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Analytics for Investigation of Disease Outbreaks: Web-Based Analytics Facilitating Situational Awareness in Unfolding Disease Outbreaks
Background: Information from historical infectious disease outbreaks provides real-world data about outbreaks and their impacts on affected populations. These data can be used to develop a picture of an unfolding outbreak in its early stages, when incoming information is sparse and isolated, to identify effective control measures and guide their implementation. Objective: This study aimed to develop a publicly accessible Web-based visual analytic called Analytics for the Investigation of Disease Outbreaks (AIDO) that uses historical disease outbreak information for decision support and situational awareness of an unfolding outbreak. Methods: We developed an algorithm to allow the matching of unfolding outbreak data to a representative library of historical outbreaks. This process provides epidemiological clues that facilitate a user’s understanding of an unfolding outbreak and facilitates informed decisions about mitigation actions. Disease-specific properties to build a complete picture of the unfolding event were identified through a data-driven approach. A method of analogs approach was used to develop a short-term forecasting feature in the analytic. The 4 major steps involved in developing this tool were (1) collection of historic outbreak data and preparation of the representative library, (2) development of AIDO algorithms, (3) development of user interface and associated visuals, and (4) verification and validation. Results: The tool currently includes representative historical outbreaks for 39 infectious diseases with over 600 diverse outbreaks. We identified 27 different properties categorized into 3 broad domains (population, location, and disease) that were used to evaluate outbreaks across all diseases for their effect on case count and duration of an outbreak. Statistical analyses revealed disease-specific properties from this set that were included in the disease-specific similarity algorithm. Although there were some similarities across diseases, we found that statistically important properties tend to vary, even between similar diseases. This may be because of our emphasis on including diverse representative outbreak presentations in our libraries. AIDO algorithm evaluations (similarity algorithm and short-term forecasting) were conducted using 4 case studies and we have shown details for the Q fever outbreak in Bilbao, Spain (2014), using data from the early stages of the outbreak. Using data from only the initial 2 weeks, AIDO identified historical outbreaks that were very similar in terms of their epidemiological picture (case count, duration, source of exposure, and urban setting). The short-term forecasting algorithm accurately predicted case count and duration for the unfolding outbreak. Conclusions: AIDO is a decision support tool that facilitates increased situational awareness during an unfolding outbreak and enables informed decisions on mitigation strategies. AIDO analytics are available to epidemiologists across the globe with access to internet, at no cost. In this study, we presented a new approach to applying historical outbreak data to provide actionable information during the early stages of an unfolding infectious disease outbreak.
Characterization of catalytic fast pyrolysis oils: The importance of solvent selection for analytical method development
Not Available
Analytical Expression for DC Link Capacitor Current in a Cascaded H-Bridge Multi-Level Active Front-End Converter
Medium-voltage grid-tied systems often use a cascaded H-bridge multi-level active front-end. In this converter, dc link bus capacitors play an important role in stabilizing the converter and enabling both active and reactive power injections. The present work provides analytical expressions for the capacitor current, which are essential for optimizing system design (especially capacitor size vs. lifetime). Then, the expression is incorporated into the grid connected bidirectional power system model. Consequently, this work contributes to the guiding principles to choose accurate dc link capacitor ratings against grid-side power delivery requirements. The analytical results have been validated with detailed simulations and hardware results.
A Big Data Analytics Framework for HPC Log Data: Three Case Studies Using the Titan Supercomputer Log
Reliability, availability and serviceability (RAS) logs of high performance computing (HPC) resources, when closely investigated in spatial and temporal dimensions, can provide invaluable information regarding system status, performance, and resource utilization. These data are often generated from multiple logging systems and sensors that cover many components of the system. The analysis of these data for finding persistent temporal and spatial insights faces two main difficulties: the volume of RAS logs makes manual inspection difficult and the unstructured nature and unique properties of log data produced by each subsystem adds another dimension of difficulty in identifying implicit correlation among recorded events. To address these issues, we recently developed a multi-user Big Data analytics framework for HPC log data at Oak Ridge National Laboratory (ORNL). This paper introduces three in-progress data analytics projects that leverage this framework to assess system status, mine event patterns, and study correlations between user applications and system events. We describe the motivation of each project and detail their workflows using three years of log data collected from ORNL's Titan supercomputer.
