• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.147-161
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• 1995

The primary objective of this paper is to review parametric models and test statistics related to overdspersion of count data. Poisson or binomial assumption often fails to explain overdispersion. We reviewed real examples of overdispersion in count data that occurred in toxicological or teratological experiments. We also reviewed several models that were suggested for implementing experiments. We also reviewed several models that were suggested for implementing the extra-binomial variation or hyper-Poisson variability, and we noted how these models were generalized and further developed. The approaches that have been suggested for the overdispersion fall into two broad categories. The one is to develop a parametric model for it, and the other is to assume a particular relationship between the variance and the mean of the response variable and to derive a score test staistics for detecting the overdispersion. Recently, Dean(1992) derived a general score test statistics for detecting overdispersion from the exponential family.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.111-120
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• 2001

Either systematic sampling or stratified sampling is usually applied to the business conditions survey when companies don't have much difference in their size. But the cutoff systematic sampling is an efficient method when only a few companies are so large that the total of them almost equals to the total of whole companies. Throughout this paper, three estimators of total and their variance estimations depending on three kinds of sampling schemes are discussed, and are compared with them via their variances. It is proved that the cut-off systematic sampling is most efficient by using a real data of the logging business conditions survey.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1191-1202
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• 1999

We propose an efficient vehicle detection and classification algorithm for an electronic toll collection using the feature which is robust to abrupt intensity change between consecutive frames. The local correlation coefficient between wavelet transformed input and reference images is used as such a feature, which takes advantage of textural similarity. The usefulness of the proposed feature is analyzed qualitatively by comparing the feature with the local variance of a difference image, and is verified by measuring the improvements in the separability of vehicle from shadowy or shadowless road for a real test image. Experimental results from field tests show that the proposed vehicle detection and classification algorithm performs well even under abrupt intensity change due to the characteristics of sensor and occurrence of shadow.

• MALSORI
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• no.44
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• pp.73-82
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• 2002

Channel distortion degrades the performance of speech recognizer in telephone environment. It mainly results from the bandwidth limitation and variation of transmission channel. Variation of channel characteristics is usually represented as baseline shift in the cepstrum domain. Thus undesirable effect of the channel variation can be removed by subtracting the mean from the cepstrum. In this paper, to improve the recognition performance of Korea connected digit telephone speech, channel compensation methods such as CMN (Cepstral Mean Normalization), RTCN (Real Time Cepatral Normalization), MCMN (Modified CMN) and MRTCN (Modified RTCN) are applied to the static MFCC. Both MCMN and MRTCN are obtained from the CMN and RTCN, respectively, using variance normalization in the cepstrum domain. Using HTK v3.1 system, recognition experiments are performed for Korean connected digit telephone speech database released by SITEC (Speech Information Technology & Industry Promotion Center). Experiments have shown that MRTCN gives the best result with recognition rate of 90.11% for connected digit. This corresponds to the performance improvement over MFCC alone by 1.72%, i.e, error reduction rate of 14.82%.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.507-513
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• 2010

Let {$X_i,-{\infty}$ < 1 < $\infty$} be a doubly infinite sequence of identically distributed and negatively associated random variables with mean zero and finite variance and {$a_i,\;-{\infty}$ < i < ${\infty}$} be an absolutely summable sequence of real numbers. Define a moving average process as $Y_n={\sum}_{i=-\infty}^{\infty}a_{i+n}X_i$, n $\geq$ 1 and $S_n=Y_1+{\cdots}+Y_n$. In this paper we prove that E|$X_1$|$^rh$($|X_1|^p$) < $\infty$ implies ${\sum}_{n=1}^{\infty}n^{r/p-2-q/p}h(n)E{max_{1{\leq}k{\leq}n}|S_k|-{\epsilon}n^{1/p}}{_+^q}<{\infty}$ and ${\sum}_{n=1}^{\infty}n^{r/p-2}h(n)E{sup_{k{\leq}n}|k^{-1/p}S_k|-{\epsilon}}{_+^q}<{\infty}$ for all ${\epsilon}$ > 0 and all q > 0, where h(x) > 0 (x > 0) is a slowly varying function, 1 ${\leq}$ p < 2 and r > 1 + p/2.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1575-1585
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• 2017

