• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.337-342
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• 2014

This paper is aims to build the advancement structural model of GICOMS through identification of required system and improvement for implementation of e-Navigation. We derived nine improvement subject for model of advanced GICOMS through the analysis of problems for GICOMS and brainstorming with expert in the maritime safety. And we analyzed the structure of nine improvement subject using by FSM(Fuzzy Structural Modeling) method, and proposed a structural model that to grasp the correlation between elements. As a result, we found out that "advancement of GICOMS" is the final goal, and "improvement a system of information production", "improvement a scheme of information providing", "linkage between GICOMS and VTS" and "building global networks for safety cooperation" are located lowest level. Especially, "advancement of GICOMS" is influenced by "advancement function of VMS" and "Activation of usage" on middle level. We suggested that utilizing state-of-the-art IT facilities, equipment and expertise to improve and enhance the user-centered transition such as maritime workers for advancement of GICOMS based on proposed structure model.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.215-229
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• 2020

In response to the recent 4th industrial revolution, the demand for 3D object models in the latest fields of digital twin, autonomous driving, and VR/AR, as well as the existing fields such as city, construction, transportation, and energy has increased significantly. It is expected that the demand for 3D object models with various precision from LOD1 to LOD4 will increase more and more in various industry fields. However, the Ministry of Land, Infrastructure and Transport, and the local government and the private sector have partially built 3D object models of different precisions for some specific regions because of the huge cost. Therefore, this study proposes a feasible plan that can solve the cost problem in generating 3D object models for the whole territory. For our purpose, we first analyzed usage, demand, generation technology and generation cost for 3D object models. Afterwards, we proposed LOD3 model generation plan for all territory using automatic 3D object model generation technology based on image matching. Additionally, we supplemented the proposed plan by using LOD4 generation plan for landmarks and LOD2 generation plan non-urban area. In the near future, we expect this would be a great help in establishing a feasible and effective 3D object model generation plan for the whole country.

• Journal of Distribution Science
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• v.14 no.4
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• pp.47-53
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• 2016

Purpose - The objective of this study is to investigate the dynamic relationships among Advertising Cost (AD), Newly Registered Users(NRU), and Buying Users(BU) of Social Network Game(SNG). SNG is getting pervasive mainly due to the rapid growth of mobile game and Social Network Service(SNS). It would be helpful for marketing researchers interested in SNG and related practitioners to understand the changes in AD, NRU, and BU with time as well as the effects on one another in mutual and dynamic way. Research Design, Data, and Methodology - Necessary data were collected from Social Network Game(SNG) company. AD, NRU, and BU are endogenous variables, but new event such as launching (event) and holidays(holiday) are exogenous dummy variables. Vector Auto regression (VAR) model is generally used to examine and capture the dynamic relationships among endogenous variables. VAR model can easily capture dynamic and endogenous relationships among time-series variables. Vector Auto regression with Exogenous variables(VARX) is a model in which exogenous variables are added to VAR. To investigate this study, VARX is applied. Result - By estimating the VARX model, the author finds that the past periods' NRU affect negatively and significantly the present AD, and past periods' BU have a positive and significant impact on the increase of AD. In addition, the author shows that the past periods' AD and BU have a positive and significant effect on the increase of NRU, and the past periods' AD affect positively and significantly BU. While the impact of AD on NRU happens after 3 or 4 days (carryover effect), that of AD on BU comes about within just 1 or 2 days (immediate effect). The effect of BU on NRU can be considered as word of mouth (WOM effect). Therefore, SNG companies can obtain not only the growth of revenue but also the increase of NRU by increasing BU. Through those results, the author can also find that there are significant interactions between endogenous variables. Conclusion - This study intends to investigate endogenous and dynamic relationships between AD, NRU, and BU. They also give managerial implications to practitioners for SNS and SNG firms. Through this study, it is found that there exist significant interactions and dynamic relationships between those three endogenous variables. The results of this study can have meaningful implications for practitioners and researchers of SNG. This research is unique in that it deals with "actual" field data and intend to find "actual" relationships among variables unlike other related existing studies which intend to investigate psychological factors affecting the intention of game usage and the intention of purchasing game items. This study is also meaningful by showing that the increase of BU can be a good strategy for "killing birds with one stone" (i.e., revenue growth and NRU increase). Although there are some limitations related with future research topics, this research contributes to the current research on SNG marketing in the above mentioned ways.

