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Terahertz SAR measurements of 1/60th scale models for rapid object recognition development
No full textStatistical Reliability Estimation of Deep Space Satellites and Launch Vehicles: 1958–2022
No full textOn-orbit flight data for deep space satellites and space launch vehicles (SLVs) servicing deep space missions operated between 1958 and 2022 is analyzed due to a lack of reliability research combining both satellites and SLVs for this class of mission. Satellite reliability is first estimated by the Kaplan–Meier estimator, and then parameterized through the Weibull distribution. This process is applied to the general deep space satellite data set as well as the delimitation of the data according to decade. SLV reliability is computed using standard maximum likelihood estimation and an evolving first-level Bayesian estimation scheme. Results from the satellite analysis demonstrated the differences between the parameterization methods used. The bulk satellite data set indicated that deep space satellites suffer from infant mortality, while certain subsets were found to have a primary wear-out failure mode. In general, U.S. deep space missions demonstrated the highest reliability. Deep space satellite reliability was also found to have increased as a function of time. Results from the SLV data set revealed that deep space launches are primarily performed by four main launch vehicle families. Additionally, most deep space SLV failures occurred in the space age (1959–1975), with the USA and USSR/Russia being the only two countries to experience deep space launch failures. With both deep space SLV and satellite reliability increasing over time, reliability is not expected to be a major hindrance to future deep space missions
Nearly Tight Weighted 2-designs in Complex Projective Spaces of Every Dimension
No full textWe use dense Sidon sets to construct small weighted projective 2-designs. This represents quantitative progress on Zauner’s conjecture
Exact and Approximate Conformal Inference for Multi-Output Regression
Full text linkIt is common in machine learning to estimate a response y given covariate information x . However, these predictions alone do not quantify any uncertainty associated with said predictions. One way to overcome this deficiency is with conformal inference methods, which construct a set containing the unobserved response with a prescribed probability. Unfortunately, even with a one-dimensional response, conformal inference is computationally expensive despite recent encouraging advances. In this paper, we explore multi-output regression, delivering exact derivations of conformal inference p-values when the predictive model can be described as a linear function of y . Additionally, we introduce a multivariate extension of rootCP as well unionCP as efficient ways of approximating the conformal prediction region for a wide array of multi-output predictors, both linear and nonlinear, while preserving computational advantages. We also provide both theoretical and empirical evidence of the effectiveness of our methods using both real-world and simulated data
Doubly Transitive Equiangular Tight Frames That Contain Regular Simplices
No full textAn equiangular tight frame (ETF) is a finite sequence of equal norm vectors in a Hilbert space that achieves equality in the Welch bound, and so has minimal coherence. The binder of an ETF is the set of all subsets of its indices whose corresponding vectors form a regular simplex. An ETF achieves equality in Donoho and Elad\u27s spark bound if and only if its binder is nonempty. When this occurs, its binder is the set of all linearly dependent subsets of it of minimal size. Moreover, if members of the binder form a balanced incomplete block design (BIBD) then its incidence matrix can be phased to produce a sparse representation of its dual (Naimark complement). A few infinite families of ETFs are known to have this remarkable property. In this paper, we relate this property to the recently introduced concept of a doubly transitive equiangular tight frame (DTETF), namely an ETF for which the natural action of its symmetry group is doubly transitive. In particular, we show that the binder of any DTETF is either empty or forms a BIBD, and moreover that when the latter occurs, any member of the binder of its dual is an oval of this BIBD. We then apply this general theory to certain known infinite families of DTETFs. Specifically, any symplectic form on a finite vector space yields a DTETF, and we compute the binder of it and its dual, showing that the former is empty except in a single notable case, and that the latter consists of affine Lagrangian subspaces. This unifies and generalizes several results from the existing literature. We then consider the binders of four infinite families of DTETFs that arise from quadratic forms over the field of two elements, showing that two of these are empty except in a finite number of cases, whereas the other two form BIBDs that relate to each other, and to Lagrangian subspaces, in nonobvious ways
Lunar Navigation Satellite System Design for In-Space Rescue Applications
No full textThe United States Cislunar Technology Strategy Working Group published the National Cislunar Science and Technology Strategy in 2022. Executive department representatives used a whole-of-government approach to address unique national challenges associated with the proliferation of human space exploration to the Moon and beyond. One of the four objectives is to implement cislunar communications and navigation capabilities with scalable and interoperable approaches to enable a cooperative and sustainable ecosystem in cislunar space. (National Science and Technology Council, 2022) Humans will return to the Moon in 2025 under the National Aeronautics and Space Administration (NASA) Artemis mission, increasing the risk of space isolation and driving the demand for Department of Defense collaboration to rescue astronauts in distress. The NASA Search and Rescue Mission Office requires Position, Navigation, Timing (PNT) services to report and locate cislunar contingencies to enable rapid response capabilities in the future. This study examines recent cislunar PNT literature and experiments to recommend a satellite-based architecture for the rescue requirement, including Lunar Navigation Satellite System Receiver designs for prototyping development. The receiver design uses PyChips and Python-based software with modified Global Navigation Satellite System (GNSS) settings to adjust for lunar signal specifications defined by NASA (Gunawardena, 2021). The optimal prototyping configurations are based on power-to-channel trade-offs and user needs. The Air Force Research Lab, in conjunction with the Air Force Institute of Technology and Draper Laboratory, modeled a theoretical Cislunar Autonomous Navigation Satellite System (CLASS) to augment earth based GNSS services. The optimal satellite orbits are based on suitable geometries to NASA Artemis operational areas, cislunar activities, and cost-benefit analysis findings gained through previous experiments. The geometric dilution of precision and simulated almanac is predicted by modeling desirable satellite vehicle orbits. This information is ingested into the receiver for software experimentation. The architecture design includes a space segment in Lunar and Lagrange orbits, a ground segment on the lunar surface, and a lunar surface user segment. The ground segment provides users the satellite positions negating the exhaustive task of satellite vehicle error calculations through ephemeris decryption. The receiver design outputs data for ranging the user position in concert with the National Geospatial Agency’s lunar reference frame. The project provides a comprehensive analysis for immediate design implementation, prototyping, and experimentation to meet U.S. government needs in line with the national science and technology strategy
