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All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Award ER25844: Minimizing System Noise Effects for Extreme-Scale Scientific Simulation Through Function Delegation

In software running on distributed computing clusters, time spent on communication between nodes in the cluster can be a significant portion of the overall computation time; background operating system tasks and other computational noise on the nodes of the system can have a significant impact on the amount of time this communication takes, especially on large systems. The research completed in this period has improved understanding of when such noise will have a significant impact. Specifically, it was demonstrated that not just noise on the nodes, but also noise on the network between nodes can have a significant impact on computation time. It was also demonstrated that noise patterns matter more than noise intensity: very regular noise can cause less disruption than lighter (on average) but less regular noise. It was also demonstrated that the effect of noise is more prominent as the speed of the network between nodes is increased. Furthermore, a tracing tool, Netgauge, was improved via our work, and a system simulator, LogGOPSim, was developed; they can be used by application developers to improve performance of their program and by system designers to mitigate the effects of noise by adjusting the noise characteristics of the operating system. Both have been made freely available as open source programs. In the course of developing these tools, we demonstrated weaknesses in existing methodologies for modeling communication, and we introduced a more detailed model, LogGOPS, for simulating systems. Not only were the deleterious effects of noise explored but we have also offered solutions. Our studies of simulations of system noise have led to specific recommendations on tuning systems to mitigate noise. We have also improved existing approaches to mitigating noise. Non-blocking collective communication avoids the effects of noise by letting communication continue simultaneously with computation (thus being non-blocking), so that the delays in communication introduced by noise have a smaller impact on overall computation time. Potentially, noise can be reduced much further by offloading communication tasks to a separate processing element than the operating system is using. We have improved our library LibNBC, which provides an implementation of non-blocking collectives, via this work. During this research, our proposal to include non-blocking collectives (which used LibNBC as a reference implementation) in the upcoming MPI-3 standard was accepted. As MPI is a ubiquitous and important standard for communication in parallel computing, this demonstrates a certain acceptance of the practicality and desirability of non-blocking collectives. Now that non-blocking collectives are a part of the standard we can expect to see optimized platform-specific implementations of non-blocking collectives. Also as part of this work we have also developed a language GOAL (Global Operation Assembly Language) that can be used as a starting point for defining languages to express optimized communication algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Classifying Cancer Pathology Reports with Hierarchical Self-Attention Networks

We introduce a deep learning architecture, hierarchical self-attention networks (HiSANs), designed for classifying pathology reports and show how its unique architecture leads to a new state-of-the-art in accuracy, faster training, and clear interpretability. We evaluate performance on a corpus of 374,899 pathology reports obtained from the National Cancer Institute's (NCI) Surveillance, Epidemiology, and End Results (SEER) program. Each pathology report is associated with five clinical classification tasks – site, laterality, behavior, histology, and grade. We compare the performance of the HiSAN against other machine learning and deep learning approaches commonly used on medical text data – Naive Bayes, logistic regression, convolutional neural networks, and hierarchical attention networks (the previous state-of-the-art). We show that HiSANs are superior to other machine learning and deep learning text classifiers in both accuracy and macro F-score across all five classification tasks. Compared to the previous state-of-the-art, hierarchical attention networks, HiSANs not only are an order of magnitude faster to train, but also achieve about 1% better relative accuracy and 5% better relative macro F-score.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

System Engineers and Decisions: It?s All about Knowledge

In order to guarantee that a system meets adequate levels of reliability and availability, system performances are continuously monitored and analyzed thanks to the technological advancements driving the Industry 4.0 revolution. An Industry 4.0 approach is typically based on advanced statistical, big data mining, machine learning, and internet-of-things methods designed to detect anomalies in the behavior of system, detect the most likely failure modes, and provide indications to system engineers on when maintenance activities should be performed before system performance are deemed unacceptable (which can be generated by diagnostic and prognostic methods). However, these analyses, which are designed to automatize and increase the efficacy of the system maintenance program, require large amount of data which can come in various forms: numeric, textual, images, sounds etc. Such data constitutes the historic knowledge benchmark to track system performances and support system engineer decisions. Here we claim that data is not sufficient to support this kind of analyses when applied to systems characterized by complex architectures and behaviors. Robust system engineer decisions require the ability to understand the system operational context that lies behind the observed data elements. In this respect, system models are in fact necessary to “put data in context” and capture relationships between data elements. Industry 4.0 methods require in fact contextual knowledge as a basis upon which hypotheses can be generated and assumptions tested. In our view, for complex systems, model-based system engineering (MBSE) models can afford this contextual knowledge, as they are typically used to describe systems architecture and dynamic behaviors. System knowledge is here intended as the blending of collected data and system architecture which takes the form of a “knowledge graph”. A knowledge graph is a database which consists of a large set of nodes (in our case an entity can be either a data or an MBSE element) which are linked to each other. The types of nodes and links follow a pre-defined topology, sometimes also refers as an ontology, that is designed to fit the actual decisions that needs to be performed. We show here how a knowledge graph can be defined to support system engineer maintenance decisions and how the same graph can be built based on system MBSE models and pre-processed data from numeric (through anomaly detections and diagnostic methods) and textual elements (through technical language processing TLP).

