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Big Data Science in Finance
Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides
Mathematical Modelling of Biosystems
This volume is an interdisciplinary book, which introduces, in a very readable way, state of the art research in the fundamental topics of mathematical modelling of Biosystems. These topics include: the study of Biological Growth and its mechanisms, the coupling of pattern to form via theorems of Differential Geometry, the human immunodeficiency virus dynamics, the inverse folding problem and the possibility of analysing true protein backbone flexibility, the Biclustering techniques for the organization of microarray data, the analytical approach to the modelling of biomolecular structure via Steiner trees, the action of biocides on resistance mechanisms of mutated and phenotypic bacteria strains, a description of the fundamental processes for the distribution and abundances of species towards a unified theory of Ecology, and a special introduction to Protein Physics aiming to explain the all-or-none first order phase transitions from native to denatured states.
Leibniz : What Kind of Rationalist?
The chapters of the book are the result of intense discussion in the course of an international conference focused on the title question of this book, and were selected in view of their contribution to this topic. They are clustered in thematically organized parts. No effort has been made to hide the controversies underlying the different interpretations of Leibniz’s “rationalism” – in each particular domain and as a whole. On the contrary, the editor firmly believes that only through a variety of conflicting interpretive perspectives can the multi-faceted nature of an oeuvre of such a magnitude and variety as Leibniz’s be brought to light and understood as it deserves.
Learning from clusters : A critical assessment from an economic-geographical perspective
Edited volumes run the danger of being a hotchpotch of contributions on a wide variety of topics. Here, we have explicitly focused on a central theme in contemporary economic geography and regional science, namely the relationship between learning, innovation and clustering. Internationally renowned scientists made both theoretical and empirical contributions to this volume. We think this book constitutes a broad palette of contemporary thinking and research on the relationship between spatial concentration and innovation and hope it will play a significant role in future debates on this issue.
Learning Classifier Systems in Data Mining
Just over thirty years after Holland first presented the outline for Learning Classifier System paradigm, the ability of LCS to solve complex real-world problems is becoming clear. In particular, their capability for rule induction in data mining has sparked renewed interest in LCS. This book brings together work by a number of individuals who are demonstrating their good performance in a variety of domains.
Classification and Clustering for Knowledge Discovery
This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. "Classification and Clustering for Knowledge Discovery" also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications.
Classical Nucleation Theory in Multicomponent Systems
Nucleation is the initial step of every first-order phase transition, and most phase transitions encountered both in everyday life and industrial processes are of the first-order. Using an elegant classical theory based on thermodynamics and kinetics, this book provides a fully detailed picture of multi-component nucleation. As many of the issues concerning multi-component nucleation theory have been solved during the last 10-15 years, it also thoroughly integrates both fundamental theory with recent advances presented in the literature. It covered are: the basic relevant thermodynamics and statistical physics; modelling a molecular cluster as a spherical liquid droplet; predicting the size and composition of the nucleating critical clusters; kinetic models for cluster growth and decay; calculating nucleation rates; and a full derivation and application of nucleation theorems that can be used to extract microscopic cluster properties from nucleation rate measurements.
CFN Lectures on Functional Nanostructures : Vol.1
This book contains a selection of lectures from the first Summer School organized by the Center for Functional Nanostructures (CFN) at the University of Karlsruhe. The mission of the CFN is to carry out research in the following areas: nanophotonics, nanoelectronics, molecular nanostructures and nanostructured materials. The aim of the summer schools is mainly to exchange new ideas and illustrate emerging research methodologies through a series of lectures. This is reflected by both the selection of topics addressed in the present volume as well as the tutorial aspect of the contributions.
Calixarenes in the Nanoworld
Calixarenes have been widely exploited in all areas of supramolecular chemistry over the past three decades and many recent developments have concerned their applications in the production of chemical entities with the dimensions of nanometres, as in "nanochemistry".Calixarenes in the Nanoworld Relates calixarenes to nanochemistry – key information for industries engaged in the production of high-tech materials. Provides a timely review of both what is known and the exciting prospects provided by calixarenes, Contains several review articles which define the importance of calixarenes as reagents in nanochemistry.
Branch-and-Bound Applications in Combinatorial Data Analysis
There are a variety of combinatorial optimization problems that are relevant to the examination of statistical data. Combinatorial problems arise in the clustering of a collection of objects, the seriation (sequencing or ordering) of objects, and the selection of variables for subsequent multivariate statistical analysis such as regression. The options for choosing a solution strategy in combinatorial data analysis can be overwhelming. Because some problems are too large or intractable for an optimal solution strategy, many researchers develop an over-reliance on heuristic methods to solve all combinatorial problems. However, with increasingly accessible computer power and ever-improving methodologies, optimal solution strategies have gained popularity for their ability to reduce unnecessary uncertainty. In this monograph, optimality is attained for nontrivially sized problems via the branch-and-bound paradigm.
