• Korean Journal of Veterinary Research
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• v.58 no.1
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• pp.27-31
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• 2018

Canine coronavirus is a single-stranded RNA virus that causes enteritis in dogs of any age. Coronaviral enteritis is seldom definitively diagnosed, since it is usually much less severe than many other types of enteritis and is self-limiting. Conventional diagnostics for the canine coronaviral enteritis such as polymerase chain reaction (PCR), virus isolation, and electron microscopic examination are inappropriate for small animal clinics due to the complicated experimental processes involved. Therefore, a commercially available lateral flow test kit based on chromatographic immunoassay techniques was tested to evaluate its performance as a first-line diagnostic test kit that could be used in clinics. The coronavirus antigen test kit detected canine coronavirus-infected dogs with 93.1% sensitivity and 97.5% specificity. The detection limit of the test kit was between $1.97{\times}10^4/mL$ and $9.85{\times}10^3/mL$ for samples with a 2-fold serial dilution from $1.25{\times}10^6\;TCID_{50}$ ($TCID_{50}$, 50% tissue culture infectious dose). Additionally, the test kit had no cross-reactivity with canine parvovirus, distemper virus, or Escherichia coli. Overall, the commercially available test kit showed good diagnostic performance in a clinical setting, with results similar to those from PCR, confirming their potential for convenient and accurate use in small animal clinics.

• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.5
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• pp.1223-1225
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• 2006

The purpose of this study was to examine the effects of enlarging the breast by the B-secret I , II( vaccum vibrator) in women. This study was one group in a pre-test / post-test desgian with repeated measures. The experimental group of 30 patients were selected through sampling from L-oriental medicine in the P-city. The subjects received B-secret 1 , 11 ( vaccum vibrator) for 15 - 20minutes / 1 day during three months . All of the subjects were examined on the volume-size of the breast & the degree on the improvement. Prior and post surveys were measured before and after the experiment. The volume and size of the breast were measured the girth of the chest on the breast and below breast, the range on nipple and the middle point of the clavicle, the range on nipple and the middle point of the sternum, the range out of two nipple, the lineal and obligue line distance on nipple and the under crumples of breast, the height on the nipple and the under crumples of the breast, the diameter of the girth of nipple. As the effect on enlargement and the degree on the improvement of breast by B-secret 1 , 11 ( vaccum vibrator) were observed the girth of the chest on the breast, the range on nipple and the middle point of the clavicle, the range on nipple and the sternum, the height on the nipple and the under crumples of the breast.

• Journal of Astronomy and Space Sciences
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• v.36 no.3
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• pp.115-119
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• 2019

This paper is a part of the series on positron annihilation spectroscopy of two-phase diffuse gas-and-dust aggregates, such as interstellar medium and the young remnants of type II supernovae. The results obtained from prior studies were applied here to detect the relationship between the processes of the annihilation of the K-shell electrons and incident positrons, and the effects of these processes on the optical spectra of their respective atoms. Particular attention was paid to the Doppler broadening of their optical lines. The relationship between the atomic mass of the elements and the Doppler broadening, ${\Delta}{\lambda}_D$ (${\AA}$), of their emission lines as produced in these processes was established. This relationship is also illustrated for isotope sets of light elements, namely $^3_2He$, $^6_3Li$, $^7_3Be$, $^{10}_5B$ and $^{11}_5B$. A direct correlation between the ${\gamma}-line$ luminosity ( $E_{\gamma}=1.022MeV$) and ${\Delta}{\lambda}_D$ (${\AA}$) was proved virtually. Qualitative estimates of the structure of such lines depending on the positron velocity distribution function, f(E), were made. The results are presented in tabular form and can be used to set up the objectives of further studies on active galactic nuclei and young remnants of type II supernovae.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.100-108
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• 2023

In this study, a neural network model inspired by a one-dimensional convolution U-net is developed to automatically accelerate edge localized mode (ELM) detection from big diagnostic data of fusion devices and increase the detection accuracy regardless of the hyperparameter setting. This model recognizes the input signal patterns and overcomes the problems of existing detection algorithms, such as the prominence algorithm and those of differential methods with high sensitivity for the threshold and signal intensity. To train the model, 10 sets of discharge radiation data from the KSTAR are used and sliced into 11091 inputs of length 12 ms, of which 20% are used for validation. According to the receiver operating characteristic curves, our model shows a positive prediction rate and a true prediction rate of approximately 90% each, which is comparable to the best detection performance afforded by other algorithms using their optimized hyperparameters. The accurate and automatic ELM-burst detection methodology used in our model can be beneficial for determining plasma properties, such as the ELM frequency from big data measured in multiple experiments using machines from the KSTAR device and ITER. Additionally, it is applicable to feature detection in the time-series data of other engineering fields.

