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Relevant bibliographies by topics / Spearman's rank-order correlation coefficient

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Academic literature on the topic 'Spearman's rank-order correlation coefficient'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 February 2022

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Journal articles on the topic "Spearman's rank-order correlation coefficient"

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Chambers, Ll G. "73.52 Spearman's Rank Correlation Coefficient." Mathematical Gazette 73, no. 466 (December 1989): 331. http://dx.doi.org/10.2307/3619313.

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Burghes, David N. "Teaching Spearman's Rank Correlation Coefficient." Teaching Statistics 15, no. 3 (September 1993): 68–69. http://dx.doi.org/10.1111/j.1467-9639.1993.tb00658.x.

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Gauthier, T. "Detecting Trends Using Spearman's Rank Correlation Coefficient." Environmental Forensics 2, no. 4 (December 2001): 359–62. http://dx.doi.org/10.1006/enfo.2001.0061.

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Gautheir, Thomas D. "Detecting Trends Using Spearman's Rank Correlation Coefficient." Environmental Forensics 2, no. 4 (January 2001): 359–62. http://dx.doi.org/10.1080/713848278.

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Hauke, Jan, and Tomasz Kossowski. "Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data." Quaestiones Geographicae 30, no. 2 (June 1, 2011): 87–93. http://dx.doi.org/10.2478/v10117-011-0021-1.

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Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data Spearman's rank correlation coefficient is a nonparametric (distribution-free) rank statistic proposed by Charles Spearman as a measure of the strength of an association between two variables. It is a measure of a monotone association that is used when the distribution of data makes Pearson's correlation coefficient undesirable or misleading. Spearman's coefficient is not a measure of the linear relationship between two variables, as some "statisticians" declare. It assesses how well an arbitrary monotonic function can describe a relationship between two variables, without making any assumptions about the frequency distribution of the variables. Unlike Pearson's product-moment correlation coefficient, it does not require the assumption that the relationship between the variables is linear, nor does it require the variables to be measured on interval scales; it can be used for variables measured at the ordinal level. The idea of the paper is to compare the values of Pearson's product-moment correlation coefficient and Spearman's rank correlation coefficient as well as their statistical significance for different sets of data (original - for Pearson's coefficient, and ranked data for Spearman's coefficient) describing regional indices of socio-economic development.

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Henery, R. J. "Asymptotic convergence in distribution for spearman's rank correlation coefficient." Communications in Statistics - Simulation and Computation 17, no. 4 (January 1988): 1449–52. http://dx.doi.org/10.1080/03610918808812734.

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Berry, Kenneth J., and Paul W. Mielke. "Spearman's Footrule as a Measure of Agreement." Psychological Reports 80, no. 3 (June 1997): 839–46. http://dx.doi.org/10.2466/pr0.1997.80.3.839.

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Spearman's footrule measure of the relationship between two sets of ranks is shown to be a chance-corrected measure of agreement. The footrule is generalized to include tied ranks and a comparison with Spearman's rank-order correlation coefficient is provided. Procedures to determine the nonasymptotic probability of the footrule with tied ranks are presented.

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Lee, Yongjoo, and Hwajoon Kim. "THE SPEARMAN RANK-ORDER CORRELATION COEFFICIENT REPRESENTED BY LAPLACE TRANSFORM." JP Journal of Heat and Mass Transfer 18, no. 2 (December 30, 2019): 363–72. http://dx.doi.org/10.17654/hm018020363.

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Franklin, L. A. "A note on approximations and convergence in distribution for spearman's rank correlation coefficient." Communications in Statistics - Theory and Methods 17, no. 1 (January 1988): 55–59. http://dx.doi.org/10.1080/03610928808829609.

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J, Ashok Kumar, and Abirami S. "Aspect-based opinion ranking framework for product reviews using a Spearman's rank correlation coefficient method." Information Sciences 460-461 (September 2018): 23–41. http://dx.doi.org/10.1016/j.ins.2018.05.003.

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Dissertations / Theses on the topic "Spearman's rank-order correlation coefficient"

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HUANG, SHIJING. "ESTIMATING ILLEGAL DRUG MARKET LOCATION IN CINCINNATI USING THE HUFF MODEL." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1090862711.

