• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.1-11
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• 2006

In this paper, we propose the novel video retrieval algorithm using non-parametric based motion classification in the shot-based video indexing structure. The proposed system firstly gets the key frame and motion information from each shot segmented by scene change detection method, and then extracts visual features and non-parametric based motion information from them. Finally, we construct real-time retrieval system supporting similarity comparison of these spatio-temporal features. After the normalized motion vector fields is created from MPEG compressed stream, the extraction of non-parametric based motion feature is effectively achieved by discretizing each normalized motion vectors into various angle bins, and considering a mean, a variance, and a direction of these bins. We use the edge-based spatial descriptor to extract the visual feature in key frames. Experimental evidence shows that our algorithm outperforms other video retrieval methods for image indexing and retrieval. To index the feature vectors, we use R*-tree structures.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.2
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• pp.73-86
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• 2000

Using monthly AVHRR-NDVI composite images, global vector data and statistical information, land cover change patterns in Asia during the major growing season (June, July and August) were analyzed for each country. Specifically, explanations on NDVI changes were developed at a regional scale emphasizing human impacts on ground vegetation. The annual mean change in each country showed NDVI-gain trends in high latitude areas and some parts of eastern China and northern/western India. On the contrary, NDVI-loss trends were distinctive in Japan, Korea, some parts of southeastern China, Vietnam, Laos, Cambodia, Thailand, Myanmar and some parts in southwestern/eastern India. These patterns largely coincided with socio-economic information reflected by human behavior. The NDVI change trends showed significant correlation with forest area changes. Also, a multiple regression model showed that the NDVI change patterns were significantly dependent on the changes in forest area and total population.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.6
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• pp.893-901
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• 2002

Effect of boundary layer thickness on the flow characteristics around a rectangular prism has been investigated by using a PIV(Particle Image Velocimetry) technique. Three different boundary layers(thick, medium and thin)were generated in the Atmospheric Boundary Layer Wind Tunnel at Pusan National University. The thick boundary layer having 670 mm thickness was generated by using spires and roughness elements. The medium thickness of boundary layer($\delta$=270 mm) was the natural turbulent boundary layer at the test section floor with fairly long developing length(18 m). The thin boundary layer($\delta$=36.5 mm) was generated on the smooth panel elevated 70cm from the wind tunnel floor. The Reynolds number based on the free stream velocity(3 ㎧) and the height of the model(40 mm) was 7.9$\times$10$^3$. The mean velocity vector fields and turbulent kinetic energy distributions were measured and compared. The effect of boundary layer thickness was clearly observed not only in the length of separation bubble but also in the location of reattachment point. The thinner the boundary layer thickness, the higher the turbulent kinetic energy Peak around the model roofbecame. It is strongly recommended that the height ratio between the model and the approaching boundary layer thickness should be encountered as a major parameter.

• Biomedical Science Letters
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• v.14 no.1
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• pp.47-53
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• 2008

Hox genes are known to be transcription factors controlling vertebrate pattern formation along the anteroposterior body axis by regulating many target gene expressions during vertebrate embryogenesis. In order to isolate in vivo Hox responsive target genes, ChIP-cloning technique has been applied using Hoxc8 antibody. Here murine embryo of day 11.5 post coitum (E11.5) highly expressing Hoxc8 gene was used after removing head and tail portions where Hoxc8 is rarely expressing. After fixation with formaldehyde, the chromatin DNAs harboring bound proteins were isolated. After sonication, about 0.5- to 1 Kb chromatin DNAs were immunoprecipitated with anti Hoxc8 antibody. After removing the bound proteins with proteinase K, DNAs were isolated, cloned into the pBluescsript II SK vector, and then sequenced. Total 33 random clones sequenced were anlalyzed to be located at 12 different genomic regions. Among these, 8 turned out to be introns and 4 were intergenic regions localized in random chromosomes. The base composition of total cloned genomic sequences (6608 bp) were AT-rich, i.e., 40% GC. When the Hoxc8 core binding sites, such as TAAT, ATTA, TTAT, and ATAA were analyzed total number of 55, 45, 54, and 55 were found, respectively, which are than twice as many as expected number of 26. Although this in silico analysis does not mean that the ChIP-cloned sequence is real Hoxc8 regulatory element in vivo, these results strongly imply that the DNA fragments cloned through chromatin immunoprecipitation could be very much likely the putative Hoxc8 downstream target genes.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.739-747
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• 2018

Integration analysis of multi-sensor satellite images is becoming increasingly important. The first step in integration analysis is image registration between multi-sensor. SIFT (Scale Invariant Feature Transform) is a representative image registration method. However, optical image and SAR (Synthetic Aperture Radar) images are different from sensor attitude and radiation characteristics during acquisition, making it difficult to apply the conventional method, such as SIFT, because the radiometric characteristics between images are nonlinear. To overcome this limitation, we proposed a modified method that combines the SAR-SIFT method and shape descriptor vector DLSS(Dense Local Self-Similarity). We conducted an experiment using two pairs of Cosmo-SkyMed and KOMPSAT-2 images collected over Daejeon, Korea, an area with a high density of buildings. The proposed method extracted the correct matching points when compared to conventional methods, such as SIFT and SAR-SIFT. The method also gave quantitatively reasonable results for RMSE of 1.66m and 2.45m over the two pairs of images.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.4112-4112
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• 2001

