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Journal articles on the topic 'Measuring applications'

Author: Grafiati
Published: 28 June 2021
Last updated: 14 February 2022

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1

Batchelor, Marjorie. "Measuring comodules — their applications." Journal of Geometry and Physics 36, no. 3-4 (December 2000): 251–69. http://dx.doi.org/10.1016/s0393-0440(00)00024-3.

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2

Hernández, David Asael Gutiérrez, and Juan Arturo Aranda Ruiz. "Novel Optoelectronics Device for Measuring Pupillary Dynamics for Medical Applications." International Journal of Scientific Research 2, no. 4 (June 1, 2012): 85–87. http://dx.doi.org/10.15373/22778179/apr2013/33.

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3

Lucca, D. A., K. Herrmann, and M. J. Klopfstein. "Nanoindentation: Measuring methods and applications." CIRP Annals 59, no. 2 (2010): 803–19. http://dx.doi.org/10.1016/j.cirp.2010.05.009.

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4

Silva, J., Y. Sharon, R. Santos, and S. Beer. "Measuring seagrass photosynthesis: methods and applications." Aquatic Biology 7 (October 22, 2009): 127–41. http://dx.doi.org/10.3354/ab00173.

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5

Jafari, Said, Fredrick Mtenzi, Ciaran O’Driscoll, Ronan Fitzpatrick, and Brendan O’Shea. "Measuring Privacy in Ubiquitous Computing Applications." International Journal for Digital Society 2, no. 3 (September 1, 2011): 552–55. http://dx.doi.org/10.20533/ijds.2040.2570.2011.0066.

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6

Oh, Haemoon, Ann Marie Fiore, and Miyoung Jeoung. "Measuring Experience Economy Concepts: Tourism Applications." Journal of Travel Research 46, no. 2 (November 2007): 119–32. http://dx.doi.org/10.1177/0047287507304039.

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7

Ismail, Noor Azina. "Measuring Agreement: Models, Methods, and Applications." Journal of the American Statistical Association 115, no. 529 (January 2, 2020): 485–86. http://dx.doi.org/10.1080/01621459.2020.1721246.

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8

NAKAGAWA, SHINICHI, NEIL J. GEMMELL, and TERRY BURKE. "Measuring vertebrate telomeres: applications and limitations." Molecular Ecology 13, no. 9 (September 2004): 2523–33. http://dx.doi.org/10.1111/j.1365-294x.2004.02291.x.

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9

Diebold, Francis X., and Lutz Kilian. "Measuring predictability: theory and macroeconomic applications." Journal of Applied Econometrics 16, no. 6 (2001): 657–69. http://dx.doi.org/10.1002/jae.619.

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10

Annetta, Leonard A., Shawn Holmes, Meng-Tzu Cheng, and Elizabeth Folta. "Measuring Student Perceptions." International Journal of Gaming and Computer-Mediated Simulations 2, no. 3 (July 2010): 24–42. http://dx.doi.org/10.4018/jgcms.2010070102.

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As educational games become more pervasive, the evolution of game design software is inevitable. This study looked at student perceptions of teacher created Serious Educational Games as part of a project striving to create a game development software where teachers and students create games as part of educational activities. The objective was to use evidence from student perceptions to inform further development of the software. A mixed method design ascertained data from 181 male and 178 females from 33 teacher created games. Results indicate that the software is relatively effective by the supporting documentation and training lacked in several areas. This information led to the creation of a commercial game development software set for release in 2010.
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11

Morimoto, Shoji. "Ambulatory gait measuring system for clinical applications." Journal of the Society of Biomechanisms 14, Special (1990): 81–99. http://dx.doi.org/10.3951/sobim.14.81.

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12

Mack, Barbara J. "Practical Applications of Measuring Bond-Level Liquidity." Practical Applications 4, no. 4 (April 30, 2017): 1.10–4. http://dx.doi.org/10.3905/pa.2017.4.4.219.

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13

Sayeed, Mohamed, Hansang Bae, Yili Zheng, Brian Armstrong, Rudolf Eigenmann, and Faisal Saied. "Measuring High-Performance Computing with Real Applications." Computing in Science & Engineering 10, no. 4 (July 2008): 60–70. http://dx.doi.org/10.1109/mcse.2008.98.

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14

Saleh, Ashraf Mousa, Roesnita Ismail, Norasikin Fabil, Norita Md Norwawi, and Fauziah Abdul Wahid. "Measuring Usability: Importance Attributes for Mobile Applications." Advanced Science Letters 23, no. 5 (May 1, 2017): 4738–41. http://dx.doi.org/10.1166/asl.2017.8879.

