Predicting Performance Ratings Using Motivational Antecedents
Author : Michelle M. Zazanis
Publisher :
Page : 86 pages
File Size : 15,12 MB
Release : 1998
Category : Motivation (Psychology)
ISBN :
Author : Michelle M. Zazanis
Publisher :
Page : 86 pages
File Size : 15,12 MB
Release : 1998
Category : Motivation (Psychology)
ISBN :
Author : Alois T. Sutor
Publisher :
Page : 706 pages
File Size : 40,12 MB
Release : 1951
Category : Airplanes
ISBN :
Analytical expressions are derived to show the geometric, thermodynamic, and aerodynamic relations among compressor, turbine, and exhaust nozzle for a gas-turbine engine. For a known compressor performance map, a matching method is described to show some of the design compromises that must be made when the components are to be combined into a turbine-propeller engine. A method of predicting engine performance for a range of operating conditions from known component maps is presented. An illustrative example of the matching method and the performance analysis is presented, showing some of the practical limitations of engine operation.
Author : Lorena Martin
Publisher : FT Press
Page : 561 pages
File Size : 29,9 MB
Release : 2016-02-03
Category : Business & Economics
ISBN : 0134193881
A PRACTICAL, REAL-WORLD GUIDE TO ANALYTICS FOR THE 5 MAJOR SPORTS: FOOTBALL, BASKETBALL, BASEBALL, SOCCER, AND TENNIS GAIN A COMPETITIVE EDGE! This is the first real-world guide to building and using analytical models for measuring and assessing performance in the five major sports: football, basketball, baseball, soccer, and tennis. Unlike books that focus strictly on theory, this book brings together sports measurement and statistical analyses, demonstrating how to examine differences across sports as well as between player positions. This book will provide you with the tools for cutting-edge approaches you can extend to the sport of your choice. Expert Northwestern University data scientist, UC San Diego researcher, and competitive athlete, Lorena Martin shows how to use measures and apply statistical models to evaluate players, reduce injuries, and improve sports performance. You’ll learn how to leverage a deep understanding of each sport’s principles, rules, attributes, measures, and performance outcomes. Sports Performance Measurement and Analytics will be an indispensable resource for anyone who wants to bring analytical rigor to athletic competition: students, professors, analysts, fans, physiologists, coaches, managers, and sports executives alike. All data sets, extensive code, and additional examples are available for download at http://www.ftpress.com/martin/ What are the qualities a person must have to become a world-class athlete? This question and many more can be answered through research, measurement, statistics, and analytics. This book gives athletes, trainers, coaches, and managers a better understanding of measurement and analytics as they relate to sports performance. To develop accurate measures, we need to know what we want to measure and why. There is great power in accurate measures and statistics. Research findings can show us how to prevent injuries, evaluate strengths and weaknesses, improve team cohesion, and optimize sports performance. This book serves many readers. People involved with sports will gain an appreciation for performance measures and analytics. People involved with analytics will gain new insights into quantified values representing physical, physiological, and psychological components of sports performance. And students eager to learn about sports analytics will have a practical introduction to the field. This is a thorough introduction to performance measurement and analytics for five of the world’s leading sports. The only book of its kind, it offers a complete overview of the most important concepts, rules, measurements, and statistics for each sport, while demonstrating applications of real-world analytics. You’ll find practical, state-of-the-art guidance on predicting future outcomes, evaluating an athlete’s market value, and more.
Author : Robert M. Losee
Publisher : Springer Nature
Page : 59 pages
File Size : 35,10 MB
Release : 2022-05-31
Category : Computers
ISBN : 303102317X
Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a measure that can be applied retrospectively or can be predicted, performance of a system using a single term can be predicted given several different types of probabilistic distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and is understood. These predictive models may be applied to realistic problems, and then the results may be used to validate the accuracy of the methods used. The application of metadata or index labels can be used to determine whether or not these features should be used in particular cases. Linguistic information, such as part-of-speech tag information, can increase the discrimination value of existing terminology and can be studied predictively. This work provides methods for measuring performance that may be used predictively. Means of predicting these performance measures are provided, both for the simple case of a single term in the query and for multiple terms. Methods of applying these formulae are also suggested.
Author : United States. Adjutant-General's Office
Publisher :
Page : 32 pages
File Size : 45,53 MB
Release : 1959
Category : Ability
ISBN :
Author : Henry H. Busciglio
Publisher :
Page : 42 pages
File Size : 42,84 MB
Release : 1994
Category : Map reading
ISBN :
Author : C. H. Walkinshaw
Publisher :
Page : 10 pages
File Size : 24,34 MB
Release : 1980
Category : Pine
ISBN :
Author : Michael Kuperberg
Publisher : KIT Scientific Publishing
Page : 442 pages
File Size : 47,44 MB
Release : 2014-09
Category : Computers
ISBN : 3866447418
The performance of software components depends on several factors, including the execution platform on which the software components run. To simplify cross-platform performance prediction in relocation and sizing scenarios, a novel approach is introduced in this thesis which separates the application performance profile from the platform performance profile. The approach is evaluated using transparent instrumentation of Java applications and with automated benchmarks for Java Virtual Machines.
Author : George K. Serovy
Publisher :
Page : 42 pages
File Size : 16,85 MB
Release : 1959
Category : Mach number
ISBN :
Author : David A. Campshure
Publisher :
Page : 76 pages
File Size : 20,90 MB
Release : 1990
Category : Tank crews
ISBN :