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CHEN, ZHAOREN. "ANALYSIS OF EQUITY MARKETS: A SPEARMAN RANK CORRELATION COEFFICIENT APPROACH." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/612636.

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In this honors thesis, I attempted to develop an investment strategy to analyze the U.S. stock market by studying the correlations between nine sectors defined by the Select Sector Standard & Poor’s Depository Receipts (SPDR). These funds are a group of exchange-traded funds (ETFs) which are traded worldwide and can adequately represent the performance of the sectors. Through my method, I hope to identify the sector trends in the future by evaluating the sector ETF’s most recent short-term period data. This analysis will provide an alternate investment method for investors to avoid short-term investment risk as well as explanations of why I think the approach may not be valid.

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Louw, Charl. "The presentation of self-concept and emotional profile in a cardiological population." Diss., Pretoria : [s.n.], 2004. http://upetd.up.ac.za/thesis/available/etd-02092005-092504.

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Borunský, Tomáš. "Optimalizace procesu tlakového lití VN přístrojových transformátorů." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2009. http://www.nusl.cz/ntk/nusl-228552.

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This thesis deals with choises of using mathematical statistics when optimising the compression casting process of high-voltage device transformer. There is a theoretical consideration to be found in the introduction which concerns the compression casting itself and all necessary information connected with it. Then there is a key numerical analysis part following. In the first instance there are variability problems of individual casting device discussed and then a regression analysis made to demonstrate and prove a link between the partial discharge and the key parameters of casting process. Finally an “optimal” casting sequence is suggested and alternative attitude problems with the assistance of Design of Experiments (DOE) are discussed.

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Kovařík, Tomáš. "Řízení poslechových testů pro subjektivní hodnocení kvality audio signálu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219467.

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The point of this thesis was to perform listening tests. Appropriate methods of performance were selected for these tests, tests were carried out and the data were analyzed using statistical analysis. Then was compiled the resulting interval scale from results of the first test and in the second listening test were determined average values SNR for background noises.

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VOMÁČKA, Pavel. "Možnosti promítnutí rizika do hodnocení finanční situace podniku." Master's thesis, 2014. http://www.nusl.cz/ntk/nusl-174018.

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Objective of this Master's thesis is to evaluate different ways of measuring financial performance of enterprise. Economic Value Added is compared with older, traditional indicators of profitability. Emphasis lies on general applicability. In theoretical part, history of entrepreneurial goals is in addition to the actual analysis of tested indicators outlined. EVA, profitability ratios are assessed using a sample of 100 Czech manufacturing companies. In practical part, outputs of thesis apart from actual testing are stated.

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Books on the topic "Spearman's rank-order correlation coefficient"

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Sloan, Luke, and Rob Angell. Spearman’s Rank-Order Correlation Coefficient and the General Social Survey (2012): Income and Political Influence. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2015. http://dx.doi.org/10.4135/9781473937987.

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Sloan, Luke, and Rob Angell. Spearman’s Rank-Order Correlation Coefficient and the General Social Survey (2012): Highest Level of Education and Income. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2015. http://dx.doi.org/10.4135/9781473937857.

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Spearman's Rank-Order Correlation Coefficient and the World DataBank (2012): Gross Domestic Product Per Capita and Internet Access. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2015. http://dx.doi.org/10.4135/9781473937871.

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Spearman’s Rank-Order Correlation Coefficient and the Global Health Observatory Data (2012): Life Expectancy and Per Capita Government Health Spending. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2015. http://dx.doi.org/10.4135/9781473948181.

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Book chapters on the topic "Spearman's rank-order correlation coefficient"

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Gooch, Jan W. "Spearman Rank Correlation Coefficient." In Encyclopedic Dictionary of Polymers, 996–97. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15382.

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MacFarland, Thomas W., and Jan M. Yates. "Spearman’s Rank-Difference Coefficient of Correlation." In Introduction to Nonparametric Statistics for the Biological Sciences Using R, 249–97. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30634-6_8.

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Grzegorzewski, Przemysław, and Paulina Ziembińska. "Spearman’s Rank Correlation Coefficient for Vague Preferences." In Flexible Query Answering Systems, 342–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24764-4_30.

