• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.265-272
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• 2020

In the research of brain computer interface (BCI) technology, one of the big problems encountered is how to deal with some people as called the BCI-illiteracy group who could not control the BCI system. To approach this problem efficiently, we investigated a kind of spectral EEG characteristics in the prior resting state in association with BCI performance in the following BCI tasks. First, spectral powers of EEG signals in the resting state with both eyes-open and eyes-closed conditions were respectively extracted. Second, a convolution neural network (CNN) based binary classifier discriminated the binary motor imagery intention in the BCI task. Both the linear correlation and binary prediction methods confirmed that the spectral EEG characteristics in the prior resting state were highly related to the BCI performance in the following BCI task. Linear regression analysis demonstrated that the relative ratio of the 13 Hz below and above the spectral power in the resting state with only eyes-open, not eyes-closed condition, were significantly correlated with the quantified metrics of the BCI performance (r=0.544). A binary classifier based on the linear regression with L1 regularization method was able to discriminate the high-performance group and low-performance group in the following BCI task by using the spectral-based EEG features in the precedent resting state (AUC=0.817). These results strongly support that the spectral EEG characteristics in the frontal regions during the resting state with eyes-open condition should be used as a good predictor of the following BCI task performance.

• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.335-345
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• 2020

This paper deals with the problem of estimating the log-transformed linear regression model to fit actual battle data from the Ardennes Campaign of World War II into the Lanchester model. The problem of determining a global solution for parameters and multicollinearity problems are identified and modified by examining the results of previous studies on data. The least squares method requires attention because a local solution can be found rather than a global solution if considering a specific constraint or a limited candidate group. The method of exploring this multicollinearity problem can be confirmed by a statistic known as a variance inflation factor. Therefore, the Lanchester model is simplified to avoid these problems, and the combat power attrition rate model was proposed which is statistically significant and easy to explain. When fitting the model, the dependence problem between the data has occurred due to autocorrelation. Matters that might be underestimated or overestimated were resolved by the Cochrane-Orcutt method as well as guaranteeing independence and normality.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.607-618
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• 2019

A new and interesting task in statistics is to effectively analyze functional data that frequently comes from advances in modern science and technology in areas such as meteorology and biomedical sciences. Functional linear regression with scalar response is a popular functional data analysis technique and it is often a common problem to determine a functional association if a functional predictor variable affects the scalar response in the models. Recently, Kong et al. (Journal of Nonparametric Statistics, 28, 813-838, 2016) established classical testing methods for this based on functional principal component analysis (of the functional predictor), that is, the resulting eigenfunctions (as a basis). However, the eigenbasis functions are not generally suitable for regression purpose because they are only concerned with the variability of the functional predictor, not the functional association of interest in testing problems. Additionally, eigenfunctions are to be estimated from data so that estimation errors might be involved in the performance of testing procedures. To circumvent these issues, we propose a testing method based on fixed basis such as B-splines and show that it works well via simulations. It is also illustrated via simulated and real data examples that the proposed testing method provides more effective and intuitive results due to the localization properties of B-splines.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.4
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• pp.60-68
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• 2003

In this study, a steady state performance analysis program was developed for a turbofan engine, and its performance was analyzed at installed conditions. For the purpose of evaluation, the developed program was compared with the performance data provided by the engine manufacturer. It was confirmed that the developed program was reliable because the results by the developed program were well agreed with those by the engine manufacturer within 3.5%. The non-linear GPA(Gas Path Analysis) program for performance diagnostics were developed, and selection of optimal measurement variables was studied. Furthermore, in order to investigate effects of the number and the kind of measurement variables, the non-linear GPA was analyzed with various measurement sets. Finally, the measurement parameters selected in the previous step were applied to the fault detection analysis of the 2-spool separate flow type turbofan engine.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.407-419
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• 2006

In this paper, we analyze household overdue loans in Korea which has been causing serious social and economical problems. We consider customers of Bank A in Korea and focus on overdue cash services which have been snowballing in the past few years. From analysis of overdue loans, one can predict possible delays for current customers as well as build a credit evaluation and risk management system for future customers. As a statistical analytical tool, we propose a two-stage Generalized Linear regression Model (GLM) which assumes a logistic model for presence/non-presence of overdue and a gamma model for the amount of overdue in the case of overdue. We perform goodness of fit test for the two-stage model and select significant explanatory variables in each stage of the model. It turns out that age, the amount of credit loans from other financial companies, the amount of cash service from other companies, debit balance, the average amount of cash service, and net profit are important explanatory variables relevant to overdue credit card cash service in Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.1
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• pp.1-16
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• 2018

Changes in the life style might vary trip purposes, ultimately leading to the change in the travel behavior. Therefore, this study analyzed the factors affecting travel time change by using the time use survey data in Seoul, surveyed by the Statistics Korea in 1999~2014. We developed multiple linear regression models for travel time, considering individual, household and time-related variables as independent variables. The models were separately estimated weekday and weekend. the model results show that the household, individual, and time related variables have an significant effect on the travel time. In addition, travel time is more influenced by individual characteristics thn household ones. Each activity time positively affects the travel time, indicating that travel is derived demand. The variable that have the greatest influence on the travel time is the activity time for leisure.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.59-66
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• 2007

