• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.5
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• pp.495-501
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• 2015

Abroad warships are confronted with various menaces. The most critical threat of the warship is an Anti-Ship Missile (ASM). The ASM is able to be launched at a variety of environments and platforms. The ASM can evades conventional naval radar systems and electronic countermeasure techniques for providing a fatal damage to the warship. To cope with the ASM, an active decoy is an effective method to minimize the direct damage to the warship. The active decoy increases survivability of the warship because the ASM can lure pursuit of the active decoy instead of the warship. In this paper, our proposed method verifies an available response time of the active decoy to deal with the ASM using the active decoy of the warship in marine environments. We defined models of the warship, the ASM, and the active decoy, and executed simulation by combining the models. By the simulation result, the proposed method demonstrated the superiority of the mobile active decoy of the response time decoy among various active decoys, and estimated a protection area to prevent the ASM according the response time of the mobile active decoy against the ASM.

• Genomics & Informatics
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• v.8 no.3
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• pp.108-115
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• 2010

Hypertension is the most prevalent disease worldwide and is itself a risk factor for cerebral, cardiac, and renal diseases. The inconsistency of candidate genes suggested by previous genomewide association studies (GWASs) may be due to not only differences in study design and genetic or environmental background but also the difference in the power of analysis between continuous traits and discrete traits. We analyzed 352,228 single nucleotide polymorphisms (SNPs) in 8842 unrelated Koreans obtained from Ansan and Ansung cohorts. We performed a series of GWA analyses using three different phenotype models; young hypertensive cases (278 subjects) versus elderly normotensive controls (680 subjects); the upper 25% (2211 hypertensive cases) versus the lower 25% of the SBP distribution (2211 hypotensive controls); and finally SBP and DBP as continuous traits (8842 subjects). The numbers of young hypertensive cases and elderly normotensive controls were not large enough to achieve genomewide significance. The model comparing the upper 25% subjects to the lower 25% of subjects showed a power that was approximate to that of QTL analysis. Two neighboring SNPs of the ATP2B1 gene, rs17249754 (SBP, p=$2.53^{-10}$; DBP, p=$1.28{\times}10^{-8}$) and rs7136259 (SBP, p=$1.30{\times}10^{-9}$; DBP, p=$6.41{\times}10^{-8}$), were associated with both SBP and DBP. Interestingly, a SNP of the RPL6 gene, rs11066280, revealed a significant genomewide association with SBP in men only (p=$3.85{\times}10^{-8}$), and four SNPs located near the MAN2A1 gene showed a strong association with DBP only in elderly men aged 60-70 years (e.g., rs6421827, p=$4.86{\times}10^{-8}$). However, we did not observe any gene variant attaining genomewide significance consistently in the three phenotype models except for the ATP2B1 gene variants. In general, the association signal with blood pressure was stronger in women than in men. Genes identified in GWASs are expected to open the way for prevention, early diagnosis, and personalized treatment of hypertension.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.227-227
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• 2015

The Wairarapa Valley occupies a predominantly rural area in the lower North Island of New Zealand. It supports a mix of intensive farming (dairy), dry stock farming (sheep and beef cattle) and horticulture (including wine grapes). The valley floor is traversed by the Ruamahanga River, the largest river in the Wellington region with a total catchment area of 3,430 km2. Environmental, cultural and recreational values associated with this Ruamahanga River are very high. The alluvial gravel and sand aquifers of the Wairarapa Valley, support productive groundwater aquifers at depths of up to 100 metres below ground while the Ruamahanga River and its tributaries present a further source of water for users. Water is allocated to users via resource consents by Greater Wellington Regional Council (GWRC). With intensifying land use, demand from the surface and groundwater resources of the Wairarapa Valley has increased substantially in recent times and careful management is needed to ensure values are maintained. This paper describes the approach being taken to manage water resources in the Wairarapa Valley and redefine appropriate limits of sustainable water use. There are three key parts: Quantifying the groundwater resource. A FEFLOW numerical groundwater flow model was developed by GWRC. This modelling phase provided a much improved understanding of aquifer recharge and abstraction processes. It also began to reveal the extent of hydraulic connection between aquifer and river systems and the importance of moving towards an integrated (conjunctive) approach to allocating water. Development of a conjunctive management framework. The FEFLOW model was used to quantify the stream flow depletion impacts of a range of groundwater abstraction scenarios. From this, three abstraction categories (A, B and C) that describe diminishing degrees of hydraulic connection between ground and surface water resources were mapped in 3 dimensions across the Valley. Interim allocation limits have been defined for each of 17 discrete management units within the valley based on both local scale aquifer recharge and stream flow depletion criteria but also cumulative impacts at the valley-wide scale. These allocation limits are to be further refined into agreed final limits through a community-led decision making process. Community involvement in the limit setting process. Historically in New Zealand, limits for sustainable resource use have been established primarily on the basis of 'hard science' and the decision making process has been driven by regional councils. Community involvement in limit setting processes has been through consultation rather than active participation. Recent legislation in the form of a National Policy Statement on Freshwater Management (2011) is reforming this approach. In particular, collaborative consensus-based decision making with active engagement from stakeholders is now expected. With this in mind, a committee of Wairarapa local people with a wide range of backgrounds was established in 2014. The role of this committee is to make final recommendations about resource use limits (including allocation of water) that reflect the aspirations of the communities they represent. To assist the committee in taking a holistic view it is intended that the existing numerical groundwater flow models will be coupled with with surface flow, contaminant transport, biological and economic models. This will provide the basis for assessing the likely outcomes of a range of future land use and resource limit scenarios.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of Korean Society of Transportation
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• v.24 no.5 s.91
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• pp.89-108
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• 2006

