Analysis of the Potential Accuracy of Thermodynamic Measurement Using the Double-Wavelength Technique

The detrimental influence of storm sewer overflows on urban river quality has been widely recognised for many years. One objective of the WRc River Basin Management programme is the development of a river impact model capable of predicting the transient quality changes in receiving waters due to intermittent storm sewage discharges. The production of SPRAT (Spill Pollution Response Assessment Technique) is the first step in the development of such a model. SPRAT incorporates a number of significant simplifications, most notably plug flow and instantaneous mixing, and does not implicitly take into account the effects of dispersion. These simplifications reflect the large errors associated with the model inputs. These errors severely limit the potential accuracy of any river impact model. The model has been applied to the Bolton river system in North West England. The development and application of SPRAT has enabled the requirements for a more sophisticated river quality impact model to be clearly defined, in addition to highlighting the problems associated with gathering suitable data with which to build and calibrate such a model.

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The Hyperbolic Method Algorithm for the Optimal Determination of Coordinates and the Evaluation of the Potential Accuracy with Which They Are Measured

Proceedings of the 2018 2nd International Conference on Electrical Engineering and Automation (ICEEA 2018) ◽

10.2991/iceea-18.2018.15 ◽

2018 ◽

Author(s):

Vladimir P. Dubykin ◽

Konstantin S. Kalashnikov ◽

Boris V. Matveev ◽

Oleg V. Chernoyarov

Keyword(s):

Potential Accuracy ◽

Hyperbolic Method

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Improving the potential accuracy and usability of EURO-CORDEX estimates of future rainfall climate using frequentist model averaging

Nonlinear Processes in Geophysics ◽

10.5194/npg-28-329-2021 ◽

2021 ◽

Vol 28 (3) ◽

pp. 329-346

Author(s):

Stephen Jewson ◽

Giuliana Barbato ◽

Paola Mercogliano ◽

Jaroslav Mysiak ◽

Maximiliano Sassi

Keyword(s):

Climate Model ◽

Model Averaging ◽

Large Data ◽

Statistical Testing ◽

Complex Method ◽

Distribution Fitting ◽

Data Set ◽

Potential Accuracy ◽

Predictive Skill ◽

Ensemble Mean

Abstract. Probabilities of future climate states can be estimated by fitting distributions to the members of an ensemble of climate model projections. The change in the ensemble mean can be used as an estimate of the change in the mean of the real climate. However, the level of sampling uncertainty around the change in the ensemble mean varies from case to case and in some cases is large. We compare two model-averaging methods that take the uncertainty in the change in the ensemble mean into account in the distribution fitting process. They both involve fitting distributions to the ensemble using an uncertainty-adjusted value for the ensemble mean in an attempt to increase predictive skill relative to using the unadjusted ensemble mean. We use the two methods to make projections of future rainfall based on a large data set of high-resolution EURO-CORDEX simulations for different seasons, rainfall variables, representative concentration pathways (RCPs), and points in time. Cross-validation within the ensemble using both point and probabilistic validation methods shows that in most cases predictions based on the adjusted ensemble means show higher potential accuracy than those based on the unadjusted ensemble mean. They also perform better than predictions based on conventional Akaike model averaging and statistical testing. The adjustments to the ensemble mean vary continuously between situations that are statistically significant and those that are not. Of the two methods we test, one is very simple, and the other is more complex and involves averaging using a Bayesian posterior. The simpler method performs nearly as well as the more complex method.

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The potential accuracy in a meter with amplitude adaptation to signal statistics

Measurement Techniques ◽

10.1007/bf00864750 ◽

1987 ◽

Vol 30 (4) ◽

pp. 310-316

Author(s):

V. V. Makarov

Keyword(s):

Potential Accuracy

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Abstract 175: Kaiser Stroke Express Program - Population Based Estimate of Potential Accuracy of Field Based Identification of Endovascular Treatment Candidates

Stroke ◽

10.1161/str.49.suppl_1.175 ◽

2018 ◽

Vol 49 (Suppl_1) ◽

Author(s):

Jeffrey Klingman ◽

Meghan Hatfield ◽

Mai N Nguyen-Huynh

Keyword(s):

Endovascular Treatment ◽

Population Based ◽

Potential Accuracy

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Thermodynamic Measurement on the Melting of a Two-Dimensional Electron Solid

Physics and Chemistry of Materials with Low-Dimensional Structures - Two-Dimensional Electron Systems ◽

10.1007/978-94-015-1286-2_4 ◽

1997 ◽

pp. 53-60

Author(s):

D. C. Glattli ◽

Eva Y. Andrei ◽

F. I. B. Williams

Keyword(s):

