basis of the way in which uncertainties are associated with the facts and rules in programs, the approaches of these frameworks have been classified into “annotation based (AB)” and “implication based (IB).” When extending both frameworks with certainty constraints, they become equivalent in terms of expressive power. In this paper, we propose a uniform environment to evaluate and experiment with logic programs in AB and IB frameworks at the same time. We also extend the existing query processing to handle certainty constraints and we carry out experiments to evaluate its performance. Our experiments and results indicate that the proposed techniques yield tools that are capable to reason with uncertainty.