• Journal of Digital Convergence
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• v.17 no.9
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• pp.97-104
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• 2019

With the development and spread of smart devices, the proportion of mobile shopping is gradually increasing, and the market for mobile gift certificates is also increasing. This study examines the usage status and acceptance attitude of mobile gift certificates for university students who are major customers of mobile gift certificates. Also, based on the extended integrated technology acceptance model (UTAUT2), the results of the analysis of the mediating effect of the intention of the user on the relationship between acceptance of mobile vouchers and recommendation intention were presented. As a result of the analysis, it was shown that the effort expectation, hedonic motivation, price utility, and habit had significant influence on the intention to use the mobile gift certificates. Also, the intention to use mobile gift certificates has mediating effects between effort expectation, hedonic motivation, price utility and recommendation intention. The results of this study can be applied to strategic marketing such as recruitment of new customers through mobile gift certificates while explaining customers' acceptance of technology to mobile gift vouchers or future prospective customers.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.5
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• pp.189-203
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• 2021

Environmental changes, which are strongly requiring technological cooperation, such as technological development and strategic alliances according to industrial ecosystem change, have a significant impact on not only product quality but also services. Thus, there is a need for 'servitization' that can satisfy the needs of customers and the ecosystem of businesses through the convergence of manufacturing companies and services. This study uses the Expectation-Confirmation Model to examine the impact on user satisfaction and Continuance Usage Intention. Research(Study) was conducted on users who are using high-tech-based cars. For this, we used Expectation Confirmation(match expections for the user's pre-and post-use relationships), Perceived Ease, Perceived Usefulness, User Satisfaction and Habitual Use and using Continuance Usage Intention as a dependent variable. Their causation was examined with the spss 26.0 and smartpls 2.0 statistical programs. As implications of this study, Expectation Confirmation has been shown to have significant positive effects on Perceived Ease, Perceived Usefulness, User Satisfaction and Habitual Use. For this results, the expectations before and after the use of high-tech cars lead to improved daily lives convenience and(or) work efficiency, leading to user satisfaction and further Continuance Usage Intention. Motors consider it important to pursue the work improvements that consumers want and use it useful in daily lives in the production and sale of high-tech cars. It is expected that it will create natural habits for services that users are satisfied with, and that these habits will affect the continuous growth and understanding of the trend of change.

• Journal of Korean Society of Rural Planning
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• v.27 no.3
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• pp.21-33
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• 2021

Rice straw management and winter crop cultivation are crucial components for the accurate estimation of paddy methane emissions. Field-based extensive investigation of paddy organic matter management requires enormous efforts however it becomes more feasible as drone technology advances. The objectives of this study were to identify paddy fields of straw application and winter crop cultivation using drone images and to apply for the estimation of yearly methane emission. Total 35 sites of over 150ha in area were selected nationwide as the study areas. Drone images of the study sites were taken twice during summer and winter in 2018 through 2019: Summer images were used to identify paddy cultivation areas, while winter images for straw and winter crop practices. Drone-image-based identification results were used to estimate paddy methane emission and compared with conventional method. As the result, mean areas for paddy, straw application and winter crop cultivation were 118.9ha, 12.0ha, and 11.3ha, respectively. Overall rice straw application rate were greater in Gyeonggi-do(20%) and Chungcheongnam-do(12%), while winter crop cultivation was greatest in Gyeongsangnam-do(30%) and Jeolla-do(27%). Yearly mean methane emission was estimated to be 226.2kg CH₄/ha/yr in this study and about 32% less when compared to 331.8kg CH₄/ha/yr estimated with the conventional method. This was primarily because of the lower rice straw application rate observed in this study, which was less than quarter the rate of 55.62% used for the conventional method. This indicates the necessity to use more accurate statistics of rice straw application as well as winter crop practices into paddy methane emission estimation. Thus it is recommended to further study to link drone technology with satellite image analysis in order to identify organic management practices at a paddy field level over extensive agricultural area.

• Journal of Environmental Impact Assessment
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• v.30 no.5
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• pp.297-304
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• 2021

The environmental impact assessment(EIA) project in Korea has undergone changes and revisions in various evaluation items for about 30 years after the introduction of the Environmental Conservation Act (1997). However, despite the importance of land use evaluation items under the current EIA Act, there are insufficient studies to consider. Therefore, this study focused on the land-use evaluation items based on the EIA guidelines, reviewed 90 of the evaluation documents and consultation documents, and tried to suggest implications and supplementary points forthe domestic EIA land-use evaluation items. As a result, the paradigm was changing from land efficiency centered on development in the past to land efficiency centered on the natural environment and resource conservation. However, in spite of the manual for fitting the paradigm change, opinions on the conservation of the natural environment are still being drawn in the consultation document, so it needs improvement. Two improvements in the impact assessment process suggested in this study are the establishment of standardized spatial data and a quantitative impact and reduction method evaluation tool based on it. In particular, there is a need for a plan evaluation tool for land use arrangement and distribution that can solve the needs of minimizing damage to the natural environment and securing green space and a green network.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.207-213
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• 2019

