• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.72-77
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• 2001

The use of hexagonal ceramic inserts for copper extrusion dies offers significant technical and economic advantages over other forms of manufacture. In this paper the data on the loading of the tools is determined from a commercial FEM package as the contact stress distribution on the die-workpiece interface and as temperature distributions in the die. This data can be processed as load input data for a finite element die-stress analysis. Process simulation and stress analysis are thus combined during the design, and a data exchange program has been developed that enables optimal design of the dies taking into account the elastic deflections generated in shrink fitting the die inserts and that caused by the stresses generated in the process. The stress analysis of the dies is used to determine the stress conditions on the ceramic insert by considering contact and interference effects under both mechanical and thermal loads.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.306-311
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• 2024

In today's globalized economy, franchise companies are strategically preparing to expand beyond domestic markets into international markets. When expanding overseas, it is crucial that the brand identity of a franchise company is well established. Through marketing activities, the brand's value must be enhanced to build a positive image of the brand, and all these activities are referred to as brand management. This study aimed to analyze the relationship between brand management and international expansion, utilizing big data analysis techniques with Textom. A total of 31,564 pieces of data were collected for the period from January 1, 2024, to May 1, 2024, and analyzed after undergoing a refinement process. The analysis results showed that brand management is an essential element in the strategic process of international expansion, and subsequent studies should focus on qualitative research

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

• Nuclear Engineering and Technology
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• v.48 no.4
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• pp.1047-1057
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• 2016

Design engineering process for field programmable gate array (FPGA)-based reactor trip functions are developed in this work. The process discussed in this work is based on the systems engineering approach. The overall design process is effectively implemented by combining with design and implementation processes. It transforms its overall development process from traditional V-model to Y-model. This approach gives the benefit of concurrent engineering of design work with software implementation. As a result, it reduces development time and effort. The design engineering process consisted of five activities, which are performed and discussed: needs/systems analysis; requirement analysis; functional analysis; design synthesis; and design verification and validation. Those activities are used to develop FPGA-based reactor bistable trip functions that trigger reactor trip when the process input value exceeds the setpoint. To implement design synthesis effectively, a model-based design technique is implied. The finite-state machine with data path structural modeling technique together with very high speed integrated circuit hardware description language and the Aldec Active-HDL tool are used to design, model, and verify the reactor bistable trip functions for nuclear power plants.

• Journal of the Korean Society of Earth Science Education
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• v.17 no.2
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• pp.153-167
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• 2024

This study explored the errors and context occurred during high school students' data analysis processes. For the study, 222 data inquiry reports produced by 74 students from 'A' High School were collected and explored the detailed error types in the data analysis processes such as data collection and preprocessing, data representation, and data interpretation. The results of study found that in the data interpretation process, students had a somewhat insufficient understanding of seasonal variations and periodic patterns about weather elements. And, various types of errors were identified in the data representation process, such as basic unit in graphs, legend settings, trend lines. The causes of these errors are the feature of authoring tools, misconceptions related to weather elements, and cognitive biases, etc. Based on the study's results, educational implications for big data education, a significant topic in future science education, were derived. And related follow-up studies were suggested.

• Smart Structures and Systems
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• v.32 no.4
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.449-451
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• 2003

The estimation of time-series data is fundamental process in many data analysis cases. However, the unwanted measurement error is usually added to true data, so that the exact estimation depends on efficient method to eliminate the error components. The wavelet transform method nowadays is expected to improve the accuracy of estimation, because it is able to decompose and analyze the data in various resolutions. Therefore, the wavelet based Kalman filter method for the estimation of time-series data is proposed in this paper. The wavelet transform separates the data in accordance with frequency bandwidth, and the detail wavelet coefficient reflects the stochastic process of error components. This property makes it possible to obtain the covariance of measurement error. We attempt the estimation of true data through recursive Kalman filtering algorithm with the obtained covariance value. The procedure is verified with the fundamental example of Brownian walk process.

• Journal of the Korea Safety Management & Science
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• v.13 no.4
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• pp.9-16
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• 2011

Modern systems become more complex and the demand for systems safety goes up sharply. Thus, the proper handling of the safety requirements in the systems design is getting greatly increased attention these days. Hazard analysis has been one of the active areas of research in connection with systems safety. In this paper, we study a subject on how the hazard analysis results can be incorporated in the systems design. To this end we set up a goal on how to systematically generate safety requirements that should reflect hazard analysis results and be implemented in the systems design and development. To do so, we first review the process for systems design and suggest the associated Model. Then the process and results of hazard analysis are analyzed and Modeled particularly with emphasis on the safety data. The resulting data Model incorporating both the hazard analysis and system life cycle is used in the generation of safety requirements. Based on the developed data Model, the generation of the requirements, the construction of requirements DB, and the change management later on is demonstrated through the use of a computer-aided software tool.

• Transactions of Materials Processing
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• v.19 no.2
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• pp.101-106
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• 2010

CB100 is one of the channel type products in the steel beam. In this study, rolling process of CB100 is analyzed by 3D FEM simulation and rolling process. FEM simulation result is compared with rolling process data. Also the intermediate & finishing roll stress analysis is carried out and the suitability of the roll through roll stress resultant analysis is evaluated. In order to decrease the roll stress, new pass schedule is developed for stable load balance between intermediate and finishing rolling stand. Therefore new rolling pass schedule is verified by the analysis results of rolling process and roll stress. By the analysis results, the credibility of rolling process analysis was obtained and it was determined that the possibility of roll damage between intermediate and finishing mill was high. So the new pass schedule was developed. Through the result of rolling process and roll stress analysis, it was obtained that the reduction of roll stress and stable load balance.

• Journal of Korean Medical classics
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• v.29 no.2
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• pp.79-90
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• 2016

Objectives : Treatment using foods has already been recorded since the time of Zhou Dynasty of China. Modifications in the cooking process of medicinal food or manufactural process of herbal medicines are accompanied by the alterations in the ingredients that affect the actual efficacies of medicinal food or herbal medicine, and may have marked effects on the patients including the difficulties that may be experienced in consuming the food or taking the medicine. Therefore, systemic management is essential in such processes. Accordingly, management of such knowledge system must be standardized and conveniently administered by grafting IT technology. This study aims to overcome the problem of the failure of the knowledge system on the material-oriented medicinal herbs to apply the knowledge on the cooking process that impart marked influence on the actual efficacies of the medicinal herbs. Methods : Therefore, analysis of the cooking process or manufacturing processes of prescriptions was executed by using the morphological analysis method in natural language. In this study, we aimed to make data structure of the terminologies that represent manufacture process of prescription and medicinal food. The data structure is combinations of smallest unit in natural language. We made the database by analyzing morpheme of the natural language to express the manufacture process of prescription and medicinal food. Results & Conclusions : As the results, we can express making process of Cheonjin-won, Guseon-wangdogo and Sanyagbaegboglyeongtalagjuk in DB. It was concluded that the development of DB through the extraction of a total of 15 types of concepts including 'order', 'action' and 'continuous action', etc. was helpful in systematization of the knowledge on medicinal herbs including the manufacturing process.