Earticle

The rise in complexity of SOC (System-on-Chip) architectures has brought into focus the need for better communication models for SOCs. The traditional bus based approach is reaching its limit with the emergence of high core count SOCs. The theory and practices of wired communication networks is being applied to tackle communication issues in complex SOCs. This is referred to as the Network on Chip (NOC) model. Routers are one of the most important elements of an on chip network. The underlying architecture of a router is based on a crossbar switch as it offers higher throughput and lower latency due to point-to-point architecture. Homogenous sizes of the input module in the router may not be efficient as some cores may be underutilized while some of them may be overloaded. A heterogeneous size of the input module is preferred for the predicted traffic but bursty in nature. We proposed, input module of size 64_packet array for the most busy node in the design while the most underutilized input module can also satisfy the need of the packet array of size 16. For moderate traffic, the input module with 32 packet array can be an efficient solution. The Islip based IQ_VOQ is the most practical combination, popular in the CISCO router [12000 series]. The input module proposed here is based on Virtual output queuing while Islip scheduling algorithm is based on unfolding and folding concept. First, the RTL implementation of input module for 3-proposed design has been carried out and later it realized using a standard-cell-based ASIC flow using 90 nm saed-typ technology library of Synopsis Educational Design Kit.

This paper presents an approach to integrate thinking styles into adaptive hypermedia system. The main objective was to develop an adaptive system and assess the effect of adapting pedagogical activities individualized to the student’s thinking style. The proposed approach used adaptive hypermedia technology to improve learning process by adapting course content presentation to student thinking styles. The design of adaptive hypermedia is based on quantitative and qualitative research. The adaptation rules are deduced from the results of a psychological questionnaire. Pedagogical activities are the outcome of a series of inferences; the final activity sets are manifested in adaptive hypermedia system. Stereotype user model is used to cluster all possible users into groups, providing mapping from a specific combination of user features to one of the stereotypes. Our approach is inspired by HBDI® model, focusing on the perspective of learner, meeting the needs of an adaptive hypermedia system.

Biometric has been implemented on numerous public facilities to enhance the security system. Fingerprint and face are the most popular biometric. Emerging technology has introduced potential biometric such as palm print, lips, teeth, vein and ear. However, most of this biometrics requires a special device to capture it. Thus, the implementation of such system will be costly. Iannarelli [1, 2] has proved that ear biometric is having a great potential for identifying a person. In this research work, an attempt is made to improve the detection and finally to segment the human ear from the whole image of human’s head. The success of this stage is very important for achieving the later goal, such as recognition and classification. This paper introduces a novel method for ear segmentation. Proposed method is based on morphological analysis fused with RBF neural network. Experiment shows that the proposed method has delivered a promising result.

Edge detection aims to mark sharp intensity changes in an image and is a basis for a large number of image analysis and machine vision applications. Ant colony optimization is an evolutionary optimization algorithm which is inspired by food searching behaviour of ant species. An edge detection algorithm that combines an ant colony optimization and fuzzy logic is presented in this paper. The heuristics information for movement of ants is decided by using fuzzy logic. Experimental results are provided to demonstrate the superior performance of proposed method.

With the development of the Internet, many people are able share information freely, and check for information from various parts of the world in real time. Internet brought about the development of diverse industries, and its utilization is likely to increase through combination with many types of media in the future. However, the Internet also causes some problems. A computer can be infected with malicious codes only from a user visiting website, and personal information can be leaked from an infected PC. In particular, malicious codes are spreading, using the search word containing the social issue. Because search work rankings are provided with various categories, such as real time search words and “sharply rising search words”, malicious code spreading using these search words seem to increase. Therefore, this paper proposes a system that automatically collects malicious codes, which are disseminated using the search function.

In this paper we propose a new scheduling algorithm called Real Time Scheduling (RTS). This algorithm deals with all the contributing components of the end-to-end travelling delay of data packets in sensor network to achieve better power management and stable routes in case of failure. RTS delays packets at intermediate hops (not just prioritizes them) for a duration that is a function of their deadline. Delaying packets allows the network to avoid hot spotting while maintaining deadline-faithfulness. We compare RTS with another prioritizing and scheduling algorithm for real-time data dissemination in sensor networks. This paper simulates RTS based on two typical routing protocols, shortest path routing and greedy forwarding with J-Sim.