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Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling
Quantifying and Managing Soil Functions in Earth's Critical Zone:
Combining Experimentation and Mathematical Modelling, Volume 142,
the latest in the Advances in Agronomy series continues its
reputation as a leading reference and first-rate source for the
latest research in agronomy. Each volume contains an eclectic group
of reviews by leading scientists throughout the world. Five volumes
are published yearly, ensuring that the authors' contributions are
disseminated to the readership in a timely manner. As always, the
subjects covered are varied and exemplary of the myriad of subject
matter dealt with by this long-running serial.
In July 2009, many experts in the mathematical modeling of
biological sciences gathered in Les Houches for a 4-week summer
school on the mechanics and physics of biological systems. The goal
of the school was to present to students and researchers an
integrated view of new trends and challenges in physical and
mathematical aspects of biomechanics. While the scope for such a
topic is very wide, they focused on problems where solid and fluid
mechanics play a central role. The school covered both the general
mathematical theory of mechanical biology in the context of
continuum mechanics but also the specific modeling of particular
systems in the biology of the cell, plants, microbes, and in
physiology.
These lecture notes are organized (as was the school) around five
different main topics all connected by the common theme of
continuum modeling for biological systems: Bio-fluidics, Bio-gels,
Bio-mechanics, Bio-membranes, and Morphogenesis. These notes are
not meant as a journal review of the topic but rather as a gentle
tutorial introduction to the readers who want to understand the
basic problematic in modeling biological systems from a mechanics
perspective.
Modelling and Control in Biomedical Systems (including Biological
Systems) was held in Reims, France, 20-22 August 2006. This
Symposium was organised by the University of Reims Champagne
Ardenne and the Societe de l Electricite, de l Electronique et des
TIC (SEE).
The Symposium attracted practitioners in engineering, information
technology, mathematics, medicine and biology, and other related
disciplines, with authors from 24 countries. Besides the abstracts
of the four plenary lectures, this volume contains the 92 papers
that were presented by their authors at the Symposium
The papers included two invited keynote presentations given by
internationally prominent and well-recognised research leaders:
Claudio Cobelli, whose talk is titled "Dynamic modelling in
diabetes: from whole body to genes"; and Irving J. Bigio, whose
talk is titled "Elastic scattering spectroscopy for non-invasive
detection of cancer." Two prestigious industrial speakers were also
invited to give keynote presentations: Terry O'Brien from LIDCO,
whose talk is titled "LIDCO: From the laboratory to protocolized
goal directed therapy"; and Lorenzo Quinzio of Philips, whose talk
is titled "Clinical decision support in monitoring and information
systems."
* A valuable source of information on the state-of- the-art in
Modelling and Control in Biomedical Systems
* Including abstracts of four plenary lectures, and 92 papers
presented by their authors"
The objective of this publication is to comprehensively discuss
the possibilities of producing steels with pre-determined
attributes, demanded by the customer to fit exacting
specifications. The information presented in the book has been
designed to indicate the reasons for the expenses and to aid in the
process of overcoming the difficulties and reducing the costs.
In nine detailed chapters, the authors cover topics including:
steel as a major contributor to the economic wealth of a country in
terms of its capabilities and production current concerns of major
steel producers phenomena contributing to the quality of the
product information concerning the boundary conditions of the
rolling process and initial conditions, put to use by mathematical
models the solid state incremental approach and flow formulation
parameters and variables - most of which make use of the
exponential nature of phenomena that are activated by thermal
energy the application of three dimensional analysis to shape
rolling the evaluation of parameters by a form of inverse analysis
to the flat rolling process knowledge based modeling, using
artificial intelligence, expert systems and neural networks
They conclude that when either mathematical or physical modeling of
the rolling process is considered and the aim is to satisfy the
demands for customers, it is possible to produce what the customer
wants, exactly.
