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Evidence for maintenance or breakdown of natural or acquired resistance of guinea pigs in simulated spacecraft environment
An intense dayside proton aurora was observed by Imager for Magnetopause-to- Aurora Global Exploration Far Ultra-Violet imager (IMAGE FUV) for an extensive period of northward interplanetary magnetic field (IMF) on 17 and 18 September 2000. This aurora partially coincided with the auroral oval and intruded farther poleward into the polar cap, and it showed longitudinal motions in response to IMF By variation. Intense magnetosheath-like electron and ion precipitations have been simultaneously detected by Defense Meteorological Satellite Program (DMSP) above the poleward portion of the high-latitude dayside aurora. They resemble the typical plasmas observed in the low-altitude cusp. However, less intense electrons and more energetic ions were detected over the equatonvard part of the aurora. These plasmas are closer to the low-latitude boundary layer (LLBL) plasmas. Under strongly northward IMF, global ionospheric convection derived from Super Dual Auroral Radar Network (SuperDARN) radar measurements showed a four-cell pattern with sunward convection in the middle of the dayside polar cap and the dayside aurora corresponded to two different convection cells. This result further supports two source regions for the aurora. The cusp proton aurora is on open magnetic field lines convecting sunward whereas the LLBL proton aurora is on closed field lines convecting antisunward. These IMAGE, DMSP, and SuperDARN observations reveal the structure and dynamics of the aurora and provide strong evidence for magnetic merging occurring at the high-latitude magnetopause poleward from the cusp. This merging process was very likely quasi-stationary.
A modular architecture has been conceived for the design of radiation-monitoring instruments used aboard spacecraft and in planetary-exploration settings. This architecture reflects lessons learned from experience with prior radiation-monitoring instruments. A prototype instrument that embodies the architecture has been developed as part of the Mars Advanced Radiation Acquisition (MARA) project. The architecture is also applicable on Earth for radiation-monitoring instruments in research of energetic electrically charged particles and instruments monitoring radiation for purposes of safety, military defense, and detection of hidden nuclear devices and materials.
The premise is more than art imitates life, or technology imitates nature it is a nascent step to see how we might be unwittingly inspired and influenced. An example that might immediately come to mind is a starling murmuration (a phenomenon called scale-free correlation) and Intels recent Coachella music festival drone performance. Superconductivity is a macroscopic manifestation of a quantum phenomenon - choreographed electrons (i.e. an electron murmuration) that enable astonishing devices. There is indeed an intimate connectedness between biology and electromagnetism. Our brains are complex neural circuits generating magnetic fields with a magnitude around 100 femtoTesla (roughly one billion times weaker than a typical magnet used to tack notes to a refrigerator door). Migratory birds navigate by orienteering with respect to the Earth's magnetic field. Electromagnetic field therapy is used in orthopedics to aid in bone repair. The electric eel generates a large electric field for self-defense. Sharks apparently detect extremely weak electric fields for finding prey. And so on. There are similarities between the way a field of wheat responds to a breeze and the natural restoring forces of a semiconductor crystal. And waves in a slowly moving river can lap backwards against a peninsular shoreline mimicking a diffraction effect. Getting back to the introductory sentence and mysterious links over cosmic distances, in August 2016, China launched the Quantum Experiments at Space Scale (QUESS) satellite. The technology is based on a non-linear crystal that produces pairs of entangled photons whose attributes apparently remain entwined regardless of how far apart they are separated. This paper will, no doubt superficially, attempt to enumerate and examine these types of connections and parallelisms.
