Open Source Algorithms - Page 14

Barracuda is a circuit board analyzer that analyze PCB and make sure the new boards doesn't contain errors Barracuda has now his first release, The error detection works fine, but it require to much calibration to get good pictures.

the package chewingum contains two main programs: - base62 - chew They have been implemented in perl. Base62 has been coded in c++ too. chew has been written to shorten long decimal integer numbers into base62 strings. It's not a mere base conversion, because it doesn't use arithmetic inside its logic. In this way it can convert very long numbers into strings quickly, without overflows. For example if I want to share an id using an url, this will make the url shorter. the base62 program has been written to encode/decode files into this format. The syntax is similar to the popular base64 command line program. Inside the package there is a working c++ version of the base62 algorithm. the sources are inside the package. Note that from release 2.0.0 the algorithm is different from the one used before. If you have coded a file using base62 < 2.0.0 DO NOT USE base62 >= 2.0.0 to decode it. The 2.0.1 release has a new algorithm for chew, we have a compat flag

Unlike the other two, openai/baselines is not currently a maintained or prominent repo in the OpenAI organization (and I found no strong reference in OpenAI’s main GitHub). Historically, “baselines” repositories are often used for baseline implementations of reinforcement learning algorithms or reference models (e.g. in the RL domain). If there was an OpenAI “baselines” repo, it might have contained reference implementations for reinforcement learning or model policy baselines to compare new work against. However, I couldn’t locate an active “openai/baselines” in the latest OpenAI repos, so it may have been archived, removed, or merged into other projects. If you meant a different “baselines” (e.g. OpenAI Baselines for reinforcement learning), I can look up that specific one.

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 tool to extract taxonomy from OWL ontology, translate it into Bayesian Nets and integrate uncertainty knowledge into result BNs.

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.

Beagle is Java open source framework for running and managing nondeterministic algorithms such as genetic algorithms for solving complex problems. Beagle is fully modular and maintains whole history of algorithm progress for further analysis.

Bebops ("Belief Base Operations") provides semi-revision, contraction and kernel operators for an OWL-backed Belief Base.

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.

My personal computing suite provides some programs I developed as a hobbyist and currently include a lambda calculus interpreter and a calculator which solves arithmetic expressions; both are written in C++.

BigAl is a free open source and platform independent software for calculating really BIG numbers. It supports not only standard arithmetic, but also exact period determination, predefined factorials, fibonacci with seeds, factorization, nth root, etc

A heuristic approach to solving the Knight's Tour Puzzle

BinBase is a software for the automatic analysis of Massspec data from LECO GC-Tofs. All code and documentation has been moved to the google code site of this project: https://code.google.com/p/binbase/ And support is provided by the company coding and more, which can be reached under: contact@codingandmore.org

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.

A library for iris-detection written in pure C# and .NET 3.5.

This is a Python script for Blender which uses short (quaternion-based, floretion-based) algorithms to draw curves in space. The user can create new shapes and curves by setting a variety of parameters.

Booleans all meshes on the screen. Plus: A fractal generator and attractor generator with a delicious SEARCH function ;) <meta name="google-site-verification" content="cULQewNGfx-aXCQR9fTJZ1Z7DXbLA5GjqjvAfF_oH5I" />

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.