The feasibility of NIR spectroscopy as a quick and nondestructive method for quality control of uniformity of coating thickness of pharmaceutical tablets was investigated. Near infrared spectra of a set of pharmaceutical tablets with varying coating thickness were measured with a diffuse reflectance fiber optic probe connected to a Broker IFS 28/N FT-NIR spectrometer. The challenging issues encountered in this study included: 1. The similarity of the formulation of the core and coating materials, 2. The lack of sufficient calibration samples and 3. The non-linear relationship between the NIR spectral intensity and coating: thickness. A peak at 7184 $cm^{-1}$ was identified that differed for the coating material and the core material when M spectra were collected at 2 $cm^{-1}$ resolution (0.4 nm at 7184 $cm^{-1}$). The study showed that the coating thickness can be analyzed by polynomial fitting of the peak area of the selected peak, while least squares calibration of the same data failed due to the lack of availability of sufficient calibration samples. Samples of coal powder and solid pieces of coal were analyzed by FT-NIR diffuse reflectance spectroscopy with the goal of predicting their ash content, percentage of volatile components, and energy content. The measurements were performed on a Broker Vector 22N spectrometer with a fiber optic probe. A partial least squares model was constructed for each of the parameters of interest for solid and powdered sample forms separately. Calibration models varied in size from 4 to 10 PLS ranks. Correlation coefficients for these models ranged from 86.6 to 95.0%, with root-mean-square errors of cross validation comparable to the corresponding reference measurement methods. The use of FT-NIR diffuse reflectance measurement techniques was found to be a significant improvement over existing measurement methodologies in terms of speed and ease of use, while maintaining the desired accuracy for all parameters and sample forms.(Figure Omitted).

• Journal of Korea Multimedia Society
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• v.14 no.2
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• pp.182-193
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• 2011

The aim of this paper is to present the methodology for hand tracking and hand gesture recognition. The detected hand and gesture can be used to implement the non-contact mouse. We had developed a MP3 player using this technology controlling the computer instead of mouse. In this algorithm, we first do a pre-processing to every frame which including lighting compensation and background filtration to reducing the adverse impact on correctness of hand tracking and hand gesture recognition. Secondly, YCbCr skin-color likelihood algorithm is used to detecting the hand area. Then, we used Continuously Adaptive Mean Shift (CAMSHIFT) algorithm to tracking hand. As the formula-based region of interest is square, the hand is closer to rectangular. We have improved the formula of the search window to get a much suitable search window for hand. And then, Support Vector Machines (SVM) algorithm is used for hand gesture recognition. For training the system, we collected 1500 hand gesture pictures of 5 hand gestures. Finally we have performed extensive experiment on a Windows XP system to evaluate the efficiency of the proposed scheme. The hand tracking correct rate is 96% and the hand gestures average correct rate is 95%.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.11
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• pp.24-29
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• 2010

Selection-type relaying protocol, which is one of cooperative relaying protocols, provides low decoding complexity and improved system performance due to selection diversity. In this paper, we deal with linear precoding technique that minimize the error probability of cooperative MIMO system. Under the assumption that full channel state information is available at whole nodes, linear source and relay precoders, which minimize mean squared error of the estimated symbol vector, are proposed. Moreover, unlikely to the conventional selection-type relaying protocol using a fixed threshold signal-to-noise-ratio, new transmission link selection algorithm selects direct link or relay link as a transmission link, is introduced. Simulation results show that the proposed linear precoder with the transmission link selection algorithm outperforms the conventional precoders for two-hop relaying protocols or selection-type relaying protocols.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.117-140
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• 2013

Hindi is the most widely spoken language in India, with more than 300 million speakers. As there is no separation between the characters of texts written in Hindi as there is in English, the Optical Character Recognition (OCR) systems developed for the Hindi language carry a very poor recognition rate. In this paper we propose an OCR for printed Hindi text in Devanagari script, using Artificial Neural Network (ANN), which improves its efficiency. One of the major reasons for the poor recognition rate is error in character segmentation. The presence of touching characters in the scanned documents further complicates the segmentation process, creating a major problem when designing an effective character segmentation technique. Preprocessing, character segmentation, feature extraction, and finally, classification and recognition are the major steps which are followed by a general OCR. The preprocessing tasks considered in the paper are conversion of gray scaled images to binary images, image rectification, and segmentation of the document's textual contents into paragraphs, lines, words, and then at the level of basic symbols. The basic symbols, obtained as the fundamental unit from the segmentation process, are recognized by the neural classifier. In this work, three feature extraction techniques-: histogram of projection based on mean distance, histogram of projection based on pixel value, and vertical zero crossing, have been used to improve the rate of recognition. These feature extraction techniques are powerful enough to extract features of even distorted characters/symbols. For development of the neural classifier, a back-propagation neural network with two hidden layers is used. The classifier is trained and tested for printed Hindi texts. A performance of approximately 90% correct recognition rate is achieved.

• Journal of Preventive Medicine and Public Health
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• v.31 no.4 s.63
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• pp.875-884
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• 1998

Missing observations are common in medical research and health survey research. Several statistical methods to handle the missing data problem have been proposed. The EM algorithm (Expectation-Maximization algorithm) is one of the ways of efficiently handling the missing data problem based on sufficient statistics. In this paper, we developed statistical models and methods for survey data with multivariate missing observations. Especially, we adopted the EM algorithm to handle the multivariate missing observations. We assume that the multivariate observations follow a multivariate normal distribution, where the mean vector and the covariance matrix are primarily of interest. We applied the proposed statistical method to analyze data from a health survey. The data set we used came from a physician survey on Resource-Based Relative Value Scale(RBRVS). In addition to the EM algorithm, we applied the complete case analysis, which uses only completely observed cases, and the available case analysis, which utilizes all available information. The residual and normal probability plots were evaluated to access the assumption of normality. We found that the residual sum of squares from the EM algorithm was smaller than those of the complete-case and the available-case analyses.