• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.3
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• pp.243-250
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• 2009

In order to reduce the time needed for design, enterprises recently need the customizing technology that can modify the functions of existing CAD systems according to the their purposes. So most of the companies developing commercial CAD system are providing API to make possible the preparation of macro or external programs, which allow automatic performance of a series of repeated tasks. The objective of the present paper is to achieve more convenient carrying out of a particular modeling, by developing 3D CAD template of the standardized engineering rule of the particular model in order to establish a knowledge-based product development system. The formula, data and design knowledge which are required for the designing of the components of refrigerator were made into a program by means of Unigraphics' UG/Open API. And examples of such a development were presented. By using them in connection with commercial CAD system, design verification and modification were efficiently applied to the product design business.

• Publications of The Korean Astronomical Society
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• v.7 no.1
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• pp.89-96
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• 1992

Recent spectroscopic observations indicate concentration of dark masses in the nuclei of nearby galaxies. This has been usually interpreted as the presence of massive black holes in these nuclei. Alternative explanations such as the dark cluster composed of low mass stars (brown dwarfs) or dark stellar remnants are possible provided that these systems can be stably maintained for the age of galaxies. For the case of low mass star cluster, mass of individual stars can grow to that of conventional stars in collision time scale. The requirement of collision time scale being shorter than the Hubble time gives the minimum cluster size. For typical conditions of M31 or M32, the half-mass radii of dark clusters can be as small as 0.1 arcsecond. For the case of clusters composed of stellar remnants, core-collapse and post-collapse expansion are required to take place in longer than Hubble time. Simple estimates reveal that the size of these clusters also can be small enough that no contradiction with observational data exists for the clusters made of white dwarfs or neutron stars. We then considered the possible outcomes of interactions between the black hole and the surrounding stellar system. Under typical conditions of M31 or M32, tidal disruption will occur every $10^3$ to $10^4$ years. We present a simple scenario for the evolution of stellar debris based on basic principles. While the accretion of stellar material could produce large amount of radiation so that the mass-to-light ratio can become too small compared to observational values it is too early to rule out the black hole model because the black hole can consume most of the stellar debris in time scale much shorter than mean time between two successive tidal disruptions. Finally we outline recent effort to simulate the process of tidal disruption and subsequent evolution of the stellar debris numerically using Smoothed Particle Hydrodynamics technique.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.3
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• pp.162-173
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• 1997

Automatic on-line surface inspection systems have been applied for monitoring a quality of steel strip surfaces. One of the important issues in this application is the performance of on-line defect classifiers. Rule-based classification table methods which are conventionally used for this purpose have been suffered from their low performances. In this work, probabilistic neural networks and the enhanced classification tables which are newly proposed here are applied as alternative on-line classifiers to identify types of surface defects on cold rolled strips. Probabilistic neural networks have shown very excellent performance for classification of surface defects.

• KEPCO Journal on Electric Power and Energy
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• v.3 no.2
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• pp.89-97
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• 2017

The substation is a critical node in the power network where power is transformed in the power generation, transmission and distribution system. The IEC 61850 is a global standard which proposes efficient substation automation by defining interoperable communication and data modelling techniques. In order to achieve this level of interoperability and automation, the IEC 61850 (Part 6) defines System Configuration description Language (SCL). The SCL is an XML based file format for defining the abstract model of primary and secondary substation equipment, communications systems and also the relationship between them. It enables the interoperable exchange of data during substation engineering by standardizing the description of applications at different stages of the engineering process. To achieve the seamless interoperability, multi-vendor devices are required to adhere completely to the IEC 61850. This paper proposes an efficient algorithm required for verifying the interoperability of multi-vendor devices by checking the adherence of the SCL file to specifications of the standard. Our proposed SCL validation algorithm consists of schema validation and other functionalities including information model validation using UML data model, the Vendor Defined Extension model validation, the User Defined Rule validation and the IED Engineering Table (IET) consistency validation. It also integrates the standard UCAIUG (Utility Communication Architecture International Users Group) Procedure validation for quality assurance testing. Our proposed algorithm is not only flexible and efficient in terms of ensuring interoperable functionality of tested devices, it is also convenient for use by system integrators and test engineers.

• Journal of Korean Library and Information Science Society
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• v.11
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• pp.143-173
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• 1984

This study has been done to review the historical development of the cataloging system of books with emphasis on those in England and the U. S. The findings can be summarized as follows: (1) In 1844, Sir Panizzi invented what seems to be the first of its kind in history to list the inventory systematically at the British Museum. It is believed to be a complete system consisting of 91 articles. (2) A comparatively systematic system was developed in America by Jewett. in 1852. Composed of only 39 articles, the system is considered a renovative one worked out with due regard to the infrastructure of a library. (3) In 1876, a classic system based on a lexicographical order was set up by Cutter. Rated as the best one that was designed by an individual, the theory has since exercised widespreading effects on cataloging. (4) American and British library scientists collaborated in printing several editions of numerous volumes on the principles of classification, but they are not believed fully successful in establishing a consistent and compressive system. Their efforts found significance rather in their being the first international collaboration and setting a foundation upon which the international system of today has been developed. (5) The ALA Rule, published concurrently in ALA and LC in 1949, had two parts in its classification, the list of authors and that of titles. Its scientific classification has completed the cataloging of books in its developmental stage. (6) The 1967 American-British Rules integrated the cataloging systems published under separate covers by authors and titles. The system as well as the 1961 Paris System has greatly contributed to the standardization of bibliographical description throughout the English-speaking countries. The International Standard Book Description standardized Bibliographic system has enabled the librarians in different countries to exchange their bibliographical sources easily, helped to overcome the language barrier in listing and contributed to the efficient reading of bibliographical records through machines. (7) The second edition of the Angelo-American cataloging Rules, promulgated in 1978 under the influence of the international standard bibliographical description, was the one in which all the previous Rules were revised to have their strong points. The adoption of punctuation system to employ the computerized data processing and the standardization of description are expected to improve the cataloging system not only in the English speaking countries but in the Universal Bibliographic Control as well.

