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At least 865 records · Page 48

Wireless Sensor Networks for Developmental and Flight Instrumentation

Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network and ZigBee Pro 2007 standards are finding increasing use in home automation and smart energy markets providing a framework for interoperable software. The Wireless Connections in Space Project, funded by the NASA Engineering and Safety Center, is developing technology, metrics and requirements for next-generation spacecraft avionics incorporating wireless data transport. The team from Stennis Space Center and Mobitrum Corporation, working under a NASA SBIR grant, has developed techniques for embedding plug-and-play software into ZigBee WSN prototypes implementing the IEEE 1451 Transducer Electronic Datasheet (TEDS) standard. The TEDS provides meta-information regarding sensors such as serial number, calibration curve and operational status. Incorporation of TEDS into wireless sensors leads directly to building application level software that can recognize sensors at run-time, dynamically instantiating sensors as they are added or removed. The Ames Research Center team has been experimenting with this technology building demonstration prototypes for on-board health monitoring. Innovations in technology, software and process can lead to dramatic improvements for managing sensor systems applied to Developmental and Flight Instrumentation (DFI) aboard aerospace vehicles. A brief overview of the plug-and-play ZigBee WSN technology is presented along with specific targets for application within the aerospace DFI market. The software architecture for the sensor nodes incorporating the TEDS information is described along with the functions of the Network Capable Gateway processor which bridges 802.15.4 PAN to the TCP/IP network. Client application software connects to the Gateway and is used to display TEDS information and real-time sensor data values updated every few seconds, incorporating error detection and logging to help measure performance and reliability in relevant target environments. Test results from our prototype WSN running the Mobitrum software system are summarized and the implications to the scalability and reliability for DFI applications are discussed. Our demonstration system, incorporating sensors for life support system and structural health monitoring is described along with test results obtained by running the demonstration prototype in relevant environments such as the Wireless Habitat Testbed at Johnson Space Center in Houston. An operations concept for improved sensor process flow from design to flight test is outlined specific to the areas of Environmental Control and Life Support System performance characterization and structural health monitoring of human-rated spacecraft. This operations concept will be used to highlight the areas where WSN technology, particularly plug-and-play software based on IEEE 1451, can improve the current process, resulting in significant reductions in the technical effort, overall cost and schedule for providing DFI capability for future spacecraft. RELEASED -

Alena, Richard↗

Foraging with MUSHROOMS: A Mixed-integer Linear Programming Scheduler for Multimessenger Target of Opportunity Searches with the Zwicky Transient Facility

Electromagnetic follow-up of gravitational-wave detections is very resource intensive, taking up hours of limited observation time on dozens of telescopes. Creating more efficient schedules for follow-up will lead to a commensurate increase in counterpart location efficiency without using more telescope time. Widely used in operations research and telescope scheduling, mixed-integer linear programming is a strong candidate to produce these higher-efficiency schedules, as it can make use of powerful commercial solvers that find globally optimal solutions to provided problems. We detail a new target-of-opportunity scheduling algorithm designed with Zwicky Transient Facility in mind that uses mixed-integer linear programming. We compare its performance to gwemopt, the tuned heuristic scheduler used by the Zwicky Transient Facility and other facilities during the third LIGO–Virgo gravitational-wave observing run. This new algorithm uses variable-length observing blocks to enforce cadence requirements and to ensure field observability, along with having a secondary optimization step to minimize slew time. We show that by employing a hybrid method utilizing both this scheduler and gwemopt, the previous scheduler used, in concert, we can achieve an average improvement in detection efficiency of 3%–11% over gwemopt alone for a simulated binary neutron star merger data set consistent with LIGO–Virgo's third observing run, highlighting the potential of mixed-integer target of opportunity schedulers for future multimessenger follow-up surveys.

B Parazin↗

Automation of the targeting and reflective alignment concept

The automated alignment system, described herein, employs a reflective, passive (requiring no power) target and includes a PC-based imaging system and one camera mounted on a six degree of freedom robot manipulator. The system detects and corrects for manipulator misalignment in three translational and three rotational directions by employing the Targeting and Reflective Alignment Concept (TRAC), which simplifies alignment by decoupling translational and rotational alignment control. The concept uses information on the camera and the target's relative position based on video feedback from the camera. These relative positions are converted into alignment errors and minimized by motions of the robot. The system is robust to exogenous lighting by virtue of a subtraction algorithm which enables the camera to only see the target. These capabilities are realized with relatively minimal complexity and expense.

