• The Korean Journal of Applied Statistics
• /
• v.2 no.2
• /
• pp.47-51
• /
• 1989

We study by stepwise regression method, the influence which atmospheric pollution in Jilin City has on the rate of death accorrding to cancer. The extremes are discovered and we know that $SO_2$ and smoking are important factors too.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.26 no.4
• /
• pp.309-314
• /
• 2013

This paper dealt with the radiated electromagnetic wave detection of partial discharge (PD) in oil for insulation diagnostics of oil-immersed transformers. Three types of electrode system were fabricated to simulate the insulation defects that could occur in oil-immersed transformers. Frequency components of radiated electromagnetic wave in oil was measured by broadband bi-conical antennas of 300 MHz~2 GHz and a spectrum analyzer of 9 kHz~3 GHz. Frequency component of electromagnetic waves from PD in oil were highly distributed at 500 MHz. From the result, a narrow-band monopole antenna with the center frequency of 500 MHz was fabricated. We could detect PD signal in insulation oil without an influence of external noise by a measurement system which consists of the prototype monopole antenna, a LNA (Low Noise Amplifier), an oscilloscope and a spectrum analyzer.

• Journal of Korean Society on Water Environment
• /
• v.23 no.1
• /
• pp.161-168
• /
• 2007

The main aim of this work is focus on the Geum river water quality evaluation of pollution data obtained by monitoring measurement during the period 2001-2005. The complex data matrix 19 (entire monitoring stations)*13 (parameters), 60 (month)*13 (parameters) and 20 (season)*13 (parameters) were treated with different multivariate techniques such as factor analysis/principal component analysis (FA/PCA). FA/PCA identified two factor (19*13) classified pollutant Loading factor (BOD, COD, pH, Cond, T-N, T-P, $NH_3$-N, $NO_3$-N, $PO_4$-P, Chl-a), seasonal factor (water temp, SS) and three Factor (60*13, 20*13) classified pollutant Loading factor (BOD, COD, Cond, T-N, T-P, $NH_3$-N, $NO_3$-N, $PO_4$-P), seasonal factor (water temp, SS) and metabolic factor (Chl-a, pH). Loadings of pollutant factor is potent influence main factor in the Geum river which is explained by loadings of pollutant factor at whole sampling stations (71.16%), month (52.75%) and season (56.57%) of main water quality stations. Result of this study is that pollutant loading factor is affected at Gongju 1, 2, Buyeo 1, 2, Gangkyeong, Yeongi stations by entire stations and entire month (Gongju 1, Cheongwon stations), April, May, July and August (buyeo 1) by month. Also the pollutant Loading factor is season gives an influence in winter (Gongju 1, buyeo 1) from main sampling stations, but Cheongwon characteristic is non-seasonal influenced. This study presents necessity and usefulness of multivariate statistic techniques for evaluation and interpretation of large complex data set with a view to get better information data effective management of water sources.

• 전기의세계
• /
• v.29 no.2
• /
• pp.118-128
• /
• 1980

The properties of plasmas produced by high power glass laser were investigated with various methods of diagnostics. Electron temperature was estimated by measurement of soft X-ray, and ion temperature was estimated by measurement of the time-of-flight of ion. The measurement of incident and reflected laser light, and Schlieren and shadowgragh methods were also used. No influence of laser pulse duration on the temperature was observed in the case of durations 2, 4 and 10 nsecs. The effective heating of plasma occurred in about 2 nsec of beginning of incident laser pulse. The experimental results for fast rising laser pulse were discussed and the influence of resetime of laser pulse on the heating of plasma was described. Neutrons produced by irradiating laser beam to solid deuterium target were detected.

• Communications for Statistical Applications and Methods
• /
• v.23 no.3
• /
• pp.231-239
• /
• 2016

A graphical diagnostic method based on multiple case deletions in a regression context is introduced by using the sampling distribution of the difference between two least squares estimators with and without multiple cases. Principal components analysis plays a key role in deriving this diagnostic method. Multiple case deletions of test statistic are also considered when a new observation is fitted to a given regression model. The result is useful for detecting influential observations in econometric data analysis, for example in checking whether the consumption pattern at a later time is the same as the one found before or not, as well as for investigating the influence of cases in the usual regression model. An illustrative example is given.

• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.11 no.1
• /
• pp.157-166
• /
• 2007

Background: The change in the respiratory pattern has an influence on the change in the autonomic nervous system, which in turn has an influence on the EGG to measure a gastric activity. However, the study on the influence on the EGG parameters by respiratory control and on the correlation between the HRV and EGG through respiratory control has not been perform yet. Objective: It is to perform a series of experiments to find out how the EGG parameters are influenced by the controlled respiration and what correlation there may exist between the EGG and HRV to measure the change in the autonomic nervous system after controlled respiration. Methods: 1st Experiment: During a 15minutes' voluntary respiration, HRV was measured, and it was measured again during another 15 minutes' controlled respiration. 2nd Experiment: After an eight hours' fast, EGG was measured for a period of 30 minutes, and then after another 15 minutes' voluntary respiration, a test-meal was offered for 10 minutes and again EGG was measured. The next day, after an 8 hour's fast, EGG was measured for 30 minutes, and after a 15 minutes' controlled respiration and offered with a test-meal for 10 minutes and then EGG was measured again for 30 minutes. Results: 1. It was observed in all the channels that the power ratio increased more after controlled respiration than after voluntary respiration. No statistical significance, however, could be observed. 2. Through controlled respiration, the HF of HRV and the power ratio of EGG Channel 4 was negatively correlated, while the LF/HF of HRV and the power ratio of EGG channel 1 & 4 was positive correlated. Such correlations as mentioned above, however, could not be observed in HRV & EGG through voluntary respiration. Conclusions: 1. It was concluded that the increase in the power of gastric contractile after controlled respiration is bigger than the increase in the power of gastric contractile after voluntary respiration. 2. It was concluded that the gastric contractile power and sympathetic activity through controlled respiration was negatively correlated, while the gastric contractile power and parasympathetic activity through controlled respiration was positively correlated.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.6
• /
• pp.1291-1300
• /
• 2017

In the high-dimensional data, the number of variables is very larger than the number of observations. In this case, the impact of influential observations on regression coefficient estimates can be very large. Jang and Anderson-Cook (2017) suggested the LASSO influence plot. In this paper, we propose the LASSO influence plot, LASSO variable selection ranking plot, and three-dimensional LASSO influence plot as graphical methods for evaluating the impact of influential observations in high-dimensional data. With real two high-dimensional data examples, we apply these graphical methods as the regression diagnostics tools for finding influential observations. It has been found that we can obtain influential observations with by these graphical methods.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.18 no.5
• /
• pp.1516-1519
• /
• 2004

I studied on the influence of Gi-Gong gymnastics in the live blood condition of women's shoulder measurement. The results are as follows: In the Erythrocyte Aggregation(4 women), the three women were not observed at all and one woman was observed a little, In the Rouleau(3 women), three women were not observed at all. In the Target Cells(3 women), the two women were not observed at all and one woman was observed a little. In the Ovalocytes (3 women), the one woman was not observed at all and two women were observed a little. And in the Poikilocytes (1 woman), one woman was observed a little, In the Cholesterol Crystals(3 women), the two women were observed a little and one woman was observed as things stand, In the Atherosclerotic Plaque(2 women), the two women were not observed at all. In the Chylous(3 women), the two women were observed a little and one woman was observed as things stand.

• Communications for Statistical Applications and Methods
• /
• v.24 no.6
• /
• pp.605-625
• /
• 2017

This paper presents proportional odds cure models to allow spatial correlations by including spatial frailty in the interval censored data setting. Parametric cure rate models with independent and dependent spatial frailties are proposed and compared. Our approach enables different underlying activation mechanisms that lead to the event of interest; in addition, the number of competing causes which may be responsible for the occurrence of the event of interest follows a Geometric distribution. Markov chain Monte Carlo method is used in a Bayesian framework for inferential purposes. For model comparison some Bayesian criteria were used. An influence diagnostic analysis was conducted to detect possible influential or extreme observations that may cause distortions on the results of the analysis. Finally, the proposed models are applied for the analysis of a real data set on smoking cessation. The results of the application show that the parametric cure model with frailties under the first activation scheme has better findings.

• Journal of Drive and Control
• /
• v.20 no.3
• /
• pp.1-8
• /
• 2023

The purpose of this study was to investigate and compare the impact of engine load on the emission characteristics of excavator engines, with the aim of improving the method for calculating the emission inventory of construction machinery. The engine load in excavators is directly correlated with the operational workload, and variations in the load factor (LF) can significantly influence the emission inventory. Thus, on-board diagnostic (OBD) data from an excavator at a construction site were systematically collected to measure engine output and emissions. The results revealed discernible differences in emissions based on engine load, even when the average excavator engine performance remained constant. This highlights the significant influence of the type and characteristics of the work being carried out on emission characteristics. Making realistic adjustments to the LF used in emission calculation formulas emerges as a crucial strategy for environmental improvement. Moreover, the analysis of the effects of engine load on emissions from excavators provides valuable insights for enhancing environmental protection measures.