• 한국안전학회지
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• 제16권4호
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• pp.168-174
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• 2001

For human error analysis, the structure and situation of a task should be analyzed in advance. The paper introduces Structured Information Analysis (SIA) as a task analysis method for error analysis, and delineates the result of application on the emergency procedure of Korean Standard Nuclear Plants (KSNPs). From the task analysis about emergency procedure of KSNP, total 72 specific task goals were identified in the level of system function, and 86 generic tasks were classified from the viewpoint of physical sameness of the task description. Human errors are dependent on task types so that the result of task analysis would be used as a basis for the error analysis on the emergency tasks in nuclear power plants.

• 설비공학논문집
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• 제15권4호
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• pp.287-293
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• 2003

This study examined the temperature-dependent regression model of energy consumption based on various measuring period. The methodology employed was to construct temperature-dependent linear regression model of daily energy consumption from one day to three months data-sets and to compare the annual heating energy consumption predicted by these models with actual annual heating energy consumption. Heating energy consumption from a building in Daejon was examined experimentally. From the results, predicted value based on one day experimental data can have error over 100%. But predicted value based on one week experimental data showed error over 30%. And predicted value based on over three months experimental data provides accurate prediction within 6% but it will be required very expensive.

• Communications for Statistical Applications and Methods
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• 제26권4호
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• pp.371-383
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• 2019

Panel data sets have been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Maximum likelihood (ML) may be the most common statistical method for analyzing panel data models; however, the inference based on the ML estimate will have an inflated Type I error because the ML method tends to give a downwardly biased estimate of variance components when the sample size is small. The under estimation could be severe when data is incomplete. This paper proposes the restricted maximum likelihood (REML) method for a random effects panel data model with a censored dependent variable. Note that the likelihood function of the model is complex in that it includes a multidimensional integral. Many authors proposed to use integral approximation methods for the computation of likelihood function; however, it is well known that integral approximation methods are inadequate for high dimensional integrals in practice. This paper introduces to use the moments of truncated multivariate normal random vector for the calculation of multidimensional integral. In addition, a proper asymptotic standard error of REML estimate is given.

• Communications for Statistical Applications and Methods
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• 제23권5호
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• pp.385-397
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• 2016

The stress-strength models have been intensively investigated in the literature in regards of estimating the reliability ${\theta}$ = P(X > Y) using parametric and nonparametric approaches under different sampling schemes when X and Y are independent random variables. In this paper, we consider the problem of estimating ${\theta}$ when (X, Y) are dependent random variables with a bivariate underlying distribution. The empirical and kernel estimates of ${\theta}$ = P(X > Y), based on bivariate ranked set sampling (BVRSS) are considered, when (X, Y) are paired dependent continuous random variables. The estimators obtained are compared to their counterpart, bivariate simple random sampling (BVSRS), via the bias and mean square error (MSE). We demonstrate that the suggested estimators based on BVRSS are more efficient than those based on BVSRS. A simulation study is conducted to gain insight into the performance of the proposed estimators. A real data example is provided to illustrate the process.

• 대한전자공학회논문지SD
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• 제40권5호
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• pp.290-297
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• 2003

전자와 정공의 온도 관련 이온화 계수로부터 추출한 온도 함수의 유효 이온화 계수 및 전자 이동도를 이용하여 실리콘 전력 MOSFET의 항복 전압과 on 저항을 위한 온도 함수의 해석적 표현식을 유도하였다. 온도 함수의 해석적 항복 전압 결과를 4x10/sup 14/ cm/sup -3/, 1x10/sup 15/ cm/sup -3/, 6x10/sup 16/ cm/sup -3/의 도핑 농도에 대해 각각 실험 결과와 비교하였고, 온도 및 항복 전압 함수의 on 저항 변화도 각각 실험 결과와 비교하였다. 각농도에 따른 온도 함수의 해석적 항복 전압은 77∼300k의 온도 범위에서 실험 결과와 10% 이내의 오차로 잘 일치하였다.

