• Title/Summary/Keyword: small sample size

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Design of Median Control Chart for Unsymmetrical Weibull Distribution (비대칭(非對稱)와이블분포공정(分布工程)에서 메디안특수관리도(特殊管理圖)의 설계(設計))

  • Sin, Yong-Baek;Hwang, Ui-Mi
    • Journal of Korean Society for Quality Management
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    • v.14 no.2
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    • pp.2-8
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    • 1986
  • This thesis is concerned with the design of control chart based on the sample median which is easy to use in practical situations and to analyze the properties for non-normally distributed Weibull process. In this cases are use to the quality characteristics of the process are not normally distributed but skewed due to the intermitted production, small lot size and sample size is small one n=3 or n=5, etc. And when it relates unsymmetrically distributed process, model designed median control chart is more effective than Shewhart $\bar{x}$-chart which assumed on normal distribution, when we exactly should be known Weibull distribution or estimated. The median control chart in this thesis is more robustness compared with other conventionally developed control chart.

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Design of an Ultra-Compact UHF Passive RFID Tag Antenna for a Medical Sample Tube

  • Lee, Jung-Nam;Hwang, Moon-Young;Lee, Sang-Il;Lee, Kwang-Chun;Park, Jong-Kweon
    • ETRI Journal
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    • v.34 no.6
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    • pp.974-977
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    • 2012
  • In this letter, a small-sized ultra-high frequency (UHF) RFID tag antenna for a medical sample tube is proposed. The RFID tag antenna is designed and fabricated based on the circular loop antenna used in the UHF band (Korea standard, 917 MHz to 923.5 MHz). The tag antenna size is reduced using a circular meander stub. The antenna has a physical size of 8 mm, which is about ${\lambda}$/40 in electrical length. The proposed tag antenna is molded into a medical sample and multitag identification is performed.

Penalizing the Negative Exponential Disparity in Discrete Models

  • Sahadeb Sarkar;Song, Kijoung-Song;Jeong, Dong-Bin
    • Communications for Statistical Applications and Methods
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    • v.5 no.2
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    • pp.517-529
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    • 1998
  • When the sample size is small the robust minimum Hellinger distance (HD) estimator can have substantially poor relative efficiency at the true model. Similarly, approximating the exact null distributions of the ordinary Hellinger distance tests with the limiting chi-square distributions can be quite inappropriate in small samples. To overcome these problems Harris and Basu (1994) and Basu et at. (1996) recommended using a modified HD called penalized Hellinger distance (PHD). Lindsay (1994) and Basu et al. (1997) showed that another density based distance, namely the negative exponential disparity (NED), is a major competitor to the Hellinger distance in producing an asymptotically fully efficient and robust estimator. In this paper we investigate the small sample performance of the estimates and tests based on the NED and penalized NED (PNED). Our results indicate that, in the settings considered here, the NED, unlike the HD, produces estimators that perform very well in small samples and penalizing the NED does not help. However, in testing of hypotheses, the deviance test based on a PNED appears to achieve the best small-sample level compared to tests based on the NED, HD and PHD.

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NIR - a Tool for Evaluation of Milling Procedure

  • Gergely, Sziveszter;Handzel, Lidia;Zoltan, Andrea;Salgo, Andras
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1125-1125
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    • 2001
  • Micro-scale test methods are producing small-sample size where the conventional physical and chemical tests can not be used (high standard deviation, uncertain sampling conditions, low repeatability). Different small-scale test methods were developed recently for determination of physico-chemical, functional, rheological properties of wheat or wheat dough using miniaturized instruments with sophisticated sample preparation/handling and mechanics (RVA, 2 g mixograph, micro-Z-arm mixer, small-scale noodle maker, micro-baking method etc.). The small-scale methodologies can be used as basic research tools or as technology supported measurements and can be also essential in the early selection for quality traits in breeding programs. The milling as a sample preparation step is essential procedure providing good quality flour or semolina samples from small amount of grain (5-10 g) in a reproducible and reliable way. The aim of present study was to use NIR as quality control tool, and to evaluate the recently developed and manufactured micro-scale lab mill (FQC-2000) produced by Inter-Labor Co. Ltd., Hungary. The milling characteristics of the new instrument were compared to other laboratory mills and the effects of milling action on the chemical composition of fractions were analysed. The fractions were tested with both chemical and near infrared spectroscopic methods. The micro-scale milling resulted significantly different yields, particle size distributions and different fractions from compositional point of view. The near infrared spectra were sensitive enough to distinguish the fractions obtained by different milling procedures. Quantitative NIR calibration equations were developed and tested in order to measure the chemical composition of characteristic milling fractions. Special qualification procedure the PQS (Polar Qualification System) method was used for detecting the differences between fractions obtained by macro and micro-milling procedures. The results and the limitations of PQS method in this application will be discussed.

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On Optimizing Dissimilarity-Based Classifier Using Multi-level Fusion Strategies (다단계 퓨전기법을 이용한 비유사도 기반 식별기의 최적화)

  • Kim, Sang-Woon;Duin, Robert P. W.
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.5
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    • pp.15-24
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    • 2008
  • For high-dimensional classification tasks, such as face recognition, the number of samples is smaller than the dimensionality of the samples. In such cases, a problem encountered in linear discriminant analysis-based methods for dimension reduction is what is known as the small sample size (SSS) problem. Recently, to solve the SSS problem, a way of employing a dissimilarity-based classification(DBC) has been investigated. In DBC, an object is represented based on the dissimilarity measures among representatives extracted from training samples instead of the feature vector itself. In this paper, we propose a new method of optimizing DBCs using multi-level fusion strategies(MFS), in which fusion strategies are employed to represent features as well as to design classifiers. Our experimental results for benchmark face databases demonstrate that the proposed scheme achieves further improved classification accuracies.

