• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1085-1086
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• 2008

An error prediction system (EPS) for a power distribution system can predict an out-of-order state based on gathered data from the system. This paper describes a software structure of an EPS that is equipped with various sensors. The software analyzes the gathered data from sensors and predict error symptoms using statistical methods. The EPS system is installed on a real power distribution system.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.5
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• pp.562-572
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• 1992

In this paper, we propose software algorithms which provide acceleration/deceleration characteristics essential to high dynamic performance at the transient states where industrial robots or CNC machine tools start and stop. Software acceleration/deceleration methods are derived from the mathematical analyses of typical hardware systems controlling acceleration/deceleration. These methods make servo motors, which drive axes of motion, start and stop smoothly without vibration in the repeated tools. The path error, which is one of the most significant factors in the performance evaluation of industrial robots or CNC machine tools, is analyzed for linear, exponential, and parabolic acceleration/deceleration algorithms in case of circular interpolation. The analyses show that path error consists of the distance between the required path and generated one through acceleration/deceleration, and that between the generated one through acceleration/deceleration algorithm and the actual one of the end effector of the industrial robot or tool of the CNC equipment.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.771-772
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• 2008

위성을 개발하고 운영하는 과정에서 다양한 소프트웨어 문제가 발생할 수 있다. 특히 각 모듈을 제작하고 연결하여 테스트를 진행할 경우 각 모듈 자체의 이상이나 통합 환경에서 각 모듈간 인터페이스에서 많은 문제가 발생하게 된다. 이러한 문제를 빨리 파악하고 해결하기 위해 위성에서 어떤 문제가 발생하였는지 각각의 오류에 대한 정의를 하고 이를 기록하는 작업이 필요하다. 본 논문에서는 위에 언급한 작업의 하나로 SET(Software Error Table) 와 SEW(Software Error Word)를 이용하여 위성에서 발생하는 소프트웨어 오류 처리 방안에 대해 소개한다.

• Journal of Advanced Navigation Technology
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• v.13 no.1
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• pp.74-78
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• 2009

This paper explains the design and implementation of the FDA(Fault Detection Agent) based on IP-USN. FDA is a system that is suitable for detecting software error for multimedia distance education running on home network environment based on IP-USN. This system consists of an ED, and ES. ED is an agent that detects an error by hooking techniques for multimedia distance education based on IP-USN environment. ES is an agent that is an error sharing system for multimedia distance education based on IP-USN environment.

• Convergence Security Journal
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• v.6 no.3
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• pp.117-126
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• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.384-390
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• 2018

This paper introduces a MATLAB graphical user interface (GUI) based software for analysis of korea augmentation satellite system (KASS) availability performance. This software uses minimum variance (MV) estimator and Kriging algorithm to generate integrity information such as user differential range error (UDRE) and grid ionospheric vertical error (GIVE). The information is offered to ground and aviation users in Korean region. The software also gives accuracy data, protection level data and availability map about each user position by using the integrity information. In particular the software calculates the protection level along a path of aircraft. We verified the result of protection level of aviation user by comparing them with the results of SBASimulator#2, which is a simulation tool of european geostationary navigation overlay service (EGNOS). As a result, the protection level error between the result of our software and the SBASimulator#2 was about 2% which means that the result of our software is accurate.

• Journal of the Korean Society for Railway
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• v.11 no.4
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• pp.404-409
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• 2008

This paper consists largely of two parts: the first part introduces the revised railway human reliability analysis (R-HRA) method which is to be used under the railway risk assessment framework, and the second part presents the features of a computer software which was developed for aiding the R-HRA process. The revised R-HRA method supplements the original R-HRA method by providing a specific task analysis guideline and a classification of performance shaping factors (PSFs) to support a consistent analysis between analysts. The R-HRA software aids the analysts in gathering information for HRA, qualitative error prediction including identification of external error modes and internal error modes, quantification of human error probability, and reporting the overall analysis results. The revised R-HRA method and software are expected to support the analysts in an effective and efficient way in analysing human error potential in railway event or accident scenarios.

