The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

Helac-nlo

Based on the OPP technique and the HELAC framework, HELAC-1LOOP is a program that is capable of numerically evaluating QCD virtual corrections to scattering amplitudes. A detailed presentation of the algorithm is given, along with instructions to run the code and benchmark results. The program is part of the HELAC-NLO framework that allows for a complete evaluation of QCD NLO corrections.Comment: minor text revisions, version to appear in Comput.Phys.Commu

ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization

ROOT is an object-oriented C++ framework conceived in the high-energy physics (HEP) community, designed for storing and analyzing petabytes of data in an efficient way. Any instance of a C++ class can be stored into a ROOT file in a machine-independent compressed binary format. In ROOT the TTree object container is optimized for statistical data analysis over very large data sets by using vertical data storage techniques. These containers can span a large number of files on local disks, the web, or a number of different shared file systems. In order to analyze this data, the user can chose out of a wide set of mathematical and statistical functions, including linear algebra classes, numerical algorithms such as integration and minimization, and various methods for performing regression analysis (fitting). In particular, ROOT offers packages for complex data modeling and fitting, as well as multivariate classification based on machine learning techniques. A central piece in these analysis tools are the histogram classes which provide binning of one- and multi-dimensional data. Results can be saved in high-quality graphical formats like Postscript and PDF or in bitmap formats like JPG or GIF. The result can also be stored into ROOT macros that allow a full recreation and rework of the graphics. Users typically create their analysis macros step by step, making use of the interactive C++ interpreter CINT, while running over small data samples. Once the development is finished, they can run these macros at full compiled speed over large data sets, using on-the-fly compilation, or by creating a stand-alone batch program. Finally, if processing farms are available, the user can reduce the execution time of intrinsically parallel tasks - e.g. data mining in HEP - by using PROOF, which will take care of optimally distributing the work over the available resources in a transparent way

Computer-based assessment system for e-learning applied to programming education

Tese de Mestrado Integrado. Engenharia Informática e Computação. Faculdade de Engemharia. Universidade do Porto. 201

A CasADi Based Toolchain For JModelica.org

Computer-aided modeling for simulation, optimization and analysis is increasingly used for product development in industry today, resulting in high demands on the tools used. A tool chain for transferring interpreted code of the modeling languages Modelica and Optimica from the simulation and optimization tool JModelica.org to CasADi has been implemented. CasADi provides several desirable features, most importantly an integrated and ecient automatic dierentiation engine and the ability to interactively work with the systems expressed using it. The biggest problems solved to enable this were the creation of a representation of the mathematical systems described by Modelica and Optimica code that is integrated with CasADi, and the construction of a transfer scheme for moving information from the Java-based JModelica.org compiler to C++ in which CasADi resides. This was successfully achieved for a continuous subset of Modelica and Optimica that may contain functions