Atnaujinkite slapukų nuostatas

El. knyga: Proceedings of the 9th International Performance Analysis Workshop and Conference & 5th IACSS Conference

Edited by , Edited by , Edited by , Edited by , Edited by

DRM apribojimai

  • Kopijuoti:

    neleidžiama

  • Spausdinti:

    neleidžiama

  • El. knygos naudojimas:

    Skaitmeninių teisių valdymas (DRM)
    Leidykla pateikė šią knygą šifruota forma, o tai reiškia, kad norint ją atrakinti ir perskaityti reikia įdiegti nemokamą programinę įrangą. Norint skaityti šią el. knygą, turite susikurti Adobe ID . Daugiau informacijos  čia. El. knygą galima atsisiųsti į 6 įrenginius (vienas vartotojas su tuo pačiu Adobe ID).

    Reikalinga programinė įranga
    Norint skaityti šią el. knygą mobiliajame įrenginyje (telefone ar planšetiniame kompiuteryje), turite įdiegti šią nemokamą programėlę: PocketBook Reader (iOS / Android)

    Norint skaityti šią el. knygą asmeniniame arba „Mac“ kompiuteryje, Jums reikalinga  Adobe Digital Editions “ (tai nemokama programa, specialiai sukurta el. knygoms. Tai nėra tas pats, kas „Adobe Reader“, kurią tikriausiai jau turite savo kompiuteryje.)

    Negalite skaityti šios el. knygos naudodami „Amazon Kindle“.

This covers the PACSS 2021 which approached interdisciplinary collaboration between theoretical computer science and practical performance analysis though an online workshop and conference. Readers find in this book the peer-reviewed and discussed evidences on how computer scientists and performance analysts can and have worked together to solve both applied and research-based problems in elite sport, using the methods of computer science. In this edition, we organize the content according to four major topics: machine learning, text mining, best practice and interdisciplinary collaboration. This is a refined material written by leading experts with up-to-date overview of research in the multidisciplinary field of computer science and elite sport performance analysis.

Text mining and performance analysis.- Match Analysis 4.0 with Big Data: From Studies to Experiments.- Using machine learning to assess and compare athletes in team sports.- Kick it to Me, or Maybe Not - How Player Roles Affect AFL Possessions.- Predicting and understanding Australian Rules Football using Markov processes.- Exercise Evaluation using Time-of-Flight Image Data.- Improving springboard diving video classification accuracy through cumulated segment values.- How Sports Scientists Explain Their Choice of Wearable.- Physical and motivational effects of Exer-games in healthy adults: Overview of Reviews.- The Impact of Order of Performance on Peer-to-Peer Learning of a Lacrosse Ball Pick-Up Skill Through Video Analysis with University Students.