• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.284-294
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• 2018

Statistical methods have been widely used to estimate the remaining battery runtime of mobile smart devices, such as smart phones, smart gears, tablets, and etc. However, existing work available in the literature only considers a particular statistical method. Thus, it is difficult to determine whether statistical methods are applicable to estimating thr remaining battery runtime of mobile devices or not. In this paper, we evaluated the performance of statistical methods applicable to estimating the remaining battery runtime of mobile smart devices. The statistical estimation methods evaluated in this paper are as follows: simple and moving average, linear regression, multivariate adaptive regression splines, auto regressive, polynomial curve fitting, and double and triple exponential smoothing methods. Research results presented in this paper give valuable data of insight to IT engineers who are willing to deploy statistical methods on estimating the remaining battery runtime of mobile smart devices.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.3
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• pp.162-168
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• 2017

Shallow-water bathymetry survey has been conducted using high definition color images obtained at the altitude of 100 m above sea level using a drone. Shallow-water bathymetry data are one of the most important input data for the research of beach erosion problems. Especially, accurate bathymetry data within closure depth are critically important, because most of the interesting phenomena occur in the surf zone. However, it is extremely difficult to obtain accurate bathymetry data due to wave-induced currents and breaking waves in this region. Therefore, optical remote sensing technique using a small drone is considered to be attractive alternative. This paper presents the potential utilization of image processing algorithms using multi-variable linear regression applied to red, green, blue and grey band images for estimating shallow water depth using a drone with HD camera. Optical remote sensing analysis conducted at Wolpo beach showed promising results. Estimated water depths within 5 m showed correlation coefficient of 0.99 and maximum error of 0.2 m compared with water depth surveyed through manual as well as ship-board echo-sounder measurements.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.38-38
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• 2011

일반적으로 레일마모는 열차의 주행안전 및 승차감에 미치는 영향이 크고, 소음 진동의 주요원인으로 작용한다. 또한 레일마모가 발생할 경우 궤도구조의 파괴를 촉진시킴으로써 차량 및 궤도유지보수비를 크게 증가시킨다. 따라서 구간 특성 및 환경 영향 인자 등 현장에서 발생하는 마모 원인을 체계적으로 분석함으로써 마모를 저감할 수 있도록 차량운행 조건과 선로선형 및 궤도구조를 설계하는 것은 중요한 과제이다. CART(Classification And Regression Tree; 분류와 회귀나무) 분석은 패키지화된 좋은 분류 및 예측도구 기법으로 나무의 상위 분리수준에서 일반적으로 나타나는 가장 중요한 입력변수들을 사용하는 등의 입력변수를 선정하는 경우 매우 유용하다. 본 연구에서는 다변수 구간특성 및 환경인자를 고려한 검측 자료 상관관계 분석을 위한 회귀 나무기반 모델(TBM: Tree Based Model) 분석 수행을 위해 지하철 2호선 마모 데이터와 마모 데이터에 영향을 미치는 각종 다변수 구간특성 및 환경인자를 사용하였다. 2호선 지하철의 구간특성 인자 및 환경인자는 레일의 종류, 레일의 위치, 도상, 곡률반경, 캔트 슬랙 및 운행 일수 등으로 구분하였다. 레일의 종류는 ks-50kg과 ks-60kg 두 종류의 레일이 있으며, 레일의 위치는 지상과 지하로 크게 구분할 수 있다. 도상은 콘크리트 도상, 자갈 도상과 일부 구간의 방진상 콘크리트 도상으로 구분할 수 있으며, 곡률반경은 직선구간과 완화곡선 구간 및 최소 250m부터 627m까지 분포된 원 곡선 구간으로 구분할 수 있다. 캔트 간격은 최소 96cm 부터 120cm 간격으로 구분하며, 슬랙은 5~9cm에 분포하고, 운행 기간은 해당 기간 동안 유지보수 이력이 없는 구간을 선정하여 2005년부터 2006년까지 4번에 걸쳐 검측된 지하철 2호선 내선 마모데이터를 사용하였다. 총 X1부터 X7까지 총 7개의 구간특성 또는 환경특성을 영향인자로 선정하였으며, 이러한 영향인자에 의해 결정되는 종속 인자로 Y1인 직마모와 Y2인 측마모를 선정하여 이 중 실질적으로 지하철 궤도의 성능 평가에 주요 판단인자로 사용되는 측마모와 구간특성 및 환경영향인자와의 상관관계 분석을 수행하였다. 해당 마모 데이터가 검측되는 기간 동안 유지보수 이력이 없는 12272 point의 데이터를 검출하였고 CART 프로그램을 이용하여 데이터를 분석하였으며, CART 프로그램의 해석을 위해 종속변수인 직마모량은 각 검측 지점의 마모량에 해당하는 등급으로 변환하여 분석을 수행하였다. 레일의 마모에 영향을 미치는 구간특성 및 환경인자와 종속 변수로 사용된 레일의 마모량 사이의 CART를 이용한 상관관계 분석은 실제 구조물에서 영향인자간의 상관 관계와 유사하며, 추후 연구에서는 이를 바탕으로 하여 정량화된 검측 데이터를 종속변수로 하여 구간특성 또는 환경인자 등 외부 영향인자를 고려한 궤도 검측데이터와의 상관관계 분석을 수행할 계획이다.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.293-308
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• 1997