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15

Abrahao, Silvia, and Oscar Pastor. "Measuring the functional size of web applications." International Journal of Web Engineering and Technology 1, no. 1 (2003): 5. http://dx.doi.org/10.1504/ijwet.2003.003265.

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16

Weissmark, Mona S., and Daniel A. Giacomo. "Measuring Therapeutic Interactions: Research and Clinical Applications." Psychiatry 58, no. 2 (May 1995): 173–88. http://dx.doi.org/10.1080/00332747.1995.11024724.

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17

Miljkovic, Dragan, and Alex Winter-Nelson. "Measuring postharvest loss inequality: Method and applications." Agricultural Systems 186 (January 2021): 102984. http://dx.doi.org/10.1016/j.agsy.2020.102984.

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18

Skabardonis, Alexander, Pravin Varaiya, and Karl F. Petty. "Measuring Recurrent and Nonrecurrent Traffic Congestion." Transportation Research Record: Journal of the Transportation Research Board 1856, no. 1 (January 2003): 118–24. http://dx.doi.org/10.3141/1856-12.

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A methodology and its application to measure total, recurrent, and nonrecurrent (incident related) delay on urban freeways are described. The methodology used data from loop detectors and calculated the average and the probability distribution of delays. Application of the methodology to two real-life freeway corridors in Los Angeles, California, and one in the San Francisco, California, Bay Area, indicated that reliable measurement of congestion also should provide measures of uncertainty in congestion. In the three applications, incident-related delay was found to be 13% to 30% of the total congestion delay during peak periods. The methodology also quantified the congestion impacts on travel time and travel time variability.
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19

Jackson, Jadin C., and A. David Redish. "Measuring ensemble consistency without measuring tuning curves." Neurocomputing 58-60 (June 2004): 91–99. http://dx.doi.org/10.1016/j.neucom.2004.01.028.

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20

Kruisselbrink, Thijs, Myriam Aries, and Alexander Rosemann. "A Practical Device for Measuring the Luminance Distribution." International Journal of Sustainable Lighting 19, no. 1 (June 29, 2017): 75–90. http://dx.doi.org/10.26607/ijsl.v19i1.76.

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Various applications in building lighting such as automated daylight systems, dynamic lighting control systems, lighting simulations, and glare analyzes can be optimized using information on the actual luminance distributions of the surroundings. Currently, commercially available luminance distribution measurement devices are often not suitable for these kind of applications or simply too expensive for broad application. This paper describes the development of a practical and autonomous luminance distribution measurement device based on a credit card-sized single-board computer and a camera system. The luminance distribution was determined by capturing High Dynamic Range images and translating the RGB information to the CIE XYZ color space. The High Dynamic Range technology was essential to accurately capture the data needed to calculate the luminance distribution because it allows to capture luminance ranges occurring in real scenarios. The measurement results were represented in accordance with established methods in the field of daylighting. Measurements showed that the accuracy of the luminance distribution measurement device ranged from 5% to 20% (worst case) which was deemed acceptable for practical measurements and broad applications in the building realm.
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21

Azar, José, Ioana Marinescu, and Marshall Steinbaum. "Measuring Labor Market Power Two Ways." AEA Papers and Proceedings 109 (May 1, 2019): 317–21. http://dx.doi.org/10.1257/pandp.20191068.

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We compute the “applications elasticity” as a proxy for firm-level labor supply elasticity by regressing the applications to a given job on the posted wage. The average applications elasticity in our data is 0.42. We then relate our elasticity estimates to concentration in labor markets defined by six-digit SOC occupations and commuting zone. We show a robust negative relationship between the two. Applications elasticity is near zero for all but the most densely populated labor markets, suggesting that 80 percent of the workforce works in labor markets where employers exercise significant monopsony power.
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22

Beck, Ashley, Kristopher Hunt, and Ross Carlson. "Measuring Cellular Biomass Composition for Computational Biology Applications." Processes 6, no. 5 (April 24, 2018): 38. http://dx.doi.org/10.3390/pr6050038.

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23

Hristoforou, E., and H. Chiriac. "Position measuring system for applications in field sports." Journal of Magnetism and Magnetic Materials 249, no. 1-2 (August 2002): 407–10. http://dx.doi.org/10.1016/s0304-8853(02)00567-x.

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24

Zhou, Hui. "Measuring available bandwidth for smart cyber-physical applications." Tsinghua Science and Technology 16, no. 6 (December 2011): 601–10. http://dx.doi.org/10.1016/s1007-0214(11)70080-3.

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25

OHASHI, Kazuhito. "Measuring Techniques and Their Applications in Grinding Process." Journal of the Japan Society for Precision Engineering 84, no. 2 (2018): 138–41. http://dx.doi.org/10.2493/jjspe.84.138.

