• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.806-807
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• 2011

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 추계학술대회 논문집
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• pp.556-557
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• 2011

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2004년도 춘계학술대회논문집
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• pp.366-371
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• 2004

For the reduction and efficient management of railway noise, first of all prediction of railway noise is necessarily requisted. At home and abroad many studies for prediction of raiiway nearby noise have been accomplished. But it is impossible to predict easily and exactly for the Korean Railway, because the acoustic powers for each rolling stock operated in Korea have not been built yet. So in this study, prediction model equation for environmental noise for Korean rolling stock Mugungwha was suggested using SEL of engine and rolling noise component separately. In this prediction model, the number of car, distance from the rail can be considered. Finally for the validation of prediction nlodel equation, the predicted Leq was compared to the measured Leq.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 춘계학술대회 논문집
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• pp.787-790
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• 2012

In downtown, construction noise related claims are the most important issues. Sometimes noise related claims halt the construction process. Therefore, Introduction of noise reduction measures is common to construction process with a loud noise. This case is about concrete pouring for mat foundation of super tall building. Concrete pouring process using High Pressure Pumping machine causes high noise level in the vicinity of area. And large number of transit-mixer truck cause traffic congestion. This paper introduces effort and process to prevention of construction noise claims on massive scale concrete pouring.

• 한국소음진동공학회논문집
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• 제16권2호
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• pp.156-162
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• 2006

For the reduction and efficient management of railway noise, first of all prediction of railway noise is necessarily requisited. Many studies for prediction of railway nearby noise have been accomplished. But it is impossible to predict easily and exactly for the Korean Railway, because the acoustic powers for each rolling stock operated in Korea have not been built yet. So in this study, Prediction model equation for environmental noise for Korean rolling stock Saemaeul was suggested using SEL of engine and rolling noise component separately. Finally for the validation of prediction equation, the predicted result was compared to the measured.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.371-376
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• 2005

For the reduction and efficient management of railway noise, first of all prediction of railway noise is necessarily requisited. Many studies for prediction of railway nearby noise have been accomplished. But it is impossible to predict easily and exactly for the Korean Railway, because the acoustic powers for each rolling stock operated in Korea have not been built yet. So in this study, prediction model equation for environmental noise for Korean rolling stock Saemaeul was suggested using SEL of engine and roiling noise component separately. Finally for the validation of prediction equation, the predicted result was compared to the measured.

• 전기학회논문지
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• 제64권1호
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• pp.196-200
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• 2015

The switching noise in the power electronics of the power conversion equipment (Power Conditioning System) for large energy storage devices are generated. Since the burst-level transient noise from being generated in the power system at a higher power change process influences the control circuit of the low voltage driver circuit. Noise may cause the malfunction of the control device even if no dielectric breakdown leads to a control circuit. To overcome this, this paper proposes the installation of an additional nano-surge protection device on the power supply DC output circuit of the battery management unit.

• 대한안전경영과학회지
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• 제19권1호
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• pp.245-255
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• 2017

This paper is a study to estimate the noise generated by fluid around each machine in the basement and basement facilities that accept major noise factor, pump fluid mechanical equipment installed to evaluate the impact on the real working environment. In particular, the review of the reliability of complementary information and reliability predict the natural frequency for generating a maximum strain when the vibration analysis, and intended to ensure that the design to avoid a natural frequency of the structure, on the basis of the this analysis result to the subject a real building.

• 한국컴퓨터정보학회논문지
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• 제21권8호
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• pp.77-84
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• 2016

In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

• 디지털산업정보학회논문지
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• 제15권4호
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• pp.103-110
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• 2019

A patent contains detailed information of the developed technology and is published to the public. Thus, patents can be used to overcome the limitations of traditional technology trend research and prediction techniques. Recently, due to the advantages of patented analytical methodology, IP R&D is carried out worldwide. The patent is big data and has a huge amount, various domains, and structured and unstructured data characteristics. For this reason, there are many difficulties in collecting and researching patent information. Patent research generally writes the Search formula to collect patent documents from DB. The collected patent documents contain some noise patents that are irrelevant to the purpose of analysis, so they are removed. However, eliminating noise patents is a manual task of reading and classifying technology, which is time consuming and expensive. In this study, we propose a model that automatically classifies The Noise patent for efficient patent information research. The proposed method performs Patent Embedding using Word2Vec and generates Noise seed label. In addition, noise patent classification is performed using the Random forest. The experimental data is published and registered with the USPTO among the patents related to Ocean Surveillance & Tracking Network technology. As a result of experimenting with the proposed model, it showed 73% accuracy with the label actually given by experts.