16 Commits

7 changed files with 554 additions and 184 deletions

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@@ -1,6 +1,6 @@
# KIT Library Hydration Study # KIT Library Hydration Study
Latex sources for a paper on the behavior of students at the KIT library with Latex sources for a paper on the behaviour of students at the KIT library with
regard to their water bottle refilling habits. regard to their water bottle refilling habits.
## Build ## Build
@@ -17,7 +17,7 @@ $ make
```bash ```bash
$ docker build -f Dockerfile . -t bib-paper $ docker build -f Dockerfile . -t bib-paper
``` ```
2. Build examples 2. Build document
```bash ```bash
$ docker run --rm -v $PWD:$PWD -w $PWD -u `id -u`:`id -g` bib-paper make $ docker run --rm -v $PWD:$PWD -w $PWD -u `id -u`:`id -g` bib-paper make
``` ```

148
paper.bib
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@@ -5,15 +5,101 @@
publisher={Penguin} publisher={Penguin}
} }
@article{chen_homotopy_2015,
title = {Homotopy continuation method for solving systems of nonlinear and polynomial equations},
volume = {15},
issn = {15267555, 21634548},
url = {https://link.intlpress.com/JDetail/1805790889102491649},
doi = {10.4310/CIS.2015.v15.n2.a1},
language = {en},
number = {2},
urldate = {2025-02-24},
journal = {Communications in Information and Systems},
author = {Chen, Tianran and Li, Tien-Yien},
year = {2015},
keywords = {/unread},
pages = {119--307},
file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/AM6X2GG5/Chen and Li - 2015 - Homotopy continuation method for solving systems of nonlinear and polynomial equations.pdf:application/pdf},
}
@misc{reichel_numerical_2023,
title = {Numerical {Methods} for {Electrical} {Engineering}, {Meteorology}, {Remote} {Sensing}, and {Geoinformatics}},
shorttitle = {Numerical {Methods}},
language = {en},
author = {Reichel, Wolfgang},
year = {2023},
keywords = {/unread},
file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/VPCNXBJJ/Reichel - for Electrical Engineering, Meteorology, Remote Sensing, and Geoinformatics.pdf:application/pdf},
}
@book{golub_matrix_2013,
edition = {fourth},
title = {Matrix {Computations}},
isbn = {1-4214-0794-9 978-1-4214-0794-4},
url = {http://www.cs.cornell.edu/cv/GVL4/golubandvanloan.htm},
publisher = {JHU Press},
author = {Golub, Gene Howard and Van Loan, Charles Francis},
year = {2013},
keywords = {/unread},
file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/ECTUSDB6/Golub and Van Loan - 2013 - Matrix Computations.pdf:application/pdf},
}
@book{allgower_introduction_2003,
address = {Philadelphia, Pa},
series = {Classics in applied mathematics},
title = {Introduction to numerical continuation methods},
isbn = {978-0-89871-544-6 978-0-89871-915-4},
abstract = {Numerical continuation methods have provided important contributions toward the numerical solution of nonlinear systems of equations for many years. The methods may be used not only to compute solutions, which might otherwise be hard to obtain, but also to gain insight into qualitative properties of the solutions. Introduction to Numerical Continuation Methods, originally published in 1979, was the first book to provide easy access to the numerical aspects of predictor corrector continuation and piecewise linear continuation methods. Not only do these seemingly distinct methods share many common features and general principles, they can be numerically implemented in similar ways. The book also features the piecewise linear approximation of implicitly defined surfaces, the algorithms of which are frequently used in computer graphics, mesh generation, and the evaluation of surface integrals. To help potential users of numerical continuation methods create programs adapted to their particular needs, this book presents pseudo-codes and Fortran codes as illustrations. Since it first appeared, many specialized packages for treating such varied problems as bifurcation, polynomial systems, eigenvalues, economic equilibria, optimization, and the approximation of manifolds have been written. The original extensive bibliography has been updated in the SIAM Classics edition to include more recent references and several URLs so users can look for codes to suit their needs. Audience: this book continues to be useful for researchers and graduate students in mathematics, sciences, engineering, economics, and business. A background in elementary analysis and linear algebra are adequate prerequisites for reading this book; some knowledge from a first course in numerical analysis may also be helpful},
language = {eng},
number = {45},
publisher = {Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104)},
author = {Allgower, Eugene L. and Georg, Kurt},
collaborator = {{Society for Industrial and Applied Mathematics}},
year = {2003},
doi = {10.1137/1.9780898719154},
keywords = {Continuation methods, Euler-Newton method, /unread},
file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/LQGFJ4LJ/Allgower and Georg - 2003 - Introduction to numerical continuation methods.pdf:application/pdf},
}
@book{higham_functions_2008,
title = {Functions of {Matrices}: {Theory} and {Computation}},
isbn = {978-0-89871-646-7},
shorttitle = {Functions of {Matrices}},
abstract = {A thorough and elegant treatment of the theory of matrix functions and numerical methods for computing them, including an overview of applications, new and unpublished research results, and improved algorithms. Key features include a detailed treatment of the matrix sign function and matrix roots; a development of the theory of conditioning and properties of the FrŸ?chet derivative; Schur decomposition; block Parlett recurrence; a thorough analysis of the accuracy, stability, and computational cost of numerical methods; general results on convergence and stability of matrix iterations; and a chapter devoted to the f(A)b problem. Ideal for advanced courses and for self-study, its broad content, references and appendix also make this book a convenient general reference. Contains an extensive collection of problems with solutions and MATLAB? implementations of key algorithms.},
language = {en},
publisher = {SIAM},
author = {Higham, Nicholas J.},
month = sep,
year = {2008},
note = {Google-Books-ID: 2Wz\_zVUEwPkC},
keywords = {Mathematics / Algebra / Linear, Mathematics / Applied, Mathematics / Mathematical Analysis, Mathematics / Matrices, Mathematics / Numerical Analysis, /unread},
file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/W3DMMA3P/Higham - 2008 - Functions of Matrices Theory and Computation.pdf:application/pdf},
}
@article{james_w_michaels_academic_1989,
title = {Academic effort and college grades},
volume = {68},
journal = {Social Forces},
author = {{James W Michaels} and {Terance D Miethe}},
