• Archives of Reconstructive Microsurgery
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• v.21 no.1
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• pp.8-13
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• 2012

Purpose: Purpose: The free deep inferior epigastric artery perforator (DIEP) flap is a popular option for autologous breast reconstruction. However, the anatomy of the deep inferior epigastric artery(DIEA) may vary from one individual to another. Unexpected vascular anomaly can confuse the surgeon and affects on the safety of the free DIEP flap. Materials and Methods: Thirty five consecutive patients who underwent free DIEP/TRAM flap for immediate breast reconstruction between Mar. 2010 and Oct. 2010 were enrolled in this study. Computed tomography angiography (CT angiography) of abdomen was evaluated part of our standard preoperative assessment: atypical patterns of DIEA/DIEP were evaluated by preoperative CT angiography and compared with intraoperative finding. Results: Atypical patterns of DIEA/DIEP which may affect preoperative planning were noted as the following: Circummusclar/subfascial DIEA (n=1), DIEA running underneath rectus muscle (n=8), septocutaneous perforator (n=3), peritoneo-cutaneous perforator (n=1), a large branch going into peritoneum (n=1), and very early division and muscle penetration of DIEA (n=1). Conclusion: Atypical DIEA/DIEP that might change the operation plan is not rare, so the individualized planning based on the preoperative CT angiography is recommended. Preoperative CT angiography could help to select reliable and easy-to-dissect perforator in free DIEP/TRAM breast reconstruction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.794-804
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• 2018

Various applications running in computers exchange information in the form of packets through the network. Most packets are formatted into UDP/IP or TCP/IP standard. Network management administrators of enterprises and organizations should be able to monitor and manage packets transmitted over the network for Internet traffic measurement & monitoring, network security, and so on. The goal of this paper is to analyze the performance of several algorithms which closely examine and analyze payloads in a DPI(Deep Packet Inspection) system. The main procedure of packet payload analysis is to quickly search for a specific pattern in a payload. In this paper, we introduce several algorithms which detect a specific pattern in payloads, analyze the performance of them from three perspectives, and suggest an application method suitable for requirements of a given DPI system.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.755-764
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• 2019

Currently commercially available light field cameras are difficult to acquire 5D light field video since it can only acquire the still images or high price of the device. In order to solve these problems, we propose a deep learning based method for synthesizing the light field video from monocular video. To solve the problem of obtaining the light field video training data, we use UnrealCV to acquire synthetic light field data by realistic rendering of 3D graphic scene and use it for training. The proposed deep running framework synthesizes the light field video with each sub-aperture image (SAI) of $9{\times}9$ from the input monocular video. The proposed network consists of a network for predicting the appearance flow from the input image converted to the luminance image, and a network for predicting the optical flow between the adjacent light field video frames obtained from the appearance flow.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.39-46
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• 2019

In recently years, it has become important to detect underground objects of various marterials including metals, such as detecting the location of sink holes and pipe. For this reason, ground penetrating radar(GPR) technology is attracting attention in the field of underground detection. GPR irradiates the radar wave to find the position of the object buried underground and express the reflected wave from the object as image. However, it is not easy to interpret GPR images because the features reflected from various objects underground are similar to each other in GPR images. Therefore, in order to solve this problem, in this paper, to estimate the piping position in the GRP image according to the threshold value using the CNN (Convolutional Neural Network) model based on deep running, which is widely used in the field of image recognition, As a result of the experiment, it is proved that the pipe position is most reliably detected when the threshold value is 7 or 8.

