• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.30 no.1
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• pp.65-68
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• 2004

CyberKnife is a stereotactic radiosurgery system which could be used to treat many tumors and lesions. It provides the surgeon unparalleled flexibility in targeting using a compact light linear accelerator mounted on a robotic arm. Advanced image guidance technology tracks patient and target position during treatment, ensuring accuracy without the use of an invasive head frame. CyberKnife with Dynamic Tracking Software is cleared to provide radiosurgery for lesions anywhere in the body when radiation treatment is indicated. It has often been used to radiosurgically treat otherwise untreatable tumors and malformations. Moreover, this instrument treats tumors at body sites, most of which are unreachable by other stereotactic systems. Compared with conventional radiotherapy, it is fundamentally different that using non-invasive, frameless, no excessive radiation exposure to normal tissue. In oral malignant neoplasm, surgical excision and radiation therapy should be tried first, additionally chemotherapy could be considered. However, after failure of conventional therapies, patients had poor systemic condition and surgical limitation. So, CyberKnife could be a suitable therapy. A 49 years man was referred in recurred mandibular cancer treated by radiotherapy. The tumor was considered inoperable, because of extensive invasion and was not expected to good response to conventional therapies. We experienced a case of CyberKnife after 4 cycle chemotherapies, so we report it with review of literature.

• Journal of the Korean Geotechnical Society
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• v.30 no.10
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• pp.45-54
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• 2014

Many studies have been made on investigation, design, explanation and treatments etc. to minimize slope failure. However, the problem is that failures of cutting slope and natural slope due to Typhoon and localized heavy rainfall are still not reduced. It is difficult to treat the problem by only strengthening the design standard. And it is very necessary to carry out design and safety analysis under the most suitable conditions considering foundation and rainfall characteristics. In this study, variations of safety factor were discussed from different aspects to investigate the influence of different parameters of rainfall and analysis conditions. Rainfall and foundation conditions are supposed to be the most sensitive parameters to slope stability, and numerical analysis were performed by changing parameters of the two conditions. Rainfall behavior is based on the domestic statistical rainfall and foundation condition is selected as unsaturated soils. Study results show that, application of rainfall characteristics in different area and parameters of unsaturated soils are responding sensitively to variations of slope safety. Therefore, the input parameters should be fully examined when performing the practical design.

• Geomechanics and Engineering
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• v.12 no.1
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• pp.161-183
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• 2017

This paper investigates the damage identification of the concrete pile element through axial wave propagation technique using computational and experimental studies. Now-a-days, concrete pile foundations are often common in all engineering structures and their safety is significant for preventing the failure. Damage detection and estimation in a sub-structure is challenging as the visual picture of the sub-structure and its condition is not well known and the state of the structure or foundation can be inferred only through its static and dynamic response. The concept of wave propagation involves dynamic impedance and whenever a wave encounters a changing impedance (due to loss of stiffness), a reflecting wave is generated with the total strain energy forked as reflected as well as refracted portions. Among many frequency domain methods, the Spectral Finite Element method (SFEM) has been found suitable for analysis of wave propagation in real engineering structures as the formulation is based on dynamic equilibrium under harmonic steady state excitation. The feasibility of the axial wave propagation technique is studied through numerical simulations using Elementary rod theory and higher order Love rod theory under SFEM and ABAQUS dynamic explicit analysis with experimental validation exercise. Towards simulating the damage scenario in a pile element, dis-continuity (impedance mismatch) is induced by varying its cross-sectional area along its length. Both experimental and computational investigations are performed under pulse-echo and pitch-catch configuration methods. Analytical and experimental results are in good agreement.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.763-768
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• 2005

Bare-chip packaging becomes more popular along with the miniaturization of IT components. In this paper, we have studied flip-chip process, and developed automated bonding system. Among the several bonding method, NCP bonding is chosen and batch-type equipment is manufactured. The dual optics and vision system aligns the chip with the substrate. The bonding head equipped with temperature and force controllers bonds the chip. The system can be easily modified for other bonding methods such as ACF In bonding process, the bonding forte and temperature are known as the most dominant bonding parameters. A parametric study is performed for these two parameters. For the test sample, we used standard flip-chip test kit which consists of FR4 boards and dummy flip-chips. The bonding test was performed fur two types of flip-chips with different chip size and lead pitch. The bonding temperatures are chosen between $25^{\circ}C\;to\;300^{\circ}C$. The bonding forces are chosen between 5N and 300N. The bonding strength is checked using bonding force tester. After the bonding force test, the samples are examined by microscope to determine the failure mode. The relations between the bonding strength and the bonding parameters are analyzed and compared with bonding models. Finally, the most suitable bonding condition is suggested in terms of temperature and force.

