• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.709-711
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• 2005

Developing fault location system for underground power cable which can detect its fault location exactly require very high speed data acquisition and signal processing capability. We are developing fault location system which is different from conventional fault locator. This fault location system monitor underground power cable by using on-line speed current sensor and if there are an accident, it record its transient signal and calculate fault location by analyzing it. Signals which acquired when power cable fault arise, showed transient characteristics and its frequency band is very hish. So, to develop fault location system, we designed special high speed data acquisition and signal processing board. In this thesis, we describe on data acquisition and signal processing H/W design for fault location system on underground power cable.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.606-608
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• 2005

In this paper, we introduce localization server system calculated real location of objects using raw data of location-awareness from sensor node gateway. The software architecture of localization server system consists of location calculation and actuator control based on location. Also, this system supports for collecting raw data, calculating location of real objects using raw data, correcting error from outer environment, and server for applications based on location.

• Journal of Information Technology Services
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• v.9 no.1
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• pp.127-139
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• 2010

Due to the development of information technology and business related to geographical location of customer, the need for the storage and analysis of geographical location data is increasing rapidly. Geographical location data have a spatio-temporal nature which is different from typical business data. Therefore, different methods of data storage and analysis are required. This paper proposes a multi-dimensional data model and data visualization to analyze geographical location data efficiently and effectively. Purchase order data of an online farm products brokerage business was used to build prototype datamart. RFM scores are calculated to classify customers and geocoding technology is applied to display information on maps, thereby to enhance data visualization.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.115-121
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• 2007

Recently, Location Based Service including tracking and way-finding services has been activated rapidly in the ubiquitous computing environment. According as the ubiquitous computing environment is developed, various types of sensor to acquire various data including location of the moving object are used widely, and acquired sensor data becomes abundant. However, the existing location management system based on a single location sensor is difficult to support LBS efficiently in the ubiquitous computing environment. In this paper, therefore, we propose the location management system in the ubiquitous computing environment that can manage the location data and the various sensor data efficiently. In addition, the location management system adopts the core technology for efficiently storing and transferring a large-volume of various data such as location data and for efficiently processing the various requests from a variety of servers and sensors. Especially, our architecture that is presented in this paper can support context-aware services and autonomous services efficiently in the ubiquitous computing environment.

• 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.

• Environmental Analysis Health and Toxicology
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• v.28
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• pp.5.1-5.7
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• 2013

Objectives Despite increasing availability of global positioning system (GPS), no research has been conducted to analyze GPS data for exposure opportunities associated with time at indoor and outdoor microenvironments. We developed location-based and time-weighted spatial measures that incorporate indoor and outdoor time-location data collected by GPS. Methods Time-location data were drawn from 38 female subjects in California who wore a GPS device for seven days. Ambient standard deviational ellipse was determined based on outdoor locations and time duration, while indoor time weighted standard deviational ellipse (SDE) was developed to incorporate indoor and outdoor times and locations data into the ellipse measure. Results Our findings indicated that there was considerable difference in the sizes of exposure potential measures when indoor time was taken into consideration, and that they were associated with day type (weekday/weekend) and employment status. Conclusions This study provides evidence that time-location weighted measure may provide better accuracy in assessing exposure opportunities at different microenvironments. The use of GPS likely improves the geographical details and accuracy of time-location data, and further development of such location-time weighted spatial measure is encouraged.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.676-678
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• 2003

Recently, in according as rapid improvement of telecommunication markets and wireless internet technology, Location- Based Services (LBS) have been discussed as new 'Killer' application. The purpose of LBS is to determine location of user through mobile handset and to offer location information service to end-user. This paper has suggested an efficient transmission scheme of maps data as one of the important content services relating to data transmission of LBS in mobile environment. The basic system consists of three parts : (1) GIS (Geographic Information System) Server for storing, processing and handling map data, (2) Middleware Server for transmitting of map data by request of client, and (3) Client for requesting map data to Server and displaying them on handset. Also, in order to transmit map data, we are to expand WKB (Well Known Binary) in conformance to Simple Feature Specification of OGC (Open GIS Consortium), and increase efficiency of data transmission by developing trans mission data format to be able to transmit lightweight data and considering data compression technology.

• Journal of Internet Computing and Services
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• v.11 no.4
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• pp.85-94
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• 2010

In this paper, we propose a location-prediction structure that can provide user service in advance. It consists of seven steps and supplies intelligent services which can forecast user's location. Context information collected from physical sensors and a history database is so difficult that it can't present importance of data and abstraction of data because of heterogeneous data type. Hence, we offer the location-prediction that change data type from heterogeneous data to homogeneous data. Extracted data is clustered by SOFM, then it gets user's location information by ARIMA and realizes the services by a reasoning engine. In order to validate the proposed location-prediction, we built a test-bed and test it by the scenario.

• The Journal of Information Systems
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• v.14 no.3
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• pp.17-22
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• 2005

Location management is very important in location-based services to provide services to the mobile users like banking, city guides and many more. Ubiquitous and mobile devices are the source of data in location management and its significant operations are update and search method. Some studies to improve these were presented by using optimal sequential paging, location area scheme and hierarchical database scheme. In addition, not all location services have the same access methods on data and it lead to difficulties of providing services. A proposed location management of multi-agent architecture is presented in this study. It shows the coordination of the agents on the distributed database of location-based services. The proposal focuses on the location management of the mobile object presented in a hierarchical search and update. Also, it uses a nearest neighbor technique for efficient search method of mobile objects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1951-1966
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• 2020

Recent advancements in mobile device technology have enabled real-time positioning so that mobile patterns of people and favorable locations can be identified and related researches have become plentiful. One of the fields of research is the relationship between the object properties and the favored location to visit. The object properties of a person include personality, which is a major property jobs, income, gender, and age. In this study, we analyzed the relationship between the human personality and the preference of the location to visit. We used Spearman's Rank correlation coefficient, one of the many methods that can be used to determine the correlation between two variables. Instead of using actual data values, Spearman's Rank correlation coefficient deals with the ranks of the two data sets. In our research, the personality and the location data sets are used. Our personality data is ranked in five ranks and the location data is ranked in 8 ranks. Spearman's Rank correlation coefficient showed better results compared to Pearson linear correlation coefficient and Kendall rank correlation coefficient. Using Spearman's correlation coefficient, the degree of the relationship between the personality and the location preference is found to be 43%.