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Fundamental Physics and Physics Education Research (Springer Proceedings In Physics Ser. #145)
by Burra G. Sidharth Jesús Carnicer Murillo Marisa Michelini Carmen PereaThis book highlights selected contributions presented at the 15th annual international symposium Frontiers of Fundamental Physics (FFP15), with the aim of informing readers about the most important recent advances in fundamental physics and physics education research. The FFP series offers a platform for physicists from around the world to present their latest theories and findings. The latest symposium was held in Orihuela, Spain and covered diverse fields of research, including gravitation, astronomy and astrophysics, physics of complex systems, high-energy physics, and mathematical physics. Considerable attention was also paid to physics education research, teacher education in physics, and the popularization of physics. In a knowledge-based society, research into fundamental physics plays a vital role in both the advancement of human knowledge and the development of new technologies. Presenting valuable new peer-reviewed contributions submitted from 15 countries, this book will appeal to a broad audience of scholars and researchers.
The Fundamental Rules of Risk Management
by Nigel LewisThe consequences of taking on risk can be ruinous to personal finances, professional careers, corporate survivability, and even nation states. Yet many risk managers do not have a clear understanding of the basics. Requiring no statistical or mathematical background, The Fundamental Rules of Risk Management gives you the knowledge to successfully h
Fundamental Solutions of Linear Partial Differential Operators
by Norbert Ortner Peter WagnerThis monograph provides the theoretical foundations needed for the construction of fundamental solutions and fundamental matrices of (systems of) linear partial differential equations. Many illustrative examples also show techniques for finding such solutions in terms of integrals. Particular attention is given to developing the fundamentals of distribution theory, accompanied by calculations of fundamental solutions. The main part of the book deals with existence theorems and uniqueness criteria, the method of parameter integration, the investigation of quasihyperbolic systems by means of Fourier and Laplace transforms, and the representation of fundamental solutions of homogeneous elliptic operators with the help of Abelian integrals. In addition to rigorous distributional derivations and verifications of fundamental solutions, the book also shows how to construct fundamental solutions (matrices) of many physically relevant operators (systems), in elasticity, thermoelasticity, hexagonal/cubic elastodynamics, for Maxwell's system and others. The book mainly addresses researchers and lecturers who work with partial differential equations. However, it also offers a valuable resource for students with a solid background in vector calculus, complex analysis and functional analysis.
Fundamental Statistical Inference: A Computational Approach (Wiley Series in Probability and Statistics)
by Marc S. PaolellaA hands-on approach to statistical inference that addresses the latest developments in this ever-growing field This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation. It emphasizes details of the relevance of the material, intuition, and discussions with a view towards very modern statistical inference. In addition to classic subjects associated with mathematical statistics, topics include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and indirect inference. Practical examples of all methods are given. Estimation issues associated with the discrete mixtures of normal distribution, and their solutions, are developed in detail. Much emphasis throughout is on non-Gaussian distributions, including details on working with the stable Paretian distribution and fast calculation of the noncentral Student's t. An entire chapter is dedicated to optimization, including development of Hessian-based methods, as well as heuristic/genetic algorithms that do not require continuity, with MATLAB codes provided. The book includes both theory and nontechnical discussions, along with a substantial reference to the literature, with an emphasis on alternative, more modern approaches. The recent literature on the misuse of hypothesis testing and p-values for model selection is discussed, and emphasis is given to alternative model selection methods, though hypothesis testing of distributional assumptions is covered in detail, notably for the normal distribution. Presented in three parts—Essential Concepts in Statistics; Further Fundamental Concepts in Statistics; and Additional Topics—Fundamental Statistical Inference: A Computational Approach offers comprehensive chapters on: Introducing Point and Interval Estimation; Goodness of Fit and Hypothesis Testing; Likelihood; Numerical Optimization; Methods of Point Estimation; Q-Q Plots and Distribution Testing; Unbiased Point Estimation and Bias Reduction; Analytic Interval Estimation; Inference in a Heavy-Tailed Context; The Method of Indirect Inference; and, as an appendix, A Review of Fundamental Concepts in Probability Theory, the latter to keep the book self-contained, and giving material on some advanced subjects such as saddlepoint approximations, expected shortfall in finance, calculation with the stable Paretian distribution, and convergence theorems and proofs.
