• Title/Summary/Keyword: Counts data

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Index Management Method using Page Mapping Log in B+-Tree based on NAND Flash Memory (NAND 플래시 메모리 기반 B+ 트리에서 페이지 매핑 로그를 이용한 색인 관리 기법)

  • Kim, Seon Hwan;Kwak, Jong Wook
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.5
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    • pp.1-12
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    • 2015
  • NAND flash memory has being used for storage systems widely, because it has good features which are low-price, low-power and fast access speed. However, NAND flash memory has an in-place update problem, and therefore it needs FTL(flash translation layer) to run for applications based on hard disk storage. The FTL includes complex functions, such as address mapping, garbage collection, wear leveling and so on. Futhermore, implementation of the FTL on low-power embedded systems is difficult due to its memory requirements and operation overhead. Accordingly, many index data structures for NAND flash memory have being studied for the embedded systems. Overall performances of the index data structures are enhanced by a decreasing of page write counts, whereas it has increased page read counts, as a side effect. Therefore, we propose an index management method using a page mapping log table in $B^+$-Tree based on NAND flash memory to decrease page write counts and not to increase page read counts. The page mapping log table registers page address information of changed index node and then it is exploited when retrieving records. In our experiment, the proposed method reduces the page read counts about 61% at maximum and the page write counts about 31% at maximum, compared to the related studies of index data structures.

Genetic Evaluation of Somatic Cell Counts of Holstein Cattle in Zimbabwe

  • Mangwiro, F.K.;Mhlanga, F.N.;Dzama, K.;Makuza, S.M.
    • Asian-Australasian Journal of Animal Sciences
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    • v.13 no.10
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    • pp.1347-1352
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    • 2000
  • The objectives of the study were to examine non-genetic factors that influence somatic cell counts in dairy cattle and to estimate the genetic parameters of somatic cell counts. A total of 34, 097-test day somatic cell count records were obtained from the Zimbabwe Dairy Services Association (ZDSA). The data were from 5, 615 Holstein daughters of 390 sires and 2, 541 dams tested between May 1994 and December 1998. First lactation cows contributed 22, 147 records to the data set, while 11, 950 records were from second and later parity cows. The model for analysis included fixed effects of month of calving, year of calving, stage of lactation, calving interval and test date. Milk yield and age on test day were fitted in the model as covariates. The additive genetic effects pertaining to cows, sires and dams and the residual error were the random effects. The Average Information Restricted Maximum Likelihood algorithm was used for analysis. The heritability of somatic cell scores was low at $0.027{\pm}0.013$ for parity one cows and $0.087{\pm}0.031$ for parity two and above. Repeatability estimates were $0.22{\pm}0.01$ and $0.30{\pm}0.01$ for the two lactation groups, respectively. Genetic and phenotypic correlations between the somatic cell scores and test day milk production were small and negative. It seems that there is no genetic link between somatic cell counts and milk yield in Holstein cattle in Zimbabwe. The results also seem to indicate that somatic cell count is a trait that is mainly governed by environmental factors.

Generalized Linear Models for the Analysis of Data from the Quality-Improvement Experiments (일반화 선형모형을 통한 품질개선실험 자료분석)

  • Lee, Youngjo;Lim, Yong Bin
    • Journal of Korean Society for Quality Management
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    • v.24 no.2
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    • pp.128-141
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    • 1996
  • The advent of the quality-improvement movement caused a great expansion in the use of statistically designed experiments in industry. The regression method is often used for the analysis of data from such experiments. However, the data for a quality characterstic often takes the form of counts or the ratio of counts, e.g. fraction of defectives. For such data the analysis using generalized linear models is preferred to that using the simple regression model. In this paper we introduce the generalized linear model and show how it can be used for the analysis of non-normal data from quality-improvement experiments.

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Exploring COVID-19 in mainland China during the lockdown of Wuhan via functional data analysis

  • Li, Xing;Zhang, Panpan;Feng, Qunqiang
    • Communications for Statistical Applications and Methods
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    • v.29 no.1
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    • pp.103-125
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    • 2022
  • In this paper, we analyze the time series data of the case and death counts of COVID-19 that broke out in China in December, 2019. The study period is during the lockdown of Wuhan. We exploit functional data analysis methods to analyze the collected time series data. The analysis is divided into three parts. First, the functional principal component analysis is conducted to investigate the modes of variation. Second, we carry out the functional canonical correlation analysis to explore the relationship between confirmed and death cases. Finally, we utilize a clustering method based on the Expectation-Maximization (EM) algorithm to run the cluster analysis on the counts of confirmed cases, where the number of clusters is determined via a cross-validation approach. Besides, we compare the clustering results with some migration data available to the public.

Survey of Yogurt Powder Storage in Ambient Export Countries A Safety Evaluation Standard Compliance and Comparative Analysis

