Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions.

PubMed

O'Loughlin, Declan; Oliveira, Bárbara L; Elahi, Muhammad Adnan; Glavin, Martin; Jones, Edward; Popović, Milica; O'Halloran, Martin

2017-12-06

Inaccurate estimation of average dielectric properties can have a tangible impact on microwave radar-based breast images. Despite this, recent patient imaging studies have used a fixed estimate although this is known to vary from patient to patient. Parameter search algorithms are a promising technique for estimating the average dielectric properties from the reconstructed microwave images themselves without additional hardware. In this work, qualities of accurately reconstructed images are identified from point spread functions. As the qualities of accurately reconstructed microwave images are similar to the qualities of focused microscopic and photographic images, this work proposes the use of focal quality metrics for average dielectric property estimation. The robustness of the parameter search is evaluated using experimental dielectrically heterogeneous phantoms on the three-dimensional volumetric image. Based on a very broad initial estimate of the average dielectric properties, this paper shows how these metrics can be used as suitable fitness functions in parameter search algorithms to reconstruct clear and focused microwave radar images.

A guide to calculating habitat-quality metrics to inform conservation of highly mobile species

USGS Publications Warehouse

Bieri, Joanna A.; Sample, Christine; Thogmartin, Wayne E.; Diffendorfer, James E.; Earl, Julia E.; Erickson, Richard A.; Federico, Paula; Flockhart, D. T. Tyler; Nicol, Sam; Semmens, Darius J.; Skraber, T.; Wiederholt, Ruscena; Mattsson, Brady J.

2018-01-01

Many metrics exist for quantifying the relative value of habitats and pathways used by highly mobile species. Properly selecting and applying such metrics requires substantial background in mathematics and understanding the relevant management arena. To address this multidimensional challenge, we demonstrate and compare three measurements of habitat quality: graph-, occupancy-, and demographic-based metrics. Each metric provides insights into system dynamics, at the expense of increasing amounts and complexity of data and models. Our descriptions and comparisons of diverse habitat-quality metrics provide means for practitioners to overcome the modeling challenges associated with management or conservation of such highly mobile species. Whereas previous guidance for applying habitat-quality metrics has been scattered in diversified tracks of literature, we have brought this information together into an approachable format including accessible descriptions and a modeling case study for a typical example that conservation professionals can adapt for their own decision contexts and focal populations.Considerations for Resource ManagersManagement objectives, proposed actions, data availability and quality, and model assumptions are all relevant considerations when applying and interpreting habitat-quality metrics.Graph-based metrics answer questions related to habitat centrality and connectivity, are suitable for populations with any movement pattern, quantify basic spatial and temporal patterns of occupancy and movement, and require the least data.Occupancy-based metrics answer questions about likelihood of persistence or colonization, are suitable for populations that undergo localized extinctions, quantify spatial and temporal patterns of occupancy and movement, and require a moderate amount of data.Demographic-based metrics answer questions about relative or absolute population size, are suitable for populations with any movement pattern, quantify demographic

Quality metrics in high-dimensional data visualization: an overview and systematization.

PubMed

Bertini, Enrico; Tatu, Andrada; Keim, Daniel

2011-12-01

In this paper, we present a systematization of techniques that use quality metrics to help in the visual exploration of meaningful patterns in high-dimensional data. In a number of recent papers, different quality metrics are proposed to automate the demanding search through large spaces of alternative visualizations (e.g., alternative projections or ordering), allowing the user to concentrate on the most promising visualizations suggested by the quality metrics. Over the last decade, this approach has witnessed a remarkable development but few reflections exist on how these methods are related to each other and how the approach can be developed further. For this purpose, we provide an overview of approaches that use quality metrics in high-dimensional data visualization and propose a systematization based on a thorough literature review. We carefully analyze the papers and derive a set of factors for discriminating the quality metrics, visualization techniques, and the process itself. The process is described through a reworked version of the well-known information visualization pipeline. We demonstrate the usefulness of our model by applying it to several existing approaches that use quality metrics, and we provide reflections on implications of our model for future research. © 2010 IEEE

[Clinical trial data management and quality metrics system].

PubMed

Chen, Zhao-hua; Huang, Qin; Deng, Ya-zhong; Zhang, Yue; Xu, Yu; Yu, Hao; Liu, Zong-fan

2015-11-01

Data quality management system is essential to ensure accurate, complete, consistent, and reliable data collection in clinical research. This paper is devoted to various choices of data quality metrics. They are categorized by study status, e.g. study start up, conduct, and close-out. In each category, metrics for different purposes are listed according to ALCOA+ principles such us completeness, accuracy, timeliness, traceability, etc. Some general quality metrics frequently used are also introduced. This paper contains detail information as much as possible to each metric by providing definition, purpose, evaluation, referenced benchmark, and recommended targets in favor of real practice. It is important that sponsors and data management service providers establish a robust integrated clinical trial data quality management system to ensure sustainable high quality of clinical trial deliverables. It will also support enterprise level of data evaluation and bench marking the quality of data across projects, sponsors, data management service providers by using objective metrics from the real clinical trials. We hope this will be a significant input to accelerate the improvement of clinical trial data quality in the industry.

