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Proceedings of the 11th International Symposium on Computer Science in Sport (IACSS 2017)

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Table of Contents

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    Book Overview
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    Chapter 1 An Empirical Analysis on European Odds of English Premier League
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    Chapter 2 Study on the “Hot Match” Effect in Professional Football Leagues
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    Chapter 3 Artificial Neural Networks Predicting the Outcome of a Throwing Task – Effects of Input Quantity and Quality
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    Chapter 4 Activity Recognition of Local Muscular Endurance (LME) Exercises Using an Inertial Sensor
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    Chapter 5 Gait Stability During Shod and Barefoot Walking and Running on a Treadmill Assessed by Correlation Entropy
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    Chapter 6 Statistical Models for Predicting Short-Term HR Responses to Submaximal Interval Exercise
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    Chapter 7 Information Systems for Top-Level Football with Focus on Performance Analysis and Healthy Reference Patterns
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    Chapter 8 Development of Real-Time Analysis System of Match Playing Time for Water Polo Player
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    Chapter 9 Reconstruction of 3D Ball/Shuttle Position by Two Image Points from a Single View
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    Chapter 10 A Comparison of Smoothing and Filtering Approaches Using Simulated Kinematic Data of Human Movements
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    Chapter 11 How to Accurately Determine the Position on a Known Course in Road Cycling
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    Chapter 12 Missing Depth Cues in Virtual Reality Decrease Performance of Three-Dimensional Reaching Movements
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    Chapter 13 Development of an Autonomous Character in Karate Kumite
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    Chapter 14 Students’ Use of and Attitudes Towards Information and Communication Technologies in Sport Education Cross-Sectional Surveys Over the Past 15 Years
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    Chapter 15 BIMROB – Bidirectional Interaction Between Human and Robot for the Learning of Movements
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    Chapter 16 A Novel Multilocus Genetic Model Can Predict Muscle Fibers Composition
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    Chapter 17 Erratum to: Information Systems for Top-Level Football with Focus on Performance Analysis and Healthy Reference Patterns
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Title
Proceedings of the 11th International Symposium on Computer Science in Sport (IACSS 2017)
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-67846-7
ISBNs
978-3-31-967845-0, 978-3-31-967846-7
Editors

Martin Lames, Dietmar Saupe, Josef Wiemeyer

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 13%
Student > Ph. D. Student 1 7%
Student > Master 1 7%
Unknown 11 73%
Readers by discipline Count As %
Engineering 3 20%
Biochemistry, Genetics and Molecular Biology 1 7%
Unknown 11 73%