ESRIMapObjectsLT 2 and MicrosoftVisual Basic6 to build an application that uses maps.
Display a map with multiple layers.
Control panning and zooming.
Create a toolbar control.
Base the display of map layers on scale.
Perform spatial and logical queries.
Display features with thematic renderers.
Add vector data and images to a map programmatically.
Abstract-In this paper, simple autonomous chaotic circuits
coupled by resistors are investigated. By carrying out computer
calculations and circuit experiments, irregular self-switching phenomenon
of three spatial patterns characterized by the phase
states of quasi-synchronization of chaos can be observed from
only four simple chaotic circuits. This is the same phenomenon
as chaotic wandering of spatial patterns observed very often from
systems with a large number of degrees of freedom. Namely, one
of spatial-temporal chaos observed from systems of large size can
be also generated in the proposed system consisting of only four
chaotic circuits. A six subcircuits case and a coupled chaotic circuits
networks are also studied, and such systems are confirmed
to produce more complicated spatio-temporal phenomena.
Servlets and JavaServer Pages is the first complete guide to building dynamic Java-based Web applications using the new JavaServer Pages 2.0 and Servlets 2.4. Servlets and JavaServer Pages (JSP) provide a robust solution to developing large, complex Web applications, including multiserver projects. In addition to built-in security, portability, and a Web server, they offer developers the freedom to work with any operating system that supports Javabe it Linux, Windows, OSX, or Solaris.
This authoritative book begins by explaining how to set up a Servlet and JSP development environment, including a discussion of containers, Java support, and installing and configuring Tomcat. The authors then thoroughly explore servlets and JSP, including significant coverage of custom tag libraries, newly available filters, and popular servlet and JSP design patterns. Readers can then test-drive the knowledge gained by constructing a book-support Web site.
This book is about writing TinyOS systems and applications in the nesC language. This chapter gives a
brief overview of TinyOS and its intended uses. TinyOS is an open-source project which a large number of
research universities and companies contribute to. The main TinyOS website, http://www.tinyos.net,
has instructions for downloading and installing the TinyOS programming environment. The website has a
great deal of useful information which this book doesn’t cover, such as common hardware platforms and
how to install code on a node.
These codes require an ASCII input file interp.dat of the following form:
N: Number of Polynomial Interpolation Points (Small)
First Sample (x1,y1)
Second Sample (x2,y2)
...
Nth Sample (xN,yN)
N1: Number of Error Evaluation Points (Large)
First Sample (x1,y1)
Second Sample (x2,y2)
...
N1th Sample (xN1,yN1)
The object detector described below has been initially proposed by
P.F. Felzenszwalb in [Felzenszwalb2010]. It is based on a
Dalal-Triggs detector that uses a single filter on histogram of
oriented gradients (HOG) features to represent an object category.
This detector uses a sliding window approach, where a filter is
applied at all positions and scales of an image. The first
innovation is enriching the Dalal-Triggs model using a
star-structured part-based model defined by a “root” filter
(analogous to the Dalal-Triggs filter) plus a set of parts filters
and associated deformation models. The score of one of star models
at a particular position and scale within an image is the score of
the root filter at the given location plus the sum over parts of the
maximum, over placements of that part, of the part filter score on
its location minus a deformation cost easuring the deviation of the
part from its ideal location relative to the root. Both root and
part filter scores are defined by the dot product between a filter
(a set of weights) and a subwindow of a feature pyramid computed
from the input image. Another improvement is a representation of the
class of models by a mixture of star models. The score of a mixture
model at a particular position and scale is the maximum over
components, of the score of that component model at the given
location.
Writing essays and dissertations can be a major concern for overseas students studying at English-medium colleges and universities. Virtually all courses contain a large degree of written assessment and it is essential to ensure that your writing skills meet the necessary standard. Academic Writing is a new kind of writing course for all international students who have to write exams or coursework in English. This practical book thoroughly explains the writing process and covers all the key writing skills.
We consider the problem of target localization by a
network of passive sensors. When an unknown target emits an
acoustic or a radio signal, its position can be localized with multiple
sensors using the time difference of arrival (TDOA) information.
In this paper, we consider the maximum likelihood formulation
of this target localization problem and provide efficient convex
relaxations for this nonconvex optimization problem.We also propose
a formulation for robust target localization in the presence of
sensor location errors. Two Cramer-Rao bounds are derived corresponding
to situations with and without sensor node location errors.
Simulation results confirm the efficiency and superior performance
of the convex relaxation approach as compared to the
existing least squares based approach when large sensor node location
errors are present.
