• Journal of The Korean Association For Science Education
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• v.39 no.4
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• pp.511-523
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• 2019

In this age of the $4^{th}$ industrial revolution, we, science educators, are giving more light on students' agentic behavior in the process of educating future scientist. This study, with the analytic lens of epistemic agency, explores the key stages of a student-driven R&E program rather than the scientist-led R&E program. It also examines to understand the emergence of students' epistemic agency in each stage of R&E. Data from participant observation for 18 months and in-depth interviews were collected and analyzed with the constant comparative method of grounded theory. This study identifies and describes five key stages of student-driven R&E: The stage of exploring research theme, designing research, performing lab activity, interpreting results, and communicating research. It also finds that (a) students' epistemic agency emerged with the constant interactions with the R&E structure; (b) students' epistemic agency has deep relations with the epistemic beliefs of the students; (c) students positioned themselves as decision-makers in the R&E practice; (d) the redistributed power and authority of the R&E contributed to the emergence of students' epistemic agency.

• Journal of Software Engineering Society
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• v.23 no.4
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• pp.151-163
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• 2010

In the defense software domain where large-scale software products in various application areas need to be built, reusing software is regarded as one of the important practices to build software products efficiently and economically. There have been many efforts to apply various methods to support software reuse in the defense software domain. However, developers in the defense software domain still experience many difficulties and face obstacles in reusing software assets. In this paper, we analyze practical problems of software reuse in the defense software domain, and define core requirements to solve those problems. To meet these requirements, we are currently developing the Component Grid system, a reuse-support system that provides a developer-centric software reuse environment. We have designed an architecture of Component Grid, and defined essential elements of the architecture. We have also developed the core approaches for developing the Component Grid system: a semantic-tagging-based requirement tracing method, a reuse-knowledge representation model, a social-network-based asset search method, a web-based asset management environment, and a wiki-based collaborative and participative knowledge construction and refinement method. We expect that the Component Grid system will contribute to increase the reusability of software assets in the defense software domain by providing the environment that supports transparent and efficient sharing and reuse of software assets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.383-392
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• 2018

This study was conducted to examine the effects of a meta-cognition teaching and learning program on nursing students' self-leadership, collaborative preference and problem solving ability. The study was designed using a nonequivalent control group pretest-posttest design. Data were collected between March 5 and June 30, 2018 from 74 2-year nursing students in D College of D City who were assigned to an experimental group (n=36) or a control group (n=38). The meta-cognition teaching and learning program consisted of 10 sessions of combined individual and small group learning. Data were analyzed using descriptive analysis, as well as a t-test, ${\chi}^2$-test, and paired t-test with the SPSS/WIN 21.0 program. After receiving the meta-cognition teaching and learning program, significant differences were observed in self-leadership (t=4.79, p<0.001), collaborative preference (t=5.07, p<0.001), and problem-solving ability (t=6.48, p<0.001) of the experimental group. The results of this study indicate that the meta-cognition teaching and learning program was effective at increasing self-leadership, collaborative preference and problem-solving ability in nursing students. It is expected that the results of this study will be used as basic data to improve self-leadership, collaborative preference and problem-solving ability of nursing students.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.64-74
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• 2019

Although a non-rigid registration has high demands in clinical practice, it has a high computational complexity and it is very difficult for ensuring the accuracy and robustness of registration. This study proposes a method of applying a non-rigid registration to 3D magnetic resonance images of brain in an unsupervised learning environment by using a deep-learning network. A feature vector between two images is produced through the network by receiving both images from two different patients as inputs and it transforms the target image to match the source image by creating a displacement vector field. The network is designed based on a U-Net shape so that feature vectors that consider all global and local differences between two images can be constructed when performing the registration. As a regularization term is added to a loss function, a transformation result similar to that of a real brain movement can be obtained after the application of trilinear interpolation. This method enables a non-rigid registration with a single-pass deformation by only receiving two arbitrary images as inputs through an unsupervised learning. Therefore, it can perform faster than other non-learning-based registration methods that require iterative optimization processes. Our experiment was performed with 3D magnetic resonance images of 50 human brains, and the measurement result of the dice similarity coefficient confirmed an approximately 16% similarity improvement by using our method after the registration. It also showed a similar performance compared with the non-learning-based method, with about 10,000 times speed increase. The proposed method can be used for non-rigid registration of various kinds of medical image data.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.33-46
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• 2019

Even though Korea is strengthening the support for startups due to the limitations of growth policies focusing on large companies, the survival rate of startups is very low, so that there should be more efforts to increase the survival rate of startups. As the existing startup support institutions have provided only fragmentary supports to startups, it would be necessary to have the comprehensive support institutions. As an alternative, the accelerator providing the comprehensive support such as spatial support, education, mentoring, networking, seed investment, and connection for follow-up investment to the initial startups was legalized in Korea of 2016, based on the registration system. Currently, within less than two year from then, there have been much interest in it enough to have about 136 registered accelerators. In the United States, the accelerator was introduced more than ten years ago. In Korea, however, it is still in the initial stage, so that the researches or social consensus on the accelerator are not sufficient. Thus, this study aims to suggest the measures for the development of accelerator and the consensus on the decision making for the selection of accelerator of startups, by researching which parts are considered when startups in the accelerator stage select the accelerator. As a result of the empirical analysis, the factor that has the greatest influence on decision making factors when startup chooses an accelerator was the subsequent investment attraction. This can be explained to the accelerator as desired, considering the factor that the startup of the initial stage places the most importance on growth as investment. We hope that these research results will be sustainable in future research related to accelerators, in hopes that it will be useful for establishing accelerator policies for domestic startups and direction for revitalizing related industries.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.27-32
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• 2020

