Computer Modeling to Evaluate the Impact of Technology Changes on Resident Procedural Volume.

PubMed

Grenda, Tyler R; Ballard, Tiffany N S; Obi, Andrea T; Pozehl, William; Seagull, F Jacob; Chen, Ryan; Cohn, Amy M; Daskin, Mark S; Reddy, Rishindra M

2016-12-01

As resident "index" procedures change in volume due to advances in technology or reliance on simulation, it may be difficult to ensure trainees meet case requirements. Training programs are in need of metrics to determine how many residents their institutional volume can support. As a case study of how such metrics can be applied, we evaluated a case distribution simulation model to examine program-level mediastinoscopy and endobronchial ultrasound (EBUS) volumes needed to train thoracic surgery residents. A computer model was created to simulate case distribution based on annual case volume, number of trainees, and rotation length. Single institutional case volume data (2011-2013) were applied, and 10 000 simulation years were run to predict the likelihood (95% confidence interval) of all residents (4 trainees) achieving board requirements for operative volume during a 2-year program. The mean annual mediastinoscopy volume was 43. In a simulation of pre-2012 board requirements (thoracic pathway, 25; cardiac pathway, 10), there was a 6% probability of all 4 residents meeting requirements. Under post-2012 requirements (thoracic, 15; cardiac, 10), however, the likelihood increased to 88%. When EBUS volume (mean 19 cases per year) was concurrently evaluated in the post-2012 era (thoracic, 10; cardiac, 0), the likelihood of all 4 residents meeting case requirements was only 23%. This model provides a metric to predict the probability of residents meeting case requirements in an era of changing volume by accounting for unpredictable and inequitable case distribution. It could be applied across operations, procedures, or disease diagnoses and may be particularly useful in developing resident curricula and schedules.

Modular Engine Noise Component Prediction System (MCP) Program Users' Guide

NASA Technical Reports Server (NTRS)

Golub, Robert A. (Technical Monitor); Herkes, William H.; Reed, David H.

2004-01-01

This is a user's manual for Modular Engine Noise Component Prediction System (MCP). This computer code allows the user to predict turbofan engine noise estimates. The program is based on an empirical procedure that has evolved over many years at The Boeing Company. The data used to develop the procedure include both full-scale engine data and small-scale model data, and include testing done by Boeing, by the engine manufacturers, and by NASA. In order to generate a noise estimate, the user specifies the appropriate engine properties (including both geometry and performance parameters), the microphone locations, the atmospheric conditions, and certain data processing options. The version of the program described here allows the user to predict three components: inlet-radiated fan noise, aft-radiated fan noise, and jet noise. MCP predicts one-third octave band noise levels over the frequency range of 50 to 10,000 Hertz. It also calculates overall sound pressure levels and certain subjective noise metrics (e.g., perceived noise levels).

Toward objective image quality metrics: the AIC Eval Program of the JPEG

NASA Astrophysics Data System (ADS)

Richter, Thomas; Larabi, Chaker

2008-08-01

Objective quality assessment of lossy image compression codecs is an important part of the recent call of the JPEG for Advanced Image Coding. The target of the AIC ad-hoc group is twofold: First, to receive state-of-the-art still image codecs and to propose suitable technology for standardization; and second, to study objective image quality metrics to evaluate the performance of such codes. Even tthough the performance of an objective metric is defined by how well it predicts the outcome of a subjective assessment, one can also study the usefulness of a metric in a non-traditional way indirectly, namely by measuring the subjective quality improvement of a codec that has been optimized for a specific objective metric. This approach shall be demonstrated here on the recently proposed HDPhoto format14 introduced by Microsoft and a SSIM-tuned17 version of it by one of the authors. We compare these two implementations with JPEG1 in two variations and a visual and PSNR optimal JPEG200013 implementation. To this end, we use subjective and objective tests based on the multiscale SSIM and a new DCT based metric.

Do Standard Measures of Preschool Quality Used in Statewide Policy Predict School Readiness?

ERIC Educational Resources Information Center

Sabol, Terri J.; Pianta, Robert C.

2014-01-01

In the majority of states using Quality Rating and Improvement Systems (QRIS) to improve children's school readiness, the Early Childhood Environmental Rating Scale-Revised (ECERS-R) is a core assessment of preschool program quality and is central to QRIS metrics and incentive structures. The present study utilizes nationally representative data…

A Locally Weighted Fixation Density-Based Metric for Assessing the Quality of Visual Saliency Predictions

NASA Astrophysics Data System (ADS)

Gide, Milind S.; Karam, Lina J.

2016-08-01

With the increased focus on visual attention (VA) in the last decade, a large number of computational visual saliency methods have been developed over the past few years. These models are traditionally evaluated by using performance evaluation metrics that quantify the match between predicted saliency and fixation data obtained from eye-tracking experiments on human observers. Though a considerable number of such metrics have been proposed in the literature, there are notable problems in them. In this work, we discuss shortcomings in existing metrics through illustrative examples and propose a new metric that uses local weights based on fixation density which overcomes these flaws. To compare the performance of our proposed metric at assessing the quality of saliency prediction with other existing metrics, we construct a ground-truth subjective database in which saliency maps obtained from 17 different VA models are evaluated by 16 human observers on a 5-point categorical scale in terms of their visual resemblance with corresponding ground-truth fixation density maps obtained from eye-tracking data. The metrics are evaluated by correlating metric scores with the human subjective ratings. The correlation results show that the proposed evaluation metric outperforms all other popular existing metrics. Additionally, the constructed database and corresponding subjective ratings provide an insight into which of the existing metrics and future metrics are better at estimating the quality of saliency prediction and can be used as a benchmark.

Empirical Evaluation of Hunk Metrics as Bug Predictors

NASA Astrophysics Data System (ADS)

Ferzund, Javed; Ahsan, Syed Nadeem; Wotawa, Franz

Reducing the number of bugs is a crucial issue during software development and maintenance. Software process and product metrics are good indicators of software complexity. These metrics have been used to build bug predictor models to help developers maintain the quality of software. In this paper we empirically evaluate the use of hunk metrics as predictor of bugs. We present a technique for bug prediction that works at smallest units of code change called hunks. We build bug prediction models using random forests, which is an efficient machine learning classifier. Hunk metrics are used to train the classifier and each hunk metric is evaluated for its bug prediction capabilities. Our classifier can classify individual hunks as buggy or bug-free with 86 % accuracy, 83 % buggy hunk precision and 77% buggy hunk recall. We find that history based and change level hunk metrics are better predictors of bugs than code level hunk metrics.

Conceptual Soundness, Metric Development, Benchmarking, and Targeting for PATH Subprogram Evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mosey. G.; Doris, E.; Coggeshall, C.

The objective of this study is to evaluate the conceptual soundness of the U.S. Department of Housing and Urban Development (HUD) Partnership for Advancing Technology in Housing (PATH) program's revised goals and establish and apply a framework to identify and recommend metrics that are the most useful for measuring PATH's progress. This report provides an evaluative review of PATH's revised goals, outlines a structured method for identifying and selecting metrics, proposes metrics and benchmarks for a sampling of individual PATH programs, and discusses other metrics that potentially could be developed that may add value to the evaluation process. The frameworkmore » and individual program metrics can be used for ongoing management improvement efforts and to inform broader program-level metrics for government reporting requirements.« less

Evaluation of Two Crew Module Boilerplate Tests Using Newly Developed Calibration Metrics

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Reaves, Mercedes C.

2012-01-01

The paper discusses a application of multi-dimensional calibration metrics to evaluate pressure data from water drop tests of the Max Launch Abort System (MLAS) crew module boilerplate. Specifically, three metrics are discussed: 1) a metric to assess the probability of enveloping the measured data with the model, 2) a multi-dimensional orthogonality metric to assess model adequacy between test and analysis, and 3) a prediction error metric to conduct sensor placement to minimize pressure prediction errors. Data from similar (nearly repeated) capsule drop tests shows significant variability in the measured pressure responses. When compared to expected variability using model predictions, it is demonstrated that the measured variability cannot be explained by the model under the current uncertainty assumptions.

Factors leading to different viability predictions for a grizzly bear data set

USGS Publications Warehouse

Mills, L.S.; Hayes, S.G.; Wisdom, M.J.; Citta, J.; Mattson, D.J.; Murphy, K.

1996-01-01

Population viability analysis programs are being used increasingly in research and management applications, but there has not been a systematic study of the congruence of different program predictions based on a single data set. We performed such an analysis using four population viability analysis computer programs: GAPPS, INMAT, RAMAS/AGE, and VORTEX. The standardized demographic rates used in all programs were generalized from hypothetical increasing and decreasing grizzly bear (Ursus arctos horribilis) populations. Idiosyncracies of input format for each program led to minor differences in intrinsic growth rates that translated into striking differences in estimates of extinction rates and expected population size. In contrast, the addition of demographic stochasticity, environmental stochasticity, and inbreeding costs caused only a small divergence in viability predictions. But, the addition of density dependence caused large deviations between the programs despite our best attempts to use the same density-dependent functions. Population viability programs differ in how density dependence is incorporated, and the necessary functions are difficult to parameterize accurately. Thus, we recommend that unless data clearly suggest a particular density-dependent model, predictions based on population viability analysis should include at least one scenario without density dependence. Further, we describe output metrics that may differ between programs; development of future software could benefit from standardized input and output formats across different programs.

Should regional ventilation function be considered during radiation treatment planning to prevent radiation-induced complications?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lan, Fujun; Jeudy, Jean; D’Souza, Warren

Purpose: To investigate the incorporation of pretherapy regional ventilation function in predicting radiation fibrosis (RF) in stage III nonsmall cell lung cancer (NSCLC) patients treated with concurrent thoracic chemoradiotherapy. Methods: Thirty-seven patients with stage III NSCLC were retrospectively studied. Patients received one cycle of cisplatin–gemcitabine, followed by two to three cycles of cisplatin–etoposide concurrently with involved-field thoracic radiotherapy (46–66 Gy; 2 Gy/fraction). Pretherapy regional ventilation images of the lung were derived from 4D computed tomography via a density change–based algorithm with mass correction. In addition to the conventional dose–volume metrics (V{sub 20}, V{sub 30}, V{sub 40}, and mean lung dose),more » dose–function metrics (fV{sub 20}, fV{sub 30}, fV{sub 40}, and functional mean lung dose) were generated by combining regional ventilation and radiation dose. A new class of metrics was derived and referred to as dose–subvolume metrics (sV{sub 20}, sV{sub 30}, sV{sub 40}, and subvolume mean lung dose); these were defined as the conventional dose–volume metrics computed on the functional lung. Area under the receiver operating characteristic curve (AUC) values and logistic regression analyses were used to evaluate these metrics in predicting hallmark characteristics of RF (lung consolidation, volume loss, and airway dilation). Results: AUC values for the dose–volume metrics in predicting lung consolidation, volume loss, and airway dilation were 0.65–0.69, 0.57–0.70, and 0.69–0.76, respectively. The respective ranges for dose–function metrics were 0.63–0.66, 0.61–0.71, and 0.72–0.80 and for dose–subvolume metrics were 0.50–0.65, 0.65–0.75, and 0.73–0.85. Using an AUC value = 0.70 as cutoff value suggested that at least one of each type of metrics (dose–volume, dose–function, dose–subvolume) was predictive for volume loss and airway dilation, whereas lung consolidation cannot be accurately predicted by any of the metrics. Logistic regression analyses showed that dose–function and dose–subvolume metrics were significant (P values ≤ 0.02) in predicting volume airway dilation. Likelihood ratio test showed that when combining dose–function and/or dose–subvolume metrics with dose–volume metrics, the achieved improvements of prediction accuracy on volume loss and airway dilation were significant (P values ≤ 0.04). Conclusions: The authors’ results demonstrated that the inclusion of regional ventilation function improved accuracy in predicting RF. In particular, dose–subvolume metrics provided a promising method for preventing radiation-induced pulmonary complications.« less

The Relation of Student Engagement and Other Admission Metrics to Master of Accounting Student Performance

ERIC Educational Resources Information Center

Buckless, Frank; Krawczyk, Kathy

2016-01-01

This paper examines whether the use of student engagement (SE) information as part of the admissions process can help us to predict student academic success in Master of Accounting (MAC) programs. The association of SE, undergraduate grade point average (UGPA), and Graduate Management Admissions Test (GMAT) score to academic performance was tested…

Techniques for Liquid Rocket Combustion Spontaneous Stability and Rough Combustion Assessments

NASA Technical Reports Server (NTRS)

Kenny, R. J.; Giacomoni, C.; Casiano, M. J.; Fischbach, S. R.

2016-01-01

This work presents techniques for liquid rocket engine combustion stability assessments with respect to spontaneous stability and rough combustion. Techniques covering empirical parameter extraction, which were established in prior works, are applied for three additional programs: the F-1 Gas Generator (F1GG) component test program, the RS-84 preburner component test program, and the Marshall Integrated Test Rig (MITR) program. Stability assessment parameters from these programs are compared against prior established spontaneous stability metrics and updates are identified. Also, a procedure for comparing measured with predicted mode shapes is presented, based on an extension of the Modal Assurance Criterion (MAC).

NASA Aviation Safety Program Systems Analysis/Program Assessment Metrics Review

NASA Technical Reports Server (NTRS)

Louis, Garrick E.; Anderson, Katherine; Ahmad, Tisan; Bouabid, Ali; Siriwardana, Maya; Guilbaud, Patrick

2003-01-01

The goal of this project is to evaluate the metrics and processes used by NASA's Aviation Safety Program in assessing technologies that contribute to NASA's aviation safety goals. There were three objectives for reaching this goal. First, NASA's main objectives for aviation safety were documented and their consistency was checked against the main objectives of the Aviation Safety Program. Next, the metrics used for technology investment by the Program Assessment function of AvSP were evaluated. Finally, other metrics that could be used by the Program Assessment Team (PAT) were identified and evaluated. This investigation revealed that the objectives are in fact consistent across organizational levels at NASA and with the FAA. Some of the major issues discussed in this study which should be further investigated, are the removal of the Cost and Return-on-Investment metrics, the lack of the metrics to measure the balance of investment and technology, the interdependencies between some of the metric risk driver categories, and the conflict between 'fatal accident rate' and 'accident rate' in the language of the Aviation Safety goal as stated in different sources.

Semantic Metrics for Analysis of Software

NASA Technical Reports Server (NTRS)

Etzkorn, Letha H.; Cox, Glenn W.; Farrington, Phil; Utley, Dawn R.; Ghalston, Sampson; Stein, Cara

2005-01-01

A recently conceived suite of object-oriented software metrics focus is on semantic aspects of software, in contradistinction to traditional software metrics, which focus on syntactic aspects of software. Semantic metrics represent a more human-oriented view of software than do syntactic metrics. The semantic metrics of a given computer program are calculated by use of the output of a knowledge-based analysis of the program, and are substantially more representative of software quality and more readily comprehensible from a human perspective than are the syntactic metrics.

Automated Performance Prediction of Message-Passing Parallel Programs

NASA Technical Reports Server (NTRS)

Block, Robert J.; Sarukkai, Sekhar; Mehra, Pankaj; Woodrow, Thomas S. (Technical Monitor)

1995-01-01

The increasing use of massively parallel supercomputers to solve large-scale scientific problems has generated a need for tools that can predict scalability trends of applications written for these machines. Much work has been done to create simple models that represent important characteristics of parallel programs, such as latency, network contention, and communication volume. But many of these methods still require substantial manual effort to represent an application in the model's format. The NIK toolkit described in this paper is the result of an on-going effort to automate the formation of analytic expressions of program execution time, with a minimum of programmer assistance. In this paper we demonstrate the feasibility of our approach, by extending previous work to detect and model communication patterns automatically, with and without overlapped computations. The predictions derived from these models agree, within reasonable limits, with execution times of programs measured on the Intel iPSC/860 and Paragon. Further, we demonstrate the use of MK in selecting optimal computational grain size and studying various scalability metrics.

Automatic documentation system extension to multi-manufacturers' computers and to measure, improve, and predict software reliability

NASA Technical Reports Server (NTRS)

Simmons, D. B.

1975-01-01

The DOMONIC system has been modified to run on the Univac 1108 and the CDC 6600 as well as the IBM 370 computer system. The DOMONIC monitor system has been implemented to gather data which can be used to optimize the DOMONIC system and to predict the reliability of software developed using DOMONIC. The areas of quality metrics, error characterization, program complexity, program testing, validation and verification are analyzed. A software reliability model for estimating program completion levels and one on which to base system acceptance have been developed. The DAVE system which performs flow analysis and error detection has been converted from the University of Colorado CDC 6400/6600 computer to the IBM 360/370 computer system for use with the DOMONIC system.

Texture metric that predicts target detection performance

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.

2015-12-01

Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

App Usage Factor: A Simple Metric to Compare the Population Impact of Mobile Medical Apps.

PubMed

Lewis, Thomas Lorchan; Wyatt, Jeremy C

2015-08-19

One factor when assessing the quality of mobile apps is quantifying the impact of a given app on a population. There is currently no metric which can be used to compare the population impact of a mobile app across different health care disciplines. The objective of this study is to create a novel metric to characterize the impact of a mobile app on a population. We developed the simple novel metric, app usage factor (AUF), defined as the logarithm of the product of the number of active users of a mobile app with the median number of daily uses of the app. The behavior of this metric was modeled using simulated modeling in Python, a general-purpose programming language. Three simulations were conducted to explore the temporal and numerical stability of our metric and a simulated app ecosystem model using a simulated dataset of 20,000 apps. Simulations confirmed the metric was stable between predicted usage limits and remained stable at extremes of these limits. Analysis of a simulated dataset of 20,000 apps calculated an average value for the app usage factor of 4.90 (SD 0.78). A temporal simulation showed that the metric remained stable over time and suitable limits for its use were identified. A key component when assessing app risk and potential harm is understanding the potential population impact of each mobile app. Our metric has many potential uses for a wide range of stakeholders in the app ecosystem, including users, regulators, developers, and health care professionals. Furthermore, this metric forms part of the overall estimate of risk and potential for harm or benefit posed by a mobile medical app. We identify the merits and limitations of this metric, as well as potential avenues for future validation and research.

Systems Engineering Techniques for ALS Decision Making

NASA Technical Reports Server (NTRS)

Rodriquez, Luis F.; Drysdale, Alan E.; Jones, Harry; Levri, Julie A.

2004-01-01

The Advanced Life Support (ALS) Metric is the predominant tool for predicting the cost of ALS systems. Metric goals for the ALS Program are daunting, requiring a threefold increase in the ALS Metric by 2010. Confounding the problem, the rate new ALS technologies reach the maturity required for consideration in the ALS Metric and the rate at which new configurations are developed is slow, limiting the search space and potentially giving the perspective of a ALS technology, the ALS Metric may remain elusive. This paper is a sequel to a paper published in the proceedings of the 2003 ICES conference entitled, "Managing to the metric: an approach to optimizing life support costs." The conclusions of that paper state that the largest contributors to the ALS Metric should be targeted by ALS researchers and management for maximum metric reductions. Certainly, these areas potentially offer large potential benefits to future ALS missions; however, the ALS Metric is not the only decision-making tool available to the community. To facilitate decision-making within the ALS community a combination of metrics should be utilized, such as the Equivalent System Mass (ESM)-based ALS metric, but also those available through techniques such as life cycle costing and faithful consideration of the sensitivity of the assumed models and data. Often a lack of data is cited as the reason why these techniques are not considered for utilization. An existing database development effort within the ALS community, known as OPIS, may provide the opportunity to collect the necessary information to enable the proposed systems analyses. A review of these additional analysis techniques is provided, focusing on the data necessary to enable these. The discussion is concluded by proposing how the data may be utilized by analysts in the future.

Examination of a Rotorcraft Noise Prediction Method and Comparison to Flight Test Data

NASA Technical Reports Server (NTRS)

Boyd, D. Douglas, Jr.; Greenwood, Eric; Watts, Michael E.; Lopes, Leonard V.

2017-01-01

With a view that rotorcraft noise should be included in the preliminary design process, a relatively fast noise prediction method is examined in this paper. A comprehensive rotorcraft analysis is combined with a noise prediction method to compute several noise metrics of interest. These predictions are compared to flight test data. Results show that inclusion of only the main rotor noise will produce results that severely underpredict integrated metrics of interest. Inclusion of the tail rotor frequency content is essential for accurately predicting these integrated noise metrics.

WSEAT Shock Testing Margin Assessment Using Energy Spectra Final Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sisemore, Carl; Babuska, Vit; Booher, Jason

Several programs at Sandia National Laboratories have adopted energy spectra as a metric to relate the severity of mechanical insults to structural capacity. The purpose being to gain insight into the system's capability, reliability, and to quantify the ultimate margin between the normal operating envelope and the likely system failure point -- a system margin assessment. The fundamental concern with the use of energy metrics was that the applicability domain and implementation details were not completely defined for many problems of interest. The goal of this WSEAT project was to examine that domain of applicability and work out the necessarymore » implementation details. The goal of this project was to provide experimental validation for the energy spectra based methods in the context of margin assessment as they relate to shock environments. The extensive test results concluded that failure predictions using energy methods did not agree with failure predictions using S-N data. As a result, a modification to the energy methods was developed following the form of Basquin's equation to incorporate the power law exponent for fatigue damage. This update to the energy-based framework brings the energy based metrics into agreement with experimental data and historical S-N data.« less

Usability: Human Research Program - Space Human Factors and Habitability

NASA Technical Reports Server (NTRS)

Sandor, Aniko; Holden, Kritina L.

2009-01-01

The Usability project addresses the need for research in the area of metrics and methodologies used in hardware and software usability testing in order to define quantifiable and verifiable usability requirements. A usability test is a human-in-the-loop evaluation where a participant works through a realistic set of representative tasks using the hardware/software under investigation. The purpose of this research is to define metrics and methodologies for measuring and verifying usability in the aerospace domain in accordance with FY09 focus on errors, consistency, and mobility/maneuverability. Usability metrics must be predictive of success with the interfaces, must be easy to obtain and/or calculate, and must meet the intent of current Human Systems Integration Requirements (HSIR). Methodologies must work within the constraints of the aerospace domain, be cost and time efficient, and be able to be applied without extensive specialized training.

Predicting Catastrophic BGP Routing Instabilities

DTIC Science & Technology

2004-03-01

predict a BGP routing instability confine their focus to either macro- or micro -level metrics, but not to both. The inherent limitations of each of...Level and Micro -Level Metrics Correlation; Worm Attack Studies; 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified 18. SECURITY... micro -level metrics, but not to both. The inherent limitations of each of these forms of metric gives rise to an excessive rate of spurious alerts

Going Metric...PAL (Programmed Assigned Learning).

ERIC Educational Resources Information Center

Wallace, Jesse D.

This 41-page programed booklet is intended for use by students and adults. It introduces the metric units for length, area, volume, and temperature through a series of questions and answers. The advantages of the metric system over the English system are discussed. Conversion factors are introduced and several applications of the metric system in…

A software technology evaluation program

NASA Technical Reports Server (NTRS)

Novaes-Card, David N.

1985-01-01

A set of quantitative approaches is presented for evaluating software development methods and tools. The basic idea is to generate a set of goals which are refined into quantifiable questions which specify metrics to be collected on the software development and maintenance process and product. These metrics can be used to characterize, evaluate, predict, and motivate. They can be used in an active as well as passive way by learning form analyzing the data and improving the methods and tools based upon what is learned from that analysis. Several examples were given representing each of the different approaches to evaluation. The cost of the approaches varied inversely with the level of confidence in the interpretation of the results.

An evaluation of plastic surgery resident selection factors.

PubMed

Liang, Fan; Rudnicki, Pamela A; Prince, Noah H; Lipsitz, Stuart; May, James W; Guo, Lifei

2015-01-01

Our purpose was to provide a metric by which evaluation criteria are prioritized during resident selection. In this study, we assessed which residency applicant qualities are deemed important by members of the American Association of Plastic Surgeons (AAPS). A survey was distributed to all 580 AAPS members, and 295 responded to rate the importance of resident metrics, including measures of competency and personal characteristics. Demographic information, background training, and interaction with residents were also noted. Using SAS v9.2 (SAS Institute, Cary, NC), outcomes were analyzed across demographic groups with column trend exact (CTE) test for ordinal variables, Mantel-Haenszel trend test for interval variables, and Fisher exact test for discrete variables. Regarding competency metrics, letters of recommendation from known sources is the most important factor, whereas letters from unknown sources ranks the lowest. Character evaluations identified honesty as the most desirable trait; dishonesty was the most despised. Across demographic groups, academic surgeons and program directors value letters from known sources more than nonacademicians or nonprogram directors (CTE p = 0.005 and 0.002, respectively). Academicians and current program directors regard research more highly than their counterparts do (CTE p = 0.022 and 0.022, respectively). Currently, practicing surgeons, academicians, and program directors value hard work more than others (CTE p = 0.008, 0.033, and 0.029, respectively). Program directors emphasize maturity and patient commitment and are less tolerant of narcissism (CTE p = 0.002, 0.005, and 0.003, respectively). Lastly, academic surgeons and program directors look more favorably upon strong team players (CTE p < 0.00001 and p = 0.008, respectively), but less so over time (Mantel-Haenszel trend p = 0.006). We have examined applicant metrics that were deemed important by AAPS members and assessed their demographic interpretation. We hope this article provides a framework for plastic surgery resident selection and a guide for applicants to ascertain which qualities are highly regarded by programs. Although these attributes are highly desirable, future studies could identify if they are predictive of successful and productive plastic surgery residencies and careers. Copyright © 2014 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

A Program Complexity Metric Based on Variable Usage for Algorithmic Thinking Education of Novice Learners

ERIC Educational Resources Information Center

Fuwa, Minori; Kayama, Mizue; Kunimune, Hisayoshi; Hashimoto, Masami; Asano, David K.

2015-01-01

We have explored educational methods for algorithmic thinking for novices and implemented a block programming editor and a simple learning management system. In this paper, we propose a program/algorithm complexity metric specified for novice learners. This metric is based on the variable usage in arithmetic and relational formulas in learner's…

Repeatability in photo-interpretation of tree canopy cover and its effect on predictive mapping

Treesearch

Thomas A. Jackson; Gretchen G. Moisen; Paul L. Patterson; John Tipton

2012-01-01

In this study, we explore repeatability in photo-interpreted imagery from the National Agriculture Imagery Program that was sampled as part of the National Land Cover Database 2011 Tree Canopy Cover pilot project. Data were collected in 5 diverse pilot areas in the US, including one each in Oregon, Utah, Kansas, Michigan and Georgia. Repeatability metrics. The intra-...

A Matched Project Evaluation of Modern Programming Practices. Volume II. Scientific Report on the ASTROS Plan.

DTIC Science & Technology

1980-02-01

formula for predictinq the number of errors during system testing. The equation he presents is B V/ ECRIT where B is the number of 19 ’R , errors...expected, V is the volume, and ECRIT is "the mean number of elementary discriminations between potential errors in programming" (p. 85). E CRIT can also...prediction of delivered bugs is: "V VX 2 B = V/ ECRIT -3- 13,824 2.3 McCabe’s Complexity Metric Thomas McCabe (1976) defined complexity in relation to

Effects of metric hierarchy and rhyme predictability on word duration in The Cat in the Hat.

PubMed

Breen, Mara

2018-05-01

Word durations convey many types of linguistic information, including intrinsic lexical features like length and frequency and contextual features like syntactic and semantic structure. The current study was designed to investigate whether hierarchical metric structure and rhyme predictability account for durational variation over and above other features in productions of a rhyming, metrically-regular children's book: The Cat in the Hat (Dr. Seuss, 1957). One-syllable word durations and inter-onset intervals were modeled as functions of segment number, lexical frequency, word class, syntactic structure, repetition, and font emphasis. Consistent with prior work, factors predicting longer word durations and inter-onset intervals included more phonemes, lower frequency, first mention, alignment with a syntactic boundary, and capitalization. A model parameter corresponding to metric grid height improved model fit of word durations and inter-onset intervals. Specifically, speakers realized five levels of metric hierarchy with inter-onset intervals such that interval duration increased linearly with increased height in the metric hierarchy. Conversely, speakers realized only three levels of metric hierarchy with word duration, demonstrating that they shortened the highly predictable rhyme resolutions. These results further understanding of the factors that affect spoken word duration, and demonstrate the myriad cues that children receive about linguistic structure from nursery rhymes. Copyright © 2018 Elsevier B.V. All rights reserved.

Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale

USGS Publications Warehouse

White, Ian R.; Kennen, Jonathan G.; May, Jason T.; Brown, Larry R.; Cuffney, Thomas F.; Jones, Kimberly A.; Orlando, James L.

2014-01-01

We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R2 for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive.

Stream Macroinvertebrate Response Models for Bioassessment Metrics: Addressing the Issue of Spatial Scale

PubMed Central

Waite, Ian R.; Kennen, Jonathan G.; May, Jason T.; Brown, Larry R.; Cuffney, Thomas F.; Jones, Kimberly A.; Orlando, James L.

2014-01-01

We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R2 for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive. PMID:24675770

A support vector machine for predicting defibrillation outcomes from waveform metrics.

PubMed

Howe, Andrew; Escalona, Omar J; Di Maio, Rebecca; Massot, Bertrand; Cromie, Nick A; Darragh, Karen M; Adgey, Jennifer; McEneaney, David J

2014-03-01

Algorithms to predict shock success based on VF waveform metrics could significantly enhance resuscitation by optimising the timing of defibrillation. To investigate robust methods of predicting defibrillation success in VF cardiac arrest patients, by using a support vector machine (SVM) optimisation approach. Frequency-domain (AMSA, dominant frequency and median frequency) and time-domain (slope and RMS amplitude) VF waveform metrics were calculated in a 4.1Y window prior to defibrillation. Conventional prediction test validity of each waveform parameter was conducted and used AUC>0.6 as the criterion for inclusion as a corroborative attribute processed by the SVM classification model. The latter used a Gaussian radial-basis-function (RBF) kernel and the error penalty factor C was fixed to 1. A two-fold cross-validation resampling technique was employed. A total of 41 patients had 115 defibrillation instances. AMSA, slope and RMS waveform metrics performed test validation with AUC>0.6 for predicting termination of VF and return-to-organised rhythm. Predictive accuracy of the optimised SVM design for termination of VF was 81.9% (± 1.24 SD); positive and negative predictivity were respectively 84.3% (± 1.98 SD) and 77.4% (± 1.24 SD); sensitivity and specificity were 87.6% (± 2.69 SD) and 71.6% (± 9.38 SD) respectively. AMSA, slope and RMS were the best VF waveform frequency-time parameters predictors of termination of VF according to test validity assessment. This a priori can be used for a simplified SVM optimised design that combines the predictive attributes of these VF waveform metrics for improved prediction accuracy and generalisation performance without requiring the definition of any threshold value on waveform metrics. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Center to Advance Palliative Care palliative care clinical care and customer satisfaction metrics consensus recommendations.

PubMed

Weissman, David E; Morrison, R Sean; Meier, Diane E

2010-02-01

Data collection and analysis are vital for strategic planning, quality improvement, and demonstration of palliative care program impact to hospital administrators, private funders and policymakers. Since 2000, the Center to Advance Palliative Care (CAPC) has provided technical assistance to hospitals, health systems and hospices working to start, sustain, and grow nonhospice palliative care programs. CAPC convened a consensus panel in 2008 to develop recommendations for specific clinical and customer metrics that programs should track. The panel agreed on four key domains of clinical metrics and two domains of customer metrics. Clinical metrics include: daily assessment of physical/psychological/spiritual symptoms by a symptom assessment tool; establishment of patient-centered goals of care; support to patient/family caregivers; and management of transitions across care sites. For customer metrics, consensus was reached on two domains that should be tracked to assess satisfaction: patient/family satisfaction, and referring clinician satisfaction. In an effort to ensure access to reliably high-quality palliative care data throughout the nation, hospital palliative care programs are encouraged to collect and report outcomes for each of the metric domains described here.

Comparison of continuous versus categorical tumor measurement-based metrics to predict overall survival in cancer treatment trials.

PubMed

An, Ming-Wen; Mandrekar, Sumithra J; Branda, Megan E; Hillman, Shauna L; Adjei, Alex A; Pitot, Henry C; Goldberg, Richard M; Sargent, Daniel J

2011-10-15

The categorical definition of response assessed via the Response Evaluation Criteria in Solid Tumors has documented limitations. We sought to identify alternative metrics for tumor response that improve prediction of overall survival. Individual patient data from three North Central Cancer Treatment Group trials (N0026, n = 117; N9741, n = 1,109; and N9841, n = 332) were used. Continuous metrics of tumor size based on longitudinal tumor measurements were considered in addition to a trichotomized response [TriTR: response (complete or partial) vs. stable disease vs. progression). Cox proportional hazards models, adjusted for treatment arm and baseline tumor burden, were used to assess the impact of the metrics on subsequent overall survival, using a landmark analysis approach at 12, 16, and 24 weeks postbaseline. Model discrimination was evaluated by the concordance (c) index. The overall best response rates for the three trials were 26%, 45%, and 25%, respectively. Although nearly all metrics were statistically significantly associated with overall survival at the different landmark time points, the concordance indices (c-index) for the traditional response metrics ranged from 0.59 to 0.65; for the continuous metrics from 0.60 to 0.66; and for the TriTR metrics from 0.64 to 0.69. The c-indices for TriTR at 12 weeks were comparable with those at 16 and 24 weeks. Continuous tumor measurement-based metrics provided no predictive improvement over traditional response-based metrics or TriTR; TriTR had better predictive ability than best TriTR or confirmed response. If confirmed, TriTR represents a promising endpoint for future phase II trials. ©2011 AACR.

Comparison of continuous versus categorical tumor measurement-based metrics to predict overall survival in cancer treatment trials

PubMed Central

An, Ming-Wen; Mandrekar, Sumithra J.; Branda, Megan E.; Hillman, Shauna L.; Adjei, Alex A.; Pitot, Henry; Goldberg, Richard M.; Sargent, Daniel J.

2011-01-01

Purpose The categorical definition of response assessed via the Response Evaluation Criteria in Solid Tumors has documented limitations. We sought to identify alternative metrics for tumor response that improve prediction of overall survival. Experimental Design Individual patient data from three North Central Cancer Treatment Group trials (N0026, n=117; N9741, n=1109; N9841, n=332) were used. Continuous metrics of tumor size based on longitudinal tumor measurements were considered in addition to a trichotomized response (TriTR: Response vs. Stable vs. Progression). Cox proportional hazards models, adjusted for treatment arm and baseline tumor burden, were used to assess the impact of the metrics on subsequent overall survival, using a landmark analysis approach at 12-, 16- and 24-weeks post baseline. Model discrimination was evaluated using the concordance (c) index. Results The overall best response rates for the three trials were 26%, 45%, and 25% respectively. While nearly all metrics were statistically significantly associated with overall survival at the different landmark time points, the c-indices for the traditional response metrics ranged from 0.59-0.65; for the continuous metrics from 0.60-0.66 and for the TriTR metrics from 0.64-0.69. The c-indices for TriTR at 12-weeks were comparable to those at 16- and 24-weeks. Conclusions Continuous tumor-measurement-based metrics provided no predictive improvement over traditional response based metrics or TriTR; TriTR had better predictive ability than best TriTR or confirmed response. If confirmed, TriTR represents a promising endpoint for future Phase II trials. PMID:21880789

Development and Application of a Message Metric for NOAA NWS Tsunami Warnings and Recommended Guidelines for the NWS TsunamiReady Program

NASA Astrophysics Data System (ADS)

Gregg, C. E.; Johnston, D. M.; Ricthie, L.; Meinhold, S.; Johnson, V.; Scott, C.; Farnham, C.; Houghton, B. F.; Horan, J.; Gill, D.

2012-12-01

Improving the quality and effectiveness of tsunami warning messages and the TsunamiReady community preparedness program of the US National Oceanic and Atmospheric Administration, National Weather Service's (NWS), Tsunami Program are two key objectives of a three year project (Award NA10NWS4670015) to help integrate social science into the NWS' Tsunami Program and improve the preparedness of member states and territories of the National Tsunami Hazard Mitigation Program (NTHMP). Research was conducted in collaboration with state and local emergency managers. Based on findings from focus group meetings with a purposive sample of local, state and Federal stakeholders and emergency managers in six states (AK, WA, OR, CA, HI and NC) and two US Territories (US Virgin Islands and American Samoa), and upon review of research literature on behavioral response to warnings, we developed a warning message metric to help guide revisions to tsunami warning messages issued by the NWS' West Coast/Alaska Tsunami Warning Center, Alaska and Pacific Tsunami Warning Center, Hawaii. The metric incorporates factors that predict response to warning information, which are divided into categories of Message Content, Style, Order and Formatting and Receiver Characteristics. A message is evaluated by cross-referencing the message with the meaning of metric factors and assigning a maximum score of one point per factor. Findings are then used to guide revisions of the message until the characteristics of each factor are met. From focus groups that gathered information on the usefulness and achievability of tsunami preparedness actions, we developed recommendations for revisions to the proposed draft guidelines of the TsunamiReady Improvement Program. Proposed key revisions include the incorporation of community vulnerability to distant (far-field) versus local (near-field) tsunamis as a primary determinant of mandatory actions, rather than community population. Our team continues to work with NWS personnel, including a NWS Tsunami Warning Improvement Team, and the focus group participants to finalize and pilot test prototype warning products and the draft TsunamiReady guidelines.

GPS Device Testing Based on User Performance Metrics

DOT National Transportation Integrated Search

2015-10-02

1. Rationale for a Test Program Based on User Performance Metrics ; 2. Roberson and Associates Test Program ; 3. Status of, and Revisions to, the Roberson and Associates Test Program ; 4. Comparison of Roberson and DOT/Volpe Programs

Objective measurement of complex multimodal and multidimensional display formats: a common metric for predicting format effectiveness

NASA Astrophysics Data System (ADS)

Marshak, William P.; Darkow, David J.; Wesler, Mary M.; Fix, Edward L.

2000-08-01

Computer-based display designers have more sensory modes and more dimensions within sensory modality with which to encode information in a user interface than ever before. This elaboration of information presentation has made measurement of display/format effectiveness and predicting display/format performance extremely difficult. A multivariate method has been devised which isolates critical information, physically measures its signal strength, and compares it with other elements of the display, which act like background noise. This common Metric relates signal-to-noise ratios (SNRs) within each stimulus dimension, then combines SNRs among display modes, dimensions and cognitive factors can predict display format effectiveness. Examples with their Common Metric assessment and validation in performance will be presented along with the derivation of the metric. Implications of the Common Metric in display design and evaluation will be discussed.

d-Neighborhood system and generalized F-contraction in dislocated metric space.

PubMed

Kumari, P Sumati; Zoto, Kastriot; Panthi, Dinesh

2015-01-01

This paper, gives an answer for the Question 1.1 posed by Hitzler (Generalized metrics and topology in logic programming semantics, 2001) by means of "Topological aspects of d-metric space with d-neighborhood system". We have investigated the topological aspects of a d-neighborhood system obtained from dislocated metric space (simply d-metric space) which has got useful applications in the semantic analysis of logic programming. Further more we have generalized the notion of F-contraction in the view of d-metric spaces and investigated the uniqueness of fixed point and coincidence point of such mappings.

Road Risk Modeling and Cloud-Aided Safety-Based Route Planning.

PubMed

Li, Zhaojian; Kolmanovsky, Ilya; Atkins, Ella; Lu, Jianbo; Filev, Dimitar P; Michelini, John

2016-11-01

This paper presents a safety-based route planner that exploits vehicle-to-cloud-to-vehicle (V2C2V) connectivity. Time and road risk index (RRI) are considered as metrics to be balanced based on user preference. To evaluate road segment risk, a road and accident database from the highway safety information system is mined with a hybrid neural network model to predict RRI. Real-time factors such as time of day, day of the week, and weather are included as correction factors to the static RRI prediction. With real-time RRI and expected travel time, route planning is formulated as a multiobjective network flow problem and further reduced to a mixed-integer programming problem. A V2C2V implementation of our safety-based route planning approach is proposed to facilitate access to real-time information and computing resources. A real-world case study, route planning through the city of Columbus, Ohio, is presented. Several scenarios illustrate how the "best" route can be adjusted to favor time versus safety metrics.

App Usage Factor: A Simple Metric to Compare the Population Impact of Mobile Medical Apps

PubMed Central

Wyatt, Jeremy C

2015-01-01

Background One factor when assessing the quality of mobile apps is quantifying the impact of a given app on a population. There is currently no metric which can be used to compare the population impact of a mobile app across different health care disciplines. Objective The objective of this study is to create a novel metric to characterize the impact of a mobile app on a population. Methods We developed the simple novel metric, app usage factor (AUF), defined as the logarithm of the product of the number of active users of a mobile app with the median number of daily uses of the app. The behavior of this metric was modeled using simulated modeling in Python, a general-purpose programming language. Three simulations were conducted to explore the temporal and numerical stability of our metric and a simulated app ecosystem model using a simulated dataset of 20,000 apps. Results Simulations confirmed the metric was stable between predicted usage limits and remained stable at extremes of these limits. Analysis of a simulated dataset of 20,000 apps calculated an average value for the app usage factor of 4.90 (SD 0.78). A temporal simulation showed that the metric remained stable over time and suitable limits for its use were identified. Conclusions A key component when assessing app risk and potential harm is understanding the potential population impact of each mobile app. Our metric has many potential uses for a wide range of stakeholders in the app ecosystem, including users, regulators, developers, and health care professionals. Furthermore, this metric forms part of the overall estimate of risk and potential for harm or benefit posed by a mobile medical app. We identify the merits and limitations of this metric, as well as potential avenues for future validation and research. PMID:26290093

Driver Injury Risk Variability in Finite Element Reconstructions of Crash Injury Research and Engineering Network (CIREN) Frontal Motor Vehicle Crashes.

PubMed

Gaewsky, James P; Weaver, Ashley A; Koya, Bharath; Stitzel, Joel D

2015-01-01

A 3-phase real-world motor vehicle crash (MVC) reconstruction method was developed to analyze injury variability as a function of precrash occupant position for 2 full-frontal Crash Injury Research and Engineering Network (CIREN) cases. Phase I: A finite element (FE) simplified vehicle model (SVM) was developed and tuned to mimic the frontal crash characteristics of the CIREN case vehicle (Camry or Cobalt) using frontal New Car Assessment Program (NCAP) crash test data. Phase II: The Toyota HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations per case within the SVM. Five occupant positioning variables were varied using a Latin hypercube design of experiments: seat track position, seat back angle, D-ring height, steering column angle, and steering column telescoping position. An additional baseline simulation was performed that aimed to match the precrash occupant position documented in CIREN for each case. Phase III: FE simulations were then performed using kinematic boundary conditions from each vehicle's event data recorder (EDR). HIC15, combined thoracic index (CTI), femur forces, and strain-based injury metrics in the lung and lumbar vertebrae were evaluated to predict injury. Tuning the SVM to specific vehicle models resulted in close matches between simulated and test injury metric data, allowing the tuned SVM to be used in each case reconstruction with EDR-derived boundary conditions. Simulations with the most rearward seats and reclined seat backs had the greatest HIC15, head injury risk, CTI, and chest injury risk. Calculated injury risks for the head, chest, and femur closely correlated to the CIREN occupant injury patterns. CTI in the Camry case yielded a 54% probability of Abbreviated Injury Scale (AIS) 2+ chest injury in the baseline case simulation and ranged from 34 to 88% (mean = 61%) risk in the least and most dangerous occupant positions. The greater than 50% probability was consistent with the case occupant's AIS 2 hemomediastinum. Stress-based metrics were used to predict injury to the lower leg of the Camry case occupant. The regional-level injury metrics evaluated for the Cobalt case occupant indicated a low risk of injury; however, strain-based injury metrics better predicted pulmonary contusion. Approximately 49% of the Cobalt occupant's left lung was contused, though the baseline simulation predicted 40.5% of the lung to be injured. A method to compute injury metrics and risks as functions of precrash occupant position was developed and applied to 2 CIREN MVC FE reconstructions. The reconstruction process allows for quantification of the sensitivity and uncertainty of the injury risk predictions based on occupant position to further understand important factors that lead to more severe MVC injuries.

Metrics for Diagnosing Undersampling in Monte Carlo Tally Estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perfetti, Christopher M.; Rearden, Bradley T.

This study explored the potential of using Markov chain convergence diagnostics to predict the prevalence and magnitude of biases due to undersampling in Monte Carlo eigenvalue and flux tally estimates. Five metrics were applied to two models of pressurized water reactor fuel assemblies and their potential for identifying undersampling biases was evaluated by comparing the calculated test metrics with known biases in the tallies. Three of the five undersampling metrics showed the potential to accurately predict the behavior of undersampling biases in the responses examined in this study.

The use of propensity scores to assess the generalizability of results from randomized trials

PubMed Central

Stuart, Elizabeth A.; Cole, Stephen R.; Bradshaw, Catherine P.; Leaf, Philip J.

2014-01-01

Randomized trials remain the most accepted design for estimating the effects of interventions, but they do not necessarily answer a question of primary interest: Will the program be effective in a target population in which it may be implemented? In other words, are the results generalizable? There has been very little statistical research on how to assess the generalizability, or “external validity,” of randomized trials. We propose the use of propensity-score-based metrics to quantify the similarity of the participants in a randomized trial and a target population. In this setting the propensity score model predicts participation in the randomized trial, given a set of covariates. The resulting propensity scores are used first to quantify the difference between the trial participants and the target population, and then to match, subclassify, or weight the control group outcomes to the population, assessing how well the propensity score-adjusted outcomes track the outcomes actually observed in the population. These metrics can serve as a first step in assessing the generalizability of results from randomized trials to target populations. This paper lays out these ideas, discusses the assumptions underlying the approach, and illustrates the metrics using data on the evaluation of a schoolwide prevention program called Positive Behavioral Interventions and Supports. PMID:24926156

Relationship between Aircraft Noise Contour Area and Noise Levels at Certification Points

NASA Technical Reports Server (NTRS)

Powell, Clemans A.

2003-01-01

The use of sound exposure level contour area reduction has been proposed as an alternative or supplemental metric of progress and success for the NASA Quiet Aircraft Technology program, which currently uses the average of predicted noise reductions at three community locations. As the program has expanded to include reductions in airframe noise as well as reduction due to optimization of operating procedures for lower noise, there is concern that the three-point methodology may not represent a fair measure of benefit to airport communities. This paper addresses several topics related to this proposal: (1) an analytical basis for a relationship between certification noise levels and noise contour areas for departure operations is developed, (2) the relationship between predicted noise contour area and the noise levels measured or predicted at the certification measurement points is examined for a wide range of commercial and business aircraft, and (3) reductions in contour area for low-noise approach scenarios are predicted and equivalent reductions in source noise are determined.

14 CFR 1260.115 - Metric system of measurement.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Institutions of Higher Education, Hospitals, and Other Non-Profit Organizations Pre-Award Requirements § 1260... Usage in Federal Government Programs.” NASA's policy with respect to the metric measurement system is stated in NASA Policy Directive (NPD) 8010.2, Use of the Metric System of Measurement in NASA Programs. ...

14 CFR § 1260.115 - Metric system of measurement.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Institutions of Higher Education, Hospitals, and Other Non-Profit Organizations Pre-Award Requirements § 1260... Usage in Federal Government Programs.” NASA's policy with respect to the metric measurement system is stated in NASA Policy Directive (NPD) 8010.2, Use of the Metric System of Measurement in NASA Programs. ...

Establishing Qualitative Software Metrics in Department of the Navy Programs

DTIC Science & Technology

2015-10-29

dedicated to provide the highest quality software to its users. In doing, there is a need for a formalized set of Software Quality Metrics . The goal...of this paper is to establish the validity of those necessary Quality metrics . In our approach we collected the data of over a dozen programs...provide the necessary variable data for our formulas and tested the formulas for validity. Keywords: metrics ; software; quality I. PURPOSE Space

Validation metrics for turbulent plasma transport

DOE PAGES

Holland, C.

2016-06-22

Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnosticsmore » to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. Furthermore, the utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak, as part of a multi-year transport model validation activity.« less

Validation metrics for turbulent plasma transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holland, C.

Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnosticsmore » to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. Furthermore, the utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak, as part of a multi-year transport model validation activity.« less

Quality Metrics in Neonatal and Pediatric Critical Care Transport: A National Delphi Project.

PubMed

Schwartz, Hamilton P; Bigham, Michael T; Schoettker, Pamela J; Meyer, Keith; Trautman, Michael S; Insoft, Robert M

2015-10-01

The transport of neonatal and pediatric patients to tertiary care facilities for specialized care demands monitoring the quality of care delivered during transport and its impact on patient outcomes. In 2011, pediatric transport teams in Ohio met to identify quality indicators permitting comparisons among programs. However, no set of national consensus quality metrics exists for benchmarking transport teams. The aim of this project was to achieve national consensus on appropriate neonatal and pediatric transport quality metrics. Modified Delphi technique. The first round of consensus determination was via electronic mail survey, followed by rounds of consensus determination in-person at the American Academy of Pediatrics Section on Transport Medicine's 2012 Quality Metrics Summit. All attendees of the American Academy of Pediatrics Section on Transport Medicine Quality Metrics Summit, conducted on October 21-23, 2012, in New Orleans, LA, were eligible to participate. Candidate quality metrics were identified through literature review and those metrics currently tracked by participating programs. Participants were asked in a series of rounds to identify "very important" quality metrics for transport. It was determined a priori that consensus on a metric's importance was achieved when at least 70% of respondents were in agreement. This is consistent with other Delphi studies. Eighty-two candidate metrics were considered initially. Ultimately, 12 metrics achieved consensus as "very important" to transport. These include metrics related to airway management, team mobilization time, patient and crew injuries, and adverse patient care events. Definitions were assigned to the 12 metrics to facilitate uniform data tracking among programs. The authors succeeded in achieving consensus among a diverse group of national transport experts on 12 core neonatal and pediatric transport quality metrics. We propose that transport teams across the country use these metrics to benchmark and guide their quality improvement activities.

Evaluation of Vehicle-Based Crash Severity Metrics.

PubMed

Tsoi, Ada H; Gabler, Hampton C

2015-01-01

Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes. The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000-2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2-) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy. The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric estimate to be a significant predictor in the model (p < 0.05). For the belted drivers, both OIV and VPI were significantly better predictors of serious injury than delta-v (p < 0.05). For the unbelted drivers, there was no statistically significant difference between delta-v, OIV, VPI, and ASI. The broad findings of this study suggest it is feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.

Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can freely available at https://github.com/NwpuSY/DT_all.git for academic users. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Metrics of Software Quality.

DTIC Science & Technology

1980-11-01

Systems: A Raytheon Project History", RADC-TR-77-188, Final Technical Report, June 1977. 4. IBM Federal Systems Division, "Statistical Prediction of...147, June 1979. 4. W. D. Brooks, R. W. Motley, "Analysis of Discrete Software Reliability Models", IBM Corp., RADC-TR-80-84, RADC, New York, April 1980...J. C. King of IBM (Reference 9) and Lori A. Clark (Reference 10) of the University of Massachusetts. Programs, so exercised must be augmented so they

Surveillance metrics sensitivity study.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamada, Michael S.; Bierbaum, Rene Lynn; Robertson, Alix A.

2011-09-01

In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculationsmore » and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.« less

Surveillance Metrics Sensitivity Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bierbaum, R; Hamada, M; Robertson, A

2011-11-01

In September of 2009, a Tri-Lab team was formed to develop a set of metrics relating to the NNSA nuclear weapon surveillance program. The purpose of the metrics was to develop a more quantitative and/or qualitative metric(s) describing the results of realized or non-realized surveillance activities on our confidence in reporting reliability and assessing the stockpile. As a part of this effort, a statistical sub-team investigated various techniques and developed a complementary set of statistical metrics that could serve as a foundation for characterizing aspects of meeting the surveillance program objectives. The metrics are a combination of tolerance limit calculationsmore » and power calculations, intending to answer level-of-confidence type questions with respect to the ability to detect certain undesirable behaviors (catastrophic defects, margin insufficiency defects, and deviations from a model). Note that the metrics are not intended to gauge product performance but instead the adequacy of surveillance. This report gives a short description of four metrics types that were explored and the results of a sensitivity study conducted to investigate their behavior for various inputs. The results of the sensitivity study can be used to set the risk parameters that specify the level of stockpile problem that the surveillance program should be addressing.« less

Launch Vehicle Production and Operations Cost Metrics

NASA Technical Reports Server (NTRS)

Watson, Michael D.; Neeley, James R.; Blackburn, Ruby F.

2014-01-01

Traditionally, launch vehicle cost has been evaluated based on $/Kg to orbit. This metric is calculated based on assumptions not typically met by a specific mission. These assumptions include the specified orbit whether Low Earth Orbit (LEO), Geostationary Earth Orbit (GEO), or both. The metric also assumes the payload utilizes the full lift mass of the launch vehicle, which is rarely true even with secondary payloads.1,2,3 Other approaches for cost metrics have been evaluated including unit cost of the launch vehicle and an approach to consider the full program production and operations costs.4 Unit cost considers the variable cost of the vehicle and the definition of variable costs are discussed. The full program production and operation costs include both the variable costs and the manufacturing base. This metric also distinguishes operations costs from production costs, including pre-flight operational testing. Operations costs also consider the costs of flight operations, including control center operation and maintenance. Each of these 3 cost metrics show different sensitivities to various aspects of launch vehicle cost drivers. The comparison of these metrics provides the strengths and weaknesses of each yielding an assessment useful for cost metric selection for launch vehicle programs.

Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising.

PubMed

Guixeres, Jaime; Bigné, Enrique; Ausín Azofra, Jose M; Alcañiz Raya, Mariano; Colomer Granero, Adrián; Fuentes Hurtado, Félix; Naranjo Ornedo, Valery

2017-01-01

The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy) and estimate the number of online views (mean error of 0.199). The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube.

Consumer Neuroscience-Based Metrics Predict Recall, Liking and Viewing Rates in Online Advertising

PubMed Central

Guixeres, Jaime; Bigné, Enrique; Ausín Azofra, Jose M.; Alcañiz Raya, Mariano; Colomer Granero, Adrián; Fuentes Hurtado, Félix; Naranjo Ornedo, Valery

2017-01-01

The purpose of the present study is to investigate whether the effectiveness of a new ad on digital channels (YouTube) can be predicted by using neural networks and neuroscience-based metrics (brain response, heart rate variability and eye tracking). Neurophysiological records from 35 participants were exposed to 8 relevant TV Super Bowl commercials. Correlations between neurophysiological-based metrics, ad recall, ad liking, the ACE metrix score and the number of views on YouTube during a year were investigated. Our findings suggest a significant correlation between neuroscience metrics and self-reported of ad effectiveness and the direct number of views on the YouTube channel. In addition, and using an artificial neural network based on neuroscience metrics, the model classifies (82.9% of average accuracy) and estimate the number of online views (mean error of 0.199). The results highlight the validity of neuromarketing-based techniques for predicting the success of advertising responses. Practitioners can consider the proposed methodology at the design stages of advertising content, thus enhancing advertising effectiveness. The study pioneers the use of neurophysiological methods in predicting advertising success in a digital context. This is the first article that has examined whether these measures could actually be used for predicting views for advertising on YouTube. PMID:29163251

Coverage Metrics for Model Checking

NASA Technical Reports Server (NTRS)

Penix, John; Visser, Willem; Norvig, Peter (Technical Monitor)

2001-01-01

When using model checking to verify programs in practice, it is not usually possible to achieve complete coverage of the system. In this position paper we describe ongoing research within the Automated Software Engineering group at NASA Ames on the use of test coverage metrics to measure partial coverage and provide heuristic guidance for program model checking. We are specifically interested in applying and developing coverage metrics for concurrent programs that might be used to support certification of next generation avionics software.

Expert Consensus on Metrics to Assess the Impact of Patient-Level Antimicrobial Stewardship Interventions in Acute-Care Settings

PubMed Central

Anderson, Deverick J.; Cochran, Ronda L.; Hicks, Lauri A.; Srinivasan, Arjun; Dodds Ashley, Elizabeth S.

2017-01-01

Antimicrobial stewardship programs (ASPs) positively impact patient care, but metrics to assess ASP impact are poorly defined. We used a modified Delphi approach to select relevant metrics for assessing patient-level interventions in acute-care settings for the purposes of internal program decision making. An expert panel rated 90 candidate metrics on a 9-point Likert scale for association with 4 criteria: improved antimicrobial prescribing, improved patient care, utility in targeting stewardship efforts, and feasibility in hospitals with electronic health records. Experts further refined, added, or removed metrics during structured teleconferences and re-rated the retained metrics. Six metrics were rated >6 in all criteria: 2 measures of Clostridium difficile incidence, incidence of drug-resistant pathogens, days of therapy over admissions, days of therapy over patient days, and redundant therapy events. Fourteen metrics rated >6 in all criteria except feasibility were identified as targets for future development. PMID:27927866

Classifying the health of Connecticut streams using benthic macroinvertebrates with implications for water management.

PubMed

Bellucci, Christopher J; Becker, Mary E; Beauchene, Mike; Dunbar, Lee

2013-06-01

Bioassessments have formed the foundation of many water quality monitoring programs throughout the United States. Like many state water quality programs, Connecticut has developed a relational database containing information about species richness, species composition, relative abundance, and feeding relationships among macroinvertebrates present in stream and river systems. Geographic Information Systems can provide estimates of landscape condition and watershed characteristics and when combined with measurements of stream biology, provide a useful visual display of information that is useful in a management context. The objective of our study was to estimate the stream health for all wadeable stream kilometers in Connecticut using a combination of macroinvertebrate metrics and landscape variables. We developed and evaluated models using an information theoretic approach to predict stream health as measured by macroinvertebrate multimetric index (MMI) and identified the best fitting model as a three variable model, including percent impervious land cover, a wetlands metric, and catchment slope that best fit the MMI scores (adj-R (2) = 0.56, SE = 11.73). We then provide examples of how modeling can augment existing programs to support water management policies under the Federal Clean Water Act such as stream assessments and anti-degradation.

From the eyes and the heart: a novel eye-gaze metric that predicts video preferences of a large audience

PubMed Central

Christoforou, Christoforos; Christou-Champi, Spyros; Constantinidou, Fofi; Theodorou, Maria

2015-01-01

Eye-tracking has been extensively used to quantify audience preferences in the context of marketing and advertising research, primarily in methodologies involving static images or stimuli (i.e., advertising, shelf testing, and website usability). However, these methodologies do not generalize to narrative-based video stimuli where a specific storyline is meant to be communicated to the audience. In this paper, a novel metric based on eye-gaze dispersion (both within and across viewings) that quantifies the impact of narrative-based video stimuli to the preferences of large audiences is presented. The metric is validated in predicting the performance of video advertisements aired during the 2014 Super Bowl final. In particular, the metric is shown to explain 70% of the variance in likeability scores of the 2014 Super Bowl ads as measured by the USA TODAY Ad-Meter. In addition, by comparing the proposed metric with Heart Rate Variability (HRV) indices, we have associated the metric with biological processes relating to attention allocation. The underlying idea behind the proposed metric suggests a shift in perspective when it comes to evaluating narrative-based video stimuli. In particular, it suggests that audience preferences on video are modulated by the level of viewers lack of attention allocation. The proposed metric can be calculated on any narrative-based video stimuli (i.e., movie, narrative content, emotional content, etc.), and thus has the potential to facilitate the use of such stimuli in several contexts: prediction of audience preferences of movies, quantitative assessment of entertainment pieces, prediction of the impact of movie trailers, identification of group, and individual differences in the study of attention-deficit disorders, and the study of desensitization to media violence. PMID:26029135

From the eyes and the heart: a novel eye-gaze metric that predicts video preferences of a large audience.

PubMed

Christoforou, Christoforos; Christou-Champi, Spyros; Constantinidou, Fofi; Theodorou, Maria

2015-01-01

Eye-tracking has been extensively used to quantify audience preferences in the context of marketing and advertising research, primarily in methodologies involving static images or stimuli (i.e., advertising, shelf testing, and website usability). However, these methodologies do not generalize to narrative-based video stimuli where a specific storyline is meant to be communicated to the audience. In this paper, a novel metric based on eye-gaze dispersion (both within and across viewings) that quantifies the impact of narrative-based video stimuli to the preferences of large audiences is presented. The metric is validated in predicting the performance of video advertisements aired during the 2014 Super Bowl final. In particular, the metric is shown to explain 70% of the variance in likeability scores of the 2014 Super Bowl ads as measured by the USA TODAY Ad-Meter. In addition, by comparing the proposed metric with Heart Rate Variability (HRV) indices, we have associated the metric with biological processes relating to attention allocation. The underlying idea behind the proposed metric suggests a shift in perspective when it comes to evaluating narrative-based video stimuli. In particular, it suggests that audience preferences on video are modulated by the level of viewers lack of attention allocation. The proposed metric can be calculated on any narrative-based video stimuli (i.e., movie, narrative content, emotional content, etc.), and thus has the potential to facilitate the use of such stimuli in several contexts: prediction of audience preferences of movies, quantitative assessment of entertainment pieces, prediction of the impact of movie trailers, identification of group, and individual differences in the study of attention-deficit disorders, and the study of desensitization to media violence.

CT Texture Analysis of Ex Vivo Renal Stones Predicts Ease of Fragmentation with Shockwave Lithotripsy.

PubMed

Cui, Helen W; Devlies, Wout; Ravenscroft, Samuel; Heers, Hendrik; Freidin, Andrew J; Cleveland, Robin O; Ganeshan, Balaji; Turney, Benjamin W

2017-07-01

Understanding the factors affecting success of extracorporeal shockwave lithotripsy (SWL) would improve informed decision-making on the most appropriate treatment modality for an individual patient. Although stone size and skin-to-stone distance do correlate with fragmentation efficacy, it has been shown that stone composition and architecture, as reflected by structural heterogeneity on CT, are also important factors. This study aims to determine if CT texture analysis (CTTA), a novel, nondestructive, and objective tool that generates statistical metrics reflecting stone heterogeneity, could have utility in predicting likelihood of SWL success. Seven spontaneously passed, intact renal tract stones, were scanned ex vivo using standard CT KUB and micro-CT. The stones were then fragmented in vitro using a clinical lithotripter, after which, chemical composition analysis was performed. CTTA was used to generate a number of metrics that were correlated to the number of shocks needed to fragment the stone. CTTA metrics reflected stone characteristics and composition, and predicted ease of SWL fragmentation. The strongest correlation with number of shocks required to fragment the stone was mean Hounsfield unit (HU) density (r = 0.806, p = 0.028) and a CTTA metric measuring the entropy of the pixel distribution of the stone image (r = 0.804, p = 0.039). Using multiple linear regression analysis, the best model showed that CTTA metrics of entropy and kurtosis could predict 92% of the outcome of number of shocks needed to fragment the stone. This was superior to using stone volume or density. CTTA metrics entropy and kurtosis have been shown in this experimental ex vivo setting to strongly predict fragmentation by SWL. This warrants further investigation in a larger clinical study for the contribution of CT textural metrics as a measure of stone heterogeneity, along with other known clinical factors, to predict likelihood of SWL success.

Establishing Quantitative Software Metrics in Department of the Navy Programs

DTIC Science & Technology

2016-04-01

13 Quality to Metrics Dependency Matrix...11 7. Quality characteristics to metrics dependecy matrix...In accomplishing this goal, a need exists for a formalized set of software quality metrics . This document establishes the validity of those necessary

Ten Commonly Asked Questions by Teachers About Metric Education

ERIC Educational Resources Information Center

Thompson, Thomas E.

1977-01-01

Lists and answers the ten questions most frequently asked by teachers in inservice programs on metric system education. Questions include ones about reasons for converting to metrics and successful methods, activities, and materials for teaching metrics. (CS)

Experimental constraints on metric and non-metric theories of gravity

NASA Technical Reports Server (NTRS)

Will, Clifford M.

1989-01-01

Experimental constraints on metric and non-metric theories of gravitation are reviewed. Tests of the Einstein Equivalence Principle indicate that only metric theories of gravity are likely to be viable. Solar system experiments constrain the parameters of the weak field, post-Newtonian limit to be close to the values predicted by general relativity. Future space experiments will provide further constraints on post-Newtonian gravity.

