• Asian Pacific Journal of Cancer Prevention
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• v.17 no.8
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• pp.3983-3988
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• 2016

Background: Cervical cancer though preventable is still the leading cause of cancer death among women secondary to breast cancer. Persistent infection with HPV has been causally linked to the disease. A school based HPV vaccination program was introduced in late 2010 in Malaysia and nurse support is essential for its success. Objectives: To determine nurses knowledge and attitudes about HPV infection and its vaccines, and factors associated with their knowledge. Materials and Methods: This cross-sectional study was conducted among nurses working at primary health clinics in Kelantan from mid-June till the end of July 2014. Its involved 330 nurses selected through multistage random sampling. A validated self-administered questionnaire consisting of 11 items for the knowledge domain and eight items for the attitude domain was used. Results: The response rate of the study was 93.7%. The mean knowledge and mean attitude (SD) scores were 5.37 (1.76) and 29.8 (3.51) respectively. Only 24% knew that HPV is the most common sexually transmitted infection and 67% correctly answered that Gardasil vaccine can protect against four types of HPV. Nearly 60% of participants wrongly answered that HPV vaccines cannot be offered to sexually active women. Likewise, 70.9% participants were not aware that HPV vaccine may be appropriate for females aged 9 through 26 years. Though 90% of participants believed that the vaccine is safe, nearly half of them were unsure about efficacy. From multiple linear regression analysis, among the factors tested only participant's level of education showed a statistically significant association with the HPV knowledge score (p <0.001). Conclusions: This study indicates nurses have favorable attitudes towards HPV vaccination; however they have significant knowledge deficit and major misunderstanding in critical knowledge items. Among the factors tested, nursing qualification is the only factor that is significantly associated with the nurses knowledge score.

• Journal of Science Education
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• v.40 no.1
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• pp.1-16
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• 2016

The purpose of this study is to explore the variables of knowledge, acceptance of theory of evolution and epistemology that could be keys for teaching and learning the theory of evolution within school contexts, and to suggest instructional tips for teaching evolution in relation to the grade levels of education. This cross-sectional study examined the grade level differences (8th, 11th, and preservice teachers) of four variables: evolutionary knowledge; acceptance of theory of evolution; and both domain-specific epistemology (nature of science in relation to evolution) and context-specific epistemology (scientific epistemological views) and their relationships. This study, then, built conceptual models of each grade level students' acceptance of theory of evolution among the factors of evolutionary knowledge and epistemology (both domain-specific and context-specific). The results showed that the scores of evolutionary knowledge, evolution in relation to NOS, and scientific epistemology increased as the grade levels of education go up(p<.05) except the scores of acceptance of theory of evolution(p>.05). In addition, the 8th graders' and the 11th graders' acceptance of evolutionary theory was most explained by 'evolution in relation to NOS', while the preservice teachers' acceptance of evolutionary theory was most explained by evolutionary knowledge. Interestingly, 'scientific epistemological views' were only included for the 8th graders, while evolutionary knowledge and 'evolution in relation to NOS' (context-specific epistemology) were included in explaining all the level of students' acceptance of evolutionary theory. This study implicated that when teaching and learning of the theory of evolution in school contexts, knowledge, acceptance of evolutionary theory and epistemology could be considered appropriately for the different grade levels of students.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.99-124
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• 2015

As the improvement of digital technologies increases the use of images from various fields, the domain of image retrieval has evolved and become a growing topic of research in the Library and Information Science field. The purpose of this study is to identify the knowledge structure of the image retrieval domain by using the author co-citation analysis and author bibliographic coupling as analytical tools in order to understand the domain's past and present. The data set for this study is 245 articles with 8,031 cited articles in the field of image retrieval from 1998 to 2013, from the Web of Science citation database. According to the results of author co-citation analysis for the past of the image retrieval domain, our findings demonstrate that the intellectual structure of image retrieval in the LIS field consists of predominantly user-oriented approaches, but also includes some areas influenced by the CBIR area. More specifically, the user-oriented approach contains six specific areas which include image needs, information seeking, image needs and search behavior, image indexing and access, indexing of image collection, and web image search. On the other hand, for CBIR approaches, it contains feature-based image indexing, shape-based indexing, and IR & CBIR. The recent trends of image retrieval based on the results from author bibliographic coupling analysis show that the domain is expanding to emerging areas of medical images, multimedia, ontology- and tag-based indexing which thus reflects a new paradigm of information environment.

• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.295-312
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• 2012

This research aims to present the ego-centered topic citation analysis, which is a new application of White's ego-centered citation analysis, for analyzing multilayered knowledge structure of a subject domain. An experimental topic citation analysis was carried out on the folksonomy research documents retrieved from Web of Science. Ego-centered topic citation analyses on folksonomy research domain were conducted in three stages: ego-documents set analysis, topic citation identity analysis, and topic citation image analysis. The results showed that the ego-centered topic citation analysis suggested in this study was successfully performed to illustrate the inner and the outer knowledge structures of folksonomy research domain.

• Journal of Korean Academy of Nursing
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• v.35 no.2
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• pp.362-371
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• 2005

Purpose: The aim of this study was to design and evaluate a scale for measuring reliability and validity in the field of oriental nursing education. Method: A questionnaire was administered to 495 university nursing students using a convenience sampling method. The period of time for collecting data was from September 2003 to January 2004. Result: The derived outcome tool consisted of 6 factors and 22 inquires on the basis of a conceptual frame of three domains (knowledge, attitude, and skill), As a result of the item analysis, 22 items were selected and the internal consistency alpha coefficient was .767. The value of Cronbach' Alpha of knowledge(factor 1) was .885, attitude(factor2)was .756, and skill (factor 3) was .610. The three factors accounted for $65.110\%$ of the variance in the total scale. Addressing the explanatory variance of each domain Cognitive domain was $22.477\%$, affective domain was $20.543\%$, and psychomotor domain was $17.090\%$. Conclusion: Further studies need to be done to verify educational evaluation and apply our outcomes to oriental nursing education.

• KIISE Transactions on Computing Practices
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• v.23 no.11
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• pp.611-616
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• 2017

In the area of Information Retrieval, Query Expansion is a well-known technique that uses external knowledge to increase an inquiry generated by users. However, ambiguous words used in the query decrease the performance of search tools. In this paper, we propose a solution to the above problem, by using domain knowledge which identifies the meaning of words in the query. In particular, we present a domain centered query expansion technique that magnifies a query using domains. By comparing with various query expansion models, we demonstrate that the proposed model performs better than the other models.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.139-144
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• 2009

The leveling of technical internet domain term with its aim to accumulate knowledge that machine can comprehend, which has been used widely in recent years. If stratify domain term weight, we believe that machine can manage and analyze in formation on its own using the ontology. In this paper, we propose an algorithm that allows us to extract properties of ontology weight from structured information already existing in web documents. In particular by stratification of the domain knowledge that is composed of property information, we were able to make the algorithm better and improve the quality of extraction results. In our experiments with 50 thousands targeted documents, we were able to extract property information with 94% confidence.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.421-424
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• 1996

To provide an appropriate knowledge representation technique dependent on a particular domain, we consider the combine analytic hierachy process(CAHP). This is an extended method of the conventional AHP which is useful when two different expert groups are involved. Our problem domain is confined to human resource management including such major activities as planning, selection, placement, compensations, performance evaluation, training, and labor-management relations. We prioritize rules, frames, semantic nets, and predicate logic representation techniques best suited to each and all domains through an exploratory study.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.159-177
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• 1995

The objective of this paper is to propose a knowledge-based fuzzy post adjustment so that unstructured problems can be solved more realistically by expert systems. Major part of this mechanism forcuses on fuzzily assessing the influence of various external factors and accordingly improving the solutions of unstructured problem being concerned. For this purpose, three kinds of knowledge are used : user knowledge, expert knowledge, and machine knowledge. User knowledge is required for evaluating the external factors as well as operating the expert systems. Machine knowledge is automatically derived from historical instances of a target problem domain by using machine learning techniques, and used as a major knowledge source for inference. Expert knowledge is incorporate dinto fuzzy membership functions for external factors which seem to significantly affect the target problems. We applied this mechanism to a prototyoe expert system whose major objective is to provide expert guidance for stock market timing such as sell, buty, or wait. Experiments showed that our proposed mechanism can improve the solution quality of expert systems operating in turbulent decision-making environments.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.793-794
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• 2007