• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.169-173
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• 2020

Location-based services are used as core services in various fields. In particular, in the field of public services such as emergency rescue, accurate location estimation technology is very important. Recently, the technology of tracking the location of self-isolation subjects for COVID-19 has become a major issue. Therefore, location estimation technology using personal smart devices is being studied in various ways, and the most widely used method is to use GPS. Other representative methods are using Wi-Fi, Pedestrian Dead Reckoning (PDR), Bluetooth Low Energy (BLE) beacons, and LTE signals. In this paper, we introduced a positioning technology using deep learning based on LTE Channel State Information-Reference Signal (CSI-RS) data, and confirmed the possibility through an outdoor location estimation experiment using a commercial LTE signal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.558-560
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• 2009

Ad hoc could be very important in the location-based technology, much research could work underway in these days. In this paper, the property of based on RSSI (Received signal strength indicator) could extract information. A distance of self-made nodes testing were implemented for an each other between given nodes. A special purpose UoC (ubiquitous of System On Chip) system was developed in this paper. This system could provide a function of RSSI property for location information experiments. This attribute information could make possible LBS (Location-Based System) experiment for ranging technique in this development system. The experiment results could show a possibility performance delivery ratio and the number of hops. This given performance of the location information could be used to acquire a ranging technique in large number of nodes network system.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.99-106
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• 2019

Technology that cannot be excluded from 4th industry is self-driving sector. The self-driving sector can be seen as a key set of technologies in the fourth industry, especially in the DB sector is getting more and more popular as a business. The DB, which was previously produced and managed in two dimensions, is now evolving into three dimensions. Among the data obtained by Mobile Mapping System () to produce the HD MAP necessary for self-driving, Point Cloud, which is LiDAR data, is used as a DB because it contains accurate location information. However, at present, it is not widely used as a base data for 3D modeling in addition to HD MAP production. In this study, MMS Point Cloud was used to extract facilities around the road and to overlay the location to expand the usability of Point Cloud. Building utility poles and communication poles DB from Point Cloud and comparing road name address base and location, it is believed that the accuracy of the location of the facility DB extracted from Point Cloud is also higher than the basic road name address of the road, It is necessary to study the expansion of the facility field sufficiently.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.49.6-49
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• 2001

This paper describes a self-localization method for the mobile robot using panoramic view images. A panoramic view image has the information of location of the objects from the viewer robot and direction between the objects at a position. Among the sequence of panoramic view images, the target objects in the image like traffic signs, facade of a building, road signs, etc. locate in the real world so that robot´s position and direction deliver to localize from his view. With the previously captured panoramic images, the method calculates the distance and direction of the region of interest, corresponds the regions between the sequences, and identifies the location in the world. To obtain the region, vertical edge line segments

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.64-77
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• 2022

The advent of location-based social networks (LBSNs), and the pervasive use of smartphones have allowed individuals to easily inform their status through locational information. This led to a new trend in social media: to upload geotagged photos that illustrate the location of the images and then share them with others. In this circumstance, the current study aims to examine the use of geotags on Instagram. Further, the motivations for using geotags as well as the relationship among the motivation, satisfaction, and location information sharing behavior are analyzed. The online survey was conducted on 411 respondents of Hong Kong who are active Instagram users. Based on uses and gratification theory and goal theory, the users' motivations and goals for utilizing geotags were divided into mainly two categories; task-involved and self-involved goals. Then, four different motivations (contribution, memory aid, showing off, and reputation gaining) were further examined. The result indicated that contribution, memory aid, and reputation gaining were the goals and motivation for the users to utilize geotags on Instagram, having a positive impact on satisfaction. However, a positive relationship between showing off and geotag satisfaction was not supported. Among four different factors, memory aid was found to have the strongest influence on geotagging satisfaction. The result of testing the relationship between geotag satisfaction and further location information sharing behavior also turned out to have a positive relationship. The implications and limitations of findings are also discussed in the study.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.654-662
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• 2016

With the advent of autonomous cars, we explored the problems which will soon arise while parking in car parks. These include structure of parking lot suitable for autonomous cars, finding the closest parking slot available, and navigation to the location. We provide an initial solution, wherein we use a central server and the graph of the parking lot to guide cars to the closest parking slots available. Our experiments have shown that the proposed method is effective for the controlled parking for self-driving cars.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.297-300
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• 2005

In this study, we proposed genetically optimized self-organizing fuzzy polynomial neural network based on information granulation and evolutionary algorithm (gdSOFPNN), develop a comprehensive design methodology involving mechanisms of genetic optimization. The proposed gdSOFPNN gives rise to a structural Iy and parametrically optimized network through an optimal parameters design available within FPN (viz. the number of input variables, the order of the polynomial, input variables, the number of membership functions, and the apexes of membership function). Here, with the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The performance of the proposed gdSOFPNN is quantified through experimentation that exploits standard data already used in fuzzy modeling.

• Journal of Science and Technology Studies
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• v.16 no.2
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• pp.1-31
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• 2016

This essay examines the recent proliferation of location-based services (LBS) within the context the expansion of the technologies of remote identification, monitoring, and tracking. Following the spatial turn in the social sciences, this essay aims to analyze LBS as a surveillance technology that can re-shape the spatial configuration of its users and their identity. The analytic focus of this essay is on LBS within the global information infrastructure, and it utilizes key LBS examples in the US and South Korea. First, as a way to discuss the technical possibilities of LBS for spatial coordination and surveillance, this essay investigates its technical architecture in terms of information flow. It then discusses the issue of privacy in LBS by analyzing some of its key legal and regulatory issues. The combination of the global information infrastructure with location-related technologies has enabled LBS companies to expand the scope of surveillance over the ever-increasing computer-mediated activities, prompting heated discussions over whether LBS is capturing "Every Moment in Your Life." This essay concludes with a discussion on how location technologies have provided a key platform for the rise of surveillance capitalism through the creation of what Marc $Aug{\acute{e}}$ called a "non-place," a place where the identified self is constituted by LBS.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.5
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• pp.129-140
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• 2014

BIST(Built-in self test) is to detect various faults of the existing memory and BIRA(Built-in redundancy analysis) is to repair detected faults by allotting spare. Also, BISR(Built-in self repair) which integrates BIST with BIRA, can enhance the whole memory's yield. However, the previous methods were suggested for RAM and are difficult to diagnose disturbance that is NAND-type flash memory's intrinsic fault when used for the NAND-type flash memory with different characteristics from RAM's memory structure. Therefore, this paper suggests a BISD(Built-in self diagnosis) to detect disturbance occurring in the NAND-type flash memory and to diagnose the location of fault, and BISR to repair faulty blocks.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.752-759
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• 2008

In this paper, we propose a high accurate geo-location system based on a single base station, where its location is obtained by Time-of-Arrival(ToA) and Direction-of-Arrival(DoA) of the radio signal. For estimating accurate ToA and DoA information, a MUltiple SIgnal Classification(MUSIC) is adopted. However, the estimation of ToA and DoA using MUSIC algorithm is a time-consuming process. The position tracking bias is occurred by the time delay caused by the estimation process. In order to mitigate the bias error, we propose the estimation method of the position tracking bias and compensate the location error produced by the time delay using the position tracking bias mitigation. For accurate self-localization of mobile robot, the Unscented Kalman Filter(UKF) with position tracking bias is applied. The simulation results show the efficiency and accuracy of the proposed geo-location system and the enhanced performance when the Unscented Kalman Filter is adopted for mobile robot application.