• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.383-390
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• 2021

The experiments in coastal engineering are very complex and a lot of components should be concerned. The experience has an important role in the successful execution. Hydraulic model experiments have been improved with the development of the wave generator and the advanced measuring apparatus. The hydraulic experiments have the advantage, that is, the stability of coastal structures and the hydraulic characteristics could be observed more intuitively rather than the numerical modelings. However, different experimental results can be drawn depending on the model scale, facilities, apparatus, and experimenters. In this study, two-dimensional hydraulic experiments were performed to suggest the guide of the test wave(random wave) generation, which is the most basic and important factor for the model test. The techniques for generating the random waves with frequency energy spectrum and the range for the incident wave height [(H_S)_M/(H_S)_T = 1~1.05] were suggested. The proposed guide for the test wave generation will contribute to enhancing the reliability of the experimental results in coastal engineering.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.2
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• pp.79-94
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• 2022

Due to the highly contagious nature and severity of the respiratory diseases caused by COVID-19, economical and accurate tests are required to better monitor and prevent the spread of this contagion. As the structural and molecular properties of SARS-CoV-2 were being revealed during the early stage of the COVID-19 pandemic, many manufacturers of COVID-19 diagnostic kits actively invested in the design, development, validation, verification, and implementation of diagnostic tests. Currently, diagnostic tests for SARS-CoV-2 are the most widely used and validated techniques for rapid antigen, and immuno-serological assays for specific IgG and IgM antibody tests and molecular diagnostic tests. Molecular diagnostic assays are the gold standard for direct detection of viral RNA in individuals suspected to be infected with SARS-CoV-2. Antibody-based serological tests are indirect tests applied to determine COVID-19 prevalence in the community and identify individuals who have obtained immunity. In the future, it is necessary to explore technical problems encountered in the early stages of global or regional outbreaks of pandemics and provide future directions for better diagnostic tests. This article evaluates the commercially available and FDA-approved molecular and immunological diagnostic assays and analyzes their performance characteristics.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.305-316
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• 2022

With the flood of digital data owing to the Internet of Things and big data, cloud service providers that process and store vast amount of data from multiple users can apply duplicate data elimination technique for efficient data management. The user experience can be improved as the notion of edge computing paradigm is introduced as an extension of the cloud computing to improve problems such as network congestion to a central cloud server and reduced computational efficiency. However, the addition of a new edge device that is not entirely reliable in the edge computing may cause increase in the computational complexity for additional cryptographic operations to preserve data privacy in duplicate identification and elimination process. In this paper, we propose an efficiency-improved duplicate data elimination protocol while preserving data privacy with an optimized user-edge-cloud communication framework by utilizing a trusted execution environment. Direct sharing of secret information between the user and the central cloud server can minimize the computational complexity in edge devices and enables the use of efficient encryption algorithms at the side of cloud service providers. Users also improve the user experience by offloading data to edge devices, enabling duplicate elimination and independent activity. Through experiments, efficiency of the proposed scheme has been analyzed such as up to 78x improvements in computation during data outsourcing process compared to the previous study which does not exploit trusted execution environment in edge computing architecture.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.62-76
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• 2023

Recently, machine learning (ML) techniques have been actively applied for seismic trace interpolation. However, because most research is based on training-inference strategies that treat missing trace gather data as a 2D image with a blank area, a sufficient number of fully sampled data are required for training. This study proposes trace interpolation using ML, which uses only irregularly sampled field data, both in training and inference, by modifying the training-inference strategies of trace-based interpolation techniques. In this study, we describe a method for constructing networks that vary depending on the maximum number of consecutive gaps in seismic field data and the training method. To verify the applicability of the proposed method to field data, we applied our method to time-migrated seismic data acquired from the Vincent oilfield in the Exmouth Sub-basin area of Western Australia and compared the results with those of the conventional trace interpolation method. Both methods showed high interpolation performance, as confirmed by quantitative indicators, and the interpolation performance was uniformly good at all frequencies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2A
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• pp.401-409
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• 2006

This study presents basic information on the mechanical properties and long-term deformations of high-strength steel fiber reinforced concrete(HSFRC). The Influence of steel fiber on modulus of elasticity, compressive, splitting tensile and flexural strength, and drying shrinkage and creep of HSFRC are investigated, and flexural fracture toughness is evaluated. Test results show that Test results show that the effect of steel fibers on the compressive strength is negligible, and the modulus of elasticity of HSFRC increased with the increase of fiber volume fraction. And the effect of fiber volume fraction($V_f$) and aspect ratio($l_f/d_f$) on tensile strength, flexural strength and toughness is extremely prominent. It is observed that the flexural deflection corresponded to ultimate load increased with the increase of $V_f$ and $l_f/d_f$, and due to fiber arresting cracking, the shape of the descending branch of load-deflection tends towards gently. Also, the effect of addition of various amounts of fiber on the creep and shrinkage is obvious. Especially, the effect of adding fibers to high-strength concrete is more pronounced in reducing the drying shrinkage than the creep.