• The Journal of the Convergence on Culture Technology
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• v.4 no.4
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• pp.393-399
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• 2018

The development of unmanned AI continues, and the development of AI unmanned is aimed at more efficiently, accurately, and speedily the work that has been resolved by manpower such as industry, welfare, and manpower. AI unmanned technology is evolving in various places, and it is time to switch to unmanned systems from many industries and factories. We take this into consideration, and use the Deep Learning technology, which is one of the core technologies of artificial intelligence (AI), not the manpower but the fruits that pour the rails at once in a large orchard. We want to study the unmanned fruit sorting machine that can be operated under manager's supervision without dividing the fruit by type and grade and dividing by country of origin and grade. This unmanned automated classification system aims to reduce the labor cost by minimizing the manpower and to improve the

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.8
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• pp.917-922
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• 2019

The recent increase in preference for teacher jobs has led to a rise in preference for education colleges. Not all students can enter teachers, but they must pass the test called the competitive examination for teacher appointment candidates after graduation. However, due to the declining population, the and employment T.O.s are decreasing every year and the competition rate is rising steeply. Therefore, in order to concentrate on the recruitment exam upon entering the university, the university is becoming a huge academy for the exam, not a place to study and learn. We found a connection between students' overall school life and their use of study groups as well as their grades and whether they passed the competition test for teachers using deep running. The academic activities did not significantly affect the acceptance process, and the accuracy of the prediction of the acceptance rate was generally 70% accurate.

• Journal of IKEEE
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• v.22 no.3
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• pp.829-835
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• 2018

Recently, studies have been actively conducted to reduce spare power that is unnecessarily generated or wasted in existing power systems and to improve energy use efficiency. In this study, smart meter, which is one of the element technologies of smart grid, is implemented to improve the efficiency of energy use by controlling power of electric devices, and predicting trends of energy usage based on deep learning. We propose and develop an algorithm that controls the power of the electric devices by comparing the predicted power consumption with the real-time power consumption. To verify the performance of the proposed smart meter based on the deep running, we constructed the actual power consumption environment and obtained the power usage data in real time, and predicted the power consumption based on the deep learning model. We confirmed that the unnecessary power consumption can be reduced and the energy use efficiency increases through the proposed deep learning-based smart meter.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 2002.08a
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• pp.208-211
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• 2002

The Kyunggi Bay (125-l28E, 36-38N) is a macro-tidal bay in the western central port of Korean Peninsula(Fig. 1). The Bay characterizes its feature as wide tidal flats, deep tidal channels and tidal sand ridges running in parallel to tidal flows. The macro-tidal range (up to approximately 8.6m) and consequent strong tidal currents erode the bottom sediment and selectively transport to the low-energy area forming tidal ridges or tidal flats. (omitted)

• The Journal of Korean Academy of Prosthodontics
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• v.15 no.1
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• pp.43-47
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• 1977

The purpose of this study was to determine human pulp reactions to temporary cements such as zinc oxide-eugenol cement, modified zinc oxide-eugenol cement (Cavitec) and calcium hydroxide cement (Dycal). Deep class V cavities were prepared in the human teeth with ultrahigh-speed handpiece operating at a free running speed of 300,000 r.p.m., using # 701 bur and water spray coolant. The cavities were flushed with water, dried with cotton pellets and filled with zinc oxide-eugenol cement, modified zinc oxide-eugenol cement and calcium hydroxide cement respectively. The teeth were divided into two groups, which one group was extracted after One day and the other was extracted after seven days. The samples were examined with microscope and the findings were as follows; 1. The pulp reactions to temporary cements were generally mild. Among them the reactions were moderate in zinc oxide-eugenol cement and, slight in calcium hydroxide cement. 2. Calcium hydroxide cement may be used properly as temporary cement for the purpose of pulp protection.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.1109-1114
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• 2005

The rolling contact fatigue of wheels for high speed trains is a matter of increasing importance. The wheel damages from fatigue crack makes noise up and safety down. RCF-casued accidents cause traffic congestion and economical costs as well as personal injuries. In this study, we examine the rolling contact fatigue of wheels for power car running at 300km/h. Using the results of multi-body dynamic analysis and the proposed procedure of Ekberg, we calculate the fatigue index of surface-initiated fatigue, subsurface-initiated fatigue and fatigue initiated at deep material defects. As a result. the fatigue index shows us whether fatigue will appear and in which form. In addition, we present Shakedown map on surface-initiated fatigue.