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite

The analysis of connected data is an increasingly important application in high-performance computing. Such analyses can reveal fraudulent patterns in financial transactions, optimize telecommunications networks, predict information flow in social networks, etc. However, the landscape of graph analytics is highly diverse. Graph algorithms stress processor architectures differently, and no one graph can represent all topologies. Consequently, no single approach or framework is expected to be optimal for all graph analytics problems. To help make sense of this diverse landscape, we evaluated four approaches to graph analytics: GraphBLAS, Galois, BGL17, GraphIt; and compare them against hand-tuned implementations that take advantage of hardware features on our test platform. Graph- BLAS formulates graph analytics as sparse linear algebra. Galois provides syntactic constructs for data parallelism over irregular data structures. BGL17 is a generic C++ template library for implementing graph algorithms. GraphIt provides a domain- specific language to describe and optimize graph algorithms. We use the GAP Benchmark Suite to establish baseline performance and guide the side-by-side evaluation of each framework. GAP consists of 30 tests: six graph analytics algorithms (breadth- first search, single-source shortest path, PageRank, betweenness centrality, connected components, and triangle counting) run on five graphs, each with different topological characteristics (e.g., high diameter, skewed degree distribution, high average degree). High-performance reference implementations are included for each benchmark algorithm. Because a graph can be loaded into memory a number of ways (e.g., flat file on disk, compressed sparse format, data frames, retrieved from SQL or NoSQL databases), our evaluation focused on computational performance rather than I/O. Our results show the relative strengths of each framework.

Graph algorithms, Benchmarking, shared-memory prog↗
DOE OSTI2016

As Permanent as Practicable: The reality of Permanent Markers - 16191

The regulatory requirements in the United States do not require any specific time frame for the duration of permanent marker systems to inform future generations of the presence of deep geologic nuclear waste repositories. The requirement is for markers to be 'as permanent as practicable'. For the Waste Isolation Pilot Plant in New Mexico, the U.S. Department of Energy chose a 10,000 year Passive Institutional Controls program goal. Passive Institutional Controls are to be designed prior to facility closure and implemented prior to the completion of the Active Institutional Controls program. Nuclear waste repositories across the world are actively developing marker and message systems, as required by their own regulations, for time frames either specified in those regulations or to be proposed to the regulator by the implementing organization. Time frames may be based upon the radioactive characteristics of the various isotopes being disposed of in the repository under consideration, or they may be based on some utility function that balances investment, practicability and risk. Scientifically, there are a number of time frames that make sense. However, an important determinant of effectiveness that has not been taken into consideration is the impact of the human connection, the receiver of the message. The major obstacle that the permanent marker systems need to overcome is the impact that humans will have over time. Historically, no monument has ever survived more than a few thousand years when humans come in contact with it. No matter what size of monument or topic the monument represents, humans have a history of destroying monuments beginning just a few generations after the monument's construction. The only way to ensure that a monument system can endure long time frames is to isolate it from humans. Eliminating contact with humans for whom the messages are meant defeats the very purpose of having an informative marker and message system. A more reasonable and historically supported time frame of 1,000 years would assure that no unreasonable cost would be incurred by current generations. Future generations could decide to continue maintaining the message, or not; and the likelihood of destruction of the markers by subsequent generations would be reduced since the knowledge of the markers and messages would have been transmitted within a more reasonable time frame over which language continuity, for example, would likely be manageable. Future preservation of the marker system and future human actions cannot be controlled, but the goal is to build a marker and message delivery system that reduces the likelihood of inadvertent future human disturbance of a deep geologic repository. This is the typical regulatory requirement on future information systems. Regulators who insist on an extremely long time frame for marker effectiveness should consider the historical realities of 'permanent' markers and monuments and propose a more reasonable time frame. Perhaps it would be more practicable to require 1,000 years for informing future generations and then allow them to determine what they wish to do to protect the future for another, perhaps similar, period of time. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Defending the Homeland: Growing Foreign Challenges to the U.S. Missile Defense Posture

