Mathematical Theory of the Influence of a Dome on the Directivity Pattern of Sound Beams, Part 4
Algebra; an Elementary Text-book for the Higher Classes of Secondary Schools and for Colleges
An Empirical Study of Re-Sampling Techniques as a Method for Improving Error Estimates in Split-Plot Designs
Using the Kth Nearest Neighbor Clustering Procedure to Determine the Number of Subpopulations
A Group Theoretic Tabu Search Approach to the Traveling Salesman Problem
A Treatise on Plane Trigonometry, Containing an Account of Hyperbolic Functions; With Numerous Examples
Pattern Search Ranking and Selection Algorithms for Mixed-Variable Optimization of Stochastic Systems
Pattern Search Ranking and Selection Algorithms for Mixed-Variable Optimization of Stochastic Systems
An Empirical Study of Re-Sampling Techniques as a Method for Improving Error Estimates in Split-Plot Designs
Exercises and Solutions in Probability and Statistics
The book contains hundreds of engaging, class-tested statistics exercises (and detailed solutions) that test students' understanding of the material. Many are educational in their own right--for example, baseball managers who played professional ball were often catchers; stocks that are deleted from the Dow Jones Industrial Average have generally done better than the stocks that replaced them; athletes may not get hot hands but they often get warm hands with modest improvements in their success probabilities.
Mathematical Inequalities Volume 5
This is Volume 5 of the five-volume book Mathematical Inequalities, which introduces and develops the main types of elementary inequalities. The first three volumes are a great opportunity to look into many old and new inequalities, as well as elementary procedures for solving them: Volume 1 - Symmetric Polynomial Inequalities, Volume 2 - Symmetric Rational and Nonrational Inequalities, Volume 3 - Cyclic and Noncyclic Inequalities. As a rule, the inequalities in these volumes are increasingly ordered according to the number of variables: two, three, four, ..., n-variables. The last two volumes (Volume 4 - Extensions and Refinements of Jensen's Inequality, Volume 5 - Other Recent Methods for Creating and Solving Inequalities) present beautiful and original methods for solving inequalities, such as Half/Partial convex function method, Equal variables method, Arithmetic compensation method, Highest coefficient cancellation method, pqr method etc. The book is intended for a wide audience: advanced middle school students, high school students, college and university students, and teachers. Many problems and methods can be used as group projects for advanced high school students.
Mathematical Inequalities Volume 1
This is Volume 1 of the five-volume book Mathematical Inequalities, that introduces and develops the main types of elementary inequalities. The first three volumes are a great opportunity to look into many old and new inequalities, as well as elementary procedures for solving them: Volume 1 - Symmetric Polynomial Inequalities, Volume 2 - Symmetric Rational and Nonrational Inequalities, Volume 3 - Cyclic and Noncyclic Inequalities. As a rule, the inequalities in these volumes are increasingly ordered according to the number of variables: two, three, four, ..., n-variables. The last two volumes (Volume 4 - Extensions and Refinements of Jensen's Inequality, Volume 5 - Other Recent Methods for Creating and Solving Inequalities) present beautiful and original methods for solving inequalities, such as Half/Partial convex function method, Equal variables method, Arithmetic compensation method, Highest coefficient cancellation method, pqr method etc. The book is intended for a wide audience: advanced middle school students, high school students, college and university students, and teachers. Many problems and methods can be used as group projects for advanced high school students.
Exercises and Solutions in Probability and Statistics
The book contains hundreds of engaging, class-tested statistics exercises (and detailed solutions) that test students' understanding of the material. Many are educational in their own right--for example, baseball managers who played professional ball were often catchers; stocks that are deleted from the Dow Jones Industrial Average have generally done better than the stocks that replaced them; athletes may not get hot hands but they often get warm hands with modest improvements in their success probabilities.
Risk and Predictive Analytics in Business with R
Supply chain operations face many risks, including political, environmental, and economic. The past five years have seen major challenges, from pandemic, impacts of global warming, wars, and tariff impositions. In this rapidly changing world, risks appear in every aspect of operations. This book presents data mining and analytics tools with R programming as well as a brief presentation of Monte Carlo simulation that can be used to anticipate and manage these risks. RStudio software and R programming language are widely used in data mining. For Monte Carlo simulation applications we cover Crystal Ball software, one of a number of commercially available Monte Carlo simulation tools.Chapter 1 of this book deals with classification of risks. It includes a typical supply chain example published in academic literature. Chapter 2 gives a brief introduction to R programming. It is not intended to be comprehensive, but sufficient for a user to get started using this free open source and highly popular analytics tool. Chapter 3 discusses risks commonly found in finance, to include basic data mining tools applied to analysis of credit card fraud data. Like the other datasets used in the book, this data comes from the Kaggle.com site, a free site loaded with realistic datasets. The remainder of the book covers risk analytics tools. Chapter 4 presents R association rule modeling using a supply chain related dataset. Chapter 5 presents Monte Carlo simulation of some supply chain risk situations. Chapter 6 gives both time series and multiple regression prediction models as well as autoregressive integrated moving average (ARIMA; Box-Jenkins) models in SAS and R. Chapter 7 covers classification models demonstrated with credit risk data. Chapter 8 deals with fraud detection and the common problem of modeling imbalanced datasets. Chapter 9 introduces Na簿ve Bayes modeling with categorical data using an employee attrition dataset.Features: Overview of predictive analytics presented in an understandable manner Presentation of useful business applications of predictive data mining Coverage of risk management in finance, insurance, and supply chain contexts Presentation of predictive models Demonstration of using these predictive models in R Screenshots enabling readers to develop their own models The purpose of the book is to present tools useful to analyze risks, especially those faced in supply chain management and finance.
