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Journal articles on the topic 'Sampling effects'

Author: Grafiati

Published: 21 December 2024

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1

Johnson, Norman L., Samuel Kotz, and Robert N. Rodriguez. "Statistical Effects of Imperfect Inspection Sampling: II. Double Sampling and Link Sampling." Journal of Quality Technology 18, no. 2 (April 1986): 116–38. http://dx.doi.org/10.1080/00224065.1986.11978996.

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2

Wade, Angie. "Matched Sampling for Causal Effects." Journal of the Royal Statistical Society: Series A (Statistics in Society) 171, no. 3 (June 2008): 760–61. http://dx.doi.org/10.1111/j.1467-985x.2008.00538_9.x.

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3

Scheiner, Samuel M. "Affinity analysis: effects of sampling." Vegetatio 86, no. 2 (April 1990): 175–81. http://dx.doi.org/10.1007/bf00031733.

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4

Snoeijs, P. J. M. "Monitoring pollution effects by diatom community composition. A comparison of sampling methods." Archiv für Hydrobiologie 121, no. 4 (August 13, 1991): 497–510. http://dx.doi.org/10.1127/archiv-hydrobiol/121/1991/497.

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5

Royle, J. Andrew, Deanna K. Dawson, and Scott Bates. "MODELING ABUNDANCE EFFECTS IN DISTANCE SAMPLING." Ecology 85, no. 6 (June 2004): 1591–97. http://dx.doi.org/10.1890/03-3127.

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6

Barcelona, Michael J., John A. Helfrich, and Edward E. Garske. "Sampling Tubing Effects on Groundwater Samples." Analytical Chemistry 57, no. 2 (February 1985): 460–64. http://dx.doi.org/10.1021/ac50001a032.

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7

OKAMOTO, Yasuharu. "Effects of Biases in Snowball Sampling." Proceedings of the Annual Convention of the Japanese Psychological Association 76 (September 11, 2012): 1EVA20. http://dx.doi.org/10.4992/pacjpa.76.0_1eva20.

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8

Skinner, C. J. "Design Effects of Two-Stage Sampling." Journal of the Royal Statistical Society: Series B (Methodological) 48, no. 1 (September 1986): 89–99. http://dx.doi.org/10.1111/j.2517-6161.1986.tb01393.x.

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9

Lauzon, M. Louis, and Brian K. Rutt. "Effects of polar sampling ink-space." Magnetic Resonance in Medicine 36, no. 6 (December 1996): 940–49. http://dx.doi.org/10.1002/mrm.1910360617.

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10

Kim, Taehoon, KeeJae Lee, and Inho Park. "Measuring stratification effects for multistage sampling." Korean Journal of Applied Statistics 36, no. 4 (August 31, 2023): 337–47. http://dx.doi.org/10.5351/kjas.2023.36.4.337.

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11

Oppenheimer, Charles. "Sampling effects on background noise corrections." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 269, no. 2 (July 14, 2024): 181–92. http://dx.doi.org/10.3397/nc_2024_0022.

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Background noise corrections are used to estimate true source levels from measured source levels. Use of a background correction involves determining the background noise from measured samples. Previous work explored the effect of sampling on the statistical background noise correction through the steadiness parameter. In this paper the effect of sampling on the statistical and legacy background noise corrections through the steadiness and source-background level difference parameters is investigated. Samples of background noise are drawn from a chi-square distribution, which has been shown to describe background noise arising from multi-path or multi-mode processes. Background mean and variance are determined from a specified number of background noise samples, and statistical distributions and confidence bands are formed. The distributions and confidence bands of the statistical and legacy background noise corrections are compared and are used to identify parameter ranges that promote accuracy of source levels obtained with background noise corrections. Specific limits on these parameters are recommended for the statistical background noise correction. The benefits and advantages of the statistical background noise correction are identified, and a path towards standardizing the statistical background noise correction is proposed.

