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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Surveillance Workload Divinator (SWORD)

The LANL Surveillance Workload Divinator (SWORD) is a high-level decision support tool that reproduces and predicts the annual values for stockpile and production disassembly and inspections (D&I) and rebuilds. SWORD, a spreadsheet-based tool, can be used to assess the surveillance workload under various planning scenarios. Results are shown graphically and updated dynamically for each weapon system or for the entire stockpile. Surveillance workload is calculated from stockpile surveillance guidance1 and from Production and Planning Directive (P&PD) data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Transboundary determinants of avian zoonotic infectious diseases: challenges for strengthening research capacity and connecting surveillance networks

As the climate changes, global systems have become increasingly unstable and unpredictable. This is particularly true for many disease systems, including subtypes of highly pathogenic avian influenzas (HPAIs) that are circulating the world. Ecological patterns once thought stable are changing, bringing new populations and organisms into contact with one another. Wild birds continue to be hosts and reservoirs for numerous zoonotic pathogens, and strains of HPAI and other pathogens have been introduced into new regions via migrating birds and transboundary trade of wild birds. With these expanding environmental changes, it is even more crucial that regions or counties that previously did not have surveillance programs develop the appropriate skills to sample wild birds and add to the understanding of pathogens in migratory and breeding birds through research. For example, little is known about wild bird infectious diseases and migration along the Mediterranean and Black Sea Flyway (MBSF), which connects Europe, Asia, and Africa. Focusing on avian influenza and the microbiome in migratory wild birds along the MBSF, this project seeks to understand the determinants of transboundary disease propagation and coinfection in regions that are connected by this flyway. Through the creation of a threat reduction network for avian diseases (Avian Zoonotic Disease Network, AZDN) in three countries along the MBSF (Georgia, Ukraine, and Jordan), this project is strengthening capacities for disease diagnostics; microbiomes; ecoimmunology; field biosafety; proper wildlife capture and handling; experimental design; statistical analysis; and vector sampling and biology. Here, we cover what is required to build a wild bird infectious disease research and surveillance program, which includes learning skills in proper bird capture and handling; biosafety and biosecurity; permits; next generation sequencing; leading-edge bioinformatics and statistical analyses; and vector and environmental sampling. Creating connected networks for avian influenzas and other pathogen surveillance will increase coordination and strengthen biosurveillance globally in wild birds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Development

The study of adverse childhood experiences and their consequences has emerged over the past 20 years. Although the conclusions from these studies are available, the same is not true of the data. Accordingly, it is a complex problem to build a training set and develop machine-learning models from these studies. Classic machine learning and artificial intelligence techniques cannot provide a full scientific understanding of the inner workings of the underlying models. This raises credibility issues due to the lack of transparency and generalizability. Explainable artificial intelligence is an emerging approach for promoting credibility, accountability, and trust in mission-critical areas such as medicine by combining machine-learning approaches with explanatory techniques that explicitly show what the decision criteria are and why (or how) they have been established. Hence, thinking about how machine learning could benefit from knowledge graphs that combine “common sense” knowledge as well as semantic reasoning and causality models is a potential solution to this problem. In this study, we aimed to leverage explainable artificial intelligence, and propose a proof-of-concept prototype for a knowledge-driven evidence-based recommendation system to improve mental health surveillance. We used concepts from an ontology that we have developed to build and train a question-answering agent using the Google DialogFlow engine. In addition to the question-answering agent, the initial prototype includes knowledge graph generation and recommendation components that leverage third-party graph technology. To showcase the framework functionalities, we here present a prototype design and demonstrate the main features through four use case scenarios motivated by an initiative currently implemented at a children’s hospital in Memphis, Tennessee. Ongoing development of the prototype requires implementing an optimization algorithm of the recommendations, incorporating a privacy layer through a personal health library, and conducting a clinical trial to assess both usability and usefulness of the implementation. This semantic-driven explainable artificial intelligence prototype can enhance health care practitioners’ ability to provide explanations for the decisions they make.

adverse childhood experiences↗
DOE OSTI2024

Enhancing Biopreparedness through a Model System to Understand the Molecular Mechanisms that Lead to Pathogenesis and Disease Transmission: NW-BRaVE

