• Horticultural Science & Technology
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• v.30 no.5
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• pp.596-602
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• 2012

Infestations of Aphis gossypii per leaf in greenhouse cultivation of cucumbers were investigated to develop binomial sampling plans. An empirical $P_T-m$ model, $ln(m)={\alpha}+{\beta}ln[-ln(1-P_T)]$, was used to evaluate relationship between the proportion of infested leaves with ${\leq}$ T aphids per leaf ($P_T$) and mean aphid density (m). Tally thresholds (T) were set to 1, 3, 5, 7, and 9 aphids per leaf to find appropriate T in greenhouse cultivation of cucumbers. Increasing sample size had little effect on the precision of the binomial sampling plan. However, the precision increased with tally threshold. The binomial model with T = 5 provided appropriate predictions of the mean densities of A. gossypii in the greenhouse cultivation of cucumbers. Using a binomial model with T = 5 (sample size = 200), a wide range of densities (1.2 - 222.8 aphids per leaf) could be estimated with precision levels of 0.346 - 0.380 for $P_T$ values between 0.15 and 0.96. Binomial models were validated at T = 5 and 7 using 12 independent data sets. Both binomial models were robust and adequately described aphid densities; most of the independent sampling data fell within 95% confidence intervals around the prediction model.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.479-482
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• 1998

Whether a given tree is a subgraph of the interconnection network topology is one of the important problem in parallel computing. Trees are used as the underlying structure for divide and conquer algorithms and provide the solution spaces for NP-complete problems. Complete binary trees are the basic structure among those trees. Binomial trees play an important role in broadcasting messages in parallel networks. If binomial trees can be efficiently embedded in complex binary trees, broadcasting algorithms can be effeciently performed on the interconnection networks. In this paper, we present average dilation 2 embedding of binomial trees in complete binary trees.

• Journal of applied mathematics & informatics
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• v.26 no.1_2
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• pp.191-201
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• 2008

In this paper, we consider an insurance risk model governed by a compound Binomial arrival claim process and by a compound Binomial arrival premium process. Some formulas for the probabilities of ruin and the distribution of ruin time are given, we also prove the integral equation of the ultimate ruin probability and obtain the Lundberg inequality by the discrete martingale approach.

• Journal of the Korean Statistical Society
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• v.29 no.3
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• pp.269-284
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• 2000

We show asymptotic normality of the sample mean and sample autocovariances function generated from first-order integer valued autoregressive process(INAR(1)) with a negative binomial or a Poisson marginal. It is shown that a Poisson INAR(1) process is a special case of a negative binomial INAR(1) process.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.811-817
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• 2011

We shall introduce a general probability mass function which includes several discrete probability mass functions. Especially, when the random variable X is Poisson, binomial, and negative binomial random variables as some special cases of the introduced distribution, the maximum likelihood estimator (MLE) and the uniformly minimum variance unbiased estimator (UMVUE) of the probability P(X ${\leq}$ t) are considered. And the efficiencies of the MLE and the UMVUE of the reliability ar compared each other.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.127-136
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• 1998

In many cases where the binomial distribution fails to apply to real world data it is because of more variability in the data than can be explained by that distribution. Several authers have proposed models that are useful in explaining extra-binomial variation. In this paper we point out a characterization of sequences of exchangeable Bernoulli variables which can be used to develop models which show more variability than the binomial. We give sufficient conditions which will yield such models and show how existing models can be continued to generate further models. A numerical example and simulation given.

• The Pure and Applied Mathematics
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• v.29 no.1
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• pp.31-35
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• 2022

In the note, by virtue of Abel's theorem and Abel's limit theorem in the theory of power series, the author provides three proofs for a sum of an alternating series involving central binomial numbers.

• International Journal of Highway Engineering
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• v.18 no.4
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• pp.83-92
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• 2016

PURPOSES : The purpose of this study was to develop safety performance functions (SPFs) that use zero-inflated negative binomial regression models for urban intersections in central business districts (CBDs), and to compare the statistical significance of developed models against that of regular negative binomial regression models. METHODS : To develop and analyze the SPFs of intersections in CBDs, data acquisition was conducted for dependent and independent variables in areas of study. We analyzed the SPFs using zero-inflated negative binomial regression model as well as regular negative binomial regression model. We then compared the results by analyzing the statistical significance of the models. RESULTS : SPFs were estimated for all accidents and injury accidents at intersections in CBDs in terms of variables such as AADT, Number of Lanes at Major Roads, Median Barriers, Right Turn with an Exclusive Turn Lane, Turning Guideline, and Front Signal. We also estimated the log-likelihood at convergence and the likelihood ratio of SPFs for comparing the zero-inflated model with the regular model. In he SPFs, estimated log-likelihood at convergence and the likelihood ratio of the zero-inflated model were at -836.736, 0.193 and -836.415, 0.195. Also estimated the log-likelihood at convergence and likelihood ratio of the regular model were at -843.547, 0.187 and -842.631, 0.189, respectively. These figures demonstrate that zero-inflated negative binomial regression models can better explain traffic accidents at intersections in CBDs. CONCLUSIONS : SPFs that use a zero-inflated negative binomial regression model demonstrate better statistical significance compared with those that use a regular negative binomial regression model.

• Honam Mathematical Journal
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• v.38 no.2
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• pp.279-294
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• 2016

Half integer values of harmonic numbers and reciprocal binomial squared coeffients sums are investigated in this paper. Closed form representations and integral expressions are developed for the infiite series.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.198-207
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• 1998

The p chart approximate to the normal distribution has a difficulty to analyze the process condition precisely when the negative LCL is occurred. Furthermore, the probability of Type I error increases compared with using its original binomial distribution. For a long time the p chart has been used as approximated to the normal distribution because of its easy use. However, it becomes rapid and convenient to calculate the binomial distribution through the development of computer and software, so it is strongly suggested to use the binomial distribution determining control limits to reduce the probability of Type I error. In this study, I suggest that the control limits can be designed in use of binomial distribution and they can be utilized without special software by illustrating the certain work for establishing p-chart with the commercial one(EXCEL).