• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1709-1718
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• 2021

The waveform data of the Airborne Bathymetric LiDAR (ABL; LiDAR: Light Detection And Ranging) system provides data with improved accuracy, resolution, and reliability compared to the discrete-return data, and increases the user's control over data processing. Furthermore, we are able to extract additional information about the return signal. Waveform decomposition is a technique that separates each echo from the received waveform with a mixture of water surface and seabed reflections, waterbody backscattering, and various noises. In this study, a new waveform decomposition technique based on a Gaussian model was developed to improve the point extraction performance from the ABL waveform data. In the existing waveform decomposition techniques, the number of decomposed echoes and decomposition performance depend on the peak detection results because they use waveform peaks as initial values. However, in the study, we improved the approximation accuracy of the decomposition model by adding the estimated potential peak candidates to the initial peaks. As a result of an experiment using waveform data obtained from the East Coast from the Seahawk system, the precision of the decomposition model was improved by about 37% based on evaluating RMSE compared to the Gaussian decomposition method.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.533-544
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• 2018

Rainfall is one of the most important meteorological variables in meteorology, agriculture, hydrology, natural disaster, construction, and architecture. Recently, satellite remote sensing is essential to the accurate detection, estimation, and prediction of rainfall. In this study, the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) product, a composite rainfall information based on Global Precipitation Measurement (GPM) satellite was evaluated with ground observation data in the inland of Korea. The Automatic Weather Station (AWS)-based rainfall measurement data were used for validation. The IMERG and AWS rainfall data were collocated and compared during one year from January 1, 2016 to December 31, 2016. The coastal regions and islands were also evaluated irrespective of the well-known uncertainty of satellite-based rainfall data. Consequently, the IMERG data showed a high correlation (0.95) and low error statistics of Bias (15.08 mm/mon) and RMSE (30.32 mm/mon) in comparison to AWS observations. In coastal regions and islands, the IMERG data have a high correlation more than 0.7 as well as inland regions, and the reliability of IMERG data was verified as rainfall data.

• Journal of Conservation Science
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• v.37 no.3
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• pp.191-208
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• 2021

In this study, the status of damage by subterranean termites and their management according to the region and type of domestic wooden cultural properties were identified. This was based on the survey reports of agencies conducting regular nationwide and regional monitoring of subterranean termites. In addition, using geographical information system (GIS) based on the survey contents, a map was constructed of termite infestation and its progress on 2,805 wooden cultural properties that were surveyed nationwide. Based on the map produced, a total of 486 cases of termite infestation were confirmed in wooden cultural properties during 2018-2019, of which 143 cases (approximately 29.4%) were confirmed to be owing to the invasion of termites in the ground and infestation of wood materials. A web platform and an application using a mapping application program interface were created to increase accessibility to the investigated damage status data. The methods employed by each institution for investigating and monitoring the invasion of termites in the ground included the use of detection dogs, visual observation, installation of wood specimens made of pine, and microwave equipment. However, it was confirmed that monitoring and survey methods were not applied to determine the territorial range of the subterranean termite colonies. Accordingly, the use of dyeing and mark-release-recapture methods were deemed necessary to understand the current status, such as calculating the scope of the target wooden cultural property, when monitoring subterranean termite colonies.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.499-506
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• 2021

Hackers' cyber attack techniques are becoming more sophisticated and diversified, with a form of attack that has never been seen before. In terms of information security vulnerability standard code (CVE), about 90,000 new codes were registered from 2015 to 2020. This indicates that security threats are increasing rapidly. When new security vulnerabilities occur, damage should be minimized by preparing countermeasures for them, but in many cases, companies are insufficient to cover the security management level and response system with a limited security IT budget. The reason is that it takes about a month for analysts to discover vulnerabilities through manual analysis, prepare countermeasures through security equipment, and patch security vulnerabilities. In the case of the public sector, the National Cyber Safety Center distributes and manages security operation policies in a batch. However, it is not easy to accept the security policy according to the characteristics of the manufacturer, and it takes about 3 weeks or more to verify the traffic for each section. In addition, when abnormal traffic inflow occurs, countermeasures such as detection and detection of infringement attacks through vulnerability analysis must be prepared, but there are limitations in response due to the absence of specialized security experts. In this paper, we proposed a method of using the security policy information sharing site "snort.org" to prepare effective countermeasures against new security vulnerability attacks.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.85-91
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• 2020

