• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.543-552
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• 2010

Due to increase in urban tunnelling as urban population and traffic volume increase, problems related with site security and civil appeal also increase. This paper presents a comparative analysis between conventional 2-arch tunnel method and non-pilot 2 arch tunnel method, which were performed in the basic design of Wie-Rae region. According to the analysis results, non-pilot 2-arch tunnel method is more efficient in terms of stability, constructability, and economic aspect. It is authors' wish that design procedure and method presented in this paper could help the design and construction of non-pilot 2-arch tunnel that should be planned in the near future.

• Spatial Information Research
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• v.18 no.3
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• pp.73-83
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• 2010

This study presents a method to segment an image, employing the statistics observed at each pixel location across sequential frame images. In the acquisition and analysis of spatial information, utilization of digital image processing technique has very important implications. Various image segmentation techniques have been presented to distinguish the area of digital images. In this study, based on the analysis of the spectroscopic characteristics of sequential frame images that had been previously researched, an image segmentation method was proposed by using the randomness occurring among a sequence of frame images for a same scene. First of all, we computed the mean and standard deviation values at each pixel and found reliable pixels to determine seed points using their standard deviation value. For segmenting an image into individual regions, we conducted region growing based on a T-test between reference and candidate sample sets. A comparative analysis was conducted to assure the performance of the proposed method with reference to a previous method. From a set of experimental results, it is confirmed that the proposed method using a sequence of frame images segments a scene better than a method using a single frame image.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1376-1384
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• 2013

In this paper, we propose an automaticdetection method of foreign bodies through template matching in industrial CT volume data. Our method is composed of three main steps. First,Indown-sampling data, the product region is separated from background after noise reduction and initial foreign-body candidates are extracted using mean and standard deviation of the product region. Then foreign-body candidates are extracted using K-means clustering. Second, the foreign body with different intensity of product region is detected using template matching. At this time, the template matching is performed by evaluating SSD orjoint entropy according to the size of detected foreign-body candidates. Third, to improve thedetection rate of foreign body in original volume data, final foreign bodiesare detected using percolation method. For the performance evaluation of our method, industrial CT volume data and simulation data are used. Then visual inspection and accuracy assessment are performed and processing time is measured. For accuracy assessment, density-based detection method is used as comparative method and Dice's coefficient is measured.

• East Asian mathematical journal
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• v.33 no.4
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• pp.467-482
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• 2017

This paper studies the relationship between the college entrance examination scores and college mathematics achievements of the freshman, who are the students of college of technology and management in Yanbian University, by employing statistical analysis. First of all, we start from the correlation analysis of the majors and regions of students. Secondly, with gender and region as the classification, we divide the sample into two parts and test the mean significance, and we find that not only different gender but also different region have significant differences to college mathematics achievements. Thirdly, we use the college entrance examination scores as independent variable, and college mathematics achievement as the dependent variable to establish regression model. The model provides a realistic basis for the education department of our school, and provides reference value for the other major research.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.05a
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• pp.693-696
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• 2006

One of the most significant characteristics of JPEG 2000, the emerging still image standards, is the Region of Interest(ROI) coding. Until now, there have been many proposed ROI methods. However, all of these methods can not be applied completely in applications. In this paper, the ROI coding mechanisms in JPEG2000 is first outlined and the diversity of ROI coding methods is discussed in detail. Then a comparative selection about using a proper ROI method according to ROI applications' requirements is proposed. Finally the experimental results show that there are also several parameters that control the effectiveness of ROI coding, such as the codeblock size, ROI size, wavelet filter type, the number of wavelet decomposition levels, and ROI importance score.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.19-27
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• 2021

In this paper, we propose a method for detecting characters in images and detecting facial regions, which consists of two tasks. First, we separate two different characters to detect the face position of the characters in the frame. For fast detection, we use You Only Look Once (YOLO), which finds faces in the image in real time, to extract the location of the face and mark them as object detection boxes. Second, we present three image processing methods to detect accurate face area based on object detection boxes. Each method uses HSV values extracted from the region estimated by the detection figure to detect the face region of the characters, and changes the size and shape of the detection figure to compare the accuracy of each method. Each face detection method is compared and analyzed with comparative data and image processing data for reliability verification. As a result, we achieved the highest accuracy of 87% when using the split rectangular method among circular, rectangular, and split rectangular methods.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.3
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• pp.156-163
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• 2009

