• 지식경영연구
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• 제16권2호
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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.

• 응용통계연구
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• 제32권1호
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• pp.41-68
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• 2019

멀티 뷰 기법은 데이터를 다양한 관점에서 보려는 접근 방법이며 데이터의 다양한 정보를 통합하여 사용하려는 시도이다. 최근 많은 연구가 진행되고 있는 멀티 뷰 기법에서는 단일 뷰 만을 이용하여 모형을 학습시켰을 때 보다 좋은 성과를 보인 경우가 많았다. 멀티 뷰 기법에서 딥 러닝 기법의 도입으로 이미지, 텍스트, 음성, 영상 등 다양한 분야에서 좋은 성과를 보였다. 본 연구에서는 멀티 뷰 기법이 인간 행동 인식, 의학, 정보 검색, 표정 인식 분야에서 직면한 여러 가지 문제들을 어떻게 해결하고 있는지 소개하였다. 또한 전통적인 멀티 뷰 기법들을 데이터 차원, 분류기 차원, 표현 간의 통합으로 분류하여 멀티 뷰 기법의 데이터 통합 원리를 리뷰 하였다. 마지막으로 딥 러닝 기법 중 가장 범용적으로 사용되고 있는 CNN, RNN, RBM, Autoencoder, GAN 등이 멀티 뷰 기법에 어떻게 응용되고 있는지를 살펴보았다. 이때 CNN, RNN 기반 학습 모형을 지도학습 기법으로, RBM, Autoencoder, GAN 기반 학습 모형을 비지도 학습 기법으로 분류하여 이 방법들이 대한 이해를 돕고자 하였다.

• 산경연구논집
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• 제5권2호
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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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• 제28권5호
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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.

• 보건교육건강증진학회지
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• 제28권5호
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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.

• 대한감각통합치료학회지
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• 제15권2호
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• pp.80-92
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• 2017

목적 : 플립드 러닝기반 감각통합치료 수업을 받은 작업치료 대학생의 경험의 의미를 파악하고 수업 후 학습자의 요구와 성찰을 알아보는 것이다. 연구방법 : 대학생의 플립드 러닝 기반 감각통합치료 수업 경험에 관한 질적 연구 중 현상학적 연구방법을 사용하였다. 본 연구의 대상자는 2017년 1학기 K대학교 작업치료학과 전공필수과목인 '감각통합치료 및 실습'을 수강한 3학년 학생 중 10명이다. 자료 수집을 위해 일대일 면담방법을 이용하였고, 녹음한 면담내용을 전사하여 분석하였다. 결과 : 의미단위 20개, 중심의미 8개, 주제 3개가 도출되었다. 연구결과는 온라인 수업에서의 학습경험, 오프라인 수업에서의 학습경험, 플립드 러닝에 대한 학습자의 요구와 성찰의 주제로 분석하였다. 온라인 수업은 원하는 시간과 공간에서 학습할 수 있다는 편리함과 반복학습의 만족감을 가져왔다. 하지만 교수와의 면대면 수업의 부재로 소통과 집중력의 문제를 호소하였다. 오프라인 수업에서는 다양한 감각통합 실습수업에 흥미를 보였고, 적극적인 실습태도의 변화가 있었다. 결론 : 실습이 요구되는 감각통합 수업에 플립드 러닝 기반 수업은 시간의 확보와 실습 몰입 면에서 효과가 있었다. 다른 작업치료교과목도 플립드 러닝으로 수업하고 싶다는 요구가 있었으며, 플립드 러닝 수업을 통해 능동적인 학습 자세가 필요하다는 성찰이 있었다. 본 연구의 결과는 작업치료 교육 분야에서 플립드 러닝 수업을 시도하는데 기초자료로 제공하고자 한다.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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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.

• 경영과학
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• 제31권3호
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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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• 제14권9호
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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.

• 한국인공지능학회지
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• 제11권4호
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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.