• Journal of Internet Computing and Services
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• v.10 no.6
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• pp.7-17
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• 2009

The development of wireless communication MAC layer is usually released as SoC which is a combination in hardware and software. In this system development environment, an environment for software development and verification is necessary because the hardware development takes a lot of time priori to completion. In integrated development of hardware and software, simulation environment of hardware and software provided by hardware modeling using HDL at RTL and ISS respectively. By increasing the development complexity of system, ESL design modeling systems at higher abstraction level than RTL has already prompted. The ESL design is divided untime model and time model. This paper present design and implementation of MCU for untime model simulation, not time model. Proposed MCU can optimize the system at early step of system development and move up the development completion time by verifying the system function easily and rapidly than part required exact time in untime model. In this paper, we present an MCU module based on SystemC and UC/OS-II Module providing real-time operate system.

• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.188-195
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• 1999

The fMRI signals are composed of many various signals. It is very difficult to find the accurate parameter for the model of fMRI signal containing only neural activity, though we may estimating the signal patterns by the modeling of several signal components. Besides the nose by the physiologic motion, the motion of object and noise of MR instruments make it more difficult to analyze signals of fMRI. Therefore, it is not easy to select an accurate reference data that can accurately reflect neural activity, and the method of an analysis of various signal patterns containing the information of neural activity is an issue of the post-processing methods for fMRI. In the present study, fMRI data was analyzed with the Independent Component Analysis(ICA) method that doesn't need a priori-knowledge or reference data. ICA can be more effective over the analytic method using cross-correlation analysis and can separate the signal patterns of the signals with delayed response or motion related components. The Principal component Analysis (PCA) threshold, wavelet spatial filtering and analysis of a part of whole images can be used for the reduction of the freedom of data before ICA analysis, and these preceding analyses may be useful for a more effective analysis. As a result, ICA method will be effective for the degree of freedom of the data.