• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.4
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• pp.331-344
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• 2023

The performance of the existing tunnel scanning system was analyzed through the post-evaluation of NETIS (New Technology Information System) and Inspection Support Technology Performance Catalog. Suggestions for improvement and development direction of the tunnel scanning system were deduced. As new technology of Japan gave priority to providing user-centered information, it was possible to objectively compare and analyze the characteristics of various tunnel scan systems through post-evaluation of NETIS and standard test methods in the Inspection Support Technology Performance Catalog. Construction New Technology of Korea was centered on suppliers of technology certification, making it impossible to objectively compare the performance of tunnel scanning systems. The performance was compared and evaluated indirectly by comparing the specifications of the camera, which is a core device of Japan's tunnel scanning system. For the future development of tunnel scanning systems, high-resolution and fast exposure performance of cameras and corresponding high-intensity lighting devices are required. For this purpose, it is necessary to make an experimental environment in which the performance of the camera and lighting can be analyzed indoors.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.157-168
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• 2023

Image segmentation and supervised classification techniques are widely used to monitor the ground surface using high-resolution remote sensing images. In order to classify various objects, a process of defining a class corresponding to each object and selecting samples belonging to each class is required. Existing methods for extracting class samples should select a sufficient number of samples having similar intensity characteristics for each class. This process depends on the user's visual identification and takes a lot of time. Representative samples of the class extracted are likely to vary depending on the user, and as a result, the classification performance is greatly affected by the class sample extraction result. In this study, we propose an image classification technique that minimizes user intervention when extracting class samples by applying the histogram back-projection technique and has consistent intensity characteristics of samples belonging to classes. The proposed classification technique using histogram back-projection showed improved classification accuracy in both the experiment using hue subchannels of the hue saturation value transformed image from Compact Advanced Satellite 500-1 imagery and the experiment using the original image compared to the technique that did not use histogram back-projection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.115-123
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• 2006

Recently, construction claims have been increased for protecting the rights of construction participants and effectively adjusting the changes under the contract. Thus, the importance of claim management has been emphasized in the construction industry. In domestic construction industry, some claim issues involved in construction activities are often being developed into disputes and even litigations because of the absence of methods or systems for the dispute resolution, and the lack of judicial precedents which can be provided as the references for resolving a particular dispute. In general, the judicial precedents related to the disputes and litigations occurred among construction participants would be extremely valuable in evaluating and analyzing current claims issues. However, such useful information has not been effectively accumulated and utilized in resolving the similar or sometimes identical types of disputes, thus requiring a large amount of additional costs, time and efforts. The primary objective of this study is to propose a web-based decision support system for construction claim management, which enables contractual participants to easily access and use the information of the judicial precedents related to the current construction claims. The decision support system is composed of 'prevention' and 'settlement' modules for avoiding and systematically resolving the construction claims.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.33-43
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• 2024

This research assessed the applicability of the You Only Look Once (YOLO)v8 and DeepLabv3+ models for the effective detection of compost heaps, identified as a significant source of non-point source pollution. Utilizing high-resolution imagery acquired through Unmanned Aerial Vehicles(UAVs), the study conducted a comprehensive comparison and analysis of the quantitative and qualitative performances. In the quantitative evaluation, the YOLOv8 model demonstrated superior performance across various metrics, particularly in its ability to accurately distinguish the presence or absence of covers on compost heaps. These outcomes imply that the YOLOv8 model is highly effective in the precise detection and classification of compost heaps, thereby providing a novel approach for assessing the management grades of compost heaps and contributing to non-point source pollution management. This study suggests that utilizing UAVs and deep learning technologies for detecting and managing compost heaps can address the constraints linked to traditional field survey methods, thereby facilitating the establishment of accurate and effective non-point source pollution management strategies, and contributing to the safeguarding of aquatic environments.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.275-290
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• 2023

We aimed to revise and supplement the art therapy kit based on the findings of a review of women's experiences participating in the art therapy kit in the 2030s. After women in their 2030s experienced the developed art therapy kit for one month, we organized two homogeneous groups of 8 art psychotherapy majors and 5 non-majors to collect data through focus group interviews and analyzed them using grounded theory methods. In the end, 100 converted meaning units, 16 subcomponents, and 5 components were derived. There is a lack of research on the development and experience of art or art therapy-based kits in Korea, so it is important for us to provide basic data on the experience of art therapy kits. In addition, the study participants experienced insights into themselves and their emotions based on the accumulated art therapy kit outputs through immersion in emotion exploration and recognition, and these experiences led to the participants' recognition of the need and value of developing art therapy kits. The individual and unique outcomes of the art therapy kits became evidence of self-awareness, confirming the therapeutic effectiveness of art therapy kits as a tool for emotion exploration and recognition and for emotional change and resolution.

