Free swot analysis software for linux

Net::Analysis are modules for analysing network traffic.

SYNOPSIS

Using an existing analyser:

$ perl -MNet::Analysis -e main help
$ perl -MNet::Analysis -e main TCP,v=1 dump.tcp - basic TCP info
$ perl -MNet::Analysis -e main HTTP,v=1 dump.tcp - HTTP stuff
$ perl -MNet::Analysis -e main Example2,regex=img dump.tcp - run an example

Writing your own analyser:

package MyExample;
use base qw(Net::Analysis::Listener::Base);
# Listen to events from other modules
sub tcp_monologue {
my ($self, $args) = @_;
my ($mono) = $args->{monologue};
my $t = $mono->t_elapsed()->as_number();
my $l = $mono->length();
# Emit your own event
$self->emit(name => example_event,
args => { kb_sec => ($t) ? $l/($t*1024) : N/A }
);
}
# Process your own event
sub example_event {
my ($self, $args) = @_;
printf "Bandwidth: %10.2f KB/secn", $args->{kb_sec};
}
1;
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ABSTRACT

Net::Analysis is a suite of modules that parse tcpdump files, reconstruct TCP sessions from the packets, and provide a very lightweight framework for writing protocol anaylsers.
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I wanted a batch version of Ethereal in Perl, so I could:

- sift through parsed protocols with structured filters
- write custom reports that mixed events from multiple protocols

So here it is. Net::Analysis is a stack of protocol handlers that emit, and listen for, events.

Network Security Analysis Tool is a fast, stable bulk security scanner designed to audit remote network services and check for versions, security problems, gather information about the servers and the machine, and much more.

A manpage providing extensive information on NSAT has been included in the distribution. It is available after a make install, or just by typing man doc/nsat.8 from this dir. It is suggested that you inform yourself at least about the -v (scan verbosity) option and edit the configuration file. To learn about changes in this version, please consult doc/CHANGES.

New to this version is support for distributed scanning. The manpage describes how to do a distributed scan. Note that distributed scanning in this version is just a preliminary, proof-of-concept, implementation with no guarantees for its security, reliability, or performance.

Check for updated vulnerability lists, config files, etc. from
http://nsat.sourceforge.net

Currently, these are lists of vulnerabilities:

nsat.cgi (CGI scripts)
nsat.conf (configuration)
src/mod/snmp.h (SNMP community names)

Market Analysis System (MAS) is an open-source software application that provides tools for analysis of financial markets using technical analysis.
Market Analysis System provides facilities for stock charting and futures charting, including price, volume, and a wide range of technical analysis indicators. Market Analysis System also allows automated processing of market data - applying technical analysis indicators with user-selected criteria to market data to automatically generate trading signals - and can be used as the main component of a sophisticated trading system.
Main features:
- Includes basic technical analysis indicators, such as Simple Moving Average, Exponential Moving Average, Stochastic, MACD, RSI, On Balance Volume, and Momentum.
- Includes more advanced indicators, such as Standard Deviation, Slope of EMA of Volume, Slope of MACD Signal Line, Bollinger Bands, and Parabolic SAR.
- User can create new technical analysis indicators, including complex indicators based on existing indicators.
- User can configure criteria for automated trading-signal generation.
- Creation of weekly, monthly, quarterly, and yearly data from daily data.
- Handles intraday data.
- Handles stock and futures data.
- Accepts input data from files, from a database, or from the web. (Includes a configuration for obtaining end-of-day data from yahoo.com.)
- Can be configured and run as a server that provides services for several clients at a time running on remote machines.

Objectrefenceanalyser (ora) helps developers find bugs or design errors by showing Java object references in an easy way.

It can be plugged into other programs for taking and saving "snapshots" of the object model at runtime for analysis.

TA-Lib provides common functions for the technical analysis of stock/future/commodity market data.
TA-Lib can be reused by trading software developers using Excel, .NET, Java, Perl or C/C++.
Main features:
- More than 120 technical analysis indicators such as ADX, MACD, RSI, Stochastic, Bollinger Bands etc...
- bullet Includes candlestick pattern recognition.
- bullet Optional abstract interface allowing your code to support new technical analysis functions without any code change!
Enhancements:
New Features
- New Functions: BETA, MINMAX, MINMAXINDEX, MININDEX, MAXINDEX
- Debian and RPM packaging available.
- Java JAR packaging available.
- New TA_FunctionDescription() returns XML description of API.
- New ta_func_api.xml file generated in root directory of the package.
- Support for unmanaged static libraries with Visual Studio 2005.
Fixes
- #1526632 : Fix bug in LINEARREG_ANGLE
- #1544555 : Now do proper divide by zero detection in TA_ADX
Other Changes
- Better Java/.NET naming convention.
- ta_func_list.txt moved in root directory of the package.
- Removed dependencies on trio and Mersenne Twister functions.
- Volume and Open Interest are now double instead of integers.
- Add license specific to Excel users.