The fuel-cut coast-down driving mode is activated when the acceleration pedal is released with transmission gear engaged, and it's a default function for electronic-controlled engine of vehicles. The fuel economy becomes better because fuel injection stops during fuel-cut driving mode. A fuel-cut detection method is suggested in the study and it's based on the speed, acceleration and road gradient data from GPS sensor. It detects fuel-cut driving mode by comparing calculated acceleration and realtime acceleration value. The one is estimated with driving resistance in the condition of fuel-cut driving and the other is from GPS sensor. The detection accuracy is about 80% when the method is verified with road driving data. The result is estimated with 9,600 data set of vehicle speed, acceleration, fuel consumption and road gradient from test driving on the road of 12km during 16 minutes, and the road slope is rather high. It's easy to detect fuel-cut without injector signal obtained by connecting wire. The detection error is from the fact that the variation range of speed, acceleration and road gradient data, used for road resistance force, is larger than the value of fuel consumption data.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.77-88
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• 2021

Cloud computing is getting a lot of attention by many people and businesses due to IT environmental changes such as the proliferation of smart devices, the increase of digital data, and the cost of IT resources. More individuals use personal cloud computing services for storing and managing information and data. Therefore, this study proposed determinants that are expected to have an influence on evaluating the value of cloud computing based on the value-based adoption model, examining the relationship between the continuous use intention of cloud computing. Results of the study show that usefulness, convenience of information access, extensibility had a positive impact on perceived value while privacy concerns and costs had a negative impact on perceived value. In addition, perceived value was found to have a significant effect on the intention to continue use of cloud computing. Finally, trust was found to have a significant effect on the perceived value and the intention to continue use of cloud computing. The findings are expected to provide useful information for understanding the factors that individual users consider important in the steadily growing cloud computing market.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.7-14
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• 2020

This study analyzed the effect of the number of deaths of circulatory system diseases according to 12-day short-term exposure of carbon monoxide from January 2010 to December 2018, and predicted the future treatment cost of circulatory system diseases according to increased carbon monoxide concentration. Data were extracted from Air Korea of Korea Environment Corporation and Korea Statistical Office, and analyzed using Poisson regression analysis and ARIMA intervention model. For statistical processing, SPSS Ver. 21.0 program was used. The results of the study are as follows. First, as a result of analyzing the relationship between the impact of short-term carbon monoxide exposure on death of circulatory system diseases from the day to the previous 11 days, it was found that the previous 11 days had the highest impact. Second, with the increase in carbon monoxide concentration, the future circulatory system disease treatment cost was estimated at 10,123 billion won in 2019, higher than the observed value of 9,443 billion won at the end of December 2018. In addition, when summarized by month, it can be seen that the cost of treatment for circulatory diseases increases from January to December, reflecting seasonal fluctuations. Through such research, the future for a healthy life for all citizens can be realized by distributing various devices and equipment utilizing IoT to preemptively respond to the increase in air pollutants such as carbon monoxide.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.570-575
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• 2021

Since humans live while feeling rich in their five senses, care must be taken not to damage their hearing in order to lead a happy life. Hearing damage suffered in a living environment is common in a partial band where a specific frequency band is first damaged. However, since the initial pain of hearing damage does not appear much, it is difficult to determine the symptoms in the early stages. In this paper, we proposed a high-speed measurement method that can easily and quickly self-measure hearing damage through a simple app. In this method, 9 pure tones compensated for gain for each voice soub-band are alternately heard in both ears, so that one's own hearing damage can be detected at high speed. When 18 tone pulses were heard for 30 seconds per person, 1 out of 12 subjects was identified as suspected of partial hearing damage. And when the test subjects were informed of the hearing determination method for the number of hearings, the participants themselves immediately determined whether their hearing was damaged. This measurement method simply judges the hearing of both ears within 30 seconds with a smart phone, so that hearing measurements that took more than 10 minutes in hospitals are relatively accurate, and it was found that hearing health can be maintained while reducing time and costs.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.34-46
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• 2021

In order to accelerate the commercialization of self-driving cars, it is necessary to accurately identify the causes of deteriorating the driving safety of the current self-driving cars and try to improve them. This study conducted a questionnaire survey of experts studying autonomous driving in Korea to identify the causes of problems in the driving safety of autonomous vehicles and the level of autonomous driving technology in Korea. As a result of the survey, the construction section, heavy rain/heavy snow conditions, fine dust conditions, and the presence of potholes were less satisfied with the current technology level than their importance, and thus priority research and development was required. Among them, the failure of road/road facilities and the performance of the sensor itself in the construction section and the porthole, and the performance of the sensor and the absence of an algorithm were the most responsible for the situation connected to the weather. In order to realize safe autonomous driving as soon as possible, it is necessary to continuously identify and resolve the causes that hinder the driving safety of autonomous vehicles.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.29-36
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• 2020

The background of this study is that machine learning administrative services are recently attracting attention as a major policy tool for non-face-to-face administrative services in the post-corona era. This study investigated the types of work expected to be effective when introducing machine learning administrative services for Seoul Metropolitan Government officials who are piloting machine learning administrative services. The research method is a machine that can be introduced by organizational unit by distributing and collecting questionnaires for Seoul administrative organizations that have performed machine learning-based administrative services for one month in July 2020 targeting Seoul public officials using machine learning-based administrative services. By analyzing the learning administration service and application service, the business characteristics of each machine learning administration service type such as supervised learning work type, unsupervised learning work type, and reinforced learning work type were analyzed. As a result of the research analysis, it was found that there were significant differences in the characteristics of administrative tasks by supervised and unsupervised learning areas. In particular, it was found that the reinforcement learning domain contains the most appropriate business characteristics for machine learning administrative services. Implications were drawn. The results of this study can be provided as a reference material to practitioners who want to introduce machine learning administration services, and can be used as basic data for research to researchers who want to study machine learning administration services in the future.