• English Language & Literature Teaching
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• v.8 no.1
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• pp.103-124
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• 2002

For the current study, five Asian English teachers participated in their case studies to investigate an in-depth understanding of their beliefs about teaching and learning English as a foreign language. Data were collected through structured and unstructured interviews, written documents, observations of teacher-participants' micro teaching, a research methodology journal and a self-reflection journal. This study described the beliefs that Asian English teachers brought to the teacher preparation program and examined to see if these teacher-participants who were involved in case studies perceived change in their beliefs. The study found that formal and informal learning experiences greatly shaped the way teacher-participants' beliefs about the way learning and teaching ought to be. In addition, early experiences of learning and teaching influenced teacher-participants' change in beliefs.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.6
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• pp.749-756
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• 2019

Big data is structured and unstructured data that is so difficult to collect, store, and so on due to the huge amount of data. Many institutions, including universities, are building student convergence systems to foster talents for data science and AI convergence, but there is an absolute lack of research on what kind of education is needed and what kind of education is required for students. Therefore, in this paper, after conducting the correlation analysis based on the questionnaire on basic surveys and courses to improve the curriculum by grasping the satisfaction and demands of the participants in the "2019 Big Data Youth Talent Training Course" held at K University, Regression analysis was performed. As a result of the study, the higher the satisfaction level, the satisfaction with class or job connection, and the self-development, the more positive the evaluation of program efficiency.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.285-295
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• 2022

The purpose of this study is to prepare primary data for providing smooth and systematic rehabilitation sports services by confirming the opinions of instructors experienced in the field of disability sports before the implementation of Article 15 'Rehabilitation sports' of the 'Act on Guarantee of Right to Health and Access to Health Services for Persons with Disabilities. In-depth interviews were conducted as a research method, and qualitative analysis was conducted on the contents of the interview. The in-depth interview is unstructured, allowing disability sports instructor to freely present their opinions on difficulties experienced while operating the program, necessary matters for rehabilitation sports implementation. We transcribed the recording data of the in-depth interview and coded the opinions through the thematic analysis method among qualitative research methods. As a result, the final 104 opinions were used and classified into 9 categories; rehabilitation sports goal, training rehabilitation sports instructor, evaluation items and educational guidelines, relationships with program participants, facilities utilization, effects, the timing of provision, and doctor roles.

• Journal of Radiation Protection and Research
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• v.41 no.4
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• pp.389-394
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• 2016

Background: Tetrahedral-mesh geometries can be used in the MCNP code, but the MCNP code accepts only the geometry in the Abaqus input file format; hence, the existing tetrahedral-mesh models first need to be converted to the Abacus input file format to be used in the MCNP code. In the present study, we developed a simple but useful computer program, TET2MCNP, for converting TetGen-generated tetrahedral-mesh models to the Abacus input file format. Materials and Methods: TET2MCNP is written in C++ and contains two components: one for converting a TetGen output file to the Abacus input file and the other for the reverse conversion process. The TET2MCP program also produces an MCNP input file. Further, the program provides some MCNP-specific functions: the maximum number of elements (i.e., tetrahedrons) per part can be limited, and the material density of each element can be transferred to the MCNP input file. Results and Discussion: To test the developed program, two tetrahedral-mesh models were generated using TetGen and converted to the Abaqus input file format using TET2MCNP. Subsequently, the converted files were used in the MCNP code to calculate the object- and organ-averaged absorbed dose in the sphere and phantom, respectively. The results show that the converted models provide, within statistical uncertainties, identical dose values to those obtained using the PHITS code, which uses the original tetrahedral-mesh models produced by the TetGen program. The results show that the developed program can successfully convert TetGen tetrahedral-mesh models to Abacus input files. Conclusion: In the present study, we have developed a computer program, TET2MCNP, which can be used to convert TetGen-generated tetrahedral-mesh models to the Abaqus input file format for use in the MCNP code. We believe this program will be used by many MCNP users for implementing complex tetrahedral-mesh models, including computational human phantoms, in the MCNP code.

• Journal of the Korea Fashion and Costume Design Association
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• v.23 no.2
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• pp.17-28
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• 2021

The baby-tech industry, which combines IT with existing parenting product, is attracting increasing amounts of attention. Consequently various types of baby products incorporating functionality and design are being launched. In recent years, particularly as the market segments increases for babywearing products, parenting products that account for the child's comfort and parents' convenience are required. Therefore, this study examines the characteristics and consumer perception of babywear products, which are important for the emotional stability, development, and rearing of children. The study utilizes text mining and a network analysis by collecting unstructured text data. An examination of the network, based on the frequency of keywords for each babywear product and the degree of the connection to the centering index, revealed that consumers value convenience and price when purchasing products. The consumer perception and consideration factors that appear individually according to the product were also identified. In addition, studying body parts with high TF-IDF values revealed a difference in the body parts considered by consumers for each product. Lastly, through the visualization data based on the keywords that appeared in public, commonly appearing keywords, and those that appeared individually were examined. Through SNS, product characteristics as well as a new parenting culture that shared child-rearing routines were confirmed. This study suggests planning and marketing directions for the development of babywear products that meet consumer needs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.171-179
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• 2022

