Free discount travel software for linux

Business::Travel::OTA is a Perl module with tools for handling OTA-compliant (Open Travel Alliance) messages.

SYNOPSIS

# This tests the "otaserver" with an OTA_PingRQ message
otaclient --ping --verbose

The Business::Travel::OTA module is the main module for the Business-Travel-OTA distribution in the OTA-Tools project. Your can see the project web site at SourceForge.

http://sourceforge.net/projects/ota-tools

The OTA-Tools project is a set of software tools useful for building, testing, and exercising web services (and other interfaces) for the travel industry which comply with the specifications of the Open Travel Alliance (OTA). You can see the OTA web site here.

http://www.opentravel.org

This project is initiated by members of the OTA, but it is not an official project of the OTA. It represents an opportunity for OTA members to collaborate on tools, test suites, and reference implementation software for the purposes of reducing the learning curve for newcomers and enhancing interoperability.

The Business-Travel-OTA distribution is a set of Perl modules and programs which demonstrate the creation, validation, transmission, processing, parsing, and manipulation of OTA messages. This software also implements reference client and server capabilities which can be adapted as necessary.

Magnificent Gunbright is an abstract shooter; destroy the black ball. An Abstract Shooter Developed For Ludum Dare in 48 Hours.

You are the flashy white blob at the bottom, with the clump of other white blobs following you around.

You have the ability to fire the blobs from your cloud at the flashy blob surrounded by a cloud of black blobs at the top of the screen.

If a black blob and white blob collide, both are destroyed. The object is to hit the evil flashy blob at the top of the screen to destroy it.

Falling from the top of the screen like rain is a steady supply of more blobs. If one of the blobs in your cloud touches a white blob that fell from the sky, even while shooting, the blob joins your cluster.

Falling from the bottom of the screen is black blobs, that your enemy can use to bulk himself up, as well. Blob rain does no damage to either party; you can tell that its rain and not bullets because rain travels away from you.

Use the arrow keys to move, and the space bar to shoot.

Once youve destroyed one evil black blob, you will face another, more powerful one! And so on forever until you eventually die.

Destroy the evil black blobs and save the League of Confederated Planets!

Asticot project is an improved Tron Game.
Asticot is a snake game but with a twist.
It allows up to 6 human controled players. You can travel in any direction (face any angle).
Original idea came from Amiga game Viper.
To Build :
$ make
$ ./asticot
Enhancements:
- Less bug, better play