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26

Tan, H. B. K., and N. L. Thein. "Measuring post-transaction error handling in database applications." Information and Software Technology 43, no. 4 (March 2001): 241–46. http://dx.doi.org/10.1016/s0950-5849(00)00171-3.

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27

Zielczynski, M., and N. Golnik. "Recombination Index of Radiation Quality - Measuring and Applications." Radiation Protection Dosimetry 52, no. 1-4 (April 1, 1994): 419–22. http://dx.doi.org/10.1093/rpd/52.1-4.419.

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28

Selinger, Jonathan V., Joseph J. Pancrazio, and Guenter W. Gross. "Measuring synchronization in neuronal networks for biosensor applications." Biosensors and Bioelectronics 19, no. 7 (February 2004): 675–83. http://dx.doi.org/10.1016/s0956-5663(03)00267-7.

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29

Chugui, Yu V., S. V. Plotnikov, A. K. Potashnikov, and A. G. Verkhogliad. "Optical Measuring Technologies for Industrial and Scientific Applications." Journal of Physics: Conference Series 48 (October 1, 2006): 495–505. http://dx.doi.org/10.1088/1742-6596/48/1/094.

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30

Whitworth, James E., Susan Rebstock Williams, Prashant C. Palvia, and Cheryl Aasheim. "Measuring the impact of global information technology applications." International Journal of Technology Management 29, no. 3/4 (2005): 280. http://dx.doi.org/10.1504/ijtm.2005.006000.

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31

Zielczynski, M., and N. Golnik. "Recombination Index of Radiation Quality - Measuring and Applications." Radiation Protection Dosimetry 52, no. 1-4 (April 1, 1994): 419–22. http://dx.doi.org/10.1093/oxfordjournals.rpd.a082226.

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32

Gupta, Viral, Parmod Kumar Kapur, and Deepak Kumar. "Measuring architecture and design efficiency for enterprise applications." International Journal of Industrial and Systems Engineering 28, no. 4 (2018): 494. http://dx.doi.org/10.1504/ijise.2018.090448.

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33

Gupta, Viral, Parmod Kumar Kapur, and Deepak Kumar. "Measuring architecture and design efficiency for enterprise applications." International Journal of Industrial and Systems Engineering 28, no. 1 (2018): 1. http://dx.doi.org/10.1504/ijise.2018.10005321.

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34

Kumar, M. "Measuring parallelism in computation-intensive scientific/engineering applications." IEEE Transactions on Computers 37, no. 9 (September 1988): 1088–98. http://dx.doi.org/10.1109/12.2259.

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35

Sepúlveda, Juan, Adriana Paternina, and Andrés Suarez. "Patent applications as source for measuring technological performance." Scientometrics 98, no. 2 (May 21, 2013): 1385–95. http://dx.doi.org/10.1007/s11192-013-1050-4.

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36

Rabin, Jeff C. "Limitations of Measuring Visual Acuity With Remote Applications." JAMA Ophthalmology 139, no. 3 (March 1, 2021): 347. http://dx.doi.org/10.1001/jamaophthalmol.2020.6155.

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37

Clare, Andrew, Simon Glover, James Seaton, Peter N. Smith, and Stephen Thomas. "Practical Applications of Measuring Sequence of Returns Risk." Practical Applications 8, no. 2 (January 17, 2021): 1.32–7. http://dx.doi.org/10.3905/pa.8.2.417.

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38

Clare, Andrew, Simon Glover, James Seaton, Peter N. Smith, and Stephen Thomas. "Practical Applications of Measuring Sequence of Returns Risk." Practical Applications 8, no. 4 (April 30, 2021): 1.4–7. http://dx.doi.org/10.3905/pa.8.4.417.

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39

Bebell, Damian, Michael Russell, and Laura O’Dwyer. "Measuring Teachers’ Technology Uses." Journal of Research on Technology in Education 37, no. 1 (September 2004): 45–63. http://dx.doi.org/10.1080/15391523.2004.10782425.

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40

Indrawati, Murali Raman, Maya Ariyanti, and Kok Wai Chew. "Materials for Measuring Instant Messenger Application Adoption: Malaysians’ Perspectives." Applied Mechanics and Materials 865 (June 2017): 720–26. http://dx.doi.org/10.4028/www.scientific.net/amm.865.720.

