• The Korean Journal of Emergency Medical Services
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• v.7 no.1
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• pp.109-118
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• 2003

With the rapid development of information and communication technology, a lot of multi-media learning programs are being developed and reported in the field of Emergency medicine both home and abroad. In this connection, this study was aimed at developing a foreign-body airway obstruction courseware in adults for EMT. The development period of CAI courseware lasted from May 2003 through November 2003. Among CAI courseware patterns, private instruction and repeat practice and simulation patterns were used as an instruction-learning strategy. The learning contents of the CAI courseware consisted of five chapters concerning (1) A relief of partial FBAO in the responsible victim, (2) A relief of complete FBAO in the responsible victim, (3) In case of unconsciousness in the responsible victim without removing all foreign body, (4) In case of consciousness in all victims after getting removed all foreign body and (5) A complete airway obstruction in victims without consciousness on the basis of assess responsiveness and the degree of airway obstruction. The way to use this courseware, with just a click on one specific chapter, was developed to proceed a course with progressive algorithm, a method of solving problems by choosing one between two situations. A characteristic of this CAI courseware is the enhanced efficiency of an instruction-learning method by providing an opportunity of choice based on situations in its effort to encourage learners to use a self-initiated learning method, not one-way method and to enhance problem solving skills among situations. Moreover, this courseware went through the diverse phases such as development, application, feedback in connection with learning process by practicing teachers, so that the courseware could be used frequently in the future. The contents of this courseware were written with the web, so that, if necessary, the contents could be continuously modified and complemented and handed out in the form of CD-ROM. This study indicates that the development of a variety of CAI courseware requires institutional and financial assistance and initiatives reflecting a reality in terms of learning process, technical assistance and resources.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.25-34
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• 2022

Today, further education of adults in the UK is one of the developing areas of continuing education. The Open University with distance learning, in the process of which innovative forms and methods based on computer and telecommunication technologies are used, is particularly successful in the organization of additional education of the adult population. The advantages of distance learning, multimedia - the latest information technologies, which provide the combination of graphic images, video, sound with the help of modern computer tools, are noted. The basic principles and forms underlying the technologies and forms of work with the elderly are defined. The international experience of implementing "Universities of the Third Age" is summarized. The most widespread approach in adult education in Great Britain is informational. The use of computer technologies motivates a new paradigm in educational methods and strategies, which requires new approaches, forms of learning, and innovative ways of delivering educational materials to adult learners. Information technologies have gained great popularity in such activities as distance learning, online learning, assistance in the education management system, development of programs and virtual textbooks in various subjects, online search for information for the educational process, computer testing of students' knowledge, creation of electronic libraries, formation of a single scientific electronic environment, publication of virtual magazines and newspapers on pedagogical topics, teleconferences, expansion of international cooperation in the field of Internet education. The information technology of synchronous distance learning "online" has gained considerable popularity in the educational process today. A promising direction is the use of multimedia technologies in educational activities to create a design of a virtual computer environment by decoding audiovisual information.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.92-98
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• 2006

The purpose of this paper is to study of the attitude of e-learning on the effectiveness of e-learning and the antecedents of e-learning. For this study, samples were collected in the school where e-learning was students of cyber lecture. Structural equation model was used to analyze the data. The result of this empirical study is summarized as followings. First, The attitude of e-learning has a positive effect on the e-learning effectiveness. Second, ease of use of learning management system, learning motivation, information quality of learning contents has positive effect on the attitude of e-learning, but usefulness of learning management system has no effect on the attitude of e-learning. Therefore, the former consists of learning management system, learning contents and information quality that are provided by e-learning and the latter means learning motivation.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.47-57
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• 2012

This study was conducted to investigate the pre-service teacher's perception of the possibility of using smartphones in the classroom, moreover, to confirm the policy related to using smartphones in schools. For the objectives, this study, firstly, investigated the pre-service teacher's awareness of having cellphones in the classroom, secondly, analyzed the pre-service teacher's opinion of using smartphones for educational objectives and elements for those investigated objectives, finally, investigated the school policy for educational objectives of using smartphones. The participants of this study were 146 pre-service teachers among three universities in Seoul. The results showed that the pre-service teachers opposed using cellphones in the classroom. Next, it was found that most of them had smartphones and they knew how to use them effectively. For the aspects of educational use of smartphones, they recognized that smartphones could be used as a smart educational tool, an efficient teaching and learning tool, and an assistant tool for teaching and learning. In order to use smartphones for the investigated educational tools, the learning contents, the ways of teaching and learning, and the technical support of the school should be prepared. Finally, the pre-service teachers thought that the school policy should be changed in order to use smartphones for educational objectives, and the school policy with regard to using smartphones in the classroom should be decided by the teachers. Most of all, for the educational use of smartphones, the pre-service teachers believed that the change of the students' perception was the most significant.

