• Journal of Korean Society of Rural Planning
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• v.10 no.2 s.23
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• pp.35-42
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• 2004

This study aimed at establishing the multi-ranged approach on data acquisition technique for rural landscape planning, which tried categorization, grading and transferring of landscape elements in the more detailed level. For the systematic management of database for the topographic informations in the village level, a kind of the aerial photographing techniques with UAV(Unmanned Aerial Vehicle) was used and its resultant data for the landscape simulation of the rural village, which in turn helped the convenient approach to understanding of its comprehensive spatial structure. The image data from aerial photography was systematically processed through; First, after revision of the distorted one, the image map was adjusted with the topographical and cadastral maps. Second, the farm houses and buildings, and other facilities difficult to find out in the topographical map was digitally read from the adjusted image. The topographical landscape view of rural village was simulated on the base of DEM(Digital Elevation Model) and the 3-dimensional shapes of farm houses and buildings were automatically modelled using the input system developed by the author. In conclusion, the aerial image information adjusted with the edited maps could give more intuitive and detailed villagescape than the ordinary one and through landscape simulation of the rural village, its topography, features of houses/buildings and spatial distribution of land uses were effectively reproduced. And, by the linkage between field survey and photographed/simulated results of the typical landscape elements using hyper-link method, it would be expected to develop as an effective visualization technique of rural landscape.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.279-286
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• 2018

In the civil works, the measurement of earth-volume is one of the important elements in the estimation of the reasonable construction cost. Related studies mainly used GPS (Global Positioning System) or total station to obtain information on civil work areas. However, these methods are difficult to implement in inaccessible areas. Therefore, the aim of this paper is to use the UAV (Unmanned Aerial Vehicle) to measure the earth-volume. The study area is located in a reservoir construction site in Sangju-si, Gyeongsangbuk-do, Republic of Korea. We compared the earth-volume amounts acquired by UAV-based surveying to ones acquired by total station-based and GPS-based surveying, respectively. In the site, the amount of earth-volume acquired by GPS was $147,286.79m^3$. The amount of earth-volume acquired by total station was $147,286.79m^3$, which is the 96.13% accuracy compared to the GPS-based surveying. The earth-volume obtained by UAV was $143,997.05m^3$ when measured without GCPs (Ground Control Points), $147,251.71m^3$ with 4 GCPs measurement, and $146,963.81m^3$ with 7 GCPs measurement. Compared to the GPS-based surveying, 97.77%, 99.98%, and 99.78% accuracies were obtained from the UAV-based surveying without GCP, 4 GCPs, and 7 GCPs, respectively. Therefore, it can be confirmed that the UAV-based surveying can be used for the earth-volume measurement.

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.2
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• pp.135-161
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• 2014

An unmanned aerial vehicle (UAV), commonly known as a drone and also referred to as an unpiloted aerial vehicle and a remotely piloted aircraft (RPA) by the International Civil Aviation Organization (ICAO), is an aircraft without a human pilot aboard. ICAO classify unmanned aircraft into two types under Circular 328 AN/190. Unmanned aircraft, which is the core of the development of the aviation industry. However, there are also elements of the legal dispute. Unmanned aircraft are manufactured in small size, it is possible to shoot a record peripheral routes stored in high-performance cameras and sensors without the consent of the citizens, there is a risk of invasion of privacy. In addition, the occurrence of the people of invasion of privacy is expected to use of civilian unmanned aircraft. If the exposure of private life that people did not want for unmanned aircraft has occurred, may occur liability to the operator of unmanned aircraft, this is a factor to be taken into account for the development of unmanned aircraft industry. In the United States, which is currently led by the unmanned aircraft industry, policy related to unmanned aircraft, invasion of privacy is under development, is preparing an efficient measures making. Unmanned aircraft special law has not been enforced. So there is a need for legal measures based on infringement of privacy by the unmanned aircraft. US was presented Privacy Protection Act of unmanned aircraft (draft). However Korea has many laws have been enacted, to enact a new law, but will be able to harm the legal stability, there is a need for the enactment of laws for public safety of life. Although in force Personal Information Protection Law, unmanned aerospace, when the invasion of privacy occurs, it is difficult to apply the Personal Information Protection Law. So, it was presented a privacy protection bill with infringement of privacy of unmanned aircraft in the reference US legislation and the Personal Information Protection Act.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.27-33
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• 2020

Recently, visual object detection and tracking has become a vital role in many different applications. It spans various applications like robotics, video surveillance, and intelligent vehicle navigation. Especially, in current situation where the use of UAVs is expanding widely, detection and tracking to soot down illegal UAVs flying over the sky at airports, nuclear power plants and core facilities is becoming a very important task. The remarkable method in object tracking is correlation filter based tracker like KCF (Kernelized Correlation Filter). But it has problems related to target drift in tracking process for long-term tracking. To mitigate the target drift problem in video surveillance application, we propose a tracking method which uses KCF, adaptive thresholding and Kalman filter. In the experiment, the proposed method was verified by using monochrome video sequences which were obtained in the operational environment of UAV.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.5
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• pp.391-400
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• 2017

