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This book ranks countries with respect to their achievement of the
Sustainable Development Goals and their vulnerability to climate
change. Human livelihoods, stable economies, health, and high
quality of life all depend on a stable climate and earth system,
and a diversity of species and ecosystems. Climate change
significantly impacts human trafficking, modern slavery, and global
hunger. This book examines these global problems using techniques
from mathematics of uncertainty. Since accurate data concerning
human trafficking and modern slavery is impossible to obtain,
mathematics of uncertainty is an ideal discipline to study these
problems. The book also considers the interconnection between
climate change, world hunger, human trafficking, modern slavery,
and the coronavirus. Connectivity properties of fuzzy graphs are
used to examine trafficking flow between regions in the world. The
book is an excellent reference source for advanced undergraduate
and graduate students in mathematics and the social sciences as
well as for researchers and teachers.
This book uses mathematics of uncertainty to examine how well
countries are achieving the 17 Sustainable Development Goals (SDGs)
set by the members of the United Nations, with a focus on climate
change, human trafficking and modern slavery. Although this
approach has never been used before, mathematics of uncertainty is
well suited to exploring these topics due to the lack of accurate
data available. The authors place several scientific studies in a
mathematical setting to pave the way for future research on issues
of sustainability, climate change, human trafficking and modern
slavery to using a wide range of mathematical techniques. Moreover,
the book ranks countries in terms of their achievement of not only
the SDGs, but in particular those SDGs pertinent to climate change,
human trafficking, and modern slavery, and highlights the
deficiencies in the foster care system that lead to human
trafficking. As such it is an excellent reference resource for
advanced undergraduate and graduate students in mathematics and the
social sciences, as well as for researchers and teachers.
This book uses mathematics of uncertainty to examine how well
countries are achieving the 17 Sustainable Development Goals (SDGs)
set by the members of the United Nations, with a focus on climate
change, human trafficking and modern slavery. Although this
approach has never been used before, mathematics of uncertainty is
well suited to exploring these topics due to the lack of accurate
data available. The authors place several scientific studies in a
mathematical setting to pave the way for future research on issues
of sustainability, climate change, human trafficking and modern
slavery to using a wide range of mathematical techniques. Moreover,
the book ranks countries in terms of their achievement of not only
the SDGs, but in particular those SDGs pertinent to climate change,
human trafficking, and modern slavery, and highlights the
deficiencies in the foster care system that lead to human
trafficking. As such it is an excellent reference resource for
advanced undergraduate and graduate students in mathematics and the
social sciences, as well as for researchers and teachers.
This book reports on advanced concepts in fuzzy graph theory,
showing a set of tools that can be successfully applied to
understanding and modeling illegal human trafficking. Building on
the previous book on fuzzy graph by the same authors, which set the
fundamentals for readers to understand this developing field of
research, this second book gives a special emphasis to applications
of the theory. For this, authors introduce new concepts, such as
intuitionistic fuzzy graphs, the concept of independence and
domination in fuzzy graphs, as well as directed fuzzy networks,
incidence graphs and many more.
This book provides a timely overview of fuzzy graph theory, laying
the foundation for future applications in a broad range of areas.
It introduces readers to fundamental theories, such as Craine's
work on fuzzy interval graphs, fuzzy analogs of Marczewski's
theorem, and the Gilmore and Hoffman characterization. It also
introduces them to the Fulkerson and Gross characterization and
Menger's theorem, the applications of which will be discussed in a
forthcoming book by the same authors. This book also discusses in
detail important concepts such as connectivity, distance and
saturation in fuzzy graphs. Thanks to the good balance between the
basics of fuzzy graph theory and new findings obtained by the
authors, the book offers an excellent reference guide for advanced
undergraduate and graduate students in mathematics, engineering and
computer science, and an inspiring read for all researchers
interested in new developments in fuzzy logic and applied
mathematics.
This book provides an examination of major problems facing the
world using mathematics of uncertainty. These problems include
climate change, coronavirus pandemic, human tracking, biodiversity,
and other grand challenges. Mathematics of uncertainty is used in a
modern more general sense than traditional mathematics. Since
accurate data is impossible to obtain concerning human tracking and
other global problems, mathematics of uncertainty is an ideal
discipline to study these problems. The authors place several
scientific studies into different mathematical settings such as
nonstandard analysis and soft logic. Fuzzy differentiation is used
to model the spread of diseases such as the coronavirus. The book
uses fuzzy graph theory to examine the problems of human tracking
and illegal immigration. The book is an excellent reference source
for advanced under-graduate and graduate students in mathematics
and the social sciences as well as for researchers and teachers.
This book ranks countries with respect to their achievement of the
Sustainable Development Goals and their vulnerability to climate
change. Human livelihoods, stable economies, health, and high
quality of life all depend on a stable climate and earth system,
and a diversity of species and ecosystems. Climate change
significantly impacts human trafficking, modern slavery, and global
hunger. This book examines these global problems using techniques
from mathematics of uncertainty. Since accurate data concerning
human trafficking and modern slavery is impossible to obtain,
mathematics of uncertainty is an ideal discipline to study these
problems. The book also considers the interconnection between
climate change, world hunger, human trafficking, modern slavery,
and the coronavirus. Connectivity properties of fuzzy graphs are
used to examine trafficking flow between regions in the world. The
book is an excellent reference source for advanced undergraduate
and graduate students in mathematics and the social sciences as
well as for researchers and teachers.