year = {1989},
keywords = {/unread},
pages = {309--319},
}
@article{michaels_academic_1989, @article{michaels_academic_1989,
title = {Academic {Effort} and {College} {Grades}*}, title = {Academic {Effort} and {College} {Grades}*},
volume = {68}, volume = {68},
issn = {0037-7732},
url = {https://doi.org/10.1093/sf/68.1.309},
doi = {10.1093/sf/68.1.309},
abstract = {This study examines the possibility that specification errors contribute to the Schuman et al (1985) findings of a weak relationship between study time and college grades. Our analyses investigate both main and interactive effects, measures of quantity and quality of study, and various context-specific models of college grades. In contrast to previous findings, we observe significant main and interactive effects of academic effort on college grades.}, abstract = {This study examines the possibility that specification errors contribute to the Schuman et al (1985) findings of a weak relationship between study time and college grades. Our analyses investigate both main and interactive effects, measures of quantity and quality of study, and various context-specific models of college grades. In contrast to previous findings, we observe significant main and interactive effects of academic effort on college grades.},
number = {1}, number = {1},
urldate = {2025-03-07},
journal = {Social Forces}, journal = {Social Forces},
author = {Michaels, James W. and Miethe, Terance D.}, author = {Michaels, James W. and Miethe, Terance D.},
month = sep, month = sep,
year = {1989}, year = {1989},
keywords = {/unread, ⭐⭐⭐},
pages = {309--319}, pages = {309--319},
file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/8UXRFWEC/Michaels and Miethe - 1989 - Academic Effort and College Grades.pdf:application/pdf;Snapshot:/home/andreas/workspace/work/hiwi/Zotero/storage/2JBVD4TS/2232194.html:text/html}, file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/8UXRFWEC/Michaels and Miethe - 1989 - Academic Effort and College Grades.pdf:application/pdf;Snapshot:/home/andreas/workspace/work/hiwi/Zotero/storage/2JBVD4TS/2232194.html:text/html},
} }
@@ -21,24 +107,31 @@
@article{dickinson_effect_1990, @article{dickinson_effect_1990,
title = {Effect of {Quality} and {Quantity} of {Study} on {Student} {Grades}}, title = {Effect of {Quality} and {Quantity} of {Study} on {Student} {Grades}},
volume = {83}, volume = {83},
issn = {0022-0671},
url = {https://www.jstor.org/stable/27540388},
abstract = {In this study we investigated the relationship between study time and test scores in a course on learning principles for college education majors. The students were required to keep a continuous log of the amount of time that they spent reading, reviewing, and organizing for the course. Weak relationships with test scores were found for total study time and time spent reviewing. A much stronger relationship was found for time spent organizing the course content. An extreme-groups analysis revealed that students with high test scores spent 40 min per week organizing compared with 10 min per week for students with low test scores. The results support the importance that information-processing theorists attribute to active learning strategies.}, abstract = {In this study we investigated the relationship between study time and test scores in a course on learning principles for college education majors. The students were required to keep a continuous log of the amount of time that they spent reading, reviewing, and organizing for the course. Weak relationships with test scores were found for total study time and time spent reviewing. A much stronger relationship was found for time spent organizing the course content. An extreme-groups analysis revealed that students with high test scores spent 40 min per week organizing compared with 10 min per week for students with low test scores. The results support the importance that information-processing theorists attribute to active learning strategies.},
number = {4}, number = {4},
urldate = {2025-03-07},
journal = {The Journal of Educational Research}, journal = {The Journal of Educational Research},
author = {Dickinson, Donald J. and O'Connell, Debra Q.}, author = {Dickinson, Donald J. and O'Connell, Debra Q.},
year = {1990}, year = {1990},
note = {Publisher: Taylor \& Francis, Ltd.}, note = {Publisher: Taylor \& Francis, Ltd.},
keywords = {/unread},
pages = {227--231}, pages = {227--231},
file = {JSTOR Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/8HZQXEEU/Dickinson and O'Connell - 1990 - Effect of Quality and Quantity of Study on Student Grades.pdf:application/pdf}, file = {JSTOR Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/8HZQXEEU/Dickinson and O'Connell - 1990 - Effect of Quality and Quantity of Study on Student Grades.pdf:application/pdf},
} }
@article{zulauf_use_1999, @article{zulauf_use_1999,
series = {Selected {Paper}}, series = {Selected {Paper}},
title = {USE OF TIME AND ACADEMIC PERFORMANCE OF COLLEGE STUDENTS: DOES STUDYING MATTER?}, title = {{USE} {OF} {TIME} {AND} {ACADEMIC} {PERFORMANCE} {OF} {COLLEGE} {STUDENTS}: {DOES} {STUDYING} {MATTER}?},
shorttitle = {{USE} {OF} {TIME} {AND} {ACADEMIC} {PERFORMANCE} {OF} {COLLEGE} {STUDENTS}},
doi = {10.22004/ag.econ.21547},
abstract = {Recursive regression analysis revealed time management skills and study time were positively related with quarter GPA for 93 students in three agricultural economics courses at Ohio State University. GPA increased only 0.04 points [4.0 scale] per additional study hour, suggesting substantial improvements in GPA require substantial increases in study time}, abstract = {Recursive regression analysis revealed time management skills and study time were positively related with quarter GPA for 93 students in three agricultural economics courses at Ohio State University. GPA increased only 0.04 points [4.0 scale] per additional study hour, suggesting substantial improvements in GPA require substantial increases in study time},
language = {eng}, language = {eng},
editor = {Zulauf, Carl R. and Gortner, Amy K.}, editor = {Zulauf, Carl R. and Gortner, Amy K.},
year = {1999}, year = {1999},
keywords = {academic performance, study time, Teaching/Communication/Extension/Profession, time management}, note = {Num Pages: 16},
keywords = {academic performance, study time, Teaching/Communication/Extension/Profession, time management, /unread, ⭐⭐⭐⭐⭐},
file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/PM7CTJ7G/Zulauf and Gortner - 1999 - USE OF TIME AND ACADEMIC PERFORMANCE OF COLLEGE STUDENTS DOES STUDYING MATTER.pdf:application/pdf}, file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/PM7CTJ7G/Zulauf and Gortner - 1999 - USE OF TIME AND ACADEMIC PERFORMANCE OF COLLEGE STUDENTS DOES STUDYING MATTER.pdf:application/pdf},
