The development of application specific instruction set processors comprises several design phases: architecture exploration, software tools design, system verification and design implementation. The LISA processor design platform (LPDP) based on machine descriptions in the LISA language provides one common environment for these design phases. Required software tools for architecture exploration and application development can be generated from one sole specification. This paper focuses on the implementation phase and the generation of synthesizable HDL code from a LISA model.

 Keywords-LISA, Architecture exploration, machine description languages.

The main objectives of this paper is to examine the   performance of the wireless broadband infrastructures and their support for Triple Play services under different separated scenarios by using OPNET Modeler 14.5. This simulation network uses several features to study the performances of WiMax on Triple Play services, 3.5GHz band is chosen in our studies because it is widely used band all over the world. Moreover, this band is licensed, so that interfere is under control and allows using higher transmission power. The best bandwidth for a carrier frequency of 3.5GHz is needed to be tested. The pathloss for urban, suburban and rural is calculated, while multipath with pathloss is calculated for ITU channel model of pedestrian in different environments. WiMax does not offer a compelling reason to switch from other forms of residential broadband. When bundled with broadband internet access and VoD, a WiMax Triple Play becomes very attractive to residential subscribers. Given the QoS and reliability mechanisms built into WiMax in this simulation scenario, subscribers will find WiMax good.
 
Keywords— WiMAX, Triple Play Service (IPTV, VoIP and Data), QoS with DiffServ architecture, simulation model design.

The present study aims at making comparison between two analyzing methods , multidimensional scaling and hierarchical clustering methods ,on the other hand, to imply data mining by using of these two analyzing  methods to classify and discriminate twenty five samples of technician pieces (Prehistoric goblets) through the study of Engineering shapes and special figures for every sample separately (case by case) , which backs to the periods before B.C. and discovered in Malaysia .The results of two methods concord  and resemble each other equally in their classifications of Data. A multidimensional Scaling method seems to be more precise and give more details in comparison with hierarchical cluster methods.

Keywords: MDS, HCA, Pattern Recognition, Data Mining

Mining frequent log items is an active area in data mining that aims at searching interesting relationships between items in databases. It can be used to address a wide variety of problems such as discovering association rules, sequential patterns, correlations and much more. Weblog that analyzes a Web site's access log and reports the number of visitors, views, hits, most frequently visited pages, and so forth. Mining frequent log items from web log data can help to optimize the structure of a web site and improve the performance of web servers. Existing methods often generate a huge set of potential high utility log items and their mining performance is degraded consequently. Two novel algorithms as well as a compact data structure for efficiently discovering high utility log items are proposed. High utility log items are maintained in a tree-based data structure called utility pattern tree. Implementing mining process is done through Discarding Local Unpromising Items and Decreasing Local Node Utility strategies. Experimental results predict that these strategies can keep track of previously accessed pages of a user, identify needed links to improve the overall performance of a web page, and improve the actual design of web pages with only two database scans.

Index Terms— frequent log items, high utility log items, Web Log file, data mining