• Earthquakes and Structures
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• v.18 no.6
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• pp.691-707
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• 2020

One of the most important issues in structural systems is evaluation of the margin of safety in low and mid-rise buildings against the progressive collapse mechanism due to the earthquake loads. In this paper, modeling of collapse propagation in structural elements of RC frame buildings is evaluated by tracing down the collapse points in beam and column structural elements, one after another, under earthquake loads and the influence of column removal is investigated on how the collapse expansion in beam and column structural members. For this reason, progressive collapse phenomenon is studied in 3-story and 5-story intermediate moment resisting frame buildings due to the corner and edge column removal in presence of the earthquake loads. In this way, distribution and propagation of the collapse in progressive collapse mechanism is studied, from the first element of the structure to the collapse of a large part of the building with investigating and comparing the results of nonlinear time history analyses (NLTHA) in presence of two-component accelograms proposed by FEMA_P695. Evaluation of the results, including the statistical survey of the number and sequence of the collapsed points in process of the collapse distribution in structural system, show that the progressive collapse distribution are special and similar in low-rise and mid-rise RC buildings due to the simultaneous effects of the column removal and the earthquake loads and various patterns of the progressive collapse distribution are proposed and presented to predict the collapse propagation in structural elements of similar buildings. So, the results of collapse distribution patterns and comparing the values of collapse can be utilized to provide practical methods in codes and guidelines to enhance the structural resistance against the progressive collapse mechanism and eventually, the value of damage can be controlled and minimized in similar buildings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.190-207
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• 2015

In the combustion engineering, to decrease pollution and increase production efficiency, and to optimally keep solid burning material amount constant in a burner online, it needs a smart method to detect the amount variation of the burning materials in a high temperature environment. This paper presents an online machine vision system for automatically measuring and detecting the burning material amount inside a burner or a boiler. In the camera-protecting box of the system, a sub-system for cooling is constructed by using the cooling water circulation techqique. In addition, the key and intelligent step in the system is to detect the pile profile of the variable burning material, and the algorithm for the pile profile tracing was studied based on the combination of the gey level (color) discontinuity and similarity based image segmentation methods, the discontinuity based sub-algorithm is made on the quaternion convolution, and the similarity based sub-algorithm is designed according to the region growing with multi-scale clustering. The results of the two sub-algoritms are fused to delineate the final pile profile, and the algorithm has been tested and applied in different industrial burners and boilers. The experiements show that the proposed algorithm works satisfactorily.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5073-5086
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• 2015

The rock fracture detection by image analysis is significant for fracture measurement and assessment engineering. The paper proposes a novel image segmentation algorithm for the centerline tracing of a rock fracture based on Hessian Matrix at Multi-scales and Steger algorithm. A traditional fracture detection method, which does edge detection first, then makes image binarization, and finally performs noise removal and fracture gap linking, is difficult for images of rough rock surfaces. To overcome the problem, the new algorithm extracts the centerlines directly from a gray level image. It includes three steps: (1) Hessian Matrix and Frangi filter are adopted to enhance the curvilinear structures, then after image binarization, the spurious-fractures and noise are removed by synthesizing the area, circularity and rectangularity; (2) On the binary image, Steger algorithm is used to detect fracture centerline points, then the centerline points or segments are linked according to the gap distance and the angle differences; and (3) Based on the above centerline detection roughly, the centerline points are searched in the original image in a local window along the direction perpendicular to the normal of the centerline, then these points are linked. A number of rock fracture images have been tested, and the testing results show that compared to other traditional algorithms, the proposed algorithm can extract rock fracture centerlines accurately.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.874-877
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• 2012

This paper proposes the new method based on contour following method with directional angle to segment the cell into the nuclei. The object image was the Thyroid Gland cell image that was diagnosed as normal and abnormal(two types of abnormal : follicular neoplastic cell, and papillary neoplastic cell), respectively. The nuclei were successfully diagnosed as normal and abnormal. this paper, improved method of digital image analysis required in basic medical science for diagnosis of cells was proposed. The object image was the Thyroid Gland cell image with difference of chromatin patterns. To segment the cell nucleus from background, the region segmentation algorithm by edge tracing was proposed. And feature parameter was obtained from discrete Fourier transformation of image. After construct a feature sample group of each cells, experiment of discrimination was executed with any verification cells. As a result of experiment using features proposed in this paper, get a better segmentation rate(70-90%) than previously reported papers, and this method give shape to get objectivity and fixed quantity in diagnosis of cells. The methods described in this paper be used immediately for discrimination of neoplastic cells.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.15-19
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• 2004

Ant Colony System(ACS) is a meta heuristic approach based on biology in order to solve combinatorial optimization problem. It is based on the tracing action of real ants which accumulate pheromone on the passed path and uses as communication medium. In order to search the optimal path, ACS requires to explore various edges. In existing ACS, the local updating rule assigns the same pheromone to visited edge. In this paper, our local updating rule gives the pheromone according to the number of visiting times and the distance between visited cities. Our approach can have less local optima than existing ACS and find better solution by taking advantage of more informations during searching.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.507-516
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• 2008

