• 한국해양학회지
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• v.17 no.2
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• pp.74-82
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• 1982

The study on the variation coefficient of water temperature and salinity was comducted during the year from 1968 to 1980 in the Southern Sea of Korea. The results obtaland from the study as followes; 1. The variation coefficient of water temperature and salinity wewe large either at the front area or the thermocline and malocline area. 2. The variation coefficient of water temperature was the largest at the time when the power was strong ty each water mass(The largest value in Tsushima and Yellow Sea Warm Current area was occurred at the 50m layer in the Summer, and that in the South Korean Coastal Water area and the Southern Part of Yellow Sea was at all layer in the Winter). 3. The variation coefficient of salinity was the largest at the surface layer in warm current area that was influenced by the low salinity of the East China Coastal Water in the Summer ,and that of salinity in the South Korean Coastal Water area and Soutern Part of Yellow Sea was nearly half of the value of the warm current area.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.1
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• pp.33-42
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• 1999

Geometrically standardized dental radiographs were taken. We prepared Digital Cu-Equivalent Image Analyzing System for quantitative assessment of mandible bone. Images of radiographs were digitized by means of Quick scanner and personal Mcquintosh computer. NIH image as software was used for analyzing images. A stepwedge composed of 10 steps of 0.1mm copper foil in thickness was used for reference material. This study evaluated the effects of step numbers of copper wedge adopted for calculating equation. kVp and exposure time on the coefficient of determination(r²)of the equation for conversion to Cu-equivalent image and the coefficient of variation and Cu-Eq value(mm) measured at each copper step and alveolar bone of the mandible. The results were as follows: 1. The coefficients of determination(r²) of 10 conversion equations ranged from 0.9996 to 0.9973(mean=0.9988) under 70kVp and 0.16 sec. exposure. The equation showed the highest r was Y=4.75614612-0.06300524x +0.00032367x² -0.00000060x³. 2. The value of r² became lower when the equation was calculated from the copper stepwedge including 1.0mm step. In case of including 0mm step for calculation. the value of r showed variability. 3. The coefficient of variation showed 0.11, 0.20 respectively at each copper step of 0.2, 0.1mm in thickness. Those of the other steps to 0.9 mm ranged from 0.06 to 0.09 in mean value. 4. The mean Cu-Eq value of alveolar bone was 0.14±0.02mm under optimal exposure. The values were lower than the mean under the exposures over 0.20sec. in 60kVp and over 0.16sec. in 70kVp. 5. Under the exposure condition of 60kVp 0.16sec.. the coefficient of variation showed 0.03. 0.05 respectively at each copper-step of 0.3, 0.2mm in thickness. The value of r² showed over 0.9991 from both 9 and 10 steps of copper. The Cu-Eq value and the coefficient of variation was 0.14±0.01mm and 0.07 at alveolar bone respectively. In summary. A clinical application of this system seemed to be useful for assessment of quantitative assessment of alveolar provided high coefficient of determination is obtained by the modified adoption of copper step numbers and the low coefficient of variation for the range of Cu-Equivalent value of alveolar bone from optimal kVp and exposure time for each x-ray machine.

• Journal of the Speleological Society of Korea
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• v.14 no.15
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• pp.42-90
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• 1987

Lee, Moon Won reported by 63 kinds lescribing the petrography and bulk chemical Composition in Petrology of Cheju volcanic island. The total Chemical Composition data was analyzed by the program of FORTRAN77. First, the Conversition equations and the scatter diagram were examined to the analysis, by the least square method. Next, a statistical data requested a mean Value, maximum value, minimum value, the range, the standard deviation, the variance, the Standord Error and the Coefficient of variation. In the standard deviation, a small Composition is MnO and P$_2$O$\sub$5/, a large Composition is SiO$_2$, Mgo and FeO. The Standard error and the variance were the tandency looked like the Standard deviation well. However, the Coefficient Variation differs from the Standard deviation. Where, a large Coefficient of variation are H$_2$O$\^$-/ and H$_2$O$\^$+/, a small Coefficient of variation are Al$_2$O$_3$ and SiO$_2$. The Correlation of Coefficient Can be Calculated numerically from the relation between SiO$_2$, Al$_2$O$_3$ and TiO$_2$ to other Compositions.

• Journal of Mechanical Science and Technology
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• v.14 no.10
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• pp.1151-1158
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• 2000

Combustion analysis based on cylinder-pressure provides a mechanism through which a combustion researcher can understand the combustion process. The objective of this paper was to identify the most significant sources of cycle-to-cycle combustion variability in a spark ignition engine at idle. To analyse the cyclic variation in a test engine, the burn parameters are determined on a cycle-to-cycle basis through the analysis of the engine pressure data. The burn rate analysis program was used here and the burn parameters were used to determine the variations in the input parameter-i. e., fuel, air, and residual mass. In this study, we investigated the relationship of indicated mean effective pressure (IMEP), coefficient of variation (COV) of IMEP, burn angles, and lowest normalized value (LNV) in a spark ignition engine in a view of cyclic variations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.116-122
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• 2016