The Office of the Secretary of Defense (OSD) for Policy requested that Lawrence Livermore National Laboratory conduct a Congressionally directed study on homeland missile defense, pursuant to Section 1692 of the fiscal year 2020 National Defense Authorization Act. In accordance with the statutory language, this study considers whether the security benefits obtained by deployment of homeland missile defenses of the United States are undermined or counterbalanced by adverse reactions of potential adversaries, and considers the effectiveness of homeland missile defense efforts of the United States to deter the development of ballistic missiles. Almost a half-century has elapsed since the United States and the Soviet Union signed the Anti-Ballistic Missile (ABM) Treaty, and almost two decades since the former withdrew. Since withdrawing, the United States has sought to develop and deploy a layered missile defense system to defend against regional threats to U.S. and allied interests abroad and to counter limited threats to the U.S. homeland. As such, missile defense supports key national defense policy objectives. Protecting the U.S. homeland, forces abroad, allies, and partners. Deterring attacks against the United States, its allies, and partners. Assuring allies an strengthening U.S. diplomatic activities in peacetime and crisis. We offer five key findings: 1. The primary benefit of the Ground-based Midcourse Defense (GMD) system is the protection it provides the U.S. homeland against a limited but evolving rogue-state missile threat. While this system has never been tested in combat, it appears thus far to have effectively paced North Korea’s development and deployment of intercontinental ballistic missiles (ICBMs). In the absence of such a defensive capability, the United States would likely have been more heavily exposed to North Korean actions, would have operated at a much higher-risk posture, and would have had less negotiating room with which to navigate coercive tactics and crises. Its allies would have been more concerned about U.S. willingness in time of crisis and war to run the risks of protecting them. The GMD system also serves as a hedge against Iranian breakout. 2. Potential adversaries continue to develop long-range ballistic missiles despite deployment of a U.S. homeland missile defense system. This includes both rogue states and major power rivals whose long-range missile programs predated the deployment of U.S. missile defenses. While North Korea has continued its long-range missile developments and achieved an intercontinental capability, Iran has not yet reached this threshold. The broader proliferation of long-range missiles anticipated in the late 1990s has not materialized. 3. While Russia has used the existence of a U.S. homeland missile defense system as a justification for its substantial and continuing weapon modernization program, neither Russian force modernization nor the limited U.S. homeland missile defense system has altered the strategic balance. Russia has long considered U.S. missile defenses—both theater and homeland—as directed against its strategic forces and as a capability that could rapidly advance, thereby eroding Russian confidence in its nuclear deterrent. Russia’s political and military actions appear excessive and negatively impact areas such as arms control, but they do not undermine the primary benefit of the U.S. system cited in Key Finding 1. 4. China’s expansion and diversification of nuclear and missile forces has been influenced by its concerns about U.S. homeland missile defense, but those concerns are only one of many factors in China’s force planning. Although China’s actions to preserve and expand its assured retaliation prospects have not fundamentally altered the strategic balance, its buildup and lack of transparency about its force modernization goals are troubling. Taken together, the aggregate pattern of China’s modernization activities over the past two decades strongly suggests a concerted effort to develop a modern military force commensurate with its intended geopolitical status. Whatever China’s legacy concerns over the survivability of its strategic nuclear forces, its ability to overwhelm the GMD system appears intact today and will be further strengthened in the years ahead as it continues its long-term modernization program. China’s political and military actions negatively affect U.S. security interests but do not undermine the primary benefit of the U.S. system cited in Key Finding 1. 5. The basic finding that benefits have not so far been undermined by adverse reactions is a function of circumstances that are increasingly in flux. The existing GMD-centered system is under increasing pressure from the pace and scope of North Korean missile deployments. The proposed “layered” system seeks to mitigate this impending capability gap in the near term and to complement future capabilities, such as the Next Generation Interceptor, when they come online. Given the pace of U.S. missile defense developments since 2000, it is possible that adversary advances in capability will outpace the U.S. system’s ability to adapt. Additionally, because this layered system is in principle more readily scaled, it will almost certainly be viewed skeptically by China and Russia. In a context of growing great-power security competition, the Department of Defense (DoD) should consider undertaking a broader net assessment of the U.S., Russian, and Chinese force balance.

