• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2009.11a
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• pp.162-167
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• 2009

With the introduction of the ubiquitous technology, the housing culture centers of construction companies have demonstrated future housing image and technology. However, ubiquitous home services are technology oriented items. The purpose of this study was to identify u- services which were realized in domestic future housing and to compare those with services the residents needed greatly refer to researches related to demand for u-service. For this study, field studies were conducted with 3 domestic future housings and precedent studies on demand for u-service were analyzed according to the standard of residents' demand. The results of the study showed that residents prefer u-services for security and control of indoor environment for housework and leisure life. As a result, u-services which residents needed mainly did not correspond with those that were displayed in future housing.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.43-48
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• 2014

With the energy paradigm shift from supply side management to demand side management, many researches have been done on demand side resource management and demand response. At the same time, Obix, BacNet-WS and OPC-UA are popularly used in buildings and industry energy management system. However, it is not easy to interchange the data and information among the systems cause a variety of protocols are used in buildings and factories. Therefore, in this paper, we are proposing an open business platform not only to integrate and manage the demand resources using various protocols and standards, but also to allow to plug-ins a new business service on top of the platform.

• Journal of Information Technology Applications and Management
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• v.26 no.2
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• pp.61-73
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• 2019

In 2019, 5G mobile communication technology will be commercialized. From the viewpoint of technological innovation, 5G service can be applied to other industries or developed further. Therefore, it is important to measure the demand of the Internet of things (IoT) because it is predicted to be commercialized widely in the 5G era and its demand hugely effects on the economic value of 5G industry. In this paper, we applied Bayesian method on regression model to find out the demand of 5G IoT service, wearable service in particular. As a result, we confirmed that the Bayesian regression model is closer to the actual value than the existing regression model. These findings can be utilized for predicting future demand of new industries.

• The Journal of Korean Association of Computer Education
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• v.5 no.1
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• pp.57-66
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• 2002

Real time multimedia data services have been made possible by the rapid development of the computer and internet technology. Based on the technology, Many multimedia system developer try to use VOD(Video on Demand) and GVA technologies for distance education. However the system has mainly been developed to provide the video screen of good quality in real time and to compose contents efficiently. Not many researches and developments have been made for providing the users that is taking distance education with various types of service using VOD and GVA. Therefore In this paper we have designed and implemented an active on-demand multimedia service system to improve user-side service quality in distance education using VOD and GVA service. The on-demand multimedia service system can prominently help users to save the time and effort to search and select the studying data by this paper enables off-line search functions through E-mail and periodical current awareness service supported by PUSH technology, user oriented information booking supported by SDI service and feedback service.

• Journal of Information Technology Services
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• v.7 no.2
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• pp.41-57
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• 2008

The development of service-based software and web-based application aims for providing user-demand service. On-demand software is emerging for same reason. Software delivery models like on-demand software is expected to change the software industry as an important technical revolution with the firm's strategy. Few research, however, has been done on the on-demand software. While much research on ASP and SaaS focused on firm' use, this study intends to examine the intention of using on-demand software targeting personal user. The intention to use of on-demand software was empirically examined in terms of quality, user characteristics, usefulness, easy of use, and security. Results shows that usefulness and easy of use are most significantly related to the intention of using on-demand software. Other factors are also found to affect the intention to use of on-demand software. This study contributes to improve the understanding and interest in on-demand software and it is expected to spread widely for individual user.

• Fire Science and Engineering
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• v.22 no.2
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• pp.9-19
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• 2008

Recently the systematic change in the fire and disaster prevention administration, which was less studied than other administrative systems, has been in progress. In particular, the fire service demands are increasing and forms are diversified. The first thing you must do is to make up the fire service power according to the fire service demands. Such an allocation results in social welfare satisfaction. The purpose of this study is to investigate the determinants of fire service force. And this study investigates that fire service demand is affected by socioeconomic factor. To do this, this study reviews fire service force, the fire service demand, socioeconomic factor and financial factor. And this study sets up four hypotheses based on the theoretical backgrounds and the past research. The statistical method used for the verification of hypotheses are multiple regression analysis and structural equitation analysis. The analysis showed that fire service demand and financial factor were positive significant variable for fire service power. But socioeconomic factor was a negative significant variable. Also the analysis showed that social factor was a positive significant variable and economic factor was a negative significant variable for fire service demand.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.495-498
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• 2007

