It covers aspects of unsupervised machine learning used for knowledge discovery in data science and introduces a data-driven approach to cluster analysis, the Databionic swarm(DBS). DBS consists of the 3D landscape visualization and clustering of data. The 3D landscape enables 3D printing of high-dimensional data structures.The clustering and numbe...

This book contains a structured collection of complete solutions of all significant axially symmetric contact problems. It provides solutions for classical profiles such as the sphere, cone or flat cylindrical punch as well as a multitude of other technically relevant shapes, e.g. the truncated cone, the worn sphere, rough profiles, hollow cylinder...

The book serves both as a reference for
various scaled models with corresponding dimensionless numbers, and as a
resource for learning the art of scaling.
A special feature of the book is the emphasis on how to create software
for scaled models, based on existing software for unscaled models.
Scaling (or non-dimensionalization) is a
mathematical...

This open access book presents the key aspects of statistics in Wasserstein spaces, i.e. statistics in the space of probability measures when endowed with the geometry of optimal transportation. Further to reviewing state-of-the-art aspects, it also provides an accessible introduction to the fundamentals of this current topic, as well as an overvie...

This open book focuses on investigating predicting precursor information and key points of rockburst in mining engineering through laboratory experiment, theoretical analysis, numerical simulation and case studies. Understanding the evolution patterns for the microstructure instability of rock is a prerequisite for rockburst prediction. The book pr...

The 4th edition of this class-tested, multi-disciplinary introduction to solid state engineering adds dozens of revised and updated sections and problems, as well as three new chapters on solar energy harvesting, thermal and photothermal energy harvesting, and photo-thermovoltaics. Combining concepts from physics, chemistry, electrical engineering,...

In problem solving, as in street fighting, rules are for fools: do whatever works - don't just stand there! Yet we often fear an unjustified leap even though it may land us on a correct result. Traditional mathematics teaching is largely about solving exactly stated problems exactly, yet life often hands us partly defined problems needing only mode...

This is one of the first books on a newly emerging field of discrete differential geometry and an excellent way to access this exciting area. It surveys the fascinating connections between discrete models in differential geometry and complex analysis, integrable systems and applications in computer graphics. The authors take a closer look at discre...

This open access edited book captures the complexities and conflicts arising at the interface of intellectual property rights (IPR) and competition law. To do so, it discusses four specific themes: (a) policies governing functioning of standard setting organizations (SSOs), transparency and incentivising future innovation; (b) issue of royalties fo...

This book studies the foundations of quantum theory through its relationship to classical physics. This idea goes back to the Copenhagen Interpretation (in the original version due to Bohr and Heisenberg), which the author relates to the mathematical formalism of operator algebras originally created by von Neumann. The book therefore includes compr...

This book chronicles the rise of a new scientific paradigm offering novel insights into the age-old enigmas of existence. Over 300 years ago, the human mind discovered the machine code of reality: mathematics. By utilizing abstract thought systems, humans began to decode the workings of the cosmos. From this understanding, the current scientific pa...

Quantitative models are omnipresent - but often controversially discussed - in todays risk management practice. New regulations, innovative ﬁnancial products, and advances in valuation techniques provide a continuous ﬂow of challenging problems for ﬁnancial engineers and risk managers alike. Designing a sound stochastic model requires ﬁndin...

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs o...

This book addresses the physical phenomenon of events that seem to occur spontaneously and without any known cause. These are to be contrasted with events that happen in a (pre-)determined, predictable, lawful, and causal way. All our knowledge is based on self-reflexive theorizing, as well as on operational means of empirical perception. Some of ...

This book, published in the Soft and Biological Matter series, presents an introduction to selected research topics in the broad field of flowing matter, including the dynamics of fluids with a complex internal structure -from nematic fluids to soft glasses- as well as active matter and turbulent phenomena.Flowing matter is a subject at the crossro...

This book brings out the state of the art on how informatics-based tools are used and expected to be used in nanomaterials research. There has been great progress in the area in which "big-data" generated by experiments or computations are fully utilized to accelerate discovery of new materials, key factors, and design rules. Data-intensi...

This book presents the deterministic view of quantum mechanics developed by Nobel Laureate Gerard 't Hooft.Dissatisfied with the uncomfortable gaps in the way conventional quantum mechanics meshes with the classical world, 't Hooft has revived the old hidden variable ideas, but now in a much more systematic way than usual. In this, quantum mechanic...

Present information in stunning new ways by transforming CSS elements in two- and three-dimensional space. Whether you're rotating a photo, doing some interesting perspective tricks, or creating an interface that lets you reveal information on an element's backside, this practical guide shows you how to use them to great effect....

Tensor network is a fundamental mathematical tool with a huge range of applications in physics, such as condensed matter physics, statistic physics, high energy physics, and quantum information sciences. This open access book aims to explain the tensor network contraction approaches in a systematic way, from the basic definitions to the important a...

Electromagnetics, volume 1 by Steven W. Ellingson is a 225-page, peer-reviewed open educational resource intended for electrical engineering students in the third year of a bachelor of science degree program. It is intended as a primary textbook for a one-semester first course in undergraduate engineering electromagnetics. The book employs the &quo...

This advanced textbook introduces the main concepts and advances in systems and control theory, and highlights the importance of geometric ideas in the context of possible extensions to the more recent developments in nonlinear systems theory. Although inspired by engineering applications, the content is presented within a strong theoretical framew...

This volume provides practical solutions and introduces recent theoretical developments in risk management, pricing of credit derivatives, quantification of volatility and copula modeling. This third edition is devoted to modern risk analysis based on quantitative methods and textual analytics to meet the current challenges in banking and finance. ...

This book covers both classical and modern models in deep learning. The chapters of this book span three categories:
The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional mac...

The revised 2nd edition of this book provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribut...

This book develops the essential tools of linear algebra, with the goal of imparting technique alongside contextual understanding. Applications go hand-in-hand with theory, each reinforcing and explaining the other. This approach encourages students to develop not only the technical proficiency needed to go on to further study, but an appreciation ...

This book is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning.With careful treatment of topics that fill the curricular needs for the course, Probab...

This book helps students to master the material of a standard US undergraduate first course in Linear Algebra.
The material is standard in that the subjects covered are Gaussian reduction, vector spaces, linear maps, determinants, and eigenvalues and eigenvectors. Another standard is book's audience: sophomores or juniors, usually with a backgro...

The subject of this book is automated learning, or, as we will more often call it, Machine Learning (ML). That is, we wish to program computers so that they can "learn" from input available to them. Roughly speaking, learning is the process of converting experience into expertise or knowledge. The input to a learning algorithm is training...

This book shows us that the way to master complexity is through insight rather than precision. Precision can overwhelm us with information, whereas insight connects seemingly disparate pieces of information into a simple picture. Unlike computers, humans depend on insight. Based on the author's fifteen years of teaching at MIT, Cambridge University...

Drawing Futures brings together international designers and artists for speculations in contemporary drawing for art and architecture.
Despite numerous developments in technological manufacture and computational design that provide new grounds for designers, the act of drawing still plays a central role as a vehicle for speculation. There is a r...

Support Vector Machines (SVMs) are some of the most performant off-the-shelf, supervised machine-learning algorithms. In Support Vector Machines Succinctly, author Alexandre Kowalczyk guides readers through the building blocks of SVMs, from basic concepts to crucial problem-solving algorithms. He also includes numerous code examples and a lengthy b...