• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.818-824
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• 2011

In this paper, we proposed a phase noise model of a frequency synthesizer for a radar system. Especially, it was proposed a phase noise model in a DAS(Direct Analog Synthesizer) and a frequency up converter system using Leeson's model. The proposed phase noise model was derived from the measurement data of model 1 and evaluated by adapting to model 2 and model 3 frequency synthesizers. The prediction phase noise by modeling was totally matched to the measured data and the effective analysis of the phase noise was done in a frequency synthesizer and a frequency converter of radar system.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.58 no.2
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• pp.130-140
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• 2022

Recently, wideband acoustic technology has been introduced and started to be used in fisheries acoustic surveys in various waters worldwide. Wideband acoustic data provides high vertical resolution, high signal-to-noise ratio and continuous frequency characteristics over a wide frequency range for species identification. In this study, the main characteristics of wideband acoustic systems were elaborated, and a general methodology for wideband acoustic data analysis was presented using data collected in frequency modulation mode for the first time in Republic of Korea. In particular, this study described the data recording method using the mission planner of the wideband autonomous acoustic system, wideband acoustic data signal processing, calibration and the wideband frequency response graph. Since wideband acoustic systems are currently installed on many training and research vessels, it is expected that the results of this study can be used as basic knowledge for fisheries acoustic research using the state-of-the-art system.

• International Journal of Advanced Culture Technology
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• v.5 no.3
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• pp.40-45
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• 2017

This data mining technique was used to extract useful information from percutaneous coronary intervention data obtained from the US public data homepage. The experiment was performed by extracting data on the area, frequency of operation, and the number of deaths. It led us to finding of meaningful correlations, patterns, and trends using various algorithms, pattern techniques, and statistical techniques. In this paper, information is obtained through efficient decision tree and cluster analysis in predicting the incidence of percutaneous coronary intervention and mortality. In the cluster analysis, EM algorithm was used to evaluate the suitability of the algorithm for each situation based on performance tests and verification of results. In the cluster analysis, the experimental data were classified using the EM algorithm, and we evaluated which models are more effective in comparing functions. Using data mining technique, it was identified which areas had effective treatment techniques and which areas were vulnerable, and we can predict the frequency and mortality of percutaneous coronary intervention for heart disease.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.535-539
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• 2008

Recently mobile devices can transmit mass data contained multi-media contents. According these flow, a demand for fast data transmission is being risen, so we acutely require remarkable technology that overcome mobile communication's poor environment and rise data transmission volume. Because it can be satisfied these needs, the OFDM(Orthogonal Frequency Division Multiplexing) that rise data transmission volume using efficient frequency, and MIMO(Multiple Input Multiple Output) that rise transmission confidence and data transmission volume using numbers of antenna is attended. Before design of MIMO-OFDM System we want to make an analysis for theory of its systems, and we want to design MIMO-OFDM simulator for verify an ability of modulation, data volume and numbers of antenna.

• The Journal of Fisheries Business Administration
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• v.36 no.1 s.67
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• pp.81-101
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• 2005

This article is to estimate the fishing frequency function in Korean recreational fishery with respect to socio-economic characteristics of anglers. First, the study described the characteristics of the entire angler population on the view points of 9 socio-economic variables. And then, the study divided the total angler population into three groups of in-land, sea, and mixed angler populations in order to investigate the differences in their characteristics. The study could confirm the existence of differences in regions, size of regions, and educational levels between the in - land and the sea angler populations by testing heterogeneity in the frequency table. The fishing frequency function is estimated using Poisson regression model in order to accomodate the count data(non-negative discrete random variable) aspects of the fishing frequency. However, the model specification error is found due to overdispersion of data. The model exhibits the lack of goodness of fit. The negative binomial regression model is adopted to cure the overdispersion of the data as an alternative estimation methodology. Finally, the study can confirm overdispersion does not exist in the model any more and the goodness of fit improved significantly to the reasonable level. The results of estimation of fishing frequency population modeled by the negative binomial regression models are following. The three variables of region, sex, and education have effects on the decision making process of fishing frequency in the case of in-land recreation fishery. On the other hand, the three variables of sex, age, and marriage status do the same job in the case of sea angler population. Among the left-over variables, both income and use of Internet variables now affect on the process in mixed angler population. Finally, the results of whole angler population show that all of the previous variables are proven to be statistically significant due to the summation of data with all three sub-groups of angler population.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4B
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• pp.319-328
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• 2009