Recently, as REID Tag and Reader has been attached to, and wireless internet has been added to a mobile phone, the commercialization of Mobile RFID Service to obtain necessary information on daily life and use various applications by using mobile communication infra is drawing nearer. A new returns by Mobile RFID Service can be expected, however, the exact demand forecasting for the Mobile RFID Service is essential to induce mass investment from related communication enterprises. This study tries to get a foothold in enlarging the investment from related communication enterprises through demand forecasting for the Mobile RFID Service and to be helpful to the decision on their investment by predicting the demand on the service various Mobile RFID Service Models.

• Journal of Korean Society of Transportation
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• v.14 no.1
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• pp.69-80
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• 1996

In most cities, travel demand is distributed along long corridors and its destinations tend to concentrate in a central business district. For this kind of many-to-one or one-to-many travel demand pattern, a zonal operation of buses can be an efficient bus operation technique in which a long bus-demand corridor is divided into service zones and each service zone is provided with its own bus route connecting the service zone and single destination separately. This paper develops models of the total transportation costs for a single-zone operation and 2-zonal operation of buses for a long demand corridor with single destination in terms of various cost parameters, demand density, bus operation speeds, and location of the boundary between two service zones. In this study the total transportation cost is assumed to consist of the bus operation cost, passenger waiting cost and passenger travel time cost. It was proved that a zonal operation of buses can be more efficient than a single-zone operation for certain circumstances of the system and an boundary condition between two operation techniques was obtained. Also, several case studies were performed for various values of the cost parameters.

• Journal of Korea Technology Innovation Society
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• v.3 no.1
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• pp.113-126
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• 2000

The purpose of this paper is to introduce and test an extension of dichotomous choice contingent valuation(DC-CV) methods of pre-test-market evaluation using the specific case of a cable telev-ision service. Specifically we used a double-bounded DC-CV approach. On the whole respondents accepted the contingent market and were willing to contribute a significant amount on average. This willingness varies according to individual characteristics and concerns about the service. It is concluded that the methods are potentially a useful tool for decision-makers in measuring the po-tential demand for a new cable television service and considering the provision of the service.

• The Journal of Information Systems
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• v.31 no.3
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• pp.197-220
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• 2022

Purpose The purpose of this study is to identifies the demand pattern categorization of repair parts of Automotive After-sales Service(A/S) and proposes a demand prediction model for Auto repair parts using Long Short-Term Memory (LSTM) of artificial neural networks (ANN). The optimal parts inventory quantity prediction model is implemented by applying daily, weekly, and monthly the parts demand data to the LSTM model for the Lumpy demand which is irregularly in a specific period among repair parts of the Automotive A/S service. Design/methodology/approach This study classified the four demand pattern categorization with 2 years demand time-series data of repair parts according to the Average demand interval(ADI) and coefficient of variation (CV²) of demand size. Of the 16,295 parts in the A/S service shop studied, 96.5% had a Lumpy demand pattern that large quantities occurred at a specific period. lumpy demand pattern's repair parts in the last three years is predicted by applying them to the LSTM for daily, weekly, and monthly time-series data. as the model prediction performance evaluation index, MAPE, RMSE, and RMSLE that can measure the error between the predicted value and the actual value were used. Findings As a result of this study, Daily time-series data were excellently predicted as indicators with the lowest MAPE, RMSE, and RMSLE values, followed by Weekly and Monthly time-series data. This is due to the decrease in training data for Weekly and Monthly. even if the demand period is extended to get the training data, the prediction performance is still low due to the discontinuation of current vehicle models and the use of alternative parts that they are contributed to no more demand. Therefore, sufficient training data is important, but the selection of the prediction demand period is also a critical factor.