Korea has been entering the ageing society as the population of age over 65 shared over 7% since the year 2000. The ageing society needs to have transportation facility considering elderly people's travel behavior. This study aims to understand the elderly people's travel behavior using recent data in Korea. The activity schedule approach begins with travel outcomes are part of an activitv scheduling decision. For tho?e approach. used discrete choice models (especially. Nested Logit Model) to address the basic modeling problem capturing decision interaction among the many choice dimensions of the immense activity schedule choice set The day activity schedule is viewed as a sot of tours and at-home activity episodes tied togather with overarching day activity pattern using the Seoul Metropolitan Area Transportation Survey data, which was conducted in June, 2002. Decisions about a specific tour in the schedule are conditioned by the choice of day activity pattern. The day activity scheduling model estimated in this study consists of tours interrelated in a day activity pattern. The day activity pattern model represents the basic decision of activity participation and priorities and places each activity in a configuration of tours and at-home episodes. Each pattern alternative is defined by the primary activity of the day, whether the primary activity occurs at home or away, and the type of tour for the primary activity. In travel mode choice of the elderly and non-workers, especially, travel cost was found to be important in understanding interpersonal variations in mode choice behavior though, travel time was found to be less important factor in choosing travel mode. In addition, although, generally, the elderly was likely to choose transit mode, private mode was preferred for the elderly over 75 years old owing to weakened physical health for such things as going up and down of stairs. Therefore. as entering the ageing society, transit mode should be invested heavily in transportation facility Planning tor improving elderly transportation service. Although the model has not yet been validated in before-and-after prediction studies. this study gives strong evidence of its behavioral soundness, current practicality. and potential for improving reliability of transportation Projects superior to those of the best existing systems in Korea.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.4
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• pp.429-439
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• 1999

Potentiometric titration data were collected for some humic acids purified from Korean upland and paddy soils over a range of pH (3.0 - 11.0) with $NaNO_3$ background electrolyte concentrations (0.01, 0.10, 0.50 and 1.00 M). The data were applied to model A and V which included both intrinsic heterogeneity of humic materials and electrostatic interaction influences on binding sites. The elemental analysis were conducted for various type of humic samples. The $E_4/E_6$ ratio proposed negative correlation with the total carboxyl groups ($r^2$= 0.9988). The charge ($cmol_c\;kg^{-1}$) on the humic acids became more negative as the ionic strength increased. In both continuous and batch titrations, the ionic strength effect was greater in Namweon series (pH 6.39) than others at pH 5.00. The effect of ionic strength on surface charge appears to be greater in batch titrations. This could suggest that continuous titrations do not represent an equilibrium state and the effects of electrolyte concentration was not fully realized during the course of titrations. Both models described experimental data obtained from continuous and batch titrations well over a range of ionic strengths. Model A is more simpler than model V but adaptes more fitted parameters. Thus, the observed change in apparent binding constants with surface charge is regarded solely due to electrostatic influences rather than functional group heterogeneity. However, Model V is more mechanistically realistic in a number of discrete ligand binding sites.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2473-2481
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• 2013

