• Journal of Venture Innovation
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• v.6 no.1
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• pp.115-137
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• 2023

This study analyzed the relationship between organizational innovative capability and absorptive capacity, market and technology orientations, and their impact on business performance for IT-BPO companies that are required to absorb new technologies from a leading perspective in the digital transformation era. To achieve this, an online specialized research company and offline surveys were conducted on 291 domestic IT-BPO companies, and SPSS 23 was used for descriptive statistics and reliability analysis while AMOS 23 was used for hypothesis testing including validity and mediating effects. The main findings were as follows: First, in the relationship between innovation and absorptive capabilities and Market Orientation Strategic(MOS), learning capability and knowledge network capability were found to have a statistically significant positive (+) effect on MOS. In the relationship between innovation and absorptive capabilities and Technology Orientation Strategic(TOS), R&D capability, potential absorptive capacity, and realized absorptive capacity had a statistically significant positive (+) effect on TOS. Second, in the relationship between innovation and absorptive capabilities and BP, only R&D capability was found to have a significant effect on BP. Third, both market orientation and technology orientation were found to have a significant positive (+) effect on BP. These findings suggest that effective competency factors can be identified according to the market and technology orientations pursued by IT-BPO companies to increase their growth and value creation, and provide implications for developing differentiated competency enhancement strategies based on strategic objectives.

• The Journal of the Korea Contents Association
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• v.14 no.4
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• pp.522-533
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• 2014

The capability of the digital communication would need to be strengthened for leveraging collaborative knowledge building and problem solving skills of the middle aged people. It was developed and implemented a smart learning model by utilizing the formative intervention based on the logic of change laboratory to target learners of 'K organization', As a results, smart learning model was composited several activities and supporting systems such as learning instructions of Smart Pad, communication games and SNS, using self-diagnosis and making posters and role-playing video by the internet applications. This research is significant that it finds efficient method to fit design of smart learning and the needs of target learners by using them as testbed which is mixed with different background and digital communication experiences.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.417-423
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• 2017

Recently, many embedded devices that have the computing capability required for deep learning have become available; hence, many new applications using these devices are emerging. However, these embedded devices have an architecture different from that of PCs and high-performance servers. In this paper, we propose a method that improves the performance of deep-learning framework by considering the architecture of an embedded device that shares memory between the CPU and the GPU. The proposed method is implemented in Caffe, an open-source deep-learning framework, and is evaluated on an NVIDIA Jetson TK1 embedded device. In the experiment, we investigate the image recognition performance of several state-of-the-art deep-learning networks, including AlexNet, VGGNet, and GoogLeNet. Our results show that the proposed method can achieve significant performance gain. For instance, in AlexNet, we could reduce image recognition latency by about 33% and energy consumption by about 50%.

• Journal of Fisheries and Marine Sciences Education
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• v.22 no.3
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• pp.431-444
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• 2010

This research aims at developing a teachers' training program to reinforce teachers' capability to perform the action learning program. To accomplish this goal, the key value of the training program based on action learning, the process of the core learning activities, and the elements to support learners and facilitators respectively were deducted on the foundation of documentary research and case study, based on which, the program was developed through the formative test by professionals and application to the field. This research was applied to 105 middle or high school teachers, the participants of the in-service training on creative problem solving hosted by B metropolitan city for one week (30 hours) from 9 a.m. on Monday, January 25th, 2010 to 4 p.m. on Friday, January 29th. The result of this research is as follows. First, as for the key values of this study, (1) the team-based learning centered on the trainees, not lecturers-oriented, knowledge-transmitting training, is possible, (2)for each process, guidelines, related information, tools, and various kinds of media are supported just in time, and (3)a focus is given on fostering facilitators centered on teachers. Second, the process of the core learning activities of the teachers' training program based on action learning consists of the procedure of a prior lecture${\rightarrow}$break${\rightarrow}$investigation into problems${\rightarrow}$clarification of problems${\rightarrow}$drawing possible solutions${\rightarrow}$decision on the priority${\rightarrow}$making an action plan${\rightarrow}$performance${\rightarrow}$evaluation, and on each stage, the contents for the activities of teachers and learners and detailed supportive elements are offered.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.6
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• pp.44-51
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• 1999

The HMM-Net is a neural network architecture that implements the computation of output probabilities of a hidden Markov model (HMM). The architecture is developed for the purpose of combining the discriminant power of neural networks with the time-domain modeling capability of HMMs. Criteria of maximum likehood(ML) and minimization of mean squared error(MMSE) are used for learning HMM-Net classifiers. The criterion MMSE is better than ML when initial learning condition is well established. However Ml is more useful one when the condition is incomplete[3]. Therefore we propose an efficient learning method of HMM-Net classifiers using a hybrid criterion(ML/MMSE). In the method, we begin a learning with ML in order to get a stable start-point. After then, we continue the learning with MMSE to search an optimal or near-optimal solution. Experimental results for the isolated numeric digits from /0/ to /9/, a training and testing time-series pattern set, show that the performance of the proposed method is better than the others in the respects of learning and recognition rates.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.126-137
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• 2020

