• Transactions of the Society of Information Storage Systems
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• v.1 no.2
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• pp.132-136
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• 2005

It is widely accepted that the reading mechanism of Super-RENS(super-resolution near field structure) and Super-ROM(super-resolution read only memory) is closely related with non-linear temperature dependent material properties such as refractive indices, phase change. Furthermore, the dynamic change of the temperature distribution also an essential part of reading mechanism of Super-RENS/ROM. Therefore, the knowledge of the temperature distribution as a function a time is one of the important keys to reveal the physics of reading mechanism in Super-RENS/ROM. We calculated time-dependent temperature distribution in a 3-dimensional Super-ROM disk structure when moving laser beam is irradiated. With a help of commercial software FEMLAB which employed finite element method, we simulated the temperature distribution of ROM structure whose pit diameter is 120-nm with 50-nm depth. Energy absorption by moving laser irradiation, time variations of heat transfer processes, heat fluxes, heat transfer ratios, and temperature distributions of the complicate 3-dimensional ROM structure have been obtained.

• Journal of Information Management
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• v.33 no.4
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• pp.107-128
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• 2002

The purpose of this study is developing a information support system for R&D decision making to maximize economic results of the R&D. This system is composed of studying the model of work flow for R&D decision making, analyzing a technology information, connecting with the databases from KISTI and others, and valuing R&D technology on line. Especially in the case of technology valuation, this system is combined with the valuation model which supports knowledge information for helping more objective estimation.

• Database Research
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• v.34 no.3
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• pp.137-147
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• 2018

A key to a well-performing human activity recognition (HAR) system through machine learning technique is the availability of a substantial amount of labeled data. Collecting sufficient labeled data is an expensive and time-consuming task. To build a HAR system in a new environment (i.e., the target domain) with very limited labeled data, it is unfavorable to naively exploit the data or trained classifier model from the existing environment (i.e., the source domain) as it is due to the domain difference. While traditional machine learning approaches are unable to address such distribution mismatch, transfer learning approach leverages the utilization of knowledge from existing well-established source domains that help to build an accurate classifier in the target domain. In this work, we propose a transfer learning approach to create an accurate HAR classifier with very limited data through the multitask neural network. The classifier loss function minimization for source and target domain are treated as two different tasks. The knowledge transfer is performed by simultaneously minimizing the loss function of both tasks using a single neural network model. Furthermore, we utilize the unlabeled data in an unsupervised manner to help the model training. The experiment result shows that the proposed work consistently outperforms existing approaches.

• Management & Information Systems Review
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• v.32 no.3
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• pp.43-59
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• 2013

The most important thing in training of organization is that how effectively it can be made most of the performance among the staff. It will be useless if the knowledge which gaining after training can not be applied. Therefore the transfer of learning is studied since it is important for decision of training. We studied the factors of transfer of learning and carried out a survey targeting the public officials of Gangwon province with the factors we made a study. We define the factor of both promoted and interrupted in training and suggest the way of improving it. The first, the modeling of competency can stimulate the desire of achievement and complete a course of training among staff of organizations. The second, the construction of training program and organizational culture just for Gangwon province can increase the satisfaction of training among the learners. The third, the establishment of management system after training can reinforce the capability making use of train. The sharing of each information with boss at the office can help to stimulate the function of feedback after training as well.

• Informatization Policy
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• v.17 no.1
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• pp.78-101
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• 2010

Unlike knowledge sharing or knowledge transfer, knowledge protection has received little attention in the literature. Knowledge protection play a very important role in keeping organization competitive. This study explores the differences in knowledge protection between public and private organizations by T-test and regression analysis. The results of this study shows that the level of knowledge protection in public organizations is lower than that in private organizations. There is even larger difference in the level of access to key knowledge from outside between the two sectors. Such difference can be explained by the unique characteristics of public sector organizations. Understanding why the level of knowledge protection differs between the public and private sector is very important. This study presents lessons and implications for management leadership.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.53-74
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• 2012

A challenge in fostering virtual communities is the continuous supply of knowledge, namely members' willingness to contribute knowledge to their communities. Previous research argues that giving away knowledge eventually causes the possessors of that knowledge to lose their unique value to others, benefiting all except the contributor. Furthermore, communication within virtual communities involves a large number of participants with different social backgrounds and perspectives. The establishment of mutual understanding to comprehend conversations and foster knowledge contribution in virtual communities is inevitably more difficult than face-to-face communication in a small group. In spite of these arguments, evidence suggests that individuals in virtual communities do engage in social behaviors such as knowledge contribution. It is important to understand why individuals provide their valuable knowledge to other community members without a guarantee of returns. In virtual communities, knowledge is inherently rooted in individual members' experiences and expertise. This personal nature of knowledge requires social interactions between virtual community members for knowledge transfer. This study employs the social capital theory in order to account for interpersonal relationship factors and identity theory for individual and group factors that may affect knowledge contribution. First, social capital is the relationship capital which is embedded within the relationships among the participants in a network and available for use when it is needed. Social capital is a productive resource, facilitating individuals' actions for attainment. Nahapiet and Ghoshal (1997) identify three dimensions of social capital and explain theoretically how these dimensions affect the exchange of knowledge. Thus, social capital would be relevant to knowledge contribution in virtual communities. Second, existing research has addressed the importance of identity in facilitating knowledge contribution in a virtual context. Identity in virtual communities has been described as playing a vital role in the establishment of personal reputations and in the recognition of others. For instance, reputation systems that rate participants in terms of the quality of their contributions provide a readily available inventory of experts to knowledge seekers. Despite the growing interest in identities, however, there is little empirical research about how identities in the communities influence knowledge contribution. Therefore, the goal of this study is to better understand knowledge contribution by examining the roles of social capital and identity in virtual communities. Based on a theoretical framework of social capital and identity theory, we develop and test a theoretical model and evaluate our hypotheses. Specifically, we propose three variables such as cohesiveness, reciprocity, and commitment, referring to the social capital theory, as antecedents of knowledge contribution in virtual communities. We further posit that members with a strong identity (self-presentation and group identification) contribute more knowledge to virtual communities. We conducted a field study in order to validate our research model. We collected data from 192 members of virtual communities and used the PLS method to analyse the data. The tests of the measurement model confirm that our data set has appropriate discriminant and convergent validity. The results of testing the structural model show that cohesion, reciprocity, and self-presentation significantly influence knowledge contribution, while commitment and group identification do not significantly influence knowledge contribution. Our findings on cohesion and reciprocity are consistent with the previous literature. Contrary to our expectations, commitment did not significantly affect knowledge contribution in virtual communities. This result may be due to the fact that knowledge contribution was voluntary in the virtual communities in our sample. Another plausible explanation for this result may be the self-selection bias for the survey respondents, who are more likely to contribute their knowledge to virtual communities. The relationship between self-presentation and knowledge contribution was found to be significant in virtual communities, supporting the results of prior literature. Group identification did not significantly affect knowledge contribution in this study, inconsistent with the wealth of research that identifies group identification as an important factor for knowledge sharing. This conflicting result calls for future research that examines the role of group identification in knowledge contribution in virtual communities. This study makes a contribution to theory development in the area of knowledge management in general and virtual communities in particular. For practice, the results of this study identify the circumstances under which individual factors would be effective for motivating knowledge contribution to virtual communities.

