الصفحة 79
الصفحة 79
An Introduction to continuous-time stochastic processes : Theory, models, and applications to finance, biology, and medicine
This book is introduction to the theory of continuous-time stochastic processes. A balance of theory and applications, the work features concrete examples of modeling real-world problems from biology, medicine, industrial applications, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required. Key topics covered include: * Interacting particles and agent-based models: from polymers to ants * Population dynamics: from birth and death processes to epidemics * Financial market models: the non-arbitrage principle * Contingent claim valuation models: the risk-neutral valuation theory * Risk analysis in insurance
An Introduction To Chemoinformatics
This, the first text written specifically for this field, aims to provide an introduction to the major techniques of chemoinformatics. The first part of the book deals with the representation of 2D and 3D molecular structures, the calculation of molecular descriptors and the construction of mathematical models. The second part describes other important topics including molecular similarity and diversity, the analysis of large data sets, virtual screening, and library design. Simple illustrative examples are used throughout to illustrate key concepts, supplemented with case studies from the literature.
An American scientist on the research frontier : Edward Morley, community, and radical ideas in nineteenth-century science
This important examination of Morley’s struggle for personal and professional legitimacy extends and transforms our understanding of science during a foundational period, and leads to a number of unique conclusions that are vital to the literature and historiography of science.
Ambisonics : A Practical 3D Audio Theory for Recording, Studio Production, Sound Reinforcement, and Virtual Reality
Provides a concise explanation of the fundamentals and background of the surround sound recording and playback technology Ambisonics. It equips readers with the psychoacoustical, signal processing, acoustical, and mathematical knowledge needed to understand the inner workings of modern processing utilities, special equipment for recording, manipulation, and reproduction in the higher-order Ambisonic format. The book comes with various practical examples based on free software tools and open scientific data for reproducible research. The book includes an extensive mathematical appendix. The book offers readers a deeper understanding of Ambisonic technologies, and will especially benefit scientists, audio-system and audio-recording engineers.
Ambient intelligence : A novel paradigm
Ambient Intelligence (AmI) is an integrating technology for supporting a pervasive and transparent infrastructure for implementing smart environments. Such technology is used to enable environments for detecting events and behaviors of people and for responding in a contextually relevant fashion. AmI proposes a multi-disciplinary approach for enhancing human machine interaction. The authors start with a description of the iDorm as an example of a smart environment conforming to the AmI paradigm, and introduces computer vision as an important component of the system. Other computer vision examples describe visual monitoring for the elderly, classic and novel surveillance techniques using clusters of cameras installed in indoor and outdoor application domains, and the monitoring of public spaces. Face and speech recognition systems are also covered as well as enhanced LEGO blocks for novel educational purposes. The book closes with a provocative chapter on how a cybernetic system can be designed as the backbone of a human machine interaction.
Amartya Sens Capability Approach: Theoretical Insights and Empirical Applications
Kuklys examines how Nobel Prize-winning economist Amartya Sen’s approach to welfare measurement can be put in practice for poverty and inequality measurement in affluent societies such as the UK. Sen argues that an individual’s welfare should not be measured in terms of her income, but in terms what she can actually do or be, her capabilities. In Chapters 1 and 2, Kuklys describes the capability approach from a standard welfare economic point of view and provides a comprehensive literature review of the empirical applications in this area of research. In the remaining chapters, novel econometric techniques are employed to operationalise the concepts of functionings and capability to investigate inequality and poverty in terms of capability in the UK. Kuklys finds that capability measurement is always a useful complement to traditional monetary analysis, and particularly so in the case of capability-deprived disabled individuals.
Alternatives to Animal Testing : Proceedings of Asian Congress 2016
This book presents recent advances in the pure sciences that are of significance in the quest for alternatives to the use of animals in research and describes a variety of practical applications of the three key guiding principles for the more ethical use of animals in experiments – replacement, reduction, and refinement, collectively known as the 3Rs. Important examples from across the world of implementation of the 3Rs in the testing of cosmetics, chemicals, pesticides, and biologics, including vaccines, are described, with additional information on relevant regulations. The coverage also encompasses emerging approaches to alternative tests and the 3Rs.
