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This book reports the results of a three-year research program
funded by the National Science Foundation which targeted students
and teachers from four Detroit high schools in order for them to
learn, experience, and use IT within the context of STEM (IT/STEM),
and explore 21st century career and educational pathways. The book
discusses the accomplishment of these goals through the creation of
a Community of Designers-- an environment in which high school
students and teachers, undergraduate/graduate student assistants,
and STEM area faculty and industry experts worked together as a
cohesive team. The program created four project-based design teams,
one for each STEM area. Each team had access to two year-round
IT/STEM enrichment experiences to create high-quality learning
projects, strategies, and curriculum models. These strategies were
applied in after school, weekend, and summer settings through
hands-on, inquiry-based activities with a strong emphasis on
non-traditional approaches to learning and understanding. The book
represents the first comprehensive description and analysis of the
research program and suggests a plan for future development and
refinement.
Progressively more and more attention has been paid to how location
affects health outcomes. The area of disease mapping focusses on
these problems, and the Bayesian paradigm has a major role to play
in the understanding of the complex interplay of context and
individual predisposition in such studies of disease. Using R for
Bayesian Spatial and Spatio-Temporal Health Modeling provides a
major resource for those interested in applying Bayesian
methodology in small area health data studies. Features: Review of
R graphics relevant to spatial health data Overview of Bayesian
methods and Bayesian hierarchical modeling as applied to spatial
data Bayesian Computation and goodness-of-fit Review of basic
Bayesian disease mapping models Spatio-temporal modeling with MCMC
and INLA Special topics include multivariate models, survival
analysis, missing data, measurement error, variable selection,
individual event modeling, and infectious disease modeling Software
for fitting models based on BRugs, Nimble, CARBayes and INLA
Provides code relevant to fitting all examples throughout the book
at a supplementary website The book fills a void in the literature
and available software, providing a crucial link for students and
professionals alike to engage in the analysis of spatial and
spatio-temporal health data from a Bayesian perspective using R.
The book emphasizes the use of MCMC via Nimble, BRugs, and
CARBAyes, but also includes INLA for comparative purposes. In
addition, a wide range of packages useful in the analysis of
geo-referenced spatial data are employed and code is provided. It
will likely become a key reference for researchers and students
from biostatistics, epidemiology, public health, and environmental
science.
Since the publication of the second edition, many new Bayesian
tools and methods have been developed for space-time data analysis,
the predictive modeling of health outcomes, and other spatial
biostatistical areas. Exploring these new developments, Bayesian
Disease Mapping: Hierarchical Modeling in Spatial Epidemiology,
Third Edition provides an up-to-date, cohesive account of the full
range of Bayesian disease mapping methods and applications. In
addition to the new material, the book also covers more
conventional areas such as relative risk estimation, clustering,
spatial survival analysis, and longitudinal analysis. After an
introduction to Bayesian inference, computation, and model
assessment, the text focuses on important themes, including disease
map reconstruction, cluster detection, regression and ecological
analysis, putative hazard modeling, analysis of multiple scales and
multiple diseases, spatial survival and longitudinal studies,
spatiotemporal methods, and map surveillance. It shows how Bayesian
disease mapping can yield significant insights into georeferenced
health data. The target audience for this text is public health
specialists, epidemiologists, and biostatisticians who need to work
with geo-referenced health data.
Progressively more and more attention has been paid to how location
affects health outcomes. The area of disease mapping focusses on
these problems, and the Bayesian paradigm has a major role to play
in the understanding of the complex interplay of context and
individual predisposition in such studies of disease. Using R for
Bayesian Spatial and Spatio-Temporal Health Modeling provides a
major resource for those interested in applying Bayesian
methodology in small area health data studies. Features: Review of
R graphics relevant to spatial health data Overview of Bayesian
methods and Bayesian hierarchical modeling as applied to spatial
data Bayesian Computation and goodness-of-fit Review of basic
Bayesian disease mapping models Spatio-temporal modeling with MCMC
and INLA Special topics include multivariate models, survival
analysis, missing data, measurement error, variable selection,
individual event modeling, and infectious disease modeling Software
for fitting models based on BRugs, Nimble, CARBayes and INLA
Provides code relevant to fitting all examples throughout the book
at a supplementary website The book fills a void in the literature
and available software, providing a crucial link for students and
professionals alike to engage in the analysis of spatial and
spatio-temporal health data from a Bayesian perspective using R.
