• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.421-430
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• 2004

Clinically, it is almost impossible for a physician to distinguish subtle changes of frequency spectrum by using a stethoscope alone especially in the early stage of thrombus formation. Considering that reliability of mechanical valve is paramount because the failure might end up with patient death, early detection of valve thrombus using noninvasive technique is important. Thus the study was designed to provide a tool for early noninvasive detection of valve thrombus by observing shift of frequency spectrum of acoustic signals with computer aid diagnosis system. A thrombus model was constructed on commercialized mechanical valves using polyurethane or silicon. Polyurethane coating was made on the valve surface, and silicon coating on the sewing ring of the valve. To simulate pannus formation, which is fibrous tissue overgrowth obstructing the valve orifice, the degree of silicone coating on the sewing ring varied from 20％, 40％, 60％ of orifice obstruction. In experiment system, acoustic signals from the valve were measured using microphone and amplifier. The microphone was attached to a coupler to remove environmental noise. Acoustic signals were sampled by an AID converter, frequency spectrum was obtained by the algorithm of spectral analysis. To quantitatively distinguish the frequency peak of the normal valve from that of the thrombosed valves, analysis using a neural network was employed. A return map was applied to evaluate continuous monitoring of valve motion cycle. The in-vivo data also obtained from animals with mechanical valves in circulatory devices as well as patients with mechanical valve replacement for 1 year or longer before. Each spectrum wave showed a primary and secondary peak. The secondary peak showed changes according to the thrombus model. In the mock as well as the animal study, both spectral analysis and 3-layer neural network could differentiate the normal valves from thrombosed valves. In the human study, one of 10 patients showed shift of frequency spectrum, however the presence of valve thrombus was yet to be determined. Conclusively, acoustic signal measurement can be of suggestive as a noninvasive diagnostic tool in early detection of mechanical valve thrombosis.

• Journal of Korea Water Resources Association
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• v.47 no.6
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• pp.537-546
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• 2014

Surface image velocimetry was introduced as an efficient and sage alternative to conventional river flow measurement methods during floods. The conventional surface image velocimetry uses a pair of images to estimate velocity fields using cross-correlation analysis. This method is appropriate to analyzing images taken with a short time interval. It, however, has some drawbacks; it takes a while to analyze images for the verage velocity of long time intervals and is prone to include errors or uncertainties due to flow characteristics and/or image taking conditions. Methods using spatio-temporal images, called STIV, were developed to overcome the drawbacks of conventional surface image velocimetry. The grayscale-gradient tensor method, one of various STIVs, has shown to be effectively reducing the analysis time and is fairly insusceptible to any measurement noise. It, unfortunately, can only be applied to the main flow direction. This means that it can not measure any two-dimensional flow field, e.g. flow in the vicinity of river structures and flow around river bends. The present study aimed to develop a new method of analyzing spatio-temporal images in two-dimension using cross-correlation analysis. Unlike the conventional STIV, the developed method can be used to measure two-dimensional flow substantially. The method also has very high spatial resolution and reduces the analysis time. A verification test using artificial images with lid-driven cavity flow showed that the maximum error of the method is less than 10 % and the average error is less than 5 %. This means that the developed scheme seems to be fairly accurate, even for two-dimensional flow.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.289-298
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• 2019

In this present study, the effects of Signal to Noise Ratio (SNR), Full Width Half Maximum (FWHM), Aerosol Optical Depth (AOD), $O_3$ Vertical Column Density ($O_3$ VCD), and Solar Zenith Angle (SZA) on the accuracy of sulfur dioxide Vertical Column Density ($SO_2$ VCD) retrieval have been quantified using the Differential Optical Absorption Spectroscopy (DOAS) method with the ground-based direct-sun synthetic radiances. The synthetic radiances produced based on the Beer-Lambert-Bouguer law without consideration of the diffuse effect. In the SNR condition of 650 (1300) with FWHM = 0.6 nm, AOD = 0.2, $O_3$ VCD = 300 DU, and $SZA=30^{\circ}$, the Absolute Percentage Difference (APD) between the true $SO_2$ VCD values and those retrieved ranges from 80% (28%) to 16% (5%) for the $SO_2$ VCD of $8.1{\times}10^{15}$ and $2.7{\times}10^{16}molecules\;cm^{-2}$, respectively. For an FWHM of 0.2 nm (1.0 nm) with the $SO_2$ VCD values equal to or greater than $2.7{\times}10^{16}molecules\;cm^{-2}$, the APD ranges from 6.4% (29%) to 6.2% (10%). Additionally, when FWHM, SZA, AOD, and $O_3$ VCD values increase, APDs tend to be large. On the other hand, SNR values increase, APDs are found to decrease. Eventually, it is revealed that the effects of FWHM and SZA on $SO_2$ VCD retrieval accuracy are larger than those of $O_3$ VCD and AOD. The SZA effects on the reduction of $SO_2$ VCD retrieval accuracy is found to be dominant over the that of FWHM for the condition of $SO_2$ VCD larger than $2.7{\times}10^{16}molecules\;cm^{-2}$.