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Kokoska, Stephen, and Christopher Nevison. "Critical Values For Spearman’s Rank Correlation Coefficient." In Springer Texts in Statistics, 86. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-9629-1_22.

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Baszczyńska, Aleksandra, and Czesław Domański. "Distribution of the Spearman’s Rank Correlation Coefficient." In Operations Research ’92, 333–35. Heidelberg: Physica-Verlag HD, 1993. http://dx.doi.org/10.1007/978-3-662-12629-5_95.

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Williams, R. B. G. "Spearman’s and Kendall’s Coefficients of Rank Correlation." In Intermediate Statistics for Geographers and Earth Scientists, 451–79. London: Macmillan Education UK, 1986. http://dx.doi.org/10.1007/978-1-349-06813-5_6.

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Zhao, Boxu, and Guiming Luo. "Reasoning of Causal Direction in Linear Model Based on Spearman’s Rank Correlation Coefficient." In Knowledge Science, Engineering and Management, 259–70. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29563-9_24.

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Gilbertson, D. D., M. Kent, and F. B. Pyatt. "Data analysis and interpretation III: correlation and regression using Spearman’s rank correlation coefficient and semi-averages regression." In Practical Ecology for Geography and Biology, 218–36. Boston, MA: Springer US, 1985. http://dx.doi.org/10.1007/978-1-4684-1415-8_13.

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Li, Zhiqiang, Shihui Wang, and Hongchen Guo. "A Label-Correlated Multi-label Classification Algorithm Based on Spearman Rank Correlation Coefficient." In Recent Developments in Intelligent Systems and Interactive Applications, 51–58. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49568-2_8.

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"Spearman's Rank-Order Correlation Coefficient." In Handbook of Parametric and Nonparametric Statistical Procedures. Chapman and Hall/CRC, 2003. http://dx.doi.org/10.1201/9781420036268.ch29.

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Conference papers on the topic "Spearman's rank-order correlation coefficient"

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Szmidt, Eulalia, and Janusz Kacprzyk. "The Spearman rank correlation coefficient between intuitionistic fuzzy sets." In 2010 5th IEEE International Conference Intelligent Systems (IS). IEEE, 2010. http://dx.doi.org/10.1109/is.2010.5548399.

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Szmidt, Eulalia, and Janusz Kacprzyk. "The Spearman and Kendall rank correlation coefficients between intuitionistic fuzzy sets." In 7th conference of the European Society for Fuzzy Logic and Technology. Paris, France: Atlantis Press, 2011. http://dx.doi.org/10.2991/eusflat.2011.85.

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Briones, Alejandro M., David L. Burrus, Joshua P. Sykes, Brent A. Rankin, and Andrew W. Caswell. "Automated Design Optimization of a Small-Scale High-Swirl Cavity-Stabilized Combustor." In ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/gt2018-76900.

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A numerical optimization study is performed on a small-scale high-swirl cavity-stabilized combustor. A parametric geometry is created in CAD software that is coupled with meshing software. The latter automatically transfers meshes and boundary conditions to the solver, which is coupled with a post-processing tool. Steady, incompressible three-dimensional simulations are performed using a multi-phase Realizable k-ϵ Reynolds-averaged Navier-Stokes (RANS) approach with the non-adiabatic flamelet progress variable (FPV). There are nine input parameters based on geometrical control variables. There are five output parameters, viz., pattern factor (PF), RMS of the profile factor deviation, averaged exit temperature, averaged exit swirl angle, and total pressure loss. An iterative design of experiments (DOE) with a recursive Latin Hypercube Sampling (LHS) is performed to filter the most important input parameters. The five major input parameters are found with Spearman’s order-rank correlation and R2 coefficient of determination. The five input parameters are used for the adaptive multiple objective (AMO) optimization. The AMO algorithm provided a candidate design point with the lowest weighted objective function. This design point was verified through CFD simulation. The combined filtering and optimization procedures improve the baseline design point in terms of pattern and profile factor. The former halved from that of the baseline design point whereas the latter turned from an outer peak to a center peak profile, closely mimicking an ideal profile. The exit swirl angle favorably increased 25%. The averaged exit temperature and the total pressure losses remained nearly unchanged from the baseline design point.

