• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.135-155
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• 2018

The purpose of this study is to analyze the difference of interpretation level and intention to use message framing when autonomous vehicle, which is emerging as the product of 4th industrial revolution, is used as taxi, Interpretation level refers to the interpretation of a product or service, assuming that it will happen in the near future or in the distant future. Message framing refers to the formation of positive or negative expressions or messages at the extremes of benefits and losses. In other words, previous studies interpret the value of a product or service differently according to these two concepts. The purpose of this study is to investigate whether there are differences in intention to use when two concepts are applied when an autonomous vehicle is launched as a taxi. The results are summarized as follows: First, the message format explaining the gain and why should be used when using the autonomous taxi in the message framing configuration, and the loss and how when the autonomous taxi is not used. Messages were constructed and compared. The two message framing differed (t = 3.063), and the message type describing the benefits and reasons showed a higher intention to use. In addition, the results according to interpretation level are summarized as follows. There was a difference in intentions to use when assuming that it would occur in the near future and in the near future with respect to the gain and loss, Respectively. In summary, in order to increase the intention of using autonomous taxis, it is concluded that messages should be given to people assuming positive messages (Gain) and what can happen in the distant future. In addition, this study will be able to utilize the research method in studying intention to use new technology. However, this study has the following limitations. First, it assumes message framing and time without user experience of autonomous taxi. This will be different from the actual experience of using an autonomous taxi in the future. Second, self-driving cars should technical progress is continuing, but laws and institutions must be established in order to commercialize it and build the infrastructure to operate the autonomous car. Considering this fact, the results of this study can not reflect a more realistic aspect. However, there is a practical limit to search for users with sufficient experience in new technologies such as autonomous vehicles. In fact, although the autonomous car to take advantage of the public transportation by taxi is now ready for the road infrastructure, and technical and legal public may not be willing to choose to not have enough knowledge to use the Autonomous cab. Therefore, the main purpose of this study is that by assuming that autonomous cars will be commercialized by taxi you can do to take advantage of the autonomous car, it is necessary to frame the message, why can most effectively be used to find how to deliver. In addition, the research methodology should be improved and future research should be done as follows. First, most students responded in this study. It is also true that it is difficult to generalize the hypotheses to be tested in this study. Therefore, in future studies, it would be reasonable to investigate the population of various distribution considering the age, area, occupation, education level, etc. Where autonomous taxi can be used rather than those who can drive. Second, it is desirable to construct various message framing of the questionnaire, but it is necessary to learn various message framing in advance and to prevent errors in response to the next message framing. Therefore, it is desirable to measure the message framing with a certain amount of time when the questionnaire is designed.

• Journal of Korea Multimedia Society
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• v.23 no.9
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• pp.1219-1228
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• 2020

In this study, the factors affecting the acceptance intention for level 4-5 of autonomous vehicles were investigated by applying TAM(Technology Acceptance Model). To this end, 332 ordinary persons interested in autonomous vehicle and experienced in driving car were analyzed by using SEM(Structural Equation Modeling). The results showed that self-efficacy and personal innovation had a positive effect on perceived usefulness. On the other hand personal innovation has been shown to have a negative effect on perceived usefulness. Perceived ease of use has a positive effect on perceived usefulness, perceived ease of use and perceived usefulness has a positive effect on acceptance intention. Safety and Privacy has been shown to have a positive effect on trust, trust has a positive effect on acceptance intention. Lastly, autonomous vehicles have a higher impact on their 20s and 30s. The result of this study is expected to be a very useful basic research for the development of target autonomous vehicles, the selection of targets, the direction of corporate marketing strategies, and the preparation of government policies.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.979-989
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• 2016

Traversable region detection is an essential step for advanced driver assistance systems and self-driving car systems, and it has been conducted by detecting lanes from input images. The performance can be unreliable, however, when the light condition is poor or there exist no lanes on the roads. To solve this problem, this paper proposes an algorithm which utilizes the information about the number of lanes and texture analysis. The proposed algorithm first specifies road region candidates by utilizing the number of lanes information. Among road region candidates, the road region is determined as the region in which texture is homogeneous and texture discontinuities occur around its boundaries. Traversable region is finally detected by dividing the estimated road region with the number of lanes information. This paper combines the proposed algorithm with a lane detection-based method to construct a system, and simulation results show that the system detects traversable region even on the road with poor light conditions or no lanes.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.31-39
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• 2021

This study collected 1,870 English news articles related to research and development of autonomous vehicles in order to identify various issues emerging in the research and development process of autonomous vehicles at home and abroad, and conducted topic modeling after data pre-processing. As a result of topic modeling, we extracted 20 topics, and we performed naming operations for topics and interpreted their meanings. A logical model for autonomous vehicle research and development projects was presented in response to the R&D process of input, activity, output, and outcome of derived topics. The analysis results of this study will be used as basic data to accurately determine the progress of domestic and foreign self-driving car research and development projects and prepare for the rapidly changing technology development.