This study provided implications for applying learner-centered teaching methods in the field of management education by adopting flipped learning and team-based learning to Business Communication classes and operating the classes according to its characteristics. Business communication capability, especially related to drawing up a document or a written report, is considered one of the crucial factors for making individuals valuable in an organization. For the identification of the subject outputs, a total of 64 students from the first and second semesters in 2018 were sampled, and the Wilcoxon signed rank test and paired t-tests were carried out. The results show that all types of communication capabilities have significantly increased at the end of each of the semesters. Also, the overall satisfaction level proved to be higher at the end rather than at the beginning of each semester. This study is especially meaningful because the results suggest concrete ways to apply learner-centered teaching methods for business education.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.69-77
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• 2017

In this paper, a disaster response scheme based on deep learning and augmented reality technology is proposed and a network resource reservation scheme is presented accordingly. The features of deep learning, augmented reality technology and its relevance to the disaster areas are explained. Deep learning technology can be used to accurately recognize disaster situations and to implement related disaster information as augmented reality, and to enhance disaster response capabilities by providing disaster response On-site disaster response agent, ICS (Incident Command System) and MCS (Multi-agency Coordination Systems). In the case of various disasters, the fire situation is focused on and it is proposed that a plan to strengthen disaster response capability effectively by providing fire situation recognition based on deep learning and augmented reality information. Finally, a scheme to secure network resources to utilize the disaster response method of this paper is proposed.

• Journal of The Korean Association of Information Education
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• v.16 no.3
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• pp.337-352
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• 2012

In this paper, a smart education system is developed and implemented for ADHD students. Usually, ADHD students lack of self efficacy. Self efficacy is very important factor for improving social adaptability and learning effect of ADHD students. In the proposed system, MLE concept is adapted. MLE concept is used to improve self efficacy of ADHD students. The purpose of the proposed system is to help ADHD students have high study capability. The proposed system is applied an ADHD student. The following results are obtained. First, the system can improve study interests. In turn, the system is helpful to improve concentration and learning effect. Second, based on successful study experience, self efficacy is improved. Third, study achievement is improved by changing cognitive structure that is due to development of meta-cognition.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.645-655
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• 2020

Bacteria are a very common cause of food poisoning. Moreover, bacteria form biofilms to protect themselves from harsh environments. Conventional detection methods for foodborne bacterial pathogens including the plate count method, enzyme-linked immunosorbent assays (ELISA), and polymerase chain reaction (PCR) assays require a lot of time and effort. Hyperspectral imaging has been used for food safety because of its non-destructive and real-time detection capability. This study assessed the feasibility of using hyperspectral imaging and machine learning techniques to detect biofilms formed by Escherichia coli. E. coli was cultured on a high-density polyethylene (HDPE) coupon, which is a main material of food processing facilities. Hyperspectral fluorescence images were acquired from 420 to 730 nm and analyzed by a single wavelength method and machine learning techniques to determine whether an E. coli culture was present. The prediction accuracy of a biofilm by the single wavelength method was 84.69%. The prediction accuracy by the machine learning techniques were 87.49, 91.16, 86.61, and 86.80% for decision tree (DT), k-nearest neighbor (k-NN), linear discriminant analysis (LDA), and partial least squares-discriminant analysis (PLS-DA), respectively. This result shows the possibility of using machine learning techniques, especially the k-NN model, to effectively detect bacterial pathogens and confirm food poisoning through hyperspectral images.

• Management & Information Systems Review
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• v.31 no.4
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• pp.611-638
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• 2012

With recognition of the self-leadership and creative personality for developing student competitive capability, this study examines the relationships among self-leadership, creative personality, innovative behaviour and learning satisfaction based on survey data from university students. The main findings of the study are as follows: first, the study found that self-leadership was positively associated with creative personality while there was also a positive relationship between self-leadership and innovative behaviour as well as learning satisfaction. Second, the empirical analysis of the paper also shows that creative personality partially mediated the relationship of self-leadership and innovative behaviour, but not for the relationship between self-leadership and learning satisfaction. In addition, the hypothesis on the positive association between learning satisfaction and innovative behaviour was not supported. This paper contributes to our understanding of self-leadership and innovative behaviour research by expanding to university student context and highlighting the role of creative personality. This study proposes that developing the self-leadership and creative personality of student are required for better innovative behaviour and thereby, learning performance.