Recently, the production cycle in manufacturing process has been getting shorter and different types of product have been produced in the same process line. In this case, the control chart using coefficient of variation would be applicable to the process. The theory that random variables are located in the three times distance of the deviation from mean value is applicable to the control chart that monitor the process in the manufacturing line, when the data of process are changed by the type of normal distribution. It is possible to apply to the control chart of coefficient of variation too. ${\bar{x}}$, s estimates that taken in the coefficient of variation have just used all of the data, but the upper control limit, center line and lower control limit have been settled by the effect of abnormal values, so this control chart could be in trouble of detection ability of the assignable value. The purpose of this study was to present the robust control chart than coefficient of variation control chart in the normal process. To perform this research, the location parameter, ${\bar{x_{\alpha}}}$, $s_{\alpha}$ were used. The robust control chart was named Tim-CV control chart. The result of simulation were summarized as follows; First, P values, the probability to get away from control limit, in Trim-CV control chart were larger than CV control chart in the normal process. Second, ARL values, average run length, in Trim-CV control chart were smaller than CV control chart in the normal process. Particularly, the difference of performance of two control charts was so sure when the change of the process was getting to bigger. Therefore, the Trim-CV control chart proposed in this paper would be more efficient tool than CV control chart in small quantity batch production.

• Journal of Korea Foundry Society
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• v.38 no.5
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• pp.95-102
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• 2018

The dependence of the tensile properties on variations in the porosity of A356 aluminium alloys was investigated in terms of the quality index of the tensile properties based upon the ultimate tensile strength and elongation as well as the variation of the strength coefficient and strain-hardening exponent with regard to a T6 treatment. The test specimens were prepared by low-pressure die-casting and a subsequent T6 treatment, and the experimental results of a tensile test carried out at room temperature were compared to the theoretical description using a modified constitutive model. The nominal value of the quality index of A356 alloys increases gradually with a lapse of the ageing time upon a T6 treatment, despite the fact that this value is temporarily decreased during the initial stage of ageing from a solutionised condition. Additionally, the quality index depends practically upon the porosity variation with a power law relationship without regard to whether in solutionised or artificial aged conditions. The theoretical description indicates that the strength coefficient directly determines the nominal level of the quality index. Moreover, the overall dependence of the quality index on the porosity variation is remarkably weakened with an increase in the tensile strain, whereas the quality index depends sensitively upon the porosity variation with a low value of the strain-hardening exponent.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.288-292
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• 2006

Usually, equations that calculate ground resistance of earth electrode was already informed well by form of earth electrode. But, when apply on the spot because general expressions are very insufficient at point that calculate exact ground resistance value by variation of earth electrode, and constant value that corrective coefficient for ground resistance calculation is fixed regardless of change of the earth resistivity specially is presented, it is actuality that difficulty is. Therefore, in this study, about these problem, proposed corrective coefficient for calculation of ground resistance according to change of the earth resistivity.

• Smart Structures and Systems
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• v.16 no.6
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• pp.1091-1105
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• 2015

Piezoelectric coefficient and dielectric constant of PZT-5H vary with electric field. In this work, variations of these coefficients with electric field are included in finite element modelling of a cantilevered plate instrumented with piezoelectric patches. Finite element model is reduced using modal truncation and then converted into state-space. First three modal displacements and velocities are estimated using Kalman observer. Negative first modal velocity feedback is used to control the vibrations of the smart plate. Three cases are considered v.i.z case 1: in which variation of piezoelectric coefficient and dielectric constant with electric field is not considered in finite element model and not considered in Kalman observer, case 2: in which variation of piezoelectric coefficient and dielectric constant with electric field is considered in finite element model and not considered in Kalman observer and case 3: in which variation of piezoelectric coefficient and dielectric constant with electric field is considered in finite element model as well as in Kalman observer. Simulation results show that appreciable amount of change would appear if variation of piezoelectric coefficient and dielectric constant with r.m.s. value of electric field is considered.

• Korean Journal of Mathematics
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• v.22 no.4
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• pp.633-644
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• 2014

We get one theorem that there exists a unique solution for the fourth order semilinear elliptic Dirichlet boundary value problem when the number 0 and the coefficient of the semilinear part belong to the same open interval made by two successive eigenvalues of the fourth order elliptic eigenvalue problem. We prove this result by the contraction mapping principle. We also get another theorem that there exist at least two solutions when there exist n eigenvalues of the fourth order elliptic eigenvalue problem between the coefficient of the semilinear part and the number 0. We prove this result by the critical point theory and the variation of linking method.

• Journal of Mechanical Science and Technology
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• v.15 no.1
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• pp.81-87
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• 2001

Cyclic variability limits the range of operating conditions of spark ignition engines, especially under lean and highly diluted operation conditions. The cyclic combustion variations can be characterized by pressure parameters, combustion related parameters, and flame-front related parameters. The coefficient of variation (COV) in indicated mean effective pressure (IMEP) defines the cyclic variability in indicated work per cycle.