Journal of the Korea Institute of Information Security & Cryptology
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v.24
no.5
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pp.795-807
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2014
Vehicular Ad hoc Network (VANET) has gone through a rich amount of research and currently is making its way towards the deployment. However, surprisingly it evolved to rather more applications and services-rich breed referred to as VANET-based clouds due to the advancements in the automobile and communication technologies. Security and privacy have always been the challenges for the think tanks to deploy this technology on mass scale. It is even worse that some security issues are orthogonally related to each other such as privacy, revocation and route tracing. In this paper, we aim at a specific VANET-based clouds framework proposed by Hussain et al. namely VANET using Clouds (VuC) where VANET and cloud infrastructure cooperate with each other in order to provide VANET users (more precisely subscribers) with services. We specifically target the aforementioned conflicted privacy, route tracing, and revocation problem in VANET-based clouds environment. We propose a multiple pseudonymous approach for privacy reasons and leverage the beacons stored in the cloud infrastructure for both route tracing and revocation. In the proposed scheme, revocation authorities after colluding, can trace the path taken by the target node for a specified timespan and can also revoke the identity if needed. Our proposed scheme is secure, conditional privacy preserved, and is computationally less expensive than the previously proposed schemes.
Korean government has taken positive policies, including making "An Basic Plan on the Conservation and Activation of the Royal Tombs of the Joseon Dynasty, UNESCO World Heritage", since 40 royal tombs of the Joseon Dynasty were inscribed as UNESCO World Heritage in 2009. However, projects utilizing the royal tombs of the Joseon Dynasty are in the beginning step and very few has been researched on those projects academically. This study analyzed total 311 projects utilizing the royal tombs of the Joseon Dynasty, which have been made by the Cultural Heritage Administration of Korea from 2009 to 2014, through the literature review and content analysis methodology. An analysis frame consists of educational, touristic, compound and industrial activation on the basis of the utilization types made by the Cultural Heritage Administration of Korea. Most projects utilizing the royal tombs of the Joseon Dynasty are in the very beginning step in terms of educational and touristic utilization. No project utilizing the royal tombs of the Joseon Dynasty in terms of industrial utilization is found. Those projects are almost similar without distinctive characteristics peculiar to each royal tombs. Most projects have been taken on the short term level and the budget size for those is not enough. Projects are mostly focused on the on-site of royal tombs with little paying attention to converging projects utilizing digital and on line techniques. Some suggestions are the followings: increase of the budget on projects utilizing the royal tombs of the Joseon Dynasty, development of content peculiar to each tomb, development of industrial projects, development of converging projects utilizing digital and on line techniques, establishment of new medium and long term plans for utilization of the royal tombs of the Joseon Dynasty and so on.
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.6
no.5
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pp.367-377
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2016
The purpose of the projects for strengthening the Service Business Competitiveness, which had been sponsored by the Ministry of Trade, Industry and Energy, and managed by the NIPA, is to support for combining the whole business process of the SMEs with the business model considering the scientific aspects of the services, to enhance the productivity of them and to add the values of their activities. 5 organizations are selected in 2014, and 4 in 2015 as leading organizations for these projects. This study analyzed the efficiency of these projects using DEA. Throughout the analysis of the prior researches, this study used the amount of government-sponsored money as the input variable, and the number of new customer business, the sales revenue, and the number of new employment as the output variables. And the result of this analysis showed that the decision making unit 12, 15, and 21 was efficient. And from this study, we found out two more performance indicators such as, the number of new employment and the amount of sales revenue, besides the number of new customer businesses.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.1
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pp.333-337
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2021
Companion animals are physically, mentally, and socially beneficial to humans, giving us great comfort in living in the Corona19 (COVID-19) era. It is also an era of the Fourth Industrial Revolution, featuring the convergence of information and communication technology. Korea, which is facing a super-aged society, has the highest suicide rate among OECD countries, and companion animals that are effective in emotional stability can be the answer. This study is about companion animals that are effective in stabilizing the emotions of the elderly, one of the major problems in the Republic of Korea, which is about to solve in a super-aged society with more than 20 percent of the elderly aged 65 or older, needs to solve. The impact of knowledge of raising companion animals on the satisfaction level of the elderly was investigated through the management and awareness of infectious diseases. Although the level of care of companion animals had a very significant (p<0.001) effect on the satisfaction of the companion animals, the recognition of infectious diseases has no statistical significance (p>0.05). Raising companion animals with knowledge of rearing increases the satisfaction level and can lead to a happier life. While personal learning is important, it is also believed that supporting education will be necessary as a policy consideration.
With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.
