• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3213-3230
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• 2016

Sensor node (SN) is a crucial part in any remote monitoring system. It is a device designed to monitor the particular changes taking place in its environs. Wireless sensor network (WSN) is a system formed by the set of wirelessly connected SNs placed at different geographical locations within a target region. Precise placement of SNs is appreciated, as it affects the efficiency and effectiveness of any WSN. The manual placement of SNs is only feasible for small scale regions. The task of SN placement becomes tedious, when the size of a target region is extremely large and manually unreachable. In this research article, an automated mechanism for fast and precise deployment of SNs in a large scale target region has been proposed. It uses an assembly of rotating cannons to launch the SNs from a moving carrier helicopter. The entire system is synchronized such that the launched SNs accurately land on the pre-computed desired locations (DLs). Simulation results show that the proposed model offers a simple, time efficient and effective technique to place SNs in a large scale target region.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2371-2379
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• 2017

For the drone that is active in a wide search area, the time to grasp the target in the field of applications such as searching for emergency patients, monitoring of natural disasters requiring prompt warning and response, that is, the speediness of target detection is very important. In the actual operation of drone, the time for target detection is highly related to collaboration between drones and search algorithm to efficiently search the navigation area. In this research, we will provide a search method with cooperation of drone based on target existence probability to solve the problem of quickness in drone target search. In particular, the proposed method increases the probability of finding a target and shorten the search time by transmitting high-altitude drone search results to a low-altitude drone after searching first and performing more precise search. We verify the performance of the proposed method through several simulations.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.559-561
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• 1998

항공영상이나 위성영상을 이용하는 원격 감지 기술(Remote Sensing)은 무인 비행, 지리 정보 시스템(GIS) 그리고 도시 계획에 이용되고 있다. 원격 감지 기술과 함께 사용될 수 있는 또 하나의 기술로는 자동 표적 탐색 기술이 있으며 현재 많은 연구가 진행되고 있으나, 대부분 특정적인 시험용 영상에만 적용되고 있어서 항공 영상과 같이 복잡하고 불규칙적인 경우에는 적용이 어렵다. 본 논문에서는 Distance Weighted Intensity Transformation (DWIT)와 Coefficients Filtering(CF) 방법을 이용하여 영상의 이동, 회전, 배경에 불변적인 항공 영상 표적 탐색 기법을 제안한다.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.88-92
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• 1999

As a part of work to simulate electromagnetic environments for Hardware-In-the-Loop(HIL) simulation, the dynamic trajectory is modeled by the Way-points method and the Event-driven method for the aerial and the naval targets. The simulated results show that the Way-points method and the Event-driven method are appropriate to simulate a low speed and a high speed target respectively.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.579-586
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• 2010

Due to the recent development of measuring technology and 3D programs, it has become possible to obtain various spatial data. This study utilizes the 2-dimensional data and 3-dimensional data extraction technology based on the existing empirical and statistical DB. The data obtained from geospatial data technology are integrated with civil engineering BIM to conduct the modeling of the topography of the target region and select the optimum location condition by using the cut and fill balance of the volume of earth. The target area is the land around Tamjin River, Jangheong-gun, Jeolla-do. The 3-dimensional topology linked with 3-dimensional mapping technology by using the orth-image and aerial LiDAR that uses aerial photo of the target area is visualized with Civil3D of AutoDesk. By using Civil3D program, the Thanks to the recent development of measuring technology and 3D programs, target area is analyzed through visualization and related data can be obtained for analysis. The method of using civil engineering BIM enables to obtain various and accurate information about the target area which is helpful for addressing the issues risen from the existing methodology. In this regard, it aims at searching for the alternatives and provides suggestions to utilize the information.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.199-213
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• 2022

The unsupervised domain adaptation can solve the impractical issue of repeatedly collecting high-quality training data every year for annual crop classification. This study evaluates the applicability of deep learning-based unsupervised domain adaptation models for crop classification. Three unsupervised domain adaptation models including a deep adaptation network (DAN), a deep reconstruction-classification network, and a domain adversarial neural network (DANN) are quantitatively compared via a crop classification experiment using unmanned aerial vehicle images in Hapcheon-gun and Changnyeong-gun, the major garlic and onion cultivation areas in Korea. As source baseline and target baseline models, convolutional neural networks (CNNs) are additionally applied to evaluate the classification performance of the unsupervised domain adaptation models. The three unsupervised domain adaptation models outperformed the source baseline CNN, but the different classification performances were observed depending on the degree of inconsistency between data distributions in source and target images. The classification accuracy of DAN was higher than that of the other two models when the inconsistency between source and target images was low, whereas DANN has the best classification performance when the inconsistency between source and target images was high. Therefore, the extent to which data distributions of the source and target images match should be considered to select the best unsupervised domain adaptation model to generate reliable classification results.

