• Journal of the Korea Convergence Society
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• v.6 no.6
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• pp.285-291
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• 2015

FTMS, TCS, ITS equipment such as high-pass highway are just a situation that does not lack traceability and passive surveillance is related to fault DB has so far consisted of an integrated operations management to maximize utilization of the facility. In addition, there is no replacement parts are replaced when a failure occurs, increasing the number of parts and repair time I have trouble growing, and becoming a service interruption whenever you replace each time. In this study, proactively manage the failure history of a highway facility ITS tries to preventive maintenance. Therefore, the error history is based on the reliability of the high-pass facilities theory to calculate the reliability of the system through a systematic statistical analysis Operational Availability. The fault number and the time the replacement period through the estimate decreases and can reduce the budget expenses by securing the spare parts quantity, establish a management plan in part by improving the quality of the system through constant preventive maintenance, quality of service at all times It may direct the non-stop operation state of the available state.

• Journal of Dental Rehabilitation and Applied Science
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• v.19 no.4
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• pp.297-308
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• 2003

Face-bow is used to transfer models to the articulator in diagnosing the patient or treating problems associated with occlusion. However, there have been few reports on the reliability of the face-bow procedure and the relationship between the experience of the operator and the reliability of the face-bow procedure. The purposes of this study are to examine the reliability of the face-bow procedure and to evaluate whether the face-bow transferring has any training effect. Nine dentists working at M hospital conducted a face-bow transfer in one patient having a normal dentition and interdental relationship. The procedure was done two times a week for four weeks. The maxillary model was mounted to the articulator every time, then the landmarks on the maxillary right first molar, the maxillary left central incisor, and the maxillary left first molar were measured with a special three-dimensional instrument. These data were input into a computer, and evaluated statistically. The results were as follows ; 1. When examined with ANOVA test, the results were p=0.2040 in maxillary right first molar, p=0.0578 in maxillary left incisor, and p=0.1433 in maxillary left first molar. There was no significant(0< $p{\leq}0.05$). 2. Training 1) The correlation coefficient between trial and rejection was -0.578 when analyzed with T-distribution. The more we tried, the less errors we found. 2) When the S.D. of the first three trials was compared to the S.D. of the last three trials in face-bow transfer, the results showed that the former was larger than the latter in thirty-nine times, and the latter was larger than the former in fifteen times. The more we tried face-bow transfer, the less errors we found. 3. When the S.D. of x, y, z coordinates were examined, the S.D. of x coordinates had the largest measurement in five times, the S.D. of y coordinates had the largest measurement in four times, and the S.D. of z coordinates had the largest measurement in nine times. The possibility which the error can occur in z coordinate was the highest.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.159-166
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• 2016

In this paper, an active object tracking system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and phase-type correlation scheme and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-embedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 480 frames of the test input stereo image, it is analyzed that a standard variation between the measured and computed the estimated target's height and an error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 1.03 and 1.18% on average, respectively. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.11
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• pp.1065-1075
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• 2017

In this study, high velocity impact tests along with modeling of material behavior and numerical analyses were conducted to predict the dispersion behavior of the debris resulting from a high velocity impact fracture. For the impact tests, two different materials were employed for both the projectile and the target plate - the first setup employed aluminum alloy while the second employed steel. The projectile impacts the target plate with a velocity of approximately 1 km/s were enforced to generate the impact damages in the aluminum witness plate through the fracture debris. It was confirmed that, depending on the material employed, the debris dispersion behavior as well as the dispersion radii on the witness plate varied. A numerical analysis was conducted for the same impact test conditions. The smoothed particle hydrodynamics (SPH)-finite element (FE) coupled technique was then applied to model the fracture and damage upon the debris. The experimental and numerical results for the diameters of the perforation holes in the target plate and the debris dispersion radii on the witness plate were in agreement within a 5％ error. In addition, the impact test using steel was found to be more threatening as proven by the larger debris dispersion radius.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.475-482
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• 2007

Most golfers believe that knowing yardages will improve their score. Certainly it helps with club selection. But, simple "Graphic" yardage guides being notorious for error and inaccuracies, which a serious golfer will pick immediately, only serve to erode the players enjoyment and ultimately, golf course satisfaction. Someone believes with low-level aerial photographic images, golfer will be impressed with the accuracy of the depiction, helping them play a more confident game. But, there are no mapping products in true 3-D available in the world that allows a golfer to determine shot distances in yards or meters. So, we suggest an lenticular technology for real 3-D display as a viable alternative to conventional image map solution. This technology is an image display method for the generation of multi-image effects like 3D visualization or animation. This methodology is cutting edge stereoscopic image which overcomes the limitation of conventional photo tech by recomposing and producing 3 dimensional images. A significant strength of this methods its versatility concerning display effects. The main use of the hardcopy 3-D lenticular displays is in the fields of science, education, planning, and representation. This paper gives a concise overview of the lenticular foil technology and describes the production of the true 3-D yardage book of golf courses. For this study, 3-D effects are achieved and evaluated with the lenticular display by incorporation multiple synthetic images based on digital topographic terrain model and by using the two images of the actual stereopair.