The "Open Device Monitoring and Tracking Protocol", otherwise known as OpenDMTP, is a protocol and framework that allows bi-directional data communications between servers and devices (clients) over the Internet and similar networks.
OpenDMTP is a highly configurable and extensible protocol for communicating with mobile devices.
OpenDMTP is particularly geared towards Location-based information (LBS) such as GPS, as well as temperature and other data collected in remote-monitoring devices. OpenDMTP is small, and is especially suited for micro-devices such as PDAs, mobile phones, and custom OEM devices.
We saw a need for a communications protocol that allowed high-latency, low-bandwidth (HL/LB) devices to transmit location data to monitoring-systems. Because these devices often have limited network connectivity, the protocol needed to be small and efficient. Example devices include mobile phones, PDAs, OEM micro-devices (alarm systems, temperature monitors, etc.), and more.
There are many mobile GPS tracking devices on the market today with their own closed proprietary protocols. Searching the web for open protocols revealed only a few available for transferring data (including GPS information) between devices. However these solutions are generally designed for non-mobile applications and/or lack some of the low-bandwidth, configurable, and extensible features that mobile applications require.
Main features:
- Small Footprint: Mobile devices typically have limited resources on which to run client code (ie. memory, processor speed). An open protocol designed with this in mind should be optimized to allow efficient implementation and should easily support devices such as PDAs, mobile phones, GPS monitoring devices, and other OEM micro-devices.
- Network Efficient: Mobile devices typically have limited network connectivity, and in some cases data communication can be quite expensive (e.g. satellite). Because of this the protocol needs to be efficient in its dialog between the client and server. The communication needs to be optimized such that the necessary information can be conveyed with a minimum number of bytes in the least amount of time.
- Bi-directional: Some devices can support two-way communication (ie. GPRS, or other socket based connections), while others may only support one-way communication (ie. some satellite communication systems). With this in mind, a protocol should be designed to support both duplex (two-way) and simplex (one-way) communication.
- Transport Media: Differrent mobile applications will have their own unique way of communicating data back to the server. Some may use GPRS, or socket based communication, others may use satellite communication, while still others may use other forms of wireless communication, such as BlueTooth. The design of the protocol should be able to encompass all such transport media types, regardless of the type of transport in use.
- Flexible Data Encoding: Most types of transport media allow for the transmission of binary encoded data. However, there may be some forms of media for which an ASCII encoded data packet is much better suited. A protocol designed with this in mind should be able to support both types of data encoding.
- Configurable Messages: Due to the broad range of data types used in mobile applications, the protocol should be flexible enough to define standard messages, yet still allow custom messages within the framework.
- Extensible: Not every mobile application is the same. Some require special handling and may have various types of inputs and outputs. A protocol designed for mobile applications should insure that the framework can be easily extended to incapsulate the specific needs of the device.
- Industry Compatibility: Having an open protocol insures better compatibility between different client devices and service providers.
- Reference Implementation: Having a reference implementation that showcases the major features of the protocol provides an easy starting point on which developers can add their own features and platform specific implementation without having to worry about how data gets from the client to the server.
OpenDMTP was specifically designed to suit all these needs, especially "Small Footprint" and "Network Efficiency". The typical data plan for GPRS communication, for instance, is usually 1Mb per month. OpenDMTP was designed to optimize packet encoding to allow the collection of GPS information packets once every 3 minutes, 24 hours a day, 30 days a month, and still stay under the 1Mb data plan limit.
While XML is very extensible, it fails the "Small Footprint" and "Network Efficiency" requirements. Thus, it was discounted as a viable protocol solution. Many mobile devices do not have the resources necessary to be able to provide full XML parsing functionality. And an XML packet may need to be several hundred bytes in length just to send a few bytes of actual data. This alone would make the solution cost prohibitive for high-cost transport media such as satellite.
OpenDMTP also includes a full-featured commercial quality reference implementation to jump-start development.
Enhancements:
- NEW: Minor optimizations made to message logging.
- FIX: Log file now properly displays account/device on client connection.

Ubercart project is an e-commerce shopping cart integrated with the Drupal CMS.
Main features:
- Configurable product catalog includes catalog pages and a block to display product categories.
- Flexible product creation system. Create normal products by default. Create product classes to store more information on a subset of your catalog. (Ex: Creating a book class would let you store and display separately the author, publisher, and length of the book.)
- Flexible product attributes system. Create user selectable attributes for your products that modify the price, SKU/model, and/or weight of items as the customer adds them to his or her cart.
- Single page checkout. All checkout information gathered on a single screen composed of configurable checkout panes. Third party modules can define checkout panes to replace or add to the default set, making it easy to customize the checkout experience.
- Automatic account generation (anonymous checkout). Accounts and emails are automatically generated based on the customers e-mail address. For return customers, previously used addresses will be listed on the checkout page for easy access.
- Simple order processing. The order administration screens have been designed by and for our salesmen. We believe there is always room for improvement and will try to make it happen! Order screens use the "pane" model, so the screens are configurable and extensible to accommodate a wide variety of e-commerce applications.
- Simple order creation and editing. Easy to create orders manually for customers, adding products, shipping prices, etc. from a single screen. Line items system makes it easy to add fees, discounts, and coupons to orders.
- Integrated payment system that acts as a bridge between acceptable payment methods (check, credit card, cod, etc.) and payment gateways (Cyber Source, Authorize.net, PayPal, etc.). Configurable payment processing and tracking, and easy to use credit card terminal with varying levels of access.
- Activity logging. Enable logging to see all the changes made to an order, including payment processing. (Your accountant will love this!)

