• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.43 no.11 s.353
• /
• pp.37-47
• /
• 2006

This work proposes a 10b 25MS/s $0.8mm^2$ 4.8mW 0.13um CMOS A/D Converter (ADC) for high-performance wireless communication systems such as DVB, DAB and DMB simultaneously requiring low voltage, low power, and small area. A two-stage pipeline architecture minimizes the overall chip area and power dissipation of the proposed ADC at the target resolution and sampling rate while switched-bias power reduction techniques reduce the power consumption of analog amplifiers. A low-power sample-and-hold amplifier maintains 10b resolution for input frequencies up to 60MHz based on a single-stage amplifier and nominal CMOS sampling switches using low threshold-voltage transistors. A signal insensitive 3-D fully symmetric layout reduces the capacitor and device mismatch of a multiplying D/A converter while low-noise reference currents and voltages are implemented on chip with optional off-chip voltage references. The employed down-sampling clock signal selects the sampling rate of 25MS/s or 10MS/s with a reduced power depending on applications. The prototype ADC in a 0.13um 1P8M CMOS technology demonstrates the measured DNL and INL within 0.42LSB and 0.91LSB and shows a maximum SNDR and SFDR of 56dB and 65dB at all sampling frequencies up to 2SMS/s, respectively. The ADC with an active die area if $0.8mm^2$ consumes 4.8mW at 25MS/s and 2.4mW at 10MS/s at a 1.2V supply.

• Progress in Medical Physics
• /
• v.21 no.2
• /
• pp.145-152
• /
• 2010

Inveon PET is a recently developed preclinical PET system for small animal. This study was conducted to measure the performance of Inveon PET as recommended by the NEMA NU 4-2008. We measured the spatial resolution, the sensitivity, the scatter fraction and the NECR using a F-18 source. A 3.432 ns coincidence window was used. A $1\;mm^3$ sized F-18 point source was used for the measurement of spatial resolution within an energy window of 350~625 keV. PET acquisition was performed to obtain the spatial resolution from the center to the 5 cm offset toward the edge of the transverse FOV. Sensitivity, scatter fraction, and NECR were measured within an energy window of 350~750 keV. For measuring the sensitivity, a F-18 line source (length: 12.7 cm) was used with concentric 5 aluminum tubes. For the acquisition of the scatter fraction and the NECR, two NEMA scatter phantoms (rat: 50 mm in diameter, 150 mm in length; mouse: 25 mm in diameter, 70 mm in length) were used and the data for 14 half-lives (25.6 hr) was obtained using the F-18 line source (rat: 316 MBq, mouse: 206 MBq). The spatial resolution of the F-18 point source was 1.53, 1.50 and 2.33 mm in the radial, tangential and axial directions, respectively. The volumetric resolution was $5.43\;mm^3$ in the center. The absolute sensitivity was 6.61%. The peak NECR was 486 kcps @121 MBq (rat phantom), and 1056 kcps @128 MBq (mouse phantom). The values of the scatter fraction were 20.59% and 7.93% in the rat and mouse phantoms, respectively. The performances of the Inveon animal PET scanner were measured in this study. This scanner will be useful for animal imaging.

• Journal of the Korean Society of Radiology
• /
• v.10 no.8
• /
• pp.597-602
• /
• 2016

Recent clinical field utilizes the aluminium filter in order to reduce the low-energy photons. However, the usage of the filter can cause adverse effect on the image quality because of the scattered dose that is generated by X-ray hardening phenomenon. Further, usage of filter with improper thickness can be a reason of dose creep phenomenon where unnecessary exposure is generated towards the patient. In this study, the author evaluated the RMS and the RSD analysis in order to have a quantitative evaluation for the effect of forward scattering dose by the filter on the image. as a result of the study, the FSR and the RSD was increased together with the increasing of thickness of the filter. In this study the RSD means the standard deviation of the mean value is relatively size. It can be understood that the signal-to-noise ratio decreases when the average value is taken as a signal and the standard deviation is judged as a noise. The signal-to-noise ratio can understanding as index of resolution at image. Based on these findings, it was quantitatively verified that there is a correlation of the image quality with the FSR by using an additional filter. The results, a 2.5 mmAl which is as recommended by NCRP in the tube voltage of 70 kVp or more showed the 14.6% on the RSD when the filter was not in used. these results are considered able to be utilized as basic data for the study about the filter to improve the quality of the image.

