• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.66-77
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• 2011

We propose a framework for grouping photographic advertising images that employs a hierarchical indexing scheme based on efficient feature combinations. The study provides one specific application of effective tools for monitoring photographic advertising information through online and offline channels. Specifically, it develops a preprocessor for advertising image information tracking. We consider both global features that contain general information on the overall image and local features that are based on local image characteristics. The developed local features are invariant under image rotation and scale, the addition of noise, and change in illumination. Thus, they successfully achieve reliable matching between different views of a scene across affine transformations and exhibit high accuracy in the search for matched pairs of identical images. The method works with global features in advance to organize coarse clusters that consist of several image groups among the image data and then executes fine matching with local features within each cluster to construct elaborate clusters that are separated by identical image groups. In order to decrease the computational time, we apply a conventional clustering method to group images together that are similar in their global characteristics in order to overcome the drawback of excessive time for fine matching time by using local features between identical images.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Journal of the Korean Society of Radiology
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• v.13 no.7
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• pp.955-960
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• 2019

The Computed tomography (CT) scan can have high radiation in a few tests, and this risk is significant given that it is often repeated in one patient. In children, the incidence of radiation-induced cancer is reported because organs are growing, are more sensitive to radiation. 3D printing has recently been studied to be applied to various applications as a research field for 3D printing applications, research on fabrication of radiation shields and materials has been conducted. The purpose of the 3D printer is to replace the existing panel-type shields and to make customized designs according to the shape of the human body. Therefore, research on 3D information processing to be input to the 3D printer is also necessary. In this study, 3D data of the human body surface, which is the preliminary step of the manufacture of patient-specific eye shield using stereo vision depth map technology, was studied. This study aims to increase the possibility of three-dimensional output. As a result of experimenting with this method, which is relatively simple compared with other methods of 3D information processing, the minimum coordinates for 3D information are extracted. The results of this study provided the advantages and limitations of stereo images using natural light and will be the basic data for the manufacture of eye shields in the future.

• Journal of Microbiology and Biotechnology
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• v.14 no.6
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• pp.1239-1248
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• 2004

The methylotrophic yeast Hansenula polymorpha has been extensively studied as a model organism for methanol metabolism and peroxisome biogenesis. Recently, this yeast has also attracted attention as a promising host organism for recombinant protein production. Here, we describe the fabrication and evaluation of a DNA chip spotted with 382 open reading frames (ORFs) of H. polymorpha. Each ORF was PCR-amplified using gene-specific primer sets, of which the forward primers had 5'-aminolink. The PCR products were printed in duplicate onto the aldehyde-coated slide glasses to link only the coding strands to the surface of the slide via covalent coupling between amine and aldehyde groups. With the partial genome DNA chip, we compared efficiency of direct and indirect cDNA target labeling methods, and found that the indirect method, using fluorescent-labeled dendrimers, generated a higher hybridization signal-to-noise ratio than the direct method, using cDNA targets labeled by incorporation of fluorescence-labeled nucIeotides during reverse transcription. In addition, to assess the quality of this DNA chip, we analyzed the expression profiles of H. polymorpha cells grown on different carbon sources, such as glucose and methanol, and also those of cells treated with the superoxide­generating drug, menadione. The profiles obtained showed a high-level induction of a set of ORFs involved in methanol metabolism and oxidative stress response in the presence of methanol and menadione, respectively. The results demonstrate the sensitivity and reliability of our arrays to analyze global gene expression changes of H. polymorpha under defined environmental conditions.

• Quality Improvement in Health Care
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• v.5 no.2
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• pp.324-334
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• 1998

Background : Strategic planning is an organizationwide or systemwide, ongoing look into the future usually of 2~3 years, based on objective analysis of the current environment and trends, but it can incorporate both short-term and long-term goals. The strategic planning process includes external analysis, internal analysis, issue analysis, development of mission, vision and values, and lastly development of organizational goals and objectives. As a part of the strategic quality planning process, certain service lines, important organizationwide functions, or key processes supporting these functions can be prioritized to expedite and roll out certain strategic goals. This is called strategic quality initiatives. Methods : We organized a quality improvement team, a subgroup of 21st century vision planning corps of our medical center, and pursued QI activities for improvement of healthcare environment, particularly in the admission setting. We developed a strategic quality initiative based on the results of patient satisfaction surveys, and carried out functions of self-directed work team. Results : The strategic goal was to be the benchmark for peer group hospitals in Korea for providing cost-effective best-practice. The QI team included 3 medical doctors, 1 nurse, 1 social worker, and 1 QI consultant as well as many operational members to support services and quality initiatives met every Tuesday for 18 weeks. Outcome objectives were to improve patient satisfaction score. The issues included in the objectives were comfort, temperature, noise, cleanliness of the admission wards, quality and education of patient meals, matters regarding the admission process, and an appurtenant facility such as restaurant or convenience store. Every issue was discussed and recommendations, conclusions and opportunities were implemented. Conclusions : By developing a strategic quality initiative as a part of the strategic quality planning process, and pursuing a self-directed work team, certain sen/ice lines, important organizationwide functions, or key processes supporting these functions can be improved effectively within a short period. Strategic quality initiatives serve to support, or roll out, certain strategic goals that are relevant to performance improvement and development of specific measurable outcome objectives, and associated performance measure for each initiative. Each strategic quality initiative should include a statement of intent outcome objectives, and performance measures. We will come back with follow up of the strategic quality initiative, for improvement of healthcare environment, and results of patient satisfaction re-survey.