"
This book provides a comprehensive introduction to the mathematical
theory of nonlinear problems described by singular elliptic
equations. There are carefully analyzed logistic type equations
with boundary blow-up solutions and generalized Lane-Emden-Fowler
equations or Gierer-Meinhardt systems with singular nonlinearity in
anisotropic media. These nonlinear problems appear as mathematical
models in various branches of Physics, Mechanics, Genetics,
Economics, Engineering, and they are also relevant in Quantum
Physics and Differential Geometry.
One of the main purposes of this volume is to deduce decay rates
for general classes of solutions in terms of estimates of
particular problems. Much of the material included in this volume
is devoted to the asymptotic analysis of solutions and to the
qualitative study of related bifurcation problems. Numerical
approximations illustrate many abstract results of this volume. A
systematic description of the most relevant singular phenomena
described in these lecture notes includes existence (or
nonexistence) of solutions, unicity or multiplicity properties,
bifurcation and asymptotic analysis, and optimal regularity.
The method of presentation should appeal to readers with different
backgrounds in functional analysis and nonlinear partial
differential equations. All chapters include detailed heuristic
arguments providing thorough motivation of the study developed
later on in the text, in relationship with concrete processes
arising in applied sciences. The book includes an extensive
bibliography and a rich index, thus allowing for quick orientation
among the vast collection of literature on the mathematical theory
of nonlinear singularphenomena
Mathematical modelling modules feature in most university
undergraduate mathematics courses. As one of the fastest growing
areas of the curriculum it represents the current trend in teaching
the more complex areas of mathematics. This book introduces
mathematical modelling to the new style of undergraduate - those
with less prior knowledge, who require more emphasis on application
of techniques in the following sections: What is mathematical
modelling?; Seeing modelling at work through population growth;
Seeing modelling at work through published papers; Modelling in
mechanics.
Written in the lively interactive style of the Modular Mathematics
Series, this text will encourage the reader to take part in the
modelling process.
While the significance of networks in various human behavior and
activities has a history as long as human's existence, network
awareness is a recent scientific phenomenon. The neologism network
science is just one or two decades old. Nevertheless, with this
limited time, network thinking has substantially reshaped the
recent development in economics, and almost all solutions to
real-world problems involve the network element. This book
integrates agent-based modeling and network science. It is divided
into three parts, namely, foundations, primary dynamics on and of
social networks, and applications. The authors begin with the
network origin of agent-based models, known as cellular automata,
and introduce a number of classic models, such as Schelling's
segregation model and Axelrod's spatial game. The essence of the
foundation part is the network-based agent-based models in which
agents follow network-based decision rules. Under the influence of
the substantial progress in network science in late 1990s, these
models have been extended from using lattices into using
small-world networks, scale-free networks, etc. The text also shows
that the modern network science mainly driven by game-theorists and
sociophysicists has inspired agent-based social scientists to
develop alternative formation algorithms, known as agent-based
social networks. It reviews a number of pioneering and
representative models in this family. Upon the given foundation,
the second part reviews three primary forms of network dynamics,
such as diffusions, cascades, and influences. These primary
dynamics are further extended and enriched by practical networks in
goods-and-service markets, labor markets, and international trade.
At the end, the book considers two challenging issues using
agent-based models of networks: network risks and economic growth.
As the operations of the world become more and more dependent on
highly interconnected, massively complex, networked systems of
computational devices, the need to develop a mathematical
understanding of their properties and behaviours is increasingly
pressing. Our approach, described in this monograph, is to combine
the compositionality of formal specification -- using techniques
from algebra, computation theory, logic, and probability theory --
with the control of level of abstraction afforded by the classical
mathematical modelling method.
From climate change forecasts and pandemic maps to Lego sets and
Ancestry algorithms, models encompass our world and our lives. In
her thought-provoking new book, Annabel Wharton begins with a
definition drawn from the quantitative sciences and the philosophy
of science but holds that history and critical cultural theory are
essential to a fuller understanding of modeling. Considering
changes in the medical body model and the architectural model, from
the Middle Ages to the twenty-first century, Wharton demonstrates
the ways in which all models are historical and political.
