• Korean journal of food and cookery science
• /
• v.19 no.2
• /
• pp.155-164
• /
• 2003

The purpose of this study was to examine, in a service context, construct validity and generalizability of widely used and accepted measures of perceived organizational support, job satisfaction, organizational commitment, and service duality, and to test each measures' predictive utility in this context with path analysis. Of 350 subjects, 309 subjects participated in the analysis. Descriptive statistics (frequencies), exploratory factor analysis, reliability analysis, zero-order partial correlation analysis, and confirmatory factor analysis were used for this study. The findings from this study are as follows. First, perceived organizational support significantly influenced job satisfaction, organizational commitment. and service quality. Second, Job satisfaction had a directional impact upon organizational commitment and service quality. Third, organizational commitment showed to have a predictive impart on service quality. Finally, the results of the study provide some insight into the types of internal marketing strategies that can be applied successfully by operators of hotel F & B departments.

• Journal of KIISE:Software and Applications
• /
• v.35 no.10
• /
• pp.636-652
• /
• 2008

In this paper, we present a modular pointer analysis algorithm based on the update history. We use the term 'module' to mean a set of mutually recursive procedures and the term 'modular analysis' to mean a program analysis that does not need the source codes of the other modules to analyze a module. Since a modular pointer analysis does not utilize any information on the callers, it is difficult to design a precise analysis that does not lose the information related to the program flow or the calling context. In this paper, we propose a modular and flow- and context-sensitive pointer analysis algorithm based on the update history that can memory states of a procedure independently of the information on the calling context and keep the information on the order of side effects performed. Such a memory representation not only enables the analysis to be formalized as a modular analysis, but also helps the analysis to effectively identify killed side effects and relevant alias contexts.

• School Mathematics
• /
• v.17 no.3
• /
• pp.493-513
• /
• 2015

This study is based on the perspective that tasks in local and global contexts are important to raise students' ability to mathematically analyze and solve diverse phenomena and social issues as members of future civil society. Therefore, this study analyzes 880 real world tasks from 13 types of 7th grade textbook based on 2009 revised Curriculum. As a result of analyzing tasks by using 3 types of context category and 9 types of ways as analysis framework and allowing repetitive coding, personal context was most frequent in the context of Younbokhap. In level of Integrated ways of Yungbokhap, sequential model in which other subjects' topics were not directly related to mathematics problem or presented in simple description is most frequent. The result shows that the textbooks are too limited to develop learner's competencies. Through such analysis result, we discuss about the necessity and methods of developing tasks which allow learners to study further in future society and global context and which connect other subjects' knowledge and social issue with mathematics in deeper level.

• Journal of the Korean Institute of Rural Architecture
• /
• v.22 no.3
• /
• pp.1-8
• /
• 2020

This paper takes Zhaoxing Dong village in Guizhou Province as the research object. The purpose is to study the continuity of landscape context in Dong Village. The research process includes specification on the evaluation system of Dong village landscape context by AHP method, and use of the questionnaire survey method in sequence, according to the specific situation of Zhaoxing Dong village, and this study develops a specific questionnaire that modifies the evaluation system suited to reflect specific problems. Through the analysis of the specific questionnaire and recycling in Zhaoxing Dong village, this study found that Zhaoxing Dong village as a whole is over commercialized due to the vigorous development of tourism service industry. As a result, whether it is experts, foreign tourists or local villagers, the rating of the village landscape is low. There are three problems in the village landscape context: historical continuity, invisible cultural heritage and contradiction in protection and development. The results of this paper provides a future direction for the protection and inheritance of Zhaoxing Dong village.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.6
• /
• pp.63-69
• /
• 2016

In this paper, we proposed the location tracking system based on MS-Based/Assisted(Mobile Station-Based and Assisted) location trigger service model with context-awareness for the intelligent location tracking of moving objects. It provides the proper resulting value that matches the context of users through the analysis about the situation of the user, physical environment, computing resource and the existing information on user input. In order to provide real-time data, we proposed the location tracking system which realizes the intelligent information such as the expecting arrival time and passing the specific area of the moving object by adopting the location trigger. So, it derives to minimize the costs of communication for the mobile object tracking applications. The proposed location tracking system based on context-awareness can be used for realtime monitoring, intelligent alarm/action, setting up of the optimized moving path, dynamic adjustment of strategies and policies. So it has the advantage to develop the application system which is aimed at optimization of the object tracking and movement.