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Recently the usage of telecommunication networks in term of duration and frequency is increasing due to the invention of instant messenger applications such as WhatsApp, Blackberry Messenger (BBM), LINE, KakaoTalk, WeChat, and Telegram. Especially in Malaysia, the usage duration is the highest among the six countries in South East Asia-- Indonesia, Philippines, Singapore, Thailand, and Vietnam. It is important to know the factors influence the behaviour Malaysian toward the adoption of Instant messenger application in order to increase the usage frequency and duration of application in other countries. A study of Indrawati, Raman, Ariyanti, and Chew in 2015 proposed a new modified model toward the instant messenger applications adoption which has not been tested yet. This study intents to propose a measurement material to test the model. The material of measurement was derived from previous published researches. The method to test the measurement material was a pilot study with 30 Malaysians’ respondents. The result of this study reveals that the measurement material is valid and reliable, therefore it can be used for further study.
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41

Davis, J. P. "Rethinking Scales for Measuring Peanut Quality." Peanut Science 46, no. 1A (July 1, 2019): 104–6. http://dx.doi.org/10.3146/0095-3679-46.1a.104.

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ABSTRACT Peanut quality is influenced by a complex web of factors with scales ranging from the molecular to global weather patterns impacting climate. In some cases these quality factors are well understood, measured and controlled. In others, due to time, technological or resource limitations, this is not the case. Success in current and future markets will depend on the capacity of a supply base to reliably deliver the most important quality factors, which must be well defined for a given application and cost balanced. New technologies and systems are needed to more efficiently provide data across the relevant quality scales, which will allow for better predictive tools, drive more differentiation/value in the supply base, and catalyze new market applications.
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42

Zhang, Yong Zhen, Yi Wang, Xue Zhi Zhang, and Fei Hou. "Microwave Measuring Instrument Application in the Radar Equipment Maintenance Support." Applied Mechanics and Materials 687-691 (November 2014): 910–14. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.910.

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With the development of science and technology ,microwave measuring instrument become more important in the radar equipment maintenance support task.This paper expounds the principles of microwave measuring instrument work and test, describes the application of microwave measuring instrument in the maintenance detection of radar antenna feed system、radar antenna pattern test、power amplifier parameters measurement、the local oscillator test and receiving systems component test. Scientific applications of microwave measuring instrument is the important guarantee to ensure the radar equipment operate effectively.
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43

Zhang, Yuan Liang, Zhi Min Zhou, Peng Sen Jiang, and Yan Gao. "Driving Techniques for Micro Gear Measuring Instrument." Advanced Materials Research 694-697 (May 2013): 1276–80. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.1276.

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Micro gears are applied in an increasing quantity in many applications. Therefore, precise measurements are of growing importance to ensure their quality. This paper studies the electronic generative and automatic indexing measurement system in a micro gear (with a module less than 0.2mm) measuring instrument, and develops a loop proportioned driving approach and a stage-error compensation technique. The approach and the technique have been successfully applied in the micro gear measuring instrument developed by the authors. The experiment shows that the application of the approach and the technique greatly reduces the cost of measuring instrument, with simple control and reliable operation.
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44

Schobel, Johannes, Thomas Probst, Manfred Reichert, Winfried Schlee, Marc Schickler, Hans Kestler, and Rüdiger Pryss. "Measuring Mental Effort for Creating Mobile Data Collection Applications." International Journal of Environmental Research and Public Health 17, no. 5 (March 3, 2020): 1649. http://dx.doi.org/10.3390/ijerph17051649.

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To deal with drawbacks of paper-based data collection procedures, the QuestionSys approach empowers researchers with none or little programming knowledge to flexibly configure mobile data collection applications on demand. The mobile application approach of QuestionSys mainly pursues the goal to mitigate existing drawbacks of paper-based collection procedures in mHealth scenarios. Importantly, researchers shall be enabled to gather data in an efficient way. To evaluate the applicability of QuestionSys, several studies have been carried out to measure the efforts when using the framework in practice. In this work, the results of a study that investigated psychological insights on the required mental effort to configure the mobile applications are presented. Specifically, the mental effort for creating data collection instruments is validated in a study with N = 80 participants across two sessions. Thereby, participants were categorized into novices and experts based on prior knowledge on process modeling, which is a fundamental pillar of the developed approach. Each participant modeled 10 instruments during the course of the study, while concurrently several performance measures are assessed (e.g., time needed or errors). The results of these measures are then compared to the self-reported mental effort with respect to the tasks that had to be modeled. On one hand, the obtained results reveal a strong correlation between mental effort and performance measures. On the other, the self-reported mental effort decreased significantly over the course of the study, and therefore had a positive impact on measured performance metrics. Altogether, this study indicates that novices with no prior knowledge gain enough experience over the short amount of time to successfully model data collection instruments on their own. Therefore, QuestionSys is a helpful instrument to properly deal with large-scale data collection scenarios like clinical trials.
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45

Dologite, D. G. "Measuring Microcomputer Literacy." Journal of Educational Technology Systems 16, no. 1 (September 1987): 29–43. http://dx.doi.org/10.2190/gwuu-h8d4-kpfg-l8xx.

