• Journal of Ship and Ocean Technology
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• v.4 no.3
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• pp.1-12
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• 2000

A number of numerical methods like Computational Fluid Dynamics(CFD) have been developed to predict the flow fields of a vessel but the present study is developed to infer the wake fields on propeller plane by Statistical Fluid Dynamics(SFD) approach which is emerging as a new technique over a wide range of industrial fields nowadays. Neural network is well known as one prospective representative of the SFD tool and is widely applied even in the engineering fields. Further to its stable and effective system structure, generalization of input training patterns into different classification or categorization in training can offer more systematic treatments of input part and more reliable result. Because neural network has an ability to learn the knowledge through the external information, it is not necessary to use logical programming and it can flexibly handle the incomplete information which is not easy to make a definition clear. Three dimensional stern hull forms and nominal wake values from a model test are structured as processing elements of input and output layer respectively and a neural network is trained by the back-propagation method. The inferred results show similar figures to the experimental wake distribution.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.5
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• pp.325-341
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• 2013

During the past several decades, the Taguchi robust design method has been widely used in various fields successfully. On the other hand, some researchers and practitioners have criticized the method with respect to the way of utilizing orthogonal arrays, the signal-to-noise ratio as a performance measure, data analysis methods, etc., and proposed alternative approaches to robust design. This paper introduces the Taguchi method first, evaluates the validity of the criticisms, and discusses advantages and disadvantages of each alternative. Finally, research issues to be addressed for effective robust design are presented.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.212-222
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• 2020

The purpose of this study is to understand the current status and trends of the research studies published by the Society for Industrial and Applied Mathematics which is a leader in the field of industrial mathematics around the world. To perform this purpose, titles and abstracts were collected from 6,255 research articles between 2016 and 2019, and the R program was used to analyze the topic modeling model with LDA techniques and a regression model. As the results of analyses, first, a variety of studies have been studied in the fields of industrial mathematics, such as algebra, discrete mathematics, geometry, topological mathematics, probability and statistics. Second, it was found that the ascending research subjects were fluid mechanics, graph theory, and stochastic differential equations, and the descending research subjects were computational theory and classical geometry. The results of the study, based on the understanding of the overall flows and changes of the intellectual structure in the fields of industrial mathematics, are expected to provide researchers in the field with implications of the future direction of research and how to build an industrial mathematics curriculum that reflects the zeitgeist in the field of education.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1338-1343
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• 2003

Data is the expression of the language or numerical values that show some characteristics. And information is extracted from data for the specific purposes. The knowledge is utilized as information to construct rules that recognize patterns and make decisions. Today, knowledge extraction and application of the knowledge are broadly accomplished to improve the comprehension and to elevate the performance of systems in several industrial fields. The knowledge extraction could be achieved by some steps that include the knowledge acquisition, expression, and implementation. Such extracted knowledge can be drawn by rules. Clustering (CU, input space partition (ISP), neuro-fuzzy (NF), neural network (NN), extension matrix (EM), etc. are employed for expression the knowledge by rules. In this paper, the various approaches of the knowledge extraction are examined by categories that separate the methods by the applied industrial fields. Also, the several test data and the experimental results are compared and analysed based upon the applied techniques that include CL, ISP, NF, NN, EM, and so on.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.4 no.1
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• pp.121-131
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• 2000

Melt flow, heat and mass transfer of oxygen have been analyzed numerically in the process of Czochralski single crystal growth of silicon under the influence of misaligned cusp magnetic fields. Since the silicon melt in a crucible for crystal growth is of high temperature and of highly electrical-conducting, experimentation method has difficulty in analyzing the behavior of the melt flow. A set of simultaneous nonlinear equations including Navier-Stokes and Maxwell equations has been used for the modelling of the melt flow which can be regarded as a liquid metal. Together with the melt flow which forms the Marangoni convection, a flow circulation is observed near the comer close both to the crucible wall and the free surface. The melt flow tends to follow the magnetic lines instead of traversing the lines. These flow characteristics helps the flow circulation exist. Mass transfer characteristics influenced by the melt flow has been analyzed and the oxygen absorption rate to the crystal has been calculated and turned out to be rather uniform than in the case of an aligned magnetic field.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.194-199
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• 2003