• Journal of the Korean Society of Radiology
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• v.13 no.1
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• pp.65-71
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• 2019

With regard to current Neck CT, Bismuth shielding boards are often being used to reduce exposure to superficial organs such as the thyroid. However, beam hardening often occurs near superficial organs with Bismuth shielding boards and variations in CT Number, Noise, and Uniformity values occur severely. This study looked into the usefulness of shielding boards made from aluminum and silicone that can be easily obtained and have good machinability by comparing them to the existing Bismuth shielding board. An Aluminum 7.3mm and a Silicone 21.5mm were made with shielding ratios similar to that of the Bismuth(0.06 mmPb). TLD (TLD-100) was placed on the thyroid area of the Phantom (RS-108T) and 5 doses were measured for each. To compare image quality, CT Number and Noise variations in axial images of the thyroid area in Neck CT images were compared. Also, variations in CT Number, Noise, and Uniformity were measured in the AAPM phantom images and compared. In the results, when thyroid doses for each shielding board were compared, the Bismuth shielding board showed a 14% reduction, the Silicone 21.5mm showed a 15% reduction, and the Aluminum 7.3mm showed a 13% reduction compared to the Non-Shield. Statistically, there were no significant differences in comparison with the Bismuth shielding board. In CT Number variations of thyroid area images, variations were largest for the Bismuth shielding board. With Uniformity evaluations of the AAPM phantom, the Bismuth shielding board was found unsuitable and the Aluminum 7.3mm and Silicone 21.5mm satisfied the acceptance criteria. Research results show that the Aluminum 7.3mm and Silicone 21.5mm have a similar shielding ratio to the high-priced Bismuth shielding board that is currently being used clinically and in comparison tests of CT Number attenuation coefficient variations, Noise, and Uniformity which are phantom image evaluation items, they proved to be better than Bismuth shielding boards. If various shielding boards are made using aluminum and silicone, sized appropriately for superficial organs, it would be useful in decreasing patient doses.

• Journal of Practical Agriculture & Fisheries Research
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• v.11 no.1
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• pp.79-94
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• 2009

The research project was conducted to develop a paper bagging machine for grape. This technology was aimed to highly reduce a labor for paper bagging in grape and bakery. In agriculture labor and farm population has rapidly decreased since 1980 in Korea so there was so limit in labor. In particular there is highly population in women and old age at rural area and thus labor cost is so high. Therefore a labor saving technology in agricultural sector might be needed to be replaced these old age with mechanical and labor saving tool in agriculture. The following was summarized of the research results for development of a paper bagging machine for grape. 1. Development of a new paper bagging machine for grape - This machine was designed by CATIA VI2/AUTO CAD2000 programme. - A paper bagging machine was mechanically binded a paper bag of grape which should be light and small size. This machine would be designed for women and old age with convenience during bagging work at the field site. - This machine was manufactured with total weight of less than 350g. - An overage bagging operation was more than 99% at the actual field process. - A paper bagging machine was designed with cartridge type which would be easily operated between rows and grape branches under field condition. - The type of cartridge pin was designed as a C-ring type with the length of 500mm which was good for bagging both grape and bakery. - In particular this machine was developed to easily operated among vines of the grape trees. 2. Field trials of a paper bagging machine in grape - There was high in grape quality as compared to the untreated control at the application of paper bagging machine. - The efficiency of paper bagging machine was 102% which was alternative tool for the conventional. - The roll pin of paper bagging machine was good with 5.3cm in terms of bagging precision. - There was no in grape quality between the paper bagging machine and the conventional method. - Disease infection and grape break was not in difference both treatments.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.305-314
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• 2023

