• Journal of Distribution Science
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• v.19 no.2
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• pp.15-24
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• 2021

Purpose: The research is to find out the perception of consumers for the convenience store (c - store) image in an emerging market, with a sample from Ho Chi Minh City. Research design, data, and methodology: Data were collected using a 24 - item structured questionnaire into six factors, namely: store atmospheric, merchandise, supplementary service, customer convenience, sales personnel, promotion. Five hundred consumers shopped at the different c - stores were collected for a multidimensional scaling technique that creates a perceptual map illustrating of c - store image. Results: The results point out that consumers' perception of a different c - store is different. The trend of c- stores are focusing on the dimensions of the function aspect. The customers also put their attention on the psychological dimension, which, in this case, is customer convenience with a sharp point. Almost all stores are bad on store atmospheric in customer- based. Conclusions: The modern retail store chains need to focus on elements to create a store image positioning and improve the perceptions of the consumers towards the store. Besides, customers not only visit the stores, not due to its convenient location, mass media or shopping experience, but also a strong identity for the store's brand image.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.47-49
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• 2022

IPS is an indoor positioning system that replaces GPS, which is less accurate due to walls and roofs inside buildings. Radio signals such as Wi-Fi are used instead of satellite signals, and complex methods are being used to increase accuracy. In this paper, we present a more efficient positioning method than before by applying high-level signals to high-accuracy fingerprint techniques. A radio map is configured with high-level signals collected by utilizing Wi-Fi APs, which are more than in the past. The suitability of use was confirmed by analyzing the pattern represented by the configured radio map for each location.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.975-981
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• 2006

This paper shows a feasibility analysis results on RFID for car positioning system. Usually, a car navigation is mainly based on GPS combined with map-matching. However, in the case of poor visibility of satellites, GPS can not supply accurate position information continuously. In recent years, RFID has been considered to be one of key technologies in positioning and localization area. But its application and research results in the area of vehicular positioning are not popular. RFID system consists of tag, reader, antenna and software such as drivers and middleware. The main function of RFID system in a vehicular positioning is to retrieve ID recorded position information from tags which set on the center of road. We propose a positioning method for vehicles using RFID and we present some indoor and outdoor experiment results to show that the proposed method is available in vehicle operational environments.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.64-69
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• 2013

Recently, users who are interested in the service at indoor spaces is increasing. An indoor positioning system can minimize a range of positioning error using a variety of wireless communication infrastructure. Also, the system improves an indoor positioning accuracy by combining a mobile communication network. However, flexible positioning technologies regardless of an environment are insufficient. Therefore, this is time for a systematic study on an indoor positioning system business model. This paper classify differences between an indoor positioning system technology and outdoor positioning system technology. And we research a construction and application of the indoor positioning system that is adapted a wireless communication system (Wi-Fi, Bluetooth, RFID, UWE, Fingerprint, etc.) in domestic and foreign. We present a successful model of indoor positioning system and the development for future systems.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.159-166
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• 2017

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.1 s.9
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• pp.71-80
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• 1997

This paper suggests a Map Accuracy Standards by analyzing U.S. National Map Accuracy Standards, by considering korean terrain feature and statistical error theory for paper and digital maps on the scale of 1:50,000. Map accuracy standards require horizontal accuracy to be reported as a circular error with 90% confidence level through Linear Error Probable(LEP) theory and Circular Error Probable(CEP) theory. In order to verify the proposed methodology for positioning accuracy testing, several kinds of test point were selected and tested. These test points were extracted at the centers of roads and bridges, the comers of the independent building, the edges of geographical botany, and the tops of mountains. The positioning accuracy assessment was peformed by comparing the positions of test points in digital maps generated three different sources with those acquired by high accurate GPS surveying. The digital maps were produced from aerial photographs and SPOT satellite image using analytical plotter and 1:50,000 paper map.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.6
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• pp.307-315
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• 2000

For the autonomy of a mobile robot it is first needed to know its position and orientation. Various methods of estimating the position of a robot have been developed. However, it is still difficult to localize the robot without any initial position or orientation. In this paper we present the method how to make the colored map and how to calculate the position and direction of a robot using the angle data of an omnidirectional image. The wall of the map is rendered with the corresponding color images and the color histograms of images and the coordinates of feature points are stored in the map. Then a mobile robot gets the color omnidirectional image at arbitrary position and orientation, segments it and recognizes objects by multiple color indexing. Using the information of recognized objects robot can have enough feature points and localize itself.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.93-97
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• 2002

In this paper, we propose personalized recommendation techniques based on multidimensional scaling (MDS) method for Business to Consumer Electronic Commerce. The multidimensional scaling method is traditionally used in marketing domain for analyzing customers' perceptional differences about brands and products. In this study, using purchase history data, customers in learning dataset are assigned to specific product categories, and after then using MDS a positioning map is generated to map product categories and alternative advertisements. The positioning map will be used to select personalized advertisement in real time situation. In this paper, we suggest the detail design of personalized recommendation method using MDS and compare with other approaches (random approach, collaborative filtering, and TOP3 approach)

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1015-1017
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• 2003

Recently, DGPS or RTK-GPS techniques enable us to use satellite based positioning systems with high accuracy. But in urban area, navigation systems suffer from problems such as signal blockage by high-rise buildings, multi-path problems, and so on. So we have to know numbers of visible satellites and quality of signals received at the ground level in urban area as accurate as possible. In this paper, we developed a simulation system called LoQAS [Location service Quality Assessment System, 2002, the University of Tokyo] which can simulate numbers of visible satellites and DOP values using accurate satellite orbital data and 3-D digital map. In this time, we evaluated this system and extended it to deal with reflected signals to assess multi-path problems.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.155-158
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• 2024

Multipath, a major error source in urban GNSS positioning (global navigation satellite system), pose a challenge due to its site-dependent nature, varying with the user's signal reception environment. In our previous study, we introduced a technique generating GNSS multipath map in urban canyon. However, due to uncertainty in initial GNSS positions, applying multipath maps required generating multiple candidate positions. In this study, we present an efficient method for applying multipath maps by projecting the multipath correction in position domain. This approach effectively applies multipath maps, addressing the challenges posed by urban user position uncertainties.