الصفحة 9
الصفحة 9
Cohesion, coherence and temporal reference from an experimental corpus pragmatics perspective
Provides new methodological and theoretical insights into temporal reference and its linguistic expression, from a cross-linguistic experimental corpus pragmatics approach. Verbal tenses, in general, and more specifically the categories of tense, grammatical and lexical aspect are treated as cohesion ties contributing to the temporal coherence of a discourse, as well as to the cognitive temporal coherence of the mental representations built in the language comprehension process. As such, it investigates the phenomenon of temporal reference at the interface between corpus linguistics, theoretical linguistics and pragmatics, experimental pragmatics, psycholinguistics, natural language processing and machine translation.
Mathematical Knowledge Management ; Vol. 4108 ; 5th International Conference, MKM 2006, Wokingham, UK, August 11-12, 2006, Proceedings
This book constitutes the refereed proceedings of the 5th International Conference on Mathematical Knowledge Management, MKM 2006, held in Wokingham, UK in August 2006 as official satellite event of the International Congress of Mathematicians, ICM 2006. The 22 revised full papers presented were carefully selected during two rounds of reviewing and improvement. The papers in this volume cover the whole area of mathematical knowledge management in the intersection of mathematics, computer science, library science, and scientific publishing. The papers are organized in topical sections on proof representations, proof processing, knowledge extraction, knowledge representation, as well as systems and tools.
Mathematical Formulas for Economists
This collection of formulas constitutes a compendium of mathematics for eco nomics and business. It contains the most important formulas, statements and algorithms in this significant subfield of modern mathematics and addresses primarily students of economics or business at universities, colleges and trade schools. But people dealing with practical or applied problems will also find this collection to be an efiicient and easy-to-use work of reference. First the book treats mathematical symbols and constants, sets and state ments, number systems and their arithmetic as well as fundamentals of com binatorics. The chapter on sequences and series is followed by mathematics of finance, the representation of functions of one and several independent vari ables, their differential and integral calculus and by differential and difference equations. In each case special emphasis is placed on applications and models in economics. The chapter on linear algebra deals with matrices, vectors, determinants and systems of linear equations. This is followed by the representation of struc tures and algorithms of linear programming. Finally, the reader finds formu las on descriptive statistics (data analysis, ratios, inventory and time series analysis), on probability theory (events, probabilities, random variables and distributions) and on inductive statistics (point and interval estimates, tests). Some important tables complete the work.
Mathematica for Theoretical Physics : Electrodynamics, Quantum Mechanics, General Relativity, and Fractals
Mathematica for Theoretical Physics: Electrodynamics, Quantum Mechanics, General Relativity, and Fractals This second edition of Baumann's Mathematica® in Theoretical Physics shows readers how to solve physical problems and deal with their underlying theoretical concepts while using Mathematica® to derive numeric and symbolic solutions. Each example and calculation can be evaluated by the reader, and the reader can change the example calculations and adopt the given code to related or similar problems. The second edition has been completely revised and expanded into two volumes: The first volume covers classical mechanics and nonlinear dynamics. Both topics are the basis of a regular mechanics course. The second volume covers electrodynamics, quantum mechanics, relativity, and fractals and fractional calculus. New examples have been added and the representation has been reworked to provide a more interactive problem-solving presentation. This book can be used as a textbook or as a reference work, by students and researchers alike. A brief glossary of terms and functions is contained in the appendices.
Mathematica for Theoretical Physics : Classical Mechanics and Nonlinear Dynamics
Mathematica for Theoretical Physics: Classical Mechanics and Nonlinear Dynamics This second edition of Baumann's Mathematica® in Theoretical Physics shows readers how to solve physical problems and deal with their underlying theoretical concepts while using Mathematica® to derive numeric and symbolic solutions. Each example and calculation can be evaluated by the reader, and the reader can change the example calculations and adopt the given code to related or similar problems. The second edition has been completely revised and expanded into two volumes: The first volume covers classical mechanics and nonlinear dynamics. Both topics are the basis of a regular mechanics course. The second volume covers electrodynamics, quantum mechanics, relativity, and fractals and fractional calculus. New examples have been added and the representation has been reworked to provide a more interactive problem-solving presentation. This book can be used as a textbook or as a reference work, by students and researchers alike. A brief glossary of terms and functions is contained in the appendices.
Materials and meaning in architecture : Essays on the bodily experience of buildings
Interweaving architecture, philosophy and cultural history, Materials and Meaning in Architecture develops a rich and multi-dimensional exploration of materials and materiality, in an age when architectural practice seems otherwise preoccupied with image and visual representation.
Materials and Interior Design - Portfolio Skills
Examines every aspect of the the use of materials in interior design, from initial concept and selection to visual representation and practical application.
Managing Large-Scale Service Deployment ; 19th IFIP/IEEE International Workshop on Distributed Systems : Operations and Management, DSOM 2008, Samos Island, Greece, September 22-26, 2008. Proceedings
Contains all papers accepted for presentation at the 19th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management (DSOM 2008),which was held September 25-26, 2008 on the island of Samos, Greece. DSOM 2008 was the 19th event in a series of annual workshops. It followed in the footsteps of previous s- cessful meetings, the most recent of which were held in San Jos´ e, California, USA (DSOM 2007), Dublin, Ireland (DSOM 2006), Barcelona, Spain (DSOM 2005), Davis, California, USA (DSOM 2004), Heidelberg, Germany (DSOM 2003), and Montreal, Canada (DSOM 2002).
Machine Learning in Computer Vision
The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.