The science of biopreparedness to counter biological threats hinges on understanding the fundamental principles and molecular mechanisms that lead to pathogenesis and disease transmission. Our vision to address this challenge is to create a powerful and user-friendly platform to elucidate the fundamental principles of how molecular interactions drive pathogen-host relationships and host shifts. We will enable groundbreaking discoveries by integrating a wide range of structural, genomics, proteomics, and other advanced omics measurements, along with evolutionary and artificial intelligence predictions. To make sure the system is applicable to real-world problems, we will develop it in the context of a tractable model system, the small, abundant, and accessible photosynthetic cyanobacteria and their constantly co-adapting viral pathogens, cyanophages. This model will maintain the system’s applicability to real-world problems and techniques, but the overall focus will be on elucidating general principles of detecting, assessing, and surveilling molecular interaction, adaptation, and coevolution that are system agnostic and therefore extensible to other viral-host interactions. Our overall objectives are to (1) identify the molecular complexes that comprise the cyanobacteria redox macromolecular subsystem and how they dynamically change with bacteriophage infection in situ, using cryo-electron tomography; (2) profile regulatory changes during infection using proteomics, multiomics, and experimental validation, and integrate the data with in situ structures; (3) use genomics and metagenomics to determine environmental and population factors across time scales that impact the interactions between marine cyanobacteria and their cyanophage parasites, predicting the evolutionary origins of in situ structural and functional interactions, convergence and coevolution; and (4) develop a data integration and transformation platform that facilitates the integration of in situ, proteomic, and evolutionary measurements of molecular interactions to surveil diverse hosts and parasites in various environmental contexts. These objectives address Focus Area 2 Reveal Molecular Interactions Across Biological Scales for Design of Targeted Interventions. Our powerful and user-friendly platform will enhance connections between the often-siloed fields of structure, molecular phenotype, and evolutionary genomics that are key to biopreparedness, but in need of integration (Figure 1). We will build an integrated navigation tool to facilitate the effective use of globally distributed experimental data for integrated analysis and predictive modeling. The project will develop, implement, and test a platform to assess host-pathogen molecular interactions, adaptation to hosts and host shifts, and coevolution between hosts and pathogens, successfully impacting the research community by revolutionizing abilities to study any host-pathogen interaction, encourage diverse community contributions, and gain fundamental insights into how proteins adapt to new contexts. This ability will be critical for designing early interventions to address future threats. We will build surveillance training capability, aiming for a fair and equitable response to future pandemics and biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

3013 Inner Container Closure Weld Region (ICCWR) Characterization by Wide Area 3D Measurement System (WAMS) Analysis (FY21 Progress Report)

As part of the 3013 Surveillance Program, through-wall penetration from stress corrosion cracking (SCC) of the 3013 inner containers has been identified as the most credible condition for failure withing the 50- years lifetime. Chlorides contained in Pu-bearing material, together with intra-canister humidity levels, metallurgical conditions, and internal stresses have been found to produce corrosion in the Inner Container Closure Weld Region (ICCWR) of the 3013 canister system. A Laser Confocal Microscope (LCM) is used as part of the 3013 Surveillance Program protocol to identify the prevalence of corrosion and corrosionrelated cracking in the ICCWR2. With the LCM, a close visual examination is made of the ICCWR surface along with measurements of corrosion-related features. LCM inspections produce immense amounts of image data that is time intensive to analyze. There is also a 9-year backlog of images, with approximately 49 canisters that must be evaluated. To expedite data analysis and reduce the amount of generated data, a Wide Area 3D Measurement System (WAMS) microscope has been added to the examination protocol. Although WAMS is a lower resolution microscope, small features of interest can be still identified. The advantage of collecting data for the full circumference using the WAMS is that it can take about 1/16 of the time needed with the LCM. Both systems offer capabilities that combined can be utilized to expedite the examination of the ICCWR. The WAMS is an efficient system for screening and identification of corrosion features while the LCM can be utilized to obtain higher resolution images areas identified by the WAMS. This report explains and justifies the data collection methods used with the WAMS. It includes a summary of the data generated by WAMS in FY21. The goals set for data collection in FY21 were met. A total of twenty-two DE’s were imaged, and analysis was carried out on eleven samples. The analyzed samples showed large numbers of potential cracks and pits distributed throughout the surfaces. Lastly, to explain the advantages of the WAMS, its capabilities were compared to those of a simpler microscope. Micrographs of the samples imaged in FY21 and those analyzed are included in the appendices.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Technical Specification Surveillance Interval Extension Using Self-Diagnostics