Regression-Based Analytics for Response Dynamics of SDN Solutions and Components
We consider Software-Defined Network (SDN) solutions that dynamically setup and teardown connections, and also their response dynamics of connectivity and TCP throughput. There is a wide variety of choices for controllers, switches, andsoftware modules, and objective analytics of measurements are needed to compare the response dynamics of solutions based on their combinations. Throughput and ping measurements during connection changes contain significant statistical variations due to the complexities of controllers, northbound scripts, and network devices. We propose analytical methods to estimate response regression functions, which provide a rigorous and objective comparison of different SDN solutions and their components, namely, controllers, switches, and OpenFlow versions. We apply this approach in two scenarios: (a) switching of long-haul connections emulated in hardware by ANUE devices over a testbed consisting of HP and Cisco switches, and (b) multi-site science infrastructure emulated using VMs and Mininet. The results provide useful practical insights including: (i) the dpctl method responds seconds faster than the OpenDayLight (ODL) method on average under OpenFlow 1.0, but performs similar to ODL under OpenFlow 1.3, and (ii) the ping response of dpctl is about 0.6 sec faster than ODL for the second scenario.
Analytic Considerations and Design Basis for the IEEE Distribution Test Feeders
One of the greatest challenges for the analysis of distribution systems is the high level of diversity across the world. For nearly 20 years the Test Feeder Working Group of the Distribution System Analysis Subcommittee has been developing distribution test feeders. The purpose of these test feeders is to provide openly-available models of distribution systems that reflect the diversity in systems and the analytic challenges they present. Because of their utility and accessibility, the test feeders have been used for a wide range of research, some of which they were not originally intended to cover. The purpose of this paper is to provide an overview of the variety of existing distribution systems, and to clarify the specific analytic challenges that each test feeder was originally designed to examine. Additionally, the paper will provide guidance on which feeders are best suited for various types of analysis. The purpose of this paper is to provide the original intent of the Working Group and to inform researchers so that they may make an informed decision on which of the test feeders are most appropriate for their work.
Synchrotron X-ray Analytical Techniques for Studying Materials Electrochemistry in Rechargeable Batteries
Abstract not provided
Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Visual Analytic Judgments
Scientists often use specific data analysis and presentation methods familiar within their domain. But does high familiarity drive better analytical judgment? This question is especially relevant when familiar methods themselves can have shortcomings: many visualizations used conventionally for scientific data analysis and presentation do not follow established best practices. This necessitates new methods that might be unfamiliar yet prove to be more effective. But there is little empirical understanding of the relationships between scientists’ subjective impressions about familiar and unfamiliar visualizations and objective measures of their visual analytic judgments. To address this gap and to study these factors, we focus on visualizations used for comparison of climate model performance. We report on a comprehensive survey-based user study with 47 climate scientists and present an analysis of : i) relationships among scientists’ familiarity, their perceived lev- els of comfort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.
237 Np analytical method using 239 Np tracers and application to a contaminated nuclear disposal facility
Environmental 237Np analyses are challenged by low 237Np concentrations and lack of an available yield tracer; we report a rapid, inexpensive 237Np analytical approach employing the short lived 239Np (t1/2 = 2.3 days) as a chemical yield tracer followed by 237Np quantification using inductively coupled plasma-mass spectrometry. 239Np tracer is obtained via separation from a 243Am stock solution and standardized using gamma spectrometry immediately prior to sample processing. Rapid digestions using a commercial, 900 watt “Walmart” microwave and Parr microwave vessels result in 99.8 ± 0.1% digestion yields, while chromatographic separations enable Np/U separation factors on the order of 106 and total Np yields of 95 ± 4% (2σ). Application of this method to legacy soil samples surrounding a radioactive disposal facility (the Subsurface Disposal Area at Idaho National Laboratory) reveal the presence of low level 237Np contamination within 600 meters of this site, with maximum 237Np concentrations on the order of 103 times greater than nuclear weapons testing fallout levels.