Machine learning approach for cloud data analytics in IoT
Covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications. Elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
Machine Learning Applications in Civil Engineering
Discusses machine learning and deep learning models for different civil engineering applications. These models work for stochastic methods wherein internal processing is done using randomized prototypes. The book explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency. It introduces Machine Learning and its applications to different Civil Engineering tasks, including Basic Machine Learning Models for data pre-processing, models for data representation, classification models for Civil Engineering Applications, Bioinspired Computing models for Civil Engineering, and their case studies.
Logical Foundations for Rule-Based Systems
Presents logical foundations for rule-based systems, as seen by the Author. An attempt has been made to provide an in-depth discussion of logical and other aspects of such systems, including languages for knowledge representation, inference mechanisms, inference control, design and verification.
Logical and Relational Learning
This textbook covers logical and relational learning in depth, and hence provides an introduction to inductive logic programming (ILP), multirelational data mining (MRDM) and (statistical) relational learning (SRL). These subfields of data mining and machine learning are concerned with the analysis of complex and structured data sets that arise in numerous applications, such as bio- and chemoinformatics, network analysis, Web mining, natural language processing, within the rich representations offered by relational databases and computational logic.
Logic Programming and Nonmonotonic Reasoning ; 9th International Conference, LPNMR 2007, Tempe, AZ, USA, May 15-17, 2007, Proceedings
This book constitutes the refereed proceedings of the 9th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2007, held in Tempe, AZ, USA, May 2007.
Logic Programming and Nonmonotonic Reasoning ; 8th International Conference, LPNMR 2005, Diamante, Italy, September 5-8, 2005, Proceedings
Thesearetheproceedingsofthe8thInternational Conference on Logic Progr- mingandNonmonotonicReasoning (LPNMR2005).Followingthepreviousones held in Washington, DC, USA (1991), Lisbon, Portugal (1993), Lexington, KY, USA(1995), Dagstuhl, Germany(1997), ElPaso, TX, USA(1999), Vienna, A- tria (2001) and Ft. Lauderdale, FL, USA (2004), the eighth conference was held in Diamante, Italy, from 5th to 8th of September 2005. TheaimoftheLPNMRconferencesistobringtogetherandfacilitateinter- tions between active researchers interested in all aspects concerning declarative logic programming, nonmonotonic reasoning, knowledge representation, and the design of logic-based systems and database systems. LPNMR strives to enc- pass theoretical and experimental studies that lead to the implementation of practi...
Logic for Programming, Artificial Intelligence, and Reasoning ; 15th International Conference, LPAR 2008, Doha, Qatar, November 22-27, 2008. Proceedings
This book constitutes the refereed proceedings of the 15th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2008, which took place in Doha, Qatar, during November 22-27, 2008.The 45 revised full papers presented together with 3 invited talks were carefully revised and selected from 153 submissions. The papers address all current issues in automated reasoning, computational logic, programming languages and their applications and are organized in topical sections on automata, linear arithmetic, verification knowledge representation, proof theory, quantified constraints, as well as modal and temporal logics.
Local Newforms for GSp(4)
Local Newforms for GSp(4) describes a theory of new- and oldforms for representations of GSp(4) over a non-archimedean local field. This theory considers vectors fixed by the paramodular groups, and singles out certain vectors that encode canonical information, such as L-factors and epsilon-factors, through their Hecke and Atkin-Lehner eigenvalues. While there are analogies to the GL(2) case, this theory is novel and unanticipated by the existing framework of conjectures. An appendix includes extensive tables about the results and the representation theory of GSp(4).
LMI Approach to Analysis and Control of Takagi-Sugeno Fuzzy Systems with Time Delay
A fuzzy system is, in a very broad sense, any fuzzy logic-based system where fuzzy logic can be used either asthebasisfor the representation of different forms of system knowledge or the model for the interactions and relationships among the system variables. Fuzzy systems have proven to be an important tool for modeling complex systems for which, due to complexity or imprecision, classical tools are unsuccessful. There have been diverse fields of applications of fuzzy technology from medicine to management, from engineering to behavioral science, from vehicle control to computational linguistics, and so on. Fuzzy modeling is a conjunction to understand the s- tem’s behavior and build useful mathematical models. Different types of fuzzy models have been proposed in the literature, among which the Takagi-Sugeno (T-S) fuzzy model is a rule-based one suitable for the accurate approximation and identi?cation of a wide class of nonlinear systems.
Linearity, Symmetry, and Prediction in the Hydrogen Atom
The predictive power of mathematics in quantum phenomena is one of the great intellectual successes of the 20th century. This textbook, aimed at undergraduate or graduate level students (depending on the college or university), concentrates on how to make predictions about the numbers of each kind of basic state of a quantum system from only two ingredients: the symmetry and the linear model of quantum mechanics. This method, involving the mathematical area of representation theory or group theory, combines three core mathematical subjects, namely, linear algebra, analysis and abstract algebra. Wide applications of this method occur in crystallography, atomic structure, classification of manifolds with symmetry, and other areas.
Linear Systems
Linear systems theory plays a broad and fundamental role in electrical, mechanical, chemical and aerospace engineering, communications, and signal processing. A thorough introduction to systems theory with emphasis on control is presented in this self-contained textbook. The book examines the fundamental properties that govern the behavior of systems by developing their mathematical descriptions. Linear time-invariant, time-varying, continuous-time, and discrete-time systems are covered. Rigorous development of classic and contemporary topics in linear systems, as well as extensive coverage of stability and polynomial matrix/fractional representation, provide the necessary foundation for further study of systems and control.
