• Journal of the Korea Institute of Information and Communication Engineering
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• 제24권11호
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• pp.1528-1533
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• 2020

Recently, indoor location recognition technology using Wi-Fi fingerprints has been applied and operated in various industrial fields and public services. Along with the interest in machine learning technology, location recognition technology based on machine learning using wireless signal data around a terminal is rapidly developing. At this time, in the process of collecting radio signal data required for machine learning, the accuracy of location recognition is lowered due to distorted or unsuitable data for learning. In addition, when location recognition is performed based on data collected at a specific location, a problem occurs in location recognition at surrounding locations that are not included in the learning. In this paper, we propose a learning data preprocessing technique to obtain an improved position recognition result through the preprocessing of the collected learning data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.490-491
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• 2021

Recently, technologies using Wi-Fi fingerprints and deep learning are being studied to provide accurate location-based services in an indoor environment. At this time, the composition of learning data is very important, and it is essential to collect sufficient data necessary for learning. However, the number of specific points for the collection of radio signal data within the area requiring positioning is infinite, and it is impossible to collect all of these data. Therefore, there is a need for a way to make up for insufficient learning data. This study proposes a method of constructing a sufficient number of location data necessary for learning based on insufficiently collected location data.

• Journal of Korean Society of Transportation
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• 제27권2호
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• pp.73-82
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• 2009

Location-based concierge services (LBCS) are considered to be one of the main service functions provided in a city in ubiquitous technology spaces. A "Ubiquitous City" is defined as a city in which both public and private services can be delivered and received anywhere and anytime. One of the key elements that make location-based concierge services successful is the interoperability of location data. Currently, several existing technologies could provide LBCS including car navigation services and ubiquitous computing. However, lack of standardized structure for location data makes it impossible for heterogeneous technologies to be able to deliver uniform LBCS. The purpose of this paper is to develop standardized locational data structure so that heterogeneous technologies could provide efficient LBCS to all users of the various transportation modes.

• Journal of Digital Contents Society
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• 제19권8호
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• pp.1617-1623
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• 2018

It is necessary to develop a next generation location referencing method with higher accuracy as advanced technologies such as autonomous vehicles require higher accuracy of location data. Thus, we proposed a framework for a lane-level location referencing method (L-LRM) based on high-precision digital road network map, and developed a tool which is capable of analyzing and evaluating the proposed method. Firstly, the necessity and definition of location referencing method was presented, followed by the proposal of an L-LRM framework with a fundamental structure of high-precision digital road network map for the method. Secondly, an architecture of the analysis and evaluation tool was described and then the Windows application program was developed using C/C++ programming language. Finally, we demonstrated the performance of the proposed framework and the application program using two different high precision digital maps with randomly generated road event data.

• The KIPS Transactions:PartD
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• 제9D권5호
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• pp.827-836
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• 2002

Moving object management systems manage spatiotemporal data, which change their location over tine such as people, animals, and cars. These moving object management systems can be applied to vehicle location tracking, digital battlefield, location-based service, and so on. The existing moving object management systems only manage past or future location of the moving objects separately. Therefore, they cannot suggest estimation method of uncertain past or future location of the moving objects. In this paper, we propose a moving object management system, which not only manages historical data of the moving objects, but also predicts past and future location of the moving objects using historical data stored in database. We define the moving objects for vehicle location tracking and propose a moving object database structure. Finally, we suggest an execution model of the proposed system and apply the execution model to a virtual scenario for vehicle tracking.

• Journal of the Korea Computer Industry Society
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• 제6권3호
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• pp.495-508
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• 2005

Moving objects are spatiotemporal data that change their location or shape continuously over time. Their location coordinates are periodically measured and stored i3l the application systems. The linear function is mainly used to estimate the location information that is not in the system at the query time point. However, a new method is needed to improve uncertainties of the location representation, because the location estimation by linear function induces the estimation error. This paper proposes an application method of the cubic spline interpolation in order to reduce deviation of the location estimation by linear function. First, we define location information of the moving object on the two-dimensional space. Next, we apply the cubic spline interpolation to location estimation of the proposed data model and describe algorithm of the estimation operation. Finally, the precision of this estimation operation model is experimented. The experimentation comes out more accurate results than the method by linear function.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.293-298
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• 2003

This study deals with the source location method of defect which can be occurred in structure. The existing methods was very difficult to be applied to predict it because of using very complex numerical formula. The triangulation method which was proposed in his study can predict the source location predicted easily with small amount of data. Wave arrival time data can be directly converted into source-sensor distance is known. For this purpose, the propagation velocity was measured by Rayleigh wave, and the propagation behavior was analyzed. For the consideration of jointed part in structure, the source location method was applied to the welded workpiece. The signal propagation velocity was measured in welding part for the purpose of application to the part and the revised algorithm of source location was proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제18권10호
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• pp.2523-2529
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• 2014

Location estimation service can be provided outdoors using various location estimation system based on GPS. However, location estimation system is based on existing indoor resources as GPS cannot be used because of insufficient visible satellites and weak signals. The fingerprinting technique that uses WLAN signal, in particular, is good to use indoors because it uses RSSI provided by AP to estimate location. However, its accuracy may vary depending on how accurate data the offline stage used where the fingerprinting map is built. The study sampled various data at the stage that builds the fingerprinting map and suggested a location estimation system that enhances its precision by saving the data of high frequency among them to improve this problem. The suggested location estimation system based on majority sampling data estimates location by filtering RSSI data of the highest frequency at the client and server to be saved at a map, building the map and measuring a similar distance. As a result of the test, the location estimation precision stood at minimum 87.5 % and maximum 90.4% with the margin of error at minimum 0.25 to 2.72m.

• Journal of Environmental Health Sciences
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• 제42권5호
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• pp.314-323
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• 2016

Objectives: Time location data are critical for accurately estimating personal exposures. This review papers summarized various measurement methods of time location pattern for air pollution exposure assessment. Methods: Forty manuscripts (papers, books and reports) were reviewed to comprehensively describe time location measurement methods. Results: This review included traditional methods such as time activity diary, questionnaire, observation, focus group and newly developed technical methods including global positioning system, web, radio frequency identification and ultrasound detection. Some research applied a combination of methods. Conclusion: Although various methods have been used to collect time location data, further development of accurate measurement methods for time location data is needed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국정보통신학회 2015년도 추계학술대회
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• pp.270-271
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• 2015

Recently, There is Increasing interest in the intelligent services using the Internet of Things indoor positioning technologies that enable the communication of information between the objects. In particular Applications and demand for the indoor location based services using smart devices has made active. An indoor location positioning technology for this purpose BLE (Bluetooth Low Energy) has been a lot of interest in technology increases. If iBeacon of BLE(Bluetooth Low Energy) is made available to provide a signal for the indoor location information measurement then reliability of Indoor location information is lowered by signal interference. In this paper, Proposes a technique for data acquisition method for obtaining reliable position information and reliable position information calculation method from signal information data of iBeacon.