• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.21 no.4
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• pp.347-353
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• 2003

Lately, Digital Photogrammetry has been increasingly applied to various hightech industries and becomes one of more interesting focuses of study than ever. Thus, this study aims to develop a Road Horizontal Alignment Information System by means of digital photogrammetry. Data acquired from digital photographic techniques were processed using Delphi, an object oriented programming language to develop a computer aided program, that allows us to build the information on Road Horizontal Alignment(Beginning Point of Curve, Ending Point of Curve, Radius, Intersection Point). The developed program could maximize visualization for better analysis compared with traditional programs because it utilizes many image data. Comparing with data from traditional horizontal alignment extraction programs based on the principle of least square method, the data acquired by Horizontal Alignment Information and kinematic GPS showed out of the developed road information systems the improved accuracy of IP value up to about 2m in the direction of X, Y axes, where the accuracy of curve radius(R) becomes enhanced up to about 2.5 m.

• Journal of Periodontal and Implant Science
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• v.31 no.2
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• pp.465-475
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• 2001

The purpose of this study was to evaluate effect of platelet rich plasma on the treatment of Grade II furcation involvement, with and without porous resorbable calcium carbonate($Biocoral^{(R)}$)in humans by digital subtraction radiography. 15 teeth(control group) were treated with porous resorbable calcium carbonate($Biocoral^{\(R)}$), and 15 teeth(test group) were treated with porous resorbable calcium carbonate($Biocoral^{(R)}$) and Platelet Rich Plasma. The change of bone density was assessed by digital subtraction radiography in this study. The change of mineral content by as much as 5%(vol) could be perceived in the subtracted images. The change of mineral content was assessed in the method that two radiographs are put into computer program to be overlapped and the previous image is subtracted by the later one. Both groups were statistically analyzed by Wilcoxon signed Ranks Test and Mann-whitney Test using SPSS program(5% significance level). The results were as follows: 1. In test group, the radiolucency in 3 months after surgry were significantly increased than 1 month after surgery(p<0.05). 2. In test group, there were no significant difference between 1 month after surgery and 6 months after surgery(p>0.05). 3. In test group, the radiopacity in 6 months after surgery were significantly increased than 3 months after surgery(p<0.05). 4. In control group, the radiolucency in 3 months and 6 months after surgery were significantly increased than 1 month after surgery(p<0.05). 5. In control group, the radiopacity in 6 months after surgery were significantly increased than 3 months after surgery(p<0.05). 6. There were no significant difference between test group and control group at 1 month, 3 months after surgery, but radiopacity in test group were significantly increased than control group at 6 months after surgery(p<0.05). In conclusion, Platelet Rich Plasma can enhance bone density.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.486-492
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• 2015

Radiation source imaging system is essential for protecting of radiation leakage accidents and minimizing damages from the radioactive materials, and is expected to play an important role in the nuclear plant decommissioning area. In this study, the stereoscopic camera principle was applied to develop a new radiation imaging device technology that can extract the radiation three-dimensional position information. This radiation three-dimensional imaging device (K3-RIS) was designed as a compact structure consisting of a radiation sensor, a CCD camera, and a pan-tilt only. It features the acquisition of stereoscopic radiation images by position change control, high-resolution detection by continuous scan mode control, and stereoscopic image signal processing. The performance analysis test of K3-RIS was conducted for a gamma-ray source(Cs-137) in radiation calibration facility. The test result showed that a performance error with less than 3% regardless of distances of the objects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1559-1564
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• 2011

This study presents the development of a machine vision inspection system(MVIS) purposely for car seat frames as an alternative for human inspection. The proposed MVIS is designed to meet the demands, features and specifications of car seat frame manufacturing companies in striving for increased throughput of better quality. This computer-based MVIS is designed to perform quality measures by detecting holes, nuts and welding spots on every car seat frame in real time. In this study, the NI Vision Builder software for Automatic Inspection was used as a solution in configuring the aimed quality measurements. The techniques for visual inspection are optimized through qualitative analysis and simulation of human tolerance on inspecting car seat frames. Furthermore, this study exemplifies the incorporation of the optimized vision inspection environment to the pre-inspection and post-inspection subsystems. The system built on this proposed MVIS for car seat frames has successfully found the possible detections.

• Radiation Oncology Journal
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• v.34 no.1
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• pp.64-75
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• 2016

Purpose: In order to evaluate the relationship between the dose to the liver parenchyma and focal liver reaction (FLR) after stereotactic ablative body radiotherapy (SABR), we suggest a novel method using a three-dimensional dose distribution and change in signal intensity of gadoxetate disodium-gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) hepatobiliary phase images. Materials and Methods: In our method, change of the signal intensity between the pretreatment and follow-up hepatobiliary phase images of Gd-EOB-DTPA-enhanced MRI was calculated and then threshold dose (TD) for developing FLR was obtained from correlation of dose with the change of the signal intensity. For validation of the method, TDs for six patients, who had been treated for liver cancer with SABR with 45-60 Gy in 3 fractions, were calculated using the method, and we evaluated concordance between volume enclosed by isodose of TD by the method and volume identified as FLR by a physician. Results: The dose to normal liver was correlated with change in signal intensity between pretreatment and follow-up MRI with a median $R^2$ of 0.935 (range, 0.748 to 0.985). The median TD by the method was 23.5 Gy (range, 18.3 to 39.4 Gy). The median value of concordance was 84.5% (range, 44.7% to 95.9%). Conclusion: Our method is capable of providing a quantitative evaluation of the relationship between dose and intensity changes on follow-up MRI, as well as determining individual TD for developing FLR. We expect our method to provide better information about the individual relationship between dose and FLR in radiotherapy for liver cancer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1897-1902
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• 2008