• Korean Journal of Agricultural Science
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• v.50 no.2
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• pp.257-270
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• 2023

The paddy environment is classified as a wetland and occupies a very large proportion of the freshwater environment. It is also ecologically important as a habitat and spawning ground for many aquatic insects and amphibian larvae. However, due to climate change and indiscriminate spraying of pesticides, the rice field ecosystem is continuously threatened. In order to restore ecologically damaged rice paddies in the future, information on organisms living in the rice paddy ecosystem, which can serve as a restoration standard, is needed. The eDNA metabarcoding analysis method is a very effective means of accumulating information on many organisms living in the rice field ecosystem because it can indirectly identify the existence of taxa that are no longer found in the target ecosystem due to different adult life periods or metamorphosis. In this study, genes of four species of frogs and nine species of aquatic insects were also discovered, and some taxa were directly discovered in the field. A large number of taxa have been discovered only by DNA searches, and traditional survey methods have only been able to identify very limited taxa. This eDNA-based paddy field biosearch is expected to be very useful in the investigation of biodiversity in agricultural ecosystems due to its strong analytical resolution.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.815-822
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• 2023

Organic pollution is one of the most common forms of water contamination. Under the Water Quality Conservation Act, indicators for measuring organic substances include BOD, COD, and TOC. Analysis of BOD and COD is labor-intensive, and in the case of organic substances where biological decomposition is not feasible or toxic substances are present, the accuracy is often low. Therefore, the Ministry of Environment is shifting towards TOC-centric management. With advancements in sensor technology today, various parameters can be monitored using sensors. In this study, digital monitoring of river TOC using a spectrophotometer called Spectro::lyser V3 was conducted. Initially, experiments were carried out at the Andong River Experiment Center to assess the applicability of the measurement equipment. Subsequently, data collected at the confluence of the Nakdong River was analyzed for the spatial distribution of TOC using the Kriging technique. This research proposes the utilization of sensors for river TOC monitoring and spatial distribution analysis. Real-time monitoring of changes in river TOC concentration can serve as fundamental data for pollution monitoring and response. Sensor-based river monitoring offers advantages in terms of temporal resolution and real-time data acquisition. When various spatial information interpretation methods are applied, it is expected to contribute to diverse studies such as aquatic ecological health, river water source selection, and stratification analysis in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.536-542
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• 2023

Satellites represent cutting-edge technology, of ering significant advantages in spatial and temporal observations. National agencies worldwide harness satellite data to respond to marine accidents and analyze ocean fluctuations effectively. However, challenges arise with high-resolution satellite-based sea surface temperature data (Operational Sea Surface Temperature and Sea Ice Analysis, OSTIA), where gaps or empty areas may occur due to satellite instrumentation, geographical errors, and cloud cover. These issues can take several hours to rectify. This study addressed the issue of missing OSTIA data by employing LaMa, the latest deep learning-based algorithm. We evaluated its performance by comparing it to three existing image processing techniques. The results of this evaluation, using the coefficient of determination (R²) and mean absolute error (MAE) values, demonstrated the superior performance of the LaMa algorithm. It consistently achieved R² values of 0.9 or higher and kept MAE values under 0.5 ℃ or less. This outperformed the traditional methods, including bilinear interpolation, bicubic interpolation, and DeepFill v1 techniques. We plan to evaluate the feasibility of integrating the LaMa technique into an operational satellite data provision system.

• Journal of Powder Materials
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• v.31 no.2
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• pp.169-179
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• 2024

Colloidal quantum dot (QDs) have emerged as a crucial building block for LEDs due to their size-tunable emission wavelength, narrow spectral line width, and high quantum efficiency. Tremendous efforts have been dedicated to improving the performance of quantum dot light-emitting diodes (QLEDs) in the past decade, primarily focusing on optimization of device architectures and synthetic procedures for high quality QDs. However, despite these efforts, the commercialization of QLEDs has yet to be realized due to the absence of suitable large-scale patterning technologies for high-resolution devices., This review will focus on the development trends associated with transfer printing, photolithography, and inkjet printing, and aims to provide a brief overview of the fabricated QLED devices. The advancement of various quantum dot patterning methods will lead to the development of not only QLED devices but also solar cells, quantum communication, and quantum computers.