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Journal articles on the topic 'Correlation properties'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Cope, Leslie, Daniel Q. Naiman, and Giovanni Parmigiani. "Integrative correlation: Properties and relation to canonical correlations." Journal of Multivariate Analysis 123 (January 2014): 270–80. http://dx.doi.org/10.1016/j.jmva.2013.09.011.

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2

Atrott, J., and T. Henle. "Methylglyoxal in Manuka Honey – Correlation with Antibacterial Properties." Czech Journal of Food Sciences 27, Special Issue 1 (2009): S163—S165. http://dx.doi.org/10.17221/911-cjfs.

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A perfect linear correlation was found for methylglyoxal levels in 61 samples of Manuka honey, ranging from 189 to 835 mg/kg, and the corresponding antibacterial activities of the samples, which were between 12.4% and 30.9% equivalent phenol concentration. This clearly underlines that methylglyoxal is the dominant bioactive compound in Manuka honey and above concentrations of around 150 mg/kg directly responsible for the characteristic antibacterial properties of Manuka honey. Methylglyoxal can be a suitable tool for labelling the unique bioactivity of Manuka honey.

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3

H. Kh. Al-Lamy, H. Kh Al-Lamy. "Morphology Characterization of InSb Films and Correlation with Optical Properties." Indian Journal of Applied Research 3, no. 5 (2011): 549–51. http://dx.doi.org/10.15373/2249555x/may2013/177.

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4

Lord, Nick. "Properties of the correlation coefficient." Teaching Statistics 13, no. 2 (1991): 42–43. http://dx.doi.org/10.1111/j.1467-9639.1991.tb00162.x.

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5

Busch, Paul, and Pekka J. Lahti. "Correlation properties of quantum measurements." Journal of Mathematical Physics 37, no. 6 (1996): 2585–601. http://dx.doi.org/10.1063/1.531530.

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6

Maia, M. A. G., and L. Nicolaci da Costa. "Correlation properties of loose groups." Astrophysical Journal 349 (February 1990): 477. http://dx.doi.org/10.1086/168332.

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7

Józef Myjak and Ryszard Rudnicki. "Typical Properties of Correlation Dimension." Real Analysis Exchange 28, no. 2 (2003): 269. http://dx.doi.org/10.14321/realanalexch.28.2.0269.

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8

Naundorf, V., and H. Wollenberger. "Damage correlation for cascade properties." Journal of Nuclear Materials 174, no. 2-3 (1990): 141–43. http://dx.doi.org/10.1016/0022-3115(90)90227-e.

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9

Platisa, Mirjana M., and Vera Gal. "Correlation properties of heartbeat dynamics." European Biophysics Journal 37, no. 7 (2008): 1247–52. http://dx.doi.org/10.1007/s00249-007-0254-z.

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10

COLANGELO, GERARDO, VINCENZO LAPENNA, and LUCIANO TELESCA. "ANALYSIS OF CORRELATION PROPERTIES IN GEOELECTRICAL DATA." Fractals 11, no. 01 (2003): 27–38. http://dx.doi.org/10.1142/s0218348x03001471.

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This paper considers four geoelectrical time series, measured in a seismic area of Southern Italy. Lomb Periodogram method, Higuchi analysis, Detrended Fluctuation Analysis (DFA) and the mean distance spanned within time L are used to discuss the correlation properties of these signals. The values of the scaling exponents from these methods of the geoelectrical data indicate that the long-range correlations are present. Furthermore, it is found that these correlations are all linear.

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11

Elamathi, V., and S. Jayalekshmi. "Quantification of Clay Minerals and Its Correlation with Chemical and Index Properties of Soil." Jordan Journal of Civil Engineering 17, no. 1 (2023): 163–75. http://dx.doi.org/10.14525/jjce.v17i1.14.

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Clay-mineral composition is one of the factors that determine the physical and engineering behaviours of finegrained soils; however, it is usually ignored in soil investigations, because the determination of clay-mineral composition necessitates using sophisticated instruments which are time-consuming and require skilled personnel. Many correlations exist for faster prediction of soil engineering properties from its index properties, but correlations for quicker determination of the amount of clay mineral in the soil are still unexplored. This study focuses on determining the amount of clay mi

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12

CHATTERJEE, SUSMITA, DAVID K. MERWINE, FRANKLIN R. AMTHOR, and NORBERTO M. GRZYWACZ. "Properties of stimulus-dependent synchrony in retinal ganglion cells." Visual Neuroscience 24, no. 6 (2007): 827–43. http://dx.doi.org/10.1017/s0952523807070757.