Fundamental Statistics for the Behavioral Sciences 8th Edition
by David C. HowellFUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES focuses on providing the context of statistics in behavioral research, while emphasizing the importance of looking at data before jumping into a test. This practical approach provides readers with an understanding of the logic behind the statistics, so they understand why and how certain methods are used--rather than simply carry out techniques by rote. Readers move beyond number crunching to discover the meaning of statistical results and appreciate how the statistical test to be employed relates to the research questions posed by an experiment. An abundance of real data and research studies provide a real-life perspective and help you understand concepts as you learn about the analysis of data.
Fundamental Statistics for the Social and Behavioral Sciences
by Howard T. TokunagaFundamental Statistics for the Social and Behavioral Sciences, Second Edition places statistics within the research process, illustrating how they are used to answer questions and test ideas. Students learn not only how to calculate statistics, but also how to interpret and communicate the results of statistical analyses in light of a study’s research hypothesis. Featuring accessible writing and well-integrated research examples, the book gives students a greater understanding of how research studies are conceived, conducted, and communicated. New and Proven Features Updated data sets and research examples address real-world issues and topics across the social and behavioral sciences, illustrating the use of statistical procedures to test research questions and hypotheses. Significantly expanded discussion of linear and multiple regression and correlation now gives regression its own separate chapter. Thorough presentation of formulas, hand calculations, and the presentation of visual data enable mastery of key techniques and prove especially helpful in flipped or online classes. In-chapter learning checks and end-of-chapter exercises give students an opportunity to continually assess their understanding. Screenshots of statistical calculations using IBM® SPSS® Statistics at the end of chapters help students learn to use SPSS software and interpret output. Original SAGE videos for each chapter, featuring author Howard K. Tokunaga, bring concepts to life and appeal to diverse learners.
Fundamental Statistics for the Social and Behavioral Sciences
by Howard T. TokunagaFundamental Statistics for the Social and Behavioral Sciences, Second Edition places statistics within the research process, illustrating how they are used to answer questions and test ideas. Students learn not only how to calculate statistics, but also how to interpret and communicate the results of statistical analyses in light of a study’s research hypothesis. Featuring accessible writing and well-integrated research examples, the book gives students a greater understanding of how research studies are conceived, conducted, and communicated. New and Proven Features Updated data sets and research examples address real-world issues and topics across the social and behavioral sciences, illustrating the use of statistical procedures to test research questions and hypotheses. Significantly expanded discussion of linear and multiple regression and correlation now gives regression its own separate chapter. Thorough presentation of formulas, hand calculations, and the presentation of visual data enable mastery of key techniques and prove especially helpful in flipped or online classes. In-chapter learning checks and end-of-chapter exercises give students an opportunity to continually assess their understanding. Screenshots of statistical calculations using IBM® SPSS® Statistics at the end of chapters help students learn to use SPSS software and interpret output. Original SAGE videos for each chapter, featuring author Howard K. Tokunaga, bring concepts to life and appeal to diverse learners.
Fundamentals of Abstract Algebra (Textbooks in Mathematics)
by Mark J. DeBonisFundamentals of Abstract Algebra is a primary textbook for a one year first course in Abstract Algebra, but it has much more to offer besides this. The book is full of opportunities for further, deeper reading, including explorations of interesting applications and more advanced topics, such as Galois theory. Replete with exercises and examples, the book is geared towards careful pedagogy and accessibility, and requires only minimal prerequisites. The book includes a primer on some basic mathematical concepts that will be useful for readers to understand, and in this sense the book is self-contained.Features Self-contained treatments of all topics Everything required for a one-year first course in Abstract Algebra, and could also be used as supplementary reading for a second course Copious exercises and examples Mark DeBonis received his PhD in Mathematics from the University of California, Irvine, USA. He began his career as a theoretical mathematician in the field of group theory and model theory, but in later years switched to applied mathematics, in particular to machine learning. He spent some time working for the US Department of Energy at Los Alamos National Lab as well as the US Department of Defense at the Defense Intelligence Agency, both as an applied mathematician of machine learning. He held a position as Associate Professor of Mathematics at Manhattan College in New York City, but later left to pursue research working for the US Department of Energy at Sandia National Laboratory as a Principal Data Analyst. His research interests include machine learning, statistics and computational algebra.
