• KIISE Transactions on Computing Practices
• /
• v.22 no.3
• /
• pp.145-150
• /
• 2016

Finding the exact location of faults in a program requires enormous time and effort. Several fault localization methods based on control flows of a program have been studied for decades. Unfortunately, these methods are not applicable to programs based on data-flow languages. A recently proposed mutation-based fault localization method is applicable to data-flow languages, as well as control-flow languages. However, there are no studies on the effectiveness of the mutation-based fault localization method for data-flow based programs. In this paper, we provided an experimental case study to evaluate the effectiveness of mutation-based fault localization on programs implemented in Function Block Diagram (FBD), a widely used data-flow based language in safety-critical systems implementation. We analyzed several real faults in the implementation of FBD programs of a nuclear reactor protection system, and evaluated the mutation-based fault localization effectiveness for each fault.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.12 no.6
• /
• pp.1121-1126
• /
• 2017

Various studies such as INS(: Inertial Navigation System) are conducting to estimate the position of UAV, because the GPS information of UAV is at risk like the GPS jamming. The position estimation using DoA and RTT are used to apply many radar systems, and that process can be applied in datalink of UAV. The general monopulse feed in UAV datalink is Multi-horn, because of the wide BW(: Band Width) and frequency range. And it needs wide SNR range of tracking because of the limited transmit power of airborne unit. The estimation error of position increase at low SNR, and the DoA is valid in only 3dB beam width but high SNR causes false of mainlobe detection because of large sidelobe. In this paper, We propose the method to achieve higher accuracy of DoA estimation on low SNR and review some idea that able to detect mainlobe.

• Journal of KIISE
• /
• v.43 no.2
• /
• pp.135-142
• /
• 2016

Visual analysis of spatiotemporal data has focused on a variety of techniques for analyzing and exploring the data. The goal of these techniques is to explore the spatiotemporal data using time information, discover patterns in the data, and analyze spatiotemporal data. The overall trend flow patterns help users analyze geo-referenced temporal events. However, it is difficult to extract and visualize overall trend flow patterns using data that has no trajectory information for movements. In order to visualize overall trend flow patterns, in this paper, we estimate continuous distributions of discrete events over time using KDE, and we extract vector fields from the continuous distributions using the gravity model. We then apply our technique on twitter data to validate techniques.

• Proceedings of the Korean Nuclear Society Conference
• /
• 1997.05a
• /
• pp.159-165
• /
• 1997

영광 3호기에서 발생한 부하탈락으로 인만 과도현상 때의 운전 데이터를 이용하여 전체의 운전 영역에서 잘 맞는 증기 발생기의 모델을 개발하였다. 모델링 기법으로는 유전자 알고리즘이 사용되었으며, 모델은 물리변수(물리적 의미를 갖는 변수)를 갖는 함수들로 구성하였다. 과도현상시의 데이터를 이용하여 증기발생기의 시변 특성을 직접 추정하기 위해 일부 물리변수를 급수온도에 대해 비선형으로 정의하였다. 잘 알려져 있는 실측 데이터를 사용하는 모델링 기법들은 선형 시불변 계에서만 적용이 가능하여 증기발생기와 같이 강한 시변 특성을 보이는 계의 모델링에 과도현상 때의 데이터를 적용할 수 없다. 물리변수를 직접 추정하면 물리적 원칙에 의해 값의 범위가 주어지며 운전 경험 또는 개략적인 데이터의 분석에 의해 예상되는 값의 범위를 비교적 작게 정할 수 있으므로 유전자 알고리즘의 적용에 유리하다. 얻어진 모델은 영광 3호기 운전원 훈련용 시뮬레이터와 발전소 설계 자료에 의해 검증되었다. 이 모델은 제어기의 설계 및 조정과 증기유량 측정 계열의 비선형 교정에도 사용될 수 있다.

• Proceedings of the Korean Information Science Society Conference
• /
• 2012.06b
• /
• pp.363-365
• /
• 2012

데이터의 규모 및 활용도, 그리고 사용자 접근성 측면에서 실세계 데이터에서 가장 중요한 이슈가 되는 것은 비디오 데이터이다. 장르나 등장인물, 배경 등이 매우 상이한 대량의 비디오 데이터들이 등장하고 있기 때문에, 통일된 사전지식을 이용한 비디오 데이터 분석이 매우 비현실적이 되어가고 있으며 사전지식을 활용하지 않는 비디오 분석기법의 중요성이 커지고 있다. 본 논문에서는 진화 파티를 필터링과 우점 이미지를 이용하여 비디오 데이터를 분절(Segmentation)하는 기법을 소개한다. 이미지 분절화 과정에서 해결해야 할 난점은 시점 변화 및 움직임 등에 의해 발생하는 사소한 변화가 컴퓨터 관점에서는 무시하기 어려운 큰 변화로 해석될 수 있다는 점이다. 동일장면에서의 시점 변화와 같은 사소한 변화로 인하여 동일 세그먼트를 추정하지 못하는 어려움을 해결하기 위하여 우리는 이미지 일부를 표현하는 파티클의 개체군을 생성하여 협력적인 방식으로 개별 이미지 세그먼트를 표현하는 방법을 개발하였다. 또한 동일 인물의 움직임과 같은 변화에 대응할 수 있도록 진화 파티를 필터링 방법을 컬러 히스토그램 방법과 결합하여 추론 성능을 한층 개선하였다. 실제 TV 드라마에 대하여 수행된 인간 평가자의 분절 평가 결과와 비교하여 제안 방법의 성능을 확인하였다.