Numerical simulation of the hot-tail runaway electron production mechanism using CQL3D and comparison with Smith–Verwichte analytical model
Abstract The hot-tail mechanism of runaway electron (RE) production (Harvey et al 2000 Phys. Plasmas 7 4590) is the primary source of RE in the case of rapidly cooling tokamak plasma. Quantifying this mechanism is very important as it can provide most of the post-thermal-quench (TQ) current, or a seed current for the secondary source of RE through the avalanche mechanism. An analytic model which omits pitch-angle scattering is often used in literature for estimating the hot-tail RE density (Smith and Verwichte 2008 Phys. Plasmas 15 072502). In the present study, we use the CQL3D bounce-averaged Fokker–Planck code (Harvey and McCoy 1992 Proc. IAEA Technical Committee Meeting on Advances in Simulation and Modeling of Thermonuclear Plasmas p 527) to test the limits of validity of the model. In particular, we examine the cases of Z = 1 and Z = 18 ions, for sets of different initial temperature, density, electric field and the characteristic time of temperature decay. We show that for Z = 1 plasma, the ratio of RE density computed by CQL3D to that estimated from the model is within 0.6–6.0 in studied cases. For the Z = 18 case, this factor is systematically a much smaller number, typically 0.02–0.6. We suggest a simple correction to the model that narrows down the range of this ratio to 0.3–3.8 in all of the cases, including Z = 1 and Z = 18 plasmas.
A visual analytics system for optimizing the performance of large-scale networks in supercomputing systems
Not Available
Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations
Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve efficiency and throughput. Because of the complexity and scale of systems and workflows and the need for low-latency response to address dynamic circumstances, automated feedback and response have the potential to be more effective than current human-in-the-loop approaches which are laborious and error prone. Progress has been limited, however, by factors such as the lack of infrastructure and feedback hooks, and successful deployment is often site- and case-specific. In this position paper we report on the outcomes and plans from a recent Dagstuhl Seminar, seeking to carve a path for community progress in the development of autonomous feedback loops for MODA, based on the established formalism of similar (MAPE-K) loops in autonomous computing and self-adaptive systems. By defining and developing such loops for significant cases experienced across HPC sites, we seek to extract commonalities and develop conventions that will facilitate interoperability and interchangeability with system hardware, software, and applications across different sites, and will motivate vendors and others to provide telemetry interfaces and feedback hooks to enable community development and pervasive deployment of MODA autonomy loops.
LLNL ES&H Analytical Services and Instrumentation Analytical Laboratory (ALAB) (CY2022 Management Review Report)
"An annual review shall be conducted of the analytical activities to ensure continuing suitability, adequacy, and effectiveness." (ALAB-01 Rev 6 ALQAP section 6.11.2) "The laboratory management shall review its management system at planned intervals, in order to ensure its continuing suitability, adequacy and effectiveness..."(ISO/IEC 17025:2017 Section 8.9.1) "In accordance with a predetermined schedule and procedure, the laboratory's top management shall periodically conduct a review of the laboratory's management system and testing and/or calibration activities to ensure their continuing suitability and effectiveness, and to introduce necessary changes or improvements. "(TNI Standard EL-V1M2-2016-Rev2.1:Quality Systems General Requirements)
A novel approach to evaluate soil heat flux calculation: An analytical review of nine methods
Abstract There are no direct methods to evaluate calculated soil heat flux (SHF) at the surface ( G 0 ). Instead, validation and cross evaluation of methods for calculating G 0 usually rely on the conventional calorimetric method or the degree of the surface energy balance closure. However, there is uncertainty in the calorimetric method itself, and factors apart from G 0 also contribute to nonclosure of the surface energy balance. Here we used a novel approach to evaluate nine different methods for calculating SHF, including the calorimetric method and methods based on analytical solutions of the heat diffusion equation. The SHF ( G z ) measured by a self‐calibrating SHF plate at a depth of z = 5 cm below the surface (hereafter G m _5 cm ) was deployed as a reference. Each SHF calculation method was assessed by comparing the calculated G z at the same depth (hereafter G c _5 cm ) with G m _5 cm . The calorimetric method and simple measurement method performed best in determining G c _5 cm but still underestimated G m _5 cm by 19% during the daytime. Possible causes for this underestimation include errors and uncertainties in SHF measurements and soil thermal properties, as well as the phase lag between G c _5 cm and G m _5 cm . Our results indicate that the calorimetric method achieves the most accurate SHF estimates if self‐calibrating SHF plates are deployed at two depths (e.g., 5 cm and 10 cm), soil temperature and water content measurements are made in a few depths between the two plates, and soil thermal properties are accurately quantified.
Analytical sizing methods for behind-the-meter battery storage
Not Available