• Journal of Climate Change Research
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• v.4 no.3
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• pp.211-219
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• 2013

This study uses the LEAP model that is a long-term energy analysis model to analyze reduction potential on S city residential sector energy usage for greenhouse gas emission. Energy consumption of S-si in 2009 is consumed most in residential and commerce sector by 39.1%. Also, energy and greenhouse gas emission of residential sector is expected to increase due to increase of households. Therefore, greenhouse gas reduction measures are desperately required in residential sector. For this study recognizes energy consumption of S-si residential sector and has established reduction measure of S-si residential sector greenhouse gas through literature search on domestic and foreign climate change correspondence policies. Also, construction of greenhouse gas reduction potential by reduction measures through LEAP model. There were a total of 5 reduction measures scenarios is Reference Scenario, LED Lighting, Energy Alternative, Green Life Practice, and Total Reduction Measure. As a result, greenhouse gas emission of Light Emitting Diode Lightings by 2020 was $1,181.0thousand\;tonCO_2eq$, decrease of 6.1% compared to the Reference Scenario and Greenhouse gas emission of Energy Alternative by 2020 was $1,171.6thousand\;tonCO_2eq$, decrease of 6.8% compared to the Reference Scenario. Greenhouse gas emission of Green Life Practice by 2020 was $1,128.7thousand\;tonCO_2eq$, decrease of 10.2% compared to the Reference Scenario. For Total Reduction Measures by 2020 emission was $966.9thousand\;tonCO_2eq$, decrease 23.1% compared to Reference Scenario.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.791-804
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• 2020

Residential electricity consumption can be predicted more accurately by utilizing the realtime household electricity consumption reference that can be collected by the AMI as the ICT developed under the smart grid circumstance. This paper studied the model that predicts residential power load using the ARIMA, TBATS, NNAR model based on the data of hour unit amount of household electricity consumption, and unlike forecasting the consumption of the whole households at once, it computed the anticipated amount of the electricity consumption by aggregating the predictive value of each established model of cluster that was collected by the households which show the similiar load profile. Especially, as the typical time series data, the electricity consumption data chose the clustering analysis method that is appropriate to the time series data. Therefore, Dynamic Time Warping and Periodogram based method is used in this paper. By the result, forecasting the residential elecrtricity consumption by clustering the similiar household showed better performance than forecasting at once and in summertime, NNAR model performed best, and in wintertime, it was TBATS model. Lastly, clustering method showed most improvements in forecasting capability when the DTW method that was manifested the difference between the patterns of each cluster was used.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.53-67
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• 2021

According to statistics, the number of mobile payment users in China shows an increasing trend year by year. However, less than half of people over 60 years old use mobile payment. The purpose of this study is to explore the reasons for the low usage rate of mobile payment platforms among the elderly in China. Through literature research, questionnaires and interviews, the author found that the main obstacle for the elderly in China to use mobile payment platforms is acceptance barrier. Then, the user experience research method and technology acceptance model (TAM) were combined to construct a new research model and five hypotheses affecting acceptance behavior in the model were summarized. Finally, the Analysis of Covariance(ANCOVA) was used to test the hypotheses and found that satisfaction (SA), perceived usefulness (PU) and job relevance (JR) had significant coefficients of 0.001, 0.000 and 0.004 respectively, all of which were less than 0.05 and therefore had a significant effect on acceptability. The other two elements, perceived ease of use (PE) and self-efficacy (SE), did not have a significant effect on acceptability. Ultimately, a new user experience acceptability model was constructed to provide theoretical support for mobile payment platform developers and designers to develop products from the acceptability perspective, so as to develop more mobile payment methods suitable for elderly users and improve the acceptance of mobile payment by the elderly.

• Journal of Korea Entertainment Industry Association
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• v.14 no.6
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• pp.91-107
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• 2020

The purpose of this study is to explore quantitatively the success factors of YouTube's music cover channel. Along the process, constructing and testing the measurement for music cover channel's characteristics. The research constructed the measurement items based on results of qualitative studies. To perform the purposes the study suggest a research model which integrated the Post Acceptance Model with five music cover channel's characteristics based on the recent case studies. The five characteristics were contents, video, creator, interactivity, and publicity. The characteristics were integrated with Post Acceptance Model. After testing reliability and validity the research model was revised then, the research hypothesis was tested. The research results show: first, it was found that the content characteristics did not meet the expected value of users. Second, among the five factors of channel characteristics presented in creator's characteristics have the largest effect on user's value perception Third, in the factor analysis process, the content factor and the video were loaded on the same factor thus integrated as one factor. Fourth, satisfaction and intention for continual usage were also loaded on the same factor thus integrated as one factor. The research results suggest that music cover channel operators need to enhance the creator's attraction, communication with user, and publicity in various ways.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.1025-1032
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• 2006

