• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.3
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• pp.66-73
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• 2019

Recently, FDM-type 3D printer technology has been developed, and efforts have been made to improve the output formability and characteristics further. Through this, 3D printers are used in various fields, and printer technologies are suggested according to usage, such as FDM, SLA, DLP, and SLM. In particular, the FDM method is the most widely used, and the FDM method technology is being developed further. The characteristics of the output are produced by the FDM-type 3D printer, which is determined by various factors, and particularly the perspective of the Inter-Layer Fill Factor, which is the volume ratio of the laminated material that exerts a direct influence. In this study, the Inter-Layer Fill Factor is theoretically obtained by presenting the internal space between each layer according to the laminate thickness as a cross-sectional shape model, and the cross section of the actual laminated sample is compared with the theoretical model through experiments. Then, the equation for the theoretical model is defined, and the strength change according to each condition (tensile strength of material, reduction slope, strength reduction rate, and output strength) is confirmed. In addition, we investigated the influence on the correlation and strength between laminate thickness and the Inter-Layer Fill Factor.

• Economic and Environmental Geology
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• v.53 no.6
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• pp.793-807
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• 2020

The policy for Green New Deal will promote the shift of the application to coal as feedstock from coal as fuel. Coal can be used as fuel for production of hydrogen and as feedstock materials such as synthetic graphite or activated carbon. Hydrogen is obtained from syngas produced through Steam carbon(SC), Water-Gas Shift(WGS), and Carbonation reactions, and these processes should be used in conjunction with CO2 sequestration technology. Anthracite has a potential in terms of cost advantage as a feedstock compared to a petroleum pitch, because Synthetic graphite is prepared by heat treating an anthracite with high rank to a graphitization temperature which is in the range of 2400~2800℃, in the presence of inorganic catalyst such as silicon or iron. From several studies, it has been confirmed that coal-based activated carbon(AC) is manufactured with quality similar to the large specific surface area and much micropore volume of lignin-based AC, can be prepared. Therefore it is expected that lignin-based AC is replaced to coal-based AC.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.4
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• pp.449-455
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• 2022

Concrete is the most widely used construction material. The heavy self-weight of concrete may offer an advantage when developing high compressive strength and good dimensional stability. However, it is limited in the construction of super-long bridges or very high skyscrapers owing to the substantially increased self-weight of the structure. For developing lightweight concrete, various lightweight aggregates have typically been utilized. However, due to the porous characteristics of lightweight aggregates, the strength at the composite level is generally decreased. To overcome this intrinsic limitation, this study aims to develop a construction material that satisfies both lightweight and high strength requirements. The developed cementitious composite was manufactured based on a high volume usage of hollow glass microspheres in a matrix with a low water-to-cement ratio. Regardless of the tested hollow glass microspheres from among four different types, compressive strength outcomes of more than 60 MPa and 80 MPa with a density of 1.7 g/cm³ were experimentally confirmed under ambient and high-temperature curing, respectively.

• The Journal of Information Systems
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• v.31 no.3
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• pp.47-65
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• 2022

Purpose With the recent development of Big Data and Artificial Intelligence technology, self-driving technology has developed into three stages (partial self-driving) or four stages (conditional self-driving), it is expected to bring a new paradigm to transportation in the city. Although many researchers are researching related technologies, there is no research on self-driving for disabled persons. In this study, the basic research was conducted based on the assumption that the shared self-driving car used by the disabled person is similar to the special transportation currently driving. Design In this study, data analysis and machine learning techniques were utilized to analyze the mobility patterns of disabled persons by type and to search for leading factors affecting the traffic volume of special transportation. Findings The study found that external physical disorders and developmental disorders often visit general welfare centers, internal organ disorders often visit general hospitals, and the elderly and mental disorders have various destinations. In addition, machine learning analysis showed that the main transportation routes for the disabled person use arterial roads and auxiliary arterial roads and that the ratio of building usage-related variables affecting the use of special transportation for a disabled person is high. In addition, the distance to the subway and bus stops was also mentioned as a meaningful variable. Based on these analysis results, it is expected that the necessary infrastructure for shared self-driving cars for disability person traffic will be used as meaningful research data in the future.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.8
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• pp.259-268
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• 2022

With prosperous usage of cloud services to improve management efficiency due to the explosive increase in data volume, various cryptographic techniques are being applied in order to preserve data privacy. In spite of the vast computing resources of cloud systems, decrease in storage efficiency caused by redundancy of data outsourced from multiple users acts as a factor that significantly reduces service efficiency. Among several approaches on privacy-preserving data deduplication over encrypted data, in this paper, the research results for improving efficiency of encrypted data deduplication using trusted execution environment (TEE) published in the recent USENIX ATC are analysed in terms of security and efficiency of the participating entities. We present a way to improve the stability of a key-managing server by integrating it with individual clients, resulting in secure deduplication without independent key servers. The experimental results show that the communication efficiency of the proposed approach can be improved by about 30% with the effect of a distributed key server while providing robust security guarantees as the same level of the previous research.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.85-92
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• 2023

