• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.211-223
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• 2018

To understand the meaning of data is a common goal of research on unstructured data. Among these unstructured data, there are difficulties in analyzing the meaning of unstructured data related to corpus and sentences. In the existing researches, the researchers used LSA to select sentences with the most similar meaning to specific words of the sentences. However, it is problematic to examine many sentences continuously. In order to solve unstructured data classification problem, several search sites are available to classify the frequency of words and to serve to users. In this paper, we propose a method of classifying documents by using the frequency of similar words, and the frequency of non-relevant words to be applied as weights, and storing them in terms of a multi-pattern storage. We use Tensorflow's Softmax to the nearby sentences for machine learning, and utilize it for unstructured data analysis and the inference of traffic information.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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• pp.255-258
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• 2003

This paper defines Normalized Term Frequency Weighting method for automatic text categorization by using Box-Cox, and then it applies automatic text categorization. Box-Cox transformation is statistical transformation method which makes normalized data. This paper applies that and suggests new term frequency weighting method. Because Normalized Term Frequency is different from every term compared by existing term frequency weighting method, it is general method more than fixed weighting method such as log or root. Normalized term frequency weighting method's reasonability has been proved though experiments, used 8000 newspapers divided in 4 groups, which resulted high categorization correctness in all cases.

• Journal of the Korean Data and Information Science Society
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• 제28권2호
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• pp.383-393
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• 2017

집단화되어 있는 통계자료의 통계량을 구하고자 하는 경우 통계량의 참값에 보다 가까운 값을 얻게 해주는 계산 방법을 사용하는 것이 바람직하다. 본 논문에서는 집단화된 자료의 분위수들을 계산하는 새로운 방법을 제시하였다. 제시된 방법의 주된 아이디어는, 히스토그램에 따라 그려지는 도수다각형에서 각 계급구간에 대응하는 오각형의 넓이를 그 계급구간의 도수보다 하나 많은 개수의 부분으로 등분함으로써 자룟값들을 계산하는 것이다. 제시된 방법을 모의실험을 통해 기존의 방법들과 비교하였는데, 통계학개론 교재에 주어져 있는 몇 가지의 자료를 대상으로 하였다. 모의자료의 생성 방법은, 각 계급구간에서 도수다각형에 의해 주어진 모양의 확률밀도함수를 갖는 분포를 찾아낸 뒤 역변환 방법을 이용하여, 이 분포를 따르는 모의자룟값들을 각 계급구간에서 주어진 도수와 같은 개수만큼 발생시키는 방식이다. 모의자료의 분위수와의 차의 제곱합을 기준으로 할 때 제시된 방법이 기존의 방법들보다 거의 모든 사분위수와 십분위수에서 우세한 결과를 주는 것을 볼 수 있었다.

• 조명전기설비학회논문지
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• 제27권4호
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• pp.16-22
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• 2013

This paper presents a method to analyze the voltage sag data obtained from monitoring systems. In order to establish effective countermeasures against voltage sag problems, an assessment of the system performance with respect to voltage sags is needed. Generally, the average annual sag frequency can be estimated by using the recorded voltage sag events for several years. However, the simple average value can not give the information about the errors of estimation. Such an average estimation is not useful for establishing effective solutions for voltage sag problems. Therefore, this paper proposes an effective method based on the Interval Estimation method. The estimation of voltage sag frequency is performed by using the average frequency and Poisson probability model. The proposed method can give the expected annual sag frequency and upper one-sided bound frequency.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2001년도 The Seoul International Simulation Conference
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• pp.313-317
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• 2001

