Award Data

CONCUR develops a computational framework for assessing and characterizing urban environments stability or fragility in response to volatility and stress, identifying specific weaknesses as well as key tipping points which could lead to rapid systemic failure. CONCUR explicitly models urban environments as emergent complex systems, focusing attention on the critical triggers that could lead to rap ...

Boston Fusion Corp. and Arizona State University will research and develop REsilience & Stability in DENse Terrains (RESIDENT), a multi-model, multi-scale framework for assessing indicators of stability and resilience in dense urban environments. Our team consists of subject matter experts in the Social and Computer Sciences providing the bedrock on which to build accurate mathematical models of u ...

Methods for interconversion between cell types (cellular reprogramming) are currently discovered through resource intensive trial and error. Experiments may test a multitude of transcription factors to identify correct combinations that influence cell fate. In addition, reprogramming approaches commonly use stem cell intermediates such as induced pluripotent stem cells (iPSCs), which are generated ...

The unique scale, population density, complexity, and connectedness of megacities requires new tools for detecting and assessing risks related to civil unrest, rule of law, terrorism, and other sources of instability, and for understanding the underlying dynamics. In addition, gray zone operations pose a new and strategically important class of threats to the stability of nation states and cities ...

Space superiority requires space protection and space situational awareness (SSA), which rely on rapid and accurate space object behavioral and operational intent discovery. The focus of this project is to develop a stochastic approach for rapid discovery of evasive satellite behaviors. Designing the innovative decision support tool has numerous challenges: (i) partial observable actions; (ii) eva ...

Target detection and recognition is a challenging problem because of changes in appearance, viewing direction, occlusion and other covariates. Systems that can accurately and efficiently detect and track objects can provide several benefits in surveillance, monitoring and other applications. As part of this effort, we propose to develop a robust learning-based approach to detect, track and recogni ...

Adverse physiological events (PEs) have plagued warfighters piloting military aircraft, in particular PEs involving hypoxia and cockpit cabin decompression. Though there has been a large variety of research performed in trying to understand the problems and why theyre caused, there are inefficiencies due to the lack of standardized cross-laboratory protocols, procedures, and metrics. To address th ...

This proposal is to develop a Handoff Training for Combat Casualty Care (HTC3) Framework.Training is the crux of the handoff problem today. Patient handoffs are a crucial part of casualty care, both in military and civilian environments; and today handoffs are being performed in less than optimal fashion, with ineffective communications accounting for 80% of the handoff errors. Our new HTC3 Framew ...

The main objective of this STTR Phase I effort is two-fold. First, to develop a robust approach for coupling the flow solver Kestrel with the multidisciplinary software tool AERO Suite in order to enable the physics-based modeling and simulation of the dynamics of Aerodynamics Decelerator Systems (ADS) such as parachutes from deployment to terminal velocity or terminal descent and touchdown, and t ...

Because of rising demand for human analysts and more efficient processing of increasingly large and challenging amounts of intelligence, human limitations on mental workload, cognitive fatigue, and attentionor task engagement, need to be accurately monitored in real-time in order to provide sensitive detection of impaired cognitive states. It is a challenge to continuously monitor these cognitive ...