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Artículos de revistas sobre el tema "Excel"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 25 de julio de 2025

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1

Ayer, Ganesh. "Excel in Excel®!*." Energy Engineering 112, no. 2 (2015): 14–25. http://dx.doi.org/10.1080/01998595.2015.11090950.

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Ayer, Ganesh. "Excel in Excel®!*." Energy Engineering 112, no. 3 (2015): 22–32. http://dx.doi.org/10.1080/01998595.2015.11414490.

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Ayer, Ganesh. "Excel in Excel®!*." Energy Engineering 112, no. 4 (2015): 50–61. http://dx.doi.org/10.1080/01998595.2015.11435394.

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Ayer, Ganesh. "Excel in Excel®!" Energy Engineering 113, no. 1 (2015): 53–65. http://dx.doi.org/10.1080/01998595.2016.11657082.

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Ayer, Ganesh. "Excel in Excel®!" Energy Engineering 113, no. 2 (2015): 63–74. http://dx.doi.org/10.1080/01998595.2016.11668653.

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Ayer, Ganesh. "Excel in Excel®!" Energy Engineering 113, no. 4 (2016): 26–40. http://dx.doi.org/10.1080/01998595.2016.11728655.

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Ayer, Ganesh. "Excel in Excel®!" Energy Engineering 113, no. 5 (2016): 18–28. http://dx.doi.org/10.1080/01998595.2016.11744689.

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Ayer, Ganesh. "Excel in Excel®!" Energy Engineering 114, no. 1 (2016): 19–38. http://dx.doi.org/10.1080/01998595.2017.11810159.

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9

Ayer, Ganesh. "Excel in Excel®!" Energy Engineering 114, no. 2 (2017): 56–65. http://dx.doi.org/10.1080/01998595.2017.11833485.

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Ayer, Ganesh. "Excel in Excel®!" Energy Engineering 114, no. 5 (2017): 8–17. http://dx.doi.org/10.1080/01998595.2017.11882306.

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Ayer, Ganesh. "Excel in Excel®!" Energy Engineering 114, no. 6 (2017): 7–12. http://dx.doi.org/10.1080/01998595.2017.11907869.

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12

Parramore, Keith. "Enlisting Excel." Teaching Mathematics and its Applications: An International Journal of the IMA 26, no. 2 (2007): 73–78. http://dx.doi.org/10.1093/teamat/hrl011.

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13

Barreto, Humberto. "Why Excel?" Journal of Economic Education 46, no. 3 (2015): 300–309. http://dx.doi.org/10.1080/00220485.2015.1029177.

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14

Sampson, Ben. "Escaping Excel." Aerospace Testing International 2024, no. 1 (2024): 40–44. http://dx.doi.org/10.12968/s1478-2774(24)50052-7.

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15

Oliphant, Alan S. "Excel 4.0." Computer Audit Update 1992, no. 6 (1992): 13–15. http://dx.doi.org/10.1016/0960-2593(92)90069-y.

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16

Facchetti, Antonio. "Gels excel." Nature Materials 7, no. 11 (2008): 839–40. http://dx.doi.org/10.1038/nmat2310.

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17

Riley, Barbara L., Steve Manske, and Roy Cameron. "Youth excel." Cancer 117, S10 (2011): 2281–88. http://dx.doi.org/10.1002/cncr.26046.

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18

Zsakó, László. "Combinatorics – competition – Excel." Teaching Mathematics and Computer Science 4, no. 2 (2006): 427–35. http://dx.doi.org/10.5485/tmcs.2006.0144.

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19

Myers, Joan. "Striving to excel." Nursing Children and Young People 25, no. 8 (2013): 38. http://dx.doi.org/10.7748/ncyp2013.10.25.8.38.s25.

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20

Jones, Alfred, Philip D. Dukes, James M. Schalk, and Max G. Hamilton. "‘Excel’ Sweet Potato." HortScience 24, no. 1 (1989): 171–72. http://dx.doi.org/10.21273/hortsci.24.1.171.

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Abstract ‘Excel’ sweet potato [Ipomoea batatas (L.) Lam.] was developed jointly by the USDA and the South Carolina Agricultural Experiment Station. This cultivar has high yield and excellent baking flavor, in combination with high levels of resistance to a wide array of disease and insect pests. Additionally, it has promise for use in snack foods.

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21

Tiwari, Rajesh Kumar, and G. Sahoo. "Microsoft Excel File." International Journal of Digital Crime and Forensics 3, no. 1 (2011): 37–52. http://dx.doi.org/10.4018/jdcf.2011010103.

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Data hiding is emerging as an important area of research with the advent of digital technologies. Watermarking, fingerprinting and steganography are important applications of data hiding techniques. Besides the classical use of data hiding in ownership protection, authentication and copy/access control, it serves as a general tool to convey side information. New files are a good choice for steganographic carriers. In this paper, the authors use Microsoft Excel as a cover file. A methodology has been developed that consists of three techniques for embedding the valuable data with three layers o

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22

Siegle, Joseph T., Michael M. Weinstein, and Morton H. Halperin. "Why Democracies Excel." Foreign Affairs 83, no. 5 (2004): 57. http://dx.doi.org/10.2307/20034067.