This report describes the results of research into the effects of environment-induced noise on the evaluation process for anomaly detectors in the cyber security domain. This research was conducted during a 10-week summer internship program from the 19th of August, 2012 to the 23rd of August, 2012 at the Jet Propulsion Laboratory in Pasadena, California. The research performed lies within the larger context of the Los Angeles Department of Water and Power (LADWP) Smart Grid cyber security project, a Department of Energy (DoE) funded effort involving the Jet Propulsion Laboratory, California Institute of Technology and the University of Southern California/ Information Sciences Institute. The results of the present effort constitute an important contribution towards building more rigorous evaluation paradigms for anomaly-based intrusion detectors in complex cyber physical systems such as the Smart Grid. Anomaly detection is a key strategy for cyber intrusion detection and operates by identifying deviations from profiles of nominal behavior and are thus conceptually appealing for detecting "novel" attacks. Evaluating the performance of such a detector requires assessing: (a) how well it captures the model of nominal behavior, and (b) how well it detects attacks (deviations from normality). Current evaluation methods produce results that give insufficient insight into the operation of a detector, inevitably resulting in a significantly poor characterization of a detectors performance. In this work, we first describe a preliminary taxonomy of key evaluation constructs that are necessary for establishing rigor in the evaluation regime of an anomaly detector. We then focus on clarifying the impact of the operational environment on the manifestation of attacks in monitored data. We show how dynamic and evolving environments can introduce high variability into the data stream perturbing detector performance. Prior research has focused on understanding the impact of this variability in training data for anomaly detectors, but has ignored variability in the attack signal that will necessarily affect the evaluation results for such detectors. We posit that current evaluation strategies implicitly assume that attacks always manifest in a stable manner; we show that this assumption is wrong. We describe a simple experiment to demonstrate the effects of environmental noise on the manifestation of attacks in data and introduce the notion of attack manifestation stability. Finally, we argue that conclusions about detector performance will be unreliable and incomplete if the stability of attack manifestation is not accounted for in the evaluation strategy.
Machine learning for cyber defense offers the promise of detecting adversarial activity against the ground data systems managing critical space assets. A fundamental challenge facing machine learning research in cybersecurity is the lack of high-fidelity, shareable datasets for robust evaluation and testing of machine learning-based solutions. High-fidelity, real-world datasets are necessary for reliable benchmarking of nominal system behavior and malicious activity. Unfortunately, such realistic datasets of both nominal and adversarial activity are rarely shared publicly by data owners due to security and privacy concerns. Besides, the available adversarial data is sparse, which makes training models on malicious activity much harder. This situation has impeded and continues to impede the research and successful adoption of machine learning methods for cyber defense. Researchers have dealt with this problem by generating data within a low-fidelity lab environment, using classified and thus unshareable datasets, or downloading low-fidelity public datasets made available by others. We propose an innovative solution to the problem by employing machine learning methods to generate high-fidelity data. Specifically, we propose the use of Generative Adversarial Networks (GANs) to generate high-fidelity data for cybersecurity purposes. GANs have found successful image processing and natural language applications, but have not yet been investigated for cyber data generation. Our proposed approach first involves training the `discriminator' network of the GAN with a sample of real-world data consisting of malicious and nominal samples. We then use the `generator' network to generate new high-fidelity data samples consisting of an appropriate mix of malicious and nominal activity. We demonstrate applications of our architecture by generating high-fidelity cybersecurity data containing both malicious and nominal samples. We thoroughly evaluate the fidelity of our generated data using heuristics and evaluate its usefulness for machine learning applications using three different datasets. Overall, our approach results in high-fidelity, shareable datasets.
High performance IR cameras are in great demand for a variety of applications, including defense (e.g. night vision, missile detection) and space (e.g. imaging at IR wavelengths). IR focal plane arrays (FPAs) are an essential component of IR cameras. An FPA is a collection of detectors at the focal plane of an imaging device, where each detector can be thought of a pixel in the image it is detecting. The FPA in this study is based on Complimentary Barrier Infrared Detectors (CBIRDs). The CBIRD FPA was tested by imaging flat black body targets at three different temperatures, 20ºC, 25ºC, and 30ºC, with images captured using SEIR software. The important figures of merit for an IR FPA, Noise Equivalent Difference Temperature (NEDT), Noise Equivalent Irradiance (NEI), detectivity (D*), responsivity, and quantum Efficiency (QE), were extracted from the image data for each individual detector using a MATLAB program, as was the array Modulation Transfer Function MTF. The test results show a mean NEDT of 16.98mK and an MTF of about 0.34 at the Nyquist frequency. Overall, the array performs well in the MWIR range and takes quality IR images.
The Mid-Course Space Experiment consists of a set of payloads on a satellite being designed and built under the sponsorship of Ballistic Missile Defense Office. The MSX satellite will conduct a series of measurements of phenomenology of backgrounds, missile targets, plumes and resident space objects (RSO's); and will engage in functional demonstrations in support of detection, acquisition and tracking for ballistic missile defense and space-based space surveillance missions. A complex satellite like the MSX has several constraints imposed on its operation by the sensors, the supporting instrumentation, power resources, data recording capability, communications and the environment in which all these operate. This paper describes the implementation of an opportunity and feasibility analysis system, developed at Lincoln Laboratory, Massachusetts Institute of Technology, specifically to support the experiments of the Principal Investigator for space-based surveillance.
