• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.160-171
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• 2008

MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.73-85
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• 2004

Recently, as the growth of the wireless Internet, PDA and HPC, the focus of research and development related with GIS(Geographic Information System) has been changed to the Real-Time Mobile GIS to service LBS. To offer LBS efficiently, there must be the Real-Time GIS platform that can deal with dynamic status of moving objects and a location index which can deal with the characteristics of location data. Location data can use the same data type(e.g., point) of GIS, but the management of location data is very different. Therefore, in this paper, we studied the Real-Time Mobile GIS using the HBR-tree to manage mass of location data efficiently. The Real-Time Mobile GIS which is developed in this paper consists of the HBR-tree and the Real-Time GIS Platform HBR-tree. we proposed in this paper, is a combined index type of the R-tree and the spatial hash Although location data are updated frequently, update operations are done within the same hash table in the HBR-tree, so it costs less than other tree-based indexes Since the HBR-tree uses the same search mechanism of the R-tree, it is possible to search location data quickly. The Real-Time GIS platform consists of a Real-Time GIS engine that is extended from a main memory database system. a middleware which can transfer spatial, aspatial data to clients and receive location data from clients, and a mobile client which operates on the mobile devices. Especially, this paper described the performance evaluation conducted with practical tests if the HBR-tree and the Real-Time GIS engine respectively.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.6
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• pp.371-377
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• 2007

In this paper, we propose the effective operating device in the container freight station by applying the RTLS (Real Time Location System) that provides information on the container's location in real time so that the performance of the port operating system can be improved. For this, we proposed the improved dual cycling method made with the new application of two types of container's location & yard tractor's location information. we applied the RTLS to the container freight station to send the container location data to the operating system in real time; we designed the data on the Yard Tractor's location to be received via the GPS receiver and then be sent to the operating system in real time via the CDMA module. According to the analysis and evaluation of the performance of the proposed method, up to 24% of performance improvement was shown compared with the existing methods, in aspect of evaluation of work time, work time deviation and performance. Therefore, we proved that the RTLS and the GPS receiver are essential elements for efficient port operation.

• Journal of Distribution Science
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• v.17 no.6
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• pp.77-84
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• 2019

Purpose - Although an extensive body of research in psychology and marketing focuses on perceived waiting time, no research has examined the effect of the location of the waiting place on perceived waiting time. In particular, this study suggests that customers who are waiting in a restaurant may have different perceived waiting time depending on whether they are in close proximity to the service area (e.g., dining area) or farther from it. In particular, the author examines how and why the location of the waiting place affects the perceived waiting time of the consumer and reveals the mental simulation as its psychological mechanism. Research design, data, and methodology - This study conducted field surveys with customers waiting in real restaurants. Eighty-eight people participated under two conditions: a restaurant with a waiting place near the dining area and a restaurant with a waiting place far from the dining area. Participants responded to questions about perceived waiting time (the dependent variable), mental simulation (the mediator), and demographic variables. To verify the hypothesis, ANOVA and bootstrapping analysis were performed. Results - The major results from the field study are as follows. First, participants perceived wait time differently depending on the location of the restaurant's waiting place: participants in the restaurant with a waiting place close to the dining area perceived significantly shorter waiting times. Second, the effect of the location of the waiting place on the perceived waiting time was mediated by mental simulation: the closer the wait location is to the dining area, the more imagination the customer exercises about the meal, which in turn distracts attention from time flow and shortens the perceived wait time. Conclusion - This study has a theoretical implication in that it extends research on perceived waiting time as the first study of how and why the location of a waiting place affects a customer's perceived waiting time. It has a practical implication that can be used as a marketing tactics to improve the image of the service provider by changing the location of the waiting place.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.986-998
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• 2003

A moving object management system manages spatiotemporal data o( moving objects which change their location continuously over time such as people, animals, cars, cellular phones, and so on. This system can be applied to location based services such as vehicle tracking systems, digital battlefields, and animal habitat management. The existing systems neither suggest location estimation of the moving objects nor handle the loss data of the moving objects in real-time environment. Thus the existing systems have problems that they give the uncertain results of the query processing to the user query. In this paper, we design a new moving object management system. The proposed system processes the past and future location information of the moving objects by the location change function. Also we propose a location triggering method, which supplements loss of the location data of the mobile objects in real-time environment. Finally, we implement and apply the proposed system to a vehicle tracking system based on PDA. Thus we ascertain that the proposed system can be applied to the location based system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.388-394
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• 2007