This book examines some issues involving climate change, human
trafficking, and other serious world challenges made worse by
climate change. Climate change increases the risk of natural
disasters and thus creates poverty and can cause situations of
conflict and instability. Displacement can occur giving traffickers
an opportunity to exploit affected people. In the fuzzy graph
theory part of the book, the relatively new concepts of fuzzy soft
semigraphs and graph structures are used to study human
trafficking, as well as its time intuitionistic fuzzy sets that
have been introduced to model forest fires. The notion of legal and
illegal incidence strength is used to analyze immigration to the
USA. The examination of return refugees to their origin countries
is undertaken. The neighborhood connectivity index is determined
for trafficking in various regions in the world. The cycle
connectivity measure for the directed graph of the flow from South
America to the USA is calculated. It is determined that there is a
need for improvement in government response by countries. Outside
the area of fuzzy graph theory, a new approach to examine climate
change is introduced. Social network theory is used to study
feedback processes that effect climate forcing. Tipping points in
climate change are considered. The relationship between terrorism
and climate change is examined. Ethical issues concerning the
obligation of business organizations to reduce carbon emissions are
also considered. Nonstandard analysis is a possible new area that
could be used by scholars of mathematics of uncertainty. A
foundation is laid to aid the researcher in the understanding of
nonstandard analysis. In order to accomplish this, a discussion of
some basic concepts from first-order logic is presented as some
concepts of mathematics of uncertainty. An application to the
theory of relativity is presented.
This book provides an examination of major problems facing the
world using mathematics of uncertainty. These problems include
climate change, coronavirus pandemic, human tracking, biodiversity,
and other grand challenges. Mathematics of uncertainty is used in a
modern more general sense than traditional mathematics. Since
accurate data is impossible to obtain concerning human tracking and
other global problems, mathematics of uncertainty is an ideal
discipline to study these problems. The authors place several
scientific studies into different mathematical settings such as
nonstandard analysis and soft logic. Fuzzy differentiation is used
to model the spread of diseases such as the coronavirus. The book
uses fuzzy graph theory to examine the problems of human tracking
and illegal immigration. The book is an excellent reference source
for advanced under-graduate and graduate students in mathematics
and the social sciences as well as for researchers and teachers.
This book reports on advanced concepts in fuzzy graph theory,
showing a set of tools that can be successfully applied to
understanding and modeling illegal human trafficking. Building on
the previous book on fuzzy graph by the same authors, which set the
fundamentals for readers to understand this developing field of
research, this second book gives a special emphasis to applications
of the theory. For this, authors introduce new concepts, such as
intuitionistic fuzzy graphs, the concept of independence and
domination in fuzzy graphs, as well as directed fuzzy networks,
incidence graphs and many more.
This book builds on two recently published books by the same
authors on fuzzy graph theory. Continuing in their tradition, it
provides readers with an extensive set of tools for applying fuzzy
mathematics and graph theory to social problems such as human
trafficking and illegal immigration. Further, it especially focuses
on advanced concepts such as connectivity and Wiener indices in
fuzzy graphs, distance, operations on fuzzy graphs involving
t-norms, and the application of dialectic synthesis in fuzzy graph
theory. Each chapter also discusses a number of key, representative
applications. Given its approach, the book provides readers with an
authoritative, self-contained guide to - and at the same time an
inspiring read on - the theory and modern applications of fuzzy
graphs. For newcomers, the book also includes a brief introduction
to fuzzy sets, fuzzy relations and fuzzy graphs.
This book provides a timely overview of fuzzy graph theory, laying
the foundation for future applications in a broad range of areas.
It introduces readers to fundamental theories, such as Craine's
work on fuzzy interval graphs, fuzzy analogs of Marczewski's
theorem, and the Gilmore and Hoffman characterization. It also
introduces them to the Fulkerson and Gross characterization and
Menger's theorem, the applications of which will be discussed in a
forthcoming book by the same authors. This book also discusses in
detail important concepts such as connectivity, distance and
saturation in fuzzy graphs. Thanks to the good balance between the
basics of fuzzy graph theory and new findings obtained by the
authors, the book offers an excellent reference guide for advanced
undergraduate and graduate students in mathematics, engineering and
computer science, and an inspiring read for all researchers
interested in new developments in fuzzy logic and applied
mathematics.
One of the remarkable mathematical inventions of the 20th century
is that of Fuzzy sets by Lotfi.A.Zadeh in 1965. His aim was to
develop a mathematical theory to deal with uncertainty and
imprecision. Fuzzy logic and the theory of fuzzy sets have been
applied widely in areas like information theory, pattern
recognition, clustering, expert systems, database theory, control
theory, robotics, networks and nanotechnology. A.Rosenfeld
introduced fuzzy graphs in 1975 to deal with relations involving
uncertainty. In this book we present basic concepts in fuzzy graph
connectivity, which plays a remarkable role in information networks
and quality based clustering. This book consists of seven chapters.
The first chapter includes motivation and basic results. Arc
analysis of fuzzy graph structures, cycles in fuzzy graphs, blocks
in fuzzy graphs, cycle connectivity of fuzzy graphs are discussed
in the subsequent chapters. We believe that this book will help
students, researchers and faculty of different institutes around
the world to do fruitful research in fuzzy graph theory and related
areas.
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