• Knowledge Management Research
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• v.16 no.2
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• pp.249-278
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• 2015

Employees' knowledge integration capabilities and innovative behavior are still of crucial importance in the effective knowledge management. Recently researchers and practitioners are interested in both the potential benefits of unlearning and the negative aspects of learning inertia. The purpose of this study is to examine the relationships among learning inertia, unlearning, knowledge integration capabilities(knowledge exploitation and knowledge exploration) and innovative behavior. The results of analysis show that learning inertia is employees' psychological obstacle factor affecting knowledge integration capabilities and unlearning, that unlearning of employees is a key factor affecting knowledge integration capabilities, and that knowledge integration capabilities are driving forces leading to innovative behaviors of employees. For theoretical and practical implications, the research presents the grounds for arguments that knowledge integration capabilities are employees' dynamic capabilities from the knowledge management perspective, that unlearning is a driving force of employees' positive behaviors, and that organizations trying to perform the dynamic knowledge management need to identify the causes of employees' psychological resistance to learning. Limitations arisen in the course of the research and suggestions for future research directions are also discussed.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.41-68
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• 2019

Multi-view learning considers data from various viewpoints as well as attempts to integrate various information from data. Multi-view learning has been studied recently and has showed superior performance to a model learned from only a single view. With the introduction of deep learning techniques to a multi-view learning approach, it has showed good results in various fields such as image, text, voice, and video. In this study, we introduce how multi-view learning methods solve various problems faced in human behavior recognition, medical areas, information retrieval and facial expression recognition. In addition, we review data integration principles of multi-view learning methods by classifying traditional multi-view learning methods into data integration, classifiers integration, and representation integration. Finally, we examine how CNN, RNN, RBM, Autoencoder, and GAN, which are commonly used among various deep learning methods, are applied to multi-view learning algorithms. We categorize CNN and RNN-based learning methods as supervised learning, and RBM, Autoencoder, and GAN-based learning methods as unsupervised learning.

• The Journal of Industrial Distribution & Business
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• v.5 no.2
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• pp.5-12
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• 2014

Purpose - The purpose of this thesis is to assess the product design digital learning status of universities that are currently involved in learning environment projects in manufacture and commerce integration (MCI). Thus, enterprises must keep learning and creating new inventions with revolutionary progress. Research design, data, and methodology - This study not only emphasizes the analysis of technical ability, course concepts, conducting models, and learning environments of every aspect, but also systematically probes the planning of learning, system framework, web learning, environmental activities, data statistics, and digitalized learning, among other aspects. Results - The results of this study help in finally understanding each school's manufacture and commerce integration situation, in order to evaluate product design learning. Consequently, it is essential to evaluate computer learning at schools, thereby affecting communication and the requirements of business education training. Conclusions - It is essential to focus on MCI to promote web teaching to preserve and enhance knowledge disseminating technologies, and immediately share knowledge with learners, while improving work efficiency and cultivating the talent needed by industry.

• Journal of Information Technology Applications and Management
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• v.28 no.5
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• pp.1-16
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• 2021

This paper attempts to explore the need and importance of values integration in educational activities to mitigate learning crisis and promote sustainable learning achievement. The traditional approach, commercial motive, focus on instrumental knowledge coupled with many other contemporary issues have collectively smothered the fundamental humanistic principles of education. To avert the situation and execute the core objectives, we need to shift our focus: a shift from instrumental knowledge to humanistic-transformational knowledge; a shift from the traditional approach of supplying and storing information to learning to deal with the real-world problems; a shift from head to heart. Values integration is an attempt to initiate and promote this shift. Rather than teaching values and moral principles under a particular subject heading, values need to be a part of everyday in-school and out-school activities. To concretize this concept, a model is proposed in this study as a holistic model of values integration via whole school ambiances and community support.

• Korean Journal of Health Education and Promotion
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• v.28 no.5
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• pp.105-116
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• 2011

Objectives: The aim of this study was to explore the influence of learning social integration and self-doubt on the suicidal ideation, and to test the mediating effect of self-doubt and the moderating effect of drinking on suicidal ideation. Methods: A cross-sectional survey was administered to a convenience sample of 1,000 freshmen in a university in S city. A total of 803 questionnaires were included in the statistical analysis. To analysed the data, Pearson correlation and structural equation modeling were performed. Results: In this study, self-doubt had a mediating effects in the path way from learning social integration to suicidal ideation. Drinking had a moderating effect between self-doubt and suicidal ideation. Conclusions: The results suggest that the low level of learning social integration increases the level of self-doubt and leads to suicidal ideation. Drinking was a significant moderator of suicidal ideation. Therefore, interventions on various strategies to enhance academic performance and social interaction skill, and to help to stop or not to initiate drinking habit are needed in the early part of the freshman year.

