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At least 631 records · Page 35

Information Content of Aerosol Retrievals in the Sunglint Region

We exploit quantitative metrics to investigate the information content in retrievals of atmospheric aerosol parameters (with a focus on single-scattering albedo), contained in multi-angle and multi-spectral measurements with sufficient dynamical range in the sunglint region. The simulations are performed for two classes of maritime aerosols with optical and microphysical properties compiled from measurements of the Aerosol Robotic Network. The information content is assessed using the inverse formalism and is compared to that deriving from observations not affected by sunglint. We find that there indeed is additional information in measurements containing sunglint, not just for single-scattering albedo, but also for aerosol optical thickness and the complex refractive index of the fine aerosol size mode, although the amount of additional information varies with aerosol type.

aerosols↗

The Dolinar Receiver in an Information Theoretic Framework

Optical communication at the quantum limit requires that measurements on the optical field be maximally informative, but devising physical measurements that accomplish this objective has proven challenging. The Dolinar receiver exemplifies a rare instance of success in distinguishing between two coherent states: an adaptive local oscillator is mixed with the signal prior to photodetection, which yields an error probability that meets the Helstrom lower bound with equality. Here we apply the same local-oscillator-based architecture with aninformation-theoretic optimization criterion. We begin with analysis of this receiver in a general framework for an arbitrary coherent-state modulation alphabet, and then we concentrate on two relevant examples. First, we study a binary antipodal alphabet and show that the Dolinar receiver's feedback function not only minimizes the probability of error, but also maximizes the mutual information. Next, we study ternary modulation consistingof antipodal coherent states and the vacuum state. We derive an analytic expression for a near-optimal local oscillator feedback function, and, via simulation, we determine its photon information efficiency (PIE). We provide the PIE versus dimensional information efficiency (DIE) trade-off curve and show that this modulation and the our receiver combination performs universally better than (generalized) on-off keying plus photoncounting, although, the advantage asymptotically vanishes as the bits-per-photon diverges towards infinity.

optical communications↗

ATM-X Digital Information Platform

High level introduction of Digital Information Platform (DIP) objectives as a sub-project under Airspace Traffic Management - Exploration (ATM-X). Important information is emerging in digital form and additional effort is required to utilize this information. DIP will provide the capability to integrate key flight information from multiple sources. DIP is currently in planning phase will take a community-involved, collaborative approach to define and develop the framework. DIP is seeking community and stakeholder input to operational needs, metrics of interest and demonstration contribution

Digital Information Platform↗

Digital Information Platform (DIP) Overview

On March 24, 2021, NASA’s Digital Information Platform (DIP) released a Request for Information (RFI) to the aviation community. The RFI was intended to request two things: 1) DIP concept input such as current challenges and needs for data and services and 2) Interest in participating in collaborative demonstrations. On July 29, 2021, DIP team will meet with Airlines for America (A4A) to share a summary of information received from the RFI responses. The objective of the meeting is to follow up with respondents with takeaways the DIP team identified that will inform the concept and demonstration plans. The forum will give participants an opportunity to add on and provide feedback to the summary. The meeting will also describe the roadmap for the Collaborative Demonstrations and next steps for partner engagement.

Digital Information Platform (DIP) RFI summary↗

Advanced Information Systems Technology (AIST) Overview & Current and Recent Projects

"NASA's Advanced Information Systems Technology (AIST) Program identifies, develops, and supports adoption of software and information systems, as well as novel computer science technologies expected to be needed by the Earth Science Division in the 5-10-year timeframe. Overall, the AIST Program is focusing on advanced technologies and innovative concepts with three main objectives: O1. Enable new observation measurements and new observing systems design and operations through intelligent, timely, dynamic, and coordinated distributed sensing; O2. Enable agile science analyses that fully utilize the large amount of diverse observations using advanced analytic tools, visualizations, and computing environments, and that interact seamlessly with relevant observing systems; O3. Enable the development of integrated Earth Science frameworks that mirror the Earth with state-of-the-art models (Earth system models and others), timely and relevant observations, and analytic tools. This thrust will provide technology for enabling near- and long-term science and policy decisions (""""science decisions"""" including planning for the acquisition of new measurements; the development of new models or science analysis; the integration of Earth observations in novel ways; applications to inform choices, support decisions, and guide actions for societal benefit; etc.). AIST objectives aim at optimizing Earth Science mission return – NOS from an observation point of view and ACF/ESDT from an information analysis and utilization point of view. The assets and data accessed and utilized in these systems may come from NASA and non-NASA sources. "