} }
@@ -56,7 +149,9 @@
author = {Rooney, Karen and Polloway, Edward A. and Hallahan, Daniel P.}, author = {Rooney, Karen and Polloway, Edward A. and Hallahan, Daniel P.},
month = aug, month = aug,
year = {1985}, year = {1985},
note = {Publisher: SAGE Publications Inc}, note = {Publisher: SAGE Publications Inc
TLDR: Investigation of the efficacy of two cognitive behavior modification procedures with a group of low functioning students in a LD self-contained class indicates that the combination was effective for all four students in improving attention-to-task and for three of the four children in percentage of accurate responses in an arithmetic task.},
keywords = {/unread, ⭐},
pages = {384--389}, pages = {384--389},
file = {SAGE PDF Full Text:/home/andreas/workspace/work/hiwi/Zotero/storage/ETX97WRA/Rooney et al. - 1985 - The Use of Self-Monitoring Procedures With Low IQ Learning Disabled Students.pdf:application/pdf}, file = {SAGE PDF Full Text:/home/andreas/workspace/work/hiwi/Zotero/storage/ETX97WRA/Rooney et al. - 1985 - The Use of Self-Monitoring Procedures With Low IQ Learning Disabled Students.pdf:application/pdf},
} }
@@ -77,7 +172,7 @@
month = feb, month = feb,
year = {2023}, year = {2023},
note = {Number: 02}, note = {Number: 02},
keywords = {Distance Learning, Online Learning, Time Management}, keywords = {Distance Learning, Online Learning, Time Management, /unread},
pages = {7731--7741}, pages = {7731--7741},
file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/FST4M46S/Napoles et al. - 2023 - The Role of Time Management to the Academic Performance of the College Students During Pandemic.pdf:application/pdf}, file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/FST4M46S/Napoles et al. - 2023 - The Role of Time Management to the Academic Performance of the College Students During Pandemic.pdf:application/pdf},
} }
@@ -98,7 +193,7 @@
year = {2014}, year = {2014},
note = {Publisher: SRHE Website note = {Publisher: SRHE Website
\_eprint: https://doi.org/10.1080/03075079.2012.721350}, \_eprint: https://doi.org/10.1080/03075079.2012.721350},
keywords = {academic performance, study time, higher education, learning environment, self-regulated learning, student characteristics}, keywords = {academic performance, study time, higher education, learning environment, self-regulated learning, student characteristics, /unread, ⭐⭐⭐⭐},
pages = {621--643}, pages = {621--643},
file = {Submitted Version:/home/andreas/workspace/work/hiwi/Zotero/storage/S7W5636G/Masui et al. - 2014 - Do diligent students perform better Complex relations between student and course characteristics, s.pdf:application/pdf}, file = {Submitted Version:/home/andreas/workspace/work/hiwi/Zotero/storage/S7W5636G/Masui et al. - 2014 - Do diligent students perform better Complex relations between student and course characteristics, s.pdf:application/pdf},
} }
@@ -106,18 +201,14 @@
@article{plant_why_2005, @article{plant_why_2005,
title = {Why study time does not predict grade point average across college students: {Implications} of deliberate practice for academic performance}, title = {Why study time does not predict grade point average across college students: {Implications} of deliberate practice for academic performance},
volume = {30}, volume = {30},
issn = {0361-476X},
shorttitle = {Why study time does not predict grade point average across college students}, shorttitle = {Why study time does not predict grade point average across college students},
url = {https://www.sciencedirect.com/science/article/pii/S0361476X04000384},
doi = {10.1016/j.cedpsych.2004.06.001},
abstract = {The current work draws upon the theoretical framework of deliberate practice in order to clarify why the amount of study by college students is a poor predictor of academic performance. A model was proposed where performance in college, both cumulatively and for a current semester, was jointly determined by previous knowledge and skills as well as factors indicating quality (e.g., study environment) and quantity of study. The findings support the proposed model and indicate that the amount of study only emerged as a significant predictor of cumulative GPA when the quality of study and previously attained performance were taken into consideration. The findings are discussed in terms of the insights provided by applying the framework of deliberate practice to academic performance in a university setting.}, abstract = {The current work draws upon the theoretical framework of deliberate practice in order to clarify why the amount of study by college students is a poor predictor of academic performance. A model was proposed where performance in college, both cumulatively and for a current semester, was jointly determined by previous knowledge and skills as well as factors indicating quality (e.g., study environment) and quantity of study. The findings support the proposed model and indicate that the amount of study only emerged as a significant predictor of cumulative GPA when the quality of study and previously attained performance were taken into consideration. The findings are discussed in terms of the insights provided by applying the framework of deliberate practice to academic performance in a university setting.},
number = {1}, number = {1},
urldate = {2025-03-07},
journal = {Contemporary Educational Psychology}, journal = {Contemporary Educational Psychology},
author = {Plant, E. Ashby and Ericsson, K. Anders and Hill, Len and Asberg, Kia}, author = {Plant, E. Ashby and Ericsson, K. Anders and Hill, Len and Asberg, Kia},
month = jan, month = jan,
year = {2005}, year = {2005},
keywords = {Academic performance, Deliberate practice, Grade point average, Study habits, Study time}, keywords = {Academic performance, Deliberate practice, Grade point average, Study habits, Study time, /unread, ⭐⭐⭐},
pages = {96--116}, pages = {96--116},
file = {ScienceDirect Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/6CLRGKBL/Plant et al. - 2005 - Why study time does not predict grade point average across college students Implications of deliber.pdf:application/pdf;ScienceDirect Snapshot:/home/andreas/workspace/work/hiwi/Zotero/storage/I7AWASSH/S0361476X04000384.html:text/html}, file = {ScienceDirect Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/6CLRGKBL/Plant et al. - 2005 - Why study time does not predict grade point average across college students Implications of deliber.pdf:application/pdf;ScienceDirect Snapshot:/home/andreas/workspace/work/hiwi/Zotero/storage/I7AWASSH/S0361476X04000384.html:text/html},
} }
@@ -132,11 +223,12 @@
author = {Schuman, Howard and Walsh, Edward and Olson, Camille and Etheridge, Barbara}, author = {Schuman, Howard and Walsh, Edward and Olson, Camille and Etheridge, Barbara},
