• Journal of applied mathematics & informatics
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• v.8 no.3
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• pp.959-973
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• 2001

We shall discuss one of some techniques needed to analyze algorithms. It is called a big-O function technique. The measures of efficiency of an algorithm have two cases. One is the time used by a computer to solve the problem using this algorithm when the input values are of a specified size. The other one is the amount of computer memory required to implement the algorithm when the input values are of a specified size. Mainly, we will restrict our attention to time complexity. To figure out the Time Complexity in nonlinear problems of Numerical Analysis seems to be almost impossible.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.423-427
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• 2003

In this paper, it is to development of brake system with ABS function for aircraft. The test of brake system is required before applying on aircraft. The real-time dynamic simulator with 5-D.O.F. aircraft dynamic model is developed for braking performance test of ABS (Anti-skid Brake System) control h/w with anti-skid brake functions. The dynamic simulator is real-time interface system that is composed of dynamic simulation parts, master control parts, digital and analog in/out interface parts, and user interface parts. The 5-D.O.F. aircraft dynamic model is composed of a big contour and a little contour by simulation s/w. The big contour represents the interactions of forces in airframe, nose and main landing gear, and engines on the center of gravity. The little contour represents interactions of wheel, braking units, hydraulic units and a control unit. ABS control h/w unit with ABS control algorithm is also developed and is tested with simulator under the some conditions of gripping coefficient. We have known that ABS control h/w unit on wet or snowy runway as well as dry runway very well protects wheel skid.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.217-220
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• 2000

This paper studies a real-time VBR traffic characterization. There are two big approaches to determine traffic. One is a statistic approach and the other is a deterministic approach. This paper proposes a new constraint function, what we called “Sub-Sum Constraint Function”(SSCF). This function is mainly based on a deterministic approach and uses a statistic approach. It predicts and calculates the next rate with a present information about the stream. SSCF captures the intuitive bounded by a rate lower than its peak rate and closer to its long-term average rate. This model makes a order of the constraint function much less than any other works (O(n)). It can also be mapped on a token bucket algorithm which consists of r (token rate) and b (token depth). We use a concept, EB(effective bandwidth) for a utility of our function and comparing with other techniques such as CBR, average VBR. We simulated 21 multimedia sources for verifying the utility of our function.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.155-162
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• 2017

In this paper we propose influence measures for two basic goodness-of-fit statistics, the coefficient of determination $R^2$ and test statistic F in the linear regression model using the deletion method. Some useful lemmas are provided. We also express the influence measures in terms of basic building blocks such as residual, leverage, and deviation that showed them as increasing function of residuals and a decreasing function of deviation. Further, the proposed measure reduces computational burden from O(n) to O(1). As illustrative examples, we applied the proposed measures to the stackloss data sets. We verified that deletion of one or few influential observations may result in big change in $R^2$ and F-statistic.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.422-425
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• 2002

Position balance control refers to ability that is kept bodily center of gravity under minimum position shake on surface of land. Patients who an injury of brain, a wound of the central nervous system or weakening of leg muscular power is fallen are trend increasing steadily by the car accident body balance function is on an increasing trended. These patients have difficulty in position balance control, receive big restriction walk and life style. This research composed to do body balance function rehabilitation training which elevate leg muscular power using step machine. And expect to become effective rehabilitation training device because measuring bodily pressure center using Force Platform and do so that can confirm training result easily as that is monitor.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.119-133
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• 2023

With the rapid growth of the economy and fossil fuel consumption, the concentration of air pollutants has increased significantly and the air pollution problem is no longer limited to small areas. We conduct statistical analysis with the actual data related to air quality that covers the entire of South Korea using R and Python. Some factors such as SO₂, CO, O₃, NO₂, PM₁₀, precipitation, wind speed, wind direction, vapor pressure, local pressure, sea level pressure, temperature, humidity, and others are used as covariates. The main goal of this paper is to predict air quality index (AQI) spatio-temporal data. The observations of spatio-temporal big datasets like AQI data are correlated both spatially and temporally, and computation of the prediction or forecasting with dependence structure is often infeasible. As such, the likelihood function based on the spatio-temporal model may be complicated and some special modelings are useful for statistically reliable predictions. In this paper, we propose several methods for this big spatio-temporal AQI data. First, random effects with spatio-temporal basis functions model, a classical statistical analysis, is proposed. Next, neural networks model, a deep learning method based on artificial neural networks, is applied. Finally, random forest model, a machine learning method that is closer to computational science, will be introduced. Then we compare the forecasting performance of each other in terms of predictive diagnostics. As a result of the analysis, all three methods predicted the normal level of PM_2.5 well, but the performance seems to be poor at the extreme value.

