是一本介紹java基礎(chǔ)應(yīng)用的好書
Java For Artists targets both the undergraduate computer science or information technology student and the practicing programmer. It is both an introductory-level textbook and trade book.
As a textbook it employs learning objectives, skill-building exercises, suggested projects, and self-test questions to reinforce the learning experience. The projects offered range from the easy to the extremely challenging. It covers all the topics you’d expect to find in an introductory Java programming textbook and then some.
As a trade book it goes purposefully deeper into topics cut short or avoided completely in most introductory textbooks. Its coverage of advanced GUI programming techniques, network programming and object-oriented theory will enable you to take your skills to a higher level.
Create a Delaunay triangulation or Voronoi diagram by clicking points. Delaunay triangulations and Voronoi diagrams are among the most widely used data structures in the field of Computational Geometry. These are Java-oriented source codes.
The Kalman filter is a set of mathematical equations that provides an efficient computational
[recursive] means to estimate the state of a process, in a way that minimizes
the mean of the squared error. The filter is very powerful in several aspects:
it supports estimations of past, present, and even future states, and it can do so even
when the precise nature of the modeled system is unknown.
nTIM PATRICK has been working professionally as a software architect and developer for nearly
25 years. By day he develops custom business applications in Visual Basic for small to medium-
sized organizations. He is a Microsoft Certified Solution Developer (MCSD). In April 2007,
Microsoft awarded Tim with its Most Valuable Professional (MVP) award for his work in sup-
porting and promoting Visual Basic and its community of users. Tim received his under-
graduate degree in computer science from Seattle Pacific University. You can contact him
through his web site, www.timaki.com.
Embedded System Design:
A Unified Hardware/Software Approach
Frank Vahid and Tony Givargis
Department of Computer Science and Engineering
University of California
This is a very good book on self learning electronics from Wiley publications and is very useful to understand basics of electronics for some one shifting from computer science to embedded system development
In the hit CBS crime show Person of Interest, which debuted in 2011,
the two heroes—one a former Central Intelligence Agency agent and
the other a billionaire technology genius—work together using the
ubiquitous surveillance system in New York City to try to stop violent
crime. It’s referred to by some as a science fiction cop show. But the
use of advanced technology for crime analysis in almost every major
police department in the United States may surpass what’s depicted
on TV crime dramas such as Person of Interest. Real-time crime cen-
ters (RTCCs) are a vital aspect of intelligent policing. Crime analysis
is no longer the stuff of science fiction. It’s real.
Applications of microelectromechanical systems (MEMS) and microfabrica-
tion have spread to different fields of engineering and science in recent years.
Perhaps the most exciting development in the application of MEMS technol-
ogy has occurred in the biological and biomedical areas. In addition to key
fluidic components, such as microvalves, pumps, and all kinds of novel
sensors that can be used for biological and biomedical analysis and mea-
surements, many other types of so-called micro total analysis systems (TAS)
have been developed.
With the continued growth in the world's population, there is a need to ensure availability of
enough food to feed everyone. Advances in science and technology have helped not only to
increase food production, but also to reduce food wastage. However, the latter has the
potential to be improved to a significant extent through appropriate matching of supply and
demand, and with proper handling during storage and transit. Given the amount of food
wastage that occurs after a food item leaves the “farm” on its way to the “fork,” and the
availability of means to reduce such wastage, there really is no excuse for feigned ignorance.
Pattern recognition has its origins in engineering, whereas machine learning grew
out of computer science. However, these activities can be viewed as two facets of
the same field, and together they have undergone substantial development over the
past ten years. In particular, Bayesian methods have grown from a specialist niche to
become mainstream, while graphical models have emerged as a general framework
for describing and applying probabilistic models. Also, the practical applicability of
Bayesian methods has been greatly enhanced through the development of a range of
approximate inference algorithms such as variational Bayes and expectation propa-
gation. Similarly, new models based on kernels have had significant impact on both
algorithms and applications.