Earth Science Remote Sensing; Information Systems↗

U.S. Patent Pending, Information Security Analysis Using Game Theory and Simulation, U.S. Patent Application No.: 14/097,840

Vulnerability in security of an information system is quantitatively predicted. The information system may receive malicious actions against its security and may receive corrective actions for restoring the security. A game oriented agent based model is constructed in a simulator application. The game ABM model represents security activity in the information system. The game ABM model has two opposing participants including an attacker and a defender, probabilistic game rules and allowable game states. A specified number of simulations are run and a probabilistic number of the plurality of allowable game states are reached in each simulation run. The probability of reaching a specified game state is unknown prior to running each simulation. Data generated during the game states is collected to determine a probability of one or more aspects of security in the information system.

Availablity↗

DOE Geothermal Data Repository - Tethering Data to Information: Preprint

Data are not inherently information. Without context, data are just numbers, figures, names, or points on a line. By assigning context to data, we can validate ideas, form opinions, and generate knowledge. This is an important distinction to information scientists, as we recognize that the context in which we keep our data plays a big part in generating its value. The mechanisms used to assign this context often include their own data, supplemental to the data being described and defining semantic relationships, commonly referred to as metadata. This paper provides the status of the DOE Geothermal Data Repository (DOE GDR), including recent efforts to tether data submissions to information, discusses the important distinction between data and information, outlines a path to generate useful knowledge from raw data, and details the steps taken in order to become a node on the National Geothermal Data System (NGDS).

15 GEOTHERMAL ENERGY↗

Explicitly Accounting for Multiple Spatial Scales in Data Informing Kd Distribution Development - 18414

This work provides an example of incorporating information about spatial scale into input parameter distribution development for probabilistic performance assessment (PA) models and highlights the importance of having an interdisciplinary team working together in the distribution development process. The novel approach is demonstrated for contaminant partitioning coefficients for water/rock (Kds), providing a specific context for discussing the approach and challenges, but the strategy is general and applies to many other PA model inputs. In this example, a PA model of a radioactive waste disposal site is assumed to have large cells representing spatial scales of up to thousands of square meters in area and several to tens of meters in depth. Spatial variability in Kds is expected to occur at scales much smaller than the units in the model domain over which values are applied, and therefore values are intended to represent possible averages over the modeled volume (i.e., spatial scale represented by a PA model cell). Information about possible Kd values for each material category comes from a variety of literature sources, and the reported results used to inform the distribution are available at a wide range of scales (e.g., individual batch experiment results from small-scale samples, averages based on samples collected over site-scales, averages based on samples from large regions, etc.). Effectively addressing the mismatch in spatial scale between available information and the PA Model is a challenge within PA distribution development and it takes effort from database managers, subject matter experts, modelers, and statisticians. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Port Hope Area Initiative: Information Management for A Very Large Radiation Survey - 19567