This study quantified the data by applying the EDA techniques considering the data structure, and the results were then used for the frequency analysis. Although traditional methods based on the method of moments provide very sensitive statistics to the extreme values, the EDA techniques have an advantage of providing very stable statistics with their small variation. For the application of the EDA techniques to the frequency analysis, it is necessary to normalization transform and inverse-transform to conserve the skewness of the raw data. That is, it is necessary to transform the raw data to make the data follow the normal distribution, to estimate the statistics by applying the EDA techniques, and then finally to inverse-transform the statistics of transformed data. These statistics decided are then applied for the frequency analysis with a given probability density function. This study analyzed the annual maxima one hour rainfall data at Seoul and Pohang stations. As a result, it was found that more stable rainfall quantiles, which were also less sensitive to extreme values, could be estimated by applying the EDA techniques. This methodology may be effectively used for the frequency analysis of rainfall at stations with especially high annual variations of rainfall due to climate change, etc.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.129-133
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• 2019

Frequency resource efficiency is important in satellite communication systems. One of the causes of a waste of frequency resource is bad flatness. In the case, flatness of satellite Tx terminals would be worse by ACI and guard band. In order to overcome this problem, this paper proposes a technique for frequency response equalization in satellite Tx terminals. First of all, a general linear polynomial expression which meets least squares of representative measurement data is calculated to interpolate unmeasured data. And then flatness can be adjusted using the polynomial expression. Simulation results illustrate adjusted data have lower peak to peak and standard deviation than original data, and these show that flatness be improved.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.547-559
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• 2022

For a chi-squared test, which is a statistical method used to test the independence of a contingency table of two factors, the expected frequency of each cell must be greater than 5. The percentage of cells with an expected frequency below 5 must be less than 20% of all cells. However, there are many cases in which the regional expected frequency is below 5 in general small area studies. Even in large-scale surveys, it is difficult to forecast the expected frequency to be greater than 5 when there is small area estimation with subgroup analysis. Another statistical method to test independence is to use the Bayes factor, but since there is a high ratio of data dependency due to the nature of the Bayesian approach, the low expected frequency tends to decrease the precision of the test results. To overcome these limitations, we will borrow information from areas with similar characteristics and pool the data statistically to propose a pooled Bayes test of independence in target areas. Jo et al. (2021) suggested hierarchical Bayesian pooling models for small area estimation of categorical data, and we will introduce the pooled Bayes factors calculated by expanding their restricted pooling model. We applied the pooled Bayes factors using bone mineral density and body mass index data from the Third National Health and Nutrition Examination Survey conducted in the United States and compared them with chi-squared tests often used in tests of independence.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.745-752
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• 2016

The parameters of Debye's equation were applied to analyze the frequency-dependent ground impedance of horizontally-buried wires. We present a new method, based on Debye's equation, of analyzing the effect of polarization on frequency-dependent ground impedance. The frequency-dependent ground impedances of a horizontally-buried wire are directly measured and calculated by applying sinusoidal current in the frequency range of 100 Hz to 10 MHz. Also, the results obtained in this work were compared with the data calculated from empirical equations and commercial programs. A new methodology using the delta-gap source model is proposed in order to calculate frequency-dependent ground impedance when the ground current is injected at the middle-point of the horizontal ground electrode. The high frequency ground impedance of horizontal electrodes longer than 30 m is larger or equal to its low frequency ground resistance. Consequently, the frequency-dependent ground impedance simulated with the proposed method is in agreement with the experimental data, and the validity of the computational simulation approach is confirmed.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.891-904
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• 2006

The estimation of the probability precipitation is essential for the design of hydrologic projects. The techniques to calculate the probability precipitation can be determined by the point frequency analysis and the regional frequency analysis. The regional frequency analysis includes index-flood technique and L-moment technique. In the regional frequency analysis, even if the rainfall data passed homogeneity, suitable distributions can be different at each point. However, the regional frequency analysis can supplement the lacking precipitation data. Therefore, the regional frequency analysis has weaknesses compared to parametric point frequency analysis because of suppositions about probability distributions. Therefore, this paper applies kernel density function to precipitation data so that homogeneity is defined. In this paper, The data from 16 rainfall observatories were collected and managed by the Korea Meteorological Administration to achieve the point frequency analysis and the regional frequency analysis. The point frequency analysis applies parametric technique and nonparametric technique, and the regional frequency analysis applies index-flood techniques and L-moment techniques. Also, the probability precipitation was calculated by the regional frequency analysis using variable kernel density function.