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Neighboring retinal ganglion cells often spike synchronously, but the possible function and mechanism of this synchrony is unclear. Recently, the strength of the fast correlation between ON-OFF directionally selective cells of the rabbit retina was shown to be stimulus dependent. Here, we extend that study, investigating stimulus-dependent correlation among multiple ganglion-cell classes, using multi-electrode recordings. Our results generalized those for directionally selective cells. All cell pairs exhibiting significant spike synchrony did it for an extended edge but rarely for full-field s

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13

Vavruch, Ivan. "Surface Properties and Mechanical Properties of Fluids: A Correlation." Journal of Colloid and Interface Science 156, no. 1 (1993): 258–60. http://dx.doi.org/10.1006/jcis.1993.1108.

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14

Pucci, M. S., and R. N. Shroff. "Correlation of blown film optical properties with resin properties." Polymer Engineering and Science 26, no. 8 (1986): 569–75. http://dx.doi.org/10.1002/pen.760260808.

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15

Hassan, Manar, Spiros Zinelis, Monika Hersberger-Zurfluh, and Theodore Eliades. "Creep, Hardness, and Elastic Modulus of Lingual Fixed Retainers Adhesives." Materials 12, no. 4 (2019): 646. http://dx.doi.org/10.3390/ma12040646.

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The aims of this study were twofold: a) to characterize a wide array of time-independent and -dependent properties and b) to find possible correlations among the properties tested. Seven commercially available orthodontic adhesives were included in this study and ten cylindrical specimens were prepared from each material. Five specimens from each material were used for the characterization of Martens Hardness (HM), indentation modulus (EIT), and elastic index (ηIT), and the remaining five for the determination of indentation creep (CIT). Al the aforementioned properties were identified by empl

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16

Martellosio, Federico. "THE CORRELATION STRUCTURE OF SPATIAL AUTOREGRESSIONS." Econometric Theory 28, no. 6 (2012): 1373–91. http://dx.doi.org/10.1017/s0266466612000175.

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This paper investigates how the correlations implied by a first-order simultaneous autoregressive (SAR(1)) process are affected by the weights matrix and the autocorrelation parameter. A graph theoretic representation of the covariances in terms of walks connecting the spatial units helps to clarify a number of correlation properties of the processes. In particular, we study some implications of row-standardizing the weights matrix, the dependence of the correlations on graph distance, and the behavior of the correlations at the extremes of the parameter space. Throughout the analysis differen

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17

Zubko, Pavol, and Ladislav Pešek. "Correlation between Hardness and Fatigue Properties." Key Engineering Materials 662 (September 2015): 197–200. http://dx.doi.org/10.4028/www.scientific.net/kem.662.197.

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The contribution deals with estimation of tensile properties and fatigue behavior based on hardness measurement. First of all the database of tensile and fatigue properties vs. hardness data was created for a group of steels, from literature survey and performed experiments. Tensile strength, yield strength, ductility and parameters of Ludwig-Hollomon equation in static and cyclic loading were extracted and fitted in relation to the hardness HB. The experimental materials were API 5 L grade steels – X60 and X70 after different deformation exposition. Measured tensile curve (SC) and cyclic defo

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18

Kontorovich, V., Z. Lovtchikova, and F. Ramos-Alarcon. "Correlation Properties of Chaos: Cumulant Approach." Mathematical and Computational Applications 15, no. 5 (2010): 946–52. http://dx.doi.org/10.3390/mca15050946.

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19

McIntosh, Gordon C. "Correlation of Mira’s SiO Maser Properties." Astrophysical Journal 649, no. 1 (2006): 406–9. http://dx.doi.org/10.1086/506318.

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20

GREEN, D. H. "Product sequences with good correlation properties." International Journal of Electronics 67, no. 5 (1989): 749–60. http://dx.doi.org/10.1080/00207218908921126.

