• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.2
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• pp.98-104
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• 2012

In this paper, precision processing is carried out for the pre hardened steel(HRC 54), which is one of injection mould materials. Processing characteristics are estimated according to the number of tool cutting blade and roundness is observed by the 3-Dimensional measuring machine. The surface roughness affected by the wire electric discharge machining are measured. Cutting component force of STAVOX is the highest in condition of 2F processing because load per a blade of cutting tool is high. Especially, the difference in Fz is over 20N by cutting load. The slower spindle rotation speed and tool feed rate are, the better cutting component force is. The roundness of hole processed in condition of 4F is good because feed rate is able to be fast. When rotation speed is increased, the surface roughness is decreased. The surface roughness acquired in condition of 2F processing is higher about 50% than 4F processing.

• Transactions of Materials Processing
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• v.32 no.2
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• pp.74-80
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• 2023

A deformation behavior of commercially pure titanium (CP-Ti) is highly dependent on material and processing parameters, such as deformation temperature, deformation direction, and strain rate. This study aims to predict the multivariable and nonlinear tensile behavior of CP-Ti using machine learning based on three algorithms: artificial neural network (ANN), light gradient boosting machine (LGBM), and long short-term memory (LSTM). The predictivity for tensile behaviors at the cryogenic temperature was lower than those in the room temperature due to the larger data scattering in the train dataset used in the machine learning. Although LGBM showed the lowest value of root mean squared error, it was not the best strategy owing to the overfitting and step-function morphology different from the actual data. LSTM performed the best as it effectively learned the continuous characteristics of a flow curve as well as it spent the reduced time for machine learning, even without sufficient database and hyperparameter tuning.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.193-198
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• 2001

In the large scale B2B transaction like buying Express-Train or selling Daewoo Motor, a tremendous amount of variables and factors of chaos functionate in it directly or indirectly. To get effective information processing on the so called complex system like this, it should be possible to unite the global insight power of the human being and the local computing power of the machine. In this paper, we suggested a union model of human being and machine using Hugent concept. Hugent is defined as an agent model which allows us to chemically unite the human's component and the machine's component in terms of information processing. In this paper, we showed that some typical problems contained in the complex system can be treated more easily through the suggested Hugent concept.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.231-234
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• 2003

This paper describes the structure, operation, image processing, and decision making techniques of a color machine vision system designed for the automatic sorting of soybeans. The system consists of feeder, conveyor belt, line-scan camera, lights. ejector, and a PC Unlike manufactured goods, agricultural products including soybeans have quite uneven features. The criteria for sorting good and bad beans also vary depending on inspectors. We tackle these problem by letting the system learn the inspecting parameters from good samples selected manually by a machine user before running the system for sorting. Real-time processing has another importance In the design. Four parallel DSPs are employed to increase the processing speed. When the designed system was tested with real soybeans and the result was successful.

• Tribology and Lubricants
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• v.12 no.3
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• pp.72-78
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• 1996

This paper was undertaken to analyze the morphology of wear debris generated from lubricated moving machine surfaces by image processing. The lubricati, ng wear test was performed under different experimental conditions using the wear test device made in our laboratory and wear test specimen of the pin on disk type wear rubbed in paraffme series base oil, by varying applied load, sliding distance. The four parameters (50% volumetric diameter, aspect, roundness and reflectivity) to describe the morphology have been developed and outlined in the paper. A system using such techniques promises to obviate the need for subjective, human interpretation of particle morphology in machine condition monitoring, thus to overcome many of the difficulties with current methods and to facilitate wider use of wear particle analysis in machine condition monitoring.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.268-281
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• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.52-59
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• 2004

This paper shows about the machine simulation embodiment when it happens NC equipment and between workpiece and interference in 5 axises machining of aluminium alloy a vehicles parts. And this research has been chosen because of the highest equipment interference occurrence rate at a vehicles parts processing of 5 axises horizontal machine. It can verify simulation and machining process through correlation of their dynamic relations, interference, collision as embodied virtual manufacturing system of machine, workpiece, and holder etc. That is necessary element in shape of machine tool, function and processing in imagination ball. Also, it verifies about interference and collision between NC equipment and workpiece, as it applied machine simulation to NC Data of actuality aircraft parts of BULKHEAD and FRAME. As the result of this study, by removing the equipment interference and collision element which creates NC data, the virtual machine tool it the efficiency of machine process has increased.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.1-8
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• 2004

In this paper, we implement the Digital Signal Processing System based on Human Machine Interface technology for the telematics with embedded noise-robust speech recognition engine and develop the communication system which can be applied to the automobile information center through the human-machine interface technology. Through the embedded speech recognition engine, we can develop the total DSP system based on Human Machine Interface for the telematics in order to test the total system and also the total telematics services.

• Language and Information
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• v.2 no.2
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• pp.185-220
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• 1998

The purpose of this research is to propose a set of basic guidelines for the construction of English test suites, a set of basic guidelines for the construction of Korean test suites to objectively evaluate the performance of machine translation systems. For this end, we constructed 650 English test sentences, 650 Korean test sentences, and developed the statistical methods and tools for the comparative evaluation of the English-Korean machine translation systems. It also evaluates the existing commercial English-Korean machine translation systems. The importance of this research lies in that it will promote an awareness of the importance and need of testing machine translation systems within the Natural Language Community. This research will also make a big contribution to the development of evaluation methods and techniques for appropriate test suites for Korean information processing systems. The results of this research can be used by the natural language community to test the performance and development of their information processing systems or machine translation systems.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.422-432
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• 2019

A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.