Search History oscillates between a wild cyberdog chase and lunch-date monologues as Eugene Lim deconstructs grieving and storytelling with uncanny juxtapositions and subversive satire. Frank Exit is dead—or is he? While eavesdropping on two women discussing a dog-sitting gig over lunch, a bereft friend comes to a shocking realization: Frank has been reincarnated as a dog! This epiphany launches a series of adventures—interlaced with digressions about AI-generated fiction, virtual reality, Asian American identity in the arts, and lost parents—as an unlikely cast of accomplices and enemies pursues the mysterious canine. In elliptical, propulsive prose, Search History plumbs the depths of personal and collective consciousness, questioning what we consume, how we grieve, and the stories we tell ourselves.
Long out of print, Eugene Lim's wry and haunting debut novel returns to shelves with a new introduction from Renee Gladman and a fresh, reversible cover. Jim Fog is marooned in a small Midwest town shortly after his divorce, succumbing to aimless nostalgia. His ex, Sarah Car, has moved to New York City, hoping to skip right over any mourning period for their marriage. Despite everything, Jim and Sarah find they're still connected through an old, shared friend. When they both decide to chase him down, the resulting coincidences and cryptic occurrences culminate in a trading of souls that blurs the lines between reality and something much stranger. A moving mystery about loss, grief, and the loneliness of the human condition, Fog & Car was hailed as the arrival of a masterful new voice in American fiction on its initial publication; now, more than a decade later, it reads as nothing less than prophetic.
This self-contained treatment of measure and integration begins with a brief review of the Riemann integral and proceeds to a construction of Lebesgue measure on the real line. From there the reader is led to the general notion of measure, to the construction of the Lebesgue integral on a measure space, and to the major limit theorems, such as the Monotone and Dominated Convergence Theorems. The treatment proceeds to $Lp$ spaces, normed linear spaces that are shown to be complete (i.e., Banach spaces) due to the limit theorems. Particular attention is paid to $L2$ spaces as Hilbert spaces, with a useful geometrical structure. Having gotten quickly to the heart of the matter, the text proceeds to broaden its scope. There are further constructions of measures, including Lebesgue measure on $n$-dimensional Euclidean space. There are also discussions of surface measure, and more generally of Riemannian manifolds and the measures they inherit, and an appendix on the integration ofdifferential forms. Further geometric aspects are explored in a chapter on Hausdorff measure. The text also treats probabilistic concepts, in chapters on ergodic theory, probability spaces and random variables, Wiener measure and Brownian motion, and martingales. This text will prepare graduate students for more advanced studies in functional analysis, harmonic analysis, stochastic analysis, and geometric measure theory.
Crisis communications and crisis management are terms often used in the corporate world but rarely understood. In the era of social media, crisis is compounded by the entry of a loud and often powerful player, the public. “We have a problem” is the first book written in Asia about contemporary corporate crisis. The title is as much a declaration of crisis as the book is a collective wisdom of solutions to unfortunate yet common events that happen to big and small businesses. The book uses five local and five foreign case studies to illustrate crisis communications and management at its worst and at its best. Creator of Today newspaper PN Balji, founder of Channel NewsAsia Woon Tai Ho, social media guru Keith Nakamura, and litigation lawyer Eugene Quah reveal the most important secrets and strategies used to rescue companies in crisis, and discuss the opportunities lost by those who did not understand the value of speed and sincerity in this digital age. Why is deleting a crisis post on social media a bad idea? Why is it important to empower every member of your staff to prepare for crisis? This team of writers know how to win, not just in the court of law, but also in the court of public opinion. Learn why it is prudent to get your holding statements endorsed by your legal team before a crisis happens. And what emergency action you must take when netizens snap compromising photographs of your backend production, whether it is repacking soya bean milk and labelling as “freshly prepared” or naming buns after a recently deceased head of state. And then, how do you say sorry in action, not in words? A tale of two Tonys, the CEO of AirAsia and the CEO of BP: how was Tony Fernandes a leader, and why was Tony Hayward not. “We have a problem” is the protection you need for your business reputation in this digital age. Skilfully managing the perception of a crisis determines the difference between a company’s life and death, because in the pitched battle between perception and reality, perception always wins.