• The Journal of Korean Academy of Sensory Integration
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• v.15 no.2
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• pp.80-92
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• 2017

Objective : The purpose of this study is to investigate the meaning of students' experience participating in the flipped learning based instruction in sensory integration, and to understand the demand and introspection of participants. Methods : This study used a phenomenological approach of qualitative study. The participants were 10 students in 3rd year of the occupational therapy program in K Univeristy. Data information was collected by one-to-one interview and analyzed through phenomenological research method. Results : Through the interview, 20 units of meaning, 8 central meanings, and 3 themes were drew. The information collected were analyzed into three themes; Learning Experiences in Online and Offline Courses, Request and Introspection of Learners on Flipped Learning. The result showed that online courses brought learners convenience and satisfaction with repeatable learning in every time and space the learner want. However, the learners appealed issues of communication and concentration due to the absence of face-to-face instruction by their instructor. For the offline courses, students showed interest in various practical classwork of sensory integration and changes in their attitude to actively engage in the practical classes. Conclusion : Flipped learning based instruction was effective for the sensory integration classes which require practice in terms of time securement and immersion in practice. The learners requested for adopting flipped learning based instruction to other subjects in occupational therapy curriculum, and introspected that they needed to actively engage in classes through the experience of flipped learning-based classes of sensory integration. The results of this study can be used as a basic resource when flipped learning classes are planned in occupational therapy education.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.37-43
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• 2001

New product development has been a key element fur organizational evolution. The bulk of research about new product strategy has focused solely on new product development function itself. This paper investigates cross-functional elements in new product development. More specifically, we suggest that there must exist a fit between new product strategy and value chain strategy. It means that, in order to support new product development activity, there must exist a relevant value chain strategy. We consider three types of integration - internal integration, customer integration, and supplier integration - as strategic elements of value chain strategy. For the case of new product strategy, we consider market newness and product technology unfamiliarity as strategic elements. We also consider two types of learning characteristic, i.e., \\\"fast-adaptive learning\\\" and \\\"slow-adaptive leaning\\\" as control factor. Learning characteristic represents firms organizational capability related with organizational learning. For example, fur fast-adaptive learning case, the effect of integration appears early in time. System dynamics simulation is employed to verify our research framework. The results exhibit that there must exist cross-functional relationships between value chain strategy and new product strategy in order to shorten total development time.al development time.

• Korean Management Science Review
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• v.31 no.3
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• pp.77-94
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• 2014

This study empirically investigated the relationships among inter-organizational cost management (IOCM), cooperation with suppliers, information exchange between partners, inter-organizational learning, control integration, and the supply-chain performance of a firm. The results showed that the adoption of IOCM positively affects the collaboration between buyers and suppliers, which also leads to the increased information flow between them. According to the results of this study, it was found that inter-organizational information flow causes inter-organizational learning, and this learning contributes to the improved supply-chain performance. In this study, the positive effects of the cooperation with suppliers through IOCM on the control integration in supply-chains were not empirically confirmed. However, the impact of IOCM on control integration was significant and positive. Finally, the fact that the enhanced control integration can improve the supply-chain performance of a firm was empirically demonstrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3730-3744
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• 2020

This study proposes a deep learning-based evolutionary recommendation model for heterogeneous big data integration, for which collaborative filtering and a neural-network algorithm are employed. The proposed model is used to apply an individual's importance or sensory level to formulate a recommendation using the decision-making feedback. The evolutionary recommendation model is based on the Deep Neural Network (DNN), which is useful for analyzing and evaluating the feedback data among various neural-network algorithms, and the DNN is combined with collaborative filtering. The designed model is used to extract health information from data collected by the Korea National Health and Nutrition Examination Survey, and the collaborative filtering-based recommendation model was compared with the deep learning-based evolutionary recommendation model to evaluate its performance. The RMSE is used to evaluate the performance of the proposed model. According to the comparative analysis, the accuracy of the deep learning-based evolutionary recommendation model is superior to that of the collaborative filtering-based recommendation model.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.29-34
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• 2023

The flow from developing a machine learning model to deploying it in a production environment suffers challenges. Efficient and reliable deployment is critical for realizing the true value of machine learning models. Bridging this gap between development and publication has become a pivotal concern in the machine learning community. FastAPI, a modern and fast web framework for building APIs with Python, has gained substantial popularity for its speed, ease of use, and asynchronous capabilities. This paper focused on leveraging FastAPI for deploying machine learning models, addressing the potentials associated with integration, scalability, and performance in a production setting. In this work, we explored the seamless integration of machine learning models into FastAPI applications, enabling real-time predictions and showing a possibility of scaling up for a more diverse range of use cases. We discussed the intricacies of integrating popular machine learning frameworks with FastAPI, ensuring smooth interactions between data processing, model inference, and API responses. This study focused on elucidating the integration of machine learning models into production environments using FastAPI, exploring its capabilities, features, and best practices. We delved into the potential of FastAPI in providing a robust and efficient solution for deploying machine learning systems, handling real-time predictions, managing input/output data, and ensuring optimal performance and reliability.