• Korean Journal of Remote Sensing
• /
• v.35 no.2
• /
• pp.343-346
• /
• 2019

This letter describes a development of satellite-based forest withering index for detection of fire burn area and its application to the Goseong-Sokcho and Gangneung-Donghae wildfires in April 4, 2019. Withered forest has very different spectral characteristics from healthy forest. In particular, a false color composite of R-NIR-G represents such difference very clearly. Using Sentinel-2 images with the forest withering index, we derived the area burned by the wildfires: approximately 701.16 ha for Goseong-Sokcho and approximately 710.60 ha for Gangneung-Donghae, although official record will be announced by the Korean government later.

• The Korean Journal of Applied Statistics
• /
• v.34 no.5
• /
• pp.795-806
• /
• 2021

Recently, as text data through online channels have become vast, there is a growing interest in research that summarizes and analyzes them. One of the fundamental analyses of text data is to extract potential topics. Although the researcher may read all the data and summarize the contents one by one, it is not easy to deal with large amounts of data. Blei and Lafferty (2007) and Blei et al. (2003) proposed topic modeling methods for extracting topics using a statistical model. Since the text data is generally collected over time, it is worthwhile to monitor the topic's changes. In this study, we propose a topic index based on the results of the topic model. In addition, a control chart, a representative tool for statistical process management, is applied to monitor the topic index over time. As a practical example, we use text data collected from Blue House National Petition boards between March 5, 2018, and March 5, 2020.

• Korean journal of applied entomology
• /
• v.60 no.1
• /
• pp.135-143
• /
• 2021

Aerospace and geospatial technologies have become more accessible by researchers and agricultural practitioners, and these technologies can play a pivotal role in transforming current pest management practices in agriculture and forestry. During the past 20 years, technologies including satellites, manned and unmanned aircraft, spectral sensors, information systems, and autonomous field equipment, have been used to detect pests and apply control measures site-specifically. Despite the availability of aerospace and geospatial technologies, along with big-data-driven artificial intelligence, applications of such technologies to apple IPM have not been realized yet. Using a case study conducted at the Korea Apple Research Institute, this article discusses the advances and limitations of current aerospace and geospatial technologies that can be used for improving apple IPM.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.19 no.5
• /
• pp.131-142
• /
• 2009

While users of information security products require high-quality products that are secure and have high performance, there are neither examples for evaluating the quality of information security products nor studies on the quality model and metrics for the quality evaluation. In this paper, information security products are categorized into three different types and the security and performance of various information security products are analyzed. Through this process and after consideration of information security products' security and performance, a new quality model that possesses 7 characteristics and 24 sub-characteristics has been defined. In addition, metrics consisting of 62 common and 45 extended metrics that can be used to evaluate the quality of information security products are introduced, and a proposition for a method of generating the quality evaluation metrics for specific information security products is included. The method of generating metrics proposed in this paper can be extended in order to be applied to a variety of information security products, and by generating and verifying the quality evaluation metrics for firewall, intrusion detection systems and fingerprint systems it is shown that it applicable on a variety of information security products.

• Journal of the Korean earth science society
• /
• v.43 no.3
• /
• pp.386-404
• /
• 2022

From April 29 to 30, 2011, under the influence of Asian dust originated from Mongolia, a high concentration of Asian dust was observed nationwide for 4 days in Korea. This study investigated the causes and characteristics of and weather conditions associated with Asian dust at high concentrations at its source in Mongolia. For analysis, Asian dust weather data, Asian dust monitoring tower data, satellite data, backward trajectory data, observation data (PM₁₀ and OPC data), and ECMWF reanalysis data were used. In the synoptic analysis, it was observed that the intervals of isobars were densely distributed in the central region of Mongolia and the pressure gradient force was strong. It could be inferenced that Asian dust occurred due to strong winds. The temperature was relatively high, above 10℃, just before the occurrence of Asian dust, and it decreased sharply at the onset of the dust. The relative humidity had a low value of less than approximately 40%. After the occurrence of Asian dust, it increased sharply to over 50% and then showed a tendency to decrease. In the aerosol index shown by the COMS satellite, a high concentration value of over 25 was detected in Inner Mongolia, and it was consistent with the observations made with naked eyes. In the 72-hour backward trajectory, the northwest airflow streamed into Korea, and on May 2, Heuksando showed the highest PM₁₀ concentration of 1,025 ㎍ m^-3(times the average). Especially, in kinematic vertical analysis, it was observed that low pressure on the ground was strengthened by cyclonic relative vorticity developed in the upper layer. Also, the vertical velocity development is considered to have played a major role in the occurrence of high concentration Asian dust.

