• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.3
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• pp.11-19
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• 2009

Recently, concerns relating to the maintenance of large structures have been increased. In addition, the number of large structures that need to be evaluated for their structural safety due to natural disasters and structural deterioration has been rapidly increasing. It is common for the structural characteristics of an older large structure to differ from the characteristics in the initial design stage, and changes in dynamic characteristics may result from a reduction in stiffness due to cracks on the materials. The process of deterioration of such structures enables the detection of damaged locations, as well as a quantitative evaluation. One of the typical measuring instruments used for the monitoring of bridges and buildings is the dynamic measurement system. Conventional dynamic measurement systems require considerable cabling to facilitate a direct connection between sensor and DAQ logger. For this reason, a method of measuring structural responses from a remote distance without the mounted sensors is needed. In terms of non-contact methods that are applicable to dynamic response measurement, the methods using the doppler effect of a laser or a GPS are commonly used. However, such methods could not be generally applied to bridge structures because of their costs and inaccuracies. Alternatively, a method using a visual image can be economical as well as feasible for measuring vibration signals of inaccessible bridge structures and extracting their dynamic characteristics. Many studies have been conducted using camera visual signals instead of conventional mounted sensors. However, these studies have been focused on measuring displacement response by an image processing technique after recording a position of the target mounted on the structure, in which the number of measurement targets may be limited. Therefore, in this study, a model experiment was carried out to verify the measurement algorithm for measuring multi-point displacement responses by using a DIC (Digital Image Correlation) technique.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.27-36
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• 2004

Detection and recognition of human faces in images can be considered as an important aspect for applications that involve interaction between human and computer. In this paper, we propose a face recognition method using eigenfaces and fuzzy neural networks. The Principal Components Analysis (PCA) is one of the most successful technique that have been used to recognize faces in images. In this technique the eigenvectors (eigenfaces) and eigenvalues of an image is extracted from a covariance matrix which is constructed form image database. Face recognition is Performed by projecting an unknown image into the subspace spanned by the eigenfaces and by comparing its position in the face space with the positions of known indivisuals. Based on this technique, we propose a new algorithm for face recognition consisting of 5 steps including preprocessing, eigenfaces generation, design of fuzzy membership function, training of neural network, and recognition. First, each face image in the face database is preprocessed and eigenfaces are created. Fuzzy membership degrees are assigned to 135 eigenface weights, and these membership degrees are then inputted to a neural network to be trained. After training, the output value of the neural network is intupreted as the degree of face closeness to each face in the training database.

• Journal of the Korea Computer Graphics Society
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• v.26 no.3
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• pp.9-19
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• 2020

With the recent development of various kinds of virtual reality devices, there has been an active research effort to increase the sense of reality by recognizing the physical behavior of users rather than by classical user input methods. Among such devices, the Leap Motion controller recognizes the user's hand gestures and can realistically trace the user's hand in a virtual reality environment. However, manipulating an object in virtual reality using a recognized user's hand often causes the hand to pass through the object, which should not occur in the real world. This study presents a way to build a visual feedback system for enhancing the user's sense of interaction between hands and objects in virtual reality. In virtual reality, the user's hands are examined precisely by using a ray tracing method to see if the virtual object collides with the user's hand, and when any collision occurs, visual feedback is given through the process of reconstructing the user's hand by moving the position of the end of the user's fingers that enter the object through sign distance field and reverse mechanics. This enables realistic interaction in virtual reality in real time.

• Journal of the Korean Electrochemical Society
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• v.19 no.2
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• pp.29-38
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• 2016

Screen printed carbon electrodes (SPCEs) with immobilized osmium-based hydrogel redox polymer, uricase and PEGDGE can be used to apply uric acid electrochemical detecting. The osmium redox complexes were synthesized by the coordinating pyridine group having different functional group at 4-position with osmium compounds. The synthesized poly-osmium hydrogel complexes are described as PAA-PVI-$[Os(dCl-bpy)_2Cl]^{+/2+}$, PAA-PVI-$[Os(dme-bpy)_2Cl]^{+/2+}$, PAA-PVI-$[Os(dmo-bpy)_2Cl]^{+/2+}$. The different concentrations of uric acid were measured by cyclic voltammetry technique using enzyme-immobilized SPCEs. The prepared SPCEs using PAA-PVI-$[Os(dme-bpy)_2Cl]^{+/2+}$ showed no interference from common physiologic interferents such as ascorbic acid (AA) or glucose. The resulting electrical currents at 0.33 V vs. Ag/AgCl displayed a good linear response with uric acid concentrations from 1.0 to 5.0 mM. Therefore, this approach allowed the development of a simple, point of care in the medical field, disposable electrochemical uric acid biosensor.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.380-389
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• 2007

In Korea, undoubtedly, the cancer is one of the most common reasons of death, and hepatoma is the second highest fatal cancer regardless of the gender only next to the stomach cancer In the middle and prime-aged between 40 and 60 years, the incidence of hepatoma is the highest in the world, and the death rate due to hepatoma is the highest among OECD countries. In this paper, we propose a novel method for automatic identification of hepatoma from a contrast enhanced CT images, which is used in an expert system that helps medical specialists. First, consecutive $40{\sim}50$ contrail enhanced CT images are photographed by every 5mm from the upper part of the chest, and using position information on the rib, we classify the internal area including only internal organs and the external one that consists of the rib, subcutaneous fat layers, and the background from the CT images. Then, the region of the liver is extracted from the classified internal area by using information on the intensity, the distribution of brightness, and using the regions extracted from consecutive images, we restore information on the 5 mm space occurred between the consecutive two slides tty applying a shape-based interpolation method. Lastly, using the characteristics such as the brightness and the morphology, we are able to extract the regions of hepatoma. The expert system based on our method is sufficiently competitive when it is compared with the diagnoses by specialists in the diagnostic radiology.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.6
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• pp.90-100
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• 2017