• 한국측량학회지
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• 제32권3호
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• pp.225-231
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• 2014

When a spatial regression model that uses kernel density values as a dependent variable is applied to retail business data, a unique model cannot be selected because kernel density values change following kernel bandwidths. To overcome this problem, this paper suggests how to use the point pattern analysis, especially the L-index to select a unique spatial regression model. In this study, kernel density values of retail business are computed by the bandwidth, the distance of the maximum L-index and used as the dependent variable of spatial regression model. To test this procedure, we apply it to meeting room business data in Seoul, Korea. As a result, a spatial error model (SEM) is selected between two popular spatial regression models, a spatial lag model and a spatial error model. Also, a unique SEM based on the real distribution of retail business is selected. We confirm that there is a trade-off between the goodness of fit of the SEM and the real distribution of meeting room business over the bandwidth of maximum L-index.

• Journal of electromagnetic engineering and science
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• 제11권2호
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• pp.133-142
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• 2011

Coded cooperation that integrates channel coding in cooperative transmission has gained a great deal of interest in wireless relay networks. The performance analysis of coded cooperation protocol with multiple relays is investigated in this paper. We show that the diversity order achieved by the coded cooperation in a multi-relay wireless network is not only dependent on the number of cooperating relays but is also dependent on the code-rate of the system. We derive the code-rate bound, which is required to achieve the full diversity gain of the order of cooperating nodes. The code-rate required to achieve full diversity is a linearly decreasing function of the number of available relays in the network. We show that the instantaneous channel state information (CSI)-based relay selection can effectively alleviate this code-rate bound. Analysis shows that the coded cooperation with instantaneous CSI-based relay selection can achieve the full diversity, for an arbitrary number of relays, with a fixed code-rate. Finally, we develop tight upper bounds for the bit error rate (BER) and frame error rate (FER) of the relay selection based on coded cooperation under a Rayleigh fading environment. The analytical upper bounds are verified with simulation results.

• International Journal of Computer Science & Network Security
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• 제24권2호
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• pp.31-42
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• 2024

Different industries mostly rely on quality certification for promoting their products or brands. Although getting quality certification, specifically by human experts is a tough job to do. But the field of machine learning play a vital role in every aspect of life, if we talk about quality certification, machine learning is having a lot of applications concerning, assigning and assessing quality certifications to different products on a macro level. Like other brands, wine is also having different brands. In order to ensure the quality of wine, machine learning plays an important role. In this research, we use two datasets that are publicly available on the "UC Irvine machine learning repository", for predicting the wine quality. Datasets that we have opted for our experimental research study were comprised of white wine and red wine datasets, there are 1599 records for red wine and 4898 records for white wine datasets. The research study was twofold. First, we have used a technique called backward elimination in order to find out the dependency of the dependent variable on the independent variable and predict the dependent variable, the technique is useful for predicting which independent variable has maximum probability for improving the wine quality. Second, we used a robust machine learning algorithm known as "XGBoost" for efficient prediction of wine quality. We evaluate our model on the basis of error measures, root mean square error, mean absolute error, R2 error and mean square error. We have compared the results generated by "XGBoost" with the other state-of-the-art machine learning techniques, experimental results have showed, "XGBoost" outperform as compared to other state of the art machine learning techniques.

• 한국기계가공학회지
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• 제20권7호
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• pp.15-24
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• 2021

In this paper, to analyze the types of surface morphology error according to factors that cause machining error, the experiments were conducted in the ultra-precision diamond machine using a diamond tool. The factors causing machining error were classified into the pressure variation of compressed air, external shock, tool errors, machining conditions (rotational speed and feed rate), tool wear, and vibration. The pressure variation of compressed air causes a form accuracy error with waviness. An external shock causes a ring-shaped surface defect. The installed diamond tool for machining often has height error, feed-direction position error, and radius size error. The types of form accuracy error according to the tool's errors were analyzed by CAD simulation. The surface roughness is dependent on the tool radius, rotational speed, and feed rate. It was confirmed that the surface roughness was significantly affected by tool wear and vibration, and the surface roughness of Rz 0.0105 ㎛ was achieved.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1073-1076
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• 1991

This paper presents a robust model reference adaptive controller for continuous-time single-input single-output linear time-invariant systems which are subjected to output-dependent disturbances as well as bounded external disturbances. In the derived controller form, an additional output error feedback term is included to over-ride the destabilizing effects by the output-dependent disturbances.