• 한국표면공학회지
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• 제40권4호
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• pp.185-189
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• 2007

A scanning electron microscope (SEM) is a complex system, consisting of many sophisticated components. For a systematic characterization, a $2^4$ full factorial experiment was conducted. The SEM components examined include condenser lens 1 and 2 (denoted as A and B, respectively), and Objective lens (coarse and fine-denoted as C and D respectively). A statistical analysis was conduced to investigate factor effects and variations In response surfaces. Among four factors, main effect analysis revealed that A and D were Identified as the dominant factor. Moreover, B showed conflicting effect against C. The $R^2$ of statistical regression model constructed was about 69.6%. The model generated 3D response surface plots facilitated understanding of complex tactor effects.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2335-2339
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• 2003

To prevent the critical situation due to the fault in the aircraft sensor system, the fault tolerant system with triple or quadruple redundancy can be made. However, if the faults are occurred in two or more than sensors simultaneously, the conventional fault detection process, such as cross-channel monitoring, may give the wrong fault alarm. For this case, we can detect the fault by estimating the state vector based on the system dynamics model, which is nonlinear for aircraft. In this paper, we propose the unscented Kalman filter to estimate the nonlinear state vector. This filter utilizes the so-called unscented transformation of sigma points featured the statistical characteristics of the random variable. For verification, we perform the simulations for F-16 aircraft with accelerometers, gyros, GPS and air data system.

• 한국멀티미디어학회논문지
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• 제24권12호
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• pp.1682-1692
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• 2021

Digital Twin, one of the core technologies of the Fourth Industrial Revolution, is attracting attention as a very suitable technology for disaster monitoring such as fires and earthquakes. In this paper, we implement a system equipped with UWB RTLS(Ultra-Wideband Real Time Location System), real-time remote control, and video streaming, which are element technologies for disaster monitoring digital twin. Since the proposed system structure is based on a cloud server, the actual location of the UWB indoor positioning-based client is transmitted to the user device in real time and stored on the cloud server for statistical and data analysis. In addition, we demonstrate through experiments that outliers occurs when the value of RSSI(Received Signal Strength Indicator) decreases due to communication collisions between UWB Tags, and propose an RSSI outlier correction algorithm to solve this problem.

• 항공우주시스템공학회지
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• 제14권2호
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• pp.50-56
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• 2020

In this study, we investigated whether long short-term memory (LSTM) can be used in the future to predict F10.7 index data; the F10.7 index is a space environment factor affecting atomic oxygen erosion. Based on this, we compared the prediction performances of LSTM, the Autoregressive integrated moving average (ARIMA) model (which is a traditional statistical prediction model), and the similar pattern searching method used for long-term prediction. The LSTM model yielded superior results compared to the other techniques in the prediction period starting from the max/min points, but presented inferior results in the prediction period including the inflection points. It was found that efficient learning was not achieved, owing to the lack of currently available learning data in the prediction period including the maximum points. To overcome this, we proposed a method to increase the size of the learning samples using the sunspot data and to upgrade the LSTM model.

• 산업경영시스템학회지
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• 제42권1호
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• pp.106-114
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• 2019

Recently, the manufacturing process system in the industrial field has become more and more complex and has been influenced by many and various factors. Moreover, these factors have the dependent correlation rather than independent of each other. Therefore, the statistical analysis has been extended from the univariate method to the multivariate method. The process capability indices have been widely used as statistical tools to assess the manufacturing process performance. Especially, the multivariate process indices need to be enhanced with more useful information and extensive application in the recent industrial fields. The various multivariate process capability indices have been studying by many researchers in recent years. Hence, the purpose of the study is to compare the useful and various multivariate process capability indices through the simulation. Among them, we compare the useful models of several multivariate process capability indices such as $MC_{pm}$, $MC^+_{pm}$ and $MC_{pl}$. These multivariate process capability indices are incorporates both the process variation and the process deviation from target or consider the expected loss caused by the process deviation from target. Through the computational examples, we compare these process capability indices and discuss their usefulness and effectiveness.

