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Modelli Matematici in Biologia = Mathematical Models in Biology
This text is addressed first of all to the students of the Specialist Degrees in Biology of the Universities, but it will also be of interest to students of Natural Sciences and Medicine. The topics covered include the most classic mathematical models of biological phenomena (population dynamics, spread of infectious diseases, simple physiology models), but a relevant part of the text is dedicated to the mathematical approach to the theory of natural evolution. The only prerequisites required of the reader are those provided by the basic courses of Mathematics of the Bachelor's Degree in Biology, Natural Sciences or Medicine.
Modelli Dinamici Discreti = Discrete Dynamic Models
Discrete mathematical modeling is one of the driving factors in modern mathematics research, and has played a role of synthesis between different disciplines, becoming a tool for qualitative and quantitative analysis in applied sciences. This volume provides an introduction to the analysis of discrete dynamic systems, following a modeling approach. An examination of a wide range of examples, models, and motivations drawn from Biology, Demography, Engineering and Economics, is followed by the presentation of the tools for the study of linear and non-linear scalar dynamical systems, with particular attention to stability analysis. The linear difference equations are studied in detail and an elementary introduction to the Z and DFT transforms is provided. One chapter is devoted to the study of bifurcations and chaotic dynamics. One-step vector dynamical systems and the applications of Markov chains are the subject of three chapters.
Modeling, Estimation and Control : Festschrift in Honor of Giorgio Picci on the Occasion of his Sixty-Fifth Birthday
Coefficients of Variations in Analysis of Macro-Policy Effects: An example of two-parameter Poisson-Dirichlet distributions.- How Many Experiments Are Needed to Adapt?- A Mutual Information Based Distance for Multivariate Gaussian Processes.- Differential Forms and Dynamical Systems.- An Algebraic Framework for Bayes Nets of Time Series.- A Birds Eye View on System Identification.- Further Results on the Byrnes-Georgiou-Lindquist Generalized Moment Problem.- Factor Analysis and Alternating Minimization.- Tensored PolynomialModels.- Distances Between Time-Series and Their Autocorrelation Statistics.- Global Identifiability of Complex Models, Constructed from Simple Submodels.- Identification of Hidden MarkovModels - Uniform LLN-s.- Identifiability and Informative Experiments in Open and Closed-Loop Identification.- On Interpolation and the Kimura-Georgiou Parametrization.- The Control of Error in Numerical Methods.- Contour Reconstruction and Matching Using Recursive Smoothing Splines.- Role of LQ Decomposition in Subspace Identification Methods.- Canonical Operators on Graphs.
Modeling, Control and Implementation of Smart Structures : A FEM-State Space Approach
This monograph presents an introductory overview of smart structures, their concepts, their active involvement in the vibration control, their applications and the extensive research work done on it so far. The modelling of flexible beams using two types of beam theories, viz., the Euler-Bernoulli theory and the Timoshenko beam theory is presented, including a new concept of finite element modeling of the flexible structures using Timoshenko beam theory with the inclusion of the shear both in the piezo-patches as well as in the host structure. It presents the design of the periodic output feedback control system for smart structure systems, the design of the FOS controllers for active vibration control and the design of Discrete Sliding Mode controllers using multirate output feedback technique.
Modeling with Itô Stochastic Differential Equations
This modeling procedure is thoroughly explained and illustrated for randomly varying systems in population biology, chemistry, physics, engineering, and finance. Introductory chapters present the fundamental concepts of random variables, stochastic processes, stochastic integration, and stochastic differential equations. These concepts are explained in a Hilbert space setting which unifies and simplifies the presentation. Computer programs, given throughout the text, are useful in solving representative stochastic problems. Analytical and computational exercises are provided in each chapter that complement the material in the text.
Modeling Solid Oxide Fuel Cells : Methods, Procedures and Techniques
The volume is structured in two parts. Part one presents the basic theory, and the general equations describing SOFC operation phenomena. Part two deals with the application of the theory to practical examples, where different SOFC geometries, configurations (from single cells to hybrid systems), operating conditions (steady-state and dynamic), and different phenomena (e.g. performance, temperature and chemical species, and mechanical stress distribution) are analyzed in detail.
