Open Source Mac Algorithms - Page 24

The Parameter Tuning Unity (PTU) aims to adapt the parameters of ever connected multi-agents system, or expert system with a plugged optimization heuristic likes the descent of gradient for instance.

This C++ library contains the 'PdfPageCount' class that performs the single task of finding the number of pages in a given PDF document. While the PdfPageCount class is very simple to use, the contained code is complex because the page count can be hidden in any number of places, quite often within compressed data.

PetoronHash2 (PH2) is a standalone ARX-based sponge construction that combines: A 4096-bit internal permutation core A sponge/duplex architecture with explicit capacity separation An extendable-output function (XOF) Memory-hard (HARD) and burn (BURN) modes A structured tagged absorb scheme A parameterized architecture suitable for hashing, KDF, and stress-oriented derivation PH2 is designed as a wide-state cryptographic primitive with explicit domain separation and configurable output length. https://github.com/01alekseev/PetoronHash2 Petoron | Ivan Alekseev | MIT license

A simply application in order to demonstrate Martinez-Silva optimization algorithm on Petri networks.

An experimental language API and interpreter which combine ideas from functional programming and graph theory.

In this Project,you can find a Phone book is implemented in an AVL Tree, you add new contacts, delete, and save the list to a text file Please check the project files here: https://sourceforge.net/projects/phonebookavl/files/

A collection of phonetic algorithms such as metaphone or soundex for use in Python.

PHP/MySQL implementation of the Active Record pattern. This project is highly focused on simplicity of usage, high compatibility (from php4/mysql3 up to php5/mysql5.1) and code cleaness.

Physhun is a Java framework for building and executing finite state machines in J2SE and J2EE environments. State models are defined as collections of Spring beans, and do not use proprietary modeling languages. The framework is simple and flexible.

Plantra-Trajectory Planning is a software to rebuild surfaces from cloud points, featuring shaded 3D visualization and path planning for robotics paths. It uses Voronoi diagram, Cyrus-Beck clipping, Delaunay triangulation and B-Splines.

PopED (Population Experimental Design) is a software tool for computing optimal experimental designs. The software has been developed with an emphasis on drug trials based on population models (non-linear mixed effects models).

The PowerCiph Data Encryption Algorithm is a versatile, yet simplistic, encryption algorithm/protocol. The ultimate goal of the algorithm is simplicity, compactness, and a lack of prerequisites.

This is a module that computes prayer times, sunrise, sunset and midnight.

Pre-projetos_MLCM - É um conjunto de Programas e códigos fonte dos mesmos, com finalidade educacionais para a área de TI. Sendo eles programas simples que foram desenvolvidos para a aquisição de nota no curso de BCC. Os programas em si, estão ainda em desenvolvimento sendo disponibilizado uma prévia dos progressivos resultados, não se tendo uma data de finalização do projeto definida. Fica a disposição os códigos deles sobre a licença GPL para que estudantes e interessados possam fazer uso e estudo dos mesmos.

ProViz is a program visualization framework for Java. It is built as a plugin to the Eclipse IDE. (We are getting close to publishing resources and making this project distributable. Stay tuned!) A video demo: http://www.youtube.com/watch?v=BsoK1n-OM

PAK is a collection of library code to handle the overhead of coding things like read-write locks, reflective multithreaded programming and simple file io. This is a java library collection, please see my API below...

Model-based AI planner using binary decision diagrams. PropPlan parses PDDL descriptions of the domain and the problem, and outputs a plan.

Provisio.Collections brings STL like iterator-based containers to the .Net world (especially C#). It offers fundamental sequential (vector/list/deque) and associative (tree/skiplist) containers that can be filled, traversed and modified using iterators.

A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer Vision and Pattern Recognition, 2012. This source code is provided without warranty and is available under the GPL license. More commercially-friendly licenses may be available. Please contact Stephen O'Hara for license options. Please view the wiki on this site for installation instructions and examples on reproducing the results of the papers.

PyPlayground is an environment for developing algorithms involving movement in a space of up to three dimensions using Python.

PyVision is a object-oriented Computer Vision Toolkit for researchers that contains vision and machine learning algorithms and algorithm analysis and easily interfaces with scipy/numpy, PIL, opencv and other computer and machine learning libraries.

A Python module to learn all the major algorithms on the go! Purely for educational purposes. If you are using Python 2.7 use pip instead. Depending on your permissions, you might need to use pip install, user pygorithm to install. To see all the available functions in a module, you can just type help() with the module name as an argument.

A Python library for easy creation and manipulation of Google Earth KML and KMZ placemark files. Please get your copy from http://pykml.cvs.sourceforge.net/viewvc/pykml/pykml/?view=tar

This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.

PyOD is a comprehensive and scalable Python toolkit for detecting outlying objects in multivariate data. This exciting yet challenging field is commonly referred as outlier detection or anomaly detection. PyOD includes more than 30 detection algorithms, from classical LOF (SIGMOD 2000) to the latest COPOD (ICDM 2020) and SUOD (MLSys 2021). Since 2017, PyOD [AZNL19] has been successfully used in numerous academic researches and commercial products [AZHC+21, AZNHL19]. PyOD has multiple neural network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models. In total, 17 benchmark datasets are used for comparison, which can be downloaded at ODDS.