Redfield, Robin C.↗

Laser-driven collisionless shock acceleration of ions from near-critical plasmas

Here, this paper overviews experimental and numerical results on acceleration of narrow energy spread ion beams by an electrostatic collisionless shockwave driven by 1 μm (Omega EP) and 10 μm (UCLA Neptune Laboratory) lasers in near critical density CH and He plasmas, respectively. Shock waves in CH targets produced high-energy ~50 MeV protons (ΔE/E of ≤30%) and 314 MeV C 6+ ions (ΔE/E of ≤10%). Observation of acceleration of both protons and carbon ions to similar velocities is consistent with reflection of particles off the moving potential of a shock front. For shocks driven by CO 2 laser in a gas jet, ~30 MeV peak in He ion spectrum was detected. Particle-in-cell simulations indicate that regardless of the target further control over its density profile is needed for optimization of accelerated ion beams in part of energy spread, yield and maximum kinetic energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Review of Intrusion Detection Methods and Tools for Distributed Energy Resources

Recent trends in the growth of distributed energy resources (DER) in the electric grid and newfound malware frameworks that target internet of things (IoT) devices is driving an urgent need for more reliable and effective methods for intrusion detection and prevention. Cybersecurity intrusion detection systems (IDSs) are responsible for detecting threats by monitoring and analyzing network data, which can originate either from networking equipment or end-devices. Creating intrusion detection systems for PV/DER networks is a challenging undertaking because of the diversity of the attack types and intermittency and variability in the data. Distinguishing malicious events from other sources of anomalies or system faults is particularly difficult. New approaches are needed that not only sense anomalies in the power system but also determine causational factors for the detected events. In this report, a range of IDS approaches were summarized along with their pros and cons. Using the review of IDS approaches and subsequent gap analysis for application to DER systems, a preliminary hybrid IDS approach to protect PV/DER communications is formed in the conclusion of this report to inform ongoing and future research regarding the cybersecurity and resilience enhancement of DER systems.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Spectrum characteristics of Denver and Philadelphia ground clutter and the problem of distinguishing wind shear targets from moving clutter

Spectral analysis of 1991 wind shear flight data has provided information about the power spectral density, spectral width, and velocity of ground clutter detected by the wind shear radar at several major airports. Ground clutter must be recognized and separated from weather targets before wind shear can be computed. Information will be presented characterizing and comparing ground clutter and weather target spectra. The information includes (1) spectral widths of stationary ground clutter seen at various scan and tilt angles, (2) power spectral density and velocity of moving ground clutter relative to the stationary ground clutter, and (3) spectral widths and velocities of weather targets. A summary of numerical results in the form of histograms and example numerical results in the form of spectral plots are presented.

Mackenzie, Anne I.↗

Rapid direct methods for enumeration of specific, active bacteria in water and biofilms

Conventional methods for detecting indicator and pathogenic bacteria in water may underestimate the actual population due to sublethal environmental injury, inability of the target bacteria to take up nutrients and other physiological factors which reduce bacterial culturability. Rapid and direct methods are needed to more accurately detect and enumerate active bacteria. Such a methodological advance would provide greater sensitivity in assessing the microbiological safety of water and food. The principle goal of this presentation is to describe novel approaches we have formulated for the rapid and simultaneous detection of bacteria plus the determination of their physiological activity in water and other environmental samples. The present version of our method involves the concentration of organisms by membrane filtration or immunomagnetic separation and combines an intracellular fluorochrome (CTC) for assessment of respiratory activity plus fluorescent-labelled antibody detection of specific bacteria. This approach has also been successfully used to demonstrate spatial and temporal heterogeneities of physiological activities in biofilms when coupled with cryosectioning. Candidate physiological stains include those capable of determining respiratory activity, membrane potential, membrane integrity, growth rate and cellular enzymatic activities. Results obtained thus far indicate that immunomagnetic separation can provide a high degree of sensitivity in the recovery of seeded target bacteria (Escherichia coli O157:H7) in water and hamburger. The captured and stained target bacteria are then enumerated by either conventional fluorescence microscopy or ChemScan(R), a new instrument that is very sensitive and rapid. The ChemScan(R) laser scanning instrument (Chemunex, Paris, France) provides the detection of individual fluorescently labelled bacterial cells using three emission channels in less than 5 min. A high degree of correlation has been demonstrated between results obtained with the ChemScan and traditional plate counts of mixed natural bacterial populations in water. The continuing evolution of these methods will be valuable in the rapid and accurate analysis of environmental samples.