• Applied Chemistry for Engineering
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• v.35 no.2
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• pp.140-147
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• 2024

In order to increase the utilization of biomass, an electrochemical performance was considered after manufacturing a carbon anode material (SV-C) for a Setaria viridis-based lithium ion secondary battery through a heat treatment process. When the heat treatment temperature of the Setaria viridis is as low as 750 ℃, the capacitance (1003.3 mAh/g, at 0.1 C) is high due to the negative (-) charge of oxygen present on the surface attracting lithium, along with the low crystallinity and high specific surface area (126 m²/g), but the capacity retention rate is believed to be as low as 61.0% (at 500 cycles and 1 C). In addition, it was confirmed that when the heat treatment temperature increased to 1150 ℃, the carbon layer was condensed to be excellent in arrangement, and the structural defects were reduced, resulting in a significant reduction in the specific surface area (32 m²/g) of the pores. Furthermore, when the surface defects of the anode material are reduced and the crystallinity is increased, the capacity retention rate is as high as 89.7% (at 500 cycles and 1 C), but the degree of defects is small, the active point is reduced, and the specific capacity is considered to be very low at 471.7 mAh/g. In the scope of this study, it was found that in the case of the Setaria viridis-based carbon anode material manufactured according to the heat treatment temperature, the surface oxygen content and crystallinity have higher reliability on the electrochemical properties of the anode material than the specific surface area.

• Journal of Korea Foundry Society
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• v.44 no.4
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• pp.97-102
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• 2024

In this study, the properties of Zr-14Cu-7.5Ni-2.6Al wide ribbon with amorphous structure and properties were analyzed using Hall effect, SEM-EDX, and XRD. Made by melt spinning method, this Zr-14Cu-7.5Ni-2.6Al based alloy ribbon is not more than 96 ㎛ thick and 100 mm wide. This amorphous alloy exhibited tensile strength of 1,641 MPa, yield strength of 1,541 MPa, elongation of 1% and elastic modulus of 98GPa. The bulk concentration, resistivity, and mobility values are midway between general heavy doping ceramics and metals, and they are about 100 times weaker than ordinary metals, so they are close to Si and have good electrical conductivity. In addition, folding tests were conducted at extreme temperatures, withstanding 150,000 times at -20℃, 300,000 times at 24℃, and 150,000 times at 60℃, with no folding defects observed. These results demonstrate the excellent durability and reliability of the Zr-14Cu-7.5Ni-2.6Al wide ribbon alloy and suggest the possibility of developing electronic products using this alloy.

• Journal of the Korean Recycled Construction Resources Institute
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• v.12 no.3
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• pp.254-262
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• 2024

The demand for high strength and ultra-lightweight materials to incorporate the advanced technology of nanomaterials into the lengthening of structures is continuously increasing. Therefore, based on existing research results and numerous mixing trials, we derived a mix of high strength and ultra-light concrete of a compressive strength of 100 MPa with a unit weight of 18 kN/m³ and a compr essive str ength of 80 MPa with a unit weight of 16 kN/m³ and evaluated their per for mance. In this paper, 108 specimens corresponding to high strength and ultra-lightweight concrete with a compressive strength of 100 MPa under a unit weight of 18 kN/m³, and a compressive strength of 80 MPa under a unit weight of 16 kN/m³ were manufactured, and the bond characteristics were identified by performing a directly tensile tests, and the bond characteristics were evaluated by comparing them with the experimental results and the current design criteria. It was judged that the bond strength calculation formula of ACI-408R and the experimental results were not accurately reflected, so an bond stress equation based on ACI-408R was proposed. The result of the proposed equation was that the deviation was somewhat reduced. In addition, the results of calculating the CEB-FIP model and the modified CMR model using statistical analysis showed slight differences from the experimental results, but considering that the bond behavior is a local behavior, the proposed model appears to explain the bond behavior of high strength and ultra-light concrete as a whole.

