|
Showing 1 - 25 of
80 matches in All Departments
Unlike some other reproductions of classic texts (1) We have not
used OCR(Optical Character Recognition), as this leads to bad
quality books with introduced typos. (2) In books where there are
images such as portraits, maps, sketches etc We have endeavoured to
keep the quality of these images, so they represent accurately the
original artefact. Although occasionally there may be certain
imperfections with these old texts, we feel they deserve to be made
available for future generations to enjoy.
Higher education has changed significantly over the past 50 years,
and the individuals who provide leadership for these institutions
has similarly changed. The pathway to the college presidency, once
the domain of academic administration, has diversified as an
increasing number of development officers, student affairs and
enrollment management professionals, and even politicians have
become common in the role. It is important to understand who the
presidents are in the current environment and the challenges they
face. Challenges such as dealing with the COVID-19 pandemic,
enrollment shortfalls, Title IX, and athletic scandals have risen
to the forefront and have contributed to the issues and role of
college and university leadership. The Handbook of Research on the
Changing Role of College and University Leadership provides
important research on the topic of college and university
leadership, especially focusing on the changing role of the college
president. The chapters discuss college leadership as it is now and
how it will evolve into the future. Topics included are the role of
the president at various types of universities, their involvement
within university functions and activities, and the duties they
must carry out and challenges they face. This book is ideal for
professionals and researchers working in higher education,
including faculty members who specialize in education, public
administration, the social sciences, and management, along with
teachers, administrators, teacher educators, practitioners,
researchers, academicians, and students who are interested in
college and university leadership and how this role is
transforming.
|
We See (Hardcover)
G. David Gardiner
|
R714
Discovery Miles 7 140
|
Ships in 10 - 15 working days
|
Database technology can be used for various ends, ranging from
promotion of democracy to strengthening of nationalism to shoring
up authoritarian regimes through misinformation. Its use affects
every layer of society: from individuals to households to local
governments, and is a consuming issue in the United States
Governments stance on privacy, security, and technology.
This anthology brings together multiple viewpoints on the social
dimensions of the revolution in information technology. The
chapters cover social, political, educational, personal, and
international dimensions of information technology impacts. Each
chapter focuses on different aspects of the effects of computing
and the new information technologies that have accelerated every
area of human life. Social Dimensions of Information Technology:
Issues for the New Millennium raises important issues with profound
implications for public policy and societal development.
With the alarming rate of information technology changes over the
past two decades, it is not unexpected that there is an evolution
of the human side of IT that has forced many organizations to
rethink their strategies in dealing with the human side of IT.
People, just like computers, are main components of any information
systems. And just as successful organizations must be willing to
upgrade their equipment and facilities, they must also be alert to
changing their viewpoints on various aspects of human behavior. New
and emerging technologies result in human behavior responses which
must be addressed with a view toward developing better theories
about people and IT. IT Solutions Series: Humanizing Information
Technology: Advice from Experts brings out a variety of views
expressed by practitioners from corporate and public settings offer
their experiences in dealing with the human byproduct of IT.
"The nature of governance is rapidly changing, due to new
technologies which expand public sector capabilities. Modern Public
Information Technology Systems: Issues and Challenges examines the
most important dimensions of managing information technology in the
public sector. It explores the impact of information technology on
governmental accountability and distribution of power, the
implications of privatization as an IT business model, and the
global governance of information technology. Modern Public
Information Technology Systems: Issues and Challenges provides a
fresh look at the evolution of federal technology and political
accountability in governmental information systems. Descriptions of
general policy and technical applications, as well as practical
implementation guidelines make this book a must-have for
professors, students, and practitioners."
Multiple myeloma is the second most common hematologic malignancy
and c- rently affects approximately 50,000 people in the United
States. Each year about 20,000 people are diagnosed with myeloma.
