Publication

Multifactor Biometrics Data Fusion for Regional Recognition

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Biometrics is the automated methodology to uniquely identify humans using their physiological or behavioral attributes. Based on our deep biometrics experience with the Navy and our data science expertise, we are exploring the fusion of multifactor biometrics data to reduce false positives and workflow inefficiencies, while increasing confidence in verification processes.    We are designing […]

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Airborne Bathymetric Analysis of Littoral Infiltration Points

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KeyLogic put together a best-of-the-best team to prototype a man-portable, unmanned airborne vehicle (UAV) to map and assess coastal region for infiltration threats.  KeyLogic designed the integration plan that combined proven platforms, sensors, processors, and applications proven for other applications with novel artificial intelligence models to enable unprecedented bathymetric analysis at the edge. By putting the

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Convolutional Neural Networks on Field Programmable Gate Arrays

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KeyLogic data scientists and embedded system software engineers are rewriting convolutional neural network (CNN) algorithms to operate smoothly and efficiently on field programmable-gate arrays (FPGAs). More than standard CPUs and even graphical processing units (GPUs), FPGAs have the capacity to massively accelerate deep learning algorithms on very low power, restricted weight, edge devices for computer

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Published paper in Journal of Natural Gas Science and Engineering on evaluation of production drivers in the Marcellus Shale using machine learning approaches

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Artificial intelligence and machine learning (ML) are being applied to many oil and gas (O&G) applications and seen as novel techniques that may facilitate efficiency gains in exploration and production operations. Significant improvements in that regard are likely to occur when ML can be applied to evaluate O&G challenges with inherent synergies that may have

Published paper in Journal of Natural Gas Science and Engineering on evaluation of production drivers in the Marcellus Shale using machine learning approaches Read More »

News release by DOE’s Loan Program office featuring report compiled by KeyLogic and partners on evaluating the potential environmental impacts and compliance best practices for carbon capture and storage

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The Loan Programs Office (LPO) takes its role in protecting taxpayer interests very seriously, including evaluating the potential impacts of projects in accordance with the National Environmental Policy Act (NEPA).  Given the growth of interest in the carbon capture utilization & sequestration (CCUS) sector, LPO’s Environmental Compliance Division prepared a report as a reference for

News release by DOE’s Loan Program office featuring report compiled by KeyLogic and partners on evaluating the potential environmental impacts and compliance best practices for carbon capture and storage Read More »

“Featured paper” published in Energies Special Issue on Alternative Energy Policy

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This paper evaluates how changes in economic market and policy conditions, including the establishment of a per-unit tax on unabated emissions of carbon dioxide (CO2) set equal to estimates of the social cost of carbon (SCC), influence the economics of carbon capture and storage (CCS) for two hypothetical power generation facilities located in the United

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Using Common Boundaries to Assess Methane Emissions: A Life Cycle Evaluation of Natural Gas and Coal Power Systems

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There is consensus on the importance of upstream methane (CH4) emissions to the life cycle greenhouse gas (GHG) footprint of natural gas systems, but inconsistencies among recent studies explain why some researchers calculate a CH4 emission rate of less than 1% whereas others calculate a CH4 emission rate as high as 10%. These inconsistencies arise from differences

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