• Proceedings of the Korean Operations and Management Science Society Conference
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• 한국경영과학회 2007년도 추계학술대회 및 정기총회
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• pp.67-89
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• 2007

This study addresses manufacturers' ability to influence their supply chain network in order to adapt to their competitive environment. From the perspective of a manufacture, the supply chain comprises a network of suppliers and customers, and is theoretically viewed as a complex adaptive system. This study considers the following questions: (1) How can adaptability of supply chain network be operationally defined? (2) How does adaptability of supply chain network lead to combinative capabilities? (3) What is the influence of adaptability of supply chain network on business performance? Drawing on literature streams in supply chain management, operations strategy, organizational change and learning, and complexity theory, this study develops and tests the constructs and operational measures of adaptability of supply chain network and model the nomological set of relationships among constructs that form the basis of our theory. This study then develops and tests a model describing the outcomes of adaptability of supply chain network and its influence on combinative capability and business performance. Empirical results of this study show that adaptability supply chain network directly and positively affects combinative capability. Further, this study finds that adaptability of supply chain network does not impact business performance directly, but rather is mediated through combinative capability, which provides the requisite variety for firms to survive and thrive in dynamic environments.

• Knowledge Management Research
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• 제5권2호
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• pp.67-98
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• 2004

New knowledge is created through the dynamic interaction of knowledge that depends largely on a social context within the organization. Social processes influence the nature of knowledge and learning. This paper is rooted in the concept of social capital. Social capital theory emphasizes the importance of social relationship. Using social capital theory, this paper suggests three factors that must be satisfied for the development of knowledge combinative capability. The first factor is that the opportunity exists to make the exchange or combination of knowledge. The second factor is that people is motivated for the creation of new knowledge. The third factor is that people must share the common knowledge. This paper examines the change case of KIPO (Korean Intellectual Property Office). This case provides evidence that the three factors can develop social relationship, and build knowledge combinative capability. The man finding from this research is that social factors play an important part in the creation of knowledge, and processes of knowledge exchange and combination heavily rely upon social patterns, practices and processes in ways which emphasize the value and importance of collective action and knowledge sharing. This research may have several implications for the development of the knowledge creation mechanisms.

• Journal of Technology Innovation
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• 제13권2호
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• pp.179-205
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• 2005

This study reveals that the user industry has a limited role in being a source of technological capability in the case of the machine tool industry in Korea where the user industry is relatively more advanced than other capital goods industries. This study examines the sources of technological capability in terms of migration of workforces and flow of product development knowledge. Although the capital goods sector is generally regarded as being the sector where user-producer interaction is important, the user industry is not the seed-bed of technological capability for machine development. Users and producers interact in terms of expressing 'needs', mainly in the form of specifications. As a result of receiving unique specifications from users, the producer learns to react by making specific customised special purpose machines. The user's specification could include information o the imported machine originally used. When confronted with technical problems in developing a new machine, the producer accesses foreign sources of knowledge. This study's finding reveals that users of special purpose machines have a significantly clearer role in providing specifications than do users of general purpose machine tools. Most intensive interactive learning between users and producers in the production process is found in special purpose machine tools. From the empirical findings, policy implications are discussed.

• Journal of the Korean Institute of Intelligent Systems
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• 제26권1호
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• pp.87-92
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• 2016

In this paper, optimization technique such as particle swarm optimization was used to optimize the parameters of fuzzy Extreme Learning Machine. While the learning speed of conventional neural networks is very slow, that of Extreme Learning Machine is very fast. Fuzzy Extreme Learning Machine is composed of the Extreme Learning Machine with very fast learning speed and fuzzy logic which can represent the linguistic information of the field experts. The general sigmoid function is used for the activation function of Extreme Learning Machine. However, the activation function of Fuzzy Extreme Learning Machine is the membership function which is defined in the procedure of fuzzy C-Means clustering algorithm. We optimize the parameters of the membership functions by using optimization technique such as Particle Swarm Optimization. In order to validate the classification capability of the proposed classifier, we make several experiments with the various machine learning datas.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.41.5-41
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• 2001

A novel method is introduced for determining the weights of a regularization network which approximates one-to-many mapping. A conventional neural network will converges to the average value when outputs are multiple for one input. The capability of proposed network is demonstrated by an example of learning inverse mapping.