Numerical continuation methods have provided important contributions toward the numerical solution of nonlinear systems of equations for many years. The methods may be used not only to compute solutions, which might otherwise be hard to obtain, but also to gain insight into qualitative properties of the solutions. Introduction to Numerical Continuation Methods, originally published in 1979, was the first book to provide easy access to the numerical aspects of predictor corrector continuation and piecewise linear continuation methods. Not only do these seemingly distinct methods share many common features and general principles, they can be numerically implemented in similar ways. Introduction to Numerical Continuation Methods also features the piecewise linear approximation of implicitly defined surfaces, the algorithms of which are frequently used in computer graphics, mesh generation, and the evaluation of surface integrals.
Stochastic Convergence, Second Edition covers the theoretical aspects of random power series dealing with convergence problems. This edition contains eight chapters and starts with an introduction to the basic concepts of stochastic convergence. The succeeding chapters deal with infinite sequences of random variables and their convergences, as well as the consideration of certain sets of random variables as a space. These topics are followed by discussions of the infinite series of random variables, specifically the lemmas of Borel-Cantelli and the zero-one laws. Other chapters evaluate the power series whose coefficients are random variables, the stochastic integrals and derivatives, and the characteristics of the normal distribution of infinite sums of random variables. The last chapter discusses the characterization of the Wiener process and of stable processes. This book will prove useful to mathematicians and advance mathematics students.
Recently much attention has been devoted to the optimization of transportation networks in a given geographic area. One assumes the distributions of population and of services/workplaces (i.e. the network's sources and sinks) are known, as well as the costs of movement with/without the network, and the cost of constructing/maintaining it. Both the long-term optimization and the short-term, "who goes where," optimization are considered. These models can also be adapted for the optimization of other types of networks, such as telecommunications, pipeline or drainage networks. In the monograph we study the most general problem settings, namely, when neither the shape nor even the topology of the network to be constructed is known a priori.
Advanced Statistics with Applications in R fills the gap between several excellent theoretical statistics textbooks and many applied statistics books where teaching reduces to using existing packages. This book looks at what is under the hood. Many statistics issues including the recent crisis with p-value are caused by misunderstanding of statistical concepts due to poor theoretical background of practitioners and applied statisticians. This book is the product of a forty-year experience in teaching of probability and statistics and their applications for solving real-life problems. There are more than 442 examples in the book: basically every probability or statistics concept is illustrated with an example accompanied with an R code. Many examples, such as Who said π? What team is better? The fall of the Roman empire, James Bond chase problem, Black Friday shopping, Free fall equation: Aristotle or Galilei, and many others are intriguing. These examples cover biostatistics, finance, physics and engineering, text and image analysis, epidemiology, spatial statistics, sociology, etc. Advanced Statistics with Applications in R teaches students to use theory for solving real-life problems through computations: there are about 500 R codes and 100 datasets. These data can be freely downloaded from the author's website dartmouth.edu/~eugened. This book is suitable as a text for senior undergraduate students with major in statistics or data science or graduate students. Many researchers who apply statistics on the regular basis find explanation of many fundamental concepts from the theoretical perspective illustrated by concrete real-world applications.
Concise Handbook of Mathematics and Physics presents a unified and coherent treatment of all the major aspects of modern elementary physics and mathematics. This complete text/reference includes definitions of fundamental notations and physical and mathematical quantities, formulas that express the laws of physics, axioms and theorems of mathematics, and more. The information is organized logically (instead of alphabetically) for better comprehension and quick, convenient access. The book contains extensive cross-referencing between the mathematical and physical sections. reflecting the considerable overlap between these two areas of study and increasing the usefulness of this handbook. Fundamental concepts, theorems, and laws are demonstrated through numerous practical examples and tasks to help build problem-solving skills.
Over the past fifteen years two new techniques have yielded extremely important contributions toward the numerical solution of nonlinear systems of equations. This book provides an introduction to and an up-to-date survey of numerical continuation methods (tracing of implicitly defined curves) of both predictor-corrector and piecewise-linear types. It presents and analyzes implementations aimed at applications to the computation of zero points, fixed points, nonlinear eigenvalue problems, bifurcation and turning points, and economic equilibria. Many algorithms are presented in a pseudo code format. An appendix supplies five sample FORTRAN programs with numerical examples, which readers can adapt to fit their purposes, and a description of the program package SCOUT for analyzing nonlinear problems via piecewise-linear methods. An extensive up-to-date bibliography spanning 46 pages is included. The material in this book has been presented to students of mathematics, engineering and sciences with great success, and will also serve as a valuable tool for researchers in the field.