We are developing tools to link the biochemical structure of selected biomarkers with putative biogenic structures observed in mineralized samples. The detection of evidence of life on Mars and other planets will rely on methods that can discriminate compounds formed exclusively by living organisms. While biogenic compounds, such as amino acids and nucleotides have been discovered in extraterrestrial sources, such as meteorites and comets, their formation can be explained by abiotic means. The formation of cellular structures, or more elaborate organic molecules, such as complex lipids, proteins or nucleic acids, however, is strongly correlated to the presence of even the most primitive life processes. Recent evidence lends support to the hypothesis that life may have once existed on Mars. Carbonate globules and ppm concentrations of polycyclic aromatic hydrocarbons (PAHs) have been described in ALH84001, a meteorite originating from Mars ejecta captured by Earth over 13,000 years ago. The localized high concentration of PAHs that follow an increasing gradient from the intact fusion crust towards the interior corresponds to microgram quantities of hydrocarbon. Even though ALH84001 and other similar meteorites have withstood the forces capable of ejecting rock through Mars' escape velocity, upon entering Earth's atmosphere, their core temperatures are likely not to have been raised significantly, as evidenced by the survival of remanent magnetic signatures. Ideal biomarkers of ancient or modern biological life would include molecules that are (or were) pervasive and highly resistant to degradation. Also, requisite methods of detection should be simple, extremely sensitive and broadly inclusive (NASA SP-530). Lipopolysaccharide (LPS), peptidoglycan or pseudopeptidoglycan and beta-glucan are microbial cell wall components which together cover the entire microbial spectrum of eubacteria, archea and fungi. They are all remarkably resistant to thermal degradation. Fortunately, many antimicrobial defense systems of higher organisms require sensitive detection to combat microbial pathogens. We employ here the primitive immune system of the evolutionarily ancient horseshoe crab, Limulus polyphemus. This species relies on multi-enzyme signal amplification detection of cell wall molecules and they can be applied to the development of useful detectors of life. An extension of this work includes the visualization of microbial signatures by labeling LAL components with chromogenic or electron dense markers. The protein Limulus Anti-LPS Factor (LALF) has an extremely high affinity for LPS. By coupling LALF binding with colloidal gold labels we demonstrate a correlation of the structures visible by electron microscopy with biochemical evidence of microbial cell wall materials. Pure silica particles were mixed with cultures of E. coli (10(exp 6) cfu/mL). Samples were washed sequentially with buffered saline, LALF, antibody to LALF and finally colloidal gold-labeled Protein A. Negative controls were not exposed to E. coli but received identical treatment otherwise. Samples were coated with carbon and imaged on a JEOL JSM-840 scanning electron microscope with LaB6 source in the back scatter mode with the JEOL annular back scatter detector. 20 nm-scale black spots in this contrast-reversed image originate from electrons back-scattered by gold atoms. Negative controls did not give any signal. Future work will expand application of this technique to soil simulants and mineralized rock samples.
Intelligent Optical Systems Inc. (IOS) completed Phase I and II Small Business Innovation Research (SBIR) contracts with NASA's Langley Research Center to develop moisture- and pH-sensitive sensors to detect corrosion or pre-corrosive conditions, warning of potentially dangerous conditions before significant structural damage occurs. This new type of sensor uses a specially manufactured optical fiber whose entire length is chemically sensitive, changing color in response to contact with its target, and demonstrated to detect potentially corrosive moisture incursions to within 2 cm. After completing the work with NASA, the company received a Defense Advanced Research Projects Agency (DARPA) Phase III SBIR to develop the sensors further for detecting chemical warfare agents, for which they proved just as successful. The company then worked with the U.S. Department of Defense (DoD) to fine tune the sensors for detecting potential threats, such as toxic industrial compounds and nerve agents. In addition to the work with government agencies, Intelligent Optical Systems has sold the chemically sensitive fiber optic cables to major automotive and aerospace companies, who are finding a variety of uses for the devices. Marketed under the brand name Distributed Intrinsic Chemical Agent Sensing and Transmission (DICAST), these unique continuous-cable fiber optic chemical sensors can serve in a variety of applications: Corrosive-condition monitoring, aiding experimentation with nontraditional power sources, as an economical means of detecting chemical release in large facilities, as an inexpensive "alarm" systems to alert the user to a change in the chemical environment anywhere along the cable, or in distance-resolved optical time domain reflectometry systems to provide detailed profiles of chemical concentration versus length.
