5,034 research outputs found
Hypermedia Learning Objects System - On the Way to a Semantic Educational Web
While eLearning systems become more and more popular in daily education,
available applications lack opportunities to structure, annotate and manage
their contents in a high-level fashion. General efforts to improve these
deficits are taken by initiatives to define rich meta data sets and a
semanticWeb layer. In the present paper we introduce Hylos, an online learning
system. Hylos is based on a cellular eLearning Object (ELO) information model
encapsulating meta data conforming to the LOM standard. Content management is
provisioned on this semantic meta data level and allows for variable,
dynamically adaptable access structures. Context aware multifunctional links
permit a systematic navigation depending on the learners and didactic needs,
thereby exploring the capabilities of the semantic web. Hylos is built upon the
more general Multimedia Information Repository (MIR) and the MIR adaptive
context linking environment (MIRaCLE), its linking extension. MIR is an open
system supporting the standards XML, Corba and JNDI. Hylos benefits from
manageable information structures, sophisticated access logic and high-level
authoring tools like the ELO editor responsible for the semi-manual creation of
meta data and WYSIWYG like content editing.Comment: 11 pages, 7 figure
SBML models and MathSBML
MathSBML is an open-source, freely-downloadable Mathematica package that facilitates working with Systems Biology Markup Language (SBML) models. SBML is a toolneutral,computer-readable format for representing models of biochemical reaction networks, applicable to metabolic networks, cell-signaling pathways, genomic regulatory networks, and other modeling problems in systems biology that is widely supported by the systems biology community. SBML is based on XML, a standard medium for representing and transporting data that is widely supported on the internet as well as in computational biology and bioinformatics. Because SBML is tool-independent, it enables model transportability, reuse, publication and survival. In addition to MathSBML, a number of other tools that support SBML model examination and manipulation are provided on the sbml.org website, including libSBML, a C/C++ library for reading SBML models; an SBML Toolbox for MatLab; file conversion programs; an SBML model validator and visualizer; and SBML specifications and schemas. MathSBML enables SBML file import to and export from Mathematica as well as providing an API for model manipulation and simulation
CEDAR: tools for event generator tuning
I describe the work of the CEDAR collaboration in developing tools for tuning
and validating Monte Carlo event generator programs. The core CEDAR task is to
interface the Durham HepData database of experimental measurements to event
generator validation tools such as the UCL JetWeb system - this has
necessitated the migration of HepData to a new relational database system and a
Java-based interaction model. The "number crunching" part of JetWeb is also
being upgraded, from the Fortran HZTool library to the new C++ Rivet system and
a generator interfacing layer named RivetGun. Finally, I describe how Rivet is
already being used as a central part of a new generator tuning system, and
summarise two other CEDAR activities, HepML and HepForge.Comment: 13 pages, prepared for XI International Workshop on Advanced
Computing and Analysis Techniques in Physics Research, Amsterdam, April 23-27
200
Document Builder
In this paper, we consider problems related to on-demand content publishing and maintenance. Specifically, we are concerned with the recent concept of structural Content Management Systems (CMS) and its design principles. We focus on Apache Ant, a popular document generator tool for the Java development industry. However, Ant has not been widely extended beyond its capacity to deal with computer programs, which limits its utility. We analyze the Ant build script structure, study its usage, and implement an on-demand document generator for Ant. The focus is to provide a better document build model based on Ant, which can provide document workflows and templates enabling people to work together more efficiently
Developing a Web Server Platform with SAPI support for AJAX RPC using JSON
Writing a custom web server with SAPI support is a useful task which helps students and future system architects to understand the link between network programming, object oriented programming, enterprise application designing patterns and development best practices because it offers a vision upon interprocess communication and application extensibility in a distributed environmentWeb, Server, Proxy, SAPI, HTTP, RPC, AJAX, JSON, XML
Iris: an Extensible Application for Building and Analyzing Spectral Energy Distributions
Iris is an extensible application that provides astronomers with a
user-friendly interface capable of ingesting broad-band data from many
different sources in order to build, explore, and model spectral energy
distributions (SEDs). Iris takes advantage of the standards defined by the
International Virtual Observatory Alliance, but hides the technicalities of
such standards by implementing different layers of abstraction on top of them.
Such intermediate layers provide hooks that users and developers can exploit in
order to extend the capabilities provided by Iris. For instance, custom Python
models can be combined in arbitrary ways with the Iris built-in models or with
other custom functions. As such, Iris offers a platform for the development and
integration of SED data, services, and applications, either from the user's
system or from the web. In this paper we describe the built-in features
provided by Iris for building and analyzing SEDs. We also explore in some
detail the Iris framework and software development kit, showing how astronomers
and software developers can plug their code into an integrated SED analysis
environment.Comment: 18 pages, 8 figures, accepted for publication in Astronomy &
Computin
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
- âŠ