• Structural Engineering and Mechanics
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• v.86 no.6
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• pp.715-730
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• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11B
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• pp.946-955
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• 2004

It is shown that the do Bruijn graph (dBG) can be used as an architecture for interconnection network and a suitable structure for parallel computation. Recent works have classified dBG based routing algorithms into shortest path routing and fault tolerant routing but investigation into fault free shortest path (FFSP) on dBG has been non-existent. In addition, as the size of the network increase, more faults are to be expected and therefore shortest path dBG algorithms in fault free mode may not be suitable routing algorithms for real interconnection networks, which contain several failures. Furthermore, long fault free path may lead to high traffic, high delay time and low throughput. In this paper we investigate routing algorithms in the condition of existing failure, based on the Bidirectional do Bruijn graph (BdBG). Two FFSP routing algorithms are proposed. Then, the performances of the two algorithms are analyzed in terms of mean path lengths and discrete set mean sizes. Our study shows that the proposed algorithms can be one of the candidates for routing in real interconnection networks based on dBG.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.569-576
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• 2007

Ventricular Assist Device(VAD) has switched its goal from a short-tenn use for bridge-to-transplantation to a long-tenn use for destination therapy, With this goal, the importance of long-tenn reliability gets more interests and importances, H-VAD is an portable extracorporeal biventricular assist device, and adopts an electro-pneumatic driving mechanism. The pneumatic pressure to pump out blood is generated with compression of bellows, and is transmitted in a closed pneumatic circuit through a pneumatic line. The existing pneumatic VAD adopts a air compressor which can generate stable pressures but has defects such as a noise and a size problem. Thus, it is not suitable for being used as a portable device, These problems are covered with adopting a closed pneumatic circuit mechanism with a bellows which has a small size and small noise generation, but it has defects that improper pneumatic setting causes a failure of adequate flow generation. In this study, the pneumatic pressure regulation system is developed to cover these defects of a bellows-type pneumatic VAD. The optimal pneumatic pressure conditions according to various afterload conditions for an optimal flow rate were investigated and the afterload estimation algorithm was developed, The final pneumatic regulation system estimates a current afterload and regulate the pneumatic pressure to the optimal point at a given afterload condition. The afterload estimation algorithm showed a sufficient performance that the standard deviation of error is 8.8 mmHg, The pneumatic pressure regulation system showed a sufficient performance that the flow rate was stably governed to various afterload conditions. In a further study, if a additional sensor such as ultrasonic sensor is developed to monitor the direct movement of diaphragm in a blood pump part, the reliability would be greatly increased. Moreover, if the afterload estimation algorithm gets more accuracy, it would be also helpful to monitor the hemodynamic condition of patients.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.299-306
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• 2019

In this study, a model experiment that simulates the behaviour of the ground composed of several compacted layer was intended to measure the loosened area in the event of a ground cavity through a LAD (Loosened area detector). It was confirmed that the size of the cone diameter was affected by the ground composed of fine grain + granulated soil layered through the model soil. In order to select the appropriate cone type, a scale effect experiment was conducted. From the test results, a micro-cone was chosen for the most suitable indoor model experiment. In the case of applying LAD in this study, the loosening condition of the ground was determined by the rapid change in penetration resistance caused by the difference in the boundary surface and relative density due to the compaction of the ground for indoor model testing. The range of loosened area occurring in the cavity was estimated through the penetration resistance characteristics on the ground, and the failure area was identified through the reduction rate of penetration resistance in the loosening area.

• Journal of Periodontal and Implant Science
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• v.48 no.4
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• pp.213-223
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• 2018

Purpose: Oral lichen planus (OLP) is a chronic oral mucosal disease that has been recognized as an immune condition. The purpose of this study was to evaluate factors affecting the clinical outcomes of topical corticosteroid application on OLP lesions using dexamethasone gargle and ointment. Methods: The charts of patients who were clinically diagnosed with OLP and treated with dexamethasone from July 2003 to August 2017 at the Section of Dentistry of Seoul National University Bundang Hospital were thoroughly evaluated to identify subjects who were suitable for this retrospective study. For each patient, age at the index date, gender, medical history, and dental records related to OLP lesions and dexamethasone treatment were reviewed. Results: In total, 113 of the 225 patients were included in the present study. Among them, 79 patients were female (69.9%) and 34 were male (30.1%), with a mean age of 57.6 years. The average duration of dexamethasone treatment was 4.7 months and the mean follow-up period was 2.24 years. Improvements were observed within 1 year after dexamethasone treatment in most cases, and 17.7% of patients had a new OLP lesion after treatment. New OLP lesions were more frequently gingival than mucosal, although mucosal OLP lesions were more common than gingival OLP lesions in all age groups. In age- and gender-adjusted multivariate logistic regression, a history of malignant disease was found to be a significant factor affecting the formation of new lesions. Gingival OLP lesions and intermittent use of dexamethasone showed near-significant associations. In Kaplan-Meier failure analysis, history of malignancy, menopausal status, age, and the site of the OLP lesion were significant factors affecting clinical outcomes. Conclusions: The treatment outcomes of OLP were significantly influenced by age, history of malignancy, menopausal status, and the site of the OLP lesion, but not by factors related to dexamethasone treatment.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.