• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.549-554
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• 2008

Support Vector machine is the classifier which is based on the statistical training theory. Twin Support Vector Machine(TWSVM) is a kind of binary classifier that determines two nonparallel planes by solving two related SVM-type problems. The training time of TWSVM is shorter than that of SVM, but TWSVM doesn't shows worse performance than that of SVM. This paper proposes the TWSVM which is applied fuzzy membership, and compares the performance of this classifier with the other classifiers using Ionosphere radar data set.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.1
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• pp.42-49
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• 2009

This study proposes a web-based remote monitoring system for evaluating degradation of machine tools using ART2(Adaptive Resonance Theory 2) neural network. A number of studies on the monitoring of machine tools using neural networks have been reported. However, when normal condition is changed due to factors such as maintenance, tool change etc., or a new failure signal is generated, such algorithms need to be entirely retrained in order to accommodate the new signals. To cope with such problems, this study develops a remote monitoring system using ART2 in which new signals when required are simply added to the classes previously trained. This system can monitor degradation as well as failure of machine tools. To show the effectiveness of the proposed approach, the system is experimentally applied to monitoring a simulator similar to the main spindle of a machine tool, and the results show that the proposed system can be extended to monitoring of real industrial machine tools and equipment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.4 no.4
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• pp.63-69
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• 1981

As enterprises are getting bigger and bigger and more competecious, an engineering economy for the maximization of profit based on basic theory must be considered. This thesis present dynamic computer model for the decision which controls complicated and various man- machine system optimally. This model occur in general stage can be adaptable to every kind of enterprises. So, any one who has no expert knowledge is able to get the optimal solution. And decision tree used in this paper can be applied in every kinds of academic circles as well as whole the industrial world. This paper studied optimal management of engineering project based upon basic theory of engineering economy. It introduces and functionizes the variables which generalize every possible elements, set up a model in order to find out the variable which maximize the calculated value among many other variables. And the selected values ate used as decision- marking variables for the optimal management of engineering projects. It found out some problem of this model. They are : 1. In some kinds of man-machine system it refers to Probability, but other case, it depends on only experimental probability. 2. Unless decision making process (decision tree) goes on, this model can not be applied. So these cases, this paper says, can be solved by adapting finite decision tree which is analyzed by using the same technic as those in product introduction problem. And this paper set up the computer model in order to control every procedure quickly and optimally, using Fortran IV.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.239-251
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• 2018

In existing cloud services, information security and privacy concerns have been worried, and have become one of the major factors that hinder the popularization and promotion of cloud computing. As the cloud computing infrastructure, the security of virtual machine systems is very important. This paper presents an immune-inspired intrusion detection model in virtual machines of cloud computing environment, denoted I-VMIDS, to ensure the safety of user-level applications in client virtual machines. The model extracts system call sequences of programs, abstracts them into antigens, fuses environmental information of client virtual machines into danger signals, and implements intrusion detection by immune mechanisms. The model is capable of detecting attacks on processes which are statically tampered, and is able to detect attacks on processes which are dynamically running. Therefore, the model supports high real time. During the detection process, the model introduces information monitoring mechanism to supervise intrusion detection program, which ensures the authenticity of the test data. Experimental results show that the model does not bring much spending to the virtual machine system, and achieves good detection performance. It is feasible to apply I-VMIDS to the cloud computing platform.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.127-134
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• 2022

Generally developed for medical testing, electrocardiogram (ECG) recordings seizure the cardiac electrical signals from the surface of the body. ECG study can consequently be a vital first step to support analyze, comprehend, and expect cardiac ailments accountable for 31% of deaths globally. Different tools are used to analyze ECG signals based on computational methods, and explicitly machine learning method. In all abovementioned computational simulations are prevailing tools for cataloging and clustering. This review demonstrates the different effective methods for heart disease based on computational methods for ECG analysis. The accuracy in machine learning and three-dimensional computer simulations, among medical inferences and contributions to medical developments. In the first part the classification and the methods developed to get data and cataloging between standard and abnormal cardiac activity. The second part emphases on patient analysis from entire ECG recordings due to different kind of diseases present. The last part represents the application of wearable devices and interpretation of computer simulated results. Conclusively, the discussion part plans the challenges of ECG investigation and offers a serious valuation of the approaches offered. Different approaches described in this review are a sturdy asset for medicinal encounters and their transformation to the medical world can lead to auspicious developments.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.369-374
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• 2001

Gear is general mechanical elements that used for power transmission between two shafts that interval is comparatively short. and it delivers big power as accurate ratio of speed. The profile of Spur gear which is the most basic factor is divided into Trochoidal fillet curve and Involute curve. Involute curve is used a lot of a shaped curve of machine parts such as a gear, a scroll compressor and a collar of centrifugal pump. However, it is poor to study the modeling of Trochoidal fillet curve and the three dimensions model shaped mathematical curve. This paper describes a mathematical model of profile shifted involute gear. and this model is based on Camus's theory. We draw three dimensions gear have accurate mathematical function using ADS, VisualLISP. and To check accuracy and perfection, we make a program of checking Interference. and use for this study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.2
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• pp.68-77
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• 2004

This paper considers the workforce assignment problem to minimize both the deviations of workloads assigned to workers and to maximize the total preference between each worker and each machine. Because of the high expense of technology education and the difficulties of firing employees, there is no part time workers in semiconductor industry. Therefore, multi-skilled workers are trained for performing various operations in several machines. The bicriteria workforce assignment problem in this paper is not easy to obtain the optimal solution considering the aisle structure and it is belong to NP-class. The proposed heuristic algorithms are developed based on the combination of spacefilling curve technique, simulated annealing technique and graph theory focusing on the multiple-row machine layout. Examples are presented for the proposed algorithms how to find a good solution.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.3
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• pp.157-162
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• 2016

In this paper, a yield prediction model based on relevance vector machine (RVM) and a granular computing model (quotient space theory) is presented. With a granular computing model, massive and complex meteorological data can be analyzed at different layers of different grain sizes, and new meteorological feature data sets can be formed in this way. In order to forecast the crop yield, a grey model is introduced to label the training sample data sets, which also can be used for computing the tendency yield. An RVM algorithm is introduced as the classification model for meteorological data mining. Experiments on data sets from the real world using this model show an advantage in terms of yield prediction compared with other models.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.8
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• pp.11-16
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• 1998

Recently, the motor-integrated spindle systems have been used to simplify the machine tool structure, to improve the motion flexibility of machine tool, and to perform the high-speed machining. In this study, a static and dynamic analysis system for motor-integrated high-speed spindle systems is developed based on Timoshenko theory, finite element method and windows programming techniques. Since the system has various analysis modules related to static deformation analysis, modal analysis, frequency response analysis, unbalance response analysis and so on, it is useful in performing systematically the design and evaluation processes of motor-integrated high-speed spindle systems under windows GUI environment.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2067-2069
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• 2002

The study of the vector control of the induction machine without speed sensor is going on and there are the adaptive performance method to use the flux observer. This study is to make the vector control without the speed sensor based on the flux oriented reference vector control theory. This paper proposes the new speed follow-up method to deduce the current value in the current sensor and the 2 order flux observer based on the observer theory and examine the possibility to realize the flux oriented vector control system using the simulation in this proposed method of this study.