Sliced inverse regression is a method for reducing the dimension of the explanatory variable X without going through any parametric or nonparametric model fitting process. This method explores the simplicity of the inverse view of regression; that is, instead of regressing the univariate output varable y against the multivariate X, we regress X against y. In this article, we propose bivariate sliced inverse regression, whose method regress the multivariate X against the bivariate output variables $y_1, Y_2$. Bivariate sliced inverse regression estimates the e.d.r. directions of satisfying two generalized regression model simultaneously. For the application of bivariate sliced inverse regression, we decompose the output variable y into two variables, one variable y gained by projecting the output variable y onto the column space of X and the other variable r through projecting the output variable y onto the space orthogonal to the column space of X, respectively and then estimate the e.d.r. directions of the generalized regression model by utilize two variables simultaneously. As a result, bivariate sliced inverse regression of considering the variable y and r simultaneously estimates the e.d.r. directions efficiently and steadily when the regression model is linear, quadratic and nonlinear, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.334-340
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• 2002

This paper proposes a self-organizing fuzzy modeling which can create a new hyperplane-shaped cluster by applying multiple regression to input/output data with relatively large fuzzy entropy, add the new cluster to fuzzy rule base and adjust parameters of the fuzzy model in repetition. Tn the coarse tuning, weighted recursive least squared algorithm and fuzzy C-regression model clustering are used and in the fine tuning, gradient descent algorithm is used to adjust parameters of the fuzzy model precisely And learning rates are optimized by utilizing meiosis-genetic algorithm. To check the effectiveness and feasibility of the suggested algorithm, four representative examples for system identification are examined and the performance of the identified fuzzy model is demonstrated in comparison with that of the conventional fuzzy models.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.286-289
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• 1997

In the design of structure the forces acting on the structure are important parameter for noise and vibration control. However, in the complex structure, the forces at the injection pomt on the structure cannot be measured directly. Thus it is necessary to find out indirect force evaluation method. In thls paper forces have been measured with in-situ vibration responses and system information. Three existing techniques of indirect force measurement, viz. direct inverse, principal component analysis and regularization have been compared. It has been shown that multi-vibration responses are essential for the precise estimation of the forces. To satisfy those cond~tions, Rotary compressor is adopted as test sample, because it is very difficult to measurc the injection forces from internal excitat~on to shell. It has also been obtained that relatively higher force IS transmitted through three welding paths to the compressor shell. It shows a good agreement between direct and indirect force evaluation wlth curvature shell and plate and is investigated the possibility of force evaluation of rotary compressor as a complex structure.

• The Korean Journal of Applied Statistics
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• v.21 no.3
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• pp.441-453
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• 2008

We analyzed Korean professional basketball and baseball players salary under the assumption that it depends on the personal records and contribution to the team in the previous year. We extensively used data visualization tools to check the relationship among the variables, to find outliers and to do model diagnostics. We used multiple linear regression and regression tree to fit the model and used cross-validation to find an optimal model. We check the relationship between variables carefully and chose a set of variables for the stepwise regression instead of using all variables. We found that points per game, number of assists, number of free throw successes, career are important variables for the basketball players. For the baseball pitchers, career, number of strike-outs per 9 innings, ERA, number of homeruns are important variables. For the baseball hitters, career, number of hits, FA are important variables.