• Journal of KIISE:Software and Applications
• /
• v.36 no.4
• /
• pp.273-282
• /
• 2009

Missing data is one of the common problems in building analysis or prediction models using software project data. Missing imputation methods are known to be more effective missing data handling method than deleting methods in small software project data. While K nearest neighbor imputation is a proper missing imputation method in the software project data, it cannot use non-missing information of incomplete project instances. In this paper, we propose an approach to missing data imputation for numerical software project data by combining K nearest neighbor and maximum likelihood estimation; we also extend the average absolute error measure by normalization for accurate evaluation. Our approach overcomes the limitation of K nearest neighbor imputation and outperforms on our real data sets.

• The Korean Journal of Applied Statistics
• /
• v.28 no.5
• /
• pp.1025-1034
• /
• 2015

Traditional Shewhart control charts assume that the observations are independent over time. Current progress in measurement and data collection technology lead to the presence of autocorrelated process data that may affect poor performance in statistical process control. One of the most popular charts for autocorrelated data is to model a correlative structure with an appropriate time series model and apply control chart to the sequence of residuals. Model parameters are estimated by an in-control Phase I reference sample since they are usually unknown in practice. This paper deals with the effects of parameter estimation on Phase II control limits to monitor autocorrelated data.

• Journal of the Korean Data and Information Science Society
• /
• v.5 no.2
• /
• pp.29-44
• /
• 1994

본 연구는 누적위험률함수에 대한 베이지안 추정량을 이용하여 생존함수의 추정량을 제안하고, counting process 이론과 martingale 이론을 이용하여 대표본하에서 제안된 추정량의 일양적 일치성과 점근적 정규성을 밝힌다. 또한 모의실험을 통하여 추정량들의 효율성을 편의와 평균제곱오차의 측면에서 비교하고자 한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.50 no.1
• /
• pp.67-74
• /
• 2022

To analyze the motion of aircraft through computing the dynamics equations, true airspeed is essential for obtaining aerodynamic loads. Although the airspeed is measured by on-board instruments such as pitot tubes, measurement data are difficult to obtain for commercial flights because they include sensitive data about the airline operations. One of the commonly available trajectory data, Automatic Dependent Surveillance-Broadcast data, provide aircraft's speed in the form of ground speed. The ground speed is a vector sum of the local wind velocity and the true airspeed. This paper present a method to estimate true airspeed by combining the trajectory, meteorological, and topology data available to the public. To integrate each data, we first matched the coordinate system and then unified the altitude reference to the mean sea level. We calculated the wind vector for all trajectory points by interpolating from the lower resolution grid of the meteorological data. Finally, we calculate the true airspeed from the ground speed and the wind vector. These processes were applied to several sample trajectories with corresponding meteorological data and the topology data, and the estimated true airspeeds are presented.

• Journal of Navigation and Port Research
• /
• v.37 no.5
• /
• pp.453-461
• /
• 2013

This paper describes evaluation procedures and experimental results for the estimation of Cumulative Distribution Functions (CDF) giving best-fit to the sample data in the Probability based risk Evaluation Techniques (PET) which is to assess the risks of a small-sized sea floater. The CDF in the PET is to provide the reference values of risk acceptance criteria which are to evaluate the risk level of the floater and, it can be estimated from sample data sets of motion response functions such as Roll, Pitch and Heave in the floater model. Using Maximum Likelihood Estimates and with the eight kinds of regulated distribution functions, the evaluation tests for the CDF having maximum likelihood to the sample data are carried out in this work. Throughout goodness-of-fit tests to the distribution functions, it is shown that the Beta distribution is best-fit to the Roll and Pitch sample data with smallest averaged probability errors $\bar{\delta}(0{\leq}\bar{\delta}{\leq}1.0)$ of 0.024 and 0.022, respectively and, Gamma distribution is best-fit to the Heave sample data with smallest $\bar{\delta}$ of 0.027. The proposed method in this paper can be expected to adopt in various application areas estimating best-fit distributions to the sample data.