Examining how cadavers have been described, exhibited, and visually
rendered, she highlights the historical dimension of the modified
body and its depictions. Analyzing the varied reworkings of the
Holy Sepulchre in Jerusalem-including by monumental commanderies of
the Knights Templar, Alberti's Rucellai Tomb in Florence,
Franciscans' olive wood replicas, and video game renderings-she
foregrounds the political force of architectural representations.
And considering black boxes-instruments whose inputs we control and
whose outputs we interpret, but whose inner workings are beyond our
comprehension-she surveys the threats posed by such opaque
computational models, warning of the dangers that models pose when
humans lose control of the means by which they are generated and
understood. Engaging and wide-ranging, Models and World Making
conjures new ways of seeing and critically evaluating how we make
and remake the world in which we live.
Physiologically Based Pharmacokinetic (PBPK) Modeling: Methods and
Applications in Toxicology and Risk Assessment presents
foundational principles, advanced techniques and applications of
PBPK modeling. Contributions from experts in PBPK modeling cover
topics such as pharmacokinetic principles, classical physiological
models, the application of physiological models for dose-response
and risk assessment, the use of in vitro information, and in silico
methods. With end-of-chapter exercises that allow readers to
practice and learn the skills associated with PBPK modeling,
dose-response, and its applications to safety and risk assessments,
this book is a foundational resource that provides practical
coverage of PBPK modeling for graduate students, academics,
researchers, and more.
Flexible Bayesian Regression Modeling is a step-by-step guide to
the Bayesian revolution in regression modeling, for use in advanced
econometric and statistical analysis where datasets are
characterized by complexity, multiplicity, and large sample sizes,
necessitating the need for considerable flexibility in modeling
techniques. It reviews three forms of flexibility: methods which
provide flexibility in their error distribution; methods which
model non-central parts of the distribution (such as quantile
regression); and finally models that allow the mean function to be
flexible (such as spline models). Each chapter discusses the key
aspects of fitting a regression model. R programs accompany the
methods. This book is particularly relevant to non-specialist
practitioners with intermediate mathematical training seeking to
apply Bayesian approaches in economics, biology, finance,
engineering and medicine.
Power Systems Modelling and Fault Analysis: Theory and Practice,
Second Edition, focuses on the important core areas and technical
skills required for practicing electrical power engineers.
Providing a comprehensive and practical treatment of the modeling
of electrical power systems, the book offers students and
professionals the theory and practice of fault analysis of power
systems, covering detailed and advanced theories and modern
industry practices. The book describes relevant advances in the
industry, such as international standards developments and new
generation technologies, such as wind turbine generators, fault
current limiters, multi-phase fault analysis, the measurement of
equipment parameters, probabilistic short-circuit analysis, and
more.
The book addresses optimization in the petroleum industry from a
practical, large-scale-application-oriented point of view. The
models and techniques presented help to optimize the limited
resources in the industry in order to maximize economic benefits,
ensure operational safety, and reduce environmental impact. The
book discusses several important real-life applications of
optimization in the petroleum industry, ranging from the scheduling
of personnel time to the blending of gasoline. It covers a wide
spectrum of relevant activities, including drilling, producing,
maintenance, and distribution. The text begins with an introductory
overview of the petroleum industry and then of optimization models
and techniques. The main body of the book details a variety of
applications of optimization models and techniques within the
petroleum industry. Applied Optimization in the Petroleum
Industry helps readers to find effective optimization-based
solutions to their own practical problems in a large and important
industrial sector, still the main source of the world’s energy
and the source of raw materials for a wide variety of industrial
and consumer products.
The modelling of systems by differential equations usually requires
that the parameters involved be completely known. Such models often
originate from problems in physics or economics where we have
insufficient information on parameter values. One important class
of stochastic mathematical models is stochastic partial
differential equations (SPDEs), which can be seen as deterministic
partial differential equations (PDEs) with finite or infinite
dimensional stochastic processes - either with colour noise or
white noise. Though white noise is a purely mathematical
construction, it can be a good model for rapid random
fluctuations.This research monograph concerns analysis of
discrete-time approximations for stochastic differential equations
(SDEs) driven by Wiener processes. The first chapter of the book
provides a theoretical basis for working with SDEs and stochastic
processes.This book has been written in a simple and clear
mathematical logical language. The basic definitions and theorems
on stochastic calculus have been provided initially. Each chapter
contains illustrated examples via figures and tables. Problems are
included which will help readers understand the theories better.
