• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.757-765
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• 2021

To carry out multi-domain operations included in the U.S. Department of Defense's national security strategy in 2018, timely data sharing between C4I systems is critical. Several studies of the Korean military have also raised the problems of interface and standardization between C4I systems, and it is necessary to establish a new plan to solve this problem. In this study, a solution to the problem was derived through case analysis that the U.S. Department of Defense has been pursuing for about 20 years to implement the data strategy after establishing the data strategy in 2003. and by establishing a data strategy suitable for the ROK military C4I system operating environment, developing a data model, selecting a standard for data sharing, and proposing a shared data development procedure, we intend to improve the data sharing capability between ROK military C4I systems.

• The Plant Pathology Journal
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• v.31 no.4
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• pp.350-362
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• 2015

A disease forecast model for bacterial grain rot (BGR) of rice, which is caused by Burkholderia glumae, was developed in this study. The model, which was named 'BGRcast', determined daily conduciveness of weather conditions to epidemic development of BGR and forecasted risk of BGR development. All data that were used to develop and validate the BGRcast model were collected from field observations on disease incidence at Naju, Korea during 1998-2004 and 2010. In this study, we have proposed the environmental conduciveness as a measure of conduciveness of weather conditions for population growth of B. glumae and panicle infection in the field. The BGRcast calculated daily environmental conduciveness, $C_i$, based on daily minimum temperature and daily average relative humidity. With regard to the developmental stages of rice plants, the epidemic development of BGR was divided into three phases, i.e., lag, inoculum build-up and infection phases. Daily average of $C_i$ was calculated for the inoculum build-up phase ($C_{inf}$) and the infection phase ($C_{inc}$). The $C_{inc}$ and $C_{inf}$ were considered environmental conduciveness for the periods of inoculum build-up in association with rice plants and panicle infection during the heading stage, respectively. The BGRcast model was able to forecast actual occurrence of BGR at the probability of 71.4% and its false alarm ratio was 47.6%. With the thresholds of $C_{inc}=0.3$ and $C_{inf}=0.5$, the model was able to provide advisories that could be used to make decisions on whether to spray bactericide at the preand post-heading stage.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.229-232
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• 2001

4H-SIC(silicon carbide) MESFET large signal model was studied using modified Materka-Kacprzak large signal MESFET model. 4H-SiC MESFET device simulation have been conducted by Silvaco's 2D device simulator, ATLAS. The result is modeled using modified Materka large signal model. simulation and modeling results are -8V pinch off voltage, under $V_{GS=0V}$, $V_{DS=25V}$ conditions, $I_{DSS=270㎃}$mm, $G_{m=45㎳}$mm were obtained. Through the power simulation 2GHz, at the bias of $V_{GS=-4V}$ and $V_{DS=25V}$, 10dB Gain, 34dBm(1dB compression point)output power, 7.6W/mm power density, 37% PAE(power added efficiency) were obtained.d.d.d.

• KIEAE Journal
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• v.13 no.3
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• pp.91-96
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• 2013

The purpose of this study was to analyze the annual energy demand including heating, cooling and lighting according to kind of windows with transparent thin-film a-Si Building Integrated Photovoltaic(a-Si BIPV) for office building. The analysis results of the annual energy demand indicated that the a-si BIPV window was reduced by 8.4% than the clear gazing window. The base model A was combinate with a-Si BIPV window area of 67% and clear window area of 33% among the total exterior area. The model B is to be applied with low-e clear glass instead of clear glass of the base model A. The model B was reduced to annual energy demand of 1% more than the model A. Therefore, By using a-si BIPV solar module, the cooling energy demand can be reduced by 53%(3.4MWh) and the heating energy demand can be increase by 58%(2.4MWh) than clear glazing window in office building. Also, Model C applied to the high efficient lighting device to the model B was reduced to annual energy demand of 14.4% more than the Model D applied to the high efficient lighting device to the model A. The Model E applied with daylight dimming control system to the Model C was reduced to annual energy demand of 5.9% more than Model C.

• Information Systems Review
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• v.23 no.4
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• pp.45-67
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• 2021

As the transaction volume of the C2C second-hand market is growing, the number of frauds, which intend to earn unfair gains by sending products different from specified ones or not sending them to buyers, is also increasing. This study explores the model that can identify frauds in the online C2C second-hand market by examining the postings for transactions. For this goal, this study collected 145,536 field data from actual C2C second-hand market. Then, the model is built with the characteristics from postings such as the topic and the linguistic characteristics of the product description, and the characteristics of products, postings, sellers, and transactions. The constructed model is then trained by the machine learning algorithm XGBoost. The final analysis results show that fraudulent postings have less information, which is also less specific, fewer nouns and images, a higher ratio of the number and white space, and a shorter length than genuine postings do. Also, while the genuine postings are focused on the product information for nouns, delivery information for verbs, and actions for adjectives, the fraudulent postings did not show those characteristics. This study shows that the various features can be extracted from postings written in C2C second-hand transactions and be used to construct an effective model for frauds. The proposed model can be also considered and applied for the other C2C platforms. Overall, the model proposed in this study can be expected to have positive effects on suppressing and preventing fraudulent behavior in online C2C markets.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.4
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• pp.1-16
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• 2011