Review, Tutorial↗

Space charge effects in the SπRIT time projection chamber

Time projection chambers (TPCs) are widely used in nuclear and particle physics. They are particularly useful when measuring reaction products from heavy ion collisions. Most nuclear experiments at low energy are performed in a fixed target configuration, in which the unreacted beam will pass through the detection volume. As the beam intensity increases, the buildup of positive ions created from the ionization of the detector gas by the beam creates the main source of space charge, distorting the nominal electric field of the TPC. This has a profound effect on the accuracy of the measured momenta of the emitted particles. In this paper we will discuss the magnitude of the effects and construct an observable appropriate for fixed target experiments to study the effects. Finally, we will present an algorithm for correcting the space charge and discuss some of the implications it has on the momentum determination.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Advanced Speckle Sensing for Internal Coronagraphs

A 4-8m telescope carrying a coronagraph instrument is a leading candidate for an anticipated flagship mission to detect and characterize Earth-size exoplanets in the 2020s. Many candidate coronagraph instruments have been proposed, and one has met many of the principal requirements for that mission. But the telescope and instrument will need exquisite stability and precise control of the incoming wavefront to enable detection of faint companions (10(exp -10) of the star) at an angular separation of 2-4 Airy radii. In particular, wavefront errors cause speckles in the image, and variations in those speckles can confound the exoplanet detection. This challenge is compounded by the background light from zodiacal dust around our Sun and the target star, which limits the speed with which we can estimate and correct the speckles. We are working on developing coherent speckle detection techniques that will allow rapid calibration of speckles on the science detector, allowing subtraction in post-processing or correction with deformable mirrors. The expected speed improvement allows a much quicker timeline for measurement & calibration, which reduces the required telescope stability requirement and eases both the flight system design and the challenge of ground testing. We will describe the experiments and summarize progress to date.

Terrestrial Planet Finder↗

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗

A multisensor system for airborne surveillance of oil pollution

The U.S. Coast Guard is developing a prototype airborne oil surveillance system for use in its Marine Environmental Protection Program. The prototype system utilizes an X-band side-looking radar, a 37-GHz imaging microwave radiometer, a multichannel line scanner, and a multispectral low light level system. The system is geared to detecting and mapping oil spills and potential pollution violators anywhere within a 25 nmi range of the aircraft flight track under all but extreme weather conditions. The system provides for false target discrimination and maximum identification of spilled materials. The system also provides an automated detection alarm, as well as a color display to achieve maximum coupling between the sensor data and the equipment operator.

Edgerton, A. T.↗

Inferring transmission heterogeneity using virus genealogies: estimation and targeted prevention

Spread of HIV typically involves uneven transmission patterns where some individuals spread to a large number of individuals while others to only a few or none. Such transmission heterogeneity can impact how fast and how much an epidemic spreads. Further, more efficient interventions may be achieved by taking such transmission heterogeneity into account. To address these issues, we developed two phylogenetic methods based on virus sequence data: 1) to generally detect if significant transmission heterogeneity is present, and 2) to pinpoint where in a phylogeny high-level spread is occurring. We derive inference procedures to estimate model parameters, including the amount of transmission heterogeneity, in a sampled epidemic. We show that it is possible to detect transmission heterogeneity under a wide range of simulated situations, including incomplete sampling, varying levels of heterogeneity, and including within-host genetic diversity. When evaluating real HIV-1 data from different epidemic scenarios, we found a lower level of transmission heterogeneity in slowly spreading situations and a higher level of heterogeneity in data that included a rapid outbreak, while R0 and Sackin’s index (overall tree shape statistic) were similar in the two scenarios, suggesting that our new method is able to detect transmission heterogeneity in real data. We then show by simulations that targeted prevention, where we pinpoint high-level spread using a coalescence measurement, is efficient when sequence data are collected in an ongoing surveillance system. Such phylogeny-guided prevention is efficient under both single-step contact tracing as well as iterative contact tracing as compared to random intervention.

59 BASIC BIOLOGICAL SCIENCES↗

Kepler Mission Development Challenges and Early Results

Kepler is NASA s first mission capable of detecting Earth-size planets orbiting in the habitable zone of stars other than the Sun. Kepler comprises a space telescope designed to continuously monitor the brightnesses of more than 100,000 target stars, and a ground segment to analyze the measured stellar light curves and detect the signatures of orbiting planets. In order to detect Earth-size planets orbiting Sun-like stars Kepler was designed to provide unprecedented photometric sensitivity and stability. This paper addresses some of the technical challenges encountered during the development of the Kepler mission and the measures taken to overcome them. Early scientific results are summarized.

exo-planets↗

Kepler Mission Development Challenges and Early Results

Kepler is NASA`s first mission capable of detecting Earth-size planets orbiting in the habitable zone of stars other than the sun. Kepler comprises a space telescope designed to continuously monitor the brightnesses of more than 100,000 target stars, and a ground segment to analyze the measured stellar light curves and detect the signatures of orbiting planets. In order to detect Earth-size planets orbiting Sun-like stars Kepler was designed to provide unprecedented photometric sensitivity and stability. This paper addresses some of the technical challenges encountered during the development of the Kepler mission and the measures taken to overcome them. Early scientific results are summarized.

habitable zones↗

Motion-sensitive optical correlator using a VanderLugt correlator

A new type of optical correlator is presented. The correlator performs motion detection or background clutter suppression and correlation simultaneously in a single photorefractive crystal. Additionally, the device is useful for moving target identification and tracking and for stationary clutter rejection. The correlation is of the VanderLugt type, and the motion detection or background clutter suppression is based on the erasing property of photorefractive crystals.