Determinants of Tax Aggressiveness: Empirical Evidence from Malaysia

  • JAFFAR, Rosmaria;DERASHID, Chek;TAHA, Roshaiza
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.5
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    • pp.179-188
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    • 2021
  • The purpose of this study is to examine the level of aggressive tax planning (ATP) among companies listed in the Access, Certainty, Efficiency (ACE) Market of Bursa Malaysia. On top of that, this study also investigates the relationship between company characteristics, ethnicity, and ATP. This study uses a balanced pooled sample of 105 firm years-observations for the period from 2014 to 2018. These samples were selected to provide new insight into this market and to explore the attitude of small firms toward ATP in Malaysia. The data was retrieved from DataStream and the downloaded annual reports. The finding shows that profitability and financial distress have a significant relationship with ATP. Other variables including size, capital intensity, inventory intensity, leverage, and ethnicity, were not determinants of ATP. The result in this study may assist the reader in understanding the nature of companies in the ACE market, particularly on its behavior toward tax planning. A strict requirement is needed to be adopted in the sample selection process, thus limiting the sample size. Further, since the previous study focused on large companies, the discussion of this paper will provide new insight into the nature of tax planning within the small- and medium-sized companies in Malaysia.

Bayesian hierarchical model for the estimation of proper receiver operating characteristic curves using stochastic ordering

  • Jang, Eun Jin;Kim, Dal Ho
    • Communications for Statistical Applications and Methods
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    • v.26 no.2
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    • pp.205-216
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    • 2019
  • Diagnostic tests in medical fields detect or diagnose a disease with results measured by continuous or discrete ordinal data. The performance of a diagnostic test is summarized using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The diagnostic test is considered clinically useful if the outcomes in actually-positive cases are higher than actually-negative cases and the ROC curve is concave. In this study, we apply the stochastic ordering method in a Bayesian hierarchical model to estimate the proper ROC curve and AUC when the diagnostic test results are measured in discrete ordinal data. We compare the conventional binormal model and binormal model under stochastic ordering. The simulation results and real data analysis for breast cancer indicate that the binormal model under stochastic ordering can be used to estimate the proper ROC curve with a small bias even though the sample sizes were small or the sample size of actually-negative cases varied from actually-positive cases. Therefore, it is appropriate to consider the binormal model under stochastic ordering in the presence of large differences for a sample size between actually-negative and actually-positive groups.

Organizational Usage of Social Media for Corporate Reputation Management

  • Becker, Kip;Lee, Jung Wan
    • The Journal of Asian Finance, Economics and Business
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    • v.6 no.1
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    • pp.231-240
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    • 2019
  • The paper aims to investigate the relationship between firm size and organizational actions on adopting social media for corporate reputation management. The sample group of 198 companies is selected with a simple random sample method from the New York Stock Exchange (NYSE) listings: Sixty nine companies were from the Fortune 500 listings, seventy one companies from the NYSE midsize capitalization and fifty eight companies from the NYSE small capitalization listings. This study employs cross tabulations and Chi-square analysis, and the Kruskal-Wallis that enables the comparison of three samples that are independent. The results of the study show that (1) large firms have more social media ownership than small firms, (2) large firms respond to social media posts at a greater frequency and quickly than small firms, and (3) firm size is less likely associated with response styles to social media for online reputation management. The results show that reply time and response styles of organizations to social media customers in the 2015 survey has no significant change compared to that of 2011. There appears to be a pervasive lack strategic framework as most firms in the study were found not to be adequately monitoring or leveraging social media communication for their reputation management.

Implementation of Nonparametric Statistics in the Non-Normal Process (비정규 공정에서 비모수 통계의 적용)

  • Choe, Seong-Un
    • Proceedings of the Safety Management and Science Conference
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    • 2012.04a
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    • pp.573-577
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    • 2012
  • Based on latest research, the parametric quality statistics cannot be used in non-normal process with demand pattern of many-variety and small-volume, since it involves extremely small sample size. The research proposes nonparametric quality statistics according to the number of lot or batch in the non-normal process. Additionally, the nonparametric Process Capability Index (PCI) is used with 14 identified non-normal distributions.

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Small sample tests for two-way contingency tables (2원 분할표의 소표본 검증법)

  • 허명회
    • The Korean Journal of Applied Statistics
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    • v.10 no.2
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    • pp.339-352
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    • 1997
  • Chi-square test based on large sample theory is inappropriate for testing the row homogeneity in two-way contingency table with several sparse cells. For that case, exact testing methods has been developed in the literature and implemented in StatXact(1991). However, considerable computing time is inevitable for moderate size tables. So, Monte Carlo approximation is recommended frequently. In this study, we propose a simple algorithm for generating two-way random tables with fixed row and column margins for small sample chi-square test. Also, we develop “Turkey-type” method for multiple between-row comparisons.

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