The book emphasizes the use of MCMC via Nimble, BRugs, and
CARBAyes, but also includes INLA for comparative purposes. In
addition, a wide range of packages useful in the analysis of
geo-referenced spatial data are employed and code is provided. It
will likely become a key reference for researchers and students
from biostatistics, epidemiology, public health, and environmental
science.
Handbook of Spatial Epidemiology explains how to model
epidemiological problems and improve inference about disease
etiology from a geographical perspective. Top epidemiologists,
geographers, and statisticians share interdisciplinary viewpoints
on analyzing spatial data and space-time variations in disease
incidences. These analyses can provide important information that
leads to better decision making in public health. The first part of
the book addresses general issues related to epidemiology, GIS,
environmental studies, clustering, and ecological analysis. The
second part presents basic statistical methods used in spatial
epidemiology, including fundamental likelihood principles, Bayesian
methods, and testing and nonparametric approaches. With a focus on
special methods, the third part describes geostatistical models,
splines, quantile regression, focused clustering, mixtures,
multivariate methods, and much more. The final part examines
special problems and application areas, such as residential history
analysis, segregation, health services research, health surveys,
infectious disease, veterinary topics, and health surveillance and
clustering. Spatial epidemiology, also known as disease mapping,
studies the geographical or spatial distribution of health
outcomes. This handbook offers a wide-ranging overview of
state-of-the-art approaches to determine the relationships between
health and various risk factors, empowering researchers and policy
makers to tackle public health problems.
Previous works on Frederick Douglass have focused either on his
life or the literary genre in which his life is framed. Frederick
Douglass: A Critical Reader is unique in that it explores his work
by way of the field of philosophy to show that Douglass offered a
wealth of arguments throughout his many texts and speeches. The
writers in this work examine the explicit and implicit
philosophical themes and arguments that resonate through his texts.
Philosophically, Douglass' work seeks to establish better ways of
thinking especially in the light of his conviction about our
genuine shared humanity and the value of a democratic political
life. His experience of, and straggle against, the institution of
American slavery shaped these views. This understanding of
Douglass' writing resonates in the essays written by contributors
to this volume who include Angela Davis, Bernard Boxill, Howard
McGary, and Lewis Gordon, to name a few. The result is a critical
anthology of note, giving more than ample demonstration of the
philosophical magnitude of Frederick Douglass' work.
Research has generated a number of advances in methods for spatial
cluster modelling in recent years, particularly in the area of
Bayesian cluster modelling. Along with these advances has come an
explosion of interest in the potential applications of this work,
especially in epidemiology and genome research. In one integrated
volume, this book reviews the state-of-the-art in spatial
clustering and spatial cluster modelling, bringing together
research and applications previously scattered throughout the
literature. It begins with an overview of the field, then presents
a series of chapters that illuminate the nature and purpose of
cluster modelling within different application areas, including
astrophysics, epidemiology, ecology, and imaging. The focus then
shifts to methods, with discussions on point and object process
modelling, perfect sampling of cluster processes, partitioning in
space and space-time, spatial and spatio-temporal process
modelling, nonparametric methods for clustering, and
spatio-temporal cluster modelling. Many figures, some in full
color, complement the text, and a single section of references
cited makes it easy to locate source material. Leading specialists
in the field of cluster modelling authored each chapter, and an
introduction by the editors to each chapter provides a cohesion not
typically found in contributed works. Spatial Cluster Modelling
thus offers a singular opportunity to explore this exciting new
field, understand its techniques, and apply them in your own
research.
This book reports the results of a three-year research program
funded by the National Science Foundation which targeted students
and teachers from four Detroit high schools in order for them to
learn, experience, and use IT within the context of STEM (IT/STEM),
and explore 21st century career and educational pathways. The book
discusses the accomplishment of these goals through the creation of
a Community of Designers-- an environment in which high school
students and teachers, undergraduate/graduate student assistants,
and STEM area faculty and industry experts worked together as a
cohesive team. The program created four project-based design teams,
one for each STEM area. Each team had access to two year-round
IT/STEM enrichment experiences to create high-quality learning
projects, strategies, and curriculum models. These strategies were
applied in after school, weekend, and summer settings through
hands-on, inquiry-based activities with a strong emphasis on
non-traditional approaches to learning and understanding. The book
represents the first comprehensive description and analysis of the
research program and suggests a plan for future development and
refinement.