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12

Poesch, Mark S. "Developing Standardized Methods for Sampling Freshwater Fishes with Multiple Gears: Effects of Sampling Order versus Sampling Method." Transactions of the American Fisheries Society 143, no. 2 (February 20, 2014): 353–62. http://dx.doi.org/10.1080/00028487.2013.860047.

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13

Long, M. "Sampling disturbance effects in soft laminated clays." Proceedings of the Institution of Civil Engineers - Geotechnical Engineering 156, no. 4 (October 2003): 213–24. http://dx.doi.org/10.1680/geng.2003.156.4.213.

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14

SEKIMOTO, Masaya, Takehiko HORITA, and Sumitoshi OGATA. "Effects of Sampling Conditions on Chaos Analysis." Transactions of the Society of Instrument and Control Engineers 33, no. 1 (1997): 69–71. http://dx.doi.org/10.9746/sicetr1965.33.69.

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15

SAI, Shido. "EFFECTS OF MISTAKEN SAMPLING METHODS ON ESTIMATION." Kodo Keiryogaku (The Japanese Journal of Behaviormetrics) 20, no. 2 (1993): 24–34. http://dx.doi.org/10.2333/jbhmk.20.2_24.

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16

SAI, Shido. "EFFECTS OF MISTAKEN SAMPLING METHODS ON ESTIMATION." Kodo Keiryogaku (The Japanese Journal of Behaviormetrics) 20, no. 2 (1993): 35–47. http://dx.doi.org/10.2333/jbhmk.20.2_35.

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17

MURPHY, GREGORY B. "THE EFFECTS OF ORGANIZATIONAL SAMPLING FRAME SELECTION." Academy of Management Proceedings 1999, no. 1 (August 1999): F1—F6. http://dx.doi.org/10.5465/apbpp.1999.27600490.

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18

Bashar, M. A., Abu Siddique, and A. M. M. Safiullah. "Sampling Disturbance Effects in Reconstituted Coastal Soils." Soils and Foundations 40, no. 5 (October 2000): 49–63. http://dx.doi.org/10.3208/sandf.40.5_49.

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19

Spyreas, Greg. "Scale and Sampling Effects on Floristic Quality." PLOS ONE 11, no. 8 (August 4, 2016): e0160693. http://dx.doi.org/10.1371/journal.pone.0160693.

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20

Lim, Guan Tor, Jubert Pineda, Nathalie Boukpeti, J. Antonio H. Carraro, and Andy Fourie. "Effects of sampling disturbance in geotechnical design." Canadian Geotechnical Journal 56, no. 2 (February 2019): 275–89. http://dx.doi.org/10.1139/cgj-2018-0016.

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This paper describes an experimental study of the effects of sampling disturbance in an Australian natural soft clay and the consequences of different sample quality on the representativeness of soil parameters used in geotechnical designs. The paper is divided into three sections. Laboratory test results obtained from specimens retrieved using three different tube samplers as well as the Sherbrooke (block) sampler are first described. Then, the sample quality assessment, using available indices proposed for soft soils, is presented. It is shown that sample quality varies with the stress paths and boundary conditions applied in laboratory tests. Finally, mechanical soil properties derived from specimens retrieved using the different samplers are used in the prediction of two classical problems in soil mechanics: the settlement and excess pore pressure response underneath an embankment as well as the settlement and bearing capacity of a shallow footing. These two examples are used here to highlight the consequences of poor sampling in practice.

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21

Azeredo-Leme, Carlos. "Clock Jitter Effects on Sampling: A Tutorial." IEEE Circuits and Systems Magazine 11, no. 3 (2011): 26–37. http://dx.doi.org/10.1109/mcas.2011.942067.

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22

Murphy, Gregory B. "The effects of organizational sampling frame selection." Journal of Business Venturing 17, no. 3 (May 2002): 237–52. http://dx.doi.org/10.1016/s0883-9026(00)00061-6.

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23

Barcelona, Michael J., John A. Helfrich, and Edward E. Garsake. "Correction. Sampling Tubing Effects on Groundwater Samples." Analytical Chemistry 57, no. 13 (November 1985): 2752. http://dx.doi.org/10.1021/ac00290a601.