As part of the Light Water Reactor Sustainability program, an ongoing research effort is being conducted on technical specifications surveillance interval extension of digital equipment in nuclear power plants. The research team is led by Idaho National Laboratory and includes Pacific Northwest National Laboratory, Technology Resources, and Oak Ridge National Laboratory. This research focuses on developing methods for applying the U.S. Nuclear Regulatory Commission (NRC)–approved guidance to implement a licensee-controlled, risk-informed surveillance frequency change program in digital instrumentation and control (I&C) systems that include self-diagnostics and online monitoring (OLM) capabilities. Although approved methods exist for extending technical specifications (TS) surveillance test intervals (STIs) for general equipment, including analog I&C equipment, gaps remain in technology and guidance on crediting newer digital equipment’s internal self-diagnostics and OLM characteristics. Previous research described a general methodology for crediting internal self-diagnostics for extending surveillance test intervals. The methodology used self-diagnostics to detect—and credited recovery from—failure. Self-diagnostics were also applied for performance monitoring during the extended surveillance interval. This report discusses the status of recent activities to evaluate the previously developed methodology using a pilot study. Although both a utility partner for a pilot study and a specific digital asset were identified in FY2020, delays in obtaining proprietary information resulted in a limited ability to fully evaluate the methodology, and further interactions were complicated by the COVID pandemic. Therefore, at that time, the use of public-domain information—along with current processes for surveillance interval extension through a surveillance frequency control program—identified the need to fully assess diagnostic coverage as part of the pilot study. Furthermore, self-diagnostics were also identified as a potential option to replace the drift analyses conducted as part of current STI extension procedures. In FY2022, the project was reconstituted with the industry partner, and information and data were made available by the industry partner to the research team for review. The shared information included failure event descriptions and data for a digital I&C system since its implementation, as well as recent STI extension interval reports developed by the utility partner on that digital I&C system. This report presents an evaluation of this information and data and describes an application of the proposed methodology cited above. The methodology seeks to take advantage of the self-diagnostics and OLM capabilities to reduce risk or reduce the level of qualitative monitoring assessment needed to perform a risk-informed STI extension using existing NRC approved guidance or both. Addressing these issues of STI extension by crediting self-diagnostics is likely to result in benefits for current and future nuclear power plant (NPP) operations, including lowering the barriers to adoption of digital I&C systems and increasing cost savings by deferring or eliminating unneeded preventive maintenance (tasks or checks or activities). Specifically, self-diagnostic and OLM capabilities of newer digital equipment being installed in non-safety and safety applications are designed to detect failures, provide early warning of potential failures, and notify plant operators to take appropriate action to reduce out of service (OOS) time thus protecting safety margins. Moreover, the equipment is expected to provide information that time-related operational degradation is identified early to ensure timely and planned corrective actions instead of a reactive and unplanned approach ahead of an extended-surveillance interval.

42 ENGINEERING↗
DOE OSTI2021

Intelligent Monitoring Systems and Advanced Well Integrity and Mitigation

Long-term seismic monitoring of carbon capture and storage projects is needed to verify that the injected gas is safely stored in the subsurface until permanence can be assured. Conventional surface seismic monitoring techniques are usually expensive, require highly invasive surface operations, and need significant time investments on the part of personnel for both the field effort and processing the acquired data. For these reasons, permanent reservoir monitoring technologies are preferred, as they can offer a cost-effective solution for long-term monitoring. As part of the monitoring program of the Archer Daniels Midland’s large-scale injection of CO 2 in Decatur, Illinois, USA, a continuous seismic monitoring array was installed using a combination of surface orbital vibrator (SOV) sources and fiber-optic cables for distributed acoustic sensing (DAS) acquisition with the objective to build a continuous monitoring array. The aim of the presented project was to build a monitoring array and platform that integrates real-time seismic data with conventional data streams and provides continuous data analysis using dynamic computational models to deliver a comprehensive real-time assessment of subsurface conditions. It is in this context that the Intelligent Monitoring Systems and Advanced Well Integrity and Mitigation project was proposed with the objective to develop an integrated architecture that utilizes a permanent seismic monitoring network, combines the real-time geophysical and process data with reservoir flow and geomechanical models to create a comprehensive monitoring, visualization, and control system that delivers critical information for process surveillance and optimization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Real time autonomous surveillance of pathogens

The present invention relates, in part, to systems configured to obtain samples from an organism in an autonomous manner. Such systems can employ a cartridge configured to provide bait to attract an organism, as well as channels to store and/or test samples obtained from the organism.