The Handbook and Atlas of Curves describes available analytic and visual properties of plane and spatial curves. Information is presented in a unique format, with one half of the book detailing investigation tools and the other devoted to the Atlas of Plane Curves. Main definitions, formulas, and facts from curve theory (plane and spatial) are discussed.
This book is an introductory real analysis textbook, presented through the lens of history. That is, it proposes that an effective way to motivate the highly non-intuitve definitions and theorems encountered in an introductory, college level Real Analysis course is via one of the stories (there are many) of the historical development of the subject, from its intuitive beginnings to modern rigor. The definitions and techniques are motivated by the actual difficulties encountered by the intuitive approach and are presented in their historical context.
A rigorous, self-contained examination of mixed model theory and application Mixed modeling is one of the most promising and exciting areas of statistical analysis, enabling the analysis of nontraditional, clustered data that may come in the form of shapes or images. This book provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as applications such as the analysis of tumor regrowth, shape, and image. Paying special attention to algorithms and their implementations, the book discusses: Modeling of complex clustered or longitudinal data Modeling data with multiple sources of variation Modeling biological variety and heterogeneity Mixed model as a compromise between the frequentist and Bayesian approaches Mixed model for the penalized log-likelihood Healthy Akaike Information Criterion (HAIC) How to cope with parameter multidimensionality How to solve ill-posed problems including image reconstruction problems Modeling of ensemble shapes and images Statistics of image processing Major results and points of discussion at the end of each chapter along with "Summary Points" sections make this reference not only comprehensive but also highly accessible for professionals and students alike in a broad range of fields such as cancer research, computer science, engineering, and industry.
This second volume of three on relativistic quantum theories of interacting charged particles discusses quantum theories of systems with variable numbers of particles. Basics of the Fock space and quantum electrodynamics are covered with an emphasis on renormalization. In contrast to the usual treatment of the topic, particles (rather than fields) are chosen as basic ingredients. Contents Fock space Scattering in Fock space Quantum electrodynamics Renormalization Useful integrals Quantum fields of fermions Quantum field of photons QED interaction in terms of particle operators Relativistic invariance of QFT Loop integrals in QED Scattering matrix in (v/c)2 approximation Checks of physical dimensions
Probability and Mathematical Statistics: An Introduction provides a well-balanced first introduction to probability theory and mathematical statistics. This book is organized into two sections encompassing nine chapters. The first part deals with the concept and elementary properties of probability space, and random variables and their probability distributions. This part also considers the principles of limit theorems, the distribution of random variables, and the so-called student's distribution. The second part explores pertinent topics in mathematical statistics, including the concept of sampling, estimation, and hypotheses testing. This book is intended primarily for undergraduate statistics students.
This book introduces notation, terminology, and basic ideas of relativistic quantum theories. The discussion proceeds systematically from the principle of relativity and postulates of quantum logics to the construction of Poincaré invariant few-particle models of interaction and scattering. It is the first of three volumes formulating a consistent relativistic quantum theory of interacting charged particles. Contents Quantum logic Poincaré group Quantum mechanics and relativity Observables Elementary particles Interaction Scattering Delta function Groups and vector spaces Group of rotations Lie groups and Lie algebras Hilbert space Operators Subspaces and projections Representations of groups and algebras Pseudo-orthogonal representation of Lorentz group
Eugene Wigner is one of the few giants of 20th-century physics. The present annotated volume begins with a short biographical sketch followed by Wigner's papers on group theory, an extremely powerful tool he created for theoretical quantum physics.
