Search Results - Python variables

Teachers' Beliefs and Practices on the Naming of Variables in Introductory Python Programming Courses by Van Der Werf, Vivian, Swidan, Alaaeddin, Hermans, Felienne, Specht, Marcus, Aivaloglou, Efthimia

“… Objective. This paper investigates naming beliefs, self-reported teaching practices, and observations regarding variable naming practices of teachers of introductory Python programming courses. Methods…”
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Innovation management model for functional food ingredients and additives. Alignment with hype cycle, Python S-curves, and open innovation variables by Montoya, Luis Horacio Botero, Sossa, Jhon Wilder Zartha, Piedrahíta, Juan Carlos Palacio, Mendoza, Gina Lía Orozco, Montoya, Andrés Felipe Restrepo, Pérez, Waldir Augusto Pacheco

“…The objective of this article is to generate an innovation management model for organizations in the functional food ingredients and additives sector, based on prioritization of variables, stakeholder…”
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chelsa‐cmip6 1.0: a python package to create high resolution bioclimatic variables based on CHELSA ver. 2.1 and CMIP6 data by Karger, Dirk Nikolaus, Chauvier, Yohann, Zimmermann, Niklaus E.

“… Here we present the chelsa_cmip6 package to create bioclimatic variables and climatological normals based on CHELSA ver…”
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HemiPy: A Python module for automated estimation of forest biophysical variables and uncertainties from digital hemispherical photographs by Brown, Luke A., Morris, Harry, Leblanc, Sylvain, Bai, Gabriele, Lanconelli, Christian, Gobron, Nadine, Meier, Courtney, Dash, Jadunandan

“… To address these limitations, we present HemiPy, an open‐source Python module for deriving forest biophysical variables and uncertainties from DHP images in an automated manner…”
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PYCV: a PLUMED 2 Module Enabling the Rapid Prototyping of Collective Variables in Python by Giorgino, Toni

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Search for dark matter particles in proton-proton collisions at s = 8 $$ \sqrt{s}=8 $$ TeV using the razor variables by Khachatryan, V., Sirunyan, A. M., Tumasyan, A., Adam, W., Asilar, E., Bergauer, T., Brandstetter, J., Brondolin, E., Dragicevic, M., Erö, J., Flechl, M., Friedl, M., Frühwirth, R., Ghete, V. M., Hartl, C., Hörmann, N., Hrubec, J., Jeitler, M., König, A., Krammer, M., Krätschmer, I., Liko, D., Matsushita, T., Mikulec, I., Rabady, D., Rad, N., Rahbaran, B., Rohringer, H., Schieck, J., Schöfbeck, R., Strauss, J., Treberer-Treberspurg, W., Waltenberger, W., Wulz, C.-E., Mossolov, V., Shumeiko, N., Suarez Gonzalez, J., Alderweireldt, S., Cornelis, T., De Wolf, E. A., Janssen, X., Knutsson, A., Lauwers, J., Luyckx, S., Van De Klundert, M., Van Haevermaet, H., Van Mechelen, P., Van Remortel, N., Van Spilbeeck, A., Abu Zeid, S., Blekman, F., D’Hondt, J., Daci, N., De Bruyn, I., Deroover, K., Heracleous, N., Keaveney, J., Lowette, S., Moortgat, S., Moreels, L., Olbrechts, A., Python, Q., Strom, D., Tavernier, S., Van Doninck, W., Van Mulders, P., Van Onsem, G. P., Van Parijs, I., Barria, P., Brun, H., Caillol, C., Clerbaux, B., De Lentdecker, G., Fasanella, G., Favart, L., Goldouzian, R., Grebenyuk, A., Karapostoli, G., Lenzi, T., Léonard, A., Maerschalk, T., Marinov, A., Perniè, L., Randle-conde, A., Seva, T., Vander Velde, C., Vanlaer, P., Yonamine, R., Zenoni, F., Zhang, F., Beernaert, K., Benucci, L., Cimmino, A., Crucy, S., Dobur, D., Fagot, A., Garcia, G., Gul, M., Mccartin, J., Ocampo Rios, A. A.

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PaCAL : A Python Package for Arithmetic Computations with Random Variables by n, Marcin Korzen, Jaroszewicz, Szymon

“…In this paper we present PaCAL, a Python package for arithmetical computations on random variables…”
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StepMix : A Python Package for Pseudo-Likelihood Estimation of Generalized Mixture Models with External Variables by Morin, Sacha, Legault, Robin, Laliberté, Félix, Bakk, Zsuzsa, Giguère, Charles-Édouard, de la Sablonnière, Roxane, Lacourse, Éric

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Monitoring Algorithm for Electrical Variables Implementing Blockchain and Python by Muñoz-Romero, Javier Andres, Giral-Ramírez, Diego Armando, Ramírez-Vanegas, Carlos Alberto

“…ABSTRACT Objective: This article presents a blockchain application in power systems using electrical variable monitoring delivered by a simulated relay. Methodology…”
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Monitoring Algorithm for Electrical Variables Implementing Blockchain and Python by Muñoz-Romero, Javier Andres, Giral-Ramírez, Diego Armando, Ramírez-Vanegas, Carlos Alberto

