• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.684-689
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• 1987

Digital Subtraction Angiography(DSA) technique has been widely used to detect vascular diseases and hemodynamic parameters noninvasively. However, there are few quantitative studies on the factors in fluencing the resultant DSA image quality. In this paper, several important factors are suggested to improved the DSA image quality based on mathematical analysis. Experimental DSA images for different filters are shown and also discussed the difference between original and processed image quality.

• 전기의세계
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• v.22 no.2
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• pp.11-18
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• 1973

This paper reports some results of Si and SiO$_{2}$ films obtained from the expitaxial growth by hydrogen reduction of SiCI$_{4}$ with a hydrogen and carbon dioxide mixture in an epitaxial-deposition chamber. The deposited Si and SiO$_{2}$ are studied by observing the process parameters affecting the rate of deposition, and the quantitative properties at the interface of Si and SiO$_{2}$ are also considered briefly according to the results of the optical absorption and the voltage-current characteristic of MOS etc. using step etching procedure for oxide films.

• Journal of Biomedical Engineering Research
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• v.5 no.2
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• pp.121-126
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• 1984

A new approach to texture classification for quantitative ultrasound liver diagnosis using run difference matrix was developed. The run difference matrix comprised the gray level difference along with a distances. From this run difference matrix, we defined several vectors and parameters such as DOD, DGD, DAD vector, SHP, SMO, SMG, LDE, LDEL etc.Each parameter values calculated in fatty, cirrhotic, normal and chronic hepatitic liver images were plotted in a plane and we found that RDM method was more sensitive to small structural changes than the conventional run length method and showed improved classification ability between the diseases.

• Proceedings of the Safety Management and Science Conference
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• 2003.11a
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• pp.407-412
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• 2003

Railroad line capacity is influenced by Quantitative and Qualitative factors which is applied by parameter to calculate it. But these parameters have been used experiential value without analyzing its reasonability or appropriate level. In this paper, we introduce the concept of robustness to Quantify parameter and evaluate robustness of it. For this purpose, we develop parameter evaluation simulator and present it. If this simulator is utilized, we can find the parameter having appropriate robustness and it will be applied to calculate more reasonable and systematic railroad line capacity.

• Journal of the Ergonomics Society of Korea
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• v.11 no.2
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• pp.47-56
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• 1992

In this paper, a mathematical model of learning curve is proposed to study the fi- nger's reaction time. The model is a logarithmic linear type which represents a lear- ning curve appropriately, and parameters are estimated by the linear. The learning coefficient and percentage of a reaction time can easily computed in the mathematical model. This quantitative approach provieds an important information to be used fot the working capqbility qualification of re-employment as well as the adaptability estimation of aged workers.

• Bulletin of the Korean Chemical Society
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• v.18 no.12
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• pp.1256-1260
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• 1997

A series of acyclic polyethers bearing amide end-groups and lipophilic alkyl chains (3-5) were successfully synthesized with quantitative yields. Based upon the transport experiment in a bulk liquid membrane (BLM) system and solvent extraction, a very high selectivity of Pb2+ over other transition metal cations was observed. Measurement of thermodynamic parameters for complexation in methanol at 25 ℃ gave a strong evidence for excellent selective complexation for lead ion over other transition metal ions.

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.309.1-309.1
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• 2003

The purposes of this study were to evaluate bioequivalence (BE) using In-transformed pharmacokinetic parameters obtained from two risperidone products and to develop the analytical methods for the quantitative determination of risperidone in human serum. In addition, the in vitro dissolution profiles of the two risperidone products in various dissolution media: pH 1.2, 4.0, 6.8 and water (KP VII Apparatus II method) were assesed. (omitted)

• Proceedings of the ESK Conference
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• 1992.10a
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• pp.113-120
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• 1992

In this paper, a mathematical model of learning curve is proposed to study the finger's reaction time. The model is a logarithmic linear type which represents a learning curve appropriately, and parameters are estimated by the linear. The learning coefficient and percentage of a reaction time can be easily computed in the mathematical model. This quantitative approach provides an important information to be used for the working capability qualification for re-employment as well as for the adaptability estimation of aged workers.

• Journal of Power System Engineering
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• v.4 no.2
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• pp.25-30
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• 2000

The grinding process is very complex and relates many parameters to control the process. As this reason, a theoretical analysis and a quantitative estimation of the grinding process has not been well established. In this study, the in-process monitoring system was suggested by applying the neural network for monitoring and shooting the malfunction of cylindrical plunge grinding process. This system used the power signals from the electric power meter. This neural network was composed of processing elements [4-(5-5)-3] with 4 identified power parameters. Because sensitivity is blunted some minute vibration components, the simulation result of this system has appeared about 10% erroneous recognition in the uncertain pattern and the average success rate of the trouble recognition was about 90%. Consequently, the developed system, which applied to the power signals, can be recognize enough to monitor the grinding process as in-process.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.469-473
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• 2007

For the quantitative analysis of inclusion using OES data, separating of noise and inclusion is needed. In previous methods assuming that noises come from a normal distribution, intensity levels beyond a specific threshold are determined as inclusions. However, it is not possible to classify inclusions in low intensity region using this method, even though every inclusion is an element of some chemical compound. In this paper, we assume that distribution of OES data is a Gaussian mixture and estimate the parameters of the mixture model using EM algorithm. Then, we calculate mixing ratio of noise and inclusion using these parameters to separate noise and inclusion.