• Korean Journal of Artificial Intelligence
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• v.8 no.2
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• pp.11-16
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• 2020

Among the innovative companies leading the era of the 4th industrial revolution, the world's largest Internet company is Google. Google has grown by providing convenient services such as Internet search, Android smartphone operating system, and video. Now, Google is leading the global IT industry by continuing to develop in various new business fields based on open service platforms, artificial intelligence, and big data. In this study, an exploratory discussion was conducted on Google's success factors and future directions. The purpose of the research is to understand the development process of the IT field from the successfactors of Google and to analyze the development direction of the future IT industry. Google's success factors were its open platform policy and successful acquisitions of external companies. In fact, most of the services Google offers come from companies that have acquired and acquired them. In addition, there was a corporate culture that values and supportsthe spirit of challenge and autonomy of members who are not afraid of failure. Based on this study's review of Google's direction analysis, the follow-up study will infer the direction of the IT industry in depth and look at the future technologies that IT majors need to prepare.

• Journal of Korea Multimedia Society
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• v.24 no.7
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• pp.913-921
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• 2021

After arranging the general usability evaluation criteria of existing VUI researchers, this study verified how appropriate these criteria are for AI VUI specialized in navigation and the priority of their suitability. The VUI used in this study was analyzed through a survey from a total of 195 Chinese users after analyzing the navigation VUI used in China. As a result of the analysis, the usability evaluation criteria of the navigation VUI were extracted from three sub-factors of 'task accuracy', 'function satisfaction', and 'information reliability' in verifying conformance with general VUI evaluation criteria. With the recent advent of self-driving cars, safety and response speed are becoming very important, so Chinese users also ranked responsiveness as the top priority in VUI design, and the importance was also found to be high. Also, both men and women have the highest reactivity and the lowest multiplicity. VUI requires a convenient and natural interface to understand the intention between two objects through usability evaluation and verification in order to have effective interaction between humans and machines.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.102-116
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• 2021

For the safe operation of autonomous vehicles, the representative technology of the 4^th industrial revolution era, a combination of various technologies such as sensor technology, software technology and car technology is required. An autonomous vehicle is a vehicle that recognizes current location and situation by using the various sensors, and makes its own decisions without depending on the driver. Perfect recognition technology is required for fully autonomous driving. Since the precise road maps provide various road information including lanes, stop lines, traffic lights and crosswalks, it is possible to minimize the cognitive errors that occur in autonomous vehicles by using the precise road maps with location information of the road facilities. In this study, the definition, necessity and technical trends of the precise road map have been analyzed, and the HD(High Definition) map prototype based on the web GIS has been built in the autonomous driving-specialized areas of Daegu Metropolitan City(Suseong Medical District, about 24km), the Happy City of Sejong Special Self-Governing City(about 33km), and the FMTC(Future Mobility Technical Center) PG(Proving Ground) of Seoul National University Siheung Campus using the MMS(Mobile Mapping System) surveying results given by the National Geographic Information Institute. In future research, the built-in precise road map service will be installed in the autonomous vehicles and control systems to verify the real-time locations and its location correction algorithm.

• Journal of Radiation Industry
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• v.9 no.3
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• pp.153-159
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• 2015

Reliability of printed circuit board (PCB), which is based on high integrated circuit technology, is having been important because of development of electric and self-driving car. In order to answer these demand, automated X-ray inspection (AXI) is best solution for PCB non-destructive test. PCB is consist of plastic, copper, and, lead, which have low to high Z-number materials. By using dual energy X-ray imaging, these materials can be inspected accurately and efficiently. Dual energy X-ray imaging, that have the advantage of separating materials, however, need some solution such as energy separation method and enhancing efficiency because PCB has materials that has wide range of Z-number. In this work, we found out several things by analysis of X-ray energy spectrum. Separating between lead and combination of plastic and copper is only possible with energy range not dose. On the other hand, separating between plastic and copper is only with dose not energy range. Moreover the copper filter of high energy part of dual X-ray imaging and 50 kVp of low energy part of dual X-ray imaging is best for efficiency.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.673-681
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• 2021

This study is a case study of artificial intelligence education subjects in the graduate school of education. The main educational contents consisted of understanding and practice of machine learning, data analysis, actual artificial intelligence using Entries, artificial intelligence and physical computing. As a result of the survey on the educational effect after the application of the curriculum, it was found that the students preferred the use of the Entry AI block and the use of the Blacksmith board as a physical computing tool as the priority applied to the elementary education field. In addition, the data analysis area is effective in linking math data and graph education. As a physical computing tool, Husky Lens is useful for scalability by using image processing functions for self-driving car maker education. Suggestions for desirable AI education include training courses by level and reinforcement of data collection and analysis education.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.401-409
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• 2021

This study is a case study of artificial intelligence education subjects in the graduate school of education. The main educational contents consisted of understanding and practice of machine learning, data analysis, actual artificial intelligence using Entries, artificial intelligence and physical computing. As a result of the survey on the educational effect after the application of the curriculum, it was found that the students preferred the use of the Entry AI block and the use of the Blacksmith board as a physical computing tool as the priority applied to the elementary education field. In addition, the data analysis area is effective in linking math data and graph education. As a physical computing tool, Husky Lens is useful for scalability by using image processing functions for self-driving car maker education. Suggestions for desirable AI education include training courses by level and reinforcement of data collection and analysis education.