• Journal of the Korean Ceramic Society
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• v.51 no.4
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• pp.350-356
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• 2014

Recently, Chemical Vapor Deposition (CVD) synthetic diamonds have been introduced to the jewelry gem market, as CVD technology has been making considerable advances. Unfortunately, CVD diamonds are not distinguishable from natural diamonds when using the conventional gemological characterization method. Therefore, we need to develop a new identification method that is non-destructive, fast, and inexpensive. In our study, we employed optical microscopy and spectroscopy techniques, including Fourier transform infra-red (FT-IR), UV-VIS-NIR, photoluminescence (PL), micro Raman, and cathodoluminescent (CL) spectroscopy, to determine the differences between a natural diamond (0.30 cts) and a CVD diamond (0.43 cts). The identification of a CVD diamond was difficult when using standard gemological techniques, UV-VIS-NIR, or micro-Raman spectroscopy. However, a CVD diamond could be identified using a FT-IR by the Type II peaks. In addition, we identified a CVD diamond conclusively with the uneven UV fluorescent local bands, additional satellite PL peaks, longer phosphorescence life time, and uneven streaks in the CL images. Our results suggest that using FT-IR combined with UV fluorescent images, PL, and CL analysis might be an appropriate method for identifying CVD diamonds.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.414-422
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• 2006

Deterministic techniques have been applied in power system planning for many years and there is a growing interest in combining these techniques with probabilistic considerations to assess the increased system stress due to the restructured electricity environment. The overall reliability framework proposed in this paper incorporates the deterministic N-1 criterion in a probabilistic framework, and results in the joint inclusion of both adequacy and security considerations in system planning. The combined framework is achieved using system well-being analysis and traditional adequacy assessment. System well-being analysis is used to quantify the degree of N-1 security and N-1 insecurity in terms of probabilities and frequencies. Traditional adequacy assessment is Incorporated to quantify the magnitude of the severity and consequences associated with system failure. The concepts are illustrated by application to two test systems. The results based on the overall reliability analysis framework indicate that adequacy indices are adversely affected by a generation deficient environment and security indices are adversely affected by a transmission deficient environment. The combined adequacy and security framework presented in this paper can assist system planners to realize the overall benefits associated with system modifications based on the degree of adequacy and security, and therefore facilitate the decision making process.

• East Asian Journal of Business Economics (EAJBE)
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• v.5 no.2
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• pp.38-47
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• 2017

In today's highly unpredictable marketing environment, where the consumer demands and behaviors are continuously and rapidly changing therefore various factors of consumer impulse buying behavior are proving to be challenging for the existing and new business organizations. Shopping has become a relaxing and rejoicing activity for the consumers making impulsive buying as a socially acceptable and common practice. So by taking into account all these aspects, the objective of this study was to understand the factors affecting impulse buying behavior of the consumer. Store atmosphere and fashion involvement were selected as independent variables while consumer impulse buying behavior was taken as dependent variable for this study. Likewise, impulse buying behavior of consumers with different monthly household income was also analyzed in this study. Primary data was collected through a questionnaire from 250 respondents of district Faisalabad, and then it was analyzed by using various statistical techniques. The results indicated a significant positive impact of store atmosphere and fashion involvement on consumer impulse buying behavior. The study also revealed that among consumer groups with different household incomes; at least one group differed from others in impulse buying behavior. These results were consistent with previous literature. These results could provide information to the marketers and retailers for planning and execution of various marketing techniques. Moreover, educators could expand on the findings by developing new studies examining consumer impulse buying behavior.

• Journal of Ocean Engineering and Technology
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• v.26 no.5
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• pp.25-30
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• 2012

This study examined the use of LIT (lock-in infrared thermography) to detect defects in the welded parts of ships and offshore structures. A quantitative analysis was used with the filtering and texture measurement of image processing techniques to find the optimized experimental condition. We verified the reliability of our methods by applying image processing techniques in order to normalize the evaluations of comparative images that showed a phase difference. In addition, it was found that a low to mid-range intensity of light exposure on the surface showed good results, whereas high exposure did not provide significant results. A lock-in frequency of around 0.1 Hz was satisfactory regardless of the intensity of the light source. In addition, making the integration time of the thermography camera inversely proportional to the intensity of the exposed light source during the experiment provided good results.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.509-515
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• 2005

