The Shared Scientific Toolbox is a library that facilitates development of efficient, modular, and robust scientific/distributed computing applications in Java. It features multidimensional arrays with extensive linear algebra and FFT support, an asynchronous, scalable networking layer, and advanced class loading, message passing, and statistics packages.
pepper is a commandline tool for retrieving statistics and generating reports from source code repositories. It ships with several graphical and textual reports, and is easily extensible using the Lua scripting language. It includes support for multiple version control systems, including Git and Subversion.
Strategico is an engine for running statistical analysis over groups of time series. It can manage one or more groups (projects) of time series: by default, you can get data from a database or CSV files, normalize them, and then save them inside the engine. The first statistical analysis implemented inside Strategico is the "Long Term Prediction": it automatically finds the best model that fits each time series. Some of the models implemented are mean, trend, linear, exponential smoothing, and Arima. Strategico is scalable: the statistical analysis over each time series (of a project) can be run separately and independently. It is suggested that you set up an HPC Cluster (High Performance Computing) and/or use a resource scheduler like slurm. It is developed with R, one of the most famous statistical languages.
Yalst ("yet another live support tool") is a powerful chatting tool that integrates easily with any Web site. The highlights are visitor and operator initiated chats, audio and video chats, visitor monitoring and tracking with alarm functionality, form monitoring, file transfers in both directions during chats, plugin-free co-browsing, marketing tools (push banners, URLs, messages, and customized surveys), ad-tracking of campaigns, conversion tracking, departments, a FAQ database, a customized contact form (if chat is offline), chat between operators, and an application programming interface for deep Web site integration.
KeyFrog monitors the keyboard and visualizes its usage statistics. The user can obtain much information about keyboard activity: the intensity of keyboard usage, how was it distributed in time, which applications were used, etc. This may be very useful, for example, to developers to monitor their productivity. The environment being monitored is the X Window System (text applications are explicitly supported if run inside an X terminal).
Countly is a real-time, mobile analytics application. It collects event data from mobile phones and visualizes this information to analyze mobile application usage. Countly dashboard gives a complete overview of your application's performance. You can view detailed metrics, including session length, hardware type, operator (carrier), connection type or speed, activity length, and more.
MLPACK is a C++ machine learning library with an emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users. It contains algorithms such as k-means, Gaussian mixture models, hidden Markov models, density estimation trees, kernel PCA, locality-sensitive hashing, sparse coding, linear regression and least-angle regression.