Validation metrics for turbulent plasma transport

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holland, C., E-mail: chholland@ucsd.edu

Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnosticsmore » to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. The utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak [J. L. Luxon, Nucl. Fusion 42, 614 (2002)], as part of a multi-year transport model validation activity.« less

Validation of a Quality Management Metric

DTIC Science & Technology

2000-09-01

quality management metric (QMM) was used to measure the performance of ten software managers on Department of Defense (DoD) software development programs. Informal verification and validation of the metric compared the QMM score to an overall program success score for the entire program and yielded positive correlation. The results of applying the QMM can be used to characterize the quality of software management and can serve as a template to improve software management performance. Future work includes further refining the QMM, applying the QMM scores to provide feedback

TU-CD-BRB-09: Prediction of Chemo-Radiation Outcome for Rectal Cancer Based On Radiomics of Tumor Clinical Characteristics and Multi-Parametric MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nie, K; Yue, N; Shi, L

2015-06-15

Purpose: To evaluate the tumor clinical characteristics and quantitative multi-parametric MR imaging features for prediction of response to chemo-radiation treatment (CRT) in locally advanced rectal cancer (LARC). Methods: Forty-three consecutive patients (59.7±6.9 years, from 09/2013 – 06/2014) receiving neoadjuvant CRT followed by surgery were enrolled. All underwent MRI including anatomical T1/T2, Dynamic Contrast Enhanced (DCE)-MRI and Diffusion-Weighted MRI (DWI) prior to the treatment. A total of 151 quantitative features, including morphology/Gray Level Co-occurrence Matrix (GLCM) texture from T1/T2, enhancement kinetics and the voxelized distribution from DCE-MRI, apparent diffusion coefficient (ADC) from DWI, along with clinical information (carcinoembryonic antigen CEA level,more » TNM staging etc.), were extracted for each patient. Response groups were separated based on down-staging, good response and pathological complete response (pCR) status. Logistic regression analysis (LRA) was used to select the best predictors to classify different groups and the predictive performance were calculated using receiver operating characteristic (ROC) analysis. Results: Individual imaging category or clinical charateristics might yield certain level of power in assessing the response. However, the combined model outperformed than any category alone in prediction. With selected features as Volume, GLCM AutoCorrelation (T2), MaxEnhancementProbability (DCE-MRI), and MeanADC (DWI), the down-staging prediciton accuracy (area under the ROC curve, AUC) could be 0.95, better than individual tumor metrics with AUC from 0.53–0.85. While for the pCR prediction, the best set included CEA (clinical charateristics), Homogeneity (DCE-MRI) and MeanADC (DWI) with an AUC of 0.89, more favorable compared to conventional tumor metrics with an AUC ranging from 0.511–0.79. Conclusion: Through a systematic analysis of multi-parametric MR imaging features, we are able to build models with improved predictive value over conventional imaging or clinical metrics. This is encouraging, suggesting the wealth of imaging radiomics should be further explored to help tailor the treatment into the era of personalized medicine. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National High Technology Research and Development Program of China (863 program, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.« less

Uncertainty quantification metrics for whole product life cycle cost estimates in aerospace innovation

NASA Astrophysics Data System (ADS)

Schwabe, O.; Shehab, E.; Erkoyuncu, J.

2015-08-01

The lack of defensible methods for quantifying cost estimate uncertainty over the whole product life cycle of aerospace innovations such as propulsion systems or airframes poses a significant challenge to the creation of accurate and defensible cost estimates. Based on the axiomatic definition of uncertainty as the actual prediction error of the cost estimate, this paper provides a comprehensive overview of metrics used for the uncertainty quantification of cost estimates based on a literature review, an evaluation of publicly funded projects such as part of the CORDIS or Horizon 2020 programs, and an analysis of established approaches used by organizations such NASA, the U.S. Department of Defence, the ESA, and various commercial companies. The metrics are categorized based on their foundational character (foundations), their use in practice (state-of-practice), their availability for practice (state-of-art) and those suggested for future exploration (state-of-future). Insights gained were that a variety of uncertainty quantification metrics exist whose suitability depends on the volatility of available relevant information, as defined by technical and cost readiness level, and the number of whole product life cycle phases the estimate is intended to be valid for. Information volatility and number of whole product life cycle phases can hereby be considered as defining multi-dimensional probability fields admitting various uncertainty quantification metric families with identifiable thresholds for transitioning between them. The key research gaps identified were the lacking guidance grounded in theory for the selection of uncertainty quantification metrics and lacking practical alternatives to metrics based on the Central Limit Theorem. An innovative uncertainty quantification framework consisting of; a set-theory based typology, a data library, a classification system, and a corresponding input-output model are put forward to address this research gap as the basis for future work in this field.

Experimental evaluation of model predictive control and inverse dynamics control for spacecraft proximity and docking maneuvers

NASA Astrophysics Data System (ADS)

Virgili-Llop, Josep; Zagaris, Costantinos; Park, Hyeongjun; Zappulla, Richard; Romano, Marcello

2018-03-01

An experimental campaign has been conducted to evaluate the performance of two different guidance and control algorithms on a multi-constrained docking maneuver. The evaluated algorithms are model predictive control (MPC) and inverse dynamics in the virtual domain (IDVD). A linear-quadratic approach with a quadratic programming solver is used for the MPC approach. A nonconvex optimization problem results from the IDVD approach, and a nonlinear programming solver is used. The docking scenario is constrained by the presence of a keep-out zone, an entry cone, and by the chaser's maximum actuation level. The performance metrics for the experiments and numerical simulations include the required control effort and time to dock. The experiments have been conducted in a ground-based air-bearing test bed, using spacecraft simulators that float over a granite table.

Auralization of NASA N+2 Aircraft Concepts from System Noise Predictions

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Burley, Casey L.; Thomas, Russel H.

2016-01-01

Auralization of aircraft flyover noise provides an auditory experience that complements integrated metrics obtained from system noise predictions. Recent efforts have focused on auralization methods development, specifically the process by which source noise information obtained from semi-empirical models, computational aeroacoustic analyses, and wind tunnel and flight test data, are used for simulated flyover noise at a receiver on the ground. The primary focus of this work, however, is to develop full vehicle auralizations in order to explore the distinguishing features of NASA's N+2 aircraft vis-à-vis current fleet reference vehicles for single-aisle and large twin-aisle classes. Some features can be seen in metric time histories associated with aircraft noise certification, e.g., tone-corrected perceived noise level used in the calculation of effective perceived noise level. Other features can be observed in sound quality metrics, e.g., loudness, sharpness, roughness, fluctuation strength and tone-to-noise ratio. A psychoacoustic annoyance model is employed to establish the relationship between sound quality metrics and noise certification metrics. Finally, the auralizations will serve as the basis for a separate psychoacoustic study aimed at assessing how well aircraft noise certification metrics predict human annoyance for these advanced vehicle concepts.

Comparison of ISS Power System Telemetry with Analytically Derived Data for Shadowed Cases

NASA Technical Reports Server (NTRS)

Fincannon, H. James

2002-01-01

Accurate International Space Station (ISS) power prediction requires the quantification of solar array shadowing. Prior papers have discussed the NASA Glenn Research Center (GRC) ISS power system tool SPACE (System Power Analysis for Capability Evaluation) and its integrated shadowing algorithms. On-orbit telemetry has become available that permits the correlation of theoretical shadowing predictions with actual data. This paper documents the comparison of a shadowing metric (total solar array current) as derived from SPACE predictions and on-orbit flight telemetry data for representative significant shadowing cases. Images from flight video recordings and the SPACE computer program graphical output are used to illustrate the comparison. The accuracy of the SPACE shadowing capability is demonstrated for the cases examined.

Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US

USGS Publications Warehouse

Waite, Ian R.; Brown, Larry R.; Kennen, Jonathan G.; May, Jason T.; Cuffney, Thomas F.; Orlando, James L.; Jones, Kimberly A.

2010-01-01

The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metrics of biological condition such as richness, tolerance, percent predators, index of biotic integrity, functional species traits, or even ordination axes scores. Our primary intent was to determine if effective models could be developed using watershed characteristics of disturbance to predict macroinvertebrate metrics among disparate and widely separated ecoregions. We aggregated macroinvertebrate data from universities and state and federal agencies in order to assemble stream data sets of high enough density appropriate for modeling in three distinct ecoregions in Oregon and California. Extensive review and quality assurance of macroinvertebrate sampling protocols, laboratory subsample counts and taxonomic resolution was completed to assure data comparability. We used widely available digital coverages of land-use and land-cover data summarized at the watershed and riparian scale as explanatory variables to predict macroinvertebrate metrics commonly used by state resource managers to assess stream condition. The “best” multiple linear regression models from each region required only two or three explanatory variables to model macroinvertebrate metrics and explained 41–74% of the variation. In each region the best model contained some measure of urban and/or agricultural land-use, yet often the model was improved by including a natural explanatory variable such as mean annual precipitation or mean watershed slope. Two macroinvertebrate metrics were common among all three regions, the metric that summarizes the richness of tolerant macroinvertebrates (RICHTOL) and some form of EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness. Best models were developed for the same two invertebrate metrics even though the geographic regions reflect distinct differences in precipitation, geology, elevation, slope, population density, and land-use. With further development, models like these can be used to elicit better causal linkages to stream biological attributes or condition and can be used by researchers or managers to predict biological indicators of stream condition at unsampled sites.

Fronto-Temporal Connectivity Predicts ECT Outcome in Major Depression.

PubMed

Leaver, Amber M; Wade, Benjamin; Vasavada, Megha; Hellemann, Gerhard; Joshi, Shantanu H; Espinoza, Randall; Narr, Katherine L

2018-01-01

Electroconvulsive therapy (ECT) is arguably the most effective available treatment for severe depression. Recent studies have used MRI data to predict clinical outcome to ECT and other antidepressant therapies. One challenge facing such studies is selecting from among the many available metrics, which characterize complementary and sometimes non-overlapping aspects of brain function and connectomics. Here, we assessed the ability of aggregated, functional MRI metrics of basal brain activity and connectivity to predict antidepressant response to ECT using machine learning. A radial support vector machine was trained using arterial spin labeling (ASL) and blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) metrics from n = 46 (26 female, mean age 42) depressed patients prior to ECT (majority right-unilateral stimulation). Image preprocessing was applied using standard procedures, and metrics included cerebral blood flow in ASL, and regional homogeneity, fractional amplitude of low-frequency modulations, and graph theory metrics (strength, local efficiency, and clustering) in BOLD data. A 5-repeated 5-fold cross-validation procedure with nested feature-selection validated model performance. Linear regressions were applied post hoc to aid interpretation of discriminative features. The range of balanced accuracy in models performing statistically above chance was 58-68%. Here, prediction of non-responders was slightly higher than for responders (maximum performance 74 and 64%, respectively). Several features were consistently selected across cross-validation folds, mostly within frontal and temporal regions. Among these were connectivity strength among: a fronto-parietal network [including left dorsolateral prefrontal cortex (DLPFC)], motor and temporal networks (near ECT electrodes), and/or subgenual anterior cingulate cortex (sgACC). Our data indicate that pattern classification of multimodal fMRI metrics can successfully predict ECT outcome, particularly for individuals who will not respond to treatment. Notably, connectivity with networks highly relevant to ECT and depression were consistently selected as important predictive features. These included the left DLPFC and the sgACC, which are both targets of other neurostimulation therapies for depression, as well as connectivity between motor and right temporal cortices near electrode sites. Future studies that probe additional functional and structural MRI metrics and other patient characteristics may further improve the predictive power of these and similar models.

Correlation of spatial climate/weather maps and the advantages of using the Mahalanobis metric in predictions

NASA Astrophysics Data System (ADS)

Stephenson, D. B.

1997-10-01

The skill in predicting spatially varying weather/climate maps depends on the definition of the measure of similarity between the maps. Under the justifiable approximation that the anomaly maps are distributed multinormally, it is shown analytically that the choice of weighting metric, used in defining the anomaly correlation between spatial maps, can change the resulting probability distribution of the correlation coefficient. The estimate of the numbers of degrees of freedom based on the variance of the correlation distribution can vary from unity up to the number of grid points depending on the choice of weighting metric. The (pseudo-) inverse of the sample covariance matrix acts as a special choice for the metric in that it gives a correlation distribution which has minimal kurtosis and maximum dimension. Minimal kurtosis suggests that the average predictive skill might be improved due to the rarer occurrence of troublesome outlier patterns far from the mean state. Maximum dimension has a disadvantage for analogue prediction schemes in that it gives the minimum number of analogue states. This metric also has an advantage in that it allows one to powerfully test the null hypothesis of multinormality by examining the second and third moments of the correlation coefficient which were introduced by Mardia as invariant measures of multivariate kurtosis and skewness. For these reasons, it is suggested that this metric could be usefully employed in the prediction of weather/climate and in fingerprinting anthropogenic climate change. The ideas are illustrated using the bivariate example of the observed monthly mean sea-level pressures at Darwin and Tahitifrom 1866 1995.

Gamut Volume Index: a color preference metric based on meta-analysis and optimized colour samples.

PubMed

Liu, Qiang; Huang, Zheng; Xiao, Kaida; Pointer, Michael R; Westland, Stephen; Luo, M Ronnier

2017-07-10

A novel metric named Gamut Volume Index (GVI) is proposed for evaluating the colour preference of lighting. This metric is based on the absolute gamut volume of optimized colour samples. The optimal colour set of the proposed metric was obtained by optimizing the weighted average correlation between the metric predictions and the subjective ratings for 8 psychophysical studies. The performance of 20 typical colour metrics was also investigated, which included colour difference based metrics, gamut based metrics, memory based metrics as well as combined metrics. It was found that the proposed GVI outperformed the existing counterparts, especially for the conditions where correlated colour temperatures differed.

Summer temperature metrics for predicting brook trout (Salvelinus fontinalis) distribution in streams

USGS Publications Warehouse

Parrish, Donna; Butryn, Ryan S.; Rizzo, Donna M.

2012-01-01

We developed a methodology to predict brook trout (Salvelinus fontinalis) distribution using summer temperature metrics as predictor variables. Our analysis used long-term fish and hourly water temperature data from the Dog River, Vermont (USA). Commonly used metrics (e.g., mean, maximum, maximum 7-day maximum) tend to smooth the data so information on temperature variation is lost. Therefore, we developed a new set of metrics (called event metrics) to capture temperature variation by describing the frequency, area, duration, and magnitude of events that exceeded a user-defined temperature threshold. We used 16, 18, 20, and 22°C. We built linear discriminant models and tested and compared the event metrics against the commonly used metrics. Correct classification of the observations was 66% with event metrics and 87% with commonly used metrics. However, combined event and commonly used metrics correctly classified 92%. Of the four individual temperature thresholds, it was difficult to assess which threshold had the “best” accuracy. The 16°C threshold had slightly fewer misclassifications; however, the 20°C threshold had the fewest extreme misclassifications. Our method leveraged the volumes of existing long-term data and provided a simple, systematic, and adaptable framework for monitoring changes in fish distribution, specifically in the case of irregular, extreme temperature events.

Advanced Life Support System Value Metric

NASA Technical Reports Server (NTRS)

Jones, Harry W.; Rasky, Daniel J. (Technical Monitor)

1999-01-01

The NASA Advanced Life Support (ALS) Program is required to provide a performance metric to measure its progress in system development. Extensive discussions within the ALS program have led to the following approach. The Equivalent System Mass (ESM) metric has been traditionally used and provides a good summary of the weight, size, and power cost factors of space life support equipment. But ESM assumes that all the systems being traded off exactly meet a fixed performance requirement, so that the value and benefit (readiness, performance, safety, etc.) of all the different systems designs are considered to be exactly equal. This is too simplistic. Actual system design concepts are selected using many cost and benefit factors and the system specification is defined after many trade-offs. The ALS program needs a multi-parameter metric including both the ESM and a System Value Metric (SVM). The SVM would include safety, maintainability, reliability, performance, use of cross cutting technology, and commercialization potential. Another major factor in system selection is technology readiness level (TRL), a familiar metric in ALS. The overall ALS system metric that is suggested is a benefit/cost ratio, SVM/[ESM + function (TRL)], with appropriate weighting and scaling. The total value is given by SVM. Cost is represented by higher ESM and lower TRL. The paper provides a detailed description and example application of a suggested System Value Metric and an overall ALS system metric.

Green Power Partnership Program Success Metrics

EPA Pesticide Factsheets

The U.S. EPA's Green Power Partnership is a voluntary program designed to reduce the environmental impact of electricity generation by promoting renewable energy. EPA evaluates partnership metrics annually to determine progress toward programmatic goals.

Advanced Life Support System Value Metric

NASA Technical Reports Server (NTRS)

Jones, Harry W.; Arnold, James O. (Technical Monitor)

1999-01-01

The NASA Advanced Life Support (ALS) Program is required to provide a performance metric to measure its progress in system development. Extensive discussions within the ALS program have reached a consensus. The Equivalent System Mass (ESM) metric has been traditionally used and provides a good summary of the weight, size, and power cost factors of space life support equipment. But ESM assumes that all the systems being traded off exactly meet a fixed performance requirement, so that the value and benefit (readiness, performance, safety, etc.) of all the different systems designs are exactly equal. This is too simplistic. Actual system design concepts are selected using many cost and benefit factors and the system specification is then set accordingly. The ALS program needs a multi-parameter metric including both the ESM and a System Value Metric (SVM). The SVM would include safety, maintainability, reliability, performance, use of cross cutting technology, and commercialization potential. Another major factor in system selection is technology readiness level (TRL), a familiar metric in ALS. The overall ALS system metric that is suggested is a benefit/cost ratio, [SVM + TRL]/ESM, with appropriate weighting and scaling. The total value is the sum of SVM and TRL. Cost is represented by ESM. The paper provides a detailed description and example application of the suggested System Value Metric.

Direct CFD Predictions of Low Frequency Sounds Generated by a Helicopter Main Rotor

DTIC Science & Technology

2010-05-01

modeling and grid constraints. NOTATION α Shaft tilt (corrected) or tip-path-plane angle BPF Blade passing frequency CT/σ Thrust coefficient to rotor...cyclic pitch angle, deg. LFSPL Low frequency sound metric (1st-6th BPF ), dB MFSPL Mid frequency sound metric (> 6th BPF ), dB OASPL Overall sound metric...Tunnel of the National Full- Scale Aerodynamic Complex (NFAC) at NASA Ames Research Center in 2008 (Fig. 2a), as a guide for prediction validation. The

Validity of the Medical College Admission Test for predicting MD-PhD student outcomes.

PubMed

Bills, James L; VanHouten, Jacob; Grundy, Michelle M; Chalkley, Roger; Dermody, Terence S

2016-03-01

The Medical College Admission Test (MCAT) is a quantitative metric used by MD and MD-PhD programs to evaluate applicants for admission. This study assessed the validity of the MCAT in predicting training performance measures and career outcomes for MD-PhD students at a single institution. The study population consisted of 153 graduates of the Vanderbilt Medical Scientist Training Program (combined MD-PhD program) who matriculated between 1963 and 2003 and completed dual-degree training. This population was divided into three cohorts corresponding to the version of the MCAT taken at the time of application. Multivariable regression (logistic for binary outcomes and linear for continuous outcomes) was used to analyze factors associated with outcome measures. The MCAT score and undergraduate GPA (uGPA) were treated as independent variables; medical and graduate school grades, time-to-PhD defense, USMLE scores, publication number, and career outcome were dependent variables. For cohort 1 (1963-1977), MCAT score was not associated with any assessed outcome, although uGPA was associated with medical school preclinical GPA and graduate school GPA (gsGPA). For cohort 2 (1978-1991), MCAT score was associated with USMLE Step II score and inversely correlated with publication number, and uGPA was associated with preclinical GPA (mspGPA) and clinical GPA (mscGPA). For cohort 3 (1992-2003), the MCAT score was associated with mscGPA, and uGPA was associated with gsGPA. Overall, MCAT score and uGPA were inconsistent or weak predictors of training metrics and career outcomes for this population of MD-PhD students.

Key Metrics and Goals for NASA's Advanced Air Transportation Technologies Program

NASA Technical Reports Server (NTRS)

Kaplan, Bruce; Lee, David

1998-01-01

NASA's Advanced Air Transportation Technologies (AATT) program is developing a set of decision support tools to aid air traffic service providers, pilots, and airline operations centers in improving operations of the National Airspace System (NAS). NASA needs a set of unifying metrics to tie these efforts together, which it can use to track the progress of the AATT program and communicate program objectives and status within NASA and to stakeholders in the NAS. This report documents the results of our efforts and the four unifying metrics we recommend for the AATT program. They are: airport peak capacity, on-route sector capacity, block time and fuel, and free flight-enabling.

Expedited CT-Based Methods for Evaluating Fracture Severity to Assess Risk of Post-Traumatic Osteoarthritis After Articular Fractures.

PubMed

Anderson, Donald D; Kilburg, Anthony T; Thomas, Thaddeus P; Marsh, J Lawrence

2016-01-01

Post-traumatic osteoarthritis (PTOA) is common after intra-articular fractures of the tibial plafond. An objective CT-based measure of fracture severity was previously found to reliably predict whether PTOA developed following surgical treatment of such fractures. However, the extended time required obtaining the fracture energy metric and its reliance upon an intact contralateral limb CT limited its clinical applicability. The objective of this study was to establish an expedited fracture severity metric that provided comparable PTOA predictive ability without the prior limitations. An expedited fracture severity metric was computed from the CT scans of 30 tibial plafond fractures using textural analysis to quantify disorder in CT images. The expedited method utilized an intact surrogate model to enable severity assessment without requiring a contralateral limb CT. Agreement between the expedited fracture severity metric and the Kellgren-Lawrence (KL) radiographic OA score at two-year follow-up was assessed using concordance. The ability of the metric to differentiate between patients that did or did not develop PTOA was assessed using the Wilcoxon Ranked Sum test. The expedited severity metric agreed well (75.2% concordance) with the KL scores. The initial fracture severity of cases that developed PTOA differed significantly (p = 0.004) from those that did not. Receiver operating characteristic analysis showed that the expedited severity metric could accurately predict PTOA outcome in 80% of the cases. The time required to obtain the expedited severity metric averaged 14.9 minutes/ case, and the metric was obtained without using an intact contralateral CT. The expedited CT-based methods for fracture severity assessment present a solution to issues limiting the utility of prior methods. In a relatively short amount of time, the expedited methodology provided a severity score capable of predicting PTOA risk, without needing to have the intact contralateral limb included in the CT scan. The described methods provide surgeons an objective, quantitative representation of the severity of a fracture. Obtained prior to the surgery, it provides a reasonable alternative to current subjective classification systems. The expedited severity metric offers surgeons an objective means for factoring severity of joint insult into treatment decision-making.

Performance evaluation of objective quality metrics for HDR image compression

NASA Astrophysics Data System (ADS)

Valenzise, Giuseppe; De Simone, Francesca; Lauga, Paul; Dufaux, Frederic

2014-09-01

Due to the much larger luminance and contrast characteristics of high dynamic range (HDR) images, well-known objective quality metrics, widely used for the assessment of low dynamic range (LDR) content, cannot be directly applied to HDR images in order to predict their perceptual fidelity. To overcome this limitation, advanced fidelity metrics, such as the HDR-VDP, have been proposed to accurately predict visually significant differences. However, their complex calibration may make them difficult to use in practice. A simpler approach consists in computing arithmetic or structural fidelity metrics, such as PSNR and SSIM, on perceptually encoded luminance values but the performance of quality prediction in this case has not been clearly studied. In this paper, we aim at providing a better comprehension of the limits and the potentialities of this approach, by means of a subjective study. We compare the performance of HDR-VDP to that of PSNR and SSIM computed on perceptually encoded luminance values, when considering compressed HDR images. Our results show that these simpler metrics can be effectively employed to assess image fidelity for applications such as HDR image compression.

Human-centric predictive model of task difficulty for human-in-the-loop control tasks

PubMed Central

Majewicz Fey, Ann

2018-01-01

Quantitatively measuring the difficulty of a manipulation task in human-in-the-loop control systems is ill-defined. Currently, systems are typically evaluated through task-specific performance measures and post-experiment user surveys; however, these methods do not capture the real-time experience of human users. In this study, we propose to analyze and predict the difficulty of a bivariate pointing task, with a haptic device interface, using human-centric measurement data in terms of cognition, physical effort, and motion kinematics. Noninvasive sensors were used to record the multimodal response of human user for 14 subjects performing the task. A data-driven approach for predicting task difficulty was implemented based on several task-independent metrics. We compare four possible models for predicting task difficulty to evaluated the roles of the various types of metrics, including: (I) a movement time model, (II) a fusion model using both physiological and kinematic metrics, (III) a model only with kinematic metrics, and (IV) a model only with physiological metrics. The results show significant correlation between task difficulty and the user sensorimotor response. The fusion model, integrating user physiology and motion kinematics, provided the best estimate of task difficulty (R2 = 0.927), followed by a model using only kinematic metrics (R2 = 0.921). Both models were better predictors of task difficulty than the movement time model (R2 = 0.847), derived from Fitt’s law, a well studied difficulty model for human psychomotor control. PMID:29621301

A Teacher's Guide to Metrics. A Series of In-Service Booklets Designed for Adult Educators.

ERIC Educational Resources Information Center

Wendel, Robert, Ed.; And Others

This series of seven booklets is designed to train teachers of adults in metrication, as a prerequisite to offering metrics in adult basic education and general educational development programs. The seven booklets provide a guide representing an integration of metric teaching methods and metric materials to place the adult in an active learning…

Evaluation of a Metric Booklet as a Supplement to Teaching the Metric System to Undergraduate Non-Science Majors.

ERIC Educational Resources Information Center

Exum, Kenith Gene

Examined is the effectiveness of a method of teaching the metric system using the booklet, Metric Supplement to Mathematics, in combination with a physical science textbook. The participants in the study were randomly selected undergraduates in a non-science oriented program of study. Instruments used included the Metric Supplement to Mathematics…

Dose-distance metric that predicts late rectal bleeding in patients receiving radical prostate external-beam radiotherapy

NASA Astrophysics Data System (ADS)

Lee, Richard; Chan, Elisa K.; Kosztyla, Robert; Liu, Mitchell; Moiseenko, Vitali

2012-12-01

The relationship between rectal dose distribution and the incidence of late rectal complications following external-beam radiotherapy has been previously studied using dose-volume histograms or dose-surface histograms. However, they do not account for the spatial dose distribution. This study proposes a metric based on both surface dose and distance that can predict the incidence of rectal bleeding in prostate cancer patients treated with radical radiotherapy. One hundred and forty-four patients treated with radical radiotherapy for prostate cancer were prospectively followed to record the incidence of grade ≥2 rectal bleeding. Radiotherapy plans were used to evaluate a dose-distance metric that accounts for the dose and its spatial distribution on the rectal surface, characterized by a logistic weighting function with slope a and inflection point d0. This was compared to the effective dose obtained from dose-surface histograms, characterized by the parameter n which describes sensitivity to hot spots. The log-rank test was used to determine statistically significant (p < 0.05) cut-off values for the dose-distance metric and effective dose that predict for the occurrence of rectal bleeding. For the dose-distance metric, only d0 = 25 and 30 mm combined with a > 5 led to statistical significant cut-offs. For the effective dose metric, only values of n in the range 0.07-0.35 led to statistically significant cut-offs. The proposed dose-distance metric is a predictor of rectal bleeding in prostate cancer patients treated with radiotherapy. Both the dose-distance metric and the effective dose metric indicate that the incidence of grade ≥2 rectal bleeding is sensitive to localized damage to the rectal surface.

Metrics for linear kinematic features in sea ice

NASA Astrophysics Data System (ADS)

Levy, G.; Coon, M.; Sulsky, D.

2006-12-01

The treatment of leads as cracks or discontinuities (see Coon et al. presentation) requires some shift in the procedure of evaluation and comparison of lead-resolving models and their validation against observations. Common metrics used to evaluate ice model skills are by and large an adaptation of a least square "metric" adopted from operational numerical weather prediction data assimilation systems and are most appropriate for continuous fields and Eilerian systems where the observations and predictions are commensurate. However, this class of metrics suffers from some flaws in areas of sharp gradients and discontinuities (e.g., leads) and when Lagrangian treatments are more natural. After a brief review of these metrics and their performance in areas of sharp gradients, we present two new metrics specifically designed to measure model accuracy in representing linear features (e.g., leads). The indices developed circumvent the requirement that both the observations and model variables be commensurate (i.e., measured with the same units) by considering the frequencies of the features of interest/importance. We illustrate the metrics by scoring several hypothetical "simulated" discontinuity fields against the lead interpreted from RGPS observations.

Sound quality evaluation of air conditioning sound rating metric

NASA Astrophysics Data System (ADS)

Hodgdon, Kathleen K.; Peters, Jonathan A.; Burkhardt, Russell C.; Atchley, Anthony A.; Blood, Ingrid M.

2003-10-01

A product's success can depend on its acoustic signature as much as on the product's performance. The consumer's perception can strongly influence their satisfaction with and confidence in the product. A metric that can rate the content of the spectrum, and predict its consumer preference, is a valuable tool for manufacturers. The current method of assessing acoustic signatures from residential air conditioning units is defined in the Air Conditioning and Refrigeration Institute (ARI 270) 1995 Standard for Sound Rating of Outdoor Unitary Equipment. The ARI 270 metric, and modified versions of that metric, were implemented in software with the flexibility to modify the features applied. Numerous product signatures were analyzed to generate a set of synthesized spectra that targeted spectral configurations that challenged the metric's abilities. A subjective jury evaluation was conducted to establish the consumer preference for those spectra. Statistical correlations were conducted to assess the degree of relationship between the subjective preferences and the various metric calculations. Recommendations were made for modifications to improve the current metric's ability to predict subjective preference. [Research supported by the Air Conditioning and Refrigeration Institute.

Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection.

PubMed

DeWeber, Jefferson T; Wagner, Tyler

2018-06-01

Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30-day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species' distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold-water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid-century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects. © 2018 John Wiley & Sons Ltd.

Probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty from maximum temperature metric selection

USGS Publications Warehouse

DeWeber, Jefferson T.; Wagner, Tyler

2018-01-01

Predictions of the projected changes in species distributions and potential adaptation action benefits can help guide conservation actions. There is substantial uncertainty in projecting species distributions into an unknown future, however, which can undermine confidence in predictions or misdirect conservation actions if not properly considered. Recent studies have shown that the selection of alternative climate metrics describing very different climatic aspects (e.g., mean air temperature vs. mean precipitation) can be a substantial source of projection uncertainty. It is unclear, however, how much projection uncertainty might stem from selecting among highly correlated, ecologically similar climate metrics (e.g., maximum temperature in July, maximum 30‐day temperature) describing the same climatic aspect (e.g., maximum temperatures) known to limit a species’ distribution. It is also unclear how projection uncertainty might propagate into predictions of the potential benefits of adaptation actions that might lessen climate change effects. We provide probabilistic measures of climate change vulnerability, adaptation action benefits, and related uncertainty stemming from the selection of four maximum temperature metrics for brook trout (Salvelinus fontinalis), a cold‐water salmonid of conservation concern in the eastern United States. Projected losses in suitable stream length varied by as much as 20% among alternative maximum temperature metrics for mid‐century climate projections, which was similar to variation among three climate models. Similarly, the regional average predicted increase in brook trout occurrence probability under an adaptation action scenario of full riparian forest restoration varied by as much as .2 among metrics. Our use of Bayesian inference provides probabilistic measures of vulnerability and adaptation action benefits for individual stream reaches that properly address statistical uncertainty and can help guide conservation actions. Our study demonstrates that even relatively small differences in the definitions of climate metrics can result in very different projections and reveal high uncertainty in predicted climate change effects.

Linking hydrodynamic complexity to delta smelt (Hypomesus transpacificus) distribution in the San Francisco Estuary, USA

USGS Publications Warehouse

Bever, Aaron J.; MacWilliams, Michael L.; Herbold, Bruce; Brown, Larry R.; Feyrer, Frederick V.

2016-01-01

Long-term fish sampling data from the San Francisco Estuary were combined with detailed three dimensional hydrodynamic modeling to investigate the relationship between historical fish catch and hydrodynamic complexity. Delta Smelt catch data at 45 stations from the Fall Midwater Trawl (FMWT) survey in the vicinity of Suisun Bay were used to develop a quantitative catch-based station index. This index was used to rank stations based on historical Delta Smelt catch. The correlations between historical Delta Smelt catch and 35 quantitative metrics of environmental complexity were evaluated at each station. Eight metrics of environmental conditions were derived from FMWT data and 27 metrics were derived from model predictions at each FMWT station. To relate the station index to conceptual models of Delta Smelt habitat, the metrics were used to predict the station ranking based on the quantified environmental conditions. Salinity, current speed, and turbidity metrics were used to predict the relative ranking of each station for Delta Smelt catch. Including a measure of the current speed at each station improved predictions of the historical ranking for Delta Smelt catch relative to similar predictions made using only salinity and turbidity. Current speed was also found to be a better predictor of historical Delta Smelt catch than water depth. The quantitative approach developed using the FMWT data was validated using the Delta Smelt catch data from the San Francisco Bay Study. Complexity metrics in Suisun Bay were-evaluated during 2010 and 2011. This analysis indicated that a key to historical Delta Smelt catch is the overlap of low salinity, low maximum velocity, and low Secchi depth regions. This overlap occurred in Suisun Bay during 2011, and may have contributed to higher Delta Smelt abundance in 2011 than in 2010 when the favorable ranges of the metrics did not overlap in Suisun Bay.

Sensitivity, Specificity, and Predictive Values: Foundations, Pliabilities, and Pitfalls in Research and Practice.

PubMed

Trevethan, Robert

2017-01-01

Within the context of screening tests, it is important to avoid misconceptions about sensitivity, specificity, and predictive values. In this article, therefore, foundations are first established concerning these metrics along with the first of several aspects of pliability that should be recognized in relation to those metrics. Clarification is then provided about the definitions of sensitivity, specificity, and predictive values and why researchers and clinicians can misunderstand and misrepresent them. Arguments are made that sensitivity and specificity should usually be applied only in the context of describing a screening test's attributes relative to a reference standard; that predictive values are more appropriate and informative in actual screening contexts, but that sensitivity and specificity can be used for screening decisions about individual people if they are extremely high; that predictive values need not always be high and might be used to advantage by adjusting the sensitivity and specificity of screening tests; that, in screening contexts, researchers should provide information about all four metrics and how they were derived; and that, where necessary, consumers of health research should have the skills to interpret those metrics effectively for maximum benefit to clients and the healthcare system.

Sensitivity, Specificity, and Predictive Values: Foundations, Pliabilities, and Pitfalls in Research and Practice

PubMed Central

Trevethan, Robert

2017-01-01

Within the context of screening tests, it is important to avoid misconceptions about sensitivity, specificity, and predictive values. In this article, therefore, foundations are first established concerning these metrics along with the first of several aspects of pliability that should be recognized in relation to those metrics. Clarification is then provided about the definitions of sensitivity, specificity, and predictive values and why researchers and clinicians can misunderstand and misrepresent them. Arguments are made that sensitivity and specificity should usually be applied only in the context of describing a screening test’s attributes relative to a reference standard; that predictive values are more appropriate and informative in actual screening contexts, but that sensitivity and specificity can be used for screening decisions about individual people if they are extremely high; that predictive values need not always be high and might be used to advantage by adjusting the sensitivity and specificity of screening tests; that, in screening contexts, researchers should provide information about all four metrics and how they were derived; and that, where necessary, consumers of health research should have the skills to interpret those metrics effectively for maximum benefit to clients and the healthcare system. PMID:29209603

Metrics in Career Education.

ERIC Educational Resources Information Center

Lindbeck, John R.

The United States is rapidly becoming a metric nation. Industry, education, business, and government are all studying the issue of metrication to learn how they can prepare for it. The book is designed to help teachers and students in career education programs learn something about metrics. Presented in an easily understood manner, the textbook's…

The Adult Conversion to Metrics: Is Education Enough?

ERIC Educational Resources Information Center

Kundel, Susan E.

1979-01-01

The American College Testing Program sought to determine whether metric education for adult consumers would result in more positive attitudes to metric conversion. Examining preopinion, pretest, posttest, post-opinion, and background data, the researchers found that simply teaching adults how to use the metric system does not significantly affect…

Understanding Acceptance of Software Metrics--A Developer Perspective

ERIC Educational Resources Information Center

Umarji, Medha

2009-01-01

Software metrics are measures of software products and processes. Metrics are widely used by software organizations to help manage projects, improve product quality and increase efficiency of the software development process. However, metrics programs tend to have a high failure rate in organizations, and developer pushback is one of the sources…

Handbook of Classroom and Workshop Metric Activity Stations.

ERIC Educational Resources Information Center

Illinois State Office of Education, Springfield.

The objectives of this handbook are to assist K-8 classroom teachers in launching an activity-oriented metric program that provides learning experiences in the measurement strands of linear, mass, and temperature, and to assist metric coordinators in planning metric awareness workshops for teachers, parents, and various community organizations.…

NEW CATEGORICAL METRICS FOR AIR QUALITY MODEL EVALUATION

EPA Science Inventory

Traditional categorical metrics used in model evaluations are "clear-cut" measures in that the model's ability to predict an exceedance is defined by a fixed threshold concentration and the metrics are defined by observation-forecast sets that are paired both in space and time. T...

Satellite Capabilities Mapping - Utilizing Small Satellites

DTIC Science & Technology

2010-09-01

Metrics Definition…………………………..50 Figure 19. System and Requirements Decomposition…………………………………...59 Figure 20. TPS Fuctional Mapping Process...offered by small satellites. “The primary force in our corner of the universe is our sun. The sun is constantly radiating enormous amounts of...weather prediction models, a primary tool for forecasting weather” [19]. The NPOESS was a tri-agency program intended to develop and operate the next

ASSESSING THE PREDICTIVE CAPABILITY OF LANDSCAPE SAMPLING UNITS OF VARYING SCALE IN THE ANALYSIS OF ESTUARINE CONDITION

EPA Science Inventory

Landscape structure metrics are often used to predict water and sediment quality of lakes, streams, and estuaries; however, the sampling units used to generate the landscape metrics are often at an irrelevant spatial scale. They are either too large (i.e., an entire watershed) or...

Manual dexterity aptitude testing: a soap carving study.

PubMed

Tang, Christopher G; Hilsinger, Raymond L; Cruz, Raul M; Schloegel, Luke J; Byl, Fred M; Rasgon, Barry M

2014-03-01

Currently there are few validated metrics for predicting surgical skill among otolaryngology residency applicants. To determine whether manual dexterity aptitude testing in the form of soap carving during otolaryngology residency interviews at Kaiser Permanente Medical Center Oakland predicts surgical skill at the time of graduation from otolaryngology residency programs. This study was conducted to determine how applicants with the best and worst soap carvings compared at the time of graduation with respect to various metrics including visuospatial ability and manual dexterity. Over the last 25 years, applicants to the residency program at Kaiser Permanente Oakland were required to carve soap during their residency interview. The 3 best and 3 worst soap carvings from 1990 through 2006 were determined. Of the individuals who carved those soaps, 62 qualified for the study and matriculated into otolaryngology residency programs. Surveys were sent to the 62 individuals' residency programs to evaluate those individuals on a 5-point Likert scale in various categories as well as to rank those individuals as being in the top 50% or bottom 50% of their graduating class. All else being equal, we hypothesized that applicants who had the manual dexterity and visuospatial skills to accurately carve a bar of soap would more likely possess the skills necessary to become a good surgeon. There was no difference between individuals with the best soap carvings and those with the worst soap carvings in all categories: cognitive knowledge, visuospatial ability, manual dexterity, decision making, and overall score (P > .10 for all categories). There was a 95% response rate, with 35 of 37 residency programs responding and 59 of 62 surveys returned. Manual dexterity aptitude testing in the form of soap carving does not appear to correlate with surgical skill at the time of graduation. Further studies need to be conducted to determine the role of manual dexterity and visuospatial aptitude testing in the otolaryngology application process.

Predicting the natural flow regime: Models for assessing hydrological alteration in streams

USGS Publications Warehouse

Carlisle, D.M.; Falcone, J.; Wolock, D.M.; Meador, M.R.; Norris, R.H.

2009-01-01

Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also demonstrate how the models can be applied to predict expected natural flow characteristics at ungaged sites. ?? 2009 John Wiley & Sons, Ltd.

Developing Metrics in Systems Integration (ISS Program COTS Integration Model)

NASA Technical Reports Server (NTRS)

Lueders, Kathryn

2007-01-01

This viewgraph presentation reviews some of the complications in developing metrics for systems integration. Specifically it reviews a case study of how two programs within NASA try to develop and measure performance while meeting the encompassing organizational goals.

Research on cardiovascular disease prediction based on distance metric learning

NASA Astrophysics Data System (ADS)

Ni, Zhuang; Liu, Kui; Kang, Guixia

2018-04-01

Distance metric learning algorithm has been widely applied to medical diagnosis and exhibited its strengths in classification problems. The k-nearest neighbour (KNN) is an efficient method which treats each feature equally. The large margin nearest neighbour classification (LMNN) improves the accuracy of KNN by learning a global distance metric, which did not consider the locality of data distributions. In this paper, we propose a new distance metric algorithm adopting cosine metric and LMNN named COS-SUBLMNN which takes more care about local feature of data to overcome the shortage of LMNN and improve the classification accuracy. The proposed methodology is verified on CVDs patient vector derived from real-world medical data. The Experimental results show that our method provides higher accuracy than KNN and LMNN did, which demonstrates the effectiveness of the Risk predictive model of CVDs based on COS-SUBLMNN.

Security Metrics: A Solution in Search of a Problem

ERIC Educational Resources Information Center

Rosenblatt, Joel

2008-01-01

Computer security is one of the most complicated and challenging fields in technology today. A security metrics program provides a major benefit: looking at the metrics on a regular basis offers early clues to changes in attack patterns or environmental factors that may require changes in security strategy. The term "security metrics"…

Evaluation of ride quality prediction methods for operational military helicopters

NASA Technical Reports Server (NTRS)

Leatherwood, J. D.; Clevenson, S. A.; Hollenbaugh, D. D.

1984-01-01

The results of a simulator study conducted to compare and validate various ride quality prediction methods for use in assessing passenger/crew ride comfort within helicopters are presented. Included are results quantifying 35 helicopter pilots' discomfort responses to helicopter interior noise and vibration typical of routine flights, assessment of various ride quality metrics including the NASA ride comfort model, and examination of possible criteria approaches. Results of the study indicated that crew discomfort results from a complex interaction between vibration and interior noise. Overall measures such as weighted or unweighted root-mean-square acceleration level and A-weighted noise level were not good predictors of discomfort. Accurate prediction required a metric incorporating the interactive effects of both noise and vibration. The best metric for predicting crew comfort to the combined noise and vibration environment was the NASA discomfort index.

VA residential substance use disorder treatment program providers' perceptions of facilitators and barriers to performance on pre-admission processes.

PubMed

Ellerbe, Laura S; Manfredi, Luisa; Gupta, Shalini; Phelps, Tyler E; Bowe, Thomas R; Rubinsky, Anna D; Burden, Jennifer L; Harris, Alex H S

2017-04-04

In the U.S. Department of Veterans Affairs (VA), residential treatment programs are an important part of the continuum of care for patients with a substance use disorder (SUD). However, a limited number of program-specific measures to identify quality gaps in SUD residential programs exist. This study aimed to: (1) Develop metrics for two pre-admission processes: Wait Time and Engagement While Waiting, and (2) Interview program management and staff about program structures and processes that may contribute to performance on these metrics. The first aim sought to supplement the VA's existing facility-level performance metrics with SUD program-level metrics in order to identify high-value targets for quality improvement. The second aim recognized that not all key processes are reflected in the administrative data, and even when they are, new insight may be gained from viewing these data in the context of day-to-day clinical practice. VA administrative data from fiscal year 2012 were used to calculate pre-admission metrics for 97 programs (63 SUD Residential Rehabilitation Treatment Programs (SUD RRTPs); 34 Mental Health Residential Rehabilitation Treatment Programs (MH RRTPs) with a SUD track). Interviews were then conducted with management and front-line staff to learn what factors may have contributed to high or low performance, relative to the national average for their program type. We hypothesized that speaking directly to residential program staff may reveal innovative practices, areas for improvement, and factors that may explain system-wide variability in performance. Average wait time for admission was 16 days (SUD RRTPs: 17 days; MH RRTPs with a SUD track: 11 days), with 60% of Veterans waiting longer than 7 days. For these Veterans, engagement while waiting occurred in an average of 54% of the waiting weeks (range 3-100% across programs). Fifty-nine interviews representing 44 programs revealed factors perceived to potentially impact performance in these domains. Efficient screening processes, effective patient flow, and available beds were perceived to facilitate shorter wait times, while lack of beds, poor staffing levels, and lengths of stay of existing patients were thought to lengthen wait times. Accessible outpatient services, strong patient outreach, and strong encouragement of pre-admission outpatient treatment emerged as facilitators of engagement while waiting; poor staffing levels, socioeconomic barriers, and low patient motivation were viewed as barriers. Metrics for pre-admission processes can be helpful for monitoring residential SUD treatment programs. Interviewing program management and staff about drivers of performance metrics can play a complementary role by identifying innovative and other strong practices, as well as high-value targets for quality improvement. Key facilitators of high-performing facilities may offer programs with lower performance useful strategies to improve specific pre-admission processes.

The Use of Remote Sensing for Monitoring, Prediction, and Management of Hydrologic, Agricultural, and Ecological Processes in the Northern Great Plains

NASA Technical Reports Server (NTRS)

Farwell, Sherry O.; DeTroye, Diane (Technical Monitor)

2002-01-01

The NASA-EPSCoR program in South Dakota is focused on the enhancement of NASA-related research in earth system science and corresponding infrastructure development to support this theme. Hence, the program has adopted a strategy that keys on research projects that: a) establish quantitative links between geospatial information technologies and fundamental climatic and ecosystem processes in the Northern Great Plains (NGP) and b) develop and use coupled modeling tools, which can be initialized by data from combined satellite and surface measurements, to provide reliable predictions and management guidance for hydrologic, agricultural, and ecological systems of the NGP. Building a partnership network that includes both internal and external team members is recognized as an essential element of the SD NASA-EPSCoR program. Hence, promoting and tracking such linkages along with their relevant programmatic consequences are used as one metric to assess the program's progress and success. This annual report first summarizes general activities and accomplishments, and then provides progress narratives for the two separate, yet related research projects that are essential components of the SD NASA-EPSCoR program.

Effects of time delay and pitch control sensitivity in the flared landing

NASA Technical Reports Server (NTRS)

Berthe, C. J.; Chalk, C. R.; Wingarten, N. C.; Grantham, W.

1986-01-01

Between December 1985 and January 1986, a flared landing program was conducted, using the USAF Total In-Flight simulator airplane, to examine time delay effects in a formal manner. Results show that as pitch sensitivity is increased, tolerance to time delay decreases. With the proper selection of pitch sensitivity, Level I performance was maintained with time delays ranging from 150 milliseconds to greater than 300 milliseconds. With higher sensitivity, configurations with Level I performance at 150 milliseconds degraded to level 2 at 200 milliseconds. When metrics of time delay and pitch sensitivity effects are applied to enhance previously developed predictive criteria, the result is an improved prediction technique which accounts for significant closed loop items.

SU-C-16A-05: OAR Dose Tolerance Recommendations for Prostate and Cervical HDR Brachytherapy: Dose Versus Volume Metrics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geneser, S; Cunha, J; Pouliot, J

Purpose: HDR brachytherapy consensus dose tolerance recommendations for organs at risk (OARs) remain widely debated. Prospective trials reporting metrics must be sufficiently data-dense to assess adverse affects and identify optimally predictive tolerances. We explore the tradeoffs between reporting dose-metrics versus volume-metrics and the potential impact on trial outcome analysis and tolerance recommendations. Methods: We analyzed 26 prostate patients receiving 15 Gy HDR single-fraction brachytherapy boost to 45 Gy external beam radiation therapy and 28 cervical patients receiving 28 Gy HDR brachytherapy monotherapy in 4 fractions using 2 implants. For each OAR structure, a robust linear regression fit was performed formore » the dose-metrics as a function of the volume-metrics. The plan quality information provided by recommended dose-metric and volume-metric values were compared. Results: For prostate rectal dose, D2cc and V75 lie close to the regression line, indicating they are similarly informative. Two outliers for prostate urethral dose are substantially different from the remaining cohort in terms of D0.1cc and V75, but not D1cc, suggesting the choice of reporting dose metric is essential. For prostate bladder and cervical bladder, rectum, and bowel, dose outliers are more apparent via V75 than recommended dose-metrics. This suggests that for prostate bladder dose and all cervical OAR doses, the recommended volume-metrics may be better predictors of clinical outcome than dose-metrics. Conclusion: For plan acceptance criteria, dose and volume-metrics are reciprocally equivalent. However, reporting dosemetrics or volume-metrics alone provides substantially different information. Our results suggest that volume-metrics may be more sensitive to differences in planned dose, and if one metric must be chosen, volumemetrics are preferable. However, reporting discrete DVH points severely limits the ability to identify planning tolerances most predictive of adverse effects. Thus, we recommend that full OAR DVH reporting be required for future prospective trials.« less

Predictors of Student Productivity in Biomedical Graduate School Applications.

PubMed

Hall, Joshua D; O'Connell, Anna B; Cook, Jeanette G

2017-01-01

Many US biomedical PhD programs receive more applications for admissions than they can accept each year, necessitating a selective admissions process. Typical selection criteria include standardized test scores, undergraduate grade point average, letters of recommendation, a resume and/or personal statement highlighting relevant research or professional experience, and feedback from interviews with training faculty. Admissions decisions are often founded on assumptions that these application components correlate with research success in graduate school, but these assumptions have not been rigorously tested. We sought to determine if any application components were predictive of student productivity measured by first-author student publications and time to degree completion. We collected productivity metrics for graduate students who entered the umbrella first-year biomedical PhD program at the University of North Carolina at Chapel Hill from 2008-2010 and analyzed components of their admissions applications. We found no correlations of test scores, grades, amount of previous research experience, or faculty interview ratings with high or low productivity among those applicants who were admitted and chose to matriculate at UNC. In contrast, ratings from recommendation letter writers were significantly stronger for students who published multiple first-author papers in graduate school than for those who published no first-author papers during the same timeframe. We conclude that the most commonly used standardized test (the general GRE) is a particularly ineffective predictive tool, but that qualitative assessments by previous mentors are more likely to identify students who will succeed in biomedical graduate research. Based on these results, we conclude that admissions committees should avoid over-reliance on any single component of the application and de-emphasize metrics that are minimally predictive of student productivity. We recommend continual tracking of desired training outcomes combined with retrospective analysis of admissions practices to guide both application requirements and holistic application review.

Metrication report to the Congress

NASA Technical Reports Server (NTRS)

1990-01-01

The principal NASA metrication activities for FY 1989 were a revision of NASA metric policy and evaluation of the impact of using the metric system of measurement for the design and construction of the Space Station Freedom. Additional studies provided a basis for focusing follow-on activity. In FY 1990, emphasis will shift to implementation of metric policy and development of a long-range metrication plan. The report which follows addresses Policy Development, Planning and Program Evaluation, and Supporting Activities for the past and coming year.

A general relativistic rotating evolutionary universe—Part II

NASA Astrophysics Data System (ADS)

Berman, Marcelo Samuel

2008-06-01

As a sequel to Berman (Astrophys. Space Sci., 2008b), we show that the rotation of the Universe can be dealt by generalised Gaussian metrics, defined in this paper. Robertson-Walker’s metric has been employed with proper-time, in its standard applications; the generalised Gaussian metric implies in the use of a non-constant temporal metric coefficient modifying Robertson-Walker’s standard form. Experimental predictions are made.

Visual Enhancement of Illusory Phenomenal Accents in Non-Isochronous Auditory Rhythms

PubMed Central

2016-01-01

Musical rhythms encompass temporal patterns that often yield regular metrical accents (e.g., a beat). There have been mixed results regarding perception as a function of metrical saliency, namely, whether sensitivity to a deviant was greater in metrically stronger or weaker positions. Besides, effects of metrical position have not been examined in non-isochronous rhythms, or with respect to multisensory influences. This study was concerned with two main issues: (1) In non-isochronous auditory rhythms with clear metrical accents, how would sensitivity to a deviant be modulated by metrical positions? (2) Would the effects be enhanced by multisensory information? Participants listened to strongly metrical rhythms with or without watching a point-light figure dance to the rhythm in the same meter, and detected a slight loudness increment. Both conditions were presented with or without an auditory interference that served to impair auditory metrical perception. Sensitivity to a deviant was found greater in weak beat than in strong beat positions, consistent with the Predictive Coding hypothesis and the idea of metrically induced illusory phenomenal accents. The visual rhythm of dance hindered auditory detection, but more so when the latter was itself less impaired. This pattern suggested that the visual and auditory rhythms were perceptually integrated to reinforce metrical accentuation, yielding more illusory phenomenal accents and thus lower sensitivity to deviants, in a manner consistent with the principle of inverse effectiveness. Results were discussed in the predictive framework for multisensory rhythms involving observed movements and possible mediation of the motor system. PMID:27880850

New Objective Refraction Metric Based on Sphere Fitting to the Wavefront

PubMed Central

Martínez-Finkelshtein, Andreí

2017-01-01

Purpose To develop an objective refraction formula based on the ocular wavefront error (WFE) expressed in terms of Zernike coefficients and pupil radius, which would be an accurate predictor of subjective spherical equivalent (SE) for different pupil sizes. Methods A sphere is fitted to the ocular wavefront at the center and at a variable distance, t. The optimal fitting distance, topt, is obtained empirically from a dataset of 308 eyes as a function of objective refraction pupil radius, r0, and used to define the formula of a new wavefront refraction metric (MTR). The metric is tested in another, independent dataset of 200 eyes. Results For pupil radii r0 ≤ 2 mm, the new metric predicts the equivalent sphere with similar accuracy (<0.1D), however, for r0 > 2 mm, the mean error of traditional metrics can increase beyond 0.25D, and the MTR remains accurate. The proposed metric allows clinicians to obtain an accurate clinical spherical equivalent value without rescaling/refitting of the wavefront coefficients. It has the potential to be developed into a metric which will be able to predict full spherocylindrical refraction for the desired illumination conditions and corresponding pupil size. PMID:29104804

New Objective Refraction Metric Based on Sphere Fitting to the Wavefront.

PubMed

Jaskulski, Mateusz; Martínez-Finkelshtein, Andreí; López-Gil, Norberto

2017-01-01

To develop an objective refraction formula based on the ocular wavefront error (WFE) expressed in terms of Zernike coefficients and pupil radius, which would be an accurate predictor of subjective spherical equivalent (SE) for different pupil sizes. A sphere is fitted to the ocular wavefront at the center and at a variable distance, t . The optimal fitting distance, t opt , is obtained empirically from a dataset of 308 eyes as a function of objective refraction pupil radius, r 0 , and used to define the formula of a new wavefront refraction metric (MTR). The metric is tested in another, independent dataset of 200 eyes. For pupil radii r 0 ≤ 2 mm, the new metric predicts the equivalent sphere with similar accuracy (<0.1D), however, for r 0 > 2 mm, the mean error of traditional metrics can increase beyond 0.25D, and the MTR remains accurate. The proposed metric allows clinicians to obtain an accurate clinical spherical equivalent value without rescaling/refitting of the wavefront coefficients. It has the potential to be developed into a metric which will be able to predict full spherocylindrical refraction for the desired illumination conditions and corresponding pupil size.

Evaluating Algorithm Performance Metrics Tailored for Prognostics

NASA Technical Reports Server (NTRS)

Saxena, Abhinav; Celaya, Jose; Saha, Bhaskar; Saha, Sankalita; Goebel, Kai

2009-01-01

Prognostics has taken a center stage in Condition Based Maintenance (CBM) where it is desired to estimate Remaining Useful Life (RUL) of the system so that remedial measures may be taken in advance to avoid catastrophic events or unwanted downtimes. Validation of such predictions is an important but difficult proposition and a lack of appropriate evaluation methods renders prognostics meaningless. Evaluation methods currently used in the research community are not standardized and in many cases do not sufficiently assess key performance aspects expected out of a prognostics algorithm. In this paper we introduce several new evaluation metrics tailored for prognostics and show that they can effectively evaluate various algorithms as compared to other conventional metrics. Specifically four algorithms namely; Relevance Vector Machine (RVM), Gaussian Process Regression (GPR), Artificial Neural Network (ANN), and Polynomial Regression (PR) are compared. These algorithms vary in complexity and their ability to manage uncertainty around predicted estimates. Results show that the new metrics rank these algorithms in different manner and depending on the requirements and constraints suitable metrics may be chosen. Beyond these results, these metrics offer ideas about how metrics suitable to prognostics may be designed so that the evaluation procedure can be standardized. 1

A binary linear programming formulation of the graph edit distance.

PubMed

Justice, Derek; Hero, Alfred

2006-08-01

A binary linear programming formulation of the graph edit distance for unweighted, undirected graphs with vertex attributes is derived and applied to a graph recognition problem. A general formulation for editing graphs is used to derive a graph edit distance that is proven to be a metric, provided the cost function for individual edit operations is a metric. Then, a binary linear program is developed for computing this graph edit distance, and polynomial time methods for determining upper and lower bounds on the solution of the binary program are derived by applying solution methods for standard linear programming and the assignment problem. A recognition problem of comparing a sample input graph to a database of known prototype graphs in the context of a chemical information system is presented as an application of the new method. The costs associated with various edit operations are chosen by using a minimum normalized variance criterion applied to pairwise distances between nearest neighbors in the database of prototypes. The new metric is shown to perform quite well in comparison to existing metrics when applied to a database of chemical graphs.

U.S. Department of Energy Reference Model Program RM1: Experimental Results.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hill, Craig; Neary, Vincent Sinclair; Gunawan, Budi

The Reference Model Project (RMP), sponsored by the U.S. Department of Energy’s (DOE) Wind and Water Power Technologies Program within the Office of Energy Efficiency & Renewable Energy (EERE), aims at expediting industry growth and efficiency by providing nonproprietary Reference Models (RM) of MHK technology designs as study objects for opensource research and development (Neary et al. 2014a,b). As part of this program, MHK turbine models were tested in a large open channel facility at the University of Minnesota’s St. Anthony Falls Laboratory (UMN-SAFL). Reference Model 1 (RM1) is a 1:40 geometric scale dual-rotor axial flow horizontal axis device withmore » counter-rotating rotors, each with a rotor diameter dT = 0.5m. Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADVs) aligned with each rotor and the midpoint for RM1. Flow conditions for each case were controlled such that depth, h = 1m, and volumetric flow rate, Qw = 2.425m3s-1, resulting in a hub height velocity of approximately Uhub = 1.05ms-1 and blade chord length Reynolds numbers of Rec ≈ 3.0x105. Vertical velocity profiles collected in the wake of each device from 1 to 10 rotor diameters are used to estimate the velocity recovery and turbulent characteristics in the wake, as well as the interaction of the counter-rotating rotor wakes. The development of this high resolution laboratory investigation provides a robust dataset that enables assessing turbulence performance models and their ability to accurately predict device performance metrics, including computational fluid dynamics (CFD) models that can be used to predict turbulent inflow environments, reproduce wake velocity deficit, recovery and higher order turbulent statistics, as well as device performance metrics.« less

Ability of LANDSAT-8 Oli Derived Texture Metrics in Estimating Aboveground Carbon Stocks of Coppice Oak Forests

NASA Astrophysics Data System (ADS)

Safari, A.; Sohrabi, H.

2016-06-01

The role of forests as a reservoir for carbon has prompted the need for timely and reliable estimation of aboveground carbon stocks. Since measurement of aboveground carbon stocks of forests is a destructive, costly and time-consuming activity, aerial and satellite remote sensing techniques have gained many attentions in this field. Despite the fact that using aerial data for predicting aboveground carbon stocks has been proved as a highly accurate method, there are challenges related to high acquisition costs, small area coverage, and limited availability of these data. These challenges are more critical for non-commercial forests located in low-income countries. Landsat program provides repetitive acquisition of high-resolution multispectral data, which are freely available. The aim of this study was to assess the potential of multispectral Landsat 8 Operational Land Imager (OLI) derived texture metrics in quantifying aboveground carbon stocks of coppice Oak forests in Zagros Mountains, Iran. We used four different window sizes (3×3, 5×5, 7×7, and 9×9), and four different offsets ([0,1], [1,1], [1,0], and [1,-1]) to derive nine texture metrics (angular second moment, contrast, correlation, dissimilar, entropy, homogeneity, inverse difference, mean, and variance) from four bands (blue, green, red, and infrared). Totally, 124 sample plots in two different forests were measured and carbon was calculated using species-specific allometric models. Stepwise regression analysis was applied to estimate biomass from derived metrics. Results showed that, in general, larger size of window for deriving texture metrics resulted models with better fitting parameters. In addition, the correlation of the spectral bands for deriving texture metrics in regression models was ranked as b4>b3>b2>b5. The best offset was [1,-1]. Amongst the different metrics, mean and entropy were entered in most of the regression models. Overall, different models based on derived texture metrics were able to explain about half of the variation in aboveground carbon stocks. These results demonstrated that Landsat 8 derived texture metrics can be applied for mapping aboveground carbon stocks of coppice Oak Forests in large areas.

Photosensitizer fluorescence and singlet oxygen luminescence as dosimetric predictors of topical 5-aminolevulinic acid photodynamic therapy induced clinical erythema.

PubMed

Mallidi, Srivalleesha; Anbil, Sriram; Lee, Seonkyung; Manstein, Dieter; Elrington, Stefan; Kositratna, Garuna; Schoenfeld, David; Pogue, Brian; Davis, Steven J; Hasan, Tayyaba

2014-02-01

The need for patient-specific photodynamic therapy (PDT) in dermatologic and oncologic applications has triggered several studies that explore the utility of surrogate parameters as predictive reporters of treatment outcome. Although photosensitizer (PS) fluorescence, a widely used parameter, can be viewed as emission from several fluorescent states of the PS (e.g., minimally aggregated and monomeric), we suggest that singlet oxygen luminescence (SOL) indicates only the active PS component responsible for the PDT. Here, the ability of discrete PS fluorescence-based metrics (absolute and percent PS photobleaching and PS re-accumulation post-PDT) to predict the clinical phototoxic response (erythema) resulting from 5-aminolevulinic acid PDT was compared with discrete SOL (DSOL)-based metrics (DSOL counts pre-PDT and change in DSOL counts pre/post-PDT) in healthy human skin. Receiver operating characteristic curve (ROC) analyses demonstrated that absolute fluorescence photobleaching metric (AFPM) exhibited the highest area under the curve (AUC) of all tested parameters, including DSOL based metrics. The combination of dose-metrics did not yield better AUC than AFPM alone. Although sophisticated real-time SOL measurements may improve the clinical utility of SOL-based dosimetry, discrete PS fluorescence-based metrics are easy to implement, and our results suggest that AFPM may sufficiently predict the PDT outcomes and identify treatment nonresponders with high specificity in clinical contexts.

Information-theoretic model comparison unifies saliency metrics

PubMed Central

Kümmerer, Matthias; Wallis, Thomas S. A.; Bethge, Matthias

2015-01-01

Learning the properties of an image associated with human gaze placement is important both for understanding how biological systems explore the environment and for computer vision applications. There is a large literature on quantitative eye movement models that seeks to predict fixations from images (sometimes termed “saliency” prediction). A major problem known to the field is that existing model comparison metrics give inconsistent results, causing confusion. We argue that the primary reason for these inconsistencies is because different metrics and models use different definitions of what a “saliency map” entails. For example, some metrics expect a model to account for image-independent central fixation bias whereas others will penalize a model that does. Here we bring saliency evaluation into the domain of information by framing fixation prediction models probabilistically and calculating information gain. We jointly optimize the scale, the center bias, and spatial blurring of all models within this framework. Evaluating existing metrics on these rephrased models produces almost perfect agreement in model rankings across the metrics. Model performance is separated from center bias and spatial blurring, avoiding the confounding of these factors in model comparison. We additionally provide a method to show where and how models fail to capture information in the fixations on the pixel level. These methods are readily extended to spatiotemporal models of fixation scanpaths, and we provide a software package to facilitate their use. PMID:26655340

Rank Order Entropy: why one metric is not enough

PubMed Central

McLellan, Margaret R.; Ryan, M. Dominic; Breneman, Curt M.

2011-01-01

The use of Quantitative Structure-Activity Relationship models to address problems in drug discovery has a mixed history, generally resulting from the mis-application of QSAR models that were either poorly constructed or used outside of their domains of applicability. This situation has motivated the development of a variety of model performance metrics (r2, PRESS r2, F-tests, etc) designed to increase user confidence in the validity of QSAR predictions. In a typical workflow scenario, QSAR models are created and validated on training sets of molecules using metrics such as Leave-One-Out or many-fold cross-validation methods that attempt to assess their internal consistency. However, few current validation methods are designed to directly address the stability of QSAR predictions in response to changes in the information content of the training set. Since the main purpose of QSAR is to quickly and accurately estimate a property of interest for an untested set of molecules, it makes sense to have a means at hand to correctly set user expectations of model performance. In fact, the numerical value of a molecular prediction is often less important to the end user than knowing the rank order of that set of molecules according to their predicted endpoint values. Consequently, a means for characterizing the stability of predicted rank order is an important component of predictive QSAR. Unfortunately, none of the many validation metrics currently available directly measure the stability of rank order prediction, making the development of an additional metric that can quantify model stability a high priority. To address this need, this work examines the stabilities of QSAR rank order models created from representative data sets, descriptor sets, and modeling methods that were then assessed using Kendall Tau as a rank order metric, upon which the Shannon Entropy was evaluated as a means of quantifying rank-order stability. Random removal of data from the training set, also known as Data Truncation Analysis (DTA), was used as a means for systematically reducing the information content of each training set while examining both rank order performance and rank order stability in the face of training set data loss. The premise for DTA ROE model evaluation is that the response of a model to incremental loss of training information will be indicative of the quality and sufficiency of its training set, learning method, and descriptor types to cover a particular domain of applicability. This process is termed a “rank order entropy” evaluation, or ROE. By analogy with information theory, an unstable rank order model displays a high level of implicit entropy, while a QSAR rank order model which remains nearly unchanged during training set reductions would show low entropy. In this work, the ROE metric was applied to 71 data sets of different sizes, and was found to reveal more information about the behavior of the models than traditional metrics alone. Stable, or consistently performing models, did not necessarily predict rank order well. Models that performed well in rank order did not necessarily perform well in traditional metrics. In the end, it was shown that ROE metrics suggested that some QSAR models that are typically used should be discarded. ROE evaluation helps to discern which combinations of data set, descriptor set, and modeling methods lead to usable models in prioritization schemes, and provides confidence in the use of a particular model within a specific domain of applicability. PMID:21875058

Metrication report to the Congress. 1991 activities and 1992 plans

NASA Technical Reports Server (NTRS)

1991-01-01

During 1991, NASA approved a revised metric use policy and developed a NASA Metric Transition Plan. This Plan targets the end of 1995 for completion of NASA's metric initiatives. This Plan also identifies future programs that NASA anticipates will use the metric system of measurement. Field installations began metric transition studies in 1991 and will complete them in 1992. Half of NASA's Space Shuttle payloads for 1991, and almost all such payloads for 1992, have some metric-based elements. In 1992, NASA will begin assessing requirements for space-quality piece parts fabricated to U.S. metric standards, leading to development and qualification of high priority parts.