Data are an expression of the language or numerical values that show some features. And the information is extracted from data for the specific purposes. The knowledge is utilized as information to construct rules that recognize patterns or make a decision. Today, knowledge extraction and application of that are broadly accomplished for the easy comprehension and the performance improvement of systems in the several industrial fields. The knowledge extraction can be achieved by some steps that include the knowledge acquisition, expression, and implementation. Such extracted knowledge is drawn by rules with data mining techniques. Clustering (CL), input space partition (ISP), neuro-fuzzy (NF), neural network (NN), extension matrix (EM), etc. are employed for the knowledge expression based upon rules. In this paper, the various approaches of the knowledge extraction are surveyed and categorized by methodologies and applied industrial fields. Also, the trend and examples of each approaches are shown in the tables and graphes using the categories such as CL, ISP, NF, NN, EM, and so on.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.3
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• pp.225-230
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• 2006

The overall performance and local flow fields of the fan, heat sink, and fan-sink were experimentally and numerically studied to investigate the flow characteristics of a fan-sink. The flow resistance of the heat sink was measured by small fan tester based on AMCA standards and compared with the CFD results to select available cooling fan for the fan-sink. The nonuniform velocity profile behind the fan outlet was shown by the flow visualization. The effects of nonuniform velocities on the performance of heat sink were discussed. To validate the commercial CFD code CFX-5.6, the predicted performance curve was compared with that of fan testing. The local flow fields of the fan-sink were analyzed by CFD results. MFR (multiple frame of reference) was used as a computational model combining rotating fan and stationary heat sink. Through the CFD results of the fan-sink, the flow patterns behind the fan outlet influenced the flow resistance and overall performance of the heat sink.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.4
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• pp.21-29
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• 2007

We derive priority decision making on healthcare service technology standardization in the home network through the decision support process with industry professionals. We configured a research group with 4 industrial areas including Industry, Academic, Research Institution and Medical Institution. And we also applied AHP methodology for the priority decision making. The research group decides an evaluation criteria which are consisted of marketability, technology, ripple effect, strategy for national policies in order to make a priority for healthcare service on a home network. And it is also decided 7 fields and 24 sub-fields, technically. In order to make a priority for the standardization, we use an AHP methodology, that is more objective and feasible, as a decision tool. After two-phase survey that consists of paper survey and face to face meeting, we get a conclusion that home healthcare content is at the top and then wireless home network follows it.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.106-113
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• 2011

Human resource theories of becoming entrepreneurs or self-employed rather than finding employment are compared as applied to fit the occupational data of technological entrepreneurs and technology jobs. The human capital theory posits that technological entrepreneurs are prepared to become a jack-of-all-trades with a variety of fields of education. Hobo theory of entrepreneurship assumes that entrepreneurs have strong taste against concentrating on a few activities, which tend to drive entrepreneurs away from employed jobs depressing their expected income. Another theory assumes that entrepreneurs have some unobserved productive qualities and abilities over employed people. Immigrant entrepreneurs could presumably be pressured out of employment under racial discrimination. Since technology jobs are mostly filled by those educated in the science and technology fields, and they presumably offer great reward to professional concentration, technological entrepreneurs may not benefit from becoming jacks-of-all-trades compared to finding employment in technological jobs income-wise. Asian immigrants in the 2000 US Census data are compared to white immigrants in technological jobs to test alternative human resource theories of entrepreneurship. Using English language ability as a proxy for the variety of education, I find in the white immigrant technological entrepreneurs support for the jack-of-all-trades theory, while in the Asian immigrant technological entrepreneurs hobo theory is supported. In the Asian technological workers only there appears the significant self-selection or comparative advantage component, while at the same time discriminatory components are significant.

• Journal of the Korean Society of Safety
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• v.36 no.5
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• pp.52-60
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• 2021

As the prevention of fatal accidents is considered an essential part of social responsibilities, both government and individual have devoted efforts to mitigate the unsafe conditions and behaviors that facilitate accidents. Several studies have analyzed the factors that cause fatal accidents and compared them to those of non-fatal accidents. However, studies on mathematical and systematic analysis techniques for identifying the features of fatal accidents are rare. Recently, various industrial fields have employed machine learning algorithms. This study aimed to apply machine learning algorithms for the classification of fatal and non-fatal accidents based on the features of each accident. These features were obtained by text mining literature on accidents. The classification was performed using four machine learning algorithms, which are widely used in industrial fields, including logistic regression, decision tree, neural network, and support vector machine algorithms. The results revealed that the machine learning algorithms exhibited a high accuracy for the classification of accidents into the two categories. In addition, the importance of comparing similar cases between fatal and non-fatal accidents was discussed. This study presented a method for classifying accidents using machine learning algorithms based on the reports on previous studies on accidents.