Liu, Tsuen-Hsi↗

Analysis of Technology for Compact Coherent Lidar

In view of the recent advances in the area of solid state and semiconductor lasers has created new possibilities for the development of compact and reliable coherent lidars for a wide range of applications. These applications include: Automated Rendezvous and Capture, wind shear and clear air turbulence detection, aircraft wake vortex detection, and automobile collision avoidance. The work performed by the UAH personnel under this Delivery Order, concentrated on design and analyses of a compact coherent lidar system capable of measuring range and velocity of hard targets, and providing air mass velocity data. The following is the scope of this work. a. Investigate various laser sources and optical signal detection configurations in support of a compact and lightweight coherent laser radar to be developed for precision range and velocity measurements of hard and fuzzy targets. Through interaction with MSFC engineers, the most suitable laser source and signal detection technique that can provide a reliable compact and lightweight laser radar design will be selected. b. Analyze and specify the coherent laser radar system configuration and assist with its optical and electronic design efforts. Develop a system design including its optical layout design. Specify all optical components and provide the general requirements of the electronic subsystems including laser beam modulator and demodulator drivers, detector electronic interface, and the signal processor. c. Perform a thorough performance analysis to predict the system measurement range and accuracy. This analysis will utilize various coherent laser radar sensitivity formulations and different target models.

Amzajerdian, Farzin↗

Use of Longitudinal Serum Analysis and Machine Learning to Develop a Classifier for Cancer Early Detection

Early detection of solid tumors through a simple screening process, such as the proteomic analysis of biofluids, has the potential to significantly alter the management and outcomes of cancers. The application of advanced targeted proteomics measurements and data analysis strategies to uniformly collected serum or plasma samples would enable longitudinal studies of cancer risk, progression, and response to therapy that have the potential to significantly reduce cancer burden in general. In this article, we describe a generalizable workflow combining robust, multiplexed targeted proteomics measurements applied to longitudinal samples from the Department of Defense Serum Repository with a Random Forest machine learning method for developing and initially evaluating the performance of candidate biomarker panels for early detection of cancers. The effectiveness of this approach was demonstrated in a cohort of 175 head and neck squamous cell carcinoma patients. The outlined protocols include methods for sample preparation, instrument analysis, and data analysis and interpretation using this workflow.

Longitudinal analysis, machine learning, cancer, e↗

Hubble Asteroid Hunter

Context: The Hubble Space Telescope (HST) archives constitute a rich dataset of high-resolution images to mine for strong gravitational lenses. While many HST programmes specifically target strong lenses, they can also be present by coincidence in other HST observations. Aims: Our aim is to identify non-targeted strong gravitational lenses, without any prior selection on the lens properties, in almost two decades of images from the ESA HST archive (eHST). Methods: We used crowdsourcing on the Hubble Asteroid Hunter (HAH) citizen science project to identify strong lenses, along with asteroid trails, in publicly available large field-of-view HST images. We visually inspected 2354 objects tagged by citizen scientists as strong lenses to clean the sample and identify the genuine lenses. Results: We report the detection of 252 strong gravitational lens candidates, which were not the primary targets of the HST observations. A total of 198 of them are new, not previously reported by other studies, consisting of 45 A grades, 74 B grades and 79 C grades. The majority are galaxy-galaxy configurations. The newly detected lenses are, on average, 1.3 magnitudes fainter than previous HST searches. This sample of strong lenses with high-resolution HST imaging is ideal to follow up with spectroscopy for lens modelling and scientific analyses. Conclusions: This paper presents the unbiased search of lenses that enabled us to find a wide variety of lens configurations, including exotic lenses. We demonstrate the power of crowdsourcing in visually identifying strong lenses and the benefits of exploring large archival datasets. This study shows the potential of using crowdsourcing in combination with artificial intelligence for the detection and validation of strong lenses in future large-scale surveys such as ESA’s Euclid mission or in James Webb Space Telescope (JWST) archival images.

79 ASTRONOMY AND ASTROPHYSICS↗