Algorithms on Trees and Graphs : With Python Code
Introduces graph algorithms on an intuitive basis followed by a detailed exposition using structured pseudocode, with correctness proofs as well as worst-case analyses. Centered around the fundamental issue of graph isomorphism, the content goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. Numerous illustrations, examples, problems, exercises, and a comprehensive bibliography support students and professionals in using the book as a text and source of reference. Furthermore, Python code for all algorithms presented is given in an appendix. Topics and features: Algorithms are first presented on an intuitive basis, followed by a detailed exposition using structured pseudocode / Correctness proofs are given, together with a worst-case analysis of the algorithms / Full implementation of all the algorithms in Python / An extensive chapter is devoted to the algorithmic techniques used in the book / Solutions to all the problems
Algorithms in Bioinformatics : Theory and Implementation
Explores a comprehensive and insightful treatment of the practical application of bioinformatic algorithms in a variety of fields. Delivers a fulsome treatment of some of the main algorithms used to explain biological functions and relationships. It introduces readers to the art of algorithms in a practical manner which is linked with biological theory and interpretation. The book covers many key areas of bioinformatics, including global and local sequence alignment, forced alignment, detection of motifs, Sequence logos, Markov chains or information entropy. Other novel approaches are also described, such as Self-Sequence alignment, Objective Digital Stains (ODSs) or Spectral Forecast and the Discrete Probability Detector (DPD) algorithm. Readers will also benefit from the inclusion of: A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast ; A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations ; Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices ; A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields ; An examination of information and entropy, including sequence logos and explanations related to their meaning ; A chapter on philosophical transactions that allows the reader a broader view of the prediction process ; Extensive worked examples with detailed case studies that point out the meaning of different results
Algorithms for Sensor and Ad Hoc Networks : Advanced Lectures
Thousands of mini computers (comparable to a stick of chewing gum in size), equipped with sensors, are deployed in some terrain or other. After activation the sensors form a self-organized network and provide data, for example about a forthcoming earthquake. The trend towards wireless communication increasingly affects electronic devices in almost every sphere of life. Conventional wireless networks rely on infrastructure such as base stations; mobile devices interact with these base stations in a client/server fashion. In contrast, current research is focusing on networks that are completely unstructured, but are nevertheless able to communicate (via several hops) with each other, despite the low coverage of their antennas. Such systems are called sensor or ad hoc networks, depending on the point of view and the application. Wireless ad hoc and sensor networks have gained an incredible research momentum. Computer scientists and engineers of all flavors are embracing the area. Sensor networks have been adopted by researchers in many fields: from hardware technology to operating systems, from antenna design to databases, from information theory to networking, from graph theory to computational geometry.
Algorithms and data structures for massive datasets
Learn: Probabilistic sketching data structures for practical problems Choosing the right database engine for your application Evaluating and designing efficient on-disk data structures and algorithms Understanding the algorithmic trade-offs involved in massive-scale systems Deriving basic statistics from streaming data Correctly sampling streaming data Computing percentiles with limited space resources Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You'll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data. These effective techniques can be applied to any discipline, from finance to text analysis. Graphics, illustrations, and hands-on industry examples make complex ideas practical to implement in your projects--and there's no mathematical proofs to puzzle over. Work through this one-of-a-kind guide, and you'll find the sweet spot of saving space without sacrificing your data's accuracy. About the Technology Standard algorithms and data structures may become slow--or fail altogether--when applied to large distributed datasets. Choosing algorithms designed for big data saves time, increases accuracy, and reduces processing cost.
Algorithmic information theory : Mathematics of digital information processing
This book treats the Mathematics of many important areas in digital information processing.It covers, in a unified presentation, five topics: Data Compression, Cryptography, Sampling (Signal Theory), Error Control Codes, Data Reduction. The thematic choices are practice-oriented. So, the important final part of the book deals with the Discrete Cosine Transform and the Discrete Wavelet Transform, acting in image compression. The presentation is dense, the examples and numerous exercises are concrete. The pedagogic architecture follows increasing mathematical complexity.
Algorithmic Aspects of Bioinformatics
Advances in bioinformatics and systems biology require improved computational methods for analyzing data, while progress in molecular biology is in turn influencing the development of computer science methods. This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithmic approaches used to solve them. After introducing the basics of molecular biology and algorithmics, Part I explains string algorithms and alignments; Part II details the field of physical mapping and DNA sequencing; and Part III examines the application of algorithmics to the analysis of biological data. Exciting application examples include predicting the spatial structure of proteins, and computing haplotypes from genotype data. This book describes topics in detail and presents formal models in a mathematically precise, yet intuitive manner, with many figures and chapter summaries, detailed derivations, and examples. It is well suited as an introduction into the field of bioinformatics, and will benefit students and lecturers in bioinformatics and algorithmics, while also offering practitioners an update on current research topics.