Progress in space safety lies in the acceptance of safety design and engineering as an integral part of the design and implementation process for new space systems. Safety must be seen as the principle design driver of utmost importance from the outset of the design process, which is only achieved through a culture change that moves all stakeholders toward front-end loaded safety concepts. This approach entails a common understanding and mastering of basic principles of safety design for space systems at all levels of the program organisation. Fully supported by the International Association for the Advancement of Space Safety (IAASS), written by the leading figures in the industry, with frontline experience from projects ranging from the Apollo missions, Skylab, the Space Shuttle and the International Space Station, this book provides a comprehensive reference for aerospace engineers in industry. It addresses each of the key elements that impact on space systems safety, including: the space environment (natural and induced); human physiology in space; human rating factors; emergency capabilities; launch propellants and oxidizer systems; life support systems; battery and fuel cell safety; nuclear power generators (NPG) safety; habitat activities; fire protection; safety-critical software development; collision avoidance systems design; operations and on-orbit maintenance. - The only comprehensive space systems safety reference, its must-have status within space agencies and suppliers, technical and aerospace libraries is practically guaranteed - Written by the leading figures in the industry from NASA, ESA, JAXA, (et cetera), with frontline experience from projects ranging from the Apollo missions, Skylab, the Space Shuttle, small and large satellite systems, and the International Space Station - Superb quality information for engineers, programme managers, suppliers and aerospace technologists; fully supported by the IAASS (International Association for the Advancement of Space Safety)
In this book, a new approach to the theory and practice of two-phase systems based on a global invariant – entropy, – and other invariants is formulated and experimentally confirmed. - Offers a novel approach to the study of the two-phase flows systems based on statistical mechanics and probability theory - Provides the tools for computing and modelling two-phase systems, predicts mass transfer and enables system optimization - Provides a plethora of examples in among others, separation processes, dust production, pneumatic transport, and boiling bed
Zusammenfassung: Robust and Adaptive Control (second edition) shows readers how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications, the focus of the book is primarily on continuous-time dynamical systems. The two-part text begins with robust and optimal linear control methods and moves on to a self-contained presentation of the design and analysis of model reference adaptive control for nonlinear uncertain dynamical systems. Features of the second edition include: sufficient conditions for closed-loop stability under output feedback observer-based loop-transfer recovery (OBLTR) with adaptive augmentation; OBLTR applications to aerospace systems; case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; realistic examples and simulation data illustrating key features of the methods described; and problem solutions for instructors and MATLAB® code provided electronically. The theory and practical applications address real-life aerospace problems, being based on numerous transitions of control-theoretic results into operational systems and airborne vehicles drawn from the authors' extensive professional experience with The Boeing Company. The systems covered are challenging--often open-loop unstable with uncertainties in their dynamics--and thus require both persistently reliable control and the ability to track commands either from a pilot or a guidance computer. Readers should have a basic understanding of root locus, Bode diagrams, and Nyquist plots, as well as linear algebra, ordinary differential equations, and the use of state-space methods in analysis and modeling of dynamical systems. The second edition contains a background summary of linear systems and control systems and an introduction to state observers and output feedback control, helping to make it self-contained. Robust and Adaptive Control teaches senior undergraduate and graduate students how to construct stable and predictable control algorithms for realistic industrial applications. Practicing engineers and academic researchers will also find the book of great instructional value
This book is intended to be a comprehensive introduction to the subject of partial differential equations. It should be useful to graduate students at all levels beyond that of a basic course in measure theory. It should also be of interest to professional mathematicians in analysis, mathematical physics, and differential geometry. This work will be divided into three volumes, the first of which focuses on the theory of ordinary differential equations and a survey of basic linear PDEs.
Describing the fundamental theory of particle physics and its applications, this book provides a detailed account of the Standard Model, focusing on techniques that can produce information about real observed phenomena. The book begins with a pedagogic account of the Standard Model, introducing essential techniques such as effective field theory and path integral methods. It then focuses on the use of the Standard Model in the calculation of physical properties of particles. Rigorous methods are emphasized, but other useful models are also described. This second edition has been updated to include recent theoretical and experimental advances, such as the discovery of the Higgs boson. A new chapter is devoted to the theoretical and experimental understanding of neutrinos, and major advances in CP violation and electroweak physics have been given a modern treatment. This book is valuable to graduate students and researchers in particle physics, nuclear physics and related fields.
This book contains a valuable discussion of renormalization through the addition of counterterms to the Lagrangian, giving the first complete proof of the cancellation of all divergences in an arbitrary interaction. The author also introduces a new method of renormalizing an arbitrary Feynman amplitude, a method that is simpler than previous approaches and can be used to study the renormalized perturbation series in quantum field theory.
