• Journal of the Korea Society for Simulation
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• v.22 no.4
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• pp.49-55
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• 2013

Recently the CGF/SAF (Computer Generated Force / Semi-Automated Force) technology has been getting attention to deal with the increasing complexity in a DM&S(Defence Modeling and Simulation) environment. OneSAF is one of well-known CGF/SAF systems, however, it is not able to support the DEVS framework which is an advanced discrete event based modeling and simulation environment. Especially, most DM&S systems in Korea has been developed on the basis of the DEVS framework. In this paper, we have proposed the agent-based SAF design methodology and tool for supporting DEVS M&S environment. The proposed SAF modeling tool is divided into two parts; the agent modeling part and SAF modeling part. In the agent modeling environment, the modeler can simply create the agent model by writing down the necessary rules. It also provides the agent testing environment so that the modeler maybe conveniently verify the prescribed agent model. The SAF model is finally created by combing the individual agents based on the pre-defined structure. DM&S engineers will be able to employ our tools and modeling methodology to design the DEVS-based DM&S system to be developed.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.375-386
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• 2008

Recently, development paradigm of information system is turning into object oriented and component based, and this methodology is leading the software industry. To acclimatize aptly to this trend, users demand the assessment of software expenses to change with the appropriate model of computing costs of the environment, and some people are actually studying the concept of Object Oriented Function Point and UCP method. Especially, Object Oriented Function Point Measurement Process has good points in overcoming the bound of LOC and the existing the Function Point Measurement Process because Object Oriented Function Point Measurement Process is applicable to the early stage of development project mainly with the used cases, and valid to the life long period as the each stage of software products develops, and always understandable to communicate with users by the UML mark rules. Accordingly, this research is to measure Functional Point at ROFP and AOFP in accordance with the development project of information system by the national defense CBD methodology procedures and UML Interrelation Analysis that are recently and widely used in the developmental environment of object oriented information system. Furthermore, this study suggests the measurement method to obtain Functional Point, and identifies service function and object/class function in the correlation analysis of use case and class based on the products and UML modeling via traditional FPA model and object oriented FPA model. Above all, this study is to demonstrate the improvement of traditional Function Point Measurement Process, IFPUG-CPM and software cost basis, and reveal Function Point Measurement Process, which is appropriate to the development of object oriented information system, and suggest the evaluation results of the compatibility through case studies.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.8
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• pp.611-620
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• 2018

For the past decades, the analytic model for distributed surface roughness has been developed to improve the accuracy of the icing simulation code. However, it remains limitations to validate the developed model and determine the empirical parameters due to the absence of the quantitative experimental data which were focused on the surface state. To this end, the experimental study conducted to analyze the ice covered surface state from a micro-perspective. Above all, the tendency of the smooth zone width which occurs near the stagnation point has been quantitatively analyzed. It is observed that the smooth zone width is increased as growing the ambient temperature and freestream velocity. Next, the characteristics of the ice covered surface under rime and glaze ice have been analyzed. For rime ice conditions, ice elements are developed as the opaque circular corn in the opposite direction of freestream. The height and interval of each circular corn are increased as rising the ambient temperature. For glaze ice conditions, numerous lumps of translucent ice can be observed. This is because the beads formed by gravity concentrate and froze on the lower surface.

• KIISE Transactions on Computing Practices
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• v.21 no.6
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• pp.393-402
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• 2015

Human resources are one of the most essential elements of an organization. In particular, the more closed a group is, the higher the value each member has. Previous studies have focused on personal attributes of individual, such as medical history, and have depended upon self-diagnosis to manage structures. However, this method has weak points, such as the timeconsuming process required, the potential for concealment, and non-disclosure of participants' mental states, as this method depends on self-diagnosis through extensive questionnaires or interviews, which is solved in an interactive way. It also suffers from another problem in that relations among people are difficult to express. In this paper, we propose a multi-faced diagnosis model based on social network analysis which overcomes former weaknesses. Our approach has the following steps : First, we reveal the states of those in a social network through 9 questions. Next, we diagnose the social network to find out specific individuals such as victims or leaders using the proposed algorithm. Experimental results demonstrated our model achieved 0.62 precision rate and identified specific people who are not revealed by the existing methods.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.1-7
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• 2017

The purpose of this paper is to examine how multi-cultural acceptability affects the perception of necessity of unification through structural equation model. The multi-cultural acceptability, familiarity with North Korean defectors, and awareness of unification were selected as the latent variables and the full / partial mediator models were built for structural equations. The observed variables for each latent variable were data that were collected through the National Survey on the Integration of North and South Korea conducted by the Korea Institute for National Unification in 2015. As a result, the acceptance of multiculturalism had a significant effect on the intimacy of the defectors, which had a positive effect on the recognition of the need for unification. The intimacy of the defectors was more influential as a parameter for full mediation than for partial mediation. Although the consciousness of unification gets weakened by postwar generations, that the phenomenon that changes into a multicultural society plays a part in recognizing the necessity of unification. In addition, the increase of North Korean defectors may ultimately become a factor in recognizing the need for unification. This study demonstrated that increasing the acceptance of multiculturalism can increase the need for unification, which means that more research fields can be derived.