Metrics for measuring performance of market transformation initiatives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gordon, F.; Schlegel, J.; Grabner, K.

1998-07-01

Regulators have traditionally rewarded utility efficiency programs based on energy and demand savings. Now, many regulators are encouraging utilities and other program administrators to save energy by transforming markets. Prior to achieving sustainable market transformation, the program administrators often must take actions to understand the markets, establish baselines for success, reduce market barriers, build alliances, and build market momentum. Because these activities often precede savings, year-by-year measurement of savings can be an inappropriate measure of near-term success. Because ultimate success in transforming markets is defined in terms of sustainable changes in market structure and practice, traditional measures of success canmore » also be misleading as initiatives reach maturity. This paper reviews early efforts in Massachusetts to develop metrics, or yardsticks, to gauge regulatory rewards for utility market transformation initiatives. From experience in multiparty negotiations, the authors review options for metrics based alternatively on market effects, outcomes, and good faith implementation. Additionally, alternative approaches are explored, based on end-results, interim results, and initial results. The political and practical constraints are described which have thus far led to a preference for one-year metrics, based primarily on good faith implementation. Strategies are offered for developing useful metrics which might be acceptable to regulators, advocates, and program administrators. Finally, they emphasize that the use of market transformation performance metrics is in its infancy. Both regulators and program administrators are encouraged to advance into this area with an experimental mind-set; don't put all the money on one horse until there's more of a track record.« less

Porphyry copper assessment of eastern Australia: Chapter L in Global mineral resource assessment

USGS Publications Warehouse

Bookstrom, Arthur A.; Len, Richard A.; Hammarstrom, Jane M.; Robinson, Gilpin R.; Zientek, Michael L.; Drenth, Benjamin J.; Jaireth, Subhash; Cossette, Pamela M.; Wallis, John C.

2014-01-01

This assessment estimates that 15 undiscovered deposits contain an arithmetic mean of ~21 million metric tons or more of copper in four tracts, in addition to the 24 known porphyry copper deposits that contain identified resources of ~16 million metric tons of copper. In addition to copper, the mean expected amount of undiscovered byproduct gold predicted by the simulation is ~1,500 metric tons. The probability associated with these arithmetic means is on the order of 30 percent. Median expected amounts of metals predicted by the simulations may be ~50 percent lower than mean estimates.

An empirical comparison of a dynamic software testability metric to static cyclomatic complexity

NASA Technical Reports Server (NTRS)

Voas, Jeffrey M.; Miller, Keith W.; Payne, Jeffrey E.

1993-01-01

This paper compares the dynamic testability prediction technique termed 'sensitivity analysis' to the static testability technique termed cyclomatic complexity. The application that we chose in this empirical study is a CASE generated version of a B-737 autoland system. For the B-737 system we analyzed, we isolated those functions that we predict are more prone to hide errors during system/reliability testing. We also analyzed the code with several other well-known static metrics. This paper compares and contrasts the results of sensitivity analysis to the results of the static metrics.

EnviroAtlas - Reptile Biodiversity Ecosystem Services Metrics by 12-digit HUC for the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset contains biodiversity metrics reflecting ecosystem services or other aspects of biodiversity for reptile species, based on the number of reptile species as measured by predicted habitat present within a pixel. These metrics were created from grouping national level single species habitat models created by the USGS Gap Analysis Program into smaller ecologically based, phylogeny based, or stakeholder suggested composites. The dataset includes reptile species richness metrics for all reptile species, lizards, snakes, turtles, poisonous reptiles, Natureserve-listed G1,G2, and G3 reptile species, and reptile species listed by IUCN (International Union for Conservation of Nature), PARC (Partners in Amphibian and Reptile Conservation) and SWPARC (Southwest Partners in Amphibian and Reptile Conservation). This dataset was produced by a joint effort of New Mexico State University, US EPA, and USGS to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa

Evaluation of ride quality prediction methods for helicopter interior noise and vibration environments

NASA Technical Reports Server (NTRS)

Leatherwood, J. D.; Clevenson, S. A.; Hollenbaugh, D. D.

1984-01-01

The results of a simulator study conducted to compare and validate various ride quality prediction methods for use in assessing passenger/crew ride comfort within helicopters are presented. Included are results quantifying 35 helicopter pilots discomfort responses to helicopter interior noise and vibration typical of routine flights, assessment of various ride quality metrics including the NASA ride comfort model, and examination of possible criteria approaches. Results of the study indicated that crew discomfort results from a complex interaction between vibration and interior noise. Overall measures such as weighted or unweighted root-mean-square acceleration level and A-weighted noise level were not good predictors of discomfort. Accurate prediction required a metric incorporating the interactive effects of both noise and vibration. The best metric for predicting crew comfort to the combined noise and vibration environment was the NASA discomfort index.

Can Tweets Predict Citations? Metrics of Social Impact Based on Twitter and Correlation with Traditional Metrics of Scientific Impact

PubMed Central

2011-01-01

Background Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact. Web 2.0 tools such as Twitter, blogs or social bookmarking tools provide the possibility to construct innovative article-level or journal-level metrics to gauge impact and influence. However, the relationship of the these new metrics to traditional metrics such as citations is not known. Objective (1) To explore the feasibility of measuring social impact of and public attention to scholarly articles by analyzing buzz in social media, (2) to explore the dynamics, content, and timing of tweets relative to the publication of a scholarly article, and (3) to explore whether these metrics are sensitive and specific enough to predict highly cited articles. Methods Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined. For a subset of 1573 tweets about 55 articles published between issues 3/2009 and 2/2010, different metrics of social media impact were calculated and compared against subsequent citation data from Scopus and Google Scholar 17 to 29 months later. A heuristic to predict the top-cited articles in each issue through tweet metrics was validated. Results A total of 4208 tweets cited 286 distinct JMIR articles. The distribution of tweets over the first 30 days after article publication followed a power law (Zipf, Bradford, or Pareto distribution), with most tweets sent on the day when an article was published (1458/3318, 43.94% of all tweets in a 60-day period) or on the following day (528/3318, 15.9%), followed by a rapid decay. The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from .42 to .72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations. A linear multivariate model with time and tweets as significant predictors (P < .001) could explain 27% of the variation of citations. Highly tweeted articles were 11 times more likely to be highly cited than less-tweeted articles (9/12 or 75% of highly tweeted article were highly cited, while only 3/43 or 7% of less-tweeted articles were highly cited; rate ratio 0.75/0.07 = 10.75, 95% confidence interval, 3.4–33.6). Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity. Conclusions Tweets can predict highly cited articles within the first 3 days of article publication. Social media activity either increases citations or reflects the underlying qualities of the article that also predict citations, but the true use of these metrics is to measure the distinct concept of social impact. Social impact measures based on tweets are proposed to complement traditional citation metrics. The proposed twimpact factor may be a useful and timely metric to measure uptake of research findings and to filter research findings resonating with the public in real time. PMID:22173204

Can tweets predict citations? Metrics of social impact based on Twitter and correlation with traditional metrics of scientific impact.

PubMed

Eysenbach, Gunther

2011-12-19

Citations in peer-reviewed articles and the impact factor are generally accepted measures of scientific impact. Web 2.0 tools such as Twitter, blogs or social bookmarking tools provide the possibility to construct innovative article-level or journal-level metrics to gauge impact and influence. However, the relationship of the these new metrics to traditional metrics such as citations is not known. (1) To explore the feasibility of measuring social impact of and public attention to scholarly articles by analyzing buzz in social media, (2) to explore the dynamics, content, and timing of tweets relative to the publication of a scholarly article, and (3) to explore whether these metrics are sensitive and specific enough to predict highly cited articles. Between July 2008 and November 2011, all tweets containing links to articles in the Journal of Medical Internet Research (JMIR) were mined. For a subset of 1573 tweets about 55 articles published between issues 3/2009 and 2/2010, different metrics of social media impact were calculated and compared against subsequent citation data from Scopus and Google Scholar 17 to 29 months later. A heuristic to predict the top-cited articles in each issue through tweet metrics was validated. A total of 4208 tweets cited 286 distinct JMIR articles. The distribution of tweets over the first 30 days after article publication followed a power law (Zipf, Bradford, or Pareto distribution), with most tweets sent on the day when an article was published (1458/3318, 43.94% of all tweets in a 60-day period) or on the following day (528/3318, 15.9%), followed by a rapid decay. The Pearson correlations between tweetations and citations were moderate and statistically significant, with correlation coefficients ranging from .42 to .72 for the log-transformed Google Scholar citations, but were less clear for Scopus citations and rank correlations. A linear multivariate model with time and tweets as significant predictors (P < .001) could explain 27% of the variation of citations. Highly tweeted articles were 11 times more likely to be highly cited than less-tweeted articles (9/12 or 75% of highly tweeted article were highly cited, while only 3/43 or 7% of less-tweeted articles were highly cited; rate ratio 0.75/0.07 = 10.75, 95% confidence interval, 3.4-33.6). Top-cited articles can be predicted from top-tweeted articles with 93% specificity and 75% sensitivity. Tweets can predict highly cited articles within the first 3 days of article publication. Social media activity either increases citations or reflects the underlying qualities of the article that also predict citations, but the true use of these metrics is to measure the distinct concept of social impact. Social impact measures based on tweets are proposed to complement traditional citation metrics. The proposed twimpact factor may be a useful and timely metric to measure uptake of research findings and to filter research findings resonating with the public in real time.

Two-layer convective heating prediction procedures and sensitivities for blunt body reentry vehicles

NASA Technical Reports Server (NTRS)

Bouslog, Stanley A.; An, Michael Y.; Wang, K. C.; Tam, Luen T.; Caram, Jose M.

1993-01-01

This paper provides a description of procedures typically used to predict convective heating rates to hypersonic reentry vehicles using the two-layer method. These procedures were used to compute the pitch-plane heating distributions to the Apollo geometry for a wind tunnel test case and for three flight cases. Both simple engineering methods and coupled inviscid/boundary layer solutions were used to predict the heating rates. The sensitivity of the heating results in the choice of metrics, pressure distributions, boundary layer edge conditions, and wall catalycity used in the heating analysis were evaluated. Streamline metrics, pressure distributions, and boundary layer edge properties were defined from perfect gas (wind tunnel case) and chemical equilibrium and nonequilibrium (flight cases) inviscid flow-field solutions. The results of this study indicated that the use of CFD-derived metrics and pressures provided better predictions of heating when compared to wind tunnel test data. The study also showed that modeling entropy layer swallowing and ionization had little effect on the heating predictions.

Validation of Metrics as Error Predictors

NASA Astrophysics Data System (ADS)

Mendling, Jan

In this chapter, we test the validity of metrics that were defined in the previous chapter for predicting errors in EPC business process models. In Section 5.1, we provide an overview of how the analysis data is generated. Section 5.2 describes the sample of EPCs from practice that we use for the analysis. Here we discuss a disaggregation by the EPC model group and by error as well as a correlation analysis between metrics and error. Based on this sample, we calculate a logistic regression model for predicting error probability with the metrics as input variables in Section 5.3. In Section 5.4, we then test the regression function for an independent sample of EPC models from textbooks as a cross-validation. Section 5.5 summarizes the findings.

WE-AB-202-02: Incorporating Regional Ventilation Function in Predicting Radiation Fibrosis After Concurrent Chemoradiotherapy for Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lan, F; Jeudy, J; Tseng, H

Purpose: To investigate the incorporation of pre-therapy regional ventilation function in predicting radiation fibrosis (RF) in stage III non-small-cell lung cancer (NSCLC) patients treated with concurrent thoracic chemoradiotherapy. Methods: 37 stage III NSCLC patients were retrospectively studied. Patients received one cycle of cisplatin-gemcitabine, followed by two to three cycles of cisplatin-etoposide concurrently with involved-field thoracic radiotherapy between 46 and 66 Gy (2 Gy per fraction). Pre-therapy regional ventilation images of the lung were derived from 4DCT via a density-change-based image registration algorithm with mass correction. RF was evaluated at 6-months post-treatment using radiographic scoring based on airway dilation and volumemore » loss. Three types of ipsilateral lung metrics were studied: (1) conventional dose-volume metrics (V20, V30, V40, and mean-lung-dose (MLD)), (2) dose-function metrics (fV20, fV30, fV40, and functional mean-lung-dose (fMLD) generated by combining regional ventilation and dose), and (3) dose-subvolume metrics (sV20, sV30, sV40, and subvolume mean-lung-dose (sMLD) defined as the dose-volume metrics computed on the sub-volume of the lung with at least 60% of the quantified maximum ventilation status). Receiver operating characteristic (ROC) curve analysis and logistic regression analysis were used to evaluate the predictability of these metrics for RF. Results: In predicting airway dilation, the area under the ROC curve (AUC) values for (V20, MLD), (fV20, fMLD), and (sV20, and sMLD) were (0.76, 0.70), (0.80, 0.74) and (0.82, 0.80), respectively. The logistic regression p-values were (0.09, 0.18), (0.02, 0.05) and (0.004, 0.006), respectively. With regard to volume loss, the corresponding AUC values for these metrics were (0.66, 0.57), (0.67, 0.61) and (0.71, 0.69), and p-values were (0.95, 0.90), (0.43, 0.64) and (0.08, 0.12), respectively. Conclusion: The inclusion of regional ventilation function improved predictability of radiation fibrosis. Dose-subvolume metrics provided a promising method for incorporating functional information into the conventional dose-volume parameters for outcome assessment.« less

Predicting human age using regional morphometry and inter-regional morphological similarity

NASA Astrophysics Data System (ADS)

Wang, Xun-Heng; Li, Lihua

2016-03-01

The goal of this study is predicting human age using neuro-metrics derived from structural MRI, as well as investigating the relationships between age and predictive neuro-metrics. To this end, a cohort of healthy subjects were recruited from 1000 Functional Connectomes Project. The ages of the participations were ranging from 7 to 83 (36.17+/-20.46). The structural MRI for each subject was preprocessed using FreeSurfer, resulting in regional cortical thickness, mean curvature, regional volume and regional surface area for 148 anatomical parcellations. The individual age was predicted from the combination of regional and inter-regional neuro-metrics. The prediction accuracy is r = 0.835, p < 0.00001, evaluated by Pearson correlation coefficient between predicted ages and actual ages. Moreover, the LASSO linear regression also found certain predictive features, most of which were inter-regional features. The turning-point of the developmental trajectories in human brain was around 40 years old based on regional cortical thickness. In conclusion, structural MRI could be potential biomarkers for the aging in human brain. The human age could be successfully predicted from the combination of regional morphometry and inter-regional morphological similarity. The inter-regional measures could be beneficial to investigating human brain connectome.

PSA: A program to streamline orbit determination for launch support operations

NASA Technical Reports Server (NTRS)

Legerton, V. N.; Mottinger, N. A.

1988-01-01

An interactive, menu driven computer program was written to streamline the orbit determination process during the critical launch support phase of a mission. Residing on a virtual memory minicomputer, this program retains the quantities in-core needed to obtain a least squares estimate of the spacecraft trajectory with interactive displays to assist in rapid radio metric data evaluation. Menu-driven displays allow real time filter and data strategy development. Graphical and tabular displays can be sent to a laser printer for analysis without exiting the program. Products generated by this program feed back to the main orbit determination program in order to further refine the estimate of the trajectory. The final estimate provides a spacecraft ephemeris which is transmitted to the mission control center and used for antenna pointing and frequency predict generation by the Deep Space Network. The development and implementation process of this program differs from that used for most other navigation software by allowing the users to check important operating features during development and have changes made as needed.

Predicting surface fuel models and fuel metrics using lidar and CIR imagery in a dense mixed conifer forest

Treesearch

Marek K. Jakubowksi; Qinghua Guo; Brandon Collins; Scott Stephens; Maggi Kelly

2013-01-01

We compared the ability of several classification and regression algorithms to predict forest stand structure metrics and standard surface fuel models. Our study area spans a dense, topographically complex Sierra Nevada mixed-conifer forest. We used clustering, regression trees, and support vector machine algorithms to analyze high density (average 9 pulses/m

A New Distance Metric in Ground Motion Prediction Equations Based On Array Back-Projections

NASA Astrophysics Data System (ADS)

Feng, T.; Meng, L.

2017-12-01

Traditional Ground Motion Prediction Equations (GMPEs) measure the distances either relative to the epicenter (Repi) or the hypocenter (Rhyp) assuming point-sources, or relative to the closest point of the fault rupture (Rrup) or its surface projection (Rjb) to account for finite earthquake dimensions. However, it has long been proven that for large megathrust earthquakes (M>8), the over-simplification of the earthquake source characteristics in these distance metrics result in significant bias and uncertainty of the ground motion predictions. Recent advances in earthquake source imaging of major subduction earthquakes highlight the frequency-dependent and depth-varying seismic radiations at the plate interfaces. Low-frequency energy mainly emanated from the shallower portion of the megathrusts while dominant high-frequency energy often radiates from the deeper portion of the megathrust. In the 2011 Tohoku-Oki earthquake, all these distance metrics produce severe biases, underestimating the ground accelerations at short distances (<100km) and overestimating them at long distances (>100km). This phenomenon motivates an alternative distance metric based on the array back-projection (BP) technique that effectively captures regions releasing high-frequency energy. Herein, we define Rbp as the distance between nearest BP radiators and the station sites. We studied five large earthquakes in Japan, and found that Rbp outperforms conventional distance metrics in predicting the Psa (Pseudo Spectral Acceleration) in the high-frequency band (0.5-4 Hz). And at low frequencies (0.1-0.5Hz), we find that Rhyp produces better fits to the Psa spectrum. Thus, we propose to combine Rhyp and Rbp in low-frequency (0.1-0.5Hz) and high-frequency (0.5-4 Hz) range to improve the GMPEs. We consider that Rbp reflects the high-frequency characters of the rupture that are complementary to conventional GMPE distance metrics and a more suitable ground motion predictors in many cases. Based on our new distance metric, we expect to build an automatic system predicting ground motion immediately after the large earthquake (M>7) happens, an alternative to the shakemap.

Metrication Ahead: What Administrators Need to Know

ERIC Educational Resources Information Center

Barbrow, L. E.

1975-01-01

Industry has believed for years that adopting the metric system would be an advantage to U. S. economy both at home and abroad. The author explains how the metric conversion program is being organized, and how educators can get information about it. (Editor)

An Introduction to the SI Metric System. Inservice Guide for Teaching Measurement, Kindergarten Through Grade Eight.

ERIC Educational Resources Information Center

California State Dept. of Education, Sacramento.

This handbook was designed to serve as a reference for teacher workshops that: (1) introduce the metric system and help teachers gain confidence with metric measurement, and (2) develop classroom measurement activities. One chapter presents the history and basic features of SI metrics. A second chapter presents a model for the measurement program.…

PDB-Metrics: a web tool for exploring the PDB contents.

PubMed

Fileto, Renato; Kuser, Paula R; Yamagishi, Michel E B; Ribeiro, André A; Quinalia, Thiago G; Franco, Eduardo H; Mancini, Adauto L; Higa, Roberto H; Oliveira, Stanley R M; Santos, Edgard H; Vieira, Fabio D; Mazoni, Ivan; Cruz, Sergio A B; Neshich, Goran

2006-06-30

PDB-Metrics (http://sms.cbi.cnptia.embrapa.br/SMS/pdb_metrics/index.html) is a component of the Diamond STING suite of programs for the analysis of protein sequence, structure and function. It summarizes the characteristics of the collection of protein structure descriptions deposited in the Protein Data Bank (PDB) and provides a Web interface to search and browse the PDB, using a variety of alternative criteria. PDB-Metrics is a powerful tool for bioinformaticians to examine the data span in the PDB from several perspectives. Although other Web sites offer some similar resources to explore the PDB contents, PDB-Metrics is among those with the most complete set of such facilities, integrated into a single Web site. This program has been developed using SQLite, a C library that provides all the query facilities of a database management system.

A novel metric for quantification of homogeneous and heterogeneous tumors in PET for enhanced clinical outcome prediction

NASA Astrophysics Data System (ADS)

Rahmim, Arman; Schmidtlein, C. Ross; Jackson, Andrew; Sheikhbahaei, Sara; Marcus, Charles; Ashrafinia, Saeed; Soltani, Madjid; Subramaniam, Rathan M.

2016-01-01

Oncologic PET images provide valuable information that can enable enhanced prognosis of disease. Nonetheless, such information is simplified significantly in routine clinical assessment to meet workflow constraints. Examples of typical FDG PET metrics include: (i) SUVmax, (2) total lesion glycolysis (TLG), and (3) metabolic tumor volume (MTV). We have derived and implemented a novel metric for tumor quantification, inspired in essence by a model of generalized equivalent uniform dose as used in radiation therapy. The proposed metric, denoted generalized effective total uptake (gETU), is attractive as it encompasses the abovementioned commonly invoked metrics, and generalizes them, for both homogeneous and heterogeneous tumors, using a single parameter a. We evaluated this new metric for improved overall survival (OS) prediction on two different baseline FDG PET/CT datasets: (a) 113 patients with squamous cell cancer of the oropharynx, and (b) 72 patients with locally advanced pancreatic adenocarcinoma. Kaplan-Meier survival analysis was performed, where the subjects were subdivided into two groups using the median threshold, from which the hazard ratios (HR) were computed in Cox proportional hazards regression. For the oropharyngeal cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak produced HR values of 1.86, 3.02, 1.34, 1.36 and 1.62, while the proposed gETU metric for a  = 0.25 (greater emphasis on volume information) enabled significantly enhanced OS prediction with HR  =  3.94. For the pancreatic cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak resulted in HR values of 1.05, 1.25, 1.42, 1.45 and 1.52, while gETU at a  = 3.2 (greater emphasis on SUV information) arrived at an improved HR value of 1.61. Overall, the proposed methodology allows placement of differing degrees of emphasis on tumor volume versus uptake for different types of tumors to enable enhanced clinical outcome prediction.

Comparing exposure metrics for classifying ‘dangerous heat’ in heat wave and health warning systems

PubMed Central

Zhang, Kai; Rood, Richard B.; Michailidis, George; Oswald, Evan M.; Schwartz, Joel D.; Zanobetti, Antonella; Ebi, Kristie L.; O’Neill, Marie S.

2012-01-01

Heat waves have been linked to excess mortality and morbidity, and are projected to increase in frequency and intensity with a warming climate. This study compares exposure metrics to trigger heat wave and health warning systems (HHWS), and introduces a novel multi-level hybrid clustering method to identify potential dangerously hot days. Two-level and three-level hybrid clustering analysis as well as common indices used to trigger HHWS, including spatial synoptic classification (SSC); and 90th, 95th, and 99th percentiles of minimum and relative minimum temperature (using a 10 day reference period), were calculated using a summertime weather dataset in Detroit from 1976 to 2006. The days classified as ‘hot’ with hybrid clustering analysis, SSC, minimum and relative minimum temperature methods differed by method type. SSC tended to include the days with, on average, 2.6 °C lower daily minimum temperature and 5.3 °C lower dew point than days identified by other methods. These metrics were evaluated by comparing their performance in predicting excess daily mortality. The 99th percentile of minimum temperature was generally the most predictive, followed by the three-level hybrid clustering method, the 95th percentile of minimum temperature, SSC and others. Our proposed clustering framework has more flexibility and requires less substantial meteorological prior information than the synoptic classification methods. Comparison of these metrics in predicting excess daily mortality suggests that metrics thought to better characterize physiological heat stress by considering several weather conditions simultaneously may not be the same metrics that are better at predicting heat-related mortality, which has significant implications in HHWSs. PMID:22673187

Metrics that differentiate the origins of osmolyte effects on protein stability: a test of the surface tension proposal.

PubMed

Auton, Matthew; Ferreon, Allan Chris M; Bolen, D Wayne

2006-09-01

Osmolytes that are naturally selected to protect organisms against environmental stresses are known to confer stability to proteins via preferential exclusion from protein surfaces. Solvophobicity, surface tension, excluded volume, water structure changes and electrostatic repulsion are all examples of forces proposed to account for preferential exclusion and the ramifications exclusion has on protein properties. What has been lacking is a systematic way of determining which force(s) is(are) responsible for osmolyte effects. Here, we propose the use of two experimental metrics for assessing the abilities of various proposed forces to account for osmolyte-mediated effects on protein properties. Metric 1 requires prediction of the experimentally determined ability of the osmolyte to bring about folding/unfolding resulting from the application of the force in question (i.e. prediction of the m-value of the protein in osmolyte). Metric 2 requires prediction of the experimentally determined ability of the osmolyte to contract or expand the Stokes radius of the denatured state resulting from the application of the force. These metrics are applied to test separate claims that solvophobicity/solvophilicity and surface tension are driving forces for osmolyte-induced effects on protein stability. The results show clearly that solvophobic/solvophilic forces readily account for protein stability and denatured state dimensional effects, while surface tension alone fails to do so. The agreement between experimental and predicted m-values involves both positive and negative m-values for three different proteins, and as many as six different osmolytes, illustrating that the tests are robust and discriminating. The ability of the two metrics to distinguish which forces account for the effects of osmolytes on protein properties and which do not, provides a powerful means of investigating the origins of osmolyte-protein effects.

Variable-Metric Algorithm For Constrained Optimization

NASA Technical Reports Server (NTRS)

Frick, James D.

1989-01-01

Variable Metric Algorithm for Constrained Optimization (VMACO) is nonlinear computer program developed to calculate least value of function of n variables subject to general constraints, both equality and inequality. First set of constraints equality and remaining constraints inequalities. Program utilizes iterative method in seeking optimal solution. Written in ANSI Standard FORTRAN 77.

RBscore&NBench: a high-level web server for nucleic acid binding residues prediction with a large-scale benchmarking database.

PubMed

Miao, Zhichao; Westhof, Eric

2016-07-08

RBscore&NBench combines a web server, RBscore and a database, NBench. RBscore predicts RNA-/DNA-binding residues in proteins and visualizes the prediction scores and features on protein structures. The scoring scheme of RBscore directly links feature values to nucleic acid binding probabilities and illustrates the nucleic acid binding energy funnel on the protein surface. To avoid dataset, binding site definition and assessment metric biases, we compared RBscore with 18 web servers and 3 stand-alone programs on 41 datasets, which demonstrated the high and stable accuracy of RBscore. A comprehensive comparison led us to develop a benchmark database named NBench. The web server is available on: http://ahsoka.u-strasbg.fr/rbscorenbench/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Applying the disability-adjusted life year to track health impact of social franchise programs in low- and middle-income countries

PubMed Central

2013-01-01

Background Developing effective methods for measuring the health impact of social franchising programs is vital for demonstrating the value of this innovative service delivery model, particularly given its rapid expansion worldwide. Currently, these programs define success through patient volume and number of outlets, widely acknowledged as poor reflections of true program impact. An existing metric, the disability-adjusted life years averted (DALYs averted), offers promise as a measure of projected impact. Country-specific and service-specific, DALYs averted enables impact comparisons between programs operating in different contexts. This study explores the use of DALYs averted as a social franchise performance metric. Methods Using data collected by the Social Franchising Compendia in 2010 and 2011, we compared franchise performance, analyzing by region and program area. Coefficients produced by Population Services International converted each franchise's service delivery data into DALYs averted. For the 32 networks with two years of data corresponding to these metrics, a paired t-test compared all metrics. Finally, to test data reporting quality, we compared services provided to patient volume. Results Social franchising programs grew considerably from 2010 to 2011, measured by services provided (215%), patient volume (31%), and impact (couple-years of protection (CYPs): 86% and DALYs averted: 519%), but not by the total number of outlets. Non-family planning services increased by 857%, with diversification centered in Asia and Africa. However, paired t-test comparisons showed no significant increase within the networks, whether categorized as family planning or non-family planning. The ratio of services provided to patient visits yielded considerable range, with one network reporting a ratio of 16,000:1. Conclusion In theory, the DALYs averted metric is a more robust and comprehensive metric for social franchising than current program measures. As social franchising spreads beyond family planning, having a metric that captures the impact of a range of diverse services and allows comparisons will be increasingly important. However, standardizing reporting will be essential to make such comparisons useful. While not widespread, errors in self-reported data appear to have included social marketing distribution data in social franchising reporting, requiring clearer data collection and reporting guidelines. Differences noted above must be interpreted cautiously as a result. PMID:23902679

Applying the disability-adjusted life year to track health impact of social franchise programs in low- and middle-income countries.

PubMed

Montagu, Dominic; Ngamkitpaiboon, Lek; Duvall, Susan; Ratcliffe, Amy

2013-01-01

Developing effective methods for measuring the health impact of social franchising programs is vital for demonstrating the value of this innovative service delivery model, particularly given its rapid expansion worldwide. Currently, these programs define success through patient volume and number of outlets, widely acknowledged as poor reflections of true program impact. An existing metric, the disability-adjusted life years averted (DALYs averted), offers promise as a measure of projected impact. Country-specific and service-specific, DALYs averted enables impact comparisons between programs operating in different contexts. This study explores the use of DALYs averted as a social franchise performance metric. Using data collected by the Social Franchising Compendia in 2010 and 2011, we compared franchise performance, analyzing by region and program area. Coefficients produced by Population Services International converted each franchise's service delivery data into DALYs averted. For the 32 networks with two years of data corresponding to these metrics, a paired t-test compared all metrics. Finally, to test data reporting quality, we compared services provided to patient volume. Social franchising programs grew considerably from 2010 to 2011, measured by services provided (215%), patient volume (31%), and impact (couple-years of protection (CYPs): 86% and DALYs averted: 519%), but not by the total number of outlets. Non-family planning services increased by 857%, with diversification centered in Asia and Africa. However, paired t-test comparisons showed no significant increase within the networks, whether categorized as family planning or non-family planning. The ratio of services provided to patient visits yielded considerable range, with one network reporting a ratio of 16,000:1. In theory, the DALYs averted metric is a more robust and comprehensive metric for social franchising than current program measures. As social franchising spreads beyond family planning, having a metric that captures the impact of a range of diverse services and allows comparisons will be increasingly important. However, standardizing reporting will be essential to make such comparisons useful. While not widespread, errors in self-reported data appear to have included social marketing distribution data in social franchising reporting, requiring clearer data collection and reporting guidelines. Differences noted above must be interpreted cautiously as a result.

Cognition in Space Workshop. 1; Metrics and Models

NASA Technical Reports Server (NTRS)

Woolford, Barbara; Fielder, Edna

2005-01-01

"Cognition in Space Workshop I: Metrics and Models" was the first in a series of workshops sponsored by NASA to develop an integrated research and development plan supporting human cognition in space exploration. The workshop was held in Chandler, Arizona, October 25-27, 2004. The participants represented academia, government agencies, and medical centers. This workshop addressed the following goal of the NASA Human System Integration Program for Exploration: to develop a program to manage risks due to human performance and human error, specifically ones tied to cognition. Risks range from catastrophic error to degradation of efficiency and failure to accomplish mission goals. Cognition itself includes memory, decision making, initiation of motor responses, sensation, and perception. Four subgoals were also defined at the workshop as follows: (1) NASA needs to develop a human-centered design process that incorporates standards for human cognition, human performance, and assessment of human interfaces; (2) NASA needs to identify and assess factors that increase risks associated with cognition; (3) NASA needs to predict risks associated with cognition; and (4) NASA needs to mitigate risk, both prior to actual missions and in real time. This report develops the material relating to these four subgoals.

Framework for assessing causality in disease management programs: principles.

PubMed

Wilson, Thomas; MacDowell, Martin

2003-01-01

To credibly state that a disease management (DM) program "caused" a specific outcome it is required that metrics observed in the DM population be compared with metrics that would have been expected in the absence of a DM intervention. That requirement can be very difficult to achieve, and epidemiologists and others have developed guiding principles of causality by which credible estimates of DM impact can be made. This paper introduces those key principles. First, DM program metrics must be compared with metrics from a "reference population." This population should be "equivalent" to the DM intervention population on all factors that could independently impact the outcome. In addition, the metrics used in both groups should use the same defining criteria (ie, they must be "comparable" to each other). The degree to which these populations fulfill the "equivalent" assumption and metrics fulfill the "comparability" assumption should be stated. Second, when "equivalence" or "comparability" is not achieved, the DM managers should acknowledge this fact and, where possible, "control" for those factors that may impact the outcome(s). Finally, it is highly unlikely that one study will provide definitive proof of any specific DM program value for all time; thus, we strongly recommend that studies be ongoing, at multiple points in time, and at multiple sites, and, when observational study designs are employed, that more than one type of study design be utilized. Methodologically sophisticated studies that follow these "principles of causality" will greatly enhance the reputation of the important and growing efforts in DM.

15 CFR 273.4 - Guidelines.

Code of Federal Regulations, 2014 CFR

2014-01-01

... for use of the metric system in procurements, grants and other business-related activities; (b... predominant influence, consistent with the legal status of the metric system as the preferred system of... system; (f) Consider cost effects of metric use in setting agency policies, programs and actions and...

Equilibrium thermodynamics and neutrino decoupling in quasi-metric cosmology

NASA Astrophysics Data System (ADS)

Østvang, Dag

2018-05-01

The laws of thermodynamics in the expanding universe are formulated within the quasi-metric framework. The quasi-metric cosmic expansion does not directly influence momenta of material particles, so the expansion directly cools null particles only (e.g., photons). Therefore, said laws differ substantially from their counterparts in standard cosmology. Consequently, all non-null neutrino mass eigenstates are predicted to have the same energy today as they had just after neutrino decoupling in the early universe. This indicates that the predicted relic neutrino background is strongly inconsistent with detection rates measured in solar neutrino detectors (Borexino in particular). Thus quasi-metric cosmology is in violent conflict with experiment unless some exotic property of neutrinos makes the relic neutrino background essentially undetectable (e.g., if all massive mass eigenstates decay into "invisible" particles over cosmic time scales). But in absence of hard evidence in favour of the necessary exotic neutrino physics needed to resolve said conflict, the current status of quasi-metric relativity has been changed to non-viable.

"Can you see me now?" An objective metric for predicting intelligibility of compressed American Sign Language video

NASA Astrophysics Data System (ADS)

Ciaramello, Francis M.; Hemami, Sheila S.

2007-02-01

For members of the Deaf Community in the United States, current communication tools include TTY/TTD services, video relay services, and text-based communication. With the growth of cellular technology, mobile sign language conversations are becoming a possibility. Proper coding techniques must be employed to compress American Sign Language (ASL) video for low-rate transmission while maintaining the quality of the conversation. In order to evaluate these techniques, an appropriate quality metric is needed. This paper demonstrates that traditional video quality metrics, such as PSNR, fail to predict subjective intelligibility scores. By considering the unique structure of ASL video, an appropriate objective metric is developed. Face and hand segmentation is performed using skin-color detection techniques. The distortions in the face and hand regions are optimally weighted and pooled across all frames to create an objective intelligibility score for a distorted sequence. The objective intelligibility metric performs significantly better than PSNR in terms of correlation with subjective responses.

Early Momentum Metrics: Why They Matter for Higher Education Reform. CCRC Research Brief. Number 65

ERIC Educational Resources Information Center

Jenkins, Davis; Bailey, Thomas

2017-01-01

In this brief, the authors propose three measures of "early momentum" for two reasons: Research is beginning to show that these near-term metrics predict long-term success, and the metrics focus attention on initial conditions at colleges that are particularly important for solidifying the foundation for student success. While these…

Far-field acoustic data for the Texas ASE, Inc. Hush-House, supplement

NASA Astrophysics Data System (ADS)

Lee, R. A.

1982-04-01

This report supplements AFAMRL-TR-73-110, which describes the data base (NOISEFILE) used in the computer program (NOISEMAP) to predict the community noise exposure resulting from military aircraft operations. The results of field test measurements to define the single-event noise produced on the ground by military aircraft/engines operating in the Texas ASE Inc. hush-house are presented as a function of angle (0 to 180 from the front of the hush-house) and distance (200 ft to 2500 ft) in various acoustic metrics.

Return on investment in healthcare leadership development programs.

PubMed

Jeyaraman, Maya M; Qadar, Sheikh Muhammad Zeeshan; Wierzbowski, Aleksandra; Farshidfar, Farnaz; Lys, Justin; Dickson, Graham; Grimes, Kelly; Phillips, Leah A; Mitchell, Jonathan I; Van Aerde, John; Johnson, Dave; Krupka, Frank; Zarychanski, Ryan; Abou-Setta, Ahmed M

2018-02-05

Purpose Strong leadership has been shown to foster change, including loyalty, improved performance and decreased error rates, but there is a dearth of evidence on effectiveness of leadership development programs. To ensure a return on the huge investments made, evidence-based approaches are needed to assess the impact of leadership on health-care establishments. As a part of a pan-Canadian initiative to design an effective evaluative instrument, the purpose of this paper was to identify and summarize evidence on health-care outcomes/return on investment (ROI) indicators and metrics associated with leadership quality, leadership development programs and existing evaluative instruments. Design/methodology/approach The authors performed a scoping review using the Arksey and O'Malley framework, searching eight databases from 2006 through June 2016. Findings Of 11,868 citations screened, the authors included 223 studies reporting on health-care outcomes/ROI indicators and metrics associated with leadership quality (73 studies), leadership development programs (138 studies) and existing evaluative instruments (12 studies). The extracted ROI indicators and metrics have been summarized in detail. Originality/value This review provides a snapshot in time of the current evidence on ROI indicators and metrics associated with leadership. Summarized ROI indicators and metrics can be used to design an effective evaluative instrument to assess the impact of leadership on health-care organizations.

Metrication study for large space telescope

NASA Technical Reports Server (NTRS)

Creswick, F. A.; Weller, A. E.

1973-01-01

Various approaches which could be taken in developing a metric-system design for the Large Space Telescope, considering potential penalties on development cost and time, commonality with other satellite programs, and contribution to national goals for conversion to the metric system of units were investigated. Information on the problems, potential approaches, and impacts of metrication was collected from published reports on previous aerospace-industry metrication-impact studies and through numerous telephone interviews. The recommended approach to LST metrication formulated in this study cells for new components and subsystems to be designed in metric-module dimensions, but U.S. customary practice is allowed where U.S. metric standards and metric components are not available or would be unsuitable. Electrical/electronic-system design, which is presently largely metric, is considered exempt from futher metrication. An important guideline is that metric design and fabrication should in no way compromise the effectiveness of the LST equipment.

[Bilingual Metric Education Module for Postsecondary and Adult Vocational Education.] Applying the Metric System (SI) in Trade and Industrial Education.

ERIC Educational Resources Information Center

Ellis Associates, Inc., College Park, MD.

This set of six instructional units on applying the metric system in trade and industrial education is one of three metric education modules designed for use with bilingual (Spanish and English) students in postsecondary and adult vocational programs. (Both the Spanish and English versions of this set are provided in the document.) Each unit…

The Publications Tracking and Metrics Program at NOAO: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Hunt, Sharon

2015-08-01

The National Optical Astronomy Observatory (NOAO) is the U.S. national research and development center for ground-based nighttime astronomy. The NOAO librarian manages the organization’s publications tracking and metrics program, which consists of three components: identifying publications, organizing citation data, and disseminating publications information. We are developing methods to streamline these tasks, better organize our data, provide greater accessibility to publications data, and add value to our services.Our publications tracking process is complex, as we track refereed publications citing data from several sources: NOAO telescopes at two observatory sites, telescopes of consortia in which NOAO participates, the NOAO Science Archive, and NOAO-granted community-access time on non-NOAO telescopes. We also identify and document our scientific staff publications. In addition, several individuals contribute publications data.In the past year, we made several changes in our publications tracking and metrics program. To better organize our data and streamline the creation of reports and metrics, we created a MySQL publications database. When designing this relational database, we considered ease of use, the ability to incorporate data from various sources, efficiency in data inputting and sorting, and potential for growth. We also considered the types of metrics we wished to generate from our publications data based on our target audiences and the messages we wanted to convey. To increase accessibility and dissemination of publications information, we developed a publications section on the library’s website, with citation lists, acknowledgements guidelines, and metrics. We are now developing a searchable online database for our website using PHP.The publications tracking and metrics program has provided many opportunities for the library to market its services and contribute to the organization’s mission. As we make decisions on collecting, organizing, and disseminating publications information and metrics, we add to the visibility of the library, gain professional recognition, and produce a value-added service.

Measuring Sustainability of Urban Systems: An Exploration based on Two Metrics for the Chicago Metropolitan Area

EPA Science Inventory

This presentation is comprised of two sustainability metrics that have been developed for the Chicago Metropolitan Area under SHC research program. The first sustainability metrics is Ecological Foot Print Analysis. Ecological Footprint Analysis (EFA) has been extensively deploy...

Planning for the Introduction of the Metric System into Occupational Education Programs

ERIC Educational Resources Information Center

Low, A. W.

1974-01-01

A three-dimensional planning model for introducting the International System of Metric Units into Canadian occupational education curricula includes employment level, career area, and metric topics. A fourth dimension, time, is considered in four separate phases: familiarization, adoption, conversion, and compulsory usage.

Implementing Metrics at a District Level. Administrative Guide. Revised Edition.

ERIC Educational Resources Information Center

Borelli, Michael L.; Morelli, Sandra Z.

Administrative concerns in implementing metrics at a district level are discussed and specific recommendations are made regarding them. The paper considers the extent and manner of staff training necessary, the curricular changes associated with metrics, and the distinctions between elementary and secondary programs. Appropriate instructional…

NursesforTomorrow: a proactive approach to nursing resource analysis.

PubMed

Bournes, Debra A; Plummer, Carolyn; Miller, Robert; Ferguson-Paré, Mary

2010-03-01

This paper describes the background, development, implementation and utilization of NursesforTomorrow (N4T), a practical and comprehensive nursing human resources analysis method to capture regional, institutional and patient care unit-specific actual and predicted nurse vacancies, nurse staff characteristics and nurse staffing changes. Reports generated from the process include forecasted shortfalls or surpluses of nurses, percentage of novice nurses, occupancy, sick time, overtime, agency use and other metrics. Readers will benefit from a description of the ways in which the data generated from the nursing resource analysis process are utilized at senior leadership, program and unit levels to support proactive hiring and resource allocation decisions and to predict unit-specific recruitment and retention patterns across multiple healthcare organizations and regions.

A report on the gravitational redshift test for non-metric theories of gravitation

NASA Technical Reports Server (NTRS)

1980-01-01

The frequencies of two atomic hydrogen masers and of three superconducting cavity stabilized oscillators were compared as the ensemble of oscillators was moved in the Sun's gravitational field by the rotation and orbital motion of the Earth. Metric gravitation theories predict that the gravitational redshifts of the two types of oscillators are identical, and that there should be no relative frequency shift between the oscillators; nonmetric theories, in contrast, predict a frequency shift between masers and SCSOs that is proportional to the change in solar gravitational potential experienced by the oscillators. The results are consistent with metric theories of gravitation at a level of 2%.

[Predictive model based multimetric index of macroinvertebrates for river health assessment].

PubMed

Chen, Kai; Yu, Hai Yan; Zhang, Ji Wei; Wang, Bei Xin; Chen, Qiu Wen

2017-06-18

Improving the stability of integrity of biotic index (IBI; i.e., multi-metric indices, MMI) across temporal and spatial scales is one of the most important issues in water ecosystem integrity bioassessment and water environment management. Using datasets of field-based macroinvertebrate and physicochemical variables and GIS-based natural predictors (e.g., geomorphology and climate) and land use variables collected at 227 river sites from 2004 to 2011 across the Zhejiang Province, China, we used random forests (RF) to adjust the effects of natural variations at temporal and spatial scales on macroinvertebrate metrics. We then developed natural variations adjusted (predictive) and unadjusted (null) MMIs and compared performance between them. The core me-trics selected for predictive and null MMIs were different from each other, and natural variations within core metrics in predictive MMI explained by RF models ranged between 11.4% and 61.2%. The predictive MMI was more precise and accurate, but less responsive and sensitive than null MMI. The multivariate nearest-neighbor test determined that 9 test sites and 1 most degraded site were flagged outside of the environmental space of the reference site network. We found that combination of predictive MMI developed by using predictive model and the nearest-neighbor test performed best and decreased risks of inferring type I (designating a water body as being in poor biological condition, when it was actually in good condition) and type II (designating a water body as being in good biological condition, when it was actually in poor condition) errors. Our results provided an effective method to improve the stability and performance of integrity of biotic index.

Prediction in complex systems: The case of the international trade network

NASA Astrophysics Data System (ADS)

Vidmer, Alexandre; Zeng, An; Medo, Matúš; Zhang, Yi-Cheng

2015-10-01

Predicting the future evolution of complex systems is one of the main challenges in complexity science. Based on a current snapshot of a network, link prediction algorithms aim to predict its future evolution. We apply here link prediction algorithms to data on the international trade between countries. This data can be represented as a complex network where links connect countries with the products that they export. Link prediction techniques based on heat and mass diffusion processes are employed to obtain predictions for products exported in the future. These baseline predictions are improved using a recent metric of country fitness and product similarity. The overall best results are achieved with a newly developed metric of product similarity which takes advantage of causality in the network evolution.

Joint learning of labels and distance metric.

PubMed

Liu, Bo; Wang, Meng; Hong, Richang; Zha, Zhengjun; Hua, Xian-Sheng

2010-06-01

Machine learning algorithms frequently suffer from the insufficiency of training data and the usage of inappropriate distance metric. In this paper, we propose a joint learning of labels and distance metric (JLLDM) approach, which is able to simultaneously address the two difficulties. In comparison with the existing semi-supervised learning and distance metric learning methods that focus only on label prediction or distance metric construction, the JLLDM algorithm optimizes the labels of unlabeled samples and a Mahalanobis distance metric in a unified scheme. The advantage of JLLDM is multifold: 1) the problem of training data insufficiency can be tackled; 2) a good distance metric can be constructed with only very few training samples; and 3) no radius parameter is needed since the algorithm automatically determines the scale of the metric. Extensive experiments are conducted to compare the JLLDM approach with different semi-supervised learning and distance metric learning methods, and empirical results demonstrate its effectiveness.

Design and Implementation of Performance Metrics for Evaluation of Assessments Data

ERIC Educational Resources Information Center

Ahmed, Irfan; Bhatti, Arif

2016-01-01

Evocative evaluation of assessment data is essential to quantify the achievements at course and program levels. The objective of this paper is to design performance metrics and respective formulas to quantitatively evaluate the achievement of set objectives and expected outcomes at the course levels for program accreditation. Even though…

75 FR 32473 - Submission for OMB Review; Comment Request; The STAR METRICS Program

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-08

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Submission for OMB Review..., supported by Federal funds. In subsequent generations of the program, it is hoped that STAR METRICS will... generation (such as citations and patents) as well as on social and health outcomes. Frequency of Response...

Validation Metrics for Improving Our Understanding of Turbulent Transport - Moving Beyond Proof by Pretty Picture and Loud Assertion

NASA Astrophysics Data System (ADS)

Holland, C.

2013-10-01

Developing validated models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. This tutorial will present an overview of the key guiding principles and practices for state-of-the-art validation studies, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. The primary focus of the talk will be the development of quantiatve validation metrics, which are essential for moving beyond qualitative and subjective assessments of model performance and fidelity. Particular emphasis and discussion is given to (i) the need for utilizing synthetic diagnostics to enable quantitatively meaningful comparisons between simulation and experiment, and (ii) the importance of robust uncertainty quantification and its inclusion within the metrics. To illustrate these concepts, we first review the structure and key insights gained from commonly used ``global'' transport model metrics (e.g. predictions of incremental stored energy or radially-averaged temperature), as well as their limitations. Building upon these results, a new form of turbulent transport metrics is then proposed, which focuses upon comparisons of predicted local gradients and fluctuation characteristics against observation. We demonstrate the utility of these metrics by applying them to simulations and modeling of a newly developed ``validation database'' derived from the results of a systematic, multi-year turbulent transport validation campaign on the DIII-D tokamak, in which comprehensive profile and fluctuation measurements have been obtained from a wide variety of heating and confinement scenarios. Finally, we discuss extensions of these metrics and their underlying design concepts to other areas of plasma confinement research, including both magnetohydrodynamic stability and integrated scenario modeling. Supported by the US DOE under DE-FG02-07ER54917 and DE-FC02-08ER54977.

Columbia Glacier stake location, mass balance, glacier surface altitude, and ice radar data, 1978 measurement year

USGS Publications Warehouse

Mayo, L.R.; Trabant, D.C.; March, Rod; Haeberli, Wilfried

1979-01-01

A 1 year data-collection program on Columbia Glacier, Alaska has produced a data set consisting of near-surface ice kinematics, mass balance, and altitude change at 57 points and 34 ice radar soundings. These data presented in two tables, are part of the basic data required for glacier dynamic analysis, computer models, and predictions of the number and size of icebergs which Columbia Glacier will calve into shipping lanes of eastern Prince William Sound. A metric, sea-level coordinate system was developed for use in surveying throughout the basin. Its use is explained and monument coordinates listed. A series of seven integrated programs for calculators were used in both the field and office to reduce the surveying data. These programs are thoroughly documented and explained in the report. (Kosco-USGS)

Metric. Career Education Program.

ERIC Educational Resources Information Center

Salem City Schools, NJ.

This is a compilation of instructional materials to assist teachers and students in learning about the metric system. Contents are organized into four color-coded sections containing the following: (1) background and reference materials for the teacher, including a list of available media and a conversion chart; (2) metric activities for primary…

Relating forest attributes with area- and tree-based light detection and ranging metrics for western Oregon

Treesearch

Michael E. Goerndt; Vincente J. Monleon; Hailemariam. Temesgen

2010-01-01

Three sets of linear models were developed to predict several forest attributes, using stand-level and single-tree remote sensing (STRS) light detection and ranging (LiDAR) metrics as predictor variables. The first used only area-level metrics (ALM) associated with first-return height distribution, percentage of cover, and canopy transparency. The second alternative...

Predicted effect of landscape position on wildlife habitat value of Conservation Reserve Enhancement Program wetlands in a tile-drained agricultural region

USGS Publications Warehouse

Otis, David L.; Crumpton, William R.; Green, David; Loan-Wilsey, Anna; Cooper, Tom; Johnson, Rex R.

2013-01-01

Justification for investment in restored or constructed wetland projects are often based on presumed net increases in ecosystem services. However, quantitative assessment of performance metrics is often difficult and restricted to a single objective. More comprehensive performance assessments could help inform decision-makers about trade-offs in services provided by alternative restoration program design attributes. The primary goal of the Iowa Conservation Reserve Enhancement Program is to establish wetlands that efficiently remove nitrates from tile-drained agricultural landscapes. A secondary objective is provision of wildlife habitat. We used existing wildlife habitat models to compare relative net change in potential wildlife habitat value for four alternative landscape positions of wetlands within the watershed. Predicted species richness and habitat value for birds, mammals, amphibians, and reptiles generally increased as the wetland position moved lower in the watershed. However, predicted average net increase between pre- and post-project value was dependent on taxonomic group. The increased average wetland area and changes in surrounding upland habitat composition among landscape positions were responsible for these differences. Net change in predicted densities of several grassland bird species at the four landscape positions was variable and species-dependent. Predicted waterfowl breeding activity was greater for lower drainage position wetlands. Although our models are simplistic and provide only a predictive index of potential habitat value, we believe such assessment exercises can provide a tool for coarse-level comparisons of alternative proposed project attributes and a basis for constructing informed hypotheses in auxiliary empirical field studies.

A novel time series link prediction method: Learning automata approach

NASA Astrophysics Data System (ADS)

Moradabadi, Behnaz; Meybodi, Mohammad Reza

2017-09-01

Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.

Handbook of aircraft noise metrics

NASA Technical Reports Server (NTRS)

Bennett, R. L.; Pearsons, K. S.

1981-01-01

Information is presented on 22 noise metrics that are associated with the measurement and prediction of the effects of aircraft noise. Some of the instantaneous frequency weighted sound level measures, such as A-weighted sound level, are used to provide multiple assessment of the aircraft noise level. Other multiple event metrics, such as day-night average sound level, were designed to relate sound levels measured over a period of time to subjective responses in an effort to determine compatible land uses and aid in community planning. The various measures are divided into: (1) instantaneous sound level metrics; (2) duration corrected single event metrics; (3) multiple event metrics; and (4) speech communication metrics. The scope of each measure is examined in terms of its: definition, purpose, background, relationship to other measures, calculation method, example, equipment, references, and standards.

Handbook of aircraft noise metrics

NASA Astrophysics Data System (ADS)

Bennett, R. L.; Pearsons, K. S.

1981-03-01

Information is presented on 22 noise metrics that are associated with the measurement and prediction of the effects of aircraft noise. Some of the instantaneous frequency weighted sound level measures, such as A-weighted sound level, are used to provide multiple assessment of the aircraft noise level. Other multiple event metrics, such as day-night average sound level, were designed to relate sound levels measured over a period of time to subjective responses in an effort to determine compatible land uses and aid in community planning. The various measures are divided into: (1) instantaneous sound level metrics; (2) duration corrected single event metrics; (3) multiple event metrics; and (4) speech communication metrics. The scope of each measure is examined in terms of its: definition, purpose, background, relationship to other measures, calculation method, example, equipment, references, and standards.

A Geometric Approach to Modeling Microstructurally Small Fatigue Crack Formation. 2; Simulation and Prediction of Crack Nucleation in AA 7075-T651

NASA Technical Reports Server (NTRS)

Hochhalter, Jake D.; Littlewood, David J.; Christ, Robert J., Jr.; Veilleux, M. G.; Bozek, J. E.; Ingraffea, A. R.; Maniatty, Antionette M.

2010-01-01

The objective of this paper is to develop further a framework for computationally modeling microstructurally small fatigue crack growth in AA 7075-T651 [1]. The focus is on the nucleation event, when a crack extends from within a second-phase particle into a surrounding grain, since this has been observed to be an initiating mechanism for fatigue crack growth in this alloy. It is hypothesized that nucleation can be predicted by computing a non-local nucleation metric near the crack front. The hypothesis is tested by employing a combination of experimentation and nite element modeling in which various slip-based and energy-based nucleation metrics are tested for validity, where each metric is derived from a continuum crystal plasticity formulation. To investigate each metric, a non-local procedure is developed for the calculation of nucleation metrics in the neighborhood of a crack front. Initially, an idealized baseline model consisting of a single grain containing a semi-ellipsoidal surface particle is studied to investigate the dependence of each nucleation metric on lattice orientation, number of load cycles, and non-local regularization method. This is followed by a comparison of experimental observations and computational results for microstructural models constructed by replicating the observed microstructural geometry near second-phase particles in fatigue specimens. It is found that orientation strongly influences the direction of slip localization and, as a result, in uences the nucleation mechanism. Also, the baseline models, replication models, and past experimental observation consistently suggest that a set of particular grain orientations is most likely to nucleate fatigue cracks. It is found that a continuum crystal plasticity model and a non-local nucleation metric can be used to predict the nucleation event in AA 7075-T651. However, nucleation metric threshold values that correspond to various nucleation governing mechanisms must be calibrated.

MOCAT: A Metagenomics Assembly and Gene Prediction Toolkit

PubMed Central

Li, Junhua; Chen, Weineng; Chen, Hua; Mende, Daniel R.; Arumugam, Manimozhiyan; Pan, Qi; Liu, Binghang; Qin, Junjie; Wang, Jun; Bork, Peer

2012-01-01

MOCAT is a highly configurable, modular pipeline for fast, standardized processing of single or paired-end sequencing data generated by the Illumina platform. The pipeline uses state-of-the-art programs to quality control, map, and assemble reads from metagenomic samples sequenced at a depth of several billion base pairs, and predict protein-coding genes on assembled metagenomes. Mapping against reference databases allows for read extraction or removal, as well as abundance calculations. Relevant statistics for each processing step can be summarized into multi-sheet Excel documents and queryable SQL databases. MOCAT runs on UNIX machines and integrates seamlessly with the SGE and PBS queuing systems, commonly used to process large datasets. The open source code and modular architecture allow users to modify or exchange the programs that are utilized in the various processing steps. Individual processing steps and parameters were benchmarked and tested on artificial, real, and simulated metagenomes resulting in an improvement of selected quality metrics. MOCAT can be freely downloaded at http://www.bork.embl.de/mocat/. PMID:23082188

MOCAT: a metagenomics assembly and gene prediction toolkit.

PubMed

Kultima, Jens Roat; Sunagawa, Shinichi; Li, Junhua; Chen, Weineng; Chen, Hua; Mende, Daniel R; Arumugam, Manimozhiyan; Pan, Qi; Liu, Binghang; Qin, Junjie; Wang, Jun; Bork, Peer

2012-01-01

MOCAT is a highly configurable, modular pipeline for fast, standardized processing of single or paired-end sequencing data generated by the Illumina platform. The pipeline uses state-of-the-art programs to quality control, map, and assemble reads from metagenomic samples sequenced at a depth of several billion base pairs, and predict protein-coding genes on assembled metagenomes. Mapping against reference databases allows for read extraction or removal, as well as abundance calculations. Relevant statistics for each processing step can be summarized into multi-sheet Excel documents and queryable SQL databases. MOCAT runs on UNIX machines and integrates seamlessly with the SGE and PBS queuing systems, commonly used to process large datasets. The open source code and modular architecture allow users to modify or exchange the programs that are utilized in the various processing steps. Individual processing steps and parameters were benchmarked and tested on artificial, real, and simulated metagenomes resulting in an improvement of selected quality metrics. MOCAT can be freely downloaded at http://www.bork.embl.de/mocat/.

Ideal cardiovascular health predicts lower risk of abnormal liver enzymes levels in the Chilean National Health Survey (2009-2010).

PubMed

García-Hermoso, Antonio; Hackney, Anthony C; Ramírez-Vélez, Robinson

2017-01-01

High levels of gamma glutamyltransferase (gamma-GT) and alanine aminotransferase (ALT), as well as fatty liver index (FLI) has been associated with higher cardiovascular disease risk factors in adults. The aim of this study was to examine the relationship between gamma-GT, ALT, and fatty liver index FLI levels across a gradient number of ideal cardiovascular health metrics in a representative sample of adults from the Chilean National Health Survey 2009-2010. Data from 1,023 men and 1,449 women (≥ 15 years) from the Chilean Health Survey 2009-2010 were analyzed. Ideal cardiovascular health was defined as meeting ideal levels of the following components: four behaviours (smoking, body mass index, physical activity and diet adherence) and three factors (total cholesterol, blood pressure and fasting glucose). Adults were grouped into three categories according to their number of ideal cardiovascular health metrics: ideal (5-7 metrics), intermediate (3-4 metrics), and poor (0-2 metrics). Blood levels of gamma-GT and ALT were measured and the FLI was calculated. A higher number of ideal cardiovascular health index metric was associated with lower gamma-GT, ALT and FLI (p from trend analysis <0.001). Also, adults meeting at least 3-4 metrics were predicted less likely to have prevalence of abnormal levels of gamma-GT and FLI (p<0.001) compared to adults who met only 0-2 metrics. These findings reinforce the usefulness of the ideal cardiovascular health metrics proposed by the American Heart Association as a tool to identify target subjects and promote cardiovascular health in South-American adults.

SU-F-J-199: Predictive Models for Cone Beam CT-Based Online Verification of Pencil Beam Scanning Proton Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yin, L; Lin, A; Ahn, P

Purpose: To utilize online CBCT scans to develop models for predicting DVH metrics in proton therapy of head and neck tumors. Methods: Nine patients with locally advanced oropharyngeal cancer were retrospectively selected in this study. Deformable image registration was applied to the simulation CT, target volumes, and organs at risk (OARs) contours onto each weekly CBCT scan. Intensity modulated proton therapy (IMPT) treatment plans were created on the simulation CT and forward calculated onto each corrected CBCT scan. Thirty six potentially predictive metrics were extracted from each corrected CBCT. These features include minimum/maximum/mean over and under-ranges at the proximal andmore » distal surface of PTV volumes, and geometrical and water equivalent distance between PTV and each OARs. Principal component analysis (PCA) was used to reduce the dimension of the extracted features. Three principal components were found to account for over 90% of variances in those features. Datasets from eight patients were used to train a machine learning model to fit these principal components with DVH metrics (dose to 95% and 5% of PTV, mean dose or max dose to OARs) from the forward calculated dose on each corrected CBCT. The accuracy of this model was verified on the datasets from the 9th patient. Results: The predicted changes of DVH metrics from the model were in good agreement with actual values calculated on corrected CBCT images. Median differences were within 1 Gy for most DVH metrics except for larynx and constrictor mean dose. However, a large spread of the differences was observed, indicating additional training datasets and predictive features are needed to improve the model. Conclusion: Intensity corrected CBCT scans hold the potential to be used for online verification of proton therapy and prediction of delivered dose distributions.« less

VHA mental health information system: applying health information technology to monitor and facilitate implementation of VHA Uniform Mental Health Services Handbook requirements.

PubMed

Trafton, Jodie A; Greenberg, Greg; Harris, Alex H S; Tavakoli, Sara; Kearney, Lisa; McCarthy, John; Blow, Fredric; Hoff, Rani; Schohn, Mary

2013-03-01

To describe the design and deployment of health information technology to support implementation of mental health services policy requirements in the Veterans Health Administration (VHA). Using administrative and self-report survey data, we developed and fielded metrics regarding implementation of the requirements delineated in the VHA Uniform Mental Health Services Handbook. Finalized metrics were incorporated into 2 external facilitation-based quality improvement programs led by the VHA Mental Health Operations. To support these programs, tailored site-specific reports were generated. Metric development required close collaboration between program evaluators, policy makers and clinical leadership, and consideration of policy language and intent. Electronic reports supporting different purposes required distinct formatting and presentation features, despite their having similar general goals and using the same metrics. Health information technology can facilitate mental health policy implementation but must be integrated into a process of consensus building and close collaboration with policy makers, evaluators, and practitioners.

Biotic, water-quality, and hydrologic metrics calculated for the analysis of temporal trends in National Water Quality Assessment Program Data in the Western United States

USGS Publications Warehouse

Wiele, Stephen M.; Brasher, Anne M.D.; Miller, Matthew P.; May, Jason T.; Carpenter, Kurt D.

2012-01-01

The U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program was established by Congress in 1991 to collect long-term, nationally consistent information on the quality of the Nation's streams and groundwater. The NAWQA Program utilizes interdisciplinary and dynamic studies that link the chemical and physical conditions of streams (such as flow and habitat) with ecosystem health and the biologic condition of algae, aquatic invertebrates, and fish communities. This report presents metrics derived from NAWQA data and the U.S. Geological Survey streamgaging network for sampling sites in the Western United States, as well as associated chemical, habitat, and streamflow properties. The metrics characterize the conditions of algae, aquatic invertebrates, and fish. In addition, we have compiled climate records and basin characteristics related to the NAWQA sampling sites. The calculated metrics and compiled data can be used to analyze ecohydrologic trends over time.

Bilingual Metric Education Modules for Postsecondary and Adult Vocational Education. Final Report.

ERIC Educational Resources Information Center

Ellis Associates, Inc., College Park, MD.

A project was conducted to develop three metric education modules for use with bilingual (Spanish and English) students in postsecondary and adult vocational education programs. Developed for the first section of each module, five instructional units cover basic metric concepts: (1) measuring length and finding area, (2) measuring volume, (3)…

A national-scale remote sensing-based methodology for quantifying tidal marsh biomass to support "Blue Carbon" accounting

NASA Astrophysics Data System (ADS)

Byrd, K. B.; Ballanti, L.; Nguyen, D.; Simard, M.; Thomas, N.; Windham-Myers, L.; Castaneda, E.; Kroeger, K. D.; Gonneea, M. E.; O'Keefe Suttles, J.; Megonigal, P.; Troxler, T.; Schile, L. M.; Davis, M.; Woo, I.

2016-12-01

According to 2013 IPCC Wetlands Supplement guidelines, tidal marsh Tier 2 or Tier 3 accounting must include aboveground biomass carbon stock changes. To support this need, we are using free satellite and aerial imagery to develop a national scale, consistent remote sensing-based methodology for quantifying tidal marsh aboveground biomass. We are determining the extent to which additional satellite data will increase the accuracy of this "blue carbon" accounting. Working in 6 U.S. estuaries (Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA), we built a tidal marsh biomass dataset (n=2404). Landsat reflectance data were matched spatially and temporally with field plots using Google Earth Engine. We quantified percent cover of green vegetation, non-vegetation, and open water in Landsat pixels using segmentation of 1m National Agriculture Imagery Program aerial imagery. Sentinel-1A C-band backscatter data were used in Chesapeake, Mississippi Delta and Puget Sound. We tested multiple Landsat vegetation indices and Sentinel backscatter metrics in 30m scale biomass linear regression models by region. Scaling biomass by fraction green vegetation significantly improved biomass estimation (e.g. Cape Cod: R2 = 0.06 vs. R2 = 0.60, n=28). The best vegetation indices differed by region, though indices based on the shortwave infrared-1 and red bands were most predictive in the Everglades and the Mississippi Delta, while the soil adjusted vegetation index was most predictive in Puget Sound and Chesapeake. Backscatter metrics significantly improved model predictions over vegetation indices alone; consistently across regions, the most significant metric was the range in backscatter values within the green vegetation segment of the Landsat pixel (e.g. Mississippi Delta: R2 = 0.47 vs. R2 = 0.59, n=15). Results support using remote sensing of biomass stock change to estimate greenhouse gas emission factors in tidal wetlands.

The relationship between assessment methods and self-directed learning readiness in medical education.