Fundamentals of Actuarial Mathematics
by S. David PromislowThis book provides a comprehensive introduction to actuarial mathematics, covering both deterministic and stochastic models of life contingencies, as well as more advanced topics such as risk theory, credibility theory and multi-state models. This new edition includes additional material on credibility theory, continuous time multi-state models, more complex types of contingent insurances, flexible contracts such as universal life, the risk measures VaR and TVaR. Key Features: Covers much of the syllabus material on the modeling examinations of the Society of Actuaries, Canadian Institute of Actuaries and the Casualty Actuarial Society. (SOA-CIA exams MLC and C, CSA exams 3L and 4.) Extensively revised and updated with new material. Orders the topics specifically to facilitate learning. Provides a streamlined approach to actuarial notation. Employs modern computational methods. Contains a variety of exercises, both computational and theoretical, together with answers, enabling use for self-study. An ideal text for students planning for a professional career as actuaries, providing a solid preparation for the modeling examinations of the major North American actuarial associations. Furthermore, this book is highly suitable reference for those wanting a sound introduction to the subject, and for those working in insurance, annuities and pensions.
Fundamentals of Actuarial Mathematics
by S. David PromislowThis book provides a comprehensive introduction to actuarial mathematics, covering both deterministic and stochastic models of life contingencies, as well as more advanced topics such as risk theory, credibility theory and multi-state models.This new edition includes additional material on credibility theory, continuous time multi-state models, more complex types of contingent insurances, flexible contracts such as universal life, the risk measures VaR and TVaR.Key Features:Covers much of the syllabus material on the modeling examinations of the Society of Actuaries, Canadian Institute of Actuaries and the Casualty Actuarial Society. (SOA-CIA exams MLC and C, CSA exams 3L and 4.)Extensively revised and updated with new material.Orders the topics specifically to facilitate learning.Provides a streamlined approach to actuarial notation.Employs modern computational methods.Contains a variety of exercises, both computational and theoretical, together with answers, enabling use for self-study.An ideal text for students planning for a professional career as actuaries, providing a solid preparation for the modeling examinations of the major North American actuarial associations. Furthermore, this book is highly suitable reference for those wanting a sound introduction to the subject, and for those working in insurance, annuities and pensions.
Fundamentals of Algebra Practice Book (Progress in Mathematics)
by Alfred S. Posamentier Catherine D. Le Tourneau Edward Wiliam Quinn*This textbook has been transcribed in UEB, formatted according to Braille textbook formats, proofread and corrected. <P><P> Progress in Mathematics 2009 Student Edition Practice Book Grade 7 In alignment with the Common Core State Standards, the scope and sequence of Fundamentals of Algebra is organized into bite-sized, manageable lessons allowing for deeper understanding of skills and concepts so students get the necessary skills for Algebra and beyond. Fundamentals of Algebra: • Focuses on conceptual development for all learners. • Builds knowledge lesson by lesson and across grade levels with coherent lessons. • Develops fluency and conceptual understanding in a multitude of ways. • Deepens understanding with vocabulary, cognitive rigor, and higher-level thinking skills. The Sourcebook allows students to focus on learning skills and concepts before moving onto independent practice in the Practice Book.
Fundamentals of Algebraic Microlocal Analysis (Chapman And Hall/crc Pure And Applied Mathematics Ser. #217)
by Goro Kato Daniele C Struppa"Provides a thorough introduction to the algebraic theory of systems of differential equations, as developed by the Japanese school of M. Sato and his colleagues. Features a complete review of hyperfunction-microfunction theory and the theory of D-modules. Strikes the perfect balance between analytic and algebraic aspects."