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23

Parramore, K. "Enlisting excel--again." Teaching Mathematics and its Applications 28, no. 1 (2008): 32–37. http://dx.doi.org/10.1093/teamat/hrp004.

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24

Christie, Derek. "Resampling with Excel." Teaching Statistics 26, no. 1 (2004): 9–14. http://dx.doi.org/10.1111/j.1467-9639.2004.00136.x.

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25

Gates, S. J., and C. Mirkin. "Engage to Excel." Science 335, no. 6076 (2012): 1545. http://dx.doi.org/10.1126/science.1222058.

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26

Berger, Nevin. "The Excel Story." Interactions 13, no. 1 (2006): 14–17. http://dx.doi.org/10.1145/1109069.1109084.

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27

Grove, Dana. "Project EXCEL-lence." Community College Journal of Research and Practice 29, no. 8 (2005): 637–38. http://dx.doi.org/10.1080/10668920591005549.

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28

Little, Bruce W. "Insurance trusts excel." Journal of the American Veterinary Medical Association 189, no. 3 (1986): 272–73. https://doi.org/10.2460/javma.1986.189.03.272.

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29

Baumann, Knut. "Accord for Excel." Journal of Chemical Information and Computer Sciences 37, no. 2 (1997): 413–14. http://dx.doi.org/10.1021/ci9501960.

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30

Hunt, Neville. "Pictograms in Excel." Teaching Statistics 22, no. 2 (2000): 56–58. http://dx.doi.org/10.1111/1467-9639.00020.

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31

Al-Ubaydli, Mohammad. "Using Microsoft Excel." BMJ 330, no. 7481 (2005): s7. http://dx.doi.org/10.1136/bmj.329.7481.s7.

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32

Zetie, K. P. "Animations in Excel." Physics Education 38, no. 2 (2003): 102–3. http://dx.doi.org/10.1088/0031-9120/38/2/405.

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33

Balik, Robert J. "Excel best practices." Managerial Finance 35, no. 5 (2009): 410–26. http://dx.doi.org/10.1108/03074350910949781.

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34

Garmaev, Igor, Torben Miny, Tobias Kleinert, Andreas Schüller, and Philipp Bitterlich. "Verwaltungsschalen aus Excel?" atp magazin 65, no. 3 (2023): 80–86. http://dx.doi.org/10.17560/atp.v65i3.2636.

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Im Rahmen von Industrie 4.0 und der damit verbundenen digitalen Transformation innerhalb der Prozessketten sollen Unternehmen zukünftig ihre Informationen standardisiert und interoperabel mit Hilfe von Verwaltungsschalen bereitstellen. Hierfür müssen sie erstellt und die bereits existierenden Informationen darin eingefügt werden. Um dies möglichst einfach und auch für kleine und mittelständige Unternehmen zu ermöglichen, wird in diesem Beitrag eine Erweiterung des AAS Managers,eines an der RWTH Aachen entwickelten Editors für Verwaltungsschalen, vorgestellt, mit Hilfe dessen diese Transformati

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35

Ji, Xiaoyun, and Bin Hu. "Macros in Excel." E3S Web of Conferences 522 (2024): 01040. http://dx.doi.org/10.1051/e3sconf/202452201040.

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Excel itself has very powerful functions: including printing documents, file processing, formatting and text editing; Exl has a large number of built-in functions, its operation interface is very familiar to the public, and can connect to a variety of databases. Therefore, it has become a widely used application development platform. For a task that needs to be repeated frequently in Excel, you can record all the steps of executing these tasks in the macro and turn the macro into an automatically executable task. In this way, it is unnecessary to repeat the operation, save a lot of manpower an

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36

Grech, Victor. "Forecasting with Excel." Acta Medica (Hradec Kralove, Czech Republic) 67, no. 3 (2024): 87–90. https://doi.org/10.14712/18059694.2025.3.

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Introduction: Time series analysis is used by statisticians to make predictions from time-ordered data. This is crucial for planning for the future. The inclusion of little-known forecasting function in Excel™ has brought this type of analysis within the ability of less mathematically sophisticated individuals, including doctors. There are two main models for time series analysis: ARIMA (Autoregressive Integrated Moving Average) and exponential smoothing. This paper will demonstrate how the ubiquitous Excel facilitates a little-known sophisticated forecasting technique that employs the latter

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37

YOGIRAJ, S. LANGOTE, R. DURUGKAR SHUBHAM, B. FULARI SHANTAPPA, B. SAGGAM VISHAL, and PATIL ANIL. "ADVANCED EXCEL TOOLKIT." JournalNX - A Multidisciplinary Peer Reviewed Journal NITET2017 (March 16, 2017): 77–79. https://doi.org/10.5281/zenodo.1461392.