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21

Karp, S. "Correlation Properties of Integrated Random Variables." IEEE Transactions on Communications 34, no. 8 (1986): 825–26. http://dx.doi.org/10.1109/tcom.1986.1096614.

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22

Briggs, Kevin B. "Correlation functions for sediment acoustic properties." Journal of the Acoustical Society of America 96, no. 5 (1994): 3245–46. http://dx.doi.org/10.1121/1.411105.

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23

Rukhin, AndrewL. "Pattern correlation matrices and their properties." Linear Algebra and its Applications 327, no. 1-3 (2001): 105–14. http://dx.doi.org/10.1016/s0024-3795(00)00316-5.

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24

Marron, Joseph, and G. Michael Morris. "Correlation properties of clipped laser speckle." Journal of the Optical Society of America A 2, no. 9 (1985): 1403. http://dx.doi.org/10.1364/josaa.2.001403.

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25

Blanter, Elena M., Mikhail G. Shnirman, and Jean-Louis Le Mouël. "Solar variability: Evolution of correlation properties." Journal of Atmospheric and Solar-Terrestrial Physics 67, no. 6 (2005): 521–34. http://dx.doi.org/10.1016/j.jastp.2004.12.002.

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26

Oberstedt, S., T. Belgya, R. Billnert, et al. "Correlation measurements of fission-fragment properties." EPJ Web of Conferences 8 (2010): 03005. http://dx.doi.org/10.1051/epjconf/20100803005.

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27

Fiebig, U. C. G., and M. Schnell. "Correlation properties of extended m-sequences." Electronics Letters 29, no. 20 (1993): 1753. http://dx.doi.org/10.1049/el:19931168.

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28

CAI, K., R. FENG, and Z. ZHENG. "Cross-Correlation Properties of Cyclotomic Sequences." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E90-A, no. 1 (2007): 281–86. http://dx.doi.org/10.1093/ietfec/e90-a.1.281.

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29

Rodriguez, E., and J. M. Martin. "Correlation properties of ocean altimeter returns." IEEE Transactions on Geoscience and Remote Sensing 32, no. 3 (1994): 553–61. http://dx.doi.org/10.1109/36.297974.

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30

ZHAO, XIAOJUN, PENGJIAN SHANG, and JINGJING HUANG. "SEVERAL FUNDAMENTAL PROPERTIES OF DCCA CROSS-CORRELATION COEFFICIENT." Fractals 25, no. 02 (2017): 1750017. http://dx.doi.org/10.1142/s0218348x17500177.

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The (detrended cross-correlation analysis) DCCA cross-correlation coefficient was proposed to measure the level of long-range cross-correlations between two non-stationary time series on multiple time scales. It has been applied to diverse areas of interest, although many properties of this method are not clear. In this paper, we theoretically study several fundamental properties of the DCCA cross-correlation coefficient, which contributes to acquiring more statistical characteristics of this measure. We resort to a synthetic time series that is followed by the integration and the detrending p

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31

Zainuddin, M. Imran, S. Tanaka, R. Furushima, and K. Uematsu. "Correlation between slurry properties and structures and properties of granules." Journal of the European Ceramic Society 30, no. 16 (2010): 3291–96. http://dx.doi.org/10.1016/j.jeurceramsoc.2010.07.004.

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32

Borůvka, L., H. Donátová, and K. Němeček. "Spatial distribution and correlation of soil properties in a field: a case study." Plant, Soil and Environment 48, No. 10 (2011): 425–32. http://dx.doi.org/10.17221/4391-pse.

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Analysis of spatial distribution and correlation of soil properties represents an important outset for precision agriculture. This paper presents an analysis of spatial distribution and mutual correlations, both classical and spatial, of soil properties in an agricultural field in Klučov. Clay and fine silt content, pH, organic carbon content (C<sub>org</sub>), moisture (Q), total porosity (Pt), capillary porosity (P<sub>c</sub>), and coefficients of aggregate vulnerability to fast wetting (K<sub>v1</sub>), to slow wetting and drying (K<sub>v2</sub&

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33

Dai, Ben-Zhong. "The X-ray Spectral Properties for Gamma-ray Loud Blazars." Symposium - International Astronomical Union 214 (2003): 299–302. http://dx.doi.org/10.1017/s0074180900194628.

