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At least 199 records · Page 11

Multidimensional indexing structure for use with linear optimization queries

Linear optimization queries, which usually arise in various decision support and resource planning applications, are queries that retrieve top N data records (where N is an integer greater than zero) which satisfy a specific optimization criterion. The optimization criterion is to either maximize or minimize a linear equation. The coefficients of the linear equation are given at query time. Methods and apparatus are disclosed for constructing, maintaining and utilizing a multidimensional indexing structure of database records to improve the execution speed of linear optimization queries. Database records with numerical attributes are organized into a number of layers and each layer represents a geometric structure called convex hull. Such linear optimization queries are processed by searching from the outer-most layer of this multi-layer indexing structure inwards. At least one record per layer will satisfy the query criterion and the number of layers needed to be searched depends on the spatial distribution of records, the query-issued linear coefficients, and N, the number of records to be returned. When N is small compared to the total size of the database, answering the query typically requires searching only a small fraction of all relevant records, resulting in a tremendous speedup as compared to linearly scanning the entire dataset.

Bergman, Lawrence David↗

Multidimensional Generalized Functions in Aeroacoustics and Fluid Mechanics: Basic Concepts and Operations - Part 1

This paper is the first part of a three part tutorial on multidimensional generalized functions (GFs) and their applications in aeroacoustics and fluid mechanics. The subject is highly fascinating and essential in many areas of science and, in particular, wave propagation problems. In this tutorial, we strive to present rigorously and clearly the basic concepts and the tools that are needed to use GFs in applications effectively and with ease. We give many examples to help the readers in understanding the mathematical ideas presented here. The first part of the tutorial is on the basic concepts of GFs. Here we define GFs, their properties and some common operations on them. We define the important concept of generalized differentiation and then give some interesting elementary and advanced examples on Green's functions and wave propagation problems. Here, the analytic power of GFs in applications is demonstrated with ease and elegance. Part 2 of this tutorial is on the diverse applications of generalized derivatives (GDs). Part 3 is on generalized Fourier transformations and some more advanced topics. One goal of writing this tutorial is to convince readers that, because of their powerful operational properties, GFs are absolutely essential and useful in engineering and physics, particularly in aeroacoustics and fluid mechanics.

Farassat, Fereidoun↗

Multidimensional Processing and Visual Rendering of Complex 3D Biomedical Images

The proposed technology uses advanced image analysis techniques to maximize the resolution and utility of medical imaging methods being used during spaceflight. We utilize COTS technology for medical imaging, but our applications require higher resolution assessment of the medical images than is routinely applied with nominal system software. By leveraging advanced data reduction and multidimensional imaging techniques utilized in analysis of Planetary Sciences and Cell Biology imaging, it is possible to significantly increase the information extracted from the onboard biomedical imaging systems. Year 1 focused on application of these techniques to the ocular images collected on ground test subjects and ISS crewmembers. Focus was on the choroidal vasculature and the structure of the optic disc. Methods allowed for increased resolution and quantitation of structural changes enabling detailed assessment of progression over time. These techniques enhance the monitoring and evaluation of crew vision issues during space flight.

Sams, Clarence F.↗

Methods of Performing Large Scale, Multidimensional Parametric Studies for Space Launch System Mission Analysis

Optimizing a large number of trajectories over a wide range of parameters is a difficult and computationally intensive, particularly when the parametric space has a large number of dimensions. Solving parametric studies like these require good initial conditions for each optimization case, which results in a significant amount of manual interaction and human judgment and can be time consuming. The Space Launch System (SLS) uses POST2 (Program to Optimize Simulated Trajectories II) to simulate different ascent trajectories and perform mission analysis. SLS mission analysis currently uses two types of large scale, multidimensional parameter spaces. The qualifying factor between these spaces is the grid density, which determines the set of applicable solution methodologies. One type has a relatively low number of dimensions (2-3), but a large number of grid coordinates (2000- 4000), whereas the second type has a relatively low number of grid coordinates (150-350), but a higher number of dimensions (7-10).

Stein, W. B.↗

I/O routing in a multidimensional torus network

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.

97 MATHEMATICS AND COMPUTING↗

Computer systems and methods for the query and visualization multidimensional databases

A method of generating a data visualization is performed at a computer having a display, one or more processors, and memory. The memory stores one or more programs for execution by the one or more processors. The process receives user specification of a plurality of characteristics of a data visualization. The data visualization is based on data from a multidimensional database. The characteristics specify at least x-position and y-position of data marks corresponding to tuples of data retrieved from the database. The process generates a data visualization according to the specified plurality of characteristics. The data visualization has an x-axis defined based on data for one or more first fields from the database that specify x-position of the data marks and the data visualization has a y-axis defined based on data for one or more second fields from the database that specify y-position of the data marks.

97 MATHEMATICS AND COMPUTING↗

I/O routing in a multidimensional torus network

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.

97 MATHEMATICS AND COMPUTING↗

An Immersive Visual Analytics Platform for Multidimensional Dataset

Abstract—Virtual Reality is a budding new medium of interaction, but ways in which to use it for data analytics are not immediately obvious. Through our research, we investigated new and useful ways to view multidimensional data in a virtual environment. In this paper, we present a virtual laboratory with collaborative visualizations in different spaces. We focused on geographic view in the center of the room by utilizing spatial freedom in Virtual Reality, which informed both the geographic visualization and time series data. Through this laboratory and the collaborative visualizations housed within, we believe we’ve found a novel way to interpret data in Virtual Reality.

97 MATHEMATICS AND COMPUTING↗

I/O routing in a multidimensional torus network

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.

