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Mechanical Properties Change of the Slacks Knee Part by the Bending Time (굽힘반복에 따른 슬랙스 무릎부위의 역학적특성 변화)

  • Lee, Joung-Suk;Kwon, Hyun-Sun;Sung, Su-Kwang
    • Fashion & Textile Research Journal
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    • v.6 no.4
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    • pp.497-502
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    • 2004
  • The mechanical properties of jean slacks to the type of cutting lines in knee region and the bending time, after doing bending 0 times, 500 times, and 1500 times, the effects of whether or not cutting line, the fabric direction of the cutting area, and the number of cutting lines were investigated for tensile, shearing, compression, and mixing value of mechanical properties. The results are as follows: EM to bending times were larger in order of weft

A Time Truncated Two-Stage Group Sampling Plan for Weibull Distribution

  • Aslam, Muhammad;Jun, Chi-Hyuck;Rasool, Mujahid;Ahmad, Munir
    • Communications for Statistical Applications and Methods
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    • v.17 no.1
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    • pp.89-98
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    • 2010
  • In this paper, a two-stage group sampling plan based on the time truncated life test is proposed for the Weibull distribution. The design parameters such as the number of groups and the acceptance number in each stage are determined by satisfying the producer's and consumer's risks simultaneously when the group size and the test duration are specified. The acceptable reliability level is expressed by the ratio of the true mean life to the specified life. It was demonstrated from the comparison with single-stage group sampling plans that the proposed plan can reduce the average sample number or improve the operating characteristics.

A Study on Microbial Contamination of Foods Exposed to Multiple Environments

  • KIM, Dan-Bee;CHA, Seong-Soo
    • The Korean Journal of Food & Health Convergence
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    • v.5 no.3
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    • pp.35-40
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    • 2019
  • In this study, general bacterial counts and coliform counts, which are hygienic indicator microorganisms, were tested for candy, chocolate, and jelly which are easily available and enjoyed around. After dropping each sample on the desk, indoors, and outdoors, it is immediately collected, or washed and collected to confirm the myth of the 3-second rule. Immediately after removing the wrapping paper, each sample was dropped on the desk, indoors, and outdoors, and after 3 seconds from the moment of contact with the surface, and then collected in a sample bag using sterilized sanitary gloves. After the same operation, each sample was rinsed for 5 seconds using sterilized sanitary gloves and sterilized distilled water, and then collected in a sample bag. The number of bacteria detected in non-washing candies was 41 CFU/g at outdoor and the number of bacteria detected in non-washing chocolate was 76 CFU/g at outdoor. The number of bacteria detected in non-washing jellies was 79 CFU/g at outdoor. Coliform group was not detected in all samples. This showed good results at the level of m = 10,000 or less, which is an allowable value suggested in the Food Code. Also, effect of washing on contaminated food was confirmed. This result is remarkably low compared with the microorganism specimens shown in Food Code, and it is confirmed that contamination occurs but not high value. Therefore, the myth of the 3-second rule is true compared to the figures based on Food Code. However, it showed the characteristics of bacteria that could survive and cross-contaminate on dry food surfaces and emphasized the importance of hygiene through food contact to unsanitary surfaces to minimize the risk of food poisoning.

Sample size determination in dental research (치의학 연구에서의 표본크기 산출)

  • Lim, Hoi-Jeong
    • The Journal of the Korean dental association
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    • v.52 no.9
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    • pp.558-569
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    • 2014
  • Sample size determination is critical, but not easy to do. Sample size defined as the number of observations in a sample to be studied should be big enough to have a high likelihood of detecting a true difference between groups. Practical procedure for determining sample size, using $G^*$power and previous dental articles, was shown in this study. Examples involving independent t-test, paired t-test, one-way analysis of variance(ANOVA), and one-way repeated-measures(RM) ANOVA were used. The purpose of this study is to enable researchers with non-statistical backgrounds to use in practice freely available statistical software G*power to determine sample size and power.

A Study on Error of Frequence Rainfall Estimates Using Random Variate (무작위변량을 이용한 강우빈도분석시 내외삽오차에 관한 연구)

  • Chai, Han Kyu;Eam, Ki Ok
    • Journal of Industrial Technology
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    • v.20 no.A
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    • pp.159-167
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    • 2000
  • In the study rainfall frequency analysis attemped the many specific property data record duration it is differance from occur to error-term and probability ditribution of concern manifest. error-term analysis of method are fact sample data using method in other hand it is not appear to be fault that sample data of number to be small random variates. Therefore, day-rainfall data: to randomicity consider of this study sample data to the Monte Carlo method by randomize after data recode duration of form was choice method which compared an assumed maternal distribution from splitting frequency analysis consequence. In the conclusion, frequency analysis of chuncheon region rainfall appeared samll RMSE to the Gamma II distribution. In the rainfall frequency analysis estimate RMSE using random variates great transform, RMSE is appear that return period increasing little by little RMSE incresed and data number incresing to RMSE decreseing.

