Computer Science in Sport: Research and Practice by Arnold Baca

By Arnold Baca

Computers are a essentially very important instrument in activity technological know-how examine, activities functionality research and, more and more, in training and schooling programmes in game. This publication defines the sphere of ‘sport informatics’, explaining how desktop technological know-how can be utilized to unravel sport-related difficulties, in either learn and utilized aspects.

Beginning with a transparent rationalization of the useful rules of and software program, the booklet examines the main useful parts during which laptop technological know-how is hired in activity, including:

  • knowledge discovery and database development
  • data acquisition, together with units for measuring functionality data
  • motion monitoring and research systems
  • modelling and simulation
  • match research systems
  • e-learning and multimedia in activities education

Bridging the distance among idea and perform, this e-book is critical studying for any scholar, researcher or practitioner operating in game technology, recreation functionality research, learn tools in recreation, utilized laptop technology or informatics.

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Additional resources for Computer Science in Sport: Research and Practice

Sample text

2009). ‘That “Internet of Things” thing. In the real world things matter more than ideas’. 4986> (accessed 3 March 2014). S. (2012) Information Theory and Evolution, 2nd edn, Singapore: World Scientific. Dabnichki, P. (2006) ‘The future synergy of computer modelling and smart technologies in sport’, in A. Baca, L. Katz, j. Perl and O. Spaniol (eds) Computer Science in Sport. Dagstuhl Seminar Proceedings, Germany: Schloss Dagstuhl. james, I. (2009). ‘Claude Elwood Shannon. 30 April 1916 – 24 February 2001’, Biographical Memoirs of Fellows of the Royal Society, 55: 257–265.

The expert system that they produced had: • • • • a carefully designed, inviting user interface; a powerful knowledge base; an extensive IF–THEN rule inference engine; a recommendation system. The overall aim of this expert system was to optimize athletes’ availability for training and competition. The knowledge base and inference engine were designed to identify any high risks to athlete well-being by monitoring the catabolic effects of exercise. It was anticipated that this system would identify prospective risks to athletes and enable coaches, sport scientists and physiotherapists to manage any potential or actual injury.

The spreadsheet created by the organization has eight fields: ID, Name, Membership Number, Qualification Name, Qualification Achieved, Qualification Expires, Assessor‘s Name, Training Provider’s Name. (ID is the first field and is generated automatically. ) No data entry is made until each field is confirmed manually and all entries are double-checked. No data entry can be initiated unless payment is received. An example of a record created by the organization following this process is: ID Name Membership Number Qualification Name Qualification Achieved Qualification Expires Assessor‘s Name Training Provider‘s Name 1 john Draw 01234 Flat-water Instructor 2014-01-01 2017-12-31 jane Sweep UCan2 Databases and expert systems 35 The data protocol for each field is defined as: ID Name Membership Number Qualification Name Qualification Achieved Qualification Expires Assessor‘s Name Training Provider‘s Name Unique number Full name Number Full word title YYYY-MM-DD YYYY-MM-DD Full name Full word title This spreadsheet has worked well for the organization.

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