• Journal of the Korean Society of Earth Science Education
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• v.15 no.3
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• pp.373-390
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• 2022

Science museums are platforms of PUS (public understanding of science). The purpose of this study was to explore the science communicators' competencies critical in interacting with visitors from the comparison of their training and professional development programs nationally and internationally. The managers running science communicators' programs and communicators themselves from six different national science museums and those from five different international ones participated in the structured survey. The data from surveys were compared among respondents to draw common and specific descriptions for communicators' competencies. In addition, the experienced exemplary science communicator, Ms. Park, participated in this study and the data from her observation field notes, her own developed science communicators' manual, and interviews were used to support the result. The contextual model of learning in science museums (Falk, 2006) was used to illustrate science communicators' expertise. National managers and science communicators showed difference in their perception about science communicators' roles, difficulties, and improvement for their competencies. Internationally, the managers and science communicators showed similar perception about communicators' competencies in terms of the contextual model of learning. It is highly suggested that practice-based science communicators' training and professional development programs must be offered on the basis of interaction between experienced and novice communicators as mentors and mentees systems.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.93-102
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• 2022

Dependency parsing is a decision problem of the syntactic relation between words in a sentence. Recently, deep learning models are used for dependency parsing based on the word representations in a continuous vector space. However, it causes a mislabeled tagging problem for the proper nouns that rarely appear in the training corpus because it is difficult to express out-of-vocabulary (OOV) words in a continuous vector space. To solve the OOV problem in dependency parsing, we explored the proper noun embedding method according to the embedding unit. Before representing words in a continuous vector space, we replace the proper nouns with a special token and train them for the contextual features by using the multi-layer bidirectional LSTM. Two models of the syllable-based and morpheme-based unit are proposed for proper noun embedding and the performance of the dependency parsing is more improved in the ensemble model than each syllable and morpheme embedding model. The experimental results showed that our ensemble model improved 1.69%p in UAS and 2.17%p in LAS than the same arc-eager approach-based Malt parser.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.211-221
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• 1998

It is becoming apparent that stereo matching algorithms need much information from high level cognitive processes. Otherwise, conventional algorithms based on bottom-up control alone are susceptible to local minima. We introduce a system that consists of two levels. A lower level, using a usual matching method, is based upon the local neighborhood and a second level, that can integrate the partial information, is aimed at contextual matching. Conceptually, the introduction of bottom-up and top-down feedback loop to the usual matching algorithm improves the overall performance. For this purpose, we model the image attributes using a Markov random field (MRF) and thereupon derive a maximum a posteriori (MAP) estimate. The energy equation, corresponding to the estimate, efficiently represents the natural constraints such as occlusion and the partial informations from the other levels. In addition to recognition, we derive a training method that can determine the system informations from the other levels. In addition to recognition, we derive a training method that can determine the system parameters automatically. As an experiment, we test the algorithms using random dot stereograms (RDS) as well as natural scenes. It is proven that the overall recognition error is drastically reduced by the introduction of contextual matching.

• Child Health Nursing Research
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• v.23 no.1
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• pp.10-18
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• 2017

Purpose: The purpose of this study was to identify personal, contextual, and cognitive factors influencing the career preparation behavior of Korean nursing students. In this study, an examination was done of the fitness of a path model for the relationship among these factors based on the social cognitive career theory. Methods: The participants were 413 nursing students in South Korea. Data were collected using self-report questionnaires that included self-esteem, social support, self-efficacy, outcome expectation, career decision level, and career preparation behavior. Data were analyzed using descriptive statistics, Pearson correlation analysis, and path analysis. Results: The factors influencing career preparation behavior were self-efficacy, career decision level, self-esteem, outcome expectation, and social support. The factors influencing career decision level were self-efficacy, outcome expectation, self-esteem, and social support. Conclusion: The findings indicate that self-efficacy is an important factor influencing the career behavior of Korean nursing students. Nurse educators should consider personal, contextual, and cognitive factors of nursing students and develop systemic career guidance programs to help nursing students' career preparation behavior.

• ETRI Journal
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• v.34 no.5
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• pp.743-752
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• 2012

Semantic interpretation of the relationship between noun compound (NC) elements has been a challenging issue due to the lack of contextual information, the unbounded number of combinations, and the absence of a universally accepted system for the categorization. The current models require a huge corpus of data to extract contextual information, which limits their usage in many situations. In this paper, a new semantic relations interpreter for NCs based on novel lightweight binary features is proposed. Some of the binary features used are novel. In addition, the interpreter uses a new feature selection method. By developing these new features and techniques, the proposed method removes the need for any huge corpuses. Implementing this method using a modular and plugin-based framework, and by training it using the largest and the most current fine-grained data set, shows that the accuracy is better than that of previously reported upon methods that utilize large corpuses. This improvement in accuracy and the provision of superior efficiency is achieved not only by improving the old features with such techniques as semantic scattering and sense collocation, but also by using various novel features and classifier max entropy. That the accuracy of the max entropy classifier is higher compared to that of other classifiers, such as a support vector machine, a Na$\ddot{i}$ve Bayes, and a decision tree, is also shown.

