• Advances in Computational Design
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• v.4 no.3
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• pp.307-326
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• 2019

A low computational cost semi-analytical method is developed, based on eigenfunction expansion, to study the vibration of rectangular plates subjected to a series of moving sprung masses, representing a bridge deck under multiple vehicle or train moving loads. The dynamic effects of the suspension system are taken into account by using flexible connections between the moving masses and the base structure. The accuracy of the proposed method in predicting the dynamic response of a rectangular plate subjected to a series of moving sprung masses is demonstrated compared to the conventional rigid moving mass models. It is shown that the proposed method can considerably improve the computational efficiency of the conventional methods by eliminating a large number of time-varying components in the coupled Ordinary Differential Equations (ODEs) matrices. The dynamic behaviour of the system is then investigated by performing a comprehensive parametric study on the Dynamic Amplification Factor (DAF) of the moving loads using different design parameters. The results indicate that ignoring the flexibility of the suspension system in both moving force and moving mass models may lead to substantially underestimated DAF predictions and therefore unsafe design solutions. This highlights the significance of taking into account the stiffness of the suspension system for accurate estimation of the plate maximum dynamic response in practical applications.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.3
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• pp.675-684
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• 2019

Under the wave of the Fourth Industrial Revolution, developed countries around the world recognize Smart Factory as a core base and strive to enhance the nation's industrial competitiveness through related policies and industry development. Domestic ministries have also set up a strategy for manufacturing innovation 3.0 and are pushing for the expansion of smart factories with 30,000 targets by 2025. In this study, we analyze the practical cases of smart factory security related companies and present the application methods for the same industry. we also intend to contribute to the protectetion of important information in Smart Factory and stable operation.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.239-246
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• 2021

This article substantiates the scientific provisions for modelling the level of Ukraine's public financial security taking into account the impact of budget policy, in the process of which identified indicators of budget policy that significantly affect the public financial security and the factors of budget policy based on regression analysis do not interact closely with each other. A seven-factor regression equation is constructed, which is statistically significant, reliable, economically logical, and devoid of autocorrelation. The objective function of maximizing the level of public financial security is constructed and strategic guidelines of budget policy in the context of Ukraine's public financial security are developed, in particular: optimization of the structure of budget revenues through the expansion of the resource base; reduction of the budget deficit while ensuring faster growth rates of state and local budget revenues compared to their expenditures; optimization of debt serviced from the budget through raising funds from the sale of domestic government bonds, mainly on a long-term basis; minimization of budgetary risks and existing threats to the public financial security by ensuring long-term stability of budgets etc.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.31-40
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• 2021

The increasing number of credit card fraud cases has become a considerable problem since the past decades. This phenomenon is due to the expansion of new technologies, including the increased popularity and volume of online banking transactions and e-commerce. In order to address the problem of credit card fraud detection, a rule-based approach has been widely utilized to detect and guard against fraudulent activities. However, it requires huge computational power and high complexity in defining and building the rule base for pattern matching, in order to precisely identifying the fraud patterns. In addition, it does not come with intelligence and ability in predicting or analysing transaction data in looking for new fraud patterns and strategies. As such, Data Mining and Machine Learning algorithms are proposed to overcome the shortcomings in this paper. The aim of this paper is to highlight the important techniques and methodologies that are employed in fraud detection, while at the same time focusing on the existing literature. Methods such as Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), naïve Bayesian, k-Nearest Neighbour (k-NN), Decision Tree and Frequent Pattern Mining algorithms are reviewed and evaluated for their performance in detecting fraudulent transaction.

• Journal of Korean Medical classics
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• v.34 no.2
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• pp.63-74
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• 2021

Objectives :This paper analyzes the newly discovered manuscripts of the Sanghanjijangdo(傷寒指掌圖). A bibliographic study was carried out to examine the contents and the background of publication. Methods : First, a bibliographical analysis of the Joseon text was conducted. Next, the contents of the composition were compared with the Yuanand early Ming publications of China. Results : 1. The Joseon publication was published based on the original publication from the Yuan period. The Sanghanjijangdo has been cited in several medical texts from early Joseon such as the Euibangyuchwi and Hyangyakjipseongbang. 3. The background for publication of the Sanghanjijangdo is as following. First, it is an introductory text for beginners of Shanghan[cold damage] studies. Second, its contents do not conflict with the specialized Shanghan text that was used as the textbook for the royal physician examination. Third, it contains many Shanghan formulas that could be composed of domestic drugs only. Conclusions : The Sanghanjijangdo could be described as an introductory text for beginners of Shanghan studies that contributed to the expansion of the base of Shanghan studies in 15c mid-Joseon. Publication of this book clearly shows that Shanghan studies in early Joseon was practiced within the scopes of practicality and localization of medicinals.