Although new treatments have been developed, which signi?cantly
prolong the survival of patients, myeloma bone d- ease still
remains a major cause of severe morbidity and increased mortality
in patients with myeloma. Myeloma bone disease is characterized by
"punched out" lytic lesions caused by increased osteoclastic bone
destruction accompanied by suppressed or even absent osteoblast
activity. Advances in our understanding of both the pathophysiology
of myeloma bone disease and the development of novel agents that
target speci?c pathways involved in both the increased osteoclast
f- mation and the suppressed osteoblast activity in myeloma provide
new hope for these patients. The treatment of myeloma bone disease
was revolutionized by cl- ical trials that demonstrated the
signi?cant bene?t of intravenous bisphosphonate therapy in patients
with myeloma bone disease. With the identi?cation of many of the
cytokines and chemokines involved in myeloma bone disease, novel
th- apies such as denosumab that blocks RANKL activity, anti-DKK1,
which targets the inhibition of osteoblast activity by blocking Wnt
signaling inhibition, and the potential anabolic effects of agents
such as bortezomib and activin have greatly improved our potential
to block the progression or reverse myeloma bone disease.
E-government has emerged not merely as a specialization in public
administration but as a transformative force affecting all leaves
and functions in government. Digital Government: Principles and
Best Practices, written by a collection of practitioners and
researchers, provides an overview of the management challenges and
issues involved in seeking a new form of governance - digital
government.
"Describes the quantitative research process--framing analytical
questions, developing a comprehensive outline, providing a roadmap
for the reader, and accessing indispensable computer and program
tools. Supplies end-of-chapter checklists, extensive examples, and
biobliographies."
G. David Howard combines two passionate interests-humor and
politics-in his first collection of personal essays that creatively
examine current events in America and the actions of our
government.
Howard, a seasoned stand-up comedian, addresses a variety of
controversial topics with both funny and frank tones intended to
provoke laughter and thought about our leaders and the direction
our country is headed. As he explores how groupless people have no
representation, why gasoline prices have doubled, and how
socialists want to destroy freedom and increase taxes, Howard
blends facts with his own spin on potential solutions. Included is
a script from an imaginary and imaginative golf game between Barack
Obama, John Boehner, Joe Biden and Chuck Schumer, as well as a
montage of Howard's opinions on a wide range of subjects, such as
climate change, driver distractions, and gun control.
Half of America Is Nuts, and They Were Allowed to Vote shares
one man's take on our world as he presents an unforgettable
roller-coaster ride through America and its political system.
Data Analytics for the Social Sciences is an introductory,
graduate-level treatment of data analytics for social science. It
features applications in the R language, arguably the fastest
growing and leading statistical tool for researchers. The book
starts with an ethics chapter on the uses and potential abuses of
data analytics. Chapters 2 and 3 show how to implement a broad
range of statistical procedures in R. Chapters 4 and 5 deal with
regression and classification trees and with random forests.
Chapter 6 deals with machine learning models and the "caret"
package, which makes available to the researcher hundreds of
models. Chapter 7 deals with neural network analysis, and Chapter 8
deals with network analysis and visualization of network data. A
final chapter treats text analysis, including web scraping,
comparative word frequency tables, word clouds, word maps,
sentiment analysis, topic analysis, and more. All empirical
chapters have two "Quick Start" exercises designed to allow quick
immersion in chapter topics, followed by "In Depth" coverage. Data
are available for all examples and runnable R code is provided in a
"Command Summary". An appendix provides an extended tutorial on R
and RStudio. Almost 30 online supplements provide information for
the complete book, "books within the book" on a variety of topics,
such as agent-based modeling. Rather than focusing on equations,
derivations, and proofs, this book emphasizes hands-on obtaining of
output for various social science models and how to interpret the
output. It is suitable for all advanced level undergraduate and
graduate students learning statistical data analysis.
Recently, the public sector has given an increasing amount of
national and international attention to electronic government
systems. Therefore, it is inevitable that the theoretical
implications and intersections between information technology and
governmental matters are more widely discussed. Public Information
Management and E-Government: Policy and Issues offers a fresh,
comprehensive dialogue on issues that occur between the public
management and information technology domains. With its focus on
political issues and their effects on the larger public sector,
this book is valuable for administrators, researchers, students,
and educators who wish to gain foundational and theoretical
knowledge on e-government policies.
Factor Analysis and Dimension Reduction in R provides coverage,
with worked examples, of a large number of dimension reduction
procedures along with model performance metrics to compare them.