“…ABSTRACT Objective: This article presents a blockchain application in power systems using electrical variable monitoring delivered by a simulated relay. Methodology…”
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Monitoring system for electrical variables implementing blockchain and python by Giral Ramírez, Diego Armando, Muñoz Romero, Javier Andres, Ramírez Vanegas, Carlos Alberto

“…Objective: This article presents one of the Blockchain applications in power systems employing the electrical variables monitoring delivered by a simulated relay. Methodology…”
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Integrating agrotechnical practices to optimize maize yield potentials in a regional variable climate: DSSAT and Python tools by Mirshekarnezhad, Babak

“…Climate simulation models, crop yield prediction and programming tools are relevant applications that help farmers to create a platform in the natural…”
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oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data by Dang, Tung, Fermin, Alan S. R., Machizawa, Maro G.

“… Here, we introduce an efficient and high-performance decoding package incorporating a forward variable selection (FVS…”
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Appendix D: Python-to-MATLAB and MATLAB-to- Python Variable Converters by Danial, Albert

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A variable selection package driving Netica with Python by Beuzen, Tomas, Simmons, Joshua

“… of software designed to work with available BN packages. CVNetica_VS is an open-source Python module that extends the functionality of Netica, a commonly used commercial BN software package, to perform variable selection…”
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Algoritmo de monitoreo de variables eléctricas implementando blockchain y Python by Muñoz-Romero, Javier Andres, Giral-Ramirez, Diego Armando, Ramírez-Vanegas, Carlos Alberto

“…Metodología: Las variables eléctricas se verifican, comparan y cargan en una red blockchain creada por una red de servidores…”
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A search for new phenomena in pp collisions at √s̅ = 13 \text TeV s=13TeV in final states with missing transverse momentum and at least one jet using the α _(\mathrm T) αT variable by Khachatryan, V., Sirunyan, A. M., Tumasyan, A., Adam, W., Asilar, E., Bergauer, T., Brandstetter, J., Brondolin, E., Dragicevic, M., Erö, J., Flechl, M., Friedl, M., Frühwirth, R., Ghete, V. M., Hartl, C., Hörmann, N., Hrubec, J., Jeitler, M., König, A., Krätschmer, I., Liko, D., Matsushita, T., Mikulec, I., Rabady, D., Rad, N., Rahbaran, B., Rohringer, H., Schieck, J., Strauss, J., Waltenberger, W., Wulz, C.-E., Dvornikov, O., Makarenko, V., Zykunov, V., Mossolov, V., Shumeiko, N., Suarez Gonzalez, J., Alderweireldt, S., De Wolf, E. A., Janssen, X., Lauwers, J., Van De Klundert, M., Van Haevermaet, H., Van Mechelen, P., Van Remortel, N., Van Spilbeeck, A., Abu Zeid, S., Blekman, F., D’Hondt, J., Daci, N., De Bruyn, I., Deroover, K., Lowette, S., Moortgat, S., Moreels, L., Olbrechts, A., Python, Q., Tavernier, S., Van Doninck, W., Van Mulders, P., Van Parijs, I., Brun, H., Clerbaux, B., De Lentdecker, G., Delannoy, H., Fasanella, G., Favart, L., Goldouzian, R., Grebenyuk, A., Karapostoli, G., Lenzi, T., Léonard, A., Luetic, J., Maerschalk, T., Marinov, A., Randle-conde, A., Seva, T., Vander Velde, C., Vanlaer, P., Vannerom, D., Yonamine, R., Zenoni, F., Zhang, F., Cimmino, A., Cornelis, T., Dobur, D., Fagot, A., Garcia, G., Gul, M., Khvastunov, I., Poyraz, D., Salva, S., Schöfbeck, R., Sharma, A., Tytgat, M., Van Driessche, W., Yazgan, E., Zaganidis, N., Bakhshiansohi, H., Beluffi, C.

“… Several kinematic variables are employed to suppress the dominant background, multijet production, as well as to discriminate between other standard model and new physics processes…”
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PYInfer: Deep Learning Semantic Type Inference for Python Variables by Cui, Siwei, Zhao, Gang, Dai, Zeyu, Wang, Luochao, Huang, Ruihong, Huang, Jeff

“…), they are usually ignored by existing tools. In this paper, we propose PYInfer, an end-to-end learning-based type inference tool that automatically generates type annotations for Python variables…”
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Operations in Synthesized Eight Link Gear Variable Topology Mechanism using Python Programming by Naveen, H. M., Balli, Shrinivas S., Daivagna, Umesh M., Patil, Rashmi

“…This paper illustrates the implementation of python programming in the field of kinematics and helps the planners to visualize the working nature of the synthesized mechanism…”
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refellips: A Python package for the analysis of variable angle spectroscopic ellipsometry data by Robertson, Hayden, Gresham, Isaac J., Prescott, Stuart W., Webber, Grant B., Wanless, Erica J., Nelson, Andrew

“…refellips is an open-source analysis package written in Python for modelling variable angle spectroscopic ellipsometry data…”
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