Fundamentals of Applied Multidimensional Scaling for Educational and Psychological Research
by Cody S. DingThis book explores the fundamentals of multidimensional scaling (MDS) and how this analytic method can be used in applied setting for educational and psychological research. The book tries to make MDS more accessible to a wider audience in terms of the language and examples that are more relevant to educational and psychological research and less technical so that the readers are not overwhelmed by equations. The goal is for readers to learn the methods described in this book and immediately start using MDS via available software programs. The book also examines new applications that have previously not been discussed in MDS literature. It should be an ideal book for graduate students and researchers to better understand MDS. Fundamentals of Applied Multidimensional Scaling for Educational and Psychological Research is divided into three parts. Part I covers the basic and fundamental features of MDS models pertaining to applied research applications. Chapters in this section cover the essential features of data that are typically associated with MDS analysis such as preference ration or binary choice data, and also looking at metric and non-metric MDS models to build a foundation for later discussion and applications in later chapters. Part II examines specific MDS models and its applications for education and psychology. This includes spatial analysis methods that can be used in MDS to test clustering effect of items and individual differences MDS model (INDSCAL). Finally, Part III focuses on new applications of MDS analysis in these research fields. These new applications consist of profile analysis, longitudinal analysis, mean-level change, and pattern change. The book concludes with a historical review of MDS development as an analytical method and a look to future directions.
The Fundamentals of Atomic and Molecular Physics
by Robert L BrooksThe Fundamentals of Atomic and Molecular Physics is intended as an introduction to the field for advanced undergraduates who have taken quantum mechanics. Each chapter builds upon the previous, using the same tools and methods throughout. As the students progress through the book, their ability to use these tools will steadily increase, along with their confidence in their efficacy. The book treats the two-electron atom as the simplest example of the many-electron atom--as opposed to using techniques that are not applicable to many-electron atoms--so that it is unnecessary to develop additional equations when turning to multielectron atoms, such as carbon. External fields are treated using both perturbation theory and direct diagonalization and spontaneous emission is developed from first principles. Only diatomic molecules are considered with the hydrogen molecular ion and neutral molecule treated in some detail. This comprehensive coverage of the quantum mechanics of complex atoms and simple diatomic molecules, developed from the very basic components, is extremely useful for students considering graduate studies in any area of physics.
Fundamentals of Calculus
by Carla C. Morris Robert M. StarkFeatures the techniques, methods, and applications of calculus using real-world examples from business and economics as well as the life and social sciences An introduction to differential and integral calculus, Fundamentals of Calculus presents key topics suited for a variety of readers in fields ranging from entrepreneurship and economics to environmental and social sciences. Practical examples from a variety of subject areas are featured throughout each chapter and step-by-step explanations for the solutions are presented. Specific techniques are also applied to highlight important information in each section, including symbols interspersed throughout to further reader comprehension. In addition, the book illustrates the elements of finite calculus with the varied formulas for power, quotient, and product rules that correlate markedly with traditional calculus. Featuring calculus as the “mathematics of change,” each chapter concludes with a historical notes section. Fundamentals of Calculus chapter coverage includes: Linear Equations and Functions The Derivative Using the Derivative Exponents and Logarithms Differentiation Techniques Integral Calculus Integrations Techniques Functions of Several Variables Series and Summations Applications to Probability Supplemented with online instructional support materials, Fundamentals of Calculus is an ideal textbook for undergraduate students majoring in business, economics, biology, chemistry, and environmental science.
