• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.515-524
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• 2022

To effectively collect, manage, and share the maritime traffic information, it is necessary to identify the technology trends concerning this particular information and analyze its current status and problems. Therefore, this study observes the domestic and foreign technology trends involving maritime traffic information while analyzing and summarizing the current status and problems in collecting, managing, and sharing it. According to the data analysis, the problems in the collecting stage are difficulties in collecting visual information from long-distance radars, CCTVs, and cameras in areas outside the LTE network coverage. Notably, this explains the challenges in detecting smuggling ships entering the territorial waters through the exclusive economic zone (EEZ) in the early stage. The problems in the management stage include difficult reductions and expansions of maritime traffic information caused by the lack of flexibility in storage spaces mostly constructed by the maritime transportation system. Additionally, it is challenging to deal with system failure with system redundancy and backup as a countermeasure. Furthermore, the problems in the sharing stage show that it is difficult to share information with external operating organizations since the internal network is mainly used to share maritime transportation information. If at all through the government cloud via platforms such as LRIT and SASS, it often fails to effectively provide various S/W applications that help use maritime big data. Therefore, it is suggested that collecting equipment such as unmanned aerial vehicles and satellites should be constructed to expand collecting areas in the collecting stage. In the management and sharing stages, the introduction and construction of private clouds are suggested, considering the operational administration and information disclosure of each maritime transportation system. Through these efforts, an enhancement of the expertise and security of clouds is expected.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• Journal of Aerospace System Engineering
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• v.17 no.4
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• pp.133-143
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• 2023

As drones (also known as UAV) become popular with advanced information and communication technology (ICT), they have been utilized for various fields (agriculture, architecture, and so on). However, malicious attackers with advanced drones may pose a threat to critical national infrastructures. Thus, anti-drone systems have been developed to respond to drone threats. In particular, remote identification data (R-ID)-based UAV detection and identification systems that detect and identify illegal drones with R-ID broadcasted by drones have been developed, and are widely employed worldwide. However, this R-ID-based UAV detection/identification system is vulnerable to security due to wireless broadcast characteristics. In this paper, we analyze the security vulnerabilities of DJI Aeroscope, a representative example of the R-ID-based UAV detection and identification system, and propose a replay-attack-based neutralization method using the analyzed vulnerabilities. To validate the proposed method, it is implemented as a software program, and verified against four types of attacks in real test environments. The results demonstrate that the proposed neutralization method is an effective neutralization method for R-ID-based UAV detection and identification systems.

• Journal of Advanced Navigation Technology
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• v.27 no.3
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• pp.306-313
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• 2023

Realistic and graphics-based virtual reality content is based on 360-degree videos, and viewport extraction through the viewer's intention or automatic recommendation function is essential. This paper designs a viewport extraction system based on multiple object tracking in 360-degree videos and proposes a parallel computing structure necessary for multiple viewport extraction. The viewport extraction process in 360-degree videos is parallelized by composing pixel-wise threads, through 3D spherical surface coordinate transformation from ERP coordinates and 2D coordinate transformation of 3D spherical surface coordinates within the viewport. The proposed structure evaluated the computation time for up to 30 viewport extraction processes in aerial 360-degree video sequences and confirmed up to 5240 times acceleration compared to the CPU-based computation time proportional to the number of viewports. When using high-speed I/O or memory buffers that can reduce ERP frame I/O time, viewport extraction time can be further accelerated by 7.82 times. The proposed parallelized viewport extraction structure can be applied to simultaneous multi-access services for 360-degree videos or virtual reality contents and video summarization services for individual users.

• The Korea Journal of Herbology
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• v.24 no.4
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• pp.115-120
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• 2009

Objectives : Due to the morphological similarity and frequent occurrence of intermediate forms as well as morphological variations of aerial part, the correct identification between Rhei Radix et Rhizoma and Rhei Undulatai Rhizoma is very difficult. To develop a reliable method for correct identification and improving the quality standards of Rhei Radix et Rhizoma and Rhei Undulatai Rhizoma, we analyzed RAPD and developed SCAR marker. Methods : To amplify target DNA at the genomic level, 32 Operon 10-mer random primers were applied with four Rheum species, R. officinale, R. palmatum, R. tanguticum and R. undulatum. The nucleotide sequences were determined and species-specific primers were prepared depending on the species-specific RAPD amplicons after subcloned into the pGEM-Teasy vector. To develop the SCAR markers, species-specific PCR amplification and multiplex-PCR were carried out using the single species-specific primer pairs and combinations of them, respectively. Results : We used RAPD analysis of four Rheum plant species to obtain several species-specific RAPD amplicons. From nucleotide sequences of these RAPD amplicons, we developed two SCAR markers that amplified 314 bp and 390 bp DNA fragments in only R. undulatum but not in R. officinale, R. palmatum, R. tanguticum and R. undulatum, for distinguishing Rhei Undulatai Rhizoma and Rhei Radix et Rhizoma. Furthermore, we established SCAR markers for the simultaneous discrimination of the three species within a single reaction by using multiplex-PCR. Conclusions : These genetic markers can be used for the efficient discrimination of plants species and commercial herbal medicines between Rhei Undulatai Rhizoma and Rhei Radix et Rhizoma, to ultimately prevent indiscriminate distribution and prescription of these herbal medicines.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1846-1854
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• 2022

The sophistication and diversification of mission equipment for surveillance and reconnaissance is leading to a demand for large-capacity public data links. Overseas, a T4 class(274Mbps) common data link was applied to the Global hwak, a high-altitude unmanned aerial vehicle, and various research and development are being conducted in Korea. In this paper, we propose a structure in which pilot is additionally applied to improve SNR performance while minimizing data transmission rate loss in the DVB-S2 frame structure, which is a european satellite broadcasting standard, for high-capacity transmission of T4 class or higher in the common data link. For the performance evaluation of the proposed structure, the performance of the DVB-S2 was compared and analyzed by simulating the UAV data link channel environment. As a result of simulation, 0.15% of transmission rate loss occurred at T4 class transmission rate compared to DVB-S2 in the proposed structure, but improved SNR reception performance of 0.2~0.3dB was confirmed in the UAV channel environment.