• Imaging Science in Dentistry
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• v.46 no.3
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• pp.211-216
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• 2016

Purpose: The use of electronic tools in teaching is growing rapidly in all fields, and there are many options to choose from. We present one such platform, Learning Catalytics$^{TM}$ (LC) (Pearson, New York, NY, USA), which we utilized in our oral and maxillofacial radiology course for second-year dental students. Materials and Methods: The aim of our study was to assess the correlation between students' performance on course exams and self-assessment LC quizzes. The performance of 354 predoctoral dental students from 2 consecutive classes on the course exams and LC quizzes was assessed to identify correlations using the Spearman rank correlation test. The first class was given in-class LC quizzes that were graded for accuracy. The second class was given out-of-class quizzes that were treated as online self-assessment exercises. The grading in the self-assessment exercises was for participation only and not accuracy. All quizzes were scheduled 1-2 weeks before the course examinations. Results: A positive but weak correlation was found between the overall quiz scores and exam scores when the two classes were combined (P<0.0001). A positive but weak correlation was likewise found between students' performance on exams and on in-class LC quizzes (class of 2016) (P<0.0001) as well as on exams and online LC quizzes (class of 2017) (P<0.0001). Conclusion: It is not just the introduction of technological tools that impacts learning, but also their use in enabling an interactive learning environment. The LC platform provides an excellent technological tool for enhancing learning by improving bidirectional communication in a learning environment.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.342-353
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• 2022

This study aims to help revitalize the real-time online education platform market by analyzing the instructor characteristics, content characteristics, and platform characteristics of real-time online education platforms for local learners in China. A total of 670 questionnaires were collected through an online survey and an empirical analysis was conducted. As a result of the analysis, first, except for attractiveness, which is the characteristic of the instructor, professionalism and sincerity had a significant positive influence on both learning satisfaction. Second, the usefulness, abundance, and appropriateness of content characteristics had a significant positive influence on learning satisfaction. Third, except for interaction, which is a platform characteristic, technology and convenience confirmed a significant positive influence relationship on both learning satisfaction. Fourth, learning satisfaction had a significant positive effect on the intention to continue using. This study presented practical implications for real-time online education platform and future research directions.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.778_779
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• 2009

The maximum output torque developed by the machine is dependent on the allowable current rating and maximum voltage that the inverter can supply to the machine. Therefore, to use the inverter capacity fully, it is desirable to use the control scheme considering the voltage and current limit condition, which can yield the maximum torque per ampere over the entire speed range. The paper is proposed maximum torque control of induction motor drive using adaptive learning neuro fuzzy controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d, q axis current $_i_{ds}$, $i_{qs}$ for maximum torque operation is derived. The proposed control algorithm is applied to induction motor drive system controlled adaptive learning neuro fuzzy controller and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the adaptive learning neuro fuzzy controller and ANN controller.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.4
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• pp.99-102
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• 2018

Caffe is a neural net learning software which is widely used in academic researches. The GPU memory capacity is one of the most important aspects of designing neural net architectures. For example, many object detection systems require to use less than 12GB to fit a single GPU. In this paper, we extended Caffe to allow to use more than 12GB GPU memory. To verify the effectiveness of the extended software, we executed some training experiments to determine the learning efficiency of the object detection neural net software using a PC with three GPUs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1466-1488
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• 2022

Recently, the importance and necessity of artificial intelligence (AI), especially machine learning, has been emphasized. In fact, studies are actively underway to solve complex and challenging problems through the use of AI systems, such as intelligent CCTVs, intelligent AI security systems, and AI surgical robots. Information security that involves analysis and response to security vulnerabilities of software is no exception to this and is recognized as one of the fields wherein significant results are expected when AI is applied. This is because the frequency of malware incidents is gradually increasing, and the available security technologies are limited with regard to the use of software security experts or source code analysis tools. We conducted a study on MalDC, a technique that converts malware into images using machine learning, MalDC showed good performance and was able to analyze and classify different types of malware. MalDC applies a preprocessing step to minimize the noise generated in the image conversion process and employs an image augmentation technique to reinforce the insufficient dataset, thus improving the accuracy of the malware classification. To verify the feasibility of our method, we tested the malware classification technique used by MalDC on a dataset provided by Microsoft and malware data collected by the Korea Internet & Security Agency (KISA). Consequently, an accuracy of 97% was achieved.