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At least 19 records

An information measure for class discrimination

This article describes a separability measure for class discrimination. This measure is based on the Fisher information measure for estimating the mixing proportion of two classes. The Fisher information measure not only provides a means to assess quantitatively the information content in the features for separating classes, but also gives the lower bound for the variance of any unbiased estimate of the mixing proportion based on observations of the features. Unlike most commonly used separability measures, this measure is not dependent on the form of the probability distribution of the features and does not imply a specific estimation procedure. This is important because the probability distribution function that describes the data for a given class does not have simple analytic forms, such as a Gaussian. Results of applying this measure to compare the information content provided by three Landsat-derived feature vectors for the purpose of separating small grains from other crops are presented.

Shen, S. S.↗

Measurement-informed Dynamic Aggregation of Distribution Systems

This paper proposes a measurement-informed dynamic aggregation methodology in order to create equivalent representations of distribution systems that are compatible with large-scale transmission analysis. By optimizing an equivalent feeder parameters using time-series measurements of active power, reactive power, and voltage at the Point of Interconnection (POI), the approach yields simplified yet dynamically accurate equivalents. Implemented in PSCAD with models of photovoltaic–battery systems, three-phase motors, and static loads, the method employs hybrid differential evolution and bounded least-squares optimization laying the foundation for for real-time state estimation and optimized sensor placement in distribution networks.

Ahmed, Kazi Ishrak [University of Tennessee, Knoxv↗

Information measures in nonlinear experimental design

Some different approaches to the problem of designing experiments which estimate the parameters of nonlinear models are discussed. The assumption in these approaches that the information in a set of data can be represented by a scalar is criticized, and the nonscalar discrimination information is proposed as the proper measure to use. The two-step decay example in Box and Lucas (1959) is used to illustrate the main points of the discussion.

Niple, E.↗

The value of forage measurement information in rangeland management

An economic model and simulation are developed to estimate the potential social benefit arising from the use of alternative measurement systems in rangeland management. In order to estimate these benefits, it was necessary to model three separate systems: the range environment, the rangeland manager, and the information system which links the two. The rancher's decision-making behavior is modeled according to sound economic principles. Results indicate substantial potential benefits, particularly when used in assisting management of government-operated ranges; possible annual benefits in this area range from $20 to $46 million, depending upon the system capabilities assumed. Possible annual benefit in privately-managed stocker operations range from $2.8 to $49.5 million, depending upon where actual rancher capabilities lie and what system capabilities are assumed.

Lietzke, K. R.↗

Python Measurement-Informed Modelling Method (PythonMIMM) v1.02

This Python program implements the calculations for electrical energy efficiency and electrical losses in the paper "Energy and power quality measurement for electrical distribution in AC and DC microgrid buildings" (https://www.sciencedirect.com/science/article/abs/pii/S0306261921015658). The inputs are metered voltage, current, or power data of meters located throughout the DC system. In the absence of metered data, the user must input some other information about the building such as the types of power converters or wire lengths. The program will build a loss model of the DC system based on metered data and electrical information. It will also generate an equivalent AC system and determine the losses and efficiency.

Gerber, Daniel [Lawrence Berkeley National Laborat↗

How can a diverse set of integral and semi-integral measurements inform identification of discrepant nuclear data?

Nuclear data are used for a variety of applications, including criticality safety, reactor performance, and material safeguards. Despite the breadth of use-cases, the effective neutron multiplication factor, keff, of ICSBEP critical assemblies are primarily used for nuclear data validation; these are sensitive to specific energy regions and nuclides and are unable to uniquely constrain nuclear data. As a consequence, general-purpose nuclear data libraries, such as ENDF/B-VIII.0, may have deficiencies that, while not apparent in criticality applications, negatively impact other applications, such as non-destructive analysis of special nuclear material and neutron diagnosed subcritical experiments. Recent work by the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project developed a machine learning tool, RAFIEKI, which uses random forests and the SHAP metric to determine which nuclear data contribute most to predicted bias between measured and simulated responses (e.g. keff). This paper contrasts RAFIEKI analysis applied to keff only against RAFIEKI analysis with keff paired with either LLNL pulsed sphere measurements or subcritical benchmarks. Two examples show that a) including pulsed sphere measurements substantially increases 9Be nuclear data importance to bias between 2 and 15 MeV, and b) including subcritical benchmarks has the potential for disentangling compensating errors between 240Pu (n,el) and (n,il) cross-sections between 0.1 and 10 MeV. These results show that RAFIEKI analysis applied to response sets that include, but go beyond, keff can aid nuclear data evaluators in identifying issues in nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Equivalent Breakeven Installed Cost: A Tradeoff-Informed Measure for Technoeconomic Analysis of Candidate Heliostat Improvements

