Caring, sharing widgets: a toolkit of sensitive widgets

Although most of us communicate using multiple sensory modalities in our lives, and many of our computers are similarly capable of multi-modal interaction, most human-computer interaction is predominantly in the visual mode. This paper describes a toolkit of widgets that are capable of presenting themselves in multiple modalities, but further are capapble of adapting their presentation to suit the contexts and environments in which they are used. This is of increasing importance as the use of mobile devices becomes ubiquitous

A toolkit of mechanism and context independent widgets

Most human-computer interfaces are designed to run on a static platform (e.g. a workstation with a monitor) in a static environment (e.g. an office). However, with mobile devices becoming ubiquitous and capable of running applications similar to those found on static devices, it is no longer valid to design static interfaces. This paper describes a user-interface architecture which allows interactors to be flexible about the way they are presented. This flexibility is defined by the different input and output mechanisms used. An interactor may use different mechanisms depending upon their suitability in the current context, user preference and the resources available for presentation using that mechanism

Transportable Applications Environment (TAE) Plus: A NASA tool for building and managing graphical user interfaces

The Transportable Applications Environment (TAE) Plus, developed at NASA's Goddard Space Flight Center, is an advanced portable user interface development which simplifies the process of creating and managing complex application graphical user interfaces (GUI's). TAE Plus supports the rapid prototyping of GUI's and allows applications to be ported easily between different platforms. This paper will discuss the capabilities of the TAE Plus tool, and how it makes the job of designing and developing GUI's easier for application developers. TAE Plus is being applied to many types of applications, and this paper discusses how it has been used both within and outside NASA

Sensing and visualizing spatial relations of mobile devices

Location information can be used to enhance interaction with mobile devices. While many location systems require instrumentation of the environment, we present a system that allows devices to measure their spatial relations in a true peer-to-peer fashion. The system is based on custom sensor hardware implemented as USB dongle, and computes spatial relations in real-time. In extension of this system we propose a set of spatialized widgets for incorporation of spatial relations in the user interface. The use of these widgets is illustrated in a number of applications, showing how spatial relations can be employed to support and streamline interaction with mobile devices

The application of the Hadoop software framework in Bioinformatics programs

The project described in this dissertation proposal attempted to improve the efficiency and scalability performance as well as the usability and user experience of three Bioinformatics applications - DNA/peptide sequence similarity comparison, digital DNA library subtraction, and DNA/peptide sequence de-duplication - by 1) adopting the Hadoop MapReduce algorithms and distributed file system and 2) implementing the fully automated Hadoop programs into a user friendly graphical user interface (GUI). In addition, the researcher was also interested in investigating the advantages and limitations of applying the Hadoop software framework as a general methodology in parallelizing Bioinformatics programs. After considering the original calculation algorithms in the serial version of the programs, the available computational resources, the nature of the MapReduce framework, and the optimization of performance, a processing pipeline with one pre-processing step, three mappers, two reducers and one post-processing step was developed. Then a GUI interface that enabled users to specify input/output files and program parameters was created. Also implanted into the GUI were user friendly features such as organized instruction, detailed log files, multi-user accessibility, and so on. The new and fully automated Hadoop Bioinformatics toolkit showed execution efficiency comparable with their MPI counterparts with median to large scale data, and better efficiency than MPI when ultra-large dataset was provided. In addition, good scalability was observed with testing dataset up to 20 Gb

Ellogon: A New Text Engineering Platform

This paper presents Ellogon, a multi-lingual, cross-platform, general-purpose text engineering environment. Ellogon was designed in order to aid both researchers in natural language processing, as well as companies that produce language engineering systems for the end-user. Ellogon provides a powerful TIPSTER-based infrastructure for managing, storing and exchanging textual data, embedding and managing text processing components as well as visualising textual data and their associated linguistic information. Among its key features are full Unicode support, an extensive multi-lingual graphical user interface, its modular architecture and the reduced hardware requirements.Comment: 7 pages, 9 figures. Will be presented to the Third International Conference on Language Resources and Evaluation - LREC 200

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