Factor analysis in the form of principal components analysis (PCA)
or principal factor analysis (PFA) is familiar to most social
scientists. However, what is less familiar is understanding that
factor analysis is a subset of the more general statistical family
of dimension reduction methods. The social scientist's toolkit for
factor analysis problems can be expanded to include the range of
solutions this book presents. In addition to covering FA and PCA
with orthogonal and oblique rotation, this book's coverage includes
higher-order factor models, bifactor models, models based on binary
and ordinal data, models based on mixed data, generalized low-rank
models, cluster analysis with GLRM, models involving supplemental
variables or observations, Bayesian factor analysis, regularized
factor analysis, testing for unidimensionality, and prediction with
factor scores. The second half of the book deals with other
procedures for dimension reduction. These include coverage of
kernel PCA, factor analysis with multidimensional scaling, locally
linear embedding models, Laplacian eigenmaps, diffusion maps, force
directed methods, t-distributed stochastic neighbor embedding,
independent component analysis (ICA), dimensionality reduction via
regression (DRR), non-negative matrix factorization (NNMF), Isomap,
Autoencoder, uniform manifold approximation and projection (UMAP)
models, neural network models, and longitudinal factor analysis
models. In addition, a special chapter covers metrics for comparing
model performance. Features of this book include: Numerous worked
examples with replicable R code Explicit comprehensive coverage of
data assumptions Adaptation of factor methods to binary, ordinal,
and categorical data Residual and outlier analysis Visualization of
factor results Final chapters that treat integration of factor
analysis with neural network and time series methods Presented in
color with R code and introduction to R and RStudio, this book will
be suitable for graduate-level and optional module courses for
social scientists, and on quantitative methods and multivariate
statistics courses.
This annual publication deals with how microcomputers and other
computers can be applied to improving the explanatory and
evaluative roles of modern social science. Each volume contains
chapters by experts in political science, psychology, sociology,
economics and computer science.
Data Analytics for the Social Sciences is an introductory,
graduate-level treatment of data analytics for social science. It
features applications in the R language, arguably the fastest
growing and leading statistical tool for researchers. The book
starts with an ethics chapter on the uses and potential abuses of
data analytics. Chapters 2 and 3 show how to implement a broad
range of statistical procedures in R. Chapters 4 and 5 deal with
regression and classification trees and with random forests.
Chapter 6 deals with machine learning models and the "caret"
package, which makes available to the researcher hundreds of
models. Chapter 7 deals with neural network analysis, and Chapter 8
deals with network analysis and visualization of network data. A
final chapter treats text analysis, including web scraping,
comparative word frequency tables, word clouds, word maps,
sentiment analysis, topic analysis, and more. All empirical
chapters have two "Quick Start" exercises designed to allow quick
immersion in chapter topics, followed by "In Depth" coverage. Data
are available for all examples and runnable R code is provided in a
"Command Summary". An appendix provides an extended tutorial on R
and RStudio. Almost 30 online supplements provide information for
the complete book, "books within the book" on a variety of topics,
such as agent-based modeling. Rather than focusing on equations,
derivations, and proofs, this book emphasizes hands-on obtaining of
output for various social science models and how to interpret the
output. It is suitable for all advanced level undergraduate and
graduate students learning statistical data analysis.
Organizational Behavior and Public Management reveals how
organizational behavior enables managers to direct resources that
advance the programs and policies of public and government. This
edition offers a public sector perspective of core topics, such as
communication, decision-making, leadership, management ethics,
motivation, organizational change, participation and performance
appraisal. Contemporary Psychology called this book "skillful and
comprehensivea ]There is a need for a text like thisa ]the device
of juxtaposing theory and application is a sound one." The authors
discuss such topics as communication, decision making, worker
participation and total quality management, organizational change,
management systems, information, computers and organization theory
in public management.
Factor Analysis and Dimension Reduction in R provides coverage,
with worked examples, of a large number of dimension reduction
procedures along with model performance metrics to compare them.