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This article discusses the results of an on-going research study to measure microcomputer literacy. College students are surveyed about their previously acquired microcomputer literacy before taking a microcomputer course. The objective of the survey is to determine if students have enough preparation for an enriched course. The study, the methodology, and a detailed comparative analysis of results from fifty-four student cases divided between the 1985 and 1986 school years are discussed. A microcomputer literacy index is developed to measure average student literacy, to compare literacy from one class year to another, and to rank students in order of literacy. Implications for broader applications of the method used are discussed.
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46

van de Klundert, Joris, Pascal Gorissen, and Stef Zeemering. "Measuring clinical pathway adherence." Journal of Biomedical Informatics 43, no. 6 (December 2010): 861–72. http://dx.doi.org/10.1016/j.jbi.2010.08.002.

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47

Macini, Paolo, and Ezio Mesini. "Measuring Reservoir Compaction Through Radioactive Marker Technique." Journal of Energy Resources Technology 124, no. 4 (November 20, 2002): 269–75. http://dx.doi.org/10.1115/1.1506700.

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Radioactive Marker Technique (RMT), an in-situ method to measure reservoir rock compaction and to evaluate uniaxial compressibility coefficients Cm, is examined here. Recent field applications seems to confirm that RMT-derived Cm’s match with sufficient precision with those calculated from land subsidence observed over the field by means of geodetic surveys, but are not always in good agreement with those derived from lab measurements. In particular, here is reported an application of RMT in the Italian Adriatic offshore, which highlights the discrepancies of Cm’s measurements from lab and RMT. At present, these discrepancies aren’t thoroughly understood, so, from an applicative standpoint, it is still necessary to perform a critical comparison and integration between both set of data.
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48

Huynh, Linh Quang, Hieu Sy Dau, Tien Van Tran, and Long Ba Chu. "LASER DOPPLER VELOCITY MEASUREMENT SYSTEM." Science and Technology Development Journal 13, no. 4 (December 30, 2010): 84–90. http://dx.doi.org/10.32508/stdj.v13i4.2180.

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Laser Doppler Velocimetry technique (LDV) isa measuring technique which has been developed since early 1980s. LDV has many advantages such as non-invasive measurement of one or all three components of velocity vector, measured dimensional vector of velocity, high accuracy, high resolution, wide measurement range ... Commercial Equipment based on LDV principle was applied to measure flow in industrial applications, in biomedical applications, etc. ... However, most of them are the specialized equipment which have high cost. In terms of technical training and education, LDV experiment is one of the basic experiments of application in high-tech optical measuring techniques, showing the skills of application of the principle of optical measurement applications in practical conditions. A model LDV system was designed and complete development within the lab for training purposes.
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49

Stokes, M. J. "Acoustic Myography: Applications and Considerations in Measuring Muscle Performance." Isokinetics and Exercise Science 3, no. 1 (January 1, 1993): 4–15. http://dx.doi.org/10.3233/ies-1993-3101.

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50

K, Samson Paul, Ateeq Ahmed H, and Emmanuel Raju A. "MEASURING PERFORMANCE OF DATABASE SYSTEMS FOR APPLICATIONS OF IOT." International Journal of Engineering Technology and Management Sciences 4, no. 5 (September 28, 2020): 49–52. http://dx.doi.org/10.46647/ijetms.2020.v04i05.009.

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Choosing the right database platform(s) for IoT solutions is daunting. First, IoT solutions can be distributed across geographical regions. As opposed to a centralized cloud-based solution, more solutions are adopting a combination of fog computing at the edge and cloud computing. As such, your database platforms must offer you the flexibility to process the data at the edge and synchronize between the edge servers and the cloud. Second, depending on your IoT use cases, the capabilities you want in your database could range from real-time data streaming, data filtering and aggregation, near-zero latency read operations, instant analytics, high availability, geo distribution, schema flexibility and so on. This article walks you through the four steps in choosing the right database platforms for your IoT solutions. The amount of data stored in IoT databases increases as the IoT applications extend throughout smart city appliances, industry and agriculture. Contemporary database systems must process huge amounts of sensory and actuator data in real-time or interactively. Facing this first wave of IoT revolution, database vendors struggle day-by-day in order to gain more market share, develop new capabilities and attempt to overcome the disadvantages of previous releases, while providing features for the IoT.
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