• Proceedings of the KIEE Conference
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• 2006.10a
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• pp.97-98
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• 2006

High current behaviors of extended drain n-type metal-oxide-semiconductor field effects transistor (EDNMOS) with double polarity source (DPS) for electrostatic discharge (ESD) protection are analyzed. Simulation based contour analyses reveal that combination of bipolar junction transistor operation and deep electron channeling induced by high electron injection gives rise to the second on-state. Therefore, the deep electron channel formation needs to be prevented in order to realize stable and robust ESD protection performance. Based on our analyses, general methodology to avoid the double snapback and to realize stable ESD protection is to be discussed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.97-98
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• 2006

High current behaviors of the grounded gate extended drain N-type metal-oxide-semiconductor field effects transistor (GG_EDNMOS) electro-static discharge (ESD) protection devices are analyzed. Simulation based contour analyses reveal that combination of BJT operation and deep electron channeling induced by high electron injection gives rise to the 2-nd on-state. Thus, the deep electron channel formation needs to be prevented in order to realize stable and robust ESD protection performance. Based on our analyses, general methodology to avoid the double snapback and to realize stable ESD protection is to be discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2359-2376
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• 2022

With the exponential growth of medical image big data represented by high-resolution CT images(CTI), the high-resolution CTI data is of great importance for clinical research and diagnosis. The paper takes lung CTI as an example to study. Retrieving answer CTIs similar to the input one from the large-scale lung CTI database can effectively assist physicians to diagnose. Compared with the conventional content-based image retrieval(CBIR) methods, the CBIR for lung CTIs demands higher retrieval accuracy in both the contour shape and the internal details of the organ. In traditional supervised deep learning networks, the learning of the network relies on the labeling of CTIs which is a very time-consuming task. To address this issue, the paper proposes a Weakly Supervised Similarity Evaluation Network (WSSENet) for efficiently support similarity analysis of lung CTIs. We conducted extensive experiments to verify the effectiveness of the WSSENet based on which the CBIR is performed.

• Journal of the Korean Geosynthetics Society
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• v.16 no.4
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• pp.191-210
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• 2017

The concern study, present the results of experimental study on the performance of deep excavation by using image processing technique particle image velocimetry (PIV). The purpose of present study is to check the application of PIV for the successive ground deformation during deep excavation. To meet the objectives of concern study, a series of reduce scale model test box experiments are performed by considering the wall stiffness, ground water table effect and ground relative density. The results are presented in form of contour and vector plots and further based on PIV analysis wall and ground displacement profile are drawn. The results of present study, indicate that, the PIV technique is useful to demonstrate the ground deformation zone during the successive ground excavation as the degree of accuracy in PIV analysis and measured results with LVDT are within 1%. Further the vector and contours plot effectively demonstrate the ground behavior under different conditions and the PIV analysis results fully support the measured results.

• Archives of Reconstructive Microsurgery
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• v.24 no.1
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• pp.32-36
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• 2015

The reconstruction of recurrent pressure sores is challenging due to a limited set of treatment options and a high risk of flap loss. Successful treatment requires scrupulous surgical planning and a multidisciplinary approach. Although the tensor fascia lata flap is regarded as the standard treatment of choice-it provides sufficient tissue bulk for a deep trochanteric sore defect-plastic surgeons must always consider the potential of recurrence and accordingly save the second-best tissues. With the various applications of anterolateral thigh (ALT) flaps in the reconstructive field, we report two cases wherein an alternative technique was applied, whereby pedicled ALT fasciocutaneous island flaps were used to cover recurrent trochanteric pressure sores. The postoperative course was uneventful without any complications. The flap provided a sound aesthetic result without causing a dog-ear formation or damaging the lower-leg contour. This flap was used as an alternative to myocutaneous flaps, as it can cover a large trochanteric defect, recurrence is minimized, and the local musculature and lower-leg contour are preserved.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.10
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• pp.2187-2193
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• 2002

We present a novel method for 3D microfabrication with LIGA process that utilizes a deep X-ray mask in which a micro-actuator is integrated. The integrated micro-actuator oscillates the X-ray absorber, which is formed on the shuttle mass of the micro-actuator, during X-ray exposures to modify the absorbed dose profile in X-ray resist, typically PMMA. 3D PMMA microstructures according to the modulated dose contour are revealed after GG development. An X-ray mask with integrated comb drive actuator is fabricated using deep reactive ion etching, absorber electroplating, and bulk micromachining with silicon-on-insulator (SOI) wafer. 1mm $\times$ 1 mm, 20 $\mu$m thick silicon shuttle mass as a mask blank is supported by four 1 mm long suspension beams and is driven by the comb electrodes. A 10 $\mu$m thick, 50 $\mu$m line and spaced gold absorber pattern is electroplated on the shuttle mass before the release step. The fundamental frequency and amplitude are around 3.6 kHz and 20 $\mu$m, respectively, for a do bias of 100 V and an ac bias of 20 $V_{p-p}$ (peak-peak). Fabricated PMMA microstructure shows 15.4 $\mu$m deep, S-shaped cross section in the case of 1.6 kJ $cm^{-3}$ surface dose and GG development at 35$^{\circ}C$ for 40 minutes.

