• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.252-255
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• 1999

Feed rate in the fed-batch reactor is the most important control variable in optimizing the reactor performance. Exact solution can be obtained only for limited cases of simple reactor. The complexity of the model equations makes it extremely difficult to solve fur the general class of system models. Evolutionary programming method is proposed to get the information of the profile types, and the final profile is calculated by that information. The modified evolutionary programming method is used to get the more optimal profiles and it is demonstrated that proposed method can solve a wide range of optimal control problems.

• Proceedings of the IEEK Conference
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• summer
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• pp.137-142
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• 2004

In this paper, we propose a new scheme for geometry coding of three-dimensional (3-D) mesh models using a fixed spectral basis. In order to code the mesh geometry information, we generate a fixed spectral basis using the dual graph derived from the 3-D mesh topology. After we partition a 3-D mesh model into several independent sub-meshes to reduce coding complexity, the mesh geometry information is projected onto the generated orthonormal bases which are the eigenvectors of the Laplacian matrix of the 3-D mesh. Finally, spectral coefficients are coded by a quantizer and a variable length coder. The proposed scheme can not only overcome difficulty of generating a fixed spectral basis, but also reduce coding complexity. Moreover, we can provide an efficient multi-resolution representation of 3-D meshes.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.1-6
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• 2008

In this paper, we present the robust fuzzy algorithm for variable speed control of wind turbines. Generally, the plants of wind turbines are consisted of complex nonlinearities, and the parameters of variable speed of wind turbines are represented as uncertain terms. For solving these complexity, we propose the robust fuzzy algorithm. At first, the exact fuzzy modeling are performed for variable speed of wind turbines. Next, we design the fuzzy controller for reanalyzed T-S fuzzy model of the wind turbines, then, we prove the stability of the plant through the Lyapunov stability theorem. At last, an example is included for visualizing the efficiency of the proposed technique.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.89-111
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• 2008

Due to the development of digital technology, studies regarding smart wear integrating daily life have rapidly increased. However, consumer research about perception and attitude toward smart clothing hardly could find. The purpose of this study was to identify innovative characteristics and perceived risk of smart clothing and to analyze the influences of theses factors on product attitudes and intention to adopt. Specifically, five hypotheses were established. H1: Perceived attributes of smart clothing except for complexity would have positive relations to product attitude or purchase intention, while complexity would be opposite. H2: Product attitude would have positive relation to purchase intention. H3: Product attitude would have a mediating effect between perceived attributes and purchase intention. H4: Perceived risks of smart clothing would have negative relations to perceived attributes except for complexity, and positive relations to complexity. H5: Product attitude would have a mediating effect between perceived risks and purchase intention. A self-administered questionnaire was developed based on previous studies. After pretest, the data were collected during September, 2006, from university students in Korea who were relatively sensitive to innovative products. A total of 300 final useful questionnaire were analyzed by SPSS 13.0 program. About 60.3% were male with the mean age of 21.3 years old. About 59.3% reported that they were aware of smart clothing, but only 9 respondents purchased it. The mean of attitudes toward smart clothing and purchase intention was 2.96 (SD=.56) and 2.63 (SD=.65) respectively. Factor analysis using principal components with varimax rotation was conducted to identify perceived attribute and perceived risk dimensions. Perceived attributes of smart wear were categorized into relative advantage (including compatibility), observability (including triability), and complexity. Perceived risks were identified into physical/performance risk, social psychological risk, time loss risk, and economic risk. Regression analysis was conducted to test five hypotheses. Relative advantage and observability were significant predictors of product attitude (adj $R^2$=.223) and purchase intention (adj $R^2$=.221). Complexity showed negative influence on product attitude. Product attitude presented significant relation to purchase intention (adj $R^2$=.692) and partial mediating effect between perceived attributes and purchase intention (adj $R^2$=.698). Therefore hypothesis one to three were accepted. In order to test hypothesis four, four dimensions of perceived risk and demographic variables (age, gender, monthly household income, awareness of smart clothing, and purchase experience) were entered as independent variables in the regression models. Social psychological risk, economic risk, and gender (female) were significant to predict relative advantage (adj $R^2$=.276). When perceived observability was a dependent variable, social psychological risk, time loss risk, physical/performance risk, and age (younger) were significant in order (adj $R^2$=.144). However, physical/performance risk was positively related to observability. The more Koreans seemed to be observable of smart clothing, the more increased the probability of physical harm or performance problems received. Complexity was predicted by product awareness, social psychological risk, economic risk, and purchase experience in order (adj $R^2$=.114). Product awareness was negatively related to complexity, meaning high level of product awareness would reduce complexity of smart clothing. However, purchase experience presented positive relation with complexity. It appears that consumers can perceive high level of complexity when they are actually consuming smart clothing in real life. Risk variables were positively related with complexity. That is, in order to decrease complexity, it is also necessary to consider minimizing anxiety factors about social psychological wound or loss of money. Thus, hypothesis 4 was partially accepted. Finally, in testing hypothesis 5, social psychological risk and economic risk were significant predictors for product attitude (adj $R^2$=.122) and purchase intention (adj $R^2$=.099) respectively. When attitude variable was included with risk variables as independent variables in the regression model to predict purchase intention, only attitude variable was significant (adj $R^2$=.691). Thus attitude variable presented full mediating effect between perceived risks and purchase intention, and hypothesis 5 was accepted. Findings would provide guidelines for fashion and electronic businesses who aim to create and strengthen positive attitude toward smart clothing. Marketers need to consider not only functional feature of smart clothing, but also practical and aesthetic attributes, since appropriateness for social norm or self image would reduce uncertainty of psychological or social risk, which increase relative advantage of smart clothing. Actually social psychological risk was significantly associated to relative advantage. Economic risk is negatively associated with product attitudes as well as purchase intention, suggesting that smart-wear developers have to reflect on price ranges of potential adopters. It will be effective to utilize the findings associated with complexity when marketers in US plan communication strategy.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.134-138
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• 1996

