• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.84-92
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• 2016

Since the mankind started its space mission, the number of artificial space objects has been increasing exponentially. It contains not just the space machines which are in use but the machines which are out of order. Meantime, those dead machines are being a serious danger, a real threat to human's lives and property because of it could re-enter into the earth's atmosphere and fall to the ground causing mega-disaster. As the number of space activities gets growing so far, the re-entry of the space objects will be a lot more happened in the future. Therefore, not just natural space object like asteroids but the artificial space object like artificial satellite and space station can cause the disaster by falling to the ground. To protect our nation and our property, the government has set up the space disaster management center in Korea astronomy and Space science Institute. In this study, we surveyed public's recognition of the space object's re-entry situation and analyzed it to contribute building national space disaster management policy.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.191-202
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• 2023

This study aims to propose a framework for evaluating the impact of artificial intelligence (AI) services, based on the concept of AI service impact. It also suggests a model for evaluating this impact and identifies relevant factors and measurement approaches for each item of the model. The study classifies the impact of AI services into five categories: ethics, safety and reliability, compliance, user rights, and environmental friendliness. It discusses these five categories from a broad perspective and provides 21 detailed factors for evaluating each category. In terms of ethics, the study introduces three additional factors-accessibility, openness, and fairness-to the ten items initially developed by KISDI. In the safety and reliability category, the study excludes factors such as dependability, policy, compliance, and awareness improvement as they can be better addressed from a technical perspective. The compliance category includes factors such as human rights protection, privacy protection, non-infringement, publicness, accountability, safety, transparency, policy compliance, and explainability.For the user rights category, the study excludes factors such as publicness, data management, policy compliance, awareness improvement, recoverability, openness, and accuracy. The environmental friendliness category encompasses diversity, publicness, dependability, transparency, awareness improvement, recoverability, and openness.This study lays the foundation for further related research and contributes to the establishment of relevant policies by establishing a model for evaluating the impact of AI services. Future research is required to assess the validity of the developed indicators and provide specific evaluation items for practical use, based on expert evaluations.

• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.1
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• pp.13-22
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• 2024

Purpose: The purpose of this study is to investigate impact of smart city awareness on citizen satisfaction and to measure various factors influencing smart city competitiveness that were rarely addressed in previous studies. For the impacts on the competitiveness of smart cities, this study explored the effects of data-driven service, economic impact, social trust through sharing, environmental protection, and sustainable growth. Research design, data and methodology: To collect data, this study employed an online survey conducted by a reputable research organization. Data analysis involved the use of factor analysis, ANOVA, and regression analysis. Results: This study identified key aspects important for enhancing citizen satisfaction. Furthermore, this research unveiled the significant impacts of data-driven service, economic impact, social trust through sharing, environmental protection, and sustainable growth on the competitiveness of smart cities. Conclusions: The results yield valuable managerial and policy implications. The study suggests that enhancing citizen satisfaction through improved awareness of the smart city is crucial for effective city marketing management. Additionally, the results highlight special aspects necessary to improve smart city competitiveness, including the implementation of promotional policies supported by the government, promoting global competitiveness for domestic companies, and fostering citizen participation for effective city marketing management.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.1
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• pp.90-98
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• 2022

On February 12, 2019, the U.S. Department of Defense newly established and announced the "Defense AI Strategy" to accelerate the use of artificial intelligence (AI) technology for military purposes. As China and Russia invested heavily in AI for military purposes, the U.S. was concerned that it could eventually lose its advantage in AI technology to China and Russia. In response, China and Russia, which are hostile countries, and especially China, are speeding up the development of new military theories related to the overall construction and operation of the Chinese military based on AI. With the rapid development of AI technology, major advanced countries such as the U.S. and China are actively researching the application of AI technology, but most existing studies do not address the special topic of defense. Fortunately, the "Future Defense 2030 Technology Strategy" classified AI technology fields from a defense perspective and analyzed advanced overseas cases to present a roadmap in detail, but it has limitations in comparing private technology-oriented benchmarking and AI technology's maturity level. Therefore, this study tried to overcome the limitations of the "Future Defense 2030 Technology Strategy" by comparing and analyzing Chinese and U.S. military research cases and evaluating the maturity level of military use of AI technology, not AI technology itself.

