• The Research Journal of the Costume Culture
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• v.13 no.2 s.55
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• pp.189-199
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• 2005

The purposes of this study are to see a manufacturing process on knit by comparison, and to present whole garment knitting machine different from the traditional method of the production by using the whole garment system. The characteristics of each stage were examined through SDS-one, Shimaseiki Design CAD System and the whole garment knitting machine. The whole garment knitting machine as a method of composing a suit of knitting product is a way of making creative knitting fashion, which also can be used as a basic material for the further study on the whole garment knitting machine. Eventually, it is expected that this machine can satisfy the knit wearers' various needs by showing more useful method to knit designers.

• Korean Management Science Review
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• v.24 no.1
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• pp.91-111
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• 2007

In this paper an effective two-phase approach adopting modified p-median mathematical model is proposed for grouping machines and parts in cellular manufacturing(CM). Unlike the conventional methods allowing machines and parts to be improperly assigned to cells and families, the proposed approach seeks to find the proper block diagonal solution where all the machines and parts are properly assigned to their most associated cells and families in term of the actual machine processing and part moves. Phase 1 uses the modified p-median formulation adopting new inter-machine similarity coefficient based on the non-binary production data-based part-machine incidence matrix(PMIM) that reflects both the operation sequences and production volumes for the parts to find machine cells. Phase 2 apollos iterative reassignment procedure to minimize inter-cell part moves and maximize within-cell machine utilization by reassigning improperly assigned machines and parts to their most associated cells and families. Computational experience with the data sets available on literature shows the proposed approach yields good-quality proper block diagonal solution.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.1134-1139
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• 2003

Vibration problems are an intrinsic characteristic in a washing machine owing to rotation working mechanism. Therefore, a right comprehension of working principle and the analysis on dynamic behavior of a washing machine is essential to design anti-vibration or vibration reduction. In this paper, we choose two kinds of a washing machine: a suspension type pulsator/drum type washing machine. Each the structure and working principle of a washing machine is discussed briefly and the dynamic behavior of it is investigated, then, the vibration detection problems of transient or excessive vibration is tented in each category. Some vibration experimented results in a washing machine are presented also.

• Nuclear Engineering and Technology
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• v.37 no.2
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• pp.151-158
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• 2005

Advanced nuclear power plants are generally large complex systems automated by computers. Whenever a rare plant emergency occurs the plant operators must cope with the emergency under severe mental stress without committing any fatal errors. Furthermore, The operators must train to improve and maintain their ability to cope with every conceivable situation, though it is almost impossible to be fully prepared for an infinite variety of situations. In view of the limited capability of operators in emergency situations, there has been a new approach to preventing the human error caused by improper human-machine interaction. The new approach has been triggered by the introduction of advanced information systems that help operators recognize and counteract plant emergencies. In this paper, the adverse effect of automation in human-machine systems is explained. The discussion then focuses on how to configure a joint human-machine system for ideal human-machine interaction. Finally, there is a new proposal on how to organize technologies that recognize the different states of such a joint human-machine system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.275-278
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• 2002

Vapnik이 제안한 Support Vector Machine은 두 개의 부류를 갖는 데이터에 대한 분류에는 매우 좋은 성능을 보인다는 점은 이미 잘 알려져 있다. 하지만 부류의 개수가 3개 이상인 다중 패턴을 갖는 데이터에 대한 분류에는 SVM을 적용하기가 쉽지 않다. Support Vector Machine의 이러한 문제점을 해결하기 위하여 Zhu는 3개 이상의 부류를 갖는 데이터의 패턴 분류를 위하여 Import Vector Machine을 제안하였다. 이 모형은 Support Vector Machine을 이용하여 해결하기 어려운 다중 패턴 분류를 가능케 한다. Import Vector Machine은 커널 로지스틱 기반의 함수만을 사용하지만 본 논문에서는 다수의 커널 함수를 적용하여 가장 성능이 우수한 커널 함수를 찾아내어 최종 분류를 수행하게되는 bagging 기법을 적용하였다 제안하는 방법이 기존의 방법에 비해, 더욱 정확한 분류를 수행함을 실험 결과를 통해 확인한다.

• Proceedings of the KIEE Conference
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• summer
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• pp.866-868
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• 2004

The flux-reversal machine(FRM) is a new brushless doubly-salient permanent-magnet machine combining the advantages of the switched-reluctance machine(SRM) and the permanent-magnet machine(PMM) into one machine. FRM has a naturally low inductance, therefore, a low electrical time constant. This feature, combined with its simple construction and low rotor inertia appear to make the FRM attractive as a low-cost high-speed machine. For high-speed applications, two alternative commutation strategies are studied, one using the phase commutation advancing technique and another using the conducting pulse-width control. This paper describes the techniques and reports the corresponding simulated and experimented performance

• Journal of Magnetics
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• v.18 no.3
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• pp.260-267
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• 2013

In this paper a general 2-D model of a large air-gap synchronous machine either with non-magnetic or magnetic core rotor is investigated and electrical characteristics of the machine are analytically calculated. Considering the general model, analytical equations for magnetic field density in different regions of the large air-gap machine are calculated. In addition, self and mutual inductances in the proposed model of the machine have been developed, which are the most important parameters in the electromagnetic design and transient analysis of synchronous machines. Finite element simulation has also been performed to verify the obtained results from the equations. Analytical results show good agreement with FEM results.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.7-13
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• 2021

Machine vision is a technology that helps the computer as if a person recognizes and determines things. In recent years, as advanced technologies such as optical systems, artificial intelligence and big data advanced in conventional machine vision system became more accurate quality inspection and it increases the manufacturing efficiency. In machine vision systems using deep learning, the image quality of the input image is very important. However, most images obtained in the industrial field for quality inspection typically contain noise. This noise is a major factor in the performance of the machine vision system. Therefore, in order to improve the performance of the machine vision system, it is necessary to eliminate the noise of the image. There are lots of research being done to remove noise from the image. In this paper, we propose an autoencoder based machine vision system to eliminate noise in the image. Through experiment proposed model showed better performance compared to the basic autoencoder model in denoising and image reconstruction capability for MNIST and fashion MNIST data sets.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.755-760
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• 2019

In this paper, we developed the multi-tool carving machine which integrates the existing hot-wire carving machine, hot-wire cutting machine and spindle so that the shape of complex structure can be produced easily and quickly. We have also developed software that solves the problem that G-Code applies only to a single tool, and controls the details of the machine's operations that can not be managed with existing 3D modeling tools.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.420-426
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• 2022

Developing a machine learning model and putting it into production goes through a number of steps. Automated Machine Learning(AutoML) appeared to increase productivity and efficiency by automating inefficient tasks that occur while repeating this process whenever machine learning is applied. The high degree of automation of AutoML models allows non-experts to use machine learning models and techniques without the need to become machine learning experts. Automating the process of applying machine learning end-to-end with AutoML models has the added benefit of creating simpler solutions, generating these solutions faster, and often generating models that outperform hand-designed models. In this paper, the AutoML data is collected and AutoML's Color Petri net model is created and analyzed based on it.