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

Demonstration and Evaluation of Explainable and Trustworthy Predictive Technology for Condition-based Maintenance

The domestic nuclear power plant (NPP) fleet has historically relied on labor-intensive and time-consuming predictive maintenance (PdM) programs, thus driving up operation and maintenance (O&M) costs to achieve high-capacity factors. Artificial intelligence (AI) and machine-learning (ML) can help simplify complex problems such as diagnosing equipment degradation to enable more effective decision-making efforts. The benefits of AI will be felt through more efficient plant O&M, improved work processes, and better integration of people and technology. Together, these benefits hold the promise to make nuclear power more sustainable by reducing O&M costs while improving employee engagement. While AI and ML technologies hold significant promise for the nuclear industry, there are challenges or barriers to their adoption. Explainability and trustworthiness of AI are two salient challenges that need to be addressed for wider deployment of these technologies in NPPs. This research focuses specifically on addressing the explainability and trustworthiness of AI technologies to advance the human, technical, and organization (HTO) readiness levels in adopting a risk-informed PdM strategy at commercial NPPs. In addition, this approach can be adapted to enhance the acceptability of AI in other nuclear applications with a few application-specific modifications. The technical approach ensuring wider adoption of AI technologies was developed by Idaho National Laboratory (INL)—in collaboration with Public Service Enterprise Group (PSEG), Nuclear, LLC—by utilizing the circulating water system (CWS) at two PSEG-owned plant sites for demonstration. Focused user studies were performed in collaboration with subject matter experts (SMEs) from PSEG and other nuclear domains to enhance human and organization readiness by building trust in AI-informed technologies. VIsualization for PrEdictive maintenance Recommendation (VIPER)—a Battelle Energy Alliance, LLC, copyrighted software—was developed and expanded to provide a user-centric visualization by incorporating inputs from the collaborating utility, human factors engineering guidelines, and data analysts. The VIPER software enables users, who may be unfamiliar with ML in general, to be interactively engaged by asking technical questions about PdM, work orders, diagnosis results and their confidence levels, the kind of data being used, and the types of ML algorithms employed. This interactive engagement enhances explainability and builds trust. One of the enabling accomplishments was the integration of large language models (LLMs), both text-based and vision-based, in the VIPER software.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

Phase 1 Development Report for the SESSA Toolkit.

The Site Exploitation System for Situational Awareness ( SESSA ) tool kit , developed by Sandia National Laboratories (SNL) , is a comprehensive de cision support system for crime scene data acquisition and Sensitive Site Exploitation (SSE). SESSA is an outgrowth of another SNL developed decision support system , the Building R estoration Operations Optimization Model (BROOM), a hardware/software solution for data acquisition, data management, and data analysis. SESSA was designed to meet forensic crime scene needs as defined by the DoD's Military Criminal Investigation Organiza tion (MCIO) . SESSA is a very comprehensive toolki t with a considerable amount of database information managed through a Microsoft SQL (Structured Query Language) database engine, a Geographical Information System (GIS) engine that provides comprehensive m apping capabilities, as well as a an intuitive Graphical User Interface (GUI) . An electronic sketch pad module is included. The system also has the ability to efficiently generate necessary forms for forensic crime scene investigations (e.g., evidence submittal, laboratory requests, and scene notes). SESSA allows the user to capture photos on site, and can read and generate ba rcode labels that limit transcription errors. SESSA runs on PC computers running Windows 7, but is optimized for touch - screen tablet computers running Windows for ease of use at crime scenes and on SSE deployments. A prototype system for 3 - dimensional (3 D) mapping and measur e ments was also developed to complement the SESSA software. The mapping system employs a visual/ depth sensor that captures data to create 3D visualizations of an interior space and to make distance measurements with centimeter - level a ccuracy. Output of this 3D Model Builder module provides a virtual 3D %22walk - through%22 of a crime scene. The 3D mapping system is much less expensive and easier to use than competitive systems. This document covers the basic installation and operation of th e SESSA tool kit in order to give the user enough information to start using the tool kit . SESSA is currently a prototype system and this documentation covers the initial release of the tool kit . Funding for SESSA was provided by the Department of Defense (D oD), Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) Rapid Fielding (RF) organization. The project was managed by the Defense Forensic Science Center (DFSC) , formerly known as the U.S. Army Criminal Investigation Laboratory (USACIL) . ACKNOWLEDGEMENTS The authors wish to acknowledge the funding support for the development of the Site Exploitation System for Situational Awareness (SESSA) toolkit from the Department of Defense (DoD), Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) Rapid Fielding (RF) organization. The project was managed by the Defense Forensic Science Center (DFSC) , formerly known as the U.S. Army Criminal Investigation Laboratory (USACIL). Special thanks to Mr. Garold Warner, of DFSC, who served as the Project Manager. Individuals that worked on the design, functional attributes, algorithm development, system arc hitecture, and software programming include: Robert Knowlton, Brad Melton, Robert Anderson, and Wendy Amai.