Technoeconomic analysis (TEA) is commonly used to determine economic viability of power-generating technologies, including concentrating solar power (CSP) and thermal (CST) production plants. Levelized cost of electricity (LCOE) and analogous measures provide an estimate of long-term costs for operating power plants over their designed lifetimes by accounting for revenues and costs in a time-discounted manner. While these measures are effective when assessing a technology’s total lifecycle costs and productivity under various designs, TEA of candidate incremental technology improvements from the lens of LCOE can be limited when required investment and LCOE impacts are small. In this work, we propose a novel metric for TEA of a plant component technology that recasts relative changes in levelized system costs into component-specific capital cost budgets. This measure, which we refer to as the equivalent breakeven installed cost, is the maximum budget for the technology component that leads to improved levelized costs. We illustrate the usefulness of this metric using the example of candidate heliostat improvements for a CSP tower plant. Here, the results suggest that a reduction in mirror washing costs yield a total plant O&M cost of $37/kWe-yr, which is a breakeven proposition if the average reflectance is reduced from 0.90 to 0.85 as a result of the cost savings.

Zolan, Alexander (ORCID:0000000326017604)↗

AHIMSA - Ad hoc histogram information measure sensing algorithm for feature selection in the context of histogram inspired clustering techniques

An algorithm is proposed for dimensionality reduction in the context of clustering techniques based on histogram analysis. The approach is based on an evaluation of the hills and valleys in the unidimensional histograms along the different features and provides an economical means of assessing the significance of the features in a nonparametric unsupervised data environment. The method has relevance to remote sensing applications.

Dasarathy, B. V.↗

Equivalent Breakeven Installed Cost: A Tradeoff-Informed Measure for Technoeconomic Analysis of Candidate Heliostat Improvements: Preprint

Technoeconomic analysis (TEA) is commonly used to determine economic viability of power-generating technologies, including concentrating solar power (CSP) and thermal (CST) production plants. Levelized cost of electricity (LCOE) and analogous measures provide an estimate of long-term costs for operating power plants over their designed lifetimes by accounting for revenues and costs in a time-discounted manner. While these measures are effective when assessing a technology's total lifecycle costs and productivity under various designs, TEA of candidate incremental technology improvements from the lens of LCOE can be limited when required investment and LCOE impacts are small. In this work, we propose a novel metric for TEA of a plant component technology that recasts relative changes in levelized system costs into component-specific capital cost budgets. This measure, which we refer to as the equivalent breakeven installed cost, is the maximum budget for the technology component that leads to improved levelized costs. We illustrate the usefulness of this metric using the example of candidate heliostat improvements for a CSP tower plant. Here, the results suggest that a reduction in mirror washing costs yield a total plant O&M cost of $37/kWe-yr, which is a breakeven proposition if the average reflectance is reduced from 0.90 to 0.85 as a result of the cost savings.

concentrating solar power↗

ASRDI oxygen technology survey. Volume 4: Low temperature measurement

Information is presented on temperature measurement between the triple point and critical point of liquid oxygen. The criterion selected is that all transducers which may reasonably be employed in the liquid oxygen (LO2) temperature range are considered. The temperature range for each transducer is the appropriate full range for the particular thermometer. The discussion of each thermometer or type of thermometer includes the following information: (1) useful temperature range, (2) general and particular methods of construction and the advantages of each type, (3) specifications (accuracy, reproducibility, response time, etc.), (4) associated instrumentation, (5) calibrations and procedures, and (6) analytical representations.

