• Journal of radiological science and technology
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• v.38 no.3
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• pp.213-220
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• 2015

This research was study the accuracy of three-dimensional stereotactic breast biopsy, using a core Needle Biopsy and to assess the accuracy of Stereotactic biopsy and Sono guided biopsy. Using Stereotactic QC phantom to measure the accuracy of the 3D sterotactic machine. CT Scan and equipment obtained in the measured X, Y, Z and compares the accuracy of the length. Using Agar power phantom compare the accuracy of the 3D sterotactic machine and 2D ultrasound machine. Z axis measured by the equipment to compare the accuracy and reliability. Check the accuracy by using visual inspection and Specimen Medical application phantom. The accuracy of the 3D sterotactic machine measured by Stereotactic QC phantom was 100%. Accuracy as compared to CT, all of X, Y, Z axis is p > 0.05. The accuracy of the two devices was 100% as measured by Agar powder phantom. There was no difference between t he t wo d evices as C T and p > 0.05. 3D sterotactic machine of the ICC was 0.954, 2D ultrasound machine was 0.785. 2D ultrasound machine was different according to the inspector. Medical application phantom experiments in 3D sterotactic machine could not find the Sliced boneless ham. 2D ultrasound machine has not been able to find a small chalk powder group. The reproducibility of the three-dimensional stereotactic breast biopsy was better than effect of Sono guided biopsy.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.1 s.178
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• pp.193-200
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• 2006

To perform the finish grinding process of ferrules which are widely used as fiber optic connectors, a high-precision centerless grinding machine is necessary. The high-precision centerless grinding machine is consisted of the hydrostatic GW and RW spindle systems, hydrostatic RW feeding mechanism, RW swivel mechanism, on-machine GW and RW dressers, and concrete-filled steel bed. In this study, the thermal characteristics of the high-precision centerless grinding machine such as the temperature distribution, temperature rise and thermal deformation, are estimated based on the virtual prototype of the grinding machine and the heat generation rates of heat sources related to the machine operation conditions. The reliability of the predicted results is demonstrated by the temperature characteristics measured from the physical prototype. Especially, the predicted and measured results show the fact that the high-precision centerless grinding machine has very stable thermal characteristics.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.1
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• pp.7-14
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• 2015

The machine tools builders are trying to improve the efficiency and performance of the machine tools. The electro-mechanical driven broaching machine has many advantages such as lower noisy operating, higher energy efficiency, and smaller space of installation. This paper presents the structural and mechanical development of an electro-mechanical driven broaching machine that is replaced for traditional hydraulic one. The servo motor, ball screw and roller linear guide are used instead of hydraulic cylinder and translation frictional sliding guides. The simulation method based on FEM was applied to analyze the stress, deformation of the machine for static analysis. The dynamic analysis was carried out for verifying and assessing the mechanical behavior of the developed broaching machine. This work helps broaching machine developer make a better product at the early design stage with lower cost and development time.

• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1597-1610
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• 2005

The conventional computerized numerical controller (CNC) of machine tools has been increasingly replaced by a PC-based open architecture CNC (OAC) that is independent of a CNC vendor. The OAC and machine tools with an OAC have led to a convenient environment in which user-defined applications can be efficiently implemented within a CNC. This paper proposes a method of diagnosing the cause of operational faults. The method is based on the status of a programmable logic controller in machine tools with an OAC. An operational fault is defined as a disability that occurs during the normal operation of machine tools. Operational faults constitute more than 70 percent of all faults and are also unpredictable because most of them occur without any warning. To quickly and correctly diagnose the cause of an operational fault, two diagnostic models are proposed: the switching function and the step switching function. The cause of the fault is logically diagnosed through a fault diagnosis system using diagnostic models. A suitable interface environment between a CNC and developed application modules is constructed to implement the diagnostic functions in the CNC domain. The results of the diagnosis were displayed on a CNC monitor for machine operators and transmitted to a remote site through a Web browser. The proposed diagnostic method and its results were useful to unskilled machine operators and reduced the machine downtime.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.378-381
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• 2003

Efficient development of method on a performance evaluation for machine tools has been regarded as the most important work for accuracy and quality enhancement to every user and manufacturer. A evaluation method of accuracy for machine tools has been studied recently according to the rapid increase of interest in precision machine tools. To this point of view, the circular interpolation test of machine tools is recognized as the most useful method to distinguish a dynamic accuracy of NC machine tools by ISO and ANSI/ASME, etc. In this paper, we have studied and developed the form measurement system with grid encoder to analyse the final accuracy of NC machine tools. we have analyzed the servo system error and geometric error of NC machine tools through measuring a dynamic error signal by this system. and then we verified the experimental result and enhanced the reliability by means of comparing the characteristics of the developed system with the kinematic ball-bar system.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.148-153
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• 1998

In order to control thermal deformation of machine origin of machine tools due to internal and external heat sources, the real-time compensation system has been developed. First, GMDH models were constructed to estimate thermal deformation of machine origin for a vertical machining center through the measurement of deformation data and temperature data of specific points on the machine tool. Thermocouples and gap sensors are used respectively for measurement. These models are nonlinear equations with high-order polynomials and implemented in a multilayered perceptron type network structure. Secondly, work origin shift method were developed by implementing digital I/O interface board between CNC controller and IBM-PC. The work origin shift method is to shift the work origin by the compensation amounts which is calculated by pre-established GMDH model. From the experimental result, thermal deformation of machine origin was reduced to below $\pm$5${\mu}{\textrm}{m}$.

• Journal of Advanced Navigation Technology
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• v.18 no.1
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• pp.74-77
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• 2014

This paper suggested an error control for multi-channel running on machine to machine environment. This system is suitable for recovering software fault for multimedia CSCW(Computer Supported Cooperative Works) based on machine to machine environment. It is necessary for the system to be protected by reactivity of media service instance instead of breaking process of session. This paper explains a performance analysis of an error recovery system of M2M based computing collaboration environment using rule-based DEVS modeling and simulation techniques.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.5
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• pp.59-65
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• 1998

In order to utilize the information of well-know grinding database or grinding machine characteristics, a database needs to be designed by considering the delicate property of the machine tools for the high precision and quality of the demanding specification. Among the machine tools for the high precision and quality of the demanding specification. Among the machine tools, machining conditions of the grinding are various and knowledge repeatance obtained form the grinding process are less credable. therefore it is desirable for database, which is used to set the grinding conditions, to utilize the maximum machine tool capability. The present paper studied on the occurance limit of chatter vibration and burn considering the characteristics of machine tool. And also basic experiments were performed to establish the optimum grinding conditions which could maximize the grinding efficiency.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.87-92
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• 2016

In this paper, optimization technique such as particle swarm optimization was used to optimize the parameters of fuzzy Extreme Learning Machine. While the learning speed of conventional neural networks is very slow, that of Extreme Learning Machine is very fast. Fuzzy Extreme Learning Machine is composed of the Extreme Learning Machine with very fast learning speed and fuzzy logic which can represent the linguistic information of the field experts. The general sigmoid function is used for the activation function of Extreme Learning Machine. However, the activation function of Fuzzy Extreme Learning Machine is the membership function which is defined in the procedure of fuzzy C-Means clustering algorithm. We optimize the parameters of the membership functions by using optimization technique such as Particle Swarm Optimization. In order to validate the classification capability of the proposed classifier, we make several experiments with the various machine learning datas.