• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.355-362
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• 2002

As electronic commerce under the digital economy environment evolves rapidly affecting the structure of our economy and individual life styles, the need for metrics system to evaluate the performance of electronic commerce activities remarkably increases. Reviewing the characteristics of electronic commerce and some issues related to its measurement, this paper proposes a framework to measure the performance of electronic commerce business activities. the proposed framework customizes the balanced scorecard method for electronic commerce practices and can be applied effectively to electronic commerce businesses as an appropriate measure.

• Journal of Korean Society for Quality Management
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• v.27 no.4
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• pp.20-41
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• 1999

This study addresses the development of a quality measurement of information systems integration(SI) service. Several dimensions which affect on quality of systems integration service have been identified and tested. Also, a measurement tool(questionnaire) of the factors has been developed. To achieve above purpose, extensive literature review and in-depth interview with several SI managers and customers were used. We suggested the analysis framework including performance variables such as quality, customer satisfaction, intention of renewal contract, and contribution to better customer's information system and the quality factors as well. To verify the research framework, collected data from the survey was analyzed statistically. The data from 73 respondents was used for analysis. Consequently, we identified eight factors and developed a 41-item instrument with Likert 5 points to measure the quality of SI service. It was proved that the 41-item instrument suggested in this study was very useful to measure the performance of SI service such as quality and customer satisfaction. Also it was shown that the instrument measured intention of renewal contract and contribution of customer's information system well.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.551-560
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• 2010

This paper considers a Bayesian approach to modeling a flexible regression function under structural measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under structural measurement error model without a semiparametric component.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.379-385
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• 2010

This paper considers Bayesian approach to modeling a flexible regression function under functional measurement error model. The regression function is modeled based on semiparametric regression with penalized splines. Model fitting and parameter estimation are carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. Their performances are compared with those of the estimators under functional measurement error model without semiparametric component.

• Water for future
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• v.49 no.12
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• pp.23-31
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• 2016

• The KIPS Transactions:PartC
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• v.14C no.7
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• pp.603-610
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• 2007

Effective handover decision is important for providing seamless services to mobile users. In this paper, we propose an analysis framework to evaluate the performance of handover decision based on received signal strength (RSS) measurements in terms of the late notification and false alarm probability. In our framework, we consider mobility of a mobile user, signaling delays for exchanging messages related to handover protocols, cell sizes and RSS measurement interval to stabilize RSS reading due to random measurement errors. By quantitatively scrutinizing the impact of each parameter on the late notification and false alarms, we suggest the research directions for effective handover decision mechanism that may provide fast and reliable handover.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.380-393
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• 2015

This study presents how we can evaluate stereo camera systems for the structural deformation monitoring. A stereo camera system, consisting of a set of stereo cameras and reflective markers attached on the structure, is introduced for the measurement and the stereo pattern recognition (SPR) method is utilized for the full-field structural deformation estimation. Performance of this measurement system depends on many parameters including types and specifications of the cameras, locations and orientations of them, and sizes and positions of markers; it is difficult to experimentally identify the effects of each parameter on the measurement performance. In this study, a simulation framework for evaluating performance of the stereo camera systems with various parameters has been developed. The maximum normalized root-mean-square (RMS) error is defined as a representative index of stereo camera system performance. A plate structure is chosen for an introductory example. Its several modal harmonic vibrations are generated and estimated in the simulation framework. Two cases of simulations are conducted to see the effects of camera locations and the resolutions of the cameras. An experimental validation is carried out for a few selected cases from the simulations. Using the simultaneous laser displacement sensor (LDS) measurements as the reference, the measurement errors are obtained and compared with the simulations.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.111-120
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• 2010

Initial stage of emotion has a great influence on building up product image and impression. Because of its influencing effects, measuring initial stage of emotion has potential to be a key factor for designers and marketers to achieve a distinct product concept. While many researchers have studied this topic with the emotion measurement method in product use stage, there are very few cases specialized in the initial stage of emotion. Even though present emotion measurement methods have difficulties to derive accurate user's initial stage of emotion, most case of initial emotion study applies these defective methods. The purpose of this study is to develop initial stage of emotion measurement method and apply this method to real product context. In the design of the initial stage of emotion measurement method, noticeable characteristics of initial stage of emotion were explored and initial emotion measurement framework was presented. Based on this framework, Initial Emotion Measurement System(IEMS) was suggested. This method collects user's eye movement, behavior and verbal data accurately and objectively.

• The Journal of Information Systems
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• v.25 no.4
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• pp.63-85
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• 2016

Purpose While the popularity of C2C auction platforms such as eBay is gradually decreased, this domain is still undermined to explain online bidding behaviors. Online bidders sometimes engage in impulsive bidding due to some of the online auction characteristics. Therefore, this study develops and tests a model of the impulsive bidding exhibited by online bidders in C2C auction platforms. Based on S-O-R framework, our model posits that both perceived time-pressure and competition intensity affect cognitive absorption which ultimately influences the impulsive bidding. Design/methodology/approach This study collected survey data from 214 C2C auction participants, who have prior experience on impulsive bidding and tested both measurement model and structural model by using CB-SEM (covariate-based structural equation modelling) technique. In this study, by using AMOS 20.0, we tested the measurement model for its overall fit, item reliability, and validity and further conducted the structural model to test our proposed hypotheses. Findings Based on our results, we found that perceived tim-pressure and competition intensity were positively related to cognitive absorption. We also found that the cognitive absorption was positively associated with impulsive bidding behavior. In this study, by developing our research model in S-O-R framework, we provide an alternative theoretical mechanism to describe online impulsive bidding behavior.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.434-436
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• 2006

In a visual driver-assistance system, separating moving objects from fixed objects are an important problem to maintain multiple hypothesis for the state. Color and edge-based tracker can often be "distracted" causing them to track the wrong object. Many researchers have dealt with this problem by using multiple features, as it is unlikely that all will be distracted at the same time. In this paper, we improve the accuracy and robustness of real-time tracking by combining a color histogram feature with a brightness of Optical Flow-based feature under a Sequential Monte Carlo framework. And it is also excepted from Tracking as time goes on, reducing density by Adaptive Particles Number in case of the fixed object. This new framework makes two main contributions. The one is about the prediction framework which separating moving objects from fixed objects and the other is about measurement framework to get a information from the visual data under a partial occlusion.