Open Source Algorithms - Page 8

The Asterisk Config PHP-Parser claims to be a simple but effective function writen in PHP non-OOP that is capable to parse any standard .conf Asterisk configuration file an drop the data into a multi-dimensional array.

Asteroid has been merged with Scampi, to give rise to OScar. Follow us on https://bitbucket.org/oscarlib/oscar/wiki/Home Asteroid offers a powerful framework for developing constraint-based local search solution to combinatorial problems. This technique provides good scalability to real-world problems. It includes a library of standard constraints and invariants to declaratively define the problem you want to solve, and it also provides powerful search mechanisms.

Awakener aims to provide a Java library for solving practical, real world optimisation problems by means of genetic algorithms (turnkey algorithms for >= 90% of industry problems). Awakener extends Sleepwalker with specific algorithms.

Very useful framework library, contains many frequent used code snippets, algorithms, data structures, WinForms & APS.NET controls for all-day work.

A C++ library for Bayesian computation, including a collection of more generally-applicable utilities.

Balie - BAseLine Information Extraction (in Java) This project is not maintained anymore.

This is module for basic computation with floating point numbers. Numbers can have very wide mantissa for good precision, for realize "arbitrary-precision arithmetic". Module was adapt for BCB and MSVC compilers. Russian comments.

The toolkit glpk supports methods for mixed integer linear programming (MILP). These methods solve Capital Budgeting Problems (CBP). Unfortunately, glpk does not support any multithreading and there is no feature to distribute problems via network connections. Today, this is a pitiable sight, because modern computer systems are coupled by networks and support multi threading. We create a distributed system with Apache thrift and the C-API of glpk. Now, it is possible to use as many cores in a network as you want. With a focus on the MILP methods we implement a load balancing and speed up the solving process in a multiplicative way. Sometimes we have super-linear speedup with a small set of hardware. With a splitting of problems, parallel computing and distributing the actual best solution to all running processes we solve CBP much faster than a sequential processing can do.

A paint program where the canvas is the visual cortex of a simple kind of artificial intelligence. You paint with the mouse into its dreams and it responds by changing what you painted gradually. There will also be an API for using it with other programs as a general high-dimensional space. Each pixel's brightness is its own dimension. Bayesian nodes have exactly 3 childs because that is all thats needed to do NAND in a fuzzy way as Bayes' Rule which is NAND at certain extremes. NAND can be used to create any logical system. In this early version, I'm still working on edge detection and its understanding of the same shapes at different brightnesses. This will be a module of the bigger Human AI Net project and will be used for adding realtime intuitive high dimensional intelligence in audio and visual interactions with the user.

Belkerda is a simple Python AI program that takes a user's input, builds a log of random numbers, picks a random entry, and displays it. If it is correct, then it reenters that number back into the log several times, overwriting the original, random numbers. If it is not, however, it overwrites a lower amount of entries.

Programm for test BinMatrix, a class for manage binary matrices.

This project is a highly flexible implementation of the well known bin packing algortihms: next fit, first fit, best fit, worst fit. The elements and bins may have any number of dimensions.

This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text. The method is based on SVM but other ML algorithms can be adopted. The method details are explained in the following paper: Ehsan Emadzadeh, Azadeh Nikfarjam, and Graciela Gonzalez. 2011. Double Layered Learning for Biological Event Extraction from Text. In Proceedings of the BioNLP 2011 Workshop Companion Volume for Shared Task, Portland, Oregon, June. Association for Computational Linguistic

It moves by itself inside networks like virus infection & plagues, it is being written to solve computer virus problem drastically and responsibly. It is legal, free and open for public domain to improve W3 ICT Security.

Modules for developing, configuring and running a computation based on function blocks entirely in Python. Function block based computation is a data, event and state driven approach to data processing.

Portable, optimised implementation of Bruce Schneier's 64-bit symmetric block cipher, Blowfish. Includes support for ECB, CBC, CFB, OFB and CTR block cipher modes, weak key detection and parallelisation using OpenMP.

Blubber system is an Eclipse RCP application for distributed systems modeling. Designed for university researches and inlcudes: task graph editor; graph transformation tools; graph modelling on distributed system; real-time modelling on GerdaFramework.

The Boehm-Demers-Weiser conservative garbage collector. The CVS source of the version 7+ collector resided here for a while, but is now on github. Other information and release snapshots are currently at http://hboehm.info/gc

Bookinex is an application designed to index your collection of books, it supports scanning of Barcodes to recognize ISB Numbers and querying web services to collect data.

Bricks4J is a set of common tools, utils and classes for Java, aiming to ease development for a widespread kind of tasks.

We present BudgetedSVM, a C++ toolbox containing highly optimized implementations of three recently proposed algorithms for scalable training of Support Vector Machine (SVM) approximators: Adaptive Multi-hyperplane Machines (AMM), Budgeted Stochastic Gradient Descent (BSGD), and Low-rank Linearization SVM (LLSVM). BudgetedSVM trains models with accuracy comparable to LibSVM in time comparable to LibLinear, as it allows solving highly non-linear classification problems with millions of high-dimensional examples within minutes on a regular personal computer. We provide command-line and Matlab interfaces to BudgetedSVM, efficient API for handling large-scale, high-dimensional data sets, as well as detailed documentation to help developers use and further extend the toolbox.

The C Algorithms library has moved to GitHub. Please go to the new project page: https://github.com/fragglet/c-algorithms

A plug-and-play class-library project of standard Data Structures and Algorithms, written in C#. It contains 75+ Data Structures and Algorithms, designed as Object-Oriented isolated components. Even though this project started for educational purposes, the implemented Data Structures and Algorithms are standard, efficient, stable and tested. This is a C#.NET solution-project, and it contains three subprojects. Algorithms, a class library project which contains the Algorithms implementations. Data Structures, a class library project which contains the Data Structures implementations. Also, UnitTest, a unit-testing project for the Algorithms and Data Structures.