Handbook of Spatial Epidemiology explains how to model
epidemiological problems and improve inference about disease
etiology from a geographical perspective. Top epidemiologists,
geographers, and statisticians share interdisciplinary viewpoints
on analyzing spatial data and space-time variations in disease
incidences. These analyses can provide important information that
leads to better decision making in public health. The first part of
the book addresses general issues related to epidemiology, GIS,
environmental studies, clustering, and ecological analysis. The
second part presents basic statistical methods used in spatial
epidemiology, including fundamental likelihood principles, Bayesian
methods, and testing and nonparametric approaches. With a focus on
special methods, the third part describes geostatistical models,
splines, quantile regression, focused clustering, mixtures,
multivariate methods, and much more. The final part examines
special problems and application areas, such as residential history
analysis, segregation, health services research, health surveys,
infectious disease, veterinary topics, and health surveillance and
clustering. Spatial epidemiology, also known as disease mapping,
studies the geographical or spatial distribution of health
outcomes. This handbook offers a wide-ranging overview of
state-of-the-art approaches to determine the relationships between
health and various risk factors, empowering researchers and policy
makers to tackle public health problems.
Aquaculture is the science and technology of balanced support from
the biological and engi producing aquatic plants and animals. It is
not neering sciences. However, commercial aqua new, but has been
practiced in certain Eastern culture has become so complex that, in
order to cultures for over 2,000 years. However, the role be
successful, one must also draw upon the ex of aquaculture in
helping to meet the world's pertise of biologists, engineers,
chemists, econ food shortages has become more recently ap omists,
food technologists, marketing special parent. ists, lawyers, and
others. The multidisciplinary The oceans of the world were once
consid approach to aquaculture production became ap ered sources of
an unlimited food supply. Bio parent during the early 1990s. It is
believed that logical studies indicate that the maximum sus this
trend will continue as aquaculture produc tainable yield of marine
species through the tion becomes more and more intensive in order
for the producer to squeeze as much product as harvest of wild
stock is 100 million MT (metric tons) per year. Studies also
indicate that we are possible out of a given parcel of land.
rapidly approaching the maximum sustainable Although many
aquaculture books exist, few yield of the world's oceans and major
freshwa explore the engineering aspects of aquaculture ter bodies.
Per capita consumption of fishery production.
Since the publication of the second edition, many new Bayesian
tools and methods have been developed for space-time data analysis,
the predictive modeling of health outcomes, and other spatial
biostatistical areas. Exploring these new developments, Bayesian
Disease Mapping: Hierarchical Modeling in Spatial Epidemiology,
Third Edition provides an up-to-date, cohesive account of the full
range of Bayesian disease mapping methods and applications. In
addition to the new material, the book also covers more
conventional areas such as relative risk estimation, clustering,
spatial survival analysis, and longitudinal analysis. After an
introduction to Bayesian inference, computation, and model
assessment, the text focuses on important themes, including disease
map reconstruction, cluster detection, regression and ecological
analysis, putative hazard modeling, analysis of multiple scales and
multiple diseases, spatial survival and longitudinal studies,
spatiotemporal methods, and map surveillance. It shows how Bayesian
disease mapping can yield significant insights into georeferenced
health data. The target audience for this text is public health
specialists, epidemiologists, and biostatisticians who need to work
with geo-referenced health data.
"Understand the nature of contemporary organizations through
systems thinking." "Psychology and Systems at Work "is a
ground-breaking text for Industrial/Organizational psychology where
the authors employ systems thinking, which emphasizes the
relationships between parts (rather than the parts themselves) as
well as the context in which an organization is nested. It is
"wide-angle thinking" about an organization and the surrounding
contexts, and it yields effective problem solving with a long-term
as well as a short-term perspective. As an organizing principle to
the entire textbook, organizational systems are identified as Level
I and Level II. Level I systems include functions like the
recruitment and selection of new members. Level II systems focus on
the social interactions between organizational members and clients
or customers as reflected in the processes of organizational
culture, leadership, and conflict management. Readers will come to
understand the nuts and bolts that shape organizational and
individual behaviors and systems that in turn give rise to quality
production of products and services. Learning GoalsUpon completing
this book, readers should be able to:
- Design systems that are flexible in a fast-changing
environment
- Understand the basic foundations that shape organizational
behavior
- Apply material they learn to real-life scenarios
020595376X / 9780205953769 Psychology and Systems at Work Plus NEW
MySearchLab with eText Package consists of 0205239927 /
9780205239924 MySearchLab with Pearson eText -- Access Card
0205735789 / 9780205735785 Psychology and Systems at Work
Global, interdisciplinary, and engaging, this textbook integrates
materials from philosophical and biological origins to the
historical development of psychology. Its extensive coverage of
women, minorities, and psychologists around the world emphasizes
psychology as a global phenomenon while looking at both local and
worldwide issues. This perspective highlights the relationship
between psychology and the environmental context in which the
discipline developed. In tracing psychology from its origins in
early civilizations, ancient philosophy, and religions to modern
science, technology, and applications, this book integrates
overarching psychological principles and ideas that have shaped the
global history of psychology, keeping an eye toward the future of
psychology. Updated and revised throughout, this new edition also
includes a new chapter on clinical psychology.