Meagher, Robert↗
DOE OSTI2020

Csx3 is a cyclic oligonucleotide phosphodiesterase associated with type III CRISPR–Cas that degrades the second messenger cA 4

Cas10 is the signature gene for type III CRISPR–Cas surveillance complexes. Unlike type I and type II systems, type III systems do not require a protospacer adjacent motif and target nascent RNA associated with transcriptionally active DNA. Further, target RNA recognition activates the cyclase domain of Cas10, resulting in the synthesis of cyclic oligoadenylate second messengers. These second messengers are recognized by ancillary Cas proteins harboring CRISPR-associated Rossmann fold (CARF) domains and regulate the activities of these proteins in response to invading nucleic acid. Csx3 is a distant member of the CARF domain superfamily previously characterized as a Mn 2+ -dependent deadenylation exoribonuclease. However, its specific role in CRISPR–Cas defense remains to be determined. Here we show that Csx3 is strongly associated with type III systems and that Csx3 binds cyclic tetra-adenylate (cA 4 ) second messenger with high affinity. Further, Csx3 harbors cyclic oligonucleotide phosphodiesterase activity that quickly degrades this cA 4 signal. In addition, structural analysis identifies core elements that define the CARF domain fold, and the mechanistic basis for ring nuclease activity is discussed. Overall, the work suggests that Csx3 functions within CRISPR–Cas as a counterbalance to Cas10 to regulate the duration and amplitude of the cA 4 signal, providing an off ramp from the programmed cell death pathway in cells that successfully cure viral infection.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Agent-Based Simulation Framework for Multi-Variant Surveillance

Early detection of an emerging VOC (Variant-Of-Concern) is essential for effective preparedness for a disease like COVID-19. The spreading of an emerging VOC not only depends on the disease dynamics of itself but also depends on the state of the circulating variants and the susceptibility of the population. Resources for testing are typically quite limited, and a number of strategies have been considered for deploying them. However, it has been difficult to evaluate the performance of such strategies, especially higher order effects, and inequities, while incorporating constraints on these resources. Here, we develop an agent-based surveillance framework, Networkdetect, to understand the early warning system of an emerging VOC. Our framework allows us to incorporate various population heterogeneities and resource constraints.

Moon, Sifat [ORNL] (ORCID:0000000344968809)↗
DOE OSTI2023

Low power and privacy preserving sensor platform for occupancy detection

A low-cost, low-power, stand-alone sensor platform having a visible-range camera sensor, a thermopile array, a microphone, a motion sensor, and a microprocessor that is configured to perform occupancy detection and counting while preserving the privacy of occupants. The platform is programmed to extract shape/texture from images in spatial domain; motion from video in time domain; and audio features in frequency domain. Embedded binarized neural networks are used for efficient object of interest detection. The platform is also programmed with advanced fusion algorithms for multiple sensor modalities addressing dependent sensor observations. The platform may be deployed for (i) residential use in detecting occupants for autonomously controlling building systems, such as HVAC and lighting systems, to provide energy savings, (ii) security and surveillance, such as to detect loitering and surveil places of interest, (iii) analyzing customer behavior and flows, (iv) identifying high performing stores by retailers.

Velipasalar, Senem↗
DOE OSTI2020

Inhibition mechanisms of AcrF9, AcrF8, and AcrF6 against type I-F CRISPR–Cas complex revealed by cryo-EM

Prokaryotes and viruses have fought a long battle against each other. Prokaryotes use CRISPR–Cas-mediated adaptive immunity, while conversely, viruses evolve multiple anti-CRISPR (Acr) proteins to defeat these CRISPR–Cas systems. The type I-F CRISPR–Cas system in Pseudomonas aeruginosa requires the crRNA-guided surveillance complex (Csy complex) to recognize the invading DNA. Although some Acr proteins against the Csy complex have been reported, other relevant Acr proteins still need studies to understand their mechanisms. As such, here, we obtain three structures of previously unresolved Acr proteins (AcrF9, AcrF8, and AcrF6) bound to the Csy complex using electron cryo-microscopy (cryo-EM), with resolution at 2.57 Å, 3.42 Å, and 3.15 Å, respectively. The 2.57-Å structure reveals fine details for each molecular component within the Csy complex as well as the direct and water-mediated interactions between proteins and CRISPR RNA (crRNA). Our structures also show unambiguously how these Acr proteins bind differently to the Csy complex. AcrF9 binds to key DNA-binding sites on the Csy spiral backbone. AcrF6 binds at the junction between Cas7.6f and Cas8f, which is critical for DNA duplex splitting. AcrF8 binds to a distinct position on the Csy spiral backbone and forms interactions with crRNA, which has not been seen in other Acr proteins against the Csy complex. Our structure-guided mutagenesis and biochemistry experiments further support the anti-CRISPR mechanisms of these Acr proteins. Our findings support the convergent consequence of inhibiting degradation of invading DNA by these Acr proteins, albeit with different modes of interactions with the type I-F CRISPR–Cas system.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Spatialyze: A Geospatial Video Analytics System with Spatial-Aware Optimizations