Also, the reader can construct new wavelets by using the procedure
presented in the book. It will certainly fill up the blank space
that the lack of a comprehensive book has caused.
Basic mathematical techniques for partial differential equations
(PDE) with applications to the life sciences form an integral part
of the core curriculum for programs in mathematical biology. Yet,
students in such a program with an undergraduate training in
biology are typically deficient in any exposure to PDE. This volume
starts with simple first order PDE and progresses through higher
order equations and systems but with interesting applications, even
at the level of a single first order PDE with constant
coefficients.Similar to the two previous volumes by the author,
another unique feature of the book is highlighting the scientific
theme(s) of interest for the biological phenomena being modelled
and analysed. In addition to temporal evolution of a biological
phenomenon, its limiting equilibrium states and their stability,
the possibility of locational variations leads to a study of
additional themes such as (signal and wave) propagation, spatial
patterning and robustness. The requirement that biological
developments are relatively insensitive to sustained environmental
changes provides an opportunity to examine the issue of feedback
and robustness not encountered in the previous two volumes of this
series.
The Institute for Mathematical Sciences at the National University
of Singapore hosted a thematic program on Quantum and Kinetic
Problems: Modeling, Analysis, Numerics and Applications from
September 2019 to March 2020. As an important part of the program,
tutorials and special lectures were given by leading experts in the
fields for participating graduate students and junior researchers.
This invaluable volume collects six expanded lecture notes with
self-contained tutorials. The coverage includes mathematical models
and numerical methods for multidimensional solitons in linear and
nonlinear potentials; Bose-Einstein condensation (BEC) with
dipole-dipole interaction, higher order interaction and spin-orbit
coupling; classical and quantum turbulence; and molecular dynamics
process based on the first-principle in quantum chemistry.This
volume serves to inspire graduate students and researchers who will
embark into original research work in these fields.
The thematic program Quantum and Kinetic Problems: Modeling,
Analysis, Numerics and Applications was held at the Institute for
Mathematical Sciences at the National University of Singapore, from
September 2019 to March 2020. Leading experts presented tutorials
and special lectures geared towards the participating graduate
students and junior researchers.Readers will find in this
significant volume four expanded lecture notes with self-contained
tutorials on modeling and simulation for collective dynamics
including individual and population approaches for population
dynamics in mathematical biology, collective behaviors for Lohe
type aggregation models, mean-field particle swarm optimization,
and consensus-based optimization and ensemble Kalman inversion for
global optimization problems with constraints.This volume serves to
inspire graduate students and researchers who will embark into
original research work in kinetic models for collective dynamics
and their applications.
Time and Methods in Environmental Interfaces Modelling: Personal
Insights considers the use of time in environmental interfaces
modeling and introduce new methods, from the global scale (e.g.
climate modeling) to the micro scale (e.g. cell and nanotubes
modeling), which primarily arise from the personal research
insights of the authors. As the field of environmental science
requires the application of new fundamental approaches that can
lead to a better understanding of environmental phenomena, this
book helps necessitate new approaches in modeling, including
category theory, that follow new achievements in physics,
mathematics, biology, and chemistry.
Within the field of modeling complex objects in natural sciences,
which considers systems that consist of a large number of
interacting parts, a good tool for analyzing and fitting models is
the theory of random evolutionary systems, considering their
asymptotic properties and large deviations. In Random Evolutionary
Systems we consider these systems in terms of the operators that
appear in the schemes of their diffusion and the Poisson
approximation. Such an approach allows us to obtain a number of
limit theorems and asymptotic expansions of processes that model
complex stochastic systems, both those that are autonomous and
those dependent on an external random environment. In this case,
various possibilities of scaling processes and their time
parameters are used to obtain different limit results.
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