Knowlton, Robert G.↗
DOE OSTI2015

Approximating Dose and Risk for Contaminants in Groundwater from the Underground Nuclear Test Areas of the Nevada National Security Site (NNSS)

As part of the Environmental Management Program at the Nevada National Security Site (NNSS), the Underground Test Area (UGTA) Activity investigates the potential impacts of radionuclides that were introduced into groundwater from the underground nuclear tests conducted near or below the NNSS water table between 1951 and 1992. Groundwater models are being used to simulate contaminant transport and forecast contaminant boundaries that encompass areas where the groundwater has a five percent or greater probability of containing contaminants above the Safe Drinking Water Act Maximum Contaminant Levels (SDWA MCLs) at any time during the next 1,000 years. Transport modeling conducted for the Frenchman Flat Corrective Action Unit (CAU) at the NNSS identified the beta/photon-emitting radionuclides tritium (3H), carbon-14 ( 14 C), chlorine-36 ( 36 Cl), technetium-99 ( 99 Tc), and iodine-129 ( 129 I) as having the greatest influence in defining the farthest extent of the modeled CAU contaminant boundary. These same radionuclides are assumed here as the contaminants of concern (COCs) for all underground nuclear tests at the NNSS because models are not yet complete for the other CAUs. Potential public exposure to the COCs will only occur and be of concern if the COCs migrate into the groundwater beneath public or private lands at levels that exceed either individual SDWA MCLs or dose and risk limits. Groundwater flow directions strongly suggest that any contaminant boundary predicted by contaminant fate and transport modeling to overlap public or private lands is more likely to occur to the west and/or southwest of the NNSS and the adjacent Nevada Test and Training Range (NTTR). Well-established, rural communities exist in these directions. Estimates of representative activity concentrations at the applicable SDWA MCL were developed for the five COCs. It is assumed that these COC concentrations may collectively occur at some public or private location in the future, but that situation does not exist today. These representative activity concentrations are evaluated with respect to conforming collectively to a modern annual committed effective dose (CED) and lifetime excess cancer morbidity risk for a hypothetical reasonably maximally exposed individual (RMEI). This approach goes beyond the SDWA MCL focus of the contaminant boundary because individual COC concentrations may comply with the SDWA MCL but not collectively meet the modern health-protection metrics and the SDWA language, especially if future modeling studies or monitoring activities show multiple radionuclides from different SDWA MCL categories to be COCs. For the drinking water exposure pathway alone, the annual committed effective dose (CED) for the RMEI from all five COCs that are collectively at estimated activity concentrations equal to their SDWA MCL is well below the U.S. Department of Energy health-protective CED limit of 100 millirem (mrem)/yr. This is consistent using both the NNSS unclassified, 1992 decay-corrected radionuclide atom inventory and the atom inventory based on radionuclides measured in groundwater obtained from the ALMENDRO cavity in 2009 to calculate the SDWA MCL activity concentrations in groundwater. The RMEI’s total lifetime excess cancer risk from the drinking water exposure pathway for both atom inventories is within the range of 1 × 10 -4 to ≤ 1 × 10 -6 , which is considered health protective according to modern SDWA MCL regulatory language. The biosphere exposure pathways are drinking water, garden produce, animal products, inadvertent soil ingestion, and indoor and outdoor air inhalation. The exposure parameters for communities west and southwest of the NNSS were developed when the Yucca Mountain high-level, nuclear-waste disposal facility was under consideration. For all biosphere exposure pathways, calculations of the annual CED and lifetime excess cancer morbidity risk for the RMEI revealed that: 1) The annual CED is well within health-protective guidance (<< 100 mrem CED /yr) for the COC activity concentrations at the SDWA MCL, regardless of the atom inventory used. 2) The calculated 70-year lifetime excess cancer morbidity risk (6 x 10 -5 ) is within the health-protective range when the five COC activity concentrations are derived using the NNSS 1992 atom inventory, but it is at the upper limit of the acceptable range (1 x 10 -4 ) using the ALMENDRO 2009 atom inventory. 3) Tritium (3H) is the principal COC for producing annual dose and lifetime excess cancer risk, regardless of the atom inventory used. 4) Overall, the drinking water ingestion pathway is the dominant exposure pathway contributing to the total annual CED and lifetime excess cancer risk, followed by eating locally grown produce and animal products. 5) When tritium completely decays (after about 100 years), the RMEI’s lifetime risk will fall well within the health-protective range (i.e., 1 × 10-4 to ≤ 1 × 10 -6 ) and 36Cl will then become the most important contributor to the RMEI’s total annual CED and lifetime excess cancer morbidity risk from eating local produce and animal products. In the event that radionuclide concentrations begin to approach SDWA MCLs, a reasonable risk-management strategy for keeping lifetime risk more in compliance with regulatory guidance would be to use local sources of groundwater that are below SDWA MCLs or to limit the consumption of local produce and animal products that have ingested COC-contaminated groundwater. The viability of the latter strategy increases where the annual CED due to 36Cl approaches that of 3H.The dose and risk values calculated here for an RMEI are specific to the assumption that the five COCs occur in groundwater beneath public or private lands at concentrations that are collectively at the SDWA MCL. Currently, these COCs are essentially absent from groundwater beneath public or private lands beyond the boundaries of the NNSS and NTTR other than at very low, naturally occurring concentrations. The analyses presented here can be readily applied to determine dose and risk for COC concentrations actually measured in future monitoring samples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Deep PDF parsing to extract features for detecting embedded malware.