• Journal of The Korean Astronomical Society
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• v.52 no.6
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• pp.217-225
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• 2019

We apply a modified Convolutional Neural Network (CNN) model in conjunction with transfer learning to predict whether an active region (AR) would produce a ≥C-class or ≥M-class flare within the next 24 hours. We collect line-of-sight magnetogram samples of ARs provided by the SHARP from May 2010 to September 2018, which is a new data product from the HMI onboard the SDO. Based on these AR samples, we adopt the approach of shuffle-and-split cross-validation (CV) to build a database that includes 10 separate data sets. Each of the 10 data sets is segregated by NOAA AR number into a training and a testing data set. After training, validating, and testing our model, we compare the results with previous studies using predictive performance metrics, with a focus on the true skill statistic (TSS). The main results from this study are summarized as follows. First, to the best of our knowledge, this is the first time that the CNN model with transfer learning is used in solar physics to make binary class predictions for both ≥C-class and ≥M-class flares, without manually engineered features extracted from the observational data. Second, our model achieves relatively high scores of TSS = 0.640±0.075 and TSS = 0.526±0.052 for ≥M-class prediction and ≥C-class prediction, respectively, which is comparable to that of previous models. Third, our model also obtains quite good scores in five other metrics for both ≥C-class and ≥M-class flare prediction. Our results demonstrate that our modified CNN model with transfer learning is an effective method for flare forecasting with reasonable prediction performance.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.24-38
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• 2021

This study aims to measure Korea's global competitiveness in intelligent information technology, which is the core technology of the 4th industrial revolution. For analysis, we collect patents of each field and prior patents cited by them, which are applied at the U.S. Patent Office (USPTO) between 2010 and 2018 from PATSTAT Online. A global knowledge transfer network was established by grouping citing- and cited-relationships at a national level. The in-degree centrality is used to evaluate technology acceptance, which indicates the process of absorbing existing technological knowledge to create new knowledge in each field. Second, to evaluate the impact of existing technological knowledge on the creation of new one, the out-degree centrality is investigated. Third, we apply the PageRank algorithm to qualitatively and quantitatively investigate the importance of the relationships between countries. As a result, it is confirmed through all the indicators that the AI sector is currently the least competitive.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.205-225
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• 2023

The Study is to investigate information resources recognition of collection development policy that is a key element of Gwangju representative library. 68 Librarians, 98 library users and 20 libraries responded the questions of information resources. The fields of the questions are media, subjects and levels of information resources. The results of the research are as follows. First, the correlation coefficients between librarian group's preference and need is lower than that of the user group. Second, information resources for the knowledge-disadvantaged has low preference and need but the actual usage rate was high. Third, Librarians need to transfer historical paper and books, historical objects, technical reports and journal articles to the representative library. Fourth, information resources about philosophy have middle preference, low need and the resources have low need for transfer to representative library. Fifth, local historical resources and administrative policy resources has low usage rate high need for transfer to representative library. Sixth, the level of public library in Gwangju is 1.837 and the expectative level of Gwangju representative library is 3.325.

• International Commerce and Information Review
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• v.8 no.3
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• pp.385-396
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• 2006

The successful knowledge and information based companies facilitate to restructure the industry and strengthen the national competitiveness in the future. The advent of information age provides us new challenge because the information breakthrough can play a pivotal role in terms of knowledge transfer in the human resource management. Executive officer must present long term vision in order to expand enterprise continuously and establish long term management goal and strategy which are appropriate for key organizational skills of future management environment (Pfeffer, 1998). Also, long term talent management based on vision, goal and strategy and talent development strategy and employment management must be established (小池, 1994)). American HRM system's reformation cannot be defined without scientific management policy. However, currently widely discussed Japanese HRM system's reformation cannot be defined without organizational commitment focused Japanese employment system. (津田, 1992 ; 太田, 1994). Japan's development of the following policies are behind comparing to Europe : (1)Skill based talent management regardless of age, sex, nationality, race and academic background (2)Consideration of retirement age of 64 (3)Creativity and freedom promoting talent management policy. Also, there are problems to be solved. Solutions will be searched for by establishing new wage policy based on tasks and individuals in the basis of lifetime employment system.