The approach to predict time series without neglecting the fluctuation in a short period is tried by using a digital FIR filter and a neural network. The differential waveform of the Nikkei average closing price is filtered by the FIR band-pass filter of 101 length. It is filtered into the five frequency bands of 0-1Hz, 1-2Hz, 2-3Hz, 3-4Hz and 4-5Hz by setting the sampling frequency 10Hz. The each filtered waveform is learned and forecasted by the neural network. The neural network of the back propagation method is adopted in the learning the waveform. By inputting the data of 20 days in the past, the prediction of 10 days ahead is carried out. After learning the time series of each frequency band by the neural network, the predicted data far each frequency band are obtained. The predicted waveforms of each frequency band are synthesized to obtain a final forecast. The waveform can be forecasted well as a whole.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 추계학술발표회
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• pp.199-201
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• 2003

The monitoring effectiveness not only depends on the effectiveness of the network, but also the costs of the network. Generally the costs of the monitoring network are mainly on the equipment and personnel; the implementation and maintenance; the observation and sample connection; the sample analysis; and the data storage and processing. The cost of the monitoring network can be expressed as a function of monitoring frequency because the monitoring method can be an automatic or a manual measurement. To determine the sampling frequency of subsidiary groundwater monitoring stations, time series data of national groundwater monitoring stations were used. The proposed optimal sampling frequency for subsidiary groundwater monitoring station is about 7 to 20 days and the average frequency is about 2 weeks.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.608-613
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• 2003

In this paper, the variability of modal properties caused by temperature effects is assessed to adjust modal data used for frequency-based damage detection in plate-girder bridges. First, experiments on model plate-girder bridges are described. Next, the relationship between temperature and natural frequencies is assessed and a set of empirical frequency-correction formula are analyzed for the test structure. Finally, a frequency-eased method is used to locate and estimate severity of damage in the test structure using experimental modal data which are adjusted by the frequency-correction formula. Here, local damage in beam-type structures is detected by using measured frequencies and analytical mode shapes.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2003년도 가을 학술발표회 논문집
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• pp.535-540
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• 2003

The objective of this paper is to assess the variability of modal properties caused by temperature effects and to adjust modal data used for frequency-based damage detection in plate-girder bridges. First, experiments on model plate-girder bridges are described. Next, the relationship between temperature and natural frequencies is assessed and a set of empirical frequency-correction formula are analyzed for the test structure. Finally, a frequency-based method is used to locate and estimate severity of damage in the test structure using experimental modal data which are adjusted by the frequency-correction formula. Here, local damage in beam-type structures is detected by using measured frequencies and analytical mode shapes.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2004년도 추계 학술발표회 제16권2호
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• pp.663-666
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• 2004

An analysis of the annual frequency of collapse(AF) is performed for each bridge pier exposed to ship collision. AF is computed for each bridge component and vessel classification. The summation of AFs computed over all of the vessel classification intervals for a specific component should equal the annual frequency of collapse of the component. The designer should use judgment in developing a distribution of the vessel frequency data based on discrete groupings or categories of vessel size by DWT. In the present study the effect of vessel classification on the annual frequency of collapse in the ship collision risk assessment is investigated by illustrative numerical examples based on the vessel frequency data of the domestic harbor. The DWT interval for larger vessels has more effect on the ship collision risk. Therefore the expert judgement in determining the larger DWT interval is required because the design impact lateral resistances of bridge components depend on the ship collision risk.

• E2M - 전기 전자와 첨단 소재
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• 제9권1호
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• pp.24-29
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• 1996

A composite piezoelectric ceramic transducer is fabricated with three piezoelectric ceramic disk vibrators and two sheets of thin insulator. Its equivalent circuit is derived from the Mason's model of a thickness-driven piezoelectric vibrator. When the electric input near its fundamental resonance frequency is applied to the center vibrator and the output voltages across the left and the right vibrators are connected in series to the resistor loads, the load characteristics at resonance frequencies under the various resistor loads and the frequency characteristics near the resonance frequency without load are investigated. Furthermore, symbolic expressions for input impedances, voltage ratios, resonance frequencies, and bandwidths are derived. The data calculated from those symbolic expressions are agreed well with the measurement data.