• The Journal of the Acoustical Society of Korea
• /
• v.33 no.4
• /
• pp.248-254
• /
• 2014

Among acoustic signal analysis tasks, acoustic context awareness is one of the most formidable tasks in terms of complexity since it requires sophisticated understanding of individual acoustic events. In conventional context awareness methods, individual acoustic event detection or recognition is employed to generate a relevant decision on the impending context. However this approach may produce poorly performing decision results in practical situations due to the possibility of events occurring simultaneously or the acoustically similar events that are difficult to distinguish with each other. Particularly, the babble noise acoustic event occurring at a bus or subway environment may create confusion to context awareness task since babbling is similar in any environment. Therefore in this paper, a frequency-cepstral feature vector is proposed to mitigate the confusion problem during the situation awareness task of binary decisions: bus or metro. By employing the Support Vector Machine (SVM) as the classifier, the proposed feature vector scheme is shown to produce better performance than the conventional scheme.

• KIPS Transactions on Software and Data Engineering
• /
• v.4 no.9
• /
• pp.409-418
• /
• 2015

In order to delivery of the correct information in IoT environment, it is important to deduce collected information according to a user's situation and to create a new information. In this paper, we propose a control access scheme of information through context-aware to protect sensitive information in IoT environment. It focuses on the access rights management to grant access in consideration of the user's situation, and constrains(access control policy) the access of the data stored in network of unauthorized users. To this end, after analysis of the existing research 'CP-ABE-based on context information access control scheme', then include dynamic conditions in the range of status information, finally we propose a access control policy reflecting the extended multi-dimensional context attribute. Proposed in this paper, access control policy considering the dynamic conditions is designed to suit for IoT sensor fusion environment. Therefore, comparing the existing studies, there are advantages it make a possible to ensure the variety and accuracy of data, and to extend the existing context properties.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.7
• /
• pp.37-45
• /
• 2013

Context dependent fusion (CDF) is a fusion algorithm that combines multiple outputs from different classifiers to achieve better performance. CDF tries to divide the problem context into several homogeneous sub-contexts and to fuse data locally with respect to each sub-context. CDF showed better performance than existing methods, however, it is sensitive to noise due to the large number of parameters optimized and the innate linearity limits the application of CDF. In this paper, a variant of CDF using support vector machines (SVMs) for fusion and kernel principal component analysis (K-PCA) for context extraction is proposed to solve the problems in CDF, named CDF-SVM. Kernel PCA can shape irregular clusters including elliptical ones through the non-linear kernel transformation and SVM can draw a non-linear decision boundary. Regularization terms is also included in the objective function of CDF-SVM to mitigate the noise sensitivity in CDF. CDF-SVM showed better performance than CDF and its variants, which is demonstrated through the experiments with a landmine data set.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.3
• /
• pp.368-374
• /
• 2010

Image segmentation is the basic step in the field of the image processing for pattern recognition, environment recognition, and context analysis. The Otsu's automatic threshold selection, which determines the optimal threshold value to maximize the between class scatter using the distribution information of the normalized histogram of a image, is the famous method among the various image segmentation methods. For the automatic threshold selection proposed by Otsu, it is difficult to determine the optimal threshold value by considering the sub-region characteristic of the image because the Otsu's algorithm analyzes the global histogram of a image. In this paper, to alleviate this difficulty of Otsu's image segmentation algorithm and to improve image segmentation capability, the original image is divided into several sub-images by using context fuzzy c-means algorithm. The proposed fuzzy Otsu threshold algorithm is applied to the divided sub-images and the several threshold values are obtained.

• Journal of Digital Convergence
• /
• v.19 no.10
• /
• pp.119-132
• /
• 2021

This study focused on examining the impact of the social context that causes gender differences in entrepreneurship, not the phenomenon itself. Specifically, this study verified the moderating effect of the social context on the relationship between gender and entrepreneurship using data from 20 countries in the Global Entrepreneurship Trend Report (GETR). In order to test hypotheses involving social context implications, Hofstede's cultural dimension factors such as power distance, individualism, masculinity, and uncertainty avoidance variables, and institutional factors such as gender equality and social security are used as specific variables reflecting the social context. Empirical analysis through GLM found that gender did not independently influence entrepreneurship, and gender had a significant effect by interacting with power distance, individualism, uncertainty avoidance, gender equality, and social security variables, respectively. Such empirical results show that the gender difference in entrepreneurship is not due to the unique characteristics inherent in each gender but on the level of the country's social context to which the individual belongs.