• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.167-175
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• 1999

So far, the remote sensing technology has widely been used in a variety of application areas such as military, medical imaging, environment, geology and so forth. The microwave remote sensing uses the wavelengths ranging from around one centimeter up to a few tens of centimeters and is known to be very effective regardless of the weather conditions and the day/night time as compared with the reflective InfraRed (IR) remote sensing or the thermal IR remote sensing. There are three generic modes of synthetic aperture radar imaging systems depending on its application, that is, stripmap mode, spotlight mode, or inverse mode. In this article we focus on the issue of imaging of flying aircrafts for the inverse mode of a ground - based, fixed radar with moving objects. The imaging of flying aircrafts is considered to be an important step for the automatic target recognition systems, and therefore a great deal of efforts have recently been made on the subject. Here we review the three representative methods including the Fourier transform processing, the time - frequency processing, and the reconstruction from the projection. Some relative merits and drawbacks are also discussed.

• Journal of the Korea Society for Simulation
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• v.31 no.2
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• pp.11-20
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• 2022

There is a critical need for AI assistance in guard operations of Army base perimeters, which is exacerbated by changes in the national defense and security environment such as force reduction. In addition, the possibility for human error inherent to perimeter guard operations attests to the need for an innovative revamp of current systems. The purpose of this study is to propose a real-time object detection AI tailored to military CCTV surveillance with three unique characteristics. First, training data suitable for situations in which relatively small objects must be recognized is used due to the characteristics of military CCTV. Second, we utilize a data augmentation algorithm suited for military context applied in the data preparation step. Third, a noise reduction algorithm is applied to account for military-specific situations, such as camouflaged targets and unfavorable weather conditions. The proposed system has been field-tested in a real-world setting, and its performance has been verified.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.407-416
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• 2022

Although environmental education has been more important due to global extreme weather and natural desasters, environmental topics are covered by several other subjects because it is not an independent subject in elementary school and they need to distribute more class hours to cover proper amount of environmental content. This study is performed to develop method to integrate environmental education and software education in elementary school. This method helps students to learn topics about recycling by using Artificial Intelligence programming and Artificial Intelligence also helps students to practice recycling in virtual reality. A new teaching and learning module(Problem Recognition→Machine Learning↔Use of AI→Collaboration) is adopted for the learning procedure and more than 80 % of the students replied positively to the survey about the interest on integrated learning, understanding of environmental education, understanding of Artificial Intelligence, further learning on Artificial Intelligence programming.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.61-71
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• 2009

Vehicle license plate is the only way to check the registrated information of a vehicle. Many works have been devoted to the vision system of recognizing the license plate, which has been widely used to control an illegal parking. However, it is difficult to correctly segment characters on the license plate since an illumination is affected by a weather change and a neighboring obstacles. This paper proposes a robust method of segmenting the character of the license plate on irregular illumination condition. The proposed method enhance the contrast of license plate images using the Chi-Square probability density function. For segmenting characters on the license plate, binary images with the high quality are gained by applying the adaptive threshold. Preprocessing and labeling algorithm are used to eliminate noises existing during the whole segmentation process. Finally, profiling method is applied to segment characters on license plate from binary images.

• Journal of Plant Biotechnology
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• v.35 no.4
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• pp.281-290
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• 2008

In plant, Receptor-like kinases (RLKs) are protein family, though its function is not yet understood, consisted of a predicted signal sequence, single transmembrane region, and cytoplasmic kinase domain. RLKs are involved in hormonal response pathways, cell differentiation, plant growth and development, self-incompatibility, and symbiont and pathogen recognition. In this study, expression levels of RLG1, RLG5, RLG6, RLG#6, RLG8, RLG10, RLG17, RLG18 and RLG20 were analyzed by Real-time PCR, when rice (Oryzae sativa) was treated abiotic stress. The expression levels of all RLGs were compared each other by analyzed value of threshold cycles ($C_T$). Consequently, RLGs were suppressed by NaCl as salinity stress, and expression of each RLK genes were showed difference treated salicylic acid and wound, respectively. However, All RLGs were induced under low temperature condition. Therefore, our results indicate protection-function of RLK genes to be an early response of rice against cold weather.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.43-54
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• 2018

The accurate estimation of reference crop evapotranspiration ($ET_o$) is essential in irrigation water management to assess the time-dependent status of crop water use and irrigation scheduling. The importance of $ET_o$ has resulted in many direct and indirect methods to approximate its value and include pan evaporation, meteorological-based estimations, lysimetry, soil moisture depletion, and soil water balance equations. Artificial neural networks (ANNs) have been intensively implemented for process-based hydrologic modeling due to their superior performance using nonlinear modeling, pattern recognition, and classification. This study adapted two well-known ANN algorithms, Backpropagation neural network (BPNN) and Generalized regression neural network (GRNN), to evaluate their capability to accurately predict $ET_o$ using daily meteorological data. All data were obtained from two automated weather stations (Chupungryeong and Jangsu) located in the Yeongdong-gun (2002-2017) and Jangsu-gun (1988-2017), respectively. Daily $ET_o$ was calculated using the Penman-Monteith equation as the benchmark method. These calculated values of $ET_o$ and corresponding meteorological data were separated into training, validation and test datasets. The performance of each ANN algorithm was evaluated against $ET_o$ calculated from the benchmark method and multiple linear regression (MLR) model. The overall results showed that the BPNN algorithm performed best followed by the MLR and GRNN in a statistical sense and this could contribute to provide valuable information to farmers, water managers and policy makers for effective agricultural water governance.

