• Smart Media Journal
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• v.13 no.6
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• pp.80-89
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• 2024

This study aims not only to address environmental issues caused by indiscriminate fashion consumption, specifically in the context of Fast Fashion but also to find an alternative and a sustainable solution that is 'Upcycling' using the 3D clothing simulation program Z-weave. Upcycling products have limitations in that it is difficult to produce samples since finished products must be produced directly with limited materials and resources like waste clothes. To overcome these limitations, a 3D clothing simulation program is introduced to effectively utilize the limited resources of waste clothing. The purpose of this study is to confirm the similarity between a virtual fabric created through Z-weave and a real fabric, through this, to evaluate the possibility of application in the actual fashion industry. As a research method, surveys and interviews were conducted with related majors on virtual clothing created as similar as possible to actual clothing by adjusting the physical properties within the Z-weave program. This study attempted to describe the impact of digital technology on the fashion industry and how 3D clothing simulation programs can be used in sustainable fashion production.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.253-260
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• 2023

The germanium-68/gallium-68 (⁶⁸Ge/⁶⁸Ga) generator has high spatial utilization and requires little maintenance, making it economical and easy to produce. Thus, the frequency of use of ⁶⁸Ga radiopharmaceuticals is rapidly increasing worldwide. Therefore, this study attempted to develop an automated synthesizer for the routine clinical application of ⁶⁸Ga radiopharmaceuticals. The automated synthesizer was based on a fixed tubing system and the structure was designed after adjusting the position of the parts to reflect the synthesis method. Using various components that can be supplied in Korea, the automated synthesizer was manufactured at a much lower price cost than that of a commercialized automated synthesizer sold by companies. ⁶⁸Ga-DOTA-[Tyr3]-octreotide (⁶⁸Ga-DOTATOC) was synthesized to evaluate the performance of the automated synthesizer. ⁶⁸Ga-DOTATOC could be synthesized with about 65% of non-decay corrected yield, and the synthesized ⁶⁸Ga-DOTATOC met all quality control standards. We have synthesized ⁶⁸Ga-DOTATOC more than 100 times, and only faced a few problems caused by mechanical errors. In this study, we successfully developed a simple automated synthesizer for ⁶⁸Ga radiopharmaceuticals with high reproducibility. As various ⁶⁸Ga radiopharmaceuticals have recently been developed, it is expected that the automated synthesizer developed in this study will be useful for routine clinical use.

• Journal of the Korean Society of Radiology
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• v.81 no.4
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• pp.912-919
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• 2020

Purpose This study aimed to compare the brain perfusion status of patients with chronic kidney disease to a normal control group to identify any significant differences. Materials and Methods The perfusion state of the brain was measured by MRI using the arterial spin labeling technique in 36 patients undergoing hemodialysis due to chronic kidney disease and 36 normal controls. Images were then analyzed in a voxel-wise manner to detect brain areas showing significant perfusion differences between the two groups. Results Patients with chronic kidney disease showed increased perfusion in the form of large clusters across the right fronto-parieto-temporal lobe and the left parieto-occipital lobe. In addition, perfusion increased in the bilateral thalami, midbrain, pons, and cerebellum (p < 0.01, familywise error corrected). Conclusion Brain perfusion appears to increase in patients with chronic kidney disease compared to normal controls. Uremic toxicity is thought to be the cause of this increase as it can cause damage to the microscopic blood vessels and their surrounding structures.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.321-332
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• 2024

Understanding the status of surface cover in riparian zones is essential for river management and flood disaster prevention. Traditional survey methods rely on expert interpretation of vegetation through vegetation mapping or indices. However, these methods are limited by their ability to accurately reflect dynamically changing river environments. Against this backdrop, this study utilized satellite imagery to apply the Random Forest method to assess the distribution of vegetation in rivers over multiple years, focusing on the Naeseong Stream as a case study. Remote sensing data from Sentinel-2 imagery were combined with ground truth data from the Naeseong Stream surface cover in 2016. The Random Forest machine learning algorithm was used to extract and train 1,000 samples per surface cover from ten predetermined sampling areas, followed by validation. A sensitivity analysis, annual surface cover analysis, and accuracy assessment were conducted to evaluate their applicability. The results showed an accuracy of 85.1% based on the validation data. Sensitivity analysis indicated the highest efficiency in 30 trees, 800 samples, and the downstream river section. Surface cover analysis accurately reflects the actual river environment. The accuracy analysis identified 14.9% boundary and internal errors, with high accuracy observed in six categories, excluding scattered and herbaceous vegetation. Although this study focused on a single river, applying the surface cover classification method to multiple rivers is necessary to obtain more accurate and comprehensive data.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.1-14
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• 2024

An image-reconstruction technology, involving the deployment of an unmanned mobility equipped with high-speed LiDAR (Light Detection And Ranging) has been proposed to reconstruct the shape of abandoned mine. Unmanned mobility operation is remarkably useful in abandoned mines fraught with operational difficulties including, but not limited to, obstacles, sludge, underwater and narrow tunnel with the diameter of 1.5 m or more. For cases of real abandoned mines, quadruped robots, quadcopter drones and underwater drones are respectively deployed on land, air, and water-filled sites. In addition to the advantage of scanning the abandoned mines with 2D solid-state lidar sensors, rotation of radiation at an inclination angle offers an increased efficiency for simultaneous reconstruction of mineshaft shapes and detecting obstacles. Sensor and robot posture were used for computing rotation matrices that helped compute geographical coordinates of the solid-state lidar data. Next, the quadruped robot scanned the actual site to reconstruct tunnel shape. Lastly, the optimal elements necessary to increase utility in actual fields were found and proposed.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.89-103
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• 2024

