• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.173-191
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• 1999

In this paper we suggest the visualized regression diagnosis tool. The tool is developed by Hangul Delphi on the basis of windows, so users can easily make use of this tool though they do not have the expert knowledge about statistics and computer. Especially, to apply this tool to teaching regression analysis or data analysis, we offer various residual plots in the tool and show the results of analysis graphically.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.172-176
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• 2015

In this research, a tool was developed to automate one-dimensional finite element analysis (1D FEA) for design of a machine tool spindle. Based on object-oriented programing, this tool employs the objects of a CAD system to construct a geometric model and then to convert it into the FE model of 1D beams at the workbenches of the CAD system with minimum data to define the spindle such as bearing positions and cross-sections of the shaft. Graphic user interfaces were developed for users to interact with the tool. This tool is helpful in identifying a near optimal design of the spindle with the automation of the FEA process with numerous design changes in minimum time and efforts. It is also expected to allow even design engineers to perform the FEA in search of an optimal design of the machine tool spindle.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.917-925
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• 2021

This study aims to specify a constructivism-based instructional method using a modular data analysis tool. The value and meaning of a modular data analysis tool have been examined to be applied in the national curriculum for artificial intelligence education and the process of cultivating problem-solving ability based on computational thinking. The modular data analysis tool visually expresses the cognitive thinking process that forms the schema in equilibrating through assimilation and adjustment. Artificial intelligence education has features that embody abstract knowledge and structure the data analysis module through the represented schema as a BlackBox implemented as an algorithm. Therefore, the value of the modular data analysis tool could be examined because it has the advantage of connecting the conceptual and implicit schema.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.169-172
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• 1995

In optmizing cutting condition for face milling operation, tool wear is an important maching factor. For the purpose of establishing the relationship between various maching factor and tool wear, cutting tests have been performed. As a result, hardness and chemical composition of workpiece material, chemical compositition and grain size of cutting tool and cutting speed have been selected as machining factor. In addition, relationship between feed rate and workpiece hardness has been observed. Prior to utilizing cutting condition recommended by 'Machining Data Hardbook(MDH)' as a Knowledge base, an analysis for the validity has been provided. Based on this analysis, tool life criteria applied by MDH has been modifiied. Finaly, using MDH recommended data for neural network trainning, we can compensate the result form the trained neural network for optimizing cutting condition for some given workpice and cutting tool.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.65-75
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• 2016

In this paper, we present a novel approach to help MSR researchers obtain necessary data with a tool, termed General Purpose Extractor for Source code (GPES). GPES has a single function extracts high-quality data, e.g., the version history, abstract syntax tree (AST), changed code diff, and software quality metrics. Moreover, features such as an AST of other languages or new software metrics can be extended easily given that GPES has a flexible data model and a component-based design. We conducted several case studies to evaluate the usefulness and effectiveness of our tool. Case studies show that researchers can reduce the overall cost of data analysis by transforming the data into the required formats.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.72-80
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• 2019

In this task, the tool dynamometer design and manufacture, and the Ansys S/W structural analysis program for tool attachment that satisfies the cutting force measurement requirements of the tool dynamometer system are used to determine the cutting force generated by metal cutting using 3-axis static structural analysis and the LabVIEW system. The cutting power in a cutting process using a milling tool for processing metals provides useful information for understanding the processing, optimization, tool status monitoring, and tool design. Thus, various methods of measuring cutting power have been proposed. The device consists of a strain-gauge-based sensor fitted to a new design force sensing element, which is then placed in a force reduction. The force-sensing element is designed as a symmetrical cross beam with four arms of a rectangular parallel line. Furthermore, data duplication is eliminated by the appropriate setting the strain gauge attachment position and the construction of a suitable Wheatstone full-bridge circuit. This device is intended for use with rotating spindles such as milling tools. Verification and machining tests were performed to determine the static and dynamic characteristics of the tool dynamometer. The verification tests were performed by analyzing the difference between strain data measured by weight and that derived by theoretical calculations. Processing test was performed by attaching a tool dynamometer to the MCT to analyze data generated by the measuring equipment during machining. To maintain high productivity and precision, the system monitors and suppresses process disturbances such as chatter vibration, imbalances, overload, collision, forced vibration due to tool failure, and excessive tool wear; additionally, a tool dynamometer with a high signal-to-noise ratio is provided.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.1
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• pp.87-92
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• 2010