• Journal of Korean Medicine Rehabilitation
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• v.27 no.4
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• pp.33-53
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• 2017

Objectives This study was designed to review animal studies about the efficacy of herbal medicine for Rheumatoid arthritis animal model which was published in Korea after 2008. We also systematically investigated the reporting quality of the animal studies. Methods We systematically searched original articles in 8 databases since 2008. And manual searching was conducted through 10 Korean medicine journals from 2008. Studies were included if they used animal experimental model(s) with orally administered herbal medicine. Data were extracted regarding animal model, rheumatoid arthritis indicator and detail of intervention. Reporting quality of each study was also assessed by the STARA and ARRIVE guidelines. Results Nine hundred two articles were screened. Finally, 35 articles were included. 35 studies all showed that the herbal medicine used in the studies has significant effect on alleviating the macroscopic indicators, hematological indicators, histological indicators, genetic indicators, osteological indicator of Rheumatoid Arthritis and others. Species of animals was reported in 100% while ventilation and noise were reported in 0% in STRASA guidelines. Ethical statement was reported in 42.9%, experimental animals and sample size were reported in 24%, 29% and there was no study reporting funding. Conclusions These results suggest that herbal medicine might be effective treatment for Rheumatoid Arthritis. It should be improved by clinical studies. And there is a need for studying about efficacy and safety of each specific herbal medicine. And we should improve the Reporting quality of the animal studies published in Korea.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.62-70
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• 2011

Nowadays image sensor is an essential component in many multimedia devices, and it is covered by a color filter array to filter out specific color components at each pixel. We need a certain algorithm to combine those color components reconstructed a full color image from incomplete color samples output from an image sensor, which is called a demosaicking process. Most existing demosaicking algorithms are developed for ideal image sensors, but they do not work well for the practical cases because of dissimilar characteristics of each sensor. In this paper, we propose a new demosaicking algorithm in which the color filter characteristics are fully utilized to generate a good image. To demonstrate significance of our algorithm, we used a commerically available sensor, CBN385B, which is a sort of Honeycomb-style CFA(Color Filter Array) CCD image sensor. As a performance metric of the algorithm, PSNR(Peak Signal to Noise Ratio) and RGB distribution of the output image are used. We first implemented our algorithm in C-language for simulation on various input images. As a result, we could obtain much enhanced images whose PSNR was improved by 4~8 dB compared to the commonly idealized approaches, and we also could remove the inclined red property which was an unique characteristics of the image sensor(CBN385B).Then we implemented it in hardware to overcome its problem of computational complexity which made it operate slow in software. The hardware was verified on Spartan-3E FPGA(Field Programable Gate Array) to give almost the same performance as software, but in much faster execution time. The total logic gate count is 45K, and it handles 25 image frmaes per second.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.2
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• pp.5-12
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• 2000

Uncooled metallic thin-film thermopile infrared detectors have been fabricated, and the figures of merit for the detectors were examined. The hot junctions of a thermopile were prepared on a $Si_{3}N_{4}/SiO_{2}/Si_{3}N_{4}$-membrane which acts as a thermal isolation layer, the cold junctions on the membrane supported with the silicon rim which functions as a heat sink, and Au-black was used as an infrared absorber. Infrared absorbance of Au-black, which strongly depends on the chamber pressure during Au-evaporation and its mass per area, was found to be about 90 ％ in the wavelength range from 3${\mu}{\textrm}{m}$ to 14${\mu}{\textrm}{m}$. Voltage responsivity, noise equivalent power, and specific detectivity of Bi-Sb thermopile infrared detector at 5 Hz-chopping frequency were about 10.5V/W, 2.3 nW/Hz$^{1/2}$, 및 $1.9\times10^{7}$ cm.Hz$^{1/2}$/w at room temperature in air, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2027-2035
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• 2001

In this paper, we present an audio stream delivery using the AMR (Adaptive Multi-Rate) coder that was adopted by ETSI and 3GPP as a standard vocoder for next generation IMT-2000 service in which includes combined sender (FEC) and receiver reconstruction technique in the Internet. By use of the media-specific FEC scheme, the possibility to recover lost packets can be much increased due to the addition of repair data to a main data stream, by which the contents of lost packets can be recovered. The AMR codec is based on the code-excited linear predictive (CELP) coding model. So we use a frame erasure concealment for CELP-based coders. The proposed scheme is evaluated with ITU-T G.729 (CS-ACELP) coder and AMR - 12.2 kbit/s through the SNR (Signal to Noise Ratio) and the MOS (Mean Opinion Score) test. The proposed scheme provides 1.1 higher in Mean Opinion Score value and 5.61 dB higher than AMR - 12.2 kbit/s in terms of SNR in 10% packet loss, and maintains the communicab1e quality speech at frame erasure rates lop to 20%.