• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.451-455
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• 2010

In this study, the various supply system of LRE such as a feed-line, an elbow, and an orifice as a part of integrated analyzing has been combined to develop the performance analysis program. Computational analysis has been used to compare the results and to verify the validity and limitation conditions of the performance analysis program by changing orifice positions.

• International Journal of Contents
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• v.15 no.1
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• pp.39-51
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• 2019

Spontaneous speech provides rich information defining the linguistic characteristics of individuals. As such, computational analysis of speech would enhance the efficiency involved in evaluating patients' speech. This study aims to provide a method to differentiate the persons with and without aphasia based on language usage. Ten aphasic patients and their counterpart normal controls participated, and they were all tasked to describe a set of given words. Their utterances were linguistically processed and compared to each other. Computational analyses from PCA (Principle Component Analysis) to machine learning were conducted to select the relevant linguistic features, and consequently to classify the two groups based on the features selected. It was found that functional words, not content words, were the main differentiator of the two groups. The most viable discriminators were demonstratives, function words, sentence final endings, and postpositions. The machine learning classification model was found to be quite accurate (90%), and to impressively be stable. This study is noteworthy as it is the first attempt that uses computational analysis to characterize the word usage patterns in Korean aphasic patients, thereby discriminating from the normal group.

• Journal of Internet Computing and Services
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• v.19 no.2
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• pp.57-67
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• 2018

The $4^{th}$ industrial revolution has brought innovation in the educational environment. The purpose of this study is to verify the educational effectiveness of smart learning environment especially with the computational thinking. A big data analysis was performed to confirm that computational thinking is the one to prepare the 4th industrial revolution. To teach computational thinking at university, educational design should be careful. This study verified the relationship between improvement of computational thinking ability and major of students with coding education. There was difference in effectiveness of the coding education depending on the major of students, it means students must be guaranteed to be educated by the differentiated coding education for different major. This study extracted factors of computational thinking through literature review. Thirteen research hypotheses were applied for the statistical analysis in R language. It was proved that expectation of class and improvement of abstraction ability and algorithmic thinking ability had mediation effect to the relationship between knowledge acquisition and problem-solving abilities. Based on this study, effectiveness of education can be improved, and it will lead to produce a lot of distinguished students who are ready for the 4th industrial revolution.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.205-209
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• 2008

In this study, very accurate computational mechatronics method has been developed for typical N.C. machine model applying to manufacturing industry in these days. Computation analysis of high speed machine tools like N.C. machine needs consideration about mechatronical features because the machine shows close interaction between dynamic behavior of the mechanical structure, drives and numerical control. For this, nonlinear structural analysis tools based on FEM are linked numerical control program to control the dynamic behavior. In this study, we studied the dynamic feature of N.C. machine by using SAMCEF as nonlinear computational structural analysis tool and simulink as drivers.

• Journal of computational fluids engineering
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• v.8 no.1
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• pp.16-22
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• 2003

The present study introduces an architecture for performing efficient numerical analysis by using the Internet and three reconstructing methods of existing numerical analysis codes were presented in order to utilize the architecture. These methods were implemented into a computational fluid dynamics program for solving two-dimensional transient flow problems with free surface. The program was reconstructed with Java technologies and compared with the original one. This study will be a preparation for numerical analysis to participate in web services for engineering.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.416-417
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• 2017

In this study, Three-Dimensional igniter modeling and computational Analysis for PMD internal flow analysis have been conducted. The igniter modeling used the lumped parameter method and the computational analysis has been performed in conjunction with the commercial program STAR-CCM+. The result of computational analysis has been compared with those of CBT and PMD experiments.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1993.04a
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• pp.101-108
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• 1993

A simplified dynamic analysis method for high-rise building structures is proposed in this study. In the proposed method, member forces are obtained through static analysis using story forces derived from story shear forces which are obtained using dynamic analysis procedure. Major advantage of the proposed method is in the convenience in load combinations for design analysis.

• Composites Research
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• v.36 no.5
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• pp.329-334
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• 2023

The classical multiscale finite element (FE² ) method involves iterative calculations of micro-boundary value problems for representative volume elements at every integration point in macro scale, making it a computationally time and data storage space. To overcome this, we developed the data-driven multiscale analysis method based on the mean-field homogenization (MFH). Data-driven computational mechanics (DDCM) analysis is a model-free approach that directly utilizes strain-stress datasets. For performing multiscale analysis, we efficiently construct a strain-stress database for the microstructure of composite materials using mean-field homogenization and conduct data-driven computational mechanics simulations based on this database. In this paper, we apply the developed multiscale analysis framework to an example, confirming the results of data-driven computational mechanics simulations considering the microstructure of a hyperelastic composite material. Therefore, the application of data-driven computational mechanics approach in multiscale analysis can be applied to various materials and structures, opening up new possibilities for multiscale analysis research and applications.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.543-550
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• 2019

In 2006, Janet Wing defined computational thinking and operated SW education as a formal curriculum in the UK in 2013. This study collected related research papers by using computational thinking, which has recently increased in importance, and analyzed it using text mining. In the first, CONCOR analysis was conducted with the keyword of computational thinking. In the second, text mining of the components of computational thinking was selected by the repr23esentative academic journals at domestic and foreign. As a result of the two-time analysis, first, abstraction, algorithm, data processing, problem decomposition, and pattern recognition were the core of the study of computational thinking component. Second, research on convergence education centered on computational thinking and science and mathematics subjects was actively conducted. Third, research on computational thinking has been expanding since 2010. Research and development of the classification and definition of computational thinking and components and applying them to education sites should be conducted steadily.

• The Journal of Korean Association of Computer Education
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• v.18 no.5
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• pp.25-34
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• 2015

The purpose of this research is to suggest the method of code analysis for evaluating learners' projects in computational thinking(CT) education. Recently, block programming tools are applied to K-12 SW education, this study considered the assessment method for evaluating students' levels and learning about CT concepts through analyzing codes of the Scratch projects that students created. As a result from the analysis of 45 projects of novices, it showed the bad coding patterns of novices and verified that it is possible to evaluate students' learning about CT concepts through the analysis of their codes. The higher learner's level, the greater scores of logical thinking, synchronization, flow control, and data representation. This result is able to apply to student assessment of CT concepts in K-12 SW education.