• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.357-365
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• 2003

The major problems with the conventional neural network, especially Back Propagation Neural Network, arise from the necessity of many training data for neural network learning and ambiguity in the relation of neural network structure to the convergence of solution. In this paper, the PNN is used as a pattern classifier to detect the damage of structure to avoid those drawbacks of the conventional neural network. In the PNN-based pattern classification problems, the probability density function for patterns is usually assumed by Gaussian distribution. But, in this paper, several probability density functions are investigated in order to select the most approriate one for structural damage assessment.

• Journal of Korean Institute of Fire Investigation
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• v.11 no.1
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• pp.37-40
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• 2008

This paper deals with damage patterns of cabinet panel for low voltage deteriorated by flame. In order to analyze damage patterns, we used Metallurgical Microscope, x-ray system, and Fourier Transform Infrared spectroscopy. Firstly, Metallurgical microscope was used for analysis of electrical causes, such as electric short and overload Secondly, X-ray system was used for analysis of internal characteristics of circuit breakers. Lastly, Fourier Transform Infrared spectroscopy was used for analysis of damage direction by flame.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.04a
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• pp.269-272
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• 2008

This paper deals with damage patterns of cabinet panel for low voltage deteriorated by flame. In order to analyze damage patterns, we used Metallurgical Microscope, x-ray system, and Fourier Transform Infrared spectroscopy. Firstly, Metallurgical microscope was used for analysis of electrical causes, such as electric short and overload. Secondly, X-ray system was used for analysis of internal characteristics of circuit breakers. Lastly, Fourier Transform Infrared spectroscopy was used for analysis of damage direction by flame. The following results were obtained.

• Journal of the Semiconductor & Display Technology
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• v.11 no.3
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• pp.7-11
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• 2012

Among various wet cleaning methods, megasonic and jet spray gained their popularity in single wafer cleaning process for the efficient removal of particulate contaminants from the wafer surface. In the present study, we evaluated these two cleaning methods for particle removal efficiency (PRE) and pattern damage on the aluminum layered wafer surface. Also the effect of $CO_2$ dissolved water in jet spray cleaning is assessed by measuring PRE. It is observed that the jet spray cleaning process is more effective in terms of PRE and pattern damage compared to megasonic cleaning and the mixing of $CO_2$ in the water during jet sprays further increases the PRE. We believe that the outcome of the present study is useful for the semiconductor cleaning process engineers and researchers.

• Journal of Korean Medical classics
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• v.36 no.3
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• pp.27-54
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• 2023

Objectives : To determine the background against which Zhishi has been applied to treat Pi pattern, through examination of changes in Pi pattern treatments in a historical context. Methods : The properties and nature of Zhishi as written in multiple bencao texts were analyzed. In addition, understanding of the Pi pattern, the changes in its treatment were examined diachronically based on opinions of Zhang Zhongjing, Zhugong, and Li Dongyuan. Examples of Zhishi application in Pi pattern treating formulas were collected and their mechanisms analyzed. Results : Zhishi is strongly effective in relieving accumulation and stagnation, due to its properties of dispersing and lowering. The early view of contrasting Pi with Jiexiong shifted to viewing the Pi pattern as an inner damage, from the perspective of rising and lowering of the Qi mechanism based on the Spleen and Stomach. As a result, Zhishi became a key ingredient in the treatment of the Pi pattern. Conclusions : As the perspective of seeing Pi as one end of the Yin-Yang coupling with Jiexiong from the Shanghanlun shifted to seeing it as a problem of Qi mechanism of the Spleen and Stomach, Zhishi became a key ingredient in the formulas to treat Pi pattern. The complexity of Zhishi's direction made it appropriate to treat the changed Pi pattern.

• Smart Structures and Systems
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• v.13 no.5
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• pp.869-890
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• 2014

In this study, a damage detection approach using train-induced vibration response of the bridge is proposed, utilizing only direct structural analysis by means of introducing soft computing methods. In this approach, the possible damage patterns of the bridge are assumed according to theoretical and empirical considerations at first. Then, the running train-induced dynamic response of the bridge under a certain damage pattern is calculated employing a developed train-bridge interaction analysis program. When the calculated result is most identical to the recorded response, this damage pattern will be the solution. However, owing to the huge number of possible damage patterns, it is extremely time-consuming to calculate the bridge responses of all the cases and thus difficult to identify the exact solution quickly. Therefore, the soft computing methods are introduced to quickly solve the problem in this approach. The basic concept and process of the proposed approach are presented in this paper, and its feasibility is numerically investigated using two different train models and a simple girder bridge model.