97 MATHEMATICS AND COMPUTING↗

I/O routing in a multidimensional torus network

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.

97 MATHEMATICS AND COMPUTING↗

Hypernetwork Science: From Multidimensional Networks to Computational Topology

As data structures and mathematical objects used for complex systems modeling, hypergraphs sit nicely poised between on the one hand the world of network models, and on the other that of higher-order mathematical abstractions from algebra, lattice theory, and topology. They are able to represent complex systems interactions more faithfully than graphs and networks, while also being some of the simplest classes of systems representing topological structures as collections of multidimensional objects connected in a particular pattern. In this paper we discuss the role of (undirected) hypergraphs in the science of complex networks, and provide a mathematical overview of the core concepts needed for hypernetwork modeling, including duality and the relationship to bicolored graphs, quantitative adjacency and incidence, the nature of walks in hypergraphs, and available topological relationships and properties. We close with a brief discussion of two example applications: biomedical databases for disease analysis, and domain-name system (DNS) analysis of cyber data.

Joslyn, Cliff A.↗

I/O routing in a multidimensional torus network

A method, system and computer program product are disclosed for routing data packet in a computing system comprising a multidimensional torus compute node network including a multitude of compute nodes, and an I/O node network including a plurality of I/O nodes. In one embodiment, the method comprises assigning to each of the data packets a destination address identifying one of the compute nodes; providing each of the data packets with a toio value; routing the data packets through the compute node network to the destination addresses of the data packets; and when each of the data packets reaches the destination address assigned to said each data packet, routing said each data packet to one of the I/O nodes if the toio value of said each data packet is a specified value. In one embodiment, each of the data packets is also provided with an ioreturn value used to route the data packets through the compute node network.

Chen, Dong↗

Results from the assessment of COBRA-IE multidimensional flow capability with selected canonical problems

A systematic assessment of the capabilities of thermal-hydraulic codes such as RELAP5-3D and COBRA-IE to handle multi-dimensional flow is ongoing. The assessment is being performed in hierarchical fashion by isolating simple processes first and building complexity along the way. The first stage in the process has been to develop simple and fundamental canonical problems which challenge key aspects of the multidimensional flow process while removing other complex processes such as interfacial mass and heat transfer. Results of this work have been presented for RELAP5-3D at the NURETH-16 conference [1], [2], [3]. The purpose of this paper is to illustrate similar results obtained using COBRA-IE. The results are presented for two canonical problems. The first pertains to the simulation of Faraday waves (CP06) in an annulus. The second problem compares the solution of 2D single-phase, inviscid, frictionless, incompressible, irrotational flow (CP07) to the potential flow solution. Results from COBRA-IE are compared with similar results obtained with RELAP5-3D which were previously published in the 2015 NURETH papers series on this topic. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multidimensional photon correlation spectroscopy of cavity polaritons

Significance We propose a spectroscopic technique that can track the time-dependent state of a dressed molecule in an optical cavity (polariton) by measuring coincidence of two emitted photons. The proposed technique offers an independent control of the spectral and temporal resolution; single-photon detection allows for low-intensity measurements, which do not disturb the state of the cavity field, and time-dependent atom/cavity coupling provides a control tool. Tracking the evolution of the polariton states with time-dependent atom/cavity coupling should be of interest in photochemistry and photobiology and could improve fundamental understanding of many physical processes in strongly coupled atom/radiation states. Possible applications include chemical sensors and quantum information processing.

74 ATOMIC AND MOLECULAR PHYSICS↗

Imaging electron-density fluctuations by multidimensional X-ray photon-coincidence diffraction

The ultrafast spontaneous electron-density fluctuation dynamics in molecules is studied theoretically by off-resonant multiple X-ray diffraction events. The time- and wavevector-resolved photon-coincidence signals give an image of electron-density fluctuations expressed through the four-point correlation function of the charge density in momentum space. A Fourier transform of the signal provides a real-space image of the multipoint charge-density correlation functions, which reveal snapshots of the evolving electron density in between the diffraction events. The proposed technique is illustrated by ab initio simulations of the momentum- and real-space inelastic scattering signals from a linear cyanotetracetylene molecule.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multidimensional perspectives of geo-epidemiology: from interdisciplinary learning and research to cost–benefit oriented decision-making

Research typically promotes two types of outcomes (inventions and discoveries), which induce a virtuous cycle: something suspected or desired (not previously demonstrated) may become known or feasible once a new tool or procedure is invented and, later, the use of this invention may discover new knowledge. Research also promotes the opposite sequence—from new knowledge to new inventions. This bidirectional process is observed in geo-referenced epidemiology—a field that relates to but may also differ from spatial epidemiology. Geo-epidemiology encompasses several theories and technologies that promote inter/transdisciplinary knowledge integration, education, and research in population health. Based on visual examples derived from geo-referenced studies on epidemics and epizootics, this report demonstrates that this field may extract more (geographically related) information than simple spatial analyses, which then supports more effective and/or less costly interventions. Actual (not simulated) bio-geo-temporal interactions (never captured before the emergence of technologies that analyze geo-referenced data, such as geographical information systems) can now address research questions that relate to several fields, such as Network Theory. Thus, a new opportunity arises before us, which exceeds research: it also demands knowledge integration across disciplines as well as novel educational programs which, to be biomedically and socially justified, should demonstrate cost-effectiveness. Grounded on many bio-temporal-georeferenced examples, this report reviews the literature that supports this hypothesis: novel educational programs that focus on geo-referenced epidemic data may help generate cost-effective policies that prevent or control disease dissemination.

59 BASIC BIOLOGICAL SCIENCES↗