• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.31 no.8
• /
• pp.91-98
• /
• 2003

In the structural analysis of a launch vehicle, the construction of loading functions and the determination of responses to them are very important. Among many kinds of loads, acoustic load generated by exhaust is a random load that can be described in a statistical manner. In this study, loading functions corresponding to the acoustic loads are constructed and applied to the structural analysis of launch vehicle. Acoustic loading functions are constructed using source allocation method. Structural analyses are carried out by using finite element modelling and frequency response function of finite element model. The stresses resulting from acoustic loads and acceleration power spectral density functions at interfaces of each section are calculated. These analyses are essential for the development of environmental test specifications and associated dynamic design requirements which are necessary to ensure overall vehicle reliability.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.48 no.1
• /
• pp.101-107
• /
• 2011

The background noises and distortions by channel are major factors that disturb the practical use of speech recognition. Usually, noise reduce the performance of speech recognition system DSR(Distributed Speech Recognition) based speech recognition also bas difficulty of improving performance for this reason. Therefore, to improve DSR-based speech recognition under noisy environment, this paper proposes a method which detects accurate speech region to extract accurate features. The proposed method distinguish speech and noise by using entropy and detection of spectral energy of speech. The speech detection by the spectral energy of speech shows good performance under relatively high SNR(SNR 15dB). But when the noise environment varies, the threshold between speech and noise also varies, and speech detection performance reduces under low SNR(SNR 0dB) environment. The proposed method uses the spectral entropy and harmonics of speech for better speech detection. Also, the performance of AFE is increased by precise speech detections. According to the result of experiment, the proposed method shows better recognition performance under noise environment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.2
• /
• pp.117-132
• /
• 2014

This paper had a purpose on analyzing result data from pan-sharpening, which have applied on the KOMPSAT-2 and -3 image. Particularly, the study focused on comparing each relative spectral response functions, which considers to cause color distortions of fused image. Two images from same time and location have been collected by KOMPSAT-2 and -3 to apply in the experiment. State-of-the-art algorithms of GIHS, GS1, GSA and GSA-CA were employed for analyzing the results in quantitatively and qualitatively. Following analysis of previous studies, GSA and GSA-CA methods resulted excellent quality in both of KOMPSAT-2/3 results, since they minimize spectral discordances between intensity and PAN image by the linear regression algorithm. It is notable that performances from KOMPSAT-2 and- 3 are not equal under same circumstances because of different spectral characteristics. In fact, KOMPSAT-2 is known as over-injection of low spatial resolution components of blue and green band, are greater than that of the PAN band. KOMPSAT-3, however, has been advanced in most of misperformances and weaknesses comparing from the KOMPSAT-2.