The Port Hope Area Initiative (PHAI) represents the Government of Canada's commitment to the cleanup and safe, local, long-term management of historic low-level radioactive waste (LLRW) in two Southern Ontario municipalities - Port Hope. The PHAI is based on community-recommended solutions for the cleanup and safe long-term management of approximately 1.7 million cubic meters of LLRW. It is currently one of Canada's largest environmental remediation projects at a cost of over one billion dollars. The PHAI is being implemented by Canadian Nuclear Laboratories (CNL) on behalf of Atomic Energy of Canada Limited, a federal Crown corporation. The waste is the result of radium and uranium processing in Port Hope by the former federal crown corporation Eldorado Nuclear Limited between 1933 and 1988. The waste has been distributed in the Municipality of Port Hope through placement of contaminated materials (e.g. fill), reuse of contaminated objects (e.g. tailings use in concrete, steel posts, structural wood) and air-borne deposition. Signature contaminants of potential concern (COPCs) are Ra-226, Th-230, uranium and arsenic; however, there are an additional 17 COPCs that also need to be considered. A very large amount of information has been collected during the survey and effectively managing and analyzing this information is critical to the success for the property owners, CNL's implementation of the PHAI, and Arcadis. Data collected during the survey includes information pertaining to long-term interior radon gas measurements, interior gamma radiation surveys, contaminated objects and surfaces, exterior gamma radiation and subsurface investigations. exterior gamma radiation surveys. The information management (IM) is structured with SharePoint as a focal point supported by an EQuIS database, mobile data collection and GIS support. The IM process for this project is being advanced using recent software developments to assist with internal activities (e.g. QA) and interactions with CNL including notifications and scheduling and status of property completion. Different applications have been developed to help automate, visualize, actively track, and QA different processes using recent software developments by Microsoft. We have used SharePoint to organize and track our data. Power BI has been used to actively track and visualize our data from Interior gamma surveying to exterior drilling. The creation of dynamic/advanced visualizations in Power BI gathers data daily from our multiple sources and analyzes it for anomalous data and trends. Microsoft Flow syncs with Power BI and has been implemented to automate many processes including the QA of surveys and soil results for identification of LLRW. To tie everything together, our GIS and EQuIS systems are our primary data compilation source that makes our advanced analytics/visualization and automation/tracking our data possible. Specific examples will be discussed, as will challenges encountered during the continuing development of the IM system. The incorporation of software advancements to the existing IM system for Port Hope characterization has improved the quality of the surveys, the tracking of completion, meeting schedule requirements and providing the required data for tracking, report preparation and supporting remediation of contamination on the properties. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

GeoBridge: Connecting Communities to Geothermal Information and Opportunities: Preprint

The geothermal community is well established with long-standing events, organizations, and tools that are known across the geothermal community. But many of these tools and resources are located behind pay walls, require memberships, or are otherwise difficult to find, especially for people looking to join the geothermal community. These barriers to access can prevent outsiders from discovering valuable geothermal resources, limiting the geothermal community's potential for collaboration with other communities, such as clean energy entrepreneurs looking to expand into geothermal energy. The Department of Energy's (DOE) GeoBridge serves to bring these communities together by acting as a single, publicly accessible, searchable portal that facilitates easy access to available geothermal knowledge and information. It works to expand and diversify the pool of geothermal stakeholders by providing in-roads to geothermal information and community resources. It helps build a stronger geothermal community; one inclusive of individuals and groups from a variety of different backgrounds, including potential investors and start-up companies looking to accelerate innovation in geothermal technologies. By linking communities to geothermal information, analysis and expertise, GeoBridge serves as a launch point, directing interested parties to existing data and tools, events, educational resources, STEM programs, permitting and regulatory information, and other resources that can be used to evaluate, promote, and discover geothermal opportunities.

access↗

GeoBridge: Connecting Communities to Geothermal Information and Opportunities

The geothermal community is well established with long-standing events, organizations, and tools that are known across the geothermal community. But many of these tools and resources are located behind pay walls, require memberships, or are otherwise difficult to find, especially for people looking to join the geothermal community. These barriers to access can prevent outsiders from discovering valuable geothermal resources, limiting the geothermal community's potential for collaboration with other communities, such as clean energy entrepreneurs looking to expand into geothermal energy. The Department of Energy's (DOE) GeoBridge serves to bring these communities together by acting as a single, publicly accessible, searchable portal that facilitates easy access to available geothermal knowledge and information. It works to expand and diversify the pool of geothermal stakeholders by providing in-roads to geothermal information and community resources. It helps build a stronger geothermal community; one inclusive of individuals and groups from a variety of different backgrounds, including potential investors and start-up companies looking to accelerate innovation in geothermal technologies. By linking communities to geothermal information, analysis and expertise, GeoBridge serves as a launch point, directing interested parties to existing data and tools, events, educational resources, STEM programs, permitting and regulatory information, and other resources that can be used to evaluate, promote, and discover geothermal opportunities.

access↗

Actions Needed to Ensure Scientific and Technical Information is Adequately Reviewed at Goddard Space Flight Center, Johnson Space Center, Langley Research Center, and Marshall Space Flight Center