• Journal of Positioning, Navigation, and Timing
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• v.3 no.4
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• pp.163-170
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• 2014

A pseudolite is used as a GPS backup system, and is also used for the purpose of indoor navigation and correction information transmission. It is installed on the ground, and transmits signals that are similar to those of a GPS satellite. In addition, in recent years, studies on the improvement of positioning accuracy using the pseudorange measurement of a pseudolite have been performed. As for the effect of the time synchronization error between a pseudolite and a GPS satellite, a time synchronization error of 1 us generally induces a pseudorange error of 300 m; and to achieve meter-level positioning, ns-level time synchronization between a pseudolite and a GPS satellite is required. Therefore, for the operation of a pseudolite, a time synchronization algorithm between a GPS satellite and a pseudolite is essential. In this study, for the time synchronization of a pseudolite, "a pseudolite time synchronization method using the time source of UTC (KRIS)" and "a time synchronization method using a GPS timing receiver" were introduced; and the time synchronization performance depending on the pseudolite time source and reference time source was evaluated by designing a software-based pseudolite time synchronization performance evaluation simulation platform.

• Journal of Information Technology Services
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• v.11 no.1
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• pp.211-221
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• 2012

Many metric-based classification models have been proposed to predict fault-proneness of software module. This paper presents two prediction models using Bayesian classifier which is one of the most popular modern classification algorithms. Bayesian model based on Bayesian probability theory can be a promising technique for software quality prediction. This is due to the ability to represent uncertainty using probabilities and the ability to partly incorporate expert's knowledge into training data. The two models, Na$\ddot{i}$veBayes(NB) and Bayesian Belief Network(BBN), are constructed and dimensionality reduction of training data and test data are performed before model evaluation. Prediction accuracy of the model is evaluated using two prediction error measures, Type I error and Type II error, and compared with well-known prediction models, backpropagation neural network model and support vector machine model. The results show that the prediction performance of BBN model is slightly better than that of NB. For the data set with ambiguity, although the BBN model's prediction accuracy is not as good as the compared models, it achieves better performance than the compared models for the data set without ambiguity.

• Journal of Sasang Constitutional Medicine
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• v.19 no.3
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• pp.51-61
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• 2007

1. Objectives The Face is an important standard for the classification of Sasang Constitutions. We are developing 3D Automatic Face Recognition Apparatus(3D-AFRA) to analyse the facial characteristics. This apparatus show us 3D image and data of man's face and measure facial figure data. So We should examine the Measurement of Facial Figure data error of 3D Automatic Face Recognition Apparatus(3D-AFRA) in Software Error Analysis. 2. Methods We scanned face status by using 3D Automatic Face Recognition Apparatus(3D-AFRA). And we measured lengths Between Facial Definition Parameters of facial figure data by Facial Measurement program. 2.1 Repeatability test We measured lengths Between Facial Definition Parameters of facial figure data restored by 3D-AFRA by Facial Measurement program 10 times. Then we compared 10 results each other for repeatability test. 2.2 Measurement error test We measured lengths Between Facial Definition Parameters of facial figure data by two different measurement program that are Facial Measurement program and Rapidform2006. At measuring lengths Between Facial Definition Parameters, we uses two measurement way. The one is straight line measurement, the other is curved line measurement. Then we compared results measured by Facial Measurement program with results measured by Rapidform2006. 3. Results and Conclusions In repeatability test, standard deviation of results is 0.084-0.450mm. And in straight line measurement error test, the average error 0.0582mm, and the maximum error was 0.28mm. In curved line measurement error test, the average error 0.413mm, and the maximum error was 1.53mm. In conclusion, we assessed that the accuracy and repeatability of Facial Measurement program is considerably good. From now on we complement accuracy of 3D-AFRA in Hardware and Software.