Sparks, L. L.↗

Performance measurement for information systems: Industry perspectives

Performance measurement has become a focal topic for information systems (IS) organizations. Historically, IS performance measures have dealt with the efficiency of the data processing function. Today, the function of most IS organizations goes beyond simple data processing. To understand how IS organizations have developed meaningful performance measures that reflect their objectives and activities, industry perspectives on IS performance measurement was studied. The objectives of the study were to understand the state of the practice in IS performance techniques for IS performance measurement; to gather approaches and measures of actual performance measures used in industry; and to report patterns, trends, and lessons learned about performance measurement to NASA/JSC. Examples of how some of the most forward looking companies are shaping their IS processes through measurement is provided. Thoughts on the presence of a life-cycle to performance measures development and a suggested taxonomy for performance measurements are included in the appendices.

Bishop, Peter C.↗

Turbulence statistical analysis of the L-H transition and RMPs in KSTAR

Here, we investigate the turbulence statistics associated with low-to-high confinement (L-H) transitions and externally applied resonant magnetic perturbations (RMPs) in KSTAR. Time-series fluctuations of electron density n e , electron temperature T e , and the time derivative of the poloidal magnetic field dB θ /dt (Mirnov coils) are analysed using information-geometric measures (information rate Γ and information length $\mathcal{L}$ = ∫ Γ dt), together with kurtosis κ and variance σ 2 . In low-density upper single-null plasmas (n e ~ 1.2 x 10 19 m -3 ), a ~80 kHz magnetic mode coupling n e , T e , dB θ /dt and emerges prior to the L-H transition and persists into the edge-localised modes H-mode. Edge-localised RMPs (ERMPs) suppress this coherent mode but enhance intermittency, producing frequent bursts that abruptly reshape the time-dependent probability density functions (PDFs) and generate large spikes in Γ (with smaller changes in κ), signalling ERMP-driven departures from quasi-stationarity. The impact of ERMPs on background fluctuation levels depends on density, radial location, and the fluctuating variable itself ($\tilde{n}$, $\tilde{T}$, $\dot{B}$ θ ), whereas $\mathcal{L}$ provides a robust, regime-agnostic measure of cumulative statistical reorganisation and spatial decorrelation. In particular, at low density we observe weaker coupling between $\tilde{n}$ and $\tilde{T}$, along with a tendency toward decreased radial correlation-most clearly for $\tilde{T}$-under ERMPs. Overall, information geometry cleanly captures intermittent events, quantifies non-equilibrium PDF evolution, and offers a compact, cross-diagnostic metric for assessing resonant magnetic perturbation effects on edge transport and correlation across densities, radial locations, and confinement states.

Kim, Eun-jin [Coventry Univ. (United Kingdom); Seo↗

Mission analysis to define satellite orbits for earth radiation budget measurements

Information is presented concerning the number of satellites, the orbit altitude, and the inclinations which will provide the spatial and temporal earth coverage required for accurate radiation measurements on regional, zonal, and global scales. Measurement considerations are discussed and an analysis is conducted regarding the selection of suitable orbit parameters. Attention is also given to the results of a simulation model study for the determination of the radiation which can be measured by satellite sensors in different orbits.

Harrison, E. F.↗

A criterion based on an information theoretic measure for goodness of fit between classifier and data base

A criterion for characterizing an iteratively trained classifier is presented. The criterion is based on an information theoretic measure that is developed from modeling classifier training iterations as a set of cascaded channels. The criterion is formulated as a figure of merit and as a performance index to check the appropriateness of application of the characterized classifier to an unknown data base and for implementing classifier updates and data selection respectively.

Eigen, D. J.↗

A criterion based on an information theoretic measure for goodness of fit between classifier and data base

A criterion for characterizing an iteratively trained classifier is presented. The criterion is based on an information theoretic measure that is developed from modeling classifier training iterations as a set of cascaded channels. The criterion is formulated as a figure of merit and as a performance index to check the appropriateness of application of the characterized classifier to an unknown data base and for implementing classifier updates and data selection, respectively.

Eigen, D. J.↗