Retrospective cohort study of pure tone audiometry hearing changes from ototoxic metals and solvents, continuous noise, and impulse noise exposures at Hill Air Force Base from 2005 to 2019
No full textThis retrospective cohort epidemiological study investigated the relative risks of hearing loss associated with ototoxicants in combination with noise exposure. Utilizing United States Department of Defense (DoD) industrial hygiene and hearing conservation data, this research expanded on a 2020 study conducted on Tinker Air Force Base (AFB), Oklahoma, applying a similar methodology to Hill AFB, Utah, adding 893 evaluated individuals. Grouped into twelve exposure combinations with a minimum of 3 years of exposure duration, the study assessed various hearing loss indicators, including DoD Significant Threshold Shift (STS) and National Institute for Occupational Safety and Health (NIOSH) STS. Ototoxic substances consistently elevated relative risk (RR) compared to noise-only exposure groups, but none reached significance at the 95% confidence level. Incorporating Hill AFB to findings from Tinker AFB (n = 2,372) revealed exposure groups with a RR greater than one for developing a NIOSH STS were significant at the 95% confidence level, with the greatest RR coming from the metal, solvent, continuous noise exposure group in the left ear at 2,000 Hz (RR = 2.25; 1.96–2.57). Logistic regression modeling identified age and audiogram duration between first and last audiogram (as a surrogate for duration of exposure) as significant independent variables for hearing loss indicator development prediction
Space vehicle reliability assessment for selected medium space powers
No full textThis research examines space launch vehicle (SLV) and satellite reliability trends through a variety of statistical methods such as the first-level Bayesian estimation and the Weibull distribution for France, India, Israel, Japan, and South Korea. Datasets derived from the Seradata database included the following information: launch date, inactive date, launch country, satellite owner country, vehicle family, satellite name, orbit category, satellite status, mass category, event, event date, and event remarks. The first-level Bayesian estimation and success rates were calculated for 538 SLV launches from each country’s first launch date to 31 December 2023. Overall, 51 launches were failures, making up 9.48 % of total launches for the countries analyzed; 57.8 % of launches were sent to low Earth orbit (LEO) while 4.28 % were sent beyond geosynchronous/geostationary orbit (GEO-GSO). Of 18 SLVs analyzed, 6 vehicle families exhibited realized success rates above 90 %. Since 1965, 809 satellites were launched, with a 1.98 % failure rate. The primary cause of failure was due to the satellites, inability to transmit signals, making communication, command, and control unattainable. Ultimately, through Weibull distribution, satellites owned by France, India, Japan, and South Korea showed a decreasing failure rate over time while results from Israeli satellites were inconclusive
Microarchitectural Malware Detection via Translation Lookaside Buffer (TLB) Events
No full textPrior work has shown that Translation Lookaside Buffer (TLB) data contains valuable behavioral information. Many existing methodologies rely on timing features or focus solely on workload classification. In this study, we propose a novel approach to malware classification using only TLB-related Hardware Performance Counters (HPCs), explicitly excluding any dependence on timing features such as task execution duration or memory access timing. Our methodology evaluates whether TLB data alone, without any timing information, can effectively distinguish between malicious and benign programs. We test this across three classification scenarios: (1) A binary classification problem involving distinguishing malicious from benign tasks, (2) a 4-way classification problem designed to improve separability, and (3) a 10-way classification problem with classes of individual benign and malware tasks. Our results demonstrate that even without execution time or memory access timing, TLB events achieve up to 81% accuracy for the binary, and 72% accuracy for the 4-class grouping, and 61% accuracy for the 10-class grouping. These findings demonstrate that time-independent TLB patterns can serve as robust behavioral signatures. This work expands the understanding of microarchitectural side effects by demonstrating that TLB-only features, independent of timing-based techniques, can be effectively used for real-world malware detection
Effect of Film Cooling Hole Location on Flow Dynamics in a Rotating Detonation Combustor
No full textDetonative combustion can be employed to develop high-power-density combustors, such as the rotating detonation combustor (RDC). The high combustor mass flow, combined with the significant heat release from detonation waves occurring near the walls of the narrow annulus, results in immense thermal loads on the walls. Managing these thermal loads is crucial for the successful application of RDCs in gas turbines. Previous studies have suggested that film cooling may offer a viable solution for mitigating the intense thermal loads. However, the impact of the coolant mass addition location on RDC performance remains unclear. Four film-cooled RDC architectures are investigated, where the holes covered different portions of the outer wall from near the reactant injection location to downstream in the oblique shock region. The high circumferential and axial pressure variations resulted in differing coolant flows, while the added coolant mass increased the chamber pressure. The increased chamber pressure significantly altered the fresh gas refill structure and the detonation height. Regarding cooling performance, the various cooling schemes had different impacts on how much the wall temperatures were reduced. Ultimately, having cooling further downstream was most effective at overall cooling of the outer wall. However, placing coolant jets in the detonation region modifies the initial mixture characteristics, affecting the detonation combustion. In each cooling scheme, the injected coolant reacted with the unburnt fuel, leading to additional secondary deflagration heat release, which reduced the amount of unburned hydrogen at the exit