• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.62-63
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• 2006

Both densification and grain growth are driven by the reduction of the interfacial area, kinetics of which depends strongly on the interface structure. Abnormal grain coarsening in the system of singular solid/liquid interface such as WC-Co alloys was explained by the growth mechanism of 2-dimensional nucleation. Based on this concept, the marked inhibition of coarsening of WC grains by VC addition can be approached by the increase in the step free energy, which increases the barrier of 2-dimensional nucleation. The activated sintering in tungsten powders can be approached by the interface structure change induced by the addition of a small amount of nickel.

• Journal of Ginseng Research
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• v.39 no.1
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• pp.1-6
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• 2015

Abnormal changes in skin color induce significant cosmetic problems and affect quality of life. There are two groups of abnormal change in skin color; hyperpigmentation and hypopigmentation. Hyperpigmentation, darkening skin color by excessive pigmentation, is a major concern for Asian people with yellowe-brown skin. A variety of hypopigmenting agents have been used, but treating the hyperpigmented condition is still challenging and the results are often discouraging. Panax ginseng has been used traditionally in eastern Asia to treat various diseases, due to its immunomodulatory, neuroprotective, antioxidative, and antitumor activities. Recently, several reports have shown that extract, powder, or some constituents of ginseng could inhibit melanogenesis in vivo or in vitro. The underlying mechanisms of antimelanogenic properties in ginseng or its components include the direct inhibition of key enzymes of melanogenesis, inhibition of transcription factors or signaling pathways involved in melanogenesis, decreasing production of inducers of melanogenesis, and enhancing production of antimelanogenic factor. Although there still remain some controversial issues surrounding the antimelanogenic activity of ginseng, especially in its effect on production of proinflammatory cytokines and nitric oxide, these recent findings suggest that ginseng and its constituents might be potential candidates for novel skin whitening agents.

• Journal of the Korean Medical Association
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• v.61 no.11
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• pp.638-642
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• 2018

Surgery is a very hands-on area of medical care, in that surgeons identify problems in patients' bodies and directly change them through operations. Therefore, it is not only necessary for surgeons to have a high level of expertise, but also to take considerable responsibility for the outcomes of each operation. However, surgery, which was once an object of envy, has long been a process to avoid, due to various circumstances, such as abnormal medical expenses in the medical field and social phenomena that avoids difficult work. It is unfortunate that medical professionals do not receive sympathy from others within the same medical field because of the general difficulties of the profession. The fundamental problem in this situation is the abnormal profit structure of the Korean medical system. Efforts by various related organizations will be needed to objectively evaluate the problems of the current medical insurance system and to make reasonable adjustments considering the difficulty, frequency, and resource-intensiveness of medical care.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.2_1
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• pp.169-176
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• 2022

Prognostics and health management (PHM) is recently converging throughout the industry, one of the trending issue is to detect abnormal conditions at decanter centrifuge during water treatment facilities. Wastewater treatment operation produces corrosive gas which results failures on attached sensors. This scenario causes frequent sensor replacement and requires highly qualified manager's visual inspection while replacing important parts such as bearings and screws. In this paper, we propose anomaly detection by measuring the vibration of the decanter centrifuge based on the video camera images. Measuring the vibration of the screw decanter by applying the optical flow technique, the amount of movement change of the corresponding pixel is measured and fed into the LST M model. As a result, it is possible to detect the normal/warning/dangerous state based on LSTM classification. In the future work, we aim to gather more abnormal data in order to increase the further accuracy so that it can be utilized in the field of industry.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.109-117
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• 2022

This paper proposes a method for detecting flight anomalies of drones through the difference between the command of flight controller (FC) and the navigation solution. If the drones make a flight normally, control errors generated by the difference between the desired control command of FC and the navigation solution should converge to zero. However, there is a risk of sudden change or divergence of control errors when the FC control feedback loop preset for the normal flight encounters interferences such as strong winds or navigation sensor abnormalities. In this paper, we propose the method with a deep neural network model that predicts the control error in the normal flight so that the abnormal flight state can be detected. The performance of proposed method was evaluated using the real-world flight data. The results showed that the method effectively detects anomalies in various situation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.295-296
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• 2021

In iris diagnostics, iris changes in its area on the iris map when abnormal changes in human tissues and organs occur in response to changes in color and iris structure. This makes it possible to determine the long-term condition in which an abnormal change has occurred, and to determine the presence or absence of a congenital illness. In this paper, we design a neural network algorithm that is displayed on the iris and classifies lesions by using a convolution neural network that has the advantage of advancing learning using images of various dip-running neural networks.