In the disposal environment, gases can be generated at the interface between canister and buffer due to various factors such as anaerobic corrosion, radiolysis, and microbial degradation. If the gas generation rate exceeds the diffusion rate, the gas within the buffer may compress, resulting in physical damage to the buffer due to the increased pore pressure. In particular, the rapid movement of gases, known as gas breakthroughs, through the dilatancy pathway formed during this process may lead to releasing radionuclide. Therefore, understanding these gas generation and movement mechanism is essential for the safety assessment of the disposal systems. In this study, an experimental apparatus for investigating gas migration within buffer was constructed based on a literature review. Subsequently, a gas injection experiment was conducted on a compacted bentonite block made of Bentonile WRK (Clariant Ltd.) powder. The results clearly demonstrated a sharp increase in stress and pressure typically observed at the onset of gas breakthrough within the buffer. Additionally, the range of stresses induced by the swelling phenomenon of the buffer, was 4.7 to 9.1 MPa. The apparent gas entry pressure was determined to be approximately 7.8 MPa. The equipment established in this study is expected to be utilized for various experiments aimed at building a database on the initial properties of buffer and the conditions during gas injection, contributing to understanding the gas migration phenomena.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.419-425
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• 2024

As digital communication gains prominence, there is an increasing trend in uncivil behaviors like rude or hateful comments and the empathetic actions towards them, highlighting the need for social efforts to address these issues. As part of these endeavors, we investigated how avatar feedback in a virtual news portal affects users' empathy towards uncivil comments. We defined both posting and empathizing with uncivil comments as antisocial actions. To this end, we posted socially controversial news in a virtual space and provided feedback in two forms when participants selected uncivil comments: text-only feedback and feedback accompanied by an avatar. We then assessed the impact of this feedback on behavioral conformity, guilt, and self-image concern through surveys. Our results showed that avatar-provided feedback significantly influenced participants' social responses more than text-based feedback. Interaction with avatars notably increased participants' behavioral conformity, guilt, and self-image concern. We concluded that avatar-based interactions can positively influence users' social behaviors and attitudes, suggesting their potential in fostering a more civil and responsible digital communication culture.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.363-384
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• 2024

This study was conducted to examine the user's experiences with the public library in Daejeon using big data analysis, focusing on the text mining technique. To know this, first, the overall evaluation and perception of users about the public library in Daejeon were explored by collecting data on social media. Second, through analysis using online news articles, the pending issues that are being discussed socially were identified. As a result of the analysis, the proportion of users with children was first high. Next, it was found that topics through LDA analysis appeared in four categories: 'cultural event/program', 'data use', 'physical environment and facilities', and 'library service'. Finally, it was confirmed that keywords for the additional construction of libraries and complex cultural spaces and the establishment of a library cooperation system appeared at the core in the news article data. Based on this, it was proposed to build a library in consideration of regional balance and to create a social parenting community network through business agreements with childcare and childcare institutions. This will contribute to identifying the policy and social trends of public libraries in Daejeon and implementing data-based public library operations that reflect local community demands.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.263-270
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• 2024

As unmanned aerial vehicles(UAVs) and sensors have been developed in a variety of ways, it has become possible to update information on the ground faster than existing aerial photography or remote sensing. However, acquisition and input of ground control points(GCPs) UAV photogrammetry takes a lot of time, and geometric distortion occurs if measurement and input of GCPs are incorrect. In this study, RGB-based orthophotos were generated to reduce GCPs measurment and input time, and comparison and evaluation were performed by applying feature point algorithms to target orthophotos from various sensors. Four feature point extraction algorithms were applied to the two study sites, and as a result, speeded up robust features(SURF) was the best in terms of the ratio of matching pairs to feature points. When compared overall, the accelerated-KAZE(AKAZE) method extracted the most feature points and matching pairs, and the binary robust invariant scalable keypoints(BRISK) method extracted the fewest feature points and matching pairs. Through these results, it was confirmed that the AKAZE method is superior when performing geometric correction of the objective orthophoto for each sensor.

• Journal of Korea Water Resources Association
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• v.57 no.9
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• pp.615-626
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• 2024

To accurately and efficiently monitor soil moisture (SM) across South Korea, this study developed a SM estimation model that integrates the cloud computing platform Google Earth Engine (GEE) and Automated Machine Learning (AutoML). Various spatial information was utilized based on Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and the global precipitation observation satellite GPM (Global Precipitation Measurement) to test optimal input data combinations. The results indicated that GPM-based accumulated dry-days, 5-day antecedent average precipitation, NDVI (Normalized Difference Vegetation Index), the sum of LST (Land Surface Temperature) acquired during nighttime and daytime, soil properties (sand and clay content, bulk density), terrain data (elevation and slope), and seasonal classification had high feature importance. After setting the objective function (Determination of coefficient, R² ; Root Mean Square Error, RMSE; Mean Absolute Percent Error, MAPE) using AutoML for the combination of the aforementioned data, a comparative evaluation of machine learning techniques was conducted. The results revealed that tree-based models exhibited high performance, with Random Forest demonstrating the best performance (R² : 0.72, RMSE: 2.70 vol%, MAPE: 0.14).