Recently, video-taping equipment such as CCTV have been seeing more use for crime prevention and general safety concerns. Since these video-taping equipment operates all throughout the day, the need for security personnel is lessened, and naturally costs incurred from managing such manpower should also decrease. However, technology currently used predominantly lacks self-sufficiency when given the task of searching for a specific object in the recorded video such as a person, and has to be done manually; current security-based video equipment is insufficient in an environment where real-time information retrieval is required. In this paper, we propose a technology that uses the latest deep-learning technology and OpenCV library to quickly search for a specific person in a video; the search is based on the clothing information that is inputted by the user and transmits the result in real time. We implemented our system to automatically recognize specific human objects in real time by using the YOLO library, whilst deep learning technology is used to classify human clothes into top/bottom clothes. Colors are also detected through the OpenCV library which are then all combined to identify the requested object. The system presented in this paper not only accurately and quickly recognizes a person object with a specific clothing, but also has a potential extensibility that can be used for other types of object recognition in a video surveillance system for various purposes.

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

• Smart Media Journal
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• v.13 no.2
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• pp.52-61
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• 2024

In the shipyard, aerial images are acquired at regular intervals using Unmanned Aerial Vehicles (UAVs) for the management of external storage yards. These images are then investigated by humans to manage the status of the storage yards. This method requires a significant amount of time and manpower especially for large areas. In this paper, we propose an automated management technology based on a semantic segmentation foundation model to address these challenges and accurately assess the status of external storage yards. In addition, as there is insufficient publicly available dataset for external storage yards, we collected a small-scale dataset for external storage yards objects and equipment. Using this dataset, we fine-tune an object detector and extract initial object candidates. They are utilized as prompts for the Segment Anything Model(SAM) to obtain precise semantic segmentation results. Furthermore, to facilitate continuous storage yards dataset collection, we propose a training data generation pipeline using SAM. Our proposed method has achieved 4.00%p higher performance compared to those of previous semantic segmentation methods on average. Specifically, our method has achieved 5.08% higher performance than that of SegFormer.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.351-360
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• 2024

With the increasing use of drone technology, the Unmanned Aerial Vehicle (UAV) is now being utilized in various fields. However, this increased use of drones has resulted in various issues. Due to its small size, the drone is difficult to detect with radar or optical equipment, so acoustical tracking methods have been recently applied. In this paper, a method of localization of multiple drones using the acoustic characteristics of the quadcopter drone is suggested. Because the acoustic characteristics induced by each rotor are differentiated depending on the type of drone and its movement state, the sound source of the drone can be reconstructed by spatially clustering the results of the estimated positions of the blade passing frequency and its harmonic sound source. The reconstructed sound sources are utilized to finally determine the location of multiple-drone sound sources by applying the source localization algorithm. An experiment is conducted to analyze the acoustic characteristics of the test quadcopter drones, and the simulations for three different types of drones are conducted to localize the multiple drones based on the measured acoustic signals. The test result shows that the location of multiple drones can be estimated by utilizing the acoustic characteristics of the drone. Also, one can see that the clarity of the separated drone sound source and the source localization algorithm affect the accuracy of the localization for multiple-drone sound sources.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.4
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• pp.303-314
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• 2024

Recently, the consecutive shield tunnel boring machine (TBM) has gained attention for its potential to enhance TBM penetration rates. However, its development requires a thorough risk assessment due to the unconventional nature of its equipment and hydraulic systems, coupled with the absence of design or construction precedents. This study investigated the causal relationships between four accidents and eight relevant sources associated with the consecutive shield TBM. Subsequently, risk levels were determined based on expert surveys and a risk matrix technique. The findings highlighted significant impacts associated with collapses or surface settlements and the likelihood of causal combinations leading to misalignment. Specifically, this study emphasized the importance of proactive mitigation measures to address collapses or surface settlements caused by inadequate continuous tail void backfill or damaged thrust jacks. Furthermore, it is recommended to develop advanced non-destructive testing technology capable of comprehensive range detection across helical segments, to design a sequential thrust jack propulsion system, and to determine an optimal pedestal angle.