• Journal of Information Technology Services
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• v.13 no.4
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• pp.1-17
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• 2014

Domestic and international energy and eco-friendly companies take advantage of social media for image enhancement and product promotion. However, there were no in-depth empirical analysis to verify specific effectiveness of social media use in these sectors. The purpose of this study is to reveal the key factors that are considered to use social media effectively for energy and eco-friendly companies. For this purpose, we regarded the effectiveness of social media as Post Awareness and Word of Mouth. Characteristics of social media as a medium were measured separately, media richness and media genre, as independent variables of social media effectiveness. We investigated 413 posts in Facebook brand page of energy and eco-friendly companies and conducted a content analysis. As a result, post awareness of users was greater when post has richer media such as video. For media genre, word of mouth appeared to be greater when the posts provide information.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.75-86
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• 2022

The existing image quality assessment (IQA) datasets have a small number of samples. Some methods based on transfer learning or data augmentation cannot make good use of image quality-related features. A No Reference (NR)-IQA method based on multi-task training and quality awareness is proposed. First, single or multiple distortion types and levels are imposed on the original image, and different strategies are used to augment different types of distortion datasets. With the idea of weak supervision, we use the Full Reference (FR)-IQA methods to obtain the pseudo-score label of the generated image. Then, we combine the classification information of the distortion type, level, and the information of the image quality score. The ResNet50 network is trained in the pre-train stage on the augmented dataset to obtain more quality-aware pre-training weights. Finally, the fine-tuning stage training is performed on the target IQA dataset using the quality-aware weights to predicate the final prediction score. Various experiments designed on the synthetic distortions and authentic distortions datasets (LIVE, CSIQ, TID2013, LIVEC, KonIQ-10K) prove that the proposed method can utilize the image quality-related features better than the method using only single-task training. The extracted quality-aware features improve the accuracy of the model.

• Journal of information and communication convergence engineering
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• v.5 no.2
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• pp.104-108
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• 2007

Ad hoc networks are a type of mobile network that function without any fixed infrastructure. One of the weaknesses of ad hoc network is that a route used between a source and a destination is to break during communication. To solve this problem, one approach consists of selecting routes whose nodes have the most stable link cost. This paper proposes a method for improving the low power distributed MAC. This method is based on the context awareness of the each nodes energy in clustering. We propose to select a new scheme to optimize energy conserving between the clustering nodes in MANET. And this architecture scheme would use context-aware considering the energy related information such as energy, RF strength, relative distances between each node in mobile ad hoc networks. The proposed networks scheme could get better improve the awareness for data to achieve and performance on their clustering establishment and messages transmission. Also, by using the context aware computing, according to the condition and the rules defined, the sensor nodes could adjust their behaviors correspondingly to improve the network routing.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.3
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• pp.201-233
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• 2016

The purpose of this study is to improve awareness of cultural diversity and respect different culture, value and lifestyle by providing children from multi cultural family and children from non multi cultural family who are from third to sixth year in elementary school with education on cultural diversity. This study developed cultural diversity education program in public library and applied it to analyze a difference in awareness of cultural diversity education program, a difference in awareness of cultural diversity education program between experimental group and comparative group, library service, use of library service and influence of expansion of service. As a results, it was found that cultural diversity education program helped children understand, accept, consider and respect cultural diversity better.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.911-913
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• 2013

The user's context awareness is important to the reliability of sensors data. The sensor data is constantly change to external temp, internal& external environment and vibration. This noise environment is affecting that the data collected information from sensors. Of course this method of digital filter and inference algorithm specifically request for the use of ripple noise and action inference. In this paper, experiment was a comparison of the KF(Kalman Filter) and WMAF(Weight Moving Average Filter) for noise decrease and distortion prevention according to user behavior. And, we compared the EWDF(Extended Weight Dual Filter) with several filer. In an experiment, in contrast to other filter, the proposed filter is robust in a noise-environment.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.3
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• pp.76-85
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• 2022

Work situational awareness test (WSAT) has been utilized to estimate the fatigue risk of workers who worked with time pressure or latent accident risks at their work environment. Thus researchers decided to use WSAT to estimate fatigue risk of cabin crews of an airline in Korea and to analyze empirically how such risk might have an effect on cabin crew's safety behavior. This was because there had not been enough research on accessing cabin crews' fatigue and analyzing its risk for the flight safety. In addition, the mediation effect of cabin crew's planning was also analyzed through Sobel-test by researchers among external factors such as lack of concentration, attention deficit, distraction and safety behavior. According to empirical analysis, it was found attention deficit and distraction of cabin crews due to fatigue during the flight had a significant negative effect on their planning. Planning was also proven to have mediation effect to cabin crew's safety behavior.