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Journal articles on the topic 'Survey methods'

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Published: 4 June 2021
Last updated: 20 February 2023

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1

Mann, W. C. "Survey Methods." American Journal of Occupational Therapy 39, no. 10 (October 1, 1985): 640–48. http://dx.doi.org/10.5014/ajot.39.10.640.

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2

Anil, Swathi, and Prof Elizabeth Issac. "Survey on Various Methods of Detecting Glaucoma." International Journal of Trend in Scientific Research and Development Volume-2, Issue-2 (February 28, 2018): 1664–71. http://dx.doi.org/10.31142/ijtsrd10704.

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3

Mackelprang, A. J., Jack E. Edwards, Marie D. Thomas, Paul Rosenfeld, Stephanie Booth-Kewley, David H. Folz, Allen I. Kraut, Louis M. Rea, and Richard A. Parker. "Survey Research and Survey Research Methods." Public Productivity & Management Review 21, no. 2 (December 1997): 209. http://dx.doi.org/10.2307/3380886.

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4

Ziegel, Eric R., B. Cox, D. Binder, B. Chinnappa, A. Christianson, M. Colledge, and P. Kott. "Business Survey Methods." Technometrics 38, no. 1 (February 1996): 89. http://dx.doi.org/10.2307/1268928.

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5

RS, B. G. Cox, D. A. Binder, B. N. Chinnappa, A. Christianson, M. J. Colledge, and P. S. Knott. "Business Survey Methods." Journal of the American Statistical Association 90, no. 432 (December 1995): 1493. http://dx.doi.org/10.2307/2291557.

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6

Calder, Judith. "Survey research methods." Medical Education 32, no. 6 (November 1998): 636–52. http://dx.doi.org/10.1046/j.1365-2923.1998.00227.x.

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7

Reece, Gloria. "Agile methods survey." Communication Design Quarterly Review 9, no. 1 (March 2008): 8–11. http://dx.doi.org/10.1145/2180835.2180836.

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8

Reece, Gloria. "Agile methods survey." Communication Design Quarterly Review 9, no. 2 (June 2008): 16–20. http://dx.doi.org/10.1145/2180838.2180840.

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9

Losh-Hesselbart, Susan, and Floyd J. Fowler. "Survey Research Methods." Journal of the American Statistical Association 80, no. 392 (December 1985): 1077. http://dx.doi.org/10.2307/2288598.

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10

THOMAS, H. F. "Survey research methods,." Postgraduate Medical Journal 75, no. 887 (September 1, 1999): 575. http://dx.doi.org/10.1136/pgmj.75.887.575b.

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11

Korimilli, Madhuri S., Ram M. Pendyala, and Elaine Murakami. "Metaanalysis of Travel Survey Methods." Transportation Research Record: Journal of the Transportation Research Board 1625, no. 1 (January 1998): 72–78. http://dx.doi.org/10.3141/1625-09.

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Travel surveys often serve as the primary sources of information on travel demand characteristics. They provide critical data for transportation planning and decision making. In recent times, several factors motivate a comparative examination of travel survey methods. First, new travel demand modeling tools, such as those based on activity-based methods, are placing greater demands on travel behavior data gathered from household travel surveys. Second, response rates from household travel surveys have been showing a steady decline, possibly because of an increasingly survey-fatigued population. Third, declining resource availability at metropolitan planning agencies places emphasis on the need to maximize response rates to lower data collection costs per completed respondent. Ideally, a comparative examination of travel survey methods is best done through a carefully constructed experimental design that permits the isolation of the impact of various survey design parameters on response rates. However, the conduct of such a controlled experiment virtually is impractical. A metaanalysis of a sample of travel surveys conducted in the past 10 years is presented. A predictive model of response rates is developed by using linear regression techniques and the practical application of the model is demonstrated through several numerical examples.
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12

Sinha, Sankalp. "Order Picking: A Survey of Methods and Problems." International Journal of Psychosocial Rehabilitation 24, no. 1 (January 20, 2020): 1876–85. http://dx.doi.org/10.37200/ijpr/v24i1/pr200290.

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13

Lešo, Martin, Jaroslava Žilková, Milan Biroš, and Peter Talian. "SURVEY OF CONTROL METHODS FOR DC-DC CONVERTERS." Acta Electrotechnica et Informatica 18, no. 3 (September 27, 2018): 41–46. http://dx.doi.org/10.15546/aeei-2018-0024.

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14

Snelgar, R. J. "Salary survey methods: Comparability problems." South African Journal of Business Management 17, no. 3 (September 30, 1986): 169–73. http://dx.doi.org/10.4102/sajbm.v17i3.1052.

