• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.4
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• pp.118-123
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• 2004

This paper studies islanding detection of DG(distributed generation) considering fault location. Through the past studies, we found that islanding detection has been studied that DG disconnected when power islanding was detected by power state change and output change of DG. But, fault location was not considered. For example, fault in adjacent distribution line, fault on interconnection line fault, load shave by overload and normal operation were not considered. In this paper, We distinguish these considerations through power state change. Also, we proved islanding detection algorithm through PSCAD/EMTDC simulation.

• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1223-1232
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• 2017

This paper presents an approach to detect changes caused by urban development over a large area using KOMPSAT optical images. In order to minimize the radiometric dissimilarities between the images acquired at different times, we apply the grid-based rough radiometric correction as a preprocessing to detect changes in a large area. To improve the accuracy of the change detection results for urban development, we mask-out non-interest areas such as water and forest regions by the use of land-cover map provided by the Ministry of Environment. The Change Vector Analysis(CVA) technique is applied to detect changes caused by urban development. To confirm the effectiveness of the proposed approach, a total of three study sites from Sejong City is constructed by combining KOMPSAT-2 images acquired on May 2007 and May 2016 and a KOMPSAT-3 image acquired on March 2014. As a result of the change detection accuracy evaluation for the study site generated from the KOMPSAT-2 image acquired on May 2007 and the KOMPSAT-3 image acquired on March 2014, the overall accuracy of change detection was about 91.00%. It is demonstrated that the proposed method is able to effectively detect urban development changes in a large area.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.69-79
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• 1997

We investigate both of central and dispersion tendencies of the observed test statistics in control charts in order to judge whether a production process is abnormal or not. In order to do it, first, we study about detection of changes of the population mean as a central tendency The $\bar{x}$ and x control charts are used for detecting the change of the population mean $\mu$. We shows the probability detecting the change of population mean using the $\bar{x}$ and x control charts. Secondly, we study about detection of changes of the population standard deviation as a dispersion tendency in the s control chart. In our studies, for the given several parameters the detection probabilities of changes of central and dispersion tendencies are calculated, the necessary sample size values n are suggested for detecting the changes, and their informations are given as various tables.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.363-366
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• 2005

In this paper, for detecting human faces under variations of lighting condition and facial expression, distance ranking feature and detection algorithm based on the feature are proposed. Distance ranking is the intensity ranking of a distance transformed image. Based on statistically consistent edge information, distance ranking is robust to lighting condition change. The proposed detection algorithm is a matching algorithm based on FFT and a solution of discretization problem in the sliding window methods. In experiments, face detection results in the situation of varying lighting condition, complex background, facial expression change and partial occlusion of face are shown

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.74-85
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• 1997

In this paper we calculate the subgroup size necessary for detecting the change of percent defective with several detection probabilities for orginal population fraction nonconforming p, changed population fraction nonconforming $p^*$, and the ratio k=$p^*$/p in the usage of p control charts. From our calculation we can know the error level of normal a, pp.oximation in detection probability calculation and recommend the subgroup size with lower error levels of normal a, pp.oximation, and then we show the reasonable subgroup size necessary for p, $p^*$, k, and the detection probability of the change of fraction nonconforming in a process. The information that we here show in tables will be useful when p control chart users decide the subgroup size in the p control chart users decide the subgroup size in the p control chart.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.11
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• pp.731-738
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• 2015

This study proposed the method of the multi-crack detection using the sensitivity coefficient matrix which is calculated from the change of eigenvalues and eigenvectors before and after the crack. Each crack is modeled by a rotational springs. The method is applied to the cantilever beam with miulti-crack. The eigenvalues and eigenvectors are determined for different crack locations and depths. The prediction of multi-crack detection are in good agreement with the results of structural reanalysis.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.205-209
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• 1997

One objective of the u control chart is to detect changes of mean nonconformities per unit occurred owing to various causes. This paper shows the detection probability using the Poisson distribution for various parameters, that is, subsample size n, mean nonconformities per unit $u_o$, and $u_o's$ change ratio k. We find that (1) as $u_o$ increases the smaller n is required for the same detection probability and the same change ratio; (2) as k gets away from 1 the smaller n is required; (3) the bigger n is required for the bigger detection probability. Several tables are given from our findings and are hoped to be used as guidelines for u chart users.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.261-269
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• 2015

Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum like-lihood estimator and remains good choice specially in confidence interval statistical inference.

• 한국지형공간정보학회:학술대회논문집
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• 2002.11a
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• pp.117-122
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• 2002

Change detection is a useful technology that can be applied to various fields, taking temporal change information with the comparison and analysis among multi-temporal satellite images. Especially, change detection that utilizes high-resolution satellite imagery can be implemented to extract useful change information for many purposes, such as the environmental inspection, the circumstantial analysis of disaster damage, the inspection of illegal building, and the military use, which cannot be achieved by lower middle-resolution satellite imagery. However, because of the special characteristics that result from high-resolution satellite imagery, it cannot use a pixel-based method that is used for low-resolution satellite imagery. Therefore, it must be used a feature-based algorithm based on the geographical and morphological feature. This paper presents the system that builds the change map by digitizing the boundary of the changed object. In this system, we can make the change map using manual or semi-automatic digitizing through the user interface implemented with a floating window that enables to detect the sign of the change, such as the construction or dismantlement, more efficiently.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.1
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• pp.81-90
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• 2004

Because satellite images include geometry distortions according to photographing conditions and sensor property, and their spatial and radiational resolution and spectrum resolution are different, it is so difficult to make a precise results of analysis. For comparing more than two images, the precise geometric corrections should be preceded because it necessary to eliminate systematic errors due to basic sensor information difference and non-systematic errors due to topographical undulations. In this study, we did sensor modeling using satellite sensor information to make a basic map of change detection for artificial topography. We eliminated the systematic errors which can be occurred in photographing conditions using GCP and DEM data. The Kompsat EOC images relief could be reduced by precise rectification method. Classifying images which was used for change detections by city and forest zone, the accuracy of the matching results are increased by 10% and the positioning accuracies also increased. The result of change detection using basic map could be used for basic data fur GIS application and topographical renovation.