• Korea Trade Review
• /
• v.45 no.5
• /
• pp.161-179
• /
• 2020

The importance of entering the international market for small and medium-sized enterprises (SMEs) has been continuously emphasized. As a way to overcome these factors, prior studies have increased interest in dynamic capability. The purpose of this study is to investigate the effects of entrepreneurial orientation, learning orientation, and dynamic capability on their international performance of SMEs. Drawing on an extensive review of the literature on dynamic capability view and internationalization, hypotheses are developed and tested using a sample of 214 SMEs in South Korea. Structural equation modeling was applied. As a result of analysis, first, dynamic capability has a significant effect on international performance. Second, entrepreneurial orientation has significant influence on dynamic capability. Third, learning orientation has significant influence on dynamic capability. Lastly, slack resource was found to moderate the relationship between dynamic capability and international performance. The results indicate that their entrepreneurial orientation and learning orientation ware driver of their dynamic capability. and that their dynamic capability was significant driver of their international performance. In the final conclusion, implications and limitations of research and suggestions for future research are discussed.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.25 no.3
• /
• pp.41-52
• /
• 2023

This study developed and taught VR content to be used in clothing design and composition practice, which are practical subjects for home education students at the College of Education, and examined the learning effects on students who participated in VR experiences. First, after experiencing classes using VR content, students' perceptions of classes were examined considering participation, class level, expectations, and satisfaction through a survey. As a result of examining the experience of learning sewing machines in classes using VR content and changes in perception of classes, it was found that the class level, class expectations, and satisfaction were affected. As a result of comparative analysis of VR experiences and the perception of VR classes prior to experiencing VR content related to sewing machines developed for practical subjects, VR experiences affected class participation, class level, expectations, but satisfaction was not affected. The advantages of the VR class that students mentioned in the subjective evaluation included interest in the class, the degree of participation, the VR experience, and the use of VR. As for the disadvantages, difficulties in using the device, dizziness, frustration when using the device, and limitations of the program were mentioned.

• The KIPS Transactions:PartB
• /
• v.15B no.4
• /
• pp.331-340
• /
• 2008

Feature Selection is one of methods to improve the classification accuracy of data in the field of machine learning. Many feature selection algorithms have been proposed and discussed for years. However, the problem of finding the optimal feature subset from full data still remains to be a difficult problem. Bio-inspired algorithms are well-known evolutionary algorithms based on the principles of behavior of organisms, and very useful methods to find the optimal solution in optimization problems. Bio-inspired algorithms are also used in the field of feature selection problems. So in this paper we proposed new improved bio-inspired algorithms for feature selection. We used well-known bio-inspired algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), to find the optimal subset of features that shows the best performance in classification accuracy. In addition, we modified the bio-inspired algorithms considering the prior importance (prior relevance) of each feature. We chose the mRMR method, which can measure the goodness of single feature, to set the prior importance of each feature. We modified the evolution operators of GA and PSO by using the prior importance of each feature. We verified the performance of the proposed methods by experiment with datasets. Feature selection methods using GA and PSO produced better performances in terms of the classification accuracy. The modified method with the prior importance demonstrated improved performances in terms of the evolution speed and the classification accuracy.

• Journal of The Korean Association For Science Education
• /
• v.15 no.2
• /
• pp.213-222
• /
• 1995

Analyzing textbook is the first step for enhancing the level of biology education especially in Korea. Prior studies of textbook analysis have mostly dealt with such topics as terminology analysis, content analysis, relationship analysis of chapters, and comparative studies. However, not much attention was paid to concept system to be learned and to relevance of concepts chosen. Therefore, the purpose of this study is to clarify the concept system and to elucidate the relationship among concepts for effective learning. Novak's concept map was utilized as a theoretical framework for the analysis of chapter I of high school biology textbook. Concept map has several distinctive merits in many aspects such as teaching, learning, and evaluation. It not only makes the understanding of key concepts and proposition a lot easier, but also helps to link prior knowledge and new concepts more effectively. This study will be a basic material for improving textbook for effective biology learning. The conclusions of the study are as follows: 1. Concepts in subchapters were arranged unsystematically or they were overlapping. For more effective understanding, those items should be rearranged. 2. Key concepts are not arrayed properly according to their hierarchy. Therefore, it was hard for students to set up concept structure. 3. The concepts emphasized by bold letters were not selected properly in accordance with their importance. Appropriate concepts should be chosen. 4. Key concepts should be explained by using examples in everyday life for easy understanding. 5. Many concepts in molecular biology is too abstract to grasp their meaning. Therefore, many audio-visual materials should be used to aid concept building.