Videos that are shot using commodity hardware such as phones and surveillance cameras record various metadata such as time and location. We encounter suchgeospatial videoson a daily basis and such videos have been growing in volume significantly. Yet, we do not have data management systems that allow users to interact with such data effectively. In this paper, we describe Spatialyze, a new framework for end-to-end querying of geospatial videos. Spatialyze comes with a domain-specific language where users can construct geospatial video analytic workflows using a 3-step, declarative,build-filter-observeparadigm. Internally, Spatialyze leverages the declarative nature of such workflows, the temporal-spatial metadata stored with videos, and physical behavior of real-world objects to optimize the execution of workflows. Our results using real-world videos and workflows show that Spatialyze can reduce execution time by up to 5.3×, while maintaining up to 97.1% accuracy compared to unoptimized execution.

Computer Science↗
DOE OSTI2020

Structures, Systems, and Components Classification Criteria for the Versatile Test Reactor

The Versatile Test Reactor (VTR) is a fast spectrum test reactor currently being developed in the United States under the direction of the US Department of Energy (DOE), Office of Nuclear Energy. The VTR mission is to enable accelerated testing of advanced reactor fuels and materials required for advanced reactor technologies. The conceptual design of the 300 MWth sodium-cooled metallic-fueled pool-type fast reactor has been led by the U.S. National Laboratories in collaboration with General Electric-Hitachi and Bechtel National Inc. As part of the VTR authorization process by the DOE, it is necessary to identify the safety classification of structures, systems, and components (SSCs) to determine the proper design, surveillance, operation, and incident-reporting requirements. Since VTR is utilizing a risk-informed, performance-based authorization process based on the Licensing Modernization Project (LMP) described in NEI 18-04 [1], the criteria for SSC classification, which are reviewed here, includes both risk information from the probabilistic risk assessment (PRA) and prescriptive requirements.

Grabaskas, David↗
DOE OSTI2025

Cyber-Physical Tabletop Exercise for Small Modular Reactor Facilities

U.S. nuclear power facilities face increasing challenges in meeting dynamic security requirements caused by evolving and expanding threats while keeping costs reasonable to make nuclear energy competitive. This evolving threat landscape includes adversaries having offensive cyber capabilities to attack information technology (IT) systems and operation technology (OT) systems. These adversaries may have the ability to attack the physical protection system (PPS) networks with potential consequential impacts that could degrade the effectiveness of the PPS. These cyber attacks may also be used to attack the safety and operational systems used to operate and ensure the safety of the reactor. Additionally, adversaries may gain access to unmanned aerial systems (UAS) that may be used to provide reconnaissance and surveillance of the facility, provide information to the adversaries, and be equipped with kinetic capabilities such as explosives or weapons that can be used to directly attack the facility. The Department of Energy’s Office of Nuclear Energy’s Advanced Reactor Safeguards and Security (ARSS) program funded Sandia National Laboratories (SNL) and Idaho National Laboratory (INL) to develop a cyber-physical tabletop exercise (TTX). This exercise was conducted on a hypothetical small modular reactor (SMR) facility, and only considered a potential adversary cyber attack on the PPS to a physical attack on the hypothetical facility to achieve a radiological release. This cyber-physical TTX is meant to provide lessons learned to integrate the cyber security system design and the physical protection system (PPS) design to decrease design, operation, and maintenance costs as well as increase effectiveness for defending against design basis threat attacks at the facility. This TTX will also provide a framework and method for SMR and microreactor vendors to conduct their own cyber-physical TTX and gain impactful insights to improving the cyber and physical protection system design for their SMR or microreactor facility design.

