• Journal of the Korean Society for Library and Information Science
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• v.27
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• pp.291-339
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• 1994

The purpose of this study is to find personal characteristics that affect users' cognitive characteristics of system, and to verify correlations between this users' cognitive characteristics and selection of system usage in using end -user searching systems (EUSS), For corroborative analysis of this study, preliminary model was constructed referring to Davis' Technology Acceptance Model. The model consists of exogenous variables (personal characteristics) , parameter variables (perceived usefulness, perceived ease of use), and effect variables (selection of system usage), When exogenous variables affect parameter variables, exogenous variables are independent variables and parameter variables are dependent variables. In addition, in correlation of parameter variables, which have been affected by exogenous variables, with effect variables, parameter variables are independent variables and effect variables are dependent variables, As for the research methodology, this study regards the Academic Information System connected with the Internet as EUSS, So questionnaires have been sent to researchers in universities who were conducting direct searching for the system. 229 valid responses to questionnaires have been analyzed according to Pearson Correlation Analysis and Stepwise Selection of Multiple Regression in the statistical software packages, 'SPSS PC+'. The findings and conclusions made in this study are summarized as follows; 1. Among the personal characteristics (age, disciplinary, computer literacy level, perceived usefulness of use education and training, perceived satisfaction of end-user searching, perceived satisfaction of system characteristics), all characteristics but age affect perceived usefulness and perceived ease of use. Specifically, perceived satisfaction of end user searching and perceived satisfaction of system characteristics most affect perceived usefulness and perceived ease of use respectively. 2. Perceived usefulness and perceived ease of use have a direct effect on selection of system usage in using EUSS. 3, Perceived usefulness more affect selection of system usage than perceived ease of use in using EUSS.

• Journal of Multimedia Information System
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• v.3 no.4
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• pp.155-160
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• 2016

The Pulse Coupled Neural Network (PCNN) is a kind of neural network models that consists of spiking neurons and local connections. The PCNN was originally proposed as a model that can reproduce the synchronous phenomena of the neurons in the cat visual cortex. Recently, the PCNN has been applied to the various image processing applications, e.g., image segmentation, edge detection, pattern recognition, and so on. The method for the image matching using the PCNN had been proposed as one of the valuable applications of the PCNN. In this method, the Genetic Algorithm is applied to the PCNN parameter learning for the image matching. In this study, we propose the method of the similar image rating using the PCNN. In our method, the Genetic Algorithm based method is applied to the parameter learning of the PCNN. We show the performance of our method by simulations. From the simulation results, we evaluate the efficiency and the general versatility of our parameter learning method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.605-606
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• 2005

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. Intra and extra parameters should be obtain to determine the relation between image and world coordination through experiment. One difficulty is in camera alignment for parallel installation: placing two CCD arrays in a plane. If the pixel distance parameter which is one of intra parameter is calibrated with known points, such error can be compensated in some amount. Such error compensation effect with the calibrated pixel distance parameter is demonstrated with various experimental results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.103-108
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• 2007

This paper presents the conceptual framework for estimating and predicting system's susceptibility to failure as function of condition parameter value which is representing the current status of performance measure using on-line performance reliability. The performance of such system depends on one parameter with a probability distribution that degrades with time gracefully. Performance reliability represents the probability that physical performance will remain satisfactory over a finite period of time or usage cycles in the future. An empirical physical performance function is constructed to incorporate explanatory variables (operating and environmental conditions) over a time or usage dimension. This function enables one to model device performance and the associated classical reliability measures simultaneously, in the performance domain and time domain. The conditional performance reliability structure developed represents a tool to predict system performance over time or usage for next usage period. By enabling such a framework, it can bring us more efficient planning and execution in system's operation control as well as maintenance to reduce costs and/or increase profits.

• International Journal of Contents
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• v.5 no.1
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• pp.51-55
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• 2009

In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.

• Journal of Korean Ophthalmic Optics Society
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• v.8 no.1
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• pp.53-57
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• 2003

R, G, Y, B color lenses Manufactured increasing tinted time by 5 min term. CIE $L^*a^*b^*$ coordination's analysis used spectrophotometer and CIE $L^*a^*b^*$ color system. CIE $L^*a^*b^*$ coordination transfer form about tinted time being $$b^*(Y-B)={\beta}a^*+{\alpha}$$ change to do linear almost. In red case, move in $G{\rightarrow}R$, $B{\rightarrow}Y$ form tinted time increases, and Parameter ${\alpha}$, ${\beta}$ value got each -3.49 and 0.90. In green case, CIE $L^*a^*b^*$ coordination transfer form is $R{\rightarrow}G$, $B{\rightarrow}Y$ form. Got the pure green color color in 10 min's tinted time. Parameter ${\alpha}$, ${\beta}$ value got each -0.72 and -0.55. Get into pure yellow and blue color case tinted time increases. Parameter ${\alpha}$, ${\beta}$ value are 14.11 and 1.58 in yellow, and Parameter ${\alpha}$, ${\beta}$ value are -11.62 and 1.30 in blue color.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.7
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• pp.873-879
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• 2010

It is common to predict structural dynamic design parameters due to the change of design parameter, but to predict the amount of changed design parameter where the mass and stiffness are being modified are rarely found in previous literature. In this study, the changed design parameter in a proportional damping system is predicted by using sensitivity coefficients and an iterative method. The sensitivity coefficients are determined from the changes in eigenvectors; these changes are due to modification. This method is applied to a three-story shear structure. To validate the prediction of the changed design parameter, the results are compared to the reanalysis results; both results are in good agreement.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.99-109
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• 2009

Negative binomial yield model for semiconductor manufacturing consists of two parameters which are the average number of defects per die and the clustering parameter. Estimating the clustering parameter is quite complex because the parameter has not clear closed form. In this paper, a Bayesian approach using Markov Chain Monte Carlo is proposed to estimate the clustering parameter. To find an appropriate estimation method for the clustering parameter, two typical estimators, the method of moments estimator and the maximum likelihood estimator, and the proposed Bayesian estimator are compared with respect to the mean absolute deviation between the real yield and the estimated yield. Experimental results show that both the proposed Bayesian estimator and the maximum likelihood estimator have excellent performance and the choice of method depends on the purpose of use.

• IE interfaces
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• v.15 no.3
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• pp.308-315
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• 2002

This study presents the web based cutting parameter selection system using Group Technology (GT). The GT is basically applied to classify and code the work material and cutting process which are main factors to affect cutting parameter selection. The proposed system has been designed to electronically select proper cutting conditions based on the stored GT database. The existing approaches used in most small and medium sized companies are basically to use manufacturing engineer's experience or to find the recommended values from the manufacturing engineers handbook. These processes are often time consuming and inconsistent, especially when a new engineer is involved. Consequently, the proposed system could automatically and consistently generate the proper cutting conditions (feed, depth of cut, and cutting speed) as soon as relatively simple data input is given thanks to the classified GT database.

• Journal of KSNVE
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• v.10 no.4
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• pp.575-583
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• 2000

In this paper, we design a vibration control system that includes a 3-D.O.F. mass-spring-damper structure for the analytical model of a building that is excited at the base of this structure by an external dynamic force, and one Active Mass Damper(AMD) on the top of this structure to generate control forces fro attenuation of the structural response. Two robust controllers based on $\mu$-synthesis and H$\infty$ optimal control are designed for the structural system to show that the performance of a control system can be degraded by some parameter uncertainties such as mass, stiffness coefficients, and/or damping coefficients. The performance of the two controllers are compared in terms of nominal performance, robust stability and robust performance by simulations.