• Structural Engineering and Mechanics
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• v.77 no.1
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• pp.47-56
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• 2021

This paper deals with damage detection using a Gapped Smoothing Method (GSM) combined with deep learning. Convolutional Neural Network (CNN) is a model of deep learning. CNN has an input layer, an output layer, and a number of hidden layers that consist of convolutional layers. The input layer is a tensor with shape (number of images) × (image width) × (image height) × (image depth). An activation function is applied each time to this tensor passing through a hidden layer and the last layer is the fully connected layer. After the fully connected layer, the output layer, which is the final layer, is predicted by CNN. In this paper, a complete machine learning system is introduced. The training data was taken from a Finite Element (FE) model. The input images are the contour plots of curvature gapped smooth damage index. A free-free beam is used as a case study. In the first step, the FE model of the beam was used to generate data. The collected data were then divided into two parts, i.e. 70% for training and 30% for validation. In the second step, the proposed CNN was trained using training data and then validated using available data. Furthermore, a vibration experiment on steel damaged beam in free-free support condition was carried out in the laboratory to test the method. A total number of 15 accelerometers were set up to measure the mode shapes and calculate the curvature gapped smooth of the damaged beam. Two scenarios were introduced with different severities of the damage. The results showed that the trained CNN was successful in detecting the location as well as the severity of the damage in the experimental damaged beam.

• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.443-450
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• 2018

The Geant 4 simulated the linear accelerator (VARIAN CLINAC) based on the previously implemented BEAMnrC data, using the head structure of the linear accelerator. In the 10 MV photon flux, Geant4 was compared with the measured value of the percentage of the deep dose and the lateral dose of the water phantom. In order to apply the dose calculation to the body part, the actual patient's lung area was scanned at 5 mm intervals. Geant4 dose distributions were obtained by irradiating 10 MV photons at the irradiation field ($5{\times}5cm^2$) and SAD 100 cm of the water phantom. This result is difficult to measure the dose absorbed in the actual lung of the patient so the doses by the treatment planning system were compared. The deep dose curve measured by water phantom and the deep dose curve calculated by Geant4 were well within ${\pm}3%$ of most depths except the build-up area. However, at the 5 cm and 20 cm sites, 2.95% and 2.87% were somewhat higher in the calculation of the dose using Geant4. These two points were confirmed by the geometry file of Genat4, and it was found that the dose was increased because thoracic spine and sternum were located. In cone beam CT, the dose distribution error of the lungs was similar within 3%. Therefore, if the contour map of the dose can be directly expressed in the DICOM file when calculating the dose using Geant4, the clinical application of Geant4 will be used variously.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.33 no.6
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• pp.525-528
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• 2011

A deep circumflex iliac artery (DCIA) flap is usually used for reconstruction in oral and maxillo-facial surgery department since introduced by O'Brien in 1975. Various flap designs are possible for osteomusculocutaneous, musculocutaneous, musculosseous and vascularized bone types. Iliac crest shape is similar to contour of mandible. Moreover, though a fibular flap has only 15~20 mm of cutting plane width, a DCIA flap contains much more bone amount, making this a similar reconstruction compare with normal mandible. A 68 year-old male with squamous cell carcinoma on the anterior floor of the mouth had an impression with T2N0Mx and the treatment procedure was DCIA reconstruction after wide resection and marginal mandibulectomy, with both supraomohyoid neck dissection. We present an experience of DCIA flap for reconstruction with a literature review.

• Smart Structures and Systems
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• v.23 no.4
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• pp.359-371
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• 2019

As part of a structural health monitoring system, the relative geometric relationship between a ship and bridge has been recognized as important for bridge authorities and ship owners to avoid ship-bridge collision. This study proposes a novel computer vision method for the real-time geometric parameter identification of moving ships based on a single shot multibox detector (SSD) by using transfer learning techniques and monocular vision. The identification framework consists of ship detection (coarse scale) and geometric parameter calculation (fine scale) modules. For the ship detection, the SSD, which is a deep learning algorithm, was employed and fine-tuned by ship image samples downloaded from the Internet to obtain the rectangle regions of interest in the coarse scale. Subsequently, for the geometric parameter calculation, an accurate ship contour is created using morphological operations within the saturation channel in hue, saturation, and value color space. Furthermore, a local coordinate system was constructed using projective geometry transformation to calculate the geometric parameters of ships, such as width, length, height, localization, and velocity. The application of the proposed method to in situ video images, obtained from cameras set on the girder of the Wuhan Yangtze River Bridge above the shipping channel, confirmed the efficiency, accuracy, and effectiveness of the proposed method.