month = jun, month = jun,
year = {1985}, year = {1985},
keywords = {/unread, ⭐⭐⭐⭐⭐},
pages = {945--966}, pages = {945--966},
file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/ST8F6X85/Schuman et al. - 1985 - Effort and Reward The Assumption that College Grades Are Affected by Quantity of Study.pdf:application/pdf;Snapshot:/home/andreas/workspace/work/hiwi/Zotero/storage/6ZFY7KPK/2232109.html:text/html}, file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/ST8F6X85/Schuman et al. - 1985 - Effort and Reward The Assumption that College Grades Are Affected by Quantity of Study.pdf:application/pdf;Snapshot:/home/andreas/workspace/work/hiwi/Zotero/storage/6ZFY7KPK/2232109.html:text/html},
} }
@misc{e_g_williamson_relationship_nodate, @misc{e_g_williamson_relationship_1935,
title = {The relationship of number of hours of study to scholarship.}, title = {The relationship of number of hours of study to scholarship.},
url = {https://psycnet.apa.org/record/1936-02704-001}, url = {https://psycnet.apa.org/record/1936-02704-001},
abstract = {A study based on the reported hours of study of 257 freshmen at the University of Minnesota during the week just prior to mid-quarter examinations. The mean hours of study were 27.09; the {\textless}em{\textgreater}r{\textless}/em{\textgreater} between scholarship and hours of study was-.06; the {\textless}em{\textgreater}r{\textless}/em{\textgreater} between scores on the Minnesota college aptitude test and hours of study was -.20. A comparison of these results with other studies is given, and it is concluded that the location of the week used in this study probably makes the new data closer approximations to the true relationships. The student of low ability must study more than the student of high ability, but the increase will not necessarily result in much higher scholarship. (PsycINFO Database Record (c) 2016 APA, all rights reserved)}, abstract = {A study based on the reported hours of study of 257 freshmen at the University of Minnesota during the week just prior to mid-quarter examinations. The mean hours of study were 27.09; the {\textless}em{\textgreater}r{\textless}/em{\textgreater} between scholarship and hours of study was-.06; the {\textless}em{\textgreater}r{\textless}/em{\textgreater} between scores on the Minnesota college aptitude test and hours of study was -.20. A comparison of these results with other studies is given, and it is concluded that the location of the week used in this study probably makes the new data closer approximations to the true relationships. The student of low ability must study more than the student of high ability, but the increase will not necessarily result in much higher scholarship. (PsycINFO Database Record (c) 2016 APA, all rights reserved)},
@@ -144,7 +236,9 @@
urldate = {2025-03-07}, urldate = {2025-03-07},
journal = {APA PsycNET}, journal = {APA PsycNET},
author = {{E. G. Williamson}}, author = {{E. G. Williamson}},
year = {1935},
doi = {10.1037/h0056481}, doi = {10.1037/h0056481},
keywords = {/unread, ⭐⭐},
file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/IIVGJSV8/The relationship of number of hours of study to scholarship..pdf:application/pdf;Snapshot:/home/andreas/workspace/work/hiwi/Zotero/storage/F4ZN6958/1936-02704-001.html:text/html}, file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/IIVGJSV8/The relationship of number of hours of study to scholarship..pdf:application/pdf;Snapshot:/home/andreas/workspace/work/hiwi/Zotero/storage/F4ZN6958/1936-02704-001.html:text/html},
} }
@@ -162,7 +256,7 @@
author = {Kember, David and Jamieson, Qun Wang and Pomfret, Mike and Wong, Eric T. T.}, author = {Kember, David and Jamieson, Qun Wang and Pomfret, Mike and Wong, Eric T. T.},
month = apr, month = apr,
year = {1995}, year = {1995},
keywords = {Academic Performance, Learn Approach, Mechanical Engineering, Promising Method, Study Time}, keywords = {Academic Performance, Learn Approach, Mechanical Engineering, Promising Method, Study Time, /unread, ⭐⭐},
pages = {329--343}, pages = {329--343},
file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/G8WUZWIJ/Kember et al. - 1995 - Learning approaches, study time and academic performance.pdf:application/pdf}, file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/G8WUZWIJ/Kember et al. - 1995 - Learning approaches, study time and academic performance.pdf:application/pdf},
} }
@@ -180,6 +274,7 @@
author = {Schuman, Howard}, author = {Schuman, Howard},
year = {2001}, year = {2001},
note = {Publisher: [Sage Publications, Inc., American Sociological Association]}, note = {Publisher: [Sage Publications, Inc., American Sociological Association]},
keywords = {/unread, ⭐⭐⭐},
pages = {73--74}, pages = {73--74},
file = {JSTOR Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/AYBTRUSF/Schuman - 2001 - Comment Students' Effort and Reward in College Settings.pdf:application/pdf}, file = {JSTOR Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/AYBTRUSF/Schuman - 2001 - Comment Students' Effort and Reward in College Settings.pdf:application/pdf},
} }
@@ -199,7 +294,7 @@
note = {Num Pages: 11 note = {Num Pages: 11
Place: Corte Madera, CA, United States Place: Corte Madera, CA, United States
Publisher: Select Press}, Publisher: Select Press},
keywords = {Psychology, Social Sciences (General), Sociology}, keywords = {Psychology, Social Sciences (General), Sociology, /unread, ⭐⭐⭐},
pages = {151--161}, pages = {151--161},
file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/X69I8QXV/Hill - 1990 - Effort and Reward in College A Replication of Some Puzzling Findings.pdf:application/pdf}, file = {Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/X69I8QXV/Hill - 1990 - Effort and Reward in College A Replication of Some Puzzling Findings.pdf:application/pdf},
} }
@@ -218,6 +313,33 @@ Publisher: Select Press},
author = {Rau, William and Durand, Ann}, author = {Rau, William and Durand, Ann},
year = {2000}, year = {2000},
note = {Publisher: [Sage Publications, Inc., American Sociological Association]}, note = {Publisher: [Sage Publications, Inc., American Sociological Association]},
keywords = {/unread, ⭐⭐⭐},
pages = {19--38}, pages = {19--38},
file = {JSTOR Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/H58YHZEJ/Rau and Durand - 2000 - The Academic Ethic and College Grades Does Hard Work Help Students to Make the Grade.pdf:application/pdf}, file = {JSTOR Full Text PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/H58YHZEJ/Rau and Durand - 2000 - The Academic Ethic and College Grades Does Hard Work Help Students to Make the Grade.pdf:application/pdf},
} }
@book{gross_fundamentals_2008,