This audit was initiated in response to a hotline complaint regarding the review, approval, and release of scientific and technical information (STI) at Johnson Space Center. The complainant alleged that Johnson personnel conducting export control reviews of STI were not fully qualified to conduct those reviews and that the reviews often did not occur until after the STI had been publicly released. NASA guidance requires that STI, defined as the results of basic and applied scientific, technical, and related engineering research and development, undergo certain reviews prior to being released outside of NASA or to audiences that include foreign nationals. The process includes technical, national security, export control, copyright, and trade secret (e.g., proprietary data) reviews. The review process was designed to preclude the inappropriate dissemination of sensitive information while ensuring that NASA complies with a requirement of the National Aeronautics and Space Act of 1958 (the Space Act)1 to provide for the widest practicable and appropriate dissemination of information resulting from NASA research activities. We focused our audit on evaluating the STI review process: specifically, determining whether the roles and responsibilities for the review, approval, and release of STI were adequately defined and documented in NASA and Center-level guidance and whether that guidance was effectively implemented at Goddard Space Flight Center, Johnson Space Center, Langley Research Center, and Marshall Space Flight Center. Johnson was included in the review because it was the source of the initial complaint, and Goddard, Langley, and Marshall were included because those Centers consistently produce significant amounts of STI.

Information management↗

Botnet behaviour analysis: How would a data analytics-based system with minimum a priori information perform?

Botnets, as one of the most aggressive threats, has used different techniques, topologies, and communication protocols in different stages of their lifecycle since 2003. Hence, identifying botnets has become very challenging specifically given that they can upgrade their methodology at any time. Various detection approaches have been proposed by the cyber-security researchers, focusing on different aspects of these threats. In this work, 5 different botnet detection approaches are investigated. These systems are selected based on the technique used and type of data used where 2 are public rule–based systems (BotHunter and Snort) and the other 3 use machine learning algorithm with different feature extraction methods (packet payload based and traffic flow based). On the other hand, 4 of these systems are based on a priori knowledge while one is using minimum a priori information. The objective here is to evaluate the effectiveness of these approaches under different scenarios (eg, multi-botnet and single-botnet classifications) as well as exploring how a system with minimum a priori information would perform. The goal is to investigate if a system with minimum a priori information could result in a competitive performance compared to systems using a priori knowledge. The evaluation is shown on 24 publicly available botnet data sets. Results indicate that a machine learning–based system with minimum a priori information not only achieves a very high performance but also generalizes much better than the other systems evaluated on a wide range of botnet structures (from centralized to decentralized botnets).

97 MATHEMATICS AND COMPUTING↗

Information or resolution: Which is required from an SEM to study bulk inorganic materials?: Evaluate SEMs’ practical performance

Significant technological advances in scanning electron microscopy (SEM) have been achieved over the past years. Different SEMs can have significant differences in functionality and performance. This work presents the perspectives on selecting an SEM for research on bulk inorganic materials. Understanding materials demands quantitative composition and orientation information, and informative and interpretable images that reveal subtle differences in chemistry, orientation/structure, topography, and electronic structure. The capability to yield informative and interpretable images with high signal-to-noise ratios and spatial resolutions is an overall result of the SEM system as a whole, from the electron optical column to the detection system. The electron optical column determines probe performance. The roles of the detection system are to capture, filter or discriminate, and convert signal electrons to imaging information. The capability to control practical operating parameters including electron probe size and current, acceleration voltage or landing voltage, working distance, detector selection, and signal filtration is inherently determined by the SEM itself. As a platform for various accessories, e.g. an energydispersive spectrometer and an electron backscatter diffraction detector, the properties of the electron optical column, specimen chamber, and stage greatly affect the performance of accessories. Ease-of-use and ease-of-maintenance are of practical importance. It is practically important to select appropriate test specimens, design suitable imaging conditions, and analyze the specimen chamber geometry and dimensions to assess the overall functionality and performance of an SEM. Finally, for an SEM that is controlled/operated with a computer, the stable software and user-friendly interface significantly affect the usability of the SEM.

36 MATERIALS SCIENCE↗

Is infrared-collinear safe information all you need for jet classification?

