Research and Development Projects

SRC's Information Science and Engineering business area performs research and development, in both internally funded (IR&D) and customer-funded (CR&D) projects, in a number of technologies and application areas, including: Workflow and Collaborative Tools, Enterprise Systems, Distributed Databases, Modeling and Simulation, and Data Visualization. In most cases, these R&D efforts are performed as the concept development or proof-of-concept steps toward product development and deployment.

Our current R&D projects include the following:

Data Mining & Predicting Biodegradability
In this project, we are developing advanced approaches for calculating the probability of whether a chemical under aerobic conditions with mixed cultures of micro-organisms will biodegrade rapidly or slowly. The R&D focuses on the application of decision trees and neural networks for discovering the effectiveness of data mining techniques for predicting biodegradability versus traditional statistical methods.

Data Fusion for Content Management
In this R&D project, we are developing a content management approach for reading, analyzing, and fusing radar with other intelligence data sources to create potential target locations. A standardized ontology has been developed using XML, which can be used in both simulations and live data acquisition environments with various fusion engines. Raw data and fused results are displayed graphically in the MATLAB environment to visualize the potential targets.

Linguistic & Visual Information Access (LiVIA)
In this project, we are developing a Knowledge Retrieval, Extraction, and Visualization capability for searching against unstructured text sources, using Natural Language Processing (NLP) techniques. NLP is a branch of Artificial Intelligence focused on analyzing text at various levels of language understanding, which humans use routinely to extract meaning. This R&D project is a collaborative effort with the Center for Natural Language Processing (CNLP) at Syracuse University. Results from this R&D can be used for Information Retrieval, Question and Answer systems, and Automated Meta-Tagging.