الصفحة 130
الصفحة 130
Allelopathy in Sustainable Agriculture and Forestry
This book reports on the latest advances in allelopathy through the contributions of leading scientists in the field. The book addresses the history of allelopathy, the science of allelochemicals, and the application of allelopathy in agriculture and forestry. An emphasis on both methodology and application makes Allelopathy a truly practical reference for scientists, researchers and students of plant science, agriculture, forestry, terrestrial ecology and environmental science.
Alive : Advancements in Adaptive Architecture
Proposes to embrace the unknown and cultivate the architectural discipline towards an integrated and cross-disciplinary practice. It unravels compelling innovative and forward-thinking design narratives by leading international practitioners and researchers who investigate novel associations between architecture, nature and humanity for a future, alive architecture.
Aligner Techniques in Orthodontics
Filled with the theoretical and practical clinical information on the popular aligner techniques with a focus on Invisalign. Written by practicing orthodontists and noted experts on the topic, the book is designed to help practitioners develop their skills in using aligners in orthodontics. The authors describe in detail the clear and simple methods for treating patients using different aligner techniques, as well as material on treating any given malocclusion.
Aligner systems in invisible orthodontics: basic concepts and clinical management
Describes the processes, techniques and biomechanics involved in providing aligner treatment for different types of malocclusions. It opens with an overview of the material characteristics and the basic concepts of aligner therapy including topics like biocompatibility and intraoral deterioration. The main part of the book is dedicated to the various types of aligners, the methods used in their application and the practical aspects of delivery. It is structured based on the type of malocclusion being managed giving the reader a systematic pattern and a practical way of progressing through the book. The book closes with a discussion of the scientific data available.
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 and Models for the Web-Graph ; 5th International Workshop, WAW 2007, San Diego, CA, USA, December 11-12, 2007, Proceedings
The book address a wide variety of topics related to the study of the Web-graph such as random graph models for the Web-graph, PageRank analysis and computation, decentralized search, local partitioning algorithms,and traceroute sampling. The Web-graph has been the focal point of a tremendous amount of research for more than a decade. The view of the Web as a graph has great practical importance and has also generated much interesting theoretical work.
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 learning theory ; Vol. 3734 ; 16th international conference, ALT 2005, Singapore, October 8-11, 2005, Proceedings
This volume contains the papers presented at the 16th Annual InternationalConference on Algorithmic Learning Theory (ALT 2005), which was held (Republic of Singapore), 2005. The main objective of theconference is to provide an interdisciplinary forum for the discussion of the the-oretical foundations of machine learning as well as their relevance to practicalapplications. The volume includes 30 technical contributions, which were selected by theprogram committee from 98 submissions.
Algorithmic Learning in a Random World
This new monograph integrates mathematical theory and revealing experimental work. It demonstrates mathematically the validity of the reliability claimed by conformal predictors when they are applied to independent and identically distributed data, and it confirms experimentally that the accuracy is sufficient for many practical problems. Later chapters generalize these results to models called repetitive structures, which originate in the algorithmic theory of randomness and statistical physics. The approach is flexible enough to incorporate most existing methods of machine learning, including newer methods such as boosting and support vector machines and older methods such as nearest neighbors and the bootstrap.
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.
Algorithmes dapproximation
Le champ des algorithmes d'approximation est aujourd'hui l'un des domaines de recherche les plus actifs en informatique. Il allie la profondeur de la théorie mathématique aux promesses d'applications pratiques d'un intérêt considérable. La plupart des problèmes issus d'applications relevant de domaines aussi différents que la conception de circuits VLSI, la conception et la planification de réseaux, l'ordonnancement, la théorie des jeux, la biologie ou la théorie des nombres, sont des problèmes NP-difficiles. Leur résolution exacte demanderait des ressources informatiques inaccessibles et ne peut donc être envisagée. Pour faire face à cette situation, un grand nombre d'algorithmes proposant des solutions approchées à ces problèmes ont été développés.
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 Geometry and Geometric Modeling
Algebraic Geometry provides an impressive theory targeting the understanding of geometric objects defined algebraically. Geometric Modeling uses every day, in order to solve practical and difficult problems, digital shapes based on algebraic models. In this book, we have collected articles bridging these two areas. The confrontation of the different points of view results in a better analysis of what the key challenges are and how they can be met. We focus on the following important classes of problems: implicitization, classification, and intersection. The combination of illustrative pictures, explicit computations and review articles will help the reader to handle these subjects.
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.
Algebraic Cycles, Sheaves, Shtukas, and Moduli : Impanga Lecture Notes
The articles in this volume are devoted to: - moduli of coherent sheaves. - principal bundles and sheaves and their moduli. - new insights into Geometric Invariant Theory. - stacks of shtukas and their compactifications. - algebraic cycles vs. commutative algebra. - Thom polynomials of singularities. - zero schemes of sections of vector bundles.
Algebra and Coalgebra in Computer Science; First International Conference, CALCO 2005, Swansea, UK, September 3-6, 2005, Proceedings
CALCO, the Conference on Algebra and Coal-gebra in Computer Science, was created to bring together researchers and practitio-ners to exchange new results related to foundational aspects, and both traditional and emerging uses of algebras and coalgebras in computer science. CALCO 2005 was the first instance of this new conference. The interest that it generated in the scientific community suggests that it will not be the last. Indeed, it attracted as many as 62 submissions covering a wide range of topics roughly divided into two areas: Algebras and Coalgebras as Mathematical Objects: Automata and languages; categorical semantics; hybrid, probabilistic, and timed systems; inductive and coin-ductive methods; modal logics; relational systems and term rewriting.
Alcohol problems in adolescents and young adults : Epidemiology. neurobiology. prevention. and treatment
Alcohol continues to be the substance of choice for today’s youth, leading to serious physical, psychological, and social consequences. Alcohol Problems in Adolescents and Young Adults ably addresses this growing trend. The latest entry in the Recent Developments in Alcoholism series, it comprehensively presents a wide-ranging clinical picture of teen drinking - epidemiology, neurobiology, behavioral phenomena, diagnostic and assessment issues, prevention and treatment data - in a developmental context. Fifty expert contributors display the scientific rigor, practical wisdom, and nuanced analysis that readers have come to expect from previous volumes.
Ajax Patterns and Best Practices
Ajax is taking us into the next generation of web applications. Ajax has broken the client-server barrier by decoupling the client from the server, but an Ajax application still needs a server to extract content from. The most effective use of Ajax and the server requires an understanding of REST, an architectural style used to define Web services. Ajax Patterns and Best Practices explores dynamic web applications that combine Ajax and REST as a single solution. A major advantage of REST is that, like Ajax, it can be used with today's existing technologies.