Italian ryegrass (IRG) is one of the fastest growing grasses available to farmers. It offers rapid establishment and starts growing early in the following spring and has fast regrowth after defoliation. So, IRG can be utilized as the dominant/single species of grass used in a farming system, or to play a role as a large producing pasture and sacrificial paddock. The objective of this study was to develop the use of unmanned aerial vehicle (UAV) for the evaluation of feed value of IRG. For this study, UAV imagery was taken on the Nonsan regions two times during the IRG growing season. We analyzed the relationships between $NDVI_{UAV}$ and feed value parameters such as fresh matter yield, dry matter yield, acid detergent fiber (ADF), neutral detergent fiber (NDF), total digestible nutrient (TDN) and crude protein at the season of harvest. Correlation analysis between $NDVI_{UAV}$ and feed value parameters of IRG revealed that $NDVI_{UAV}$ correlated well with crude protein (r = 0.745), and fresh matter yield (r = 0.655). According to the relationship, the variation of $NDVI_{UAV}$ was significant to interpret feed value parameters of IRG. Eight different regression models such as Linear, Logarithmic, Inverse, Quadratic, Cubic, Power, S, and Exponential model were used to estimate IRG feed value parameters. The S and exponential model provided more accurate results to predict fresh matter yield and crude protein than other models based on coefficient of determination, p- and F-value. The spatial distribution map of feed values in IRG plot was in strong agreement with the field measurements in terms of geographical variation and relative numerical values when $NDVI_{UAV}$ was applied to regression equation. These lead to the result that the characteristics of variations in feed value of IRG according to $NDVI_{UAV}$ were well reflected in the model.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.213-217
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• 2006

An intelligent performance diagnostic program using the Neural Network was proposed for PW206C turboshaft engine. It was selected as a power plant for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle) which has been developed by KARI (Korea Aerospace Research Institute). For teaming the NN, a BPN with one hidden, one input and one output layer was used. The input layer had seven neurons of variations of measurement parameters such as SHP, MF, P2, T2, P4, T4 and T5, and the output layer used 6 neurons of degradation ratios of flow capacities and efficiencies for compressor, compressor turbine and power turbine. Database for network teaming and test was constructed using a gas turbine performance simulation program. From application results for diagnostics of the PW206C turboshaft engine using the learned networks, it was confirmed that the proposed diagnostics algorithm could detect well the single fault types such as compressor fouling and compressor turbine erosion.

• Journal of Advanced Navigation Technology
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• v.19 no.3
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• pp.217-223
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• 2015

This paper describes the design and implementation of a network system for UAV for multiple clients that enables long-range operation based on a commercial mobile network. A prototype data modem is developed with a commercial embedded M2M module in order to provide an access to the mobile network. A central server with a database is constructed to record all of real-time flight and video data and communicate with a ground control system. A GCS is developed for the central control, the single UAV and the smart phone version to be used for different purposes. Performance tests were progressed for data delay, video frame rate and state of clients. Flight tests were also performed to verify the reliability of the modem with respect to altitude.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.4
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• pp.266-269
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• 2018

A compact Q-band waveguide-to-microstrip transition for UAV(Unmanned Aerial Vehicle) radiometer applications is presented. The key features of this transition are simplicity, compactness, easy matching, and lower sensitivity to the dimensions and fabrication tolerances. The simple E-plane patch-type design is insensitive to the backshort cavity enclosure and misalignment between the waveguide and microstrip substrate. The primary parameters are optimized using a three-dimensional(3D) electromagnetic simulator(ANSYS HFSS). It exhibited better than 20-dB return loss at mid-band frequencies with less than 1-dB insertion loss for the back-to-back transition, and a return loss better than 15 dB over the frequency range of 36 GHz to 42 GHz.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.6
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• pp.468-477
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• 2014

In this research, how a solar powered HALE (high altitude long endurance) UAV (Unmanned Aerial Vehicle) can climb and reach mission altitude, 18km, starting from the ground using only solar energy. A glider type aircraft was assumed as a baseline configuration which has wing area of $35.98m^2$ and aspect ratio of 25. Configuration parameters, lift and drag coefficients were calculated using OpenVSP and XFLR5 that are NASA open source programs, and climb flights were predicted through energy balance between available energy from solar power and energy necessary for a climb flight. Minimum time climb flight was obtained by minimizing flight velocities at each altitude and total time and total energy consumption to reach the mission altitude were predicted for different take off time. Also, aircraft moving distances due to westerly wind and flight speed were calculated.

• 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.