• Korean Management Science Review
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• v.27 no.3
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• pp.161-196
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• 2010

This paper empirically investigates the impact of winning a service quality award on the market value in Korea. We estimates the mean "abnormal" change in the stock prices of sample firms when information of winning a service quality award was publicly announced. To access the validity of the research question, this paper employed collected 47 firms data that received the Korean Service Quality Awards so far. Event study methodology was used to analyze the effect of Korean service quality awards. The findings are as follows; The average abnormal returns on the event date are not significant at the 0.05 level which means that the receiving Korean Service Quality Awards has no influence on the firms' market value. On the other hand successive awarded firms have an increasing effect on the market value and it is significant at the 0.05 level. Furthermore, the results show that the factors of firm size such as firm's total assets are critical to vary the firms' abnormal returns. There might be some limitations in this study. The most obvious problem is the limitation of sample size. Although 518 sample cases were found during the period from 2000 to 2008, most of the cases were deleted according to the sample criteria. We are expecting the future research with more data and more precise results. Furthermore, our research consider the only two service award institutions even though there are several different service award authorities in Korea. It is needed to expand the research scope and range to adopt the various service award institutions for the future work.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.9-10
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• 2002

Human circulatory system between heart and tissue is not directly connected in normal condition but mandatory to go through the capillary system in order to fulfill its physiologic aim to deliver oxygen and nutrients, etc. to the tissue and retrieve used blood together with waste products from the tissue properly. When abnormal connection between arterial and venous system (AV fistula), these two circulatory systems respond differently to the hemodynamic impact of this abnormal connection between high pressure (artery) and low pressure (vein) system. Depending upon the location and/or degree (e.g. size and flow) of fistulous condition, each circulatory system exerts different compensatory hemodynamic response to this newly developed abnormal inter-relationship between two systems in order to minimize its hemodynamic impact to own system of different hemodynamic characteristics. Pump action of the heart can assist the failing arterial system directly to maintain arterial circulation against newly established low peripheral resistance by the AV fistula during the compensation period, while it affects venous system in negative way with increased venous loading. However, the negative impact of increased heart action to the venous system is partly compensated by the lymphatic system which is the third circulatory system to assist venous system independently with different hemodynamics. The lymphatic system with own unique Iymphodynamics based on peristaltic circulation from low resistance to high resistance condition, also increases its circulation to assist the compensation of overloaded venous system. Once these compensation mechanisms should fail to fight to newly established hemodynamic condition due to this abnormal AV connection, each system start to show different physiologic ${\underline{de}compensation}$ including heart and lymphatic system. The vicious cycle of decompensation between arterial and vein, two circulatory system affecting each other by mutually negative way steadily progresses to show series of hemodynamic change throughout entire circulation system altogether including heart. Clinical outcome of AV fistula from the compensated status to decompensated status is closely affected by various biological and mechanical factors to make the hemodynmic status more complicated. Proper understanding of these crucial biomechanical factors iii particular on hemodyanmic point of view is mandatory for the advanced assessment of biomechanical impact of AV fistula, since this new advanced concept of AY fistula based on blomechanical information will be able to improve clinical control of the complicated AV fistula, either congenital or acquired.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.15-22
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• 2020

The 4th industrial revolution and the rapid change in the data environment revealed technical limitations in the existing relational database(RDB). As a new analysis method for unstructured data in all fields such as IDC/finance/insurance, interest in graph database(GDB) technology is increasing. The graph database is an efficient technique for expressing interlocked data and analyzing associations in a wide range of networks. This study extended the existing RDB to the GDB model and applied machine learning algorithms (pattern recognition, clustering, path distance, core extraction) to detect new abnormal signs. As a result of the performance analysis, it was confirmed that the performance of abnormal behavior(about 180 times or more) was greatly improved, and that it was possible to extract an abnormal symptom pattern after 5 steps that could not be analyzed by RDB.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.80-92
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• 2023

As cities are becoming densely populated, previously unexpected events such as crimes, accidents, and infectious diseases are bound to affect user demands. With a time-series prediction of demand using information with uncertainty, it is impossible to derive reliable results. In particular, the COVID-19 outbreak in early 2020 caused changes in abnormal travel patterns and made it difficult to predict demand for time series. A methodology that accurately predicts demand by detecting and reflecting these changes is, therefore, required. The current study suggests a time series modeling pipeline that automatically detects and predicts abnormal events caused by COVID-19. We expect its wide application in various situations where there is a change in demand due to irregular and abnormal events.