• Journal of Sasang Constitutional Medicine
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• v.16 no.1
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• pp.61-73
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• 2004

This study was prepared to investigate the correlation between Sasang constitutional groups and voice characteristics using voice analysis system(in this study, CSL). I focused on the voice characteristics in terms of harmonics, Formant frequency and Formant Bandwidth. The subjects were 71 males. I classified them into three groups, that is Soeumin group, Soyangin group and Taeumin group. The classification method of Constitution used two ways, QSCCII(Questionnarie for the Sasang Constitution Classification II) and Interview with a specialist in Sasang Constitution. So 71 people were categorized into 31 Soeumin(people), 18 Soyangin(people) and 22 Taeumin(people). Pitch is approximately similar to the fundamental frequency(F0) in voices. Shimmer in dB gives an evaluation of the period-to-period variability of the peak-to-peak amplitude within the analyzed voice sample. FFT(Fast Fourier Transform) method in CSL can display sampled voices into harmonics. H1 is the first peak and h2 is the second peak in the harmonics. The amplitude difference of h1 and h2(h1-h2) can be explained as the speaker's phonation type, And Formant frequency and bandwidth can be explained as the speaker's vocal tract. So I checked the harmonics and Formant frequency and Bandwidth as the voice parameters. First I have captured /e/ voices from all subjects using microphone. And then I analyzed /e/ voices with CSL. Power Spectrum and Formant History is the menu in the CSL which can display harmonics and Formant frequency and bandwidth. The results about the correlation between Sasang Constitutional Groups and voice parameters are as follows; 1. There is no significant amplitude difference of harmonics(h1-h2) among three groups. 2. There is the significant difference between Soeumin Group and Soyangin Group in Formant Frequency 1 and Formant Bandwidth 1(p<0.05). Any other parameters have no significance. I assume that Soyangin Group has clearer and brighter voice than Soeumin Group according to the Formant Bandwidth difference. And I think its result has coincidence with the context of "Dongyi Suse Bowon" and "Sasangimhejinam".

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.5
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• pp.45-54
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• 2007

Time/frequency analysis has been extensively used in biomedical signal processing. By extracting some essential features from the electro-physiological signals, these methods are able to determine the clinical pathology mechanisms of some diseases. However, this method assumes that the signal should be stationary, which limits its application in non-stationary system. In this paper, we develop a new signal processing method using Hilbert-Huang Transform to perform analysis of the nonlinear and non-stationary ventricular fibrillation(VF). Hilbert-Huang Transform combines two major analytical theories: Empirical Mode Decomposition(EMD) and the Hilbert Transform. Hilbert-Huang Transform can be used to decompose natural data into independent Intrinsic Mode Functions using the theories of EMD. Furthermore, Hilbert-Huang Transform employs Hilbert Transform to determine instantaneous frequency and amplitude, and therefore can be used to accurately describe the local behavior of signals. This paper studied for Return Of Spontaneous Circulation(ROSC) and non-ROSC prediction performance by Support Vector Machine and three parameters(EMD-IF, EMD-FFT) extracted from ventricular fibrillation ECG waveform using Hilbert-Huang transform. On the average results of sensitivity and specificity were 87.35% and 76.88% respectively. Hilbert-Huang Transform shows that it enables us to predict the ROSC of VF more precisely.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.544-555
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• 2002

The aim of this study is to develop the $^1H$-MRS data postprocessing software for both single-voxel and multi-voxel technique, which plays and important role as a diagnostic tool in clinical field. This software is based on graphical user interface(GUI) under windows operating system of personal computer(PC). In case of single-voxel MRS, both of raw data in time-domain and spectrum data in frequency-domain are simultaneously displayed in a screen. Several functions such as DC correction, zero filling, line broadening, Lorentz-Gauss filtering and phase correction, etc. are included to increase the quality of spectrum data. In case of multi-voxel analysis, spectroscopic image reconstructed by 3-D FFT was displayed as a spectral grid and overlapped over previously obtained T1- or T2-weighted image for the spectra to be spatially registered with the image. The analysis of MRS peaks were performed by obtaining the ratio of peak area. In single-voxel method, statistically processed peak-area ratios of MRS data obtained from normal human brain are presented. Using multi-voxel method, MR spectroscopic image and metabolite image acquired from brain tumor are demonstrated.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.485-494
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• 2008

Huge amounts of various web items such as keywords, images, and web pages are being made widely available on the Web. The popularities of such web items continuously change over time, and mining temporal patterns in popularities of web items is an important problem that is useful for several web applications. For example, the temporal patterns in popularities of search keywords help web search enterprises predict future popular keywords, enabling them to make price decisions when marketing search keywords to advertisers. However, presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in popularities of web items. We treat the popularities of web items as time-series, and propose gapmeasure to quantify the similarity between the popularities of two web items. To reduce the computation overhead for this measure, an efficient method using the Fast Fourier Transform (FFT) is presented. We assume that the popularities of web items are not necessarily following any probabilistic distribution or periodic. For finding clusters of web items with similar popularity trends, we propose to use a density-based clustering algorithm based on the gap measure. Our experiments using the popularity trends of search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.699-710
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• 2009