PubMed

Monroe, Katherine S

2016-03-11

This research explored the assessment of self-directed learning readiness within the comprehensive evaluation of medical students' knowledge and skills and the extent to which several variables predicted participants' self-directed learning readiness prior to their graduation. Five metrics for evaluating medical students were considered in a multiple regression analysis. Fourth-year medical students at a competitive US medical school received an informed consent and an online survey. Participants voluntarily completed a self-directed learning readiness scale that assessed four subsets of self-directed learning readiness and consented to the release of their academic records. The assortment of metrics considered in this study only vaguely captured students' self-directedness. The strongest predictors were faculty evaluations of students' performance on clerkship rotations. Specific clerkship grades were mildly predictive of three subscales. The Pediatrics clerkship modestly predicted critical self-evaluation (r=-.30, p=.01) and the Psychiatry clerkship mildly predicted learning self-efficacy (r =-.30, p=.01), while the Junior Surgery clerkship nominally correlated with participants' effective organization for learning (r=.21, p=.05). Other metrics examined did not contribute to predicting participants' readiness for self-directed learning. Given individual differences among participants for the variables considered, no combination of students' grades and/or test scores overwhelmingly predicted their aptitude for self-directed learning. Considering the importance of fostering medical students' self-directed learning skills, schools need a reliable and pragmatic approach to measure them. This data analysis, however, offered no clear-cut way of documenting students' self-directed learning readiness based on the evaluation metrics included.

Validity of the two-level model for Viterbi decoder gap-cycle performance

NASA Technical Reports Server (NTRS)

Dolinar, S.; Arnold, S.

1990-01-01

A two-level model has previously been proposed for approximating the performance of a Viterbi decoder which encounters data received with periodically varying signal-to-noise ratio. Such cyclically gapped data is obtained from the Very Large Array (VLA), either operating as a stand-alone system or arrayed with Goldstone. This approximate model predicts that the decoder error rate will vary periodically between two discrete levels with the same period as the gap cycle. It further predicts that the length of the gapped portion of the decoder error cycle for a constraint length K decoder will be about K-1 bits shorter than the actual duration of the gap. The two-level model for Viterbi decoder performance with gapped data is subjected to detailed validation tests. Curves showing the cyclical behavior of the decoder error burst statistics are compared with the simple square-wave cycles predicted by the model. The validity of the model depends on a parameter often considered irrelevant in the analysis of Viterbi decoder performance, the overall scaling of the received signal or the decoder's branch-metrics. Three scaling alternatives are examined: optimum branch-metric scaling and constant branch-metric scaling combined with either constant noise-level scaling or constant signal-level scaling. The simulated decoder error cycle curves roughly verify the accuracy of the two-level model for both the case of optimum branch-metric scaling and the case of constant branch-metric scaling combined with constant noise-level scaling. However, the model is not accurate for the case of constant branch-metric scaling combined with constant signal-level scaling.

Can spatial statistical river temperature models be transferred between catchments?

NASA Astrophysics Data System (ADS)

Jackson, Faye L.; Fryer, Robert J.; Hannah, David M.; Malcolm, Iain A.

2017-09-01

There has been increasing use of spatial statistical models to understand and predict river temperature (Tw) from landscape covariates. However, it is not financially or logistically feasible to monitor all rivers and the transferability of such models has not been explored. This paper uses Tw data from four river catchments collected in August 2015 to assess how well spatial regression models predict the maximum 7-day rolling mean of daily maximum Tw (Twmax) within and between catchments. Models were fitted for each catchment separately using (1) landscape covariates only (LS models) and (2) landscape covariates and an air temperature (Ta) metric (LS_Ta models). All the LS models included upstream catchment area and three included a river network smoother (RNS) that accounted for unexplained spatial structure. The LS models transferred reasonably to other catchments, at least when predicting relative levels of Twmax. However, the predictions were biased when mean Twmax differed between catchments. The RNS was needed to characterise and predict finer-scale spatially correlated variation. Because the RNS was unique to each catchment and thus non-transferable, predictions were better within catchments than between catchments. A single model fitted to all catchments found no interactions between the landscape covariates and catchment, suggesting that the landscape relationships were transferable. The LS_Ta models transferred less well, with particularly poor performance when the relationship with the Ta metric was physically implausible or required extrapolation outside the range of the data. A single model fitted to all catchments found catchment-specific relationships between Twmax and the Ta metric, indicating that the Ta metric was not transferable. These findings improve our understanding of the transferability of spatial statistical river temperature models and provide a foundation for developing new approaches for predicting Tw at unmonitored locations across multiple catchments and larger spatial scales.

Accounting for the phase, spatial frequency and orientation demands of the task improves metrics based on the visual Strehl ratio.

PubMed

Young, Laura K; Love, Gordon D; Smithson, Hannah E

2013-09-20

Advances in ophthalmic instrumentation have allowed high order aberrations to be measured in vivo. These measurements describe the distortions to a plane wavefront entering the eye, but not the effect they have on visual performance. One metric for predicting visual performance from a wavefront measurement uses the visual Strehl ratio, calculated in the optical transfer function (OTF) domain (VSOTF) (Thibos et al., 2004). We considered how well such a metric captures empirical measurements of the effects of defocus, coma and secondary astigmatism on letter identification and on reading. We show that predictions using the visual Strehl ratio can be significantly improved by weighting the OTF by the spatial frequency band that mediates letter identification and further improved by considering the orientation of phase and contrast changes imposed by the aberration. We additionally showed that these altered metrics compare well to a cross-correlation-based metric. We suggest a version of the visual Strehl ratio, VScombined, that incorporates primarily those phase disruptions and contrast changes that have been shown independently to affect object recognition processes. This metric compared well to VSOTF for letter identification and was the best predictor of reading performance, having a higher correlation with the data than either the VSOTF or cross-correlation-based metric. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Memory colours and colour quality evaluation of conventional and solid-state lamps.

PubMed

Smet, Kevin A G; Ryckaert, Wouter R; Pointer, Michael R; Deconinck, Geert; Hanselaer, Peter

2010-12-06

A colour quality metric based on memory colours is presented. The basic idea is simple. The colour quality of a test source is evaluated as the degree of similarity between the colour appearance of a set of familiar objects and their memory colours. The closer the match, the better the colour quality. This similarity was quantified using a set of similarity distributions obtained by Smet et al. in a previous study. The metric was validated by calculating the Pearson and Spearman correlation coefficients between the metric predictions and the visual appreciation results obtained in a validation experiment conducted by the authors as well those obtained in two independent studies. The metric was found to correlate well with the visual appreciation of the lighting quality of the sources used in the three experiments. Its performance was also compared with that of the CIE colour rendering index and the NIST colour quality scale. For all three experiments, the metric was found to be significantly better at predicting the correct visual rank order of the light sources (p < 0.1).

PREDICTION METRICS FOR CHEMICAL DETECTION IN LONG-WAVE INFRARED HYPERSPECTRAL IMAGERY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chilton, M.; Walsh, S.J.; Daly, D.S.

2009-01-01

Natural and man-made chemical processes generate gaseous plumes that may be detected by hyperspectral imaging, which produces a matrix of spectra affected by the chemical constituents of the plume, the atmosphere, the bounding background surface and instrument noise. A physics-based model of observed radiance shows that high chemical absorbance and low background emissivity result in a larger chemical signature. Using simulated hyperspectral imagery, this study investigated two metrics which exploited this relationship. The objective was to explore how well the chosen metrics predicted when a chemical would be more easily detected when comparing one background type to another. The twomore » predictor metrics correctly rank ordered the backgrounds for about 94% of the chemicals tested as compared to the background rank orders from Whitened Matched Filtering (a detection algorithm) of the simulated spectra. These results suggest that the metrics provide a reasonable summary of how the background emissivity and chemical absorbance interact to produce the at-sensor chemical signal. This study suggests that similarly effective predictors that account for more general physical conditions may be derived.« less

Disturbance metrics predict a wetland Vegetation Index of Biotic Integrity

USGS Publications Warehouse

Stapanian, Martin A.; Mack, John; Adams, Jean V.; Gara, Brian; Micacchion, Mick

2013-01-01

Indices of biological integrity of wetlands based on vascular plants (VIBIs) have been developed in many areas in the USA. Knowledge of the best predictors of VIBIs would enable management agencies to make better decisions regarding mitigation site selection and performance monitoring criteria. We use a novel statistical technique to develop predictive models for an established index of wetland vegetation integrity (Ohio VIBI), using as independent variables 20 indices and metrics of habitat quality, wetland disturbance, and buffer area land use from 149 wetlands in Ohio, USA. For emergent and forest wetlands, predictive models explained 61% and 54% of the variability, respectively, in Ohio VIBI scores. In both cases the most important predictor of Ohio VIBI score was a metric that assessed habitat alteration and development in the wetland. Of secondary importance as a predictor was a metric that assessed microtopography, interspersion, and quality of vegetation communities in the wetland. Metrics and indices assessing disturbance and land use of the buffer area were generally poor predictors of Ohio VIBI scores. Our results suggest that vegetation integrity of emergent and forest wetlands could be most directly enhanced by minimizing substrate and habitat disturbance within the wetland. Such efforts could include reducing or eliminating any practices that disturb the soil profile, such as nutrient enrichment from adjacent farm land, mowing, grazing, or cutting or removing woody plants.

LANDSCAPE METRICS THAT ARE USEFUL FOR EXPLAINING ESTUARINE ECOLOGICAL RESPONSES

EPA Science Inventory

We investigated whether land use/cover characteristics of watersheds associated with estuaries exhibit a strong enough signal to make landscape metrics useful for predicting estuarine ecological condition. We used multivariate logistic regression models to discriminate between su...

Draft Software Metrics Panels Final Report. Papers Presented at the 30 June 1980 Meeting on Software Metrics, Washington DC.

DTIC Science & Technology

1980-06-01

measuring program understanding. Shneiderman, Mayer, McKay, and Heller [241 found that flowcharts are redundant and have a potential negative affect on...dictionaries of program variables are superior to macro flowcharts as an aid to understand program control and data structures. Chrysler [5], using no...procedures as do beginners . Also; guaranteeing that groups of begining programmers have equal ability is not trivial. 3-10 The problem with material

Decision-relevant evaluation of climate models: A case study of chill hours in California

NASA Astrophysics Data System (ADS)

Jagannathan, K. A.; Jones, A. D.; Kerr, A. C.

2017-12-01

The past decade has seen a proliferation of different climate datasets with over 60 climate models currently in use. Comparative evaluation and validation of models can assist practitioners chose the most appropriate models for adaptation planning. However, such assessments are usually conducted for `climate metrics' such as seasonal temperature, while sectoral decisions are often based on `decision-relevant outcome metrics' such as growing degree days or chill hours. Since climate models predict different metrics with varying skill, the goal of this research is to conduct a bottom-up evaluation of model skill for `outcome-based' metrics. Using chill hours (number of hours in winter months where temperature is lesser than 45 deg F) in Fresno, CA as a case, we assess how well different GCMs predict the historical mean and slope of chill hours, and whether and to what extent projections differ based on model selection. We then compare our results with other climate-based evaluations of the region, to identify similarities and differences. For the model skill evaluation, historically observed chill hours were compared with simulations from 27 GCMs (and multiple ensembles). Model skill scores were generated based on a statistical hypothesis test of the comparative assessment. Future projections from RCP 8.5 runs were evaluated, and a simple bias correction was also conducted. Our analysis indicates that model skill in predicting chill hour slope is dependent on its skill in predicting mean chill hours, which results from the non-linear nature of the chill metric. However, there was no clear relationship between the models that performed well for the chill hour metric and those that performed well in other temperature-based evaluations (such winter minimum temperature or diurnal temperature range). Further, contrary to conclusions from other studies, we also found that the multi-model mean or large ensemble mean results may not always be most appropriate for this outcome metric. Our assessment sheds light on key differences between global versus local skill, and broad versus specific skill of climate models, highlighting that decision-relevant model evaluation may be crucial for providing practitioners with the best available climate information for their specific needs.

Gravitation theory - Empirical status from solar system experiments.

NASA Technical Reports Server (NTRS)

Nordtvedt, K. L., Jr.

1972-01-01

Review of historical and recent experiments which speak in favor of a post-Newtonian relativistic gravitational theory. The topics include the foundational experiments, metric theories of gravity, experiments designed to differentiate among the metric theories, and tests of Machian concepts of gravity. It is shown that the metric field for any metric theory can be specified by a series of potential terms with several parameters. It is pointed out that empirical results available up to date yield values of the parameters which are consistent with the prediction of Einstein's general relativity.

How Much Does it Cost to Go Metric?

ERIC Educational Resources Information Center

Lindbeck, John R.

1976-01-01

Presents information on metric conversion costs and offers suggestions to aid teachers in making intelligent decisions with regard to programs in drafting, woodworking, metal working, and graphic arts. (HD)

Energy prediction using spatiotemporal pattern networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated bymore » the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.« less

Your Brain on the Movies: A Computational Approach for Predicting Box-office Performance from Viewer’s Brain Responses to Movie Trailers

PubMed Central

Christoforou, Christoforos; Papadopoulos, Timothy C.; Constantinidou, Fofi; Theodorou, Maria

2017-01-01

The ability to anticipate the population-wide response of a target audience to a new movie or TV series, before its release, is critical to the film industry. Equally important is the ability to understand the underlying factors that drive or characterize viewer’s decision to watch a movie. Traditional approaches (which involve pilot test-screenings, questionnaires, and focus groups) have reached a plateau in their ability to predict the population-wide responses to new movies. In this study, we develop a novel computational approach for extracting neurophysiological electroencephalography (EEG) and eye-gaze based metrics to predict the population-wide behavior of movie goers. We further, explore the connection of the derived metrics to the underlying cognitive processes that might drive moviegoers’ decision to watch a movie. Towards that, we recorded neural activity—through the use of EEG—and eye-gaze activity from a group of naive individuals while watching movie trailers of pre-selected movies for which the population-wide preference is captured by the movie’s market performance (i.e., box-office ticket sales in the US). Our findings show that the neural based metrics, derived using the proposed methodology, carry predictive information about the broader audience decisions to watch a movie, above and beyond traditional methods. In particular, neural metrics are shown to predict up to 72% of the variance of the films’ performance at their premiere and up to 67% of the variance at following weekends; which corresponds to a 23-fold increase in prediction accuracy compared to current neurophysiological or traditional methods. We discuss our findings in the context of existing literature and hypothesize on the possible connection of the derived neurophysiological metrics to cognitive states of focused attention, the encoding of long-term memory, and the synchronization of different components of the brain’s rewards network. Beyond the practical implication in predicting and understanding the behavior of moviegoers, the proposed approach can facilitate the use of video stimuli in neuroscience research; such as the study of individual differences in attention-deficit disorders, and the study of desensitization to media violence. PMID:29311885

Your Brain on the Movies: A Computational Approach for Predicting Box-office Performance from Viewer's Brain Responses to Movie Trailers.

PubMed

Christoforou, Christoforos; Papadopoulos, Timothy C; Constantinidou, Fofi; Theodorou, Maria

2017-01-01

The ability to anticipate the population-wide response of a target audience to a new movie or TV series, before its release, is critical to the film industry. Equally important is the ability to understand the underlying factors that drive or characterize viewer's decision to watch a movie. Traditional approaches (which involve pilot test-screenings, questionnaires, and focus groups) have reached a plateau in their ability to predict the population-wide responses to new movies. In this study, we develop a novel computational approach for extracting neurophysiological electroencephalography (EEG) and eye-gaze based metrics to predict the population-wide behavior of movie goers. We further, explore the connection of the derived metrics to the underlying cognitive processes that might drive moviegoers' decision to watch a movie. Towards that, we recorded neural activity-through the use of EEG-and eye-gaze activity from a group of naive individuals while watching movie trailers of pre-selected movies for which the population-wide preference is captured by the movie's market performance (i.e., box-office ticket sales in the US). Our findings show that the neural based metrics, derived using the proposed methodology, carry predictive information about the broader audience decisions to watch a movie, above and beyond traditional methods. In particular, neural metrics are shown to predict up to 72% of the variance of the films' performance at their premiere and up to 67% of the variance at following weekends; which corresponds to a 23-fold increase in prediction accuracy compared to current neurophysiological or traditional methods. We discuss our findings in the context of existing literature and hypothesize on the possible connection of the derived neurophysiological metrics to cognitive states of focused attention, the encoding of long-term memory, and the synchronization of different components of the brain's rewards network. Beyond the practical implication in predicting and understanding the behavior of moviegoers, the proposed approach can facilitate the use of video stimuli in neuroscience research; such as the study of individual differences in attention-deficit disorders, and the study of desensitization to media violence.

The Assignment of Scale to Object-Oriented Software Measures

NASA Technical Reports Server (NTRS)

Neal, Ralph D.; Weistroffer, H. Roland; Coppins, Richard J.

1997-01-01

In order to improve productivity (and quality), measurement of specific aspects of software has become imperative. As object oriented programming languages have become more widely used, metrics designed specifically for object-oriented software are required. Recently a large number of new metrics for object- oriented software has appeared in the literature. Unfortunately, many of these proposed metrics have not been validated to measure what they purport to measure. In this paper fifty (50) of these metrics are analyzed.

Predicting the Overall Spatial Quality of Automotive Audio Systems

NASA Astrophysics Data System (ADS)

Koya, Daisuke

The spatial quality of automotive audio systems is often compromised due to their unideal listening environments. Automotive audio systems need to be developed quickly due to industry demands. A suitable perceptual model could evaluate the spatial quality of automotive audio systems with similar reliability to formal listening tests but take less time. Such a model is developed in this research project by adapting an existing model of spatial quality for automotive audio use. The requirements for the adaptation were investigated in a literature review. A perceptual model called QESTRAL was reviewed, which predicts the overall spatial quality of domestic multichannel audio systems. It was determined that automotive audio systems are likely to be impaired in terms of the spatial attributes that were not considered in developing the QESTRAL model, but metrics are available that might predict these attributes. To establish whether the QESTRAL model in its current form can accurately predict the overall spatial quality of automotive audio systems, MUSHRA listening tests using headphone auralisation with head tracking were conducted to collect results to be compared against predictions by the model. Based on guideline criteria, the model in its current form could not accurately predict the overall spatial quality of automotive audio systems. To improve prediction performance, the QESTRAL model was recalibrated and modified using existing metrics of the model, those that were proposed from the literature review, and newly developed metrics. The most important metrics for predicting the overall spatial quality of automotive audio systems included those that were interaural cross-correlation (IACC) based, relate to localisation of the frontal audio scene, and account for the perceived scene width in front of the listener. Modifying the model for automotive audio systems did not invalidate its use for domestic audio systems. The resulting model predicts the overall spatial quality of 2- and 5-channel automotive audio systems with a cross-validation performance of R. 2 = 0.85 and root-mean-squareerror (RMSE) = 11.03%.

A College Level Program for Instructing the Metric System.

ERIC Educational Resources Information Center

Thrall, Marjorie A.

Although the Congress of the United States has enacted legislation calling for a conversion to the metric system by October 1992, recent government reports suggest that the country may not be prepared to meet that deadline. In an effort to develop a learning module for instructing community college students in the application of the metric system,…

Hyperspectral face recognition using improved inter-channel alignment based on qualitative prediction models.

PubMed

Cho, Woon; Jang, Jinbeum; Koschan, Andreas; Abidi, Mongi A; Paik, Joonki

2016-11-28

A fundamental limitation of hyperspectral imaging is the inter-band misalignment correlated with subject motion during data acquisition. One way of resolving this problem is to assess the alignment quality of hyperspectral image cubes derived from the state-of-the-art alignment methods. In this paper, we present an automatic selection framework for the optimal alignment method to improve the performance of face recognition. Specifically, we develop two qualitative prediction models based on: 1) a principal curvature map for evaluating the similarity index between sequential target bands and a reference band in the hyperspectral image cube as a full-reference metric; and 2) the cumulative probability of target colors in the HSV color space for evaluating the alignment index of a single sRGB image rendered using all of the bands of the hyperspectral image cube as a no-reference metric. We verify the efficacy of the proposed metrics on a new large-scale database, demonstrating a higher prediction accuracy in determining improved alignment compared to two full-reference and five no-reference image quality metrics. We also validate the ability of the proposed framework to improve hyperspectral face recognition.

Multi-mode evaluation of power-maximizing cross-flow turbine controllers

DOE PAGES

Forbush, Dominic; Cavagnaro, Robert J.; Donegan, James; ...

2017-09-21

A general method for predicting and evaluating the performance of three candidate cross-flow turbine power-maximizing controllers is presented in this paper using low-order dynamic simulation, scaled laboratory experiments, and full-scale field testing. For each testing mode and candidate controller, performance metrics quantifying energy capture (ability of a controller to maximize power), variation in torque and rotation rate (related to drive train fatigue), and variation in thrust loads (related to structural fatigue) are quantified for two purposes. First, for metrics that could be evaluated across all testing modes, we considered the accuracy with which simulation or laboratory experiments could predict performancemore » at full scale. Second, we explored the utility of these metrics to contrast candidate controller performance. For these turbines and set of candidate controllers, energy capture was found to only differentiate controller performance in simulation, while the other explored metrics were able to predict performance of the full-scale turbine in the field with various degrees of success. Finally, effects of scale between laboratory and full-scale testing are considered, along with recommendations for future improvements to dynamic simulations and controller evaluation.« less

Multi-mode evaluation of power-maximizing cross-flow turbine controllers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forbush, Dominic; Cavagnaro, Robert J.; Donegan, James

A general method for predicting and evaluating the performance of three candidate cross-flow turbine power-maximizing controllers is presented in this paper using low-order dynamic simulation, scaled laboratory experiments, and full-scale field testing. For each testing mode and candidate controller, performance metrics quantifying energy capture (ability of a controller to maximize power), variation in torque and rotation rate (related to drive train fatigue), and variation in thrust loads (related to structural fatigue) are quantified for two purposes. First, for metrics that could be evaluated across all testing modes, we considered the accuracy with which simulation or laboratory experiments could predict performancemore » at full scale. Second, we explored the utility of these metrics to contrast candidate controller performance. For these turbines and set of candidate controllers, energy capture was found to only differentiate controller performance in simulation, while the other explored metrics were able to predict performance of the full-scale turbine in the field with various degrees of success. Finally, effects of scale between laboratory and full-scale testing are considered, along with recommendations for future improvements to dynamic simulations and controller evaluation.« less

Ideal cardiovascular health predicts lower risk of abnormal liver enzymes levels in the Chilean National Health Survey (2009–2010)

PubMed Central

Hackney, Anthony C.

2017-01-01

High levels of gamma glutamyltransferase (gamma-GT) and alanine aminotransferase (ALT), as well as fatty liver index (FLI) has been associated with higher cardiovascular disease risk factors in adults. The aim of this study was to examine the relationship between gamma-GT, ALT, and fatty liver index FLI levels across a gradient number of ideal cardiovascular health metrics in a representative sample of adults from the Chilean National Health Survey 2009–2010. Data from 1,023 men and 1,449 women (≥ 15 years) from the Chilean Health Survey 2009–2010 were analyzed. Ideal cardiovascular health was defined as meeting ideal levels of the following components: four behaviours (smoking, body mass index, physical activity and diet adherence) and three factors (total cholesterol, blood pressure and fasting glucose). Adults were grouped into three categories according to their number of ideal cardiovascular health metrics: ideal (5–7 metrics), intermediate (3–4 metrics), and poor (0–2 metrics). Blood levels of gamma-GT and ALT were measured and the FLI was calculated. A higher number of ideal cardiovascular health index metric was associated with lower gamma-GT, ALT and FLI (p from trend analysis <0.001). Also, adults meeting at least 3–4 metrics were predicted less likely to have prevalence of abnormal levels of gamma-GT and FLI (p<0.001) compared to adults who met only 0–2 metrics. These findings reinforce the usefulness of the ideal cardiovascular health metrics proposed by the American Heart Association as a tool to identify target subjects and promote cardiovascular health in South-American adults. PMID:29049384

Evaluation of image quality metrics for the prediction of subjective best focus.

PubMed

Kilintari, Marina; Pallikaris, Aristophanis; Tsiklis, Nikolaos; Ginis, Harilaos S

2010-03-01

Seven existing and three new image quality metrics were evaluated in terms of their effectiveness in predicting subjective cycloplegic refraction. Monochromatic wavefront aberrations (WA) were measured in 70 eyes using a Shack-Hartmann based device (Complete Ophthalmic Analysis System; Wavefront Sciences). Subjective cycloplegic spherocylindrical correction was obtained using a standard manifest refraction procedure. The dioptric amount required to optimize each metric was calculated and compared with the subjective refraction result. Metrics included monochromatic and polychromatic variants, as well as variants taking into consideration the Stiles and Crawford effect (SCE). WA measurements were performed using infrared light and converted to visible before all calculations. The mean difference between subjective cycloplegic and WA-derived spherical refraction ranged from 0.17 to 0.36 diopters (D), while paraxial curvature resulted in a difference of 0.68 D. Monochromatic metrics exhibited smaller mean differences between subjective cycloplegic and objective refraction. Consideration of the SCE reduced the standard deviation (SD) of the difference between subjective and objective refraction. All metrics exhibited similar performance in terms of accuracy and precision. We hypothesize that errors pertaining to the conversion between infrared and visible wavelengths rather than calculation method may be the limiting factor in determining objective best focus from near infrared WA measurements.

Metrics for assessing the performance of morphodynamic models of braided rivers at event and reach scales

NASA Astrophysics Data System (ADS)

Williams, Richard; Measures, Richard; Hicks, Murray; Brasington, James

2017-04-01

Advances in geomatics technologies have transformed the monitoring of reach-scale (100-101 km) river morphodynamics. Hyperscale Digital Elevation Models (DEMs) can now be acquired at temporal intervals that are commensurate with the frequencies of high-flow events that force morphological change. The low vertical errors associated with such DEMs enable DEMs of Difference (DoDs) to be generated to quantify patterns of erosion and deposition, and derive sediment budgets using the morphological approach. In parallel with reach-scale observational advances, high-resolution, two-dimensional, physics-based numerical morphodynamic models are now computationally feasible for unsteady, reach-scale simulations. In light of this observational and predictive progress, there is a need to identify appropriate metrics that can be extracted from DEMs and DoDs to assess model performance. Nowhere is this more pertinent than in braided river environments, where numerous mobile channels that intertwine around mid-channel bars result in complex patterns of erosion and deposition, thus making model assessment particularly challenging. This paper identifies and evaluates a range of morphological and morphological-change metrics that can be used to assess predictions of braided river morphodynamics at the timescale of single storm events. A depth-averaged, mixed-grainsize Delft3D morphodynamic model was used to simulate morphological change during four discrete high-flow events, ranging from 91 to 403 m3s-1, along a 2.5 x 0.7 km reach of the braided, gravel-bed Rees River, New Zealand. Pre- and post-event topographic surveys, using a fusion of Terrestrial Laser Scanning and optical-empirical bathymetric mapping, were used to produce 0.5 m resolution DEMs and DoDs. The pre- and post-event DEMs for a moderate (227m3s-1) high-flow event were used to calibrate the model. DEMs and DoDs from the other three high-flow events were used for model assessment using two approaches. First, "morphological" metrics were applied to compare observed and predicted post-event DEMs. These metrics include measures of confluence and bifurcation node density, bar shape, braiding intensity, and topographic comparisons using a form of the Brier Skill Score and cumulative frequency distributions of rugosity. Second, "morphological change" metrics were used to compare observed and predicted morphological change. These metrics included the extent of the morphologically active area, pairwise comparisons of morphological change (using kappa and fuzzy kappa statistics), and comparisons between vertical morphological change magnitude and elevation distribution. Results indicate that those metrics that assess characteristic features of braiding, rather than making direct comparisons, are most useful for assessing reach-scale braided river morphodynamic models. Together, the metrics indicate that there was a general affinity between observed and predicted braided river morphodynamics, both during small and large magnitude high-flow events. These results thus demonstrate how high-resolution, reach-scale, natural experiment datasets can be used to assess the efficacy of morphological models in predicting realistic patterns of erosion and deposition. This lays the foundation for the development and assessment of decadal scale morphodynamic models and their use in adaptive river basin management.

Spatial-temporal forecasting the sunspot diagram

NASA Astrophysics Data System (ADS)

Covas, Eurico

2017-09-01

Aims: We attempt to forecast the Sun's sunspot butterfly diagram in both space (I.e. in latitude) and time, instead of the usual one-dimensional time series forecasts prevalent in the scientific literature. Methods: We use a prediction method based on the non-linear embedding of data series in high dimensions. We use this method to forecast both in latitude (space) and in time, using a full spatial-temporal series of the sunspot diagram from 1874 to 2015. Results: The analysis of the results shows that it is indeed possible to reconstruct the overall shape and amplitude of the spatial-temporal pattern of sunspots, but that the method in its current form does not have real predictive power. We also apply a metric called structural similarity to compare the forecasted and the observed butterfly cycles, showing that this metric can be a useful addition to the usual root mean square error metric when analysing the efficiency of different prediction methods. Conclusions: We conclude that it is in principle possible to reconstruct the full sunspot butterfly diagram for at least one cycle using this approach and that this method and others should be explored since just looking at metrics such as sunspot count number or sunspot total area coverage is too reductive given the spatial-temporal dynamical complexity of the sunspot butterfly diagram. However, more data and/or an improved approach is probably necessary to have true predictive power.

Building a Metric

NASA Technical Reports Server (NTRS)

Spencer, Shakira

2007-01-01

Launch Services Program is a Kennedy Space Center based program whose job it is to undertake all the necessary roles required to successfully launch Expendable Launch Vehicles. This project was designed to help Launch Services Program accurately report how successful they have been at launching missions on time or +/- 2 days from the scheduled launch date and also if they weren't successful, why. This information will be displayed in the form of a metric, which answers these questions in a clear and accurate way.

Modeled hydrologic metrics show links between hydrology and the functional composition of stream assemblages.

PubMed

Patrick, Christopher J; Yuan, Lester L

2017-07-01

Flow alteration is widespread in streams, but current understanding of the effects of differences in flow characteristics on stream biological communities is incomplete. We tested hypotheses about the effect of variation in hydrology on stream communities by using generalized additive models to relate watershed information to the values of different flow metrics at gauged sites. Flow models accounted for 54-80% of the spatial variation in flow metric values among gauged sites. We then used these models to predict flow metrics in 842 ungauged stream sites in the mid-Atlantic United States that were sampled for fish, macroinvertebrates, and environmental covariates. Fish and macroinvertebrate assemblages were characterized in terms of a suite of metrics that quantified aspects of community composition, diversity, and functional traits that were expected to be associated with differences in flow characteristics. We related modeled flow metrics to biological metrics in a series of stressor-response models. Our analyses identified both drying and base flow instability as explaining 30-50% of the observed variability in fish and invertebrate community composition. Variations in community composition were related to variations in the prevalence of dispersal traits in invertebrates and trophic guilds in fish. The results demonstrate that we can use statistical models to predict hydrologic conditions at bioassessment sites, which, in turn, we can use to estimate relationships between flow conditions and biological characteristics. This analysis provides an approach to quantify the effects of spatial variation in flow metrics using readily available biomonitoring data. © 2017 by the Ecological Society of America.

Characterization of exposure in epidemiological studies on air pollution from biodegradable wastes: Misclassification and comparison of exposure assessment strategies.

PubMed

Cantuaria, Manuella Lech; Suh, Helen; Løfstrøm, Per; Blanes-Vidal, Victoria

2016-11-01

The assignment of exposure is one of the main challenges faced by environmental epidemiologists. However, misclassification of exposures has not been explored in population epidemiological studies on air pollution from biodegradable wastes. The objective of this study was to investigate the use of different approaches for assessing exposure to air pollution from biodegradable wastes by analyzing (1) the misclassification of exposure that is committed by using these surrogates, (2) the existence of differential misclassification (3) the effects that misclassification may have on health effect estimates and the interpretation of epidemiological results, and (4) the ability of the exposure measures to predict health outcomes using 10-fold cross validation. Four different exposure assessment approaches were studied: ammonia concentrations at the residence (Metric I), distance to the closest source (Metric II), number of sources within certain distances from the residence (Metric IIIa,b) and location in a specific region (Metric IV). Exposure-response models based on Metric I provided the highest predictive ability (72.3%) and goodness-of-fit, followed by IV, III and II. When compared to Metric I, Metric IV yielded the best results for exposure misclassification analysis and interpretation of health effect estimates, followed by Metric IIIb, IIIa and II. The study showed that modelled NH 3 concentrations provide more accurate estimations of true exposure than distances-based surrogates, and that distance-based surrogates (especially those based on distance to the closest point source) are imprecise methods to identify exposed populations, although they may be useful for initial studies. Copyright © 2016 Elsevier GmbH. All rights reserved.

Effects of metric change on safety in the workplace for selected occupations

NASA Astrophysics Data System (ADS)

Lefande, J. M.; Pokorney, J. L.

1982-04-01

The study assesses the potential safety issues of metric conversion in the workplace. A purposive sample of 35 occupations based on injury and illnesses indexes were assessed. After an analysis of workforce population, hazard analysis and measurement sensitivity of the occupations, jobs were analyzed to identify potential safety hazards by industrial hygienists, safety engineers and academia. The study's major findings were as follows: No metric hazard experience was identified. An increased exposure might occur when particular jobs and their job tasks are going the transition from customary measurement to metric measurement. Well planned metric change programs reduce hazard potential. Metric safety issues are unresolved in the aviation industry.

Synthesized view comparison method for no-reference 3D image quality assessment

NASA Astrophysics Data System (ADS)

Luo, Fangzhou; Lin, Chaoyi; Gu, Xiaodong; Ma, Xiaojun

2018-04-01

We develop a no-reference image quality assessment metric to evaluate the quality of synthesized view rendered from the Multi-view Video plus Depth (MVD) format. Our metric is named Synthesized View Comparison (SVC), which is designed for real-time quality monitoring at the receiver side in a 3D-TV system. The metric utilizes the virtual views in the middle which are warped from left and right views by Depth-image-based rendering algorithm (DIBR), and compares the difference between the virtual views rendered from different cameras by Structural SIMilarity (SSIM), a popular 2D full-reference image quality assessment metric. The experimental results indicate that our no-reference quality assessment metric for the synthesized images has competitive prediction performance compared with some classic full-reference image quality assessment metrics.

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2013-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography. These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC. Distribution Statement A: Approved for Public Release; distribution is unlimited

Verification of Meteorological and Oceanographic Ensemble Forecasts in the U.S. Navy

NASA Astrophysics Data System (ADS)

Klotz, S. P.; Hansen, J.; Pauley, P.; Sestak, M.; Wittmann, P.; Skupniewicz, C.; Nelson, G.

2012-12-01

The Navy Ensemble Forecast Verification System (NEFVS) has been promoted recently to operational status at the U.S. Navy's Fleet Numerical Meteorology and Oceanography Center (FNMOC). NEFVS processes FNMOC and National Centers for Environmental Prediction (NCEP) meteorological and ocean wave ensemble forecasts, gridded forecast analyses, and innovation (observational) data output by FNMOC's data assimilation system. The NEFVS framework consists of statistical analysis routines, a variety of pre- and post-processing scripts to manage data and plot verification metrics, and a master script to control application workflow. NEFVS computes metrics that include forecast bias, mean-squared error, conditional error, conditional rank probability score, and Brier score. The system also generates reliability and Receiver Operating Characteristic diagrams. In this presentation we describe the operational framework of NEFVS and show examples of verification products computed from ensemble forecasts, meteorological observations, and forecast analyses. The construction and deployment of NEFVS addresses important operational and scientific requirements within Navy Meteorology and Oceanography (METOC). These include computational capabilities for assessing the reliability and accuracy of meteorological and ocean wave forecasts in an operational environment, for quantifying effects of changes and potential improvements to the Navy's forecast models, and for comparing the skill of forecasts from different forecast systems. NEFVS also supports the Navy's collaboration with the U.S. Air Force, NCEP, and Environment Canada in the North American Ensemble Forecast System (NAEFS) project and with the Air Force and the National Oceanic and Atmospheric Administration (NOAA) in the National Unified Operational Prediction Capability (NUOPC) program. This program is tasked with eliminating unnecessary duplication within the three agencies, accelerating the transition of new technology, such as multi-model ensemble forecasting, to U.S. Department of Defense use, and creating a superior U.S. global meteorological and oceanographic prediction capability. Forecast verification is an important component of NAEFS and NUOPC.

Predictors of Student Productivity in Biomedical Graduate School Applications

PubMed Central

O’Connell, Anna B.; Cook, Jeanette G.

2017-01-01

Many US biomedical PhD programs receive more applications for admissions than they can accept each year, necessitating a selective admissions process. Typical selection criteria include standardized test scores, undergraduate grade point average, letters of recommendation, a resume and/or personal statement highlighting relevant research or professional experience, and feedback from interviews with training faculty. Admissions decisions are often founded on assumptions that these application components correlate with research success in graduate school, but these assumptions have not been rigorously tested. We sought to determine if any application components were predictive of student productivity measured by first-author student publications and time to degree completion. We collected productivity metrics for graduate students who entered the umbrella first-year biomedical PhD program at the University of North Carolina at Chapel Hill from 2008–2010 and analyzed components of their admissions applications. We found no correlations of test scores, grades, amount of previous research experience, or faculty interview ratings with high or low productivity among those applicants who were admitted and chose to matriculate at UNC. In contrast, ratings from recommendation letter writers were significantly stronger for students who published multiple first-author papers in graduate school than for those who published no first-author papers during the same timeframe. We conclude that the most commonly used standardized test (the general GRE) is a particularly ineffective predictive tool, but that qualitative assessments by previous mentors are more likely to identify students who will succeed in biomedical graduate research. Based on these results, we conclude that admissions committees should avoid over-reliance on any single component of the application and de-emphasize metrics that are minimally predictive of student productivity. We recommend continual tracking of desired training outcomes combined with retrospective analysis of admissions practices to guide both application requirements and holistic application review. PMID:28076439

Interferometric tests of Planckian quantum geometry models

DOE PAGES

Kwon, Ohkyung; Hogan, Craig J.

2016-04-19

The effect of Planck scale quantum geometrical effects on measurements with interferometers is estimated with standard physics, and with a variety of proposed extensions. It is shown that effects are negligible in standard field theory with canonically quantized gravity. Statistical noise levels are estimated in a variety of proposals for nonstandard metric fluctuations, and these alternatives are constrained using upper bounds on stochastic metric fluctuations from LIGO. Idealized models of several interferometer system architectures are used to predict signal noise spectra in a quantum geometry that cannot be described by a fluctuating metric, in which position noise arises from holographicmore » bounds on directional information. Lastly, predictions in this case are shown to be close to current and projected experimental bounds.« less

Measuring the Impact of Longitudinal Faculty Development: A Study of Academic Achievement.

PubMed

Newman, Lori R; Pelletier, Stephen R; Lown, Beth A

2016-12-01

Although faculty development programs in medical education have increased over the past two decades, there is a lack of rigorous program evaluation. The aim of this study was to determine quantifiable outcomes of Harvard Medical School's (HMS's) Fellowship in Medical Education and evaluate attainment of its goals. In 2005 and 2009 the authors collected curricula vitae (CVs) and conducted within-subject analysis of 42 fellowship graduates and also conducted comparison analysis between 12 academic year 2005 fellows and 12 faculty who did not participate in the program. The authors identified 10 metrics of academic advancement. CV analysis for the 42 graduates started 2 years prior to fellowship enrollment and continued for 2-year intervals until June 2009 (10 years of data collection). CV analysis for the comparison group was from 2003 to 2009. The authors also analyzed association between gender and academic outcomes. Fellowship graduates demonstrated significant changes in 4 of 10 academic metrics by the end of the fellowship year: academic promotion, educational leadership, education committees, and education funding. Two metrics-educational leadership and committees-showed increased outcomes two years post fellowship, with a positive trend for promotions. Fellowship graduates significantly outpaced the comparison group in 6 of 10 metrics. Women did significantly more committee work, secured more education funding, and were promoted more often than men. Findings indicate that the HMS Fellowship in Medical Education meets programmatic goals and produces positive, measurable academic outcomes. Standardized evaluation metrics of longitudinal faculty development programs would aid cross-institutional comparisons.

Performance metrics used by freight transport providers.

DOT National Transportation Integrated Search

2008-09-30

The newly-established National Cooperative Freight Research Program (NCFRP) has allocated $300,000 in funding to a project entitled Performance Metrics for Freight Transportation (NCFRP 03). The project is scheduled for completion in September ...

Wafer hot spot identification through advanced photomask characterization techniques: part 2

NASA Astrophysics Data System (ADS)

Choi, Yohan; Green, Michael; Cho, Young; Ham, Young; Lin, Howard; Lan, Andy; Yang, Richer; Lung, Mike

2017-03-01

Historically, 1D metrics such as Mean to Target (MTT) and CD Uniformity (CDU) have been adequate for mask end users to evaluate and predict the mask impact on the wafer process. However, the wafer lithographer's process margin is shrinking at advanced nodes to a point that classical mask CD metrics are no longer adequate to gauge the mask contribution to wafer process error. For example, wafer CDU error at advanced nodes is impacted by mask factors such as 3-dimensional (3D) effects and mask pattern fidelity on sub-resolution assist features (SRAFs) used in Optical Proximity Correction (OPC) models of ever-increasing complexity. To overcome the limitation of 1D metrics, there are numerous on-going industry efforts to better define wafer-predictive metrics through both standard mask metrology and aerial CD methods. Even with these improvements, the industry continues to struggle to define useful correlative metrics that link the mask to final device performance. In part 1 of this work, we utilized advanced mask pattern characterization techniques to extract potential hot spots on the mask and link them, theoretically, to issues with final wafer performance. In this paper, part 2, we complete the work by verifying these techniques at wafer level. The test vehicle (TV) that was used for hot spot detection on the mask in part 1 will be used to expose wafers. The results will be used to verify the mask-level predictions. Finally, wafer performance with predicted and verified mask/wafer condition will be shown as the result of advanced mask characterization. The goal is to maximize mask end user yield through mask-wafer technology harmonization. This harmonization will provide the necessary feedback to determine optimum design, mask specifications, and mask-making conditions for optimal wafer process margin.

Predicting streamflow regime metrics for ungauged streamsin Colorado, Washington, and Oregon

NASA Astrophysics Data System (ADS)

Sanborn, Stephen C.; Bledsoe, Brian P.

2006-06-01

Streamflow prediction in ungauged basins provides essential information for water resources planning and management and ecohydrological studies yet remains a fundamental challenge to the hydrological sciences. A methodology is presented for stratifying streamflow regimes of gauged locations, classifying the regimes of ungauged streams, and developing models for predicting a suite of ecologically pertinent streamflow metrics for these streams. Eighty-four streamflow metrics characterizing various flow regime attributes were computed along with physical and climatic drainage basin characteristics for 150 streams with little or no streamflow modification in Colorado, Washington, and Oregon. The diverse hydroclimatology of the study area necessitates flow regime stratification and geographically independent clusters were identified and used to develop separate predictive models for each flow regime type. Multiple regression models for flow magnitude, timing, and rate of change metrics were quite accurate with many adjusted R2 values exceeding 0.80, while models describing streamflow variability did not perform as well. Separate stratification schemes for high, low, and average flows did not considerably improve models for metrics describing those particular aspects of the regime over a scheme based on the entire flow regime. Models for streams identified as 'snowmelt' type were improved if sites in Colorado and the Pacific Northwest were separated to better stratify the processes driving streamflow in these regions thus revealing limitations of geographically independent streamflow clusters. This study demonstrates that a broad suite of ecologically relevant streamflow characteristics can be accurately modeled across large heterogeneous regions using this framework. Applications of the resulting models include stratifying biomonitoring sites and quantifying linkages between specific aspects of flow regimes and aquatic community structure. In particular, the results bode well for modeling ecological processes related to high-flow magnitude, timing, and rate of change such as the recruitment of fish and riparian vegetation across large regions.

First results from a combined analysis of CERN computing infrastructure metrics

NASA Astrophysics Data System (ADS)

Duellmann, Dirk; Nieke, Christian

2017-10-01

The IT Analysis Working Group (AWG) has been formed at CERN across individual computing units and the experiments to attempt a cross cutting analysis of computing infrastructure and application metrics. In this presentation we will describe the first results obtained using medium/long term data (1 months — 1 year) correlating box level metrics, job level metrics from LSF and HTCondor, IO metrics from the physics analysis disk pools (EOS) and networking and application level metrics from the experiment dashboards. We will cover in particular the measurement of hardware performance and prediction of job duration, the latency sensitivity of different job types and a search for bottlenecks with the production job mix in the current infrastructure. The presentation will conclude with the proposal of a small set of metrics to simplify drawing conclusions also in the more constrained environment of public cloud deployments.

Lexical Predictability During Natural Reading: Effects of Surprisal and Entropy Reduction.

PubMed

Lowder, Matthew W; Choi, Wonil; Ferreira, Fernanda; Henderson, John M

2018-06-01

What are the effects of word-by-word predictability on sentence processing times during the natural reading of a text? Although information complexity metrics such as surprisal and entropy reduction have been useful in addressing this question, these metrics tend to be estimated using computational language models, which require some degree of commitment to a particular theory of language processing. Taking a different approach, this study implemented a large-scale cumulative cloze task to collect word-by-word predictability data for 40 passages and compute surprisal and entropy reduction values in a theory-neutral manner. A separate group of participants read the same texts while their eye movements were recorded. Results showed that increases in surprisal and entropy reduction were both associated with increases in reading times. Furthermore, these effects did not depend on the global difficulty of the text. The findings suggest that surprisal and entropy reduction independently contribute to variation in reading times, as these metrics seem to capture different aspects of lexical predictability. Copyright © 2018 Cognitive Science Society, Inc.

Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction.

PubMed

Xu, Yonghui; Min, Huaqing; Wu, Qingyao; Song, Hengjie; Ye, Bicui

2017-02-06

Multi-Instance (MI) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with multiple instances. Many studies in this literature attempted to find an appropriate Multi-Instance Learning (MIL) method for genome-wide protein function prediction under a usual assumption, the underlying distribution from testing data (target domain, i.e., TD) is the same as that from training data (source domain, i.e., SD). However, this assumption may be violated in real practice. To tackle this problem, in this paper, we propose a Multi-Instance Metric Transfer Learning (MIMTL) approach for genome-wide protein function prediction. In MIMTL, we first transfer the source domain distribution to the target domain distribution by utilizing the bag weights. Then, we construct a distance metric learning method with the reweighted bags. At last, we develop an alternative optimization scheme for MIMTL. Comprehensive experimental evidence on seven real-world organisms verifies the effectiveness and efficiency of the proposed MIMTL approach over several state-of-the-art methods.

Development of new VOC exposure metrics and their relationship to ''Sick Building Syndrome'' symptoms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ten Brinke, JoAnn

1995-08-01

Volatile organic compounds (VOCs) are suspected to contribute significantly to ''Sick Building Syndrome'' (SBS), a complex of subchronic symptoms that occurs during and in general decreases away from occupancy of the building in question. A new approach takes into account individual VOC potencies, as well as the highly correlated nature of the complex VOC mixtures found indoors. The new VOC metrics are statistically significant predictors of symptom outcomes from the California Healthy Buildings Study data. Multivariate logistic regression analyses were used to test the hypothesis that a summary measure of the VOC mixture, other risk factors, and covariates for eachmore » worker will lead to better prediction of symptom outcome. VOC metrics based on animal irritancy measures and principal component analysis had the most influence in the prediction of eye, dermal, and nasal symptoms. After adjustment, a water-based paints and solvents source was found to be associated with dermal and eye irritation. The more typical VOC exposure metrics used in prior analyses were not useful in symptom prediction in the adjusted model (total VOC (TVOC), or sum of individually identified VOCs (ΣVOC i)). Also not useful were three other VOC metrics that took into account potency, but did not adjust for the highly correlated nature of the data set, or the presence of VOCs that were not measured. High TVOC values (2--7 mg m -3) due to the presence of liquid-process photocopiers observed in several study spaces significantly influenced symptoms. Analyses without the high TVOC values reduced, but did not eliminate the ability of the VOC exposure metric based on irritancy and principal component analysis to explain symptom outcome.« less

Serial MR diffusion to predict treatment response in high-grade pediatric brain tumors: a comparison of regional and voxel-based diffusion change metrics

PubMed Central

Rodriguez Gutierrez, Daniel; Manita, Muftah; Jaspan, Tim; Dineen, Robert A.; Grundy, Richard G.; Auer, Dorothee P.

2013-01-01

Background Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response. Methods Eighteen patients (age range, 1.9–20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1–16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM). Results Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η2 = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis. Conclusions We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols. PMID:23585630

Here's the Answer. Was There a Question? Avoiding the Top 10 Metrics Mistakes

ERIC Educational Resources Information Center

Vaillancourt, Allison

2007-01-01

It's no secret that all organizations wish to better themselves, and the best way to do so is to measure past successes and failures and apply these measurements to the future. In higher education, this means creating a metrics strategy that addresses the particular needs of your institution. There is no "one-size-fits-all" metrics program, but…

Temporal Variability of Daily Personal Magnetic Field Exposure Metrics in Pregnant Women

PubMed Central

Lewis, Ryan C.; Evenson, Kelly R.; Savitz, David A.; Meeker, John D.

2015-01-01

Recent epidemiology studies of power-frequency magnetic fields and reproductive health have characterized exposures using data collected from personal exposure monitors over a single day, possibly resulting in exposure misclassification due to temporal variability in daily personal magnetic field exposure metrics, but relevant data in adults are limited. We assessed the temporal variability of daily central tendency (time-weighted average, median) and peak (upper percentiles, maximum) personal magnetic field exposure metrics over seven consecutive days in 100 pregnant women. When exposure was modeled as a continuous variable, central tendency metrics had substantial reliability, whereas peak metrics had fair (maximum) to moderate (upper percentiles) reliability. The predictive ability of a single day metric to accurately classify participants into exposure categories based on a weeklong metric depended on the selected exposure threshold, with sensitivity decreasing with increasing exposure threshold. Consistent with the continuous measures analysis, sensitivity was higher for central tendency metrics than for peak metrics. If there is interest in peak metrics, more than one day of measurement is needed over the window of disease susceptibility to minimize measurement error, but one day may be sufficient for central tendency metrics. PMID:24691007

Metrics for the National SCADA Test Bed Program

DOE Office of Scientific and Technical Information (OSTI.GOV)

Craig, Philip A.; Mortensen, J.; Dagle, Jeffery E.

2008-12-05

The U.S. Department of Energy Office of Electricity Delivery and Energy Reliability (DOE-OE) National SCADA Test Bed (NSTB) Program is providing valuable inputs into the electric industry by performing topical research and development (R&D) to secure next generation and legacy control systems. In addition, the program conducts vulnerability and risk analysis, develops tools, and performs industry liaison, outreach and awareness activities. These activities will enhance the secure and reliable delivery of energy for the United States. This report will describe metrics that could be utilized to provide feedback to help enhance the effectiveness of the NSTB Program.

Analytical approaches used in stream benthic macroinvertebrate biomonitoring programs of State agencies in the United States

USGS Publications Warehouse

Carter, James L.; Resh, Vincent H.

2013-01-01

Biomonitoring programs based on benthic macroinvertebrates are well-established worldwide. Their value, however, depends on the appropriateness of the analytical techniques used. All United States State, benthic macroinvertebrate biomonitoring programs were surveyed regarding the purposes of their programs, quality-assurance and quality-control procedures used, habitat and water-chemistry data collected, treatment of macroinvertebrate data prior to analysis, statistical methods used, and data-storage considerations. State regulatory mandates (59 percent of programs), biotic index development (17 percent), and Federal requirements (15 percent) were the most frequently reported purposes of State programs, with the specific tasks of satisfying the requirements for 305b/303d reports (89 percent), establishment and monitoring of total maximum daily loads, and developing biocriteria being the purposes most often mentioned. Most states establish reference sites (81 percent), but classify them using State-specific methods. The most often used technique for determining the appropriateness of a reference site was Best Professional Judgment (86 percent of these states). Macroinvertebrate samples are almost always collected by using a D-frame net, and duplicate samples are collected from approximately 10 percent of sites for quality assurance and quality control purposes. Most programs have macroinvertebrate samples processed by contractors (53 percent) and have identifications confirmed by a second taxonomist (85 percent). All States collect habitat data, with most using the Rapid Bioassessment Protocol visual-assessment approach, which requires ~1 h/site. Dissolved oxygen, pH, and conductivity are measured in more than 90 percent of programs. Wide variation exists in which taxa are excluded from analyses and the level of taxonomic resolution used. Species traits, such as functional feeding groups, are commonly used (96 percent), as are tolerance values for organic pollution (87 percent). Less often used are tolerance values for metals (28 percent). Benthic data are infrequently modified (34 percent) prior to analysis. Fixed-count subsampling is used widely (83 percent), with the number of organisms sorted ranging from 100 to 600 specimens. Most programs include a step during sample processing to acquire rare taxa (79 percent). Programs calculate from 2 to more than100 different metrics (mean 20), and most formulate a multimetric index (87 percent). Eleven of the 112 metrics reported represent 50 percent of all metrics considered to be useful, and most of these are based on richness or percent composition. Biotic indices and tolerance metrics are most oftenused in the eastern U.S., and functional and habitat-type metrics are most often used in the western U.S. Sixty-nine percent of programs analyze their data in-house, typically performing correlations and regressions, and few use any form of data transformation (34 percent). Fifty-one percent of the programs use multivariate analyses, typically non-metric multi-dimensional scaling. All programs have electronic data storage. Most programs use the Integrated Taxonomic Information System (75 percent) for nomenclature and to update historical data (78 percent). State procedures represent a diversity of biomonitoring approaches which likely compromises comparability among programs. A national-state consensus is needed for: (1) developing methods for the identification of reference conditions and reference sites, (2) standardization in determining and reporting species richness, (3) testing and documenting both the theoretical and mechanistic basis of often-used metrics, (4) development of properly replicated point-source study designs, and (5) curation of benthic macroinvertebrate data, including reference and voucher collections, for successful evaluation of future environmental changes.

Alternatives to accuracy and bias metrics based on percentage errors for radiation belt modeling applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morley, Steven Karl

This report reviews existing literature describing forecast accuracy metrics, concentrating on those based on relative errors and percentage errors. We then review how the most common of these metrics, the mean absolute percentage error (MAPE), has been applied in recent radiation belt modeling literature. Finally, we describe metrics based on the ratios of predicted to observed values (the accuracy ratio) that address the drawbacks inherent in using MAPE. Specifically, we define and recommend the median log accuracy ratio as a measure of bias and the median symmetric accuracy as a measure of accuracy.

The virial theorem and the dark matter problem in hybrid metric-Palatini gravity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Capozziello, Salvatore; Harko, Tiberiu; Koivisto, Tomi S.

2013-07-01

Hybrid metric-Palatini gravity is a recently proposed theory, consisting of the superposition of the metric Einstein-Hilbert Lagrangian with an f(R) term constructed à la Palatini. The theory predicts the existence of a long-range scalar field, which passes the Solar System observational constraints, even if the scalar field is very light, and modifies the cosmological and galactic dynamics. Thus, the theory opens new possibilities to approach, in the same theoretical framework, the problems of both dark energy and dark matter. In this work, we consider the generalized virial theorem in the scalar-tensor representation of the hybrid metric-Palatini gravity. More specifically, takingmore » into account the relativistic collisionless Boltzmann equation, we show that the supplementary geometric terms in the gravitational field equations provide an effective contribution to the gravitational potential energy. We show that the total virial mass is proportional to the effective mass associated with the new terms generated by the effective scalar field, and the baryonic mass. In addition to this, we also consider astrophysical applications of the model and show that the model predicts that the mass associated to the scalar field and its effects extend beyond the virial radius of the clusters of galaxies. In the context of the galaxy cluster velocity dispersion profiles predicted by the hybrid metric-Palatini model, the generalized virial theorem can be an efficient tool in observationally testing the viability of this class of generalized gravity models.« less

Diagnosing Undersampling in Monte Carlo Eigenvalue and Flux Tally Estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perfetti, Christopher M; Rearden, Bradley T

2015-01-01

This study explored the impact of undersampling on the accuracy of tally estimates in Monte Carlo (MC) calculations. Steady-state MC simulations were performed for models of several critical systems with varying degrees of spatial and isotopic complexity, and the impact of undersampling on eigenvalue and fuel pin flux/fission estimates was examined. This study observed biases in MC eigenvalue estimates as large as several percent and biases in fuel pin flux/fission tally estimates that exceeded tens, and in some cases hundreds, of percent. This study also investigated five statistical metrics for predicting the occurrence of undersampling biases in MC simulations. Threemore » of the metrics (the Heidelberger-Welch RHW, the Geweke Z-Score, and the Gelman-Rubin diagnostics) are commonly used for diagnosing the convergence of Markov chains, and two of the methods (the Contributing Particles per Generation and Tally Entropy) are new convergence metrics developed in the course of this study. These metrics were implemented in the KENO MC code within the SCALE code system and were evaluated for their reliability at predicting the onset and magnitude of undersampling biases in MC eigenvalue and flux tally estimates in two of the critical models. Of the five methods investigated, the Heidelberger-Welch RHW, the Gelman-Rubin diagnostics, and Tally Entropy produced test metrics that correlated strongly to the size of the observed undersampling biases, indicating their potential to effectively predict the size and prevalence of undersampling biases in MC simulations.« less

JPEG2000 still image coding quality.

PubMed

Chen, Tzong-Jer; Lin, Sheng-Chieh; Lin, You-Chen; Cheng, Ren-Gui; Lin, Li-Hui; Wu, Wei

2013-10-01

This work demonstrates the image qualities between two popular JPEG2000 programs. Two medical image compression algorithms are both coded using JPEG2000, but they are different regarding the interface, convenience, speed of computation, and their characteristic options influenced by the encoder, quantization, tiling, etc. The differences in image quality and compression ratio are also affected by the modality and compression algorithm implementation. Do they provide the same quality? The qualities of compressed medical images from two image compression programs named Apollo and JJ2000 were evaluated extensively using objective metrics. These algorithms were applied to three medical image modalities at various compression ratios ranging from 10:1 to 100:1. Following that, the quality of the reconstructed images was evaluated using five objective metrics. The Spearman rank correlation coefficients were measured under every metric in the two programs. We found that JJ2000 and Apollo exhibited indistinguishable image quality for all images evaluated using the above five metrics (r > 0.98, p < 0.001). It can be concluded that the image quality of the JJ2000 and Apollo algorithms is statistically equivalent for medical image compression.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Angers, Crystal Plume; Bottema, Ryan; Buckley, Les

Purpose: Treatment unit uptime statistics are typically used to monitor radiation equipment performance. The Ottawa Hospital Cancer Centre has introduced the use of Quality Control (QC) test success as a quality indicator for equipment performance and overall health of the equipment QC program. Methods: Implemented in 2012, QATrack+ is used to record and monitor over 1100 routine machine QC tests each month for 20 treatment and imaging units ( http://qatrackplus.com/ ). Using an SQL (structured query language) script, automated queries of the QATrack+ database are used to generate program metrics such as the number of QC tests executed and themore » percentage of tests passing, at tolerance or at action. These metrics are compared against machine uptime statistics already reported within the program. Results: Program metrics for 2015 show good correlation between pass rate of QC tests and uptime for a given machine. For the nine conventional linacs, the QC test success rate was consistently greater than 97%. The corresponding uptimes for these units are better than 98%. Machines that consistently show higher failure or tolerance rates in the QC tests have lower uptimes. This points to either poor machine performance requiring corrective action or to problems with the QC program. Conclusions: QATrack+ significantly improves the organization of QC data but can also aid in overall equipment management. Complimenting machine uptime statistics with QC test metrics provides a more complete picture of overall machine performance and can be used to identify areas of improvement in the machine service and QC programs.« less

Modeling Air Pollution Exposure Metrics for the Diabetes and Environment Panel Study (DEPS)

EPA Science Inventory

Air pollution health studies of fine particulate matter (PM) often use outdoor concentrations as exposure surrogates. To improve exposure assessments, we developed and evaluated an exposure model for individuals (EMI), which predicts five tiers of individual-level exposure metric...

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Owen, D; Anderson, C; Mayo, C

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinFormsmore » to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.« less

Analysis of Skeletal Muscle Metrics as Predictors of Functional Task Performance

NASA Technical Reports Server (NTRS)

Ryder, Jeffrey W.; Buxton, Roxanne E.; Redd, Elizabeth; Scott-Pandorf, Melissa; Hackney, Kyle J.; Fiedler, James; Ploutz-Snyder, Robert J.; Bloomberg, Jacob J.; Ploutz-Snyder, Lori L.

2010-01-01

PURPOSE: The ability to predict task performance using physiological performance metrics is vital to ensure that astronauts can execute their jobs safely and effectively. This investigation used a weighted suit to evaluate task performance at various ratios of strength, power, and endurance to body weight. METHODS: Twenty subjects completed muscle performance tests and functional tasks representative of those that would be required of astronauts during planetary exploration (see table for specific tests/tasks). Subjects performed functional tasks while wearing a weighted suit with additional loads ranging from 0-120% of initial body weight. Performance metrics were time to completion for all tasks except hatch opening, which consisted of total work. Task performance metrics were plotted against muscle metrics normalized to "body weight" (subject weight + external load; BW) for each trial. Fractional polynomial regression was used to model the relationship between muscle and task performance. CONCLUSION: LPMIF/BW is the best predictor of performance for predominantly lower-body tasks that are ambulatory and of short duration. LPMIF/BW is a very practical predictor of occupational task performance as it is quick and relatively safe to perform. Accordingly, bench press work best predicts hatch-opening work performance.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction.

PubMed

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-06-15

Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence-structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM-HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods. Our program is freely available for download from http://sfb.kaust.edu.sa/Pages/Software.aspx : xin.gao@kaust.edu.sa Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Overview of Mars Technology Program

NASA Technical Reports Server (NTRS)

Hayati, Samad A.

2006-01-01

This viewgraph presentation reviews the development of a technology program leading to Mars missions. The presentation includes: the goals of technology program, elements of technology program, program metrics, major accomplishments, examples and Information about the Mars Technology Program.

Developing the Translational Research Workforce: A Pilot Study of Common Metrics for Evaluating the Clinical and Translational Award KL2 Program

PubMed Central

Guerrero, Lourdes; Jones, Lisa B.; Tong, Greg; Ireland, Christine; Dumbauld, Jill; Rainwater, Julie

2015-01-01

Abstract Purpose This pilot study describes the career development programs (i.e., NIH KL2 awards) across five Clinical and Translational Science Award (CTSA) institutions within the University of California (UC) system, and examines the feasibility of a set of common metrics for evaluating early outcomes. Methods A survey of program administrators provided data related to the institutional environment within which each KL2 program was implemented. Application and progress report data yielded a combined data set that characterized KL2 awardees, their initial productivity, and early career outcomes. Results The pilot project demonstrated the feasibility of aggregating common metrics data across multiple institutions. The data indicated that KL2 awardees were an accomplished set of investigators, both before and after the award period, representing a wide variety of disciplines. Awardees that had completed their trainee period overwhelmingly remained active in translational research conducted within an academic setting. Early indications also suggest high rates of success with obtaining research funding subsequent to the KL2 award. Conclusion This project offers a model for how to collect and analyze common metrics related to the education and training function of the CTSA Consortium. Next steps call for expanding participation to other CTSA sites outside of the University of California system. PMID:26602332

Topographic metric predictions of soil organic carbon in Iowa fields

USDA-ARS?s Scientific Manuscript database

Topography is one of the key factors affecting soil organic carbon (SOC) redistribution (erosion or deposition) because it influences the gravity-driven movement of soil by water flow and tillage operations. In this study, we examined impacts of sixteen topographic metrics derived from Light Detecti...

Entropies of negative incomes, Pareto-distributed loss, and financial crises.

PubMed

Gao, Jianbo; Hu, Jing; Mao, Xiang; Zhou, Mi; Gurbaxani, Brian; Lin, Johnny

2011-01-01

Health monitoring of world economy is an important issue, especially in a time of profound economic difficulty world-wide. The most important aspect of health monitoring is to accurately predict economic downturns. To gain insights into how economic crises develop, we present two metrics, positive and negative income entropy and distribution analysis, to analyze the collective "spatial" and temporal dynamics of companies in nine sectors of the world economy over a 19 year period from 1990-2008. These metrics provide accurate predictive skill with a very low false-positive rate in predicting downturns. The new metrics also provide evidence of phase transition-like behavior prior to the onset of recessions. Such a transition occurs when negative pretax incomes prior to or during economic recessions transition from a thin-tailed exponential distribution to the higher entropy Pareto distribution, and develop even heavier tails than those of the positive pretax incomes. These features propagate from the crisis initiating sector of the economy to other sectors.

Can rodents conceive hyperbolic spaces?

PubMed Central

Urdapilleta, Eugenio; Troiani, Francesca; Stella, Federico; Treves, Alessandro

2015-01-01

The grid cells discovered in the rodent medial entorhinal cortex have been proposed to provide a metric for Euclidean space, possibly even hardwired in the embryo. Yet, one class of models describing the formation of grid unit selectivity is entirely based on developmental self-organization, and as such it predicts that the metric it expresses should reflect the environment to which the animal has adapted. We show that, according to self-organizing models, if raised in a non-Euclidean hyperbolic cage rats should be able to form hyperbolic grids. For a given range of grid spacing relative to the radius of negative curvature of the hyperbolic surface, such grids are predicted to appear as multi-peaked firing maps, in which each peak has seven neighbours instead of the Euclidean six, a prediction that can be tested in experiments. We thus demonstrate that a useful universal neuronal metric, in the sense of a multi-scale ruler and compass that remain unaltered when changing environments, can be extended to other than the standard Euclidean plane. PMID:25948611

A no-reference image and video visual quality metric based on machine learning

NASA Astrophysics Data System (ADS)

Frantc, Vladimir; Voronin, Viacheslav; Semenishchev, Evgenii; Minkin, Maxim; Delov, Aliy

2018-04-01

The paper presents a novel visual quality metric for lossy compressed video quality assessment. High degree of correlation with subjective estimations of quality is due to using of a convolutional neural network trained on a large amount of pairs video sequence-subjective quality score. We demonstrate how our predicted no-reference quality metric correlates with qualitative opinion in a human observer study. Results are shown on the EVVQ dataset with comparison existing approaches.