• Korean Journal of Remote Sensing
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• v.20 no.5
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• pp.289-305
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• 2004

Atmospheric correction of Landsat Visible and Near Infrared imagery (VIS/NIR) over aquatic environment is more demanding than over land because the signal from the water column is small and it carries immense information about biogeochemical variables in the ocean. This paper introduces two methods, a modified dark-pixel substraction technique (path--extraction) and our spectral shape matching method (SSMM), for the correction of the atmospheric effects in the Landsat VIS/NIR imagery in relation to the retrieval of meaningful information about the ocean color, especially from Case-2 waters (Morel and Prieur, 1977) around Korean peninsula. The results of these methods are compared with the classical atmospheric correction approaches based on the 6S radiative transfer model and standard SeaWiFS atmospheric algorithm. The atmospheric correction scheme using 6S radiative transfer code assumes a standard atmosphere with constant aerosol loading and a uniform, Lambertian surface, while the path-extraction assumes that the total radiance (L/sub TOA/) of a pixel of the black ocean (referred by Antoine and Morel, 1999) in a given image is considered as the path signal, which remains constant over, at least, the sub scene of Landsat VIS/NIR imagery. The assumption of SSMM is nearly similar, but it extracts the path signal from the L/sub TOA/ by matching-up the in-situ data of water-leaving radiance, for typical clear and turbid waters, and extrapolate it to be the spatially homogeneous contribution of the scattered signal after complex interaction of light with atmospheric aerosols and Raleigh particles, and direct reflection of light on the sea surface. The overall shape and magnitude of radiance or reflectance spectra of the atmospherically corrected Landsat VIS/NIR imagery by SSMM appears to have good agreement with the in-situ spectra collected for clear and turbid waters, while path-extraction over turbid waters though often reproduces in-situ spectra, but yields significant errors for clear waters due to the invalid assumption of zero water-leaving radiance for the black ocean pixels. Because of the standard atmosphere with constant aerosols and models adopted in 6S radiative transfer code, a large error is possible between the retrieved and in-situ spectra. The efficiency of spectral shape matching has also been explored, using SeaWiFS imagery for turbid waters and compared with that of the standard SeaWiFS atmospheric correction algorithm, which falls in highly turbid waters, due to the assumption that values of water-leaving radiance in the two NIR bands are negligible to enable retrieval of aerosol reflectance in the correction of ocean color imagery. Validation suggests that accurate the retrieval of water-leaving radiance is not feasible with the invalid assumption of the classical algorithms, but is feasible with SSMM.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.64-78
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• 2019

This paper explores key factors affecting taxi travel using global positioning system(GPS) data in Seoul, Korea, considering spatial dependence. We first analyzed the travel characteristics of taxis such as average travel time, average travel distance, and spatial distribution of taxi trips according to the time of the day and the day of the week. As a result, it is found that the most taxi trips were generated during the morning peak time (8 a.m. to 9 a.m.) and after the midnight (until 1 a.m.) on weekdays. The average travel distance and travel time for taxi trips were 5.9 km and 13 minutes, respectively. This implies that taxis are mainly used for short-distance travel and as an alternative to public transit after midnight in a large city. In addition, we identified that taxi trips were spatially correlated at the traffic analysis zone(TAZ) level through the Moran's I test. Thus, spatial regression models (spatial-lagged and spatial-error models) for taxi trips were developed, accounting for socio-demographics (such as the number of households, the number of elderly people, female ratio to the total population, and the number of vehicles), transportation services (such as the number of subway stations and bus stops), and land-use characteristics (such as population density, employment density, and residential areas) as explanatory variables. The model results indicate that these variables are significantly associated with taxi trips.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.48-55
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• 2022

The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

• Journal of IKEEE
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• v.27 no.3
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• pp.345-349
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• 2023

In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.

• Journal of the Korea Institute of Building Construction
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• v.23 no.4
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• pp.417-428
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• 2023

The demolition of domestic infrastructures mirrors other significant construction initiatives in presenting a markedly high accident rate. A comprehensive investigation into the origins of such accidents is crucial for the prevention of future incidents. Upon detailed inspection, the causes of demolition construction accidents are multifarious, encompassing unsafe worker behavior, hazardous conditions, psychological and physical states, and site management deficiencies. While statistics relating to demolition construction accidents are consistently collated and reported, there exists an exigent need for a more foundational cause categorization system based on accident type. Drawing from Heinrich's Domino Theory, this study classifies the origins of accidents(unsafe behavior, unsafe conditions) and human errors(human factors) as per the type of accidents experienced during demolition construction. In this study, a three-step model of QFD-FMEA(Quality Function Deployment - Failure Mode Effect Analysis) is employed to systematically categorize accident causes according to the types of accidents that occur during demolition construction. The QFD-FMEA method offers a technique for cause classification at each stage of the demolition process, including direct causes(unsafe behavior, unsafe environment), and human errors(human factors) through a tri-stage process. The results of this accident cause classification can serve as safety knowledge and reference checklists for accident prevention efforts.