address = {Hoboken, NJ},
edition = {4. ed},
series = {Wiley series in probability and statistics},
title = {Fundamentals of queueing theory},
isbn = {978-0-471-79127-0},
language = {eng},
publisher = {Wiley},
author = {Gross, Donald and Shortle, John F. and Thompson, James M. and Harris, Carl M.},
year = {2008},
keywords = {/unread, Queuing theory, Warteschlangentheorie},
file = {Ebook:/home/andreas/workspace/work/hiwi/Zotero/storage/ZGBENDHH/Gross et al. - 2008 - Fundamentals of queueing theory.epub:application/epub+zip},
}
@book{stewart_probability_2009,
title = {Probability, {Markov} {Chains}, {Queues}, and {Simulation}: {The} {Mathematical} {Basis} of {Performance} {Modeling}},
shorttitle = {Probability, {Markov} {Chains}, {Queues}, and {Simulation}},
abstract = {Probability, Markov Chains, Queues, and Simulation provides a modern and authoritative treatment of the mathematical processes that underlie performance modeling. The detailed explanations of mathematical derivations and numerous illustrative examples make this textbook readily accessible to graduate and advanced undergraduate students taking courses in which stochastic processes play a fundamental role. The textbook is relevant to a wide variety of fields, including computer science, engineering, operations research, statistics, and mathematics.The textbook looks at the fundamentals of probability theory, from the basic concepts of set-based probability, through probability distributions, to bounds, limit theorems, and the laws of large numbers. Discrete and continuous-time Markov chains are analyzed from a theoretical and computational point of view. Topics include the Chapman-Kolmogorov equations; irreducibility; the potential, fundamental, and reachability matrices; random walk problems; reversibility; renewal processes; and the numerical computation of stationary and transient distributions. The M/M/1 queue and its extensions to more general birth-death processes are analyzed in detail, as are queues with phase-type arrival and service processes. The M/G/1 and G/M/1 queues are solved using embedded Markov chains; the busy period, residual service time, and priority scheduling are treated. Open and closed queueing networks are analyzed. The final part of the book addresses the mathematical basis of simulation.Each chapter of the textbook concludes with an extensive set of exercises. An instructor's solution manual, in which all exercises are completely worked out, is also available (to professors only).Numerous examples illuminate the mathematical theoriesCarefully detailed explanations of mathematical derivations guarantee a valuable pedagogical approachEach chapter concludes with an extensive set of exercises},
publisher = {Princeton University Press},
author = {Stewart, William J.},
month = jul,
year = {2009},
keywords = {Mathematics / Applied, /unread, Computers / Data Science / Data Modeling \& Design, Mathematics / Probability \& Statistics / General, Technology \& Engineering / Engineering (General)},
file = {PDF:/home/andreas/workspace/work/hiwi/Zotero/storage/L2FEI8HG/Stewart - 2009 - Probability, Markov Chains, Queues, and Simulation The Mathematical Basis of Performance Modeling.pdf:application/pdf},
}

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paper.tex
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\documentclass[journal]{IEEEtran} \documentclass[journal]{IEEEtran}
\usepackage{amsmath,amsfonts} \usepackage{amsmath,amsfonts}
\usepackage{float}
\usepackage{algorithmic}
\usepackage{algorithm}
\usepackage{siunitx} \usepackage{siunitx}
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\usepackage{dsfont}
\usepackage{mleftright} \usepackage{mleftright}
\usepackage{bbm} \usepackage{float}
\usepackage{titlesec}
\usepackage[ \usepackage[
backend=biber, backend=biber,
style=ieee, style=ieee,
sorting=nty, sorting=nty,
]{biblatex} ]{biblatex}
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% Template modifications
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
\hyphenation{op-tical net-works semi-conduc-tor IEEE-Xplore} \titlespacing*{\section}{0mm}{3mm}{1mm}
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% %
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@@ -36,7 +46,6 @@
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% %
% Figures % Figures
% %
@@ -45,19 +54,19 @@
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DFRPlot/.style={ DFRPlot/.style={
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% %
@@ -67,227 +76,222 @@
\addbibresource{paper.bib} \addbibresource{paper.bib}
\AtBeginBibliography{\footnotesize} \AtBeginBibliography{\footnotesize}
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Custom commands
% Title, Header, Footer, etc.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
\newcommand\todo[1]{\textcolor{red}{#1}} \newcommand\todo[1]{\textcolor{red}{#1}}
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Title, Header, Footer, etc. % Title, Header, Footer, etc.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
\begin{document} \begin{document}
\title{\vspace{-3mm}The Effect of the Choice of Hydration Strategy on
\title{The Effect of the Choice of Hydration Strategy on Average Academic Average Academic
Performance} Performance}
\author{Some concerned fellow students% \author{Some concerned fellow students%
\thanks{The authors would like to thank their hard-working peers as well as \thanks{The authors would like to thank their hard-working peers as
the staff of the KIT library for their unknowing - but vital - well as the staff of the KIT library for their unknowing - but vital
participation.}} - participation.}}
\markboth{Journal of the Association of KIT Bibliophiles}{The \markboth{Journal of the Association of KIT Bibliophiles}{The Effect
Effect of the Choice of Hydration Strategy on Average Academic Performance} of the Choice of Hydration Strategy on Average Academic Performance}
\maketitle \maketitle
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Abstract & Index Terms % Abstract & Index Terms
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
\begin{abstract} \begin{abstract}
We evaluate the \todo{\ldots} and project that by using the right button of We evaluate the relationship between hydration strategy and
the water dispenser to fill up their water bottles, students can potentially academic performance and project that by using the right button
gain up to \todo{5 minutes} of study time a day, which is equivalent to of the water dispenser to fill up their water bottles, students
raising their grades by up to \todo{0.01} levels. can potentially gain up to \SI{4.14}{\second} of study time per
refill, which is amounts to raising their grades by up to 0.00103 points.
