Electronic Signatures of Products – Barcodesĥ.5.2. Computer Augmented Reality and Its Use in Industryĥ.5.1. Computer 3D Visualisations and Virtual Realityĥ.4.2. Prediction Using Past Stock Market Values in the Financial Industryĥ.4.1. Computer Control System Terminologyĥ.3.3. Prediction Using Sensor Data in Process Control Operationsĥ.3.2. PREDICTION IN PLAYER PERFORMANCE AND TEAM TRACKINGĥ.3.1. Track Prediction in Football and Application to Gamingĥ.2. Sports Analytics and Prediction – Baseballĥ.1.4. Track Prediction during Tennis Gamesĥ.1.3. PRESENT-DAY SPORTS (CRICKET, TENNIS, BASEBALL, AND FOOTBALL TECHNOLOGY)ĥ.1.1. Bayes’ Theorem of Probability or ChanceĬHAPTER 5: Track Prediction in Sports and Industryĥ.1. Probability of a Prediction Being CorrectĤ.3.5. Regression and Least Squares (Best Fit)Ĥ.3.4. BASIC REGRESSION ANALYSIS AND PREDICTIONS OF FUTURE DATAĤ.3.1. Average versus Mean, versus RMS TrackĤ.3. UNDERSTANDING THE MEANING OF AVERAGE TRACKĤ.1.1. Application of Correlation in IndustryĬHAPTER 4: Average Track and Prediction of Future LocationĤ.1. Application of Correlation to EM Fields (Credit Card or Door Key)ģ.4.4. Application of Correlation to Soundģ.4.3. Application of Correlation to Pictures (Face in the Crowd)ģ.4.2. CORRELATION APPLICATIONS AND USE IN SECURITY DEVICES – FROM CROWDS TO EYEBALLSģ.4.1. EM Data Scanning for Financial and Other Transactionsģ.4.
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Facial Recognition (on a TV or Monitor Screen)ģ.3.2. APPLICATION USING A PIXELATED-MATRIX DISPLAYģ.3.1. Increasing Resolution through Pixel Mixingģ.3. Effect of Higher Sample Rate on Accuracy of Correlationsģ.2.4.
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Flagging a Good Number Series Correlation versus a Weak Correlationģ.2.3. Simple Correlation of Two Sets of Numbers – Recognition of a Wavy Line Is Simpleģ.2.2. Rebuilding the Analogue Graphic Using a Digital Number Series (DAC)ģ.2.1. Bit Resolution, Formats, and Storageģ.1.5. Higher Sampling Rate of Bits versus Accuracyģ.1.4. Number Systems Using BITS and BYTESģ.1.3. Basics of Data Analysis – the Time Seriesģ.1.2. INTRODUCTION TO NUMBER (DATA) REPRESENTATIONģ.1.1. Tracking in 3D from Multiple Observation PointsĬHAPTER 3: Pattern Recognition and Its Applicationsģ.1. CALCULATING POSITION FROM THE TV SCREEN VIEWĢ.2.1. Calculating Speed (Velocity) of a Moving Object Using Multiple Fixed CamerasĢ.1.3. Animations of a Moving Object Using Multiple Fixed CamerasĢ.1.2. Basics of Clock Rate (aka Timing Frequency or Sample Speed)ĬHAPTER 2: Tracking and Triangulation: It’s SimpleĢ.1.1. What You Can See (and Hear) – Is Not What You Always Getġ.4.3. Use of the Frequency Spectrum – More Than Just Coloursġ.4.2. FREQUENCY AND THE BASICS OF SAMPLING SPEEDġ.4.1. The Physics from Analogue TV to Smart Viewing – LED, QLED, LCD, OLEDġ.3.3. Basic History of Technology Development Leading to Data Analyticsġ.3.2. BASIC PHYSICS OF EVERYDAY TECHNOLOGY INNOVATIONSġ.3.1. Introduction to New Technology Analyticsġ.3. APPLICATION OF NEW TECHNOLOGIES IN SPORT AND INDUSTRYġ.2.1. Why STEM and Analytics Have Become Importantġ.2. What Is Network Speed, 3G, 4G, 5G, Wifi, and Bluetooth?ġ.1.3. OVERVIEW OF BASIC TECHNOLOGY AND WHY THE RAPID INCREASE IN NETWORK SPEED IS IMPORTANTġ.1.2.
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