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Most organizations regard the accurate determination of prevailing labour market rates as being of primary importance to decisions regarding the setting of competitive wage and salary levels. The techniques involved in establishing these rates are fraught with problems, mainly revolving around efforts at obtaining comparability. Justification has been provided for organizations using tailor-made survey approaches in preference to professional or 'commercial' surveys, as this allows reduction to a minimum of such comparability problems as those associated with job description responsibilities, and compensation mix. This study reveals the extent to which a single pay structure received differing adjustments as a result of analysis of data obtained from a tailor-made survey approach as opposed to that obtained from a 'commercial' survey. Results indicate significant differences in adjustments over a three-year survey period, attributable essentially to the wide range of comparability difficulties associated with use of 'commercial' survey data.
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15

Lang, Iain. "The Survey Methods Workbook." Sociological Research Online 10, no. 1 (June 2005): 200–201. http://dx.doi.org/10.1177/136078040501000108.

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16

Brown, Catherine. "Spatial Survey Methods Workshops." Bulletin of the Ecological Society of America 84, no. 2 (April 2003): 53. http://dx.doi.org/10.1890/0012-9623(2003)84[53b:ssmw]2.0.co;2.

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17

Couper, M. P., and P. V. Miller. "Web Survey Methods: Introduction." Public Opinion Quarterly 72, no. 5 (December 1, 2008): 831–35. http://dx.doi.org/10.1093/poq/nfn066.

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18

Rokicki, Jarek. "SURVEY OF SKELETONIZATION METHODS." Mokslas - Lietuvos ateitis 2, no. 1 (February 28, 2010): 19–22. http://dx.doi.org/10.3846/mla.2010.004.

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In this article we present a brief survey on skeletons. The skeleton types are reviewed and definitions given for each of them. The desirable skeleton properties are named: centred, thin, robust, connected, indexed, smooth, reliable and reconstructable. Also different methods groups of skeleton extraction are discussed based on: topological thinning, distance transform, geometrical, path planning, general field and propagating waves. Advantages and disadvantages are discussed for each of them.
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19

Sheela, S. V., and P. A. Vijaya. "Iris Recognition Methods - Survey." International Journal of Computer Applications 3, no. 5 (June 10, 2010): 19–25. http://dx.doi.org/10.5120/729-1022.

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20

Rees, Colin. "Survey methods in midwifery." British Journal of Midwifery 3, no. 12 (December 2, 1995): 652–55. http://dx.doi.org/10.12968/bjom.1995.3.12.652.

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21

Penížek, V., and L. Borůvka. "Processing of conventional soil survey data using geostatistical methods." Plant, Soil and Environment 50, No. 8 (December 10, 2011): 352–57. http://dx.doi.org/10.17221/4043-pse.

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The aim of this study is to find a suitable treatment of conventional soil survey data for geostatistical exploitation. Different aims and methods of a conventional soil survey and the geostatistics can cause some problems. The spatial variability of clay content and pH for an area of 543 km<sup>2</sup> was described by variograms. First the original untreated data were used. Then the original data were treated to overcome the problems that arise from different aims of conventional soil survey and geostatistical approaches. Variograms calculated from the original data, both for clay content and pH, showed a big portion of nugget variability caused by a few extreme values. Simple exclusion of data representing some specific soil units (local extremes, non-zonal soils) did not bring almost any improvement. Exclusion of outlying values from the first three lag classes that were the most influenced due to a relatively big portion of these extreme values provided much better results. The nugget decreased from pure nugget to 50% of the sill variability for clay content and from 81 to 23% for pH.
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22

Tsantaki, M., E. Pancino, P. Marrese, S. Marinoni, M. Rainer, N. Sanna, A. Turchi, et al. "Survey of Surveys." Astronomy & Astrophysics 659 (March 2022): A95. http://dx.doi.org/10.1051/0004-6361/202141702.