Deep learning applications are increasingly being leveraged for disease detection tasks in medical imaging modalities such as X-ray, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI). Most data-centric deep learning challenges necessitate the use of supervised learning methodologies to attain high accuracy and to facilitate performance evaluation through comparison with the ground truth. Supervised learning mandates a substantial amount of image and label sets, however, procuring an adequate volume of medical imaging data for training is a formidable task. Various data augmentation strategies can mitigate the underfitting issue inherent in supervised learning-based models that are trained on limited medical image and label sets. This research investigates the enhancement of a deep learning-based rib fracture segmentation model and the efficacy of data augmentation techniques such as left-right flipping, rotation, and scaling. Augmented dataset with L/R flipping and rotations(30°, 60°) increased model performance, however, dataset with rotation(90°) and ⨯0.5 rescaling decreased model performance. This indicates the usage of appropriate data augmentation methods depending on datasets and tasks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.363-370
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• 2023

Due to the spread of COVID-19, the use of public transportation such as urban railroads has changed significantly since the beginning of 2020. Therefore, in this study, daily time series data for each urban railway station were collected for three years before COVID-19 and after the spread of COVID-19, and the similarity of time series analysis was evaluated through DTW (Dynamic Time Warping) distance method to derive regression centers for each cluster, and the effect of various external events such as COVID-19 on changes in the number of users was diagnosed as a time series impact detection function. In addition, the characteristics of use by cluster of urban railway stations were analyzed, and the change in passenger volume due to external shocks was identified. The purpose was to review measures for the maintenance and recovery of usage in the event of re-proliferation of COVID-19.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.191-198
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• 2024

Korea is an import and export-oriented economy that relies on shipping transportation, and sea ports play an important role in national economic growth. To secure and maintain the competitiveness of these ports, hardware and software investments are required, but policy support can also be expected to have an effect. This study identified the irrationality of the system by exploratory analysis of the port facility fee discount system for Ulsan Port, an energy hub port, and suggested improvement measures to resolve it.This study analyzed the volume of Ulsan Port and the reduction of port facility usage fees for about 10 years and identified irrational factors that despite a special port for liquid cargo, a considerable reduction for container cargo is concentrated, and even because it was a passing ship, 100% reduction for entrance and clearance fees were provided to them, which could cause serious moral hazard.. As a way to improve the port facility charge discount system at Ulsan Port, this study proposed strengthening support for eco-friendly activities to support containers, adjusting the reduction rate for passing ships, or improving the reduction and exemption application process.

• International Journal of Heart Failure
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• v.6 no.1
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• pp.22-27
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• 2024

Body fluid monitoring and management are essential to control dyspnea and prevent re-hospitalization in patients with chronic heart failure (HF). There are several methods to estimate and monitor patient's volume status, such as symptoms, signs, body weight, and implantable devices. However, these methods might be difficult to use for reasons that are slow to reflect body water change, inaccurate in specific patients' condition, or invasive. Bioelectrical impedance analysis (BIA) is a novel method for body water monitoring in patients with HF, and the value in prognosis has been proven in previous studies. We aim to determine the efficacy and safety of home BIA body water monitoring-guided HF treatment in patients with chronic HF. This multi-center, open-label, randomized control trial will enroll patients with HF who are taking loop diuretics. The home BIA group patients will be monitored for body water using a home BIA device and receive messages regarding their edema status and direction of additional diuretics usage or behavioral changes through the linked application system once weekly. The control group patients will receive the usual HF management. The primary endpoint is the change in N-terminal prohormone of brain natriuretic peptide levels from baseline after 12 weeks. This trial will provide crucial evidence for patient management with a novel home BIA body water monitoring system in patients with HF.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.2
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• pp.309-317
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• 2014

The purpose of this study was to investigate convenience foods at convenience stores, by examining consumption patterns, as well as the degree of checking food-nutrition labeling. In this study, 208 workers in Busan in their 20s or 30s were surveyed using 1:1 interview questionnaires. The weekly usage frequencies of cup-ramyeon, gimbap, ramyeon, and sandwiches were 41.0%, 39.4%, 32.7%, and 19.0% respectively. The usage frequency of convenience foods was 12.0% for 'over 5 times/week', 23.0% for '3~4 times/week', 31.7% for '1~2 times/week', 29.8% for '1~2 times/month', and 3.4% for zero usage. Workers in their 20s showed a significantly (P<0.05) higher rate in the '3~4 times/week' as well as '1~2 times/week' intervals than workers in their 30s. Single people showed a significantly (P<0.01) higher rate than married people. Workers in their 20s showed a significantly higher score for the '3~4 times/week' as well as '1~2 times/week' intervals (P<0.05). The mean score of checking food labeling was 4.02/5.00 for the manufacturer's date, or expiration date, 3.23/5.00 for weight or volume, 2.99/5.00 for cooking method, and 2.85/5.00 for storage method. Females showed significantly (P<0.01) higher rates for checking the manufacturer's date or expiration date, as well as source of the raw material. Single workers showed significantly (P<0.01) higher rates for checking the manufacture's or expiration date as well as storage method. The mean score for checking nutrition labeling was 3.06/5.00 for calories, 2.84/5.00 for trans fat, 2.80/5.00 for sodium, and 2.76/5.00 for cholesterol. Females showed a significantly (P<0.01) higher rate for six of 10 items. Workers in their 20s showed a significantly (P<0.05) higher rate for four of 10 items. Expert officials showed significantly higher rate for six of 10 items (P<0.05) and two of 10 items (P<0.01), respectively.