• Smart Structures and Systems
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• v.29 no.1
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• pp.237-250
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• 2022

Structural health monitoring (SHM) plays an important role in ensuring the safety and functionality of critical civil infrastructure. In recent years, numerous researchers have conducted studies to develop computer vision and machine learning techniques for SHM purposes, offering the potential to reduce the laborious nature and improve the effectiveness of field inspections. However, high-quality vision data from various types of damaged structures is relatively difficult to obtain, because of the rare occurrence of damaged structures. The lack of data is particularly acute for fatigue crack in steel bridge girder. As a result, the lack of data for training purposes is one of the main issues that hinders wider application of these powerful techniques for SHM. To address this problem, the use of synthetic data is proposed in this article to augment real-world datasets used for training neural networks that can identify fatigue cracks in steel structures. First, random textures representing the surface of steel structures with fatigue cracks are created and mapped onto a 3D graphics model. Subsequently, this model is used to generate synthetic images for various lighting conditions and camera angles. A fully convolutional network is then trained for two cases: (1) using only real-word data, and (2) using both synthetic and real-word data. By employing synthetic data augmentation in the training process, the crack identification performance of the neural network for the test dataset is seen to improve from 35% to 40% and 49% to 62% for intersection over union (IoU) and precision, respectively, demonstrating the efficacy of the proposed approach.

• Korean Institute of Interior Design Journal
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• v.23 no.3
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• pp.173-180
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• 2014

Dwelling connotes characteristics like social and cultural and technical climatic conditions, lifestyles and demands of regions, and especially, apartment, as one of dwelling types, shows various aspects of modern society. With the economic development centering on large cities, apartments have been established as universal housing forms in Seoul and Shanghai. The deepening of economic development in cities has increased small households consisting of one or two persons by affecting the population and household structure, and they've become information consumer groups. This has also influenced the size of apartment and increased the demand for small-sized housing. If the floor area is small, it is possible to use space widely according to the plan composition, so there is a need for floor planning to understand natural environment, physical environment and residents.This study compared and analyzed plan compositions of small-sized apartments which have been parceled out for the recent three years in Seoul and Shanghai. This study aims to understand housing cultures and users in the two countries depending on natural environments, living habits and spatial functions by analyzing common points and differences of public spaces like living room, dining room and kitchen, and private spaces like bedroom which have absolute effects on room arrangement and traffic line. The study results are as follows. From the perspective of natural environments, in Seoul, two-sided open cross-ventilation structure where is favorable to lighting and ventilation, occupied the biggest proportion of public space, while in Shanghai, most public spaces had lighting and ventilation structures through windows in each room. In Seoul, 3R type occupied the largest proportion of private space(87.7%), and privacy was maintained and space scale was adjusted using spaces with diverse functions such as bathroom in the couple bedroom, dress room and powder room and variable walls. But 2R type occupied the largest proportion of private space(60.2%) in Shanghai, and they emphasized private space and privacy of each room depending on major living habits. In conclusion, this study for comparing and analyzing common points and differences of small-sized apartment plan compositions in Seoul and Shanghai will provide proper guidelines for small-sized apartments to be built in Seoul and Shanghai in the future, if strong points and weak points of plan compositions in the two countries will be additionally analyzed and remedied.

• Journal of Plant Biotechnology
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• v.42 no.3
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• pp.245-256
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• 2015

In the agricultural industries, LEDs are used as supplementary, as well as main lighting sources in closed cultivation systems. In cultivation using artificial light sources, various light qualities have been tried to supplement fluorescent lamps to promote plant growth and metabolism. Microarray analysis of Brassica rapa seedlings under blue and fluorescent mixed with blue light conditions identified changes in three genes of the glucosinolate pathway. This attracted attention as functional materials highly expressed 3.6-4.6 fold under latter condition. We selected four more genes of the glucosinolate pathway from the Brassica database and tested their expression changes under fluorescent light mixed with red, green, and blue, respectively. Some genes increased expression under red and blue mixed conditions. The Bra026058, Bra015379, and Bra021429; the orthologous genes of CYP79F1, ST5a, and FMOGS-OX1 in Arabidopsis, are highly expressed in Brassica rapa under fluorescent mixed with blue light conditions. Further, Bra029355, Bra034180, Bra024634, and Bra022448; the orthologous genes of MAM1, AOP3, UGT74B1, and BCAT4 in Arabidopsis, are highly expressed in Brassica rapa under fluorescent mixed with red light conditions. The various light conditions had unique effects on the varieties of Brassica, resulting in differences in glucosinolate synthesis. However, in some varieties, glucosinolate synthesis increased under mixed blue light conditions. These results will help to construct artificial light facilities, which increase functional crops production.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.123-134
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• 2008

In this paper, we propose a real-tin e face recognition system that is robust under various lighting conditions. Th Modified Census Transform algorithm that is insensitive to illumination variations is employed to extract local structure features. In a practical face recognition system, acquired images through a camera are likely to be blurred and some of them could be side face images, resulting that unacceptable performance could be obtained. To improve stability of a practical face recognition system, we propose a real-time algorithm that rejects unnecessary facial picture and makes use of recognition consistency between successive frames. Experimental results on the Yale database with large illumination variations show that the proposed approach is approximately 20% better than conventional appearance-based approaches. We also found that the proposed real-time method is more stable than existing methods that produces recognition result for each frame.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.122-130
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• 2009