Path planning is an important issue for space robotics. Finding safe and energy-efficient paths in the presence of obstacles and other constraints can be complex although important. High-level (large-scale) path planning for robotic vehicles was investigated in three-dimensional space with obstacles, accounting for: (1) energy costs proportional to path length; (2) turn costs where paths change trajectory abruptly; and (3) safety costs for the danger associated with traversing a particular path due to visibility or invisibility from a fixed set of observers. Paths optimal with respect to these cost factors are found. Autonomous or semi-autonomous vehicles were considered operating either in a space environment around satellites and space platforms, or aircraft, spacecraft, or smart missiles operating just above lunar and planetary surfaces. One class of applications concerns minimizing detection, as for example determining the best way to make complex modifications to a satellite without being observed by hostile sensors; another example is verifying there are no paths (holes) through a space defense system. Another class of applications concerns maximizing detection, as finding a good trajectory between mountain ranges of a planet while staying reasonably close to the surface, or finding paths for a flight between two locations that maximize the average number of triangulation points available at any time along the path.
Detection of ultraviolet (UV) bands provides distinct advantages for NASA, defense, and commercial applications, including increased spatial resolution, small pixel sizes, and large format arrays. AlxGa1-xN semiconductor alloys have attracted great interest for detection in the UV spectral region because of their potential for high optical gain, high sensitivity, and low dark current performance in ultraviolet avalanche photodiodes (UV-APDs). We are developing GaN/AlGaN UV-APDs that demonstrate consistent and reliable UV-APD performance and operation. For these UV detectors we have measured gains of above 5×10(exp 6) and high quantum efficiencies at ~350 nm enabled by a strong avalanche multiplication process. These UV-APDs are fabricated through high quality metal organic chemical vapor deposition (MOCVD) growth on lattice-matched, low dislocation density GaN substrates with optimized GaN/AlGaN UV-APD material growth and doping parameters. The high performance, variable-area GaN/AlGaN UV-APD detectors and arrays can be customized to a wide variety of sizes including large-area formats to enable sensing and high-resolution detection over UV bands of interest.
This Tech Report summarizes years of study and experiences on using GOES Water vapor (6.7 micron and precipitable water) and Special Sensor Microwave Imager (SSM/1) from the Defense Meteorological Satellite Program (DMSP) derived Precipitable Water (PNAI) for detecting environments favorable for convectively produced flash floods. An emphasis is on the moisture. upper air flow, and equivalent potential temperature (Theta(sub e)) patterns that lead to devastating flood events. The 15 minute 6.7 micron water vapor imagery is essential for tracking middle to upper tropospheric disturbances that produce upward vertical motion and initiate flash flood producing systems. Water vapor imagery at 6.7 micron is also used to detect surges of upper level moisture (called tropical water vapor plumes) that have been associated with extremely heavy rainfall. Since the water vapor readily depicts lifting mechanisms and upper level moisture, water vapor imagery is often an excellent source of data for recognizing patterns of heavy precipitation and flash floods. In order to analyze the depth of the moisture, the PW aspects of the troposphere must be measured. The collocation (or nearby location) of high values ofP\V and instability are antecedent conditions prior to the flash flood or heavy rainfall events. Knowledge of PW magnitudes have been used as thresholds for impending flash flood events, PW trends are essential in flash flood prediction. Conceptual models and water vapor products are used to study some of the characteristics of convective systems that occurred over the United States of America (USA) during the summer of 1997 and the 1997-1998 El Nino. P\V plumes were associated with most of the \vest coast heavy precipitation events examined during the winter season of 1997 - 1998, In another study, conducted during the summer season of 1997. results showed that the collocation of water vapor (6.7 micron) and P\N' plumes possessed higher correlations with predicted rainfall amounts than when PW plumes occurred by themselves (i.e.. without the presence of 6.7 micron water vapor plumes). Satellite Analysis Branch (SAB) meteorologists use the 6.7 micron water and P\V products for their QPE's (interactive Flash Flood Analyzer (IFFA) and Auto-Estimator precipitation estimates), Outlooks, and heavy precipitation briefings with the Hydrometeorological Prediction Center/National Center for Environmental Prediction.
The United States Space Command (USSPACECOM) is a unified command of the Department of Defense, and one of its tasks is to detect, track, identify, and maintain a catalog of all man-made objects in Earth orbit. This task is called space surveillance, and the most important tool for space surveillance is the satellite catalog. The command's reasons for performing satellite catalog maintenance is presented. A satellite catalog is described, and small satellite-debris catalog-maintenance issues are identified. The underlying rationale is to describe the catalog maintenance services so that the members of the community can use them with assurance.