Machine learning-based jet classifiers are able to achieve impressive tagging performance in a variety of applications in high-energy and nuclear physics. However, it remains unclear in many cases which aspects of jets give rise to this discriminating power, and whether jet observables that are tractable in perturbative QCD such as those obeying infrared-collinear (IRC) safety serve as sufficient inputs. In this article, we introduce a new classifier, Jet Flow Networks (JFNs), in an effort to address the question of whether IRC unsafe information provides additional discriminating power in jet classification. JFNs are permutation-invariant neural networks (deep sets) that take as input the kinematic information of reconstructed subjets. The subjet radius and a cut on the subjet’s transverse momenta serve as tunable hyperparameters enabling a controllable sensitivity to soft emissions and nonperturbative effects. We demonstrate the performance of JFNs for quark vs. gluon and Z vs. QCD jet tagging. For small subjet radii and transverse momentum cuts, the performance of JFNs is equivalent to the IRC-unsafe Particle Flow Networks (PFNs), demonstrating that infrared-collinear unsafe information is not necessary to achieve strong discrimination for both cases. As the subjet radius is increased, the performance of the JFNs remains essentially unchanged until physical thresholds that we identify are crossed. For relatively large subjet radii, we show that the JFNs may offer an increased model independence with a modest tradeoff in performance compared to classifiers that use the full particle information of the jet. These results shed new light on how machines learn patterns in high-energy physics data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Controllable quantum information network with a superconducting system

We propose a controllable and scalable architecture for quantum information processing using a superconducting system network, which is composed of current-biased Josephson junctions (CBJJs) as tunable couplers between the two superconducting transmission line resonators (TLRs), each coupling to multiple superconducting qubits (SQs). We explicitly demonstrate that the entangled state, the phase gate, and the information transfer between any two selected SQs can be implemented, respectively. Lastly, numerical simulation shows that our scheme is robust against the decoherence of the system. -- Highlights: •An architecture for quantum information processing is proposed. •The quantum information transfer between any two selected SQs is implemented. •This proposal is robust against the decoherence of the system. •This architecture can be fabricated on a chip down to the micrometer scale.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Universal upper bounds for Gaussian information capacity

The most natural way to describe an information-carrying system containing a specific noise is an additive white Gaussian-noise (AWGN) channel. In bosonic quantum systems (especially the Gaussian case), although the classical information capacity for a phase-insensitive and thermal-noise channel is additive based on a proof of the minimum output entropy conjecture, several open questions remain. By generalizing the Gaussian noise model from thermal noise to general Gaussian noise, we rigorously revisit and calculate these strong upper bounds on the information capacity for single-mode with general Gaussian-noise channels. In this study, we use the quantum entropy power inequality (QEPI) approach. This framework gives a new formula for finding upper bounds on the information capacity of bosonic Gaussian channels.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis

We report high quality energy systems information is a crucial input to energy systems research, modeling, and decision-making. Unfortunately, actionable information about energy systems is often of limited availability, incomplete, or only accessible for a substantial fee or through a non-disclosure agreement. Recently, remotely sensed data (e.g., satellite imagery, aerial photography) have emerged as a potentially rich source of energy systems information. However, the use of these data is frequently challenged by its sheer volume and complexity, precluding manual analysis. Recent breakthroughs in machine learning have enabled automated and rapid extraction of useful information from remotely sensed data, facilitating large-scale acquisition of critical energy system variables. Here we present a systematic review of the literature on this emerging topic, providing an in-depth survey and review of papers published within the past two decades. We first taxonomize the existing literature into ten major areas, spanning the energy value chain. Within each research area, we distill and critically discuss major features that are relevant to energy researchers, including, for example, key challenges regarding the accessibility and reliability of the methods. We then synthesize our findings to identify limitations and trends in the literature as a whole, and discuss opportunities for innovation. These include the opportunity to extend the methods beyond electricity to broader energy systems and wider geographic areas; and the ability to expand the use of these methods in research and decision making as satellite data become cheaper and easier to access. We also find that there are persistent challenges: limited standardization and rigor of performance assessments; limited sharing of code, which would improve replicability; and a limited consideration of the ethics and privacy of data.

97 MATHEMATICS AND COMPUTING↗