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Context. In the present-day panorama of large spectroscopic surveys, the amount, diversity, and complexity of the available data continuously increase. The overarching goal of studying the formation and evolution of our Galaxy is hampered by the heterogeneity of instruments, selection functions, analysis methods, and measured quantities. Aims. We present a comprehensive catalogue, the Survey of Surveys (SoS), built by homogeneously merging the radial velocity (RV) determinations of the largest ground-based spectroscopic surveys to date, such as APOGEE, GALAH, Gaia-ESO, RAVE, and LAMOST, using Gaia as a reference. This pilot study serves to prove the concept and to test the methodology that we plan to apply in the future to the stellar parameters and abundance ratios as well. Methods. We have devised a multi-staged procedure that includes: (i) the cross match between Gaia and the spectroscopic surveys using the official Gaia cross-match algorithm, (ii) the normalisation of uncertainties using repeated measurements or the three-cornered hat method, (iii) the cross calibration of the RVs as a function of the main parameters on which depend (magnitude, effective temperature, surface gravity, metallicity, and signal-to-noise ratio) to remove trends and zero point offsets, and (iv) the comparison with external high-resolution samples, such as the Gaia RV standards and the Geneva-Copenhagen survey, to validate the homogenisation procedure and to calibrate the RV zero-point of the SoS catalogue. Results. We provide the largest homogenised RV catalogue to date, containing almost 11 million stars, of which about half come exclusively from Gaia and half in combination with the ground-based surveys. We estimate the accuracy of the RV zero-point to be about 0.16−0.31 km s−1 and the RV precision to be in the range 0.05−1.50 km s−1 depending on the type of star and on its survey provenance. We validate the SoS RVs with open clusters from a high resolution homogeneous samples and provide the systemic velocity of 55 individual open clusters. Additionally, we provide median RVs for 532 clusters recently discovered by Gaia data. Conclusions. The SoS is publicly available and ready to be applied to various research projects, such as the study of star clusters, Galactic archaeology, stellar streams, or the characterisation of planet-hosting stars, to name a few. We also plan to include survey updates and more data sources in future versions of the SoS.
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23

Masood, Saleha, Muhammad Sharif, Mussarat Yasmin, Muhammad Alyas Shahid, and Amjad Rehman. "Image Fusion Methods: A Survey." Journal of Engineering Science and Technology Review 10, no. 6 (2017): 186–95. http://dx.doi.org/10.25103/jestr.106.24.

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24

H T, Bhavana, and Srikanth H T. "Pattern Classification Methods: A Survey." International Journal of Scientific and Research Publications (IJSRP) 9, no. 8 (August 12, 2019): p9299. http://dx.doi.org/10.29322/ijsrp.9.08.2019.p9299.

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25

Deepikaa, S., and R. Saravanan. "VoIP Steganography Methods, a Survey." Cybernetics and Information Technologies 19, no. 1 (March 1, 2019): 73–87. http://dx.doi.org/10.2478/cait-2019-0004.

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Abstract Achieving secured data transmission is not always an easy job. Secret data sharing requires confidentiality and Undetectability. Steganography is preferred than cryptography to achieve undetectability. Steganography hides the secret data inside the other file such as text, audio, video, so that the existence of the secret data is completely hidden. Recent research focuses much on utilizing Voice over Internet Protocol (VoIP) calls as a carrier for data hiding. VoIP calls are much preferred among internet users for its wide availability, dynamic time limit and low cost. This paper focuses on data hiding methods that uses VoIP as a carrier. The paper also analyzes the performance of the algorithms using the three metrics undetectability, bandwidth and robustness.
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26

John, Rosebell. "A Survey on Denoising Methods." IOSR Journal of Engineering 02, no. 10 (October 2012): 85–89. http://dx.doi.org/10.9790/3021-021018589.

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27

Mohammed, Somia B., Ahmed Khalid, and SaifeEldin F. Osman. "A Survey of Classification Methods." International Journal of Advanced Engineering Research and Science 3, no. 10 (2016): 148–52. http://dx.doi.org/10.22161/ijaers/310.24.

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28

Taket, Ann, Eleanor Singer, and Stanley Presser. "Survey Research Methods: A Reader." Journal of the Operational Research Society 41, no. 9 (September 1990): 891. http://dx.doi.org/10.2307/2583515.

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29

C, Mariyammal, and Sasireka S. "Survey on Image Segmentation Methods." IARJSET 5, no. 11 (November 30, 2018): 23–26. http://dx.doi.org/10.17148/iarjset.2018.5115.

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30

Fuller, Todd K., Sean M. Matthews, Sadie S. Stevens, Nathaniel D. Rayl, Christopher J. Zieminski, Andrew R. Whiteley, Paul R. Sievert, John F. Organ, and Mourad W. Gabriel. "Noninvasive Survey Methods for Carnivores." Journal of Wildlife Diseases 46, no. 3 (July 2010): 1055–58. http://dx.doi.org/10.7589/0090-3558-46.3.1055.

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31

M. Khalaf, Bashir, Mohammed A. Al-Taee, and Abdulhabib Abdullah. "Survey of Parallel Block Methods." JOURNAL OF EDUCATION AND SCIENCE 23, no. 3 (September 1, 2010): 130–44. http://dx.doi.org/10.33899/edusj.2010.58397.

