• Proceedings of the KIEE Conference
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• 2004.11a
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• pp.264-267
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• 2004

The conventional testing as IEC-60587 is widely used in surface aging measurement of outside insulator those testing can carry out very short time in Lab testing. Also IEC-60587 testing is able to offer the standard judgement of relative degradation level of out side HV machine. Therefore it is very useful method compare to previous conventional tracking testing method and effective Lab testing method, But surface discharges(SD) have very complex characteristics of discharge pattern so it is required estimation research to development of precise analysis method. In recent, the study of IRR Camera is carrying out discover of temperature of power equipment through condition diagnosis and system development of degradation diagnosis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.32-36
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• 2002

This paper presents the structural characteristic analysis of a centerless grinding machine with concrete bed. The centerless grinding machine is composed of grinding wheel head, regulating wheel head, concrete bed, wheel dresser and so on. Especially, the concrete bed is introduced to improve the static, dynamic and thermal characteristics of the centerless grinding machine. The structural analysis model of centerless grinding machine is constructed by the finite element method, and the structural characteristics in the design stage are estimated based on the structural deformation and harmonic response under the various testing conditions related to gravity force and directional farces

• Journal of the Korean Society for Precision Engineering
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• v.18 no.2
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• pp.126-131
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• 2001

One of the major obstacles in testing or evaluating precisely the thermal behavior of a machine tool is the difficulty in measuring the heat transfer coefficients on the surfaces by a conventional method. This paper presents a new approach based on the inverse method to identify the values of heat transfer coefficients by using temperature changes measured on the surfaces of a machine tool during a short period in its operating. In the present method, a machine tool structure is modeled by the finite element method and the characteristic curves of the temperature change at several points on machine tool surfaces are theoretically derived in the form that they contain the heat transfer coefficient as an unfixed heat source are approximated so that the theoretical characteristic curves of temperature change fit the measured ones as closely as possible.

• 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 the Korea Society of Computer and Information
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• v.25 no.7
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• pp.113-123
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• 2020

Obstructive sleep apnea (OSA) among sleep disorders is one of relatively common diseases. Patients can be checked for the disease through sleep polysomnography. However, as far as he diagnosis of OSA using polysomnography (PSG) is concerned, many practical problems such as an increasing number of patients, expensive testing cost, discomfort during examination, and the limited number of people for testing have been pointed out. Accordingly, for the purpose of substituting PSG researchers have been actively conducting studies on OSA diagnosis based on machine learning using bio signals. In this regard, we review a rich body of existing OSA diagnosis studies applying machine learning techniques based on bio-signal data. As a result, this paper presents a novel taxonomy of the reviewed studies and provides their comprehensive comparative analysis results. Also, we reveal various limitations of the studies using the bio signals and suggest several improvements about utilization of the used machine learning methods. Finally, this paper presents future research topics related to the application of machine learning techniques using bio signals.

• Computers and Concrete
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• v.19 no.3
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• pp.275-282
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• 2017

The aim of this study is to build Machine Learning models to evaluate the effect of blast furnace slag (BFS) and waste tire rubber powder (WTRP) on the compressive strength of cement mortars. In order to develop these models, 12 different mixes with 288 specimens of the 2, 7, 28, and 90 days compressive strength experimental results of cement mortars containing BFS, WTRP and BFS+WTRP were used in training and testing by Random Forest, Ada Boost, SVM and Bayes classifier machine learning models, which implement standard cement tests. The machine learning models were trained with 288 data that acquired from experimental results. The models had four input parameters that cover the amount of Portland cement, BFS, WTRP and sample ages. Furthermore, it had one output parameter which is compressive strength of cement mortars. Experimental observations from compressive strength tests were compared with predictions of machine learning methods. In order to do predictive experimentation, we exploit R programming language and corresponding packages. During experimentation on the dataset, Random Forest, Ada Boost and SVM models have produced notable good outputs with higher coefficients of determination of R2, RMS and MAPE. Among the machine learning algorithms, Ada Boost presented the best R2, RMS and MAPE values, which are 0.9831, 5.2425 and 0.1105, respectively. As a result, in the model, the testing results indicated that experimental data can be estimated to a notable close extent by the model.

• Science of Emotion and Sensibility
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• v.8 no.1
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• pp.37-45
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• 2005

This paper reports the remedial effect measurement of an obesity remedy machine for home use which has been developed by H Co. and the authors. It is expected that the machine enhances it's remedial effect and usability by utilizing medium frequency and thermotherapy belt etc. In order to measure it's remedial effect, a clinical experiment, which participates eight young female subjects, has been conducted for one month. The experiment includes the measurements on the changes of Gas-Exchange Responses of subjects through Cardio-Pulmonary Exercise Testing. The experimental results show that the obesity remedy machine helps the subjects to reduce their weights, fat rates, and $VCO_2s$. Thus, it turns out that the machine can be a good candidate for medical treatment on the obesity.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.1233-1240
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• 2005

As the geotechnical technologies have grown, the size of civil structures has become bigger than before, thereby requiring large-scale geotechnical testing equipments which can evaluate the mechanical behavior of large size testing materials such as gravel, crushed rock and so on. These kind of large testing equipments are usually used to evaluate the mechanical characteristics of large size material which are applied in the large infra structures like dam, seashore structure, coastal landfill, soil-structure interaction and seismic response of large-scale structure. In this research, state-of-the-art information in the field of geotechnical engineering was collected and summarized for such large-scale experimental equipments as large-scale geo-centrifuge, large-scale triaxial testing machine, large-scale direct shear testing apparatus and large-scale oedometer.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.744-751
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• 2003

A hybrid least square Support Vector Machine combined with First Principle(FP) knowledge is proposed. We compare hybrid least square Support Vector Machine(HLS-SVM) with early proposed models such as Hybrid Neural Network(HNN) and HNN with Extended Kalman Filter(HNN-EKF). In the training and validation stage HLS-SVM shows similar performance with HNN-EKF but better than HNN, whereas, in the testing stage, it shows three times better than HNN-EKF, hundred times better than HNN model.

• Journal of the Korean Society for Railway
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• v.6 no.4
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• pp.265-272
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• 2003

The computer program for the accelerated life testing technique of a machine part under the service conditions is developed under the GUI environment so that the user can easily obtain the results by selecting the program module. Also, the theoretical backgrounds for the computer program and the procedures of the accelerated testing method are introduced by testing the specimens made of the stainless steel 316L under the high temperature and random loading. The reliability of the program is discussed by the experimental results of the fatigue life, age degradation and accelerated testing conditions.