Cardiac disease is the leading cause of death in the world. Quantification of cardiac function is performed by manually calculating blood volume and ejection fraction in routine clinical practice, but it requires high computational costs. In this study, an automatic left ventricle (LV) segmentation algorithm using short-axis cine cardiac MRI is presented. We compensate coil sensitivity of magnitude images depending on coil location, classify edge information after extracting edges, and segment LV by applying region-growing segmentation. We design a weighting function for intensity signal and calculate a blood volume of LV considering partial voxel effects. Using cardiac cine SSFP of 38 subjects with Cornell University IRB approval, we compared our algorithm to manual contour tracing and MASS software. Without partial volume effects, we achieved segmentation accuracy of $3.3mL{\pm}5.8$ (standard deviation) and $3.2mL{\pm}4.3$ in diastolic and systolic phases, respectively. With partial volume effects, the accuracy was $19.1mL{\pm}8.8$ and $10.3mL{\pm}6.1$ in diastolic and systolic phases, respectively. Also in ejection fraction, the accuracy was $-1.3%{\pm}2.6$ and $-2.1%{\pm}2.4$ without and with partial volume effects, respectively. Results support that the proposed algorithm is exact and useful for clinical practice.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.1-8
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• 2023

Modeling of artificial targets in Synthetic Aperture radar (SAR) mainly simulates radar signals reflected from the faces and edges of the 3D Computer Aided Design (CAD) model with a ray-tracing method, and modeling of the clutter on the Earth's surface uses a method of distinguishing types with similar distribution characteristics through statistical analysis of the SAR image itself. In this paper, man-made targets on the surface and background clutter on the terrain are integrated and made into a three-dimensional (3D) point cloud scatterer model, and SAR image were created through computational signal processing. The results of the SAR Stripmap image generation of the actual automobile based SAR radar system and the results analyzed using EM modeling or statistical distribution models are compared with this 3D point cloud scatterer model. The modeling target is selected as an bridge because it has the characteristic of having both water surface and ground terrain around the bridge and is also a target of great interest in both military and civilian use.

• The KIPS Transactions:PartA
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• v.14A no.2
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• pp.77-84
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• 2007

The intima media thickness(IMT) of the carotid artery from B mode ultrasound images has recently been proposed as the most useful index of individual atherosclerosis and can be used to predict major cardiovascular events. Ultrasonic measurements of the IMT are conventionally obtained by manually tracing interfaces between tissue layers. The drawbacks of this method are the inter and intra observer variability and its inefficiency. In this paper, we present a multiresolution snake method combined with the dynamic programming, which overcomes the various noises and sensitivity to initialization of conventional snake. First, an image pyramid is constructed using the Gaussian pyramid that maintains global edge information with smoothing in the images, and then the boundaries are automatically detected in the lowest resolution level by minimizing a cost function based on dynamic programming. The cost function includes cost terms which are representing image features and geometrical continuity of the vessel interfaces. Since the detected boundaries are selected as initial contour of the snake for the next level, this automated approach solves the problem of the initialization. Moreover, the proposed snake improves the problem of converging th the local minima by defining the external energy based on multiple image features. In this paper, our method has been validated by computing the correlation between manual and automatic measurements. This automated detection method has obtained more accurate and reproducible results than conventional edge detection by considering multiple image features.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.12
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• pp.982-992
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• 2017

In this paper, we introduce a method of selection for the optimal transmission polarization of a W-band seeker through the extraction of the one-dimensional scattering center of a ground tank target. We calculated the surface scattering and edge scattering using the shooting and bouncing ray tracing method of the CST A-solver. Based on 4-channel RCS data, using the one-dimensional RELAX algorithm, which is a kind of spectral estimation technique, scattering centers of ground targets were extracted. According to the changes in the polarization state and look angle, we compared and analyzed the scattering center results. Through simulation, we verified that the scattering center results can be applied when feature vectors are used for target recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.385-396
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• 1993

In this paper, a improved method of digital image analysis required in basic medical science for diagnosis of cells was proposed. The object image was the thyroid gland cell image, and the purpose was automatic discrimination of three classes cells(normal cell, follicular neoplastic cells, and papillary neoplastic cells) by difference of chromatin patterns. To segment the cell nucleus from background, the region segmentation algorithm by edge tracing was proposed. And feature parameter was obtained from discrete Fourier transformation of image. After construct a feature sample group of each cells, experiment of discrimination was executed with any verification cells. As a consequency of using features proposed in this paper, get a better recognition rate(70-90%) than previously reported papers, and this method give shape to get objectivity and fixed quantity in diagnosis of cells, The methods described in this paper be used immediately for discrimination of neoplastic cells.