Blind Speech Separation
This is the first book to provide a cutting edge reference to the fascinating topic of blind source separation (BSS) for convolved speech mixtures. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications. The individual chapters are designed to be tutorial in nature with specific emphasis on an in-depth treatment of state of the art techniques. Blind Speech Separation is divided into three parts:Part 1 presents overdetermined or critically determined BSS. Here the main technology is independent component analysis (ICA). ICA is a statistical method for extracting mutually independent sources from their mixtures. Part 2 addresses underdetermined BSS, where there are fewer microphones than source signals. Here, the sparseness of speech sources is very useful; we can utilize time-frequency diversity, where sources are active in different regions of the time-frequency plane.Part 3 presents monaural BSS where there is only one microphone. Here, we can separate a mixture by using the harmonicity and temporal structure of the sources. We can build a probabilistic framework by assuming a source model, and separate a mixture by maximizing the a posteriori probability of the sources.
Bioinformatics and Computational Biology Solutions Using R and Bioconductor
Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R. This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including: Importation and preprocessing of high-throughput data from microarray, proteomic, and flow cytometry platforms / Curation and delivery of biological metadata for use in statistical modeling and interpretation. / Statistical analysis of high-throughput data, including machine learning and visualization,modeling and visualization of graphs and networks. This book is a dynamic document. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
Atoms, molecules and photons : An introduction to atomic- molecular- and quantum physics
This introduction to Atomic and Molecular Physics explains how our present model of atoms and molecules has been developed over the last two centuries both by many experimental discoveries and, from the theoretical side, by the introduction of quantum physics to the adequate description of micro-particles. It illustrates the wave model of particles by many examples and shows the limits of classical description. The interaction of electromagnetic radiation with atoms and molecules and its potential for spectroscopy is outlined in more detail and in particular lasers as modern spectroscopic tools are discussed more thoroughly. Many examples and problems with solutions are offered to encourage readers to actively engage in experimentation.
Astrophysics is easy! : An introduction for the amateur astronomer
With some justification, many amateur astronomers believe astrophysics is a very difficult subject, requiring at least degree-level mathematics to understand it properly. This isn’t necessarily the case. Mike Inglis' quantitative approach to the subject explains all aspects of astrophysics in simple terms and cuts through the incomprehensible mathematics with which this fascinating subject is all too often associated. Astrophysics is Easy! begins by looking at the H-R diagram and other basic tools of astrophysics, then ranges across the universe, from a first look at the interstellar medium and nebulae, through the birth, evolution and death of stars, to the physics of galaxies and clusters of galaxies.
Astrophysics : A new approach
For a quantitative understanding of the physics of the universe - from the solar system through the milky way to clusters of galaxies all the way to cosmology - these edited lecture notes are perhaps among the most concise and also among the most critical ones: Astrophysics has not yet stood the redundancy test of laboratory physics, hence should be wary of early interpretations. Special chapters are devoted to magnetic and radiation processes, supernovae, disks, black-hole candidacy, bipolar flows, cosmic rays, gamma-ray bursts, image distortions, and special sources. At the same time, planet earth is viewed as the arena for life, with plants and animals having evolved to homo sapiens during cosmic time. -- This text is unique in covering the basic qualitative and quantitative tools, formulae as well as numbers, needed for the precise interpretation of frontline phenomena in astrophysical research. The author compares mainstream interpretations with new and even controversial ones he wishes to emphasize.
Artificial Mind System : Kernel Memory Approach
This book is written from an engineer's perspective of the mind. "Artificial Mind System" exposes the reader to a broad spectrum of interesting areas in general brain science and mind-oriented studies. In this research monograph a picture of the holistic model of an artificial mind system and its behaviour is drawn, as concretely as possible, within a unified context, which could eventually lead to practical realisation in terms of hardware or software. With a view that "the mind is a system always evolving", ideas inspired by many branches of studies related to brain science are integrated within the text, i.e. artificial intelligence, cognitive science / psychology, connectionism, consciousness studies, general neuroscience, linguistics, pattern recognition / data clustering, robotics, and signal processing.
Applied Multivariate Statistical Analysis
This book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who face statistical data analysis.
Analysis and Control of Ultrafast Photoinduced Reactions
The present monograph summarizes, in a comprehensive way, several years of joint experimental and theoretical frontier research on ultrafast laser-induced molecular dynamics and its control. Emphasis is set on the characterization of the nuclear dynamics within molecular systems in various environments (gas phase, surfaces, solids, solution, strong fields) triggered by optical excitations spanning from the infrared to the ultraviolet. Building on the converged analysis between experiment and theory, control of chemical reactions is established by means of optimally shaped laser pulses. This paves the road toward new applications and future challenges in this rapidly developing research field.
An R and S-Plus® Companion to Multivariate Analysis
Most data sets collected by researchers are multivariate, and in the majority of cases the variables need to be examined simultaneously to get the most informative results. This requires the use of one or other of the many methods of multivariate analysis, and the use of a suitable software package such as S-PLUS or R. In this book the core multivariate methodology is covered along with some basic theory for each method described. The necessary R and S-PLUS code is given for each analysis in the book, with any differences between the two highlighted.
Algorithms for Fuzzy Clustering : Methods in c-Means Clustering with Applications
The main subject of this book is the fuzzy c-means proposed by Dunn and Bezdek and their variations including recent studies. We emphasize in this book is a family of algorithms using entropy or entropy-regularized methods which are less known, but we consider the entropy-based method to be another useful method of fuzzy c-means.