• Knowledge Management Research
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• v.19 no.1
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• pp.59-77
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• 2018

The tourism industry is now changing to smart tourism, which maximizes tourists' overall tourism experience with the use of advanced mobile technologies and emphasizes the utilization of tourism information. Despite the quantitative expansion of the tourism industry, there is a lack of academic and practical discussion on tourism safety. Especially, in the context of walking tourism, tourists are more likely to be exposed to natural or social disasters and emergencies. Therefore, it is necessary to build a system that can provide walking tourists with safety information not only on dangerous factors which are anticipated to be confronted during a walking trip in advance but also on specific dangers in real time. Under the circumstances, this study seeks to identify the types of tourism safety information that can be offered by using publicly available open data, drawing on the safety information framework on the walking tourism that is presented in Choi et al. (2017)'s study. More specifically, this study focuses on the use of open data which is provided by the Korean government. Furthermore, this study verifies the types of safety information that are most urgently needed in walking travel situations. Specifically, this study aims to derive the importance and priority of each type of safety information for a walking trip by applying the analytic hierarchy process (AHP) analysis. For this, we collected 35 questionnaires from walking tour operators (practitioners) and walking tourists. The main results are as follows. First, natural disaster information is the most important factor in the top-level factor of safety information for walking tourists, followed by social disaster, life safety, and exhibition (security crisis) information. Second, information on natural disasters, environmental pollution, and weather is considered to be important at the sub-level factor. Lastly, the noteworthy result of this study is that the importance of each type of safety information varies depending on the walking tour operators (practitioners) and the walking tourists. That is, there is a recognition difference between the operator (practitioner) and the user in the importance and priority of the safety information of the walking trip. Therefore, it is necessary to develop policies and services reflecting the opinions of potential users when providing safety information so that the most importantly recognized information can be provided first.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.175-181
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• 2009

Intelligent Transportation Systems(ITS) enables road users to enhance efficiency of their trips in a variety of traffic conditions. As a significant part of ITS, information communication technology among vehicles and between vehicles and infrastructure has been being developed to upgrade current traffic data collection technology through location-based traffic surveillance systems. A wider and detailed range of traffic data can be acquired with ease by the technology. However, its performance level falls with environmental impediments such as large vehicles, buildings, harsh weather, which often bring about wireless communication failure. For imputation of vehicle trajectory data discontinued by the failure, several potential existing methods were reviewed and a new method to complement them was devised. AIMSUN API(Application Programming Interface) software was utilized to simulate vehicle trajectories data and missing vehicle trajectories data was randomly generated for the verification of the method. The method was proven to yield more accurate and reliable traffic data than the existing ones.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.3
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• pp.247-256
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• 2014

Recently, camera and RADAR are used for more effective and accurate observation of the bird migration. In recent years, many researches on the bird migration using RADAR are undertaking and in active, thus causes the advent of "RADAR ornithology" as a new academic field. Due to the lack of accessibility, economic feasibility and mobility of weather RADAR, airport searching RADAR and tracking RADAR, Nowadays, a marine RADAR is widely used for a bird observation. In this paper, we deals with a study on development of a remote bird observation system using marine FMCW RADAR, which monitors, records and analyzes bird movement by RADAR image processing and target recognition technology. Also, we conduct first test and second test for availability of the developed system, and verify the system to apply in bird observation domain. Consequently, we figured problems out, and correct the problems to improve the system. The developed system can apply in other domains such as environment evaluation. In the future, the system needs to improve accuracy of statistics and to track migration route of bird.

• Journal of the Korean GEO-environmental Society
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• v.16 no.8
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• pp.13-20
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• 2015

Due to the population growth and exhaustion of resource, the development on the harsh environment such as cold weather is emerging as an alternative for new resource development. The permafrost area covers about 14 percent of the world's land area and the global construction market for such area is rapidly expanded. Whereas the developed countries have already recognition of the need for research of coldest place and invested heavily in technology development, the domestic technology for the coldest place development is less developed and related research has rarely been performed. There is not a detailed national specification standard for the strength and deformation properties of the earthworks at sub-zero temperature but simple field directions. Therefore, the D compaction tests were conducted on the sand with fine contents of 0%, 5%, 10% and 15% at room temperature ($18^{\circ}C$), $-3^{\circ}C$ and $-8^{\circ}C$ to investigate the effect of the compaction energy on the compacted soils at sub-zero temperatures. Based on the test results, the larger compaction energy, the larger maximum dry unit weight under sub-zero temperature and D type compaction at $-3^{\circ}C$ show similar max. dry unit weights as those obtained from the compaction at the room temperature. However, compaction at $-8^{\circ}C$ showed significant performance degradation regardless of the compaction energy.