• Korean Journal of Veterinary Service
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• v.46 no.1
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• pp.15-27
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• 2023

Bordetella (B.) bronchiseptica, Mycoplasma (M.) cynos, and M. canis are the major bacterial pathogens that cause canine infectious respiratory disease complex (CIRDC). In this study, we developed a triplex real-time polymerase chain reaction (tqPCR) assay for the differential detection of these bacteria in a single reaction. The assay specifically amplified three bacterial genes with a detection limit of below 10 copies/reaction. The assay showed high repeatability and reproducibility, with coefficients of intra- and inter-assay variations of less than 1%. The diagnostic results of the assay using 94 clinical samples from household dogs with CIRDC clinical signs, the prevalence of B. bronchiseptica, M. cynos, and M. canis was 22.3%, 18.1%, and 20.2%, respectively, indicating that the diagnostic sensitivity was comparable to those of previously reported qPCR assays. The dual infection rate of B. bronchiseptica and M. cynos, B. bronchiseptica and M. canis, and M. cynos and M. canis was 5.3%, 7.4%, and 3.1%, respectively. Moreover, the triple infection rate of B. bronchiseptica, M. cynos, and M. canis was 2.1%. These results indicate that coinfections with B. bronchiseptica, M. cynos, and M. canis have frequently occurred in the Korean dog population. The newly developed tqPCR assay in the present study will be a useful tool for etiological and epidemiological studies on these three CIRDC-associated bacterial pathogens. The prevalence and coinfection data revealed through this study will contribute to expanding knowledge on the epidemiology of CIRDC in the recent Korean dog population.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.24-35
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• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.

• Laboratory Medicine Online
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• v.1 no.2
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• pp.110-114
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• 2011

There have been a few reports of hemophagocytic lymphohistiocytosis (HLH) with chromosomal abnormalities. Clonal chromosomal abnormalities in HLH patients are usually found in association with hematologic malignancies and rarely with epstein-barr virus (EBV) infection. Here, we report a fatal case of HLH with clonal karyotype abnormalities. A 75-yr-old man was admitted with persistent anorexia and high fever. Laboratory data revealed pancytopenia, hypofibrinogenemia, hyperferritinemia, prolonged prothrombin time and activated partial thromboplastin time, and marked elevated level of serum transaminases. In real time-PCR using whole blood, EBV DNA was not detected but cytomegalovirus (CMV) DNA was detected. The bone marrow aspiration smear showed hyperplasia of mature histiocytes with prominent hemophagocytosis. In chromosomal analysis of bone marrow aspirates, complex chromosomal abnormalities were found. In spite of steroid pulse therapy and antibiotic treatment, he died of disseminated intravascular coagulopathy.

• Korea Science and Art Forum
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• v.22
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• pp.169-183
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• 2015

As time is rapidly changing, the culture to represent an era is getting more subdivided and complex. Due to cultural diversity, the influence, cause, characteristics which could be understood in individual field centered by space in the past cannot be understood now only by the viewpoint of one field, and it has become difficult to predict and correspond to the change of the future. With the development of information and knowledge delivery system, various cultural contents to form a space are being created and lapsed, but there are a lot of parts which cannot be explained or understood by only one point of view. To inspect these situation, this study is aimed to draw the Tangibility and Intangibility Value causes that became the influence with Jongmyo Shrine, designated from UNESCO at February 1995, a traditional space with historical superiority, analyze the key factors that became the main factor to form the space, and consider the importance of the related factors. The unconstructured data technique which is applied as the method of analysis in this study can be said to be a new value judgement and viewpoint in interpreting the space. Therefore, this study is a new trial to provide a frame for multilaterally interpreting the various traditional space and culture of Korea from the past to the present.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.85-100
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• 2023

Corporate ESG performance (environmental, social, and corporate governance) reflecting a company's strategic sustainability has emerged as one of the main factors in today's investment decisions. The traditional ESG performance rating process is largely performed in a qualitative and subjective manner based on the institution-specific criteria, entailing limitations in reliability, predictability, and timeliness when making investment decisions. This study attempted to predict the corporate ESG rating through automated machine learning based on quantitative and disclosed corporate financial information. Using 12 types (21,360 cases) of market-disclosed financial information and 1,780 ESG measures available through the Korea Institute of Corporate Governance and Sustainability during 2019 to 2021, we suggested a deep neural network prediction model. Our model yielded about 86% of accurate classification performance in predicting ESG rating, showing better performance than other comparative models. This study contributed the literature in a way that the model achieved relatively accurate ESG rating predictions through an automated process using quantitative and publicly available corporate financial information. In terms of practical implications, the general investors can benefit from the prediction accuracy and time efficiency of our proposed model with nominal cost. In addition, this study can be expanded by accumulating more Korean and international data and by developing a more robust and complex model in the future.