Optimization of Regression Models of Experimental Data Using Confirmation Points

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2010-01-01

A new search metric is discussed that may be used to better assess the predictive capability of different math term combinations during the optimization of a regression model of experimental data. The new search metric can be determined for each tested math term combination if the given experimental data set is split into two subsets. The first subset consists of data points that are only used to determine the coefficients of the regression model. The second subset consists of confirmation points that are exclusively used to test the regression model. The new search metric value is assigned after comparing two values that describe the quality of the fit of each subset. The first value is the standard deviation of the PRESS residuals of the data points. The second value is the standard deviation of the response residuals of the confirmation points. The greater of the two values is used as the new search metric value. This choice guarantees that both standard deviations are always less or equal to the value that is used during the optimization. Experimental data from the calibration of a wind tunnel strain-gage balance is used to illustrate the application of the new search metric. The new search metric ultimately generates an optimized regression model that was already tested at regression model independent confirmation points before it is ever used to predict an unknown response from a set of regressors.

The proposed 'concordance-statistic for benefit' provided a useful metric when modeling heterogeneous treatment effects.

PubMed

van Klaveren, David; Steyerberg, Ewout W; Serruys, Patrick W; Kent, David M

2018-02-01

Clinical prediction models that support treatment decisions are usually evaluated for their ability to predict the risk of an outcome rather than treatment benefit-the difference between outcome risk with vs. without therapy. We aimed to define performance metrics for a model's ability to predict treatment benefit. We analyzed data of the Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) trial and of three recombinant tissue plasminogen activator trials. We assessed alternative prediction models with a conventional risk concordance-statistic (c-statistic) and a novel c-statistic for benefit. We defined observed treatment benefit by the outcomes in pairs of patients matched on predicted benefit but discordant for treatment assignment. The 'c-for-benefit' represents the probability that from two randomly chosen matched patient pairs with unequal observed benefit, the pair with greater observed benefit also has a higher predicted benefit. Compared to a model without treatment interactions, the SYNTAX score II had improved ability to discriminate treatment benefit (c-for-benefit 0.590 vs. 0.552), despite having similar risk discrimination (c-statistic 0.725 vs. 0.719). However, for the simplified stroke-thrombolytic predictive instrument (TPI) vs. the original stroke-TPI, the c-for-benefit (0.584 vs. 0.578) was similar. The proposed methodology has the potential to measure a model's ability to predict treatment benefit not captured with conventional performance metrics. Copyright © 2017 Elsevier Inc. All rights reserved.

Phylogenetic structure of soil bacterial communities predicts ecosystem functioning.

PubMed

Pérez-Valera, Eduardo; Goberna, Marta; Verdú, Miguel

2015-05-01

Quantifying diversity with phylogeny-informed metrics helps understand the effects of diversity on ecosystem functioning (EF). The sign of these effects remains controversial because phylogenetic diversity and taxonomic identity may interactively influence EF. Positive relationships, traditionally attributed to complementarity effects, seem unimportant in natural soil bacterial communities. Negative relationships could be attributed to fitness differences leading to the overrepresentation of few productive clades, a mechanism recently invoked to assemble soil bacteria communities. We tested in two ecosystems contrasting in terms of environmental heterogeneity whether two metrics of phylogenetic community structure, a simpler measure of phylogenetic diversity (NRI) and a more complex metric incorporating taxonomic identity (PCPS), correctly predict microbially mediated EF. We show that the relationship between phylogenetic diversity and EF depends on the taxonomic identity of the main coexisting lineages. Phylogenetic diversity was negatively related to EF in soils where a marked fertility gradient exists and a single and productive clade (Proteobacteria) outcompete other clades in the most fertile plots. However, phylogenetic diversity was unrelated to EF in soils where the fertility gradient is less marked and Proteobacteria coexist with other abundant lineages. Including the taxonomic identity of bacterial lineages in metrics of phylogenetic community structure allows the prediction of EF in both ecosystems. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Vowel Acoustics in Dysarthria: Mapping to Perception

ERIC Educational Resources Information Center

Lansford, Kaitlin L.; Liss, Julie M.

2014-01-01

Purpose: The aim of the present report was to explore whether vowel metrics, demonstrated to distinguish dysarthric and healthy speech in a companion article (Lansford & Liss, 2014), are able to predict human perceptual performance. Method: Vowel metrics derived from vowels embedded in phrases produced by 45 speakers with dysarthria were…

Rotating metric in nonsingular infinite derivative theories of gravity

NASA Astrophysics Data System (ADS)

Cornell, Alan S.; Harmsen, Gerhard; Lambiase, Gaetano; Mazumdar, Anupam

2018-05-01

In this paper, we will provide a nonsingular rotating spacetime metric for a ghost-free infinite derivative theory of gravity in a linearized limit. We will provide the predictions for the Lense-Thirring effect for a slowly rotating system, and how it is compared with that from general relativity.

An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks

PubMed Central

Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

2014-01-01

We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches. PMID:25574490

An adaptive handover prediction scheme for seamless mobility based wireless networks.

PubMed

Sadiq, Ali Safa; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

2014-01-01

We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches.

Cochlea-scaled spectral entropy predicts rate-invariant intelligibility of temporally distorted sentences.

PubMed

Stilp, Christian E; Kiefte, Michael; Alexander, Joshua M; Kluender, Keith R

2010-10-01

Some evidence, mostly drawn from experiments using only a single moderate rate of speech, suggests that low-frequency amplitude modulations may be particularly important for intelligibility. Here, two experiments investigated intelligibility of temporally distorted sentences across a wide range of simulated speaking rates, and two metrics were used to predict results. Sentence intelligibility was assessed when successive segments of fixed duration were temporally reversed (exp. 1), and when sentences were processed through four third-octave-band filters, the outputs of which were desynchronized (exp. 2). For both experiments, intelligibility decreased with increasing distortion. However, in exp. 2, intelligibility recovered modestly with longer desynchronization. Across conditions, performances measured as a function of proportion of utterance distorted converged to a common function. Estimates of intelligibility derived from modulation transfer functions predict a substantial proportion of the variance in listeners' responses in exp. 1, but fail to predict performance in exp. 2. By contrast, a metric of potential information, quantified as relative dissimilarity (change) between successive cochlear-scaled spectra, is introduced. This metric reliably predicts listeners' intelligibility across the full range of speaking rates in both experiments. Results support an information-theoretic approach to speech perception and the significance of spectral change rather than physical units of time.

Proceedings of the 66th National Conference on Weights and Measures, 1981

NASA Astrophysics Data System (ADS)

Wollin, H. F.; Barbrow, L. E.; Heffernan, A. P.

1981-12-01

Major issues discussed included measurement science education, enforcement uniformly, national type approval, inch pound and metric labeling provisions, new design and performance requirements for weighing and measuring technology, metric conversion of retail gasoline dispensers, weights and measures program evaluation studies of model State laws and regulations and their adoption by citation or other means by State and local jurisdictions, and report of States conducting grain moisture meter testing programs.

Do Clinical Standards for Diabetes Care Address Excess Risk for Hypoglycemia in Vulnerable Patients? A Systematic Review

PubMed Central

Berkowitz, Seth A; Aragon, Katherine; Hines, Jonas; Seligman, Hilary; Lee, Sei; Sarkar, Urmimala

2013-01-01

Objective To determine whether diabetes clinical standards consider increased hypoglycemia risk in vulnerable patients. Data Sources MEDLINE, the National Guidelines Clearinghouse, the National Quality Measures Clearinghouse, and supplemental sources. Study Design Systematic review of clinical standards (guidelines, quality metrics, or pay-for-performance programs) for glycemic control in adult diabetes patients. The primary outcome was discussion of increased risk for hypoglycemia in vulnerable populations. Data Collection/Extraction Methods Manuscripts identified were abstracted by two independent reviewers using prespecified inclusion/exclusion criteria and a standardized abstraction form. Principal Findings We screened 1,166 titles, and reviewed 220 manuscripts in full text. Forty-four guidelines, 17 quality metrics, and 8 pay-for-performance programs were included. Five (11 percent) guidelines and no quality metrics or pay-for-performance programs met the primary outcome. Conclusions Clinical standards do not substantively incorporate evidence about increased risk for hypoglycemia in vulnerable populations. PMID:23445498

Do clinical standards for diabetes care address excess risk for hypoglycemia in vulnerable patients? A systematic review.

PubMed

Berkowitz, Seth A; Aragon, Katherine; Hines, Jonas; Seligman, Hilary; Lee, Sei; Sarkar, Urmimala

2013-08-01

To determine whether diabetes clinical standards consider increased hypoglycemia risk in vulnerable patients. MEDLINE, the National Guidelines Clearinghouse, the National Quality Measures Clearinghouse, and supplemental sources. Systematic review of clinical standards (guidelines, quality metrics, or pay-for-performance programs) for glycemic control in adult diabetes patients. The primary outcome was discussion of increased risk for hypoglycemia in vulnerable populations. Manuscripts identified were abstracted by two independent reviewers using prespecified inclusion/exclusion criteria and a standardized abstraction form. We screened 1,166 titles, and reviewed 220 manuscripts in full text. Forty-four guidelines, 17 quality metrics, and 8 pay-for-performance programs were included. Five (11 percent) guidelines and no quality metrics or pay-for-performance programs met the primary outcome. Clinical standards do not substantively incorporate evidence about increased risk for hypoglycemia in vulnerable populations. © Health Research and Educational Trust.

The X-windows interactive navigation data editor

NASA Technical Reports Server (NTRS)

Rinker, G. C.

1992-01-01

A new computer program called the X-Windows Interactive Data Editor (XIDE) was developed and demonstrated as a prototype application for editing radio metric data in the orbit-determination process. The program runs on a variety of workstations and employs pull-down menus and graphical displays, which allow users to easily inspect and edit radio metric data in the orbit data files received from the Deep Space Network (DSN). The XIDE program is based on the Open Software Foundation OSF/Motif Graphical User Interface (GUI) and has proven to be an efficient tool for editing radio metric data in the navigation operations environment. It was adopted by the Magellan Navigation Team as their primary data-editing tool. Because the software was designed from the beginning to be portable, the prototype was successfully moved to new workstation environments. It was also itegrated into the design of the next-generation software tool for DSN multimission navigation interactive launch support.

Data Based Prediction of Blood Glucose Concentrations Using Evolutionary Methods.

PubMed

Hidalgo, J Ignacio; Colmenar, J Manuel; Kronberger, Gabriel; Winkler, Stephan M; Garnica, Oscar; Lanchares, Juan

2017-08-08

Predicting glucose values on the basis of insulin and food intakes is a difficult task that people with diabetes need to do daily. This is necessary as it is important to maintain glucose levels at appropriate values to avoid not only short-term, but also long-term complications of the illness. Artificial intelligence in general and machine learning techniques in particular have already lead to promising results in modeling and predicting glucose concentrations. In this work, several machine learning techniques are used for the modeling and prediction of glucose concentrations using as inputs the values measured by a continuous monitoring glucose system as well as also previous and estimated future carbohydrate intakes and insulin injections. In particular, we use the following four techniques: genetic programming, random forests, k-nearest neighbors, and grammatical evolution. We propose two new enhanced modeling algorithms for glucose prediction, namely (i) a variant of grammatical evolution which uses an optimized grammar, and (ii) a variant of tree-based genetic programming which uses a three-compartment model for carbohydrate and insulin dynamics. The predictors were trained and tested using data of ten patients from a public hospital in Spain. We analyze our experimental results using the Clarke error grid metric and see that 90% of the forecasts are correct (i.e., Clarke error categories A and B), but still even the best methods produce 5 to 10% of serious errors (category D) and approximately 0.5% of very serious errors (category E). We also propose an enhanced genetic programming algorithm that incorporates a three-compartment model into symbolic regression models to create smoothed time series of the original carbohydrate and insulin time series.

Effects of Land Use Land Cover (LULC) and Climate on Simulation of Phosphorus loading in the Southeast United States Region

NASA Astrophysics Data System (ADS)

Jima, T. G.; Roberts, A.

2013-12-01

Quality of coastal and freshwater resources in the Southeastern United States is threatened due to Eutrophication as a result of excessive nutrients, and phosphorus is acknowledged as one of the major limiting nutrients. In areas with much non-point source (NPS) pollution, land use land cover and climate have been found to have significant impact on water quality. Landscape metrics applied in catchment and riparian stream based nutrient export models are known to significantly improve nutrient prediction. The regional SPARROW (Spatially Referenced Regression On Watershed attributes), which predicts Total Phosphorus has been developed by the Southeastern United States regions USGS, as part of the National Water Quality Assessment (NAWQA) program and the model accuracy was found to be 67%. However, landscape composition and configuration metrics which play a significant role in the source, transport and delivery of the nutrient have not been incorporated in the model. Including these matrices in the models parameterization will improve the models accuracy and improve decision making process for mitigating and managing NPS phosphorus in the region. The National Land Cover Data 2001 raster data will be used (since the base line is 2002) for the region (with 8321 watersheds ) with fragstats 4.1 and ArcGIS Desktop 10.1 for the analysis of landscape matrices, buffers and creating map layers. The result will be imported to the Southeast SPARROW model and will be analyzed. Resulting statistical significance and model accuracy will be assessed and predictions for those areas with no water quality monitoring station will be made.

Intensity attenuation for active crustal regions

NASA Astrophysics Data System (ADS)

Allen, Trevor I.; Wald, David J.; Worden, C. Bruce

2012-07-01

We develop globally applicable macroseismic intensity prediction equations (IPEs) for earthquakes of moment magnitude M W 5.0-7.9 and intensities of degree II and greater for distances less than 300 km for active crustal regions. The IPEs are developed for two distance metrics: closest distance to rupture ( R rup) and hypocentral distance ( R hyp). The key objective for developing the model based on hypocentral distance—in addition to more rigorous and standard measure R rup—is to provide an IPE which can be used in near real-time earthquake response systems for earthquakes anywhere in the world, where information regarding the rupture dimensions of a fault may not be known in the immediate aftermath of the event. We observe that our models, particularly the model for the R rup distance metric, generally have low median residuals with magnitude and distance. In particular, we address whether the direct use of IPEs leads to a reduction in overall uncertainties when compared with methods which use a combination of ground-motion prediction equations and ground motion to intensity conversion equations. Finally, using topographic gradient as a proxy and median model predictions, we derive intensity-based site amplification factors. These factors lead to a small reduction of residuals at shallow gradients at strong shaking levels. However, the overall effect on total median residuals is relatively small. This is in part due to the observation that the median site condition for intensity observations used to develop these IPEs is approximately near the National Earthquake Hazard Reduction Program CD site-class boundary.

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity.

PubMed

Swann, Abigail L S; Hoffman, Forrest M; Koven, Charles D; Randerson, James T

2016-09-06

Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.

Plant responses to increasing CO2 reduce estimates of climate impacts on drought severity

PubMed Central

Koven, Charles D.; Randerson, James T.

2016-01-01

Rising atmospheric CO2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area. This area drops to 37% with the use of precipitation minus evapotranspiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment. PMID:27573831

A comprehensive comparison of network similarities for link prediction and spurious link elimination

NASA Astrophysics Data System (ADS)

Zhang, Peng; Qiu, Dan; Zeng, An; Xiao, Jinghua

2018-06-01

Identifying missing interactions in complex networks, known as link prediction, is realized by estimating the likelihood of the existence of a link between two nodes according to the observed links and nodes' attributes. Similar approaches have also been employed to identify and remove spurious links in networks which is crucial for improving the reliability of network data. In network science, the likelihood for two nodes having a connection strongly depends on their structural similarity. The key to address these two problems thus becomes how to objectively measure the similarity between nodes in networks. In the literature, numerous network similarity metrics have been proposed and their accuracy has been discussed independently in previous works. In this paper, we systematically compare the accuracy of 18 similarity metrics in both link prediction and spurious link elimination when the observed networks are very sparse or consist of inaccurate linking information. Interestingly, some methods have high prediction accuracy, they tend to perform low accuracy in identification spurious interaction. We further find that methods can be classified into several cluster according to their behaviors. This work is useful for guiding future use of these similarity metrics for different purposes.

User's manual for the National Water-Quality Assessment Program Invertebrate Data Analysis System (IDAS) software, version 5

USGS Publications Warehouse

Cuffney, Thomas F.; Brightbill, Robin A.

2011-01-01

The Invertebrate Data Analysis System (IDAS) software was developed to provide an accurate, consistent, and efficient mechanism for analyzing invertebrate data collected as part of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program. The IDAS software is a stand-alone program for personal computers that run Microsoft Windows(Registered). It allows users to read data downloaded from the NAWQA Program Biological Transactional Database (Bio-TDB) or to import data from other sources either as Microsoft Excel(Registered) or Microsoft Access(Registered) files. The program consists of five modules: Edit Data, Data Preparation, Calculate Community Metrics, Calculate Diversities and Similarities, and Data Export. The Edit Data module allows the user to subset data on the basis of taxonomy or sample type, extract a random subsample of data, combine or delete data, summarize distributions, resolve ambiguous taxa (see glossary) and conditional/provisional taxa, import non-NAWQA data, and maintain and create files of invertebrate attributes that are used in the calculation of invertebrate metrics. The Data Preparation module allows the user to select the type(s) of sample(s) to process, calculate densities, delete taxa on the basis of laboratory processing notes, delete pupae or terrestrial adults, combine lifestages or keep them separate, select a lowest taxonomic level for analysis, delete rare taxa on the basis of the number of sites where a taxon occurs and (or) the abundance of a taxon in a sample, and resolve taxonomic ambiguities by one of four methods. The Calculate Community Metrics module allows the user to calculate 184 community metrics, including metrics based on organism tolerances, functional feeding groups, and behavior. The Calculate Diversities and Similarities module allows the user to calculate nine diversity and eight similarity indices. The Data Export module allows the user to export data to other software packages (CANOCO, Primer, PC-ORD, MVSP) and produce tables of community data that can be imported into spreadsheet, database, graphics, statistics, and word-processing programs. The IDAS program facilitates the documentation of analyses by keeping a log of the data that are processed, the files that are generated, and the program settings used to process the data. Though the IDAS program was developed to process NAWQA Program invertebrate data downloaded from Bio-TDB, the Edit Data module includes tools that can be used to convert non-NAWQA data into Bio-TDB format. Consequently, the data manipulation, analysis, and export procedures provided by the IDAS program can be used to process data generated outside of the NAWQA Program.

A content-boosted collaborative filtering algorithm for personalized training in interpretation of radiological imaging.

PubMed

Lin, Hongli; Yang, Xuedong; Wang, Weisheng

2014-08-01

Devising a method that can select cases based on the performance levels of trainees and the characteristics of cases is essential for developing a personalized training program in radiology education. In this paper, we propose a novel hybrid prediction algorithm called content-boosted collaborative filtering (CBCF) to predict the difficulty level of each case for each trainee. The CBCF utilizes a content-based filtering (CBF) method to enhance existing trainee-case ratings data and then provides final predictions through a collaborative filtering (CF) algorithm. The CBCF algorithm incorporates the advantages of both CBF and CF, while not inheriting the disadvantages of either. The CBCF method is compared with the pure CBF and pure CF approaches using three datasets. The experimental data are then evaluated in terms of the MAE metric. Our experimental results show that the CBCF outperforms the pure CBF and CF methods by 13.33 and 12.17 %, respectively, in terms of prediction precision. This also suggests that the CBCF can be used in the development of personalized training systems in radiology education.

A Contrast in Use of Metrics in Earth Science Data Systems

NASA Technical Reports Server (NTRS)

Ramapriyan, Hampapuram; Behnke, Jeanne; Hines-Watts, Tonjua

2007-01-01

In recent years there has been a surge in the number of systems for processing, archiving and distributing remotely sensed data. Such systems, working independently as well as in collaboration, have been contributing greatly to the advances in the scientific understanding of the Earth system, as well as utilization of the data for nationally and internationally important applications. Among such systems, we consider those that are developed by or under the sponsorship of NASA to fulfill one of its strategic objectives: "Study Earth from space to advance scientific understanding and meet societal needs." NASA's Earth science data systems are of varying size and complexity depending on the requirements they are intended to meet. Some data systems are regarded as NASA's "Core Capabilities" that provide the basic infrastructure for processing, archiving and distributing a set of data products to a large and diverse user community in a robust and reliable manner. Other data systems constitute "Community Capabilities". These provide specialized and innovative services to data users and/or research products offering new scientific insight. Such data systems are generally supported by NASA through peer reviewed competition. Examples of Core Capabilities are 1. Earth Observing Data and Information System (EOSDIS) with its Distributed Active Archive Centers (DAACs), Science Investigator-led Processing Systems (SIPSs), and the EOS Clearing House (ECHO); 2. Tropical Rainfall Measurement Mission (TRMM) Science Data and Information System (TSDIS); 3. Ocean Data Processing System (ODPS); and 4. CloudSat Data Processing Center. Examples of Community Capabilities are projects under the Research, Education and Applications Solutions Network (REASON), and Advancing Collaborative Connections for Earth System Science (ACCESS) Programs. In managing these data system capabilities, it is necessary to have well-established goals and to measure progress relative to them. Progress is measured through "metrics", which can be a combination of quantitative as well as qualitative assessments. The specific metrics of interest depend on the user of the metrics as well as the type of data system. The users of metrics can be data system managers, program managers, funding agency or the public. Data system managers need metrics for assessing and improving the performance of the system and for future planning. Program managers need metrics to assess progress and the value of the data systems sponsored by them. Also, there is a difference in the metrics needed for core capabilities that tend to be more complex, larger and longer-term compared to community capabilities and the community capabilities that tend to be simpler, smaller and shorter-term. Even among community capabilities there are differences; hence the same set of metrics does not apply to all. Some provide data products to users, some provide services that enable better utilization of data or interoperability among other systems, and some are a part of a larger project where provision of data or services is only a minor activity. There is also a contrast between metrics used for internal and external purposes. Examples of internal purposes are: ensuring that the system meets its requirements, and planning for evolution and growth. Examples of external purposes are: providing to sponsors indicators of success of the systems, demonstrating the contributions of the system to overall program success, etc. This paper will consider EOSDIS, REASON and ACCESS programs to show the various types of metrics needed and how they need to be tailored to the types of data systems while maintaining the overall management goals of measuring progress and contributions made by the data systems.

A Contrast in Use of Metrics in Earth Science Data Systems

NASA Astrophysics Data System (ADS)

Ramapriyan, H. K.; Behnke, J.; Hines-Watts, T. M.

2007-12-01

In recent years there has been a surge in the number of systems for processing, archiving and distributing remotely sensed data. Such systems, working independently as well as in collaboration, have been contributing greatly to the advances in the scientific understanding of the Earth system, as well as utilization of the data for nationally and internationally important applications. Among such systems, we consider those that are developed by or under the sponsorship of NASA to fulfill one of its strategic objectives: "Study Earth from space to advance scientific understanding and meet societal needs." NASA's Earth science data systems are of varying size and complexity depending on the requirements they are intended to meet. Some data systems are regarded as NASA's Core Capabilities that provide the basic infrastructure for processing, archiving and distributing a set of data products to a large and diverse user community in a robust and reliable manner. Other data systems constitute Community Capabilities. These provide specialized and innovative services to data users and/or research products offering new scientific insight. Such data systems are generally supported by NASA through peer reviewed competition. Examples of Core Capabilities are 1. Earth Observing Data and Information System (EOSDIS) with its Distributed Active Archive Centers (DAACs), Science Investigator-led Processing Systems (SIPSs), and the EOS Clearing House (ECHO); 2. Tropical Rainfall Measurement Mission (TRMM) Science Data and Information System (TSDIS); 3. Ocean Data Processing System (ODPS); and 4. CloudSat Data Processing Center. Examples of Community Capabilities are projects under the Research, Education and Applications Solutions Network (REASoN), and Advancing Collaborative Connections for Earth System Science (ACCESS) Programs. In managing these data system capabilities, it is necessary to have well-established goals and to measure progress relative to them. Progress is measured through metrics, which can be a combination of quantitative as well as qualitative assessments. The specific metrics of interest depend on the user of the metrics as well as the type of data system. The users of metrics can be data system managers, program managers, funding agency or the public. Data system managers need metrics for assessing and improving the performance of the system and for future planning. Program managers need metrics to assess progress and the value of the data systems sponsored by them. Also, there is a difference in the metrics needed for core capabilities that tend to be more complex, larger and longer-term compared to community capabilities and the community capabilities that tend to be simpler, smaller and shorter-term. Even among community capabilities there are differences; hence the same set of metrics does not apply to all. Some provide data products to users, some provide services that enable better utilization of data or interoperability among other systems, and some are a part of a larger project where provision of data or services is only a minor activity. There is also a contrast between metrics used for internal and external purposes. Examples of internal purposes are: ensuring that the system meets its requirements, and planning for evolution and growth. Examples of external purposes are: providing to sponsors indicators of success of the systems, demonstrating the contributions of the system to overall program success, etc. This paper will consider EOSDIS, REASoN and ACCESS programs to show the various types of metrics needed and how they need to be tailored to the types of data systems while maintaining the overall management goals of measuring progress and contributions made by the data systems.

New exposure-based metric approach for evaluating O3 risk to North American aspen forests

Treesearch

K.E. Percy; M. Nosal; W. Heilman; T. Dann; J. Sober; A.H. Legge; D.F. Karnosky

2007-01-01

The United States and Canada currently use exposure-based metrics to protect vegetation from O3. Using 5 years (1999-2003) of co-measured O3, meteorology and growth response, we have developed exposure-based regression models that predict Populus tremuloides growth change within the North American ambient...

Biofuel Supply Chains: Impacts, Indicators and Sustainability Metrics

EPA Science Inventory

The U.S. EPA’s Office of Research and Development has introduced a program to study the environmental impacts and sustainability of biofuel supply chains. Analyses will provide indicators and metrics for valuating sustainability. In this context, indicators are supply chain rat...

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes.

PubMed

Kireeva, Natalia V; Ovchinnikova, Svetlana I; Kuznetsov, Sergey L; Kazennov, Andrey M; Tsivadze, Aslan Yu

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes

NASA Astrophysics Data System (ADS)

Kireeva, Natalia V.; Ovchinnikova, Svetlana I.; Kuznetsov, Sergey L.; Kazennov, Andrey M.; Tsivadze, Aslan Yu.

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Application of Sigma Metrics Analysis for the Assessment and Modification of Quality Control Program in the Clinical Chemistry Laboratory of a Tertiary Care Hospital.

PubMed

Iqbal, Sahar; Mustansar, Tazeen

2017-03-01

Sigma is a metric that quantifies the performance of a process as a rate of Defects-Per-Million opportunities. In clinical laboratories, sigma metric analysis is used to assess the performance of laboratory process system. Sigma metric is also used as a quality management strategy for a laboratory process to improve the quality by addressing the errors after identification. The aim of this study is to evaluate the errors in quality control of analytical phase of laboratory system by sigma metric. For this purpose sigma metric analysis was done for analytes using the internal and external quality control as quality indicators. Results of sigma metric analysis were used to identify the gaps and need for modification in the strategy of laboratory quality control procedure. Sigma metric was calculated for quality control program of ten clinical chemistry analytes including glucose, chloride, cholesterol, triglyceride, HDL, albumin, direct bilirubin, total bilirubin, protein and creatinine, at two control levels. To calculate the sigma metric imprecision and bias was calculated with internal and external quality control data, respectively. The minimum acceptable performance was considered as 3 sigma. Westgard sigma rules were applied to customize the quality control procedure. Sigma level was found acceptable (≥3) for glucose (L2), cholesterol, triglyceride, HDL, direct bilirubin and creatinine at both levels of control. For rest of the analytes sigma metric was found <3. The lowest value for sigma was found for chloride (1.1) at L2. The highest value of sigma was found for creatinine (10.1) at L3. HDL was found with the highest sigma values at both control levels (8.8 and 8.0 at L2 and L3, respectively). We conclude that analytes with the sigma value <3 are required strict monitoring and modification in quality control procedure. In this study application of sigma rules provided us the practical solution for improved and focused design of QC procedure.

Metric Conversion. Hearing Before the Committee on Commerce, United States Senate, 92 Congress, Second Session on S.2483 and S.J.Res. 219.

ERIC Educational Resources Information Center

Congress of the U.S., Washington, DC. Senate Committee on Commerce.

Presented in this bulletin is the text of the hearing before the Committee on Commerce, United States Senate, ninety-second Congress, concerning coversion of the Nation to a metric system of weights and measures. Bill S. 2483 calls for providing a national program in order to make the international metric system the official and standard system of…

Purely electromagnetic spacetimes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivanov, B. V.

The Rainich's program of describing metrics induced by pure electromagnetic fields is implemented in a simpler way by using the Ernst formalism and increasing the symmetry of spacetime. Stationary metrics possessing one, two or three Killing vectors are studied and classified. Three branches of solutions exist. Electromagnetically induced mass terms appear in two of them, including a class of solutions in harmonic functions. The static subcase is discussed too. Relations to other well-known electrovacuum metrics are elucidated.

Defense Standardization Program Journal. November 2002/February 2003

DTIC Science & Technology

2003-02-01

8217 website, the nonprofit USMA has The National Council of Teachers many types of metric supplies and I I of Mathematics ( NCTM ), in recogni- training...aids available for sale. Also . ,. tion of the metrication efforts of available is a CD) that contains a Met- mathematics teachers , started National...ric Bibliography database of more thanE Metric Week in 1976. In those early 14,000 references to articles about the years, NCTM celebrated National

Scoring Coreference Partitions of Predicted Mentions: A Reference Implementation.

PubMed

Pradhan, Sameer; Luo, Xiaoqiang; Recasens, Marta; Hovy, Eduard; Ng, Vincent; Strube, Michael

2014-06-01

The definitions of two coreference scoring metrics- B 3 and CEAF-are underspecified with respect to predicted , as opposed to key (or gold ) mentions. Several variations have been proposed that manipulate either, or both, the key and predicted mentions in order to get a one-to-one mapping. On the other hand, the metric BLANC was, until recently, limited to scoring partitions of key mentions. In this paper, we (i) argue that mention manipulation for scoring predicted mentions is unnecessary, and potentially harmful as it could produce unintuitive results; (ii) illustrate the application of all these measures to scoring predicted mentions; (iii) make available an open-source, thoroughly-tested reference implementation of the main coreference evaluation measures; and (iv) rescore the results of the CoNLL-2011/2012 shared task systems with this implementation. This will help the community accurately measure and compare new end-to-end coreference resolution algorithms.

The influence of acoustical and non-acoustical factors on short-term annoyance due to aircraft noise in the field - The COSMA study.

PubMed

Bartels, Susanne; Márki, Ferenc; Müller, Uwe

2015-12-15

Air traffic has increased for the past decades and is forecasted to continue to grow. Noise due to current airport operations can impair the physical and psychological well-being of airport residents. The field study investigated aircraft noise-induced short-term (i.e., within hourly intervals) annoyance in local residents near a busy airport. We aimed at examining the contribution of acoustical and non-acoustical factors to the annoyance rating. Across four days from getting up till going to bed, 55 residents near Cologne/Bonn Airport (M=46years, SD=14years, 34 female) rated their annoyance due to aircraft noise at hourly intervals. For each participant and each hour, 26 noise metrics from outdoor measurements and further 6 individualized metrics that took into account the sound attenuation due to each person's whereabouts in and around their homes were obtained. Non-acoustical variables were differentiated into situational factors (time of day, performed activity during past hour, day of the week) and personal factors (e.g., sensitivity to noise, attitudes, domestic noise insulation). Generalized Estimation Equations were applied for the development of a prediction model for annoyance. Acoustical factors explained only a small proportion (13.7%) of the variance in the annoyance ratings. The number of fly-overs predicted annoyance better than did equivalent and maximum sound pressure levels. The proportion of explained variance in annoyance rose considerably (to 27.6%) when individualized noise metrics as well as situational and personal variables were included in the prediction model. Consideration of noise metrics related to the number of fly-overs and individual adjustment of noise metrics can improve the prediction of short-term annoyance compared to models using equivalent outdoor levels only. Non-acoustical factors have remarkable impact not only on long-term annoyance as shown before but also on short-term annoyance judged in the home environment. Copyright © 2015 Elsevier B.V. All rights reserved.

Neurones associated with saccade metrics in the monkey central mesencephalic reticular formation

PubMed Central

Cromer, Jason A; Waitzman, David M

2006-01-01

Neurones in the central mesencephalic reticular formation (cMRF) begin to discharge prior to saccades. These long lead burst neurones interact with major oculomotor centres including the superior colliculus (SC) and the paramedian pontine reticular formation (PPRF). Three different functions have been proposed for neurones in the cMRF: (1) to carry eye velocity signals that provide efference copy information to the SC (feedback), (2) to provide duration signals from the omnipause neurones to the SC (feedback), or (3) to participate in the transformation from the spatial encoding of a target selection signal in the SC into the temporal pattern of discharge used to drive the excitatory burst neurones in the pons (feed-forward). According to each respective proposal, specific predictions about cMRF neuronal discharge have been formulated. Individual neurones should: (1) encode instantaneous eye velocity, (2) burst specifically in relation to saccade duration but not to other saccade metrics, or (3) have a spectrum of weak to strong correlations to saccade dynamics. To determine if cMRF neurones could subserve these multiple oculomotor roles, we examined neuronal activity in relation to a variety of saccade metrics including amplitude, velocity and duration. We found separate groups of cMRF neurones that have the characteristics predicted by each of the proposed models. We also identified a number of subgroups for which no specific model prediction had previously been established. We found that we could accurately predict the neuronal firing pattern during one type of saccade behaviour (visually guided) using the activity during an alternative behaviour with different saccade metrics (memory guided saccades). We suggest that this evidence of a close relationship of cMRF neuronal discharge to individual saccade metrics supports the hypothesis that the cMRF participates in multiple saccade control pathways carrying saccade amplitude, velocity and duration information within the brainstem. PMID:16308353

DEVELOPMENT OF METRICS FOR TECHNICAL PRODUCTION: QUALIS BOOKS AND BOOK CHAPTERS.

PubMed

Ribas-Filho, Jurandir Marcondes; Malafaia, Osvaldo; Czeczko, Nicolau Gregori; Ribas, Carmen A P Marcondes; Nassif, Paulo Afonso Nunes

2015-01-01

To propose metrics to qualify the publication in books and chapters, and from there, establish guidance for the evaluation of the Medicine III programs. Analysis of some of the 2013 area documents focusing this issue. Were analyzed the following areas: Computer Science; Biotechnology; Biological Sciences I; Public Health; Medicine I. Except for the Medicine I, which has not adopted the metric for books and chapters, all other programs established metrics within the intellectual production, although with unequal percentages. It´s desirable to include metrics for books and book chapters in the intellectual production of post-graduate programs in Area Document with percentage-value of 5% in publications of Medicine III programs. Propor a métrica para qualificar a produção veiculada através de livros e capítulos e, a partir daí, estabelecer orientação para a avaliação dos programas de pós-graduação da Medicina III. Análise dos documentos de área de 2013 dos programas de pós-graduação senso estrito das áreas: Ciência da Computação; Biotecnologia; Ciências Biológicas I; Saúde Coletiva; Medicina I. Excetuando-se o programa da Medicina I, que não adotou a métrica para classificação de livros e capítulos, todos os demais estabeleceram-na dentro da sua produção intelectual, embora com percentuais desiguais. É desejável inserir a métrica de livros e capitulos de livros na produção intelectual do Documento de Área dos programas, ortorgando a ela percentual de 5% das publicações qualificadas dos programas da Medicina III.

Automated Generation and Assessment of Autonomous Systems Test Cases

NASA Technical Reports Server (NTRS)

Barltrop, Kevin J.; Friberg, Kenneth H.; Horvath, Gregory A.

2008-01-01

This slide presentation reviews some of the issues concerning verification and validation testing of autonomous spacecraft routinely culminates in the exploration of anomalous or faulted mission-like scenarios using the work involved during the Dawn mission's tests as examples. Prioritizing which scenarios to develop usually comes down to focusing on the most vulnerable areas and ensuring the best return on investment of test time. Rules-of-thumb strategies often come into play, such as injecting applicable anomalies prior to, during, and after system state changes; or, creating cases that ensure good safety-net algorithm coverage. Although experience and judgment in test selection can lead to high levels of confidence about the majority of a system's autonomy, it's likely that important test cases are overlooked. One method to fill in potential test coverage gaps is to automatically generate and execute test cases using algorithms that ensure desirable properties about the coverage. For example, generate cases for all possible fault monitors, and across all state change boundaries. Of course, the scope of coverage is determined by the test environment capabilities, where a faster-than-real-time, high-fidelity, software-only simulation would allow the broadest coverage. Even real-time systems that can be replicated and run in parallel, and that have reliable set-up and operations features provide an excellent resource for automated testing. Making detailed predictions for the outcome of such tests can be difficult, and when algorithmic means are employed to produce hundreds or even thousands of cases, generating predicts individually is impractical, and generating predicts with tools requires executable models of the design and environment that themselves require a complete test program. Therefore, evaluating the results of large number of mission scenario tests poses special challenges. A good approach to address this problem is to automatically score the results based on a range of metrics. Although the specific means of scoring depends highly on the application, the use of formal scoring - metrics has high value in identifying and prioritizing anomalies, and in presenting an overall picture of the state of the test program. In this paper we present a case study based on automatic generation and assessment of faulted test runs for the Dawn mission, and discuss its role in optimizing the allocation of resources for completing the test program.

Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grierson, B. A.; Yuan, X.; Gorelenkova, M.

TRANSP simulations are being used in the OMFIT work- flow manager to enable a machine independent means of experimental analysis, postdictive validation, and predictive time dependent simulations on the DIII-D, NSTX, JET and C-MOD tokamaks. The procedures for preparing the input data from plasma profile diagnostics and equilibrium reconstruction, as well as processing of the time-dependent heating and current drive sources and assumptions about the neutral recycling, vary across machines, but are streamlined by using a common workflow manager. Settings for TRANSP simulation fidelity are incorporated into the OMFIT framework, contrasting between-shot analysis, power balance, and fast-particle simulations. A previouslymore » established series of data consistency metrics are computed such as comparison of experimental vs. calculated neutron rate, equilibrium stored energy vs. total stored energy from profile and fast-ion pressure, and experimental vs. computed surface loop voltage. Discrepancies between data consistency metrics can indicate errors in input quantities such as electron density profile or Zeff, or indicate anomalous fast-particle transport. Measures to assess the sensitivity of the verification metrics to input quantities are provided by OMFIT, including scans of the input profiles and standardized post-processing visualizations. For predictive simulations, TRANSP uses GLF23 or TGLF to predict core plasma profiles, with user defined boundary conditions in the outer region of the plasma. ITPA validation metrics are provided in post-processing to assess the transport model validity. By using OMFIT to orchestrate the steps for experimental data preparation, selection of operating mode, submission, post-processing and visualization, we have streamlined and standardized the usage of TRANSP.« less

Effect of Pupil Size on Wavefront Refraction during Orthokeratology.

PubMed

Faria-Ribeiro, Miguel; Navarro, Rafael; González-Méijome, José Manuel

2016-11-01

It has been hypothesized that central and peripheral refraction, in eyes treated with myopic overnight orthokeratology, might vary with changes in pupil diameter. The aim of this work was to evaluate the axial and peripheral refraction and optical quality after orthokeratology, using ray tracing software for different pupil sizes. Zemax-EE was used to generate a series of 29 semi-customized model eyes based on the corneal topography changes from 29 patients who had undergone myopic orthokeratology. Wavefront refraction in the central 80 degrees of the visual field was calculated using three different quality metrics criteria: Paraxial curvature matching, minimum root mean square error (minRMS), and the Through Focus Visual Strehl of the Modulation Transfer Function (VSMTF), for 3- and 6-mm pupil diameters. The three metrics predicted significantly different values for foveal and peripheral refractions. Compared with the Paraxial criteria, the other two metrics predicted more myopic refractions on- and off-axis. Interestingly, the VSMTF predicts only a marginal myopic shift in the axial refraction as the pupil changes from 3 to 6 mm. For peripheral refraction, minRMS and VSMTF metric criteria predicted a higher exposure to peripheral defocus as the pupil increases from 3 to 6 mm. The results suggest that the supposed effect of myopic control produced by ortho-k treatments might be dependent on pupil size. Although the foveal refractive error does not seem to change appreciably with the increase in pupil diameter (VSMTF criteria), the high levels of positive spherical aberration will lead to a degradation of lower spatial frequencies, that is more significant under low illumination levels.

Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT

DOE PAGES

Grierson, B. A.; Yuan, X.; Gorelenkova, M.; ...

2018-02-21

TRANSP simulations are being used in the OMFIT work- flow manager to enable a machine independent means of experimental analysis, postdictive validation, and predictive time dependent simulations on the DIII-D, NSTX, JET and C-MOD tokamaks. The procedures for preparing the input data from plasma profile diagnostics and equilibrium reconstruction, as well as processing of the time-dependent heating and current drive sources and assumptions about the neutral recycling, vary across machines, but are streamlined by using a common workflow manager. Settings for TRANSP simulation fidelity are incorporated into the OMFIT framework, contrasting between-shot analysis, power balance, and fast-particle simulations. A previouslymore » established series of data consistency metrics are computed such as comparison of experimental vs. calculated neutron rate, equilibrium stored energy vs. total stored energy from profile and fast-ion pressure, and experimental vs. computed surface loop voltage. Discrepancies between data consistency metrics can indicate errors in input quantities such as electron density profile or Zeff, or indicate anomalous fast-particle transport. Measures to assess the sensitivity of the verification metrics to input quantities are provided by OMFIT, including scans of the input profiles and standardized post-processing visualizations. For predictive simulations, TRANSP uses GLF23 or TGLF to predict core plasma profiles, with user defined boundary conditions in the outer region of the plasma. ITPA validation metrics are provided in post-processing to assess the transport model validity. By using OMFIT to orchestrate the steps for experimental data preparation, selection of operating mode, submission, post-processing and visualization, we have streamlined and standardized the usage of TRANSP.« less

Definition and classification of evaluation units for tertiary structure prediction in CASP12 facilitated through semi-automated metrics.

PubMed

Abriata, Luciano A; Kinch, Lisa N; Tamò, Giorgio E; Monastyrskyy, Bohdan; Kryshtafovych, Andriy; Dal Peraro, Matteo

2018-03-01

For assessment purposes, CASP targets are split into evaluation units. We herein present the official definition of CASP12 evaluation units (EUs) and their classification into difficulty categories. Each target can be evaluated as one EU (the whole target) or/and several EUs (separate structural domains or groups of structural domains). The specific scenario for a target split is determined by the domain organization of available templates, the difference in server performance on separate domains versus combination of the domains, and visual inspection. In the end, 71 targets were split into 96 EUs. Classification of the EUs into difficulty categories was done semi-automatically with the assistance of metrics provided by the Prediction Center. These metrics account for sequence and structural similarities of the EUs to potential structural templates from the Protein Data Bank, and for the baseline performance of automated server predictions. The metrics readily separate the 96 EUs into 38 EUs that should be straightforward for template-based modeling (TBM) and 39 that are expected to be hard for homology modeling and are thus left for free modeling (FM). The remaining 19 borderline evaluation units were dubbed FM/TBM, and were inspected case by case. The article also overviews structural and evolutionary features of selected targets relevant to our accompanying article presenting the assessment of FM and FM/TBM predictions, and overviews structural features of the hardest evaluation units from the FM category. We finally suggest improvements for the EU definition and classification procedures. © 2017 Wiley Periodicals, Inc.

Improved Mental Acuity Forecasting with an Individualized Quantitative Sleep Model.

PubMed

Winslow, Brent D; Nguyen, Nam; Venta, Kimberly E

2017-01-01

Sleep impairment significantly alters human brain structure and cognitive function, but available evidence suggests that adults in developed nations are sleeping less. A growing body of research has sought to use sleep to forecast cognitive performance by modeling the relationship between the two, but has generally focused on vigilance rather than other cognitive constructs affected by sleep, such as reaction time, executive function, and working memory. Previous modeling efforts have also utilized subjective, self-reported sleep durations and were restricted to laboratory environments. In the current effort, we addressed these limitations by employing wearable systems and mobile applications to gather objective sleep information, assess multi-construct cognitive performance, and model/predict changes to mental acuity. Thirty participants were recruited for participation in the study, which lasted 1 week. Using the Fitbit Charge HR and a mobile version of the automated neuropsychological assessment metric called CogGauge, we gathered a series of features and utilized the unified model of performance to predict mental acuity based on sleep records. Our results suggest that individuals poorly rate their sleep duration, supporting the need for objective sleep metrics to model circadian changes to mental acuity. Participant compliance in using the wearable throughout the week and responding to the CogGauge assessments was 80%. Specific biases were identified in temporal metrics across mobile devices and operating systems and were excluded from the mental acuity metric development. Individualized prediction of mental acuity consistently outperformed group modeling. This effort indicates the feasibility of creating an individualized, mobile assessment and prediction of mental acuity, compatible with the majority of current mobile devices.

Quality metrics for sensor images

NASA Technical Reports Server (NTRS)

Ahumada, AL

1993-01-01

Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.

Moss and vascular plant indices in Ohio wetlands have similar environmental predictors

USGS Publications Warehouse

Stapanian, Martin A.; Schumacher, William; Gara, Brian; Adams, Jean V.; Viau, Nick

2016-01-01

Mosses and vascular plants have been shown to be reliable indicators of wetland habitat delineation and environmental quality. Knowledge of the best ecological predictors of the quality of wetland moss and vascular plant communities may determine if similar management practices would simultaneously enhance both populations. We used Akaike's Information Criterion to identify models predicting a moss quality assessment index (MQAI) and a vascular plant index of biological integrity based on floristic quality (VIBI-FQ) from 27 emergent and 13 forested wetlands in Ohio, USA. The set of predictors included the six metrics from a wetlands disturbance index (ORAM) and two landscape development intensity indices (LDIs). The best single predictor of MQAI and one of the predictors of VIBI-FQ was an ORAM metric that assesses habitat alteration and disturbance within the wetland, such as mowing, grazing, and agricultural practices. However, the best single predictor of VIBI-FQ was an ORAM metric that assessed wetland vascular plant communities, interspersion, and microtopography. LDIs better predicted MQAI than VIBI-FQ, suggesting that mosses may either respond more rapidly to, or recover more slowly from, anthropogenic disturbance in the surrounding landscape than vascular plants. These results supported previous predictive studies on amphibian indices and metrics and a separate vegetation index, indicating that similar wetland management practices may result in qualitatively the same ecological response for three vastly different wetland biological communities (amphibians, vascular plants, and mosses).

Large-Scale Biomonitoring of Remote and Threatened Ecosystems via High-Throughput Sequencing

PubMed Central

Gibson, Joel F.; Shokralla, Shadi; Curry, Colin; Baird, Donald J.; Monk, Wendy A.; King, Ian; Hajibabaei, Mehrdad

2015-01-01

Biodiversity metrics are critical for assessment and monitoring of ecosystems threatened by anthropogenic stressors. Existing sorting and identification methods are too expensive and labour-intensive to be scaled up to meet management needs. Alternately, a high-throughput DNA sequencing approach could be used to determine biodiversity metrics from bulk environmental samples collected as part of a large-scale biomonitoring program. Here we show that both morphological and DNA sequence-based analyses are suitable for recovery of individual taxonomic richness, estimation of proportional abundance, and calculation of biodiversity metrics using a set of 24 benthic samples collected in the Peace-Athabasca Delta region of Canada. The high-throughput sequencing approach was able to recover all metrics with a higher degree of taxonomic resolution than morphological analysis. The reduced cost and increased capacity of DNA sequence-based approaches will finally allow environmental monitoring programs to operate at the geographical and temporal scale required by industrial and regulatory end-users. PMID:26488407

Optimal Modality Selection for Cooperative Human-Robot Task Completion.

PubMed

Jacob, Mithun George; Wachs, Juan P

2016-12-01

Human-robot cooperation in complex environments must be fast, accurate, and resilient. This requires efficient communication channels where robots need to assimilate information using a plethora of verbal and nonverbal modalities such as hand gestures, speech, and gaze. However, even though hybrid human-robot communication frameworks and multimodal communication have been studied, a systematic methodology for designing multimodal interfaces does not exist. This paper addresses the gap by proposing a novel methodology to generate multimodal lexicons which maximizes multiple performance metrics over a wide range of communication modalities (i.e., lexicons). The metrics are obtained through a mixture of simulation and real-world experiments. The methodology is tested in a surgical setting where a robot cooperates with a surgeon to complete a mock abdominal incision and closure task by delivering surgical instruments. Experimental results show that predicted optimal lexicons significantly outperform predicted suboptimal lexicons (p <; 0.05) in all metrics validating the predictability of the methodology. The methodology is validated in two scenarios (with and without modeling the risk of a human-robot collision) and the differences in the lexicons are analyzed.

An Improved Suite of Object Oriented Software Measures

NASA Technical Reports Server (NTRS)

Neal, Ralph D.; Weistroffer, H. Roland; Coppins, Richard J.

1997-01-01

In the pursuit of ever increasing productivity, the need to be able to measure specific aspects of software is generally agreed upon. As object oriented programming languages are becoming more and more widely used, metrics specifically designed for object oriented software are required. In recent years there has been an explosion of new, object oriented software metrics proposed in the literature. Unfortunately, many or most of these proposed metrics have not been validated to measure what they claim to measure. In fact, an analysis of many of these metrics shows that they do not satisfy basic properties of measurement theory, and thus their application has to be suspect. In this paper ten improved metrics are proposed and are validated using measurement theory.

Understanding software faults and their role in software reliability modeling

NASA Technical Reports Server (NTRS)

Munson, John C.

1994-01-01

This study is a direct result of an on-going project to model the reliability of a large real-time control avionics system. In previous modeling efforts with this system, hardware reliability models were applied in modeling the reliability behavior of this system. In an attempt to enhance the performance of the adapted reliability models, certain software attributes were introduced in these models to control for differences between programs and also sequential executions of the same program. As the basic nature of the software attributes that affect software reliability become better understood in the modeling process, this information begins to have important implications on the software development process. A significant problem arises when raw attribute measures are to be used in statistical models as predictors, for example, of measures of software quality. This is because many of the metrics are highly correlated. Consider the two attributes: lines of code, LOC, and number of program statements, Stmts. In this case, it is quite obvious that a program with a high value of LOC probably will also have a relatively high value of Stmts. In the case of low level languages, such as assembly language programs, there might be a one-to-one relationship between the statement count and the lines of code. When there is a complete absence of linear relationship among the metrics, they are said to be orthogonal or uncorrelated. Usually the lack of orthogonality is not serious enough to affect a statistical analysis. However, for the purposes of some statistical analysis such as multiple regression, the software metrics are so strongly interrelated that the regression results may be ambiguous and possibly even misleading. Typically, it is difficult to estimate the unique effects of individual software metrics in the regression equation. The estimated values of the coefficients are very sensitive to slight changes in the data and to the addition or deletion of variables in the regression equation. Since most of the existing metrics have common elements and are linear combinations of these common elements, it seems reasonable to investigate the structure of the underlying common factors or components that make up the raw metrics. The technique we have chosen to use to explore this structure is a procedure called principal components analysis. Principal components analysis is a decomposition technique that may be used to detect and analyze collinearity in software metrics. When confronted with a large number of metrics measuring a single construct, it may be desirable to represent the set by some smaller number of variables that convey all, or most, of the information in the original set. Principal components are linear transformations of a set of random variables that summarize the information contained in the variables. The transformations are chosen so that the first component accounts for the maximal amount of variation of the measures of any possible linear transform; the second component accounts for the maximal amount of residual variation; and so on. The principal components are constructed so that they represent transformed scores on dimensions that are orthogonal. Through the use of principal components analysis, it is possible to have a set of highly related software attributes mapped into a small number of uncorrelated attribute domains. This definitively solves the problem of multi-collinearity in subsequent regression analysis. There are many software metrics in the literature, but principal component analysis reveals that there are few distinct sources of variation, i.e. dimensions, in this set of metrics. It would appear perfectly reasonable to characterize the measurable attributes of a program with a simple function of a small number of orthogonal metrics each of which represents a distinct software attribute domain.

Gravitation Theory: Empirical Status from Solar System Experiments: All observations to date are consistent with Einstein's general relativity theory of gravity.

PubMed

Nordtvedt, K L

1972-12-15

I have reviewed the historical and contemporary experiments that guide us in choosing a post-Newtonian, relativistic gravitational theory. The foundation experiments essentially constrain gravitation theory to be a metric theory in which matter couples solely to one gravitational field, the metric field, although other cosmological gravitational fields may exist. The metric field for any metric theory can be specified (for the solar system, for our present purposes) by a series of potential terms with several parameters. A variety of experiments specify (or put limits on) the numerical values of the seven parameters in the post-Newtonian metric field, and other such experiments have been planned. The empirical results, to date, yield values of the parameters that are consistent with the predictions of Einstein's general relativity.

A Graph Analytic Metric for Mitigating Advanced Persistent Threat

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, John R.; Hogan, Emilie A.

2013-06-04

This paper introduces a novel graph analytic metric that can be used to measure the potential vulnerability of a cyber network to specific types of attacks that use lateral movement and privilege escalation such as the well known Pass The Hash, (PTH). The metric is computed from an oriented subgraph of the underlying cyber network induced by selecting only those edges for which a given property holds between the two vertices of the edge. The metric with respect to a select node on the subgraph is defined as the likelihood that the select node is reachable from another arbitrary nodemore » in the graph. This metric can be calculated dynamically from the authorization and auditing layers during the network security authorization phase and will potentially enable predictive deterrence against attacks such as PTH.« less

CADRE-SS, an in Silico Tool for Predicting Skin Sensitization Potential Based on Modeling of Molecular Interactions.

PubMed

Kostal, Jakub; Voutchkova-Kostal, Adelina

2016-01-19

Using computer models to accurately predict toxicity outcomes is considered to be a major challenge. However, state-of-the-art computational chemistry techniques can now be incorporated in predictive models, supported by advances in mechanistic toxicology and the exponential growth of computing resources witnessed over the past decade. The CADRE (Computer-Aided Discovery and REdesign) platform relies on quantum-mechanical modeling of molecular interactions that represent key biochemical triggers in toxicity pathways. Here, we present an external validation exercise for CADRE-SS, a variant developed to predict the skin sensitization potential of commercial chemicals. CADRE-SS is a hybrid model that evaluates skin permeability using Monte Carlo simulations, assigns reactive centers in a molecule and possible biotransformations via expert rules, and determines reactivity with skin proteins via quantum-mechanical modeling. The results were promising with an overall very good concordance of 93% between experimental and predicted values. Comparison to performance metrics yielded by other tools available for this endpoint suggests that CADRE-SS offers distinct advantages for first-round screenings of chemicals and could be used as an in silico alternative to animal tests where permissible by legislative programs.

An Examination of Existing Guidelines for Programs for the Preservice and Inservice Education of Teachers in Metric Education and the Modification of These and the Development of New Ones if Deemed Necessary. Final Report of Objective No. 3.

ERIC Educational Resources Information Center

Granito, Dolores

These guidelines for in-service and preservice teacher education related to the conversion to the metric system were developed from a survey of published materials, university faculty, and mathematics supervisors. The eleven guidelines fall into three major categories: (1) design of teacher training programs, (2) teacher training, and (3)…

Metrics for the NASA Airspace Systems Program

NASA Technical Reports Server (NTRS)

Smith, Jeremy C.; Neitzke, Kurt W.

2009-01-01

This document defines an initial set of metrics for use by the NASA Airspace Systems Program (ASP). ASP consists of the NextGen-Airspace Project and the NextGen-Airportal Project. The work in each project is organized along multiple, discipline-level Research Focus Areas (RFAs). Each RFA is developing future concept elements in support of the Next Generation Air Transportation System (NextGen), as defined by the Joint Planning and Development Office (JPDO). In addition, a single, system-level RFA is responsible for integrating concept elements across RFAs in both projects and for assessing system-wide benefits. The primary purpose of this document is to define a common set of metrics for measuring National Airspace System (NAS) performance before and after the introduction of ASP-developed concepts for NextGen as the system handles increasing traffic. The metrics are directly traceable to NextGen goals and objectives as defined by the JPDO and hence will be used to measure the progress of ASP research toward reaching those goals. The scope of this document is focused on defining a common set of metrics for measuring NAS capacity, efficiency, robustness, and safety at the system-level and at the RFA-level. Use of common metrics will focus ASP research toward achieving system-level performance goals and objectives and enable the discipline-level RFAs to evaluate the impact of their concepts at the system level.

Assessing deep and shallow learning methods for quantitative prediction of acute chemical toxicity.

PubMed

Liu, Ruifeng; Madore, Michael; Glover, Kyle P; Feasel, Michael G; Wallqvist, Anders

2018-05-02

Animal-based methods for assessing chemical toxicity are struggling to meet testing demands. In silico approaches, including machine-learning methods, are promising alternatives. Recently, deep neural networks (DNNs) were evaluated and reported to outperform other machine-learning methods for quantitative structure-activity relationship modeling of molecular properties. However, most of the reported performance evaluations relied on global performance metrics, such as the root mean squared error (RMSE) between the predicted and experimental values of all samples, without considering the impact of sample distribution across the activity spectrum. Here, we carried out an in-depth analysis of DNN performance for quantitative prediction of acute chemical toxicity using several datasets. We found that the overall performance of DNN models on datasets of up to 30,000 compounds was similar to that of random forest (RF) models, as measured by the RMSE and correlation coefficients between the predicted and experimental results. However, our detailed analyses demonstrated that global performance metrics are inappropriate for datasets with a highly uneven sample distribution, because they show a strong bias for the most populous compounds along the toxicity spectrum. For highly toxic compounds, DNN and RF models trained on all samples performed much worse than the global performance metrics indicated. Surprisingly, our variable nearest neighbor method, which utilizes only structurally similar compounds to make predictions, performed reasonably well, suggesting that information of close near neighbors in the training sets is a key determinant of acute toxicity predictions.

Development of a metrics dashboard for monitoring involvement in the 340B Drug Pricing Program.

PubMed

Karralli, Rusol; Tipton, Joyce; Dumitru, Doina; Scholz, Lisa; Masilamani, Santhi

2015-09-01

An electronic tool to support hospital organizations in monitoring and addressing financial and compliance challenges related to participation in the 340B Drug Pricing Program is described. In recent years there has been heightened congressional and regulatory scrutiny of the federal 340B program, which provides discounted drug prices on Medicaid-covered drugs to safety net hospitals and other 340B-eligible healthcare organizations, or "covered entities." Historically, the 340B program has lacked a metrics-driven reporting framework to help covered entities capture the value of 340B program involvement, community benefits provided to underserved populations, and costs associated with compliance with 340B eligibility requirements. As part of an initiative by a large health system to optimize its 340B program utilization and regulatory compliance efforts, a team of pharmacists led the development of an electronic dashboard tool to help monitor 340B program activities at the system's 340B-eligible facilities. After soliciting input from an array of internal and external 340B program stakeholders, the team designed the dashboard and associated data-entry tools to facilitate the capture and analysis of 340B program-related data in four domains: cost savings and revenue, program maintenance costs, community benefits, and compliance. A large health system enhanced its ability to evaluate and monitor 340B program-related activities through the use of a dashboard tool capturing key metrics on cost savings achieved, maintenance costs, and other aspects of program involvement. Copyright © 2015 by the American Society of Health-System Pharmacists, Inc. All rights reserved.

Plant responses to increasing CO 2 reduce estimates of climate impacts on drought severity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Swann, Abigail L. S.; Hoffman, Forrest M.; Koven, Charles D.

Rising atmospheric CO 2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO 2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO 2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area.more » This area drops to 37% with the use of precipitation minus evapo-transpiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO 2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO 2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.« less

Plant responses to increasing CO 2 reduce estimates of climate impacts on drought severity

DOE PAGES

Swann, Abigail L. S.; Hoffman, Forrest M.; Koven, Charles D.; ...

2016-08-29

Rising atmospheric CO 2 will make Earth warmer, and many studies have inferred that this warming will cause droughts to become more widespread and severe. However, rising atmospheric CO 2 also modifies stomatal conductance and plant water use, processes that are often are overlooked in impact analysis. We find that plant physiological responses to CO 2 reduce predictions of future drought stress, and that this reduction is captured by using plant-centric rather than atmosphere-centric metrics from Earth system models (ESMs). The atmosphere-centric Palmer Drought Severity Index predicts future increases in drought stress for more than 70% of global land area.more » This area drops to 37% with the use of precipitation minus evapo-transpiration (P-E), a measure that represents the water flux available to downstream ecosystems and humans. The two metrics yield consistent estimates of increasing stress in regions where precipitation decreases are more robust (southern North America, northeastern South America, and southern Europe). The metrics produce diverging estimates elsewhere, with P-E predicting decreasing stress across temperate Asia and central Africa. The differing sensitivity of drought metrics to radiative and physiological aspects of increasing CO 2 partly explains the divergent estimates of future drought reported in recent studies. Further, use of ESM output in offline models may double-count plant feedbacks on relative humidity and other surface variables, leading to overestimates of future stress. The use of drought metrics that account for the response of plant transpiration to changing CO 2, including direct use of P-E and soil moisture from ESMs, is needed to reduce uncertainties in future assessment.« less

Reference-Free Assessment of Speech Intelligibility Using Bispectrum of an Auditory Neurogram.

PubMed

Hossain, Mohammad E; Jassim, Wissam A; Zilany, Muhammad S A

2016-01-01

Sensorineural hearing loss occurs due to damage to the inner and outer hair cells of the peripheral auditory system. Hearing loss can cause decreases in audibility, dynamic range, frequency and temporal resolution of the auditory system, and all of these effects are known to affect speech intelligibility. In this study, a new reference-free speech intelligibility metric is proposed using 2-D neurograms constructed from the output of a computational model of the auditory periphery. The responses of the auditory-nerve fibers with a wide range of characteristic frequencies were simulated to construct neurograms. The features of the neurograms were extracted using third-order statistics referred to as bispectrum. The phase coupling of neurogram bispectrum provides a unique insight for the presence (or deficit) of supra-threshold nonlinearities beyond audibility for listeners with normal hearing (or hearing loss). The speech intelligibility scores predicted by the proposed method were compared to the behavioral scores for listeners with normal hearing and hearing loss both in quiet and under noisy background conditions. The results were also compared to the performance of some existing methods. The predicted results showed a good fit with a small error suggesting that the subjective scores can be estimated reliably using the proposed neural-response-based metric. The proposed metric also had a wide dynamic range, and the predicted scores were well-separated as a function of hearing loss. The proposed metric successfully captures the effects of hearing loss and supra-threshold nonlinearities on speech intelligibility. This metric could be applied to evaluate the performance of various speech-processing algorithms designed for hearing aids and cochlear implants.

Reference-Free Assessment of Speech Intelligibility Using Bispectrum of an Auditory Neurogram

PubMed Central

Hossain, Mohammad E.; Jassim, Wissam A.; Zilany, Muhammad S. A.

2016-01-01

Sensorineural hearing loss occurs due to damage to the inner and outer hair cells of the peripheral auditory system. Hearing loss can cause decreases in audibility, dynamic range, frequency and temporal resolution of the auditory system, and all of these effects are known to affect speech intelligibility. In this study, a new reference-free speech intelligibility metric is proposed using 2-D neurograms constructed from the output of a computational model of the auditory periphery. The responses of the auditory-nerve fibers with a wide range of characteristic frequencies were simulated to construct neurograms. The features of the neurograms were extracted using third-order statistics referred to as bispectrum. The phase coupling of neurogram bispectrum provides a unique insight for the presence (or deficit) of supra-threshold nonlinearities beyond audibility for listeners with normal hearing (or hearing loss). The speech intelligibility scores predicted by the proposed method were compared to the behavioral scores for listeners with normal hearing and hearing loss both in quiet and under noisy background conditions. The results were also compared to the performance of some existing methods. The predicted results showed a good fit with a small error suggesting that the subjective scores can be estimated reliably using the proposed neural-response-based metric. The proposed metric also had a wide dynamic range, and the predicted scores were well-separated as a function of hearing loss. The proposed metric successfully captures the effects of hearing loss and supra-threshold nonlinearities on speech intelligibility. This metric could be applied to evaluate the performance of various speech-processing algorithms designed for hearing aids and cochlear implants. PMID:26967160

Alternative metrics for real-ear-to-coupler difference average values in children.

