• Journal of Microbiology and Biotechnology
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• v.15 no.3
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• pp.595-602
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• 2005

A one-step real-time quantitative RT-PCR assay in combination with automated RNA extraction was evaluated for routine testing of HCV RNA in the laboratory. Specific primers and probes were developed to detect 302 bp on 5'-UTR of HCV RNA. The assay was able to quantitate a dynamic linear range of $10^7-10^1$ HCV RNA copies/reaction ($R^2=0.997$). The synthetic HCV RNA standard of $1.84{\pm}0.1\;(mean{\pm}SD)$ copies developed in this study corresponded to 1 international unit (IU) of WHO International Standard for HCV RNA (96/790 I). The detection limit of the assay was 3 RNA copies/reaction (81 IU/ml) in plasma samples. The assay was comparable to the Amplicor HCV Monitor (Monitor) assay with correlation coefficient r=0.985, but was more sensitive than the Monitor assay. The assay could be completed within 3 h from RNA extraction to detection and data analysis for up to 32 samples. It allowed rapid RNA extraction, detection, and quantitation of HCV RNA in plasma samples. The method provided sufficient sensitivity and reproducibility and proved to be fast and labor-saving, so that it was suitable for high throughput HCV RNA test.

• Journal of Animal Environmental Science
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• v.20 no.3
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• pp.117-124
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• 2014

The objectives were to assess the use of near-infrared reflectance spectroscopy (NIRS) as a tool for estimating nutrient compositions of corn kernel, and to apply an NIRS-based indium gallium arsenide array detector to the system for collecting spectra and analyzing calibration equations using equipments designed for field application. Partial Least Squares Regression (PLSR) was employed to develop calibration equations based on representative data sets. The kennard-stone algorithm was applied to induce a calibration set and a validation set. As a result, the method for structuring a calibration set significantly affected prediction accuracy. The prediction of chemical composition of corn kernel resulted in the following (kennard-stone algorithm: relative) moisture ($R^2=0.82$, RMSEP=0.183), crude protein ($R^2=0.80$, RMSEP=0.142), crude fat ($R^2=0.84$, RMSEP=0.098), crude fiber ($R^2=0.74$, RMSEP=0.098), and crude ash ($R^2=0.81$, RMSEP=0.048). Result of this experiment showed the potential of NIRS to predict the chemical composition of corn kernel.

• Food Science and Biotechnology
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• v.14 no.1
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• pp.42-45
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• 2005

The present study was carried out to envisage the aerobic growth of Listeria monocytogenes and Yersinia enterocolitica on pork, which is one of the major meat sources in Korea. The results were compared with the previously developed predictive model systems for the verification of microbial growth in a real situation during pork processing. Pork loin samples (8.0 g, 5 mm thick) were aseptically prepared and inoculated with each pathogen by immersing into the respective inoculums for one min. Each of the samples were then wrapped with PE film and stored at 5, 10, and $15^{\circ}C$ up to 36 days to measure the growth profile of the respective pathogens. The growth parameters were calculated by using Gompertz equation and were compared with the previously reported data. The predicted generation time (GT) of L. monocytogenes at 5, 10 and $15^{\circ}C$ was 28.74, 7.85 and 4.02 hr, respectively, and for Y. enterocolitica was 10.29, 4.74 and 2.50 hr, at the same temperatures respectively. In this study, the GT values predicted on pork were slightly higher than the values predicted in other studies using liquid model systems. Unlike previous reports, both the pathogens were found to grow at $5^{\circ}C$ on pork. This finding recommends the necessity of controlling the growth of both the pathogens during the slaughtering process and distribution.

• Atmosphere
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• v.26 no.2
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• pp.277-288
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• 2016

Polar lows are intense mesoscale cyclones that mainly occur over the sea in polar regions. Owing to their small spatial scale of a diameter less than 1000 km, simulating polar lows is a challenging task. At King Sejong station in West Antartica, polar lows are often observed. Despite the recent significant climatic changes observed over West Antarctica, adequate validation of regional simulations of extreme weather events such as polar lows are rare for this region. To address this gap, simulation results from a recent version of the Polar Weather Research and Forecasting model (Polar WRF) covering Antartic Peninsula at a high horizontal resolution of 3 km are validated against near-surface meteorological observations. We selected a case of high wind speed event on 7 January 2013 recorded at Automatic Meteorological Observation Station (AMOS) in King Sejong station, Antarctica. It is revealed by in situ observations, numerical weather prediction, and reanalysis fields that the synoptic and mesoscale environment of the strong wind event was due to the passage of a strong mesoscale polar low of center pressure 950 hPa. Verifying model results from 3 km grid resolution simulation against AMOS observation showed that high skill in simulating wind speed and surface pressure with a bias of $-1.1m\;s^{-1}$ and -1.2 hPa, respectively. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation of Antartic weather systems and the near-surface meteorological instruments installed in King Sejong station can provide invaluable data for polar low studies over West Antartica.