Conventional approaches for car number plate detection have dealt with those input images having similar sizes and simple background acquired under well organized environment. Thus their performance get reduced when input images include number plates with different sizes and when they are acquired under different lighting conditions. To solve these problem, this paper proposes a new scheme that uses the geometrical features of number plates and their topological information with reference to other features of the car. In the first step, those edges constructing a rectangle are detected and several pixels neighboring those edges are selected as the seed pixels for region growing. For region growing, color and intensity are used as the features, and the result regions are merged to construct the candidate for a number plate if their features are within a certain boundary. Once the candidates for the number plates are generated then their topological relations with other parts of the car such as lights are tested to finally determine the number plate region. The experimental results have shown that the proposed method can be used even for detecting small size number plates where characters are not visible.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1972-1978
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• 2010

AAM(Active Appearance Model) is one of the most effective ways to detect deformable 2D objects and is a kind of mathematical optimization methods. The cost function is a convex function because it is a least-square function, but the search space is not convex space so it is not guaranteed that a local minimum is the optimal solution. That is, if the initial value does not depart from around the global minimum, it converges to a local minimum, so it is difficult to detect face contour correctly. In this study, an AAM-based face tracking algorithm is proposed, which is robust to various lighting conditions and backgrounds. Eye detection is performed using SIFT and Genetic algorithm, the information of eye are used for AAM's initial matching information. Through experiments, it is verified that the proposed AAM-based face tracking method is more robust with respect to pose and background of face than the conventional basic AAM-based face tracking method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.8C
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• pp.505-515
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• 2011

This paper describes a normalization method of Haar-like features used for object detection. Previous method which performs variance normalization on Haar-like features requires a lot of calculations, since it uses an additional integral image for calculating the standard deviation of intensities of pixels in a candidate window and increases possibility of false detection in the area where variance of brightness is small. The proposed normalization method can be performed much faster than the previous method by not using additional integral image and classifiers which are trained with the proposed normalization method show robust performance in various lighting conditions. Experimental result shows that the object detector which uses the proposed method is 26% faster than the one which uses the previous method. Detection rate is also improved by 5% without increasing false alarm rate and 45% for the samples whose brightness varies significantly.

• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1131-1138
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• 2006

This paper proposes a novel method for grading of underground communication conduits by laser projection image analysis. The equipment thrust into conduit consists of a laser diode, a light emitting diode and a camera, the laser diode is utilized for generating projection image onto pipe wall, the light emitting diode for lighting environment and the image of conduit is acquired by the camera. In order to segment profile region, we used a novel color difference model and multiple thresholds method. The shape of profile ring is represented as a minimum diameter and the Fourier descriptor, and then the pipe status is graded by the rule-based method. Both local and global features of the segmented ring shaped, the minimum diameter and the Fourier descriptor, are utilized, therefore injured and distorted pipes can be correctly graded. From the experimental results, the classification is measured with accuracy such that false alarms are less than 2% under the various conditions.

• Proceedings of the Materials Research Society of Korea Conference
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• 2010.05a
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• pp.19.2-19.2
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• 2010

Printed electronics using printing process has broadened in all respects such as electrics (lighting, batteries, solar cells etc) as well as electronics (OLED, LCD, E-paper, transistor etc). Copper is considered to be a promising alternative to silver for printed electronics, due to very high conductivity at a low price. However, Copper is easily oxidized, and its oxide is non-conductive. This is the highest hurdle for making copper inks, since the heat and humidity that occurs during ink making and printing simply accelerates the oxidation process. A variety of chemical treatments including organic capping agents and metallic coating have been used to slow this oxidation. We have established synthetic conditions of copper nanoparticles (CuNPs) which are resistant to oxidation and average diameter of 20 to 50nm. Specific resistivity should be less than $4\;{\mu}{\Omega}{\cdot}cm$ when sintered at lower temperature than $250^{\circ}C$ to be able to apply to conductive patterns of FPCBs using ink-jet printing. Through this study, the parameters to control average diameter of CuNPs were found to be the introduction of additive agent, the feeding rate of reducing agent, and reaction temperature. The CuNPs with various average diameters (58, 40, 26, 20nm) could be synthesized by controlling these parameters. The dispersed solution of CuNPs with an average size of 20 nm was made with nonpolar solvent containing 3 wt% of binder, and then coated onto glass substrate. After sintering the coated substrates at $250^{\circ}C$ for 30 minutes in nitrogen atmosphere, metallic copper film resulted in a specific resistivity of $4.2\;{\mu}{\Omega}{\cdot}cm$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.453-458
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• 2016

One of the most common applications of machine vision is quality inspections in automated production. In this study, a welding inspection system that is controlled by a PC and a PLC equipped with a multi-camera setup was developed. The system was designed to measure the primary dimensions, such as the length and width of the welding areas. The TCP/IP protocols and multi-threading techniques were used for parallel control of the optical components and physical distribution. A coaxial light was used to maintain uniform lighting conditions and enhance the image quality of the weld areas. The core image processing system was established through a combination of various algorithms from the OpenCV library. The proposed vision inspection system was fully validated for an actual weld production line and was shown to satisfy the functional and performance requirements.