Gamma-ray burst detectors are aboard six U. S. Air Force defense Meteorological Satellite Program (DMSP) spacecraft, two of which are currently in use. Their 800-km altitude orbits give a field of view to 117 degrees from the zenith. A great many bursts have been detected, usually in coincidence with detections by GRO or other satellites such as PVO or ULYSSES. The directions of the sources can be determined with considerable accuracy from such correlated observations, even when GRO/BATSE with its directional capabilities is not involved. Thus these DMSP data, especially in conjunction with other observations, should be helpful in trying to understand the true nature of gamma-ray bursts.
The NASA Glenn Research Center, partner universities, and defense contractors are working to develop intelligent power management and distribution (PMAD) technologies for future spacecraft and launch vehicles. The goals are to provide higher performance (efficiency, transient response, and stability), higher fault tolerance, and higher reliability through the application of digital control and communication technologies. It is also expected that these technologies will eventually reduce the design, development, manufacturing, and integration costs for large, electrical power systems for space vehicles. The main focus of this research has been to incorporate digital control, communications, and intelligent algorithms into power electronic devices such as direct-current to direct-current (dc-dc) converters and protective switchgear. These technologies, in turn, will enable revolutionary changes in the way electrical power systems are designed, developed, configured, and integrated in aerospace vehicles and satellites. Initial successes in integrating modern, digital controllers have proven that transient response performance can be improved using advanced nonlinear control algorithms. One technology being developed includes the detection of "soft faults," those not typically covered by current systems in use today. Soft faults include arcing faults, corona discharge faults, and undetected leakage currents. Using digital control and advanced signal analysis algorithms, we have shown that it is possible to reliably detect arcing faults in high-voltage dc power distribution systems (see the preceding photograph). Another research effort has shown that low-level leakage faults and cable degradation can be detected by analyzing power system parameters over time. This additional fault detection capability will result in higher reliability for long-lived power systems such as reusable launch vehicles and space exploration missions.
The purpose of investigation is to develop the fundamental materials and fabrication technology for field-controlled spectrally active optics that are essential for industry, NASA, and DOD (Department of Defense) applications such as: membrane optics, filters for LIDARs (Light Detection and Ranging), windows for sensors and probes, telescopes, spectroscopes, cameras, light valves, light switches, flat-panel displays, etc. The proposed idea is based on the quantum-dots (QD) array or thin-film of field-sensitive Stark and Zeeman materials and the bound excitonic state of organic crystals that will offer optical adaptability and reconfigurability. Major tasks are the development of concept demonstration article and test data of field-controlled spectrally smart active optics (FCSAO) for optical multi-functional capabilities on a selected spectral range.
The National Aeronautics and Space Administration (NASA) Unmanned Aircraft Systems Integration in the National Airspace System (UAS-NAS) Project has conducted a series of flight test campaigns intended to support the reduction of barriers that prevent unmanned aircraft from flying without the required waivers from the Federal Aviation Administration (FAA). The 2019 Flight Test Series 6 (FT6) campaign furthered this path and supported three test configurations: 1) Radar Characterization, 2) Scripted Encounters and 3) Full Mission. Radar Characterization assessed the performance of Honeywell’s low size, weight, and power (low SWaP) radar system; Scripted Encounters investigated the timing of Detect and Avoid (DAA) alerting thresholds using a Department of Defense (DoD) Group 3 unmanned aircraft system (UAS) equipped with low SWaP sensors and three different live intruder aircraft flown at varying encounter geometries; and Full Mission validated human-in-the-loop simulations by collecting pilot performance data from a ground control station while controlling a live unmanned aircraft on a mission in both virtual and live air traffic controlled airspace. The subject pilot observed a research display that presented DAA advisories to maintain separation from live and virtual aircraft. The test was conducted over a twenty-week period within the R-2508 special use airspace located near Edwards Air Force Base (EAFB), CA. Over 240 encounters were flown during the test series and FT6 proved to be invaluable for the purposes of planning, managing, and executing this type of integrated flight test in both live and virtual environments. Data collected from FT6 was provided to the RTCA Special Committee 228 (SC-228) to help inform the Phase 2 Minimum Operational Performance Standards (MOPS). FT6 was the final test series for the UAS-NAS project that began in 2012. This paper provides an overview of FT6 and its success can be directly attributed to the diligent work of the men and women who supported this effort.