• Journal of the Korea Society of Computer and Information
• /
• v.18 no.12
• /
• pp.123-138
• /
• 2013

This paper was to figure out why online wine purchasing is not activated despite of the many advantages of having online transactions and to fine key determinants of online wine purchasing intention. Thus, the purpose of this study was to identify the determinants of online wine purchase intention, and examines the relationships between the determinants and online wine purchase intention. Data was collected from those who have experienced in using online wine store to purchase wine, and data was used to test the proposed research model. The findings showed that perceived usefulness and social influence(subjective norm, image) were key determinants of online wine site trust, but they were not related to online wine site trust. It also was found that perceived usefulness, perceived ease of use and subjective norm were positively and significantly related to online wine purchase intention whereas it had no relationship with image. In addition, online wine site trust was shown to influence on online wine purchase intention. Finally, the mediating effects were found in the relationships between perceived usefulness, subjective norm, and online wine purchase intention. Based on the results of the study, implications for future research are drawn.

• Korean Journal of Remote Sensing
• /
• v.37 no.6_1
• /
• pp.1573-1587
• /
• 2021

A Drone image is an ultra-high-resolution image that is several or tens of times higher in spatial resolution than a satellite or aerial image. Therefore, drone image-based remote sensing is different from traditional remote sensing in terms of the level of object to be extracted from the image and the amount of data to be processed. In addition, the optimal scale and size of data used for model training is different depending on the characteristics of the applied deep learning model. However, moststudies do not consider the size of the object to be found in the image, the spatial resolution of the image that reflects the scale, and in many cases, the data specification used in the model is applied as it is before. In this study, the effect ofspatial resolution and image size of drone image on the accuracy and training time of the semantic segmentation deep learning model of six wintering vegetables was quantitatively analyzed through experiments. As a result of the experiment, it was found that the average accuracy of dividing six wintering vegetablesincreases asthe spatial resolution increases, but the increase rate and convergence section are different for each crop, and there is a big difference in accuracy and time depending on the size of the image at the same resolution. In particular, it wasfound that the optimal resolution and image size were different from each crop. The research results can be utilized as data for getting the efficiency of drone images acquisition and production of training data when developing a winter vegetable segmentation model using drone images.

• Journal of vocational education research
• /
• v.37 no.3
• /
• pp.25-45
• /
• 2018

This study investigates the relationship between the social supports & the transformational leadership from career mentors and high school students' GRIT & career preparation behavior. The purpose of this study was to provide baseline data for Development of Career-program so that they can provide effective career advice to students, through analyzing preceding researches that highlight the impact from career mentors on students' GRIT and career preparation behavior. For this study, the questionnaires for students' GRIT & career preparation behavior were completed by 257 sophomore high school students participating in the career mentor program. also, This data was analyzed to find student's perception of social supports and transformational leadership from career mentors. Correlation analysis was used to investigate the relationship among four variable(GRIT, career preparation behavior, career mentor's social supports, career mentor's transformational leadership) and regression analysis was used to find the influence from the career mentor's social supports and career mentor's transformational leadership on student's GRIT & career preparation behavior. The result showed the change of students' GRIT & career preparation behavior have risen on average. Also, it showed the change of students' career preparation behavior is influenced by career mentor's emotional support, informational support and individualized consideration. Lastly, the change of students' GRIT is influenced by career mentor's emotional support, appraisal support and individualized consideration. This result was able to identify the relationship and influence of career mentor who were limited to social support by their parents and teachers. And, it suggests that the appropriate social supports need to be provided to students by understanding the type of social supports that meet student's expectations.

• Journal of vocational education research
• /
• v.35 no.6
• /
• pp.85-112
• /
• 2016

This study aims to identify the cooperative relations among researchers and their network structures based on the academic papers published in the field of lifelong vocational education and training from 2000 to 2015. Authors in three representative journals, 'Journal of Lifelong Education', 'Journal of Vocational Education Research', and 'Korea Research Institute for Vocational Education & Training,' during the periods, were selected and co-authorship network analysis was applied using NetMiner 4.0 in order to find the social relation among researchers and their academic influences. The results showed that the research productivity in the field of lifelong vocational education and training forms a shape of the power function where there exist components called, 'detailed research groups.' This network structure represents characteristics of a small world. In addition, the centrality analysis suggest authors with high centrality serve as co-authors who play as a central role on the network and exchange information with other researchers, while those with high betweenness centrality serve as a channel where they transfer knowledge and information among research groups. Increasing member of co-authorship has positively contributed to the opportunity and development of cooperative research among researchers in the field of lifelong vocational education and training. However it is recommended co-authorship be formed more heterogeneously instead of a few researches centrally dominate co-authorship. Various researchers should continually conduct research for good research performances.