Factor analysis in the form of principal components analysis (PCA)
or principal factor analysis (PFA) is familiar to most social
scientists. However, what is less familiar is understanding that
factor analysis is a subset of the more general statistical family
of dimension reduction methods. The social scientist's toolkit for
factor analysis problems can be expanded to include the range of
solutions this book presents. In addition to covering FA and PCA
with orthogonal and oblique rotation, this book's coverage includes
higher-order factor models, bifactor models, models based on binary
and ordinal data, models based on mixed data, generalized low-rank
models, cluster analysis with GLRM, models involving supplemental
variables or observations, Bayesian factor analysis, regularized
factor analysis, testing for unidimensionality, and prediction with
factor scores. The second half of the book deals with other
procedures for dimension reduction. These include coverage of
kernel PCA, factor analysis with multidimensional scaling, locally
linear embedding models, Laplacian eigenmaps, diffusion maps, force
directed methods, t-distributed stochastic neighbor embedding,
independent component analysis (ICA), dimensionality reduction via
regression (DRR), non-negative matrix factorization (NNMF), Isomap,
Autoencoder, uniform manifold approximation and projection (UMAP)
models, neural network models, and longitudinal factor analysis
models. In addition, a special chapter covers metrics for comparing
model performance. Features of this book include: Numerous worked
examples with replicable R code Explicit comprehensive coverage of
data assumptions Adaptation of factor methods to binary, ordinal,
and categorical data Residual and outlier analysis Visualization of
factor results Final chapters that treat integration of factor
analysis with neural network and time series methods Presented in
color with R code and introduction to R and RStudio, this book will
be suitable for graduate-level and optional module courses for
social scientists, and on quantitative methods and multivariate
statistics courses.
One of the most exciting developments in fighting crime at the turn
of the twenty-first century has been the integration of Geographic
Information Systems (GIS) into law enforcement, and includes crime
analysis. This book provides an overview of the implementation and
integration of GIS technology into various aspects of law
enforcement, including important mapping concepts and their use in
crime analysis. Crime mapping basics are discussed, including pin
mapping, mapping « hot spots, mapping crime density, and creating
briefing maps. Other topics include the integration of crime
mapping with police decision-making, the use of various forms of
spatial modeling in law enforcement, and integrating inter-agency
data as part of a regional approach to crime. As a way of better
understanding the practical applications, the authors include a
list of police agencies providing real crime data and analysis
tools on the World Wide Web.
Both algorithms and the software . and hardware of automatic
computers have gone through a rapid development in the past 35
years. The dominant factor in this development was the advance in
computer technology. Computer parameters were systematically
improved through electron tubes, transistors and integrated
circuits of ever-increasing integration density, which also
influenced the development of new algorithms and programming
methods. Some years ago the situation in computers development was
that no additional enhancement of their performance could be
achieved by increasing the speed of their logical elements, due to
the physical barrier of the maximum transfer speed of electric
signals. Another enhancement of computer performance has been
achieved by parallelism, which makes it possible by a suitable
organization of n processors to obtain a perform ance increase of
up to n times. Research into parallel computations has been carried
out for several years in many countries and many results of
fundamental importance have been obtained. Many parallel computers
have been designed and their algorithmic and program ming systems
built. Such computers include ILLIAC IV, DAP, STARAN, OMEN,
STAR-100, TEXAS INSTRUMENTS ASC, CRAY-1, C mmp, CM*, CLIP-3, PEPE.
This trend is supported by the fact that: a) many algorithms and
programs are highly parallel in their structure, b) the new LSI and
VLSI technologies have allowed processors to be combined into large
parallel structures, c) greater and greater demands for speed and
reliability of computers are made."
This book was first published in 2008. Multiple pregnancies are the
most frequent and serious complication of assisted reproduction.
Both high-order multiple and twin pregnancies entail a number of
medical and economic outcomes that affect the children, the mother,
the parents, the families, and society as a whole. Limiting the
number of embryos to transfer is the only method available to
decrease the incidence of multiple pregnancies. Single Embryo
Transfer reviews the advantages and limitations of this approach to
assisted reproduction. The crucial issue of selecting the best
embryo will be reviewed in detail. All clinical issues involved in
setting up and running an SET programme will be covered, including
important topics such as cryopreservation of embryos, embryo
donation, and patient counselling. The final chapters on future SET
trends in Europe and North America are written by leading figures
in the IVF world. The book is of interest to physicians,
embryologists, nurses, insurers, politicians, ethicists and
patients.
|
You may like...
Loot
Nadine Gordimer
Paperback
(2)
R383
R318
Discovery Miles 3 180
Ab Wheel
R209
R149
Discovery Miles 1 490
|