• Journal of the Korean Institute of Rural Architecture
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• v.24 no.1
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• pp.9-17
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• 2022

Rural spaces are increasingly valuable as areas for introducing renewable energy infrastructure to achieve carbon neutrality. Rural areas are the living grounds of rural residents, and the balance of conservation and development for rural areas is important for the introduction of reasonable facilities. In order to maintain a balance between development and preservation and to introduce reasonable renewable energy facilities, it is necessary to develop a current status survey and an effective survey method to utilize a space capable of introducing renewable energy facilities such as idle land and vacant houses. Therefore, this study was conducted to verify the readability using an unmanned aerial vehicle, and the main results are as follows. The detection of photovoltaic power generation facilities using unmanned aerial vehicles was effective in analyzing the location and area of photovoltaic panels located on the roofs of buildings, and it was possible to calculate the expected power generation by region through the area calculation of photovoltaic panels. The vacant house detection can be used to select an investigation target for an vacant house condition survey as it can identify damage to buildings that are expected to be empty houses, management status, and electricity supply facilities through aerial photos. It is judged that the unmanned aerial vehicle detection capability can be utilized as a method to improve the efficiency of investigation and supplement the data related to solar power generation facilities and vacant houses provided by public institutions. Although this study detected the status of solar power generation facilities and vacant houses through high-resolution aerial image analysis, as a follow-up study, automatic measurement methods using the temperature difference of solar power generation facilities and general characteristics of vacant houses that can be read from the air were investigated. If the deriving research is carried out, it is judged that it will be possible to contribute to the improvement of the accuracy of the detection result using the unmanned aerial vehicle and the expansion of the application range.

• Korean Journal of Computational Design and Engineering
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• v.18 no.3
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• pp.155-166
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• 2013

We present recent human-vehicle interaction (HVI) research conducted in the area of defense and military application. Research topics discussed in this paper include: training simulation for overland navigation tasks; expertise effects in overland navigation performance and scan patterns; pilot's perception and confidence on an overland navigation task; effects of UAV (Unmanned Aerial Vehicle) supervisory control on F-18 formation flight performance in a simulator environment; autonomy balancing in a manned-unmanned teaming (MUT) swarm attack, enabling visual detection of IED (Improvised Explosive Device) indicators through Perceptual Learning Assessment and Training; usability test on DaViTo (Data Visualization Tool); and modeling peripheral vision for moving target search and detection. Diverse and leading HVI study in the defense domain suggests future research direction in other HVI emerging areas such as automotive industry and aviation domain.

• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.288-298
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• 2015

For the commercialization of unmanned aircraft, we must validate the safety of the air/ground collision alert systems (CAS). The validation procedure of CAS requires the flight test which is not only expensive but also dangerous. To alleviate this problem, we need the simulation based validation process for the CAS. We developed an integrated UAV simulation (IUS) environment which interconnect the flight simulator, the Matlab/Simulink, and a target avionics simulation model. We developed the collision warning module of the TCAS and tested using IUS and flight encounter models. Using IUS, we can evaluate the performance and reliability of a target avionic system at the preliminary design stage of a development life cycle.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.134-141
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• 2019

Radar systems are divided into the pulse Doppler (PD) radar and the frequency modulated continuous wave (FMCW) radar depending on the transmission waveform. In particular, the PD radar is advantageous for long-range target detection, and the FMCW radar is suitable for short-range target detection. In this paper, we present design and implementation results for a multi-mode radar signal processor (RSP) that can support both PD and FMCW radar systems to detect unmanned aerial vehicles (UAVs) at short distances as well as long distances. The proposed radar signal processor can be implemented based on Altera Cyclone-IV FPGA with 19,623 logic elements, 9,759 registers, and 25,190,400 memory bits. The logic elements and registers of the proposed radar signal processor are reduced by approximately 43% and 30%, respectively, compared to the sum of logic elements and registers of the conventional PD radar and FMCW radar signal processor.