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32

Maylahn, Christopher. "Survey Methods in Community Medicine." Annals of Internal Medicine 132, no. 10 (May 16, 2000): 848. http://dx.doi.org/10.7326/0003-4819-132-10-200005160-00035.

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33

Gajendragadkar, Uma, and Sarang Joshi. "Survey on Relevance Calculation Methods." International Journal of Computer Applications 96, no. 3 (June 18, 2014): 37–42. http://dx.doi.org/10.5120/16777-6352.

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34

RS and Vic Barnett. "Sample Survey: Principles and Methods." Journal of the American Statistical Association 90, no. 430 (June 1995): 809. http://dx.doi.org/10.2307/2291109.

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35

HOSHINO, Takahiro, Wataru MATSUMOTO, and Kensuke OKADA. "Recent Development in Survey Methods." Kodo Keiryogaku (The Japanese Journal of Behaviormetrics) 44, no. 2 (2017): 115–16. http://dx.doi.org/10.2333/jbhmk.44.115.

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36

Finn, Adam, Eleanor Singer, and Stanley Presser. "Survey Research Methods: A Reader." Journal of Marketing Research 27, no. 2 (May 1990): 241. http://dx.doi.org/10.2307/3172854.

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37

Gabani, Krina B., Mayuri A. Mehta, and Stephanie Noronha. "Racial Categorization Methods: A Survey." Advances in Science, Technology and Engineering Systems Journal 5, no. 3 (2020): 388–401. http://dx.doi.org/10.25046/aj050350.

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38

Ghosh, Malay, and Tomasz Żądło. "Special Issue: Survey Sampling Methods." Mathematical Population Studies 21, no. 1 (January 2, 2014): 1. http://dx.doi.org/10.1080/08898480.2013.836334.

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39

Katifori, Akrivi, Constantin Halatsis, George Lepouras, Costas Vassilakis, and Eugenia Giannopoulou. "Ontology visualization methods—a survey." ACM Computing Surveys 39, no. 4 (November 2, 2007): 10. http://dx.doi.org/10.1145/1287620.1287621.

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40

Duque, Juan Carlos, Raúl Ramos, and Jordi Suriñach. "Supervised Regionalization Methods: A Survey." International Regional Science Review 30, no. 3 (July 2007): 195–220. http://dx.doi.org/10.1177/0160017607301605.

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41

Brouse, Suzanne H. "Survey Research Methods, 3rd edition." Journal of Advanced Nursing 40, no. 1 (October 2002): 123. http://dx.doi.org/10.1046/j.1365-2648.2002.23814.x.

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42

Taket, Ann. "Survey Research Methods: A Reader." Journal of the Operational Research Society 41, no. 9 (September 1990): 891–93. http://dx.doi.org/10.1057/jors.1990.137.

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43

Zitová, Barbara, and Jan Flusser. "Image registration methods: a survey." Image and Vision Computing 21, no. 11 (October 2003): 977–1000. http://dx.doi.org/10.1016/s0262-8856(03)00137-9.

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44

Kemp, Freda. "Sample Survey Principles and Methods." Journal of the Royal Statistical Society: Series D (The Statistician) 52, no. 3 (October 2003): 404. http://dx.doi.org/10.1111/1467-9884.00369_2.

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45

LEFF, A., and L. GOLDSTEIN. "Survey methods in stroke medicine." Seminars in Cerebrovascular Diseases and Stroke 3, no. 2 (June 2003): 77–84. http://dx.doi.org/10.1053/scds.2003.0018.

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46

Minton, Paul D. "Sample Survey Principles and Methods." Technometrics 35, no. 2 (May 1993): 235. http://dx.doi.org/10.1080/00401706.1993.10485065.

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47

Kossatchev, A. S., and M. A. Posypkin. "Survey of Compiler Testing Methods." Programming and Computer Software 31, no. 1 (January 2005): 10–19. http://dx.doi.org/10.1007/s11086-005-0002-z.

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48

Kossatchev, A. S., and M. A. Posypkin. "Survey of compiler testing methods." Programming and Computer Software 31, no. 1 (January 2005): 10–19. http://dx.doi.org/10.1007/s11086-005-0008-6.

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49

Karlsson, Andreas. "Survey sampling: theory and methods." Metrika 67, no. 2 (November 22, 2007): 241–42. http://dx.doi.org/10.1007/s00184-007-0161-4.

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50

Skinner, C. J., and V. Barnett. "Sample Survey Principles and Methods." Journal of the Royal Statistical Society. Series A (Statistics in Society) 155, no. 3 (1992): 472. http://dx.doi.org/10.2307/2982900.

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