Refuse incineration plant operations involve many kinds of uncertain factors, such as the variable physical properties of refuse as fuel and the complexity of the burning phenomenon. That makes it very difficult apply conventional control methods to the combustion control of the refuse. In this paper, an adaptive fuzzy model predictive controller is proposed for the combustion control of the refuse. In this paper, an adaptive fuzzy model predictive controller is proposed for the combustion control of the refuse. And computer simulation was carried out to evaluate performance of the proposed controller.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1077-1084
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• 2006

This paper proposed a fast algorithm to reduce the amount of calculation for inter prediction which takes a great deal of the operational time in H.264/AVC. This algorithm decides a search range according to the direction of predicted motion vector, and then performs an adaptive spiral search for the candidates with JM(Joint Model) FME(Fast Motion Estimation) which employs the rate-distortion optimization(RDO) method. Simultaneously, it decides a threshold cost value for each of the variable block sizes and performs the motion estimation for the variable search ranges with the threshold. These activities reduce the great amount of the complexity in inter prediction encoding. Experimental results by applying the proposed method .to various video sequences showed that the process time was decreased up to 80% comparing to the previous prediction methods. The degradation of video quality was only from 0.05dB to 0.19dB and the compression ratio decreased as small as 0.58% in average. Therefore, we are sure that the proposed method is an efficient method for the fast inter prediction.

• Knowledge Management Research
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• v.16 no.3
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• pp.41-63
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• 2015

This paper investigated main determinants of purchase intention for VOD contents by employing an extended technology acceptance model. The findings showed that 'user activeness' is the critical external variable influencing five perceived belief variables, namely perceived usefulness, perceived playfulness, perceived quality, perceived complexity and perceived cost. Regarding consumer satisfaction for free VOD service, it had no direct effect but indirect effect on the purchase behavior, meaning that the satisfaction causes purchase intention for VOD contents via the cognitive attitude. Also, the moderating e!ect of use experience on the relationship between the belief variables and the purchase intention was confirmed. Users with much experience showed a higher perception for usefulness and quality, whereas users with less experience placed a higher value on the hedonic factors and costs. In contrast to previous studies on IPTV that mainly focused on determinant of IPTV subscription, this paper analyzed VOD that is a killer application of IPTV in identification of key factors for the acceptance. The findings provide IPTV operators some strategies to create customer value and improve profitability.

• Transactions of Materials Processing
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• v.29 no.5
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• pp.241-250
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• 2020

In this study, the methodology of the springback prediction of automotive parts applied 3rd generation AHSS was investigated using the response surface model analysis based on a regression model, and the meta model analysis based on a Kriging model. To design the learning data set for constructing the springback prediction models, and the experimental design was conducted at three levels for each processing variable using the definitive screening designs method. The hat-shaped member, which is the basic shape of the member parts, was selected and the springback values were measured for each processing type and processing variable using the finite element analysis. When the nonlinearity of the variables is small during the hat-shaped member forming, the response surface model and the meta model can provide the same processing parameter. However, the accuracy of the springback prediction of the meta model is better than the response surface model. Even in the case of the simple shape parts forming, the springback prediction accuracy of the meta model is better than that of the response surface model, when more variables are considered and the nonlinearity effect of the variables is large. The efficient global optimization algorithm-based Kriging is appropriate in resolving the high computational complexity optimization problems such as developing automotive parts.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.61-74
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• 2015

Structural equation modeling (SEM) is a widely used in social sciences such as education, business administration, and psychology. In SEM, the latent variable score is the estimate of the latent variable which cannot be observed directly. This study uses stagewise structural equation modeling(stagewise SEM; SSEM) by partitioning the whole model into several stages. The traditional estimation method minimizes the discrepancy function using the variance-covariance of all observed variables. This method can lead to inappropriate situations where exogenous latent variables may be affected by endogenous latent variables. The SSEM approach can avoid such situations and reduce the complexity of the whole SEM in estimating parameters.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.1
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• pp.62-68
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• 2016

The fingerprint, which is one of the methods of indoor localization using WiFi, has been frequently studied because of its ability to be implemented via wireless access points. This method has low positioning resolution and high computational complexity compared to other methods, caused by its dependence of reference points in the radio map. In order to compensate for these problems, this paper presents a radio map designed algorithm based on the log-distance path loss model fusing a WiFi and BLE fingerprint. The proposed algorithm designs a radio map with variable values using the log-distance path loss model and reduces distance errors using a median filter. The experimental results of the proposed algorithm, compared with existing fingerprinting methods, show that the accuracy of positioning improved by from 2.747 m to 2.112 m, and the computational complexity reduced by a minimum of 33% according to the access points.