• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.281-284
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• 2009

In this paper, we propose a method that applies Adaptive Frequency Sampling(AFS) technique to the equivalent circuit model for RF passive components. Thes days wireless communication system is getting smaller and smaller. So EMI/EMC is an issue in RF. We can solve PI(Power Integrity)/SI(Signal Integrity) that one of EMI/EMC problem apply IFFT for 3D EM simulation multiple with input signal. That is time comuming task. Therefore equivalent circuit model using RF passive component is important. AFS schemes are implemented to obtain the rational functions. S parameters of the equivalent circuit moldel is compared to those of EM simulation in case of the microstrip line structure.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.825-836
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• 2019

One of the most challenging safety precautions for workers in dynamic, radioactive environments is avoiding radiation sources and sustaining low exposure. This paper presents a sampling-based algorithm, DL-RRT*, for minimum dose walk-path re-planning in radioactive environments, expedient for occupational workers in nuclear facilities to avoid unnecessary radiation exposure. The method combines the principle of random tree star ($RRT^*$) and $D^*$ Lite, and uses the expansion strength of grid search strategy from $D^*$ Lite to quickly find a high-quality initial path to accelerate convergence rate in $RRT^*$. The algorithm inherits probabilistic completeness and asymptotic optimality from $RRT^*$ to refine the existing paths continually by sampling the search-graph obtained from the grid search process. It can not only be applied to continuous cost spaces, but also make full use of the last planning information to avoid global re-planning, so as to improve the efficiency of path planning in frequently changing environments. The effectiveness and superiority of the proposed method was verified by simulating radiation field under varying obstacles and radioactive environments, and the results were compared with $RRT^*$ algorithm output.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.73-85
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• 2001

The spatial population existing in a plane ares, such as an animal or aerial population, have certain relationships among regions which are located within a fixed distance from one selected region. We consider with the adaptive searching estimation in spatial sampling for a spatial population. The adaptive searching estimation depends on values of sample points during the survey and on the nature of the surfaces under investigation. In this paper we study the estimation by the adaptive searching in a spatial sampling for the purpose of estimating the area possessing a particular characteristic in a spatial population. From the viewpoint of adaptive searching, we empirically compare systematic sampling with stratified sampling in spatial sampling through the simulation data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.687-695
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• 2005

A bandpass sampling technique, which is a method directly downconverting a bandpass signal to a baseband or a low IF signal without analog mixers, can be an alterative choice for the SDR system to minimize the RF front-end. In this paper, a complex bandpass sampling technique for two bandpass-filtered signals is proposed. We derived generalized formulae for the available sampling range, the signal's IF and the minimum sampling frequency taking into consideration the guard-bands for the multiple RE signals. Thru the simulation experiments, the advantages of the . complex bandpass sampling over the pre-reported real bandpass sampling are investigated for applications in the SDR design.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.435-443
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• 2015

Two phase sampling design is useful to increase estimation efficiency using deep stratification, improved non-response adjustment and reduced coverage bias. The same sampling units are commonly used for the first and the second phases in complex two-phase sampling design. In this paper we consider a sampling scheme where the first phase sampling units are clusters and the second phase sampling units are list samples. Using selected clusters in first phase requires that we list up elements in the selected clusters from the first phase and then use the list as a secondary sampling frame for the second phase sampling design. Then we select second phase samples from the listed sampling frame. We suggest an estimator based on the complex two-phase sampling design with different sampling units of each phase. Also the estimated variances of the estimator obtained by using classic and replication variance methods are considered and compared using simulation studies. For real data analysis, 2010 Korea Farm Household Economy Survey (KFHES) and 2011 Korea Agriculture Survey (KAS) are used.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1743-1753
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• 2017

Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRS-MCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.

• Journal of Microbiology and Biotechnology
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• v.16 no.5
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• pp.683-688
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• 2006

We have developed a program for generating shotgun data sets from known genome sequences. Generation of synthetic data sets by computer program is a useful alternative to real data to which students and researchers have limited access. Uniformly-distributed-sampling clones that were adopted by previous programs cannot account for the real situation where sampled reads tend to come from particular regions of the target genome. To reflect such situation, a probabilistic model for biased sampling distribution was developed by using an experimental data set derived from a microbial genome project. Among the experimental parameters tested (varied fragment or read lengths, chimerism, and sequencing error), the extent of sequencing error was the most critical factor that hampered sequence assembly. We propose that an optimum sequencing strategy employing different insert lengths and redundancy can be established by performing a variety of simulations.

• The Journal of Natural Sciences
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• v.15 no.1
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• pp.11-34
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• 2005

It is no exaggeration to say that the productivity of a research using computer simulations on complex molecular systems like biomolecules depends on the ability of the sampling algorithm to explore the relevant parts of configuration space. In this study, we investigate the properties on the mutiensemble sampling (MES) which is one of the solutions that surmount limitations of conventional sampling algorithms. Works for finding out practical systematic ways of using the MES efficiently to explore distantly separated regions in configuration space are performed. In this work, the more generalized form of weighting function for MES is used and 'cavity formation in water' is simulated using Monte Carlo. investigating the correlation of simulation parameters and the efficiency of the method, we propose a practical way of maximizing the power of the MES. We applied the way to 'cavity formation in water' and were able to explore the parts of configuration space relevant to cavities of radius from 0 to 5.6A in a single simulation.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.677-682
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• 2012

There are lots of sampling design which is determined for sample survey in various fields. Especially, it is important problem for clinical data because basic characteristic variables by group which consist of experiment group and control group in population should be reflect to sample. Therefore, frequencies, center scales and dispersion scales of variables by group in population should be similar in sample. But usual sampling design is very complicate so it is difficult to use in practice for researcher. In this paper, we consider the sampling method using simulation. We applied the proposed method to colon cancer data from a hospital. We compare basic characteristic variables between population and sample with mean, frequency and statistic hypothesis test.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.468-471
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• 1997

In this paper, we investigate the time-sampling effects on the digital implementation of singular perturbation based STT autopilot with excellent performance and propose a compensation method for the time-sampling effects. In digitization of analog STT autopilot, it is found that the stability margin of the fast dynamics is mostly affected to lead to rapid decrease. Under the this analysis, a composite digital controller with additional compensator for fast dynamics is proposed to improve the time-sampling effect and a simulation verifies the result.