• Journal of the Korean Chemical Society
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• 제60권2호
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• pp.137-143
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• 2016

Effective teaching and learning is a continuous process of monitoring and re-organization of teaching method, so to benefit both students and educators. Reflective journal writing is an effective method for students to reflect on their learning experience about a new concept or subject taught and at the same time enables educators to improve on their academic skills. In the present paper, we have examined and evaluated the effectiveness of the Uncritical Inference Test (UIT) that was conducted in our basic organic chemistry course through a systematic network built based on students’ reflective writing. From the data analysis, the UIT has benefited students in three dimensions, namely cognitive, affective and group learning domains. Moreover, the UIT activity instilled an active learning environment in organic chemistry classroom and deeper learning among chemistry students as shown in the collected data. In future, this activity could be adapted as a teaching method to enhance students’ critical thinking skills and question-asking capability in other teaching courses.

• The Journal of Korean Association of Computer Education
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• 제14권2호
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• pp.13-22
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• 2011

The importance of algorithm education has been emphasized for creative problem-solving capability. Especially, algorithm teaching materials related with mathematics and science are under development to enhance logical thinking. However, there are not enough teaching-learning models applicable in the field of education. Therefore, this paper proposed a teaching-learning model for effective algorithm education. The teaching-learning model reflects two characteristics : an algorithm learning process is spiral, and algorithm education is based on logical thinking. Furthermore, a survey was conducted for students' satisfaction, and the result was a mixed teaching-learning model with PBL, SDL, and peer tutoring. Based on the proposed model, examples of classes for mathematics and science are suggested to show the feasibility of effective algorithm education.

• Journal of KIISE:Computing Practices and Letters
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• 제16권5호
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• pp.601-605
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• 2010

In this paper, we propose a GBL(Game Based Learning) content of intelligent tutoring capability. The objective of our GBL content is to learn the Karnaugh Map which is generally used to simplify boolean functions. Our GBL content well-motivates learners with interesting game-based scenarios and also, through an intelligent tutoring module, gives learners adaptive feedbacks such as hints and explanations while maintaining learners' contextual immersion. Additionally, we identified significant improvement in terms of learning effectiveness by analyzing the test results of two (experimental and controlled) student groups learning the Karnaugh Map.

• Journal of Internet Computing and Services
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• 제20권5호
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• pp.79-86
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• 2019

This paper is an overview of key elements of Korea National Open University's smart mobile learning system, and an attempt to evaluate its main services relative to the FRAME model and the Mobile Learning Development Model for distance learning in higher education. KNOU improved its system architecture to one based on xMOOC e-learning content delivery while also upgrading its PC-based online/mobile learning services to facilitate an easier and more convenient access to lectures and for better interactivity. From the users' viewpoint, the upgraded 'U-KNOU Campus' allows for a more integrated search capability coupled with better course recommendations and a customized notification service. Using the new system, the students can access not only the school- and peer-issued messages via online bulletin boards but also share information and pose questions to others including to the school faculty/officials and system administrators. Additionally, a new mobile payment method has been incorporated into the system so that the students can select and pay for additional courses from anywhere. In spite of these advances, the issue of device usability and content development remain; specifically U-KNOU Campus needs to improve its instructor-learner and learner-to-learner interactivity and mobile evaluation interface.

• Journal of Institute of Control, Robotics and Systems
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• 제17권8호
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• pp.731-738
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• 2011

In this paper, we introduce an advanced architecture of K-Means clustering-based polynomial Radial Basis Function Neural Networks (p-RBFNNs) designed with the aid of SSOA (Space Search Optimization Algorithm) and develop a comprehensive design methodology supporting their construction. In order to design the optimized p-RBFNNs, a center value of each receptive field is determined by running the K-Means clustering algorithm and then the center value and the width of the corresponding receptive field are optimized through SSOA. The connections (weights) of the proposed p-RBFNNs are of functional character and are realized by considering three types of polynomials. In addition, a WLSE (Weighted Least Square Estimation) is used to estimate the coefficients of polynomials (serving as functional connections of the network) of each node from output node. Therefore, a local learning capability and an interpretability of the proposed model are improved. The proposed model is illustrated with the use of nonlinear function, NOx called Machine Learning dataset. A comparative analysis reveals that the proposed model exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.