These files contain all of the code listings in
Java 2: The Complete Reference
The source code is organized into files by chapter.
Within each chapter file, the listings are stored
in the same order as they appear in the book.
Simply edit the appropriate file to extract the
listing in which you are interested.
The code for Scrabblet is in its own ZIP file,
called CHAP32.ZIP.
Watermarking schemes evaluation
Abstract鈥擠igital watermarking has been presented as a solution to copy protection of multimedia objects and dozens of schemes and algorithms have been proposed. Two main problems seriously darken the future of this technology though.
Firstly, the large number of attacks and weaknesses which appear as fast as new algorithms are proposed, emphasizes the limits of this technology and in particu-lar the fact that it may not match users expectations.
Secondly, the requirements, tools and methodologies to assess the current technologies are almost non-existent. The lack of benchmarking of current algorithms is bla-tant. This confuses rights holders as well as software and hardware manufacturers and prevents them from using the solution appropriate to their needs. Indeed basing long-lived protection schemes on badly tested watermarking technology does not make sense.
Compression using lempel-ziv
-for a dictionary size of 2k
-provide dictionary
Lempel ziv algorithm is a dictionary based algorithm that addresses byte sequences from former contents instead of the original data. This algorithm consists of a rule for parsing strings of symbols from a finite alphabet into substrings, whose lengths do not exceed a prescribed integer and a coding scheme which maps these substrings sequentially into uniquely decipherable code words of fixed length. The strings are selected so that they have nearly equal probability of occurrence. Frequently-occurring symbols are grouped into longer strings while occasional symbols appear in short strings.
This m file hide an image jpeg,png in another jpeg,png image.
The height and width of the secret image is in LSB of 1st 32 pixels of 1st row of the cover image.This helps in the recovery of secret image.
The secret image must be smaller than cover image.A message box will appear with a number ,that number is the maximum product of width and height of secret image that can be successfully embedded in the cover image.
The final png image will appear in workspace with random name.This image contains the secret image.One such png image is in the zip file with name 4447.png it contains an image of res 100x122.
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and the information contained herein and assumes no responsibility for any errors that may appear
in this document, nor does the PCI Special Interest Group make a commitment to update the
information contained herein.
The Java Platform, Enterprise Edition 5 (Java EE 5) has two different but complementary
technologies for producing dynamic web content in the presentation tier—namely Java
Servlet and JavaServer Pages (JSP).
Java Servlet, the first of these technologies to appear, was initially described as extensions
to a web server for producing dynamic web content. JSP, on the other hand, is a newer technology
but is equally capable of generating the same dynamic content. However, the way in
which a servlet and a JSP page produce their content is fundamentally different servlets
embed content into logic, whereas JSP pages embed logic into content.
Mobile communication has gained significant importance in today’s society. As
of 2010, the number of mobile phone subscribers has surpassed 5 billion [ABI10],
and the global annual mobile revenue is soon expected to top $1 trillion [Inf10].
While these numbers appear promising for mobile operators at first sight, the
major game-changer that has come up recently is the fact that the market is
more and more driven by the demand for mobile data traffic [Cis10].
Resource allocation is an important issue in wireless communication networks. In
recent decades, cognitive radio technology and cognitive radio-based networks have
obtained more and more attention and have been well studied to improve spectrum
utilization and to overcomethe problem of spectrum scarcity in future wireless com-
munication systems. Many new challenges on resource allocation appear in cogni-
tive radio-based networks. In this book, we focus on effective solutions to resource
allocation in several important cognitive radio-based networks, including a cogni-
tive radio-basedopportunisticspectrum access network, a cognitiveradio-basedcen-
tralized network, a cognitive radio-based cellular network, a cognitive radio-based
high-speed vehicle network, and a cognitive radio-based smart grid.
