Theory and Practice of Mathematics and Computer Science Vol. 1
Synopsis
This book covers all areas of mathematics and computer science. The contributions by the authors include bivariate normal distribution; Morgenstern type bivariate logistic distribution; Morgenstern type bivariate exponential distribution; best linear unbiased estimation; coefficient of variation; concomitants of record values; logical reads; numeric data type; SQL performance; textual data type; DBMS; information retrieval; polynomial; polar derivative of a polynomial; maximum modulus; operating system; disk scheduling; seek time; average seek time; FCFS; IFCFS; polynomial Inequalities; maximum modulus; map reduce; Hadoop; distributed computing; SkorohodWichura theorem; weak convergence of probability measure; product spaces; arbitrary products; complete spaces; moment problems; ordered HahnBanach theorem version; probability measures characterizations by moments; weak convergence using moments; RiemannStieltjes integral; LebesgueStieltjes integral; jump points and functions; integrability; integral formulas; Standard Brownian motion; Kolmogorov existence theorem; dyadic numbers; sequential construction; linear and circular consecutivekoutofn system; reliability function; failure rate; shock model; normal distribution; logistic distribution; double exponential distribution; best linear unbiased estimation; coefficient of variation; order statistics; Ustatistic estimator; majority judgment; meanmedian compromise method etc. This book contains various materials suitable for students, researchers and academicians in the field of mathematics and computer science.
Chapters

Chapter 1Estimation of a Parameter of Certain Bivariate Distributions with Equal Coefficients of Variation by Concomitants of Record Values

Chapter 2Evaluation of Arithmetic Searches over String Searches for Better Performance

Chapter 3Selection of Table Scan or Seek Scan on the Basis of Data Size to Reduce Number of Logical Reads

Chapter 4Extensions of Bernstein Type Inequalities of a Polynomial to Polar Derivative

Chapter 5An Experimental Approach to Improve the Performance of FCFS Disk Scheduling Algorithm

Chapter 6Higher Power Growth of Polynomials with Prescribed Zeros

Chapter 7An Experimental Implementation of Map Reduce on the Hadoop for Analyzing Big Data

Chapter 8A Detailed and Direct Proof of SkorohodWichura's Theorem

Chapter 9A Recent and Modern Approach to The Moment Problem on R

Chapter 10A Comparative study between RiemannStieltjes and LebesgueStieltjes Integration using Discrete Distribution Functions

Chapter 11Study on A Direct Construction of the Standard Brownian Motion

Chapter 12Studies on Reliability of Linear and Circular Consecutivekoutofn Systems with Shock Model

Chapter 13Estimation of the Parameter of Certain Distributions with Known Coefficient of Variation by UStatistics

Chapter 14Hybridizing Median and Average for Measuring, Electing and Ranking Candidates