• Journal of Distribution Science
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• v.17 no.8
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• pp.5-14
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• 2019

Purpose - This study aims to proposes a conceptual framework to segment multi-national products based on a Chinese consumer's perception of multi-national products, to find the role of consumer ethnocentrism (CET) in country of origin (COO) effects for Chinese, and to figure out how different dimension of CET Effects on purchase intention developed market and home country. Research design, data and methodology - This study selected a 2×2×2 factorial design for the hypothesis test based on the product category × combination of manufactured type × Ethnocentrism level. This study distinguishes products between luxury (Burberry) and non-luxury (Nike) products and choose combination of manufactured type (Spain vs India/ Spain vs China) in order to perform comparative studies. A total of 223 Chinese participated in the experiment. After being exposed to each scenario, participants were asked to respond to questions about brand preference and purchase intention Results - Regarding to luxury made in developed country, it is worth that exposing COO information to low level of ethnocentrism consumers. Regarding to non-luxury product made in emerging country, it makes it worse when COO information to high level of ethnocentrism consumers. Lastly, regarding to non-luxury product, patriotic consumers prefer to purchase product made in home country.

• Knowledge Management Research
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• v.20 no.4
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• pp.75-97
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• 2019

In the rapidly changing business environment, knowledge has been recognized as a core asset for sustaining an organization's competitive advantage. In addition, knowledge sharing is one of the key elements of knowledge management, emphasizing external knowledge sharing beyond initial internal knowledge sharing. However, while knowledge management research emphasizes knowledge sharing, which is a positive aspect, research on preventing knowledge leakage that can have negative consequences is relatively lacking. Companies have tried to minimize the negative effects of knowledge management but many knowledge leakage accidents are still occurring. Therefore, this study aims to examine the effects of external factors based on deterrence theory and internal factors based on self-determination theory on knowledge leakage intention focusing on tacit knowledge. The results of the empirical analysis of 100 data sets collected through a scenario-based survey show that certainty of sanctions, social disapproval, and competence are found to have a significant effect on reducing tacit knowledge leakage intention. Furthermore, informal sanctions have a greater impact on tacit knowledge leakage intention than formal sanctions and external factors have a greater effect on tacit knowledge leakage intention than internal factors.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.50-53
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• 2016

Image processing techniques play an increasingly important role in many aspects of our daily life. For example, it has been shown to improve agricultural productivity in a number of ways such as plant pest detecting or fruit grading. However, massive quantities of images generated in real-time through multi-devices such as remote sensors during monitoring plant growth lead to the challenges of big data. Meanwhile, most current image processing systems are designed for small-scale and local computation, and they do not scale well to handle big data problems with their large requirements for computational resources and storage. In this paper, we have proposed an IPABigData (Image Processing Algorithm BigData) platform which provides algorithms to support large-scale image processing in agriculture based on Hadoop framework. Hadoop provides a parallel computation model MapReduce and Hadoop distributed file system (HDFS) module. It can also handle parallel pipelines, which are frequently used in image processing. In our experiment, we show that our platform outperforms traditional system in a scenario of image segmentation.

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.2
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• pp.331-342
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• 2009

The purposes of this study were to provide the apparel companies with a effective marketing strategy by identifying the present condition of loyalty programs and designing the type of reward and the timing of reward, and to investigate the effects of loyalty programs on customers' satisfaction and loyalty. The experimental study was conducted to examine the relationship between loyalty programs and performances. The experiment, which adopted a scenario methodology, was a 2(type of rewards)${\times}$2(timing of rewards) between subjects factorial design. The sample was based on 362 college students. The data analysis was completed on the basis of SPSS 12.0 package, using descriptive analysis, frequency, factor analysis, Cronbach's a, ANOVA, and regression analysis. The following results were found in this research. First the respondent's recognition of reward(benefit, reserve fund, experience) was not relatively high. Second, the interaction effect of type of rewards and timing of rewards on the loyalty programs' satisfaction(p<.01) and customer loyalty(p<.001) was significant, but that on customer satisfaction was not significant. Finally, loyalty programs' satisfaction positively affected customer satisfaction and loyalty. The implications of the research and directions for future researchers were discussed.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.1
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• pp.35-44
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• 2017

Supercavitation is one of the most attractive technologies to achieve high speed for underwater vehicles. However, the multiphase flow with high-speed around the supercavitating vehicle (SCV) is difficult to simulate accurately. In this paper, we use modified the turbulent viscosity formula in the Standard K-Epsilon (SKE) turbulent model to simulate the supercavitating flow. The numerical results of flow over several typical cavitators are in agreement with the experimental data and theoretical prediction. In the last part, a flying SCV was studied by unsteady numerical simulation. The selected computation setup corresponds to an outdoor supercavitating experiment. Only very limited experimental data was recorded due to the difficulties under the circumstance of high-speed underwater condition. However, the numerical simulation recovers the whole scenario, the results are qualitatively reasonable by comparing to the experimental observations. The drag reduction capacity of supercavitation is evaluated by comparing with a moving vehicle launching at the same speed but without supercavitation. The results show that the supercavitation reduces the drag of the vehicle dramatically.