• Journal of KIISE
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• v.45 no.1
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• pp.30-35
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• 2018

GuessWhat?! is a game in which two machine players, composed of questioner and answerer, ask and answer yes-no-N/A questions about the object hidden for the answerer in the image, and the questioner chooses the correct object. GuessWhat?! has received much attention in the field of deep learning and artificial intelligence as a testbed for cutting-edge research on the interplay of computer vision and dialogue systems. In this study, we discuss the objective function and characteristics of the GuessWhat?! game. In addition, we propose a simple solver for GuessWhat?! using a simple rule-based algorithm. Although a human needs four or five questions on average to solve this problem, the proposed method outperforms state-of-the-art deep learning methods using only two questions, and exceeds human performance using five questions.

• Fire Science and Engineering
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• v.30 no.4
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• pp.20-26
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• 2016

When the fire takes place in Nuclear Powr Plants(NPPs), the reactor should achieve and maintain safe shut-down conditions and minimize the radioactive material released to the environment. The U.S. Nuclear Regulatory Commission (NRC) has issued numerous generic communications related to fire protection over the past 20 years, after it issued its requirements in the Fire Protection Rule set forth in Title 10, Section 50.48 of the Code of Federal Regulations (10 CFR 50.48) and Appendix R to the 10 CFR 50. The and Nuclear Energy Institute (NEI) has developed a Methodology for Risk Informed Fire Safe-Shutdown Analysis, which is related to the Deterministic Method for Multiple Spurious Operations solutions. The aim of this study was to identify, achieve, and maintain Post-Fire Safe-Shutdown of the Main Control Room (MCR) of the CANDU reactor, even though one train of the multiple Safety Structures, Systems, and Components (SCCs) fail by the technical specification and analysis method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2401-2406
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• 2015

Pipelines are used by large heavy industries to deliver various types of fluids. Since this is important to maintain the performance of large systems, it is necessary to accurately predict remaining life of the corroded pipeline. However, predicting the remaining life is difficult due to uncertainties in the associated variables, such as geometries, material properties, corrosion rate, etc. In this paper, a statistical method for predicting corrosion remaining life is proposed using Bayesian inference. To accomplish this, pipeline failure probability was calculated using prior information about pipeline failure pressure according to elapsed time, and the given experimental data based on Bayes' rule. The corrosion remaining life was calculated as the elapsed time with 10 % failure probability. Using 10 and 50 samples generated from random variables affecting the corrosion of the pipe, the pipeline failure probability was estimated, after which the estimated remaining useful life was compared with the assumed true remaining useful life.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.89-98
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• 2014

This study was accomplished to examine the relationship between the videogame player's perceived congruity and intention to game use, and to investigate the mediating effect of emotion as the psychological factor. Games for the research subject are confined to single player games on console or PC not online or mobile games to rule out human interaction. The results proposed that self and functional congruity have positive impact on intention to game use, and emotion is in the mediating effect of these relationships. Based on the results of the analysis, game producers have some implications for the game which is appropriate for the quality, the gamer's image, and the emotional aspect.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.56-64
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• 2018

In recent years, imbalanced data is one of the most important and frequent issue for quality control in industrial field. As an example, defect rate has been drastically reduced thanks to highly developed technology and quality management, so that only few defective data can be obtained from production process. Therefore, quality classification should be performed under the condition that one class (defective dataset) is even smaller than the other class (good dataset). However, traditional multi-class classification methods are not appropriate to deal with such an imbalanced dataset, since they classify data from the difference between one class and the others that can hardly be found in imbalanced datasets. Thus, one-class classification that thoroughly learns patterns of target class is more suitable for imbalanced dataset since it only focuses on data in a target class. So far, several one-class classification methods such as one-class support vector machine, neural network and decision tree there have been suggested. One-class support vector machine and neural network can guarantee good classification rate, and decision tree can provide a set of rules that can be clearly interpreted. However, the classifiers obtained from the former two methods consist of complex mathematical functions and cannot be easily understood by users. In case of decision tree, the criterion for rule generation is ambiguous. Therefore, as an alternative, a new one-class classifier using hyper-rectangles was proposed, which performs precise classification compared to other methods and generates rules clearly understood by users as well. In this paper, we suggest an approach for improving the limitations of those previous one-class classification algorithms. Specifically, the suggested approach produces more improved one-class classifier using hyper-rectangles generated by using Gaussian function. The performance of the suggested algorithm is verified by a numerical experiment, which uses several datasets in UCI machine learning repository.