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Kairiene, Aida. "The Relationship between English Language Skills and Learning Needs of Secondary School Students." In 14th International Scientific Conference "Rural Environment. Education. Personality. (REEP)". Latvia University of Life Sciences and Technologies. Faculty of Engineering. Institute of Education and Home Economics, 2021. http://dx.doi.org/10.22616/reep.2021.14.010.

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Students learn English with certain motives. Many students seek to improve their careers, others seek to gain confidence, and others plan to live abroad. Thus, the problematic question arises: how do English language skills and learning needs of secondary school students relate to each other? The research aim is to designate the relationship between English language skills and learning needs of secondary school students. The methods of descriptive statistics were used. The Spearman rank correlation coefficient was applied. Mostly the medium correlation and a weak correlation were dominated between English language skills and learning needs. The analysis disclosed that students give more priority to receptive skills ‒ reading and listening than to communicative - speaking and writing skills.

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Zhao, Peirui, Xiaohong Wang, Hongliang Yu, and Shizeng Lu. "Method for Identifying Current Operating Conditions of Main Motor of Cement Rotary Kiln Based on Spearman Rank Correlation Coefficient." In 2019 34rd Youth Academic Annual Conference of Chinese Association of Automation (YAC). IEEE, 2019. http://dx.doi.org/10.1109/yac.2019.8787648.

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Bozdağ, Emre Güneşer, and Sıtkıcan Saraçoğlu. "Analysis of Competitiveness of Turkey and Commonwealth of Independent States in their Automotive Market." In International Conference on Eurasian Economies. Eurasian Economists Association, 2013. http://dx.doi.org/10.36880/c04.00679.

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Automotive sector is a driving sector for countries due to forward and backward linkages and employment and value added it creates. Starting from this point, this study aims to analyze the competitiveness of CIS and Turkey automotive sector in their market. The competitiveness of the countries should be assessed with their production potential. The countries subject to the study are thirteen Eurasian countries, Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyz Republic, Republic of Moldova, Russian Federation, Tajikistan, Turkey, Turkmenistan, Ukraine and Uzbekistan. The data from UNCTAD for 1995-2011 period for these countries and Liesner Index (RCAL), Balassa Index (RCA), Relative Trade Advantage Index (RTA) and Relative Competitiveness Index (RC) are used and the rank correlation between the outcomes are checked via Spearman Rank Correlation coefficient. According to the outcomes, Belarus, Turkey and Uzbekistan have higher comparative advantage compared to the other countries. The cooperation of these countries with Russia and Ukraine on production and trade of automotive sector will enhance their comparative advantage against third countries.

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Butryn, Krzysztof, and Edward Preweda. "Analysis of the Impact of Quantitative and Qualitative Price-setting Attributes on a Market of Real Estate Intended for the Purpose of the Transformer Stations on the Example of Krakow." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.177.

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Based on appraisal reports, obtained from the City Office of Krakow, there were formulated base of real estate properties on which is situated the building of transformer station or which are intended for such purpose. The base consists of 90 properties located in the administrative boundaries of the city of Krakow. Most of these properties are the plots of very small areas, mainly in the range from 30 to 70 square meters. Based on the completed database, there were conducted a statistical analysis of the relevant market the property. In order to determine the relationship between the attributes and the price of real estate, there were calculated coefficients of the Pearson complete correlation and coefficients of the Spearman correlation. The analysis showed significant differences between quantitative and qualitative correlation coefficients for some variables. In order to improve the consistency of the database, using statistical methods eliminated property turned out. Finally, the analysis considered two bases, numbering respectively 90 and 77 real estates. In the following values, there were defined standardized regression coefficients (scale 9), the partial correlation coefficients for the dependent variable (price) relative to the rest of variables and coefficients of determination. On the basis of calculations and analysis, there have been drawn conclusions on the impact of each attribute on the market prices of these unusual properties.

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Kumar, Rahul, Sayan Gupta, and Shaikh Faruque Ali. "Random Field Modeling and Analysis of Rotor Bladed Disc Sector Using a Data Driven PCE Based Approach." In ASME 2019 Gas Turbine India Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gtindia2019-2497.

