• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.155-156
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• 2019

Traditional machine learning based emotion analysis methods such as Classification and Regression Tree (CART), Support Vector Machine (SVM), and k-nearest neighbor classification (kNN) are less accurate. In this paper, we propose an improved kNN classification method. Improved methods and data normalization achieve the goal of improving accuracy. Then, three classification algorithms and an improved algorithm were compared based on experimental data.

• Journal of Power Electronics
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• v.19 no.3
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• pp.744-750
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• 2019

A new type of auto-rotary PM mechanical flux-varying PM machine (ARPMMFVPMM) is proposed in this paper, which can overcome the problem where the air-gap magnetic field of a PM machine is difficult to freely adjust. The topology structures of the machine and the mechanical flux-adjusting device are given. In addition, the operation principle of flux-adjusting is analyzed in detail. Furthermore, the deformation of a spring with the speed variation is obtained by virtual prototype technology. Electromagnetic characteristics including the flux distribution, air gap flux density, flux linkage, electromagnetic-magnetic-force (EMF), and flux weakening ability are computed by 2D finite element method (FEM). Results show that the machine has some advantages such as the good field control ability.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.149-155
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• 2023

In urban areas it can be difficult to utilize global navigation satellite systems (GNSS) due to signal reflections and blockages. It is thus crucial to detect reflected or blocked signals because they lead to significant degradation of GNSS positioning accuracy. In a previous study, a classifier for global positioning system (GPS) signal reception conditions was developed using three features and the support vector machine (SVM) algorithm. However, this classifier had limitations in its classification performance. Therefore, in this study, we developed an improved machine learning based method of classifying GPS signal reception conditions by including an additional feature with the existing features. Furthermore, we applied various machine learning classification algorithms. As a result, when tested with datasets collected in different environments than the training environment, the classification accuracy improved by nine percentage points compared to the existing method, reaching up to 58%.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1565-1568
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• 1997

In this paper, a fuzzy based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy lovic is employed to express the degree of appropriateness when alternative machnies are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

• Journal of the Korea Safety Management & Science
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• v.6 no.3
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• pp.27-40
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• 2004

There are much dangerous machine in worksite. These make the rate of accidents increase. Specially, among them, the Press work has the highest rate of accidents. Therefore, it has been managed by Industrial safety-health law. It is very important to make a special study of work using the dangerous machine. In press work, it is also important to develop safety system program to improve productivity and work safely, In this reaserch, the safety management system is built for the work improvement of the Press. This paper showed method about dangerous machine.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.7
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• pp.1025-1032
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• 1990

We proposed a neural network energy function for the optimal graph partitioning and its optimization method using Boltzmann Machine. We composed a Boltzmann Machine with the proposed neural network energy function, and the simulation results show that we can obtain an optimal solution with the energy function parameters of A=50, B=5, c=14 and D=10, at the Boltzmann Machine parameters of To=80 and \ulcorner0.07 for a 6-node 3-partition problem. As a result, the proposed energy function and optimization parameters are proved to be feasible for the optimal graph partitioning.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.365-369
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• 2002

This paper introduces that the machine tools's feed system optimizes by modeling for simulation and adjusting drive control parameter. The first method is frequency response of speed loop with design parameter by use of MATLAB application, in order that other axis can do equal to bandwidth. The second meted uses various sensor for analyzing machine tools's structure and adjustes jirk limitter.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.32 no.11
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• pp.404-416
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• 1983

This paper is concerned with the design automation of the sequential machines. The operations of sequential machine can be diveded into two types such as synchronous and asynchronous sequential machine and their realization is treated in separate mode. But, in order to integrate logic circuits in high volume, mixed mode sequential machine uses common circuitry that consists of gates and flip-flops. Proposed sequential machine can be designed by several method, which are hard-wired implementation, firmware realization by PLA and ROM. And then onr example shows the differnces among three design mothods. Finally, computer algorithm(called MINIPLA) is discussed for various application of mixed-mode sequential machine.

• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.159-164
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• 2018

Human-machine serial systems must be normal in both systems. Though the failure of machine is irreducible by itself, the human errors are of recurring type. When the human performance is described quantitatively, non-homogeneous Poisson Process model of human errors can be developed. And the model parameters can be estimated by maximum likelihood estimation and numerical analysis method. System reliability is obtained by multiplying machine reliability by human reliability.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.921-929
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• 2011

In Information age, the academic liberal art Computer education course set up goals for promoting computer literacy and for developing the ability to cope actively with in Information Society and for improving productivity and competition among nations. In this paper, we analyze on discovering of decisive property and satisfaction index to have a influence on computer education on university students. As a preprocessing method, the proposed method select optimum property using correlation feature selection of machine learning tool based on Java and then we use multiclass least square support vector machine based on statistical learning theory. After applying that compare with multiclass support vector machine and multiclass least square support vector machine, we can see the fact that the proposed method have a excellent result like multiclass support vector machine in analysis of the academic liberal art computer education satisfaction index data.