• Journal of Oriental Neuropsychiatry
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• v.26 no.3
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• pp.319-336
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• 2015

Objectives: The object of this study was to evaluate the cognition and motor function recovery effects of Sungshim-san (SSS), a traditional Korean cardio-protective polyherbal formula in the severe rat stroke, permanent middle cerebral artery occlusion (pMCAO) model. Methods: The experimental animals were divided into 6 groups. SSS aqueous extracts (yield=16.82%; 400, 200 and 100 mg/kg) were administered orally by using Sonde, once daily, for 28 continuous days from 24 hrs post-pMCAO. Donepezil 10 mg/kg, a representative drug for dementia, was used as a reference drug. The body weight changes, infarct/defect sizes, sensorimotor function and cognitive motor behavior were serially monitored. Limb placing and body-swing test for sensorimotor functions were conducted at 1 day before operation (base line), and 1, 3, 7, 14, 21 and 28 days post-pMCAO; and water maze test for the cognitive motor behavior was conducted at 14 and 28 days post-pMCAO, respectively. Results: Focal cerebral cortex infarct and defects due to pMCAO resulted in marked decreases of body weight, disorders of sensorimotor functions and cognitive motor behaviors. However, the pMCAO-related ischemic damages were markedly and dose-dependently inhibited by treatment with SSS 400 and 200 mg/kg, respectively. Donepezil markedly decreased the body weight and gains, as compared with pMCAO control rats; however, SSS 400 and 200 mg/kg favorably ameliorated the pMCAO-induced decreases in body weight and gains. SSS 100 mg/kg treated rats did not show any favorable effects on the pMCAO-related ischemic damages, as compared with pMCAO control rats. Conclusions: The results of the study indicated that oral administration of SSS 400 and 200 mg/kg accelerated cognition and motor function recovery in the rat pMCAO model. The treatment effect was potentially mediated by neuroprotection via the known augmentation of cerebral antioxidant defense system of SSS itself or its individual herbal components. Especially, the overall effects of SSS 200 mg/kg were similar to those of donepezil 10 mg/kg, but less toxic.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.495-503
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• 2014

In recent days, a study of the intrusion detection system collecting and analyzing network data, packet or logs, has been actively performed to response the network threats in computer security fields. In particular, Bayesian network has advantage of the inference functionality which can infer with only some of provided data, so studies of the intrusion system based on Bayesian network have been conducted in the prior. However, there were some limitations to calculate high detection performance because it didn't consider the problems as like complexity of the relation among network packets or continuos input data processing. Therefore, in this paper we proposed two methodologies based on K-menas clustering to improve detection rate by reforming the problems of prior models. At first, it can be improved by sophisticatedly setting interval range of nodes based on K-means clustering. And for the second, it can be improved by calculating robust CPT through applying weighted-leaning based on K-means clustering, too. We conducted the experiments to prove performance of our proposed methodologies by comparing K_WTAN_EM applied to proposed two methodologies with prior models. As the results of experiment, the detection rate of proposed model is higher about 7.78% than existing NBN(Naive Bayesian Network) IDS model, and is higher about 5.24% than TAN(Tree Augmented Bayesian Network) IDS mode and then we could prove excellence our proposing ideas.

• Composites Research
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• v.27 no.5
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• pp.190-195
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• 2014

This paper predicts the complex permittivity of MWNT added epoxy depending on agglomeration by numerical analysis. 1wt% MWNT added epoxy specimen is prepared using 3-roll-mill method and its complex permittivity is measured in X-band (8.2~12.4 GHz) using freespace measurement system. The analytic model is comprised of cube epoxy and perfect sphere agglomeration. The complex permittivity of the agglomeration model is predicted by complex permittivity mixing rule using the measured complex permittivity of epoxy and 1 wt% MWNT added epoxy. Commercial electromagnetic analysis software, CST, is used to obtain S-parameter of the analytic model and MATLAB code is used to calculate complex permittivity from the S-parameter. It is confirmed that the complex permittivity increases when the agglomeration size decreases.

• Journal of Korean Biological Nursing Science
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• v.3 no.1
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• pp.41-52
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• 2001

This study was undertaken to investigate the effects of n-6(corn oil) & n-3(fish oil) fatty acids on infarction size and the cerebral activities of antioxidant enzyme in rat focal brain ischemia model. Weaning Sprague-Dawley rats were fed with either corn oil supplemented diet(COD, 14% corn oil) or fish oil supplemented diet(FOD, 14% menhaden oil) for 6 weeks. The right middle cerebral artery was occluded for 2 hours with a silicon rubber coated nylon surgical thread. After 24 hours of recirculation, the rats were sacrificed and brain sections were photographed using CCD camera after staining with 2, 3, 5-triphenyltetrazolium chloride for 60 minutes in room temperature. The infarcted area was measured and the volume of infarction was calculated. Catalase(CAT), superoxide dismutase(SOD) activities, and fatty acid composition in the brain were also measured. The total and corrected infarction volumes were not significantly different between FOD and COD group. The docosagexaenoic acid(DHA) and DHA content/arachidonic acid(AA) ratio of the cerebral cortex, an index of defense against lipid oxidation, were significantly increased in FOD group compared to those of COD group(p<0.05). In the left cortex(non-infarction side) as well as the right cortex(infarction side) of FOD group, CAT and Cu/Zn SOD activities were higher than those of the COD group(p<0.05). However, CAT and Cu/Zn SOD activities were not significantly different between the left cortex(non-infarction side) and the right cortex(infarction side) of both FOD and COD group. GPx activities were also not significantly different between two groups. Our results demonstrate that the brain infarction size in FOD and COD were not significantly different. However, cerebral lipid composition and antioxidant enzyme activities in FOD and COD group were different. Fish oil, a source of n-3 polyunsaturated fatty acid(PUFA) and corn oil, that of n-6(PUFA) may have a protective effect against oxidative stress induced via different mechanisms.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.