• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.415-425
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• 2007

This paper proposes a method of underwater source localization using the wideband interference patterns matching. By matching two interference patterns in the spectrogram, it is estimated a ratio of the range from source to sensor5, and then this ratio is applied to the Apollonius circle. The Apollonius circle is defined as the locus of all points whose distances from two fixed points are in a constant value so that it is possible to represent the locus of potential source location. The Apollonius circle alone, however still keeps the ambiguity against the correct source location. Therefore another equation is necessary to estimate the unique locus of the source location. By estimating time differences of signal arrivals between source and sensors, the hyperbola equation is used to get the cross point of the two equations, where the point being assumed to be the source position. Simulations are performed to get performances of the proposed algorithm. Also, comparisons with real sea experiment data are made to prove applicability of the algorithm in real environment. The results show that the proposed algorithm successfully estimates the source position within an error bound of 10%.

• The Journal of the Acoustical Society of Korea
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• v.26 no.1
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• pp.48-54
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• 2007

In this paper we have implemented a 3-D PL (Position Location) system to estimate the 3-dimensional position of a moving object in underwater environments. In this research, we let four sensors fixed in different Positions and moving sensorsto communicate with each other to find the 3-dementianal positions for both the fixed and moving objects. Using this we were also able to control the moving object remotely. When finding the position, we calculated the norm of the Jacobian matrix every iteration in the Newton algorithm. Also by using a different initial value for calculating the solution when the norm became higher than the critical value and the solution from the inverse matrix became unstable, we could find a more reliable position for the moving object. The proposed algorithm was used in implementing a DSP system capable of real-time position location. To verify the performance, experiments were done in a water tank. As a result we could see that our system could located the position of an object every 2 seconds with a error range of 5cm.

• The Journal of the Acoustical Society of Korea
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• v.26 no.7
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• pp.366-374
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• 2007

In underwater wireless communication, needs for long distance communication using the high frequency are surpassing ones of short range communication by ultrasonic wave, and demands for transmitting and receiving various data such as voice or high resolution image data are increasing as well. In this work, we studied the effects on the real underwater communication depending on the difference of digital modulation methods. Simulation shows that only the performance of GMSK among many other PSK based modulation schemes(BPSK, QPSK, MSK, GMSK) is significant. Test condition simulates the oceanographic conditions along the 207-survey line, 15Km south of Busan and SNR is maintained 35dB or below. Simulated tests are composed of both transmitting image data($3{\times}10^5$ pixel, 4 bit per pixel) and voice communication($10^{-2}$BER, channel capacity of 1Kbps). Test results show that there are gain of about 7 seconds in transmission time in image transmission case, where channel capacity for BPSK, QPSK, and MSK and for GMSK were 65 Kbps and 45 Kbps, respectively and gain of about 8Km in distances in voice communication case.

• The Journal of the Acoustical Society of Korea
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• v.26 no.6
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• pp.301-305
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• 2007

In this paper, we propose a simple algorithm for detecting underwater transient signals on the fact that the frequency range of underwater transient signals is similar to audio frequency. For this, we use a preprocessing module of EVRC speech codec that is the standard speech codec of the mobile communications. If a signal is entered into EVRC noise suppression module, we can get some parameters such as the update flag, the energy of each channel, the noise suppressed signal, the energy of input signal, the energy of background noise, and the energy of enhanced signal. Therefore the energy of the enhanced signal that is normalized with the energy of the background noise is compared with the pre-defined detection threshold, and then we can detect the transient signal. And the detection threshold is updated using the previous value in the noisy period. The experimental result shows that the proposed algorithm has $0{\sim}4% error rate in the AWGN or the colored noise environment.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.3
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• pp.121-128
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• 2024

There are growing concerns that the recently implemented Earthquake Early Warning service is overestimating the rapidly provided earthquake magnitudes (M). As a result, the predicted damages unnecessarily activate earthquake protection systems for critical facilities and lifeline infrastructures that are far away. This study is conducted to improve the estimation accuracy of M by incorporating the observed S-wave seismograms in the near source region after removing the site effects of the seismograms in real time by filtering in the time domain. The ensemble of horizontal S-wave spectra from at least five seismograms without site effects is calculated and normalized to a hypocentric target distance (21.54 km) by using the distance attenuation model of Q(f)=348f^0.52 and a cross-over distance of 50 km. The natural logarithmic mean of the S-wave ensemble spectra is then fitted to Brune's source spectrum to obtain the best estimates for M and stress drop (SD) with the fitting weight of 1/standard deviation. The proposed methodology was tested on the 18 recent inland earthquakes in South Korea, and the condition of at least five records for the near-source region is sufficiently fulfilled at an epicentral distance of 30 km. The natural logarithmic standard deviation of the observed S-wave spectra of the ensemble was calculated to be 0.53 using records near the source for 1~10 Hz, compared to 0.42 using whole records. The result shows that the root-mean-square error of M and ln(SD) is approximately 0.17 and 0.6, respectively. This accuracy can provide a confidence interval of 0.4~2.3 of Peak Ground Acceleration values in the distant range.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.319-334
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• 2024