Python Traffic Analyzer is a Python base class and sample driver script written to retrieve and manipulate images from the TrafficLand cameras and calculate a numeric value representing the current traffic flow.

PyTrAn, an example driver script, an image collector and an image mask creator are available for download from the link shown at the bottom. To use the PyTrAn package begin by choosing a camera that you wish to analyze, for this example well use the camera captioned above.

We want to construct a mask over the area of the image that we are interested in, namely the road. In this particular example the road takes up the majority of the image but that is not always the case.

We will apply the mask over captured images to fine tune the area over which we are looking for movement. To create the mask we will first need to collect a sequential series of snapshots from the target camera. The image_collector.py script was written for this task:

$ mkdir mask_200003
$ cd mask_200003
$ ../image_collector.py 200003 30
Collecting 30 images...
30

Done.

The script is hard coded to capture images on a 2-second delay. The delay is necessary to ensure the image has changed. I believe 2-seconds to be the absolute minimum. Once complete, 30 images numbered 1 through 30 will be created in the current directory.

We construct a mask from these captured images by creating a diff-image for each sequential image pair and then adding each diff-image together. Naturally, a script was written to automate this task as well:

$ ../mask_maker.py 1 30
Creating a diff for each sequential image pair.
Diffing 29

Creating the initial mask from the first image pair.

Adding the rest of the diffs to the mask.
Masking 29

Done.

A number of .diff files are generated in this process. These files repesent the movement between individual sequence pairs.

The .diff files are simply intermediary files, the important bit is the mask file, which is generated as the sum of all differences.

The mask file may be dirty (as in this case) and require manual cleanup. The basic shape of the road however is clearly visible, evidence that we can with minimal effort automate the mask generation process. Also, this run was conducted at night, day-time images yield better results.

There are a few final steps we need to take before we can use the example PyTrAn driver script. First we need to convert the mask to ASCII (noraw) format:

$ pnmnoraw mask > mask_200003.ascii

Then we need to open an ImageMagick display window and get its X-window-ID using xwininfo. Finally, update camera_id and window_id in pytran_sampling.py and launch the driver:

$ ../pytran_sampling.py
DEBUG> grabbing frame from camera 200003
DEBUG> rotating image: pytran.this > pytran.last
DEBUG> refreshing image in 3 secs
taking a 5 minute sample at various thresholds.
DEBUG> grabbing frame from camera 200003
DEBUG> generating frame diff on pytran.last, pytran.this
DEBUG> displaying image: pytran.diff
DEBUG> converting pytran.diff to ascii
DEBUG> calculating traffic ratio...
ratio[5]: 55%
DEBUG> calculating traffic ratio...
ratio[10]: 52%
...
...
5 minute sample[5]: 67.88
5 minute sample[10]: 42.66
5 minute sample[15]: 30.57
5 minute sample[20]: 23.03
5 minute sample[25]: 18.39
5 minute sample[30]: 14.79
5 minute sample[35]: 12.42
5 minute sample[40]: 10.53
5 minute sample[45]: 9.06
5 minute sample[50]: 7.85

The sampling script will take 5 minute samples at varying color thresholds. The optimal threshold must be manually chosen. Furthermore, you will need to sample the traffic ratios during both heavy and light traffic times to get a good feel for your acceptable range. Also, keep in mind that the traffic ratio value is simply the percent change detected, or in other words the movement detected within the masked region. This means that a completely empty road will register similar values to a road so congested it looks like a parking lot. The time of day can be combined with the traffic ration to determine the logical truth.

With this task implemented and abstracted more complex systems can be built. When I find the time Id like to create a system that will take multiple potential travel routes and times, and during the travel time e-mail the traveler with the best route to take. Another idea I had would be to record the traffic flow values for each camera, for each day and for each half hour interval. Travelers and other interested parties can then analyze traffic patterns to determine the fastest route dependant on date/time.