• Journal of Life Science
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• v.26 no.8
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• pp.911-920
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• 2016

Norovirus is the most common causative agent of acute gastroenteritis. This study was carried out to investigate molecular epidemiology of norovirus infections from outbreaks in Busan from 2012 to 2015. Total of 581 stool specimens were collected from diarrhea patients in outbreaks in Busan, 71 samples were resulted in positive to norovirus. The data were analyzed according to seasonality, patient, age and gender. Noroviruses were detected most frequently during the winter season from November (25.4%) to February (28.2%). The age group from teens was the most susceptible to norovirus infections. To obtain the molecular genetic information of norovirus, we performed sequencing analyses of the strains detected. Norovirus genotypes have been reported to show high genetic diversity. Four kinds of GI genotypes (GI-1, GI-2, GI-3, GI-5) and five kinds of GII genotypes (GII-1, GII-4, GII-5, GII-6, GII-17) were indentified in outbreaks in Busan. Other previous studies have shown that GII-4 is the most predominant circulating in Korea and worldwide. The most prevalent norovirus genotypes of each year were GII-6 in 2012, GII-6 in 2013, GII-4 in 2014 and GII-6 in 2015. Except for 2014, GII-6 genotype was the most prevalent and predominant in Busan. We described the epidemiological analysis of the noroviruses in outbreaks in Busan. The result of this study will contribute to update the epidemiological data and improve hygiene and public health via sustainable surveillance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.909-916
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• 2009

This paper presents the automatic vision algorithm to generate and calibrate reference phase plane to improve the accuracy of 3D measuring machine of using phase shifting projection moire method, which is not traditional N-bucket method, but is based on direct image processing method to the pattern projection image. Generally, to acquire accurate reference phase plane, the calibration specimen with well treated surface is needed, and detailed calibration method should be performed. For the cost reduction of specimen manufacturing and the calibration time reduction, on the specimen, not specially designed, with general accuracy level, an efficient calibration procedure for the reference phase generation is proposed. The proposed vision algorithm is developed to extract the line center points of the projected line pattern from acquired images, derive the line feature information consisting of its slope and intercept by using sampled feature points, and finally generate the related reference phase between line pairs. Experimental results show that the proposed method make reference phase plane with a good accuracy under noisy environment and the proposed algorithm can reduce the total cost to make high accurate calibration specimen, also increase the accuracy of reference phase plane, and reduce the complex calibration procedure to move grid via N-bucket algorithm precisely.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.104-109
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• 2010

The lighting reflection is a common problem in image analysis and causes the many difficulties to extract distinct features in related fields. Furthermore, the problem grows in the rainy night. In this paper, we aim to remove light reflection effects and reconstruct a road surface without lighting reflections in order to extract distinct features. The proposed method utilizes a 3D analysis based on a multiple geometry using captured images, with which we can combine each reflected areas; that is, we can remove lighting reflection effects and reconstruct the surface. At first, the regions of lighting sources and reflected surfaces are extracted by local maxima based on vertically projected intensity-histograms. After that, a fundamental matrix and homography matrix among multiple images are calculated by corresponding points in each image. Finally, we combine each surface by selecting minimum value among multiple images and replace it on a target image. The proposed method can reduces lighting reflection effects and the property on the surface is not lost. While the experimental results with collected data shows plausible performance comparing to the speed, reflection-overlapping areas which can not be reconstructed remain in the result. In order to solve this problem, a new reflection model needs to be constructed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.7
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• pp.1797-1806
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• 1998

Future satellite communication systems will be developed at Ka-band (20/30 GHz) owing to the relatively wide frequency allocation and current freedom from terrestrial interference for multimedia services. A serious disadvantage of the Ka-band, however, is the very high atmospheric attenuation in rainy weather. Synchronous CDMA drastically redces the effect of self-noise with several interesting features of CDMA for mobile communications such as fixible freuqncy rese, the capability of performin soft-handover and a lower sensitivity to interference. This paper evaluates the performance of a synchronous CDMA reture link for a Ka-band geostationary satellite communication system. For a fixed satellite channel whose characteristics depend on weather conditions, the signal envelope and phase for this channel is modelled as Gaussian. The bit error and outage probability, and the detection loss due to imperfect chip timing synchronization is analytically evaluated and the system capacity degaradation due to the weather condition is estimated. The two cases consist of the general case in which all users are affected by rain condition, and the worst case in which the reference user is only affected by rain attenuation. the results for two cases of rain condition clearly show that synchronous CDMA eases the power control requirements and has less sensitivity to imperfect power control.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.11-17
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• 2022

In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

• Korean Journal of Clinical Laboratory Science
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• v.47 no.2
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• pp.83-89
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• 2015

Although Mycobacterium tuberculosis complex strains remain responsible for the majority of diseases caused by mycobacterial infections worldwide, the increase in HIV (human immuno deficiency virus) infections has allowed for the emergence of other non-tuberculous mycobacteria as clinically significant pathogens. M. tuberculosis was detected by two-tube nested polymerase chain reaction (PCR) and non-tuberculous mycobacteria was detected by PCR-restriction fragment length polymorphism (RFLP) with Msp I. Result of niacin test is equal to result of two-tube nested PCR after culture for M. tuberculosis. In this study, acid fast bacilli stain (AFB. stain) >2+ case, Detection of Mycobacteria is similar to result before culture and after culture. AFB. stain <1+ case, result of mycobacteria is distinguished. Conclusionly, these results suggest that identification of mycobacteria must go side by side both culture and PCR for more fast and accuracy.