PubMed

Blumsack, Judith T; Clark-Lewis, Sandra; Watts, Kelli M; Wilson, Martha W; Ross, Margaret E; Soles, Lindsey; Ennis, Cydney

2014-10-01

Ideally, individual real-ear-to-coupler difference (RECD) measurements are obtained for pediatric hearing instrument-fitting purposes. When RECD measurements cannot be obtained, age-related average RECDs based on typically developing North American children are used. Evidence suggests that these values may not be appropriate for populations of children with retarded growth patterns. The purpose of this study was to determine if another metric, such as head circumference, height, or weight, can be used for prediction of RECDs in children. Design was a correlational study. For all participants, RECD values in both ears, head circumference, height, and weight were measured. The sample consisted of 68 North American children (ages 3-11 yr). Height, weight, head circumference, and RECDs were measured and were analyzed for both ears at 500, 750, 1000, 1500, 2000, 3000, 4000, and 6000 Hz. A backward elimination multiple-regression analysis was used to determine if age, height, weight, and/or head circumference are significant predictors of RECDs. For the left ear, head circumference was retained as the only statistically significant variable in the final model. For the right ear, head circumference was retained as the only statistically significant independent variable at all frequencies except at 2000 and 4000 Hz. At these latter frequencies, weight was retained as the only statistically significant independent variable after all other variables were eliminated. Head circumference can be considered as a metric for RECD prediction in children when individual measurements cannot be obtained. In developing countries where equipment is often unavailable and stunted growth can reduce the value of using age as a metric, head circumference can be considered as an alternative metric in the prediction of RECDs. American Academy of Audiology.

Comparative assessment of GIS-based methods and metrics for estimating long-term exposures to air pollution

NASA Astrophysics Data System (ADS)

Gulliver, John; de Hoogh, Kees; Fecht, Daniela; Vienneau, Danielle; Briggs, David

2011-12-01

The development of geographical information system techniques has opened up a wide array of methods for air pollution exposure assessment. The extent to which these provide reliable estimates of air pollution concentrations is nevertheless not clearly established. Nor is it clear which methods or metrics should be preferred in epidemiological studies. This paper compares the performance of ten different methods and metrics in terms of their ability to predict mean annual PM 10 concentrations across 52 monitoring sites in London, UK. Metrics analysed include indicators (distance to nearest road, traffic volume on nearest road, heavy duty vehicle (HDV) volume on nearest road, road density within 150 m, traffic volume within 150 m and HDV volume within 150 m) and four modelling approaches: based on the nearest monitoring site, kriging, dispersion modelling and land use regression (LUR). Measures were computed in a GIS, and resulting metrics calibrated and validated against monitoring data using a form of grouped jack-knife analysis. The results show that PM 10 concentrations across London show little spatial variation. As a consequence, most methods can predict the average without serious bias. Few of the approaches, however, show good correlations with monitored PM 10 concentrations, and most predict no better than a simple classification based on site type. Only land use regression reaches acceptable levels of correlation ( R2 = 0.47), though this can be improved by also including information on site type. This might therefore be taken as a recommended approach in many studies, though care is needed in developing meaningful land use regression models, and like any method they need to be validated against local data before their application as part of epidemiological studies.

FAST COGNITIVE AND TASK ORIENTED, ITERATIVE DATA DISPLAY (FACTOID)

DTIC Science & Technology

2017-06-01

approaches. As a result, the following assumptions guided our efforts in developing modeling and descriptive metrics for evaluation purposes...Application Evaluation . Our analytic workflow for evaluation is to first provide descriptive statistics about applications across metrics (performance...distributions for evaluation purposes because the goal of evaluation is accurate description , not inference (e.g., prediction). Outliers depicted

Prediction of fatigue-related driver performance from EEG data by deep Riemannian model.

PubMed

Hajinoroozi, Mehdi; Jianqiu Zhang; Yufei Huang

2017-07-01

Prediction of the drivers' drowsy and alert states is important for safety purposes. The prediction of drivers' drowsy and alert states from electroencephalography (EEG) using shallow and deep Riemannian methods is presented. For shallow Riemannian methods, the minimum distance to Riemannian mean (mdm) and Log-Euclidian metric are investigated, where it is shown that Log-Euclidian metric outperforms the mdm algorithm. In addition the SPDNet, a deep Riemannian model, that takes the EEG covariance matrix as the input is investigated. It is shown that SPDNet outperforms all tested shallow and deep classification methods. Performance of SPDNet is 6.02% and 2.86% higher than the best performance by the conventional Euclidian classifiers and shallow Riemannian models, respectively.

Prediction uncertainty and optimal experimental design for learning dynamical systems.

PubMed

Letham, Benjamin; Letham, Portia A; Rudin, Cynthia; Browne, Edward P

2016-06-01

Dynamical systems are frequently used to model biological systems. When these models are fit to data, it is necessary to ascertain the uncertainty in the model fit. Here, we present prediction deviation, a metric of uncertainty that determines the extent to which observed data have constrained the model's predictions. This is accomplished by solving an optimization problem that searches for a pair of models that each provides a good fit for the observed data, yet has maximally different predictions. We develop a method for estimating a priori the impact that additional experiments would have on the prediction deviation, allowing the experimenter to design a set of experiments that would most reduce uncertainty. We use prediction deviation to assess uncertainty in a model of interferon-alpha inhibition of viral infection, and to select a sequence of experiments that reduces this uncertainty. Finally, we prove a theoretical result which shows that prediction deviation provides bounds on the trajectories of the underlying true model. These results show that prediction deviation is a meaningful metric of uncertainty that can be used for optimal experimental design.

The influence of vegetation height heterogeneity on forest and woodland bird species richness across the United States.

PubMed

Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J

2014-01-01

Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r(2) = ∼ 0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r(2) = ∼ 0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness.

Evaluating the critical source area concept of phosphorus loss from soils to water-bodies in agricultural catchments.

PubMed

Shore, M; Jordan, P; Mellander, P-E; Kelly-Quinn, M; Wall, D P; Murphy, P N C; Melland, A R

2014-08-15

Using data collected from six basins located across two hydrologically contrasting agricultural catchments, this study investigated whether transport metrics alone provide better estimates of storm phosphorus (P) loss from basins than critical source area (CSA) metrics which combine source factors as well. Concentrations and loads of P in quickflow (QF) were measured at basin outlets during four storm events and were compared with dynamic (QF magnitude) and static (extent of highly-connected, poorly-drained soils) transport metrics and a CSA metric (extent of highly-connected, poorly-drained soils with excess plant-available P). Pairwise comparisons between basins with similar CSA risks but contrasting QF magnitudes showed that QF flow-weighted mean TRP (total molybdate-reactive P) concentrations and loads were frequently (at least 11 of 14 comparisons) more than 40% higher in basins with the highest QF magnitudes. Furthermore, static transport metrics reliably discerned relative QF magnitudes between these basins. However, particulate P (PP) concentrations were often (6 of 14 comparisons) higher in basins with the lowest QF magnitudes, most likely due to soil-management activities (e.g. ploughing), in these predominantly arable basins at these times. Pairwise comparisons between basins with contrasting CSA risks and similar QF magnitudes showed that TRP and PP concentrations and loads did not reflect trends in CSA risk or QF magnitude. Static transport metrics did not discern relative QF magnitudes between these basins. In basins with contrasting transport risks, storm TRP concentrations and loads were well differentiated by dynamic or static transport metrics alone, regardless of differences in soil P. In basins with similar transport risks, dynamic transport metrics and P source information additional to soil P may be required to predict relative storm TRP concentrations and loads. Regardless of differences in transport risk, information on land use and management, may be required to predict relative differences in storm PP concentrations between these agricultural basins. Copyright © 2014 Elsevier B.V. All rights reserved.

The Influence of Vegetation Height Heterogeneity on Forest and Woodland Bird Species Richness across the United States

PubMed Central

Huang, Qiongyu; Swatantran, Anu; Dubayah, Ralph; Goetz, Scott J.

2014-01-01

Avian diversity is under increasing pressures. It is thus critical to understand the ecological variables that contribute to large scale spatial distribution of avian species diversity. Traditionally, studies have relied primarily on two-dimensional habitat structure to model broad scale species richness. Vegetation vertical structure is increasingly used at local scales. However, the spatial arrangement of vegetation height has never been taken into consideration. Our goal was to examine the efficacies of three-dimensional forest structure, particularly the spatial heterogeneity of vegetation height in improving avian richness models across forested ecoregions in the U.S. We developed novel habitat metrics to characterize the spatial arrangement of vegetation height using the National Biomass and Carbon Dataset for the year 2000 (NBCD). The height-structured metrics were compared with other habitat metrics for statistical association with richness of three forest breeding bird guilds across Breeding Bird Survey (BBS) routes: a broadly grouped woodland guild, and two forest breeding guilds with preferences for forest edge and for interior forest. Parametric and non-parametric models were built to examine the improvement of predictability. Height-structured metrics had the strongest associations with species richness, yielding improved predictive ability for the woodland guild richness models (r2 = ∼0.53 for the parametric models, 0.63 the non-parametric models) and the forest edge guild models (r2 = ∼0.34 for the parametric models, 0.47 the non-parametric models). All but one of the linear models incorporating height-structured metrics showed significantly higher adjusted-r2 values than their counterparts without additional metrics. The interior forest guild richness showed a consistent low association with height-structured metrics. Our results suggest that height heterogeneity, beyond canopy height alone, supplements habitat characterization and richness models of forest bird species. The metrics and models derived in this study demonstrate practical examples of utilizing three-dimensional vegetation data for improved characterization of spatial patterns in species richness. PMID:25101782

Technology transfer metrics: Measurement and verification of data/reusable launch vehicle business analysis

NASA Technical Reports Server (NTRS)

Trivoli, George W.

1996-01-01

Congress and the Executive Branch have mandated that all branches of the Federal Government exert a concentrated effort to transfer appropriate government and government contractor-developed technology to the industrial use in the U.S. economy. For many years, NASA has had a formal technology transfer program to transmit information about new technologies developed for space applications into the industrial or commercial sector. Marshall Space Flight Center (MSFC) has been in the forefront of the development of U.S. industrial assistance programs using technologies developed at the Center. During 1992-93, MSFC initiated a technology transfer metrics study. The MSFC study was the first of its kind among the various NASA centers. The metrics study is a continuing process, with periodic updates that reflect on-going technology transfer activities.

Estimation of time-series properties of gourd observed solar irradiance data using cloud properties derived from satellite observations

NASA Astrophysics Data System (ADS)

Watanabe, T.; Nohara, D.

2017-12-01

The shorter temporal scale variation in the downward solar irradiance at the ground level (DSI) is not understood well because researches in the shorter-scale variation in the DSI is based on the ground observation and ground observation stations are located coarsely. Use of dataset derived from satellite observation will overcome such defect. DSI data and MODIS cloud properties product are analyzed simultaneously. Three metrics: mean, standard deviation and sample entropy, are used to evaluate time-series properties of the DSI. Three metrics are computed from two-hours time-series centered at the observation time of MODIS over the ground observation stations. We apply the regression methods to design prediction models of each three metrics from cloud properties. The validation of the model accuracy show that mean and standard deviation are predicted with a higher degree of accuracy and that the accuracy of prediction of sample entropy, which represents the complexity of time-series, is not high. One of causes of lower prediction skill of sample entropy is the resolution of the MODIS cloud properties. Higher sample entropy is corresponding to the rapid fluctuation, which is caused by the small and unordered cloud. It seems that such clouds isn't retrieved well.

Predicting dual-task performance with the Multiple Resources Questionnaire (MRQ).

PubMed

Boles, David B; Bursk, Jonathan H; Phillips, Jeffrey B; Perdelwitz, Jason R

2007-02-01

The objective was to assess the validity of the Multiple Resources Questionnaire (MRQ) in predicting dual-task interference. Subjective workload measures such as the Subjective Workload Assessment Technique (SWAT) and NASA Task Load Index are sensitive to single-task parameters and dual-task loads but have not attempted to measure workload in particular mental processes. An alternative is the MRQ. In Experiment 1, participants completed simple laboratory tasks and the MRQ after each. Interference between tasks was then correlated to three different task similarity metrics: profile similarity, based on r(2) between ratings; overlap similarity, based on summed minima; and overall demand, based on summed ratings. Experiment 2 used similar methods but more complex computer-based games. In Experiment 1 the MRQ moderately predicted interference (r = +.37), with no significant difference between metrics. In Experiment 2 the metric effect was significant, with overlap similarity excelling in predicting interference (r = +.83). Mean ratings showed high diagnosticity in identifying specific mental processing bottlenecks. The MRQ shows considerable promise as a cognitive-process-sensitive workload measure. Potential applications of the MRQ include the identification of dual-processing bottlenecks as well as process overloads in single tasks, preparatory to redesign in areas such as air traffic management, advanced flight displays, and medical imaging.

Social Media Metrics and Bibliometric Profiles of Neurosurgical Departments and Journals: Is There a Relationship?

PubMed

Alotaibi, Naif M; Guha, Daipayan; Fallah, Aria; Aldakkan, Abdulrahman; Nassiri, Farshad; Badhiwala, Jetan H; Ibrahim, George M; Shamji, Mohammed F; Macdonald, R Loch; Lozano, Andres M

2016-06-01

Social media plays an increasingly important role in dissemination of knowledge and raising awareness of selected topics among the general public and the academic community. To investigate the relationship between social media metrics and academic indices of neurosurgical programs and journals. A 2-step online search was performed to identify official social media accounts of neurosurgical departments that were accredited by the Accreditation Council for Graduate Medical Education and the Royal College of Physicians and Surgeons of Canada. Dedicated neurosurgery and spine journals' social media accounts also were identified through an online search on SCImago Journal and Country Rank portal. Nonparametric tests were performed with bootstrapping to compare groups and to look for correlations between social media and academic metrics. We identified 36 social media accounts officially affiliated with academic neurosurgical institutions. These accounts represented 22 of 119 neurosurgical programs in North America (18.4%). The presence of a social media account for neurosurgical departments was associated with statistically significant higher values of academic impact metrics (P < 0.05). Specific social media metrics for neurosurgical department accounts, however, did not correlate with any values of academic indices. For journals, there were 11 journals present on social media and had greater academic metrics compared with journals without social media presence (P < 0.05). Social media presence is associated with stronger academic bibliometrics profiles for both neurosurgical departments and journals. The impact of social media metrics on indices of scientific impact in neurosurgery is not known. Copyright © 2016 Elsevier Inc. All rights reserved.

In Transit...Making the Change to Metrics.

ERIC Educational Resources Information Center

Farnsworth, Briant J.; And Others

1980-01-01

Granite School District (Utah) developed a systematic, effective, and cost-efficient teacher inservice program which provides a basic understanding of metrics, materials and methods for direct classroom use, and evaluation of the learning process, through the use of self-contained, three-phase modules for home or school use. (Author/SB)

Clean Cities 2010 Annual Metrics Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, C.

2012-10-01

This report details the petroleum savings and vehicle emissions reductions achieved by the U.S. Department of Energy's Clean Cities program in 2010. The report also details other performance metrics, including the number of stakeholders in Clean Cities coalitions, outreach activities by coalitions and national laboratories, and alternative fuel vehicles deployed.

Clean Cities 2011 Annual Metrics Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, C.

2012-12-01

This report details the petroleum savings and vehicle emissions reductions achieved by the U.S. Department of Energy's Clean Cities program in 2011. The report also details other performance metrics, including the number of stakeholders in Clean Cities coalitions, outreach activities by coalitions and national laboratories, and alternative fuel vehicles deployed.

Metric System.

ERIC Educational Resources Information Center

Del Mod System, Dover, DE.

This autoinstructional unit deals with the identification of units of measure in the metric system and the construction of relevant conversion tables. Students in middle school or in grade ten, taking a General Science course, can handle this learning activity. It is recommended that high, middle or low level achievers can use the program.…

Identification of the ideal clutter metric to predict time dependence of human visual search

NASA Astrophysics Data System (ADS)

Cartier, Joan F.; Hsu, David H.

1995-05-01

The Army Night Vision and Electronic Sensors Directorate (NVESD) has recently performed a human perception experiment in which eye tracker measurements were made on trained military observers searching for targets in infrared images. This data offered an important opportunity to evaluate a new technique for search modeling. Following the approach taken by Jeff Nicoll, this model treats search as a random walk in which the observers are in one of two states until they quit: they are either searching, or they are wandering around looking for a point of interest. When wandering they skip rapidly from point to point. When examining they move more slowly, reflecting the fact that target discrimination requires additional thought processes. In this paper we simulate the random walk, using a clutter metric to assign relative attractiveness to points of interest within the image which are competing for the observer's attention. The NVESD data indicates that a number of standard clutter metrics are good estimators of the apportionment of observer's time between wandering and examining. Conversely, the apportionment of observer time spent wandering and examining could be used to reverse engineer the ideal clutter metric which would most perfectly describe the behavior of the group of observers. It may be possible to use this technique to design the optimal clutter metric to predict performance of visual search.

Eyetracking Metrics in Young Onset Alzheimer’s Disease: A Window into Cognitive Visual Functions

PubMed Central

Pavisic, Ivanna M.; Firth, Nicholas C.; Parsons, Samuel; Rego, David Martinez; Shakespeare, Timothy J.; Yong, Keir X. X.; Slattery, Catherine F.; Paterson, Ross W.; Foulkes, Alexander J. M.; Macpherson, Kirsty; Carton, Amelia M.; Alexander, Daniel C.; Shawe-Taylor, John; Fox, Nick C.; Schott, Jonathan M.; Crutch, Sebastian J.; Primativo, Silvia

2017-01-01

Young onset Alzheimer’s disease (YOAD) is defined as symptom onset before the age of 65 years and is particularly associated with phenotypic heterogeneity. Atypical presentations, such as the clinic-radiological visual syndrome posterior cortical atrophy (PCA), often lead to delays in accurate diagnosis. Eyetracking has been used to demonstrate basic oculomotor impairments in individuals with dementia. In the present study, we aim to explore the relationship between eyetracking metrics and standard tests of visual cognition in individuals with YOAD. Fifty-seven participants were included: 36 individuals with YOAD (n = 26 typical AD; n = 10 PCA) and 21 age-matched healthy controls. Participants completed three eyetracking experiments: fixation, pro-saccade, and smooth pursuit tasks. Summary metrics were used as outcome measures and their predictive value explored looking at correlations with visuoperceptual and visuospatial metrics. Significant correlations between eyetracking metrics and standard visual cognitive estimates are reported. A machine-learning approach using a classification method based on the smooth pursuit raw eyetracking data discriminates with approximately 95% accuracy patients and controls in cross-validation tests. Results suggest that the eyetracking paradigms of a relatively simple and specific nature provide measures not only reflecting basic oculomotor characteristics but also predicting higher order visuospatial and visuoperceptual impairments. Eyetracking measures can represent extremely useful markers during the diagnostic phase and may be exploited as potential outcome measures for clinical trials. PMID:28824534

Eyetracking Metrics in Young Onset Alzheimer's Disease: A Window into Cognitive Visual Functions.

PubMed

Pavisic, Ivanna M; Firth, Nicholas C; Parsons, Samuel; Rego, David Martinez; Shakespeare, Timothy J; Yong, Keir X X; Slattery, Catherine F; Paterson, Ross W; Foulkes, Alexander J M; Macpherson, Kirsty; Carton, Amelia M; Alexander, Daniel C; Shawe-Taylor, John; Fox, Nick C; Schott, Jonathan M; Crutch, Sebastian J; Primativo, Silvia

2017-01-01

Young onset Alzheimer's disease (YOAD) is defined as symptom onset before the age of 65 years and is particularly associated with phenotypic heterogeneity. Atypical presentations, such as the clinic-radiological visual syndrome posterior cortical atrophy (PCA), often lead to delays in accurate diagnosis. Eyetracking has been used to demonstrate basic oculomotor impairments in individuals with dementia. In the present study, we aim to explore the relationship between eyetracking metrics and standard tests of visual cognition in individuals with YOAD. Fifty-seven participants were included: 36 individuals with YOAD ( n  = 26 typical AD; n  = 10 PCA) and 21 age-matched healthy controls. Participants completed three eyetracking experiments: fixation, pro-saccade, and smooth pursuit tasks. Summary metrics were used as outcome measures and their predictive value explored looking at correlations with visuoperceptual and visuospatial metrics. Significant correlations between eyetracking metrics and standard visual cognitive estimates are reported. A machine-learning approach using a classification method based on the smooth pursuit raw eyetracking data discriminates with approximately 95% accuracy patients and controls in cross-validation tests. Results suggest that the eyetracking paradigms of a relatively simple and specific nature provide measures not only reflecting basic oculomotor characteristics but also predicting higher order visuospatial and visuoperceptual impairments. Eyetracking measures can represent extremely useful markers during the diagnostic phase and may be exploited as potential outcome measures for clinical trials.

An algorithmic and information-theoretic approach to multimetric index construction

USGS Publications Warehouse

Schoolmaster, Donald R.; Grace, James B.; Schweiger, E. William; Guntenspergen, Glenn R.; Mitchell, Brian R.; Miller, Kathryn M.; Little, Amanda M.

2013-01-01

The use of multimetric indices (MMIs), such as the widely used index of biological integrity (IBI), to measure, track, summarize and infer the overall impact of human disturbance on biological communities has been steadily growing in recent years. Initially, MMIs were developed for aquatic communities using pre-selected biological metrics as indicators of system integrity. As interest in these bioassessment tools has grown, so have the types of biological systems to which they are applied. For many ecosystem types the appropriate biological metrics to use as measures of biological integrity are not known a priori. As a result, a variety of ad hoc protocols for selecting metrics empirically has developed. However, the assumptions made by proposed protocols have not be explicitly described or justified, causing many investigators to call for a clear, repeatable methodology for developing empirically derived metrics and indices that can be applied to any biological system. An issue of particular importance that has not been sufficiently addressed is the way that individual metrics combine to produce an MMI that is a sensitive composite indicator of human disturbance. In this paper, we present and demonstrate an algorithm for constructing MMIs given a set of candidate metrics and a measure of human disturbance. The algorithm uses each metric to inform a candidate MMI, and then uses information-theoretic principles to select MMIs that capture the information in the multidimensional system response from among possible MMIs. Such an approach can be used to create purely empirical (data-based) MMIs or can, optionally, be influenced by expert opinion or biological theory through the use of a weighting vector to create value-weighted MMIs. We demonstrate the algorithm with simulated data to demonstrate the predictive capacity of the final MMIs and with real data from wetlands from Acadia and Rocky Mountain National Parks. For the Acadia wetland data, the algorithm identified 4 metrics that combined to produce a -0.88 correlation with the human disturbance index. When compared to other methods, we find this algorithmic approach resulted in MMIs that were more predictive and comprise fewer metrics.

Comparison and statistical analysis of four write stability metrics in bulk CMOS static random access memory cells

NASA Astrophysics Data System (ADS)

Qiu, Hao; Mizutani, Tomoko; Saraya, Takuya; Hiramoto, Toshiro

2015-04-01

The commonly used four metrics for write stability were measured and compared based on the same set of 2048 (2k) six-transistor (6T) static random access memory (SRAM) cells by the 65 nm bulk technology. The preferred one should be effective for yield estimation and help predict edge of stability. Results have demonstrated that all metrics share the same worst SRAM cell. On the other hand, compared to butterfly curve with non-normality and write N-curve where no cell state flip happens, bit-line and word-line margins have good normality as well as almost perfect correlation. As a result, both bit line method and word line method prove themselves preferred write stability metrics.

Models of Marine Fish Biodiversity: Assessing Predictors from Three Habitat Classification Schemes.

PubMed

Yates, Katherine L; Mellin, Camille; Caley, M Julian; Radford, Ben T; Meeuwig, Jessica J

2016-01-01

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modelling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modelling metrics of fish biodiversity that are not fully captured by remotely sensed data. As such, the use of remotely sensed data to model biodiversity represents a compromise between model performance and data availability.

Models of Marine Fish Biodiversity: Assessing Predictors from Three Habitat Classification Schemes

PubMed Central

Yates, Katherine L.; Mellin, Camille; Caley, M. Julian; Radford, Ben T.; Meeuwig, Jessica J.

2016-01-01

Prioritising biodiversity conservation requires knowledge of where biodiversity occurs. Such knowledge, however, is often lacking. New technologies for collecting biological and physical data coupled with advances in modelling techniques could help address these gaps and facilitate improved management outcomes. Here we examined the utility of environmental data, obtained using different methods, for developing models of both uni- and multivariate biodiversity metrics. We tested which biodiversity metrics could be predicted best and evaluated the performance of predictor variables generated from three types of habitat data: acoustic multibeam sonar imagery, predicted habitat classification, and direct observer habitat classification. We used boosted regression trees (BRT) to model metrics of fish species richness, abundance and biomass, and multivariate regression trees (MRT) to model biomass and abundance of fish functional groups. We compared model performance using different sets of predictors and estimated the relative influence of individual predictors. Models of total species richness and total abundance performed best; those developed for endemic species performed worst. Abundance models performed substantially better than corresponding biomass models. In general, BRT and MRTs developed using predicted habitat classifications performed less well than those using multibeam data. The most influential individual predictor was the abiotic categorical variable from direct observer habitat classification and models that incorporated predictors from direct observer habitat classification consistently outperformed those that did not. Our results show that while remotely sensed data can offer considerable utility for predictive modelling, the addition of direct observer habitat classification data can substantially improve model performance. Thus it appears that there are aspects of marine habitats that are important for modelling metrics of fish biodiversity that are not fully captured by remotely sensed data. As such, the use of remotely sensed data to model biodiversity represents a compromise between model performance and data availability. PMID:27333202

Physiologically grounded metrics of model skill: a case study estimating heat stress in intertidal populations

PubMed Central

Kish, Nicole E.; Helmuth, Brian; Wethey, David S.

2016-01-01

Models of ecological responses to climate change fundamentally assume that predictor variables, which are often measured at large scales, are to some degree diagnostic of the smaller-scale biological processes that ultimately drive patterns of abundance and distribution. Given that organisms respond physiologically to stressors, such as temperature, in highly non-linear ways, small modelling errors in predictor variables can potentially result in failures to predict mortality or severe stress, especially if an organism exists near its physiological limits. As a result, a central challenge facing ecologists, particularly those attempting to forecast future responses to environmental change, is how to develop metrics of forecast model skill (the ability of a model to predict defined events) that are biologically meaningful and reflective of underlying processes. We quantified the skill of four simple models of body temperature (a primary determinant of physiological stress) of an intertidal mussel, Mytilus californianus, using common metrics of model performance, such as root mean square error, as well as forecast verification skill scores developed by the meteorological community. We used a physiologically grounded framework to assess each model's ability to predict optimal, sub-optimal, sub-lethal and lethal physiological responses. Models diverged in their ability to predict different levels of physiological stress when evaluated using skill scores, even though common metrics, such as root mean square error, indicated similar accuracy overall. Results from this study emphasize the importance of grounding assessments of model skill in the context of an organism's physiology and, especially, of considering the implications of false-positive and false-negative errors when forecasting the ecological effects of environmental change. PMID:27729979

Benefits of Sharing Information: Supermodel Ensemble and Applications in South America

NASA Astrophysics Data System (ADS)

Dias, P. L.

2006-05-01

A model intercomparison program involving a large number of academic and operational institutions has been implemented in South America since 2003, motivated by the SALLJEX Intercomparison Program in 2003 (a research program focused on the identification of the role of the Andes low level jet moisture transport from the Amazon to the Plata basin) and the WMO/THORPEX (www.wmo.int/thorpex) goals to improve predictability through the proper combination of numerical weather forecasts. This program also explores the potential predictability associated with the combination of a large number of possible scenarios in the time scale of a few days to up to 15 days. Five academic institutions and five operational forecasting centers in several countries in South America, 1 academic institution in the USA, and the main global forecasting centers (NCEP, UKMO, ECMWF) agreed to provide numerical products based on operational and experimental models. The metric for model validation is concentrated on the fit of the forecast to surface observations. Meteorological data from airports, synoptic stations operated by national weather services, automatic data platforms maintained by different institutions, the PIRATA buoys etc are all collected through LDM/NCAR or direct transmission. Approximately 40 models outputs are available on a daily basis, twice a day. A simple procedure based on data assimilation principles was quite successful in combining the available forecasts in order to produce temperature, dew point, wind, pressure and precipitation forecasts at station points in S. America. The procedure is based on removing each model bias at the observational point and a weighted average based on the mean square error of the forecasts. The base period for estimating the bias and mean square error is of the order of 15 to 30 days. Products of the intercomparison model program and the optimal statistical combination of the available forecasts are public and available in real time (www.master.iag.usp.br/). Monitoring of the use of the products reveal a growing trend in the last year (reaching about 10.000 accesses per day in recent months). The intercomparison program provides a rich data set for educational products (real time use in Synoptic Meteorology and Numerical Weather Forecasting lectures), operational weather forecasts in national or regional weather centers and for research purposes. During the first phase of the program it was difficult to convince potential participants to share the information in the public homepage. However, as the system evolved, more and more institutions became associated with the program. The general opinion of the participants is that the system provides an unified metric for evaluation, a forum for discussion of the physical origin of the model forecast differences and therefore improvement of the quality of the numerical guidance.

Predicting age from cortical structure across the lifespan.

PubMed

Madan, Christopher R; Kensinger, Elizabeth A

2018-03-01

Despite interindividual differences in cortical structure, cross-sectional and longitudinal studies have demonstrated a large degree of population-level consistency in age-related differences in brain morphology. This study assessed how accurately an individual's age could be predicted by estimates of cortical morphology, comparing a variety of structural measures, including thickness, gyrification and fractal dimensionality. Structural measures were calculated across up to seven different parcellation approaches, ranging from one region to 1000 regions. The age prediction framework was trained using morphological measures obtained from T1-weighted MRI volumes collected from multiple sites, yielding a training dataset of 1056 healthy adults, aged 18-97. Age predictions were calculated using a machine-learning approach that incorporated nonlinear differences over the lifespan. In two independent, held-out test samples, age predictions had a median error of 6-7 years. Age predictions were best when using a combination of cortical metrics, both thickness and fractal dimensionality. Overall, the results reveal that age-related differences in brain structure are systematic enough to enable reliable age prediction based on metrics of cortical morphology. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Gaining Control and Predictability of Software-Intensive Systems Development and Sustainment

DTIC Science & Technology

2015-02-04

implementation of the baselines, audits , and technical reviews within an overarching systems engineering process (SEP; Defense Acquisition University...warfighters’ needs. This management and metrics effort supplements and supports the system’s technical development through the baselines, audits and...other areas that could be researched and added into the nine-tier model. Areas including software metrics, quality assurance , software-oriented

Predicting a contact's sensitivity to initial conditions using metrics of frictional coupling

DOE PAGES

Flicek, Robert C.; Hills, David A.; Brake, Matthew Robert W.

2016-09-29

This paper presents a method for predicting how sensitive a frictional contact’s steady-state behavior is to its initial conditions. Previous research has proven that if a contact is uncoupled, i.e. if slip displacements do not influence the contact pressure distribution, then its steady-state response is independent of initial conditions, but if the contact is coupled, the steady-state response depends on initial conditions. In this paper, two metrics for quantifying coupling in discrete frictional systems are examined. These metrics suggest that coupling is dominated by material dissimilarity due to Dundurs’ composite material parameter β when β ≥ 0.2, but geometric mismatchmore » becomes the dominant source of coupling for smaller values of β. Based on a large set of numerical simulations with different contact geometries, material combinations, and friction coefficients, a contact’s sensitivity to initial conditions is found to be correlated with the product of the coupling metric and the friction coefficient. For cyclic shear loading, this correlation is maintained for simulations with different contact geometries, material combinations, and friction coefficients. Furthermore, for cyclic bulk loading, the correlation is only maintained when the contact edge angle is held constant.« less

Predicting a contact's sensitivity to initial conditions using metrics of frictional coupling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flicek, Robert C.; Hills, David A.; Brake, Matthew Robert W.

This paper presents a method for predicting how sensitive a frictional contact’s steady-state behavior is to its initial conditions. Previous research has proven that if a contact is uncoupled, i.e. if slip displacements do not influence the contact pressure distribution, then its steady-state response is independent of initial conditions, but if the contact is coupled, the steady-state response depends on initial conditions. In this paper, two metrics for quantifying coupling in discrete frictional systems are examined. These metrics suggest that coupling is dominated by material dissimilarity due to Dundurs’ composite material parameter β when β ≥ 0.2, but geometric mismatchmore » becomes the dominant source of coupling for smaller values of β. Based on a large set of numerical simulations with different contact geometries, material combinations, and friction coefficients, a contact’s sensitivity to initial conditions is found to be correlated with the product of the coupling metric and the friction coefficient. For cyclic shear loading, this correlation is maintained for simulations with different contact geometries, material combinations, and friction coefficients. Furthermore, for cyclic bulk loading, the correlation is only maintained when the contact edge angle is held constant.« less

Responses of benthic macroinvertebrates to urbanization in nine metropolitan areas of the conterminous United States

USGS Publications Warehouse

Cuffney, T.F.; McMahon, G.; Kashuba, R.; May, J.T.; Waite, I.R.

2009-01-01

The effects of urbanization on benthic macroinvertebrates were investigated in nine metropolitan areas (Boston, MA; Raleigh, NC; Atlanta, GA; Birmingham, AL; Milwaukee–Green Bay, WI; Denver, CO; Dallas–Fort Worth, TX; Salt Lake City, UT; and Portland, OR) as a part of the U.S. Geological Survey National Water Quality Assessment Program. Several invertebrate metrics showed strong, linear responses to urbanization when forest or shrublands were developed. Responses were difficult to discern in areas where urbanization was occurring on agricultural lands because invertebrate assemblages were already severely degraded. There was no evidence that assemblages showed any initial resistance to urbanization. Ordination scores, EPT taxa richness, and the average tolerance of organisms were the best indicators of changes in assemblage condition at a site. Richness metrics were better indicators than abundance metrics, and qualitative samples were as good as quantitative samples. A common set of landscape variables (population density, housing density, developed landcover, impervious surface, and roads) were strongly correlated with urbanization and invertebrate responses in all non-agricultural areas. The instream environmental variables (hydrology, water chemistry, habitat, and temperature) that were strongly correlated with urbanization and invertebrate responses were influenced by environmental setting (e.g., dominant ecoregion) and varied widely among metropolitan areas. Multilevel hierarchical regression models were developed that predicted invertebrate responses using only two landcover variables—basinscale landcover (percentage of basin area in developed land) and regional-scale landcover (antecedent agricultural land).

Universe without dark energy: Cosmic acceleration from dark matter-baryon interactions

NASA Astrophysics Data System (ADS)

Berezhiani, Lasha; Khoury, Justin; Wang, Junpu

2017-06-01

Cosmic acceleration is widely believed to require either a source of negative pressure (i.e., dark energy), or a modification of gravity, which necessarily implies new degrees of freedom beyond those of Einstein gravity. In this paper we present a third possibility, using only dark matter (DM) and ordinary matter. The mechanism relies on the coupling between dark matter and ordinary matter through an effective metric. Dark matter couples to an Einstein-frame metric, and experiences a matter-dominated, decelerating cosmology up to the present time. Ordinary matter couples to an effective metric that depends also on the DM density, in such a way that it experiences late-time acceleration. Linear density perturbations are stable and propagate with arbitrarily small sound speed, at least in the case of "pressure" coupling. Assuming a simple parametrization of the effective metric, we show that our model can successfully match a set of basic cosmological observables, including luminosity distance, baryon acoustic oscillation measurements, angular-diameter distance to last scattering, etc. For the growth history of density perturbations, we find an intriguing connection between the growth factor and the Hubble constant. To get a growth history similar to the Λ CDM prediction, our model predicts a higher H0, closer to the value preferred by direct estimates. On the flip side, we tend to overpredict the growth of structures whenever H0 is comparable to the Planck preferred value. The model also tends to predict larger redshift-space distortions at low redshift than Λ CDM .

Graph Metrics of Structural Brain Networks in Individuals with Schizophrenia and Healthy Controls: Group Differences, Relationships with Intelligence, and Genetics.

PubMed

Yeo, Ronald A; Ryman, Sephira G; van den Heuvel, Martijn P; de Reus, Marcel A; Jung, Rex E; Pommy, Jessica; Mayer, Andrew R; Ehrlich, Stefan; Schulz, S Charles; Morrow, Eric M; Manoach, Dara; Ho, Beng-Choon; Sponheim, Scott R; Calhoun, Vince D

2016-02-01

One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia. Participants (N=116 controls, 80 patients with schizophrenia) were recruited from four sites. GCA was represented by the first principal component of a large battery of neurocognitive tests. Graph metrics were derived from diffusion-weighted imaging. The global metrics of longer characteristic path length and reduced overall connectivity predicted lower GCA across groups, and group differences were noted for both variables. Measures of clustering, efficiency, and modularity did not differ across groups or predict GCA. Follow-up analyses investigated three topological types of connectivity--connections among high degree "rich club" nodes, "feeder" connections to these rich club nodes, and "local" connections not involving the rich club. Rich club and local connectivity predicted performance across groups. In a subsample (N=101 controls, 56 patients), a genetic measure reflecting mutation load, based on rare copy number deletions, was associated with longer characteristic path length. Results highlight the importance of characteristic path lengths and rich club connectivity for GCA and provide no evidence for group differences in the relationships between graph metrics and GCA.

On the relationship between tumour growth rate and survival in non-small cell lung cancer.

PubMed

Mistry, Hitesh B

2017-01-01

A recurrent question within oncology drug development is predicting phase III outcome for a new treatment using early clinical data. One approach to tackle this problem has been to derive metrics from mathematical models that describe tumour size dynamics termed re-growth rate and time to tumour re-growth. They have shown to be strong predictors of overall survival in numerous studies but there is debate about how these metrics are derived and if they are more predictive than empirical end-points. This work explores the issues raised in using model-derived metric as predictors for survival analyses. Re-growth rate and time to tumour re-growth were calculated for three large clinical studies by forward and reverse alignment. The latter involves re-aligning patients to their time of progression. Hence, it accounts for the time taken to estimate re-growth rate and time to tumour re-growth but also assesses if these predictors correlate to survival from the time of progression. I found that neither re-growth rate nor time to tumour re-growth correlated to survival using reverse alignment. This suggests that the dynamics of tumours up until disease progression has no relationship to survival post progression. For prediction of a phase III trial I found the metrics performed no better than empirical end-points. These results highlight that care must be taken when relating dynamics of tumour imaging to survival and that bench-marking new approaches to existing ones is essential.

Diagnosing Undersampling Biases in Monte Carlo Eigenvalue and Flux Tally Estimates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perfetti, Christopher M.; Rearden, Bradley T.; Marshall, William J.

2017-02-08

Here, this study focuses on understanding the phenomena in Monte Carlo simulations known as undersampling, in which Monte Carlo tally estimates may not encounter a sufficient number of particles during each generation to obtain unbiased tally estimates. Steady-state Monte Carlo simulations were performed using the KENO Monte Carlo tools within the SCALE code system for models of several burnup credit applications with varying degrees of spatial and isotopic complexities, and the incidence and impact of undersampling on eigenvalue and flux estimates were examined. Using an inadequate number of particle histories in each generation was found to produce a maximum bias of ~100 pcm in eigenvalue estimates and biases that exceeded 10% in fuel pin flux tally estimates. Having quantified the potential magnitude of undersampling biases in eigenvalue and flux tally estimates in these systems, this study then investigated whether Markov Chain Monte Carlo convergence metrics could be integrated into Monte Carlo simulations to predict the onset and magnitude of undersampling biases. Five potential metrics for identifying undersampling biases were implemented in the SCALE code system and evaluated for their ability to predict undersampling biases by comparing the test metric scores with the observed undersampling biases. Finally, of the five convergence metrics that were investigated, three (the Heidelberger-Welch relative half-width, the Gelman-Rubin more » $$\\hat{R}_c$$ diagnostic, and tally entropy) showed the potential to accurately predict the behavior of undersampling biases in the responses examined.« less

Economic Metrics for Commercial Reusable Space Transportation Systems

NASA Technical Reports Server (NTRS)

Shaw, Eric J.; Hamaker, Joseph (Technical Monitor)

2000-01-01

The success of any effort depends upon the effective initial definition of its purpose, in terms of the needs to be satisfied and the goals to be fulfilled. If the desired product is "A System" that is well-characterized, these high-level need and goal statements can be transformed into system requirements by traditional systems engineering techniques. The satisfaction of well-designed requirements can be tracked by fairly straightforward cost, schedule, and technical performance metrics. Unfortunately, some types of efforts, including those that NASA terms "Programs," tend to resist application of traditional systems engineering practices. In the NASA hierarchy of efforts, a "Program" is often an ongoing effort with broad, high-level goals and objectives. A NASA "project" is a finite effort, in terms of budget and schedule, that usually produces or involves one System. Programs usually contain more than one project and thus more than one System. Special care must be taken in the formulation of NASA Programs and their projects, to ensure that lower-level project requirements are traceable to top-level Program goals, feasible with the given cost and schedule constraints, and measurable against top-level goals. NASA Programs and projects are tasked to identify the advancement of technology as an explicit goal, which introduces more complicating factors. The justification for funding of technology development may be based on the technology's applicability to more than one System, Systems outside that Program or even external to NASA. Application of systems engineering to broad-based technology development, leading to effective measurement of the benefits, can be valid, but it requires that potential beneficiary Systems be organized into a hierarchical structure, creating a "system of Systems." In addition, these Systems evolve with the successful application of the technology, which creates the necessity for evolution of the benefit metrics to reflect the changing baseline. Still, economic metrics for technology development in these Programs and projects remain fairly straightforward, being based on reductions in acquisition and operating costs of the Systems. One of the most challenging requirements that NASA levies on its Programs is to plan for the commercialization of the developed technology. Some NASA Programs are created for the express purpose of developing technology for a particular industrial sector, such as aviation or space transportation, in financial partnership with that sector. With industrial investment, another set of goals, constraints and expectations are levied on the technology program. Economic benefit metrics then expand beyond cost and cost savings to include the marketability, profit, and investment return requirements of the private sector. Commercial investment criteria include low risk, potential for high return, and strategic alignment with existing product lines. These corporate criteria derive from top-level strategic plans and investment goals, which rank high among the most proprietary types of information in any business. As a result, top-level economic goals and objectives that industry partners bring to cooperative programs cannot usually be brought into technical processes, such as systems engineering, that are worked collaboratively between Industry and Government. In spite of these handicaps, the top-level economic goals and objectives of a joint technology program can be crafted in such a way that they accurately reflect the fiscal benefits from both Industry and Government perspectives. Valid economic metrics can then be designed that can track progress toward these goals and objectives, while maintaining the confidentiality necessary for the competitive process.

Performance of five surface energy balance models for estimating daily evapotranspiration in high biomass sorghum

NASA Astrophysics Data System (ADS)

Wagle, Pradeep; Bhattarai, Nishan; Gowda, Prasanna H.; Kakani, Vijaya G.

2017-06-01

Robust evapotranspiration (ET) models are required to predict water usage in a variety of terrestrial ecosystems under different geographical and agrometeorological conditions. As a result, several remote sensing-based surface energy balance (SEB) models have been developed to estimate ET over large regions. However, comparison of the performance of several SEB models at the same site is limited. In addition, none of the SEB models have been evaluated for their ability to predict ET in rain-fed high biomass sorghum grown for biofuel production. In this paper, we evaluated the performance of five widely used single-source SEB models, namely Surface Energy Balance Algorithm for Land (SEBAL), Mapping ET with Internalized Calibration (METRIC), Surface Energy Balance System (SEBS), Simplified Surface Energy Balance Index (S-SEBI), and operational Simplified Surface Energy Balance (SSEBop), for estimating ET over a high biomass sorghum field during the 2012 and 2013 growing seasons. The predicted ET values were compared against eddy covariance (EC) measured ET (ETEC) for 19 cloud-free Landsat image. In general, S-SEBI, SEBAL, and SEBS performed reasonably well for the study period, while METRIC and SSEBop performed poorly. All SEB models substantially overestimated ET under extremely dry conditions as they underestimated sensible heat (H) and overestimated latent heat (LE) fluxes under dry conditions during the partitioning of available energy. METRIC, SEBAL, and SEBS overestimated LE regardless of wet or dry periods. Consequently, predicted seasonal cumulative ET by METRIC, SEBAL, and SEBS were higher than seasonal cumulative ETEC in both seasons. In contrast, S-SEBI and SSEBop substantially underestimated ET under too wet conditions, and predicted seasonal cumulative ET by S-SEBI and SSEBop were lower than seasonal cumulative ETEC in the relatively wetter 2013 growing season. Our results indicate the necessity of inclusion of soil moisture or plant water stress component in SEB models for the improvement of their performance, especially under too dry or wet environments.

Bayesian performance metrics and small system integration in recent homeland security and defense applications

NASA Astrophysics Data System (ADS)

Jannson, Tomasz; Kostrzewski, Andrew; Patton, Edward; Pradhan, Ranjit; Shih, Min-Yi; Walter, Kevin; Savant, Gajendra; Shie, Rick; Forrester, Thomas

2010-04-01

In this paper, Bayesian inference is applied to performance metrics definition of the important class of recent Homeland Security and defense systems called binary sensors, including both (internal) system performance and (external) CONOPS. The medical analogy is used to define the PPV (Positive Predictive Value), the basic Bayesian metrics parameter of the binary sensors. Also, Small System Integration (SSI) is discussed in the context of recent Homeland Security and defense applications, emphasizing a highly multi-technological approach, within the broad range of clusters ("nexus") of electronics, optics, X-ray physics, γ-ray physics, and other disciplines.

Disconnection of network hubs and cognitive impairment after traumatic brain injury.

PubMed

Fagerholm, Erik D; Hellyer, Peter J; Scott, Gregory; Leech, Robert; Sharp, David J

2015-06-01

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R(2) = 0.64), executive function (R(2) = 0.56) and associative memory (R(2) = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain.

Evaluation of developmental metrics for utilization in a pediatric advanced automatic crash notification algorithm.

PubMed

Doud, Andrea N; Weaver, Ashley A; Talton, Jennifer W; Barnard, Ryan T; Petty, John; Stitzel, Joel D

2016-01-01

Appropriate treatment at designated trauma centers (TCs) improves outcomes among injured children after motor vehicle crashes (MVCs). Advanced Automatic Crash Notification (AACN) has shown promise in improving triage to appropriate TCs. Pediatric-specific AACN algorithms have not yet been created. To create such an algorithm, it will be necessary to include some metric of development (age, height, or weight) as a covariate in the injury risk algorithm. This study sought to determine which marker of development should serve as a covariate in such an algorithm and to quantify injury risk at different levels of this metric. A retrospective review of occupants age < 19 years within the MVC data set NASS-CDS 2000-2011 was performed. R(2) values of logistic regression models using age, height, or weight to predict 18 key injury types were compared to determine which metric should be used as a covariate in a pediatric AACN algorithm. Clinical judgment, literature review, and chi-square analysis were used to create groupings of the chosen metric that would discriminate injury patterns. Adjusted odds of particular injury types at the different levels of this metric were calculated from logistic regression while controlling for gender, vehicle velocity change (delta V), belted status (optimal, suboptimal, or unrestrained), and crash mode (rollover, rear, frontal, near-side, or far-side). NASS-CDS analysis produced 11,541 occupants age < 19 years with nonmissing data. Age, height, and weight were correlated with one another and with injury patterns. Age demonstrated the best predictive power in injury patterns and was categorized into bins of 0-4 years, 5-9 years, 10-14 years, and 15-18 years. Age was a significant predictor of all 18 injury types evaluated even when controlling for all other confounders and when controlling for age- and gender-specific body mass index (BMI) classifications. Adjusted odds of key injury types with respect to these age categorizations revealed that younger children were at increased odds of sustaining Abbreviated Injury Scale (AIS) 2+ and 3+ head injuries and AIS 3+ spinal injuries, whereas older children were at increased odds of sustaining thoracic fractures, AIS 3+ abdominal injuries, and AIS 2+ upper and lower extremity injuries. The injury patterns observed across developmental metrics in this study mirror those previously described among children with blunt trauma. This study identifies age as the metric best suited for use in a pediatric AACN algorithm and utilizes 12 years of data to provide quantifiable risks of particular injuries at different levels of this metric. This risk quantification will have important predictive purposes in a pediatric-specific AACN algorithm.

CLIVAR Asian-Australian Monsoon Panel Report to Scientific Steering Group-18

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sperber, Ken R.; Hendon, Harry H.

2011-05-04

These are a set of slides on CLIVAR Asian-Australian Monsoon Panel Report to Scientific Steering Group-18. These are the major topics covered within: major activities over the past year, AAMP Monsoon Diagnostics/Metrics Task Team, Boreal Summer Asian Monsoon, Workshop on Modelling Monsoon Intraseasonal Variability, Workshop on Interdecadal Variability and Predictability of the Asian-Australian Monsoon, Evidence of Interdecadal Variability of the Asian-Australian Monsoon, Development of MJO metrics/process-oriented diagnostics/model evaluation/prediction with MJOTF and GCSS, YOTC MJOTF, GEWEX GCSS, AAMP MJO Diabatic Heating Experiment, Hindcast Experiment for Intraseasonal Prediction, Support and Coordination for CINDY2011/DYNAMO, Outreach to CORDEX, Interaction with FOCRAII, WWRP/WCRP Multi-Week Predictionmore » Project, Major Future Plans/Activities, Revised AAMP Terms of Reference, Issues and Challenges.« less

Aligning compensation with education: design and implementation of the Educational Value Unit (EVU) system in an academic internal medicine department.

PubMed

Stites, Steven; Vansaghi, Lisa; Pingleton, Susan; Cox, Glendon; Paolo, Anthony

2005-12-01

The authors report the development of a new metric for distributing university funds to support faculty efforts in education in the department of internal medicine at the University of Kansas School of Medicine. In 2003, a committee defined the educational value unit (EVU), which describes and measures the specific types of educational work done by faculty members, such as core education, clinical teaching, and administration of educational programs. The specific work profile of each faculty member was delineated. A dollar value was calculated for each 0.1 EVU. The metric was prospectively applied and a faculty survey was performed to evaluate the faculty's perception of the metric. Application of the metric resulted in a decrease in university support for 34 faculty and an increase in funding for 23 faculty. Total realignment of funding was US$1.6 million, or an absolute value of US$29,072 +/- 38,320.00 in average shift of university salary support per faculty member. Survey results showed that understanding of the purpose of university funding was enhanced, and that faculty members perceived a more equitable alignment of teaching effort with funding. The EVU metric resulted in a dramatic realignment of university funding for educational efforts in the department of internal medicine. The metric was easily understood, quickly implemented, and perceived to be fair by the faculty. By aligning specific salary support with faculty's educational responsibilities, a foundation was created for applying mission-based incentive programs.

Zone calculation as a tool for assessing performance outcome in laparoscopic suturing.

PubMed

Buckley, Christina E; Kavanagh, Dara O; Nugent, Emmeline; Ryan, Donncha; Traynor, Oscar J; Neary, Paul C

2015-06-01

Simulator performance is measured by metrics, which are valued as an objective way of assessing trainees. Certain procedures such as laparoscopic suturing, however, may not be suitable for assessment under traditionally formulated metrics. Our aim was to assess if our new metric is a valid method of assessing laparoscopic suturing. A software program was developed to order to create a new metric, which would calculate the percentage of time spent operating within pre-defined areas called "zones." Twenty-five candidates (medical students N = 10, surgical residents N = 10, and laparoscopic experts N = 5) performed the laparoscopic suturing task on the ProMIS III(®) simulator. New metrics of "in-zone" and "out-zone" scores as well as traditional metrics of time, path length, and smoothness were generated. Performance was also assessed by two blinded observers using the OSATS and FLS rating scales. This novel metric was evaluated by comparing it to both traditional metrics and subjective scores. There was a significant difference in the average in-zone and out-zone scores between all three experience groups (p < 0.05). The new zone metrics scores correlated significantly with the subjective-blinded observer scores of OSATS and FLS (p = 0.0001). The new zone metric scores also correlated significantly with the traditional metrics of path length, time, and smoothness (p < 0.05). The new metric is a valid tool for assessing laparoscopic suturing objectively. This could be incorporated into a competency-based curriculum to monitor resident progression in the simulated setting.

Quantifying and estimating the predictive accuracy for censored time-to-event data with competing risks.

PubMed

Wu, Cai; Li, Liang

2018-05-15

This paper focuses on quantifying and estimating the predictive accuracy of prognostic models for time-to-event outcomes with competing events. We consider the time-dependent discrimination and calibration metrics, including the receiver operating characteristics curve and the Brier score, in the context of competing risks. To address censoring, we propose a unified nonparametric estimation framework for both discrimination and calibration measures, by weighting the censored subjects with the conditional probability of the event of interest given the observed data. The proposed method can be extended to time-dependent predictive accuracy metrics constructed from a general class of loss functions. We apply the methodology to a data set from the African American Study of Kidney Disease and Hypertension to evaluate the predictive accuracy of a prognostic risk score in predicting end-stage renal disease, accounting for the competing risk of pre-end-stage renal disease death, and evaluate its numerical performance in extensive simulation studies. Copyright © 2018 John Wiley & Sons, Ltd.

Product Operations Status Summary Metrics

NASA Technical Reports Server (NTRS)

Takagi, Atsuya; Toole, Nicholas

2010-01-01

The Product Operations Status Summary Metrics (POSSUM) computer program provides a readable view into the state of the Phoenix Operations Product Generation Subsystem (OPGS) data pipeline. POSSUM provides a user interface that can search the data store, collect product metadata, and display the results in an easily-readable layout. It was designed with flexibility in mind for support in future missions. Flexibility over various data store hierarchies is provided through the disk-searching facilities of Marsviewer. This is a proven program that has been in operational use since the first day of the Phoenix mission.

Rage against the Machine: Evaluation Metrics in the 21st Century

ERIC Educational Resources Information Center

Yang, Charles

2017-01-01

I review the classic literature in generative grammar and Marr's three-level program for cognitive science to defend the Evaluation Metric as a psychological theory of language learning. Focusing on well-established facts of language variation, change, and use, I argue that optimal statistical principles embodied in Bayesian inference models are…

Metric Inservice Teacher Training: Learning from the English and Australian Experience. Final Report.

ERIC Educational Resources Information Center

Chalupsky, Albert B.; And Others

This study was conducted in order to gain detailed information about teacher education programs related to the English and Australian conversions to the metric system of measurement. Information was gathered by review and analysis of relevant official and unofficial documents, and by intensive interviews of key persons involved in teacher…

The SI Metric System and Practical Applications.

ERIC Educational Resources Information Center

Carney, Richard W.

Intended for use in the technical program of a technical institute or community college, this student manual is designed to provide background in the metric system contributing to employability. Nine units are presented with objectives stated for each unit followed by questions or exercises. (Printed answers are supplied when necessary.) Unit 1…

A Classification Metric for Computer Procedures in a Structured Educational Environment.

ERIC Educational Resources Information Center

Linton, M. J.; And Others

Use of a computer programming language in problem-solving activities provides an opportunity to examine how young children use a restricted set of language primitives. The generation, and execution of computer instructions was used as a verification stage in the problem-solution process. The metric is intended to provide a descriptive…

Supervision and autonomy of ophthalmology residents in the outpatient Clinic in the United States: a survey of ACGME-accredited programs.

PubMed

Singman, Eric L; Srikumaran, Divya; Green, Laura; Tian, Jing; McDonnell, Peter

2017-06-26

The development and demonstration of incremental trainee autonomy is required by the ACGME. However, there is scant published research concerning autonomy of ophthalmology residents in the outpatient clinic setting. This study explored the landscape of resident ophthalmology outpatient clinics in the United States. A link to an online survey using the QualtricsTM platform was emailed to the program directors of all 115 ACGME-accredited ophthalmology programs in the United States. Survey questions explored whether resident training programs hosted a continuity clinic where residents would see their own patients, and if so, the degree of faculty supervision provided therein. Metrics such as size of the resident program, number of faculty and clinic setting were also recorded. Correlations between the degree of faculty supervision and other metrics were explored. The response rate was 94%; 69% of respondents indicated that their trainees hosted continuity clinics. Of those programs, 30% required a faculty member to see each patient treated by a resident, while 42% expected the faculty member to at least discuss (if not see) each patient. All programs expected some degree of faculty interaction based upon circumstances such as the level of training of the resident or complexity of the clinical situation. 67% of programs that tracked the contribution of the clinic to resident surgical caseloads reported that these clinics provided more than half of the resident surgical volumes. More ¾ of resident clinics were located in urban settings. The degree of faculty supervision did not correlate to any of the other metrics evaluated. The majority of ophthalmology resident training programs in the United States host a continuity clinic located in an urban environment where residents follow their own patients. Furthermore, most of these clinics require supervising faculty to review both the patients seen and the medical documentation created by the resident encounters. The different degrees of faculty supervision outlined by this survey might provide a useful guide presuming they can be correlated with validated metrics of educational quality. Finally, this study could provide an adjunctive resource to current international efforts to standardize ophthalmic residency education.

The data quality analyzer: a quality control program for seismic data

USGS Publications Warehouse

Ringler, Adam; Hagerty, M.T.; Holland, James F.; Gonzales, A.; Gee, Lind S.; Edwards, J.D.; Wilson, David; Baker, Adam

2015-01-01

The quantification of data quality is based on the evaluation of various metrics (e.g., timing quality, daily noise levels relative to long-term noise models, and comparisons between broadband data and event synthetics). Users may select which metrics contribute to the assessment and those metrics are aggregated into a “grade” for each station. The DQA is being actively used for station diagnostics and evaluation based on the completed metrics (availability, gap count, timing quality, deviation from a global noise model, deviation from a station noise model, coherence between co-located sensors, and comparison between broadband data and synthetics for earthquakes) on stations in the Global Seismographic Network and Advanced National Seismic System.

Predicting infant cortical surface development using a 4D varifold-based learning framework and local topography-based shape morphing.

PubMed

Rekik, Islem; Li, Gang; Lin, Weili; Shen, Dinggang

2016-02-01

Longitudinal neuroimaging analysis methods have remarkably advanced our understanding of early postnatal brain development. However, learning predictive models to trace forth the evolution trajectories of both normal and abnormal cortical shapes remains broadly absent. To fill this critical gap, we pioneered the first prediction model for longitudinal developing cortical surfaces in infants using a spatiotemporal current-based learning framework solely from the baseline cortical surface. In this paper, we detail this prediction model and even further improve its performance by introducing two key variants. First, we use the varifold metric to overcome the limitations of the current metric for surface registration that was used in our preliminary study. We also extend the conventional varifold-based surface registration model for pairwise registration to a spatiotemporal surface regression model. Second, we propose a morphing process of the baseline surface using its topographic attributes such as normal direction and principal curvature sign. Specifically, our method learns from longitudinal data both the geometric (vertices positions) and dynamic (temporal evolution trajectories) features of the infant cortical surface, comprising a training stage and a prediction stage. In the training stage, we use the proposed varifold-based shape regression model to estimate geodesic cortical shape evolution trajectories for each training subject. We then build an empirical mean spatiotemporal surface atlas. In the prediction stage, given an infant, we select the best learnt features from training subjects to simultaneously predict the cortical surface shapes at all later timepoints, based on similarity metrics between this baseline surface and the learnt baseline population average surface atlas. We used a leave-one-out cross validation method to predict the inner cortical surface shape at 3, 6, 9 and 12 months of age from the baseline cortical surface shape at birth. Our method attained a higher prediction accuracy and better captured the spatiotemporal dynamic change of the highly folded cortical surface than the previous proposed prediction method. Copyright © 2015 Elsevier B.V. All rights reserved.

Modeling individual exposures to ambient PM2.5 in the diabetes and the environment panel study (DEPS).

PubMed

Breen, Michael; Xu, Yadong; Schneider, Alexandra; Williams, Ronald; Devlin, Robert

2018-06-01

Air pollution epidemiology studies of ambient fine particulate matter (PM 2.5 ) often use outdoor concentrations as exposure surrogates, which can induce exposure error. The goal of this study was to improve ambient PM 2.5 exposure assessments for a repeated measurements study with 22 diabetic individuals in central North Carolina called the Diabetes and Environment Panel Study (DEPS) by applying the Exposure Model for Individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM 2.5 using outdoor concentrations, questionnaires, weather, and time-location information. Using EMI, we linked a mechanistic air exchange rate (AER) model to a mass-balance PM 2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (F inf_home , Tier 2), indoor concentrations (C in , Tier 3), personal exposure factors (F pex , Tier 4), and personal exposures (E, Tier 5) for ambient PM 2.5 . We applied EMI to predict daily PM 2.5 exposure metrics (Tiers 1-5) for 174 participant-days across the 13 months of DEPS. Individual model predictions were compared to a subset of daily measurements of F pex and E (Tiers 4-5) from the DEPS participants. Model-predicted F pex and E corresponded well to daily measurements with a median difference of 14% and 23%; respectively. Daily model predictions for all 174 days showed considerable temporal and house-to-house variability of AER, F inf_home , and C in (Tiers 1-3), and person-to-person variability of F pex and E (Tiers 4-5). Our study demonstrates the capability of predicting individual-level ambient PM 2.5 exposure metrics for an epidemiological study, in support of improving risk estimation. Copyright © 2018. Published by Elsevier B.V.

An investigation of fighter aircraft agility

NASA Technical Reports Server (NTRS)

Valasek, John; Downing, David R.

1993-01-01

This report attempts to unify in a single document the results of a series of studies on fighter aircraft agility funded by the NASA Ames Research Center, Dryden Flight Research Facility and conducted at the University of Kansas Flight Research Laboratory during the period January 1989 through December 1993. New metrics proposed by pilots and the research community to assess fighter aircraft agility are collected and analyzed. The report develops a framework for understanding the context into which the various proposed fighter agility metrics fit in terms of application and testing. Since new metrics continue to be proposed, this report does not claim to contain every proposed fighter agility metric. Flight test procedures, test constraints, and related criteria are developed. Instrumentation required to quantify agility via flight test is considered, as is the sensitivity of the candidate metrics to deviations from nominal pilot command inputs, which is studied in detail. Instead of supplying specific, detailed conclusions about the relevance or utility of one candidate metric versus another, the authors have attempted to provide sufficient data and analyses for readers to formulate their own conclusions. Readers are therefore ultimately responsible for judging exactly which metrics are 'best' for their particular needs. Additionally, it is not the intent of the authors to suggest combat tactics or other actual operational uses of the results and data in this report. This has been left up to the user community. Twenty of the candidate agility metrics were selected for evaluation with high fidelity, nonlinear, non real-time flight simulation computer programs of the F-5A Freedom Fighter, F-16A Fighting Falcon, F-18A Hornet, and X-29A. The information and data presented on the 20 candidate metrics which were evaluated will assist interested readers in conducting their own extensive investigations. The report provides a definition and analysis of each metric; details of how to test and measure the metric, including any special data reduction requirements; typical values for the metric obtained using one or more aircraft types; and a sensitivity analysis if applicable. The report is organized as follows. The first chapter in the report presents a historical review of air combat trends which demonstrate the need for agility metrics in assessing the combat performance of fighter aircraft in a modern, all-aspect missile environment. The second chapter presents a framework for classifying each candidate metric according to time scale (transient, functional, instantaneous), further subdivided by axis (pitch, lateral, axial). The report is then broadly divided into two parts, with the transient agility metrics (pitch lateral, axial) covered in chapters three, four, and five, and the functional agility metrics covered in chapter six. Conclusions, recommendations, and an extensive reference list and biography are also included. Five appendices contain a comprehensive list of the definitions of all the candidate metrics; a description of the aircraft models and flight simulation programs used for testing the metrics; several relations and concepts which are fundamental to the study of lateral agility; an in-depth analysis of the axial agility metrics; and a derivation of the relations for the instantaneous agility and their approximations.

Performance regression manager for large scale systems

DOEpatents

Faraj, Daniel A.

2017-10-17

System and computer program product to perform an operation comprising generating, based on a first output generated by a first execution instance of a command, a first output file specifying a value of at least one performance metric, wherein the first output file is formatted according to a predefined format, comparing the value of the at least one performance metric in the first output file to a value of the performance metric in a second output file, the second output file having been generated based on a second output generated by a second execution instance of the command, and outputting for display an indication of a result of the comparison of the value of the at least one performance metric of the first output file to the value of the at least one performance metric of the second output file.

Model assessment using a multi-metric ranking technique

NASA Astrophysics Data System (ADS)

Fitzpatrick, P. J.; Lau, Y.; Alaka, G.; Marks, F.

2017-12-01

Validation comparisons of multiple models presents challenges when skill levels are similar, especially in regimes dominated by the climatological mean. Assessing skill separation will require advanced validation metrics and identifying adeptness in extreme events, but maintain simplicity for management decisions. Flexibility for operations is also an asset. This work postulates a weighted tally and consolidation technique which ranks results by multiple types of metrics. Variables include absolute error, bias, acceptable absolute error percentages, outlier metrics, model efficiency, Pearson correlation, Kendall's Tau, reliability Index, multiplicative gross error, and root mean squared differences. Other metrics, such as root mean square difference and rank correlation were also explored, but removed when the information was discovered to be generally duplicative to other metrics. While equal weights are applied, weights could be altered depending for preferred metrics. Two examples are shown comparing ocean models' currents and tropical cyclone products, including experimental products. The importance of using magnitude and direction for tropical cyclone track forecasts instead of distance, along-track, and cross-track are discussed. Tropical cyclone intensity and structure prediction are also assessed. Vector correlations are not included in the ranking process, but found useful in an independent context, and will be briefly reported.

Evaluating community and campus environmental public health programs.

PubMed

Pettibone, Kristianna G; Parras, Juan; Croisant, Sharon Petronella; Drew, Christina H

2014-01-01

The National Institute of Environmental Health Sciences' (NIEHS) Partnerships for Environmental Public Health (PEPH) program created the Evaluation Metrics Manual as a tool to help grantees understand how to map out their programs using a logic model, and to identify measures for documenting their achievements in environmental public health research. This article provides an overview of the manual, describing how grantees and community partners contributed to the manual, and how the basic components of a logic model can be used to identify metrics. We illustrate how the approach can be implemented, using a real-world case study from the University of Texas Medical Branch, where researchers worked with community partners to develop a network to address environmental justice issues.

