This study is to inquire respective patterns of mental models caused by wrongful usages which can be experienced when a user who is used to a keypad-based mobile phone starts using a touch screen mobile phone and to find out the features of the user's logical process of correcting such wrongful usages to a new mental model. In addition, design improvement to be considered for easy generation of the mental model regarding touch screen mobile phones was reviewed in this study. We set up test subjects for the most frequently used seven high priority functions among touch screen phone functions and carried out the subject assessment together with interview surveys after the video observation experiment. Our test results show that test subjects who were used to keypad-based mobile phones tend to use operation knowledge related to the computer operational system(Window) or the web browse, navigation including Tap or Double Tap in order to correct the mental model when a wrongful usage is made. In addition, the result of comparison and analysis of the subject assessment and the video observation experiment data shows that wrongful usages of touch screen mobile phones mostly occurred in the field of 'information feedback' and 'navigation' among mobile phone components.
Journal of the Korea Society of Computer and Information
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v.25
no.1
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pp.141-149
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2020
The proportion of commercial vehicles currently used by the private sector among the vehicles operated by the military is very high at 58% and plans to increase further in the future. As the proportion of commercial vehicles in the military has increased, it is also an important issue to determine whether to disuse of commercial vehicles. At present, the decision of disuse of commercial vehicles is subjectively judged by vehicle technical inspector using design life and vehicle usage information. However, the difference according to the military operation environment is not reflected and objective judgment criteria are not presented. The purpose of this study is to develop a model to determine the disuse status of commercial vehicles in consideration of military operating environment. The data used in the study were 1,746 commercial vehicles of three types: cars, vans and trucks. Using the information of the operating area, climate characteristic, vehicle condition the decision model of disuse status was constructed using the classification machine learning technique. The proposed decision model of disuse status has an average accuracy of about 97% and can be used in the field. Based on the results of the study, the policy suggestions were proposed in the short and long term to improve the performance of decision model of disuse status of commercial vehicles in the future and to establish a new data construction method within the logistics information system.
KSCE Journal of Civil and Environmental Engineering Research
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v.39
no.6
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pp.877-886
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2019
The size of the subway entrance should be calculated according to the user's demand, but Korea has the same size for each entrance by applying a uniform value. Recently, the installation of mobile convenience facilities such as escalators, elevators, etc. is mandated by the traffic weakness promotion law, but it is inconvenient to use the existing stations because it is mainly arranged in the place where it can be installed regardless of user demand. This study aims to establish a model for estimating the size of mobile convenience facilities by predicting the use demand of each station entrance so that the location and size of mobile facilities can be reflected in the design or construction of the station. To this end, a multiple regression model was established to forecast daily demand by utilizing the demand for getting on and off by station and the building association area for each purpose around the railway station. The actual data of Dongdaemun and Jonggak Stations were used to verify the estimated model. In addition, the escalator installation scale was compared / analyzed by doorway using domestic and overseas escalator equations. As a result, it was more accurate to estimate the usage demand for a single station. Also, Jonggak Station has an up and down escalator installed at exit 1, but it was analyzed that it is appropriate to install at exit 4. This study is an advanced form of the essay model for estimating the users of the entrance and exit users of urban railway stations published in 2018. In addition, it seems to be the basis of the current escalator installation criteria.
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.
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.
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.
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.
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.
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
/
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.
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