Micromachining technology using a ultra-precision micromachining system is widely applied in the fields of optics, biotechnology and analytical chemistry, etc. specially in microfabrication of fresnel lens, light guide panels of TFT-LED and PDP ribs with micro-patterns, machining errors have an effect on the performance of those products. The deflection of tool and tool holder is known to be one of the very important factors that is due to machining errors in micromachining. The deflections of diamond tool and tool holder used in micro-grooving are analysed by FEM. We analysed by FEM. With an linearity valuation of FEM, deflection of tool and tool holder is calculated by using the data of cutting force which is acquired from micro-V groove machining experiments in micromachining system.

• Journal of Engineering Education Research
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• v.26 no.4
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• pp.22-35
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• 2023

As information and communication technology has developed remarkably, it has become possible to analyze various types of large-volume data generated at a speed close to real time, and based on this, reliable value creation has become possible. Such big data analysis is becoming an important means of supporting decision-making based on scientific figures. The purpose of this study is to develop a big data analysis tool that can analyze large amounts of data generated through engineering education. The tasks of this study are as follows. First, a database is designed to store the information of entries in the National Creative Capstone Design Contest. Second, the pre-processing process is checked for analysis with big data analysis tools. Finally, analyze the data using the developed big data analysis tool. In this study, 1,784 works submitted to the National Creative Comprehensive Design Contest from 2014 to 2019 were analyzed. As a result of selecting the top 10 words through topic analysis, 'robot' ranked first from 2014 to 2019, and energy, drones, ultrasound, solar energy, and IoT appeared with high frequency. This result seems to reflect the current core topics and technology trends of the 4th Industrial Revolution. In addition, it seems that due to the nature of the Capstone Design Contest, students majoring in electrical/electronic, computer/information and communication engineering, mechanical engineering, and chemical/new materials engineering who can submit complete products for problem solving were selected. The significance of this study is that the results of this study can be used in the field of engineering education as basic data for the development of educational contents and teaching methods that reflect industry and technology trends. Furthermore, it is expected that the results of big data analysis related to engineering education can be used as a means of preparing preemptive countermeasures in establishing education policies that reflect social changes.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.265-273
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• 2020

In this paper, to design a basic data science practice curriculum as a liberal arts subject for non-majors, we proposed an educational method using an Excel(spreadsheet) data analysis tool. Tools for data collection, data processing, and data analysis include Excel, R, Python, and Structured Query Language (SQL). When it comes to practicing data science, R, Python and SQL need to understand programming languages and data structures together. On the other hand, the Excel tool is a data analysis tool familiar to the general public, and it does not have the burden of learning a programming language. And if you practice basic data science practice with Excel, you have the advantage of being able to concentrate on acquiring data science content. In this paper, a basic data science practice curriculum for one semester and weekly Excel practice contents were proposed. And, to demonstrate the substance of the educational content, examples of Linear Regression Analysis were presented using Excel data analysis tools.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.321-324
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• 2022

The Korean halibut farming industry suffer from price instability and demand decrease due to various environmental and social issues. It is urgent to predict the appropriate amount of halibut production. However, it is not easy for employments working in the halibut farming industry to handle statistical tools in order to perform the prediction. In this paper, we implemented a Excel-based regression analysis tool that allows users to get a regression analysis result by just entering historical data in a sheet. Our tool will reduce workloads of employments working in the halibut farming industry by enabling them to perform a regression analysis with Excel on-the-fly. This study expect that by using the tool the halibut farming industry cope actively with the real-time change in the industry.