KIC 12557548 and Similar Stars as SETI Targets

NASA Astrophysics Data System (ADS)

Star Cartier, Kimberly Michelle

2015-01-01

This project aims to construct a robust information theoretic metric to quantify anomalous transit light curves and compare regular and irregular transits in a reproducible way. Using this metric we can distinguish natural transits from predicted extraterrestrial intelligence (ETI) communication that utilizes transiting mega-structures to alter the transit shape and depth in a measurable way. KIC-12557548b (KIC-1255b) is such an anomalous planet, with highly variable consecutive transit depths and shapes that have been explained by Rappaport et al. (2012) and Croll et al. (2014) as due to a disintegrating sub-Mercury sized planet with a debris tail encompassing the planetary orbit. However, Arnold (2005) and later Forgan (2013) presented models showing that planet-sized, non-circular artificial structures transiting their host star could be identified as non-natural by light curves anomalous in their duration and asymmetry, as in the case of KIC-1255b. If such mega-engineering structures were able to alter their aspects on orbital timescales, the resulting transit depths could be used to transmit information at low bandwidth. We use KIC-1255b as a benchmark case for separating anomalous transit signals that resemble ETI predictions but are naturally occurring. To do this, we use the Kullback-Leibler (KL) divergence of the KIC-1255b transit depth time series to quantify the entropy of the transit depth series. We calibrate our relative entropy metric by calculating the KL divergence of the Kepler-5b transits, which are markedly constant compared to KIC-1255b. Artificially generated transit depth time series data using Arnold's beacons allow us to calculate the KL divergence of predicted ETI communications and show that while KIC-1255b might match ETI predictions of shape and depth variations, the entropy content of the datasets are distinct by our metric. Thus we can use the entropy metric to test other cases of anomalous transits to separate out those transiting planets that can be explained through natural models and those for which an ETI hypothesis might be entertained.

Managing Reliability in the 21st Century

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dellin, T.A.

1998-11-23

The rapid pace of change at Ike end of the 20th Century should continue unabated well into the 21st Century. The driver will be the marketplace imperative of "faster, better, cheaper." This imperative has already stimulated a revolution-in-engineering in design and manufacturing. In contrast, to date, reliability engineering has not undergone a similar level of change. It is critical that we implement a corresponding revolution-in-reliability-engineering as we enter the new millennium. If we are still using 20th Century reliability approaches in the 21st Century, then reliability issues will be the limiting factor in faster, better, and cheaper. At the heartmore » of this reliability revolution will be a science-based approach to reliability engineering. Science-based reliability will enable building-in reliability, application-specific products, virtual qualification, and predictive maintenance. The purpose of this paper is to stimulate a dialogue on the future of reliability engineering. We will try to gaze into the crystal ball and predict some key issues that will drive reliability programs in the new millennium. In the 21st Century, we will demand more of our reliability programs. We will need the ability to make accurate reliability predictions that will enable optimizing cost, performance and time-to-market to meet the needs of every market segment. We will require that all of these new capabilities be in place prior to the stint of a product development cycle. The management of reliability programs will be driven by quantifiable metrics of value added to the organization business objectives.« less

On the Tradeoff Between Altruism and Selfishness in MANET Trust Management

DTIC Science & Technology

2016-04-07

to discourage selfish behaviors, using a hidden Markov model (HMM) to quanti - tatively measure the trustworthiness of nodes. Adams et al. [18...based reliability metric to predict trust-based system survivability. Section 4 analyzes numerical results obtained through the evaluation of our SPN...concepts in MANETs, trust man- agement for MANETs should consider the following design features: trust metrics must be customizable, evaluation of

Landform and terrain shape indices are related to oak site index in the Missouri Ozarks

Treesearch

Jason L. Villwock; John M. Kabrick; W. Henry McNab; Daniel C. Dey

2011-01-01

In the Southern Appalachians, metrics for quantifying the geometric shape of the land surface (terrain shape index or "tsi") and of the landform (land form index or "lfi") were developed and found to be correlated to yellow-poplar site index. However, the utility of these metrics for predicting site index for oaks in the Ozark Highlands has not been...

Visible contrast energy metrics for detection and discrimination

NASA Astrophysics Data System (ADS)

Ahumada, Albert J.; Watson, Andrew B.

2013-03-01

Contrast energy was proposed by Watson, Barlow, and Robson (Science, 1983) as a useful metric for representing luminance contrast target stimuli because it represents the detectability of the stimulus in photon noise for an ideal observer. We propose here the use of visible contrast energy metrics for detection and discrimination among static luminance patterns. The visibility is approximated with spatial frequency sensitivity weighting and eccentricity sensitivity weighting. The suggested weighting functions revise the Standard Spatial Observer (Watson and Ahumada, J. Vision, 2005) for luminance contrast detection , extend it into the near periphery, and provide compensation for duration. Under the assumption that the detection is limited only by internal noise, both detection and discrimination performance can be predicted by metrics based on the visible energy of the difference images.

Porphyry copper assessment of Central America and the Caribbean Basin: Chapter I in Global mineral resource assessment

USGS Publications Warehouse

Gray, Floyd; Hammarstrom, Jane M.; Ludington, Stephen; Zürcher, Lukas; Nelson, Carl E.; Robinson, Gilpin R.; Miller, Robert J.; Moring, Barry C.

2014-01-01

This assessment estimated a total mean of 37 undiscovered porphyry copper deposits within the assessed permissive tracts in Central America and the Caribbean Basin. This represents more than five times the seven known deposits. Predicted mean (arithmetic) resources that could be associated with these undiscovered deposits are about 130 million metric tons of copper and about 5,200 metric tons of gold, as well as byproduct molybdenum and silver. The reported identified resources for the seven known deposits total about 39 million metric tons of copper and about 930 metric tons of gold. The assessment area is estimated to contain nearly four times as much copper and six times as much gold in undiscovered porphyry copper deposits as has been identified to date.

MO-AB-BRA-10: Cancer Therapy Outcome Prediction Based On Dempster-Shafer Theory and PET Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lian, C; University of Rouen, QuantIF - EA 4108 LITIS, 76000 Rouen; Li, H

2015-06-15

Purpose: In cancer therapy, utilizing FDG-18 PET image-based features for accurate outcome prediction is challenging because of 1) limited discriminative information within a small number of PET image sets, and 2) fluctuant feature characteristics caused by the inferior spatial resolution and system noise of PET imaging. In this study, we proposed a new Dempster-Shafer theory (DST) based approach, evidential low-dimensional transformation with feature selection (ELT-FS), to accurately predict cancer therapy outcome with both PET imaging features and clinical characteristics. Methods: First, a specific loss function with sparse penalty was developed to learn an adaptive low-rank distance metric for representing themore » dissimilarity between different patients’ feature vectors. By minimizing this loss function, a linear low-dimensional transformation of input features was achieved. Also, imprecise features were excluded simultaneously by applying a l2,1-norm regularization of the learnt dissimilarity metric in the loss function. Finally, the learnt dissimilarity metric was applied in an evidential K-nearest-neighbor (EK- NN) classifier to predict treatment outcome. Results: Twenty-five patients with stage II–III non-small-cell lung cancer and thirty-six patients with esophageal squamous cell carcinomas treated with chemo-radiotherapy were collected. For the two groups of patients, 52 and 29 features, respectively, were utilized. The leave-one-out cross-validation (LOOCV) protocol was used for evaluation. Compared to three existing linear transformation methods (PCA, LDA, NCA), the proposed ELT-FS leads to higher prediction accuracy for the training and testing sets both for lung-cancer patients (100+/−0.0, 88.0+/−33.17) and for esophageal-cancer patients (97.46+/−1.64, 83.33+/−37.8). The ELT-FS also provides superior class separation in both test data sets. Conclusion: A novel DST- based approach has been proposed to predict cancer treatment outcome using PET image features and clinical characteristics. A specific loss function has been designed for robust accommodation of feature set incertitude and imprecision, facilitating adaptive learning of the dissimilarity metric for the EK-NN classifier.« less

Optimizing Blasting’s Air Overpressure Prediction Model using Swarm Intelligence

NASA Astrophysics Data System (ADS)

Nur Asmawisham Alel, Mohd; Ruben Anak Upom, Mark; Asnida Abdullah, Rini; Hazreek Zainal Abidin, Mohd

2018-04-01

Air overpressure (AOp) resulting from blasting can cause damage and nuisance to nearby civilians. Thus, it is important to be able to predict AOp accurately. In this study, 8 different Artificial Neural Network (ANN) were developed for the purpose of prediction of AOp. The ANN models were trained using different variants of Particle Swarm Optimization (PSO) algorithm. AOp predictions were also made using an empirical equation, as suggested by United States Bureau of Mines (USBM), to serve as a benchmark. In order to develop the models, 76 blasting operations in Hulu Langat were investigated. All the ANN models were found to outperform the USBM equation in three performance metrics; root mean square error (RMSE), mean absolute percentage error (MAPE) and coefficient of determination (R2). Using a performance ranking method, MSO-Rand-Mut was determined to be the best prediction model for AOp with a performance metric of RMSE=2.18, MAPE=1.73% and R2=0.97. The result shows that ANN models trained using PSO are capable of predicting AOp with great accuracy.

Air pollution exposure prediction approaches used in air pollution epidemiology studies.

PubMed

Özkaynak, Halûk; Baxter, Lisa K; Dionisio, Kathie L; Burke, Janet

2013-01-01

Epidemiological studies of the health effects of outdoor air pollution have traditionally relied upon surrogates of personal exposures, most commonly ambient concentration measurements from central-site monitors. However, this approach may introduce exposure prediction errors and misclassification of exposures for pollutants that are spatially heterogeneous, such as those associated with traffic emissions (e.g., carbon monoxide, elemental carbon, nitrogen oxides, and particulate matter). We review alternative air quality and human exposure metrics applied in recent air pollution health effect studies discussed during the International Society of Exposure Science 2011 conference in Baltimore, MD. Symposium presenters considered various alternative exposure metrics, including: central site or interpolated monitoring data, regional pollution levels predicted using the national scale Community Multiscale Air Quality model or from measurements combined with local-scale (AERMOD) air quality models, hybrid models that include satellite data, statistically blended modeling and measurement data, concentrations adjusted by home infiltration rates, and population-based human exposure model (Stochastic Human Exposure and Dose Simulation, and Air Pollutants Exposure models) predictions. These alternative exposure metrics were applied in epidemiological applications to health outcomes, including daily mortality and respiratory hospital admissions, daily hospital emergency department visits, daily myocardial infarctions, and daily adverse birth outcomes. This paper summarizes the research projects presented during the symposium, with full details of the work presented in individual papers in this journal issue.

The Creation of a Pediatric Hospital Medicine Dashboard: Performance Assessment for Improvement.

PubMed

Fox, Lindsay Anne; Walsh, Kathleen E; Schainker, Elisabeth G

2016-07-01

Leaders of pediatric hospital medicine (PHM) recommended a clinical dashboard to monitor clinical practice and make improvements. To date, however, no programs report implementing a dashboard including the proposed broad range of metrics across multiple sites. We sought to (1) develop and populate a clinical dashboard to demonstrate productivity, quality, group sustainability, and value added for an academic division of PHM across 4 inpatient sites; (2) share dashboard data with division members and administrations to improve performance and guide program development; and (3) revise the dashboard to optimize its utility. Division members proposed a dashboard based on PHM recommendations. We assessed feasibility of data collection and defined and modified metrics to enable collection of comparable data across sites. We gathered data and shared the results with division members and administrations. We collected quarterly and annual data from October 2011 to September 2013. We found comparable metrics across all sites for descriptive, productivity, group sustainability, and value-added domains; only 72% of all quality metrics were tracked in a comparable fashion. After sharing the data, we saw increased timeliness of nursery discharges and an increase in hospital committee participation and grant funding. PHM dashboards have the potential to guide program development, mobilize faculty to improve care, and demonstrate program value to stakeholders. Dashboard implementation at other institutions and data sharing across sites may help to better define and strengthen the field of PHM by creating benchmarks and help improve the quality of pediatric hospital care. Copyright © 2016 by the American Academy of Pediatrics.

A novel ECG detector performance metric and its relationship with missing and false heart rate limit alarms.

PubMed

Daluwatte, Chathuri; Vicente, Jose; Galeotti, Loriano; Johannesen, Lars; Strauss, David G; Scully, Christopher G

Performance of ECG beat detectors is traditionally assessed on long intervals (e.g.: 30min), but only incorrect detections within a short interval (e.g.: 10s) may cause incorrect (i.e., missed+false) heart rate limit alarms (tachycardia and bradycardia). We propose a novel performance metric based on distribution of incorrect beat detection over a short interval and assess its relationship with incorrect heart rate limit alarm rates. Six ECG beat detectors were assessed using performance metrics over long interval (sensitivity and positive predictive value over 30min) and short interval (Area Under empirical cumulative distribution function (AUecdf) for short interval (i.e., 10s) sensitivity and positive predictive value) on two ECG databases. False heart rate limit and asystole alarm rates calculated using a third ECG database were then correlated (Spearman's rank correlation) with each calculated performance metric. False alarm rates correlated with sensitivity calculated on long interval (i.e., 30min) (ρ=-0.8 and p<0.05) and AUecdf for sensitivity (ρ=0.9 and p<0.05) in all assessed ECG databases. Sensitivity over 30min grouped the two detectors with lowest false alarm rates while AUecdf for sensitivity provided further information to identify the two beat detectors with highest false alarm rates as well, which was inseparable with sensitivity over 30min. Short interval performance metrics can provide insights on the potential of a beat detector to generate incorrect heart rate limit alarms. Published by Elsevier Inc.

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

NASA Technical Reports Server (NTRS)

Sharma, Shivanjli; Fergus, John

2017-01-01

A real time dashboard was developed in order to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users across a number of roles benefit from a real time system that enables common situational awareness. In addition to shared situational awareness the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial set of metrics computed on operational data. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017; Charlotte-Douglas International Airport. Analysis and metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of metrics across delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

Numerical model validation using experimental data: Application of the area metric on a Francis runner

NASA Astrophysics Data System (ADS)

Chatenet, Q.; Tahan, A.; Gagnon, M.; Chamberland-Lauzon, J.

2016-11-01

Nowadays, engineers are able to solve complex equations thanks to the increase of computing capacity. Thus, finite elements software is widely used, especially in the field of mechanics to predict part behavior such as strain, stress and natural frequency. However, it can be difficult to determine how a model might be right or wrong, or whether a model is better than another one. Nevertheless, during the design phase, it is very important to estimate how the hydroelectric turbine blades will behave according to the stress to which it is subjected. Indeed, the static and dynamic stress levels will influence the blade's fatigue resistance and thus its lifetime, which is a significant feature. In the industry, engineers generally use either graphic representation, hypothesis tests such as the Student test, or linear regressions in order to compare experimental to estimated data from the numerical model. Due to the variability in personal interpretation (reproducibility), graphical validation is not considered objective. For an objective assessment, it is essential to use a robust validation metric to measure the conformity of predictions against data. We propose to use the area metric in the case of a turbine blade that meets the key points of the ASME Standards and produces a quantitative measure of agreement between simulations and empirical data. This validation metric excludes any belief and criterion of accepting a model which increases robustness. The present work is aimed at applying a validation method, according to ASME V&V 10 recommendations. Firstly, the area metric is applied on the case of a real Francis runner whose geometry and boundaries conditions are complex. Secondly, the area metric will be compared to classical regression methods to evaluate the performance of the method. Finally, we will discuss the use of the area metric as a tool to correct simulations.

32 CFR 272.5 - Responsibilities.

Code of Federal Regulations, 2011 CFR

2011-07-01

... for plans and programs; develop policies; conduct analyses and studies; and make recommendations for... research programs and projects to eliminate unpromising or unnecessarily duplicative programs, and to... of Defense, appropriate funding levels for DoD basic research. (4) Develop and maintain a metrics...

Research and development on performance models of thermal imaging systems

NASA Astrophysics Data System (ADS)

Wang, Ji-hui; Jin, Wei-qi; Wang, Xia; Cheng, Yi-nan

2009-07-01

Traditional ACQUIRE models perform the discrimination tasks of detection (target orientation, recognition and identification) for military target based upon minimum resolvable temperature difference (MRTD) and Johnson criteria for thermal imaging systems (TIS). Johnson criteria is generally pessimistic for performance predict of sampled imager with the development of focal plane array (FPA) detectors and digital image process technology. Triangle orientation discrimination threshold (TOD) model, minimum temperature difference perceived (MTDP)/ thermal range model (TRM3) Model and target task performance (TTP) metric have been developed to predict the performance of sampled imager, especially TTP metric can provides better accuracy than the Johnson criteria. In this paper, the performance models above are described; channel width metrics have been presented to describe the synthesis performance including modulate translate function (MTF) channel width for high signal noise to ration (SNR) optoelectronic imaging systems and MRTD channel width for low SNR TIS; the under resolvable questions for performance assessment of TIS are indicated; last, the development direction of performance models for TIS are discussed.

A Conceptual Methodology for Assessing Acquisition Requirements Robustness against Technology Uncertainties

NASA Astrophysics Data System (ADS)

Chou, Shuo-Ju

2011-12-01

In recent years the United States has shifted from a threat-based acquisition policy that developed systems for countering specific threats to a capabilities-based strategy that emphasizes the acquisition of systems that provide critical national defense capabilities. This shift in policy, in theory, allows for the creation of an "optimal force" that is robust against current and future threats regardless of the tactics and scenario involved. In broad terms, robustness can be defined as the insensitivity of an outcome to "noise" or non-controlled variables. Within this context, the outcome is the successful achievement of defense strategies and the noise variables are tactics and scenarios that will be associated with current and future enemies. Unfortunately, a lack of system capability, budget, and schedule robustness against technology performance and development uncertainties has led to major setbacks in recent acquisition programs. This lack of robustness stems from the fact that immature technologies have uncertainties in their expected performance, development cost, and schedule that cause to variations in system effectiveness and program development budget and schedule requirements. Unfortunately, the Technology Readiness Assessment process currently used by acquisition program managers and decision-makers to measure technology uncertainty during critical program decision junctions does not adequately capture the impact of technology performance and development uncertainty on program capability and development metrics. The Technology Readiness Level metric employed by the TRA to describe program technology elements uncertainties can only provide a qualitative and non-descript estimation of the technology uncertainties. In order to assess program robustness, specifically requirements robustness, against technology performance and development uncertainties, a new process is needed. This process should provide acquisition program managers and decision-makers with the ability to assess or measure the robustness of program requirements against such uncertainties. A literature review of techniques for forecasting technology performance and development uncertainties and subsequent impacts on capability, budget, and schedule requirements resulted in the conclusion that an analysis process that coupled a probabilistic analysis technique such as Monte Carlo Simulations with quantitative and parametric models of technology performance impact and technology development time and cost requirements would allow the probabilities of meeting specific constraints of these requirements to be established. These probabilities of requirements success metrics can then be used as a quantitative and probabilistic measure of program requirements robustness against technology uncertainties. Combined with a Multi-Objective Genetic Algorithm optimization process and computer-based Decision Support System, critical information regarding requirements robustness against technology uncertainties can be captured and quantified for acquisition decision-makers. This results in a more informed and justifiable selection of program technologies during initial program definition as well as formulation of program development and risk management strategies. To meet the stated research objective, the ENhanced TEchnology Robustness Prediction and RISk Evaluation (ENTERPRISE) methodology was formulated to provide a structured and transparent process for integrating these enabling techniques to provide a probabilistic and quantitative assessment of acquisition program requirements robustness against technology performance and development uncertainties. In order to demonstrate the capabilities of the ENTERPRISE method and test the research Hypotheses, an demonstration application of this method was performed on a notional program for acquiring the Carrier-based Suppression of Enemy Air Defenses (SEAD) using Unmanned Combat Aircraft Systems (UCAS) and their enabling technologies. The results of this implementation provided valuable insights regarding the benefits and inner workings of this methodology as well as its limitations that should be addressed in the future to narrow the gap between current state and the desired state.

SmartWay Program Successes

EPA Pesticide Factsheets

This page provides success metrics and statistics about the SmartWay program and what is has done to reduce greenhouse gas emissions, climate change, and other environmental impacts of freight transportation and supply chain.

Web Analytics

EPA Pesticide Factsheets

EPA’s Web Analytics Program collects, analyzes, and provides reports on traffic, quality assurance, and customer satisfaction metrics for EPA’s website. The program uses a variety of analytics tools, including Google Analytics and CrazyEgg.

Making the Case for Objective Performance Metrics in Newborn Screening by Tandem Mass Spectrometry

ERIC Educational Resources Information Center

Rinaldo, Piero; Zafari, Saba; Tortorelli, Silvia; Matern, Dietrich

2006-01-01

The expansion of newborn screening programs to include multiplex testing by tandem mass spectrometry requires understanding and close monitoring of performance metrics. This is not done consistently because of lack of defined targets, and interlaboratory comparison is almost nonexistent. Between July 2004 and April 2006 (N = 176,185 cases), the…

An Evaluation of Output Signal to Noise Ratio as a Predictor of Cochlear Implant Speech Intelligibility.

PubMed

Watkins, Greg D; Swanson, Brett A; Suaning, Gregg J

2018-02-22

Cochlear implant (CI) sound processing strategies are usually evaluated in clinical studies involving experienced implant recipients. Metrics which estimate the capacity to perceive speech for a given set of audio and processing conditions provide an alternative means to assess the effectiveness of processing strategies. The aim of this research was to assess the ability of the output signal to noise ratio (OSNR) to accurately predict speech perception. It was hypothesized that compared with the other metrics evaluated in this study (1) OSNR would have equivalent or better accuracy and (2) OSNR would be the most accurate in the presence of variable levels of speech presentation. For the first time, the accuracy of OSNR as a metric which predicts speech intelligibility was compared, in a retrospective study, with that of the input signal to noise ratio (ISNR) and the short-term objective intelligibility (STOI) metric. Because STOI measured audio quality at the input to a CI sound processor, a vocoder was applied to the sound processor output and STOI was also calculated for the reconstructed audio signal (vocoder short-term objective intelligibility [VSTOI] metric). The figures of merit calculated for each metric were Pearson correlation of the metric and a psychometric function fitted to sentence scores at each predictor value (Pearson sigmoidal correlation [PSIG]), epsilon insensitive root mean square error (RMSE*) of the psychometric function and the sentence scores, and the statistical deviance of the fitted curve to the sentence scores (D). Sentence scores were taken from three existing data sets of Australian Sentence Tests in Noise results. The AuSTIN tests were conducted with experienced users of the Nucleus CI system. The score for each sentence was the proportion of morphemes the participant correctly repeated. In data set 1, all sentences were presented at 65 dB sound pressure level (SPL) in the presence of four-talker Babble noise. Each block of sentences used an adaptive procedure, with the speech presented at a fixed level and the ISNR varied. In data set 2, sentences were presented at 65 dB SPL in the presence of stationary speech weighted noise, street-side city noise, and cocktail party noise. An adaptive ISNR procedure was used. In data set 3, sentences were presented at levels ranging from 55 to 89 dB SPL with two automatic gain control configurations and two fixed ISNRs. For data set 1, the ISNR and OSNR were equally most accurate. STOI was significantly different for deviance (p = 0.045) and RMSE* (p < 0.001). VSTOI was significantly different for RMSE* (p < 0.001). For data set 2, ISNR and OSNR had an equivalent accuracy which was significantly better than that of STOI for PSIG (p = 0.029) and VSTOI for deviance (p = 0.001), RMSE*, and PSIG (both p < 0.001). For data set 3, OSNR was the most accurate metric and was significantly more accurate than VSTOI for deviance, RMSE*, and PSIG (all p < 0.001). ISNR and STOI were unable to predict the sentence scores for this data set. The study results supported the hypotheses. OSNR was found to have an accuracy equivalent to or better than ISNR, STOI, and VSTOI for tests conducted at a fixed presentation level and variable ISNR. OSNR was a more accurate metric than VSTOI for tests with fixed ISNRs and variable presentation levels. Overall, OSNR was the most accurate metric across the three data sets. OSNR holds promise as a prediction metric which could potentially improve the effectiveness of sound processor research and CI fitting.

Antimicrobial Stewardship Programs: Appropriate Measures and Metrics to Study their Impact.

PubMed

Morris, Andrew M

Antimicrobial stewardship is a new field that struggles to find the right balance between meaningful and useful metrics to study the impact of antimicrobial stewardship programs (ASPs). ASP metrics primarily measure antimicrobial use, although microbiological resistance and clinical outcomes are also important measures of the impact an ASP has on a hospital and its patient population. Antimicrobial measures looking at consumption are the most commonly used measures, and are focused on defined daily doses, days of therapy, and costs, usually standardized per 1,000 patient-days. Each measure provides slightly different information, with their own upsides and downfalls. Point prevalence measurement of antimicrobial use is an increasingly used approach to understanding consumption that does not entirely rely on sophisticated electronic information systems, and is also replicable. Appropriateness measures hold appeal and promise, but have not been developed to the degree that makes them useful and widely applicable. The primary reason why antimicrobial stewardship is necessary is the growth of antimicrobial resistance. Accordingly, antimicrobial resistance is an important metric of the impact of an ASP. The most common approach to measuring resistance for ASP purposes is to report rates of common or important community- or nosocomial-acquired antimicrobial-resistant organisms, such as methicillin-resistant Staphylococcus aureus and Clostridium difficile. Such an approach is dependent on detection methods, community rates of resistance, and co-interventions, and therefore may not be the most accurate or reflective measure of antimicrobial stewardship interventions. Development of an index to reflect the net burden of resistance holds theoretical promise, but has yet to be realized. Finally, programs must consider patient outcome measures. Mortality is the most objective and reliable method, but has several drawbacks. Disease- or organism-specific mortality, or cure, are increasingly used metrics.

Stream salamanders as indicators of stream quality in Maryland, USA

USGS Publications Warehouse

Southerland, M.T.; Jung, R.E.; Baxter, D.P.; Chellman, I.C.; Mercurio, G.; Volstad, J.H.

2004-01-01

Biological indicators are critical to the protection of small, headwater streams and the ecological values they provide. Maryland and other state monitoring programs have determined that fish indicators are ineffective in small streams, where stream salamanders may replace fish as top predators. Because of their life history, physiology, abundance, and ubiquity, stream salamanders are likely representative of biological integrity in these streams. The goal of this study was to determine whether stream salamanders are effective indicators of ecological conditions across biogeographic regions and gradients of human disturbance. During the summers of 2001 and 2002, we intensively surveyed for stream salamanders at 76 stream sites located west of the Maryland Coastal Plain, sites also monitored by the Maryland Biological Stream Survey (MBSS) and City of Gaithersburg. We found 1,584 stream salamanders, including all eight species known in Maryland, using two 15 ? 2 m transects and two 4 m2 quadrats that spanned both stream bank and channel. We performed removal sampling on transects to estimate salamander species detection probabilities, which ranged from 0.67-0.85. Stepwise regressions identified 15 of 52 non-salamander variables, representing water quality, physical habitat, land use, and biological conditions, which best predicted salamander metrics. Indicator development involved (1) identifying reference (non-degraded) and degraded sites (using percent forest, shading, riparian buffer width, aesthetic rating, and benthic macroinvertebrate and fish indices of biotic integrity); (2) testing 12 candidate salamander metrics (representing species richness and composition, abundance, species tolerance, and reproductive function) for their ability to distinguish reference from degraded sites; and (3) combining metrics into an index that effectively discriminated sites according to known stream conditions. Final indices for Highlands, Piedmont, and Non-Coastal Plain regions comprised four metrics: number of species, number of salamanders, number of intolerant salamanders, and number of adult salamanders, producing classification efficiencies between 87% and 90%. Partial validation of these indices was obtained when a test of the number of salamanders metric produced an 82% correct classification of 618 MBSS sites surveyed in 1995-97. This study supports the use of stream salamander monitoring and a composite stream salamander index of biotic integrity (SS-IBI) to determine stream quality in Maryland.

Comparison of Home Retrofit Programs in Wisconsin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cunningham, Kerrie; Hannigan, Eileen

2013-03-01

To explore ways to reduce customer barriers and increase home retrofit completions, several different existing home retrofit models have been implemented in the state of Wisconsin. This study compared these programs' performance in terms of savings per home and program cost per home to assess the relative cost-effectiveness of each program design. However, given the many variations in these different programs, it is difficult to establish a fair comparison based on only a small number of metrics. Therefore, the overall purpose of the study is to document these programs' performance in a case study approach to look at general patternsmore » of these metrics and other variables within the context of each program. This information can be used by energy efficiency program administrators and implementers to inform home retrofit program design. Six different program designs offered in Wisconsin for single-family energy efficiency improvements were included in the study. For each program, the research team provided information about the programs' approach and goals, characteristics, achievements and performance. The program models were then compared with performance results-program cost and energy savings-to help understand the overall strengths and weaknesses or challenges of each model.« less

Comparison of Home Retrofit Programs in Wisconsin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cunningham, K.; Hannigan, E.

2013-03-01

To explore ways to reduce customer barriers and increase home retrofit completions, several different existing home retrofit models have been implemented in the state of Wisconsin. This study compared these programs' performance in terms of savings per home and program cost per home to assess the relative cost-effectiveness of each program design. However, given the many variations in these different programs, it is difficult to establish a fair comparison based on only a small number of metrics. Therefore, the overall purpose of the study is to document these programs' performance in a case study approach to look at general patternsmore » of these metrics and other variables within the context of each program. This information can be used by energy efficiency program administrators and implementers to inform home retrofit program design. Six different program designs offered in Wisconsin for single-family energy efficiency improvements were included in the study. For each program, the research team provided information about the programs' approach and goals, characteristics, achievements and performance. The program models were then compared with performance results -- program cost and energy savings -- to help understand the overall strengths and weaknesses or challenges of each model.« less

Assessment of Computational Fluid Dynamics (CFD) Models for Shock Boundary-Layer Interaction

NASA Technical Reports Server (NTRS)

DeBonis, James R.; Oberkampf, William L.; Wolf, Richard T.; Orkwis, Paul D.; Turner, Mark G.; Babinsky, Holger

2011-01-01

A workshop on the computational fluid dynamics (CFD) prediction of shock boundary-layer interactions (SBLIs) was held at the 48th AIAA Aerospace Sciences Meeting. As part of the workshop numerous CFD analysts submitted solutions to four experimentally measured SBLIs. This paper describes the assessment of the CFD predictions. The assessment includes an uncertainty analysis of the experimental data, the definition of an error metric and the application of that metric to the CFD solutions. The CFD solutions provided very similar levels of error and in general it was difficult to discern clear trends in the data. For the Reynolds Averaged Navier-Stokes methods the choice of turbulence model appeared to be the largest factor in solution accuracy. Large-eddy simulation methods produced error levels similar to RANS methods but provided superior predictions of normal stresses.

Earned Value Management Considering Technical Readiness Level and Its Application to New Space Launcher Program

NASA Astrophysics Data System (ADS)

Choi, Young-In; Ahn, Jaemyung

2018-04-01

Earned value management (EVM) is a methodology for monitoring and controlling the performance of a project based on a comparison between planned and actual cost/schedule. This study proposes a concept of hybrid earned value management (H-EVM) that integrates the traditional EVM metrics with information on the technology readiness level. The proposed concept can reflect the progress of a project in a sensitive way and provides short-term perspective complementary to the traditional EVM metrics. A two-dimensional visualization on the cost/schedule status of a project reflecting both of the traditional EVM (long-term perspective) and the proposed H-EVM (short-term perspective) indices is introduced. A case study on the management of a new space launch vehicle development program is conducted to demonstrate the effectiveness of the proposed H-EVM concept, associated metrics, and the visualization technique.

Clustering of the human skeletal muscle fibers using linear programming and angular Hilbertian metrics.

PubMed

Neji, Radhouène; Besbes, Ahmed; Komodakis, Nikos; Deux, Jean-François; Maatouk, Mezri; Rahmouni, Alain; Bassez, Guillaume; Fleury, Gilles; Paragios, Nikos

2009-01-01

In this paper, we present a manifold clustering method fo the classification of fibers obtained from diffusion tensor images (DTI) of the human skeletal muscle. Using a linear programming formulation of prototype-based clustering, we propose a novel fiber classification algorithm over manifolds that circumvents the necessity to embed the data in low dimensional spaces and determines automatically the number of clusters. Furthermore, we propose the use of angular Hilbertian metrics between multivariate normal distributions to define a family of distances between tensors that we generalize to fibers. These metrics are used to approximate the geodesic distances over the fiber manifold. We also discuss the case where only geodesic distances to a reduced set of landmark fibers are available. The experimental validation of the method is done using a manually annotated significant dataset of DTI of the calf muscle for healthy and diseased subjects.

StreamThermal: A software package for calculating thermal metrics from stream temperature data

USGS Publications Warehouse

Tsang, Yin-Phan; Infante, Dana M.; Stewart, Jana S.; Wang, Lizhu; Tingly, Ralph; Thornbrugh, Darren; Cooper, Arthur; Wesley, Daniel

2016-01-01

Improving quality and better availability of continuous stream temperature data allows natural resource managers, particularly in fisheries, to understand associations between different characteristics of stream thermal regimes and stream fishes. However, there is no convenient tool to efficiently characterize multiple metrics reflecting stream thermal regimes with the increasing amount of data. This article describes a software program packaged as a library in R to facilitate this process. With this freely-available package, users will be able to quickly summarize metrics that describe five categories of stream thermal regimes: magnitude, variability, frequency, timing, and rate of change. The installation and usage instruction of this package, the definition of calculated thermal metrics, as well as the output format from the package are described, along with an application showing the utility for multiple metrics. We believe this package can be widely utilized by interested stakeholders and greatly assist more studies in fisheries.

Performance regression manager for large scale systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faraj, Daniel A.

System and computer program product to perform an operation comprising generating, based on a first output generated by a first execution instance of a command, a first output file specifying a value of at least one performance metric, wherein the first output file is formatted according to a predefined format, comparing the value of the at least one performance metric in the first output file to a value of the performance metric in a second output file, the second output file having been generated based on a second output generated by a second execution instance of the command, and outputtingmore » for display an indication of a result of the comparison of the value of the at least one performance metric of the first output file to the value of the at least one performance metric of the second output file.« less

Modelling the Relationship Between Land Surface Temperature and Landscape Patterns of Land Use Land Cover Classification Using Multi Linear Regression Models

NASA Astrophysics Data System (ADS)

Bernales, A. M.; Antolihao, J. A.; Samonte, C.; Campomanes, F.; Rojas, R. J.; dela Serna, A. M.; Silapan, J.

2016-06-01

The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC) and land surface temperature (LST). Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric "Effective mesh size" was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas) and looking for common predictors between LSTs of these two different farming periods.

Asymptomatic Alzheimer disease: Defining resilience.

PubMed

Hohman, Timothy J; McLaren, Donald G; Mormino, Elizabeth C; Gifford, Katherine A; Libon, David J; Jefferson, Angela L

2016-12-06

To define robust resilience metrics by leveraging CSF biomarkers of Alzheimer disease (AD) pathology within a latent variable framework and to demonstrate the ability of such metrics to predict slower rates of cognitive decline and protection against diagnostic conversion. Participants with normal cognition (n = 297) and mild cognitive impairment (n = 432) were drawn from the Alzheimer's Disease Neuroimaging Initiative. Resilience metrics were defined at baseline by examining the residuals when regressing brain aging outcomes (hippocampal volume and cognition) on CSF biomarkers. A positive residual reflected better outcomes than expected for a given level of pathology (high resilience). Residuals were integrated into a latent variable model of resilience and validated by testing their ability to independently predict diagnostic conversion, cognitive decline, and the rate of ventricular dilation. Latent variables of resilience predicted a decreased risk of conversion (hazard ratio < 0.54, p < 0.0001), slower cognitive decline (β > 0.02, p < 0.001), and slower rates of ventricular dilation (β < -4.7, p < 2 × 10 -15 ). These results were significant even when analyses were restricted to clinically normal individuals. Furthermore, resilience metrics interacted with biomarker status such that biomarker-positive individuals with low resilience showed the greatest risk of subsequent decline. Robust phenotypes of resilience calculated by leveraging AD biomarkers and baseline brain aging outcomes provide insight into which individuals are at greatest risk of short-term decline. Such comprehensive definitions of resilience are needed to further our understanding of the mechanisms that protect individuals from the clinical manifestation of AD dementia, especially among biomarker-positive individuals. © 2016 American Academy of Neurology.

Solar system anomalies: Revisiting Hubble's law

NASA Astrophysics Data System (ADS)

Plamondon, R.

2017-12-01

This paper investigates the impact of a new metric recently published [R. Plamondon and C. Ouellet-Plamondon, in On Recent Developments in Theoretical and Experimental General Relativity, Astrophysics, and Relativistic Field Theories, edited by K. Rosquist, R. T. Jantzen, and R. Ruffini (World Scientific, Singapore, 2015), p. 1301] for studying the space-time geometry of a static symmetric massive object. This metric depends on a complementary error function (erfc) potential that characterizes the emergent gravitation field predicted by the model. This results in two types of deviations as compared to computations made on the basis of a Newtonian potential: a constant and a radial outcome. One key feature of the metric is that it postulates the existence of an intrinsic physical constant σ , the massive object-specific proper length that scales measurements in its surroundings. Although σ must be evaluated experimentally, we use a heuristic to estimate its value and point out some latent relationships between the Hubble constant, the secular increase in the astronomical unit, and the Pioneers delay. Indeed, highlighting the systematic errors that emerge when the effect of σ is neglected, one can link the Hubble constant H 0 to σ Sun and the secular increase V AU to σ Earth . The accuracy of the resulting numerical predictions, H 0 = 74 . 42 ( 0 . 02 ) ( km / s ) / Mpc and V AU ≅ 7.8 cm yr-1 , calls for more investigations of this new metric by specific experts. Moreover, we investigate the expected impacts of the new metric on the flyby anomalies, and we revisit the Pioneers delay. It is shown that both phenomena could be partly taken into account within the context of this unifying paradigm, with quite accurate numerical predictions. A correction for the osculating asymptotic velocity at the perigee of the order of 10 mm/s and an inward radial acceleration of 8 . 34 × 10 - 10 m / s 2 affecting the Pioneer ! space crafts could be explained by this new model.

SU-D-218-05: Material Quantification in Spectral X-Ray Imaging: Optimization and Validation.

PubMed

Nik, S J; Thing, R S; Watts, R; Meyer, J

2012-06-01

To develop and validate a multivariate statistical method to optimize scanning parameters for material quantification in spectral x-rayimaging. An optimization metric was constructed by extensively sampling the thickness space for the expected number of counts for m (two or three) materials. This resulted in an m-dimensional confidence region ofmaterial quantities, e.g. thicknesses. Minimization of the ellipsoidal confidence region leads to the optimization of energy bins. For the given spectrum, the minimum counts required for effective material separation can be determined by predicting the signal-to-noise ratio (SNR) of the quantification. A Monte Carlo (MC) simulation framework using BEAM was developed to validate the metric. Projection data of the m-materials was generated and material decomposition was performed for combinations of iodine, calcium and water by minimizing the z-score between the expected spectrum and binned measurements. The mean square error (MSE) and variance were calculated to measure the accuracy and precision of this approach, respectively. The minimum MSE corresponds to the optimal energy bins in the BEAM simulations. In the optimization metric, this is equivalent to the smallest confidence region. The SNR of the simulated images was also compared to the predictions from the metric. TheMSE was dominated by the variance for the given material combinations,which demonstrates accurate material quantifications. The BEAMsimulations revealed that the optimization of energy bins was accurate to within 1keV. The SNRs predicted by the optimization metric yielded satisfactory agreement but were expectedly higher for the BEAM simulations due to the inclusion of scattered radiation. The validation showed that the multivariate statistical method provides accurate material quantification, correct location of optimal energy bins and adequateprediction of image SNR. The BEAM code system is suitable for generating spectral x- ray imaging simulations. © 2012 American Association of Physicists in Medicine.

Specification and implementation of IFC based performance metrics to support building life cycle assessment of hybrid energy systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morrissey, Elmer; O'Donnell, James; Keane, Marcus

2004-03-29

Minimizing building life cycle energy consumption is becoming of paramount importance. Performance metrics tracking offers a clear and concise manner of relating design intent in a quantitative form. A methodology is discussed for storage and utilization of these performance metrics through an Industry Foundation Classes (IFC) instantiated Building Information Model (BIM). The paper focuses on storage of three sets of performance data from three distinct sources. An example of a performance metrics programming hierarchy is displayed for a heat pump and a solar array. Utilizing the sets of performance data, two discrete performance effectiveness ratios may be computed, thus offeringmore » an accurate method of quantitatively assessing building performance.« less

A probability metric for identifying high-performing facilities: an application for pay-for-performance programs.

PubMed

Shwartz, Michael; Peköz, Erol A; Burgess, James F; Christiansen, Cindy L; Rosen, Amy K; Berlowitz, Dan

2014-12-01

Two approaches are commonly used for identifying high-performing facilities on a performance measure: one, that the facility is in a top quantile (eg, quintile or quartile); and two, that a confidence interval is below (or above) the average of the measure for all facilities. This type of yes/no designation often does not do well in distinguishing high-performing from average-performing facilities. To illustrate an alternative continuous-valued metric for profiling facilities--the probability a facility is in a top quantile--and show the implications of using this metric for profiling and pay-for-performance. We created a composite measure of quality from fiscal year 2007 data based on 28 quality indicators from 112 Veterans Health Administration nursing homes. A Bayesian hierarchical multivariate normal-binomial model was used to estimate shrunken rates of the 28 quality indicators, which were combined into a composite measure using opportunity-based weights. Rates were estimated using Markov Chain Monte Carlo methods as implemented in WinBUGS. The probability metric was calculated from the simulation replications. Our probability metric allowed better discrimination of high performers than the point or interval estimate of the composite score. In a pay-for-performance program, a smaller top quantile (eg, a quintile) resulted in more resources being allocated to the highest performers, whereas a larger top quantile (eg, being above the median) distinguished less among high performers and allocated more resources to average performers. The probability metric has potential but needs to be evaluated by stakeholders in different types of delivery systems.

Spread spectrum image watermarking based on perceptual quality metric.

PubMed

Zhang, Fan; Liu, Wenyu; Lin, Weisi; Ngan, King Ngi

2011-11-01

Efficient image watermarking calls for full exploitation of the perceptual distortion constraint. Second-order statistics of visual stimuli are regarded as critical features for perception. This paper proposes a second-order statistics (SOS)-based image quality metric, which considers the texture masking effect and the contrast sensitivity in Karhunen-Loève transform domain. Compared with the state-of-the-art metrics, the quality prediction by SOS better correlates with several subjectively rated image databases, in which the images are impaired by the typical coding and watermarking artifacts. With the explicit metric definition, spread spectrum watermarking is posed as an optimization problem: we search for a watermark to minimize the distortion of the watermarked image and to maximize the correlation between the watermark pattern and the spread spectrum carrier. The simple metric guarantees the optimal watermark a closed-form solution and a fast implementation. The experiments show that the proposed watermarking scheme can take full advantage of the distortion constraint and improve the robustness in return.

Use of Normalized Difference Vegetation Index (NDVI) habitat models to predict breeding birds on the San Pedro River, Arizona

USGS Publications Warehouse

McFarland, Tiffany Marie; van Riper, Charles

2013-01-01

Successful management practices of avian populations depend on understanding relationships between birds and their habitat, especially in rare habitats, such as riparian areas of the desert Southwest. Remote-sensing technology has become popular in habitat modeling, but most of these models focus on single species, leaving their applicability to understanding broader community structure and function largely untested. We investigated the usefulness of two Normalized Difference Vegetation Index (NDVI) habitat models to model avian abundance and species richness on the upper San Pedro River in southeastern Arizona. Although NDVI was positively correlated with our bird metrics, the amount of explained variation was low. We then investigated the addition of vegetation metrics and other remote-sensing metrics to improve our models. Although both vegetation metrics and remotely sensed metrics increased the power of our models, the overall explained variation was still low, suggesting that general avian community structure may be too complex for NDVI models.

Measuring the distance between multiple sequence alignments.

PubMed

Blackburne, Benjamin P; Whelan, Simon

2012-02-15

Multiple sequence alignment (MSA) is a core method in bioinformatics. The accuracy of such alignments may influence the success of downstream analyses such as phylogenetic inference, protein structure prediction, and functional prediction. The importance of MSA has lead to the proliferation of MSA methods, with different objective functions and heuristics to search for the optimal MSA. Different methods of inferring MSAs produce different results in all but the most trivial cases. By measuring the differences between inferred alignments, we may be able to develop an understanding of how these differences (i) relate to the objective functions and heuristics used in MSA methods, and (ii) affect downstream analyses. We introduce four metrics to compare MSAs, which include the position in a sequence where a gap occurs or the location on a phylogenetic tree where an insertion or deletion (indel) event occurs. We use both real and synthetic data to explore the information given by these metrics and demonstrate how the different metrics in combination can yield more information about MSA methods and the differences between them. MetAl is a free software implementation of these metrics in Haskell. Source and binaries for Windows, Linux and Mac OS X are available from http://kumiho.smith.man.ac.uk/whelan/software/metal/.

Impact of hydrogeological data on measures of uncertainty, site characterization and environmental performance metrics

NASA Astrophysics Data System (ADS)

de Barros, Felipe P. J.; Ezzedine, Souheil; Rubin, Yoram

2012-02-01

The significance of conditioning predictions of environmental performance metrics (EPMs) on hydrogeological data in heterogeneous porous media is addressed. Conditioning EPMs on available data reduces uncertainty and increases the reliability of model predictions. We present a rational and concise approach to investigate the impact of conditioning EPMs on data as a function of the location of the environmentally sensitive target receptor, data types and spacing between measurements. We illustrate how the concept of comparative information yield curves introduced in de Barros et al. [de Barros FPJ, Rubin Y, Maxwell R. The concept of comparative information yield curves and its application to risk-based site characterization. Water Resour Res 2009;45:W06401. doi:10.1029/2008WR007324] could be used to assess site characterization needs as a function of flow and transport dimensionality and EPMs. For a given EPM, we show how alternative uncertainty reduction metrics yield distinct gains of information from a variety of sampling schemes. Our results show that uncertainty reduction is EPM dependent (e.g., travel times) and does not necessarily indicate uncertainty reduction in an alternative EPM (e.g., human health risk). The results show how the position of the environmental target, flow dimensionality and the choice of the uncertainty reduction metric can be used to assist in field sampling campaigns.

It's All Relative: A Validation of Radiation Quality Comparison Metrics

NASA Technical Reports Server (NTRS)

Chappell, Lori J.; Milder, Caitlin M.; Elgart, S. Robin; Semones, Edward J.

2017-01-01

The difference between high-LET and low-LET radiation is quantified by a measure called relative biological effectiveness (RBE). RBE is defined as the ratio of the dose of a reference radiation to that of a test radiation to achieve the same effect level, and thus, is described either as an iso-effector dose-to-dose ratio. A single dose point is not sufficient to calculate an RBE value; therefore, studies with only one dose point usually calculate an effect-to-effect ratio. While not formally used in radiation protection, these iso-dose values may still be informative. Shuryak, et al 2017 investigated the use of an iso-dose metric termed "radiation effects ratio" (RER) and used both RBE and RER to estimate high-LET risks. To apply RBE or RER to risk prediction, the selected metric must be uniquely defined. That is, the calculated value must be consistent within a model given a constant set of constraints and assumptions, regardless of how effects are defined using statistical transformations from raw endpoint data. We first test the RBE and the RER to determine whether they are uniquely defined using transformations applied to raw data. Then, we test whether both metrics can predict heavy ion response data after simulated effect size scaling between human populations or when converting animal to human endpoints.

Contrast model for three-dimensional vehicles in natural lighting and search performance analysis

NASA Astrophysics Data System (ADS)

Witus, Gary; Gerhart, Grant R.; Ellis, R. Darin

2001-09-01

Ground vehicles in natural lighting tend to have significant and systematic variation in luminance through the presented area. This arises, in large part, from the vehicle surfaces having different orientations and shadowing relative to the source of illumination and the position of the observer. These systematic differences create the appearance of a structured 3D object. The 3D appearance is an important factor in search, figure-ground segregation, and object recognition. We present a contrast metric to predict search and detection performance that accounts for the 3D structure. The approach first computes the contrast of the front (or rear), side, and top surfaces. The vehicle contrast metric is the area-weighted sum of the absolute values of the contrasts of the component surfaces. The 3D structure contrast metric, together with target height, account for more than 80% of the variance in probability of detection and 75% of the variance in search time. When false alarm effects are discounted, they account for 89% of the variance in probability of detection and 95% of the variance in search time. The predictive power of the signature metric, when calibrated to half the data and evaluated against the other half, is 90% of the explanatory power.

An automated, quantitative, and case-specific evaluation of deformable image registration in computed tomography images

NASA Astrophysics Data System (ADS)

Kierkels, R. G. J.; den Otter, L. A.; Korevaar, E. W.; Langendijk, J. A.; van der Schaaf, A.; Knopf, A. C.; Sijtsema, N. M.

2018-02-01

A prerequisite for adaptive dose-tracking in radiotherapy is the assessment of the deformable image registration (DIR) quality. In this work, various metrics that quantify DIR uncertainties are investigated using realistic deformation fields of 26 head and neck and 12 lung cancer patients. Metrics related to the physiologically feasibility (the Jacobian determinant, harmonic energy (HE), and octahedral shear strain (OSS)) and numerically robustness of the deformation (the inverse consistency error (ICE), transitivity error (TE), and distance discordance metric (DDM)) were investigated. The deformable registrations were performed using a B-spline transformation model. The DIR error metrics were log-transformed and correlated (Pearson) against the log-transformed ground-truth error on a voxel level. Correlations of r  ⩾  0.5 were found for the DDM and HE. Given a DIR tolerance threshold of 2.0 mm and a negative predictive value of 0.90, the DDM and HE thresholds were 0.49 mm and 0.014, respectively. In conclusion, the log-transformed DDM and HE can be used to identify voxels at risk for large DIR errors with a large negative predictive value. The HE and/or DDM can therefore be used to perform automated quality assurance of each CT-based DIR for head and neck and lung cancer patients.

Accelerometer-derived activity correlates with volitional swimming speed in lake sturgeon (Acipenser fulvescens)

USGS Publications Warehouse

Thiem, J.D.; Dawson, J.W.; Gleiss, A.C.; Martins, E.G.; Haro, Alexander J.; Castro-Santos, Theodore R.; Danylchuk, A.J.; Wilson, R.P.; Cooke, S.J.

2015-01-01

Quantifying fine-scale locomotor behaviours associated with different activities is challenging for free-swimming fish.Biologging and biotelemetry tools can help address this problem. An open channel flume was used to generate volitionalswimming speed (Us) estimates of cultured lake sturgeon (Acipenser fulvescens Rafinesque, 1817) and these were paired withsimultaneously recorded accelerometer-derived metrics of activity obtained from three types of data-storage tags. This studyexamined whether a predictive relationship could be established between four different activity metrics (tail-beat frequency(TBF), tail-beat acceleration amplitude (TBAA), overall dynamic body acceleration (ODBA), and vectorial dynamic body acceleration(VeDBA)) and the swimming speed of A. fulvescens. Volitional Us of sturgeon ranged from 0.48 to 2.70 m·s−1 (0.51–3.18 bodylengths (BL) · s−1). Swimming speed increased linearly with all accelerometer-derived metrics, and when all tag types werecombined, Us increased 0.46 BL·s−1 for every 1 Hz increase in TBF, and 0.94, 0.61, and 0.94 BL·s−1 for every 1g increase in TBAA,ODBA, and VeDBA, respectively. Predictive relationships varied among tag types and tag-specific parameter estimates of Us arepresented for all metrics. This use of acceleration data-storage tags demonstrated their applicability for the field quantificationof sturgeon swimming speed.

Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description.

PubMed

Gu, Ke; Jakhetiya, Vinit; Qiao, Jun-Fei; Li, Xiaoli; Lin, Weisi; Thalmann, Daniel

2017-07-28

New challenges have been brought out along with the emerging of 3D-related technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR). Free viewpoint video (FVV), due to its applications in remote surveillance, remote education, etc, based on the flexible selection of direction and viewpoint, has been perceived as the development direction of next-generation video technologies and has drawn a wide range of researchers' attention. Since FVV images are synthesized via a depth image-based rendering (DIBR) procedure in the "blind" environment (without reference images), a reliable real-time blind quality evaluation and monitoring system is urgently required. But existing assessment metrics do not render human judgments faithfully mainly because geometric distortions are generated by DIBR. To this end, this paper proposes a novel referenceless quality metric of DIBR-synthesized images using the autoregression (AR)-based local image description. It was found that, after the AR prediction, the reconstructed error between a DIBR-synthesized image and its AR-predicted image can accurately capture the geometry distortion. The visual saliency is then leveraged to modify the proposed blind quality metric to a sizable margin. Experiments validate the superiority of our no-reference quality method as compared with prevailing full-, reduced- and no-reference models.

Pressure-specific and multiple pressure response of fish assemblages in European running waters☆

PubMed Central

Schinegger, Rafaela; Trautwein, Clemens; Schmutz, Stefan

2013-01-01

We classified homogenous river types across Europe and searched for fish metrics qualified to show responses to specific pressures (hydromorphological pressures or water quality pressures) vs. multiple pressures in these river types. We analysed fish taxa lists from 3105 sites in 16 ecoregions and 14 countries. Sites were pre-classified for 15 selected pressures to separate unimpacted from impacted sites. Hierarchical cluster analysis was used to split unimpacted sites into four homogenous river types based on species composition and geographical location. Classification trees were employed to predict associated river types for impacted sites with four environmental variables. We defined a set of 129 candidate fish metrics to select the best reacting metrics for each river type. The candidate metrics represented tolerances/intolerances of species associated with six metric types: habitat, migration, water quality sensitivity, reproduction, trophic level and biodiversity. The results showed that 17 uncorrelated metrics reacted to pressures in the four river types. Metrics responded specifically to water quality pressures and hydromorphological pressures in three river types and to multiple pressures in all river types. Four metrics associated with water quality sensitivity showed a significant reaction in up to three river types, whereas 13 metrics were specific to individual river types. Our results contribute to the better understanding of fish assemblage response to human pressures at a pan-European scale. The results are especially important for European river management and restoration, as it is necessary to uncover underlying processes and effects of human pressures on aquatic communities. PMID:24003262

Predictive modeling of nanomaterial exposure effects in biological systems

PubMed Central

Liu, Xiong; Tang, Kaizhi; Harper, Stacey; Harper, Bryan; Steevens, Jeffery A; Xu, Roger

2013-01-01

Background Predictive modeling of the biological effects of nanomaterials is critical for industry and policymakers to assess the potential hazards resulting from the application of engineered nanomaterials. Methods We generated an experimental dataset on the toxic effects experienced by embryonic zebrafish due to exposure to nanomaterials. Several nanomaterials were studied, such as metal nanoparticles, dendrimer, metal oxide, and polymeric materials. The embryonic zebrafish metric (EZ Metric) was used as a screening-level measurement representative of adverse effects. Using the dataset, we developed a data mining approach to model the toxic endpoints and the overall biological impact of nanomaterials. Data mining techniques, such as numerical prediction, can assist analysts in developing risk assessment models for nanomaterials. Results We found several important attributes that contribute to the 24 hours post-fertilization (hpf) mortality, such as dosage concentration, shell composition, and surface charge. These findings concur with previous studies on nanomaterial toxicity using embryonic zebrafish. We conducted case studies on modeling the overall effect/impact of nanomaterials and the specific toxic endpoints such as mortality, delayed development, and morphological malformations. The results show that we can achieve high prediction accuracy for certain biological effects, such as 24 hpf mortality, 120 hpf mortality, and 120 hpf heart malformation. The results also show that the weighting scheme for individual biological effects has a significant influence on modeling the overall impact of nanomaterials. Sample prediction models can be found at http://neiminer.i-a-i.com/nei_models. Conclusion The EZ Metric-based data mining approach has been shown to have predictive power. The results provide valuable insights into the modeling and understanding of nanomaterial exposure effects. PMID:24098077

Abstract Conceptual Feature Ratings Predict Gaze within Written Word Arrays: Evidence from a Visual Wor(l)d Paradigm

ERIC Educational Resources Information Center

Primativo, Silvia; Reilly, Jamie; Crutch, Sebastian J

2017-01-01

The Abstract Conceptual Feature (ACF) framework predicts that word meaning is represented within a high-dimensional semantic space bounded by weighted contributions of perceptual, affective, and encyclopedic information. The ACF, like latent semantic analysis, is amenable to distance metrics between any two words. We applied predictions of the ACF…

Using community-level metrics to monitor the effects of marine protected areas on biodiversity.

PubMed

Soykan, Candan U; Lewison, Rebecca L

2015-06-01

Marine protected areas (MPAs) are used to protect species, communities, and their associated habitats, among other goals. Measuring MPA efficacy can be challenging, however, particularly when considering responses at the community level. We gathered 36 abundance and 14 biomass data sets on fish assemblages and used meta-analysis to evaluate the ability of 22 distinct community diversity metrics to detect differences in community structure between MPAs and nearby control sites. We also considered the effects of 6 covariates-MPA size and age, MPA size and age interaction, latitude, total species richness, and level of protection-on each metric. Some common metrics, such as species richness and Shannon diversity, did not differ consistently between MPA and control sites, whereas other metrics, such as total abundance and biomass, were consistently different across studies. Metric responses derived from the biomass data sets were more consistent than those based on the abundance data sets, suggesting that community-level biomass differs more predictably than abundance between MPA and control sites. Covariate analyses indicated that level of protection, latitude, MPA size, and the interaction between MPA size and age affect metric performance. These results highlight a handful of metrics, several of which are little known, that could be used to meet the increasing demand for community-level indicators of MPA effectiveness. © 2015 Society for Conservation Biology.

Systems Engineering Design Via Experimental Operation Research: Complex Organizational Metric for Programmatic Risk Environments (COMPRE)

NASA Technical Reports Server (NTRS)

Mog, Robert A.

1999-01-01

Unique and innovative graph theory, neural network, organizational modeling, and genetic algorithms are applied to the design and evolution of programmatic and organizational architectures. Graph theory representations of programs and organizations increase modeling capabilities and flexibility, while illuminating preferable programmatic/organizational design features. Treating programs and organizations as neural networks results in better system synthesis, and more robust data modeling. Organizational modeling using covariance structures enhances the determination of organizational risk factors. Genetic algorithms improve programmatic evolution characteristics, while shedding light on rulebase requirements for achieving specified technological readiness levels, given budget and schedule resources. This program of research improves the robustness and verifiability of systems synthesis tools, including the Complex Organizational Metric for Programmatic Risk Environments (COMPRE).

Notes on wall crossing and instanton in compactified gauge theory with matter

NASA Astrophysics Data System (ADS)

Chen, Heng-Yu; Petunin, Kirill

2010-10-01

We study the quantum effects on the Coulomb branch of mathcal{N} = 2 SU(2) super-symmetric Yang-Mills with fundamental matters compactified on {mathbb{R}^3} × {S^1} , and extract the explicit perturbative and leading non-perturbative corrections to the moduli space metric predicted from the recent work of Gaiotto, Moore and Neitzke on wall-crossing [1]. We verify the predicted metric by computing the leading weak coupling instanton contribution to the four fermion correlation using standard field theory techniques, and demonstrate perfect agreement. We also demonstrate how previously known three dimensional quantities can be recovered in appropriate small radius limit, and provide a simple geometric picture from brane construction.

Reconstructing the metric of the local Universe from number counts observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vallejo, Sergio Andres; Romano, Antonio Enea, E-mail: antonio.enea.romano@cern.ch

Number counts observations available with new surveys such as the Euclid mission will be an important source of information about the metric of the Universe. We compute the low red-shift expansion for the energy density and the density contrast using an exact spherically symmetric solution in presence of a cosmological constant. At low red-shift the expansion is more precise than linear perturbation theory prediction. We then use the local expansion to reconstruct the metric from the monopole of the density contrast. We test the inversion method using numerical calculations and find a good agreement within the regime of validity ofmore » the red-shift expansion. The method could be applied to observational data to reconstruct the metric of the local Universe with a level of precision higher than the one achievable using perturbation theory.« less

[Perceptual sharpness metric for visible and infrared color fusion images].

PubMed

Gao, Shao-Shu; Jin, Wei-Qi; Wang, Xia; Wang, Ling-Xue; Luo, Yuan

2012-12-01

For visible and infrared color fusion images, objective sharpness assessment model is proposed to measure the clarity of detail and edge definition of the fusion image. Firstly, the contrast sensitivity functions (CSF) of the human visual system is used to reduce insensitive frequency components under certain viewing conditions. Secondly, perceptual contrast model, which takes human luminance masking effect into account, is proposed based on local band-limited contrast model. Finally, the perceptual contrast is calculated in the region of interest (contains image details and edges) in the fusion image to evaluate image perceptual sharpness. Experimental results show that the proposed perceptual sharpness metrics provides better predictions, which are more closely matched to human perceptual evaluations, than five existing sharpness (blur) metrics for color images. The proposed perceptual sharpness metrics can evaluate the perceptual sharpness for color fusion images effectively.

A framework for quantification of groundwater dynamics - redundancy and transferability of hydro(geo-)logical metrics

NASA Astrophysics Data System (ADS)

Heudorfer, Benedikt; Haaf, Ezra; Barthel, Roland; Stahl, Kerstin

2017-04-01

A new framework for quantification of groundwater dynamics has been proposed in a companion study (Haaf et al., 2017). In this framework, a number of conceptual aspects of dynamics, such as seasonality, regularity, flashiness or inter-annual forcing, are described, which are then linked to quantitative metrics. Hereby, a large number of possible metrics are readily available from literature, such as Pardé Coefficients, Colwell's Predictability Indices or Base Flow Index. In the present work, we focus on finding multicollinearity and in consequence redundancy among the metrics representing different patterns of dynamics found in groundwater hydrographs. This is done also to verify the categories of dynamics aspects suggested by Haaf et al., 2017. To determine the optimal set of metrics we need to balance the desired minimum number of metrics and the desired maximum descriptive property of the metrics. To do this, a substantial number of candidate metrics are applied to a diverse set of groundwater hydrographs from France, Germany and Austria within the northern alpine and peri-alpine region. By applying Principle Component Analysis (PCA) to the correlation matrix of the metrics, we determine a limited number of relevant metrics that describe the majority of variation in the dataset. The resulting reduced set of metrics comprise an optimized set that can be used to describe the aspects of dynamics that were identified within the groundwater dynamics framework. For some aspects of dynamics a single significant metric could be attributed. Other aspects have a more fuzzy quality that can only be described by an ensemble of metrics and are re-evaluated. The PCA is furthermore applied to groups of groundwater hydrographs containing regimes of similar behaviour in order to explore transferability when applying the metric-based characterization framework to groups of hydrographs from diverse groundwater systems. In conclusion, we identify an optimal number of metrics, which are readily available for usage in studies on groundwater dynamics, intended to help overcome analytical limitations that exist due to the complexity of groundwater dynamics. Haaf, E., Heudorfer, B., Stahl, K., Barthel, R., 2017. A framework for quantification of groundwater dynamics - concepts and hydro(geo-)logical metrics. EGU General Assembly 2017, Vienna, Austria.

Spatial statistical network models for stream and river temperature in New England, USA

NASA Astrophysics Data System (ADS)

Detenbeck, Naomi E.; Morrison, Alisa C.; Abele, Ralph W.; Kopp, Darin A.

2016-08-01

Watershed managers are challenged by the need for predictive temperature models with sufficient accuracy and geographic breadth for practical use. We described thermal regimes of New England rivers and streams based on a reduced set of metrics for the May-September growing season (July or August median temperature, diurnal rate of change, and magnitude and timing of growing season maximum) chosen through principal component analysis of 78 candidate metrics. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance along the flow network and Euclidean distance between points. Calculation of spatial autocorrelation based on travel or retention time in place of network distance yielded tighter-fitting Torgegrams with less scatter but did not improve overall model prediction accuracy. We predicted monthly median July or August stream temperatures as a function of median air temperature, estimated urban heat island effect, shaded solar radiation, main channel slope, watershed storage (percent lake and wetland area), percent coarse-grained surficial deposits, and presence or maximum depth of a lake immediately upstream, with an overall root-mean-square prediction error of 1.4 and 1.5°C, respectively. Growing season maximum water temperature varied as a function of air temperature, local channel slope, shaded August solar radiation, imperviousness, and watershed storage. Predictive models for July or August daily range, maximum daily rate of change, and timing of growing season maximum were statistically significant but explained a much lower proportion of variance than the above models (5-14% of total).

Human Performance Optimization Metrics: Consensus Findings, Gaps, and Recommendations for Future Research.

PubMed

Nindl, Bradley C; Jaffin, Dianna P; Dretsch, Michael N; Cheuvront, Samuel N; Wesensten, Nancy J; Kent, Michael L; Grunberg, Neil E; Pierce, Joseph R; Barry, Erin S; Scott, Jonathan M; Young, Andrew J; OʼConnor, Francis G; Deuster, Patricia A

2015-11-01

Human performance optimization (HPO) is defined as "the process of applying knowledge, skills and emerging technologies to improve and preserve the capabilities of military members, and organizations to execute essential tasks." The lack of consensus for operationally relevant and standardized metrics that meet joint military requirements has been identified as the single most important gap for research and application of HPO. In 2013, the Consortium for Health and Military Performance hosted a meeting to develop a toolkit of standardized HPO metrics for use in military and civilian research, and potentially for field applications by commanders, units, and organizations. Performance was considered from a holistic perspective as being influenced by various behaviors and barriers. To accomplish the goal of developing a standardized toolkit, key metrics were identified and evaluated across a spectrum of domains that contribute to HPO: physical performance, nutritional status, psychological status, cognitive performance, environmental challenges, sleep, and pain. These domains were chosen based on relevant data with regard to performance enhancers and degraders. The specific objectives at this meeting were to (a) identify and evaluate current metrics for assessing human performance within selected domains; (b) prioritize metrics within each domain to establish a human performance assessment toolkit; and (c) identify scientific gaps and the needed research to more effectively assess human performance across domains. This article provides of a summary of 150 total HPO metrics across multiple domains that can be used as a starting point-the beginning of an HPO toolkit: physical fitness (29 metrics), nutrition (24 metrics), psychological status (36 metrics), cognitive performance (35 metrics), environment (12 metrics), sleep (9 metrics), and pain (5 metrics). These metrics can be particularly valuable as the military emphasizes a renewed interest in Human Dimension efforts, and leverages science, resources, programs, and policies to optimize the performance capacities of all Service members.