• Steel and Composite Structures
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• v.48 no.2
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• pp.207-233
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• 2023

Steel-concrete composite box girder bridges are widely used in the construction of highway and railway bridges both domestically and abroad due to their advantages of being light weight and having a large spanning ability and very large torsional rigidity. Composite box girder bridges exhibit the effects of shear lag, restrained torsion, distortion and interface bidirectional slip under various loads during operation. As one of the most commonly used calculation tools in bridge engineering analysis, one-dimensional models offer the advantages of high calculation efficiency and strong stability. Currently, research on the one-dimensional model of composite beams mainly focuses on simulating interface longitudinal slip and the shear lag effect. There are relatively few studies on the one-dimensional model which can consider the effects of restrained torsion, distortion and interface transverse slip. Additionally, there are few studies on vehicle-bridge integrated systems where a one-dimensional model is used as a tool that only considers the calculations of natural frequency, mode and moving load conditions to study the dynamic response of composite beams. Some scholars have established a dynamic analysis model of a coupled composite beam bridge-train system, but where the composite beam is only simulated using a Euler beam or Timoshenko beam. As a result, it is impossible to comprehensively consider multiple complex force effects, such as shear lag, restrained torsion, distortion and interface bidirectional slip of composite beams. In this paper, a 27 DOF vehicle rigid body model is used to simulate train operation. A two-node 26 DOF finite beam element with composed box beams considering the effects of shear lag, restrained torsion, distortion and interface bidirectional slip is proposed. The dynamic analysis model of the coupled composite box girder bridge-train system is constructed based on the wheel-rail contact relationship of vertical close-fitting and lateral linear creeping slip. Furthermore, the accuracy of the dynamic analysis model is verified via the measured dynamic response data of a practical composite box girder bridge. Finally, the dynamic analysis model is applied in order to study the influence of various mechanical effects on the dynamic performance of the vehicle-bridge system.

• Journal of Life Science
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• v.33 no.7
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• pp.538-548
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• 2023

The research has been conducted on the isolation of antimicrobial compounds from plant natural extracts and their potential application in oral health care products. This study aimed to investigate the antimicrobial mechanism by analyzing the changes in gene expression of Streptococcus mutans, a major oral pathogen, in response to complex compounds extracted from Aralia continentalis and Arctii Semen using organic solvents. Transcriptome analysis (RNA-seq) revealed that both natural extracts commonly upregulated or downregulated the expression of various genes associated with different metabolic and physiological activities. Three genes (SMU_1584c, SMU_2133c, SMU_921), particularly SMU_921 (rcrR), known as a transcription activator of two sugar phosphotransferase systems (PTS) involved in sugar transport and biofilm formation, exhibited consistent high expression levels. Additionally, component analysis of the A. continentalis extract was performed to compare its effects on gene expression changes with the A. Semen extract, and two active compounds were identified through gas chromatography-mass spectrometry (GC-MS) analysis of the active fraction. The n-hexane fraction (ACEH) from the A. continentalis extract exhibited antibacterial specificity against S. mutans, leading to a significant reduction in the viable cell counts of Streptococcus sanguinis and Streptococcus gordonii among the tested multi-species bacterial communities. These findings suggest the broad-spectrum antibacterial activity of the A. continentalis extract and provide essential foundational data for the development of customized antimicrobial materials by elucidating the antibacterial mechanism of the identified active compounds.

• The Journal of Bigdata
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• v.6 no.2
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• pp.151-159
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• 2021

Construction of a blockchain network needs a cumbersome and time consuming activity. To overcome these limitations, global IT companies such as Microsoft are providing cloud-based blockchain services. In this paper, we propose a blockchain-based construction and management tool that enables blockchain developers, blockchain operators, and enterprises to deploy blockchain more comfortably in their infrastructure. This tool is implemented using Hyperledger Fabric, one of the famous private blockchain platforms, and Ansible, an open-source IT automation engine that supports network-wide deployment. Instead of complex and repetitive text commands, the tool provides a user-friendly web dashboard interface that allows users to seamlessly set up, deploy and interact with a blockchain network. With this proposed solution, blockchain developers, operators, and blockchain researchers can more easily build blockchain infrastructure, saving time and cost. To verify the usefulness and convenience of the proposed tool, a blockchain network that conducts electronic voting was built and tested. The construction of a blockchain network, which consists of writing more than 10 setting files and executing commands over hundreds of lines, can be replaced with simple input and click operations in the graphical user interface, saving user convenience and time. The proposed blockchain tool will be used to build trust data infrastructure in various fields such as food safety supply chain construction in the future.

• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.139-150
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• 2023

Terretial LiDAR surveying is highly useful for maintenance of civil facilities as it can easily detect the temporal deformation of structures or topography. However, for river facilities such as levess, it is difficult to detect the deformation of the topography or structure under vegetations due to the influence of vegetation. Vegetation filters can be divided into color filters and morphological filters. In this study, combined filters with color and morphology are developed to improve the accuracy of vegetation filters. 8 color filters, 6 morphological filters, and 4 combined filters are applied to the vegetation removal on the embankment slope, and their accuracy and calculation time are compared. Color filters show a short calculation time, but the accuracy was low in the vegetation area. Morphological filters show high accuracy in the vegetation area, but low accuracy in places with severe local topographical changes such as heavy rocks. Combined filters also show a tendency similar to morphological filters, but in the case of ExGGM, the accuracy is excellent in both the vegetation and rock area. Considering the accuracy and calculation time, the combined filter ExGGM is suitable for general cases, and the shape filter GrMIn or the complex filter ExGISL is suitable for cases where the local topographical change is not severe.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.363-369
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• 2008

Change is inevitable and is a reality of construction projects. Change adjustment includes the cost associated with materials, labor, etc. However, the actions of a contractor can cause a loss of productivity and furthermore can result in disruption of the whole project because of a cumulative or ripple effect. Because of its complicated nature, it becomes a complex issue to determine the cumulative impact (ripple effect) caused by single or multiple change orders. Furthermore, owners and contractors do not always agree on the adjusted contract price for the cumulative impact of the changes. What is needed is a reliable method to identify and quantify the loss of productivity caused by cumulative impact of change orders. This study survey the change orders data in domestic area for public construction and analyze to quantify change order impact. This study developed concepts of "%CO", "%Delta", "%T" to capture change order effect on project and search the relationships between them. Finally, this study find strong relationship between change order and loss.