In computer vision analysis of detecting concrete slab surface cracks, there are many difficulties to overcome. Target images often have defamations due to the light condition and other external environment. Another difficulties in detecting concrete crack image is that there is no clear distinction in intensity between the crack and the surface since the surface is often irregular. In this paper, we apply ART2 based quantization in order to classify target concrete slab surface images into several areas with respect to the light intensity. From those quantized areas, we investigate the distribution of real cracks and noises. Then, we extract candidate crack areas after applying noise removal process to areas which have be th oracle and noises. Finally, crack areas are recognized by using morphological features of cracks from such candidate areas. In experiment with real world concrete slab structure images, our algorithm has advantage in recognizing accuracy of cracks to other algorithms especially in relatively brighter areas of concrete surface.

• Smart Structures and Systems
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• v.24 no.5
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• pp.567-585
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• 2019

In the past two decades, structural health monitoring (SHM) systems have been widely installed on various civil infrastructures for the tracking of the state of their structural health and the detection of structural damage or abnormality, through long-term monitoring of environmental conditions as well as structural loadings and responses. In an SHM system, there are plenty of sensors to acquire a huge number of monitoring data, which can factually reflect the in-service condition of the target structure. In order to bridge the gap between SHM and structural maintenance and management (SMM), it is necessary to employ advanced data processing methods to convert the original multi-source heterogeneous field monitoring data into different types of specific physical indicators in order to make effective decisions regarding inspection, maintenance and management. Conventional approaches to data analysis are confronted with challenges from environmental noise, the volume of measurement data, the complexity of computation, etc., and they severely constrain the pervasive application of SHM technology. In recent years, with the rapid progress of computing hardware and image acquisition equipment, the deep learning-based data processing approach offers a new channel for excavating the massive data from an SHM system, towards autonomous, accurate and robust processing of the monitoring data. Many researchers from the SHM community have made efforts to explore the applications of deep learning-based approaches for structural damage detection and structural condition assessment. This paper gives a review on the deep learning-based SHM of civil infrastructures with the main content, including a brief summary of the history of the development of deep learning, the applications of deep learning-based data processing approaches in the SHM of many kinds of civil infrastructures, and the key challenges and future trends of the strategy of deep learning-based SHM.

• Journal of Magnetics
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• v.20 no.1
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• pp.40-46
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• 2015

This study investigated the accuracy of magnetic resonance angiography (MRA) and computed tomography angiography (CTA) in terms of reflecting the actual vascular length. Three-dimensional time of flight (3D TOF) MRA, 3D contrast-enhanced (CE) MRA, volume-rendering after CTA and maximum intensity projection were investigated using a flow model phantom with a diameter of 2.11 mm and area of $0.26cm^2$. 1.5 and 3.0 Tesla devices were used for 3D TOF MRA and 3D CE MRA. CTA was investigated using 16 and 64 channel CT scanners, and the images were transmitted and reconstructed by volume-rendering and maximum intensity projection, followed by conduit length measurement as described above. The smallest 3D TOF MRA measure was $2.51{\pm}0.12mm$ with a flow velocity of 40 cm/s using the 3.0 Tesla apparatus, and $2.57{\pm}0.07mm$ with a velocity of 71.5 cm/s using the 1.5 Tesla apparatus; both images were magnified from the actual measurement of 2.11 mm. The measurement with the 16 channel CT scanner was smaller ($3.83{\pm}0.37mm$) than the reconstructed image on maximum intensity projection. The images from CTA from examination apparatus and reconstruction technique were all larger than the actual measurement.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.141-147
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• 2021

In this paper, in order to improve the utilization of hyperspectral large-capacity data feature information by reducing complex computations by dimension reduction of neural network inputs in embedded systems, the band selection algorithm is applied in each subset. Among feature extraction and feature selection techniques, the feature selection aim to improve the optimal number of bands suitable for datasets, regardless of wavelength range, and the time and performance, more than others algorithms. Through this experiment, although the time required was reduced by 1/3 to 1/9 times compared to the others band selection technique, meaningful results were improved by more than 4% in terms of performance through the K-neighbor classifier. Although it is difficult to utilize real-time hyperspectral data analysis now, it has confirmed the possibility of improvement.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.201-210
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• 2019

This paper proposes the AMCS(Agricultural Machine Control System that distinguishes farms using satellite photos or drone photos of farms and controls the self-driving and operation of farm drones and tractors. The AMCS consists of the LSM(Local Server Module) which separates farm boundaries from sensor data and video image of drones and tractors, reads remote control commands from the main server, and then delivers remote control commands within the management area through the link with drones and tractor sprinklers and the PSM that sets a path for drones and tractors to move from the farm to the farm and to handle work at low cost and high efficiency inside the farm. As a result of AMCS performance analysis proposed in this paper, the PSM showed a performance improvement of about 100% over Dijkstra algorithm when setting the path from external starting point to the farm and a higher working efficiency about 13% than the existing path when setting the path inside the farm. Therefore, the PSM can control tractors and drones more efficiently than conventional methods.