• 소성∙가공
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• 제14권8호통권80호
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• pp.655-660
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• 2005

• 한국염색가공학회:학술대회논문집
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• 한국염색가공학회 2009년도 학술발표대회
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• pp.233-234
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• 2009

• 한국재료학회:학술대회논문집
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• 한국재료학회 2002년도 추계학술발표강연 및 논문개요집
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• pp.134-134
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• 2002

• 한방안이비인후피부과학회지
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• 제24권3호
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• pp.17-26
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• 2011

Objectives : Corydalis tuber has been used for promoting blood circulation and for relieving pain in Oriental medicine. In the present study, we focused on the antimicrobial activity of Corydalis tuber and compared its antimicrobial activity with the processed Corydalis tuber. Methods : Processing of Corydalis tuber was accomplished by immersing in 5% of acetic acid for 12 h and then by roasting at $250^{\circ}C$ for indicated time periods(0-30 min). Minimum inhibitory concentration(MIC) and the zone of growth inhibition were determined against Propionibacterium acnes(P. acnes). Results : The methanolic extracts of Corydalis tuber showed potent antimicrobial effect(MIC 62.5 ${\mu}g/ml$). Its alkaloidal component, dehydrocorydaline, also exhibited antibacterial activity(MIC 25.0 ${\mu}g/ml$). After processing of Corydalis tuber, its inhibitory effect on the growth of P. acnes was significantly enhanced compared with that of unprocessed Corydalis tuber. Furthermore, elevated content of dehydrocorydaline was found in the processed than the unprocessed Corydalis tuber. However, the different roasting minutes effected on antimicrobial activity. The best roasting time of Corydalis tuber was 10 min, while roasting for the time above 15 min resulted in diminishing antimicrobial activity. Thus, it was concluded that the standardized processing condition of Corydalis tuber should be established to obtain enhanced antimicrobial(P. acnes) activity. Conclusion : For antimicrobial effect against P. acnes, the best processing condition of Corydalis tuber is immersing in 5% of acetic acid for 12 h and by roasting at $250^{\circ}C$ for 10 min.

• 한국재료학회지
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• 제9권9호
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• pp.865-871
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• 1999

지르콘 쉘 몰드를 제조하여 소결 온도 및 시간에 따른 소결거동이 기계적특성에 미치는 영향을 관찰하였다. $1000^{\circ}C$에서 1.5시간동안 소결 한 쉘 몰드의 1차 코팅 표면층에서 미세균열의 크기 및 수가 극대화되었으며 소결온도 및 시간이 증가할수록 상온강도와 기공의 비표면은 감소하였다. 1차 소결 후 $1500^{\circ}C$에서 4시간동안 소결 처리한 주형의 고온변형거동은 백업층과 하중의 역방향으로 스터코와 지르콘 슬러리의 경계면을 따라 변형이 발생하였다. 1차 코팅층에서 알루미나 스터코와 지르콘 슬러리의 열팽창계수 차이와 백업 코팅층에서 지르콘 슬러리간의 입도 차이가 고온변형시험 중 역변형을 일으킨 것으로 판단된다.

• Smart Structures and Systems
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• 제22권2호
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• pp.231-237
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• 2018

A significant data problem is encountered with condition monitoring because the sensors need to measure vibration data at a continuous and sometimes high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate their efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer data than traditional data sampling methods. This sensing paradigm is applied to condition monitoring with an improved machine learning algorithm in this study. For the experiments, a built-in rotating system was used, and all data were compressively sampled to obtain compressed data. The optimal signal features were then selected without the signal reconstruction process. For damage classification, we used the Variance Considered Machine, utilizing only the compressed data. The experimental results show that the proposed compressive sensing method could effectively improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• Smart Structures and Systems
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• 제13권6호
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• pp.901-925
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• 2014

The reliability of a Bridge management System depends on the quality of visual inspection and the reliable estimation of bridge condition rating. However, the current practices of visual inspection have been identified with several limitations, such as: they are time-consuming, provide incomplete information, and their reliance on inspectors' experience. To overcome such limitations, this paper presents an approach of automating the prediction of condition rating for bridges based on digital image analysis. The proposed methodology encompasses image acquisition, development of 3D visualization model, image processing, and condition rating model. Under this method, scaling defect in concrete bridge components is considered as a candidate defect and the guidelines in the Ontario Structure Inspection Manual (OSIM) have been adopted for developing and testing the proposed method. The automated algorithms for scaling depth prediction and mapping of condition ratings are based on training of back propagation neural networks. The result of developed models showed better prediction capability of condition rating over the existing methods such as, Naïve Bayes Classifiers and Bagged Decision Tree.

• 감성과학
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• 제6권3호
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• pp.21-28
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• 2003

본 연구에서는 악보 읽기에서 나타나는 전문가와 초보자의 작업기억에서의 처리 유형의 차이를 연구하기 위해 조음 억제 조건을 사용하여 2개의 실험을 실시하였다. 실험 1에서는 8개의 4분 음표가 스크린에 제시되었다가 사라지면, 참가자가 그 음표들을 기억해서 악보에 그리도록 했다. 자극은 선율적인 멜로디와 비선율적인 멜로디로 나뉘어졌다. 같은 방법으로, 실험 2에서는 각각 3개의 음으로 구성된 4개의 코드가 제시되었다. 자극은 화성적인 코드와 비화성적인 코드로 나뉘어졌다. 실험 1과 2의 분석 결과, 초보자는 공통적으로 조음 억제를 하지 않은 조건에서 조음 억제 조건보다 나은 수행을 보였다. 하지만 전문가들은 화성적 자극에 대해서는 상대적으로 조음 억제의 영향을 덜 받았다. 이러한 결과는 초보자가 조음 루프에 전적으로 의지하여 음을 처리하는 반면, 전문가는 자극이 친숙할 경우, 조음 루프로 정보를 넘기기 전에 시공간 잡기장을 통해 음을 부호화할 수 있음을 암시한다.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1997년도 춘계학술대회 논문집
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• pp.82-87
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• 1997

In order to make unmanned machining systems with satisfactory performances, it is necessary to incorporate appropriate condition monitoring systems in the machining workstation to provide the required intelligence of the expert. This paper deals with condition monitoring for tool wear and fracture during turning operation. Developing economic sensing and identification methods for turning processes, sound pressure measurement and digital signal processing technique are proposed. The validity of the proposed system is confirmed through the large number of cutting tests.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.361-364
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• 1995

Wavelet Transform is a new tools for signal processing, such as data compressing extraction of parameter for Reconition and Diagnostics. This transform has an advandage of a good resolution compared to Fast Fourier Transform (FFT) In this study, we employ the wavelet transform for analysis of Acoustic Emission raw signal generated form rotary compressor. In abnormal condition of rotary compressor, the state of operating condition can be classified by analizing coefficient of wavelet transformed signal.