The purpose of this study is to detect and label the vehicles using the drone images as a way to overcome the limitation of the existing point and section detection system and vehicle gap estimation on Arterial road. In order to select the appropriate time zone, position, and altitude for the acquisition of the drone image data, the final image data was acquired by shooting under various conditions. The vehicle was detected by applying mixed Gaussian, image binarization and morphology among various image analysis techniques, and the vehicle was labeled by applying Kalman filter. As a result of the labeling rate analysis, it was confirmed that the vehicle labeling rate is 65% by detecting 185 out of 285 vehicles. The gap was calculated by pixel unitization, and the results were verified through comparison and analysis with Daum maps. As a result, the gap error was less than 5m and the mean error was 1.67m with the preceding vehicle and 1.1m with the following vehicle. The gaps estimated in this study can be used as the density of the urban roads and the criteria for judging the service level.

• Korean Journal of Optics and Photonics
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• v.4 no.1
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• pp.15-21
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• 1993

This paper describes the design and development of a KrF excimer laser stepper and discusses the detailed system parameters and characterization data obtained from the performance test. We have developed a deep UV step-and-repeat system, operating at 248 nm, by retrofitting a commercial modules such as KrF excimer laser, precision wafer stage and fused silica illumination and 5X projection optics of numerical aperture 0.42. What we have developed, to the basic structure, are wafer alignment optics, reticle alignment system, autofocusing/leveling mechanisms and environment chamber. Finally, all these subsystem were integrated under the control of microprocessor-based controllers and computer. The wafer alignment system comprises the OFF-AXIS and the TTL alignment. The OFF-AXIS alignment system was realized with two kinds of optics. One is the magnification system with the image processing technique and the other is He-Ne laser diffraction type system using the alignment grating on the wafer. 'The TTL alignment system employs a dual beam inteferometric method, which takes advantages of higher diffraction efficiency compared with other TTL type alignment systems. As the results, alignment accuracy for OFF-AXIS and TTL alignment system were obtained within 0.1 $\mu\textrm{m}$/ 3 $\sigma$ for the various substrate on the wafers. The wafer focusing and leveling system is modified version of the conventional systems using position sensitive detectors (PSD). This type of detection method showed focusing and leveling accuracies of about $\pm$ 0.1 $\mu\textrm{m}$ and $\pm$ 0.5 arcsec, respectively. From the CD measurement, we obtained 0.4 $\mu\textrm{m}$ resolution features over the full field with routine use, and 0.3 $\mu\textrm{m}$ resolution was attainable under more strict conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.749-754
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• 2011

In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.

• Journal of Microbiology and Biotechnology
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• v.16 no.10
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• pp.1561-1569
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• 2006

Denaturing gradient gel electrophoresis (DGGE) is one of the most frequently used methods for analysis of soil microbial community structure. Unbiased PCR amplification of target DNA templates is crucial for efficient detection of multiple microbial populations mixed in soil. In this study, DGGE profiles were compared using different pairs of primers targeting different hypervariable regions of thirteen representative soil bacteria and clones. The primer set (1070f-1392r) for the E. coli numbering 1,071-1,391 region could not resolve all the 16S rDNA fragments of the representative bacteria and clones, and moreover, yielded spurious bands in DGGE profiles. For the E. coli numbering 353-514 region, various forward primers were designed to investigate the efficiency of PCR amplification. A degenerate forward primer (F357IW) often yielded multiple bands for a certain single 16S rDNA fragment in DGGE analysis, whereas nondegenerate primers (338f, F338T2, F338I2) differentially amplified each of the fragments in the mixture according to the position and the number of primer-template mismatches. A forward primer (F352T) designed to have one internal mismatch commonly with all the thirteen 16S rDNA fragments efficiently produced and separated all the target DNA bands with similar intensities in the DGGE profiles. This primer set F352T-519r consistently yielded the best DGGE banding profiles when tested with various soil samples. Touchdown PCR intensified the uneven amplification, and lowering the annealing temperature had no significant effect on the DGGE profiles. These results showed that PCR amplification bias could be much improved by properly designing primers for use in fingerprinting soil bacterial communities with the DGGE technique.

• Journal of Animal Science and Technology
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• v.47 no.1
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• pp.1-10
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• 2005

Intramuscular fat content(lMF) is considered as one of major economic traits in the pig breeding and industry. In general, high IMF results in better meat quality. Several approaches to detect quantitative trait 10ci( QTL) for IMF indicated a strong possibility of the existence of a QTL related to IMF between the microsatellite marker SW71 and SW1881 on SSC6q. Porcine FABP3 has been considered as a candidate gene affecting IMF due to its physiological roles and position on the pig genome. Two novel mutations, g.-114T> C and g.-158T>G were detected by duplicate sequencing of the porcine FABP3 promoter region. These two mutations were identified as absolute linkage disequilibrium. The g.-158T> G mutation was used for investigating relationships with growth and fat deposition traits. The GG genotype of the g.-158T> G polymorphism showed highly negative effects(P< 0.01) on body weights at 3 and 12 weeks of age, and a positive effect(P< 0.05) on IMF. However, backfat thickness(BF) and carcass fat(CF) content were not significantly associated with the genotype. The result indicates that the novel mutations, identified in this study, could be utilized as possible genetic markers to improve IMF, independent with BF.