It is important not only to introduce the C4I(Command and Control, Communication, Computer, Intelligence) system for realizing the NCW(Network Centric Warfare) but also to evaluate the synergistic effect by the C4I system. However, the study effort for evaluating the system's synergistic effect is insufficient compared with introducing the system. Therefore, in this paper, we proposed a model that measures the synergistic effect of combat power by the warfare information system. To measure the synergistic effect of warfare information system, the network power must be considered, so we also proposed a new methodology for measurement of network power based on SNA(Social Network Analysis), not Metcalfe's law. A model we proposed is a model that measures the raised combat power by the network effectiveness. The methodology and model we proposed in this paper will be used usefully to analyze the practical effect of constructing future warfare information system.

• Journal of the Korean Society for Heat Treatment
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• v.31 no.4
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• pp.180-186
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• 2018

High temperature flow behaviors of Fe-Cr-Mo-V-W-C tool steel were investigated using isothermal compression tests on a Gleeble simulator. The compressive test temperature was varied from 850 to $1,150^{\circ}C$ with the strain rate ranges of 0.05 and $10s^{-1}$. The maximum height reduction was 45%. The dynamic softening related to the dynamic recrystallization was observed during hot deformation. The constitutive model based on Arrhenius-typed equation with the Zener-Hollomon parameter was proposed to simulate the hot deformation behavior of Fe-Cr-Mo-V-W-C steel. An artificial neural network (ANN) model was also developed to compare with the constitutive model. It was concluded that the ANN model showed more accurate prediction compared with the constitutive model for describing the hot compressive behavior of Fe-Cr-Mo-V-W-C steel.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.109-112
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• 2001

In this paper, I present a MPEG4 decoding system modeling in SystemC, a new C/C++ based system simulation approach, In the modeling, MPEG4 decoding behavior is modeled and verified. And I partitions the MPEG4 decoding system into several hardware components which will be implemented at low level hardware design flow and I model a synchronized hardware block communication through data ports.

• Journal of Food Hygiene and Safety
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• v.19 no.1
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• pp.49-54
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• 2004

The prevention of infectious disease from contaminated foods is very important in public health. Quantitative microbial risk assessment has been used in advance countries to achieve the safety of public health against hazardous microbial causing contaminated foods. This study was conducted to estimate maximum edible time without producing enterotoxin from Staphylococcus aureus in Kimbap selling at different domestic store using Food MicroModel and monitoring data and to compute maximum edible time by temperature with 99th percentile safety probability based on only restaurant data. For estimating maximum edible time, model operation conditions like reaching time at 2 ${\times}$ 10$^{7}$ , which enterotoxin was known as producing point from S. aureus, temperature of 28∼3$0^{\circ}C$, pH 5.2, NaCl 0.22%, aw(water activity) 0.99, and intaking one serving size of 171g in Kimbap were considered. Estimated maximum edible times by regarding outdoor temperature in summer were 3.9∼4.6 hrs in restaurant, 6.7∼7.9 hrs in department store and 7.4∼8.7 hrs in convenient store. Based on restaurant data, estimated maximum edible times with 99th percentile safety probability by temperature were 1.9 hrs in 3$0^{\circ}C$ and 17.7 hrs in 15$^{\circ}C$.

• Food Science and Preservation
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• v.24 no.6
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• pp.778-785
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• 2017

This study was conducted to develop a predictive model for the growth of Escherichia coli strain RC-4-D isolated from red kohlrabi sprout seeds. We collected E. coli kinetic growth data during red kohlrabi seed sprouting under isothermal conditions (10, 15, 20, 25, and $30^{\circ}C$). Baranyi model was used as a primary order model for growth data. The maximum growth rate (${\mu}max$) and lag-phase duration (LPD) for each temperature (except for $10^{\circ}C$ LPD) were determined. Three kinds of secondary models (suboptimal Ratkowsky square-root, Huang model, and Arrhenius-type model) were compared to elucidate the influence of temperature on E. coli growth rate. The model performance measures for three secondary models showed that the suboptimal Huang square-root model was more suitable in the accuracy (1.223) and the suboptimal Ratkowsky square-root model was less in the bias (0.999), respectively. Among three secondary order model used in this study, the suboptimal Ratkowsky square-root model showed best fit for the secondary model for describing the effect of temperature. This model can be utilized to predict E. coli behavior in red kohlrabi sprout production and to conduct microbial risk assessments.