Fundamentals of Calculus
by Robert M. Stark Carla C. MorrisFeatures the techniques, methods, and applications of calculus using real-world examples from business and economics as well as the life and social sciences An introduction to differential and integral calculus, Fundamentals of Calculus presents key topics suited for a variety of readers in fields ranging from entrepreneurship and economics to environmental and social sciences. Practical examples from a variety of subject areas are featured throughout each chapter and step-by-step explanations for the solutions are presented. Specific techniques are also applied to highlight important information in each section, including symbols interspersed throughout to further reader comprehension. In addition, the book illustrates the elements of finite calculus with the varied formulas for power, quotient, and product rules that correlate markedly with traditional calculus. Featuring calculus as the "mathematics of change," each chapter concludes with a historical notes section. Fundamentals of Calculus chapter coverage includes: Linear Equations and Functions The Derivative Using the Derivative Exponents and Logarithms Differentiation Techniques Integral Calculus Integrations Techniques Functions of Several Variables Series and Summations Applications to Probability Supplemented with online instructional support materials, Fundamentals of Calculus is an ideal textbook for undergraduate students majoring in business, economics, biology, chemistry, and environmental science.
Fundamentals of Causal Inference: With R (Chapman & Hall/CRC Texts in Statistical Science)
by Babette A. BrumbackOne of the primary motivations for clinical trials and observational studies of humans is to infer cause and effect. Disentangling causation from confounding is of utmost importance. Fundamentals of Causal Inference explains and relates different methods of confounding adjustment in terms of potential outcomes and graphical models, including standardization, difference-in-differences estimation, the front-door method, instrumental variables estimation, and propensity score methods. It also covers effect-measure modification, precision variables, mediation analyses, and time-dependent confounding. Several real data examples, simulation studies, and analyses using R motivate the methods throughout. The book assumes familiarity with basic statistics and probability, regression, and R and is suitable for seniors or graduate students in statistics, biostatistics, and data science as well as PhD students in a wide variety of other disciplines, including epidemiology, pharmacy, the health sciences, education, and the social, economic, and behavioral sciences. Beginning with a brief history and a review of essential elements of probability and statistics, a unique feature of the book is its focus on real and simulated datasets with all binary variables to reduce complex methods down to their fundamentals. Calculus is not required, but a willingness to tackle mathematical notation, difficult concepts, and intricate logical arguments is essential. While many real data examples are included, the book also features the Double What-If Study, based on simulated data with known causal mechanisms, in the belief that the methods are best understood in circumstances where they are known to either succeed or fail. Datasets, R code, and solutions to odd-numbered exercises are available at www.routledge.com.
Fundamentals of Chaos and Fractals for Cardiology
by Gary DrzewieckiThis textbook serves as an introduction to nonlinear dynamics and fractals for physiological modeling. Examples and demonstrations from current research in cardiopulmonary engineering and neuro-systems engineering are provided, as well as lab and computer exercises that encourage readers to apply the course material. This is an ideal textbook for graduate students in biomedical engineering departments, researchers who analyze physiological data, and researchers interested in physiological modeling.
Fundamentals of Clinical Trials
by Lawrence M. Friedman Curt D. Furberg David L. DemetsThis is the fourth edition of a very successful textbook on clinical trials methodology, written by three recognized experts who have long and extensive experience in all areas of clinical trials. Most chapters have been revised considerably from the third edition. A chapter on ethics has been added and topics such as noninferiority and adaptive designs now receive considerable discussion. There is much new material on adverse events, adherence, data monitoring, and issues in analysis. This book is intended for the clinical researcher who is interested in designing a clinical trial and developing a protocol. It is also of value to researchers and practitioners who must critically evaluate the literature of published clinical trials and assess the merits of each trial and the implications for the care and treatment of patients. The authors use numerous examples of published clinical trials from a variety of medical disciplines to illustrate the fundamentals. The text is organized sequentially from defining the question to trial closeout. One chapter is devoted to each of the critical areas to aid the clinical trial researcher. These areas include pre-specifying the scientific questions to be tested and appropriate outcome measures, determining the organizational structure, estimating an adequate sample size, specifying the randomization procedure, implementing the intervention and visit schedules for participant evaluation, establishing an interim data and safety monitoring plan, detailing the final analysis plan, and reporting the trial results according to the pre-specified objectives. Although a basic introductory statistics course is helpful in maximizing the benefit of this book, a researcher or practitioner with limited statistical background would still find most if not all the chapters understandable and helpful. While the technical material has been kept to a minimum, the statistician may still find the principles and fundamentals presented in this text useful. This book has been successfully used for teaching courses in clinical trial methodology.