EOID System Model Validation, Metrics, and Synthetic Clutter Generation

DTIC Science & Technology

2003-09-30

Our long-term goal is to accurately predict the capability of the current generation of laser-based underwater imaging sensors to perform Electro ... Optic Identification (EOID) against relevant targets in a variety of realistic environmental conditions. The models will predict the impact of

Measuring the Effects of Virtual Pair Programming in an Introductory Programming Java Course

ERIC Educational Resources Information Center

Zacharis, N. Z.

2011-01-01

This study investigated the effectiveness of virtual pair programming (VPP) on student performance and satisfaction in an introductory Java course. Students used online tools that integrated desktop sharing and real-time communication, and the metrics examined showed that VPP is an acceptable alternative to individual programming experience.…

ACSYNT inner loop flight control design study

NASA Technical Reports Server (NTRS)

Bortins, Richard; Sorensen, John A.

1993-01-01

The NASA Ames Research Center developed the Aircraft Synthesis (ACSYNT) computer program to synthesize conceptual future aircraft designs and to evaluate critical performance metrics early in the design process before significant resources are committed and cost decisions made. ACSYNT uses steady-state performance metrics, such as aircraft range, payload, and fuel consumption, and static performance metrics, such as the control authority required for the takeoff rotation and for landing with an engine out, to evaluate conceptual aircraft designs. It can also optimize designs with respect to selected criteria and constraints. Many modern aircraft have stability provided by the flight control system rather than by the airframe. This may allow the aircraft designer to increase combat agility, or decrease trim drag, for increased range and payload. This strategy requires concurrent design of the airframe and the flight control system, making trade-offs of performance and dynamics during the earliest stages of design. ACSYNT presently lacks means to implement flight control system designs but research is being done to add methods for predicting rotational degrees of freedom and control effector performance. A software module to compute and analyze the dynamics of the aircraft and to compute feedback gains and analyze closed loop dynamics is required. The data gained from these analyses can then be fed back to the aircraft design process so that the effects of the flight control system and the airframe on aircraft performance can be included as design metrics. This report presents results of a feasibility study and the initial design work to add an inner loop flight control system (ILFCS) design capability to the stability and control module in ACSYNT. The overall objective is to provide a capability for concurrent design of the aircraft and its flight control system, and enable concept designers to improve performance by exploiting the interrelationships between aircraft and flight control system design parameters.

Development of quality metrics for ambulatory pediatric cardiology: Infection prevention.

PubMed

Johnson, Jonathan N; Barrett, Cindy S; Franklin, Wayne H; Graham, Eric M; Halnon, Nancy J; Hattendorf, Brandy A; Krawczeski, Catherine D; McGovern, James J; O'Connor, Matthew J; Schultz, Amy H; Vinocur, Jeffrey M; Chowdhury, Devyani; Anderson, Jeffrey B

2017-12-01

In 2012, the American College of Cardiology's (ACC) Adult Congenital and Pediatric Cardiology Council established a program to develop quality metrics to guide ambulatory practices for pediatric cardiology. The council chose five areas on which to focus their efforts; chest pain, Kawasaki Disease, tetralogy of Fallot, transposition of the great arteries after arterial switch, and infection prevention. Here, we sought to describe the process, evaluation, and results of the Infection Prevention Committee's metric design process. The infection prevention metrics team consisted of 12 members from 11 institutions in North America. The group agreed to work on specific infection prevention topics including antibiotic prophylaxis for endocarditis, rheumatic fever, and asplenia/hyposplenism; influenza vaccination and respiratory syncytial virus prophylaxis (palivizumab); preoperative methods to reduce intraoperative infections; vaccinations after cardiopulmonary bypass; hand hygiene; and testing to identify splenic function in patients with heterotaxy. An extensive literature review was performed. When available, previously published guidelines were used fully in determining metrics. The committee chose eight metrics to submit to the ACC Quality Metric Expert Panel for review. Ultimately, metrics regarding hand hygiene and influenza vaccination recommendation for patients did not pass the RAND analysis. Both endocarditis prophylaxis metrics and the RSV/palivizumab metric passed the RAND analysis but fell out during the open comment period. Three metrics passed all analyses, including those for antibiotic prophylaxis in patients with heterotaxy/asplenia, for influenza vaccination compliance in healthcare personnel, and for adherence to recommended regimens of secondary prevention of rheumatic fever. The lack of convincing data to guide quality improvement initiatives in pediatric cardiology is widespread, particularly in infection prevention. Despite this, three metrics were able to be developed for use in the ACC's quality efforts for ambulatory practice. © 2017 Wiley Periodicals, Inc.

Facial Structure Predicts Sexual Orientation in Both Men and Women.

PubMed

Skorska, Malvina N; Geniole, Shawn N; Vrysen, Brandon M; McCormick, Cheryl M; Bogaert, Anthony F

2015-07-01

Biological models have typically framed sexual orientation in terms of effects of variation in fetal androgen signaling on sexual differentiation, although other biological models exist. Despite marked sex differences in facial structure, the relationship between sexual orientation and facial structure is understudied. A total of 52 lesbian women, 134 heterosexual women, 77 gay men, and 127 heterosexual men were recruited at a Canadian campus and various Canadian Pride and sexuality events. We found that facial structure differed depending on sexual orientation; substantial variation in sexual orientation was predicted using facial metrics computed by a facial modelling program from photographs of White faces. At the univariate level, lesbian and heterosexual women differed in 17 facial features (out of 63) and four were unique multivariate predictors in logistic regression. Gay and heterosexual men differed in 11 facial features at the univariate level, of which three were unique multivariate predictors. Some, but not all, of the facial metrics differed between the sexes. Lesbian women had noses that were more turned up (also more turned up in heterosexual men), mouths that were more puckered, smaller foreheads, and marginally more masculine face shapes (also in heterosexual men) than heterosexual women. Gay men had more convex cheeks, shorter noses (also in heterosexual women), and foreheads that were more tilted back relative to heterosexual men. Principal components analysis and discriminant functions analysis generally corroborated these results. The mechanisms underlying variation in craniofacial structure--both related and unrelated to sexual differentiation--may thus be important in understanding the development of sexual orientation.

Community-wide Validation of Geospace Model Ground Magnetic Field Perturbation Predictions to Support Model Transition to Operations

NASA Technical Reports Server (NTRS)

Pulkkinen, A.; Rastaetter, L.; Kuznetsova, M.; Singer, H.; Balch, C.; Weimer, D.; Toth, G.; Ridley, A.; Gombosi, T.; Wiltberger, M.;

Analyzing System on A Chip Single Event Upset Responses using Single Event Upset Data, Classical Reliability Models, and Space Environment Data

NASA Technical Reports Server (NTRS)

Berg, Melanie; LaBel, Kenneth; Campola, Michael; Xapsos, Michael

2017-01-01

We are investigating the application of classical reliability performance metrics combined with standard single event upset (SEU) analysis data. We expect to relate SEU behavior to system performance requirements. Our proposed methodology will provide better prediction of SEU responses in harsh radiation environments with confidence metrics. single event upset (SEU), single event effect (SEE), field programmable gate array devises (FPGAs)

Geostatistical Prediction of Microbial Water Quality Throughout a Stream Network Using Meteorology, Land Cover, and Spatiotemporal Autocorrelation.

PubMed

Holcomb, David A; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R

2018-06-25

Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modeled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was ≥90%, ≤10%, or >10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.

Linking Field and Satellite Observations to Reveal Differences in Single vs. Double-Cropped Soybean Yields in Central Brazil

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.

2016-12-01

Soy-corn double cropping (DC) has been widely adopted in Central Brazil alongside single cropped (SC) soybean production. DC involves different cropping calendars, soy varieties, and may be associated with different crop yield patterns and volatility than SC. Study of the performance of the region's agriculture in a changing climate depends on tracking differences in the productivity of SC vs. DC, but has been limited by crop yield data that conflate the two systems. We predicted SC and DC yields across Central Brazil, drawing on field observations and remotely sensed data. We first modeled field yield estimates as a function of remotely sensed DC status and vegetation index (VI) metrics, and other management and biophysical factors. We then used the statistical model estimated to predict SC and DC soybean yields at each 500 m2 grid cell of Central Brazil for harvest years 2001 - 2015. The yield estimation model was constructed using 1) a repeated cross-sectional survey of soybean yields and management factors for years 2007-2015, 2) a custom agricultural land cover classification dataset which assimilates earlier datasets for the region, and 3) 500m 8-day MODIS image composites used to calculate the wide dynamic range vegetation index (WDRVI) and derivative metrics such as area under the curve for WDRVI values in critical crop development periods. A statistical yield estimation model which primarily entails WDRVI metrics, DC status, and spatial fixed effects was developed on a subset of the yield dataset. Model validation was conducted by predicting previously withheld yield records, and then assessing error and goodness-of-fit for predicted values with metrics including root mean squared error (RMSE), mean squared error (MSE), and R2. We found a statistical yield estimation model which incorporates WDRVI and DC status to be way to estimate crop yields over the region. Statistical properties of the resulting gridded yield dataset may be valuable for understanding linkages between crop yields, farm management factors, and climate.

Abstract conceptual feature ratings predict gaze within written word arrays: evidence from a Visual Wor(l)d paradigm

PubMed Central

Primativo, Silvia; Reilly, Jamie; Crutch, Sebastian J

2016-01-01

The Abstract Conceptual Feature (ACF) framework predicts that word meaning is represented within a high-dimensional semantic space bounded by weighted contributions of perceptual, affective, and encyclopedic information. The ACF, like latent semantic analysis, is amenable to distance metrics between any two words. We applied predictions of the ACF framework to abstract words using eye tracking via an adaptation of the classical ‘visual word paradigm’. Healthy adults (N=20) selected the lexical item most related to a probe word in a 4-item written word array comprising the target and three distractors. The relation between the probe and each of the four words was determined using the semantic distance metrics derived from ACF ratings. Eye-movement data indicated that the word that was most semantically related to the probe received more and longer fixations relative to distractors. Importantly, in sets where participants did not provide an overt behavioral response, the fixation rates were none the less significantly higher for targets than distractors, closely resembling trials where an expected response was given. Furthermore, ACF ratings which are based on individual words predicted eye fixation metrics of probe-target similarity at least as well as latent semantic analysis ratings which are based on word co-occurrence. The results provide further validation of Euclidean distance metrics derived from ACF ratings as a measure of one facet of the semantic relatedness of abstract words and suggest that they represent a reasonable approximation of the organization of abstract conceptual space. The data are also compatible with the broad notion that multiple sources of information (not restricted to sensorimotor and emotion information) shape the organization of abstract concepts. Whilst the adapted ‘visual word paradigm’ is potentially a more metacognitive task than the classical visual world paradigm, we argue that it offers potential utility for studying abstract word comprehension. PMID:26901571

Response Assessment and Prediction in Esophageal Cancer Patients via F-18 FDG PET/CT Scans

NASA Astrophysics Data System (ADS)

Higgins, Kyle J.

Purpose: The purpose of this study is to utilize F-18 FDG PET/CT scans to determine an indicator for the response of esophageal cancer patients during radiation therapy. There is a need for such an indicator since local failures are quite common in esophageal cancer patients despite modern treatment techniques. If an indicator is found, a patient's treatment strategy may be altered to possibly improve the outcome. This is investigated with various standard uptake volume (SUV) metrics along with image texture features. The metrics and features showing the most promise and indicating response are used in logistic regression analysis to find an equation for the prediction of response. Materials and Methods: 28 patients underwent F-18 FDG PET/CT scans prior to the start of radiation therapy (RT). A second PET/CT scan was administered following the delivery of ~32 Gray (Gy) of dose. A physician contoured gross tumor volume (GTV) was used to delineate a PET based GTV (GTV-pre-PET) based on a threshold of >40% and >20% of the maximum SUV value in the GTV. Deformable registration was used in VelocityAI software to register the pre-treatment and intra-treatment CT scans so that the GTV-pre-PET contours could be transferred from the pre to intra scans (GTV-intra-PET). The fractional decrease in the maximum, mean, volume to the highest intensity 10%-90%, and combination SUV metrics of the significant previous SUV metrics were compared to post-treatment pathologic response for an indication of response. Next for the >40% threshold, texture features based on a neighborhood gray-tone dimension matrix (NGTDM) were analyzed. The fractional decrease in coarseness, contrast, busyness, complexity, and texture strength were compared to the pathologic response of the patients. From these previous two types of analysis, SUV and texture features, the two most significant results were used in logistic regression analysis to find an equation to predict the probability of a non-responder. These probability values were then used to compare against the pathological response to test for indication of response. Results: 20 of the 28 patients underwent post treatment surgery and their pathologic response was determined. 9 of the patients were classified as being responders (treatment effect grade ≤ 1) while 11 of the patients were classified as being non-responders (treatment effect grade > 1). The fractional difference in the different SUV metrics has shown that the most commonly used maximum SUV and mean SUV were not significant in determining response to the treatment. Other SUV metrics however did show promise as being indicators. For the >40% threshold SUV to the highest 10%, 20%, and 30% (SUV10%, SUV20%, SUV30%) were found to significantly distinguish between responders and non-responders (p=0.004) and had an area under the Receiver Operating Characteristic curve (AUC) of 0.7778. Combining these significant metrics (SUV10% with SUV20% and SUV 20% with SUV30%) also was able to distinguish response (p=0.033, AUC=0.7879). Cross validation of these results shown that these metrics could be used to find the response on previously unseen data. The three individual SUV terms distinguished responders from non-responders with a sensitivity of 0.7143 and a specificity of 0.6400 from the cross validation. Cross validation yielded a sensitivity of 0.8333 and a specificity of 0.7727 for the combination of SUV10% and SUV20% and a sensitivity of 0.8333 and specificity of 0.7273 for the combination of SUV20% and SUV30%. For the >20% threshold two SUV metrics were found to be significant. These were the SUV to the highest 10% and 20% (p=0.0048). The AUC for the 10% metrics was 0.7677 and for the 20% metric it was 0.7374. Cross validation of these two metrics shown that the 10% metric was the better indicator with being able to distinguish response in unseen data with a sensitivity of 0.7778 and a specificity of 0.7727. The only texture feature that was able to determine response was complexity (p-0.04, AUC=0.7778). This metric was no more significant than the three individual SUV metrics but less significant than both of the combination metrics. As with the SUV metrics, cross validation was able to show the robustness of these results. Cross validation yielded a result that could accurately distinguish a response with a sensitivity of 0.8333 and a specificity of 0.7273. Logistic regression fit with features of the two most significant results (complexity and combination of SUV10% with SUV20%) yielded the most significant result (p=0.004. AUC=0.8889). Cross validation of this model resulted in a sensitivity of 0.7982 and a specificity 0.7940. This shows that the model would accurately predict the response to unseen data. Conclusions: This study revealed that previously used SUV metrics, maximum and mean SUV, may have to be rethought about being used to determine a response in esophageal cancer patients. The most promising SUV metric was a combination of the SUV10% and SUV20% metric for a GTV created from a threshold of >40% of the maximum SUV value, while the most significant texture feature was complexity. The overall best indicator was the logistic regression fit of the significant metrics of complexity and combination of SUV10% with SUV20%. This was able to distinguish responders from non-responders with a threshold of 0.3186 (sensitivity=0.9091, specificity=0.7778).

Research on quality metrics of wireless adaptive video streaming

NASA Astrophysics Data System (ADS)

Li, Xuefei

2018-04-01

With the development of wireless networks and intelligent terminals, video traffic has increased dramatically. Adaptive video streaming has become one of the most promising video transmission technologies. For this type of service, a good QoS (Quality of Service) of wireless network does not always guarantee that all customers have good experience. Thus, new quality metrics have been widely studies recently. Taking this into account, the objective of this paper is to investigate the quality metrics of wireless adaptive video streaming. In this paper, a wireless video streaming simulation platform with DASH mechanism and multi-rate video generator is established. Based on this platform, PSNR model, SSIM model and Quality Level model are implemented. Quality Level Model considers the QoE (Quality of Experience) factors such as image quality, stalling and switching frequency while PSNR Model and SSIM Model mainly consider the quality of the video. To evaluate the performance of these QoE models, three performance metrics (SROCC, PLCC and RMSE) which are used to make a comparison of subjective and predicted MOS (Mean Opinion Score) are calculated. From these performance metrics, the monotonicity, linearity and accuracy of these quality metrics can be observed.

A cross-validation package driving Netica with python

USGS Publications Warehouse

Fienen, Michael N.; Plant, Nathaniel G.

2014-01-01

Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).

A STATISTICAL MODELING METHODOLOGY FOR THE DETECTION, QUANTIFICATION, AND PREDICTION OF ECOLOGICAL THRESHOLDS

EPA Science Inventory

This study will provide a general methodology for integrating threshold information from multiple species ecological metrics, allow for prediction of changes of alternative stable states, and provide a risk assessment tool that can be applied to adaptive management. The integr...

Customizing Countermeasure Prescriptions using Predictive Measures of Sensorimotor Adaptability

NASA Technical Reports Server (NTRS)

Bloomberg, J. J.; Peters, B. T.; Mulavara, A. P.; Miller, C. A.; Batson, C. D.; Wood, S. J.; Guined, J. R.; Cohen, H. S.; Buccello-Stout, R.; DeDios, Y. E.;

Conservation laws for waves on a string from isometries and conformal isometries of the Minkowski metric

NASA Astrophysics Data System (ADS)

Miller, Brandon; Menon, Balraj

Noether's theorems describe the interplay between variational symmetries (symmetries of the action functional) and local conservation laws admitted by a physical system. In Lagrangian field theories defined on a differentiable manifold  endowed with a metric g, the variational symmetries are intimately tied to the isometries of the metric g. We highlight this connection by relating the variational symmetries of waves on a string to the isometries and conformal isometries of the Minkowski metric. The associated local conservation laws and conserved quantities for this physical system are determined and their physical significance discussed. The geometric nature of these conservation laws are further elucidated by discussing their Poisson bracket formulation in the Hamiltonian framework. This work was partially supported by the UCA Robert Noyce Scholars Program.

Computer programs for producing single-event aircraft noise data for specific engine power and meteorological conditions for use with USAF (United States Air Force) community noise model (NOISEMAP)

NASA Astrophysics Data System (ADS)

Mohlman, H. T.

1983-04-01

The Air Force community noise prediction model (NOISEMAP) is used to describe the aircraft noise exposure around airbases and thereby aid airbase planners to minimize exposure and prevent community encroachment which could limit mission effectiveness of the installation. This report documents two computer programs (OMEGA 10 and OMEGA 11) which were developed to prepare aircraft flight and ground runup noise data for input to NOISEMAP. OMEGA 10 is for flight operations and OMEGA 11 is for aircraft ground runups. All routines in each program are documented at a level useful to a programmer working with the code or a reader interested in a general overview of what happens within a specific subroutine. Both programs input normalized, reference aircraft noise data; i.e., data at a standard reference distance from the aircraft, for several fixed engine power settings, a reference airspeed and standard day meteorological conditions. Both programs operate on these normalized, reference data in accordance with user-defined, non-reference conditions to derive single-event noise data for 22 distances (200 to 25,000 feet) in a variety of physical and psycho-acoustic metrics. These outputs are in formats ready for input to NOISEMAP.

Prognostic Value of Quantitative Metabolic Metrics on Baseline Pre-Sunitinib FDG PET/CT in Advanced Renal Cell Carcinoma

PubMed Central

Minamimoto, Ryogo; Barkhodari, Amir; Harshman, Lauren; Srinivas, Sandy; Quon, Andrew

2016-01-01

Purpose The objective of this study was to prospectively evaluate various quantitative metrics on FDG PET/CT for monitoring sunitinib therapy and predicting prognosis in patients with metastatic renal cell cancer (mRCC). Methods Seventeen patients (mean age: 59.0 ± 11.6) prospectively underwent a baseline FDG PET/CT and interim PET/CT after 2 cycles (12 weeks) of sunitinib therapy. We measured the highest maximum standardized uptake value (SUVmax) of all identified lesions (highest SUVmax), sum of SUVmax with maximum six lesions (sum of SUVmax), total lesion glycolysis (TLG) and metabolic tumor volume (MTV) from baseline PET/CT and interim PET/CT, and the % decrease in highest SUVmax of lesion (%Δ highest SUVmax), the % decrease in sum of SUVmax, the % decrease in TLG (%ΔTLG) and the % decrease in MTV (%ΔMTV) between baseline and interim PET/CT, and the imaging results were validated by clinical follow-up at 12 months after completion of therapy for progression free survival (PFS). Results At 12 month follow-up, 6/17 (35.3%) patients achieved PFS, while 11/17 (64.7%) patients were deemed to have progression of disease or recurrence within the previous 12 months. At baseline, PET/CT demonstrated metabolically active cancer in all cases. Using baseline PET/CT alone, all of the quantitative imaging metrics were predictive of PFS. Using interim PET/CT, the %Δ highest SUVmax, %Δ sum of SUVmax, and %ΔTLG were also predictive of PFS. Otherwise, interim PET/CT showed no significant difference between the two survival groups regardless of the quantitative metric utilized including MTV and TLG. Conclusions Quantitative metabolic measurements on baseline PET/CT appears to be predictive of PFS at 12 months post-therapy in patients scheduled to undergo sunitinib therapy for mRCC. Change between baseline and interim PET/CT also appeared to have prognostic value but otherwise interim PET/CT after 12 weeks of sunitinib did not appear to be predictive of PFS. PMID:27123976

Scaling Student Success with Predictive Analytics: Reflections after Four Years in the Data Trenches

ERIC Educational Resources Information Center

Wagner, Ellen; Longanecker, David

2016-01-01

The metrics used in the US to track students do not include adults and part-time students. This has led to the development of a massive data initiative--the Predictive Analytics Reporting (PAR) framework--that uses predictive analytics to trace the progress of all types of students in the system. This development has allowed actionable,…

Cognitive Performance in Operational Environments

NASA Technical Reports Server (NTRS)

Russo, Michael; McGhee, James; Friedler, Edna; Thomas, Maria

2005-01-01

Optimal cognition during complex and sustained operations is a critical component for success in current and future military operations. "Cognitive Performance, Judgment, and Decision-making" (CPJD) is a newly organized U.S. Army Medical Research and Materiel Command research program focused on sustaining operational effectiveness of Future Force Warriors by developing paradigms through which militarily-relevant, higher-order cognitive performance, judgment, and decision-making can be assessed and sustained in individuals, small teams, and leaders of network-centric fighting units. CPJD evaluates the impact of stressors intrinsic to military operational environments (e.g., sleep deprivation, workload, fatigue, temperature extremes, altitude, environmental/physiological disruption) on military performance, evaluates noninvasive automated methods for monitoring and predicting cognitive performance, and investigates pharmaceutical strategies (e.g., stimulant countermeasures, hypnotics) to mitigate performance decrements. This manuscript describes the CPJD program, discusses the metrics utilized to relate militarily applied research findings to academic research, and discusses how the simulated combat capabilities of a synthetic battle laboratory may facilitate future cognitive performance research.

SU-C-9A-02: Structured Noise Index as An Automated Quality Control for Nuclear Medicine: A Two Year Experience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, J; Christianson, O; Samei, E

Purpose: Flood-field uniformity evaluation is an essential element in the assessment of nuclear medicine (NM) gamma cameras. It serves as the central element of the quality control (QC) program, acquired and analyzed on a daily basis prior to clinical imaging. Uniformity images are traditionally analyzed using pixel value-based metrics which often fail to capture subtle structure and patterns caused by changes in gamma camera performance requiring additional visual inspection which is subjective and time demanding. The goal of this project was to develop and implement a robust QC metrology for NM that is effective in identifying non-uniformity issues, reporting issuesmore » in a timely manner for efficient correction prior to clinical involvement, all incorporated into an automated effortless workflow, and to characterize the program over a two year period. Methods: A new quantitative uniformity analysis metric was developed based on 2D noise power spectrum metrology and confirmed based on expert observer visual analysis. The metric, termed Structured Noise Index (SNI) was then integrated into an automated program to analyze, archive, and report on daily NM QC uniformity images. The effectiveness of the program was evaluated over a period of 2 years. Results: The SNI metric successfully identified visually apparent non-uniformities overlooked by the pixel valuebased analysis methods. Implementation of the program has resulted in nonuniformity identification in about 12% of daily flood images. In addition, due to the vigilance of staff response, the percentage of days exceeding trigger value shows a decline over time. Conclusion: The SNI provides a robust quantification of the NM performance of gamma camera uniformity. It operates seamlessly across a fleet of multiple camera models. The automated process provides effective workflow within the NM spectra between physicist, technologist, and clinical engineer. The reliability of this process has made it the preferred platform for NM uniformity analysis.« less

Road weather management program performance metrics : implementation and assessment.

DOT National Transportation Integrated Search

2009-08-31

Since the late 1990s, the U.S. Department of Transportation (USDOT), Federal Highway Administration (FHWA) has managed a program dedicated to improving the safety, mobility and productivity of the nations surface transportation modes by integra...

Skill Assessment for Coupled Biological/Physical Models of Marine Systems.

PubMed

Stow, Craig A; Jolliff, Jason; McGillicuddy, Dennis J; Doney, Scott C; Allen, J Icarus; Friedrichs, Marjorie A M; Rose, Kenneth A; Wallhead, Philip

2009-02-20

Coupled biological/physical models of marine systems serve many purposes including the synthesis of information, hypothesis generation, and as a tool for numerical experimentation. However, marine system models are increasingly used for prediction to support high-stakes decision-making. In such applications it is imperative that a rigorous model skill assessment is conducted so that the model's capabilities are tested and understood. Herein, we review several metrics and approaches useful to evaluate model skill. The definition of skill and the determination of the skill level necessary for a given application is context specific and no single metric is likely to reveal all aspects of model skill. Thus, we recommend the use of several metrics, in concert, to provide a more thorough appraisal. The routine application and presentation of rigorous skill assessment metrics will also serve the broader interests of the modeling community, ultimately resulting in improved forecasting abilities as well as helping us recognize our limitations.

Sediment transport-based metrics of wetland stability

USGS Publications Warehouse

Ganju, Neil K.; Kirwan, Matthew L.; Dickhudt, Patrick J.; Guntenspergen, Glenn R.; Cahoon, Donald R.; Kroeger, Kevin D.

2015-01-01

Despite the importance of sediment availability on wetland stability, vulnerability assessments seldom consider spatiotemporal variability of sediment transport. Models predict that the maximum rate of sea level rise a marsh can survive is proportional to suspended sediment concentration (SSC) and accretion. In contrast, we find that SSC and accretion are higher in an unstable marsh than in an adjacent stable marsh, suggesting that these metrics cannot describe wetland vulnerability. Therefore, we propose the flood/ebb SSC differential and organic-inorganic suspended sediment ratio as better vulnerability metrics. The unstable marsh favors sediment export (18 mg L−1 higher on ebb tides), while the stable marsh imports sediment (12 mg L−1 higher on flood tides). The organic-inorganic SSC ratio is 84% higher in the unstable marsh, and stable isotopes indicate a source consistent with marsh-derived material. These simple metrics scale with sediment fluxes, integrate spatiotemporal variability, and indicate sediment sources.

Stability Metrics for Simulation and Flight-Software Assessment and Monitoring of Adaptive Control Assist Compensators

NASA Technical Reports Server (NTRS)

Hodel, A. S.; Whorton, Mark; Zhu, J. Jim

2008-01-01

Due to a need for improved reliability and performance in aerospace systems, there is increased interest in the use of adaptive control or other nonlinear, time-varying control designs in aerospace vehicles. While such techniques are built on Lyapunov stability theory, they lack an accompanying set of metrics for the assessment of stability margins such as the classical gain and phase margins used in linear time-invariant systems. Such metrics must both be physically meaningful and permit the user to draw conclusions in a straightforward fashion. We present in this paper a roadmap to the development of metrics appropriate to nonlinear, time-varying systems. We also present two case studies in which frozen-time gain and phase margins incorrectly predict stability or instability. We then present a multi-resolution analysis approach that permits on-line real-time stability assessment of nonlinear systems.

Older driver fitness-to-drive evaluation using naturalistic driving data.

PubMed

Guo, Feng; Fang, Youjia; Antin, Jonathan F

2015-09-01

As our driving population continues to age, it is becoming increasingly important to find a small set of easily administered fitness metrics that can meaningfully and reliably identify at-risk seniors requiring more in-depth evaluation of their driving skills and weaknesses. Sixty driver assessment metrics related to fitness-to-drive were examined for 20 seniors who were followed for a year using the naturalistic driving paradigm. Principal component analysis and negative binomial regression modeling approaches were used to develop parsimonious models relating the most highly predictive of the driver assessment metrics to the safety-related outcomes observed in the naturalistic driving data. This study provides important confirmation using naturalistic driving methods of the relationship between contrast sensitivity and crash-related events. The results of this study provide crucial information on the continuing journey to identify metrics and protocols that could be applied to determine seniors' fitness to drive. Published by Elsevier Ltd.

Testing general relativity's no-hair theorem with x-ray observations of black holes

NASA Astrophysics Data System (ADS)

Hoormann, Janie K.; Beheshtipour, Banafsheh; Krawczynski, Henric

2016-02-01

Despite its success in the weak gravity regime, general relativity (GR) has yet to be verified in the regime of strong gravity. In this paper, we present the results of detailed ray-tracing simulations aiming at clarifying if the combined information from x-ray spectroscopy, timing, and polarization observations of stellar mass and supermassive black holes can be used to test GR's no-hair theorem. The latter states that stationary astrophysical black holes are described by the Kerr family of metrics, with the black hole mass and spin being the only free parameters. We use four "non-Kerr metrics," some phenomenological in nature and others motivated by alternative theories of gravity, and study the observational signatures of deviations from the Kerr metric. Particular attention is given to the case when all the metrics are set to give the same innermost stable circular orbit in quasi-Boyer-Lindquist coordinates. We give a detailed discussion of similarities and differences of the observational signatures predicted for black holes in the Kerr metric and the non-Kerr metrics. We emphasize that even though some regions of the parameter space are nearly degenerate even when combining the information from all observational channels, x-ray observations of very rapidly spinning black holes can be used to exclude large regions of the parameter space of the alternative metrics. Although it proves difficult to distinguish between the Kerr and non-Kerr metrics for some portions of the parameter space, the observations of very rapidly spinning black holes like Cyg X-1 can be used to rule out large regions for several black hole metrics.

Productivity in Pediatric Palliative Care: Measuring and Monitoring an Elusive Metric.

PubMed

Kaye, Erica C; Abramson, Zachary R; Snaman, Jennifer M; Friebert, Sarah E; Baker, Justin N

2017-05-01

Workforce productivity is poorly defined in health care. Particularly in the field of pediatric palliative care (PPC), the absence of consensus metrics impedes aggregation and analysis of data to track workforce efficiency and effectiveness. Lack of uniformly measured data also compromises the development of innovative strategies to improve productivity and hinders investigation of the link between productivity and quality of care, which are interrelated but not interchangeable. To review the literature regarding the definition and measurement of productivity in PPC; to identify barriers to productivity within traditional PPC models; and to recommend novel metrics to study productivity as a component of quality care in PPC. PubMed ® and Cochrane Database of Systematic Reviews searches for scholarly literature were performed using key words (pediatric palliative care, palliative care, team, workforce, workflow, productivity, algorithm, quality care, quality improvement, quality metric, inpatient, hospital, consultation, model) for articles published between 2000 and 2016. Organizational searches of Center to Advance Palliative Care, National Hospice and Palliative Care Organization, National Association for Home Care & Hospice, American Academy of Hospice and Palliative Medicine, Hospice and Palliative Nurses Association, National Quality Forum, and National Consensus Project for Quality Palliative Care were also performed. Additional semistructured interviews were conducted with directors from seven prominent PPC programs across the U.S. to review standard operating procedures for PPC team workflow and productivity. Little consensus exists in the PPC field regarding optimal ways to define, measure, and analyze provider and program productivity. Barriers to accurate monitoring of productivity include difficulties with identification, measurement, and interpretation of metrics applicable to an interdisciplinary care paradigm. In the context of inefficiencies inherent to traditional consultation models, novel productivity metrics are proposed. Further research is needed to determine optimal metrics for monitoring productivity within PPC teams. Innovative approaches should be studied with the goal of improving efficiency of care without compromising value. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Establishing Common Cost Measures to Evaluate the Economic Value of Patient Navigation Programs

PubMed Central

Whitley, Elizabeth; Valverde, Patricia; Wells, Kristen; Williams, Loretta; Teschner, Taylor; Shih, Ya-Chen Tina

2011-01-01

Background Patient navigation is an intervention aimed at reducing barriers to healthcare for underserved populations as a means to reduce cancer health disparities. Despite the proliferation of patient navigation programs across the United States, information related to the economic impact and sustainability of these programs is lacking. Method Following a review of the relevant literature, the Health Services Research (HSR) cost workgroup of the American Cancer Society National Patient Navigator Leadership Summit met to examine cost data relevant to assessing the economic impact of patient navigation and to propose common cost metrics. Results Recognizing that resources available for data collection, management and analysis vary, five categories of core and optional cost measures were identified related to patient navigator programs, including, program costs, human capital costs, direct medical costs, direct non-medical costs and indirect costs. Conclusion(s) Information demonstrating economic as well as clinical value is necessary to make decisions about sustainability of patient navigation programs. Adoption of these common cost metrics are recommended to promote understanding of the economic impact of patient navigation and comparability across diverse patient navigation programs. PMID:21780096

Evaluation Strategies in Financial Education: Evaluation with Imperfect Instruments

ERIC Educational Resources Information Center

Robinson, Lauren; Dudensing, Rebekka; Granovsky, Nancy L.

2016-01-01

Program evaluation often suffers due to time constraints, imperfect instruments, incomplete data, and the need to report standardized metrics. This article about the evaluation process for the Wi$eUp financial education program showcases the difficulties inherent in evaluation and suggests best practices for assessing program effectiveness. We…

Clinical metric and medication persistency effects: evidence from a Medicaid care management program.

PubMed

Berg, Gregory D; Leary, Fredric; Medina, Wendie; Donnelly, Shawn; Warnick, Kathleen

2015-02-01

The objective was to estimate clinical metric and medication persistency impacts of a care management program. The data sources were Medicaid administrative claims for a sample population of 32,334 noninstitutionalized Medicaid-only aged, blind, or disabled patients with diagnosed conditions of asthma, coronary artery disease, chronic obstructive pulmonary disease, diabetes, or heart failure between 2005 and 2009. Multivariate regression analysis was used to test the hypothesis that exposure to a care management intervention increased the likelihood of having the appropriate medication or procedures performed, as well as increased medication persistency. Statistically significant clinical metric improvements occurred in each of the 5 conditions studied. Increased medication persistency was found for beta-blocker medication for members with coronary artery disease, angiotensin-converting enzyme inhibitor/angiotensin receptor blocker and diuretic medications for members with heart failure, bronchodilator and corticosteroid medications for members with chronic obstructive pulmonary disease, and aspirin/antiplatelet medications for members with diabetes. This study demonstrates that a care management program increases the likelihood of having an appropriate medication dispensed and/or an appropriate clinical test performed, as well as increased likelihood of medication persistency, in people with chronic conditions.

Putting health metrics into practice: using the disability-adjusted life year for strategic decision making.

PubMed

Longfield, Kim; Smith, Brian; Gray, Rob; Ngamkitpaiboon, Lek; Vielot, Nadja

2013-01-01

Implementing organizations are pressured to be accountable for performance. Many health impact metrics present limitations for priority setting; they do not permit comparisons across different interventions or health areas. In response, Population Services International (PSI) adopted the disability-adjusted life year (DALY) averted as its bottom-line performance metric. While international standards exist for calculating DALYs to determine burden of disease (BOD), PSI's use of DALYs averted is novel. It uses DALYs averted to assess and compare the health impact of its country programs, and to understand the effectiveness of a portfolio of interventions. This paper describes how the adoption of DALYs averted influenced organizational strategy and presents the advantages and constraints of using the metric. Health impact data from 2001-2011 were analyzed by program area and geographic region to measure PSI's performance against its goal of doubling health impact between 2007-2011. Analyzing 10 years of data permitted comparison with previous years' performance. A case study of PSI's Asia and Eastern European (A/EE) region, and PSI/Laos, is presented to illustrate how the adoption of DALYs averted affected strategic decision making. Between 2007-2011, PSI's programs doubled the total number of DALYs averted from 2002-2006. Most DALYs averted were within malaria, followed by HIV/AIDS and family planning (FP). The performance of PSI's A/EE region relative to other regions declined with the switch to DALYs averted. As a result, the region made a strategic shift to align its work with countries' BOD. In PSI/Laos, this redirection led to better-targeted programs and an approximate 50% gain in DALYs averted from 2009-2011. PSI's adoption of DALYs averted shifted the organization's strategic direction away from product sales and toward BOD. Now, many strategic decisions are based on "BOD-relevance," the share of the BOD that interventions can potentially address. This switch resulted in more targeted strategies and greater program diversification. Challenges remain in convincing donors to support interventions in disease areas that are relevant to a country's BOD, and in developing modeling methodologies. The global health community will benefit from the use of standard health impact metrics to improve strategic decision making and more effectively respond to the changing global burden of disease.

A simple, sufficient, and consistent method to score the status of threats and demography of imperiled species

PubMed Central

Webber, Whitney M.; Li, Ya-Wei

2016-01-01

Managers of large, complex wildlife conservation programs need information on the conservation status of each of many species to help strategically allocate limited resources. Oversimplifying status data, however, runs the risk of missing information essential to strategic allocation. Conservation status consists of two components, the status of threats a species faces and the species’ demographic status. Neither component alone is sufficient to characterize conservation status. Here we present a simple key for scoring threat and demographic changes for species using detailed information provided in free-form textual descriptions of conservation status. This key is easy to use (simple), captures the two components of conservation status without the cost of more detailed measures (sufficient), and can be applied by different personnel to any taxon (consistent). To evaluate the key’s utility, we performed two analyses. First, we scored the threat and demographic status of 37 species recently recommended for reclassification under the Endangered Species Act (ESA) and 15 control species, then compared our scores to two metrics used for decision-making and reports to Congress. Second, we scored the threat and demographic status of all non-plant ESA-listed species from Florida (54 spp.), and evaluated scoring repeatability for a subset of those. While the metrics reported by the U.S. Fish and Wildlife Service (FWS) are often consistent with our scores in the first analysis, the results highlight two problems with the oversimplified metrics. First, we show that both metrics can mask underlying demographic declines or threat increases; for example, ∼40% of species not recommended for reclassification had changes in threats or demography. Second, we show that neither metric is consistent with either threats or demography alone, but conflates the two. The second analysis illustrates how the scoring key can be applied to a substantial set of species to understand overall patterns of ESA implementation. The scoring repeatability analysis shows promise, but indicates thorough training will be needed to ensure consistency. We propose that large conservation programs adopt our simple scoring system for threats and demography. By doing so, program administrators will have better information to monitor program effectiveness and guide their decisions. PMID:27478713

A simple, sufficient, and consistent method to score the status of threats and demography of imperiled species.

PubMed

Malcom, Jacob W; Webber, Whitney M; Li, Ya-Wei

2016-01-01

Managers of large, complex wildlife conservation programs need information on the conservation status of each of many species to help strategically allocate limited resources. Oversimplifying status data, however, runs the risk of missing information essential to strategic allocation. Conservation status consists of two components, the status of threats a species faces and the species' demographic status. Neither component alone is sufficient to characterize conservation status. Here we present a simple key for scoring threat and demographic changes for species using detailed information provided in free-form textual descriptions of conservation status. This key is easy to use (simple), captures the two components of conservation status without the cost of more detailed measures (sufficient), and can be applied by different personnel to any taxon (consistent). To evaluate the key's utility, we performed two analyses. First, we scored the threat and demographic status of 37 species recently recommended for reclassification under the Endangered Species Act (ESA) and 15 control species, then compared our scores to two metrics used for decision-making and reports to Congress. Second, we scored the threat and demographic status of all non-plant ESA-listed species from Florida (54 spp.), and evaluated scoring repeatability for a subset of those. While the metrics reported by the U.S. Fish and Wildlife Service (FWS) are often consistent with our scores in the first analysis, the results highlight two problems with the oversimplified metrics. First, we show that both metrics can mask underlying demographic declines or threat increases; for example, ∼40% of species not recommended for reclassification had changes in threats or demography. Second, we show that neither metric is consistent with either threats or demography alone, but conflates the two. The second analysis illustrates how the scoring key can be applied to a substantial set of species to understand overall patterns of ESA implementation. The scoring repeatability analysis shows promise, but indicates thorough training will be needed to ensure consistency. We propose that large conservation programs adopt our simple scoring system for threats and demography. By doing so, program administrators will have better information to monitor program effectiveness and guide their decisions.

Developing a Predictive Metric to Assess School Viability

ERIC Educational Resources Information Center

James, John T.; Tichy, Karen L.; Collins, Alan; Schwob, John

2008-01-01

This article examines a wide range of parish school indicators that can be used to predict long-term viability. The study reported in this article explored the relationship between demographic variables, financial variables, and parish grade school closures in the Archdiocese of Saint Louis. Specifically, this study investigated whether…

An Underwater Color Image Quality Evaluation Metric.

PubMed

Yang, Miao; Sowmya, Arcot

2015-12-01

Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.

Use of erythrocyte indicators of health and condition in vertebrate ecophysiology: a review and appraisal.

PubMed

Johnstone, Christopher P; Lill, Alan; Reina, Richard D

2017-02-01

We review evidence for and against the use of erythrocyte indicators of health status and condition, parasite infection level and physiological stress in free-living vertebrates. The use of indicators that are measured directly from the blood, such as haemoglobin concentration, haematocrit and erythrocyte sedimentation rate, and parameters that are calculated from multiple measured metrics, such as mean cell volume, mean cell haemoglobin content or mean cell haemoglobin concentration is evaluated. The evidence for or against the use of any given metric is equivocal when the relevant research is considered in total, although there is sometimes strong support for using a particular metric in a particular taxon. Possibly the usefulness of these metrics is taxon, environment or condition specific. Alternatively, in an uncontrolled environment where multiple factors are influencing a metric, its response to environmental change will sometimes, but not always, be predictable. We suggest that (i) researchers should validate a metricfres utility before use, (ii) multiple metrics should be used to construct an overall erythrocyte profile for an individual or population, (iii) there is a need for researchers to compile reference ranges for free-living species, and (iv) some metrics which are useful under controlled, clinical conditions may not have the same utility or applicability for free-living vertebrates. Erythrocyte metrics provide useful information about health and condition that can be meaningfully interpreted in free-living vertebrates, but their use requires careful forethought about confounding factors. © 2015 Cambridge Philosophical Society.

Algal Attributes: An Autecological Classification of Algal Taxa Collected by the National Water-Quality Assessment Program

USGS Publications Warehouse

Porter, Stephen D.

2008-01-01

Algae are excellent indicators of water-quality conditions, notably nutrient and organic enrichment, and also are indicators of major ion, dissolved oxygen, and pH concentrations and stream microhabitat conditions. The autecology, or physiological optima and tolerance, of algal species for various water-quality contaminants and conditions is relatively well understood for certain groups of freshwater algae, notably diatoms. However, applications of autecological information for water-quality assessments have been limited because of challenges associated with compiling autecological literature from disparate sources, tracking name changes for a large number of algal species, and creating an autecological data base from which algal-indicator metrics can be calculated. A comprehensive summary of algal autecological attributes for North American streams and rivers does not exist. This report describes a large, digital data file containing 28,182 records for 5,939 algal taxa, generally species or variety, collected by the U.S. Geological Survey?s National Water-Quality Assessment (NAWQA) Program. The data file includes 37 algal attributes classified by over 100 algal-indicator codes or metrics that can be calculated easily with readily available software. Algal attributes include qualitative classifications based on European and North American autecological literature, and semi-quantitative, weighted-average regression approaches for estimating optima using regional and national NAWQA data. Applications of algal metrics in water-quality assessments are discussed and national quartile distributions of metric scores are shown for selected indicator metrics.

Application of Support Vector Machine to Forex Monitoring

NASA Astrophysics Data System (ADS)

Kamruzzaman, Joarder; Sarker, Ruhul A.

Previous studies have demonstrated superior performance of artificial neural network (ANN) based forex forecasting models over traditional regression models. This paper applies support vector machines to build a forecasting model from the historical data using six simple technical indicators and presents a comparison with an ANN based model trained by scaled conjugate gradient (SCG) learning algorithm. The models are evaluated and compared on the basis of five commonly used performance metrics that measure closeness of prediction as well as correctness in directional change. Forecasting results of six different currencies against Australian dollar reveal superior performance of SVM model using simple linear kernel over ANN-SCG model in terms of all the evaluation metrics. The effect of SVM parameter selection on prediction performance is also investigated and analyzed.

Towards Principled Experimental Study of Autonomous Mobile Robots

NASA Technical Reports Server (NTRS)

Gat, Erann

1995-01-01

We review the current state of research in autonomous mobile robots and conclude that there is an inadequate basis for predicting the reliability and behavior of robots operating in unengineered environments. We present a new approach to the study of autonomous mobile robot performance based on formal statistical analysis of independently reproducible experiments conducted on real robots. Simulators serve as models rather than experimental surrogates. We demonstrate three new results: 1) Two commonly used performance metrics (time and distance) are not as well correlated as is often tacitly assumed. 2) The probability distributions of these performance metrics are exponential rather than normal, and 3) a modular, object-oriented simulation accurately predicts the behavior of the real robot in a statistically significant manner.

{sup 18}F-Fluorodeoxyglucose Positron Emission Tomography Can Quantify and Predict Esophageal Injury During Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niedzielski, Joshua S., E-mail: jsniedzielski@mdanderson.org; University of Texas Houston Graduate School of Biomedical Science, Houston, Texas; Yang, Jinzhong

Purpose: We sought to investigate the ability of mid-treatment {sup 18}F-fluorodeoxyglucose positron emission tomography (PET) studies to objectively and spatially quantify esophageal injury in vivo from radiation therapy for non-small cell lung cancer. Methods and Materials: This retrospective study was approved by the local institutional review board, with written informed consent obtained before enrollment. We normalized {sup 18}F-fluorodeoxyglucose PET uptake to each patient's low-irradiated region (<5 Gy) of the esophagus, as a radiation response measure. Spatially localized metrics of normalized uptake (normalized standard uptake value [nSUV]) were derived for 79 patients undergoing concurrent chemoradiation therapy for non-small cell lung cancer. We usedmore » nSUV metrics to classify esophagitis grade at the time of the PET study, as well as maximum severity by treatment completion, according to National Cancer Institute Common Terminology Criteria for Adverse Events, using multivariate least absolute shrinkage and selection operator (LASSO) logistic regression and repeated 3-fold cross validation (training, validation, and test folds). This 3-fold cross-validation LASSO model procedure was used to predict toxicity progression from 43 asymptomatic patients during the PET study. Dose-volume metrics were also tested in both the multivariate classification and the symptom progression prediction analyses. Classification performance was quantified with the area under the curve (AUC) from receiver operating characteristic analysis on the test set from the 3-fold analyses. Results: Statistical analysis showed increasing nSUV is related to esophagitis severity. Axial-averaged maximum nSUV for 1 esophageal slice and esophageal length with at least 40% of axial-averaged nSUV both had AUCs of 0.85 for classifying grade 2 or higher esophagitis at the time of the PET study and AUCs of 0.91 and 0.92, respectively, for maximum grade 2 or higher by treatment completion. Symptom progression was predicted with an AUC of 0.75. Dose metrics performed poorly at classifying esophagitis (AUC of 0.52, grade 2 or higher mid treatment) or predicting symptom progression (AUC of 0.67). Conclusions: Normalized uptake can objectively, locally, and noninvasively quantify esophagitis during radiation therapy and predict eventual symptoms from asymptomatic patients. Normalized uptake may provide patient-specific dose-response information not discernible from dose.« less

(18)F-Fluorodeoxyglucose Positron Emission Tomography Can Quantify and Predict Esophageal Injury During Radiation Therapy.

PubMed

Niedzielski, Joshua S; Yang, Jinzhong; Liao, Zhongxing; Gomez, Daniel R; Stingo, Francesco; Mohan, Radhe; Martel, Mary K; Briere, Tina M; Court, Laurence E

2016-11-01

We sought to investigate the ability of mid-treatment (18)F-fluorodeoxyglucose positron emission tomography (PET) studies to objectively and spatially quantify esophageal injury in vivo from radiation therapy for non-small cell lung cancer. This retrospective study was approved by the local institutional review board, with written informed consent obtained before enrollment. We normalized (18)F-fluorodeoxyglucose PET uptake to each patient's low-irradiated region (<5 Gy) of the esophagus, as a radiation response measure. Spatially localized metrics of normalized uptake (normalized standard uptake value [nSUV]) were derived for 79 patients undergoing concurrent chemoradiation therapy for non-small cell lung cancer. We used nSUV metrics to classify esophagitis grade at the time of the PET study, as well as maximum severity by treatment completion, according to National Cancer Institute Common Terminology Criteria for Adverse Events, using multivariate least absolute shrinkage and selection operator (LASSO) logistic regression and repeated 3-fold cross validation (training, validation, and test folds). This 3-fold cross-validation LASSO model procedure was used to predict toxicity progression from 43 asymptomatic patients during the PET study. Dose-volume metrics were also tested in both the multivariate classification and the symptom progression prediction analyses. Classification performance was quantified with the area under the curve (AUC) from receiver operating characteristic analysis on the test set from the 3-fold analyses. Statistical analysis showed increasing nSUV is related to esophagitis severity. Axial-averaged maximum nSUV for 1 esophageal slice and esophageal length with at least 40% of axial-averaged nSUV both had AUCs of 0.85 for classifying grade 2 or higher esophagitis at the time of the PET study and AUCs of 0.91 and 0.92, respectively, for maximum grade 2 or higher by treatment completion. Symptom progression was predicted with an AUC of 0.75. Dose metrics performed poorly at classifying esophagitis (AUC of 0.52, grade 2 or higher mid treatment) or predicting symptom progression (AUC of 0.67). Normalized uptake can objectively, locally, and noninvasively quantify esophagitis during radiation therapy and predict eventual symptoms from asymptomatic patients. Normalized uptake may provide patient-specific dose-response information not discernible from dose. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction of user preference over shared-control paradigms for a robotic wheelchair.

PubMed

Erdogan, Ahmetcan; Argall, Brenna D

2017-07-01

The design of intelligent powered wheelchairs has traditionally focused heavily on providing effective and efficient navigation assistance. Significantly less attention has been given to the end-user's preference between different assistance paradigms. It is possible to include these subjective evaluations in the design process, for example by soliciting feedback in post-experiment questionnaires. However, constantly querying the user for feedback during real-world operation is not practical. In this paper, we present a model that correlates objective performance metrics and subjective evaluations of autonomous wheelchair control paradigms. Using off-the-shelf machine learning techniques, we show that it is possible to build a model that can predict the most preferred shared-control method from task execution metrics such as effort, safety, performance and utilization. We further characterize the relative contributions of each of these metrics to the individual choice of most preferred assistance paradigm. Our evaluation includes Spinal Cord Injured (SCI) and uninjured subject groups. The results show that our proposed correlation model enables the continuous tracking of user preference and offers the possibility of autonomy that is customized to each user.

Perceptual color difference metric including a CSF based on the perception threshold

NASA Astrophysics Data System (ADS)

Rosselli, Vincent; Larabi, Mohamed-Chaker; Fernandez-Maloigne, Christine

2008-01-01

The study of the Human Visual System (HVS) is very interesting to quantify the quality of a picture, to predict which information will be perceived on it, to apply adapted tools ... The Contrast Sensitivity Function (CSF) is one of the major ways to integrate the HVS properties into an imaging system. It characterizes the sensitivity of the visual system to spatial and temporal frequencies and predicts the behavior for the three channels. Common constructions of the CSF have been performed by estimating the detection threshold beyond which it is possible to perceive a stimulus. In this work, we developed a novel approach for spatio-chromatic construction based on matching experiments to estimate the perception threshold. It consists in matching the contrast of a test stimulus with that of a reference one. The obtained results are quite different in comparison with the standard approaches as the chromatic CSFs have band-pass behavior and not low pass. The obtained model has been integrated in a perceptual color difference metric inspired by the s-CIELAB. The metric is then evaluated with both objective and subjective procedures.

Relationships among exceedences of metals criteria, the results of ambient bioassays, and community metrics in mining-impacted streams.

PubMed

Griffith, Michael B; Lazorchak, James M; Herlihy, Alan T

2004-07-01

If bioassessments are to help diagnose the specific environmental stressors affecting streams, a better understanding is needed of the relationships between community metrics and ambient criteria or ambient bioassays. However, this relationship is not simple, because metrics assess responses at the community level of biological organization, while ambient criteria and ambient bioassays assess or are based on responses at the individual level. For metals, the relationship is further complicated by the influence of other chemical variables, such as hardness, on their bioavailability and toxicity. In 1993 and 1994, U.S. Environmental Protection Agency (U.S. EPA) conducted a Regional Environmental Monitoring and Assessment Program (REMAP) survey on wadeable streams in Colorado's (USA) Southern Rockies Ecoregion. In this ecoregion, mining over the past century has resulted in metals contamination of streams. The surveys collected data on fish and macroinvertebrate assemblages, physical habitat, and sediment and water chemistry and toxicity. These data provide a framework for assessing diagnostic community metrics for specific environmental stressors. We characterized streams as metals-affected based on exceedence of hardness-adjusted criteria for cadmium, copper, lead, and zinc in water; on water toxicity tests (48-h Pimephales promelas and Ceriodaphnia dubia survival); on exceedence of sediment threshold effect levels (TELs); or on sediment toxicity tests (7-d Hyalella azteca survival and growth). Macroinvertebrate and fish metrics were compared among affected and unaffected sites to identify metrics sensitive to metals. Several macroinvertebrate metrics, particularly richness metrics, were less in affected streams, while other metrics were not. This is a function of the sensitivity of the individual metrics to metals effects. Fish metrics were less sensitive to metals because of the low diversity of fish in these streams.

Managing for value. It's not just about the numbers.

PubMed

Haspeslagh, P; Noda, T; Boulos, F

2001-01-01

In theory, value-based management programs sound seductively simple. Just adopt an economic profit metric, tie compensation to agreed-upon improvement targets in that metric, and voilà! Managers and employees will start making all kinds of value-creating decisions. If only it were that easy. The reality is, almost half of the companies that have adopted a VBM metric have met with mediocre success. That's because, the authors contend, the successful VBM program is really about introducing fundamental changes to a big company's culture. Results from their major research project into the practice of VBM reveal that putting VBM into practice is far more complicated than many of its proponents make it out to be, requiring a great deal of patience, effort, and money. According to the authors' study, companies that successfully use VBM programs share five main characteristics. First, nearly all made explicit and public their commitment to shareholder value. Second, through training, they created an environment receptive to the changes the program would engender. Third, they reinforced that training with broad-based incentive systems closely tied to the VBM performance measures, which gave employees a sense of ownership in both the company and the program. Fourth, they were willing to craft major organizational changes to allow all their workers to make those value-creating decisions. Finally, the changes they introduced to the company's systems and processes were broad and inclusive rather than focused narrowly on financial reports and compensation. A VBM program is difficult and expensive. Still, the authors argue, properly applied, it will put your company's profitability firmly on track.

A concept for performance management for Federal science programs

USGS Publications Warehouse

Whalen, Kevin G.

2017-11-06

The demonstration of clear linkages between planning, funding, outcomes, and performance management has created unique challenges for U.S. Federal science programs. An approach is presented here that characterizes science program strategic objectives by one of five “activity types”: (1) knowledge discovery, (2) knowledge development and delivery, (3) science support, (4) inventory and monitoring, and (5) knowledge synthesis and assessment. The activity types relate to performance measurement tools for tracking outcomes of research funded under the objective. The result is a multi-time scale, integrated performance measure that tracks individual performance metrics synthetically while also measuring progress toward long-term outcomes. Tracking performance on individual metrics provides explicit linkages to root causes of potentially suboptimal performance and captures both internal and external program drivers, such as customer relations and science support for managers. Functionally connecting strategic planning objectives with performance measurement tools is a practical approach for publicly funded science agencies that links planning, outcomes, and performance management—an enterprise that has created unique challenges for public-sector research and development programs.

Evaluating an accelerated nursing program: a dashboard for diversity.

PubMed

Schmidt, Bonnie J; MacWilliams, Brent R

2015-01-01

Diversity is a topic of increasing attention in higher education and the nursing workforce. Experts have called for a nursing workforce that mirrors the population it serves. Students in nursing programs in the United States do not reflect our country's diverse population; therefore, much work is needed before that goal can be reached. Diversity cannot be successfully achieved in nursing education without inclusion and attention to quality. The Inclusive Excellence framework can be used by nurse educators to promote inclusion, diversity, and excellence. In this framework, excellence and diversity are linked in an intentional metric-driven process. Accelerated programs offer a possible venue to promote diversity, and one accelerated program is examined using a set of metrics and a dashboard approach commonly used in business settings. Several recommendations were made for future assessment, interventions, and monitoring. Nurse educators are called to examine and adopt a diversity dashboard in all nursing programs. Copyright © 2015 Elsevier Inc. All rights reserved.

Gödel metrics with chronology protection in Horndeski gravities

NASA Astrophysics Data System (ADS)

Geng, Wei-Jian; Li, Shou-Long; Lü, H.; Wei, Hao

2018-05-01

Gödel universe, one of the most interesting exact solutions predicted by General Relativity, describes a homogeneous rotating universe containing naked closed time-like curves (CTCs). It was shown that such CTCs are the consequence of the null energy condition in General Relativity. In this paper, we show that the Gödel-type metrics with chronology protection can emerge in Einstein-Horndeski gravity. We construct such exact solutions also in Einstein-Horndeski-Maxwell and Einstein-Horndeski-Proca theories.

Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy.

PubMed

Dean, Jamie A; Wong, Kee H; Welsh, Liam C; Jones, Ann-Britt; Schick, Ulrike; Newbold, Kate L; Bhide, Shreerang A; Harrington, Kevin J; Nutting, Christopher M; Gulliford, Sarah L

2016-07-01

Severe acute mucositis commonly results from head and neck (chemo)radiotherapy. A predictive model of mucositis could guide clinical decision-making and inform treatment planning. We aimed to generate such a model using spatial dose metrics and machine learning. Predictive models of severe acute mucositis were generated using radiotherapy dose (dose-volume and spatial dose metrics) and clinical data. Penalised logistic regression, support vector classification and random forest classification (RFC) models were generated and compared. Internal validation was performed (with 100-iteration cross-validation), using multiple metrics, including area under the receiver operating characteristic curve (AUC) and calibration slope, to assess performance. Associations between covariates and severe mucositis were explored using the models. The dose-volume-based models (standard) performed equally to those incorporating spatial information. Discrimination was similar between models, but the RFCstandard had the best calibration. The mean AUC and calibration slope for this model were 0.71 (s.d.=0.09) and 3.9 (s.d.=2.2), respectively. The volumes of oral cavity receiving intermediate and high doses were associated with severe mucositis. The RFCstandard model performance is modest-to-good, but should be improved, and requires external validation. Reducing the volumes of oral cavity receiving intermediate and high doses may reduce mucositis incidence. Copyright © 2016 The Author(s). Published by Elsevier Ireland Ltd.. All rights reserved.

Fronto-temporal connectivity predicts cognitive empathy deficits and experiential negative symptoms in schizophrenia.

PubMed

Abram, Samantha V; Wisner, Krista M; Fox, Jaclyn M; Barch, Deanna M; Wang, Lei; Csernansky, John G; MacDonald, Angus W; Smith, Matthew J

2017-03-01

Impaired cognitive empathy is a core social cognitive deficit in schizophrenia associated with negative symptoms and social functioning. Cognitive empathy and negative symptoms have also been linked to medial prefrontal and temporal brain networks. While shared behavioral and neural underpinnings are suspected for cognitive empathy and negative symptoms, research is needed to test these hypotheses. In two studies, we evaluated whether resting-state functional connectivity between data-driven networks, or components (referred to as, inter-component connectivity), predicted cognitive empathy and experiential and expressive negative symptoms in schizophrenia subjects. Study 1: We examined associations between cognitive empathy and medial prefrontal and temporal inter-component connectivity at rest using a group-matched schizophrenia and control sample. We then assessed whether inter-component connectivity metrics associated with cognitive empathy were also related to negative symptoms. Study 2: We sought to replicate the connectivity-symptom associations observed in Study 1 using an independent schizophrenia sample. Study 1 results revealed that while the groups did not differ in average inter-component connectivity, a medial-fronto-temporal metric and an orbito-fronto-temporal metric were related to cognitive empathy. Moreover, the medial-fronto-temporal metric was associated with experiential negative symptoms in both schizophrenia samples. These findings support recent models that link social cognition and negative symptoms in schizophrenia. Hum Brain Mapp 38:1111-1124, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Development of Cardiovascular and Neurodevelopmental Metrics as Sublethal Endpoints for the Fish Embryo Toxicity Test.

PubMed

Krzykwa, Julie C; Olivas, Alexis; Jeffries, Marlo K Sellin

2018-06-19

The fathead minnow fish embryo toxicity (FET) test has been proposed as a more humane alternative to current toxicity testing methods, as younger organisms are thought to experience less distress during toxicant exposure. However, the FET test protocol does not include endpoints that allow for the prediction of sublethal adverse outcomes, limiting its utility relative to other test types. Researchers have proposed the development of sublethal endpoints for the FET test to increase its utility. The present study 1) developed methods for previously unmeasured sublethal metrics in fathead minnows (i.e., spontaneous contraction frequency and heart rate) and 2) investigated the responsiveness of several sublethal endpoints related to growth (wet weight, length, and growth-related gene expression), neurodevelopment (spontaneous contraction frequency, and neurodevelopmental gene expression), and cardiovascular function and development (pericardial area, eye size and cardiovascular related gene expression) as additional FET test metrics using the model toxicant 3,4-dichloroaniline. Of the growth, neurological and cardiovascular endpoints measured, length, eye size and pericardial area were found to more responsive than the other endpoints, respectively. Future studies linking alterations in these endpoints to longer-term adverse impacts are needed to fully evaluate the predictive power of these metrics in chemical and whole effluent toxicity testing. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Algal bioassessment metrics for wadeable streams and rivers of Maine, USA

USGS Publications Warehouse

Danielson, Thomas J.; Loftin, Cynthia S.; Tsomides, Leonidas; DiFranco, Jeanne L.; Connors, Beth

2011-01-01

Many state water-quality agencies use biological assessment methods based on lotic fish and macroinvertebrate communities, but relatively few states have incorporated algal multimetric indices into monitoring programs. Algae are good indicators for monitoring water quality because they are sensitive to many environmental stressors. We evaluated benthic algal community attributes along a landuse gradient affecting wadeable streams and rivers in Maine, USA, to identify potential bioassessment metrics. We collected epilithic algal samples from 193 locations across the state. We computed weighted-average optima for common taxa for total P, total N, specific conductance, % impervious cover, and % developed watershed, which included all land use that is no longer forest or wetland. We assigned Maine stream tolerance values and categories (sensitive, intermediate, tolerant) to taxa based on their optima and responses to watershed disturbance. We evaluated performance of algal community metrics used in multimetric indices from other regions and novel metrics based on Maine data. Metrics specific to Maine data, such as the relative richness of species characterized as being sensitive in Maine, were more correlated with % developed watershed than most metrics used in other regions. Few community-structure attributes (e.g., species richness) were useful metrics in Maine. Performance of algal bioassessment models would be improved if metrics were evaluated with attributes of local data before inclusion in multimetric indices or statistical models. ?? 2011 by The North American Benthological Society.

Light Water Reactor Sustainability Program Operator Performance Metrics for Control Room Modernization: A Practical Guide for Early Design Evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ronald Boring; Roger Lew; Thomas Ulrich

2014-03-01

As control rooms are modernized with new digital systems at nuclear power plants, it is necessary to evaluate the operator performance using these systems as part of a verification and validation process. There are no standard, predefined metrics available for assessing what is satisfactory operator interaction with new systems, especially during the early design stages of a new system. This report identifies the process and metrics for evaluating human system interfaces as part of control room modernization. The report includes background information on design and evaluation, a thorough discussion of human performance measures, and a practical example of how themore » process and metrics have been used as part of a turbine control system upgrade during the formative stages of design. The process and metrics are geared toward generalizability to other applications and serve as a template for utilities undertaking their own control room modernization activities.« less

Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction

PubMed Central

Venkatesan, R.

2016-01-01

Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets. PMID:27738649

Cost-Sensitive Radial Basis Function Neural Network Classifier for Software Defect Prediction.

PubMed

Kumudha, P; Venkatesan, R

Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.

OVERVIEW OF EPA'S LANDSCAPE SCIENCE PROGRAM

EPA Science Inventory

Over the past 10 years, the U.S. Environmental Protection Agency's Office of Research and Development's National Exposure Research Laboratory has expanded it's ecological research program to include the development of landscape metrics and indicators to assess ecological risk and...