• Journal of Yeungnam Medical Science
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• v.6 no.1
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• pp.109-119
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• 1989

We measured fasting serum angiotensin -converting enzyme (SACE) in 100 healthy controls and 75 coal worker's pneumoconiosis (CWP) patients by a commercial kits($ACEcolor^{(R)}$, Fujirio Inc., Japan) and evaluated this manual method. The linear range extends to an activity of 80U/L. Precision on a commercial control serum (ACE control-$N^{(R)}$, Sigma Co.)with a mean value, of 9.47U/L yielded a within-run and between-run CVs are 5.6% (N=15) and 6.9% (N=14) respectively. SAVE in 75 CWP was $20.3{\pm}5.7U/L$ ($mean{\pm}s.d.$) ; higher than in healthy controls ($13.4{\pm}3.9U/L$, P<0.01). No correlation was found between SACE, sex, and age. The results suggest that the measurement of SACE and follow-up SACE in coal workers may be a useful diagnostic fools for CWP.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.105-106
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• 2009

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.79-89
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• 2009

As an IETF standard protocol, WebDAV provides infrastructure for managing and authoring resources and supports asynchronous collaborative authoring on the Web. The CoSlide server is an extension of the Jakarta Slide WebDAV server, providing various workspaces and collaborative services through the WebDAV protocol. The CoSlide server supports workspaces for storing and sharing information of various users, and provides environment for effective collaborative authoring. Actual collaboration activities are performed through a collaboration client software which provides collaboration services along with the CoSlide server. In this paper, we describe the development of the CoSpace client which operates in association with the CoSlide server, presenting effective collaborative environment. The CoSpace client provides user interfaces for accessing and controlling the resources of each workspace on the CoSlide server. In particular, CoSpace provides the facility to launch an authoring application from its workspace view, automatic locking, and downloading the content to be edited, and resource movement using mouse drag & drop.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.1
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• pp.27-35
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• 2005

Ultrasonic inspection methods are widely used for detecting flaws in materials. The signal analysis step plays a crucial part in the data interpretation process. A number of signal processing methods have been proposed to classify ultrasonic flaw signals. One of the more popular methods involves the extraction of an appropriate set of features followed by the use of a neural network for the classification of the signals in the feature spare. This paper describes an alternative approach which uses the least mean square (LMS) method and exportation maximization (EM) algorithm with the model based deconvolution which is employed for classifying nondestructive evaluation (NDE) signals from steam generator tubes in a nuclear power plant. The signals due to cracks and deposits are not significantly different. These signals must be discriminated to prevent from happening a huge disaster such as contamination of water or explosion. A model based deconvolution has been described to facilitate comparison of classification results. The method uses the space alternating generalized expectation maximiBation (SAGE) algorithm ill conjunction with the Newton-Raphson method which uses the Hessian parameter resulting in fast convergence to estimate the time of flight and the distance between the tube wall and the ultrasonic sensor. Results using these schemes for the classification of ultrasonic signals from cracks and deposits within steam generator tubes are presented and showed a reasonable performances.