\end{abstract} \end{abstract}
\begin{IEEEkeywords} \begin{IEEEkeywords}
KIT Library, Academic Performance, Hydration KIT Library, Academic Performance, Hydration
\end{IEEEkeywords} \end{IEEEkeywords}
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Content % Content
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
\vspace*{-5mm}
\vspace*{-1mm}
%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Introduction} \section{Introduction}
\IEEEPARstart{T}{he} concepts of hydration and study have always been tightly % TODO: "The right strategy" pun?
interwoven. As an example, an investigation was once conducted by Bell Labs
into the productivity of their employees that found that ``workers with the \IEEEPARstart{T}{he} concepts of hydration and study have always been
most patents often shared lunch or breakfast with a Bell Labs electrical tightly interwoven. As an example, an investigation was once
engineer named Harry Nyquist'' \cite{gertner_idea_2012}, and we presume that conducted by Bell Labs into the productivity of their employees that
they also paired their food with something to drink. We can see that found that ``workers with the most patents often shared lunch or
intellectual achievement and hydration are related even for the most breakfast with a Bell Labs electrical engineer named Harry Nyquist''
\cite{gertner_idea_2012}, and we presume that they also paired their
food with something to drink. We can see that intellectual
achievement and fluid consumption are related even for the most
prestigious research institutions. prestigious research institutions.
In this work, we quantify this relationship in the context of studying at the In this work, we quantify this relationship in the context of
KIT library and subsequently develop a novel and broadly applicable strategy studying at the KIT library and subsequently develop a novel and
to leverage it to improve the academic performance of KIT students. broadly applicable strategy to leverage it to improve the academic
performance of KIT students.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Experimental Setup} \section{Experimental Setup}
Over a period of one week, we monitored the usage of the water dispenser Over a period of one week, we monitored the usage of the water
on the ground floor of the KIT library at random times during the day. dispenser on the ground floor of the KIT library at random times
The experiment comprised two parts, a system measurement to determine the during the day. The experiment comprised two parts, a system
flowrate of the water dispenser, and a behavioral measurement, i.e., a recording measurement to determine the flowrate of the water dispenser, and a
of the choice of hydration strategy of the participants: $S_\text{L}$ denotes behavioural measurement, i.e., a recording of the choice of hydration
pressing the left button of the water dispenser, $S_\text{R}$ the right one, strategy of the participants: $S_\text{L}$ denotes pressing the left
and $S_\text{B}$ pressing both buttons. button of the water dispenser, $S_\text{R}$ the right one, and
$S_\text{B}$ pressing both buttons.
As is always the case with measurements, care must be taken not to alter
quantities by measuring them. To this end, we made sure only to take system
measurements in the absence of participants and to only record data on the
behaviour of participants discreetly.
% TODO: Describe the actual measurement setup? (e.g., filling up a 0.7l bottle
% and timing with a standard smartphone timer)
For the system measurement $10$ datapoints were recorded for each
strategy, for the behavioural measurement $113$ in total.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Experimental Results} \section{Experimental Results}
\begin{figure}[H] \begin{figure}[H]
\centering \centering
\vspace*{-4mm}
\begin{tikzpicture} \begin{tikzpicture}
\begin{axis}[ \begin{axis}[
width=0.85\columnwidth, width=0.8\columnwidth,
height=0.4\columnwidth, height=0.35\columnwidth,
boxplot/draw direction = x, boxplot/draw direction = x,
grid, grid,
ytick = {1, 2, 3}, ytick = {1, 2, 3},
yticklabels = {$S_\text{B}$ (Both buttons), $S_\text{R}$ (Right button), $S_\text{L}$ (Left button)}, yticklabels = {$S_\text{B}$ (Both buttons),
xlabel = {Flowrate (\si{\milli\litre\per\second})}, $S_\text{R}$ (Right button), $S_\text{L}$ (Left button)},
] xlabel = {Flowrate (\si{\milli\litre\per\second})},
]
\addplot[boxplot, fill, scol1, draw=black] \addplot[boxplot, fill, scol1, draw=black]
table[col sep=comma, x=flowrate] table[col sep=comma, x=flowrate]
{res/flowrate_both.csv}; {res/flowrate_both.csv};
\addplot[boxplot, fill, scol2, draw=black] \addplot[boxplot, fill, scol2, draw=black]
table[col sep=comma, x=flowrate] table[col sep=comma, x=flowrate]
{res/flowrate_right.csv}; {res/flowrate_right.csv};
\addplot[boxplot, fill, scol3, draw=black] \addplot[boxplot, fill, scol3, draw=black]
table[col sep=comma, x=flowrate] table[col sep=comma, x=flowrate]
{res/flowrate_left.csv}; {res/flowrate_left.csv};
\end{axis} \end{axis}
\end{tikzpicture} \end{tikzpicture}
\caption{Flow rate of the water dispenser depending on the button pressed.} \vspace*{-3mm}
\caption{Flow rate of the water dispenser depending on the
hydration strategy.}
\label{fig:System} \label{fig:System}
\vspace*{-2mm}
\end{figure} \end{figure}
Fig. \ref{fig:System} shows the results of the system measurement. We
observe that $S_\text{L}$ is the slowest strategy, while $S_\text{R}$
and $S_\text{B}$ are similar. Due to the small sample size and the
unknown distribution, the test we chose to verify this observation is
a Mann Whitney U test. We found that $S _\text{L}$ is faster than
$S_\text{R}$ with a significance of $p < 0.0001$, while no
significant statement could be made about $S_\text{R}$ and
$S_\text{B}$. Fig. \ref{fig:Behavior} shows the results of the
behavioural measurement.