Algèbre, Chapitres 1 à 3 = Algebra, Chapters 1 to 3
To do algebra is essentially to calculate, that is to say to perform, on elements of a set, (<algebraic operations n, the best-known example of which is provided by the (<four rules)) of elementary arithmetic. This is not the place to retrace the slow process of progressive abstraction by which the notion of algebraic operation, initially restricted to natural integers and to measurable quantities, gradually widened its field, as it grew. at the same time generalized the notion of ((number O, until, going beyond the latter, it came to apply to elements which no longer had any character ((numeric)>, for example to permutations of a - seems (see Historical Note in chap. 1).
Algebraic Methodology and Software Technology ; 11th International Conference, AMAST 2006, Kuressaare, Estonia, July 5-8, 2006, Proceedings
This is the proceedings of the 11th edition of the Algebraic Methodology and Software Technology (AMAST) conference series. The rst conference was held in the USA in 1989, and since then AMAST conferences have been held on (or near) fve diferent continents and have been hosted by many of the most prominent people and organizations in the ?eld. The AMAST initiative has always sought to have practical efects by dev- oping the science of software and basing it on a ?rm mathematical foundation. AMAST hasinterpretedsoftwaretechnologybroadly,andhas, for example, held AMAST workshops in areas as diverse as real-time systems and (natural) l- guage processing. Similarly, algebraic methodology is interpreted broadly and includes abstract algebra, category theory, logic, and a range of other ma- ematical subdisciplines.
Algebraic Groups and Lie Groups with Few Factors
Algebraic groups are treated in this volume from a group theoretical point of view and the obtained results are compared with the analogous issues in the theory of Lie groups. The main body of the text is devoted to a classification of algebraic groups and Lie groups having only few subgroups or few factor groups of different type. In particular, the diversity of the nature of algebraic groups over fields of positive characteristic and over fields of characteristic zero is emphasized. This is revealed by the plethora of three-dimensional unipotent algebraic groups over a perfect field of positive characteristic, as well as, by many concrete examples which cover an area systematically. In the final section, algebraic groups and Lie groups having many closed normal subgroups are determined.
Algebraic Geometry : An Introduction
The book starts with easily-formulated problems with non-trivial solutions – for example, Bézout’s theorem and the problem of rational curves – and uses these problems to introduce the fundamental tools of modern algebraic geometry: dimension; singularities; sheaves; varieties; and cohomology. The treatment uses as little commutative algebra as possible by quoting without proof (or proving only in special cases) theorems whose proof is not necessary in practice, the priority being to develop an understanding of the phenomena rather than a mastery of the technique. A range of exercises is provided for each topic discussed, and a selection of problems and exam papers are collected in an appendix to provide material for further study.
AI in marketing : Applications, insights, and analysis
AI in marketing equips students with the knowledge to understand the impact of artificial intelligence (AI) on marketing strategies, processes, and activities, empowering them to navigate the AI-driven marketing landscape confidently. divided into four parts, it provides a comprehensive exploration of AI's transformative role in marketing. the first part lays the groundwork, offering foundational insights into the intersection of AI and marketing. Part II explores the various applications of AI in marketing, and the tools marketers use to optimize their processes and deliver enhanced customer experiences. the third part focuses on leveraging AI for consumer insights, enabling marketers to craft data-driven strategies. the final part examines ethical considerations and the pedagogical integration of AI into marketing education.
AI in banking : Practical applications and case studies
Delves into the application of AI from theory to practice, offering detailed insights into AI project design and code implementation across eleven business scenarios in four major sectors: retail banking, e-banking, bank credit, and tech operations. it provides hands-on examples of various technologies, including automatic machine learning, integrated learning, graph computation, recommendation systems, causal inference, generative adversarial networks, supervised learning, unsupervised learning, computer vision, reinforcement learning, fuzzy control, automatic control, speech recognition, semantic understanding, bayesian networks, edge computing, and more. this book stands as a rare and practical guide to AI projects in the banking industry.
AI and UX : Why artificial intelligence needs user experience
Great effort has been put forth to continuously make AI “smarter.” But, will smarter always equal more successful AI? It is not just about getting a product to market, but about getting the product into a user’s hands in a form that will be embraced. This demands examining the product from the perspective of the user. Authors Gavin Lew and Robert Schumacher have written AI and UX to examine just how product managers and designers can best strike this balance. From exploring the history of the parallel journeys of AI and UX, to investigating past product examples and failures, to practical expert knowledge on how to best execute a positive user experience, AI and UX examines all angles of how AI can best be developed within a UX framework.
