• Proceedings of the KSRS Conference
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• v.2
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• pp.852-855
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• 2006

There is an increasing need to use data from different sensors in order to maximize the chances of obtaining a cloud-free image and to meet timely requirements for information. However, the use of data from multiple sensor systems is depending on comprehensive relationships between sensors of different types. Indeed, a study of inter-sensor relationships is well advanced in the effective use of remotely sensed data from multiple sensors. This paper was concerned with relationships between sensors of different types for vegetation indices (VI). The study was conducted using IKONOS and Landsat-7 ETM+ images. IKONOS and Landsat-7 ETM+ image of the same or about the same dates were acquired. The Landsat-7 ETM+ images were resampled in order to make them coincide with the pixel sizes of IKONOS. Inter-relationships of vegetation indices between images were performed using at-satellite reflectance obtained by converting image digital number (DN). All images were applied to topographic normalization method in order to reduce topographic effect in digital imagery. Also, Inter-sensor model equations between two sensors were developed and applied to other study region. In the result, the relational equations can be used to compute or interpret VI of one sensor using the VI of another sensor.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.109-124
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• 2003

Although most commercial relational DBMSs Provide a graphical query language for the user friendly interfaces of the databases, few research has been done for graphical query languages in object databases. Expressing complex query conditions in a concise and intuitive way has been an important issue in the design of graphical query languages. Since the object data model and object query languages are more complex than those of the relational ones, the graphical object query language should have a concise and intuitive representation method. We propose a graphical object query language called GOQL (Graphical Object Query Language) for object databases. By employing simple graphical notations, advanced features of the object queries such as path expressions including set attributes, quantifiers, and/or methods can be represented in a simple graphical notation. GOQL has an excellent expressive power compared with previous graphical object query languages. We show that path expressions in XSQL(1,2) can be represented by the simple graphical notations in GOQL. We also propose an algorithm that translates a graphical query in GOQL into the textual object query with the same semantics. We finally describe implementation results of GOQL in the Internet environments.

• Journal of the Korean Society of Food Culture
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• v.20 no.5
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• pp.561-573
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• 2005

This research is to examine the structural relationships between transformational/transactional leadership, empowerment, relationship quality, and organizational commitment in Chinese restaurant context. In order to empirically investigate the proposed model, the data were collected from 188 respondents randomly selected from among the managers who work in 188 Chinese restaurants in Seoul and Kyonggi-do, which registered in Korean Food Central Association, korean foodservice management Association, Menupan.com We choose to limit our investigation to luxury Chinese restaurants where the average check is above 12,000 won. The survey was executed during two-week period in the autumn of 2004. The findings and discussion are as follows: First, intellectual stimulus behavior of transformational leadership had a positive effect on empowerment. Second, contingent reward leadership had a positive effect on empowerment. Third, empowerment had a positive effect on affective organizational commitment. Fourth, empower had a negative effect on continuous organizational commitment. Fifth, intellectural stimulus behavior of transformation leadership had a positive effect on affective organizational commitment indirectly and had a negative effect on continuous organizational commitment indirectly through mediating role of empowerment. Finally, contingent reward leadership had a positive effect on affective organizational commitment indirectly and had a negative effect on continuous organizational commitment indirectly through mediating role of empowerment. At the end of this paper, managerial implications, discussions, and limitations and future research directions are presented.

• Fashion & Textile Research Journal
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• v.21 no.3
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• pp.346-355
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• 2019

This study aimed to determine the factors of the make-up artist experience and establish their effects on brand loyalty through the mediation of trust and brand satisfaction. The step of first surveyed the make-up artist experience level through precedent research and made concept frame of study. The step of second checked up the effects of make-up artist experience through the desires for change. The step of third established to the effects of brand loyalty through make-up artist experience brand through mediation of make-up artist trust and brand satisfaction. The survey was carried out on 440 women aged 20 to 40 who experienced make-up services in Seoul, Gyeonggi-do, Sejong and Daejeon. The data were analyzed using SPSS 23.0, and AMOS 18.0 using frequency analysis, factor analysis, reliability analysis, structural model analysis and t-tests. 1)Make-up artist experiences were divided into informational/ relational experiences and emotional experiences. 2)Desires for change influenced positive effects about information/relational experience and emotional experience. 3)The information/relation experiences influenced positive effects about artist trust and brand satisfaction. 4)The emotional experiences influenced positive effects about make-up artist trust and brand satisfaction. 5) The make-up artist trust influenced positive effects about brand satisfaction. Trust in the make-up artist did not directly influence brand loyalty, but influenced it through satisfaction. 6)The brand satisfaction influenced positive effects about brand loyalty. This study identified the roles of make-up artist and the importance of the make-up experience.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.9
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• pp.647-658
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• 2018