Along with the aging of the population, the number of dementia patients is increasing, and the social and economic burden is also increasing. Currently, the effective way to manage dementia patients is to identify patients with dementia early. However, in rural and island areas where medical staff are scarce, there is a problem that it is difficult to visit a hospital and get an early examination. Therefore, we propose a remote early detection system for dementia to solve the problems. The remote dementia early diagnosis system is a system that allows a patient to receive examination and treatment from a remote dementia expert using remote medical technology based on real-time image communication. The remote early diagnosis system for dementia consists of a local client system used by medical staff at health centers in the island, an image server that transmits, stores and manages images, and an expert client used by remote dementia experts. The local client subsystem satisfies the current medical law's remote collaboration by allowing the patient to use it with the health center's medical staff. In addition, expert clients are used by dementia experts, and can store/manage patient information, analyze patient history information, and predict the degree of dementia progression in the future.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.651-658
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• 2020

The basic medical subjects are essential for the understanding of the major in the department of health science and are very important. Anatomy is one of the fundamental areas of medical education. On the other hand, the application of new teaching method is being attempted in various fields. Station rotation model, one of the blended learning, is also one of the popular teaching method. Station rotation model allows students to rotate through stations on a fixed schedule, where at least one of the stations is an online learning station. This study investigate the satisfaction of students when applying station rotation model to anatomy class. Each station in the station rotation model consisted of VR application learning, online problem solving, model observation and oral test. After applying station rotation model (2 weeks) to the 'Functional anatomy and Practice' course taken by 37 students of the'Department of Occupational Therapy'at H University, this study conducted a satisfaction survey compare with lecture class for students taking the course. At the result, station rotation model was significantly higher than lecture class in both understanding, interest, concentration and diversity degree. Based on these results, I suggest applying the station rotation model to the anatomy class because it also showed high satisfaction in that.

• Journal of the Korea Institute of Building Construction
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• v.22 no.4
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• pp.403-414
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• 2022

Many studies have been conducted on asset management of public facilities, as the importance of such management has been increasing. This basic study aims to present strategies for the practical use of public asset management, and seeks to propose efficient management and utilization measures from a cost perspective by comparing and analyzing the importance and impact relationship between cost items for public asset management. In this study, 19 sub-items and the top 4 items were chosen by deriving cost factors based on the previous literature. A survey was conducted, and the results of the survey were analyzed by using the Analytic Hierarchy Process(AHP) and Interpretive Structural Modeling (ISM) methods. The AHP was used to derive the priority between items, and ISM was used to identify major groups and mutual influences. As a result, those items showing both high priority and high importance, such as user cost, dismantling/disposal cost, replacement cost, maintenance/repair cost, etc. are determined as priority items to be considered for public asset management of public facilities. Also, it is necessary to minimize the impact on other items in public asset management by those items which are impacted less by other items but have significant impact on the items such as initial construction costs, conceptual design costs, construction costs, and supervision costs. It is expected that the results and analysis methods presented in this study can be used to provide strategies for asset management of public facilities.

• Smart Media Journal
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• v.12 no.3
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• pp.19-29
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• 2023

The eye tracking technology is widespread all around the society, and is demonstrating great performances in both preciseness and convenience. Hereby we can glimpse new possibility of an interface's conduct without screen-touching. This technology can become a new way of conversation for those including but not limited to the patients suffering from Lou Gehrig's disease, who are paralyzed each part by part of the body and finally cannot help but only moving eyes. Formerly in that case, the patients were given nothing to do but waiting for the death, even being unable to communicate with there families. A new interface that harnesses eyes as a new means of communication, although it conveys great difficulty, can be helpful for them. There surely are some eye tracking systems and equipment for their exclusive uses on the market. Notwithstanding, several obstacles including the complexity of operation and their high prices of over 12 million won($9,300) are hindering universal supply to people and coverage for the patients. Therefore, this paper suggests wearable-type eye tracking device that can support minorities and vulnerable people and be occupied inexpensively and study eye tracking method in order to maximize the possibility of future development across the world, finally proposing the way of designing and developing a brought-down costed eye tracking system based on high-efficient wearable device.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.2
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• pp.151-162
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• 2009

This study proposes a new methodology for quantitative rock classification in unsampled rock zone, which occupies the most of tunnel design area. This methodology is to train an ANN (artificial neural network) by using results from a drilling investigation combined with electric resistivity survey in sampled zone, and then apply the trained ANN to making a prediction of grade of rock classification in unsampled zone. The prediction is made at the center point of a shifting window by using a number of electric resistivity values within the window as input reference information. The ANN training in this study was carried out by the RPROP (Resilient backpropagation) training algorithm and Early-Stopping method for achieving a generalized training. The proposed methodology is then applied to generate a rock grade distribution on a real tunnel site where drilling investigation and resistivity survey were undertaken. The result from the ANN based prediction is compared with one from a conventional kriging method. In the comparison, the proposed ANN method shows a better agreement with the electric resistivity distribution obtained by field survey. And it is also seen that the proposed method produces a more realistic and more understandable rock grade distribution.