• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.86-93
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• 2016

Information technology, such as IoT, Big Data, Drone, Cloud etc., is evolving every year. Information Society is changing Intelligence Society and Creative Society. A new Construction Projects Management System Roadmap is required because it is difficult to reflect the current IT environments based on the CALS(Continuous Acquisition & Life-cycle Support) master plan, which is performed to establish every five years since 1998. This study was prepared for the Roadmap with a focus on Construction Management System based on the 4th CALS master plan, which was performed to establish the 2012 year. To this end, the construction environment and several information systems were investigated and analyzed. The problems of the construction project information system were derived using SWOT analysis, the vision, goal, direction, strategy, main tasks, specific tasks, and timetable of the Construction Project Management System are presented. This roadmap is designed to be used as operational indicators of a future construction project management system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.469-476
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• 2021

An electronic attack (EA) system is an essential weapon system for performing electronic warfare missions that contain signal tracking and jamming against multiple threats using electromagnetic waves, such as air defense radars, wireless command and communication networks, and guided missiles. The combat effectiveness can be maximized, and the survivability of militarily protecting combat power can be enhanced through EA mission operations, such as disabling the functions of multiple threats. The EA system can be used as a radio frequency jamming system to respond to drone attacks on the core infrastructure, such as airports, power plants, and communication broadcasting systems, in the civilian field. This study examined the criteria for classification according to the electronic attack missions of foreign EA systems based on an aviation platform. The foreign R&D trends by those criteria were investigated. Moreover, by analyzing the R&D trends of domestic EA systems and future battlefields in the domestic security environments, this paper proposes technological development plans of EA systems suitable for the future battlefield environments compared to the foreign R&D trends.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1749-1760
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• 2022

In modern society, human and social damages caused by natural disasters and frequent disaster accidents have been increased year by year. Prompt access to dangerous disaster sites that are inaccessible or inaccessible using state-of-the-art Earth observation equipment such as satellites, drones, and survey robots, and timely collection and analysis of meaningful disaster information. It can play an important role in protecting people's property and life throughout the entire disaster management cycle, such as responding to disaster sites and establishing mid-to long-term recovery plans. This special issue introduces the National Disaster Management Research Institute (NDMI)'s disaster management technology that utilizes various Earth observation platforms, such as mobile survey vehicles equipped with close-range disaster site survey sensors, drones, and survey robots, as well as satellite technology, which is a tool of remote earth observation. Major research achievements include detection of damage from water disasters using Google Earth Engine, mid- and long-term time series observation, detection of reservoir water bodies using Sentinel-1 Synthetic Aperture Radar (SAR) images and artificial intelligence, analysis of resident movement patterns in case of forest fire disasters, and data analysis of disaster safety research. Efficient integrated management and utilization plan research results are summarized. In addition, research results on scientific investigation activities on the causes of disasters using drones and survey robots during the investigation of inaccessible and dangerous disaster sites were described.

• Ecology and Resilient Infrastructure
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• v.10 no.4
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• pp.97-106
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• 2023

This study analyzed morphological changes in the Singwangcheon and Naengcheon streams in Pohang caused by flooding due to Typhoon Hinnamnor. Analysis of the changes in river channel area from the past to recent times using aerial photos and drone-taken images showed that the river width had gradually decreased since the 1960s. However, after the flood, the river width increased again. Changes in the river cross-section before and after the flood show that a large amount of coarse sediment was deposited inside the river bend while the outer bank was eroded. The water levels calculated using HEC-RAS for the pre-flood cross-section based on the flood frequency discharges and estimated discharge from Oer Reservoir were significantly lower than the observed water level, which means that the cross-sectional change was not considered. The results of this study suggest that it is necessary to consider cross-sectional changes due to sediment transport when estimating the flood level of small and medium-sized mountain streams, and it is needed to investigate the geomorphic changes after floods.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.38 no.1
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• pp.77-84
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• 2020

This study is apply 3D spatial information per traditional landscape space by comparing spatial information data created using a small drone and 3D scanner used for 3D spatial information construction for efficient preservation and management of traditional landscaping space composed of areas such as scenic sites and traditional landscape architectures. The analysis results are as follows. First, aerial photogrammetry data is less accurate than 3D scanners, but it was confirmed to be more suitable for monitoring landscape changes by reading RGB images than 3D scanners by texture mapping using digital data in constructing orthographic image data. Second, the orthographic image data constructed by aerial photogrammetry in a traditional landscaping space consisting of a fixed area, such as Gwanghalluwon Garden, produced visually accurate and precise results. However, as a result of the data extraction, data for trees, which is one of the elements that make up the traditional landscaping, was not extracted, so it was determined that 3D scanning and aerial surveying had to be performed in parallel, especially in areas where trees were densely populated. Third, The surrounding trees in Soswaewon Garden caused many errors in 3D spatial information data including topographic data. It was analyzed that it is preferable to use 3D scanning technology for precise measurement rather than aerial photogrammetry because buildings, landscaping facilities and trees are dense in a relatively small space. When 3D spatial information construction data for a traditional landscaping space composed of area using a small drone and a 3D scanner free from temporal and spatial constraints and compared the data was compared, the aerial photogrammetry is effective for large site such as Hahoe Village, Gyeongju and construction of a 3D space using a 3D scanner is effective for traditional garden such as Soswaewon Garden.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.111-116
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• 2017