This paper presents a synchronous generator with a distributed system of multiple parallel three-phase power cells. This generator can immediately output high DC. Each power cell comprises three-phase windings and a three-phase synchronous rectification bridge with a deadbeat control of load power feedforward, which can improve the characteristics of dynamic response and reflect the load variance in real time. Furthermore, each power cell works well independently and modularly using the method of automatic maximum current sharing. The simulation and experimental results for the distributed controller of multiple power cells demonstrate that the deadbeat control method can respond quickly and optimize the quality of the energy. Meanwhile, automatic maximum current sharing can realize the validity of current sharing among power cells.

• Journal of the Korean Society of Marine Environment & Safety
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• v.10 no.2 s.21
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• pp.49-53
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• 2004

In this paper, we study a FDS(fishery detection system) for protection of an aquaculture farm. The FDS will identify a robbing vessel with real time and detect variance of the position of aquaculture farm. We also propose a F-AIS(Fishery- Automatic Identification System), which can detect the object approaching to aquaculture farm and distinguish fishing boats from thief vessel The F-AIS with low price and wideband responsibility will be adopted to the FDS.

• The Journal of the Acoustical Society of Korea
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• v.30 no.8
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• pp.474-481
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• 2011

Conventional beamforming is ineffective in producing directional information in system with sparse degree of the freedom such as DIFAR (DIrectional Frequency Analysis and Recording) sonobuoy and in the presence of high directional noise. In this paper, Adaptive beamforming techniques are applied to produce directional spectra from a small number of sensors in highly directional noise environment. Conventional method as well as minimum variance and eigenvectors as adaptive method are evaluated via numerical test and real data.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.1-21
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• 2016

The Markowitz portfolio selection model uses estimators to deduce input parameters. However, the estimation errors of input parameters negatively influence the performance of portfolios. Therefore, this model cannot be reliably applied to real-world investments. To overcome this problem, we suggest an algorithm that can exclude stocks with large estimation error from the portfolio by applying a tracking signal to the Markowitz portfolio selection model. By calculating the tracking signal of each stock, we can monitor whether unexpected departures occur on the outcomes of the forecasts on rate of returns. Thereafter, unreliable stocks are removed. By using this approach, portfolios can comprise relatively reliable stocks that have comparatively small estimation errors. To evaluate the performance of the proposed approach, a 10-year investment experiment was conducted using historical stock returns data from 6 different stock markets around the world. Performance was assessed and compared by the Markowitz portfolio selection model with additional constraints and other benchmarks such as minimum variance portfolio and the index of each stock market. Results showed that a portfolio using the proposed approach exhibited a better Sharpe ratio and rate of return than other benchmarks.

• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.11-18
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• 2017

The cycle time of construction equipment for earthwork operations has a significant impact on project productivity. Elements that directly impact a haul vehicle's cycle time must be identified in order to accurately quantify the haul cycle time and implement strategies to decrease it. The objective of this research is to scientifically identify and quantify variables that have a significant impact on the cycle time of a dump truck used for earthwork. Real-time location data collected by GPS devices deployed in an active earthwork moving construction site was analyzed using statistical regression. External data including environmental components and haul road conditions were also collected periodically throughout the study duration. Several statistical analyses including a variance analysis and regression analysis were completed on the dump truck location data. Collected data was categorized by stage of the dump truck cycle. Results indicate that a dump truck's enter idle time, exit idle time, moving speed and driver visibility can significantly impact the dump truck cycle time. The contribution of this research is the identification and analysis of statistically significant correlations of variables within the cycle time.