• The Korean Journal of Nuclear Medicine
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• v.34 no.1
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• pp.30-38
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• 2000

Purpose: We investigated the role of myocardial perfusion SPECT in prediction of ventricular dilatation and the role of revascularization including thrombolytic therapy and PTCA in prevention of ventricular dilatation after an acute myocardial infarction (AMI). Materials and Methods: We performed dipyridamole stress, 4 hour redistribution, and 24 hour reinjection Tl-201 SPECT in 16 patients with AMI two to nine days after attack. Perfusion and wall motion abnormalities were quantified by perfusion index (PI) and wall motion index (WMI). Left ventricular ejection fraction (LVEF), WMI and ventricular volume were measured within 1 week of AMI and after average of 6 months. According to serial changes of left ventricular end-diastolic volume (LVEDV), patients were divided into two groups. We compared WMI, PI and LVEF between the two groups. Relationships among degree of volume, stress-rest PI, WMI, CKMB, Q wave, LVEF and revascularization were analysed using multivariate analysis. Results: Only initial rest perfusion index was significantly different between the two groups (p<0.05). While initial LVEF, stress PI, CKMB, trial of revascularization procedure, presence of Q wave and WMI were not significantly different between the two groups. Eight of 16 patients (50%) showed LV dilatation on follow-up echocardiography. Three of 3 patients (100%) who did not undergo revascualrization procedure documented LV dilatation. And only 5 (38%) of the remaining 13 patients who underwent revascularization revealed LV dilatation. There was no difference in infarct location between the two groups. By multivariate linear regression analysis in patients only undergoing revascularization, rest perfusion index was the only significant factor. Conclusion: Myocardial perfusion SPECT performed prior to revascularization was useful in prediction of LV dilatation after an AMI. Rest perfusion index on myocardial perfusion plays as a significant predictor of left ventricular dilatation after AMI. And revascularization appears to be a valuable procedure in alleviating LV dilatation after AMI with or without viable myocardium in a limited number of patients studied retrospectively.

• Management & Information Systems Review
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• v.39 no.2
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• pp.17-37
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• 2020

The purpose of this study is to investigate the global spillover effects through the existence of linear and nonlinear causal relationships between the US, European and BRIC financial markets after the period from the introduction of the Euro, the financial crisis and the subsequent EU debt crisis in 2007~2010. Although the global spillover effects of the financial crisis are well described, the nature of the volatility effects and the spread mechanisms between the US, Europe and BRIC stock markets have not been systematically examined. A stepwise filtering methodology was introduced to investigate the dynamic linear and nonlinear causality, which included a vector autoregressive regression model and a multivariate GARCH model. The sample in this paper includes the post-Euro period, and also includes the financial crisis and the Eurozone financial and sovereign crisis. The empirical results can have many implications for the efficiency of the BRIC stock market. These results not only affect the predictability of this market, but can also be useful in future research to quantify the process of financial integration in the market. The interdependence between the United States, Europe and the BRIC can reveal significant implications for financial market regulation, hedging and trading strategies. And the findings show that the BRIC has been integrated internationally since the sub-prime and financial crisis erupted in the United States, and the spillover effects have become more specific and remarkable. Furthermore, there is no consistent evidence supporting the decoupling phenomenon. Some nonlinear causality persists even after filtering during the investigation period. Although the tail distribution dependence and higher moments may be significant factors for the remaining interdependencies, this can be largely explained by the simple volatility spillover effects in nonlinear causality.

• Journal of the Korean Society for Nondestructive Testing
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• v.21 no.1
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• pp.80-90
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• 2001

The aim of this study is to develop the methodology which enables to identify the mechanical properties of element such as stress intensity factor by using the AE parameters. Considering the multivariate and nonlinear properties of AE parameters such as ringdown count, rise time, energy, event duration and peak amplitude from fatigue cracks of machine element the principal component regression(PCR) and artificial neural network(ANN) models for the estimation of stress intensity factor were developed and validated. The AE parameters were found to be very significant to estimate the stress intensity factor. Since the statistical values including correlation coefficients, standard mr of calibration, standard error of prediction and bias were stable, the PCR and ANN models for stress intensity factor were very robust. The performance of ANN model for unknown data of stress intensity factor was better than that of PCR model.