Modern society is complex and rapidly changing, and knowledge sharing is needed to acquire and create knowledge. Knowledge sharing is the act of providing information knowledge and know-how of their own in order to cooperate with or help their colleagues. This study presents a research model using social capital theory to explain the mobile knowledge sharing behavior of virtual community members. Based on previous studies, social capital theory is divided into structural, relational, and cognitive aspects. It was composed of social interaction ties as a measure of structural aspect, trust as a measure of cognitive aspect, shared language, shared vision and relational aspect. After collecting survey data, factor analysis and regression analysis were performed using SPSS 22. In this way, we examined how the detailed factors of social capital affect information sharing behavior and how the level of knowledge sharing affects community promotion. The results showed that social interaction ties, shared language, shared vision, and trust affect knowledge sharing. Knowledge sharing has had a positive impact on community promotion.

• The Journal of Information Systems
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• v.27 no.1
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• pp.171-191
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• 2018

Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology' carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME's technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.31-47
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• 2008

As OWL(Web Ontology Language) has been selected as a standard ontology description language by W3C, many ontologies have been building and developing in OWL. The lena developed by HP as an Application Programming Interface(API) provides various APIs to develop inference engines as well as storages, and it is widely used for system development. However, the storage model of Jena2 stores most owl documents not acceptable into a single table and it shows low processing performance for a large ontology data set. Most of all, Jena2 storage model does not consider hierarchical structures of classes and properties. In addition, it shows low query processing performance using the hierarchical structure because of many join operations. To solve these issues, this paper proposes an OWL ontology relational database model. The proposed model semantically classifies and stores information such as classes, properties, and instances. It improves the query processing performance by managing hierarchical information in a separate table. This paper also describes the implementation and evaluation results. This paper also shows the experiment and evaluation result and the comparative analysis on both results. The experiment and evaluation show our proposal provides a prominent performance as against Jena2.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.598-605
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• 2018

Behavior awareness is a technology that recognizes human behavior through data and can be used in applications such as risk behavior through video surveillance systems. Conventional behavior recognition algorithms have been performed using the 2D camera image device or multi-mode sensor or multi-view or 3D equipment. When two-dimensional data was used, the recognition rate was low in the behavior recognition of the three-dimensional space, and other methods were difficult due to the complicated equipment configuration and the expensive additional equipment. In this paper, we propose a method of recognizing human behavior using only CCTV images without additional equipment using only RGB and depth information. First, the skeleton extraction algorithm is applied to extract points of joints and body parts. We apply the equations to transform the vector including the displacement vector and the relational vector, and study the continuous vector data through the RNN model. As a result of applying the learned model to various data sets and confirming the accuracy of the behavior recognition, the performance similar to that of the existing algorithm using the 3D information can be verified only by the 2D information.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1095-1101
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• 2008

The desirable method to diagnose abnormal blood pressure is to measure and manage blood pressure continuously and regularly. However, the sphygmomanometers that are based on a cuff have faults in that they can not measure the blood pressure continuously and they cause an unpleasant feeling. Therefore, it is essential to develop a new measuring method that causes no pain and that can obtain blood pressure continuously without any unpleasant feeling. Thus, we propose here a regression method to estimate the systolic blood pressure by using the PTTL(pulse transit time on leg) with some body parameters which are chosen from the relational analysis with systolic blood pressure. The data we use to make the regression model were obtained in triplicate from each of 50 males who were from 18 to 35 years. And we made estimation experiments of blood pressure on 10 males who did not take part in the making the regression model. According to the results, the proposed method showed a mean error of 4.00 mmHg and the standard variance was 2.45 mmHg. When we comparing the results of the proposed method with the rule of American National Standards Institute of the Association of the Advancement of Medical Instruments(ANSI/AAMI), the results satisfied the rule of a mean error less than 5 mmHg and a standard variance less than 8 mmHg. Therefore we were able to validate the usefulness of the proposed method.

• Asia pacific journal of information systems
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• v.15 no.4
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• pp.165-192
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• 2005

This study introduces how to estimate the monetary value of intellectual capital of a public research institute by incorporating a non-market valuation technique, the choice experiments(CE). CE is a survey-based environmental valuation technique that has increasingly been popular over the last decade. The members of institute E, a typical type of public research institutes in Korea, were surveyed, before the data were fit to the conditional logit and mixed logit models. The total value of the institute's intellectual capital was estimated at approximately W3,377 billion for the year 2003. The institute's human, structural and relational capitals that comprise the intellectual capital were estimated at W18.7 billion, W10.7 billion and W4.4 billion respectively, for each of the components' index values improving by 1%. The human capital was placed a higher value than the other two. The study also shows that CE is a flexible technique that enables the researcher to estimate the monetary value of the intellectual capital whatever the index values of the component capitals and to interpret model estimation results more in depth by incorporating the mixed logit, a state-of-the-art discrete choice model, than the conventional conditional logic.