• Journal of Biosystems Engineering
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• v.34 no.2
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• pp.127-132
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• 2009

In the working population, muscle fatigue and musculoskeletal discomfort are common, which, in the case of insufficient recovery may lead to musculoskeletal pain. Workers suffering from musculoskeletal pains need to be rehabilitated for recovery. Isokinetic testing has been used in physical strengthening, rehabilitation and post-operative orthopedic surgery. Frequency analysis of electromyography (EMG) signals using the mean frequency (MNF) has been widely used to characterize muscle fatigue. During isokinetic contractions, EMG signals present strong nonstationarities. Hilbert-Haung transform (HHT) and autoregressive (AR) model have been known more suitable than Fourier or wavelet transform for nonstationary signals. Moreover, several analyses have been performed within each active phase during isokinetic contractions. Thus, the aims of this study were i) to determine which one was better suitable for the analysis of MNF between HHT and AR model during repetitive maximum isokinetic extensions and ii) to investigate whether the analysis could be repeated for sequential fixed epoch lengths. Seven healthy volunteers (five males and two females) performed isokinetic knee extensions at $60^{\circ}/s$ and $240^{\circ}/s$ until 50% of the maximum peak torque was reached. Surface EMG signals were recorded from the rectus femoris of the right thigh. An algorithm detecting the onset and offset of EMG signals was applied to extract each active phase of the muscle. Following the results, slopes from the least-square error linear regression of MNF values showed that muscle fatigue of all subjects occurred. The AR model is better suited than HHT for estimating MNF from nonstationary EMG signals during isokinetic knee extensions. Moreover, the linear regression can be extracted from MNF values calculated by sequential fixed epoch lengths (p> 0.0I).

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.31-39
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• 2009

Purpose : This study proposes the keyhole method in order to improve the time resolution of the proton resonance frequency(PRF) MR temperature monitoring technique. The values of Root Mean Square (RMS) error of measured temperature value and Signal-to-Noise Ratio(SNR) obtained from the keyhole and full phase encoded temperature images were compared. Materials and Methods : The PRF method combined with GRE sequence was used to get MR temperature images using a clinical 1.5T MR scanner. It was conducted on the tissue-mimic 2% agarose gel phantom and swine's hock tissue. A MR compatible coaxial slot antenna driven by microwave power generator at 2.45GHz was used to heat the object in the magnetic bore for 5 minutes followed by a sequential acquisition of MR raw data during 10 minutes of cooling period. The acquired raw data were transferred to PC after then the keyhole images were reconstructed by taking the central part of K-space data with 128, 64, 32 and 16 phase encoding lines while the remaining peripheral parts were taken from the 1st reference raw data. The RMS errors were compared with the 256 full encoded self-reference temperature image while the SNR values were compared with the zero filling images. Results : As phase encoding number at the center part on the keyhole temperature images decreased to 128, 64, 32 and 16, the RMS errors of the measured temperature increased to 0.538, 0.712, 0.768 and 0.845$^{\circ}C$, meanwhile SNR values were maintained as the phase encoding number of keyhole part is reduced. Conclusion : This study shows that the keyhole technique is successfully applied to temperature monitoring procedure to increases the temporal resolution by standardizing the matrix size, thus maintained the SNR values. In future, it is expected to implement the MR real time thermal imaging using keyhole method which is able to reduce the scan time with minimal thermal variations.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.221-232
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• 2021

This study analyzed co-registration results according to the geometric processing level of reference image, which are Level 1R and Level 1G provided from KOMPSAT-3 and KOMPSAT-3A images. We performed co-registration using each Level 1R and Level 1G image as a reference image, and Level 1R image as a sensed image. For constructing the experimental dataset, seven Level 1R and 1G images of KOMPSAT-3 and KOMPSAT-3A acquired from Daejeon, South Korea, were used. To coarsely align the geometric position of the two images, SURF (Speeded-Up Robust Feature) and PC (Phase Correlation) methods were combined and then repeatedly applied to the overlapping region of the images. Then, we extracted tie-points using the SURF method from coarsely aligned images and performed fine co-registration through affine transformation and piecewise Linear transformation, respectively, constructed with the tie-points. As a result of the experiment, when Level 1G image was used as a reference image, a relatively large number of tie-points were extracted than Level 1R image. Also, in the case where the reference image is Level 1G image, the root mean square error of co-registration was 5 pixels less than the case of Level 1R image on average. We have shown from the experimental results that the co-registration performance can be affected by the geometric processing level related to the initial geometric relationship between the two images. Moreover, we confirmed that the better geometric quality of the reference image achieved the more stable co-registration performance.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.7
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• pp.1013-1018
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• 2014

In this study, we developed kinetic models to predict the growth of pathogenic Escherichia coli on cheeses during storage at constant and changing temperatures. A five-strain mixture of pathogenic E. coli was inoculated onto natural cheeses (Brie and Camembert) and processed cheeses (sliced Mozzarella and sliced Cheddar) at 3 to 4 log CFU/g. The inoculated cheeses were stored at 4, 10, 15, 25, and $30^{\circ}C$ for 1 to 320 h, with a different storage time being used for each temperature. Total bacteria and E. coli cells were enumerated on tryptic soy agar and MacConkey sorbitol agar, respectively. E. coli growth data were fitted to the Baranyi model to calculate the maximum specific growth rate (${\mu}_{max}$; log CFU/g/h), lag phase duration (LPD; h), lower asymptote (log CFU/g), and upper asymptote (log CFU/g). The kinetic parameters were then analyzed as a function of storage temperature, using the square root model, polynomial equation, and linear equation. A dynamic model was also developed for varying temperature. The model performance was evaluated against observed data, and the root mean square error (RMSE) was calculated. At $4^{\circ}C$, E. coli cell growth was not observed on any cheese. However, E. coli growth was observed at $10{\circ}C$ to $30^{\circ}C$C with a ${\mu}_{max}$ of 0.01 to 1.03 log CFU/g/h, depending on the cheese. The ${\mu}_{max}$ values increased as temperature increased, while LPD values decreased, and ${\mu}_{max}$ and LPD values were different among the four types of cheese. The developed models showed adequate performance (RMSE = 0.176-0.337), indicating that these models should be useful for describing the growth kinetics of E. coli on various cheeses.