M-STATISTICS A comprehensive resource providing new statistical methodologies and demonstrating how new approaches work for applications M-statistics introduces a new approach to statistical inference, redesigning the fundamentals of statistics, and improving on the classical methods we already use. This book targets exact optimal statistical inference for a small sample under one methodological umbrella. Two competing approaches are offered: maximum concentration (MC) and mode (MO) statistics combined under one methodological umbrella, which is why the symbolic equation M=MC+MO. M-statistics defines an estimator as the limit point of the MC or MO exact optimal confidence interval when the confidence level approaches zero, the MC and MO estimator, respectively. Neither mean nor variance plays a role in M-statistics theory. Novel statistical methodologies in the form of double-sided unbiased and short confidence intervals and tests apply to major statistical parameters: Exact statistical inference for small sample sizes is illustrated with effect size and coefficient of variation, the rate parameter of the Pareto distribution, two-sample statistical inference for normal variance, and the rate of exponential distributions. M-statistics is illustrated with discrete, binomial, and Poisson distributions. Novel estimators eliminate paradoxes with the classic unbiased estimators when the outcome is zero. Exact optimal statistical inference applies to correlation analysis including Pearson correlation, squared correlation coefficient, and coefficient of determination. New MC and MO estimators along with optimal statistical tests, accompanied by respective power functions, are developed. M-statistics is extended to the multidimensional parameter and illustrated with the simultaneous statistical inference for the mean and standard deviation, shape parameters of the beta distribution, the two-sample binomial distribution, and finally, nonlinear regression. Our new developments are accompanied by respective algorithms and R codes, available at GitHub, and as such readily available for applications. M-statistics is suitable for professionals and students alike. It is highly useful for theoretical statisticians and teachers, researchers, and data science analysts as an alternative to classical and approximate statistical inference.
Advances in the study of dynamical systems have revolutionized the way that classical mechanics is taught and understood. Classical Dynamics, first published in 1998, is a comprehensive textbook that provides a complete description of this fundamental branch of physics. The authors cover all the material that one would expect to find in a standard graduate course: Lagrangian and Hamiltonian dynamics, canonical transformations, the Hamilton-Jacobi equation, perturbation methods, and rigid bodies. They also deal with more advanced topics such as the relativistic Kepler problem, Liouville and Darboux theorems, and inverse and chaotic scattering. A key feature of the book is the early introduction of geometric (differential manifold) ideas, as well as detailed treatment of topics in nonlinear dynamics (such as the KAM theorem) and continuum dynamics (including solitons). The book contains many worked examples and over 200 homework exercises. It will be an ideal textbook for graduate students of physics, applied mathematics, theoretical chemistry, and engineering, as well as a useful reference for researchers in these fields. A solutions manual is available exclusively for instructors.
Questions of existence, multiplicity, and regularity of free boundaries for prescribed data need to be addressed and their solutions lead to nonlinear problems. In this paper an equivalence is established between Bernoulli free-boundary problems and a class of equations for real-valued functions of one real variable.
The Text book is arranges so that I can be used for self-study by the engineering in practice.Included are as many examples of feedback control system in various areas of practice while maintaining a strong basic feedback control text that can be used for study in any of the various branches of engineering.
For scientific, technological and organizational reasons, the end of World War II (in 1945) saw a rapid acceleration in the tempo of discovery and understanding in nuclear physics, cosmic rays and quantum field theory, which together triggered the birth of modern particle physics. The first fifteen years (1945-60) following the war's end ? the ?Startup Period? in modern particle physics -witnessed a series of major experimental and theoretical developments that began to define the conceptual contours (non-Abelian internal symmetries, Yang-Mills fields, renormalization group, chirality invariance, baryon-lepton symmetry in weak interactions, spontaneous symmetry breaking) of the quantum field theory of three of the basic interactions in nature (electromagnetic, strong and weak). But it took another fifteen years (1960-75) ? the ?Heroic Period? in modern particle physics ? to unravel the physical content and complete the mathematical formulation of the standard gauge theory of the strong and electroweak interactions among the three generations of quarks and leptons. The impressive accomplishments during the ?Heroic Period? were followed by what is called the ?period of consolidation and speculation (1975-1990)?, which includes the experimental consolidation of the standard model (SM) through precision tests, theoretical consolidation of SM through the search for more rigorous mathematical solutions to the Yang-Mills-Higgs equations, and speculative theoretical excursions ?beyond SM?.Within this historical-conceptual framework, the author ? himself a practicing