CosmoDM and its application to Pan-STARRS data

The Cosmology Data Management system (CosmoDM) is an automated and flexible data management system for the processing and calibration of data from optical photometric surveys. It is designed to run on supercomputers and to minimize disk I/O to enable scaling to very high throughput during periods of reprocessing. It serves as an early prototype for one element of the ground-based processing required by the Euclid mission and will also be employed in the preparation of ground based data needed in the eROSITA X-ray all sky survey mission. CosmoDM consists of two main pipelines. The first is the single-epoch or detrending pipeline, which is used to carry out the photometric and astrometric calibration of raw exposures. The second is the co- addition pipeline, which combines the data from individual exposures into deeper coadd images and science ready catalogs. A novel feature of CosmoDM is that it uses a modified stack of As- tromatic software which can read and write tile compressed images. Since 2011, CosmoDM has been used to process data from the DECam, the CFHT MegaCam and the Pan-STARRS cameras. In this paper we shall describe how processed Pan-STARRS data from CosmoDM has been used to optically confirm and measure photometric redshifts of Planck-based Sunyaev-Zeldovich effect selected cluster candidates.Comment: 11 pages, 4 figures. Proceedings of Precision Astronomy with Fully Depleted CCDs Workshop (2014). Accepted for publication in JINS

ECONOMIC AND ENVIRONMENTAL EVALUATION OF DAIRY MANURE UTILIZATION FOR YEAR ROUND CROP PRODUCTION

The production of excess on-farm manure is placing continuous pressures on dairy producers to meet or exceed standards for environmental regulations while maintaining profitability and competitiveness. Evaluation of the effects of recycling nutrients on the profitability of the whole farm enterprise is important for a dairy operation. The objective of this study was to develop a linear programming model that evaluates the economic performance of a dairy operation considering production and environmental constraints. The main goal was to maximize profits from the dairy enterprise considering milk production, manure production, crop production while maintaining a balance of nutrients in the system. Results from simulation analyses showed greater effects on total farm profits at the more restrictive P-based than N-based manure application rates.Environmental Economics and Policy,

Single lens off-chip cellphone microscopy

Within the last few years, cellphone subscriptions have widely spread and now cover even the remotest parts of the planet. Adequate access to healthcare, however, is not widely available, especially in developing countries. We propose a new approach to converting cellphones into low-cost scientific devices for microscopy. Cellphone microscopes have the potential to revolutionize health-related screening and analysis for a variety of applications, including blood and water tests. Our optical system is more flexible than previously proposed mobile microscopes and allows for wide field of view panoramic imaging, the acquisition of parallax, and coded background illumination, which optically enhances the contrast of transparent and refractive specimens

Layered 3D: tomographic image synthesis for attenuation-based light field and high dynamic range displays

We develop tomographic techniques for image synthesis on displays composed of compact volumes of light-attenuating material. Such volumetric attenuators recreate a 4D light field or high-contrast 2D image when illuminated by a uniform backlight. Since arbitrary oblique views may be inconsistent with any single attenuator, iterative tomographic reconstruction minimizes the difference between the emitted and target light fields, subject to physical constraints on attenuation. As multi-layer generalizations of conventional parallax barriers, such displays are shown, both by theory and experiment, to exceed the performance of existing dual-layer architectures. For 3D display, spatial resolution, depth of field, and brightness are increased, compared to parallax barriers. For a plane at a fixed depth, our optimization also allows optimal construction of high dynamic range displays, confirming existing heuristics and providing the first extension to multiple, disjoint layers. We conclude by demonstrating the benefits and limitations of attenuation-based light field displays using an inexpensive fabrication method: separating multiple printed transparencies with acrylic sheets.Dolby Laboratories Inc.Samsung ElectronicsAlfred P. Sloan Foundatio

Tensor displays: compressive light field synthesis using multilayer displays with directional backlighting

We introduce tensor displays: a family of compressive light field displays comprising all architectures employing a stack of time-multiplexed, light-attenuating layers illuminated by uniform or directional backlighting (i.e., any low-resolution light field emitter). We show that the light field emitted by an N-layer, M-frame tensor display can be represented by an Nth-order, rank-M tensor. Using this representation we introduce a unified optimization framework, based on nonnegative tensor factorization (NTF), encompassing all tensor display architectures. This framework is the first to allow joint multilayer, multiframe light field decompositions, significantly reducing artifacts observed with prior multilayer-only and multiframe-only decompositions; it is also the first optimization method for designs combining multiple layers with directional backlighting. We verify the benefits and limitations of tensor displays by constructing a prototype using modified LCD panels and a custom integral imaging backlight. Our efficient, GPU-based NTF implementation enables interactive applications. Through simulations and experiments we show that tensor displays reveal practical architectures with greater depths of field, wider fields of view, and thinner form factors, compared to prior automultiscopic displays.United States. Defense Advanced Research Projects Agency (DARPA SCENICC program)National Science Foundation (U.S.) (NSF Grant IIS-1116452)United States. Defense Advanced Research Projects Agency (DARPA MOSAIC program)United States. Defense Advanced Research Projects Agency (DARPA Young Faculty Award)Alfred P. Sloan Foundation (Fellowship

Building a Socio-technical Perspective of Community Resilience with a Semiotic Approach

Situated in the diversity and adversity of real-life contexts facing crisis situations, this research aims at boosting the resilience process within communities supported by digital and social technology. In this paper, eight community leaders in different parts of the world are invited to express their issues and wishes regarding the support of technology to face social challenges. Methods and artefacts based on the Organisational Semiotics (OS) and the Socially-Aware computing have been applied to analyse and consolidate this data. By providing both a systemic view of the problem and also leading to the identification of requirements, the analysis evidences some benefits of the OS-based approach to consolidate perspectives from different real-life scenarios towards building a socio-technical solution

Diffusion in the Dark: A Diffusion Model for Low-Light Text Recognition

Capturing images is a key part of automation for high-level tasks such as scene text recognition. Low-light conditions pose a challenge for high-level perception stacks, which are often optimized on well-lit, artifact-free images. Reconstruction methods for low-light images can produce well-lit counterparts, but typically at the cost of high-frequency details critical for downstream tasks. We propose Diffusion in the Dark (DiD), a diffusion model for low-light image reconstruction for text recognition. DiD provides qualitatively competitive reconstructions with that of state-of-the-art (SOTA), while preserving high-frequency details even in extremely noisy, dark conditions. We demonstrate that DiD, without any task-specific optimization, can outperform SOTA low-light methods in low-light text recognition on real images, bolstering the potential of diffusion models to solve ill-posed inverse problems.Comment: WACV 2024. Project website: https://ccnguyen.github.io/diffusion-in-the-dark