Recently, the necessity of safety diagnosis of electrical devices has been increasing as the fire caused by electric devices has increased rapidly. This study is concerned with the safety diagnosis of electric equipment using intelligent Fuzzy technology. It is used as a diagnostic input for the multiple electrical safety factors such as the use current, cumulative use time, deterioration and arc characteristics inherent to the equipment. In order to extract these information in real time, a device composed of various sensor circuits, DSP signal processing, and communication circuit is implemented. The fuzzy logic algorithm using the Gaussian function for each information is designed and compiled to be implemented on a small DSP board. The fuzzy logic receives the four diagnostic information, deduces it by the fuzzy engine, and outputs the overall safety status of the device as a 100-step analog fuzzy value familiar to human sensibility. By experiments of a device that combines hardware and fuzzy algorithm implemented in this study, it is verified that it can be implemented in a small DSP board with human-friendly fuzzy value, diagnosing real-time safety conditions during operation of electric equipment. In the future, we expect to be able to study more intelligent diagnostic systems based on artificial intelligent with AI dedicated Micom.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.14
no.4
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pp.101-111
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2019
In distance learning, quality of service is an important part of improving customer satisfaction and customer loyalty. However, in verifying the effectiveness of remote education service quality, it has been researched based on fragmentary effects on remote education service quality, and the effect study on the specific target is insufficient. In this study, the effects of remote education service factors on customer satisfaction and customer loyalty were analyzed in the previous study and among job seekers. The survey was conducted from March 2019 and 258 samples of job seekers who experienced remote education were used for empirical analysis. As a result of the analysis, typology, problem solving, interaction, information serviceability, and convenience had a positive effect on customer satisfaction, and satisfaction had a significant influence on customer loyalty. In addition, it was analyzed that characterization, problem-solving, interaction, information serviceability, convenience and customer loyalty were affected in the verification of the mediated effects of satisfaction. In response, the implications of this study were derived from practical research on customer satisfaction and loyalty of educational companies related to eduTech, where education and ICT (Information Communication Technology) were integrated during the 4th Industrial Revolution, which suggested that the quality of a company's remote education service affected customer satisfaction and customer loyalty to entrepreneurs and marketers in the education company's start-up and marketing process. Further, further research will be needed in other areas as well as in the areas of employment education to verify the importance of service quality and assess the various effects.
KIPS Transactions on Software and Data Engineering
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v.8
no.6
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pp.243-250
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2019
Because of a moving UAV has a lot of potential/kinetic energy, if the UAV falls to the ground, it may have a lot of impact. Because this can lead to human casualities, in this paper, the population density area on the UAV flight path is defined as a dangerous area. The conventional UAV path flight was a passive form in which a UAV moved in accordance with a path preset by a user before the flight. Some UAVs include safety features such as a obstacle avoidance system during flight. Still, it is difficult to respond to changes in the real-time flight environment. Using public Big Data for UAV path flight can improve response to real-time flight environment changes by enabling detection of dangerous areas and avoidance of the areas. Therefore, in this paper, we propose a method to detect and avoid dangerous areas for UAVs by utilizing the Big Data collected in real-time. If the routh is designated according to the destination by the proposed method, the dangerous area is determined in real-time and the flight is made to the optimal bypass path. In further research, we will study ways to increase the quality satisfaction of the images acquired by flying under the avoidance flight plan.
Recently, youth unemployment, especially the unemployment problem of university graduates, has emerged as a social problem. Unemployment of university graduates is both a pan-national issue and a university-level issue, and each university is making many efforts to increase the employment rate of graduates. In this study, we present a model that predicts employment availability of D-university graduates by utilizing Machine Learning. The variables used were analyzed using up to 138 personal information, admission information, bachelor's information, etc., but in order to reflect them in the future curriculum, only the data after admission works effectively, so by department / student. The proposal was limited to the recommended ability to improve the separate employment rate. In other words, since admission grades are indicators that cannot be improved due to individual efforts after enrollment, they were used to improve the degree of prediction of employment rate. In this research, we implemented a employment prediction model through analysis of the core ability of D-University, which reflects the university's philosophy, goals, human resources awards, etc., and machined the impact of the introduction of a new core ability prediction model on actual employment. Use learning to evaluate. Carried out. It is significant to establish a basis for improving the employment rate by applying the results of future research to the establishment of curriculums by department and guidance for student careers.
Researchers are making contradictory claims through the concept of superstars and long tails about how the development of IT technology affects demand distribution. Unlike previous studies that focused on changes in demand from a macro point of view, this study explored whether the relationship between a company's marketing activities and consumer response differs depending on the product location (i.e., superstar vs. long tail) from a micro point of view. Based on the marketing mix framework, hypotheses were developed based on the relevant literature. In the case of empirical analysis, 2,835 daily data from 63 Korean films were tested using the quantile regression method. As a result of the analysis, it was found that the influence of marketing mix factors on sales varies depending on the location of the product. Specifically, the appeal breadth of the film and the effect of owned media are enhanced in superstar products, and the effect of acquisition media in long-tail products is enhanced and the negative effects of competition are mitigated. Unlike previous studies that focused on macroscopic changes in demand distribution, this study suggested marketing activities suitable for practitioners through microscopic analysis.
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