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Advanced excel tool kit is a bunch of applications which is highly required in day today life. It provides customized functions which helps the user to do their business operations easily. The applications in the toolkit are based on automation terminology. The main objective is nontechnical users can also handle the application easily, without any confusion. The advanced excel toolkit includes auto typer ,customized online typing data, data extraction, expense manger , which reduces the expenditure of overall system as well as high efficiency is obtained. https://journalnx.com/journal-article

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38

Korosov, Andrey Victorovich. "Maxent in the Excel." Principles of the Ecology 47, no. 1 (2023): 93–95. http://dx.doi.org/10.15393/j1.art.2023.13502.

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39

Hampel, György. "Excel alkalmazása normális eloszlás tesztelésére Shapiro-Wilk próbával." Jelenkori Társadalmi és Gazdasági Folyamatok 13, no. 1-2 (2018): 77–82. http://dx.doi.org/10.14232/jtgf.2018.1-2.77-82.

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A Microsoft Excel Visual Basic fór Application programok segítségével nagyméretű adathalmazok szűrésével kapott adatsorain képes programozottan megismételni a számításokat. Több statisztikai programmal tudnánk a Shapiro-Wilk próbát alkalmazni normális eloszlás ellenőrzésére, de programozható módon erre csak az Excelt használhatjuk. Az Excel táblázatkezelő program segítségével felhasználóbarát kezelőfelületet alakítunk ki a számítások automatizált elvégzéséhez.

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40

KATAOKA, Yosuke, and Yuri YAMADA. "Molecular Dynamics by EXCEL." Journal of Computer Chemistry, Japan 14, no. 1 (2015): 18–21. http://dx.doi.org/10.2477/jccj.2015-0001.

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41

Abbott, Steve, and John Shannon. "Excel for Business Mathematics." Mathematical Gazette 83, no. 496 (1999): 150. http://dx.doi.org/10.2307/3618715.

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42

Setiyanto, Sigit, and Ismail Setiawan. "Data Science With Excel." International Journal of Computer and Information System (IJCIS) 3, no. 3 (2022): 104–10. http://dx.doi.org/10.29040/ijcis.v3i3.79.

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The stages in data science consist of several stages, one of which is data preparation. At this stage, many things are done so that the dirty data becomes clean data that is ready for modeling. Many applications offer data science convenience in terms of processing data. One of them is excel, this application from Microsoft can perform data processing so that the data is ready for modeling. However, there are limitations in using excel. The maximum number of rows that excel has is only 1,048,576 and the number of columns is 16,384. However, if you process data of no more than 1 million rows, e

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43

Rasmusson, D. C., R. D. Wilcoxson, and J. V. Wiersma. "Registration of ‘Excel’ Barley." Crop Science 31, no. 1 (1991): 227. http://dx.doi.org/10.2135/cropsci1991.0011183x003100010050x.

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44

Chao, K. S. Clifford. "Transform today, excel tomorrow." Therapeutic Radiology and Oncology 1 (2017): 1. http://dx.doi.org/10.21037/tro.2017.08.01.

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45

Sastry, M. V. "Make Your Team Excel." Review of Professional Management- A Journal of New Delhi Institute of Management 6, no. 2 (2008): 106. http://dx.doi.org/10.20968/rpm/2008/v6/i2/100963.

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46

Moon, J. R. A. "Excel 410 anaesthetic machine." Anaesthesia 44, no. 2 (1989): 177–78. http://dx.doi.org/10.1111/j.1365-2044.1989.tb11209.x.

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47

Littlefield, Stan. "Software Reviews : EXCEL (Macintosh)." Social Science Microcomputer Review 4, no. 2 (1986): 264–65. http://dx.doi.org/10.1177/089443938600400226.

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48

&NA;. "EXCEL III study results." Inpharma Weekly &NA;, no. 805 (1991): 16–17. http://dx.doi.org/10.2165/00128413-199108050-00042.

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49

Sdvizhkov, O. A. "APPLICATION EXCEL FOR KINEMATICS." Physics in School, no. 7 (2020): 30–39. http://dx.doi.org/10.47639/0130-5522_2020_7_30.

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50

Baum, Eric B., Dan Boneh, and Charles Garrett. "Where Genetic Algorithms Excel." Evolutionary Computation 9, no. 1 (2001): 93–124. http://dx.doi.org/10.1162/10636560151075130.

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We analyze the performance of a genetic algorithm (GA) we call Culling, and a variety of other algorithms, on a problem we refer to as the Additive Search Problem (ASP). We show that the problem of learning the Ising perceptron is reducible to a noisy version of ASP. Noisy ASP is the first problem we are aware of where a genetic-type algorithm bests all known competitors. We generalize ASP to k-ASP to study whether GAs will achieve “implicit parallelism” in a problem with many more schemata. GAs fail to achieve this implicit parallelism, but we describe an algorithm we call Explicitly Parallel

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