Tag: INSPEC: NON CONTROLLED INDEXING

 
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Sensing methods of Dielectrophories from Bulky Instruments to Lab-on-a-chip

Recently, the sensing methods for dielectrophoresis (DEP) have been changed from bulky instruments to lab-on-a-chip. Lab-on-a-chip based the dielectrophoresis phenomenon holds the promise to give biology the advantage of miniaturization for carrying out complex experiments. However, until now, there is an unmet need for lab-on-a-chip to effectively deal with the biological systems at the cell level.

Published in:

Circuits and Systems Magazine, IEEE  (Volume:4 ,  Issue: 3 )

 

Yehya H. Ghallab, and Wael Badawy, “Sensing methods of Dielectrophories from Bulky Instruments to Lab-on-a-chip,” IEEE Circuit and Systems, Vol. 4, Issue 3, 2004

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CAVLC Encoder Design for Real-Time Mobile Video Applications

Abstract

This brief presents a new context-based adaptive variable length coding (CAVLC) architecture. The prototype is designed for the H.264/AVC baseline profile entropy coder. The proposed design offers area savings by reducing the size of the statistic buffer. The arithmetic table elimination technique further reduces the area. The split VLC tables simplify the process of bit-stream generation and also help in reducing some area. The proposed architecture is implemented on Xilinx Virtex II field-programmable gate array (2v3000fg676-4). Simulation result shows that the architecture is capable of processing common/quarter-common intermediate format frame sequences in real-time at a core speed of 50 MHz with 6.85-K logic gates.

Published in:

Circuits and Systems II: Express Briefs, IEEE Transactions on  (Volume:54 ,  Issue: 10 )

C. A. Rahman and W. Badawy, “CAVLC Encoder Design for Real-time Mobile Video Applications”, The IEEE Trans. on Circuits and Systems II, Oct. 2007 Vol 54, Issue: 10, pp. 873-877.
Link to the list of other Peer Journal Publications

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Video-based Automatic Incident Detection for Intelligent Transportation systems: The Outdoor Environmental Challenges

Video-based automatic incident detection (AID) systems are increasingly being used in intelligent transportation systems (ITS). Video-based AID is a promising method of incident detection. However, the accuracy of video-based AID is heavily affected by environmental factors such as shadows, snow, rain, and glare. This paper presents a review of the different work done in the literature to detect outdoor environmental factors, namely, static shadows, snow, rain, and glare. Once these environmental conditions are detected, they can be compensated for, and hence, the accuracy of alarms detected by video-based AID systems will be enhanced. Based on the presented review, this paper will highlight potential research directions to address gaps that currently exist in detecting outdoor environmental conditions. This will lead to an overall enhancement in the reliability of video-based AID systems and, hence, pave the road for more usage of these systems in the future. Last, this paper suggests new contributions in the form of new suggested algorithmic ideas to detect environmental factors that affect AID systems accuracy.

Published in:

Intelligent Transportation Systems, IEEE Transactions on  (Volume:9 ,  Issue: 2 )