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We selected a sample of bright γ-ray (E>100 MeV) blazars whose X-rays in 0.1–10.0 keV band are observed by ROSAT and other X-ray satellites, and make a detailed spectral analysis between the soft (0.1–2.0 keV) and hard band (2.0–10.0keV) as well as between X-ray and γ-ray properties using both un-weighted and weighted analysis methods. Our results indicate: (i) there are significant anti-correlations of the spectral indices between soft X-rays and γ-rays, and between hard X-ray and γ-ray of flat-spectrum radio quasars (FSRQs) and BL Lac objects; (ii) in the X-ray band, the correlation is co

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34

Okotie, S., and A. E. Fasanya. "PARTICLE SWARM OPTIMIZATION OF SOLUTION GAS OIL RATIO." Open Journal of Engineering Science (ISSN: 2734-2115) 1, no. 1 (2020): 14–25. http://dx.doi.org/10.52417/ojes.v1i1.81.

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Reservoir fluid properties are very important in reservoir engineering computations such as material balance calculation, well test analysis, reserves estimate and numerical reservoir simulations. Ideally, these properties should be obtained from laboratory pressure-volume-temperature (PVT) analysis. Quite often, however, these measurements are either not available, or very costly to obtain. In such cases, empirically derived correlations are used to estimate the needed properties, all computation therefore, will depend on the accuracy of the correlations used for estimating the fluid properti

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35

Hassn, Omar F., and Dhefaf J. Sadiq. "NEW CORRELATION FOR OIL FORMATION VOLUME FACTOR AT AND BELOW BUBBLE POINT PRESSURE." Journal of Engineering 15, no. 04 (2009): 4347–55. http://dx.doi.org/10.31026/j.eng.2009.04.16.

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The best source of oil properties data is the laboratory PVT analysis of a reservoir fluid sample. However, in the absence of experimentally measured properties of reservoir fluids, these physical properties must be estimated from correlations. This paper employs more than thirty PVT reports that have been taken from different Iraqi fields. These reports contain about four hundred experimental points.The paper suggests new correlation to calculate oil formation volume factor at and below bubble point pressure. All of the previous correlations did not take the pressure as a factor or independen

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36

Eom, Cheoljun, Taisei Kaizoj, Jong Won Park, and Enrico Scalas. "Realized FX Volatility : Statistical Properties and Applications." Journal of Derivatives and Quantitative Studies 26, no. 1 (2018): 1–25. http://dx.doi.org/10.1108/jdqs-01-2018-b0001.

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This paper empirically examines the statistical properties of realized volatility and the relationships between volatility and correlation measurements of realized volatility by using intraday high-frequency foreign exchange (FX) rates. Results regarding the distributional and dynamic properties of realized volatility are in agreement with the findings of previous studies. However, the positive correlation present in previous studies is not found in the case of JPY. On trading days with low volatility in the FX market, realized correlation coefficients between JPY and other currencies have pos

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37

Belamri, Zehira. "Correlation between Structural, Morphological and Hydrophobic Properties of MgO Coating of Aluminium Substrate." METALLOFIZIKA I NOVEISHIE TEKHNOLOGII 46, no. 6 (2024): 549–57. https://doi.org/10.15407/mfint.46.06.0549.

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38

Robinson, Peter M., and Francesca Rossi. "REFINED TESTS FOR SPATIAL CORRELATION." Econometric Theory 31, no. 6 (2014): 1249–80. http://dx.doi.org/10.1017/s0266466614000498.

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We consider testing the null hypothesis of no spatial correlation against the alternative of pure first order spatial autoregression. A test statistic based on the least squares estimate has good first-order asymptotic properties, but these may not be relevant in small- or moderate-sized samples, especially as (depending on properties of the spatial weight matrix) the usual parametric rate of convergence may not be attained. We thus develop tests with more accurate size properties, by means of Edgeworth expansions and the bootstrap. Although the least squares estimate is inconsistent for the c

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39

Lisin, A. N., and I. I. Nabokov. "Correlation characteristics of the mechanical metal properties." Izvestiya MGTU MAMI 7, no. 2-2 (2013): 343–48. http://dx.doi.org/10.17816/2074-0530-68389.