• 한국해양학회지
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• v.18 no.2
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• pp.117-124
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• 1983

Pizza's synthetic model, a modified Wiener filter method, was tested to establish the procedure of desirable interpretive wavelet extraction and its application to the marine seismic exploration using several approaches with a real offshore seismic data of the southeast Asia. Noise spectrum acquisition is difficult and any assumptions for it do not produce interpretive wavelets as good as synthetic model result by Piazza (1979). however the resolution could be improved with spiking deconvoultion and following zero phase bandpass filter, and the testing procedure and evaluatttion of results can hopefully contribute in future study and practical evaluation of Piazza's method.

• Journal of Broadcast Engineering
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• v.1 no.2
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• pp.85-95
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• 1996

The purpose of this paper Is to propose a dubbed signal time-synchroniztion technique based on the SOLA(Synchronized Over-Lap and Add) method which has been widely used to modify the time scale of speech signal. In broadcasting audio recording environments, the high degree of background noise requires dubbing process. Since the time difference between the original and the dubbed signal ranges about 200mili seconds, process is required to make the dubbed signal synchronize to the corresponding image. The proposed method finds he starting point of the dubbing signal using the short-time energy of the two signals. Thereafter, LPC cepstrum analysis and DTW(Dynamic Time Warping) process are applied to synchronize phoneme positions of the two signals. After determining the matched point by the minimum mean square error between orignal and dubbed LPC cepstrums, the SOLA method is applied to the dubbed signal, to maintain the consistency of the corresponding phase. Effectiveness of proposed method is verified by comparing the waveforms and the spectrograms of the original and the time synchronized dubbing signal.

• Journal of Advanced Navigation Technology
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• v.20 no.2
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• pp.155-160
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• 2016

Recently, underwater acoustic communication (UWAC) has been studied by many scholars and researchers. In order to use UWAC, we need to estimate time difference between the two signals in underwater environment. Typically, there are major three methods to estimate the time-difference between the two signals such as estimating the arrival time of the first non-background segment and calculate the temporal difference, calculating the cross-correlation between the two signal to infer the time-lagged, and estimating the phase delay to infer the time difference. In this paper, we present calculating the cross-correlation between the two signals to infer the time-lagged to apply UWAC. We also present the experimental result of estimating the arrival time by using cross-correlation. We get EXCORR = 0.003055 second as the estimation error in mean absolute difference.

• Journal of Biomedical Engineering Research
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• v.29 no.5
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• pp.371-375
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• 2008

In blood pressure measurement, the oscillometric method detects and analyzes the pulse pressure oscillation while deflating the cuff around the arm. For its principle, one has to inflate cuff pressure above the subject's systolic pressure and deflate below the diastolic pressure. Most of the commercialized devices inflate until the fixed target pressure and deflate until the fixed completion pressure because there is no way to know the systolic and diastolic pressure before measurement. Too high target pressure makes stress to the subject and too low target pressure makes big error or long measurement time because of re-inflation. There are similar problems for inadequate completion pressure. In this study, we suggest new algorithm to set proper target and completion pressure for each subject by analyzing pressure waveform while inflating period. We compared our proposed method and auscultation method to see the errors of estimation. The differences between the two measurements were -4.02$\pm$4.80mmHg, -10.50$\pm$10.57mmHg and -0.78$\pm$5.l7mmHg for mean arterial pressure, systolic pressure and diastolic pressure respectively. Consequently, we could set the target pressure by 30 mmHg higher than our estimation and we could stop at 20mmHg lower than our estimated diastolic pressure. Using this method, we could reduce the measurement time.

• Journal of Preventive Medicine and Public Health
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• v.17 no.1
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• pp.231-238
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• 1984

Normal range has use mainly in the first phase of the diagnostic process, that is, to screen or to raise ideas about possible pathology. The traditional method of determining it is based on the probability paper or on the mean plus or minus two standard deviations. These methods are often turned out to be vague and impractical. The percentile method is adequate and flexible, though. The appropriate limit of lower and upper points should be chosen by considering medical aspects above all things and also the reliability of the range determined by the standard error. The results of normal range are interesting, strictly speaking, only for the hospital concerned. Differences exist between the normal ranges reported by various sources (Bezemer et al, 1983). It would be best to establish the normal range based on a population comparable to a group of individuals to whom the normal range is to serve as a norm.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.3 s.21
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• pp.107-114
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• 2002

The cadastral surveying is essential for the effective management of a country, the D/B building of NGIS. Many of GPS applications require a positioning accuracy of several centimeters for rover in real-times. But, to achieve higher positioning accuracies in real-time, the double differencing technique should be implemented using carrier phase data. Corrected observations at the reference station can be transmitted and used to form double difference observations at the rover using a data link. In this study, the area accuracy of cadastral survey using the RTK GPS will be assessed, and will produce area of parcel of land. As the result of comparison among area by TS, planer surveying and RTK GPS. parcels-register for site is analyzed by this data. The results show that mean error of area calculated min. $2.42m^{2}{\sim}\;max.\;13.69m^{2}$ and RMSE calculated min. $0.00329\;{\sim}\;max.\;0.01846$.