• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.79-82
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• 2005

Recently the necessity of road data is still being increased in industrial society, so there are many repairing and new constructions of roads at many areas. According to the development of government, city and region, the update and acquisition of road data for GIS (Geographical Information System) is very necessary. In this study, the fusion method with range data(3D Ground Coordinate System Data) and Intensity data in stand alone LiDAR data is used for road extraction and then digital image processing method is applicable. Up to date Intensity data of LiDAR is being studied. This study shows the possibility method for road extraction using Intensity data. Intensity and Range data are acquired at the same time. Therefore LiDAR does not have problems of multi-sensor data fusion method. Also the advantage of intensity data is already geocoded, same scale of real world and can make ortho-photo. Lastly, analysis of quantitative and quality is showed with extracted road image which compare with I: 1,000 digital map.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.646-649
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• 2004

LiDAR(Light Detection and Ranging) system can record intensity data as well as range data. Recently, LiDAR intensity data is widely used for landcover classification, ancillary data of feature extraction, vegetation species identification, and so on. Since the intensity return value is associated with several factors, same features is not consistent for same flight or multiple flights. This paper investigated correlation between intensity and range data. Once the effects of range was determined, the single flight line normalization and the multiple flight line normalization was performed by an empirical function that was derived from relationship between range and return intensity

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1998.04a
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• pp.23-30
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• 1998

An estimation of seismic risk parameters by seismic zones of the Korea Peninsula in order to calculate the seismic hazard values using these was erformed. Seven seismic source zones were selected in consideration of seismicity and geology of Korean Peninsula. The seismicity parameters that should be estimated are maximum intensity, activity rate and b value in the Gutenberg - Richter relation. For computation of these parameters, least square method or maximum likelihood method is applied to the earthquake data in two ways; the one for the data without maximum intensity and the other with maximum intensity. Earthquake data since Choseon Dynasty is regarded as complete and estimation of parameters was made for these data using above two ways. And recently, a new method is published that estimate the seismicity parameters using mixed data containing large historical events and recent complete observations. Therefore, this method is applied to the whole earthquake data of the Korean Peninsula. It turns out that the b value computed considering maximum intensity is slightly lower than that computed considering without maximum intensity, and it becomes still lower when the incomplete data prior to Choseon Dynasty is used. In the case of the activity rates, the values obtained without maximum intensity and that with maximum intensity are similar, though they are lower when the incomplete data is used. The values of maximum intensities are usually lower when considering incomplete data. In the seismic source zone including the Yangsan Fault zone, however, the values are higher when considering the incomplete data.

• Journal of the Optical Society of Korea
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• v.16 no.2
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• pp.91-94
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• 2012

Arrayed waveguide grating (AWG) phase errors are normally assessed from the Fourier transform of the interference intensity data in the frequency domain method. However it is possible to identify the phases directly from the intensity data if one adopts a trial-and-error method. Since the functional form of the intensity profile is known, the intensities can be calculated theoretically by assuming arbitrary phase errors. Then we decide the phases that give the best fit to the experimental data. We verified this method by a simulation. We calculated the intensities for an artificial AWG which is given arbitrary phases and amplitudes. Then we extracted the phases and amplitudes from the intensity data by using our trial-and-error method. The extracted values are in good agreement with the originally given values. This approach yields better results than the analysis using Fourier transforms.

• Journal of the Korea Society of Computer and Information
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• v.19 no.10
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• pp.35-42
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• 2014

It is possible to improve the obstacle avoidance capability by training and recognizing the obstacles which is in certain indoor environment. We propose the technique that use underlying intensity value along with intensity map from RGB-D image which is derived from stereo vision Kinect sensor and recognize an obstacle within constant distance. We test and experiment the accuracy and execution time of the pattern recognition algorithms like PCA, ICA, LDA, SVM to show the recognition possibility of it. From the comparison experiment between RGB-D data and intensity data, RGB-D data got 4.2% better accuracy rate than intensity data but intensity data got 29% and 31% faster than RGB-D in terms of training time and intensity data got 70% and 33% faster than RGB-D in terms of testing time for LDA and SVM, respectively. So, LDA, SVM have good accuracy and better training/testing time to use for obstacle avoidance based on intensity dataset of mobile robot.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.555-560
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• 2010

One-dimensional approach to two-dimensional warranty data involves modeling us- age as a function of time. Iskandar (1993) suggests a simple linear model for usage. However, simple linear form of intensity function is of limited value to model the situa-tion where the intensity varies over time. In this study Weibull intensity is considered where the scale parameter is expressed in terms of different models. We will nd out how each parameter in the model a ects the warranty cost and which model gives a bigger number of failures within the two-dimensional warranty region.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.509-518
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• 2002

This paper is concerned with semiparametric Bayesian analysis of the proportional intensity regression model of the Poisson process for multiple event time data. A nonparametric prior distribution is put on the baseline cumulative intensity function and a usual parametric prior distribution is given to the regression parameter. Also we allow heterogeneity among the intensity processes in different subjects by using unobserved random frailty components. Gibbs sampling approach with the Metropolis-Hastings algorithm is used to explore the posterior distributions. Finally, the results are applied to a real data set.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.3
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• pp.179-188
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• 2015

We propose obstacle classification method based on 2D LIDAR(Light Detecting and Ranging) database. The existing obstacle classification method based on 2D LIDAR, has an advantage in terms of accuracy and shorter calculation time. However, it was difficult to classifier the type of obstacle and therefore accurate path planning was not possible. In order to overcome this problem, a method of classifying obstacle type based on width data of obstacle was proposed. However, width data was not sufficient to improve accuracy. In this paper, database was established by width, intensity, variance of range, variance of intensity data. The first classification was processed by the width data, and the second classification was processed by the intensity data, and the third classification was processed by the variance of range, intensity data. The classification was processed by comparing to database, and the result of obstacle classification was determined by finding the one with highest similarity values. An experiment using an actual autonomous vehicle under real environment shows that calculation time declined in comparison to 3D LIDAR and it was possible to classify obstacle using single 2D LIDAR.

• Transactions of the Society of Information Storage Systems
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• v.6 no.1
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• pp.1-5
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• 2010

Holographic data storage system(HDSS) has many noise sources - crosstalk, scattering and inter pixel interference, etc. Generally the intensity of a light generated from the laser source has Gaussian distribution and this ununiformity of light also can make the data page to have a low SNR. A beam apodizer is used to make the laser as a flat-top beam but the intensity distribution is not strictly uniform. The intensity of light can be controlled using image mask. In this paper the intensity distribution of light used for HDSS is controlled by a digital image mask. The digital image mask is changed arbitrarily in real-time with suggested algorithm for the HDSS.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.620-624
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• 2007

Recently, Gonzalez-Audicana et al. proposed the substitute wavelet intensity (SWI) method which provided a solution based on the intensity-hue-saturation (IHS) method for the fusing of panchromatic (PAN) and multispectral (MS) images. Although the spectral quality of the fused MS images is enhanced, this method is not efficient enough to quickly merge massive volumes of data from satellite. To overcome this problem, we introduce a new SWI method based on a fast IHS transform to implement efficiently as an alternative procedure. In addition, we show that the method is well applicable for fusing IKONOS PAN with MS images.