In this study, comparative analysis on the back-layer phenomena in the tunnel-fire driven flow is performed using numerical simulation with LES and RANS. FDS(Fire Dynamics Simulator) code is employed to calculate the fire-driven turbulent flow for LES and Smartfire code is used for RANS. Hwang and Wargo's data of scaling tunnel fire experiment are employed to compare with the present numerical simulation. The modeled tunnel is 5.4m(L) ${\times}$ 0.4m(W) ${\times}$ 0.3m(H). Heat Release Rate (HRR) of fire is 3.3kW and ventilation-velocity is 0.33m/s in the main stream. The various grid-distributions are systematically tested with FDS code to analyze the effects of grid size. The LES method with FDS provides an improved back-layer flow behavior in comparison with the RANS (${\kappa}-{\epsilon}$) method by Smartfire. The FDS solvers, however, overpredict the velocity in the center region of flow which is caused by the defects in the tunnel-entrance turbulence strength and in the near-wall turbulent flow in FDS code.

• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.460-472
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• 2015

Most of previous visual attention system finds attention regions based on saliency map which is combined by multiple extracted features. The differences of these systems are in the methods of feature extraction and combination. This paper presents a new system which has an improvement in feature extraction method of color and motion, and in weight decision method of spatial and temporal features. Our system dynamically extracts one color which has the strongest response among two opponent colors, and detects the moving objects not moving pixels. As a combination method of spatial and temporal feature, the proposed system sets the weight dynamically by each features' relative activities. Comparative results show that our suggested feature extraction and integration method improved the detection rate of attention region.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.49-59
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• 2023

Recently, attention to the pandemic situation represented by COVID-19 emerged problems caused by unexpected shortage of medical personnel. In this paper, we present a method for diagnosing the presence or absence of lesional sign on PA chest X-ray images as computer vision solution to support diagnosis tasks. Method for visual anomaly detection based on feature modeling can be also applied to X-ray images. With extracting feature vectors from PA chest X-ray images and divide to patch unit, region-specific abnormality can be detected. As preliminary experiment, we created simulation data set containing multiple objects and present results of the comparative experiments in this paper. We present method to improve both efficiency and performance of the process through hard masking of patch features to aligned images. By summing up regional specificity and global anomaly detection results, it shows improved performance by 0.069 AUROC compared to previous studies. By aggregating region-specific and global anomaly detection results, it shows improved performance by 0.069 AUROC compared to our last study.

• Journal of the Korean Society of Safety
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• v.35 no.3
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• pp.49-57
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• 2020

In comparison with the existing static reliability analysis methods, the dynamic reliability analysis(DyRA) method is more suitable for estimating the failure probability of a structure subjected to earthquake excitations because it can take into account the frequency characteristics and damping capacity of the structure. However, the DyRA is known to have an issue of numerical stability due to the uncertainty in random sampling of the earthquake excitations. In order to solve this numerical stability issue in the DyRA approach, this study proposed two earthquake-scale factors. The first factor is defined as the ratio of the first earthquake excitation over the maximum value of the remaining excitations, and the second factor is defined as the condition number of the matrix consisting of the earthquake excitations. Then, we have performed parametric studies of two factors on numerical stability of the DyRA method. In illustrative example, it was clearly confirmed that the two factors can be used to verify the numerical stability of the proposed DyRA method. However, there exists a difference between the two factors. The first factor showed some overlapping region between the stable results and the unstable results so that it requires some additional reliability analysis to guarantee the stability of the DyRA method. On the contrary, the second factor clearly distinguished the stable and unstable results of the DyRA method without any overlapping region. Therefore, the second factor can be said to be better than the first factor as the criterion to determine whether or not the proposed DyRA method guarantees its numerical stability. In addition, the accuracy of the numerical analysis results of the proposed DyRA has been verified in comparison with those of the existing first-order reliability method(FORM), Monte Carlo simulation(MCS) method and subset simulation method(SSM). The comparative results confirmed that the proposed DyRA method can provide accurate and reliable estimation of the structural failure probability while maintaining the superior numerical efficiency over the existing methods.