• Journal of the Korean Geotechnical Society
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• v.40 no.5
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• pp.113-129
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• 2024

This study reclassifies the risk levels of cut-slopes and addresses the limitations inherent in existing evaluation methods using road slope maintenance data. Conventional risk assessment predominantly relies on subjective expert judgment, resulting in issues of consistency and reliability. To mitigate these limitations, this study applies dimensionality reduction techniques, specifically Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), followed by K-means clustering, to classify new risk levels. The clustering results using PCA demonstrated more distinct cluster separation compared to LDA, and also showed superior performance in terms of the silhouette coefficient and other clustering metrics. This suggests that the existing risk level labels may not adequately capture the underlying data structure. Furthermore, the inconsistency observed between LDA-based clustering results and current risk labels indicates potential reliability issues in the present labeling approach. To resolve this, new risk levels were assigned using PCA and K-means clustering, with cluster risk levels evaluated based on risk scores. A quantitative analysis of key risk factors was also conducted to establish criteria for risk classification and assess the impact of each variable on the different risk levels. This study proposes a data-driven, objective, and quantitative approach to risk level evaluation, aiming to improve the efficiency and reliability of road slope management.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.161-177
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• 2019

In this paper, we study the performance improvement of the answer extraction in Question-Answering system by using sentence dependency parsing result. The Question-Answering (QA) system consists of query analysis, which is a method of analyzing the user's query, and answer extraction, which is a method to extract appropriate answers in the document. And various studies have been conducted on two methods. In order to improve the performance of answer extraction, it is necessary to accurately reflect the grammatical information of sentences. In Korean, because word order structure is free and omission of sentence components is frequent, dependency parsing is a good way to analyze Korean syntax. Therefore, in this study, we improved the performance of the answer extraction by adding the features generated by dependency parsing analysis to the inputs of the answer extraction model (Bidirectional LSTM-CRF). The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. In this study, we compared the performance of the answer extraction model when inputting basic word features generated without the dependency parsing and the performance of the model when inputting the addition of the Eojeol tag feature and dependency graph embedding feature. Since dependency parsing is performed on a basic unit of an Eojeol, which is a component of sentences separated by a space, the tag information of the Eojeol can be obtained as a result of the dependency parsing. The Eojeol tag feature means the tag information of the Eojeol. The process of generating the dependency graph embedding consists of the steps of generating the dependency graph from the dependency parsing result and learning the embedding of the graph. From the dependency parsing result, a graph is generated from the Eojeol to the node, the dependency between the Eojeol to the edge, and the Eojeol tag to the node label. In this process, an undirected graph is generated or a directed graph is generated according to whether or not the dependency relation direction is considered. To obtain the embedding of the graph, we used Graph2Vec, which is a method of finding the embedding of the graph by the subgraphs constituting a graph. We can specify the maximum path length between nodes in the process of finding subgraphs of a graph. If the maximum path length between nodes is 1, graph embedding is generated only by direct dependency between Eojeol, and graph embedding is generated including indirect dependencies as the maximum path length between nodes becomes larger. In the experiment, the maximum path length between nodes is adjusted differently from 1 to 3 depending on whether direction of dependency is considered or not, and the performance of answer extraction is measured. Experimental results show that both Eojeol tag feature and dependency graph embedding feature improve the performance of answer extraction. In particular, considering the direction of the dependency relation and extracting the dependency graph generated with the maximum path length of 1 in the subgraph extraction process in Graph2Vec as the input of the model, the highest answer extraction performance was shown. As a result of these experiments, we concluded that it is better to take into account the direction of dependence and to consider only the direct connection rather than the indirect dependence between the words. The significance of this study is as follows. First, we improved the performance of answer extraction by adding features using dependency parsing results, taking into account the characteristics of Korean, which is free of word order structure and omission of sentence components. Second, we generated feature of dependency parsing result by learning - based graph embedding method without defining the pattern of dependency between Eojeol. Future research directions are as follows. In this study, the features generated as a result of the dependency parsing are applied only to the answer extraction model in order to grasp the meaning. However, in the future, if the performance is confirmed by applying the features to various natural language processing models such as sentiment analysis or name entity recognition, the validity of the features can be verified more accurately.