• Communications for Statistical Applications and Methods
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• 제16권4호
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• pp.557-572
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• 2009

공무원연금제도가 도입된 지 40여 년이 지난 현재, 기대여명의 증가로 인해 수급자가 크게 늘어나 부양률이 상승하면서 공무원연금 재정이 문제가 되고 있다. 본 논문에서는 현재 공무원연금제도와 노령화 수준을 반영한 확률모형을 설정하여 개인가입자의 혜택수준을 검토하며, 연금재정의 안정성을 모의실험 하였다. 연구방법으로는 개인가입자별 총기여금과 총수령금의 기대값을 비교하는 방법과 몬테카를로 모의시행을 통해 기금의 파산확률 및 준비금, 국가보전금을 구해보는 방법을 이용하였다.

• Communications for Statistical Applications and Methods
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• 제28권4호
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• pp.393-410
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• 2021

The Korean Long-Term Care Insurance (K-LTCI) provides financial support for long-term care service to people who need various types of assistance with daily activities. As the number of elderly people in Korea is expected to increase in the future, the demand for long-term care insurance would also increase over time. Projection of future expenditure on K-LTCI depends on the number of beneficiaries within the grading system of K-LTCI based on the test scores of applicants. This study investigated the suitability of mixture distributions to the model K-LTCI score distribution using recent empirical data on K-LTCI, provided by the National Health Insurance Service (NHIS). Based on the developed mixture models, the number of beneficiaries in each grade and its variability under the current grading system were estimated by simulation. It was observed that a mixture model is suitable for K-LTCI score distribution and may prove useful in devising a funding plan for K-LTCI benefit payment and investigating the effects of any possible revision in the K-LTCI grading system.

• 한국인공지능학회지
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• 제12권1호
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• 응용통계연구
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• 제30권1호
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• pp.13-24
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• 2017

국민건강보험공단에서 제공하는 표본코호트DB는 보건의료계뿐만 아니라 통계학 연구를 위한 중요한 자원이다. 일반적으로 이들 자료에서 연구에 필요한 정보를 얻기 위하여 관련 사례들을 추출하는 과정에는 많은 시간과 노력이 들게 된다. 본 논문에서는 표본코호트DB를 이용하고자 할 때 사례 추출과정에 도움을 주는 데이터베이스 시스템인 National Health Insurance Service Cohort DB Extract Tool(NICE Tool)을 소개한다. SAS의 DATA 명령문이나 SQL문에 익숙하지 않은 연구자들도 쉽게 마우스 클릭만으로 DB에서 필요한 변수들과 조건에 맞는 사례들을 추출할 수 있는 기능을 제공한다. 이 시스템을 활용하면 빠른 사례추출이 가능하여 표본코호트DB를 사용한 연구들이 더욱 활성화되리라 판단된다.

• 한국기후변화학회지
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• 제6권3호
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• pp.203-208
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• 2015

This study was conducted to provide the agricultural climatological basic data for the reset of sowing period of the winter crop on the double cropping system with rice. During the past 30 years from 1981 to 2010, mean air temperature has risen by $0.45^{\circ}C$ per 10 years (with statistical significance), while precipitation has decreased by 6.74 mm per 10 years and the numbers of days for precipitation has reduced by 0.23 days per 10 years (with no statistical significance) in the sowing period ($1^{st}$ Oct. to $5^{th}$ Nov.) of winter crop. It was analyzed that double cropping system of rice and winter crops need to be reset in the way of delaying the sowing time of winter crops, because rising trend of temperature was clear while variability of precipitation was great and the trend was not clear in the sowing period of winter crops. We have also analyzed the meteorological features of the sowing period of winter crops in 2014, and found that mean air temperature in 2014 was higher than that in normal years (similar to recent temperature change feature) while precipitation in 2014 was much more frequent than that in normal years (unlike recent precipitation features). Such tendency in 2014 made the sowing of winter crops difficult because mechanical sowing could not be worked in flooded paddy fields. Heavy rain in October 2014 was also analyzed as a rare phenomenon.