• Korean Journal of Optics and Photonics
• /
• v.29 no.3
• /
• pp.110-118
• /
• 2018

We have designed a mid-infrared optical system for an airborne electro-optical targeting system. The mid-IR optical system is a dual-field-of-view (FOV) optics for an airborne electro-optical targeting system. The optics consists of a beam-reducer, a zoom lens group, a relay lens group, a cold stop conjugation optics, and an IR detector. The IR detector is an f/5.3 cooled detector with a resolution of $1280{\times}1024$ square pixels, with a pixel size of $15{\times}15{\mu}m$. The optics provides two stepwise FOVs ($1.50^{\circ}{\times}1.20^{\circ}$ and $5.40^{\circ}{\times}4.23^{\circ}$) by the insertion of two lenses into the zoom lens group. The IR optical system was designed in such a way that the working f-number (f/5.3) of the cold stop internally provided by the IR detector is maintained over the entire FOV when changing the zoom. We performed two analyses to investigate thermal effects on the image quality: athermalization analysis and Narcissus analysis. Athermalization analysis investigated the image focus shift and residual high-order wavefront aberrations as the working temperature changes from $-55^{\circ}C$ to $50^{\circ}C$. We first identified the best compensator for the thermal focus drift, using the Zernike polynomial decomposition method. With the selected compensator, the optics was shown to maintain the on-axis MTF at the Nyquist frequency of the detector over 10%, throughout the temperature range. Narcissus analysis investigated the existence of the thermal ghost images of the cold detector formed by the optics itself, which is quantified by the Narcissus Induced Temperature Difference (NITD). The reported design was shown to have an NITD of less than $1.5^{\circ}C$.

• Geophysics and Geophysical Exploration
• /
• v.21 no.3
• /
• pp.171-182
• /
• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.47 no.2
• /
• pp.21-31
• /
• 2010

This paper presents a design of PLL and SSCG for reducing the EMI effect at the electronic machinery and tools for DisplayPort application. This system is composed of the essential element of PLL and Charge-Pump2 and Reference Clock Divider to implement the SSCG operation. In this paper, 270MHz/162MHz dual-mode PLL that can provide 10-phase and 1.35GHz/810MHz PLL that can reduce the jitter are designed for 2.7Gbps/162Gbps DisplayPort application. The jitter can be reduced drastically by combining 270MHz/162MHz PLL with 2-stage 5 to 1 serializer and 1.35GHz PLL with 2 to 1 serializer. This paper propose the frequency divider topology which can share the divider between modes and guarantee the 50% duty ratio. And, the output current mismatch can be reduced by using the proposed charge-pump topology. It is implemented using 0.13 um CMOS process and die areas of 270MHz/162MHz PLL and 1.35GHz/810MHz PLL are $650um\;{\times}\;500um$ and $600um\;{\times}\;500um$, respectively. The VCO tuning range of 270 MHz/162 MHz PLL is 330 MHz and the phase noise is -114 dBc/Hz at 1 MHz offset. The measured SSCG down spread amplitude is 0.5% and modulation frequency is 31kHz. The total power consumption is 48mW.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.201-220
• /
• 2019

Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.57-78
• /
• 2023

COVID-19, which started in Wuhan, China in November 2019, spread beyond China in 2020 and spread worldwide in March 2020. It is important to prevent a highly contagious virus like COVID-19 in advance and to actively treat it when confirmed, but it is more important to identify the confirmed fact quickly and prevent its spread since it is a virus that spreads quickly. However, PCR test to check for infection is costly and time consuming, and self-kit test is also easy to access, but the cost of the kit is not easy to receive every time. Therefore, if it is possible to determine whether or not a person is positive for COVID-19 based on the sound of a cough so that anyone can use it easily, anyone can easily check whether or not they are confirmed at anytime, anywhere, and it can have great economic advantages. In this study, an experiment was conducted on a method to identify whether or not COVID-19 was confirmed based on a cough sound. Cough sound features were extracted through MFCC, Mel-Spectrogram, and spectral contrast. For the quality of cough sound, noisy data was deleted through SNR, and only the cough sound was extracted from the voice file through chunk. Since the objective is COVID-19 positive and negative classification, learning was performed through XGBoost, LightGBM, and FCNN algorithms, which are often used for classification, and the results were compared. Additionally, we conducted a comparative experiment on the performance of the model using multidimensional vectors obtained by converting cough sounds into both images and vectors. The experimental results showed that the LightGBM model utilizing features obtained by converting basic information about health status and cough sounds into multidimensional vectors through MFCC, Mel-Spectogram, Spectral contrast, and Spectrogram achieved the highest accuracy of 0.74.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.11 no.1
• /
• pp.79-94
• /
• 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 Intelligence and Information Systems
• /
• v.23 no.2
• /
• pp.107-122
• /
• 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.