• Journal of the Korean Society of Costume
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• v.58 no.9
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• pp.114-128
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• 2008

The current study aims to classify types of traditional fur Garments in Jeju into Dusik(hat), dress, Jokui(socks) and accessaries, and examine characteristics of them through demonstrative study focusing on collections of museums in Jeju. Dusik is a kind of hat for protection against the cold, and there are badger leather Gamtaes and cow hair Beonggeojis(fur hats). Especially leather gamtae was used to protect against the cold when people hunted roe deers in Mt. Halla. Beonggeoji was producted in the form of felt with fine hair collected coat-shedding of cows and dogs in spring, therefore it was too warm and practical to be damaged from storm or pressure. Fur coat is a general name of dress made of leather without hair. It is a kind of clothes with a hat worn while taking care of horses and cows. Also people wore dog leather topcoats and cow leather topcoats when they hunted in Mt. Halla. As for Jokui, there are leather Beoseon(socks) made of cow leather, leather shoes in the form of straw shoes, and leather Balle embracing the low half of the body warmly. Accessaries include a rectangular cow leather bag for storing an iron piece for making fire. These traditional fur robs in Jeju not only have practicality for protection against the cold, but also symbolized richness by using leathers of badgers, roe deers, etc. that were previous during that times. Also they used partially cut leather for decoration at the edge.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.3
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• pp.131-140
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• 2015

Antennas at permanent GPS stations operated by the former Ministry of Government Administration and Home Affairs (MOGAHA) in Korea were replaced in years 2008 and 2009, and these changes caused abrupt discontinuities in precise coordinate time series. In this study, an algorithm that eliminates those breaks was developed based on 15-year-long coordinate time series for the purpose of creating clean and continuous coordinate time series. The newly developed algorithm to correct for sudden jumps and dips in the GPS time series due to the antenna change was designed to consider all the linear and annual signals observed before and after the event. The accuracy of the new algorithm was confirmed to be at the Root Mean Square Error (RMSE) level of 2.3-2.6 mm. The new algorithm was also found to be capable of reflect site-specific characteristics at each station.

• Journal of Positioning, Navigation, and Timing
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• v.4 no.2
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• pp.87-95
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• 2015

In this study, the temporal and spatial variation in precipitable water vapor (PWV) was analyzed for typhoon Ewiniar which had made landfall in the Korean peninsula in 2006. To make a contour map of PWV, zenith total delay (ZTD) was calculated using about 60 GPS permanent stations in Korea, and the pressure and temperature data of nearby AWS stations were interpolated and applied to the equation for calculating the PWV. While Typhoon Ewiniar was migrating north from the southern coast to the eastern coast of Korea, the PWV migrated showing a spatial distribution similar to that of rainfall. Also, the fluctuating pattern of the normalized PWV was analyzed, and the moving speed of the PWV was estimated using the delay time of the increase/decrease pattern in the eight-test stations. The result indicated that the moving speed of the PWV was about 35 km/h, which was similar to the average moving speed of the typhoon (38.9 km/h).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.2
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• pp.133-140
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• 2015

In this paper, a roll angle estimation method of a rolling airframe using a low grade GPS and a roll rate gyro is proposed. The strength of the received signal of the GPS antenna attached on the rolling airframe is maximized when the GPS satellite is placed on the plane determined by the x-axis of the rolling airframe and the GPS antenna axis. Under the assumption that the x-axis of the rolling airframe is coincident with its velocity vector, the roll angle of the rolling airframe is calculated from the relative position vector of the satellite to the GPS when the GPS signal strength becomes maximum. The Kalman filter combined with a roll rate gyro is introduced to increase the determination accuracy of the roll angle. The performance of the proposed method is verified via 6-DOF simulations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.559-568
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• 2016

For the economic management of photovoltaic power plants, it is necessary to regularly monitor the panels within the plants to detect malfunctions. Thermal infrared image cameras are generally used for monitoring, since malfunctioning panels emit higher temperatures compared to those that are functioning. Recently, technologies that observe photovoltaic arrays by mounting thermal infrared cameras on UAVs (Unmanned Aerial Vehicle) are being developed for the efficient monitoring of large-scale photovoltaic power plants. However, the technologies developed until now have had the shortcomings of having to analyze the images manually to detect malfunctioning panels, which is time-consuming. In this paper, we propose an automatic photovoltaic panel area extraction algorithm for thermal infrared images acquired via a UAV. In the thermal infrared images, panel boundaries are presented as obvious linear features, and the panels are regularly arranged. Therefore, we exaggerate the linear features with a vertical and horizontal filtering algorithm, and apply a modified hierarchical histogram clustering method to extract candidates of panel boundaries. Among the candidates, initial panel areas are extracted by exclusion editing with the results of the photovoltaic array area detection. In this step, thresholding and image morphological algorithms are applied. Finally, panel areas are refined with the geometry of the surrounding panels. The accuracy of the results is evaluated quantitatively by manually digitized data, and a mean completeness of 95.0%, a mean correctness of 96.9%, and mean quality of 92.1 percent are obtained with the proposed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.90-95
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• 2018