We propose the compact circular polarized antenna. The radiation elements of the proposed antenna is designed using FR4 substrate with the size of $25mm{\times}3.2mm{\times}5mm$ and stand on four corners of the feed network substrate. The feeder network is designed on FR4 substrate with the size of $40mm{\times}40mm{\times}0.8mm$ and has four oupt signals with same magnitude and $90^{\circ}$ phase difference. The input impedances of the designed radiation elements and the output impedances of the feeder network are $100{\Omega}$. The designed antenna has the dimension of $40mm{\times}40mm{\times}5.8mm$ and the operated frequency band of 1.559 - 1.609 GHz. The fabricated antenna has RHCP radiation pattern and the measured results of axial ratio less than 3.5 dB and radiated gain more than 1.5 dBic. The fabricated antenna can apply to GLONASS and Beiodu systems as well as GPS system.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.9
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• pp.429-436
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• 2017

Unmanned Aerial Vehicles (UAV) that are piloted without human pilots can be commanded remotely via frequencies or perform pre-inputted missions. UAVs have been mainly used for military purposes, but due to the development of ICT technology, they are now widely used in the private sector. Teal Group's 2014 World UAV Forecast predicts that the UAV market will grow by 10% annually over the next decade, reaching $ 12.5 billion by 2023. However, because UAVs are primarily remotely controlled, if a malicious user accesses a remotely controlled UAV, it could seriously infringe privacy and cause financial loss or even loss of life. To solve this problem, a secure channel must be established through mutual authentication between the UAV and the control center. However, existing security techniques require a lot of computing resources and power, and because communication distances, infrastructure, and data flow are different from UAV networks, it is unsuitable for application in UAV environments. To resolve this problem, the study presents a lightweight UAV authentication method based on Physical Unclonable Functions (PUFs) that requires less computing resources in the ground Control and Non-Payload Communication (CNPC) environment, where recently, technology standardization is actively under progress.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.353-361
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• 2020

Due to the rapid urbanization, various traffic problems such as traffic jams during commute and regular traffic jams are occurring. In order to solve these traffic problems, it is necessary to quickly and accurately estimate and analyze traffic volume. ITS (Intelligent Transportation System) is a system that performs optimal traffic management by utilizing the latest ICT (Information and Communications Technology) technologies, and research has been conducted to analyze fast and accurate traffic volume through various techniques. In this study, we proposed a deep learning-based vehicle detection method using UAV (Unmanned Aerial Vehicle) video for real-time traffic analysis with high accuracy. The UAV was used to photograph orthogonal videos necessary for training and verification at intersections where various vehicles pass and trained vehicles by classifying them into sedan, truck, and bus. The experiment on UAV dataset was carried out using YOLOv3 (You Only Look Once V3), a deep learning-based object detection technique, and the experiments achieved the overall object detection rate of 90.21%, precision of 95.10% and the recall of 85.79%.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.471-476
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• 2020

We propose an practical embodiment-based programming training course for middle school students using Arduino and conduct survey before and after the curriculum. Arduino is an open source physical computing platform that integrates the IDE used in processing language. It is a low-cost, relatively simple I/O interface compared to other platforms, and because of its practical formability, it is educational material suitable for programming. Subsequent surveys will provide feedback on changes in cognition of programming needs and improvement in thinking skills. In this study, the program based on embody-based programming using Arduino was conducted for 8 weeks for each first grade, and 112 middle school students for two years from '16 to '17. Based on the theoretical and practical training, the training was based on the application of the ultrasonic sensor to the RC car and the preparation of the adduction quadrotor drone. The purpose of this study is to prove that the recognition, necessity, and programming education of middle school students are effective for the improvement of thinking ability through the program based on embody-based programming using Arduino.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1669-1683
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• 2021

AI intelligent agriculture and digital agriculture are important for the science of agriculture. Leaf chlorophyll contents(LCC) are one of the most important indicators to determine the growth status of vegetable crops. In this study, a support vector machine (SVM) regression model was produced using an unmanned aerial vehicle-based RGB camera and a multispectral (MSP) sensor for onions and garlic, and the LCC estimation applicability of the RGB camera was reviewed by comparing it with the MSP sensor. As a result of this study, the RGB-based LCC model showed lower results than the MSP-based LCC model with an average R² of 0.09, RMSE 18.66, and nRMSE 3.46%. However, the difference in accuracy between the two sensors was not large, and the accuracy did not drop significantly when compared with previous studies using various sensors and algorithms. In addition, the RGB-based LCC model reflects the field LCC trend well when compared with the actual measured value, but it tends to be underestimated at high chlorophyll concentrations. It was possible to confirm the applicability of the LCC estimation with RGB considering the economic feasibility and versatility of the RGB camera. The results obtained from this study are expected to be usefully utilized in digital agriculture as AI intelligent agriculture technology that applies artificial intelligence and big data convergence technology.