• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.509-518
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• 2002

This paper is concerned with semiparametric Bayesian analysis of the proportional intensity regression model of the Poisson process for multiple event time data. A nonparametric prior distribution is put on the baseline cumulative intensity function and a usual parametric prior distribution is given to the regression parameter. Also we allow heterogeneity among the intensity processes in different subjects by using unobserved random frailty components. Gibbs sampling approach with the Metropolis-Hastings algorithm is used to explore the posterior distributions. Finally, the results are applied to a real data set.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.3
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• pp.15-21
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• 2008

This paper presents a new association mining algorithm that uses two phase sampling for shortening the execution time at the cost of precision of the mining result. Previous FAST(Finding Association by Sampling Technique) algorithm has the weakness in that it only considered the frequent 1-itemsets in trimming/growing, thus, it did not have ways of considering mulit-itemsets including 2-itemsets. The new algorithm reflects the multi-itemsets in sampling transactions. It improves the mining results by adjusting the counts of both missing itemsets and false itemsets. Experimentally, on a representative synthetic database, the algorithm produces a sampled subset of results with an increased accuracy in terms of the 2-itemsets while it maintains the same 1uality of the data set.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.834-840
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• 2009

This paper discusses about an empirical study to design a suitable experience monitoring and sampling system for mobile phone applications. We designed a new experience sampling method (ESM) research system iteratively. The research system is characterized by context-aware experience sampling, real-time data management, supporting data analyzing tools, and integrating ESM with ex-situ diary. From literature review, we derived initial design of the ESM research system. With the first system, we held the first experiment that evaluates three applications. From the experiment, we found that more functions are required, thus we improved the ESM system. Finally, we propose an ESM system design goal for the third iteration with experience of two experiments.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2106-2117
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• 2017

An effective statistical feature extraction approach of data sampling of fault in the combined transmission system is presented in this paper. The proposed algorithm leads to high accuracy at minimum cost to predict fault location and fault type classification. This algorithm requires impedance measurement data from one end of the transmission line. Modal decomposition is used to extract positive sequence impedance. Then, the fault signal is decomposed by using discrete wavelet transform. Statistical sampling is used to extract appropriate fault features as benchmark of decomposed signal to train classifier. Support Vector Machine (SVM) is used to illustrate the performance of statistical sampling performance. The overall time of sampling is not exceeding 1 1/4 cycles, taking into account the interval time. The proposed method takes two steps of sampling. The first step takes 3/4 cycle of during-fault and the second step takes 1/4 cycle of post fault impedance. The interval time between the two steps is assumed to be 1/4 cycle. Extensive studies using MATLAB software show accurate fault location estimation and fault type classification of the proposed method. The classifier result is presented and compared with well-established travelling wave methods and the performance of the algorithms are analyzed and discussed.

• Smart Structures and Systems
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• v.17 no.4
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• pp.647-667
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• 2016

In this paper, dynamic displacement is estimated with high accuracy by blending high-sampling rate acceleration data with low-sampling rate displacement measurement using a two-stage Kalman estimator. In Stage 1, the two-stage Kalman estimator first approximates dynamic displacement. Then, the estimator in Stage 2 estimates a bias with high accuracy and refines the displacement estimate from Stage 1. In the previous Kalman filter based displacement techniques, the estimation accuracy can deteriorate due to (1) the discontinuities produced when the estimate is adjusted by displacement measurement and (2) slow convergence at the beginning of estimation. To resolve these drawbacks, the previous techniques adopt smoothing techniques, which involve additional future measurements in the estimation. However, the smoothing techniques require more computational time and resources and hamper real-time estimation. The proposed technique addresses the drawbacks of the previous techniques without smoothing. The performance of the proposed technique is verified under various dynamic loading, sampling rate and noise level conditions via a series of numerical simulations and experiments. Its performance is also compared with those of the existing Kalman filter based techniques.

• Korean Journal of Environmental Biology
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• v.22 no.1
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• pp.1-11
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• 2004

Ecological methods were reviewed through reports such as environmental impact assessment and damage effect of fishery in the Korean watershed. Survey items in marine ecological field were included: phytoplankton, zooplankton, benthic animal, algae, adult fish, egg and juvenile of fish. A standardization of survey method in the field of community ecology was suggested to consider the convenience, Sequency in Use of device, accuracy of data collected from that. It is necessary that spatial data should be sufficiently acquired toy statistical analysis of biodiversity and spatial comparison. Quantitative sampling method must be inevitably adopted based nature of biota and geographical type of the survey area. The same sampling method can make the data compared spatially but can't be applicable in all area. Standardizing survey method should be by no means under certain restriction of study and would become different according to survey environments. The first thing is minutely understanding about ecological character of biota inhabiting in certain area, and then determining survey method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.245-248
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• 2010

Almost all of control schemes proposed so far have been designed in the continuous-time domain theoretically. Actual systems, however, have been implemented in the discrete-time domain since Micro Control Unit(MCU) and/or microprocessors have been used for the controllers. Thus, the overall system turned to be a sampled-data system, and generally speaking, the ultimate error cannot converge to zero in the actual system even though the proposed control algorithm showed the asymptotic stability in the continuous-time domain. In this paper, therefore, the ultimate error bound of a sampled data system with a short sampling period has been investigated. The ultimate error is shown to be related in the sampling period.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2643-2645
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• 2001

In this paper, a problem of limited sampling time that occurs essentially in digital data acquisition system is discussed. Low sampling frequency and a lot of processed data in micro-controller interferes normal operation of the controller from acquiring information in some case. To settle this problem, we design the sub-system which consists of a new simple micro-controller. which is managed the particular sensor making the trouble to main-controller system.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.593-599
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• 2009

We consider the problem of using control charts to monitor more than one parameter with emphasis on simultaneously monitoring the mean and variance. The fixed sampling interval (FSI) control charts are modified to use variable sampling interval (VSI) control charts depending on what is being observed from the data. In general, approaches of monitoring the mean and variance simultaneously is to use separate charts for each parameter and a combined chart. In this paper, we use three basic strategies which are separate Shewhart charts for each parameter, a combined Shewhart chart and a combined CUSUM chart. We showed that a combined VSI CUSUM chart is comparatively more efficient than any other chart if the shifts in both mean and variance are small.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.49-51
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• 1996

The z-transform method is a basic mathematical tool in analyzing and designing sampled-data control systems. However, since the z-transform method relates only the sampling-instants signals, another mathematical tool is necessary to describe the continous signals between the sampling instants. For this purpose the delayed and the modi fled z-transform methods were developed. The definition of the modi fled z-transform includes a sample in the interval [-T,0] of the original signal in its series expression, where the signal value is always zero for any physical system. From this reason one step skew of the time index always appears in its application formulas. This introduces an unnecessary operation and a gap in linking the mathematical formula and its physical interpretation. Considering the conceptual difficulty and application inconvenience, a method of using the advanced z-transform in analysis of sampled-data control systems is developed as a replacement of the modi fled z-transform. With one formulation of the advanced z-transform, now it is possible to relate both the signals of the sampling instants and those in between without any complication and conceptual difficulty.