• Proceedings of the Korea Society of Design Studies Conference
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• 2003.05a
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• pp.226-227
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• 2003

• Journal of Information Processing Systems
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• v.3 no.2
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• pp.64-72
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• 2007

Mobile technology appears promising as a method to promote group performance in circumstances dependent on time, but not member proximity. However, the success of mobile technology in group decision-making situations has not yet been proven. This paper aims to see how mobile technology affects the performance of group decision-making tasks that should be resolved urgently and/or sources of idea are disconnected with on-line network. Laboratory experiment was used to investigate the effects of mobile factors on group decision-making. The results from the experiment supported the proposition that pressures of time and location play a significant role in the assessment of group decision performance measures. We found that the adoption of mobile technology to group decision-making procedures might be competitive when group decision-making tasks are urgent and sources of idea are disconnected with on-line network, even though mobile technology is not a panacea on which to depend when designing group decision-making.

• Journal of Global Scholars of Marketing Science
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• v.13
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• pp.135-158
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• 2004

On-line consumers have some visit behavior characteristics when they visit internet-shopping mall between visit-stage and purchase-stage. Therefore, information of on-line consumers have influenced on internet-shopping mall's profitabilities at site manager's perspectives. For examples, Are any on-line consumers continuous visiting under any situations? Or are any on-line consumers purchased on any specific internet-shopping mall? Expecially in this paper, researcher tried to understand visit behavioral characteristics of on-line consumers using two-stage mixture regression analysis. Throughout this process, it could be proposed method, which could be reinforced competitiveness of internet-shopping mall by segmental decision-making method. Additionally, it is expected that visit behavioral characteristics' information could be supplied strategic implications between visit-stage and purchase-stage Throughout empirical test it could be proved two-stage decision-making process, which decision-making process of on-line consumers would be processed visit-stage and purchase-stage. In this study, researcher proposed suitable response strategy after understanding visiting behavioral characteristics of on-line consumers. This paper has some academical contributions, which visit behavioral characteristics of on-line consumers could be grasped the meaning by site stickiness and navigation pattern.

• 한국경영정보학회:학술대회논문집
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• 2008.06a
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• pp.957-962
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• 2008

We propose a model for the line expansion problem in the AMOLED (Active Matrix Organic Light Emitting Diodes) industry, which now faces market uncertainty: for example, changing customer needs, technological development path, etc. We focus on the optimal investment time and size of the AMOLED production lines. In particular, employed here is the ROV (Real Options Valuation) model to show how to capture the value of line expansion and to determine the optimal investment time. The ROV framework provides a systematic procedure to quantify an expected outcome of a flexible decision which is not possible in the frame of the traditional NPV (Net Present Value) approach. Furthermore, we also use Monte Carlo simulation to measure the uncertainty associated with the line expansion decision; Monte Carlo simulation estimates the volatility of a decision alternative. Lastly, we present a scenario planning to be conducted for what-if analysis of the ROV model.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1196-1203
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• 2004

Autonomous agents need considerable computational resources to perform rational decision-making. The complexity of decision-making becomes prohibitive when large number of agents are present and when decisions have to be made under time pressure. One of approaches in time-critical domains is to respond to an observed condition with a predefined action. Although such a system may be able to react very quickly to environmental conditions, predefined plans are of less value if a situation changes and re-planning is needed. In this paper we investigate strategies intended to tame the computational burden by using off-line computation in conjunction with on-line reasoning. We use performance profiles computed off-line and the notion of urgency (i.e., the value of time) computed on-line to choose the amount of information to be included during on-line deliberation. This method can adjust to various levels of real-time demands, but incurs some overhead associated with iterative deepening. We test our framework with experiments in a simulated anti-air defense domain. The experiments show that the off-line performance profiles and the on-line computation of urgency are effective in time-critical situations.

• Journal of the Optical Society of Korea
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• v.18 no.4
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• pp.317-329
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• 2014

In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.

• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.189-207
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• 1997

Recently, we have witnessed a host of emerging tools in the management support systems (MSS) area including the data warehouse/multidimensinal databases (MDDB), data mining, on-line analytical processing (OLAP), intelligent agents, World Wide Web(WWW) technologies, the Internet, and corporate intranets. These tools are reshaping MSS developments in organizations. This article reviews a set of emerging data management technologies in the knowledge discovery in databases(KDD) process and analyzes their implications for decision support. Furthermore, today's MSS are equipped with a plethora of AI techniques (artifical neural networks, and genetic algorithms, etc) fuzzy sets, modeling by example , geographical information system(GIS), logic modeling, and visual interactive modeling (VIM) , All these developments suggest that we are shifting the corporate decision making paradigm form information-driven decision making in the1980s to knowledge-driven decision making in the 1990s.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.6-13
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• 2021

Cases and studies on the selection method of CTQ are relatively active, but there are few cases or studies on the selection method of CTP which is important in the device industry. In fact, many companies simply select and manage CTP from the point of contact based on their experience and intuition. The purpose of this study is to present an evaluation model and a mathematical decision model for rational and systematic CTP selection to improve the process quality of semiconductor equipment lines. In the evaluation model, AHP (Analytic Hierarchy Process) analysis technique was applied to show objective and quantitative figures, and Fuzzy decision-making model was used to solve the ambiguity and uncertainty in the decision-making process. Decision Value (DV) was presented. The subjects were 22 process factors managed in the Plating Process that the representative equipment line can do. As a result, the evaluation model proposed in this study can support more efficient and effective decision-making for process quality improvement by more objectively measuring the problem of subjective CTP selection in manufacturing sites.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.3
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• pp.107-120
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• 2011

The increased availability of store brand suppliers now provides retailers with opportunities to create their own lines of vertically differentiated multiple store brands within a product category. As the number of store brands increase, the retailer's shelf space becomes more crowded, which may force the retailer to consider dropping some national brands from its assortment. Despite these trends, the problem of product line design in a vertically differentiated product category has been analyzed mainly from a manufacturer's perspective in the marketing literature and it is not known to what extent the findings of the existing product line design literature provide applicable strategic guidelines for the new problem faced by retailers. In this study, we address this deficiency in the literature and conduct an in-depth study of the retailer's strategic design of a line of store brands and its assortment decision within the context of retail category management. We analyze the retailer's decision about not only how to design a line of store brands but also which national brand to drop from its assortment. The results of our analysis are as follows. First, if the retailer has to drop one of national brands from its assortment, it is the best for the retailer to drop the low-quality national brand rather than the high-quality national brand. Second, the retailer has to position the high-quality store brand relatively close to the high-quality national brand, remained on its shelf, in terms of quality so as to maximize the size of retail margin from the national brand. On the other hand, the retailer should set the quality of the low-quality store brand at a lower level than that of the low-quality national brand to increase the total category demand by attracting more price sensitive consumers. By doing so, the retailer can also minimize cannibalization between two store brands. Lastly, our analysis shows that the introduction of a line of store brands improves consumer welfare by increasing real values of all products on the shelf.

• IE interfaces
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• v.16 no.spc
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• pp.111-115
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• 2003

Railroad system is consisted of resources of rail track, signal system, and vehicles. Railway operation must use these limited resources and maximize resource utilization. Line capacity(number of trains throughput/day) is determined by such as parameters, line utilization rate($\alpha$), dummy rate for the break-through hour($\beta$), and dummy rate for the number of rail track intervals($\delta$). Line capacity simulation(LCS) determined the line capacity through simulation given $\alpha$, $\beta$, and $\delta$. This paper deals with the development of parameter evaluation simulation(PES). PES presents the decision maker with the relationship of line capacity and measurement of robustness for various scenarios in different parameters and then the decision maker can determine the appropriate parameters.