Purpose - The purpose of this study is to examine the gravity model commonly used for demand forecasting upon the implementation of new tourist facilities and analyze the main causation of forecasting errors to provide a suggestion on how to improve. Design/methodology/approach - This study first measured the errors in predicted values derived from past feasibility study reports by examining the cases of five national science museums. Next, to improve the predictive accuracy of the gravity model, the study identified the five most likely issues contributing to errors, applied modified values, and recalculated. The potential for improvement was then evaluated through a comparison of forecasting errors. Findings - First, among the five science museums with very similar characteristics, there was no clear indication of a decrease in the number of visitors to existing facilities due to the introduction of new facilities. Second, representing the attractiveness of tourist facilities using the facility size ratio can lead to significant prediction errors. Third, the impact of distance on demand can vary depending on the characteristics of the facility and the conditions of the area where the facility is located. Fourth, if the distance value is below 1, it is necessary to limit the range of that value to avoid having an excessively small value. Fifth, depending on the type of population data used, prediction results may vary, so it is necessary to use population data suitable for each latent market instead of simply using overall population data. Finally, if a clear trend is anticipated in a certain type of tourist behavior, incorporating this trend into the predicted values could help reduce prediction errors. Research implications or Originality - This study identified the key factors causing prediction errors by using national science museums as cases and proposed directions for improvement. Additionally, suggestions were made to apply the model more flexibly to enhance predictive accuracy. Since reducing prediction errors contributes to increased reliability of analytical results, the findings of this study are expected to contribute to policy decisions handled with more accurate information when running feasibility analyses.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.1
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• pp.23-30
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• 2015

Purpose : External markers respiratory movement measuring device (RPM; Real-time Position Management, Varian Medical System, USA) Liver Cancer Radiation Therapy Respiratory gated with respiratory signal with irradiation time and the actual research by analyzing the respiratory phase with the breathing motion measurement device respiratory tuning evaluate the accuracy of radiation therapy Materials and Methods : May-September 2014 Novalis Tx. (Varian Medical System, USA) and liver cancer radiotherapy using respiratory gated RPM (Duty Cycle 20%, Gating window 40% ~ 60%) of 16 patients who underwent total when recording the analyzed respiratory movement. After the breathing motion of the external markers recorded on the RPM was reconstructed by breathing through the acts phase analysis, for Beam-on Time and Duty Cycle recorded by using the reconstructed phase breathing breathing with RPM gated the prediction accuracy of the radiation treatment analysis and analyzed the correlation between prediction accuracy and Duty Cycle in accordance with the reproducibility of the respiratory movement. Results : Treatment of 16 patients with respiratory cycle during the actual treatment plan was analyzed with an average difference -0.03 seconds (range -0.50 seconds to 0.09 seconds) could not be confirmed statistically significant difference between the two breathing (p = 0.472). The average respiratory period when treatment is 4.02 sec (${\pm}0.71sec$), the average value of the respiratory cycle of the treatment was characterized by a standard deviation 7.43% (range 2.57 to 19.20%). Duty Cycle is that the actual average 16.05% (range 13.78 to 17.41%), average 56.05 got through the acts of the show and then analyzed% (range 39.23 to 75.10%) is planned in respiratory research phase (40% to 60%) in was confirmed. The investigation on the correlation between the ratio Duty Cycle and planned respiratory phase and the standard deviation of the respiratory cycle was analyzed in each -0.156 (p = 0.282) and -0.385 (p = 0.070). Conclusion : This study is to analyze the acts after the breathing motion of the external markers recorded during the actual treatment was confirmed in a reproducible ratios of actual treatment of breathing motion during treatment, and Duty Cycle, planned respiratory gated window. Minimizing an error of the treatment plan using 4DCT and enhance the respiratory training and respiratory signal monitoring for effective treatment it is determined to be necessary.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.409-415
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• 2022