• The Journal of Information Systems
• /
• v.27 no.2
• /
• pp.1-28
• /
• 2018

Purpose More than 7.6 million mobile apps could be approved on both Apple iTunes Store and Google Play. For managing those existed Apps, Apple Inc. established twenty-four primary categories, as well as Google Play had thirty-three primary categories. However, all of their categorizations have appeared more and more problems in managing and classifying numerous apps, such as app miscategorized, cross-attribution problems, lack of categorization keywords index, etc. The purpose of this study focused on introducing individual information cognitive processing as the classification criteria to update the current categorization on Apple iTunes Store. Meanwhile, we tried to observe the effectiveness of the new criteria from a classification process on Apple iTunes Store. Design/Methodology/Approach A research approach with four research stages were performed and a series of mixed methods was developed to identify the feasibility of adopting individual information cognitive processing as categorization criteria. By using machine-learning techniques with Term Frequency-Inverse Document Frequency and Singular Value Decomposition, keyword lists were extracted. By using the prior research results related to car app's categorization, we developed individual information cognitive processing. Further keywords extracting process from the extracted keyword lists was performed. Findings By TF-IDF and SVD, keyword lists from more than five thousand apps were extracted. Furthermore, we developed individual information cognitive processing that included a categorization teaching process and learning process. Three top three keywords for each category were extracted. By comparing the extracted results with prior studies, the inter-rater reliability for two different methods shows significant reliable, which proved the individual information cognitive processing to be reliable as criteria of categorization on Apple iTunes Store. The updating suggestions for Apple iTunes Store were discussed in this paper and the results of this paper may be useful for app store hosts to improve the current categorizations on app stores as well as increasing the efficiency of app discovering and locating process for both app developers and users.

• (The)Korea Educational Review
• /
• v.23 no.1
• /
• pp.379-404
• /
• 2017

The purpose of this study is to seek practical implementation of adult learner-targeted college. For this, it first of all pointed out expanding opportunities of adult learners to learn and limitation of current lifelong education system at higher education level as well as lifelong learning centered university project. Then it selected and examined 3 university cases abroad, such as Harvard university, the university of Chicago in US and Warwick university in UK in terms of their curriculum and operating method for adult learners. In addition to the literature and case studies, this study did interviews on 5 professors with major of lifelong education and 5 managerial experts of university to suggest practical operating approach of adult learner-targeted college, which is as following. University's philosophy should be geared to meet public responsibility, specialization and persistency of the system and proper measurement be followed such as various range of admission track, prior education courses, recognition of prior learning experience, major, teaching method, curriculum and extra adult learner tailored service including financial support. Based on the study result, practical implications were suggested.

• Journal of the Korea Computer Graphics Society
• /
• v.29 no.4
• /
• pp.7-16
• /
• 2023

For decades, creating a desired locomotive motion in a goal-oriented manner has been a challenge in character animation. Data-driven methods using generative models have demonstrated efficient ways of predicting long sequences of motions without the need for explicit conditioning. While these methods produce high-quality long-term motions, they can be limited when it comes to synthesizing motion for challenging novel scenarios, such as punching a random target. A state-of-the-art solution to overcome this limitation is by using a GAN Discriminator to imitate motion data clips and incorporating reinforcement learning to compose goal-oriented motions. In this paper, our research aims to create characters performing combat sports such as boxing, using a novel reward design in conjunction with existing GAN-based approaches. We experimentally demonstrate that both the Adversarial Motion Prior [3] and Adversarial Skill Embeddings [4] methods are capable of generating viable motions for a character punching a random target, even in the absence of mocap data that specifically captures the transition between punching and locomotion. Also, with a single learned policy, multiple task controllers can be constructed through the TimeChamber framework.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.1
• /
• pp.23-30
• /
• 2022

Recently, there are various studies underway on the deep learning-used image matting methods. Even in the field of photogrammetry, a process of extracting information about relics from images photographed is essential to produce a high-quality realistic model. Such a process requires a great deal of time and manpower, so chroma-key has been used for extraction so far. This method is low in accuracy of sub-classification, however, it is difficult to apply the existing method to high-quality realistic models. Thus, this study attempted to remove background information from high-resolution relic images by using prior background information and trained learning data and evaluate both qualitative and quantitative results of the relic images extracted. As a result, this proposed method with FBA(manual trimap) showed quantitatively better results, and even in the qualitative evaluation, it was high in accuracy of classification around relics. Accordingly, this study confirmed the applicability of the proposed method in the indoor relic photography since it showed high accuracy and fast processing speed by acquiring prior background information when classifying high-resolution relic images.

• Journal of Digital Convergence
• /
• v.11 no.2
• /
• pp.127-135
• /
• 2013

For the successful implementation of IT projects, individual consultant's competency in the project is very important. Especially, 3 key factors which are 1) Learning-by-Doing, 2) Learning-from-Others, and 3) Learning-by-Investment with individual consultant's competency, are required for solving various critical issues which can be occurred during implementing IT project. The objective of this research is to examine the effects of these learning processes on decision performance of consultants. Prior to setup the research model, we conducted 3 times in-depth interviews with IT consultants who have over 20 years IT project experiences. Through interviews with IT project expert, we tried to validate our research model and develop survey questionnaires. Over 100 consultants, who are working at SI companies those of Samsung SDS, LG CNS, SK C&C and other small SI companies, were participated to survey. In the contrary of our thoughts before conducted experiment, we got the interesting result from pilot experiment. Most influenced learning process was Learning-by-Doing and less influenced learning process was Learning-from-Others.

• Proceedings of the Korea Contents Association Conference
• /
• 2006.05a
• /
• pp.160-163
• /
• 2006

If an instruction system understood the interest and activeness of a learner in real time, it could provide some interesting factors when a learner is tired of learning. It could work as an adaptive tutoring system to help a learner to understand something difficult to understand. Currently the area of the facial expression recognition mainly deals with the facial expression of adults focusing on anger, hatred, fear, sadness, surprising and gladness. These daily facial expressions couldn't be one of expressions of a learner in e-Learning. They should first study the facial expressions of a learner in e-Learning to recognize the feeling of a learner. Collecting as many expression pictures as possible, they should study the meaning of each expression. This study, as a prior research, analyzes the feelings of learners and facial expressions of learners in e-Learning in relation to the feelings to establish the facial expressions database.