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 ...

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 ...

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 ...

On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

Understanding and minimizing RF loss in tunable components is key to the successful integration of this technology in high performance wireless devices. Filter applications, in particular, fundamentally require extremely low loss to operate efficiently. Agile’s high-frequency tunable filter development efforts using BST have found that loss due to surface or series resistance (Rs) is a significa ...

The objective of this project is to implement and demonstrate a new robotic system enabling Natural Orifice Transluminal Endoscopic Surgery (NOTES) that improves surgical care of warfighters and their families. The proposed NOTES system will be used for many military and civilian surgery needs, especially on natural orifice diagnosis and treatment of acute appendicitis at a role 2 facility with re ...

The duties of modern military personnel often require the completion of challenging tasks, in stressful environments, and with multiple demands competing for the warfighter’s focus. Measuring the stress, anxiety, uncertainty, and fatigue (SAUF) of the warfighter during a particular task would have multiple benefits: (1) commanders would be able to detect problems and reallocate workload or addre ...

Hemorrhagic shock remains a leading cause of death for soldiers on the battlefield. The first 60 minutes following a traumatic injury is vital to saving lives; therefore, it is critical to provide medical personnel with real time monitoring of soldiers with traumatic injuries. Recent research indicates, however, that no single measure alone is sufficient to determine the severity of hemorrhage in ...