• Smart Structures and Systems
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• v.29 no.1
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• pp.105-116
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• 2022

Stay cables play an essential role in cable-stayed bridges. Severe vibrations and/or harsh environment may result in cable failures. Therefore, an efficient structural health monitoring (SHM) solution for cable damage detection is necessary. This study proposes a data-driven method for immediately detecting cable damage from measured cable forces by recognizing pattern transition from the intact condition when damage occurs. In the proposed method, pattern recognition for cable damage detection is realized by time series classification (TSC) using a deep learning (DL) model, namely, the long short term memory fully convolutional network (LSTM-FCN). First, a TSC classifier is trained and validated using the cable forces (or cable force ratios) collected from intact stay cables, setting the segmented data series as input and the cable (or cable pair) ID as class labels. Subsequently, the classifier is tested using the data collected under possible damaged conditions. Finally, the cable or cable pair corresponding to the least classification accuracy is recommended as the most probable damaged cable or cable pair. A case study using measured cable forces from an in-service cable-stayed bridge shows that the cable with damage can be correctly identified using the proposed DL-TSC method. Compared with existing cable damage detection methods in the literature, the DL-TSC method requires minor data preprocessing and feature engineering and thus enables fast and convenient early detection in real applications.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.6
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• pp.77-84
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• 2020

In this paper, we developed a damage evaluation technique that can determine the damage location of a long-sized structure such as a cable-stayed bridge, and verified the performance of the developed technique through experiments. The damage assessment method aims to extract data that can evaluate the damage of the structure without the undamage data and can determine the damage location only by analyzing the response data of the structure. To complete this goal, we developed a damage assessment technique that considers variability based on the IMD theory, which is a statistical pattern recognition technique, to identify the damage location. To complete this goal, we developed a damage assessment technique that considers variability based on the IMD theory, which is a statistical pattern recognition technique, to identify the damage location. To evaluate the performance of the developed technique experimentally, cable damage experiments were conducted on model cable-stayed bridges. As a result, the damage assessment method considering variability automatically outputs the damageless data according to external force, and it is confirmed that the performance of extracting information that can determine the damage location of the cable through the analysis of the outputted damageless data and the measured damage data is shown.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.18 no.3
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• pp.149-174
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• 2014

Objectives to study definition and treatment of dizziness in the books of Cold damage which are classified as symptoms of all time. Methods 1. Quote provisions related to dizziness in "Sanghanlon(傷寒論)" 2. Among the books of Cold damage which are classified as symptoms, select 19 literatures on dizziness with table of contents and collect data and categorize in two perspectives on theories and disease pattern. 3. Compare and draw a chart all data collected in above methods. Results & Conclusions 1. In the books on Cold damage, dizziness is expressed in 2 ways such as head dizziness(頭眩) and fainting(鬱冒). fainting is much more several symptoms than head dizziness and it is the difference that it has mental confusion. 2. The cause of head dizziness after promoting sweating, vomiting and purgation is that source qi(元氣) of upper energizer(上焦) is deficiency, and cause of head dizziness before using method of treatment is wind(風), heat(熱), phlegm(痰), blood deficiency(血虛) and etc. 3. Main cause of fainting is that deficiency is getting severe so that cold invades, and symptoms are blood deficiency, after giving birth and excess pattern of fire and heat. 4. Remedies for head dizziness are using Yeonggyechulgam-tang(苓桂朮甘湯), jinmu-tang(眞武湯), sosiho-tang(小柴胡湯), sagunja-tang(四君子湯), samul-tang(四物湯) and etc. 5. Insamsambaek-tang (人蔘三白湯) and Sayeok-tang(四逆湯) are used for deficiency pattern of fainting, and Dojeok-san(導赤散), Daeseunggi-tang(大承氣湯), and Hwangryeonhaedok-tang(黃連解毒湯) are used for excess pattern(實證).

• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2511-2514
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• 2008

As the minimum feature size decreases, techniques to avoid contamination and processes to maintain clean wafer surfaces have become very important. The deposition and detachment of nanoparticles from surfaces are major problem to integrated circuit fabrication. Therefore, cleaning technology which reduces nanoparticles is essential to increase yield. Previous megasonic cleaning technology has reached the limits to reduce nanoparticles. Megasonic cleaning is one of the efficiency method to reduce contamination nanoparticle. Two major mechanisms are active in a megasonic cleaning, namely, acoustic streaming and cavitation. Acoustic streaming does not lead to sufficiently strong force to cause damage to the substrates or patterns. Sonoluminescence is a phenomenon of light emission associated with the cavitation of a bubble under ultrasound. We studied a correlation between sonoluminescence and sound pressure distribution for the minimum of pattern damage in megasonic cleaning.