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved it more powerful than traditional artificial neural networks (ANNs)(Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al, 2005; Kim, 2003). The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is cost-sensitive. Therefore, it is necessary to convert the output of the classifier into well-calibrated posterior probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create probabilities (Platt, 1999; Drish, 2001). This study applies a method to estimate the probability of outputs of SVM to bankruptcy prediction and then suggests credit scoring methods using the estimated probability for bank's loan decision making.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.739-744
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• 2000

As DNA sequences have been known through the Genome project the techniques for dealing with molecule-level gene information are being made researches briskly. It is also urgent to develop new computer algorithms for making databases and analyzing it efficiently considering the vastness of the information for known sequences. In this respect, this paper studies the association rule search algorithms for finding out the characteristics shown by means of the association between promoter sequences and genes, which is one of the important research areas in molecular biology. This paper treat biological data, while previous search algorithms used transaction data. So, we design a transformed association rule algorithm that covers data types and biological properties. These research results will contribute to reducing the time and the cost for biological experiments by minimizing their candidates.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.178-184
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• 2003

Case-based reasoning (CBR) often shows significant promise for improving effectiveness of complex and unstructured decision making. Consequently, it has been applied to various problem-solving areas including manufacturing, finance and marketing. However, the design of appropriate case indexing and retrieval mechanisms to improve the performance of CBR is still challenging issue. Most of previous studies to improve the effectiveness for CBR have focused on the similarity function or optimization of case features and their weights. However, according to some of prior researches, finding the optimal k parameter for k-nearest neighbor (k-NN) is also crucial to improve the performance of CBR system. Nonetheless, there have been few attempts which have tried to optimize the number of neighbors, especially using artificial intelligence (AI) techniques. In this study, we introduce a genetic algorithm (GA) to optimize the number of neighbors to combine. This study applies the new model to the real-world case provided by an online shopping mall in Korea. Experimental results show that a GA-optimized k-NN approach outperforms other AI techniques for purchasing behavior forecasting.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.919-925
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• 2006

Mobile IPv6 generates the loss of packets and out of sequencing when hand off, In this paper, We propose a improved hand off techniques using the mobility pattern of mobile nodes. As making group by presetting the moving range of mobile nodes, and putting buffer server in the group, the packet loss and out of packet sequence can be reduced. The proposed method prevents the out of packet sequence in If level which can be happened in the stable state, minimizes the packet re-send in TCP level. In the simulation, the proposed hand off techniques transmits packets efficiently by using the mobility pattern of mobile nodes.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.4
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• pp.104-111
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• 2016

The flame stabilization is one of the topics which have to be solved for the airbreathing propulsion systems, using the entering air which is supersonic velocity as an oxygen sources. Making a recirculation zone with an eddy flow, installed the reducing velocity devices such as the bluff body, is the typical method of the flame stabilization. Recently using a cavity flame stabilization at the wall is an emerging technique as an effective method which extends the stabilization zone, and the related research papers have been published on the flow separation and reattachment, pressures and oscillations including length/depth ratios in the cavities. Even though, still there are lots of topics to study more in the cavity flame stabilization field as the preceding techniques, as well as the research and the development of the airbreathing propulsion system itself.

• Knowledge Management Research
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• v.19 no.4
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• pp.59-76
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• 2018

With the arrival of the big data era, customer data and data mining analysis have gradually dominated the process of Customer Relationship Management (CRM). This phenomenon indicates that customer data along with the use of information techniques (IT) have become the basis for building a successful CRM strategy. However, some companies can not discover valuable information through a large amount of customer data, which leads to the failure of making appropriate business strategy. Without suitable strategies, the companies may lose the competitive advantage or probably go bankrupt. The purpose of this study is to propose CRM strategies by segmenting customers into VIPs and Non-VIPs and identifying purchase patterns using the the VIPs' transaction data and data mining techniques (K-means clustering and association rules) of online shopping mall in Korea. The results of this paper indicate that 227 customers were segmented into VIPs among 1866 customers. And according to 51,080 transactions data of VIPs, home product and women wear are frequently associated with food, which means that the purchase of home product or women wears mainly affect the purchase of food. Therefore, marketing managers of shopping mall should consider these shopping patterns when they build CRM strategy.