Fundamentals of Clinical Trials
by Lawrence M. Friedman Curt D. Furberg David L. DeMets David M. Reboussin Christopher B. GrangerThis is the fifth edition of a very successful textbook on clinical trials methodology, written by recognized leaders who have long and extensive experience in all areas of clinical trials. The three authors of the first four editions have been joined by two others who add great expertise. A chapter on regulatory issues has been included and the chapter on data monitoring has been split into two and expanded. Many contemporary clinical trial examples have been added. There is much new material on adverse events, adherence, issues in analysis, electronic data, data sharing and international trials.This book is intended for the clinical researcher who is interested in designing a clinical trial and developing a protocol. It is also of value to researchers and practitioners who must critically evaluate the literature of published clinical trials and assess the merits of each trial and the implications for the care and treatment of patients. The authors use numerous examples of published clinical trials to illustrate the fundamentals.The text is organized sequentially from defining the question to trial closeout. One chapter is devoted to each of the critical areas to aid the clinical trial researcher. These areas include pre-specifying the scientific questions to be tested and appropriate outcome measures, determining the organizational structure, estimating an adequate sample size, specifying the randomization procedure, implementing the intervention and visit schedules for participant evaluation, establishing an interim data and safety monitoring plan, detailing the final analysis plan and reporting the trial results according to the pre-specified objectives.Although a basic introductory statistics course is helpful in maximizing the benefit of this book, a researcher or practitioner with limited statistical background would still find most if not all the chapters understandable and helpful. While the technical material has been kept to a minimum, the statistician may still find the principles and fundamentals presented in this text useful.
Fundamentals of College Algebra (10th Edition)
by Earl William Swokowski Jeffrey A. ColeThis textbook introduces two-dimensional graphs, polynomial, inverse, exponential, and logarithmic functions, and methods for solving systems of inequalities and plane geometry. Keystroke instructions for the TI-83 Plus and TI-86 calculators are provided throughout. The eleventh edition features 100 new examples and exercises. Annotation ©2004 Book News, Inc., Portland, OR (booknews.com)
Fundamentals of Complex Analysis with Applications to Engineering and Science: Classic Version (Pearson Modern Classics for Advanced Mathematics)
by Edward Saff Arthur SniderThis is the best seller in this market. It provides a comprehensive introduction to complex variable theory and its applications to current engineering problems. It is designed to make the fundamentals of the subject more easily accessible to students who have little inclination to wade through the rigors of the axiomatic approach. Modeled after standard calculus books–both in level of exposition and layout–it incorporates physical applications throughout the presentation, so that the mathematical methodology appears less sterile to engineering students.
Fundamentals of Corrosion: Mechanisms, Causes, and Preventative Methods (Corrosion Technology)
by P.E., Philip SchweitzerWritten by an authority in corrosion science, this reference offers a comprehensive description of the causes of corrosion as well as the means to limit or prevent it. It explains the mechanisms and forms of corrosion, the methods of attack on plastic materials, and the causes of failure in protective coatings, linings, and paints. Emphasizing atmospheric exposure, the text presents vital information regarding the design of structures, automobiles, household plumbing, manufacturing equipment, and other entities, as well as the effects of de-icing chemicals on highways and bridges.
Fundamentals of Data Analytics: With a View to Machine Learning
by Rudolf Mathar Gholamreza Alirezaei Emilio Balda Arash BehboodiThis book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
Fundamentals of Data Science
by Sanjeev J. Wagh Manisha S. Bhende Anuradha D. ThakareFundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science. Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes Readers will learn the steps necessary to create the application with SQl, NoSQL, Python, R, Matlab, Octave and Tablue. This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals, performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge. Features : Simple strategies for developing statistical models that analyze data and detect patterns, trends, and relationships in data sets. Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals, Methodology and Tools. Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice. Information is presented in an accessible way for students, researchers and academicians and professionals.