• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3390-3398
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• 2009

The knowledge management starts from the enhancement of learning capability in the members of the organization. The strategic change into the learning organization should be aligned with the change of organizational strategy, structure and processes. The study employed action learning methodology to transform the traditional organization into the learning one. The learning organization project has been successful thanks to the members' zeal and consensus to change the processes. However, not every learning team has been so successful. Some cases complained time consuming where others expect to be helpful for their incentives. The researchers concluded that the most important point for success of the learning organization project should be the support of top management.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.725-731
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• 2008

In this paper, we propose a novel construction scheme for the personalized e-Learning system based on IRT(item response theory), which can be applied to the content including non-hierarchical and horizontal learning objects in its learning nodes. Especially the proposed system performs tests and re-estimates examinee ability during the learning nodes are operating so that the results are directly applied to the next node. This scheme can be called a dynamic relationship between test and learning which is totally different from conventional customization based on learning procedures separated from test steps. Moreover, we should periodically modify the averages of node difficulties, item parameters, and ability parameters of students so that the system have more accurate personalized learning capability. As a result, this scheme maximizes learning efficiency offering the most appropriate learning objects and items to the individual students according to their estimated abilities and the system itself should obtain continuous improvements by modifying the parameters and fulfilling periodical feedbacks.

• 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.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.443-458
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• 2014

An extreme learning machine (ELM) is a recently proposed learning algorithm for a single-layer feed forward neural network. In this paper we studied the ensemble of ELM by using a bagging algorithm for facial expression recognition (FER). Facial expression analysis is widely used in the behavior interpretation of emotions, for cognitive science, and social interactions. This paper presents a method for FER based on the histogram of orientation gradient (HOG) features using an ELM ensemble. First, the HOG features were extracted from the face image by dividing it into a number of small cells. A bagging algorithm was then used to construct many different bags of training data and each of them was trained by using separate ELMs. To recognize the expression of the input face image, HOG features were fed to each trained ELM and the results were combined by using a majority voting scheme. The ELM ensemble using bagging improves the generalized capability of the network significantly. The two available datasets (JAFFE and CK+) of facial expressions were used to evaluate the performance of the proposed classification system. Even the performance of individual ELM was smaller and the ELM ensemble using a bagging algorithm improved the recognition performance significantly.

• The Journal of Korean Academic Society of Nursing Education
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• v.25 no.3
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• pp.300-311
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• 2019

Purpose: The purpose of this study was to review and synthesize the existing literature on the experience of nursing students in simulation. Methods: A systematic review was undertaken using meta-ethnography. Eight databases were searched up to January 2014 for peer-reviewed studies, written in Korean and English, that reported primary data, used identifiable and interpretative qualitative methods, and offered a valuable contribution to the synthesis. Results: Nine studies were identified, with quality appraisal undertaken. Three key concepts were generated: ambivalence of simulation practice, learning by reflection, and building up of the competency as a future nurse. Six sub-concepts emerged: double sidedness of simulation setting; feeling ambivalence of simulation; learning from others; learning from self-reflection; improvement of confidence by role experience; and internalization of nursing knowledge. A line of argument has been developed based on the themes generated. Conclusion: The findings from this qualitative synthesis and other related literature indicated the importance of capability of educator and extension of the simulation system to facilitate effective simulation-based education.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.1013-1020
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• 2021

This study examines the role of dynamic socio-emotional capabilities to increase proactive stakeholder engagement in family businesses. The research sample includes all furniture enterprises scattered in Jepara Regency sub-districts as many as 3,945 companies. The sampling in this research is purposive; as many as 210 respondents, 181 could be used. The sampling unit is the owners and managers, considering that most company owners are also company managers. This study examines how learning and supply chain management in the family business can be integrated to enable a set of resources and capabilities provided by the family to be developed to build closer relationships with stakeholders. The findings showed the importance of a family business's supply chain management perspective in the relationship between dynamic socio-emotional capabilities to mediate organizational learning to proactive stakeholder engagement significantly. Based on this study's results, companies can build dynamic socio-emotional capabilities through organizational learning to increase proactive stakeholder engagement. Dynamic socio-emotional capabilities proved to play a role as a mediator for organizational learning by family companies for proactive stakeholder engagement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3868-3888
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• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.107-118
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• 2024

The purpose of this paper is to investigate the factors affecting digital entrepreneurship and digital innovation and the moderating effect of technology absorptive capacity. To achieve the research purpose, the contributing factors are set as technical characteristic (digital technology capability), organizational characteristics (digital learning capability and financial readiness), and institutional pressures (coercive pressure, mimetic pressure, and normative pressure). The research model and hypothesis are established based on the theoretical background of digital entrepreneurship, digital innovation, institutional pressure, and technology absorptive capacity. The proposed model is analyzed by targeting 104 companies. Smart Partial Least Square (PLS) 4.0 is utilized for deriving the study results. The results of hypothesis testing are as follows: First, digital technology capability, digital learning capability, financial readiness, and institutional pressure have a positive influence on digital entrepreneurship. Second, digital entrepreneurship has a positive impact on digital innovation. Finally, technology absorptive capacity has a moderating effect in influencing digital entrepreneurship on digital innovation. The results of this study emphasize the need for digital entrepreneurship in the era of the Fourth Industrial Revolution and digital transformation, and may provide strategic implications for companies that desire to achieve digital innovation through digital entrepreneurship.

• Journal of Korea Game Society
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• v.15 no.1
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• pp.115-124
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• 2015

This research analyzed the case of Ncsoft to study the organizational learning, exploitation and exploration that create dynamic capability in hypercompetitive environment. First of all, we demonstrated the activities of exploitation and exploration in Ncsoft according to the life cycle of online game industry. An exploitation related to routine, learning and fit with existing environment brings about incremental innovation. In contrast, an exploration associated with non-learning, flexibility with changing environment results in radical innovation. We examined them based on the life cycle of its various game services. NCsoft that built the leading position in online game industry focused the exploitation activities at the stage of beginning period and growth, whereas NCsoft has increased the activities of exploration at period of mature. In addition, the firm conducts an exploration for its brand new game services and R&D. Conversely, An exploitation is conducted for sustainable updating of patch service and marketing and system building. The result implies that online game companies create sustainable competitive advantage using the balance between exploitation and exploration.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.53-59
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• 2012

This article reviews the current issues of engineering education: engineering creativity, R&D 3.0 and Education 3.0 and comfirms need of refining quality of engineering education through learner-centered hybrid project learning. this article suggests the Global engineering project(GEP) program as an ideal hybrid project learning model that develop student's creativity and convergence capability. GEP program is learnner-centered interdisciplinary program that whole processes are managed by interdisciplinary students team aiming to global engineers who are globally competent and locally relevant so that they can function effectively in any country by local activity in developing country. The program consist of four main parts: 1)pre activity, 2)local activity from abroad, 3)design and producing prototype and 4)participating in the design contest or academic conference with the products. As a result, students' global competence, teamwork skill and capability of creative problem solving are remarkably improved.