Sensor modeling of high-resolution satellites is a prerequisite procedure for mapping and GIS applications. Sensor models, describing the geometric relationship between scene and object, are divided into two main categories, which are rigorous and approximate sensor models. A rigorous model is based on the actual geometry of the image formation process, involving internal and external characteristics of the implemented sensor. However, approximate models require neither a comprehensive understanding of imaging geometry nor the internal and external characteristics of the imaging sensor, which has gathered a great interest within photogrammetric communities. This paper described a comparison between rigorous and various approximate sensor models that have been used to determine three-dimensional positions, and proposed the appropriate sensor model in terms of the satellite imagery usage. Through the case study of using IKONOS satellite scenes, rigorous and approximate sensor models have been compared and evaluated for the positional accuracy in terms of acquirable number of ground controls. Bias compensated RFM(Rational Function Model) turned out to be the best among compared approximate sensor models, both modified parallel projection and parallel-perspective model were able to be modelled with a small number of controls. Also affine transformation, one of the approximate sensor models, can be used to determine the planimetric position of high-resolution satellites and perform image registration between scenes.

• Information Systems Review
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• v.26 no.2
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• pp.95-121
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• 2024

The rapid increase in smartphone ownership underscores the importance of service delivery in the mobile environment. Accordingly, the public sector is allocating budget and effort towards providing services through mobile applications. While some have recorded high download numbers, contributing to the proliferation of public services, issues such as low user engagement and budgetary concerns have simultaneously been raised. This study aims to analyze factors influencing the intention to use public apps with the theoretical foundation of the Technology Readiness Acceptance Model (TRAM) to enhance users' acceptance of public apps. Previous research has primarily focused on system characteristics, but this study constructs the model with a significant consideration for user characteristics. Additionally, through a comprehensive examination of publicness, which has been lacking in existing research, the study integrates this aspect into the model. Ultimately, this research provides insights into the factors influencing users' intention to use public apps and suggests approaches to enhance usage intention for the successful implementation of a Digital Platform Government.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.50-63
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• 2018

The rapid urbanization had led to a distortion of natural hydrological cycle system. The change in hydrological cycle structure is causing streamflow depletion, changing the existing use tendency of water resources. To manage such phenomena, a streamflow depletion impact assessment technology to forecast depletion is required. For performing such technology, it is indispensable to build GIS-based spatial data as fundamental data, but there is a shortage of related research. Therefore, this study was conducted to use the use of GIS-based time series spatial data for streamflow depletion assessment. For this study, GIS data over decades of changes on a national scale were constructed, targeting 6 streamflow depletion impact factors (weather, soil depth, forest density, road network, groundwater usage and landuse) and the data were used as the basic data for the operation of continuous hydrologic model. Focusing on these impact factors, the causes for streamflow depletion were analyzed depending on time series. Then, using distributed continuous hydrologic model based DrySAT, annual runoff of each streamflow depletion impact factor was measured and depletion assessment was conducted. As a result, the default value of annual runoff was measured at 977.9mm under the given weather condition without considering other factors. When considering the decrease in soil depth, the increase in forest density, road development, and groundwater usage, along with the change in land use and development, and annual runoff were measured at 1,003.5mm, 942.1mm, 961.9mm, 915.5mm, and 1003.7mm, respectively. The results showed that the major causes of the streaflow depletion were lowered soil depth to decrease the infiltration volume and surface runoff thereby decreasing streamflow; the increased forest density to decrease surface runoff; the increased road network to decrease the sub-surface flow; the increased groundwater use from undiscriminated development to decrease the baseflow; increased impervious areas to increase surface runoff. Also, each standard watershed depending on the grade of depletion was indicated, based on the definition of streamflow depletion and the range of grade. Considering the weather, the decrease in soil depth, the increase in forest density, road development, and groundwater usage, and the change in land use and development, the grade of depletion were 2.1, 2.2, 2.5, 2.3, 2.8, 2.2, respectively. Among the five streamflow depletion impact factors except rainfall condition, the change in groundwater usage showed the biggest influence on depletion, followed by the change in forest density, road construction, land use, and soil depth. In conclusion, it is anticipated that a national streamflow depletion assessment system to be develop in the future would provide customized depletion management and prevention plans based on the system assessment results regarding future data changes of the six streamflow depletion impact factors and the prospect of depletion progress.