• Research in Mathematical Education
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• v.19 no.2
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• pp.89-100
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• 2015

The study investigated pre-service teachers' knowledge and computational skills by using Triangular Arithmagon. Participants included 90 pre-service teachers from two schools in the United States and Taiwan. The Triangular Arithmagons Test (TAT) was used to measure pre-service teachers' performance in whole number, fractions, and decimals operations (i.e., addition, subtraction, multiplication, and division), each of which included level-1 (basic) and level-2 (advanced) tests. MANOVA analysis was performed to compare the performance between teachers from the United States and Taiwan. Results indicated that overall, pre-service teachers in Taiwan outperformed those in the United States, especially on the advanced-level tests. Pre-service teachers in the United States were found to have poor ability of solving complex operation problems. Different curriculum plans and teaching methods may lead to the performance gap between the two countries.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.44
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• pp.181-210
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• 2009

This paper discusses global expansion and global strategies of shipping firms. Acknowledging the lack of research on global expansion by freight transport companies, this paper employs the resource-focused model, and explores "why shipping companies emerge" and "why the strategic behaviour of shipping companies is different in the global market". Despite there being a plethora of theoretical and empirical studies on the international operations of business organisations, it is acknowledged that researchers have largely neglected the issues regarding the international expansion within the freight transport industry. Identifying the general lack of contemporary studies concerning the international behaviour of shipping firms, this study addresses the important gap in our knowledge in the theoretical manner. The theoretical analysis suggests that the shipping company's internal resources can be a real reason for the international market participation.

• Computers and Concrete
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• v.24 no.3
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• pp.271-282
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• 2019

Concrete undergoes a series of thermo-based physio-chemical changes once exposed to elevated temperatures. Such changes adversely alter the composition of concrete and oftentimes lead to fire-induced explosive spalling. Spalling is a multidimensional, complex and most of all sophisticated phenomenon with the potential to cause significant damage to fire-exposed concrete structures. Despite past and recent research efforts, we continue to be short of a systematic methodology that is able of accurately assessing the tendency of concrete to spall under fire conditions. In order to bridge this knowledge gap, this study explores integrating novel artificial intelligence (AI) techniques; namely, artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA), together with traditional statistical analysis (multilinear regression (MLR)), to arrive at state-of-the-art procedures to predict occurrence of fire-induced spalling. Through a comprehensive datadriven examination of actual fire tests, this study demonstrates that AI techniques provide attractive tools capable of predicting fire-induced spalling phenomenon with high precision.

• Asia Pacific Journal of Corpus Research
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• v.4 no.2
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• pp.57-74
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• 2023

Having a firm grasp of technical terms is essential for learners of Japanese for Specific Purposes (JSP). This research aims to analyze Japanese nursing care vocabulary based on objective corpus-based frequency and subjectively rated word familiarity. For this purpose, we constructed a text corpus centered on the National Examination for Certified Care Workers to extract nursing care keywords. The Log-Likelihood Ratio (LLR) was used as the statistical criterion for keyword identification, giving a list of 300 keywords as target words for a further word recognition survey. The survey involved 115 participants of whom 51 were certified care workers (CW group) and 64 were individuals from the general public (GP group). These participants rated the familiarity of the target keywords through crowdsourcing. Given the limited sample size, Bayesian linear mixed models were utilized to determine word familiarity rates. Our study conducted a comparative analysis of word familiarity between the CW group and the GP group, revealing key terms that are crucial for professionals but potentially unfamiliar to the general public. By focusing on these terms, instructors can bridge the knowledge gap more efficiently.

• Spatial Information Research
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• v.17 no.1
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• pp.145-157
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• 2009

Rapidly evolving field of GIS and the social demand for university education to address the gap in the training of human resources, and future-oriented, engineering accreditation system based on the introduction of measures in the field of GIS is the need. In this thesis, the domestic and international undergraduate curriculum including University of Seoul's was analysed. A GIS curriculum of the domestic and abroad department course was analyzed. The present status of the domestic engineering accreditation and problems were analyzed and a desirable casting plan was shown through the abroad GIS related accreditation case analysis to analyze the validity of the engineering accreditation introduction of the GIS field. A standardized GIS curriculum was shown through the analysis of the core curriculum and the body of knowledge of the GIS field shown at the advanced of foreign countries all together. The industry-academia cooperation forum which made the Surveying and GIS related society the center by a political alternative, the construction of the caucus and the argument to execute this effectively are needed.

• Journal of Information Science Theory and Practice
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• v.12 no.2
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• pp.49-63
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• 2024

Information behavior played a significant role in minimizing the risks of the COVID-19 pandemic. When faced with such a situation, an individual needs information for decision-making and in order to determine the best course of action relating to their health. This study aims to explore information behavior during each phase of the COVID-19 pandemic in Indonesia, which is known for its close-knit collective culture. A sensemaking approach is used, which emphasizes the process individuals go through to understand their situation and give meaning to the information they are getting from their environment. Data was collected through in-depth interviews with 10 participants to obtain a description of their information behaviors during the pandemic. Data analysis was carried out using open, axial, and selective coding. We propose a sensemaking-based information behavior strategy framework for mitigating risk and reducing ongoing health crises. Changes in information behavior strategies, including search, prevention, and restriction of information exposure, were random at the beginning of the pandemic, but became more regular in later phases. This was influenced by the "knowledge gap fulfillment" and "use of local knowledge" among the participants throughout the pandemic. In conclusion, the participants developed a sensemaking process including an understanding of the pandemic situation and the risks that they faced. They used a number of information behavior strategies to prevent transmission, and their perception of the risks changed across the course of the pandemic, up til the situation began to be considered back to normal again in Indonesia.

