• Communications of the Korean Mathematical Society
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• v.21 no.3
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• pp.429-432
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• 2006

We use Cauchy's functional equation to construct a new non-measurable set which is a (vector) subspace of \mathbb{R}$ and is of a codimensiion 1, considering \mathbb{R}$, the set of real numbers, as a vector space over a field \mathbb{Q}$ of rational numbers. Moreover, we show that \mathbb{R}$ can be partitioned into a countable family of disjoint non-measurable subsets.

• Journal of Engineering Education Research
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• v.21 no.1
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• pp.27-36
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• 2018

This study aims to deduce operational implication of R-WeSET program through women students in science & engineering and companies's perception and assessment on the basis of NCS key competency. The significant results are as follows. Firstly, companies and women students in science & engineering share a similar perception on importance of NCS key competencies. The programs should be reviewed and improved for women students who are truly aware of companies' needs. Secondly, the main areas of NCS key competency that are poor in companies' perception are 'positive thinking & drive', 'creativity & challenge spirit', 'communication skills' and 'problem-solving skills'. To enhance these weak skills, activating the actual programs such as "Convergence Design Camp", "Field Adaptability Improvement" and developing the new communication program are required. Lastly, most of women students have attained the satisfying result from "Field Competency Reinforcement Program". Especially, "Industry Field Training" shared the great progresses on all skills of key competency, hence why the progressive model should be developed in the future. This study figures out who's the right person for the 4th Industrial Revolution era, producing a meaningful result in order to change in the higher education system of women students and to grow human resources who will contribute to the community and company.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1627-1648
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• 2012

We propose an adaptive method for detecting plagiarized pairs from a large set of source code. This method is adaptive in that it uses an adaptive algorithm and it provides an adaptive threshold for determining plagiarism. Conventional algorithms are based on greedy string tiling or on local alignments of two code strings. However, most of them are not adaptive; they do not consider the characteristics of the program set, thereby causing a problem for a program set in which all the programs are inherently similar. We propose adaptive local alignment-a variant of local alignment that uses an adaptive similarity matrix. Each entry of this matrix is the logarithm of the probabilities of the keywords based on their frequency in a given program set. We also propose an adaptive threshold based on the local outlier factor (LOF), which represents the likelihood of an entity being an outlier. Experimental results indicate that our method is more sensitive than JPlag, which uses greedy string tiling for detecting plagiarism-suspected code pairs. Further, the adaptive threshold based on the LOF is shown to be effective, and the detection performance shows high sensitivity with negligible loss of specificity, compared with that using a fixed threshold.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1798-1805
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• 2010

The Railroad Safety Technology R&D Program has been supported by the Ministry of Land, Transport and Maritime Affairs. The Program consists of dozen or more projects and thus is quite complex, which requires effective project management. This paper is discussing how to effectively manage the railroad safety technology R&D program based on systems engineering management plan (SEMP). The key issues dealt in this paper include the SE management, requirements management, verification and validation, integrated data base management, and traceability management. To achieve the goal, we first defined an appropriate SE process to be adopted in the program and the result was documented in the systems engineering management plan. According to the process defined, we set up the environmental frame in database. Using the database and SEMP, each project of the program was verified with respect to the corresponding requirements utilizing the traceability. All these efforts were carried out using a computer-aided SE tool, which enables efficient management of complex database.

• Proceedings of the KIEE Conference
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• 1995.07c
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• pp.1229-1231
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• 1995

XLPE cable, which has excellent electrical and thermal performance, has been widely used for HV transmission & distribution lines. The most important thing to produce the cable products having good performance is to set the optimal operating conditions of cable machinery. Because it is very difficult to measure the temperature of cable under curing process practically, it is necessary to evaluate the cable temperature by using the method to simulate real conditions numerically. In this work, We investigate the basic theory on transient heat transfer between curing tube and cable for making a numerical simulation program using computer. In this program, a differential equation is approximated by a infinite differential method and a few assumptions are used to simplify the model and minimize the calculation time of program.