Self-Modifying-Code is a code that changes the code by itself during execution time. This technique is particularly abused by malicious code to bypass static analysis. Therefor, in order to effectively detect such malicious codes, it is important to identify self-modifying-codes. In the meantime, Self-modify-codes have been analyzed using dynamic analysis methods, but this is time-consuming and costly. If static analysis can detect self-modifying-code it will be of great help to malicious code analysis. In this paper, we propose a static analysis method to detect self-modified code for binary executable programs converted to LLVM IR and apply this method by making a self-modifying-code benchmark. As a result of the experiment in this paper, the designed static analysis method was effective for the standardized LLVM IR program that was compiled and converted to the benchmark program. However, there was a limitation in that it was difficult to detect the self-modifying-code for the unstructured LLVM IR program in which the binary was lifted and transformed. To overcome this, we need an effective way to lift the binary code.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.369-376
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• 2021

With the development of artificial intelligence (AI) technology, discussions on the use of artificial intelligence are actively taking place in many fields, and various policies for nurturing artificial intelligence talents are being promoted in the field of education. In this study, we propose a robot programming framework using artificial intelligence technology, and based on this, we use Python, which is used frequently in the machine learning field, and an educational robot that is highly utilized in the field of education to provide artificial intelligence. (AI) education program was proposed. The level of autonomous driving (levels 0-5) suggested by the International Society of Automotive Engineers (SAE) is simplified to four levels, and based on this, the camera attached to the robot recognizes and detects lines (objects). The goal was to make a line detector that can move by itself. The developed program is not a standardized form of solving a given problem by simply using a specific programming language, but has the experience of defining complex and unstructured problems in life autonomously and solving them based on artificial intelligence (AI) technology. It is meaningful.

• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.65-70
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• 2024

As the interest in AI education grows, researchers have made efforts to implement AI education programs. However, research targeting pre-service teachers has been limited thus far. Therefore, this study was conducted to develop an AI literacy education program for preservice secondary teachers. The research results revealed that the weekly topics included the definition and applications of AI, analysis of intelligent agents, the importance of data, understanding machine learning, hands-on exercises on prediction and classification, hands-on exercises on clustering and classification, hands-on exercises on unstructured data, understanding deep learning, application of deep learning algorithms, fairness, transparency, accountability, safety, and social integration. Through this research, it is hoped that AI literacy education programs for preservice teachers will be expanded. In the future, it is anticipated that follow-up studies will be conducted to implement relevant education in teacher training institutions and analyze its effectiveness.

• Journal of computational fluids engineering
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• v.19 no.3
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• pp.52-61
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• 2014

The present paper deals with the efficient computation of higher-order CFD methods for compressible flow using graphics processing units (GPU). The higher-order CFD methods, such as discontinuous Galerkin (DG) methods and correction procedure via reconstruction (CPR) methods, can realize arbitrary higher-order accuracy with compact stencil on unstructured mesh. However, they require much more computational costs compared to the widely used finite volume methods (FVM). Graphics processing unit, consisting of hundreds or thousands small cores, is apt to massive parallel computations of compressible flow based on the higher-order CFD methods and can reduce computational time greatly. Higher-order multi-dimensional limiting process (MLP) is applied for the robust control of numerical oscillations around shock discontinuity and implemented efficiently on GPU. The program is written and optimized in CUDA library offered from NVIDIA. The whole algorithms are implemented to guarantee accurate and efficient computations for parallel programming on shared-memory model of GPU. The extensive numerical experiments validates that the GPU successfully accelerates computing compressible flow using higher-order method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1071-1076
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• 2003

In this work, we propose a new framework of robot control for a variety of applications to our unstructured everyday environments. Programming robots can be a very time-consuming process and seems almost impossible for ordinary end users. To cope with this, this work is to provide a software framework for building robot application programs automatically, where we have robots learn how to accomplish a commanded task from the object. An integrated sensing and computing tag is embedded into every single object in the environment. In the robot controller, only the basic software libraries for low-level robot motion control are provided from the robot manufacturer. The main contributions of this work is to develop a server platform that we call Omniscient Server that generates the application programs and send them to the robot controller through the network. The object-related information from the object server merges into robot control software to generate a detailed application program based on the task commands from the human. We have built a test bed and demonstrated that a robot can perform a common household task within the proposed framework.