Two Dimensional ◽

Dimensional Electron ◽

Thermodynamic Measurement

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Direct-from-Blood-Culture Disk Diffusion To Determine Antimicrobial Susceptibility of Gram-Negative Bacteria: Preliminary Report from the Clinical and Laboratory Standards Institute Methods Development and Standardization Working Group

Journal of Clinical Microbiology ◽

10.1128/jcm.01678-17 ◽

2018 ◽

Vol 56 (3) ◽

Cited By ~ 27

Author(s):

Sukantha Chandrasekaran ◽

April Abbott ◽

Shelley Campeau ◽

Barbara L. Zimmer ◽

Melvin Weinstein ◽

...

Keyword(s):

Blood Culture ◽

Clinical Laboratory ◽

Blood Cultures ◽

Disk Diffusion ◽

Random Errors ◽

Disk Diffusion Test ◽

Potential Accuracy ◽

Content Type ◽

Methods Development ◽

Zones Of Inhibition

ABSTRACTThe performance of a disk diffusion test using broth from positive blood cultures as inoculum (direct disk diffusion [dDD]) was evaluated for a collection of 20 challenge isolates ofEnterobacteriaceae,Acinetobacter baumannii, andPseudomonas aeruginosa. Isolates seeded into human blood were inoculated into Bactec Plus Aerobic/F, VersaTREK Redox 1, and BacT/Alert FA Plus bottles and incubated in the respective automated blood culture systems. Disk diffusion results were compared to reference disk diffusion results. Categorical agreement (CA) values for dDD, after removal of random errors due to natural MIC variation, were 87.8%, 88.4%, and 92.2% for the BacT/Alert, Bactec, and VersaTREK systems, respectively. No very major errors (VME) were observed, and major error (ME) rates were 3.0%, 2.3%, and 1.7%, respectively. Incubation of the dDD test samples for 6 h compared to incubation for 16 to 18 h resulted in 19.9% of tests having too light of growth to allow reading of zones of inhibition. Among the evaluable dDD tests, CA values were 58.9%, 76.6%, and 73.2% for the isolates seeded into the BacT/Alert, Bactec, and VersaTREK systems, respectively. VME rates for isolates seeded into these systems were 2.2%, 1.8%, and 3.0%, respectively, and ME rates were 25.4%, 6.1%, and 2.8%, respectively, at the 6-h reading. The best performance of dDD was found for blood cultures with bacterial concentrations in the range of 7.6 × 107to 5.0 × 108CFU/ml; CA values ranged from 94.7 to 96.2% for these concentrations after 18 h of incubation and from 76.9 to 84.1% after 6 h of incubation. These preliminary data demonstrate the potential accuracy of dDD testing by the clinical laboratory.

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Expanding the Capabilities of Radar-Based Vehicle Detection Systems: Noise Characterization and Removal Procedures

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119852607 ◽

2019 ◽

Vol 2673 (11) ◽

pp. 150-160

Author(s):

Kelvin R. Santiago-Chaparro ◽

David A. Noyce

Keyword(s):

Performance Measures ◽

Vehicle Detection ◽

Ground Truth ◽

Noise Removal ◽

Performance Measure ◽

Signalized Intersections ◽

Volume Data ◽

Trajectory Data ◽

Potential Accuracy ◽

Detection Systems

The capabilities of radar-based vehicle detection (RVD) systems used at signalized intersections for stop bar and advanced detection are arguably underutilized. Underutilization happens because RVD systems can monitor the position and speed (i.e., trajectory) of multiple vehicles at the same time but these trajectories are only used to emulate the behavior of legacy detection systems such as inductive loop detectors. When full vehicle trajectories tracked by an RVD system are collected, detailed traffic operations and safety performance measures can be calculated for signalized intersections. Unfortunately, trajectory datasets obtained from RVD systems often contain significant noise which makes the computation of performance measures difficult. In this paper, a description of the type of trajectory datasets that can be obtained from RVD systems is presented along with a characterization of the noise expected in these datasets. Guidance on the noise removal procedures that can be applied to these datasets is also presented. This guidance can be applied to the use of data from commercially-available RVD systems to obtain advanced performance measures. To demonstrate the potential accuracy of the noise removal procedures, the procedures were applied to trajectory data obtained from an existing intersection, and data on a basic performance measure (vehicle volume) were extracted from the dataset. Volume data derived from the de-noised trajectory dataset was compared with ground truth volume and an absolute average difference of approximately one vehicle every 5 min was found, thus highlighting the potential accuracy of the noise removal procedures introduced.

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