Award Data

Knowledge Based Systems, Inc. (KBSI) is pleased to propose the further design and development of MySidewalk mobile application facilitating the crowd-sourced collection of sidewalk inventory and condition data. The MySidewalk application utilizes advances in social networks and data mining to provide integrated sidewalk datasets. Phase I and II research was facilitated by inputs from City of Colle ...

Gun-launched applications currently expose inertial measurement units (IMUs) to harsh acceleration, shock, and vibration environments. Furthermore, as they become smarter, they present tighter constraints on size, weight, power, and cost (SWaP-C), while still requiring high levels of performance. New accelerometer technology must reduce SWaP-C while operating through high-g acceleration environmen ...

Nanohmics proposes to develop a chip-scale inertial measurement unit (IMU) for munitions applications. The miniaturization is key to extreme-G survivability and operation. Models and simulations will provide primary support for the feasibility and a hardware demonstration will provide additional proof-of-concept and improve the program risk assessment prior to a Phase II program.

Mission times for high velocity projectiles (HVP) are very short and detection and discrimination of targets must happen quickly and decisively. One way to achieve this is through the enhanced contrast resulting from polarized sensing, which tends to highlight manmade objects and suppress natural background clutter. Thermal polarimetric sensing in a small package has been demonstrated already but ...

The development of a guided hypervelocity projectile (HVP) must surmount a number of significant technical challenges. Texas Research Institute Austin (TRI Austin) proposes to address leading edge/control surface challenges, sabot design, and the sub-projectile issues through the selection of materials, material processes, and component manufacturing methods. TRI Austin has assembled a team of tec ...

Homomorphic Encryption (HE) allows for training and deployment of neural networks on encrypted data. Furthermore, HE allows for encryption of neural network model parameters such as weights. Thus, HE provides robustness against both black-box and white-box attacks. In the emerging cloud-based AI environments with edge computing nodes, HE enables privacy-preserving training and deployment of neural ...

We propose a quantum adversarial machine learning (QAML) approach that combines ideas from different classical AML techniques such as Defense-GAN and thermometer-encoding of inputs. We propose an implementation of Defense-GAN on the D-Wave Leap quantum computing environment. We also propose to leverage ideas from quantum information science such as noisy inputs/outputs/parameters to improve the ro ...

Protecting the effectiveness of US advanced weapon systems and the technology they rely on is a national priority. Unfortunately, individuals tasked with this mission are met with disjointed guidance, no training, and competing processes to consider. It is no wonder adversaries continue to exploit these weaknesses in the Department of Defense (DOD); stealing our Critical Program Information (CPI) ...

Existing physics-based device simulation tools are prohibitively expensive computationally, and therefore ill-suited for parametric analysis and design optimization of photonic integrated circuits (PIC). The proposed effort aims to develop and demonstrate an innovative, easy-to-use simulation tool for accurate, fast circuit/system analysis of PICs. The salient aspects of the proposed solution are: ...

Increasing the autonomy of unmanned vehicles potentially reduces operator workload and cognitive load. Realizing the promise of autonomy however, is difficult when deploying in environments with mobility and visibility challenges, enemy threats, risks of endangering civilians, and limited communication. Achieving full autonomy in the face of these challenges is both a hard technical problem and do ...