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Cumulative Sequential Control Charts with Sample Size Bound (표본크기에 제약이 있는 누적 축차관리도)

  • Chang, Young-Soon;Bai, Do-Sun
    • Journal of Korean Institute of Industrial Engineers
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    • v.25 no.4
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    • pp.448-458
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    • 1999
  • This paper proposes sequential control charts with an upper bound on sample size. Existing sequential control charts have no restriction on the number of observations at a sampling point. For situations where sampling and testing an item is time-consuming or expensive, sequential control charts may not be directly applied. When the number of observations in a sampling point reaches the upper bound and there is no out-of-control signal, the proposed cumulative sequential control chart defers the decision to the next sampling point of which starting value is the value of the current statistic. Two Markov chains, inner and outer chains, are used to derive the formulas for evaluating the performance of the proposed chart. It is compared with $\bar{X}$ and cumulative sum control charts with fixed and variable sample sizes. The fast initial response (FIR) feature is studied. Guidelines for the design of the proposed charts are also given.

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On-line System Identification using State Observer

  • Park, Duck-Gee;Hong, Suk-Kyo
    • 제어로봇시스템학회:학술대회논문집
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    • pp.2538-2541
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    • 2005
  • This paper deals one of the methods of system identification, especially on-line system identification in time-domain. The algorithm in this study needs all states of the system as well input to it for system identification. In this reason, Kalman filter is used for state estimation. But in order to implement a state estimator, the fact that a system model must be known is logical contradiction. To overcome this, state estimation and system parameter estimation are performed simultaneously in one sample. And the result of the system parameter estimation is used as basis to state estimation in next sample. On-line system identification comes, in every sample by performing both processes of state estimation and parameter estimation that are related mutually and recursively. This paper demonstrates the validity of proposed algorithm through an example of an unstable inverted pendulum system. This algorithm can be useful for on-line system identification of a system that has fewer number of measurable output than system order or number of states.

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Studies on the Quality Evaluation and Metal Content of Sanitary Canned by Fermented Soybean of Bacillus starter (위생캔으로 제조한 Bacillus Starter 발효대두의 품질 평가와 금속물질 함량에 관한 연구)

  • 허윤행
    • Journal of environmental and Sanitary engineering
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    • v.17 no.3
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    • pp.14-20
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    • 2002
  • In order to improve the quality and sensory evaluation of Fermented Soybean(Chungkugjang meju) were investigated. The samples were prepared and fermented by the inoculation of Bacillus strains (B. subtilis, number 1, B. natto, number 2) that the product made With sanitary canned food. 1. The water content of samples was 46.75~50.60%, pH 5.35~6.95 and total acidity 3.26~3.62. 2. The reducing sugar of content for sample was 9.49~10.05%, Amino-N, 67~396mg% and the activity of protease was 0.36~1.49unit/g. 3. The heavy metals analyzed from sample cans, iron, tin and lead content of sample were 5.32~5.84ppm, 27.31~29.04ppm and 0.019~0.021ppm. 4. Therefore, results that Chungkugjang-meju manufactured from B. natto starter induced better product Quality and sensory test than that of the B. subtilis strain.

Allocation in Multi-way Stratification by Linear Programing

  • NamKung, Pyong;Choi, Jae-Hyuk
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.327-341
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    • 2006
  • Winkler (1990, 2001), Sitter and Skinner (1994), Wilson and Sitter (2002) present a method which applies linear programing to designing surveys with multi-way stratification, primarily in situation where the desired sample size is less than or only slightly larger than the total number of stratification cells. A comparison is made with existing methods both by illustrating the sampling schemes generated for specific examples, by evaluating sample mean, variance estimation, and mean squared errors, and by simulating sample mean for all methods. The computations required can, however, increase rapidly as the number of cells in the multi-way classification increase. In this article their approach is applied to multi-way stratification using real data.

Imbalanced SVM-Based Anomaly Detection Algorithm for Imbalanced Training Datasets

  • Wang, GuiPing;Yang, JianXi;Li, Ren
    • ETRI Journal
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    • v.39 no.5
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    • pp.621-631
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    • 2017
  • Abnormal samples are usually difficult to obtain in production systems, resulting in imbalanced training sample sets. Namely, the number of positive samples is far less than the number of negative samples. Traditional Support Vector Machine (SVM)-based anomaly detection algorithms perform poorly for highly imbalanced datasets: the learned classification hyperplane skews toward the positive samples, resulting in a high false-negative rate. This article proposes a new imbalanced SVM (termed ImSVM)-based anomaly detection algorithm, which assigns a different weight for each positive support vector in the decision function. ImSVM adjusts the learned classification hyperplane to make the decision function achieve a maximum GMean measure value on the dataset. The above problem is converted into an unconstrained optimization problem to search the optimal weight vector. Experiments are carried out on both Cloud datasets and Knowledge Discovery and Data Mining datasets to evaluate ImSVM. Highly imbalanced training sample sets are constructed. The experimental results show that ImSVM outperforms over-sampling techniques and several existing imbalanced SVM-based techniques.