The two characteristics of two-lane-and-two-way traffic flow are platoon and overtaking triggered by low-speed vehicle. It is crucial to develop a robust model which simultaneously generates the behaviors of platoon by low-speed vehicle and overtaking using opposite lane. Hence, a microscopic two-lane and two-way vehicle model was introduced (B. Yoon, 2011), which is based on CA (Cellular Automata) which is one of discrete time-space models, in Korea. While the model very reasonably explains the behaviour of overtaking low-speed vehicle in stable traffic flow below critical density, it has shortcomings to the overtaking process in unstable traffic flow above the critical density. Therefore, the objective of this study is to develope a vehicle model to more realistically explain overtaking process in unstable traffic flow state based on the model developed in the previous study. The experimental results revealed that the car-following model robustly generates the various macroscopic relationships of traffic flow generating stop-and-go traffic flow and the overtaking model reasonably explains the behaviors of overtaking under the conditions of both opposite traffic flow and stochastic parameter to consider overtaking in unstable traffic flow state. The vehicle model presented in this study can be expected to be utilized for the analysis of two-lane-and-two-way traffic flows more realistically than before.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.936-946
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• 2009

A graph cuts method has recently attracted a lot of attentions for image segmentation, as it can globally minimize energy functions composed of data term that reflects how each pixel fits into prior information for each class and smoothness term that penalizes discontinuities between neighboring pixels. In previous approaches to graph cuts-based automatic image segmentation, GMM(Gaussian mixture models) is generally used, and means and covariance matrixes calculated by EM algorithm were used as prior information for each cluster. However, it is practicable only for clusters with a hyper-spherical or hyper-ellipsoidal shape, as the cluster was represented based on the covariance matrix centered on the mean. For arbitrary-shaped clusters, this paper proposes graph cuts-based image segmentation using mean shift analysis. As a prior information to estimate the data term, we use the set of mean trajectories toward each mode from initial means randomly selected in $L^*u^*{\upsilon}^*$ color space. Since the mean shift procedure requires many computational times, we transform features in continuous feature space into 3D discrete grid, and use 3D kernel based on the first moment in the grid, which are needed to move the means to modes. In the experiments, we investigate the problems of mean shift-based and normalized cuts-based image segmentation methods that are recently popular methods, and the proposed method showed better performance than previous two methods and graph cuts-based automatic image segmentation using GMM on Berkeley segmentation dataset.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.3
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• pp.509-521
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• 1994

This study is an effort to develop computer simulation model that produce precipitation patterns from stochastic model. A stochastic model is formulated for the process of daily precipitation with considering the sequences of wet and dry days and the precipitation amounts on wet days. This study consists of 2 papers and the process of precipitation occurrence is modelled by an alternate renewal process (ARP) in paper (I). In the ARP model for the precipitation occurrence, four discrete distributions, used to fit the wet and dry spells, were as follows; truncated binomial distribution (TBD), truncated Poisson distribution (TPD), truncated negative binomial distribution (TNBD), logarithmic series distribution (LSD). In companion paper (II) the process of occurrence is developed by Markov chain. The amounts of precipitation, given that precipitation has occurred, are described by a Gamma. Pearson Type-III, Extremal Type-III, and 3 parameter Weibull distribution. Daily precipitation series model consists of two models, A-Wand A-G model, by combining the process of precipitation occurrence and a continuous probability distribution on the precipitation of wet days. To evaluate the performance of the simulation model, output from the model was compared with historical data of 7 stations in the Nakdong and Seomjin river basin. The results of paper (1) show that it is possible to design a model for the synthetic generation of IX)int precipitation patterns.

• Journal of the Korean Society of Groundwater Environment
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• v.3 no.2
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• pp.51-59
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• 1996

In case waste disposal site is to be constructed close to the underground facilities such as LPG storage cavern which is completely maintained by groundwater pressure, it is generally requested that the possibility on leachate contamination of cavern area be reviewed and the countermeasure, if it is estimated cavern area is severely affected by leachate, be taken into consideration. Prediction was performed and leachate control plan was made using by analytical and the numerical analysis on the leachate migration which is likely to happen at the area between the proposed waste disposal site and the underground LPG storage cavern located at the U petrochemical complex. Analytical solutions were obtained by the conservative mass advection-diffusion equation and the effect of advection and dispersion factor on the leachate migration was reviewed through peclet number calculation and the functional relationship between the factors and leachate transport velocity was established, which leads to enable us to predict the leachate transport velocity without difficulties when different parameters (factors) are used for analytical solution. Numerical solutions were obtained by FEM using AQUA2D which is for the simulation of groundwater flow and contaminant transport. 3-D discrete fracture models were simulated and fracture flow analysis was performed and feasibility study on the water-curtain system was conducted through the fracture connectivity analysis in rock mass. As results of those analyses, it was interpreted that the leachate would trespass on the LPG storage cavern area in 30 years from the proposed wate disposal site and the vertical water-curtain system was effective mathod for the prevention of leachate's migration further into the cavern area.