Modeling Solar Radiation at the Earth’s Surface : Recent Advances
Solar radiation data is important for a wide range of applications, e.g. in engineering, agriculture, health sector, and in many fields of the natural sciences. A few examples showing the diversity of applications may include: architecture and building design e.g. air conditioning and cooling systems; solar heating system design and use; solar power generation; weather and climate prediction models; evaporation and irrigation; calculation of water requirements for crops; monitoring plant growth and disease control; skin cancer research.
Modeling Semantic Web Services : The Web Service Modeling Language
In this book, Jos de Bruijn and his coauthors lay the foundations for understanding the requirements that shape the description of the various aspects related to Semantic Web services, such as the static background knowledge in the form of ontologies, the functional description of the service, and the behavioral description of the service. They introduce the Web Service Modeling Language (WSML), which provides means for describing the functionality and behavior of Web services, as well as the underlying business knowledge, in the form of ontologies, with a conceptual grounding in the Web Service Modeling Ontology.
Modeling Decisions for Artificial Intelligence ; Vol.3885 ; 3rd International Conference, MDAI 2006, Tarragona, Spain, April 3-5, 2006, Proceedings
This book constitutes the refereed proceedings of the Third International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2006, held in Tarragona, Spain, in April 2006.
Modeling decisions : Information fusion and aggregation operators
This book covers the underlying science and application issues related to aggregation operators, focusing on tools used in practical applications that involve numerical information. Starting with detailed introductions to information fusion and integration, measurement and probability theory, fuzzy sets, and functional equations.
Modeling Complex Living Systems : A Kinetic Theory and Stochastic Game Approach
Using tools from mathematical kinetic theory and stochastic game theory, this work deals with the modeling of large complex systems in the applied sciences, particularly those comprised of several interacting individuals whose dynamics follow rules determined by some organized, or even "intelligent" ability. Traditionally, methods of mathematical kinetic theory have been applied to model the evolution of large systems of interacting classical or quantum particles. This book, on the other hand, examines the modeling of living systems as opposed to inert systems.
Modeling Communication with Robots and Virtual Humans ; Second ZiF Research Group International Workshop on Embodied Communication in Humans and Machines, Bielefeld, Germany, April 5-8, 2006, Revised Selected Papers
The 17 articles in this state-of-the-art survey address artificial intelligence research on communicative agents and also provide an interdisciplinary perspective from linguistics, behavioral research, theoretical biology, philosophy, communication psychology, and computational neuroscience. The topics include studies on human multimodal communication; the modeling of feedback signals, facial expression, eye contact, and deception; the recognition and comprehension of hand gestures and head movements; communication interfaces for humanoid robots; the evolution of cognition and language; emotion and social appraisal in nonverbal communication; dialogue models and methodologies; theory of mind and intentionality; complex systems, dynamic field theory, and connectionist modeling.
Modeling Chemical Systems using Cellular Automata
The book will be of great value in undergraduate courses in chemistry, physics, biology, applied mathematics, and bioinformatics, and as a supplement for laboratory courses in introductory chemistry, organic chemistry, physical chemistry, medicinal chemistry, chemical engineering and other courses dealing with statistical and dynamic systems. It allows the exploration of a wide range of dynamic phenomena, many of which are not normally accessible within conventional laboratory settings due to limitations of time, cost, and experimental equipment. The book is both a textbook on applied Cellular Automata and a lab manual for chemistry (physics, engineering) courses with lab activity. It would supplement other lab work and be an additonal book the students would use in the course.
Modeling biological systems : Principles and applications
This extensively revised second edition of Modeling Biological Systems: Principles and Applications describes the essentials of creating and analyzing mathematical and computer simulation models for advanced undergraduates and graduate students. It offers a comprehensive understanding of the underlying principle, as well as details and equations applicable to a wide variety of biological systems and disciplines. Students will acquire from this text the tools necessary to produce their own models. The text contains two major sections: Principles and Applications. The first section discusses the principles of biological systems with a thorough description of the essential modeling activities of formulation, implementation, validation, and analysis. These activities are illustrated by a set of example models taken from recent and classical literature, chosen for their breadth of coverage and current timeliness. The new edition updates extensively many of these topics, especially quantitative model formulation, validation and model discrimination using information theory measures and Bayesian probability, and stability analysis and non-dimensionalization.
Modeling and using context ; 6th International and interdisciplinary Conference, CONTEXT 2007, Roskilde, Denmark, August 20-24, 2007, Proceedings
This volume contains the papers presented at CONTEXT 2007, the Sixth International and Interdisciplinary Conference on Modeling and Using Context. We believe that the papers of this volume represent a snapshot of current work and contribute to both theoretical and applied aspects of research.