• Journal of Cadastre & Land InformatiX
• /
• v.52 no.1
• /
• pp.17-36
• /
• 2022

The purpose of this study is to diagnose problems in the regulation and management of Restricted Development Zone and to prepare a construction plan to convert it to a data-based monitoring system. Unlike other land-use zones, the Restricted Development Zone is a exceptional zone that prohibits all development activities other than the minimum maintenance and must be strictly controlled and managed by the local government. However, the current Restricted Development Zone management is distributed according to the conditions of each local government, and it is not possible to monitor changes in the entire Restricted Development Zone as shown in the survey results. In particular, in this study, by introducing an AI-based monitoring system, MOLIT sends the results of detecting changes across the country at regular time points(monthly and quarterly) to the local governments based on the same regulation standards, and the local governments can be trusted while inputting the regulation results into the system. To propose this methodology, first, a survey and interview were conducted with local government officials and experts. Second, we analyzed cases in which AI analysis was applied to local governments and proposed a plan to improve the efficiency of regulation work according to the introduction of the monitoring system. Third, a plan was prepared to establish a monitoring system based on the advancement of the management information system. This monitoring system can be expanded and applied to land that needs periodic regulation and management in the future, and this study tried to propose a methodology and policy for this.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1245-1255
• /
• 2022

Terra Nova Bay polynya (TNBP) is a representative coastal polynya in East Antarctica, which is formed by strong katabatic winds. As the TNBP is one of the major sea ice factory in East Antarctica and has a great impact on regional ocean circulation and surrounding marine ecosystem, it is very important to analyze its area change and development characteristics. In this study, we detected the TNBP from synthetic aperture radar (SAR) and optical images obtained from April 2007 to April 2022 by visually analyzing the stripes caused by the Langmuir circulation effect and the boundary between the polynya and surrounding sea ice. Then, we analyzed the area change and development characteristics of the TNBP. The TNBP occurred frequently but in a small size during the Antarctic winter (April-July) when strong katabatic winds blow, whereas it developed in a large size in March and November when sea ice thickness is thin. The 12-hour mean wind speed before the satellite observations showed a correlation coefficient of 0.577 with the TNBP area. This represents that wind has a significant effect on the formation of TNBP, and that other environmental factors might also affect its development process. The direction of TNBP expansion was predominantly determined by the wind direction and was partially influenced by the local ocean current. The results of this study suggest that the influences of environmental factors related to wind, sea ice, ocean, and atmosphere should be analyzed in combination to identify the development characteristics of TNBP.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.913-924
• /
• 2022

In this paper, we presented a database construction of undersea images for the Habitats of Ecklonia cava and Sargassum and conducted an experiment for semantic segmentation using state-of-the-art (SOTA) models such as High Resolution Network-Object Contextual Representation (HRNet-OCR) and Shifted Windows-L (Swin-L). The result showed that our segmentation models were superior to the existing experiments in terms of the 29% increased mean intersection over union (mIOU). Swin-L model produced better performance for every class. In particular, the information of the Ecklonia cava class that had small data were also appropriately extracted by Swin-L model. Target objects and the backgrounds were well distinguished owing to the Transformer backbone better than the legacy models. A bigger database under construction will ensure more accuracy improvement and can be utilized as deep learning database for undersea images.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.25 no.4
• /
• pp.56-64
• /
• 2021

Leakage due to deterioration and damage is one of the major causes of volume change by freezing and thawing, and it leads micro-cracking and surface scaling in concrete structures. The deterioration of damaged concrete accelerates with the chloride attack. Thus, in the detailed guidelines for facility performance evaluation (2020), the quality of cover concrete and the freeze-thaw (FT) repetition cycle were newly suggested for concrete durability assessment. The quality of cover concrete should be evaluated by the rebound hammer test and the FT repetition cycle should be also considered in the deterioration environmental assessment. This study suggested the application of fast dynamic based nonlinear ultrasound method to monitor initial micro-scale damage under freezing and thawing environment. Concrete specimens were fabricated with different water-cement ratios (40%, 60%) and air contents (1.5% and 3.0%). The compressive strength, rebound number, relative dynamic modulus, and nonlinear ultrasound were measured with different FT cycles. The scanning electron microscopy was also performed to investigate the micro-scale FT damage. As a result, both the rebound number and the relative dynamic modulus had difficulty to detect early damage but the proposed method showed a potential to detect initial micro-scale damage and predict the FT resistance performance of concrete.

• Journal of Software Assessment and Valuation
• /
• v.17 no.1
• /
• pp.101-113
• /
• 2021

In this paper, we introduce a speaker overlap system and look at the process of converting the existed system on the specific framework of artificial intelligence. Speaker overlap is when two or more speakers speak at the same time during a conversation, and can lead to performance degradation in the fields of speech recognition or speaker recognition, and a lot of research is being conducted because it can prevent performance degradation. Recently, as application of artificial intelligence is increasing, there is a demand for switching between artificial intelligence frameworks. However, when switching frameworks, performance degradation is observed due to the unique characteristics of each framework, making it difficult to switch frameworks. In this paper, the process of converting the speaker overlap detection system based on the Keras framework to the pytorch-based system is explained and considers components. As a result of the framework switching, the pytorch-based system showed better performance than the existing Keras-based speaker overlap detection system, so it can be said that it is valuable as a fundamental study on systematic framework conversion.