EDB (Evan s Debugger) is a QT4 based binary mode debugger with the goal of having usability on par with OllyDbg. It uses a plugin architecture, so adding new features can be done with ease. The current release is for Linux, but future releases will target more platforms.
Release focus: Major feature enhancements
Changes:
A new disassembly engine. A bug that could cause crashing was fixed. There is a new flags breakdown in the register view, an environment view plugin, and improved analysis (including a good speed increase). A bug in QT where disabled events could be triggered has been worked around.
2.0.12 (May 13th, 2004)
- Flag driver threads with PF_FREEZE to support software suspend.
2.0.11 (May 7th, 2004)
- Avoid split-completion bugs in certain PCI-X chipsets by
breaking up large completion entry DMAs on ADB boundaries.
2.0.10 (April 9th, 2004)
- Return "command timeout" status instead of "selection timeout
status" to the SCSI mid-layer in response to selection timeouts.
While the latter may seem more correct, the mid-layer will not
offline devices suffering from persistent selection timeouts.
This leads to extremely long recovery times for devices that
go missing. Returning command timeout status causes the mid-layer
to enter recovery and eventually offline persistently missing
devices.
μC/OS-II Goals
Probably the most important goal of μC/OS-II was to make it backward compatible with μC/OS (at least from an
application’s standpoint). A μC/OS port might need to be modified to work with μC/OS-II but at least, the application
code should require only minor changes (if any). Also, because μC/OS-II is based on the same core as μC/OS, it is just
as reliable. I added conditional compilation to allow you to further reduce the amount of RAM (i.e. data space) needed
by μC/OS-II. This is especially useful when you have resource limited products. I also added the feature described in
the previous section and cleaned up the code.
Where the book is concerned, I wanted to clarify some of the concepts described in the first edition and provide
additional explanations about how μC/OS-II works. I had numerous requests about doing a chapter on how to port
μC/OS and thus, such a chapter has been included in this book for μC/OS-II.
On-Line MCMC Bayesian Model Selection
This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
The XC226x derivatives are high-performance members of the Infineon XC2000 Family
of full-feature single-chip CMOS microcontrollers. These devices extend the functionality
and performance of the C166 Family in terms of instructions (MAC unit), peripherals, and
speed. They combine high CPU performance (up to 80 million instructions per second)
with extended peripheral functionality and enhanced IO capabilities. Optimized
peripherals can be adapted flexibly to meet the application requirements. These
derivatives utilize clock generation via PLL and internal or external clock sources. Onchip
memory modules include program Flash, program RAM, and data RAM.
Exceptional C++ shows by example how to go about solid software engineering. Along with a lot of other material, this book includes expanded versions of the first 30 issues of the popular Internet C++ feature Guru of the Week (or, in its short form, GotW), a series of self-contained C++ engineering problems and solutions that illustrate specific design and coding techniques.
bubble sort
quick sort
selection sort
developed to measure time performance of each sorting and compare their results with each other
for very large data set 2
base implementaion of the protein (starting from the amino acid sequence) feature extractor used in "L. Nanni and A. Lumini, An ensemble of Support Vector Machines for predicting virulent proteins, Expert Systems With Applications, vol.36, no.4, pp.7458-7462, May 2009. "
This Symbian C++ code example demonstrates how to easily use the onboard camera with zoom and autofocus, utilising an accompanying CameraWrapper made by Forum Nokia. The Camera Wrapper supports all Nokia s S60 devices based on S60 3rd Edition and newer, providing a unified interface for various Symbian and S60 camera APIs some of which have previously been Feature Pack specific or only available via an SDK plug-in. The example application supports the use of both the keypad and touch UI. The application can be self-signed, but it also provides an option to use the dedicated camera key (Symbian signing required). The example application replaces the separate examples published for S60 3rd Edition, FP1 (S60 Platform: Camera Example with AutoFocus Support v2.2) and FP2 (S60 Camera Example AutoFocus 3rd Ed FP2).