  • Kim, Na-Kyeong;Park, Jung-Min;Lee, Jung-Hoon;Kim, Ha-Jung;Oh, Sejong;Imm, Jee-Young;Lim, Kwang-Sei;Kim, Jin-Man
    • Food Science of Animal Resources
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    • v.35 no.1
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    • pp.143-148
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    • 2015
  • Yogurt powder is fermented milk processed in the form of dry yogurt, and has advantages such as stability, storability, convenience, and portability. China and Vietnam are important export target countries because of the increased demand for dairy products. Therefore, we surveyed dairy product standardization in order to establish an export strategy. Lactic acid bacteria counts are unregulated in Korea and Vietnam. In China, lactic acid bacteria counts are regulated at $1{\times}10^6$ colonyforming units (CFU)/mL and detected at $6.24{\pm}0.33\;Log\;CFU/mL$. All three countries have regulated standards for total bacterial counts. In China, total bacterial counts of milk powder are regulated to n=5, c=2, m=50,000, M=200,000 and detected at $6.02{\pm}0.12\;Log\;CFU/mL$, exceeding the acceptable level. Lactic acid bacterial counts appeared to exceed total bacterial counts. Coliform group counts, Staphylococcus aureus, Listeria monocytogenes, and Salmonella species were not detected. Acidity is not regulated in Korea and Vietnam. In China, acidity was regulated to over $70^{\circ}T$ and detected $352.38{\pm}10.24^{\circ}T$. pH is unregulated in all three countries. pH was compared to that of general fermented milk, which is 4.2, and that of the sample was $4.28{\pm}0.01$. Aflatoxin levels are not regulated in Korea and China. In Vietnam, aflatoxin level is regulated at 0.05 ppb. Therefore, all ingredients of the yogurt powder met the safety standards. This data obtained in this study can be used as the basic data in assessing the export quality of yogurt powder.

A Note on the Chi-Square Test for Multivariate Normality Based on the Sample Mahalanobis Distances

  • Park, Cheolyong
    • Journal of the Korean Statistical Society
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    • v.28 no.4
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    • pp.479-488
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    • 1999
  • Moore and Stubblebine(1981) suggested a chi-square test for multivariate normality based on cell counts calculated from the sample Mahalanobis distances. They derived the limiting distribution of the test statistic only when equiprobable cells are employed. Using conditional limit theorems, we derive the limiting distribution of the statistic as well as the asymptotic normality of the cell counts. These distributions are valid even when equiprobable cells are not employed. We finally apply this method to a real data set.

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Effects on Regression Estimates under Misspecified Generalized Linear Mixed Models for Counts Data

  • Jeong, Kwang Mo
    • The Korean Journal of Applied Statistics
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    • v.25 no.6
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    • pp.1037-1047
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    • 2012
  • The generalized linear mixed model(GLMM) is widely used in fitting categorical responses of clustered data. In the numerical approximation of likelihood function the normality is assumed for the random effects distribution; subsequently, the commercial statistical packages also routinely fit GLMM under this normality assumption. We may also encounter departures from the distributional assumption on the response variable. It would be interesting to investigate the impact on the estimates of parameters under misspecification of distributions; however, there has been limited researche on these topics. We study the sensitivity or robustness of the maximum likelihood estimators(MLEs) of GLMM for counts data when the true underlying distribution is normal, gamma, exponential, and a mixture of two normal distributions. We also consider the effects on the MLEs when we fit Poisson-normal GLMM whereas the outcomes are generated from the negative binomial distribution with overdispersion. Through a small scale Monte Carlo study we check the empirical coverage probabilities of parameters and biases of MLEs of GLMM.

Application of Bootstrap Method to Primary Model of Microbial Food Quality Change

  • Lee, Dong-Sun;Park, Jin-Pyo
    • Food Science and Biotechnology
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    • v.17 no.6
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    • pp.1352-1356
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    • 2008
  • Bootstrap method, a computer-intensive statistical technique to estimate the distribution of a statistic was applied to deal with uncertainty and variability of the experimental data in stochastic prediction modeling of microbial growth on a chill-stored food. Three different bootstrapping methods for the curve-fitting to the microbial count data were compared in determining the parameters of Baranyi and Roberts growth model: nonlinear regression to static version function with resampling residuals onto all the experimental microbial count data; static version regression onto mean counts at sampling times; dynamic version fitting of differential equations onto the bootstrapped mean counts. All the methods outputted almost same mean values of the parameters with difference in their distribution. Parameter search according to the dynamic form of differential equations resulted in the largest distribution of the model parameters but produced the confidence interval of the predicted microbial count close to those of nonlinear regression of static equation.

An ICN In-Network Caching Policy for Butterfly Network in DCN

  • Jeon, Hongseok;Lee, Byungjoon;Song, Hoyoung;Kang, Moonsoo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.7
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    • pp.1610-1623
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    • 2013
  • In-network caching is a key component of information-centric networking (ICN) for reducing content download time, network traffic, and server workload. Data center network (DCN) is an ideal candidate for applying the ICN design principles. In this paper, we have evaluated the effectiveness of caching placement and replacement in DCN with butterfly-topology. We also suggest a new cache placement policy based on the number of routing nodes (i.e., hop counts) through which travels the content. With a probability inversely proportional to the hop counts, the caching placement policy makes each routing node to cache content chunks. Simulation results lead us to conclude (i) cache placement policy is more effective for cache performance than cache replacement, (ii) the suggested cache placement policy has better caching performance for butterfly-type DCNs than the traditional caching placement policies such as ALWASYS and FIX(P), and (iii) high cache hit ratio does not always imply low average hop counts.

The Application of a Pulsed Photostimulated Luminescence (PPSL) Method for the Detection of Irradiated Foodstuffs

  • Yi, Sang-Duk;Yang, Jae-Seung
    • Preventive Nutrition and Food Science
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    • v.5 no.3
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    • pp.136-141
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    • 2000
  • The properties of pulsed photostimulated luminescence (PPSL) were measured to use as basis data for the detection of irradiated foodstuffs (34 different foods). Samples were packed in polyethylene bags and irradiated at 1, 5, and 10 kGy with a dose rate of 10 kGy/h. The samples irradiated were introduced in the sample chamber without other preparation and measured PPSL photon counts for 60 and 120 s. The PPSL photo counts of the irradiated samples were higher than the unirradiated, increased with increasing irradiation dose, and showed a good relationship between irradiation doses and photon counts in a multinomial expression. These results suggest that the detection of irradiated foodstuffs was possible by PPSL. Therefore, PPSL can be proposed as the method for the detection of irradiated foodstuffs.

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