• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.392-399
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• 2005

Shear modulus (or rigidity) of dam material is an important parameter which can be directly associated with the deformation of dam. Seepage or leakage of water can cause the defects or cracks of dam body. The existence of cracks and rigidity of dam body are decisive information for the estimation of dam safety. Rigidity of material is mainly determined from S-wave velocity and the defects of dam body can be detected by seismic reflection survey. Therefore, seismic reflection survey will be a desirable method which can give a solution about dam safety problem. Among various physical properties of dam body, S-wave velocity is the most important information but it is not easy to get the information. In this study, diverse measuring techniques of S-wave reflection survey were attempted to get the information about S-wave velocity of dam body. Ultimately, S-wave velocity could be estimated by the analysis of SH reflection events which can be easily observed in shot gather data obtained from SH measuring technique. Meanwhile, P-wave reflection survey was also performed at the same profile. P-beam radiation technique which can reduce the surface waves and reinforce the P-wave reflection events was applied for giving a help to analyse P-wave velocity. In the end, P-and S-wave velocity, Vs/Vp, Poisson's ratio distribution of the vertical section under the profile could be acquired.

• Journal of the Korean Ceramic Society
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• v.44 no.9
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• pp.529-535
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• 2007

Calcium oxide has been used as a demolition agent in fracturing rocks and old concrete structures, etc. With the agent, demolition work can be done in safety without a noise, vibration and any other pollution, since high expansive pressure is obtained gradually by only mixing the agents with water and pouring the slurry into boreholes. But application of the non-explosive demolition agent is a time-consuming job, especially in winter. Essentially, this problem is related to the reaction rate of calcium oxide with water. This study examines the influence of additives such as cement and anhydrite on expansion pressure of calcium oxide at different curing temperatures. The expansion pressure of calcium oxide began to increase steadily with the rise of the curing temperature. When mixing calcium oxide alone with water, blown-out shot occurred. But as additives were added to calcium oxide, the reaction of calcium oxide delayed and the expansion pressure showed gradual increment. Especially, anhydrite showed a superior delaying effect than cement on the reaction of calcium oxide.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.218.2-218.2
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• 2012

In the remote sensing researches, the reflected bright source such as snow, cloud have effects on the image quality of wanted signal. Even though those signal from bright source are adjusted in corresponding pixel level with atmospheric correction algorithm or radiometric correction, those can be problem to the nearby signal as one of the stray light source. Especially, in the step and stare observational method which makes one mosaic image with several snap shots, one of target area can affect next to the other snap shot each other. Presented in this paper focused on the stray light analysis from unwanted reflected bright source for geostationary ocean color sensor. The stray light effect for total 16 slot images each other were performed according to 8 band filters. For the realistic simulation, we constructed system modeling with integrated ray tracing technique which realizes the same space time in the remote sensing observation among the Sun, the Earth, and the satellite. Computed stray light effect in the results of paper demonstrates the distinguishable radiance value at the specific time and space.

• Design & Manufacturing
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• v.11 no.3
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• pp.19-24
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• 2017

In these days, increase requirement of TEM (Transmission Electro Microscope) in not only scientific field but also industrial field. Because TEM can measure inner-structure of specimen a variety of materials like metal, bio. etc. When use TEM, specimen should be thin about 50nm. So making for thin specimen, use Ion milling device that include specimen holder. The holder generally made of Aluminium Aluminium holder is worn away easily. For this reason, using time of ion milling with aluminum holder is too short. To solve the problem, we replace aluminium holer to molybdenum alloy holder. In this paper, we design molybdenum alloy holer for CAM and modify CAD modeling for effective machining process. So we array a specimen 3 by 4 and setup orientation for one-shot machining process. Next we make a CAM program for machining. we making a decision two machining strategy that chose condition of tool-path method, step-down, step-over. etc. And then conduct machining using CNC milling machining center. To make clear difference between case.1 and case.2, we fixed machining conditions like feed-rate, main spindle rpm, etc. After machining, we confirm the condition of workpiece and analysis the problems case by case. Finally, case.2 work piece that superior than case.1 cutting with WEDM because that method can not ant mechanical effect on workpiece.

• Archives of Reconstructive Microsurgery
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• v.7 no.1
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• pp.35-40
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• 1998