Scientific Research and Methodology
This textbook is designed for teaching quantitative research in the scientific, health and engineering disciplines at first-year undergraduate level, with an emphasis on statistics. It covers the research process, including asking research questions, research design, data collection, summarising data, analysis and communication. Many real journal articles are used throughout the text as examples that demonstrate the use of the techniques.Students are introduced to statistics as a method for answering questions. Descriptive research questions lead to analysis of single proportions and means. Repeated-measures research questions are answered using paired quantitative data. Relational research questions compare proportions, odds and means in different groups. Correlational research questions are studied using correlation and regression techniques.Statistical topics include numerical summary methods (such as means, odds ratios and identification of outliers), graphing (such as histograms, case-profile plots and scatterplots), confidence intervals and hypothesis testing. Emphasis is placed on understanding and concepts; while calculations are shown in simple situations, they are deferred to software when the computations become tedious and disruptive to understanding.Almost every dataset used is a real dataset, and is available online or in an associated R package SRMData. Software output is often used when calculations become onerous. The output is sufficiently generic that the book can be used in conjunction with any statistical software.
Mathematical Inequalities Volume 2
This is Volume 2 of the five-volume book Mathematical Inequalities, which introduces and develops the main types of elementary inequalities. The first three volumes are a great opportunity to look into many old and new inequalities, as well as elementary procedures for solving them: Volume 1 - Symmetric Polynomial Inequalities, Volume 2 - Symmetric Rational and Nonrational Inequalities, Volume 3 - Cyclic and Noncyclic Inequalities. As a rule, the inequalities in these volumes are increasingly ordered according to the number of variables: two, three, four, ..., n-variables. The last two volumes (Volume 4 - Extensions and Refinements of Jensen's Inequality, Volume 5 - Other Recent Methods for Creating and Solving Inequalities) present beautiful and original methods for solving inequalities, such as Half/Partial convex function method, Equal variables method, Arithmetic compensation method, Highest coefficient cancellation method, pqr method etc. The book is intended for a wide audience: advanced middle school students, high school students, college and university students, and teachers. Many problems and methods can be used as group projects for advanced high school students.
Proof Complexity Generators
The P vs. NP problem is one of the fundamental problems of mathematics. It asks whether propositional tautologies can be recognized by a polynomial-time algorithm. The problem would be solved in the negative if one could show that there are propositional tautologies that are very hard to prove, no matter how powerful the proof system you use. This is the foundational problem (the NP vs. coNP problem) of proof complexity, an area linking mathematical logic and computational complexity theory. Written by a leading expert in the field, this book presents a theory for constructing such hard tautologies. It introduces the theory step by step, starting with the historic background and a motivational problem in bounded arithmetic, before taking the reader on a tour of various vistas of the field. Finally, it formulates several research problems to highlight new avenues of research.
Variational and Information Flows in Machine Learning and Optimal Transport
The Asymptotic Behavior of Porous Systems
This book presents a rigorous and comprehensive treatment of the mathematical theory and real-world applications of porous systems, with a special focus on their asymptotic behavior. It combines analytical, numerical, and computational perspectives to bridge fundamental science and engineering applications, making it relevant to mathematicians, physicists, engineers, and material scientists. It also synthesizes the mathematical foundations, modeling strategies, and engineering practices of porous media systems with asymptotic behavior as a unifying theme, which empowers the readers to model, analyze, and design next-generation porous systems across diverse disciplines.
A New Method of Time Series Forecast
This book determines the trend and variability of a time series data, focused on traditional time series models forecast analysis and their volatility and also focuses on a comparative study of different existing individual and combination forecasts with a proposed Hybrid Stochastic Model (HSM) forecast procedure. For this considered a hydrological time series data of the Indian subcontinent to test the proposed forecast model, and also examined the model's dimension reduction approach to choose an optimum number of forecast techniques to be included in the model to yield the best forecasts.