The number of PDF files with embedded malicious code has risen significantly in the past few years. This is due to the portability of the file format, the ways Adobe Reader recovers from corrupt PDF files, the addition of many multimedia and scripting extensions to the file format, and many format properties the malware author may use to disguise the presence of malware. Current research focuses on executable, MS Office, and HTML formats. In this paper, several features and properties of PDF Files are identified. Features are extracted using an instrumented open source PDF viewer. The feature descriptions of benign and malicious PDFs can be used to construct a machine learning model for detecting possible malware in future PDF files. The detection rate of PDF malware by current antivirus software is very low. A PDF file is easy to edit and manipulate because it is a text format, providing a low barrier to malware authors. Analyzing PDF files for malware is nonetheless difficult because of (a) the complexity of the formatting language, (b) the parsing idiosyncrasies in Adobe Reader, and (c) undocumented correction techniques employed in Adobe Reader. In May 2011, Esparza demonstrated that PDF malware could be hidden from 42 of 43 antivirus packages by combining multiple obfuscation techniques [4]. One reason current antivirus software fails is the ease of varying byte sequences in PDF malware, thereby rendering conventional signature-based virus detection useless. The compression and encryption functions produce sequences of bytes that are each functions of multiple input bytes. As a result, padding the malware payload with some whitespace before compression/encryption can change many of the bytes in the final payload. In this study we analyzed a corpus of 2591 benign and 87 malicious PDF files. While this corpus is admittedly small, it allowed us to test a system for collecting indicators of embedded PDF malware. We will call these indicators features throughout the rest of this report. The features are extracted using an instrumented PDF viewer, and are the inputs to a prediction model that scores the likelihood of a PDF file containing malware. The prediction model is constructed from a sample of labeled data by a machine learning algorithm (specifically, decision tree ensemble learning). Preliminary experiments show that the model is able to detect half of the PDF malware in the corpus with zero false alarms. We conclude the report with suggestions for extending this work to detect a greater variety of PDF malware.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗
DOE OSTI2018

Prototype System for Detecting Interactions between Current Plant Configuration States and Component Manipulations Directed by In-Use Procedures

