• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1998.06b
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• pp.99-104
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• 1998

Application sharing is the ability to use existing applications, such as Excel or MS-Word, during a group session without modification. In this paper, we present the design and implementation of an application sharing system, called ShareIt, which enable users to share arbitrary MS-Windows applications under the Win 3.1/95/NT and X window system, and evaluation of the system performance. To share an application, the image of the application window is captured and transmitted to other sites. With the use of the window capturing method, ShareIt allows any MS-Windows application to be shared regardless of not only the window systems but also the version-up of window systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.631-653
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• 2020

Sign language is a natural, visually oriented and non-verbal communication channel between people that facilitates communication through facial/bodily expressions, postures and a set of gestures. It is basically used for communication with people who are deaf or hard of hearing. In order to understand such communication quickly and accurately, the design of a successful sign language translation system is considered in this paper. The proposed system includes object detection and classification stages. Firstly, Single Shot Multi Box Detection (SSD) architecture is utilized for hand detection, then a deep learning structure based on the Inception v3 plus Support Vector Machine (SVM) that combines feature extraction and classification stages is proposed to constructively translate the detected hand gestures. A sign language fingerspelling dataset is used for the design of the proposed model. The obtained results and comparative analysis demonstrate the efficiency of using the proposed hybrid structure in sign language translation.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.277-292
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• 2018

This paper presents the development and implementation of an artificial intelligence (AI)-based deep excavation induced wall and ground displacements and wall support member forces prediction program (ANN-EXCAV). The program has been developed in a C# environment by using the well-known AI technique artificial neural network (ANN). Program used ANN to predict the induced displacement, groundwater drawdown and wall and support member forces parameters for deep excavation project and run the stability check by comparing predict values to the calculated allowable values. Generalised ANNs were trained to predict the said parameters through databases generated by numerical analysis for cases that represented real field conditions. A practical example to run the ANN-EXCAV is illustrated in this paper. Results indicate that the program efficiently performed the calculations with a considerable accuracy, so it can be handy and robust tool for preliminary design of wall and support members for deep excavation project.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.1-6
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• 2021

This study designed an artificial intelligence education program using localized public data as an educational method for improving computational thinking in elementary school students. Program design and development was carried out based on the results of pre-requisite analysis on elementary school students according to the ADDIE model. Based on localized public data, the program was organized to learn the principles of artificial intelligence by utilizing "Machine Learning for Kids" and "Scratch" and to solve problems and improve computational thinking skills through abstracting public data for purpose.Through subsequent research, it is necessary to put this education program into the field and verify the change in students' computational thinking as a result.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.688-701
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• 2020

In this study, a total of 68 domestic and international papers were selected from 1993 to August 2020 in order to examine the research trends related to artificial intelligence for the visually impaired. The papers were compared and analyzed by the number of papers published by year, research method, research topic, keyword analysis status, research type, and implementation method. As a result of the study, the number of papers during the study period seemed to increase steadily. But in the case of domestic research, It can be seen that it has become active since 2016. As for research methods, development research accounted for 89.7% of both domestic and foreign research. Keywords was in Visually Impaired, Deep Learning, and Assistive Device order in domestic research. And it was in Visually Impaired, Deep learning, Artificial intelligence order in foreign research. There was a difference in the frequency of words. Research type were Design, development and implementation both in domestic and foreign. Implementation method were in System 13.2%, Solution 7.4%, App. 4.4% order in domestic research, and it was in System 32.4%, App. 13.2%, Device 7.4% order in foreign research. As for the applied technology of the implementation method, were in YOLO 2.7%, TTS 2.1%, Tensorflow 2.1% order in domestic research, and it was used in CNN 8.0%, TTS 5.3%, MS-COCO 4.3% order in foreign research. The purpose of this study was to compare and analyze the trends of artificial intelligence-related research targeting the visually impaired, to immediately know the current status of domestic and foreign research, and to present the direction of artificial intelligence research for the visually impaired in the future.

• Convergence Security Journal
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• v.20 no.2
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• pp.123-135
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• 2020

Since AlphaGo's Match in 2016, there has been a growing calls for artificial intelligence applications in various industries, and research related to it has been actively conducted. The same is true in the military field, and since there has been no weapon system with artificial intelligence so far, effort to implement it are posing a challenge. Meanwhile, AlphaGo Zero, which beat AlphaGo, showed that artificial intelligence's self-training data-based approach can lead to better results than the knowledge-based approach by humans. Taking this point into consideration, this paper proposes to apply Reinforcement Learning, which is the basis of AlphaGo Zero, to the Shipboard Combat System or Combat Management System. This is how an artificial intelligence application to the Shipboard Combat System or Combat Management System that allows the optimal tactical assist with a constant win rate to be recommended to the user, that is, the commanding officer and operation personnel. To this end, the definition of the combat performance of the system, the design plan for the Shipboard Combat System, the mapping with the real system, and the training system are presented to smoothly apply the current operations.