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24

Bogus, E. G., M. J. Hoskins, and B. J. Hunsinger. "Sampling time effects in the ACT device." IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 38, no. 4 (July 1991): 344–49. http://dx.doi.org/10.1109/58.84273.

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25

RILLING, GABRIEL, and PATRICK FLANDRIN. "SAMPLING EFFECTS ON THE EMPIRICAL MODE DECOMPOSITION." Advances in Adaptive Data Analysis 01, no. 01 (January 2009): 43–59. http://dx.doi.org/10.1142/s1793536909000023.

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Standard exposition of Empirical Mode Decomposition (EMD) is usually done within a continuous-time setting whereas, in practice, the effective implementation always operates in discrete-time. The purpose of this contribution is to summarize a number of results aimed at quantifying the influence of sampling on EMD. The idealized case of a sampled pure tone is first considered in detail and a theoretical model is proposed for upper bounding the approximation error due to finite sampling rates. A more general approach is then discussed, based on the analysis of the nonlinear operator that underlies the EMD (one step) sifting process. New explicit, yet looser, bounds are obtained this way, whose parameters can be estimated directly from the analyzed signal. Theoretical predictions are compared to simulation results in a number of well-controlled numerical experiments.

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26

Amidror, Isaac. "Sub-Nyquist artefacts and sampling moiré effects." Royal Society Open Science 2, no. 3 (March 2015): 140550. http://dx.doi.org/10.1098/rsos.140550.

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Sampling moiré effects are well known in signal processing. They occur when a continuous periodic signal g ( x ) is sampled using a sampling frequency f s that does not respect the Nyquist condition, and the signal-frequency f folds over and gives a new, false low frequency in the sampled signal. However, some visible beating artefacts may also occur in the sampled signal when g ( x ) is sampled using a sampling frequency f s which fully respects the Nyquist condition. We call these phenomena sub-Nyquist artefacts . Although these beating effects have already been reported in the literature, their detailed mathematical behaviour is not widely known. In this paper, we study the behaviour of these phenomena and compare it with analogous results from the moiré theory. We show that both sampling moirés and sub-Nyquist artefacts obey the same basic mathematical rules, in spite of the differences between them. This leads us to a unified approach that explains all of these phenomena and puts them under the same roof. In particular, it turns out that all of these phenomena occur when the signal-frequency f and the sampling frequency f s satisfy f ≈( m / n ) f s with integer m , n , where m / n is a reduced integer ratio; cases with n =1 correspond to true sampling moiré effects.

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27

Santagata, M. C., and J. T. Germaine. "Sampling Disturbance Effects in Normally Consolidated Clays." Journal of Geotechnical and Geoenvironmental Engineering 128, no. 12 (December 2002): 997–1006. http://dx.doi.org/10.1061/(asce)1090-0241(2002)128:12(997).

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28

Romay, Francisco J., David Y. H. Pui, Timothy J. Smith, Nam Duc Ngo, and James H. Vincent. "Corona discharge effects on aerosol sampling efficiency." Atmospheric Environment 30, no. 14 (July 1996): 2607–13. http://dx.doi.org/10.1016/1352-2310(95)00423-8.

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29

Lauzon, M. Louis, and Brian K. Rutt. "Polar sampling in k-space: Reconstruction effects." Magnetic Resonance in Medicine 40, no. 5 (November 1998): 769–82. http://dx.doi.org/10.1002/mrm.1910400519.

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30

Archambault, Aubin, Caroline Crauste-Thibierge, Sergio Ciliberto, and Ludovic Bellon. "Inertial effects in discrete sampling information engines." Europhysics Letters 148, no. 4 (November 1, 2024): 41002. http://dx.doi.org/10.1209/0295-5075/ad8bf0.

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Abstract We describe an experiment on an underdamped mechanical oscillator used as an information engine. The system is equivalent to an inertial Brownian particle confined in a harmonic potential whose center is controlled by a feedback protocol which measures the particle position at a specific sampling frequency . Several feedback protocols are applied and the power generated by the engine is measured as a function of the oscillator parameters and the sampling frequency. The optimal parameters are then determined. The results are compared to the theoretical predictions and numerical simulations on overdamped systems. We highlight the specific effects of inertia, which can be used to increase the amount of power extracted by the engine. In the regime of large τ, we show that the produced work has a tight bound determined by information theories.