\begin{figure}[H] \begin{figure}[H]
\centering \centering
\vspace*{-2mm}
\begin{tikzpicture} \begin{tikzpicture}
\begin{axis}[ \begin{axis}[
ybar, ybar,
bar width=15mm, bar width=15mm,
width=\columnwidth, width=\columnwidth,
height=0.4\columnwidth, height=0.35\columnwidth,
area style, area style,
xtick = {0, 1, 2}, xtick = {0, 1, 2},
grid, grid,
ymin = 0, ymin = 0,
enlarge x limits=0.3, enlarge x limits=0.3,
xticklabels = {Left button, Right button, Both buttons}, xticklabels = {\footnotesize{$S_\text{L}$ (Left
ylabel = {No. of presses}, button)}, \footnotesize{$S_\text{R}$ (Right
] button)}, \footnotesize{$S_\text{B}$} (Both buttons)},
\addplot+[ybar,mark=no,fill=scol1] table[skip first n=1, col sep=comma, x=button, y=count] ylabel = {No. chosen},
{res/left_right_distribution.csv}; ]
\addplot+[ybar,mark=no,fill=scol1] table[skip first n=1,
col sep=comma, x=button, y=count]
{res/left_right_distribution.csv};
\end{axis} \end{axis}
\end{tikzpicture} \end{tikzpicture}
\vspace*{-3mm}
\caption{Distribution of the choice of hydration strategy.} \caption{Distribution of the choice of hydration strategy.}
\label{fig:Behavior} \label{fig:Behavior}
\end{figure} \end{figure}
Fig. \ref{fig:System} indicates that $S_\text{L}$ is the slowest
strategy, while $S_\text{R}$ and $S_\text{B}$ are similar.
Due to the small sample size ($N=10$) and the unknown distribution, the test
we chose to verify this observation is a Mann-Whitney U test. We found that
$S _\text{L}$ is faster than $S_\text{R}$ with a significance of $p < 0.0001$,
while no significant statement could be made about $S_\text{R}$ and
$S_\text{B}$.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Discussion} \section{Modelling the grade improvement}
We can consider the water dispenser and students as comprising a
We examine the effects of the choice of hydration strategy. To queueing system, specifically an M/G/1 queue
this end, we first estimate the amount of time saved by choosing a certain \cite{stewart_probability_2009}. The expected response time, i.e.,
strategy and relate that to a possible gain in academic performance, i.e., the time spent waiting as well as the time dispensing water, is
grades.% \cite[Section 14.3]{stewart_probability_2009}%
% %
\todo{ \begin{align*}
\begin{itemize} W = E\mleft\{ S \mright\} + \frac{\lambda E\mleft\{ S^2
\item ``We measured the average bottle size'' \mright\}}{2\mleft( 1-\rho \mright)}
\item Quantify relationship: Compute average time saving by using right ,%
button $\rightarrow$ translate into grade gain \end{align*}%
\item People using the left button slow down the entire queue %
behind them, not only themselves where $S$ denotes the service time (i.e., the time spent refilling a
\end{itemize} bottle), $\lambda$ the mean arrival rate, and $\rho = \lambda \cdot
}% E\mleft\{ S \mright\}$ the system utilization. Using our experimental
data we can approximate all parameters and obtain $W \approx
Many attempts have been made in the literature to relate the time spent \SI{23.3}{\second}$. The difference to always using the fastest
studying to academic achievement - see, e.g. strategy amounts to $\SI{4.14}{\second}$.
\cite{schuman_effort_1985, zulauf_use_1999, michaels_academic_1989, dickinson_effect_1990}.
The overwhelming consensus is that there is a significant relationship,
though it is a weak one.
%Many of the studies were only performed over
% a period of one week or even day, so we believe care should be taken when
% generlizing these results. Nevertheless, the overwhelming consensus in the
% literature is that a significant relationship exists, though it is a weak one.
Strangely, it is the consensus of current research that there is only
a weak relationship between academic performance and hours studied
\cite{plant_why_2005}. The largest investigation into the matter
found a correlation of $\rho = 0.18$ \cite{schuman_effort_1985}
between GPA and average time spend studying per day. Using a rather
high estimate of 5 refills per day, we predict a possible grade gain
of up to $0.00103$ points.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\section{Conclusion} \section{Discussion and Conclusion}
Further research is needed, particularly on the modelling of the
arrival process and the relationship between the response time gain
the grade gain. Nevertheless, we believe this work serves as a solid
first step on the path towards achieving optimal study behaviour.
In this study, we investigated how the choice of hydration strategy affects In this study, we investigated how the choice of hydration strategy
the average academic performance of a student. We found that always choosing to affects average academic performance. We found that always choosing
press the right button leads to an average time gain of \todo{\SI{10}{\second}} to press the right button leads to an average time gain of
per day, which translates into a grade improvement of $\todo{0.001}$ levels. \SI{4.14}{\second} per refill, which translates into a grade
We thus propose a novel and broadly applicable strategy to boost the average improvement of up to $0.00103$ levels. We thus propose a novel and
academic performance of KIT students: always pressing the right button. broadly applicable strategy to boost the average academic performance
of KIT students: always using the right button.
Further research is needed to develop a better model of how the choice of
hydration strategy is related to academic performance. We
suspect that there is a compounding effect that leads to $S_\text{L}$ being an
even worse choice of hydration strategy: When the queue is long, students are
less likely to refill their empty water bottles, leading to reduced mental
ability. Nevertheless, we believe that with this work we have laid a solid
foundation and hope that our results will find widespread acceptance among the
local student population.