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This paper is one of the attempts to approach the problem of fatigue failure, based on a systematic approach, which lies at the intersection of solid mechanics and physics of strength and plasticity. The paper describes methods for determining the fatigue life of the product, focused on the practical use during the design calculations and debugging studies based on existing theories of strength.

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40

Goncharov, O. Yu. "Correlation model to estimate the thermodynamic properties." Journal of Theoretical and Computational Chemistry 16, no. 06 (2017): 1750050. http://dx.doi.org/10.1142/s021963361750050x.

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A technique for constructing the correlation dependencies of the thermodynamic properties of similar compounds was proposed. This technique is based on the Taylor expansion in the supposed analytic relationship between properties. The constructed correlation dependencies were used to estimate the thermodynamic properties of the condensed bromides and iodides of hafnium HfGn (G [Formula: see text] Br, I and [Formula: see text], 2, 3, 4) and the compounds formed in the PbO–SiO2 system. Standard formation enthalpy [Formula: see text], entropy [Formula: see text], heat capacity [Formula: see text]

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41

Gutynska, O., J. Šafránková, and Z. Němeček. "Correlation properties of magnetosheath magnetic field fluctuations." Journal of Geophysical Research: Space Physics 114, A8 (2009): n/a. http://dx.doi.org/10.1029/2009ja014173.

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42

Aielli, Gian Piero. "Dynamic Conditional Correlation: On Properties and Estimation." Journal of Business & Economic Statistics 31, no. 3 (2013): 282–99. http://dx.doi.org/10.1080/07350015.2013.771027.

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43

Zhuo, Ze-peng. "On cross-correlation properties of Boolean functions." International Journal of Computer Mathematics 88, no. 10 (2011): 2035–41. http://dx.doi.org/10.1080/00207160.2010.539367.

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44

Bakunin, Oleg G. "Correlation and percolation properties of turbulent diffusion." Physics-Uspekhi 46, no. 7 (2003): 733–44. http://dx.doi.org/10.1070/pu2003v046n07abeh001348.

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45

Bakunin, Oleg G. "Correlation and percolation properties of turbulent diffusion." Uspekhi Fizicheskih Nauk 173, no. 7 (2003): 757. http://dx.doi.org/10.3367/ufnr.0173.200307f.0757.

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46

Musto, Pellegrino, Giuseppe Ragosta, Gennaro Scarinzi, and Leno Mascia. "Structure-Properties Correlation in Polyimide/Silica Hybrids." High Performance Polymers 18, no. 5 (2006): 799–816. http://dx.doi.org/10.1177/0954008306068257.

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47

Embrechts, P. "Linear Correlation and EVT: Properties and Caveats." Journal of Financial Econometrics 7, no. 1 (2008): 30–39. http://dx.doi.org/10.1093/jjfinec/nbn015.

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48

Tregubov, Dmytro, Larisa Trefilova, Evgen Slepuzhnikov, Dmytro Sokolov, and Flora Trehubova. "Correlation of properties in hydrocarbons homologous series." Problems of Emergency Situations, no. 38 (November 2023): 96–118. http://dx.doi.org/10.52363/2524-0226-2023-38-7.

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Correlations between combustible substances properties in the homologous series of n-alkanes and n-alcohols with a length of nС=1–20 were studied in order to determine ways to increase the methods convergence for assessing fire hazard parameters. The cluster length was added to the substance modulating parameters set. It should be noted that substances properties are often predicted using a molecule coarse-grained model, which has discreteness, does not describe short molecules, and requires an individual approach. It is shown that there are substance "arithmetic" parameters that directly depe

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49

Kang, Jae Won, Younghoon Whang, Byung Hoon Ko, and Kwang Soon Kim. "Generalized Cross-Correlation Properties of Chu Sequences." IEEE Transactions on Information Theory 58, no. 1 (2012): 438–44. http://dx.doi.org/10.1109/tit.2011.2166244.

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50

Hallin, P. F. "Genome Update: correlation of bacterial genomic properties." Microbiology 150, no. 12 (2004): 3899–903. http://dx.doi.org/10.1099/mic.0.27720-0.

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