Compressive Wavefront Sensing with Weak Values

We demonstrate a wavefront sensor based on the compressive sensing, single-pixel camera. Using a high-resolution spatial light modulator (SLM) as a variable waveplate, we weakly couple an optical field's transverse-position and polarization degrees of freedom. By placing random, binary patterns on the SLM, polarization serves as a meter for directly measuring random projections of the real and imaginary components of the wavefront. Compressive sensing techniques can then recover the wavefront. We acquire high quality, 256x256 pixel images of the wavefront from only 10,000 projections. Photon-counting detectors give sub-picowatt sensitivity

Nā Hīmeni Hawai‘i: Transcending Kū‘ē, Promoting Kūpa‘a.

M.A. Thesis. University of Hawaiʻi at Mānoa 2017

Photon counting compressive depth mapping

We demonstrate a compressed sensing, photon counting lidar system based on the single-pixel camera. Our technique recovers both depth and intensity maps from a single under-sampled set of incoherent, linear projections of a scene of interest at ultra-low light levels around 0.5 picowatts. Only two-dimensional reconstructions are required to image a three-dimensional scene. We demonstrate intensity imaging and depth mapping at 256 x 256 pixel transverse resolution with acquisition times as short as 3 seconds. We also show novelty filtering, reconstructing only the difference between two instances of a scene. Finally, we acquire 32 x 32 pixel real-time video for three-dimensional object tracking at 14 frames-per-second.Comment: 16 pages, 8 figure

Flight elements: Fault detection and fault management

Fault management for an intelligent computational system must be developed using a top down integrated engineering approach. An approach proposed includes integrating the overall environment involving sensors and their associated data; design knowledge capture; operations; fault detection, identification, and reconfiguration; testability; causal models including digraph matrix analysis; and overall performance impacts on the hardware and software architecture. Implementation of the concept to achieve a real time intelligent fault detection and management system will be accomplished via the implementation of several objectives, which are: Development of fault tolerant/FDIR requirement and specification from a systems level which will carry through from conceptual design through implementation and mission operations; Implementation of monitoring, diagnosis, and reconfiguration at all system levels providing fault isolation and system integration; Optimize system operations to manage degraded system performance through system integration; and Lower development and operations costs through the implementation of an intelligent real time fault detection and fault management system and an information management system

Compressively characterizing high-dimensional entangled states with complementary, random filtering

The resources needed to conventionally characterize a quantum system are overwhelmingly large for high- dimensional systems. This obstacle may be overcome by abandoning traditional cornerstones of quantum measurement, such as general quantum states, strong projective measurement, and assumption-free characterization. Following this reasoning, we demonstrate an efficient technique for characterizing high-dimensional, spatial entanglement with one set of measurements. We recover sharp distributions with local, random filtering of the same ensemble in momentum followed by position---something the uncertainty principle forbids for projective measurements. Exploiting the expectation that entangled signals are highly correlated, we use fewer than 5,000 measurements to characterize a 65, 536-dimensional state. Finally, we use entropic inequalities to witness entanglement without a density matrix. Our method represents the sea change unfolding in quantum measurement where methods influenced by the information theory and signal-processing communities replace unscalable, brute-force techniques---a progression previously followed by classical sensing.Comment: 13 pages, 7 figure

Sensory Evaluation of Ice Cream made with Prebiotic Ingredients

Fructooligosaccharides (FOS) and inulin are considered prebiotic ingredients and are FDA approved for use in food for human consumption. A prebiotic is a food ingredient that benefits the host by selectively stimulating the growth and activity of the beneficial bacteria in the colon. In this project, consumer acceptability of ice cream made with 10% of the sugar substituted with either inulin or FOS was tested. Physical tests were also conducted. The texture, water activity and L and b color values did not differ significantly for the treatments (Inulin and FOS) versus the control sample. The a value for color (red/green) differed (p=0.02) for the treatment samples when compared to the control. For the sensory evaluation, 71 participants ranked the ice cream samples made with inulin and FOS equally as well liked (6.56 and 6.80, respectively) on a 17 cm hedonic scale (0 = like and 17 = dislike). However, the participants liked the control ice cream better than the ice cream with a prebiotic ingredient (P\u3c0.001). Inulin and FOS are potential ingredients for use in ice cream

Cultural health assets of Somali and Oromo refugees and immigrants in Minnesota: Findings from a community-based participatory research project

This community-based participatory research study sought to identify the cultural health assets of the Somali and Oromo communities in one Minnesota neighborhood that could be mobilized to develop culturally appropriate health interventions. Community asset mappers conducted 76 interviews with Somali and Oromo refugees in in Minnesota regarding the cultural assets of their community. A community-university data analysis team coded data for major themes. Key cultural health assets of the Somali and Oromo refugee communities revealed in this study include religion and religious beliefs, religious and cultural practices, a strong culture of sharing, interconnectedness, the prominence of oral traditions, traditional healthy eating and healthy lifestyles, traditional foods and medicine, and a strong cultural value placed on health. These cultural health assets can be used as building blocks for culturally relevant health interventions.published_or_final_versio

Virus Propagation in Multiple Profile Networks

Suppose we have a virus or one competing idea/product that propagates over a multiple profile (e.g., social) network. Can we predict what proportion of the network will actually get "infected" (e.g., spread the idea or buy the competing product), when the nodes of the network appear to have different sensitivity based on their profile? For example, if there are two profiles $\mathcal{A}$ and $\mathcal{B}$ in a network and the nodes of profile $\mathcal{A}$ and profile $\mathcal{B}$ are susceptible to a highly spreading virus with probabilities $\beta_{\mathcal{A}}$ and $\beta_{\mathcal{B}}$ respectively, what percentage of both profiles will actually get infected from the virus at the end? To reverse the question, what are the necessary conditions so that a predefined percentage of the network is infected? We assume that nodes of different profiles can infect one another and we prove that under realistic conditions, apart from the weak profile (great sensitivity), the stronger profile (low sensitivity) will get infected as well. First, we focus on cliques with the goal to provide exact theoretical results as well as to get some intuition as to how a virus affects such a multiple profile network. Then, we move to the theoretical analysis of arbitrary networks. We provide bounds on certain properties of the network based on the probabilities of infection of each node in it when it reaches the steady state. Finally, we provide extensive experimental results that verify our theoretical results and at the same time provide more insight on the problem