% %
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
@@ -295,9 +299,6 @@ local student population.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% %
\printbibliography \printbibliography
\end{document} \end{document}

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time,button
28,left
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16.43,left
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29,left
20,left
24,left
22,left
15,left
13,left
22,left
23,left
40,left
19.8,left
35.38,left
21,left
16.3,left
29.3,left
30.3,left
30.2,left
25,left
14,left
14.1,left
40,left
24.4,left
5.2,left
50,left
29.7,left
39,left
17,left
40.7,left
27.3,left
19.8,left
7.55,right
14,right
9,right
13,right
5,right
13,right
13.58,right
15.58,right
25,right
20,right
14,right
13,right
14,right
13.3,right
19,right
13,right
10,right
15,right
14,right
19.4,right
12.8,right
13.5,right
19.31,right
27.5,right
13.1,right
23.6,right
15,right
18.7,right
18,right
12.7,right
40.3,right
12.86,right
22.9,right
10,right
20,right
12,right
19,right
39.8,right
20,both
20,both
15,both
19,both
13,both
7,both
15,both
17.3,both
12,both
23,both
11.26,both
35.66,both
13.54,both
27.81,both
16.83,both
17.13,both
17.8,both
39,both
11,both
13.6,both
21.7,both
14.25,both
12,both
12.9,both
12.35,both
1 time button
2 28 left
3 22 left
4 17 left
5 40 left
6 24 left
7 41 left
8 11 left
9 11 left
10 26.56 left
11 37 left
12 30 left
13 30 left
14 8 left
15 21 left
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18 28 left
19 20 left
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21 16.43 left
22 16 left
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24 20 left
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26 22 left
27 15 left
28 13 left
29 22 left
30 23 left
31 40 left
32 19.8 left
33 35.38 left
34 21 left
35 16.3 left
36 29.3 left
37 30.3 left
38 30.2 left
39 25 left
40 14 left
41 14.1 left
42 40 left
43 24.4 left
44 5.2 left
45 50 left
46 29.7 left
47 39 left
48 17 left
49 40.7 left
50 27.3 left
51 19.8 left
52 7.55 right
53 14 right
54 9 right
55 13 right
56 5 right
57 13 right
58 13.58 right
59 15.58 right
60 25 right
61 20 right
62 14 right
63 13 right
64 14 right
65 13.3 right
66 19 right
67 13 right
68 10 right
69 15 right
70 14 right
71 19.4 right
72 12.8 right
73 13.5 right
74 19.31 right
75 27.5 right
76 13.1 right
77 23.6 right
78 15 right
79 18.7 right
80 18 right
81 12.7 right
82 40.3 right
83 12.86 right
84 22.9 right
85 10 right
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87 12 right
88 19 right
89 39.8 right
90 20 both
91 20 both
92 15 both
93 19 both
94 13 both
95 7 both
96 15 both
97 17.3 both
98 12 both
99 23 both
100 11.26 both
101 35.66 both
102 13.54 both
103 27.81 both
104 16.83 both
105 17.13 both
106 17.8 both
107 39 both
108 11 both
109 13.6 both
110 21.7 both
111 14.25 both
112 12 both
113 12.9 both
114 12.35 both

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import pandas as pd
import numpy as np
filename_participants = "res/full_participant_measurement.csv"
filename_left = "res/flowrate_left.csv"
filename_right = "res/flowrate_right.csv"
filename_both = "res/flowrate_both.csv"
arrival_rate = 1 / 36.66 # Measured
def get_response_time_and_utilization(S, arrival_rate):
df = pd.read_csv(filename_participants)
E_S = S.mean()
E_S2 = (S**2).mean()
utilization = arrival_rate * E_S
W = E_S + (arrival_rate * E_S2) / 2*(1 - utilization)
return W, utilization
def print_response_time():
df = pd.read_csv(filename_participants)
S = df["time"]
W, rho = get_response_time_and_utilization(S, arrival_rate)
print(f"//")
print(f"// Response time")
print(f"// ")
print(f" E{{S}} = {S.mean():.3f} s")
print(f"1/lambda = {1/arrival_rate:.3f} s")
print(f" rho = {rho:.3f}")
print(f" W = {W:.3f} s")
def print_best_achievable_response_time():
# Get mean flowrates
df_left = pd.read_csv(filename_left)
df_right = pd.read_csv(filename_right)
df_both = pd.read_csv(filename_both)
flowrate_left = np.mean(np.array(df_left["flowrate"]))
flowrate_right = np.mean(np.array(df_right["flowrate"]))
flowrate_both = np.mean(np.array(df_both["flowrate"]))
# Convert service times to what they would be with the best strategy
df_part = pd.read_csv(filename_participants)
times_left = np.array(df_part[df_part["button"] == "left"]["time"])
times_right = np.array(df_part[df_part["button"] == "right"]["time"])
times_both = np.array(df_part[df_part["button"] == "both"]["time"])
sizes_left = times_left * flowrate_left
sizes_right = times_right * flowrate_right
sizes_both = times_both * flowrate_both
sizes = np.concatenate([sizes_left, sizes_right, sizes_both])
S = sizes / flowrate_right
# Calculate response time
W, rho = get_response_time_and_utilization(S, arrival_rate)
print(f"//")
print(f"// Best possible response time")
print(f"// ")
print(f" E{{S}} = {S.mean():.3f} s")
print(f"1/lambda = {1/arrival_rate:.3f} s")
print(f" rho = {rho:.3f}")
print(f" W = {W:.3f} s")
def main():
print_response_time()
print_best_achievable_response_time()
if __name__ == "__main__":
main()

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@@ -0,0 +1,45 @@
import numpy as np
import pandas as pd
filename_participants = "res/full_participant_measurement.csv"
filename_left = "res/flowrate_left.csv"
filename_right = "res/flowrate_right.csv"
filename_both = "res/flowrate_both.csv"
def main():
# Get bottle fillup times
df_part = pd.read_csv(filename_participants)
times_left = np.array(df_part[df_part["button"] == "left"]["time"])
times_right = np.array(df_part[df_part["button"] == "right"]["time"])
times_both = np.array(df_part[df_part["button"] == "both"]["time"])
# Get mean flowrates
df_left = pd.read_csv(filename_left)
df_right = pd.read_csv(filename_right)
df_both = pd.read_csv(filename_both)
flowrate_left = np.mean(np.array(df_left["flowrate"]))
flowrate_right = np.mean(np.array(df_right["flowrate"]))
flowrate_both = np.mean(np.array(df_both["flowrate"]))
# Calculate mean bottle size
sizes_left = times_left * flowrate_left
sizes_right = times_right * flowrate_right
sizes_both = times_both * flowrate_both
sizes = np.concatenate([sizes_left, sizes_right, sizes_both])
mean_size = np.mean(sizes)
print(f"Mean bottle size: {mean_size}")
if __name__ == "__main__":
main()

View File

@@ -16,7 +16,7 @@ def main():
flowrate_right = np.array(df_right["flowrate"]) flowrate_right = np.array(df_right["flowrate"])
df_both = pd.read_csv(filename_both) df_both = pd.read_csv(filename_both)
flowrate_both = np.array(df_right["flowrate"]) flowrate_both = np.array(df_both["flowrate"])
U_lr, p_lr = mannwhitneyu(flowrate_left, flowrate_both, method="exact") U_lr, p_lr = mannwhitneyu(flowrate_left, flowrate_both, method="exact")
U_rb, p_rb = mannwhitneyu(flowrate_right, flowrate_both, method="exact") U_rb, p_rb = mannwhitneyu(flowrate_right, flowrate_both, method="exact")