• Journal of Service Research and Studies
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• v.3 no.2
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• pp.61-74
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• 2013

Lately, We have experienced increasing of Smartphone. Therefore we have experienced increasing of Application for Smartphone. This study suggested Lock-Toeic Learning Application using the smartphone. English the universal language of the world. TOEIC need to get job in Korea. It should be able to learn using LOCK-TOEIC Application of smartphone. This study add an Lock Screen Learning differentiate function of other smartphone application. We can expect Iteration learning effect using this study of Loch TOEIC smatphone application.

• Journal of Industrial Convergence
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• v.19 no.4
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• pp.1-8
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• 2021

This study was conducted with the aim of developing a mobile app so that parents and children can provide questions and conversation-based Home Humanity Education. App development was developed in four stages: analysis, design, development, and evaluation by modifying the ADDIE model. In the analysis stage, education goals were set and seven core competencies were extracted for the app. In the design stage, 15 menus, including character to implement seven core competencies, were selected for learning contents. In the development stage, questions were asked based on 1,000 photos, and parents and children naturally talked to strengthen their core competencies. In the evaluation stage, the user's evaluation interview was followed by a reflux process that produced and reflected improvements. Based on research results, it is going to suggest follow-up research on developing apps for home humanity education. First, it is necessary to verify the learning experiences and changes that occur when parents and children use apps for a long time through longitudinal research. Second, a follow-up study is needed on how to use the home humanity education app by age and how to improve it accordingly. Third, as the number of cases in which grandparents raise their grandchildren increases, it is necessary to study the process and learning effects of grandparents and grandchildren using the app.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.607-612
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• 2002

An automatic design method of behaviors in behavior-based robotics is proposed. With this method, a robot can design its behaviors by itself without aids of human designer. Automating design procedure of behaviors can make the human designer free from somewhat tedious endeavor that requires to predict all possible situations in which the robot will work and to design a suitable behavior for each situation. A simple reinforcement learning strategy is the main frame of this method and the key parameter of the learning process is significant change of reward value. A successful application to mobile robot navigation is reported too.

• Cross-Cultural Studies
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• v.31
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• pp.263-286
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• 2013

The goal of this study is to explore the possibility of applying the podcasting in Korean education for foreign students. To achieve this goal, concepts and applicability of the podcasting is discussed. Previous studies on foreign language education are reviewed and the cases on Korean language education based on technology using mobile phones are investigated. Some of the outstanding merits of the podcasting are found to be its accessibility, mobility and variability along with its room for control by the learners. It also enables the learners to be motivated and to enhance their learning ability. In addition, the podcasting with the content-based instruction is applied for the foreign students majoring in business and its results and implications are discussed. Based on the above results of this study, more active discussions are expected on such issues as educational designs through the podcasting, related variables and the performance evaluation.

• Electronics and Telecommunications Trends
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• v.38 no.6
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• pp.95-106
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• 2023

As artificial intelligence has become commonplace in various fields, the transparency of AI in its development and implementation has become an important issue. In safety-critical areas, the eXplainable and/or understandable of artificial intelligence is being actively studied. On the other hand, machine learning have been applied to the intelligence of self-organizing network (SON), but transparency in this application has been neglected, despite the critical decision-makings in the operation of mobile communication systems. We describes concepts of eXplainable machine learning (ML), along with research trends, major issues, and research directions. After summarizing the ML research on SON, research directions are analyzed for explainable ML required in intelligent SON of beyond 5G and 6G communication.

• Journal of The Korean Association of Information Education
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• v.9 no.3
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• pp.511-522
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• 2005

The rapid development of information & communication technology has changed the paradigm of education. Recently the area of education is introducing u-Learning, in which learning is possible at any time and in any place through personal information devices such as PDA, tablet PC and mobile phone terminals. Taking advantage of the mobility and individuality of personal information devices, u-Learning can provide learning customized to the characteristics of individual learners without the limitations of time and space and can be effective in situational learning and experiential learning. In order to identify the uses of PDA in teaching.learning and to develop a basic teachinglearning model using PDA, the present study applied PDA directly to classes and examined the effects. According to the result, most students were satisfied with classes utilizing PDA but problems were also found in connection, insufficient contents for PDA, the quality of screen, etc.

• Journal of The Korean Association of Information Education
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• v.16 no.2
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• pp.265-273
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• 2012

Current computer education is moving its focus from using oriented education to improving students' creativity and problem solving ability by computer science education. Robot programming education is becoming a major research issue of computer education in the context of creativity education. One of the mainstream ideas of prior research about robot programming is the effect of robot programming. Another is curriculum development of robot programming. But, the focus of current research is moving toward teaching methods of robot programming. The theme of this research is to use examples in robot programming. Example programs are considered the most useful type of material both by the students and the teachers. Example programs play a important role in learning to program. They work as templates, guidelines, and hints for learners when developing their own programs. In this study, I developed a example-based robot programming support system. Due to the trends of smart learning, I developed this system as a mobile web application.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.89-95
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• 2020

Recently, studies are being conducted to recognize a sketch image of a GUI (Graphical User Interface) based on a deep learning and to make it into a code implemented in an application. UI / UX designers can communicate with developers through storyboards when developing mobile applications. However, UI / UX designers can create different widgets for ambiguous widgets. In this paper, we propose an automatic UI detection method using symbol markers to improve the accuracy of DNN (Deep Neural Network) based UI identification. In order to evaluate the performance with or without the symbol markers, their accuracy is compared. In order to improve the accuracy according to of the symbol marker, the results are analyzed when the shape is a circle or a parenthesis. The use of symbol markers will reduce feedback between developer and designer, time and cost, and reduce sketch image UI false positives and improve accuracy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1111-1116
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• 2017

In this paper, we developed bio-signal based eye tracking system using electrooculogram (EOG) and electromyogram (EMG) which measured simultaneously from same electrodes. In this system, eye gazing position can be estimated using EOG signal and we can use EMG signal at the same time for additional command control interface. For EOG signal processing, PLA algorithms are applied to reduce processing complexity but still it can guarantee less than 0.2 seconds of reaction delay time. Also, we developed dual machine learning structure and it showed robust and enhanced tracking performances. Compare to conventional EOG based eye tracking system, developed system requires relatively light hardware system specification with only two skin contact electrodes on both sides of temples and it has advantages on application to mobile equipments or wearable devices. Developed system can provide a different UX for consumers and especially it would be helpful to disabled persons with application to orthotics for those of quadriplegia or communication tools for those of intellectual disabilities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.383-403
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• 2021

With the development of mobile edge computing (MEC), some late-model application technologies, such as self-driving, augmented reality (AR) and traffic perception, emerge as the times require. Nevertheless, the high-latency and low-reliability of the traditional cloud computing solutions are difficult to meet the requirement of growing smart cars (SCs) with computing-intensive applications. Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency. To solve this problem with effect, we propose a context-aware offloading strategy based on differential evolution algorithm (DE) by considering vehicle mobility, roadside units (RSUs) coverage, vehicle priority. On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. Simulation results demonstrate that the practical performance of the context-aware vehicular task offloading (CAVTO) optimization scheme could reduce the system delay significantly.