The incidence of brachial plexus injury is increasing because of the development of motor vehicle but the the results of treatment was reported poor due to its complex anatomical structure and changes of function and sensory during the recovery after trauma. But the results of treatment has been improved by the recently introduced high sensitive diagnostic method that can evaluate accurately the site and extent of the injury and treatment method. Restoration of the elbow flexion is the most important goal of treatment after brachial plexus injury and nerve graft, neurotization and muscle transfer were used for methods of treatment. From December 1992 to May 1994, the author performed 6 cases of latissimus dorsi transfer at the same side for the improvement of elbow flexion in the patients of brachial plexus injury. There were 5 cases of male, one case of female and average age was 22 years old. The causes of injury were traffic accident in 3 cases, gun shot injury, falldown and birth injury in each one case and in all cases, the type of injury were upper arm type. The average follow up period were 1 year 5 months ranging from 12 months to 4 years 5 months. In all cases, active elbow flexion was impossible before operation and average muscle power was grade I. We analysed the active range of motion, muscle power and the functional results. At the last follow up, range of active elbow flexion was average $124^{\circ}$ and flexion contracture was average 11 degrees and the average of muscle power was grade IV. In the functional analysis, there were two cases of excellent, three cases of good and 1 case of fair. There was no complications including wound infection, vascular compromise and donor site problem. The results of latissimus dorsi transfer for improvement elbow flexion in the patients of brachial plexus injury is one of the useful mettled for the restoration of elbow flexion.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4431-4440
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• 2022

An advanced nuclear reactor based on molten salts including a molten salt reactor and pyroprocessing needs a sensitive monitoring system suitable for operation in harsh environments with limited access. Multi-element detection is challenging with the conventional technologies that are compatible with the in-situ operation; hence laser-induced breakdown spectroscopy (LIBS) has been investigated as a potential alternative. However, limited precision is a chronic problem with LIBS. We increased the precision of LIBS under high temperature by protecting optics using a gas protective layer and correcting for shotto-shot variance and lens-to-sample distance using a laser-induced acoustic signal. This study investigates cerium as a surrogate for uranium and corrosion products for simulating corrosive environments in LiCl-KCl. While the un-corrected limit of detection (LOD) range is 425-513 ppm, the acoustic-corrected LOD range is 360-397 ppm. The typical cerium concentrations in pyroprocessing are about two orders of magnitude higher than the LOD found in this study. A LIBS monitoring system that adopts these methods could have a significant impact on the ability to monitor and provide early detection of the transient behavior of salt composition in advanced molten salt-based nuclear reactors.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.97-105
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• 2020

Recently, Artificial Neural Network receives attention as a data prediction method. Among these, a Long Shot-term Memory (LSTM) model specialized for time-series data prediction was utilized as a prediction method of hydrological time series data. In this study, the LSTM model was constructed utilizing deep running open source library TensorFlow which provided by Google, to predict inflows of multipurpose dams. We predicted the inflow of the Yongdam Multipurpose Dam which is located in the upper stream of the Geumgang. The hourly flow data of Yongdam Dam from 2006 to 2018 provided by WAMIS was used as the analysis data. Predictive analysis was performed under various of variable condition in order to compare and analyze the prediction accuracy according to four learning parameters of the LSTM model. Root mean square error (RMSE), Mean absolute error (MAE) and Volume error (VE) were calculated and evaluated its accuracy through comparing the predicted and observed inflows. We found that all the models had lower accuracy at high inflow rate and hourly precipitation data (2006~2018) of Yongdam Dam utilized as additional input variables to solve this problem. When the data of rainfall and inflow were utilized together, it was found that the accuracy of the prediction for the high flow rate is improved.

• Journal of the Earthquake Engineering Society of Korea
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• v.10 no.2 s.48
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• pp.39-50
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• 2006

Site response analyses were peformed based on equivalent linear technique using the shear wave velocity profiles of 162 sites collected around the Korean Peninsula. The she characteristics, particularly the shear wave velocities and the depth to bedrock, are compared to those in the western United States. The site coefficients of short period $(F_a)$ and the long period $(F_v)$ obtained from this study were significantly different compared to 1997 Uniform Building Code (1997 UBC). $F_a$ underestimated the motion in shot period ranges and $F_v$ overestimated the motion in mid period ranges in Korean seismic guideline. It is found that the existing Korean seismic design code were is required to be modified considering geological site conditions in Korea for the reliable estimation of sue amplification. Problems of the current seismic design code were dicussed in this paper and the development of site classification method and modification of desing response spectra were discussed in the companion papers(II-Development of Site Classification System and III-Modification of Dosing Response Specra).

• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.119-133
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• 2019

Recently, the importance prediction of photovoltaic power (PV) is considered as an essential function for scheduling adjustments, deciding on storage size, and overall planning for stable operation of PV facility systems. In particular, since most of PV power is generated in peak time, PV power prediction in a peak time is required for the PV system operators that enable to maximize revenue and sustainable electricity quantity. Moreover, Prediction of the PV power output in peak time without meteorological information such as solar radiation, cloudiness, the temperature is considered a challenging problem because it has limitations that the PV power was predicted by using predicted uncertain meteorological information in a wide range of areas in previous studies. Therefore, this paper proposes the LSTM (Long-Short Term Memory) based the PV power prediction model only using the meteorological, seasonal, and the before the obtained PV power before peak time. In this paper, the experiment results based on the proposed model using the real-world data shows the superior performance, which showed a positive impact on improving the PV power in a peak time forecast performance targeted in this study.