Fast query-optimized kernel machine classification via incremental approximate nearest support vectors
Support vector machines (and other kernel machines) offer robust modern machine learning methods for nonlinear classfication.
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Support vector machines (and other kernel machines) offer robust modern machine learning methods for nonlinear classfication.
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Smoothed-particle hydrodynamics (SPH) is a mesh-free method used to simulate volumetric media in fluids, astrophysics, and solid mechanics. Visualizing these simulations is problematic because these datasets often contain millions, if not billions of particles carrying physical attributes and moving over time. Radial basis functions (RBFs) are used to model particles, and overlapping particles are interpolated to reconstruct a high-quality volumetric field; however, this interpolation process is expensive and makes interactive visualization difficult. Existing RBF interpolation schemes do not account for color-mapped attributes and are instead constrained to visualizing just the density field. To address these challenges, we exploit ray tracing cores in modern GPU architectures to accelerate scalar field reconstruction. We use a novel RBF interpolation scheme to integrate per-particle colors and densities, and leverage GPU-parallel tree construction and refitting to quickly update the tree as the simulation animates over time or when the user manipulates particle radii. We also propose a Hilbert reordering scheme to cluster particles together at the leaves of the tree to reduce tree memory consumption. Finally, we reduce the noise of volumetric shadows by adopting a spatially temporal blue noise sampling scheme. Our method can provide a more detailed and interactive view of these large, volumetric, time-series particle datasets than traditional methods, leading to new insights into these physics simulations.
Discovering novel catalysts requires complex reasoning involving multiple chemical properties and resultant trade-offs, leading to a combinatorial growth in the search space. While large language models (LLM) have demonstrated novel capabilities for chemistry through complex instruction following capabilities and high quality reasoning, a goal-driven combinatorial search using LLMs has not been explored in detail. In this work, we present a Monte Carlo Tree Search-based approach that improves beyond state-of-the-art chain-of-thought prompting variants to augment scientific reasoning. We introduce two new reasoning datasets: 1) a curation of computational chemistry simulations, and 2) diverse questions written by catalysis researchers for reasoning about novel chemical conversion processes. We improve over the best baseline by 25.8\% and find that our approach can augment scientist's reasoning and discovery process with novel insights.\footnote{All resources will be publicly available upon publication.
In FY20, the Savannah River National Laboratory (SRNL) was funded by the National Nuclear Security Administration’s Office of Defense Nuclear Non-Proliferation Research and Development (NA-22) to build a machine learning based modeling pipeline that could extract proliferation events of interest from open text-based data sources. As a test case, the research team targeted the identification/fusion of events and indicators that fissile core fabrication would be executed at the Savannah River Site prior to its official announcement in May of 2018. The demonstration prototype proved successful by applying natural language processing and graph theoretical techniques to identify contextual shifts in key words and phrases that acted as indicators that pit production would be carried out at the Savannah River Site up to two years prior to the official announcement.
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Seven solar flares that were followed by major proton events were examined to determine the diverse and common properties of major flares. The most probable site of primary proton acceleration is cospatial with the site and instant of formation of coronal loops. Because loop formation occurs through the entire duration of major solar flares over significantly large areas of active centers, it is proposed that proton injection occurs from a relatively large volume of space in the corona of active centers and is continuous throughout, and possibly even after, the visible duration of the related chromospheric flare. The flare veil is hypothesized to occur as a result of proton charge exchange taking place in the white-light transient. The Kopp and Pneuman model of loop formation by magnetic reconnection is suggested as an adequate and satisfactory model for all major flares with the provision that the beginning of rapid magnetic field reconnection is coincident with flare start.
The objective of the Distributed Access View Integrated Database (DAVID) project is the development of an easy to use computer system with which NASA scientists, engineers and administrators can uniformly access distributed heterogeneous databases. Basically, DAVID will be a database management system that sits alongside already existing database and file management systems. Its function is to enable users to access the data in other languages and file systems without having to learn the data manipulation languages. Given here is an outline of a talk on the DAVID project and several charts.
Results of research and development efforts are presented for Task 1, Phase 2 of a general project entitled, The Development of a Program Analysis Environment for Ada. A prototype of the QUEST/Ada system was developed to collect data to determine the effectiveness of the rule-based testing paradigm. The prototype consists of five parts: the test data generator, the parser/scanner, the test coverage analyzer, a symbolic evaluator, and a data management facility, known as the Librarian. These components are discussed at length. Also presented is an experimental design for the evaluations, an overview of the project, and a schedule for its completion.
