Throughout his career, Keith Hossack has made outstanding contributions to the theory of knowledge, metaphysics and the philosophy of mathematics. This collection of previously unpublished papers begins with a focus on Hossack's conception of the nature of knowledge, his metaphysics of facts and his account of the relations between knowledge, agents and facts. Attention moves to Hossack's philosophy of mind and the nature of consciousness, before turning to the notion of necessity and its interaction with a priori knowledge. Hossack's views on the nature of proof, logical truth, conditionals and generality are discussed in depth. In the final chapters, questions about the identity of mathematical objects and our knowledge of them take centre stage, together with questions about the necessity and generality of mathematical and logical truths. Knowledge, Number and Reality represents some of the most vibrant discussions taking place in analytic philosophy today.

This proceedings volume collects select contributions presented at the International Conference in Operator Theory held at Hammamet, Tunisia, on April 30 May 3, 2018. Edited and refereed by well-known experts in the field, this wide-ranging collection of survey and research articles presents the state of the art in the field of operator theory, covering topics such as operator and spectral theory, fixed point theory, functional analysis etc.

Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples, and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as 'First week of class'- with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn't, how to set up effective demonstrations, how to encourage students to participate in class and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and data science.

Magic squares are among the more popular mathematical recreations. Over the last 50 years, many generalizations of "magic" ideas have been applied to graphs. Recently there has been a resurgence of interest in "magic labelings" due to a number of results that have applications to the problem of decomposing graphs into trees.

Key features of this second edition include:

. a new chapter on magic labeling of directed graphs

. applications of theorems from graph theory and interesting counting arguments

. new research problems and exercises covering a range of difficulties

. a fully updated bibliography and index

This concise, self-contained exposition is unique in its focus on the theory of magic graphs/labelings. It may serve as a graduate or advanced undergraduate text for courses in mathematics or computer science, and as reference for the researcher."

The book systematically introduces smart power system design and its infrastructure, platform and operating standards. It focuses on multi-objective optimization and illustrates where the intelligence of the system lies. With abundant project data, this book is a practical guideline for engineers and researchers in electrical engineering, as well as power network designers and managers in administration.

Boltzmann and Vlasov equations played a great role in the past and still play an important role in modern natural sciences, technique and even philosophy of science. Classical Boltzmann equation derived in 1872 became a cornerstone for the molecular-kinetic theory, the second law of thermodynamics (increasing entropy) and derivation of the basic hydrodynamic equations. After modifications, the fields and numbers of its applications have increased to include diluted gas, radiation, neutral particles transportation, atmosphere optics and nuclear reactor modelling. Vlasov equation was obtained in 1938 and serves as a basis of plasma physics and describes large-scale processes and galaxies in astronomy, star wind theory. This book provides a comprehensive review of both equations and presents both classical and modern applications. In addition, it discusses several open problems of great importance.

Written for students with basic experience in college algebra and applied calculus, Fundamentals of Statistical Thinking: Tools and Applications familiarizes readers with fundamental concepts in statistical thinking in order to prepare them for specialized management courses such as econometrics and quantitative analysis. The book is organized into four sections, each of which focuses on a common tool used in application. Chapters 1 through 4 discuss data analysis and summaries, with an emphasis on descriptive statistics and visualization. In Chapters 5 through 8 students learn about probability models and sampling distributions. Chapters 9 and 10 deal with statistical inferences, while Chapters 11 and 12 provide further applications for categorical data and simple linear regression models. Graphical illustrations support the written text and each chapter concludes with a visual summary. Rooted in over ten years of classroom experience at both the undergraduate and graduate levels, Fundamentals of Statistical Thinking helps readers understand the importance of the main technical tools of statistical decision making, and explains when they can most appropriately be used for applied studies.

This is a guide, in theory and in practice, to how current technological changes have impacted our interaction with texts and with each other. Henry Sussman rereads pivotal moments in literary, philosophical and cultural modernity as anticipating the cybernetic discourse that has increasingly defined theory since the computer revolution. Cognitive science, psychoanalysis and systems theory are paralleled to current trends in literary and philosophical theory. Chapters alternate between theory and readings of literary texts, resulting in a broad but rigorously grounded framework for the relation between literature and computer science. This book is a refreshing perspective on the analog-orientated tradition of theory in the humanities - and offers the first literary-textual genealogy of the digital.

With a long history of innovation in the market, Larson/Edwards' Calculus, International Metric Edition has been widely praised by a generation of students and professors for solid and effective pedagogy that addresses the needs of a broad range of teaching and learning styles and environments. This edition clearly presents and effectively demonstrates the concepts and rules of calculus with a student-focused approach. It offers a wealth of learning support and digital resources - all thoroughly updated and refined using proven learning design principles that remove typical barriers to learning to create a carefully planned, inclusive experience for all students.

This bookdescribes computational financetools. It covers fundamental numerical analysis and computational techniques, such asoption pricing, and givesspecial attention tosimulation and optimization. Many chapters are organized as case studies aroundportfolio insurance and risk estimation problems. In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.
Shows ways to build and implement tools that help test ideasFocuses on the application of heuristics; standard methods receive limited attentionPresents as separate chapters problems from portfolio optimization, estimation of econometric models, and calibration of option pricing models"