• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.385-392
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• 2011

Recently, the concern of IT-in-Agriculture convergence technology that combines information technology and agriculture is increasing rapidly. Especially, the crop cultivation related prediction services by spatial data mining (SDM) can play an important role in reducing the damage of natural disaster and enhancing crop productivity. However, the data conversion and integration procedure to acquire the learning dataset of SDM for the prediction service need a lot of effort and time, because of their heterogeneity between distributed data. In addition, calculating spatial neighborhood relationships between spatial and non-spatial data necessitates requires the complicated calculation procedure for large dataset. In this paper, we suggest a SOA-based data integration framework that can effectively integrate distributed heterogeneous data by treating each data source as a service unit and support to find the optimal prediction service by improving productivity of learning dataset for SDM. In our experiment, we confirmed that our framework can be effectively applied to find the optimal prediction service for the frost damage area, by considering the case of peach crop cultivation in Icheon in Korea.

• Knowledge Management Research
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• v.15 no.2
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• pp.129-145
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• 2014

As a community of practice (CoP) is known to facilitate team learning, it is increasingly important to understand the mechanisms of CoP, thereby enabling organizations to fully utilize it and optimize its benefits. To explain how CoP improves organizational performance, we focus on its effects on social capital and knowledge management activities, and propose a research model suggesting that shared goals and trust in CoP improve its performance through knowledge integration. Our analysis uses structural equation modeling, with field data collected from 372 members of 46 CoPs in three companies; the analysis validates our research model. Our findings also suggest that CoP diversity can strengthen the link between knowledge integration and CoP performance.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.204-214
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• 2017

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

• Educational Technology International
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• v.11 no.2
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• pp.25-41
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• 2010

Challenges brought by applications of advanced technologies in education call for new approaches that can best ensure the provision of quality e-learning experiences. This paper presents an ecological approach as one of such approaches to quality assurance in e-learning that can monitor, assess and improve the effectiveness and the links between the various elements of e-learning. The ecological model for QA in e-learning emphasizes interrelation transactions between elements (e.g. providers, learners, cultures and policies) and systemic integration of those elements, and stresses that all these elements within a QA system play an equal role in maintaining balance of the whole. The model focuses attention both on individual and societal/cultural environmental factors as cornerstones for QA efforts in e-learning. It addresses the importance of QA efforts directed at changing QA transactions from provider-centered to 'all stakeholder-oriented', from one-size-fits-all model to 'globally oriented, locally adaptive model' and from control framework to 'culture creation framework'.

• Journal of The Korean Association For Science Education
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• v.21 no.2
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• pp.357-384
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• 2001

In this paper, we described practical teaching-learning plans based on three different theoretical approaches to Integrated Science Education (ISE): a knowledge centered ISE, a social problem centered ISE, and an individual interest centered ISE. We believe that science teachers can understand integrated science education through this paper and they are able to apply simultaneously our integrated science teaching materials to their real instruction in classroom. For this we developed integrated science teaching-learning plans for the topic of energy which has a integrated feature strongly among integrated science subject contents. These modules were based upon the teaching strategies of 'Energy' following each integrated directions organized in the previous paper (Three Strategies for Integrated Science Teaching of "Energy" Applying Knowledge, Social Problem, and Individual Interest Centered Approaches) and we applied instruction models fitting each features of integrated directions to the teaching strategies of 'Energy'. There is a concrete describing on the above three integrated science teaching-learning plans as follows. 1. For the knowledge centered integration, we selected the topic, 'Journey of Energy' and we tried to integrate the knowledge of physics, chemistry, biology, and earth science applying the instruction model of 'Free Discovery Learning' which is emphasized on concepts and inquiry. 2. For the social problem centered integration, we selected the topic, 'Future of Energy' to resolve the science-related social problems and we applied the instruction model of 'Project Learning' which is emphasized on learner's cognitive process to the topic. 3. For the individual interest centered integration, we selected the topic, 'Transformation of Energy' for the integration of science and individual interest and we applied the instruction model of 'Project Learning' centering learner's interest and concern. Based upon the above direction, we developed the integrated science teaching-learning plans as following steps. First, we organized 'Integrated Teaching-Learning Contents' according to the topics. Second, based upon the above organization, we designed 'Instructional procedures' to integrate within the topics. Third, in accordance with the above 'Instructional Procedures', we created 'Instructional Coaching Plan' that can be applied in the practical world of real classrooms. These plans can be used as models for the further development of integrated science instruction for teacher preparation, textbook development, and classroom learning.

• Research in Mathematical Education
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• v.19 no.3
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• pp.177-193
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• 2015

Mathematical creativity, an important goal in mathematics education, can be promoted through an integrated learning environment where students explore mathematics with other subject areas such as science, technology, engineering and art. Establishing such learning environments is not a trivial task. Therefore, this creates a need for the development of instructional resources promoting meaningful integration. This paper focuses on integration of the fields of mathematics and music. Beginning with some of the historical discoveries and views of the connections between mathematics and music, this paper attends to several musical concepts correlating to middle school mathematical content and then provides ideas for teaching.

• Korean System Dynamics Review
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• v.15 no.4
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• pp.61-84
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• 2014

This study aims to explore the development and application of a simulated skills package designed to improve nursing students' knowledge integration and their system thinking(ST) skills about congestive heart failure(CHF) and to identify the change in students' ST levels using a ST-based learning approach. A simulated learning support package was developed by nurse educators and ST experts. The developed program was implemented with 35 third-year nursing students from S university in Seoul. The subjects improved their ST skills regarding CHF after intervention. Mean test scores for students completing the program were significantly higher than pre-intervention scores, including measures of direction of causality, polarity of causal relationship, feedback loop, polarity of feedback loop (reinforcing, balancing) and time delay (t=2.26~6.53, p=.030~p<.001). It is suggested that more educational programs be developed on various topics in order for nursing students to improve their ST skills as well as knowledge integration in clinical nursing practicum packages.

• Asia pacific journal of information systems
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• v.10 no.1
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• pp.19-35
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• 2000

Data Envelopment Analysis(DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.

• The Mathematical Education
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• v.53 no.3
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• pp.435-447
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• 2014

Recently, the interdisciplinary integration and story-telling are often mentioned in mathematics education. It is probably because they might be helpful to students for positive attitude for mathematics. In this research, through brief discussion mathematics related with wallpaper patterns, we try to integrate mathematics and design, and eventually develop the teaching/learning materials for experience activities and story-telling.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.77-88
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• 2006

Data Envelopment Analysis (DEA), a non-parametric productivity analysis tool, has become an accepted approach for assessing efficiency in a wide range of fields. Despite of its extensive applications, some features of DEA remain bothersome. DEA offers no guidelines to where relatively inefficient DMU(Decision Making Unit) improve since a reference set of an inefficient DMU consists of several efficient DMUs and it doesn't provide a stepwise path for improving the efficiency of each inefficient DMU considering the difference of efficiency. We aim to show that DEA can be used to evaluate the efficiency of System Integration Projects and suggest the methodology which overcomes the limitation of DEA through hybrid analysis utilizing DEA along with machine learning.