In this paper, we consider the non-fragile robust guaranteed cost state feedback controllers design method for descriptor systems with parameter uncertainties and static state feedback controller with multiplicative uncertainty. The sufficient condition of controller existence, the design method of non-fragile robust guaranteed cost controller, the measure of non-fragility in controller, the upper bound of guaranteed cost performance measure to minimize the guaranteed cost are presented via LMI(linear matrix inequality) technique. Also, the sufficient condition can be rewritten as LMI form in terms of transformed variables through singular value decomposition, some changes of variables, and Schur complements. Therefore, the obtained non-fragile robust guaranteed cost controller satisfies the asymptotic stability and minimizes the guaranteed cost for the closed loop descriptor systems with parameter uncertainties and controller fragility. Finally, a numerical example is given to illustrate the design method.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.286-286
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• 2018

하천에서 점착성 유사의 부유사는 입자 표면의 전자기적, 생화학적 점착력과 충돌에 의해 플럭(Floc)을 형성하고 응집된 플럭은 하천의 흐름 및 난류에 의해 파괴되기도 한다. 이 과정을 응집현상이라고 한다. 하천의 점착성 유사는 보통 플럭의 형태를 띠며 응집현상으로 인해 플럭의 밀도와 크기는 지속적으로 변화한다. 일반적으로 변화하는 플럭의 크기는 높은 질량 농도에서 증가한다고 알려져 있다(McAnally and Mehta, 2000; Maggi et al., 2007). 하지만 현장 연구에서 실측된 자료들은 종종 플럭의 크기와 농도가 반비례 관계를 가지는 경향을 보여준다(Gartner et al., 2001; Fettweis et al., 2006; Todd, 2014). 이에 따라 본 연구는 현장의 실측 자료가 일반적인 연구와 다르게 플럭의 크기와 농도가 반비례 관계를 가지는 현상을 규명하기 위해 점착성 유사의 이동을 모의하는 1차원 연직 수치 모형으로 수치 실험을 실시하고 그 결과를 분석한다. 수치 실험은 현장연구와 조건이 비슷한 이상적인 조류조건과 정류상태의 한 방향 흐름(Current Flow)을 함께 발생시키고 점착성 유사의 특징인 응집현상을 고려하였다. 모의 결과, 실측 자료와 같이 총 모의 수심 중 하상과 가까운 측정 수심에서는 플럭의 크기와 농도가 반비례 관계를 가지는 경향을 보였다. 그러나 측정 수심이 수표면 쪽으로 갈수록 플럭 크기와 농도가 비례하는 현상을 보였다. 이와 같이 서로 다른 두 가지 결과를 분석하기 위해 플럭의 크기를 결정하는 대표적인 매개변수인 농도와 난류의 강도를 나타내는 난류소산매개변수(Turbulent shear, G)를 가지고 새로운 매개변수를 만들었다. 플럭의 크기를 결정하는 방정식에서 농도는 응집의 과정에 G는 응집과 파괴의 과정에 관여한다고 알려져 있다. 새로운 매개변수로 총 모의 수심에 걸쳐 분석한 결과 하상에서 수표면 쪽으로 갈 때 난류와 농도 모두 줄어들지만 파괴와 응집의 우세를 나타내는 매개변수가 도치되는 현상을 보였다. 즉 하상부근의 강한 난류와 높은 농도가 응집현상을 만들지만 농도는 응집현상에, 난류는 응집과 파괴 모두 관여하므로 상대적으로 농도와 난류가 만들어내는 응집보다 난류가 만드는 파괴가 강할 때 플럭의 크기가 줄어드는 것으로 예측된다. 이에 따라 점착성 유사의 플럭 크기를 예측할 때에는 플럭의 크기가 농도와 선형의 관계를 가지는 것이 아닌 농도와 난류가 함께 작용하는 비선형 관계임을 고려해야 한다.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.115-121
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• 2022

In this paper, we analyze trends in the use of mobile forensic technology, focusing on cases where mobile forensics are used, and we predict the development of future mobile forensics technology using linear regression used in future prediction models. For the current status and outlook analysis, we extracted a total of 8 variables by analyzing 1,397 domestic and foreign mobile forensics-related cases and newspaper articles. We analyzed the prospects for each variable using the year of occurrence as an independent variable, seven variables such as text (text message usage information), communication information (cell phone communication information), Internet usage information, messenger usage information, stored files, GPS, and others as dependent variables. As a result of the analysis, among various aspects of the use of mobile devices, the use of Internet usage information, messenger usage information, and data stored in mobile devices is expected to increase. Therefore, it is expected that continuous research on technologies that can effectively extract and analyze characteristic information of mobile devices such as file systems, the Internet, and messengers will be needed As mobile devices increase performance and utilization in the future and security technology.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.45-54
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• 2006

To obtain realistic stress-strain relation in concrete, it is necessary to improve the constitutive model for creep and shrinkage of concrete. This study is made up with predicting model of creep using rheological approach and mathematical development which is solution for phenomenon of concrete creep. Long-term deformation components are combined based on traditional 4-parameters model. Creep deformation is obtained adequately using 4-parameters determined by considering aging effect and microprestress among gels. And coefficient of effective viscosity is able to represent both basic creep and total creep included drying creep. This study attempt to establish mathematical model considering effects of aging, hydration, and variations of pore humidity. It can predict both basic creep and total creep. Values of result between prediction and experiment have greater than correlation factor 99%. Additionally experimental results report bad consentaneity with highway design specification adopting FIB MC 90. Rather than those are similar to FIB MC 90 rev.99.