• IMMUNE NETWORK
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• v.16 no.5
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• pp.311-315
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• 2016

A pandemic influenza A (H1N1) virus strain was isolated from a pig farm in Korea in December 2009. The strain was propagated in and isolated from both the Madin-Darby canine kidney cell line and embryonated eggs. The partial and complete sequences of the strain were identical to those of A/California/04/2009, with >99% sequence similarity in the HA, NA, M, NS, NP, PA, PB1, and PB2 genes. The isolated strain was inactivated and used to prepare a swine influenza vaccine. This trial vaccine, containing the new isolate that has high sequence similarity with the pandemic influenza A (H1N1) virus, resulted in seroconversion in Guinea pigs and piglets. This strain could therefore be a potential vaccine candidate for swine influenza control in commercial farms.

• The Korean Journal of Physiology and Pharmacology
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• v.28 no.5
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• pp.403-411
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• 2024

The global spread of flaviviruses has triggered major outbreaks worldwide, significantly impacting public health, society, and economies. This has intensified research efforts to understand how flaviviruses interact with their hosts and manipulate the immune system, underscoring the need for advanced research tools. RNA-sequencing (RNA-seq) technologies have revolutionized our understanding of flavivirus infections by offering transcriptome analysis to dissect the intricate dynamics of virus-host interactions. Bulk RNA-seq provides a macroscopic overview of gene expression changes in virus-infected cells, offering insights into infection mechanisms and host responses at the molecular level. Single-cell RNA sequencing (scRNA-seq) provides unprecedented resolution by analyzing individual infected cells, revealing remarkable cellular heterogeneity within the host response. A particularly innovative advancement, virus-inclusive single-cell RNA sequencing (viscRNA-seq), addresses the challenges posed by non-polyadenylated flavivirus genomes, unveiling intricate details of virus-host interactions. In this review, we discuss the contributions of bulk RNA-seq, scRNA-seq, and viscRNA-seq to the field, exploring their implications in cell line experiments and studies on patients infected with various flavivirus species. Comprehensive transcriptome analyses from RNA-seq technologies are pivotal in accelerating the development of effective diagnostics and therapeutics, paving the way for innovative treatments and enhancing our preparedness for future outbreaks.

• Journal of Distribution Science
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• v.14 no.11
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• pp.83-90
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• 2016

Purpose - During the last two years, convenient stores (CS) are emerging as one of the most fast-growing retail trades in Korea. The goal of this work is to forecast and to analyze sales at CS using ARIMA-Intervention model (IM) and exponential smoothing method (ESM), together with sales at supermarkets in South Korea. Considering that two retail trades above are homogeneous and comparable in size and purchasing items on off-line distribution channel, individual behavior and characteristic can be detected and also relative superiority of future growth can be forecasted. In particular, the rapid growth of sales at CS is regarded as an everlasting external event, or step intervention, so that IM with season variation can be examined. At the same time, Winters ESM can be investigated as an alternative to seasonal ARIMA-IM, on the assumption that the underlying series shows exponentially decreasing weights over time. In case of sales at supermarkets, the marked intervention could not be found over the underlying periods, so that only Winters ESM is considered. Research Design, Data, and Methodology - The dataset of this research is obtained from Korean Statistical Information Service (1/2010~7/2016) and Survey of Service Trend of Korea Statistics Administration. This work is exploited time series analyses such as IM, ESM and model-fitting statistics by using TSPLOT, TSMODEL, EXSMOOTH, ARIMA and MODELFIT procedures in SPSS 23.0. Results - By applying seasonal ARIMA-Intervention model to sales at CS, the steep and persisting increase can be expected over the next one year. On the other hand, we expect the rate of sales growth of supermarkets to be lagging and tied up constantly in the next 2016 year. Conclusions - Based on 2017 one-year sales forecasts for CS and supermarkets, we can yield the useful information for the development of CS and also for all retail trades. Future study is needed to analyze sales of popular items individually such as tobacco, banana milk, soju and so on and to get segmented results. Furthermore, we can expand sales forecasts to other retail trades such as department stores, hypermarkets, non-store retailing, so that comprehensive diagnostics can be delivered in the future.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1705-1711
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• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• Journal of the Korean Society for Nondestructive Testing
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• v.23 no.5
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• pp.445-454
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• 2003

Health monitoring is a major concern not only in the design and manufacturing but also in service stages for composite laminated structures. Excessive loads or low velocity impact can cause matrix cracks and delaminations that may severely degrade the load carrying capability of the composite laminated structures. To develop the health monitoring techniques providing on-line diagnostics of smart composite structures can be helpful in keeping the composite structures sound during their service. In this study, we discuss the signal processing techniques and some applications for health monitoring of composite structures using piezoceramic sensors and fiber optic sensors.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.40-45
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• 2018

Intelligent monitoring and diagnosis of production processes based on multivariate statistical methods has been one of important tasks for safety and quality issues. This is due to the fact that faults and unexpected events may have serious impacts on the operation of processes. This study proposes a diagnostic scheme based on effective representation of process measurement data and is evaluated using simulation process data. The effects of utilizing a preprocessing step and nonlinear statistical methods are also tested using fifteen faults of the simulation process. Results show that the proposed scheme produced more reliable results and outperformed other tested schemes with none of the filtering step and nonlinear methods. The proposed scheme is expected to be robust to process noises and easy to develop due to the lack of required rigorous mathematical process models or expert knowledge.