This research effort is a part of the Light Water Reactor Sustainability (LWRS) Program, which is a research and development (R&D) program sponsored by the Department of Energy. The LWRS Program is performed in close collaboration with industry R&D programs that provide the technical foundations for licensing and managing the long term, safe, and economical operation of current nuclear power plants (NPPs). The LWRS Program serves to help the United States (U.S.) nuclear industry adopt new technologies and engineering solutions that facilitate the continued safe operation of these NPPs and extension of their current operating licenses. The Outage Risk Management Improvement Pilot Project seeks to improve the management of nuclear power plant outages through the development of tools to assist in evaluating pending activities against requirements to detect undesired interactions. Significant efforts are expended to manage the nuclear risk of an outage. The utilities conduct pre outage risk assessments, based on a very detailed review of the outage schedule, to identify where combinations of outage work and equipment out of service would result in degraded conditions with respect to nuclear safety or regulatory compliance. Probabilistic risk assessment studies are conducted to quantify the incremental core damage frequency as a result of the outage activities and system unavailability. These studies are usually presented to site and fleet management, the site plant operational review committee, and the NPP’s independent Nuclear Safety Review Board for concurrence that the outage is planned safely and that reasonable measures have been taken to reduce the added risk of conducting the outage. During the outage, the plant configuration is monitored continuously to ensure that it conforms to the approved safety plan. Deviations must be assessed and approved by management committees and, in some cases, the plant operational review committee. In virtually all outage meetings and job briefings, the current nuclear safety status of the plant is communicated, including information on the specific equipment that is being relied on to meet the requirements of the nuclear safety plan. In addition, Operations and the Outage organizations implement several layers of physical and administrative barriers to prevent unintended interaction with the systems and equipment credited for nuclear safety. In spite of all these efforts, nuclear safety challenges still occur too frequently in outages. While some of these are due to failures of equipment credited for safety, the majority occur because of human error. These typically involve some form of interaction between work activities and plant configuration changes. Some of them are very subtle and are extremely challenging to detect in advance. Nevertheless, they are not acceptable and represent clear opportunities to improve nuclear safety during outages. This project will develop tools and strategies to minimize these interactions. This report describes a prototype tool designed to support plant personnel in controlling work during NPP outages to prevent unintended interactions. A software application was created to manage and display important configuration information and utilize natural language processing to access the impacts of upcoming procedures and work orders. Initial industry feedback is also presented.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Epi Archive: automated data collection of notifiable disease data

LANL has built a software program that automatically collects global notifiable disease data—particularly data stored in files—and makes it available and shareable within the Biosurveillance Ecosystem(BSVE) as a new data source. This will improve the prediction and early warning of disease events and other applications. Most countries do not report national notifiable disease data in a machine-readable format. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health as exemplified by the Biosurveillance Ecosystem(BSVE).While most nations do likely store their data in a machine-readable format, the governments are often hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational issues. For example, an attempt by LANL to obtain a weekly version of openly available monthly data, reported by the Australian government, resulted in an onerous bureaucratic reply. The obstacles to obtaining data included: paperwork to request data from each of the Australian states and territories, a long delay to obtain data (up to 3 months) and extensive limitations on the data’s use that prohibit collaboration and sharing. This type of experience when attempting to contact public health departments or ministries of health for data is not uncommon. A survey conducted by LANL of notifiable disease data reporting in 52 countries identified only 10 as being machine-readable and 42 being reported in pdf files on a regular basis. Within the 42 nations that report in pdf files, 32 report in a structured, tabular format and10 in a non-structured way. As a result, LANL has developed a tool-Epi Archive (formerly known as EPIC)-to automatically and continuously collect global notifiable disease data and make it readily accessible. We conducted a survey of the national notifiable disease reporting systems notating how the data is reported in two important dimensions: date standards and case definitions. The development of software to regularly ingests notifiable disease data frand makes this data available involved four main steps scraping, extracting, parsing and persisting. For scraping: we would examine website designs and determine reporting mechanisms for each country/website as well as what varies across the reporting mechanisms. We then designed and wrote code to automate the downloading of report pdf files, for each country. We stored report pdfs along with appropriate metadata for extracting and parsing. For extracting: we developed software that can extract notifiable disease data presented in tabular form from a pdf file. We combined the methodology of figure placement detection with the in-house developed table extraction and annotation heuristics. For parsing: we determined what to extract from each pdf dataset from the survey conducted. We then parsed the extracted data into uniform data structures correctly accommodating the dimensions surveyed and the various human languages. This task involved ingesting notifiable disease data in many disparate formats extracted from pdf files and coalescing the data into a standardized format. For persisting: We then store the data in the Epi Archive PostgreSQL database and make it available through the BSVE. The EpiArchive tool currently contains subnational notifiable disease data from 10 nations. When a user accesses the EpiArchive site, they are prompted with four fields: country, region, disease, and date duration. These fields allow the user to specify the location(down to the state level), the disease of interest, and the duration of interest. Upon form submission, a time series is generated from the users’ specifications. The generated time series can then be downloaded into a csv file if a user is interested in performing personal analysis. Additionally, the data from EpiArchive can be reached through an API. LANL as part of a currently funded DTRA effort so that it will automatically and continuously collect global notifiable disease data—particularly data stored in pdf files—and make it available and shareable within the Biosurveillance Ecosystem (BSVE) as a new data source. This will provide data to analytics and users that will improve the prediction and early warning of disease events and other applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Coeur d’Alene Tribe Benewah Market Energy Efficiency Project Final Technical Report