• Journal of the Korean institute of surface engineering
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• v.55 no.6
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• pp.376-382
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• 2022

Yb₂Si₂O₇ has a coefficient of thermal expansion similar to that of the base material of SiC and has excellent corrosion resistance in a high-temperature oxidizing atmosphere including water vapor, so it is being studied as one of the materials for environmental barrier coatings (EBCs). In this study, Yb₂Si₂O₇ powder granule is deposited using atmospheric plasma spraying (APS) with different Ar/He ratios. Phase formation and microstructural characteristics are investigated with the coated specimens. In the coating layer, the crystallinity decreased, and the amorphous content increased from an increase in the ratio of Ar. In addition, the various types of particles involved by local volatilization of Si according to the Ar/He ratios were identified.

• Korean Journal of Plant Taxonomy
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• v.51 no.1
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• pp.10-17
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• 2021

Invasive alien species management is pivotal for biodiversity conservation. Commelina caroliniana Walter, from the family Commelinaceae, is an alien plant native to the Himalayas and India, but it has been widely introduced around the world, including in the United States, Brazil, Philippines, and Japan. In Korea, the first population was found growing adjacent to agricultural land and farm roads on Jejudo Island, and field observations confirmed the presence of at least nine populations there. It is similar morphologically to C. diffusa Burm. f. but can be distinguished by involucral bracts that are ciliate at the base, hairs on the peduncle and obsolete upper cincinnus, brown spots on its 4-lobed antherode, and seed surfaces that are smooth to slightly alveolate. It was determined to have an invasiveness low score of 8 according to the Korean 'Invasive Alien Plant Risk Assessment', suggesting that it may spread to natural habitats. Although the current distribution of C. caroliniana is restricted to Jeju-si, it has spread dramatically in many other areas of the world. At present, it has had a limited impact on the local environment, but local and regulatory authorities should pay close attention to this plant and take measures to prevent its expansion in the future.

• Journal of the Korean institute of surface engineering
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• v.56 no.6
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• pp.443-450
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• 2023

SiC/SiC_f CMC is vulnerable to water vapor corrosion at a high temperature of 1500℃. So, EBC (Environmental Barrier Coating) materials are required to protect Si-based CMCs. Ytterbium silicates are reported to have coefficient of thermal expansion (CTE) similar to that of the base material, such as SiC/SiC_f CMC. When the EBC are materials exposed to high temperature environment, the interface between ytterbium silicates and SiC/SiC_f CMC is not separated, and the coating purpose can be safely achieved. For the perspective of EBC applications, thermally grown oxide (TGO) layer with different CTE is formed by the reaction with water vapor in EBC, which leads to a decrease in life time. In this study, we prepare two types of ytterbium silicates to observe the corrosion behavior during the expose to high temperature and water vapor. In order to observe this behavior, the steam-jet furnace is prepared. In addition, phase formation of these ytterbium silicates is analyzed with microstructures by the before/after steam-jet evaluation at 1500℃ for 100 h.

• Korean Journal of Materials Research
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• v.1 no.3
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• pp.156-167
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• 1991

The purpose of this study is to develop a data base for material selection of turbofan engines, which is preferred in these days on many application due to their high performance with economical operation. Hundreds of Super Alloys have been developed by this time, each having special properties. Since it is very difficult task for a design engineer to select materials of adequate Properties for specific engine components, a good data bate is strongly desired to manage informations on various kinds of materials. However, no basic research is reported in this area so far in our country. The operating conditions such as temperature, pressure, rpm of spools are assumed to be provided by other mechanical studies. Creep rupture strength, corrosion resistance, yield strength, thermal expansion, melting point, etc., are considered as typical properties in this study to search a group of candidate materials. Formability, manufacturing or purchase cost can also be important variables to be considered. As a result of this study, a user-friendly computer program has been developed for input of new material information, interactive material selection, and output of selection results. Finally, discussion is presented from. the viewpoint of materials engineering. A method to evaluate the performance of the selected materials is also suggested.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.