Purpose - Aviation control, navigation, and aircraft control in the air transportation area are very specialized. Each part is in progress for safety, efficiency, automation, and further. On the other hand co-work among each part including knowledge sharing has been inattentive for many reasons. The purpose of this research is to show how practicians and professionals in the air transportation area perceive the issue of knowledge sharing and to recall the necessity of knowledge sharing in the area. And we try to find ways to activate the knowledge sharing in the area. Research design, data, methodology - For the research, we inquired into whether practicians and professionals think knowledge sharing can effect safe aviation positively or not and what steps are necessary to activate knowledge sharing in the area. We adopted survey method using questionnaires for current practicians and interview for specialists. The survey and interview results were analyzed using regression analysis and AHP method. The interview for specialists and analyzing the results using AHP was to investigate what are the precedence factors to activate the knowledge sharing. Results - First, practicians perceive that knowledge sharing will affect aviation safe positively. Second objective knowledges such as, tower air traffic control procedure of aviation control area, flight principle and structure of aircraft control area, instrument landing system of navigation area, for knowledge sharing of each area were identified. Also the precedence factors such as, knowledge absorbability of personal factor, personal expectation of result of expectation factor, leadership of management of Structure factor, method of knowledge spread of application factor for knowledge sharing were found. Conclusions - Knowledge sharing for practicians and professionals in the aviation area is very important especially from the perspective of safety. However, for various many reasons including the environment of each special area that focusing on their own area, knowledge sharing has not been emphasized. We found that practicians in the area feel that knowledge sharing is necessary and helpful. For it, each practician's active participation is the most important and many ways such as chatting room to share knowledge are to be developed. And the organization culture should be changed to encourage knowledge sharing.
In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.
The Journal of Asian Finance, Economics and Business
/
v.7
no.11
/
pp.557-561
/
2020
This paper explores the attitudes of accounting students toward knowledge sharing at Umm Al-Gura University for the academic year 2013-2014. The study explored knowledge sharing among 202 accounting students at Umm Al-Gura University in session during the 2013-2014 academic year. Primary data came from a 3-item questionnaire collected from students; secondary data were source from scholarly publication. Descriptive statistics was used. The findings of this study revealed that the students had a medium to high degree of positive attitude toward knowledge sharing. The students had a positive perception of the use of knowledge sharing in supporting their education. The findings are essential for several stakeholders, such as university policymakers, lecturers, and the students, to provide a deeper understanding of knowledge sharing at the university education level. The findings may encourage policymakers at the university and the classroom levels to organize activities that promote knowledge sharing such as seminars, symposiums, or knowledge sharing exercises during the classroom hours to raise the students' knowledge sharing behavior and enhance education. The results of this study should be useful to policy makers at the university level and the classroom level as there is a positive attitude in disseminating knowledge in the higher educational setting.
In this research, we proposed the mechanism to develop self evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most former researchers tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, thy have some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, many of researchers had tried to develop an automatic knowledge extraction and refining mechanisms. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, in this study, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference. Our proposed mechanism has five advantages empirically. First, it could extract and reduce the specific domain knowledge from incomplete database by using data mining algorithm. Second, our proposed mechanism could manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it could construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems). Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic. Fifth, RDB-driven forward and backward inference is faster than the traditional text-oriented inference.
Purpose - This study empirically investigates how the effects of localized knowledge spillovers on technology adoption are conditional on the organizational capabilities of potential adopters. Design/methodology - The empirical model utilized in this study examines how the presence of prior adopters of advanced manufacturing technologies affects a plant's technology adoption decision differently based on its organizational capabilities, measured by plant size and plant status (single-plant firm vs. multi-plant firm). Moreover, this study investigates how the scope of knowledge spillovers from prior adopters, both in terms of geographical and functional proximities, differ for plants with different organizational capabilities. Findings - The main findings of this study are as follows: 1. Although plants with lower organizational capabilities are less likely to adopt advanced technologies, such plants receive greater marginal benefits from knowledge spillovers from prior adopters in their region. 2. Plants with greater organizational capabilities can benefit from knowledge spillovers from a wider set of prior adopters. In other words, while plants with lower organizational capabilities tend to benefit from knowledge spillovers from "similar" and "local" adopters, plants with greater organizational capabilities can also benefit from knowledge spillovers from "not-too-similar" or are geographically distant prior adopters. Originality/value - While existing studies mainly focus on the effects of the various kinds of regional agglomeration, few studies investigate localized knowledge spillovers in technology adoption. Moreover, no prior studies have explored how the effects of knowledge spillovers on technology adoption depend on a plant's organizational capabilities and how the scope of knowledge spillovers differs for plants with different organizational capabilities. This study is the first to empirically investigate this topic.