• Parasites, Hosts and Diseases
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• v.34 no.1
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• pp.1-6
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• 1996

Mccroorchis spinuLosw Ando, 1918 (Digenea: Nanophyetidael is redescribed based on adult flukes recovered from experimental mice, rats and cats which were fed with metacercariae encysted in the muscle of the crayfish, Cambnroines similis. A total of 117 adult flukes were harvested from the small intestine of the experimental animals at S-21 days post-infection. The worm recovery rate was 31-37%, not significantly different among the three kinds of animals. The metacercariae were round, 0.18 mm in average diameter, encysted with two layers of thick walls, and possessing a stylets on the oral sucker and Y- shaped exc retory bladder. The adult flukes were oval, 0.66-0.71 mm long and 0.36-0.41 mm wide, and characterized by the presence of a stylet on the oral sucker, variable location of the ovary near the mid-portion of the body, bilobed seminal vesicle, and anterolateral location of two testes. These morphological features were a little different from the original description, hence, an emended version of M. spinulosw was given. M. spinuLosw is a new intestinal trematode of animals and possibly man in Korea.

• Applied Chemistry for Engineering
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• v.35 no.2
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• pp.67-78
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• 2024

Light absorption has potential as a signal in biochemical analyses due to its simplicity in measurement and interpretational clarity. Among substances that generate absorption signals, gold nanoparticles possess advantages such as chemical stability, biological compatibility, and unique optical properties from the localized surface plasmon resonance (LSPR) in the visible light range. They also exhibit versatility compared to other colorimetric substances effective only for specific target molecules, as they easily conjugate with various detection active substances like antibodies and aptamers. Particularly due to advantages such as low cost, ease of particle synthesis, and high environmental stability compared to enzyme-based colorimetric methods, gold nanoparticles are extensively researched as signal substances in colorimetric assays. This review summarizes various strategies utilizing gold nanoparticles as absorption signal substances, focusing on recent research. Based on the characteristics of gold nanoparticles, where the optical property is influenced by particle morphology, literature is classified and reviewed based on strategies controlling the shape of gold nanoparticles during signal generation. Through this, it is observed that gold nanoparticles, which have been used as absorption signal substances, continue to be actively researched, affirming their potential for broad and continuous improvement in the future.

• Korean Journal of Heritage: History & Science
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• v.53 no.2
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• pp.242-253
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• 2020

Six ornamental metal quiver fittings were excavated from stone chamber No.1 of the ancient tombs of Jeongchon, Bokam-ri, Naju. The ornamental quiver fittings are metal, but the body of the quiver was made of organic material, so that it corroded and disappeared in the burial environment. The ornamental metal quiver fittings were made in pairs, and decorated one quiver according to the location they were found in and their forms. The ornamental metal quiver fitting can be divided into two types: A band style ornament (帶輪狀金具) which decorates the arrow pouch, and a board style ornament (板狀金具) which decorates the board connecting the waist belt. Two ornamental metal quiver fittings excavated from wooden coffin 2 of stone chamber No.1, were made in the band style, while the ornamental metal quiver fittings from southeast of stone chamber No.1 were identified as two boardstyle ornaments and two band-style ornaments for what was presumed to be belt loops. Material analysis of the ornamental metal quiver fittings shows that they are made of a gilt bronze plate attached to an iron plate, and the surface is marked with a speck of chisel to make lines and patterns. Chemical composition analysis (XRF) established that 24~40wt% Au and 50~93wt% Cu were detected on the gold surface, and it was confirmed that bronze corrosion had taken place on the gilt surface. SEM-EDS analysis of the gold plating layer identified a working line for glossing, and 7~9wt% Hg and an amalgam of gilt layers was detected, confirming the amalgam gilding. CT and FT-IR analysis established that the band style was double-layered with silk fabric under the iron plate, and there was also a lacquer piece underneath. The band-style ornaments have two layers of silk under the iron plate, along with lacquer pieces. Adding the fabric to the arrow pouch increases adhesion and decorative value. It is assumed that the lacquer pieces indicate that the surface of the lacquered arrow pouch had fallen together with the ornaments. On the other hand, the board-style ornaments have a thick layer of organic matter under the iron plate, but this is difficult to identify and appears to be a remnant of the quiver board. The characteristics of these ornamental metal quiver fittings were similar in Baekje, Silla, and Gaya cultures from the late 4th to the late 5th centuries, and enable us to identify the art of ancient gold craftwork at that time.

• Journal of the Korean Society of Radiology
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• v.14 no.6
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• pp.773-780
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• 2020

With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.