• Journal of Gastric Cancer
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• v.15 no.4
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• pp.262-269
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• 2015

Purpose: Intraabdominal abscess is one of the most common reasons for re-hospitalization after gastrectomy. This study aimed to develop a model for estimating the probability of intraabdominal abscesses that can be used during the postoperative period. Materials and Methods: We retrospectively reviewed the clinicopathological data of 1,564 patients who underwent gastrectomy for gastric cancer between 2010 and 2012. Twenty-six related markers were analyzed, and multivariate logistic regression analysis was used to develop the probability estimation model for intraabdominal abscess. Internal validation using a bootstrap approach was employed to correct for bias, and the model was then validated using an independent dataset comprising of patients who underwent gastrectomy between January 2008 and March 2010. Discrimination and calibration abilities were checked in both datasets. Results: The incidence of intraabdominal abscess in the development set was 7.80% (122/1,564). The surgical approach, operating time, pathologic N classification, body temperature, white blood cell count, C-reactive protein level, glucose level, and change in the hemoglobin level were significant predictors of intraabdominal abscess in the multivariate analysis. The probability estimation model that was developed on the basis of these results showed good discrimination and calibration abilities (concordance index=0.828, Hosmer-Lemeshow chi-statistic P=0.274). Finally, we combined both datasets to produce a nomogram that estimates the probability of intraabdominal abscess. Conclusions: This nomogram can be useful for identifying patients at a high risk of intraabdominal abscess. Patients at a high risk may benefit from further evaluation or treatment before discharge.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4A
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• pp.377-384
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• 2006

According to fast VoIP technology development, more and more companies change voice network into IP based network among branch offices. IP PBX, which is deployed up to now, composed of IP phone and VoIP Gateway. Every telphone has replaced with If phone which support VoIP and VoIP gateway is installed in PBTN connection point to relay voice data. It can reduce the communication expense of International call, long distance call and call between a headquater and a trance because it uses internet line. In this paper, IP PBX is implemented that can distribute call using PBX network only usig personal terminal without Proxy Server. Depending on Role, terminal can be registered Master, Server and Client and it is verified in terms of performance and validation.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.227-242
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• 2012

It is a daunting task to theorize the process effectiveness of IT convergence based service model. Despite the criticalness of investigating process enhancement impact of IT-convergence based service model, the theoretical research in this field is relatively scarce, possibly due to the too wide and comprehensiveness of research scope. In this vein, we conducted exploratory study to understand the contributional impact of IT convergence based service model on resolving service process limitations. We first identified five IT convergence based service models in the area of typical service industry, which include entertainment, learning, location based services, tourism, and healthcare. Our research model classified value creation factors of the IT convergence model in twofold. The one is defined as basic value creation factor of the IT convergence, which is treated as the second-order factor that consists of two first-order factors of mobile functionality and Internet with digital contents merging functionality. The other is defined as service process limitations resolving factor which are comprised with the two first-order factors of simultaneousity and perishability. Both the second-order factors are modeled, each respectively, with the two first-order factors in formative manner. Using PLS, empirical validation is executed to analyze each value creating factor's contribution impact on the relative advantage, as well as the mediating effect of basic value creation factor on resolving service process limitations. On the basis of the insights revealed from this paper, further theory building research could be elaborated in the area of IT convergence applications for service industry.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.7
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• pp.907-911
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• 2017

Objective: Intramuscular fat is one of the meat quality traits that is considered in the selection strategies for Hanwoo (Korean cattle). Different methods are used to estimate the breeding value of selection candidates. In the present work we focused on accuracy of different genotype relationship matrices as described by forni and pedigree based relationship matrix. Methods: The data set included a total of 778 animals that were genotyped for BovineSNP50 BeadChip. Among these 778 animals, 72 animals were sires for 706 reference animals and were used as a validation dataset. Single trait animal model (best linear unbiased prediction and genomic best linear unbiased prediction) was used to estimate the breeding values from genomic and pedigree information. Results: The diagonal elements for the pedigree based coefficients were slightly higher for the genomic relationship matrices (GRM) based coefficients while off diagonal elements were considerably low for GRM based coefficients. The accuracy of breeding value for the pedigree based relationship matrix (A) was 13% while for GRM (GOF, G05, and Yang) it was 0.37, 0.45, and 0.38, respectively. Conclusion: Accuracy of GRM was 1.5 times higher than A in this study. Therefore, genomic information will be more beneficial than pedigree information in the Hanwoo breeding program.

• CELLMED
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• v.5 no.3
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• pp.15.1-15.12
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• 2015

Comparative studies have established that the North-Eastern (NE) region of India which is a part of the Eastern Himalayan region is affluent in both traditional knowledge based phytomedicine and biodiversity. About 1953 ethno-medicinal plants are detailed from the NE region of India out of which 1400 species are employed both as food and ethnopharmacological resources. Nearly 70% of species diversity has been reported from the two Indian biodiversity hotspots-The Western Ghats and the Eastern Himalayas and these hotspots are protected by tribal communities and their ancient traditional knowledge system. Paris polyphylla Smith belongs to the family Melanthiaceae and is a traditional medicinal herb which is known to cure some major ailments such as different types of Cancer, Alzheimer's disease, abnormal uterine bleeding, leishmaniasis etc. The major phytoconstituents are dioscin, polyphyllin D, and balanitin 7. Phylogeny of Paris was inferred from nuclear ITS and plastid psbA-trnH and trnL-trnF DNA sequence data. Results indicated that Paris is monophyletic in all analyses. Rhizoma Paridis, which is the dried rhizome of Paris polyphylla is mainly used in Traditional Chinese Medicine and its mode of action is known for only a few cancer cell lines. The current review determines to sketch an extensive picture of the potency, diversity, distribution and efficacy of Paris polyphylla from the Eastern Himalayan region and the future validation of its phytotherapeutical and molecular attributes by recognizing the Intellectual Property Rights of the Traditional Knowledge holders.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.84-93
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• 2018

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of power energy consumption. To this end, we consider the volatility of the time series and apply the sample variance and the detrended fluctuation analyses to the volatilities. We demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the power consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the power consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of "context units" in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the power consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. To further confirm the experimental results, we performed two types of the cross validations designed for the time series data. We also support the validity of the model by analyzing the multi-step forecasting. We found that the prediction errors tend to be saturated although they increase as the prediction time step increases. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.