If a country has her geoid model, it could be determine accurate orthometric height because the geoid model could provide continuous equi-gravity potential surface. And it is possible to improve the coordinates accuracy of national control points through geodetic network adjustment considering geoidal heights. This study aims to find the best way to develop geoid model in Philippines which have similar topographic conditions as like Malaysia and Indonesia in Eastsouth asia. So, in this study, it is surveyed the general theories of geoid determination and development cases of geoid model in Asia and it is computed that the geoidal heights and gravity anomalies by spherical harmonic analysis using EGM2008, the latest earth geopotential model. The results show that first, the development of gravimetric geoid model based on airborne gravimetry is needed and second, about 200 GPS surveying data at national benchmark is needed. It is concluded that it is the most reasonable way to develop the hybrid geoid model through fitting geometric geoid by GPS/leveling data to gravimetric geoid. Also, it is proposed that four band spherical Fast fourier transformation(FFT) method for evaluation of Stokes integration and remove and restore technique using EGM2008 and SRTM for calculation of gravimetric geoid model and least square collocation algorithm for calculation of hybrid geoid model.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.581-587
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• 2004

Conventional power spectrum methods based on FFT, AR method are not appropriate for analyzing biomedical signals whose spectral characteristics change rapidly. On the other hand, time-frequency analysis has more desirable characteristics of a time-varying spectrum. In this study, we investigated the spectral components of heart rate variability(HRV) in time-frequency domain using time frequency analysis methods. In the various time-frequency kernels functions, we studied the suitable kernels for the analysis of HRV using synthetic HRV signals. First, we evaluated the time/frequency resolution and cross term reduction of various kernel functions. Then, from the instantaneous frequency, obtained from time-frequency distribution, the method extracting frequency components of HRV was proposed. Subjects were 17 healthy young men. A coin-stacking task was used to induce mental stress. For each subjects, the experiment time was 3 minutes. Electrocardiogram, measured during the experiment, was analyzed after converted to HRV signal. In the results, emotional stress of subjects produced an increase in sympathetic activity. Sympathetic activation was responsible for the significant increase in the LF/HF ratio. Subjects were divided into two groups with task ability. Subjects who have higher mental stress have lack of task ability.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.3
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• pp.169-172
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• 2015

Dalvik is a virtual machine (VM) that is designed to run Java-based Android applications. A trace-based just-in-time (JIT) compilation technique is currently employed to improve performance of the Dalvik VM. However, due to runtime compilation overhead, the trace-based JIT compiler provides only a few simple optimizations. Moreover, because each trace contains only a few instructions, the trace-based JIT compiler inherently exploits fewer optimization and parallelization opportunities than a method-based JIT compiler that compiles method-by-method. So we propose a new method-based JIT compiler, named DEX2C, in order to improve performance by finding more opportunities for both optimization and parallelization in Android applications. We employ C code as an intermediate product in order to find more optimization opportunities by using the GNU C Compiler (GCC), and we will detect parallelism by using the Intel C/C++ parallel compiler and the AESOP compiler in our future work. In this paper, we introduce our DEX2C compiler, which dynamically translates Dalvik bytecodes (DEX) into C code with method granularity. We also describe a new method-based JIT interface in the Dalvik VM for the DEX2C compiler. Our experiment results show that our compiler and its interface achieve significant performance improvement by up to 15.2 times and 3.7 times on average, in Element Benchmark, and up to 2.8 times for FFT in Smartbench.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.755-761
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• 2005

In this paper, we proposed a channel estimation method by impulse signal train in OFDM. In order to estimate the channel response, 4 impulse signals are generated and transmitted during one OFDM (Orthogonal Frequency Division Multiplexing) symbol. The intervals between the impulse signals are all equal in time domain. At the receiver, the impulse response signals are summed and averaged. And then, the averaged impulse response signal is zero padded and fast Fourier transformed to obtain the channel estimation. The BER performance of the proposed method is compared with those of conventional estimation method using the long training sequence in fast fading environments. The simulation results show that the proposed method improves by 3 dB in terms of Eb/No, compared with the conventional method.

• The Journal of the Acoustical Society of Korea
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• v.7 no.2
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• pp.26-38
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• 1988

This paper describes three methods for the estimation of the impulse reponse in an indoor acoustic transfer system which rather has long reverberation time by the cross spectrum. The first method, which is the conventional one, will use the white noise as the source signal. Therefore, the very long time window data and numerous number of DFT are necessary for this estimation. The second method has been disigned in order to shorten the length of time window of the first method by using a burst of noise as the source signal. The third method which will be suggested in this paper uses too types of definite signal with short duration time of the source signal. According to the view point of computation capacity, and estimation accuracy of the impulse response, the compared experimental results show that the third method will be better than the others.

• Smart Structures and Systems
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• v.17 no.2
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• pp.209-230
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• 2016

The Canton Tower is a high-rise slender structure with a height of 610 m. A structural health monitoring system has been instrumented on the structure, by which data is continuously monitored. This paper presents an investigation on the identified modal properties of the Canton Tower using ambient vibration data collected during a whole day (24 hours). A recently developed Fast Bayesian FFT method is utilized for operational modal analysis on the basis of the measured acceleration data. The approach views modal identification as an inference problem where probability is used as a measure for the relative plausibility of outcomes given a model of the structure and measured data. Focusing on the first several modes, the modal properties of this supertall slender structure are identified on non-overlapping time windows during the whole day under normal wind speed. With the identified modal parameters and the associated posterior uncertainty, the distribution of the modal parameters in the future is predicted and assessed. By defining the modal root-mean-square value in terms of the power spectral density of modal force identified, the identified natural frequencies and damping ratios versus the vibration amplitude are investigated with the associated posterior uncertainty considered. Meanwhile, the correlations between modal parameters and temperature, modal parameters and wind speed are studied. For comparison purpose, the frequency domain decomposition (FDD) method is also utilized to identify the modal parameters. The identified results obtained by the Bayesian method, the FDD method and a finite element model are compared and discussed.