Plant growth and development are also affected by root-zone environment. Therefore, it is important to consider the variables of the root-zone environment when establishing an irrigation strategy. The purpose of this study is to analyze the relationship between the volumetric moisture content (VWC), Bulk EC (ECb), and Pore EC (ECp) used by plant roots using FDR sensors in two types of rockwool media with different water transmission characteristics, using the method above this was used to establish a method for collecting and correcting available root-zone environmental data. For the experiment, two types of rockwool medium (RW1, RW2) with different physical characteristics were used. The moisture content (MC) and ECb were measured using an FDR sensor, ECp was measured after extracting the residual nutrient solution from the medium using a disposable syringe in the center of the medium at a volumetric moisture content (VWC) of 10-100%. Then, ECb and ECp are measured by supplying nutrient solution having different concentration (distilled water, 0.5-5.0) to two types of media (RW1, RW2) in each volume water content range (0 to 100%). The relationship between ECb and ECp in RW1 and RW2 media is best suited for cubic polynomial. The relationship between ECb and ECp according to volume moisture content (VWC) range showed a large error rate in the low volume moisture content (VWC) range of 10-60%. The correlation between the sensor measured value (ECb) and the ECp used by plant roots according to the volumetric water content (VWC) range was the most suitable for the Paraboloid equation in both media (RW1, RW2). The coefficient of determination the calibration equation for RW1 and RW2 media were 0.936, 0.947, respectively.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.213-225
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• 2018

In order to access the accuracy of the gridded daily Advanced Scatterometer (hereafter DASCAT) ocean surface wind data in the surrounding of Korea, the DASCAT was compared with the wind data from buoys. In addition, the reanalysis data for wind at 10 m provided by European Centre for Medium-Range Weather Forecasts (ECMWF, hereafter ECMWF), National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR, hereafter NCEP), Modern Era Retrospective-analysis for Research and Applications-2 (MERRA-2, hereafter MERRA) were compared and analyzed. As a result, the RMSE of DASCAT for the actual wind speed is about 3 m/s. The zonal components of wind of buoys and the DASCAT have strong correlation more than 0.8 and the meridional components of wind them have lower correlation than that of zonal wind and are the lowest in the Yellow Sea (r=0.7). When the actual wind speed is below 10 m/s, the EMCWF has the highest accuracy, followed by DASCAT, MERRA, and NCEP. However, under the wind speed more than 10 m/s, DASCAT shows the highest accuracy. In the nature of error according to the wind direction, when the zonal wind is strong, all dataset has the error of more than $70^{\circ}$ on the average. On the other hand, the RMSE of wind direction was recorded $50^{\circ}$ under the strong meridional winds. ECMWF shows the highest accuracy in these results. The RMSE of the wind speed according to the wind direction varied depending on the actual wind direction. Especially, MERRA has the highest RMSE under the westerly and southerly wind condition, while the NCEP has the highest RMSE under the easterly and northerly wind condition.

• The Korean Journal of Nuclear Medicine Technology
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• v.21 no.2
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• pp.44-48
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• 2017

Purpose Estradiol (E2) is a steroid hormone mainly produced in women and is a useful indicator for diagnosis of gynecological diseases, menstrual cycle, menopause, and precocious puberty. E2 measurement is performed by diluting the $^{125}I$ radioactive tracer and tracer buffer in the kit. However, It was not precisely specified when the period of tracer is available after activating. The purpose of this study was to determine the appropriate dilution time based on the measurement value with dilution time. Materials and Methods From December 2016 to February 2017, 60 E2 samples with concentrations ranging from 8 to 4577 pg/mL were divided into low, medium, and high concentrations. Dilution of the $^{125}I$ tracer was performed on a 230 RPM agitator for 30 minutes, 1 hour 30 minutes, and 2 hours 30 minutes, respectively. 24 hour dilution was gently shaken and refrigerated. To verify the difference and significance of the results according to the dilution time, a test of normality was performed using SPSS 18.0 and analyzed by Kruskal-Wallis test. The measured value according to the dilution time was compared with the interquartile range of the absolute error. Results The results of Kruskal-Wallis test were not significant (P>0.05). Measurement results are showed as interquartile range of absolute error. At low concentration, it is 0.052 between 1 hour 30 minutes and 2 hours 30 minutes, and 0.105 between 30 minutes and 1 hour 30 minutes. At medium concentration, 0.062 between 30 minutes and 1 hour 30 minutes, and 0.038 between 1 hour 30 minutes and 2 hours 30 minutes. At high concentration, it is 0.029 between 1 hour 30 minutes and 2 hours 30 minutes, and 0.06 between 2 hours 30 minutes and 24 hours. Conclusion There were no statistically significant differences. However, the change in the measured value is the smallest between 1 hour and 30 minutes to 2 hours and 30 minutes. Therefore, we recommend diluting time between 1 hour 30 minutes and 2 hours 30 minutes.