The results of research and development efforts of the first six months of Task 1, Phase 3 of the project are presented. The goals of Phase 3 are: (1) to further refine the rule base and complete the comparative rule base evaluation; (2) to implement and evaluate a concurrency testing prototype; (3) to convert the complete (unit-level and concurrency) testing prototype to a workstation environment; and (4) to provide a prototype development document to facilitate the transfer of research technology to a working environment. These goals were partially met and the results are summarized.
Geographic information systems (GIS) deal with collecting, modeling, man- aging, analyzing, and integrating spatial (locational) and non-spatial (attribute) data required for geographic applications. Examples of spatial data are digital maps, administrative boundaries, road networks, and those of non-spatial data are census counts, land elevations and soil characteristics. GIS shares common areas with a number of other disciplines such as computer- aided design, computer cartography, database management, and remote sensing. None of these disciplines however, can by themselves fully meet the requirements of a GIS application. Examples of such requirements include: the ability to use locational data to produce high quality plots, perform complex operations such as network analysis, enable spatial searching and overlay operations, support spatial analysis and modeling, and provide data management functions such as efficient storage, retrieval, and modification of large datasets; independence, integrity, and security of data; and concurrent access to multiple users. It is on the data management issues that we devote our discussions in this monograph. Traditionally, database management technology have been developed for business applications. Such applications require, among other things, capturing the data requirements of high-level business functions and developing machine- level implementations; supporting multiple views of data and yet providing integration that would minimize redundancy and maintain data integrity and security; providing a high-level language for data definition and manipulation; allowing concurrent access to multiple users; and processing user transactions in an efficient manner. The demands on database management systems have been for speed, reliability, efficiency, cost effectiveness, and user-friendliness. Significant progress have been made in all of these areas over the last two decades to the point that many generalized database platforms are now available for developing data intensive applications that run in real-time. While continuous improvement is still being made at a very fast-paced and competitive rate, new application areas such as computer aided design, image processing, VLSI design, and GIS have been identified by many as the next generation of database applications. These new application areas pose serious challenges to the currently available database technology. At the core of these challenges is the nature of data that is manipulated. In traditional database applications, the database objects do not have any spatial dimension, and as such, can be thought of as point data in a multi-dimensional space. For example, each instance of an entity EMPLOYEE will have a unique value corresponding to every attribute such as employee id, employee name, employee address and so on. Thus, every Employee instance can be thought of as a point in a multi-dimensional space where each dimension is represented by an attribute. Furthermore, all operations on such data are one-dimensional. Thus, users may retrieve all entities satisfying one or more constraints. Examples of such constraints include employees with addresses in a certain area code, or salaries within a certain range. Even though constraints can be specified on multiple attributes (dimensions), the search for such data is essentially orthogonal across these dimensions.
A new type of in situ, remotely monitored magnetism-based sensor is presented that is comprised of an array of magnetically soft, magnetostatically-coupled ferromagnetic thin-film elements or particles combined with a chemically responsive material that swells or shrinks in response to the analyte of interest. As the chemically responsive material changes size the distance between the ferromagnetic elements changes, altering the inter-element magnetostatic coupling. This in turn changes the coercive force of the sensor, the amplitude of the voltage spikes detected in nearby pick-up coils upon magnetization reversal and the number of higher-order harmonics generated by the flux reversal. Since the sensor is monitored through changes in magnetic flux, no physical connections such as wires or cables are needed to obtain sensor information, nor is line of sight alignment required as with laser telemetry; the sensors can be detected from within sealed, opaque or thin metallic enclosures.
A pressure sensing apparatus for operative arrangement within an environment, having: a sensor comprising a hermetically-sealed receptacle, at least one side of which has an flexible membrane to which a magnetically hard element is attached. Enclosed within the receptacle is a magnetostrictive element that vibrates in response to a time-varying magnetic field. Also included is a receiver to measure a plurality of successive values for magneto-elastic emission intensity of the sensor taken over an operating range of successive interrogation frequencies to identify a resonant frequency value for the sensor. Additional features include: (a) the magnetically hard element may be adhered to an inner or outer side of, or embedded within, the membrane; (b) the magnetostrictive element can include one or more of a variety of different pre-formed, hardened regions; (c) the magneto-elastic emission may be a primarily acoustic or electromagnetic emission; and (d) in the event the time-varying magnetic field is emitted as a single pulse or series of pulses, the receiver unit can detect a transitory time-response of the emission intensity of each pulse (detected after a threshold amplitude value for the transitory time-response is observed). A Fourier transform of the time-response can yield results in the frequency domain. Also, an associated method of sensing pressure of an environment is included that uses a sensor having a magnetostrictive element to identify a magneto-elastic resonant frequency value therefore. Using the magneto-elastic resonant frequency value identified, a value for the pressure of the environment can be identified.