• Composites Research
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• v.36 no.3
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• pp.211-216
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• 2023

When designing ships and aircraft structures, it is important to design them to satisfy weight reduction and strength. Currently, studies related to topology optimization using 3D printed composite materials are being actively conducted to satisfy the weight reduction and strength of the structure. In this study, structural analysis was performed to analyze the applicability of 3D printed composite materials to the flight control surface, one of the parts of an aircraft or unmanned aerial vehicle. The optimal topology shape of the flight control surface for the bending load was analyzed by considering three types (hexagonal, rectangular, triangular) of the topology shape of the flight control surface. In addition, the bending strength of the flight control surface was analyzed when four types of reinforcing materials (carbon fiber, glass fiber, high-strength high-temperature glass fiber, and kevlar) of the 3D printed composite material were applied. As a result of comparing the three-point bending test results with the finite element method results, it was confirmed that the flight control surface with hexagonal topology shape made of carbon fiber and Kevlar had excellent performance. And it is judged that the 3D printed composite can be sufficiently applied to the flight control surface.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4D
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• pp.569-577
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• 2008

The purpose of this study is focused on the development of compound classification process by mixing multitemporal data and annexing a specific image enhancement technique with a specific image classification algorithm, to gain more accurate land information from satellite imagery. That is, this study suggests the classification process using canonical correlation classification technique after principal component analysis for the mixed multitemporal data. The result of this proposed classification process is compared with the canonical correlation classification result of one date images, multitemporal imagery and a mixed image after principal component analysis for one date images. The satellite images which are used are the Landsat 5 TM images acquired on July 26, 1994 and September 1, 1996. Ground truth data for accuracy assessment is obtained from topographic map and aerial photograph, and all of the study area is used for accuracy assessment. The proposed compound classification process showed superior efficiency to appling canonical correlation classification technique for only one date image in classification accuracy by 8.2%. Especially, it was valid in classifying mixed urban area correctly. Conclusively, to improve the classification accuracy when extracting land cover information using Landsat TM image, appling canonical correlation classification technique after principal component analysis for multitemporal imagery is very useful.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6D
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• pp.871-879
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• 2008

Recently, as there are a rise in the standard of living and higher concerns of an electromagnetic wave and environment, undergrounding the aerial cables which are supported by large pylons and generally considered as the least attractive feature of an urban area is on an increasing trend to improve aesthetic benefits and electric reliability. This study applied Contingent Valuation Method (CVM) which is expected to become an effective tool to measure indirect benefit to estimate the substantial benefits of undergrounding overhead power line projects in an urban area. The tunneling construction project of the 345kV Shinsungnam electric power cable in Seongnam city was selected and a hypothetical scenario was given to respondents to determine their levels of Willingness to Pay (WTP) for undergrounding overhead power lines. The result from the estimation of the WTP of undergrounding overhead power lines in Seongnam city was calculated as approximately 17.1 billion won. Placing existing overhead lines underground is difficult to justify economically. Most undergrounding costs appear to be justified by aesthetic and public policy considerations. Therefore, considering the result of this study, undergrounding overhead power lines is of great benefit to public.

• Journal of The Geomorphological Association of Korea
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• v.27 no.1
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• pp.61-89
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• 2020

The objective of this study is to characterize landslide susceptibility depending on various geo-environmental variables as well as to compare the Frequency Ratio (FR) and Evidential Belief Function (EBF) methods for landslide susceptibility analysis of rainfall-induced landslides. In 2013, a total of 259 landslides occurred in Chuncheon, Gangwon Province, South Korea, due to heavy rainfall events with a total cumulative rainfall of 296~721mm in 106~231 hours duration. Landslides data were mapped with better accuracy using the geographic information system (ArcGIS 10.6 version) based on the historic landslide records in Chuncheon from the National Disaster Management System (NDMS), the 2013 landslide investigation report, orthographic images, and aerial photographs. Then the landslides were randomly split into a testing dataset (70%; 181 landslides) and validation dataset (30%; 78 landslides). First, geo-environmental variables were analyzed by using FR and EBF functions for the full data. The most significant factors related to landslides were altitude (100~200m), slope (15~25°), concave plan curvature, high SPI, young timber age, loose timber density, small timber diameter, artificial forests, coniferous forests, soil depth (50~100cm), very well-drained area, sandy loam soil and so on. Second, the landslide susceptibility index was calculated by using selected geo-environmental variables. The model fit and prediction performance were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under Curve (AUC) methods. The AUC values of both model fit and prediction performance were 80.5% and 76.3% for FR and 76.6% and 74.9% for EBF respectively. However, the landslide susceptibility index, with classes of 'very high' and 'high', was detected by 73.1% of landslides in the EBF model rather than the FR model (66.7%). Therefore, the EBF can be a promising method for spatial prediction of landslide occurrence, while the FR is still a powerful method for the landslide susceptibility mapping.