42 ENGINEERING↗
DOE OSTI2020

Development and evaluation of a Novel RT‐PCR system for reliable and rapid SARS‐CoV ‐2 screening of blood donations

Abstract Background The ongoing outbreak of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has caused great global concerns. In contrast to SARS, some SARS‐CoV‐2–infected people can be asymptomatic or have only mild nonspecific symptoms. Furthermore, there is evidence that SARS‐CoV‐2 may be infectious during an asymptomatic incubation period. With the discovery that SARS‐CoV‐2 can be detected in plasma or serum, blood safety is worthy of consideration. Study Design and Methods We developed a nucleic acid test (NAT) screening system for SARS‐CoV‐2 targeting nucleocapsid protein (N) and open reading frame 1ab (ORF 1ab) gene that could screen 5076 samples every 24 hours. The 2019 novel coronavirus RNA standard was used to evaluate linearity of standard curves. Diagnostic sensitivity and reproducibility were evaluated using artificial SARS‐CoV‐2. Specificity was evaluated with 61 other respiratory pathogens. Diagnostic performance was evaluated by testing two sputum and nine oropharyngeal swab specimens. The reverse transcription polymerase chain reaction (RT‐PCR) assay was used to screen SARS‐CoV‐2 RNA in blood donor specimens collected during the outbreak of SARS‐CoV‐2 in Chengdu. Results Limits of detection of the SARS‐CoV‐2 RT‐PCR assay for N and ORF 1ab gene were 12.5 and 27.58 copies/mL, respectively. Intra‐assay and interassay for the SARS‐CoV‐2 RT‐PCR assay based on cycle threshold were acceptably low. No cross‐reactivity was observed with other respiratory virus and bacterial isolates. The overall agreement value between the SARS‐CoV‐2 RT‐PCR assay and clinical diagnostic results was 100%. A total of 16 287 blood specimens collected from blood donors during SARS‐CoV‐2 surveillance were tested negative. Conclusions A high‐throughput NAT screening system was developed for SARS‐CoV‐2 screening of blood donations during the outbreak of SARS‐CoV‐2.

Li, Meng↗
DOE OSTI2026

Quantifying Operational Drivers of Multimodal Biometric Verification in Aerial Surveillance

Multimodal biometric verification is increasingly applied across operational contexts ranging from close-range security cameras and building-mounted surveillance to long-range ground sensors and unmanned aerial system (UAS) imagery. Variations in acquisition conditions—such as image resolution, viewing geometry, and motion artifacts—pose significant challenges for cross-domain algorithmic generalization. This study evaluates two independent multimodal biometric verification systems developed under the Intelligence Advanced Research Projects Activity (IARPA) Biometric Recognition and Identification at Altitude and Range (BRIAR) program, comparing performance on close-range and aerial datasets. Close-range video served as a baseline to quantify the decline in verification performance on aerial footage. The dataset included six UAS platforms, spanning small quadcopters at 10m altitude to medium-sized fixed-wing aircraft at 360m. Mixed-effects logistic regression identified image resolution (head and body pixel counts), head height, sensor characteristics, and algorithm selection as primary determinants of verification success, whereas demographic attributes and mission gait were not significant predictors. Activity type and collection site influenced performance in close-range data but had negligible impact on UAS imagery. These results clarify modality-specific strengths and limitations and highlight opportunities to enhance cross-domain biometric verification.

Peluso, Alina [ORNL] (ORCID:0000000328950406)↗
DOE OSTI2020

Counter Unmanned Aircraft System (CUAS) Implementation Storyline

This report is an FY21 Deliverable for NA-21.1, International Nuclear Security, WBS 21.1.1.1.4 Counter Unmanned Aircraft Systems (CUAS), under C.1.4, Develop Suite of Engagement Materials and Tools for Country/Regional Teams. The responsibility for protecting nuclear assets is an immense challenge for governments. Policy changes based on geopolitics, instability of government regimes, and technological advances that facilitate theft of nuclear material all contribute to the enduring task of staying current with these and other threats. One of the recent threats to come along is the use of drones or Unmanned Aircraft Systems (UAS) to circumvent traditional Physical Security Systems. There are significant resources invested on physical protection systems for securing nuclear assets, but many of these systems can now be bypassed by simply flying over these measures intended to guard against ground attacks. In recent years the threat increased to hostile groups to attack or surveil due to advances and availability of UAS platforms. It is now more urgent to implement systems and procedures to counter the UAS threat. The United States (U.S.) federal government granted authority to the Department of Energy (DOE) to implement a Counter UAS to protect nuclear assets. This document provides a very practical and transparent view of the trials, tribulations and challenges we encountered while implementing the first Counter-Unmanned Aircraft System (CUAS) Program in the DOE at Los Alamos National Laboratory (LANL).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