Purpose: Business education is in high demand whereas knowledge is critical for an individual's professional development in general, and for teachers in particular. In this research, the effect of the distributions of teachers' business knowledge on schools' achievement were investigated. Research design, data and methodology: This study employs a quantitative method to investigate the level of business knowledge distributions of teachers on schools' achievement. 155 business studies subject teachers were categorised into 66 respective schools to measure the correlation and regression between teachers' business knowledge distribution and schools' achievement. Results: The results of the study show that there is a significant relationship between school achievement from the aspect of teachers' business knowledge distributions, with the score of, r = 0.345, p < 0.05. The value of R2 shows a moderate relationship between the teachers' knowledge distributions on school achievement but still plays a role in determining the measurement of the school's level of achievement. Conclusions: It is concluded that the relationship between teacher's business knowledge and school achievement in the subject of Business Studies is significant. This study proves that the teacher's knowledge about business is very important in guaranteeing the success of students who took this subject.
This comparative study conducted to examine the differences between Korean and Chinese consumers. The specific goals of the study were as follows; First, It was to investigate the influences of COO(Country of Origin) image on the customer…s buying intention through the brand association knowledge. It is also aimed at analyzing the moderating effects of consumer's ethnocentrism on the influence of brand association knowledge on the buying intention. To test the hypotheses, 117 questionnaires were collected from university students in Korea and 119 questionnaires did from China and put to the test with SPSS 17.0 and AMOS 7.0. The results indicated the followings: For consumers in both countries, the COO image had not influences on the buying intention. For Korean consumers the COO image had positive impacts on the brand association knowledge, which in turn had positive impacts on the buying intention. For Chinese consumer, COO image did not have influences on the brand association knowledge, but the brand association knowledge had positive impact on the buying intention. In addition, the consumer's ethnocentrism had moderating effects on the influences of the brand association knowledge on the buying intention.
Park, Sang-Tae;Lee, Hee-Bok;Jeong, Kee-Ju;Kim, Seok-Cheon
Journal of The Korean Association For Science Education
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v.27
no.4
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pp.346-353
/
2007
In order to be efficient in teaching, a teacher should understand the current learner's level through diagnostic evaluation. This study has examined the major issues arising from the noble diagnostic assessment tool based on the theory of knowledge space. The knowledge state analysis method is actualizing the theory of knowledge space for practical use. The knowledge state analysis method is very advantageous when a certain group or individual student's knowledge structure is analyzed especially for strong hierarchical subjects such as mathematics, physics, chemistry, etc. Students' knowledge state helps design an efficient teaching plan by referring their hierarchical knowledge structure. The knowledge state analysis method can be enhanced by computer due to fast data processing. In addition, each student's knowledge can be improved effectively through individualistic feedback depending on individualized knowledge structure. In this study, we have developed a diagnostic assessment test for measuring student's learning outcome which is unattainable from the conventional examination. The diagnostic assessment test was administered to middle school students and analyzed by the knowledge state analysis method. The analyzed results show that students' knowledge structure after learning found to be more structured and well-defined than the knowledge structure before the learning.
The purpose of this study is to examine consumer characteristics according to analyze the level of consumer knowledge, skill, and consciousness through the comparison between young-elderly people and elderly people in Cheju. For the empirical analysis, the data was collected 428 consumers from May to June, 1999. The statistical methods for this study were descriptive statistics, t-test, ANOVA, correlation using SPSS Win program. The major findings of this study were as follows; 1) The level of consumer consciousness was very high, but the level of consumer knowledge and consumer skill were low. 2) Drug un, Recall system, Frozen-food management, Indication for consumer knowledge; Planning, Discontent treatment for consumer skill; Responsibility for consumer consciousness area were very low state. 3) Correlation according to Pearson's γ²were positive relationship between all of that consumer knowledge and consumer skill and consumer consciousness areas. 4) Sum of 3 findings were no great difference between young-elderly people and elderly people. From now on, some suggestions from this study how to stress on the consumer knowledge and consumer skill as well as consumer consciousness of the elderly in Cheju.
The purpose of this study was to obtain the basic information needed for an effective program of nutrition education and the establishment of desirable dietary attitudes in elementary school children. The study was conducted using a self-administered questionnaire, and the participants were 281 elementary school children. The data were analyzed in terms of the participants' gender and level of nutritional knowledge, and group differences were assessed using chi-square and Duncan's multiple range tests. The results were as following: Male and female students did not differ in nutritional knowledge. In terms of health-related life style, there were significant differences according to gender and nutrition knowledge. In terms of dietary habits, there were significant differences in the regularity of meal times according to gender and nutrition knowledge. With regard to food preferences, there was a significant gender difference in taste preferences with the male students preferring a salty taste more than the female students.
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