• KIEAE Journal
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• v.3 no.2
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• pp.59-66
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• 2003

To be the design method supporting aesthetic ability of human, CAAD system should essentially recognize architectural form in the same way of human. In this study, visual perception process of human was analyzed to search proper computational method performing similar step of perception of it. Through the analysis of visual perception, vision was separated to low-level vision and high-level vision. Edge detection and neural network were selected to model after low-level vision and high-level vision. The 24 images of building, tree and landscape were processed by edge detection and trained by neural network. And 24 new images were used to test trained network. The test shows that trained network gives right perception result toward each images with low error rate. This study is on the meaning of artificial intelligence in design process rather than on the design automation strategy through artificial intelligence.

• The Journal of Industrial Distribution & Business
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• v.11 no.6
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• pp.41-53
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• 2020

Purpose: The purpose of this study is to review the previous studies on the characteristics of the image search service provided by using artificial intelligence, the social impact characteristics, and the moderating effect of perceived anthropomorphism, and conduct empirical analysis to identify the constituent factors affecting purchase intention. To clarify. Through this, I tried to present theoretical and practical implications. Research design, data, and methodology: Research design was that characteristics of image search service (ubiquity and information quality) and social impact characteristics (subjective norms, electronic word of mouth marketing) are affected by mediation of satisfaction and flow, therefore, control of perceived anthropomorphism have an effect on purchase intention to increase. For analysis, research conducted literature review, and developed questionnaires, so that EM firm which is a specialized research institute has collected data. This was conducted on 410 people between the 20s and 50s who have mobile shopping experiences. SPSS Statistics 23 and AMOS 23 had been used to perform necessary analysis such as exploratory factor analysis, reliability analysis, feasibility analysis, and structural equation modeling based on this data. Results: first, ubiquity, information quality and subjective norms were found to have a positive effect on purchase intention through satisfaction and flow parameters. Second, satisfaction and flow were found to have a mediating effect between ubiquity, information quality, and subjective norms and purchase intentions. However, there was no mediating effect between eWOM information and purchase intention. Third, perceived anthropomorphism was found to have a moderating effect between information quality and satisfaction, and it was found that there was no moderating effect on the relationship between information quality and flow. Conclusions: The information quality of image search services using artificial intelligence has a positive effect on satisfaction, and it has been found that there is a positive moderate effect of perceived anthropomorphism in this relationship, which may be an academic contribution to the distribution science utilizing artificial intelligence. Therefore, it is possible to propose a distribution strategy that improves purchase intention by utilizing image search service and anthropomorphism in practical business and providing a more enjoyable immersive experience to customers.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.927-934
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• 2021

AI(Artificial intelligence) is gradually taking up a large part of our lives, and the pace of AI development is accelerating. It is called ACT that develop students' computational thinking in the way artificial intelligence learns. Among ACTs, pattern recognition is an essential factor in efficiently solving problems. Pattern analysis is part of the pattern recognition process. In fact, Netflix's personalized movie recommendation service and what it named Covid-19 after repeated symptoms are all the results of pattern analysis. While the importance of ACT, including pattern recognition, is highlighted, software education for kindergarten and elementary school lower grades is much insufficient compared to foreign countries. Therefore, this study aims to design and develop textbooks for the development of artificial intelligence-based computational thinking through pattern analysis for kindergarten students.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.229-235
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• 2021

Artificial intelligence technology is influencing across all areas as technology advances and social needs change. Therefore, Korean universities have actively developed and operated classes related to artificial intelligence, and have emphasized the importance of artificial intelligence not only in major education but also in liberal arts education. However, there is a lack of research on the development of educational methods and educational programs because artificial intelligence education in liberal arts is in its early stages. SSI is an education that can apply social and ethical problems related to science to open problems that can creatively and reasonably present solutions. SSI can be applied to make AI education more effective. In this study, an artificial intelligence liberal arts curriculum applied SSI was developed with three purposes: First, it is designed is designed so that students subject to education can access it by considering its characteristics as actors of the intelligent information society. Second, it is designed so that students can experience artificial intelligence programs themselves and deal with science technology and social relevance in depth, focusing on various examples of real life. Third, it is designed and approached so that students can participate and cooperate for the purpose of solving common problems to develop cooperative problem-solving skills.