The Analysis & Reconstruction Sound Engine also known as ARSE, is a program that analyses a sound file into a spectrogram and is able to synthetise this spectrogram, or any other user-created image, back into a sound.
The ARSE consists in two main parts, a spectrographer with a base-2 logarithmic frequency scale, and a spectrogram synthetiser.
Unlike most spectrographers which are based on STFTs and perform the analysis by cutting the signal into small time slices to analyse these slices in the frequency domain, the ARSE is based on a filter bank followed by envelope detection, which means that the signal is cut into small frequency-domain slices, and then analysed in the time domain.
The filter bank is, as of now, made up with overlapping bandpass FIR filters defined logarithmically. Once the original signal is filtered with the filter bank, each resulting signal is sent to envelope detection.
Envelope detection in the ARSE isnt based on a Hilbert transform and peak detection, as its usually done. To achieve envelope detection, we first perform a FFT on the signal, zero-pad the beginning of the signal in the frequency domain according to a user-defined setting, then we perform an IFFT, and, now in the time domain, we turn every negative sample into a positive one, and we low-pass filter (and eventually decimate) the signal according to the same user-defined setting as we previously used.
For instance, lets say we have a signal with a sampling frequency of 44,100 Hz, and that we want to obtain an envelope for it which sampling frequency would be 100 Hz. Once we perform the FFT, we add enough zeroes in the frequency domain at the beginning of our signal so that every frequency component shifts by 50 Hz (100 Hz divided by two, it will later appear obvious why), and we perform an IFFT. Our signal now has a sampling frequency of 44,200 Hz (44,100 + 100 Hz), and the original signal which previously spanned from 0 Hz to 22,050 Hz now spans from 50 Hz to 22,100 Hz.
Now we turn every time-domain sample into its absolute value by turning every negative sample into a positive one. To perform this on a signal means that, for example, a sine wave of a certain frequency would become a signal which periodicity would be twice that frequency. Once we low-pass filter that signal to twice that frequency we obtain that signals envelope. In our case, now that we have obtained the absolute values for our signal, since the periodicity of a sine at the lowest frequency - 50 Hz - would now be 100 Hz, we only low-pass filter our signal at 100 Hz to obtain the original signals envelope. We can now decimate the signal to a sample rate of 100 Hz.
The resulting envelope for each frequency band makes the horizontal lines of the image representing the spectrogram. The amplitude of the envelopes translate linearly into intensity in the image.
The spectrogram synthetiser is based on modulation using horizontal lines of the image as envelopes. Each horizontal line is upsampled to the sampling rate of the desired final signals sampling rate, and is then modulated with, depending on the synthetisation mode chosen by the user, sines matching to the central frequency each horizontal line represents, or noise filtered through the filter bank.
Enhancements:
- Replaced fixed phase sine generation with random phase sine generation
- Changed the PRNG
- Removed the unused code
- Removed every call of nearbyint() due to compatibility issues
- Included the necessary files in order to make using ./configure && make && make install

Commonly referred to as GRASS, this is a Geographic Information System (GIS) used for geospatial data management and analysis, image processing, graphics/maps production, spatial modeling, and visualization. GRASS is currently used in academic and commercial settings around the world, as well as by many governmental agencies and environmental consulting companies.

GRASS GIS is free software released under the GNU/GPL license.

SenseClusters is a natural language processing package that allows you to cluster similar contexts or to identify clusters of related words.
SenseClusters supports its own native methods based on first and second order representations of context, and also supports Latent Semantic Analysis. It is fully unsupervised, and can automatically discover the optimal number of clusters in your text.
SenseClusters is a complete system that takes users from preprocessing of raw text to providing clustered output.
Enhancements:
- Full support for Latent Semantic Analysis was introduced.
- Both contexts and words may be clustered using either native SenseClusters methods (first or second order) or Latent Semantic Analysis.