Award Data

Modern processor design is trending increasingly toward multicore architectures. This is problematic for programmers because writing a correct parallel program is known to be difficult compared to writing the equivalent sequential program. Additionally, a wide body of sequential code has already been developed that cannot exploit the power offered by these new cores because it was written in a s ...

ABSTRACT: Barron Associates Inc. proposes development of a Game-based AutonoMy-Enabled Response (GAMER) system for spacecraft protection. The effort extends leading-edge research in dynamic games to enable autonomous defensive response to space threats. GAMER introduces a hierarchical approach that enables multiple satellites to work together towards a common protection strategy in an evolving en ...

ABSTRACT: We propose to develop an assured information sharing framework for cloud-based systems that leverages our ongoing work in the areas of policy-based usage management and semantic interoperability. The development of this framework will involve the creation of a novel approach to information sharing that treats security as a commodity that can be dynamically provisioned within the cloud, ...

Thegoal is to develop asoftwaretool that implementsa novelapproach applicableto fitgeneral pharmacologic, toxicology, or other biomedical data, that mayexhibita non-monotonic dose-responserelationship for which thecurrent parametricmodels fail. Thesoftwareexplores dose-responserelationships using both monotonicand non-monotonicmodels,and estimates theassociated doseresponsecurves,which can further ...

For this STTR Intelligent Automation, Inc. teams with researchers from University of Maryland, College Park to develop SLA, a self-learned agent system for collective human activities and events in aerial videos. Aerial video analytics often faces challenges such as low resolution, shadows, varied spatio-temporal dynamics, etc. The traditional methods depending on the object detection and tracking ...

The project will develop and validate a geometry scalable CNTFET compact model for HF circuit design and extract the model parameters from the measured characteristics of the fabricated devices. The ballistic and quasi-ballistic transport, quantum and parasitic effects will be accounted for the predicted performance will be compared to 130 nm RF Si-CMOS to determine the conditions for breaking eve ...

The machine learning and artificial intelligence community has recently garnered much attention for ground breaking performance of novel neural network architectures for self-driving cars. One of the machine learning methods used in self-driving cars is semantic segmentation. In this fashion each pixel in an image is label with a class, allowing for contour-based image segmentation which is differ ...

Adiabatic logic-based energy-conserving circuits have potential to significantly improve energy efficiency. Adiabatic circuits recycle charge stored in load capacitance resulting in lower power dissipation as compared to conventional CMOS. However, these circuits have only targeted low-frequency operations. Research is needed to develop adiabatic logic circuits for high performance applications wi ...

This effort will investigate the use MALDI (matrix assisted laser desorption/ionization)-TOF (time-of-flight) mass spectrometer as a platform for rapid analysis of biomarkers in operational and training environments. In Phase I samples, will be acquired from human subjects under stress. These samples will be processed for analysis using our prototype portable MALDI TOF mass spectrometer. Samples w ...

Locating objects that vibrate is a way to discern potential threats and locate targets. However, current vibrometry technology typically measures only the global vibration of target and cannot create an extended spatial measurement of the vibration profile of the target. These solutions cannot identify what the target is, nor can they locate potential weak spots on the target, because they lack sp ...