• Korean Journal of Adult Nursing
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• v.20 no.5
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• pp.707-718
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• 2008

Purpose: The present study was designed to understand the conceptual definition and attributes of the clinical critical thinking ability(CCTA) in nursing and to grasp the characteristics of clinical critical thinking abilities. Methods: The data were analyzed using the Hybrid model of Schwartz-Barcott and Kim(2000). Results: Having the skills and dispositions to think critically, CCTA refers to something that implies the cognizant ability to interpret contextual meanings, analyze the relationships between materials or circumstances, draw out the best conclusions, predict things using relevant information and evaluate the reliability of information and the strength of inference on the one hand and the emphatic disposition to be curious, open-minded, intellectually integral, systematic and creative and to reflect on things in contextual terms on the other. Conclusion: CCTA is characterized by clinical circumstances, such as guessing the reasons for facts, predicting things, connecting theory to practice and approaching individual situation in total terms as well as by the Korean circumstances, such as taking another person's perspective. Hence, this study proposes developing the tools to measure the clinical critical thinking ability and the strategies to improve the clinical critical thinking ability and seeking to verify their validity, on the basis of the findings.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.115-135
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• 2012

Currently, smart signage as a new kind of advertisement media has been widely used and has had a significant effect on consumers. In this study, we examine the impact on the attitude towards smart signage advertisement based on the Ducoffe's Web advertisement model. In particular, we investigate how the advertising factors (interaction, informativeness, irritation, and entertainment) as well as the contextual factors (localization, immediacy, and personalization) have effects on the value and attitude towards smart signage advertisement. Furthermore, we examine the moderating effect of individual defensive propensity on the relationship between affecting factors and the advertising value. By analyzing 192 samples from undergraduates, we found that four out of seven factors have significant effects on the value towards smart signage. More specifically, for advertising factors, informativeness and irritation have positive effects on the advertising value. For contextual factors, on the other hand, localization and entertainment have positive effects on the value towards smart signage. Besides, we discovered that the defensive propensity moderate the relationship between localization and the advertising value.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.959-968
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• 2020

Research underlined that Small and Medium Enterprises' performance is enhanced by different types of innovation capabilities. This research tends to present a comprehensive model to explain the relationship between innovation capabilities and SMEs' financial and operational performance. Specifically, this study tends to achieve three objectives: explores the set of product, process, organizational and marketing innovation capabilities possessed by owners/managers of SMEs and their impact on Chinese manufacturing SMEs' operational and financial performance dimensions, identify the determinants of innovation capabilities, and determine the contextual factors that moderate innovation capabilities and SMEs' performance. This research employed a qualitative research method using in-depth interviews with eight owners/managers of Chinese manufacturing SMEs. Research findings revealed that product and marketing innovation capabilities have a significant impact on SMEs' financial performance while process and organizational innovation capabilities positively influence SMEs' operational performance. The major determinants of innovation capabilities involved availability of sufficient organizational resources, entrepreneurial orientation, knowledge development and external networks. The contextual moderating factors on the relationship between innovation capabilities and SMEs' performance involved internal factors which are: SME size, SMEs' owner/manager work experience, entrepreneurial mindset; and external factors: market dynamism and cooperation strategies. This paper ends by drawing some concluding remarks and proposing future research avenues.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.355-357
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• 2003

본 응용에 새로운 기술이 적용되면서 그 구조가 더욱 복잡해져 사용자가 웹 응용을 사용할 때 자주 혼동을 느낀다. 따라서 사용자가 웹 응용 컨텐츠와 서비스에 효과적으로 접근할 수 있게 하기 위한 항해 설계를 위한 모델이 필요하다. 본 논문에서는 문맥 지표를 사용한 웹 응용의 항해를 UML을 사용하여 모델링하는 방법을 제안한다 본 방법은 웹 응용 구성 요소의 추상화 정도에 따라 다른 항해 모델을 지원하며 모델들 사이의 연결성을 제공하므로 웹 응용 개발에 적용이 용이하다.

• Journal of The Korean Association of Information Education
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• v.8 no.4
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• pp.547-554
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• 2004

Education is the largest application area of adaptive hypermedia systems. The user modeling is considered a very important part of the field of adpative hypermedia systems. In this paper we present the developed user model which provides different educational contents using a neural network. The user model has been verified on hypermedia for learning about basic web concepts, multimedia and HTML. This paper reports the results of simulation. Our simulation shows that the user model exactly can provide contextual different links for different students.