• KIPS Transactions on Computer and Communication Systems
• /
• v.8 no.1
• /
• pp.17-28
• /
• 2019

In the financial investment management strategy, the distributed investment selecting and combining various financial assets is called portfolio management theory. In recent years, the blockchain based financial assets, such as cryptocurrencies, have been traded on several well-known exchanges, and an efficient portfolio management approach is required in order for investors to steadily raise their return on investment in cryptocurrencies. On the other hand, deep learning has shown remarkable results in various fields, and research on application of deep reinforcement learning algorithm to portfolio management has begun. In this paper, we propose an efficient financial portfolio investment management method based on Asynchronous Advantage Actor-Critic (A3C), which is a representative asynchronous reinforcement learning algorithm. In addition, since the conventional cross-entropy function can not be applied to portfolio management, we propose a proper method where the existing cross-entropy is modified to fit the portfolio investment method. Finally, we compare the proposed A3C model with the existing reinforcement learning based cryptography portfolio investment algorithm, and prove that the performance of the proposed A3C model is better than the existing one.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.21 no.4
• /
• pp.14-25
• /
• 2018

The operation of high-speed rail (HSR) has an effect on the agglomeration economies, and the impact is shown as a relocation of individual firm and worker to where business activity can be maximized. The proximity to the HSR station could be considered as a core district to maximize the industrial benefit through the HSR network. From this perspective, this study considers the agglomeration effect of HSR within the HSR station-area and analyzed the agglomerated spatial pattern through hotspot analysis by service industry in the cases of Korea and Japan using GIS. This study analyzed the service industry within 1km distance from 8 HSR stations of Korea and 4 Kyushu Shinkansen stations of Japan. The results suggest that the hotspot patterns are observed in the service industry within 1km distance from the HSR station of Korea and Japan, except for two HSR stations of Gupo station and Kagoshima-Chuo station. Leisure, amusement, association, and other specific service industries could be affected by HSR passengers and knowledge-spillovers through HSR station. Therefore, the observed hotspot districts near the HSR station-area could explain an agglomeration pattern of the service industry through a closeness to the HSR station. Further, we could expect that the impact of HSR affects the service industry, and the impact could attract business activities of the service-area to maximize their benefit from HSR travelers. With the result, it is required to build up a supportive policy to maximize the HSR's impact on the service industry when considering the HSR station-area development.

• Journal of Korea Society of Industrial Information Systems
• /
• v.24 no.4
• /
• pp.65-77
• /
• 2019

Adolescents reach the game-use states of adaptive and maladaptive by the absorption to computer game. Authors claimed that the two states are commonly related with the time of game-use, and the degree of them are distinctive according to adolescent individuals, specifically their self-control propensity. Authors proposed a conceptual research model that Big Five personality types predict their self-control which moderates the relationships from game use-time to the maladaptive and adaptive states. The data to test its validity and reliability had been sampled 999 Korean students in elementary school, middle school, and high school. Resultingly, the openness and conscientiousness of the adolescents affected positively on the self-control, which moderated negatively the relationship from the game use time to the maladaptive use state, but the positive moderation on the relationships from game use time to adpative state was not significant. These results mean that we could apply teenager's Big Five personality type and their self-control traits as a tool for preventing teens from the overuse state like addiction.

• Journal of the Korea Convergence Society
• /
• v.11 no.12
• /
• pp.113-123
• /
• 2020

In this paper, big data analysis was conducted for past and present fashion trends and fashion cycle. We focused on daily look for ordinary people instead of the fashion professionals and fashion show. Using the social matrix tool, Textom, we performed frequency analysis, N-gram analysis, network analysis and structural equivalence analysis on the big data containing fashion trends and cycles. The results are as follows. First, this study extracted the major key words related to fashion trends for the daily look from the past(1980s, 1990s) and the present(2019 and 2020). Second, the frequence analysis and N-gram analysis showed that the fashion cycle has shorten to 30-40 years. Third, the structural equivalence analysis found the four representative clusters. The past four clusters are jean, retro codi, athleisure look, celebrity retro and the present clusters are retro, newtro, lady chic, retro futurism. Fourth, through the network analysis and N-gram analysis, it turned out that the past fashion is reproduced and evolves to the current fashion with certain reasoning.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.21 no.1
• /
• pp.65-75
• /
• 2011

Power Line Communication (PLC) is a system for carrying data on a conductor used for electric power transmission. Recently, PLC has received much attention due to connection efficiency and possibility of extension. It can be used for not only alternative communication, in which communication line is not sufficient, but also for communication between home appliances. Korea Electronic Power Cooperation (KEPCO) is constructing the system, which automatically collects values of power consumption of every household. Due to the randomness and complicated physical characteristics of PLC protocol (KS X4600-1), it has been believed that the current PLC is secure in the sense that it is hard that an attacker guesses or modifies the value of power consumption. However, we show that the randomness of the protocol is closely related to state of the communication line and thus anyone can easily guess the randomness by checking the state of the communication line. In order to analyze the security of PLC, we study the protocol in detail and show some vulnerability. In addition, we suggest that PLC needs more secure protocol on higher layers. We expect that the study of PLC help in designing more secure protocol as well.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.9
• /
• pp.1172-1179
• /
• 2020

With the establishment of the railway integrated radio network (LTE-R) environment, radio-based train control transmission and reception and various forms of service are provided. The smooth delivery of these services requires improved performance in a highly reliable and available wireless environment. This paper measured the LTE-R radio communication environment to improve radio communication performance of railway integrated wireless network reliability and availability, analyzed the results, and established the wireless environment model. Based on the built-up model, we also proposed an improved radio-access algorithm to control trains for improved reliability, suggesting a way to improve stability for handover that occur during open-air operation, and proposed an algorithm for frequency auto-heating to improve availability. For simulation, data were collected from the Korea Rail Network Authority (Daejeon), Manjong-Gangneung KTX route, which can measure the actual data of LTE-R wireless environment, and the results of the simulation show performance improvement through algorithm.