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31

Sakin, Ahmet Egemen, Fatma Esen, and Yucel Tasdemir. "Effects of sampling interval on the passive air sampling of atmospheric PCBs levels." Journal of Environmental Science and Health, Part A 52, no. 7 (March 23, 2017): 673–79. http://dx.doi.org/10.1080/10934529.2017.1297148.

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32

Borges, Lisa, Alain F. Zuur, Emer Rogan, and Rick Officer. "Optimum sampling levels in discard sampling programs." Canadian Journal of Fisheries and Aquatic Sciences 61, no. 10 (October 1, 2004): 1918–28. http://dx.doi.org/10.1139/f04-138.

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This paper presents optimum sampling levels in discard sampling programs considering cost and precision objectives simultaneously and explores their dependence on both variables. The analysis is based on the Irish discard program: an onboard-observer voluntary sampling scheme aimed at estimating discard rates in trawl fisheries. Multistage analysis was performed to establish the precision levels achieved in the past, and a cost function was determined to estimate the financial cost of the program. Gear, fishing ground, targeted species, and International Council for the Exploration of the Sea (ICES) divisions were the main factors affecting discarding, together with random effects of the three nested groups considered: haul, trip, and vessel. Reductions in the present budget will imply only marginal decreases in precision, although changes in cost variables can have an impact on sampling levels. On the other hand, increasing the target precision by one-half will imply a considerable increase in sampling and associated cost, which will be difficult if not impossible to achieve. Finally, the analysis by fleet components suggests a marked increase in sampling levels, which emphasizes the importance of clearly stated discard sampling objectives.

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33

Clarke, Ralph T., Armin Lorenz, Leonard Sandin, Astrid Schmidt-Kloiber, Joerg Strackbein, Nick T. Kneebone, and Peter Haase. "Effects of sampling and sub-sampling variation using the STAR-AQEM sampling protocol on the precision of macroinvertebrate metrics." Hydrobiologia 566, no. 1 (August 2006): 441–59. http://dx.doi.org/10.1007/s10750-006-0078-3.

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34

Jacobsen, Robert Dahl, Jesper Møller, Morten Nielsen, and Morten Grud Rasmussen. "Investigations of the effects of random sampling schemes on the stability of generalized sampling." Applied and Computational Harmonic Analysis 45, no. 2 (September 2018): 453–61. http://dx.doi.org/10.1016/j.acha.2017.09.004.

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35

Beisel, Jean-Nicolas, Philippe Usseglio-Polatera, Sandra Thomas, and Jean-Claude Moreteau. "Effects of mesohabitat sampling strategy on the assessment of stream quality with benthic invertebrate assemblages." Fundamental and Applied Limnology 142, no. 4 (July 30, 1998): 493–510. http://dx.doi.org/10.1127/archiv-hydrobiol/142/1998/493.

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36

Loreau, Michel. "Separating Sampling and Other Effects in Biodiversity Experiments." Oikos 82, no. 3 (September 1998): 600. http://dx.doi.org/10.2307/3546381.

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37

Nielsen, Jennifer L. "Scientific Sampling Effects: Electrofishing California's Endangered Fish Populations." Fisheries 23, no. 12 (December 1998): 6–12. http://dx.doi.org/10.1577/1548-8446(1998)023<0006:sseece>2.0.co;2.

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38

Ding, Zhao Yong, Bao Min Sun, Yong Hong Guo, and Bing Hao Xu. "Effects of Sampling Substrate for Carbon Nanotubes Synthesis." Advanced Materials Research 129-131 (August 2010): 1341–45. http://dx.doi.org/10.4028/www.scientific.net/amr.129-131.1341.