• 한국균학회소식:학술대회논문집
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• 2018.05a
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• pp.19-19
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• 2018

Fungal pathogens have huge impact on health and economic wellbeing of human by causing life-threatening mycoses in immune-compromised patients or by destroying crop plants. A key determinant of fungal pathogenesis is their ability to undergo developmental change in response to host or environmental factors. Genetic pathways that regulate such morphological transitions and adaptation are therefore extensively studied during the last few decades. Given that epigenetic as well as genetic components play pivotal roles in development of plants and mammals, contribution of microbial epigenetic counterparts to this morphogenetic process is intriguing yet nearly unappreciated question to date. To bridge this gap in our knowledge, we set out to investigate histone modifications among epigenetic mechanisms that possibly regulate fungal adaptation and processes involved in pathogenesis of a model plant pathogenic fungus, Magnaporthe oryzae. For functional and comparative analysis of histone modifications, a web-based database (dbHiMo) was constructed first to archive and analyze histone modifying enzymes from eukaryotic species whose genome sequences are available. Based on the database entries, we carried out functional analysis of genes encoding histone modifying enzymes. Here I provide examples of such analyses that show how histone acetylation and methylation is implicated in regulating important aspects of fungal pathogenesis. Current analysis of histone modifying enzymes is followed by ChIP-seq and RNA-seq experiments to pinpoint the genes that are controlled by particular histone modifications. We anticipate that our work will provide not only the significant advances in our understanding of epigenetic mechanisms operating in microbial eukaryotes but also basis to expand our perspective on regulation of development in fungal pathogens.

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.3
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• pp.443-451
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• 2014

Purpose: The purpose of this study was to understand the clinical instructors' role experience in college of nursing. Method: Two focus group interviews were held with a total of 12 clinical instructors. All interviews were recorded and transcribed as they were spoken, and the collected data were analyzed using content analysis of Downe-Wamboldt(1992). Results: Three themes and six subthemes were extracted from the analysis: 1) Getting recognition of special roles as a clinical instructor: 'Recognizing the role of clinical instructor for guiding student's individual practice goals', 'Recognizing helping and supporting roles for student's successful clinical practice', 2) Having difficulty in performing the role of clinical practice instructor: 'Difficulty from the lack of knowledge and experience as a clinical practice instructor', 'Difficulty from the gap between current clinical practice and purpose of clinical nursing practice', 3) Making efforts to overcome the difficulties as a clinical instructor and accomplishing personal development: 'Making efforts to acquire personal knowledge and experience', 'Making a chance to reflect on and grow up oneself'. Conclusion: Clinical instructors take an important part of clinical nursing education. To improve the quality of clinical nursing education, it is needed role reestablishment and institutional support for clinical instructors on the basis of the understanding of instructors' experience.

• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.103-112
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• 2006

Priority-based network service has been widely adopted for the Internet traffic management in the context of IETF differentiated services, and computing optimal prices for such priority-based service is the key topic in many pricing literature. While the equilibrium analysis has been commonly used to this end, many have criticized the validity of the underlying assumption of equilibrium analysis that user utility functions are precisely known. In this paper, we propose a solution for bridging the gap between the existing theoretical work on optimal pricing and the unavailability of precise user utility information in real networks. In the proposed method, the service provider obtains more and more accurate estimates of user utility functions from the initial imprecise knowledge by iteratively changing the price of service levels and observing the users' decisions under the changed price. Our contribution is two-fold. First, we have developed a general principle for estimating the user utility functions. Second, we have developed a novel method for setting the prices that can optimize the extraction of the knowledge about user utility functions. The extensive simulation results demonstrate the effectiveness of our method.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.129-140
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• 2021

Recently, interest in AI tutors is rising as a way to bridge the educational gap in school settings. However, research confirming the effectiveness of AI tutors is lacking. The purpose of this study is to explore how effective learner characteristics and recommended item learning activities are in predicting learner's academic performance in an adaptive online learning environment. This study proposed the hypothesis that learner characteristics (prior knowledge, midterm evaluation) and recommended item learning activities (learning time, correct answer check, incorrect answer correction, satisfaction, correct answer rate) predict academic achievement. In order to verify the hypothesis, the data of 362 learners were analyzed by collecting data from the learning management system (LMS) from the perspective of learning analytics. For data analysis, regression analysis was performed using the regsubset function provided by the leaps package of the R program. The results of analyses showed that prior knowledge, midterm evaluation, correct answer confirmation, incorrect answer correction, and satisfaction had a positive effect on academic performance, but learning time had a negative effect on academic performance. On the other hand, the percentage of correct answers did not have a significant effect on academic performance. The results of this study suggest that recommended item learning activities, which mean behavioral indicators of interaction with AI tutors, are important in the learning process stage to increase academic performance in an adaptive online learning environment.