• Bulletin of the Korean Chemical Society
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• v.33 no.2
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• pp.613-619
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• 2012

We applied several machine learning methods for developing QSAR models for prediction of acute toxicity to fathead minnow. The multiple linear regression (MLR) and artificial neural network (ANN) method were applied to predict 96 h $LC_{50}$ (median lethal concentration) of 555 chemical compounds. Molecular descriptors based on 2D chemical structure were calculated by PreADMET program. The recursive partitioning (RP) model was used for grouping of mode of actions as reactive or narcosis, followed by MLR method of chemicals within the same mode of action. The MLR, ANN, and two RP-MLR models possessed correlation coefficients ($R^2$) as 0.553, 0.618, 0.632, and 0.605 on test set, respectively. The consensus model of ANN and two RP-MLR models was used as the best model on training set and showed good predictivity ($R^2$=0.663) on the test set.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1451-1458
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• 2013

This paper deals with the programs and algorithms that generate the full data set that satisfy the basic combinatorial requirement of combination, permutation, partial permutation or shortly r-permutation, which are used in the application of the total data testing or the simulation input. We search the programs able to meet the rules which is permutations and combinations, r-permutations, select the fastest program by field. With further study, we developed a new program reducing the time required to processing. Our research performs the following pre-study. Firstly, hundreds of algorithms and programs in the internet are collected and corrected to be executable. Secondly, we measure running time for all completed programs and select a few fast ones. Thirdly, the fast programs are analyzed in depth and its pseudo-code programs are provided. We succeeded in developing two programs that run faster. Firstly, the combination program can save the running time by removing recursive function and the r-permutation program become faster by combining the best combination program and the best permutation program. According to our performance test, the former and later program enhance the running speed by 22% to 34% and 62% to 226% respectively compared with the fastest collected program. The programs suggested in this study could apply to a particular cases easily based on Pseudo-code., Predicts the execution time spent on data processing, determine the validity of the processing, and also generates total data with minimum access programming.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.59.1-59.1
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• 2018

SNe light curves have been used to understand the expansion history of the universe, and a lot of efforts have gone into understanding the overall shape of the radioactively powered light curve. However, we still have little direct observational evidence for the theorized SN progenitor systems. Recent studies suggest that the light curve of a supernova shortly after its explosion (< 1 day) contains valuable information about its progenitor system and can be used to set a limit on the progenitor size, R*. In order to catch the early light curve of SNe explosion and understand SNe progenitors, we are performing a ~8hr interval monitoring survey of nearby galaxies (d < 50 Mpc) with 1-m class telescopes around the world. Through this survey, we expect to catch the very early precursor emission as faint as R=21 mag (~0.1 Rsun for the progenitor). In this poster, we outline this project, and provide updates on IMSNG projects during 2017/2018 seasons.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.4
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• pp.277-285
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• 2022

There has been significant increase in demand of launch opportunities from the small satellite sector that represents the new space era. Providing smallsat-dedicated launch service at an affordable price is a new business model many startup companies have pursued, which requires innovative solutions for cost reduction in combination of low cost components, volume production and optimized manufacturing. We set out a preceding study at KARI to develop a suite of critical and cost-cutting technologies in preparation for a two-staged small launch vehicle development, based on the liquid rocket engine technologies developed from the Nuri program in accordance with the 3^rd master plan for national space development. In this work, we introduce the concept of a two-staged small launch vehicle that aims to be innovative and cost competitive for small satellites, and describe mission design results including staging as well as overall vehicle configuration of the launch vehicle.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.31.1-31.1
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• 2016

SNe light curves have been used to understand the expansion history of the universe, and a lot of efforts have gone into understanding the overall shape of the radioactively powered light curve. However, we still have little direct observational evidence for the theorized SN progenitor systems. Recent studies suggest that the light curve of a supernova shortly after its explosion (< 1 day) contains valuable information about its progenitor system and can be used to set a limit on the progenitor size, R*. In order to catch the early light curve of SNe explosion and understand SNe progenitors, we are performing a ~8hr interval monitoring survey of nearby galaxies (d < 50 Mpc) with 1-m class telescopes around the world. Through this survey, we expect to catch the very early precursor emission as faint as R=21 mag (~0.1 Rsun for the progenitor). In this talk, we outline this project, and present a few scientific highlights, such as the early light curve of SN 2015F in NGC 2442.