Modeling and Using Context ; 5th International and Interdisciplinary Conference, CONTEXT 2005, Paris, France, July 5-8, 2005, Proceedings
Context is of crucial importance for research and applications in many disciplines, as evidenced by many workshops, symposia, seminars, and conferences on specific aspects of context. The International and Interdisciplinary Conference on Modeling and Using Context (CONTEXT), the oldest conference series focusing on context, provides a unique interdisciplinary emphasis, bringing together participants from a wide range of disciplines, including artificial intelligence, cognitive science, computer science, linguistics, organizational science, philosophy, psychology, ubiquitous computing, and application areas such as medicine and law, to discuss and report on context-related research and projects. Previous CONTEXT conferences were held in Rio de Janeiro, Brazil (1997), Trento, Italy (1999, LNCS 1688), Dundee, UK (2001, LNCS 2116), and Palo Alto, USA (2003, LNCS 2680). CONTEXT 2005 was held in Paris, France during July 5–8, 2005. There was a strong response to the CONTEXT 2005 Call for Papers, with 120 submissions received. A careful review process assessed all submissions, with each paper first reviewed by the international Program Committee, and then reviewer discussions were initiated as needed to assure that the final decisions carefully considered all aspects of each paper. Reviews of submissions by the Program Chairs were supervised independently and anonymously, to assure fair consideration of all work. Out of the 120 submissions, 23 were selected as full papers for oral presentation, and 20 were selected as full papers for poster presentation. These outstanding papers are presented in this proceedings.
Modeling and simulation of complex communication networks
Covers important topics and approaches related to the modeling and simulation of complex communication networks from a complex adaptive systems perspective. The authors present different modeling paradigms and approaches as well as surveys and case studies. Modern network systems such as Internet of Things, Smart Grid, VoIP traffic, Peer-to-Peer protocol, and social networks, are inherently complex. They require powerful and realistic models and tools not only for analysis and simulation but also for prediction. With contributions from an international panel of experts, this book is essential reading for networking, computing, and communications professionals, researchers and engineers in the field of next generation networks and complex information and communication systems, and academics and advanced students working in these fields.
Modeling and Simulation in Scilab
Scilab is a free open-source software package for scientific computation. It includes hundreds of general purpose and specialized functions for numerical computation, organized in libraries called toolboxes, which cover such areas as simulation, optimization, systems and control, and signal processing. One important Scilab toolbox is Scicos. Scicos provides a block diagram graphical editor for the construction and simulation of dynamical systems. The objective of this book is to provide a tutorial for the use of Scilab/Scicos with a special emphasis on modeling and simulation tools. The book is divided into two parts. The first part concerns Scilab and includes a tutorial covering the language features, the data structures and specialized functions for doing graphics, importing, exporting data and interfacing external routines. It also covers in detail Scilab numerical solvers for ordinary differential equations and differential-algebraic equations. Even though the emphasis is placed on modeling and simulation applications, this part provides a global view of Scilab. The second part is dedicated to modeling and simulation of dynamical systems in Scicos. This type of modeling tool is widely used in industry because it provides a means for constructing modular and reusable models. This part contains a detailed description of the editor and its usage, which is illustrated through numerous examples.
Modeling and Simulation for RF System Design
The focus of Modeling and Simulation for RF System Design lies on RF specific modeling and simulation methods and the consideration of system and circuit level descriptions. It contains application-oriented training material for RF designers which combines the presentation of a mixed-signal design flow.
Modeling and Management of Fuzzy Semantic RDF Data
Presents the latest research findings in fuzzy RDF data modeling and management. Fuzziness widely exist in many data and knowledge intensive applications. With the increasing amount of metadata available, efficient and scalable management of massive semantic data with uncertainty is of crucial importance. This book goes to great depth concerning the fast-growing topic of technologies and approaches of modeling and managing fuzzy metadata with Resource Description Framework (RDF) format. Its major topics include representation of fuzzy RDF data, fuzzy RDF graph matching, query of fuzzy RDF data, and persistence of fuzzy RDF data in diverse databases. The objective of the book is to provide the state-of-the-art information to researchers, practitioners, and postgraduates students who work on the area of big data intelligence and at the same time serve as the uncertain data and knowledge engineering professional as a valuable real-world reference.