In this powerful volume, 15 leading American philosophers examine
and critically reassess Douglass's significance for contemporary
social and political thought.
Philosophically, Douglass's work sought to establish better ways of
thinking, especially in the light of his convictions about our
humanity and democratic legitimacy - convictions that were
culturally and historically shaped by his experience of, and
struggle against, the institution of American slavery.
Contributors include Bernard R. Boxill, Angela Y. Davis, Lewis R.
Gordon, Leonard Harris, Tommy L. Lott, Howard McGary, and John P.
Pittman.
Many homeowners express a preference for older homes rather than
new ones because of the quality of the craftsmanship, the
architectural elements, the character of the home, and the
solidness of the structure. Houses can be changed - they can be
made bigger or smaller according to your desires. Remodeling your
home can make it come alive, fix its flaws, and enhance its
interior. However, renovating can be time consuming, expensive,
nerve-racking, and messy.
The Complete Guide to Renovating Older Homes will help you overcome
these challenges. In this new book, you will learn how to estimate
costs and how to create a budget. You will learn how to select and
install cabinets, countertops, flooring, sinks, faucets,
appliances, bath tubs, showers, and toilets.
You will learn about the unique challenges of small and large
bathrooms, home offices, and home theaters. You will also learn how
to overcome the challenges associated with water, foundation,
cracks, lead, electricity, asbestos, windows, tanks, wells, and
cesspools. Additionally, you will be presented with ideas for
renovating your family room, bedrooms, attic, basement, kitchen,
and bathroom, as well as a variety of floor plans. You will learn
about unique architectural elements, closets, and the tools you
will need. Furthermore, you will be provided with step-by-step
instructions for some of the most common projects, including
installing drywall, upgrading windows and doors, and installing
flooring.
Also included is a section on exterior renovations, which contains
information on windows, skylights, finish materials, garage doors,
sunrooms, porches, decks, and pools. The Complete Guide to
Renovating Older Homes will inspire you to create the home of your
dreams and will help save you thousands of dollars while doing so.
Whether you are attempting your first renovation project or are a
seasoned pro, you will be sure to find numerous tips and
suggestions in this book, making it an indispensable companion for
any homeowner with a project or two in mind.
Atlantic Publishing is a small, independent publishing company
based in Ocala, Florida. Founded over twenty years ago in the
company president's garage, Atlantic Publishing has grown to become
a renowned resource for non-fiction books. Today, over 450 titles
are in print covering subjects such as small business, healthy
living, management, finance, careers, and real estate. Atlantic
Publishing prides itself on producing award winning, high-quality
manuals that give readers up-to-date, pertinent information,
real-world examples, and case studies with expert advice. Every
book has resources, contact information, and web sites of the
products or companies discussed.
"This Atlantic Publishing eBook was professionally written, edited,
fact checked, proofed and designed. The print version of this book
is 288 pages and you receive exactly the same content. Over the
years our books have won dozens of book awards for content, cover
design and interior design including the prestigious Benjamin
Franklin award for excellence in publishing. We are proud of the
high quality of our books and hope you will enjoy this eBook
version. "
View From the Cockpit: Looking Up is written for those interested
in flying, those who appreciate unique stories, and those excited
about seeing how God works wonders in mighty ways.
Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research.
In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal cluster modelling.
Many figures, some in full color, complement the text, and a single section of references cited makes it easy to locate source material. Leading specialists in the field of cluster modelling authored each chapter, and an introduction by the editors to each chapter provides a cohesion not typically found in contributed works. Spatial Cluster Modelling thus offers a singular opportunity to explore this exciting new field, understand its techniques, and apply them in your own research.
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