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Abstract Bladed disc systems, are designed to be rotationally periodic i.e. each sector repeats itself in an angular manner. This ensures that the response characteristics preserve this rotational periodicity and is defined as a tuned system. However, due to manufacturing limitations, there are invariably random spatial variations in the sectors which constitute the rotor. This in turn destroys the periodicity (angular symmetry) of the rotor. Such a system is defined as a mistuned system, leads to energy localization and makes the rotor susceptible to damage leading to a loss of its service life. This study focusses on developing a methodology for modeling the random spatial inhomogeneities and integrating with finite element analysis for estimating the behavior of a sector of a rotor blade assembly. Approximations for the non-Gaussian random fields for the spatial inhomogeneities are directly developed from the data set of measurements available from coordinate measuring machine (CMM). Subsequently, Rosenblatt’s transformations are applied to each component of the discrete measurement data set for polynomial chaos (PC) representation of the parameter to get the estimated probability density function (pdf). Spearman’s rank correlation coefficient (SRCC) is calculated to obtain the correlation parameter. Kullback–Liebler entropy (KLE) is used as a metric to compare the estimated pdf obtained through the PC representation of the measured data. The in-house PC based developed codes are subsequently integrated with commercially available finite element software which enable quantifying the propagation of the spatial random uncertainties into the response characteristics. Statistical processing of the response quantities is carried out to estimate probabilistic measures of the corresponding response quantities.

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Kumar, Rahul, Sayan Gupta, and Shaikh Faruque Ali. "Stochastic Modelling and Analysis of Rotating Bladed Discs." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-16212.

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Abstract This study focusses on probabilistic modelling of the bladed disc system and numerical estimation of the distributions of the response quantities of the system. Stochastic finite element model of the system consisting of all the assemblies and the hub is developed and reported. The spatial inhomogeneity of mistuned structures is modelled as non-Gaussian random field. Experimentally, the system parameters can be measured at the specified locations of the bladed disk structure. In this analysis, a synthetic data is generated which represent this measured data set. Further, Nataf transformation is implemented to each component of the data set to get the polynomial chaos expansion framework of the system parameters. Since, the random field of the system parameter is approximated as correlated random variables, Spearman’s rank correlation coefficient is used in this manuscript to obtain that correlation among the random parameters across the domain. The approximated probability density function obtained through the aforementioned methodology is compared with the target probability density function of the parameter using Kullback–Liebler (KL) entropy as a metric. Also, the same KL entropy is used as a metric to check the convergence of polynomial chaos terms in the expansion. Next, the proposed polynomial chaos method is integrated with commercial finite element software to quantify the propagation of randomness associated with system parameters into the response quantities. Subsequently, the statistical processing helps in estimating the probabilistic measure of the required response quantities. The results obtained through the conventional Monte Carlo (MC) simulations have been used as the benchmark to compare the response characteristics obtained through the proposed algorithm.

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Wang, Jui-lin, and Feng-Hsiung Hou. "Research on the Relationship between the Internet Usages and the Organizational Performance in the Taiwanese E-commerce Business Organization." In 2003 Informing Science + IT Education Conference. Informing Science Institute, 2003. http://dx.doi.org/10.28945/2593.

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The purpose of this research was to explore the possible relationship between the Internet usage and the organizational performance in the Taiwanese e-commerce business organizations. The hypothesis for this research was: There was a significant relationship between the Internet usage and the organizational performance in the Taiwanese e-commerce business organizations. The method employed quantitative research method in conducting this study was measure the use of Internet in various Taiwanese e-commerce business organizations and provided an overview of the method of Internet use in e-commerce business organizations’ organizational performances. The research participants were 50 own-ers/managers in Taiwanese e-commerce business organizations. The Spearman Rank Correlation Coefficient and descriptive statistics were used to test the research hypothesis. Research result supported the research hypothesis that there was a significant relationship between the Internet usage and the organizational performance in the Taiwanese e-commerce business organizations. Research result also indicated that this relationship between the Internet usage and the organizational performance was positive. Results showed that Taiwanese e-commerce business organizations’ owners/managers were agreed and strongly agree for there was significant impact of Internet usage and organizational performance in their e-commerce business organizations in following:

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