With the development of medical technology and radiation treatment equipment, the frequency of high-precision radiation therapy such as intensity modulation radiation therapy has increased. Image-guided radiation therapy has become essential for radiation therapy in precise and complex treatment plans. In particular, with the introduction of imaging equipment for diagnosis in a linear accelerator, CBCT scanning became possible, which made it possible to calibrate and correct the patient's posture through 3D images. Although more precise reproduction of the patient's posture has become possible, the exposure dose delivered to the patient during the image acquisition process cannot be ignored. Radiation optimization is necessary in the field of radiation therapy, and efforts to reduce exposure are necessary. However, when acquiring 3D CBCT images by changing the imaging conditions to reduce exposure, there should be no image quality or artefacts that would make it impossible to align the patient's position. In this study, Rando phantom was used to scan and evaluate images for each shooting condition. The highest SNR was obtained at 100 kV 80 mA 25 ms F1 filter 180°. As the tube voltage and tube current increased, the noise decreased, and the bowtie filter showed the optimal effect at high tube current. Based on the actual scanned images, it was confirmed that patient alignment was possible under all imaging conditions, and that image-guided radiation therapy for patient alignment was possible under the condition of 70 kV 10 mA 20 ms F0 filter 180°, which showed the lowest SNR. In this study, image evaluation was conducted according to the imaging conditions, and low tube voltage, tube current, and small rotation angle scan are expected to be effective in reducing radiation exposure. Based on this, the patient's exposure dose should be kept as low as possible during CBCT imaging.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.2
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• pp.22-27
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• 2014

Purpose There is the recent PET/CT scan in tendency that use low dose to reduce patient's exposure along with development of equipments. We diminished $^{18}F$-FDG dose of patient to reduce patient's exposure after setting up GE Discovery 690 PET/CT scanner (GE Healthcare, Milwaukee, USA) establishment at this hospital in 2011. Accordingly, We evaluate acquisition time per proper bed by change of infusion dose to maintain quality of image of PET/CT scanner. Materials and Methods We inserted Air, Teflon, hot cylinder in NEMA NU2-1994 phantom and maintained radioactivity concentration based on the ratio 4:1 of hot cylinder and back ground activity and increased hot cylinder's concentration to 3, 4.3, 5.5, 6.7 MBq/kg, after acquisition image as increase acquisition time per bed to 30 seconds, 1 minute, 1 minute 30 seconds, 2 minute, 2 minutes 30 seconds, 3 minutes, 3 minutes 30 seconds, 4 minutes, 4 minutes 30 seconds, 5 minutes, 5 minutes 30 seconds, 10 minutes, 20 minutes, and 30 minutes, ROI was set up on hot cylinder and back radioactivity region. We computated standard deviation of Signal to Noise Ratio (SNR) and BKG (Background), compared with hot cylinder's concentration and change by acquisition time per bed, after measured Standard Uptake Value maximum ($SUV_{max}$). Also, we compared each standard deviation of $SUV_{max}$, SNR, BKG following in change of inspection waiting time (15minutes and 1 hour) by using 4.3 MBq phantom. Results The radioactive concentration per unit mass was increased to 3, 4.3, 5.5, 6.7 MBqs. And when we increased time/bed of each concentration from 1 minute 30 seconds to 30 minutes, we found that the $SUV_{max}$ of hot cylinder acquisition time per bed changed seriously according to each radioactive concentration in up to 18.3 to at least 7.3 from 30 seconds to 2 minutes. On the other side, that displayed changelessly at least 5.6 in up to 8 from 2 minutes 30 seconds to 30 minutes. SNR by radioactive change per unit mass was fixed to up to 0.49 in at least 0.41 in 3 MBqs and accroding as acquisition time per bed increased, rose to up to 0.59, 0.54 in each at least 0.23, 0.39 in 4.3 MBqs and in 5.5 MBqs. It was high to up to 0.59 from 30 seconds in radioactivity concentration 6.7 MBqs, but kept fixed from 0.43 to 0.53. Standard deviation of BKG (Background) was low from 0.38 to 0.06 in 3 MBqs and from 2 minutes 30 seconds after, low from 0.38 to 0 in 4.3 MBqs and 5.5 MBqs from 1 minute 30 seconds after, low from 0.33 to 0.05 in 6.7 MBqs at all section from 30 seconds to 30 minutes. In result that was changed the inspection waiting time to 15 minutes and 1 hour by 4.3 MBq phantoms, $SUV_{max}$ represented each other fixed values from 2 minutes 30 seconds of acquisition time per bed and SNR shown similar values from 1 minute 30 seconds. Conclusion As shown in the above, when we increased radioactive concentration per unit mass by 3, 4.3, 5.5, 6.7 MBqs, the values of $SUV_{max}$ and SNR was kept changelessly each other more than 2 minutes 30 seconds of acquisition time per bed. In the same way, in the change of inspection waiting time (15 minutes and 1 hour), we could find that the values of $SUV_{max}$ and SNR was kept changelessly each other more than 2 minutes 30 seconds of acquisition time per bed. In the result of this NEMA NU2-1994 phantom experiment, we found that the minimum acquisition time per bed was 2 minutes 30 seconds for evaluating values of fixed $SUV_{max}$ and SNR even in change of inserting radioactive concentration. However, this acquisition time can be different according to features and qualities of equipment.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.