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Pyramid shaped pyrolysis flame is a new method for carbon nanotubes synthesis. Oxy-acetylene flame outside the frustum of pyramid shaped reactor provides the necessary high temperature environment, while carbon monoxide is used as the source of carbon, iron pentacarbonyl (Fe(CO)5) as the source of catalyst precursor in reactor. In this experimental, substrate is the platform on which carbon nanotubes produced. The locations of 304 stainless steel and 201 stainless steel as substrates stayed in flame, 304 stainless steel pretreated or not, and different thickness of red copper and brass were studied. The results of 304 stainless steel substrate at the height of 10mm are the best, comparing with others at 7mm, 5mm, and 0mm heights. Although using 201 stainless steel as substrates has the same results, the results of it are not as good as 304 stainless steel. Pretreated 304 stainless steel as substrate can gain better properties of carbon nanotubes. Different thickness of brass and red copper can not get carbon nanotubes, only copper oxide on the surface of red copper while particles on brass.

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39

GÜVEN, M. Haluk, and Tayfun ARI. "Sampling Effects In Reconstruction for Digital Amplitude Holograms." Turkish Journal of Physics 20, no. 3 (January 1, 1996): 232–37. http://dx.doi.org/10.55730/1300-0101.2597.

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40

Palmer, Derecke, Bruce Goleby, and Barry Drummond. "The effects of spatial sampling on refraction statics." Exploration Geophysics 31, no. 1-2 (March 2000): 270–74. http://dx.doi.org/10.1071/eg00270.

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41

Borah, D. K., R. A. Kennedy, Zhi Ding, and I. Fijalkow. "Sampling and prefiltering effects on blind equalizer design." IEEE Transactions on Signal Processing 49, no. 1 (2001): 209–18. http://dx.doi.org/10.1109/78.890364.

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42

Souders, T. M., D. R. Flach, C. Hagwood, and G. L. Yang. "The effects of timing jitter in sampling systems." IEEE Transactions on Instrumentation and Measurement 39, no. 1 (1990): 80–85. http://dx.doi.org/10.1109/19.50421.

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43

Lynn, Peter. "Sampling Frame Effects on the British Crime Survey." Journal of the Royal Statistical Society: Series A (Statistics in Society) 160, no. 2 (January 1997): 253–69. http://dx.doi.org/10.1111/1467-985x.00060.

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44

Grenfell, Matt, and Kevin C. Burns. "Sampling Effects and Host Ranges in Australian Mistletoes." Biotropica 41, no. 6 (November 2009): 656–58. http://dx.doi.org/10.1111/j.1744-7429.2009.00586.x.

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45

BARON, PAUL A., and GREGORY J. DEYE. "Electrostatic Effects in Asbestos Sampling I: Experimental Measurements." American Industrial Hygiene Association Journal 51, no. 2 (February 1990): 51–62. http://dx.doi.org/10.1080/15298669091369330.

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46

Bowden, Roger J. "Repeated Sampling in the Presence of Publication Effects." Journal of the American Statistical Association 82, no. 398 (June 1987): 476–84. http://dx.doi.org/10.1080/01621459.1987.10478450.

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47

Lade, Steven J. "Finite sampling interval effects in Kramers–Moyal analysis." Physics Letters A 373, no. 41 (October 2009): 3705–9. http://dx.doi.org/10.1016/j.physleta.2009.08.029.

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48

Perez Ballesta, P., E. Gonzalez Ferradas, and A. Minana Aznar. "Effects of the diffusion membrane on passive sampling." Environmental Science & Technology 27, no. 10 (September 1993): 2031–34. http://dx.doi.org/10.1021/es00047a007.

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49

Wahlberg, Bo. "The effects of rapid sampling in system identification." Automatica 26, no. 1 (January 1990): 167–70. http://dx.doi.org/10.1016/0005-1098(90)90167-g.

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50

Gray, John S., Paul Dayton, Simon Thrush, and Michel J. Kaiser. "On effects of trawling, benthos and sampling design." Marine Pollution Bulletin 52, no. 8 (August 2006): 840–43. http://dx.doi.org/10.1016/j.marpolbul.2006.07.003.

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