particle theorist for the past fifty years ? attempts to trace the highlights in the conceptual evolution of modern particle physics from its early beginnings until the present time. Apart from the first chapter ? which sketches a broad overview of the entire field ? the remaining nine chapters of the book offer detailed discussions of the major concepts and principles that prevailed and were given wide currency during each of the fifteen-year periods that comprise the history of modern particle physics. Those concepts and principles that contributed only peripherally to the standard model are given less coverage but an attempt is made to inform the reader about such contributions (which may turn out to be significant at a future time) and to suggest references that supply more information. Chapters 2 and 3 of the book cover a range of topics that received dedicated attention during the ?Startup Period? although some of the results were not incorporated into the structure of the standard model. Chapters 4-6 constitute the core of the book and try to recapture much of the conceptual excitement of the ?Heroic Period?, when quantum flavordynamics (QFD) and quantum chromodynamics (QCD) received their definitive formulation. [It should be emphasized that, throughout the book, logical coherence takes precedence over historical chronology (e.g. some of the precision tests of QFD are discussed in Chapter 6)]. Chapter 7 provides a fairly complete discussion of the chiral gauge anomalies in four dimensions with special application to the standard model (although the larger unification models are also considered). The remaining three chapters of the book (Chapters 7-10) cover concepts and principles that originated primarily during the ?Period of Consolidation and Speculation? but, again, this is not a literal statement. Chapters 8 and 9 report on two of the main directions that were pursued to overcome acknowledged deficiencies of the standard model: unification models in Chapter 8 and attempts to account for the existence of precisely three generations of quarks and leptons, primarily by means of preon models, in Chapter 9. The most innovative of the final three chapters of the book is Chapter 10 on topological conservation laws. This last chapter tries to explain the significance of topologically non-trivial solutions in four-dimensional (space-time) particle physics (e.g. 't Hooft-Polyakov monopoles, instantons, sphalerons, global SU(2) anomaly, Wess-Zumino term, etc.) and to reflect on some of the problems that have ensued (e.g. the ?strong CP problem? in QCD) from this effort. It turns out that the more felicitous topological applications of field theory are found ? as of now ? in condensed matter physics; these successful physical applications (to polyacetylene, quantized magnetic flux in type-II low temperature superconductivity, etc.) are discussed in Chapter 10, as a good illustration of the conceptual unity of modern physics.
Optimization in Solving Elliptic Problems focuses on one of the most interesting and challenging problems of computational mathematics - the optimization of numerical algorithms for solving elliptic problems. It presents detailed discussions of how asymptotically optimal algorithms may be applied to elliptic problems to obtain numerical solutions meeting certain specified requirements. Beginning with an outline of the fundamental principles of numerical methods, this book describes how to construct special modifications of classical finite element methods such that for the arising grid systems, asymptotically optimal iterative methods can be applied. Optimization in Solving Elliptic Problems describes the construction of computational algorithms resulting in the required accuracy of a solution and having a pre-determined computational complexity. Construction of asymptotically optimal algorithms is demonstrated for multi-dimensional elliptic boundary value problems under general conditions. In addition, algorithms are developed for eigenvalue problems and Navier-Stokes problems. The development of these algorithms is based on detailed discussions of topics that include accuracy estimates of projective and difference methods, topologically equivalent grids and triangulations, general theorems on convergence of iterative methods, mixed finite element methods for Stokes-type problems, methods of solving fourth-order problems, and methods for solving classical elasticity problems. Furthermore, the text provides methods for managing basic iterative methods such as domain decomposition and multigrid methods. These methods, clearly developed and explained in the text, may be used to develop algorithms for solving applied elliptic problems. The mathematics necessary to understand the development of such algorithms is provided in the introductory material within the text, and common specifications of algorithms that have been developed for typical problems in mathematical physics are identified. These features of the book make it more widely accessible to those interested in numerical methods and their optimization, including students and researchers in mathematical physics, functional analysis, theory of differential equations, approximation theory of functions, and geometry.
Practical text focuses on fundamental applied math needed to deal with physics and engineering problems: elementary vector calculus, special functions of mathematical physics, calculus of variations, much more. 1968 edition.
Math enthusiasts of all ages will delight in these 200 riddles, based on concepts from geometry, trigonometry, algebra, infinity, probability, and logic. Includes complete solutions and 113 illustrations.
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