The Coeur d’Alene Reservation has been the home of the Coeur d’Alene Tribe since time immemorial and it is fitting that the Tribe’s name in the Coeur d’Alene language is schitsu’umsh, “the ones who were found here.” The Reservation is located in northern Idaho, is approximately 345,000 acres and is comprised of forest land, agricultural land, several streams, Coeur d’Alene Lake and the St. Joe River and a small amount of developed land. The project area was conducted within the boundaries of the Coeur d’Alene Reservation. The population of the Reservation is 6,760 (2010 Census). Currently, there are approximately 2,463 enrolled Coeur d’Alene Tribal members (Coeur d’Alene Tribe Enrollment 2016). The Benewah Market is a Tribally-owned and operated facility located at 1111 B St. Plummer, ID 83851. The Benewah Market is an approximately 23,500 square foot single-story structure. The majority of the building is occupied by a grocery store with a full meat department, deli, and bakery. Approximately 20% of the floor area at the northeast corner is occupied by an Ace Hardware retailer. The largest part of the building is approximately 17,000 square feet, is separately metered and houses the grocery store which was constructed in 1984. The market is the largest full service market serving the Coeur d’Alene Reservation and is the only full service market in a 35-mile radius. The Tribe has benefited greatly from the Benewah Market Energy Efficiency Project and will continue to do so for many years: The health and safety of the food has been improved greatly now that the refrigeration and freezer cases are at a constant and safe temperature on a monitoring and alarm system. There is no longer a thaw and freeze cycle that allows fluctuations in temperature. If the power goes out, there is an immediate alarm and contact so that time may be tracked and food kept safe during an outage. The overall annual energy use in the Benewah Market has dropped by 22.9% -Energy costs for the Market decreased by an estimated 11,620 dollars in one year due to this project. The Tribe has seen an increase in the cost of energy from Plummer Power and this was offset by the reduction in energy consumed. This estimate assumes that the Tribe would have consumed the same amount of energy as the prior year. -Maintenance costs are estimated to have decreased by $10,000 in just the one year since installation in contract repair and maintenance. The Tribe estimates that it has saved 24,000 dollars over a one-year time period in labor costs to maintain the older system. Due to having a more efficient store, with safer, more attractive display of food and lower energy and maintenance costs, the store is able to be more viable economically. The store has increased its sales and has been able to pass along operations and maintenance savings to its customers and employees. The Tribe hosted a ribbon-cutting ceremony on February 28, 2017 at the Benewah Market with Chris Deschene, then Office of Indian Energy Director, as well as representatives from the Coeur d’Alene Tribe and Bonneville Power Administration. While the ribbon-cutting ceremony was going on, the Tribe’s media outlets covered the ceremony and placed information about the project on the Tribe’s Facebook page on two separate occasions. The Coeur d’Alene Tribe’s Natural Resources Department and the Tribe’s Development Corporation are thankful for the opportunity that the Benewah Market Energy Efficiency Project has afforded the Coeur d’Alene Tribal community. Without the U.S. Department of Energy’s Indian Energy Program funding and its dedicated staff, this project would not have been completed. This has been a lot of work for all parties involved but has provided benefits to thousands of people for many years to come.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