• Journal of Korean Society of Transportation
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• v.36 no.3
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• pp.203-215
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• 2018

This study suggests a method to construct large scale dynamic O/D reflecting the characteristic that the passengers' travel patterns change according to the land use patterns of the destination. There are limitations in the existing research about dynamic O/D estimation method, such as the difficulty of collecting data, which can be applied only to a small area, or limiting to a specific transportation network such as highway networks or public transportation networks. In this paper, we propose a method to estimate dynamic O/D without limitation of analysis area based on transportation resources that can be easily collected and used according to the big data era. Clustering analysis was used to calculate the departure time trip distribution ratio based on arrival time and departure time trip distribution function was estimated by each cluster. As a result of the comparison test with the survey data, the estimated distribution function was statistically significant.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.961-969
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• 2004

A panic state is often caused by careless computer control. It could be also caused by a kernel programmer's mistake. It can make a big problem in computer system when it happens a lot. When a panic occurs, the process of the panic state has to be checked, then if it can be restored, operating system restores it, but if not, operating system runs the panic function to stop the system in the kernel hardening O.S. To decide recovery of the process, the type of the panic for the present process should be checked. 1'he value type and the address type have to restore the process. If the system process is in a panic state, the system should be designed to shutdown hardening function In the Linux operating system. So it has to decide whether the process should be restored or not before going to the panic state.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.24 no.3
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• pp.51-58
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• 1998

Generally pigment differs from dye stuff because it cannot be melted in water but also because it is stable physically and chemically. In this study you will discover the function, properties and effects of Micai-TiO$_2$-SiO$_2$pigment as abase material pigment. But until now used Mica of the base material is about 7-l5${\mu}{\textrm}{m}$ with an average diameters of 15${\mu}{\textrm}{m}$. A new characteristic superficial pigment was obtained from covering the TiO$_2$ and SiO$_2$ with the adsorption result of isoelectric point of a Mica flake, TiO$_2$ and SiO$_2$In the composition reaction study of adsorption was done as well as the physical characteristics of the superficial texture of the obtained material. L,a,b of color change as oil was absorbed, optical nature and change of reflection according to direct and diffused reflection. In the composition of Mica slurry the best result obtained was in a solution with pH 2.0 to 2.3. Following this result, we can come to the idea that electrical attraction was done during the change of electrical charge of the Mica and TiO$_2$ deposit. Also this pigment shows a big scale between the direct reflection and diffused reflection light. Using this characteristic in cosmetic, it was obtained a natural but a contrast between light and shadow making possible a sculptured make-up. Color change due to oil adsorption was insignificant which improved the last of make up.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.325-330
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• 2004

The Big O notation of a sorting algorithm analysis is an asymptotic algorithm analysis which gives information of a rough mathematical function with an infinite increase of a sample size, without any specification of a probabilistic model. Hence. in an application with a limited finite number of data, it is necessary to test efficiencies of sorting algorithms. I estimated probabilistic models which analyze the number of exchanges varying input sizes to sort. The estimated models to explain the relationship of sorting efficiency on the sample size (N of the sample size and S of the number of exchange of elements) are S=0.9305 $N^{1.339}$ for Quick sort algorithm with O(nlogn) time complexity, and S=0.2232 $N^{2.0130}$ for Insertion sort algorithm with O( $n^2$) time complexity. Furthermore, there are strongly supports that more than 99% of the above relationship could be explained by the estimated models (p＜0.001). These findings suggest it is necessary to analyze sorting algorithm efficiency in applications with a finite number of data or a newly developed sorting algorithm.