The Korean Peninsula is no longer safe from volcanic disasters. Therefore, the Korean government has been developing a spatial information-based system implementation technology since 2014. VDRS (Volcanic Disaster Response System), which is the result of the technology, was implemented in 2016 as Phase I. Since then, phase II implementation technology has been developed for an advanced system reflecting the user's requirements. To advance the system, redesign architecture is essential. This paper examined the redesign application architecture for an advanced VDRS. First, existing application architecture, which was implemented in phase I, was analyzed. Second, the user's requirements for advanced VDRS were analyzed. The analyzed user's requirements were categorized as a transforming service oriented to a business-oriented architecture, improving accuracy, and expanding the spatial range and target disaster. Third, application architecture was redesigned based on gap analysis between the existing architecture and user's requirements. The results of the proposed redesign architecture are presented as the application system structure and description of the application function based on owner's point of view in the enterprise architecture. The results of this paper can be used to derive the application module design and provide a detailed description of the application module based on the designer's point of view. Further research focused on structuring the HW/SW architecture will be required for system implementation.

• Journal of Navigation and Port Research
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• v.36 no.10
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• pp.825-832
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• 2012

GPS signal delay that caused by dry gases and water vapor in troposphere is a main error source of GPS point positioning and it must be eliminated for precise point positioning. In this paper, we implemented to generate tropospheric delay grid map over the Korean Peninsula based on post-processing method by using the GPS permanent station network in order to determine the availability of tropospheric delay generation algorithm. GIPSY 5.0 was used for GPS data process and nationwide AWS observation network was used to calculate the amount of dry delay and wet delay separately. As the result of grid map's accuracy analysis, the RMSE between grid map data and GPS site data was 0.7mm in ZHD, 7.6mm in ZWD and 8.5mm in ZTD. After grid map accuracy analysis, we applied the calculated tropospheric delay grid map to single frequency relative positioning algorithm and analyzed the positioning accuracy enhancement. As the result, positioning accuracy was improved up to 36% in case of relative positioning of Suwon(SUWN) and Mokpo(MKPO), that the baseline distance is about 297km.

• Journal of Navigation and Port Research
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• v.39 no.1
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• pp.7-13
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• 2015

The number of mobile terminals equipped with a GPS module is steadily increasing today. However, because they using code pseudorange measurements in positioning, the positioning accuracy of mobile terminals is lower than that of those receivers using carrier phases. Especially, the multipath signal causes more significant errors in code pseudoranges. Therefore, the techniques of multipath detection and elimination is necessary. In this study, as an initial analysis of multipath detection and elimination technique development, we tested the feasibility of multipath signal detection using GPS signal strength information. We found that the GPS signal strength increases as the elevation angle gets higher in the open-sky environment. Also, we found that the signal strength decreases when there were some signal reflectors nearby. We checked the repeatability of the signal strength variation characteristics by reflecting repeat time of GPS satellites. As a result, this characteristics repeats almost perfectly when GPS satellites pass the same orbit. Therefore, we found that it is not a temporary phenomenon and the multipath signal detection should be possible by using GPS signal strength information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.619-627
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• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.415-423
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• 2021

Citizen participation and Living Lab are attracting interest as one of the major strategies for the success of smart cities. In a Living Lab, citizens, who are the end-users of technology, participate in the search for alternatives to define and solve problems and repeat experiments to verify alternatives in a circular process. The purpose of this research was to present an operating model of a citizen-participating online community platform to improve urban problems, implement and test it, and show its applicability. To this end, an operation model of a citizen-participating online community platform was proposed to improve urban problems. An online platform was designed and implemented to reflect the functions pursued by the operation model. Finally, a pilot test for the function was performed using the Oma Elementary School case located in Ilsan, Goyang-si, Gyeonggi-do. The operating model was designed with the city's pedestrian environment and children. As a result, the sharing and communicating process of urban issues among community members worked appropriately according to the designed intention. The Living Lab coordinator could visualize and view urban issues posted by users on a map based on location information. Visualizing the urban problem as a heat map confirmed that urban problems were concentrated in a specific area.