• Journal of Korean Society for Quality Management
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• v.42 no.1
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• pp.63-70
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• 2014

Purpose: This article introduces a case study of using Taguchi Method to improve lecture satisfaction. Developed by Taguchi Genichi, this method has its strength in finding the control factor that is robust against noise factor. Finding the condition for such control factor has an effect of reducing the dispersion of the Lecture satisfaction. Methods: There are various factors in university classrooms. The factors which influenced the Lecture Satisfaction are analyzed by control factors and noise factors, control factors which is controllable are lecture completeness and thoroughly test the degree of supervision and noise factors which is not controllable is degree of physical and psychological Lecturer tired, then the experiment is conducted as guided by Taguchi's experimental design, one semester are experimented by eight professor with 2 classes, after discussion of the results the optimal lecture condition is suggested. Results: To improve Lecture Satisfaction under noise factor of physical and psychological Lecturer tired, optimal condition are that lecture completeness have scenario note during lecture and thoroughly test the degree of supervision have two proctors during test. Conclusion: In this paper, we have succession case by applying Taguchi methods in Lecture Satisfaction. We can apply to improve service by applying the Taguchi methods. In the future we hope to have many succession cases.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.545-559
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• 2010

This paper presents the results of a pilot study and verification of a concept of a novel methodology for damage detection and assessment of water distribution system. The unique feature of the proposed noninvasive methodology is the use of accelerometers installed on the pipe surface, instead of pressure sensors that are traditionally installed invasively. Experimental observations show that a sharp change in pressure is always accompanied by a sharp change of pipe surface acceleration at the corresponding locations along the pipe length. Therefore, water pressure-monitoring can be transformed into acceleration-monitoring of the pipe surface. The latter is a significantly more economical alternative due to the use of less expensive sensors such as MEMS (Micro-Electro-Mechanical Systems) or other acceleration sensors. In this scenario, monitoring is made for Maximum Pipe Acceleration Gradient (MPAG) rather than Maximum Water Head Gradient (MWHG). This paper presents the results of a small-scale laboratory experiment that serves as the proof of concept of the proposed technology. The ultimate goal of this study is to improve upon the existing SCADA (Supervisory Control And Data Acquisition) by integrating the proposed non-invasive monitoring techniques to ultimately develop the next generation SCADA system for water distribution systems.

• Structural Engineering and Mechanics
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• v.50 no.5
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• pp.617-633
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• 2014

Because the elevated temperature degrades the mechanical properties of materials used in containments, the global behavior of containments subjected to the internal pressure under high temperature is remarkably different from that subjected to the internal pressure only. This paper concentrates on the nonlinear finite element analyses of the nuclear power plant containment structures, and the importance for the consideration of the elevated temperature effect has been emphasized because severe accident usually accompanies internal high pressure together with a high temperature increase. In addition to the consideration of nonlinear effects in the containment structure such as the tension stiffening and bond-slip effects, the change in material properties under elevated temperature is also taken into account. This paper, accordingly, focuses on the three-dimensional nonlinear analyses with thermal effects. Upon the comparison of experiment data with numerical results for the SNL 1/4 PCCV tested by internal pressure only, three-dimensional analyses for the same structure have been performed by considering internal pressure and temperature loadings designed for two kinds of severe accidents of Saturated Station Condition (SSC) and Station Black-out Scenario (SBO). Through the difference in the structural behavior of containment structures according to the addition of temperature loading, the importance of elevated temperature effect on the ultimate resisting capacity of PCCV has been emphasized.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1494-1507
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• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.3
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• pp.51-59
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• 2008

The biometrics has been researched as a means for authenticating user's identity. Among the biometrics schemes for face recognition, the eigenvector-based schemes, which use eigenvector made from training data for transforming test data to abstracted data, are widely adopted. From those schemes, however, it is hard to expect cancelable feature, which is a general concept for security in the biometrics. In this paper, we point out the security problem that is the recovery of valuable face information from the abstracted face data and consider a possible attack scenario by showing our experiment results.