In wireless network, we propose a predictive location update scheme which considers mobile user's(MU's) mobility patterns. MU's mobility patterns can be found from a movement history data. The prediction accuracy and model complexity depend on the degree of application of history data. The more data we use, the more accurate the prediction is. As a result, the location management cost is reduced, but complexity of the model increases. In this paper, we classify MU's mobility patterns into four types. For each type, we find the respective optimal number of application of history data, and predictive location area by using the simulation. The optimal numbers of four types are shown to be different. When we use more than three application of history data, the simulation time and data storage are shown to increase very steeply.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.83-95
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• 2021

In this study, various usage patterns were analyzed after establishing a data mart for micro mobility analysis based on the rental history of public bicycles in Seoul. Rental history data is origin-destination data that includes the rental location and time, and the return location and time. About 1500 rental locations were classified according to the characteristics of the location to create a 'station type' dimension. We also created a 'path type' dimension that displays whether the rental location and return location are the same. In addition, a derived variable called speed, which is obtained by dividing the distance used by the time used, is added, and through this, the characteristics of the riding area and the reason for the rental can be estimated. Meanwhile, administrative district link, administrative neighborhood link, and station type link were created to apply network analysis. Through this analysis, the roles and proportions of administrative districts, public facilities, and private facilities engaged in micro-mobility services were visualized. 49.9% of rentals occur at rental offices near transportation facilities, and half of them occur at rental offices near subway stations. The number of rentals during the evening rush hour is more than double that of the morning rush hour. When the path type is unidirectional, there is a fixed destination, so the distance and time used are short, and the movement speed tends to be high. In the case of round-trip, the purpose of use is exercise or leisure, so the distance and time used are long, and the movement speed is slow. It is expected that the results of the analysis can be used as reference materials for selecting new rental locations, providing convenient services for users, and developing user-specialized products.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.41-47
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• 2019

A BIS(Bus Information System) collects, processes and analyzes information such as real-time location and operation status during bus operation. And It is a system that provides valid information to citizens, drivers, traffic centers and bus companies. Transport information system sent by an each bus is collected through GPS(Global Positioning System), DSRC(Dedicated Short Range Communications), Beacon and passed to transport information center. BIS data by collected is handled and analyzed. Next, it is transmitted to citizen, drivers and bus companies in real time. The result of 5 times simulation satisfied the test criteria(error range ${\pm}10m$) with an average error range of 3.306m, and the reliability is increased. In this paper, we propose a improved location transfer component that can provide users to quicker and more accurate location information than existing BIS using GPS of smart phone. It can be seen that reliability is improved by securing improved bus position data.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.295-300
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• 1998

In this paper, a real time diagnostic algorithm fur estimating the impact location by loose parts is proposed. It is composed of two modules such as the alarm discrimination module (ADM) and the impact-location estimation module(IEM). ADM decides whether the detected signal that triggers the alarm is the impact signal by loose parts or the noise signal. When the decision from ADM is concluded as the impact signal, the beginning time of burst-type signal, which the impact signal has usually such a form in time domain, provides the necessary data fur IEM. IEM by use of the arrival time method estimates the impact location of loose parts. The overall results of the estimated impact location are displayed on a computer monitor by the graphical mode and numerical data composed of the impact point, and thereby a plant operator can recognize easily the status of the impact event. This algorithm can perform the diagnosis process automatically and hence the operator's burden and the possible operator's error due to lack of expert knowledge of impact signals can be reduced remarkably. In order to validate the application of this method, the test experiment with a mock-up (flat board and reactor) system is performed. The experimental results show the efficiency of this algorithm even under high level noise and potential application to Loose Part Monitoring System (LPMS) for improving diagnosis capability in nuclear power plants.

• The KIPS Transactions:PartD
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• v.10D no.1
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• pp.45-56
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• 2003

In the wireless environment, according to the development of technology, which is able to obtain location information of spatiotemporal moving object, the various application systems are developed such as vehicle tracking system, forest fire management system and digital battle field system. These application systems need the data model, which is able to represent and process the continuous change of moving object. However, if moving objects are expressed by a relational model, there is a problem which is not able to store all location information that changed per every time. Also, existing data models of moving object have a week point, which constrain the query time to the time that is managed in the database such as past or current and near future. Therefore, in this paper, we propose a data model, which is able to not only express the continuous movement of moving point and moving region but also process the operation at all query time by using shape-change process and location determination functions for past and future. In addition, we apply the proposed model to forest fire management system and evaluate the validity through the implementation result.