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

Large radius of curvature measurement based on the evaluation of interferogram-quality metric in non-null interferometry

NASA Astrophysics Data System (ADS)

Yang, Zhongming; Dou, Jiantai; Du, Jinyu; Gao, Zhishan

2018-03-01

Non-null interferometry could use to measure the radius of curvature (ROC), we have presented a virtual quadratic Newton rings phase-shifting moiré-fringes measurement method for large ROC measurement (Yang et al., 2016). In this paper, we propose a large ROC measurement method based on the evaluation of the interferogram-quality metric by the non-null interferometer. With the multi-configuration model of the non-null interferometric system in ZEMAX, the retrace errors and the phase introduced by the test surface are reconstructed. The interferogram-quality metric is obtained by the normalized phase-shifted testing Newton rings with the spherical surface model in the non-null interferometric system. The radius curvature of the test spherical surface can be obtained until the minimum of the interferogram-quality metric is found. Simulations and experimental results are verified the feasibility of our proposed method. For a spherical mirror with a ROC of 41,400 mm, the measurement accuracy is better than 0.13%.

Software Quality Metrics Enhancements. Volume 1

DTIC Science & Technology

1980-04-01

the mathematical relationships which relate metrics to ratings of the various quality factors) for factors which were not validated previously were...function, provides a mathematical relationship between the metrics and the quality factors. (3) Validation of these normalization functions was performed by...samples, further research is needed before a high degree of confidence can be placed on the mathematical relationships established to date l (3.3.3) 6

Degraded visual environment image/video quality metrics

NASA Astrophysics Data System (ADS)

Baumgartner, Dustin D.; Brown, Jeremy B.; Jacobs, Eddie L.; Schachter, Bruce J.

2014-06-01

A number of image quality metrics (IQMs) and video quality metrics (VQMs) have been proposed in the literature for evaluating techniques and systems for mitigating degraded visual environments. Some require both pristine and corrupted imagery. Others require patterned target boards in the scene. None of these metrics relates well to the task of landing a helicopter in conditions such as a brownout dust cloud. We have developed and used a variety of IQMs and VQMs related to the pilot's ability to detect hazards in the scene and to maintain situational awareness. Some of these metrics can be made agnostic to sensor type. Not only are the metrics suitable for evaluating algorithm and sensor variation, they are also suitable for choosing the most cost effective solution to improve operating conditions in degraded visual environments.

National evaluation of multidisciplinary quality metrics for head and neck cancer.

PubMed

Cramer, John D; Speedy, Sedona E; Ferris, Robert L; Rademaker, Alfred W; Patel, Urjeet A; Samant, Sandeep

2017-11-15

The National Quality Forum has endorsed quality-improvement measures for multiple cancer types that are being developed into actionable tools to improve cancer care. No nationally endorsed quality metrics currently exist for head and neck cancer. The authors identified patients with surgically treated, invasive, head and neck squamous cell carcinoma in the National Cancer Data Base from 2004 to 2014 and compared the rate of adherence to 5 different quality metrics and whether compliance with these quality metrics impacted overall survival. The metrics examined included negative surgical margins, neck dissection lymph node (LN) yield ≥ 18, appropriate adjuvant radiation, appropriate adjuvant chemoradiation, adjuvant therapy within 6 weeks, as well as overall quality. In total, 76,853 eligible patients were identified. There was substantial variability in patient-level adherence, which was 80% for negative surgical margins, 73.1% for neck dissection LN yield, 69% for adjuvant radiation, 42.6% for adjuvant chemoradiation, and 44.5% for adjuvant therapy within 6 weeks. Risk-adjusted Cox proportional-hazard models indicated that all metrics were associated with a reduced risk of death: negative margins (hazard ratio [HR] 0.73; 95% confidence interval [CI], 0.71-0.76), LN yield ≥ 18 (HR, 0.93; 95% CI, 0.89-0.96), adjuvant radiation (HR, 0.67; 95% CI, 0.64-0.70), adjuvant chemoradiation (HR, 0.84; 95% CI, 0.79-0.88), and adjuvant therapy ≤6 weeks (HR, 0.92; 95% CI, 0.89-0.96). Patients who received high-quality care had a 19% reduced adjusted hazard of mortality (HR, 0.81; 95% CI, 0.79-0.83). Five head and neck cancer quality metrics were identified that have substantial variability in adherence and meaningfully impact overall survival. These metrics are appropriate candidates for national adoption. Cancer 2017;123:4372-81. © 2017 American Cancer Society. © 2017 American Cancer Society.

Evaluating which plan quality metrics are appropriate for use in lung SBRT.

PubMed

Yaparpalvi, Ravindra; Garg, Madhur K; Shen, Jin; Bodner, William R; Mynampati, Dinesh K; Gafar, Aleiya; Kuo, Hsiang-Chi; Basavatia, Amar K; Ohri, Nitin; Hong, Linda X; Kalnicki, Shalom; Tome, Wolfgang A

2018-02-01

Several dose metrics in the categories-homogeneity, coverage, conformity and gradient have been proposed in literature for evaluating treatment plan quality. In this study, we applied these metrics to characterize and identify the plan quality metrics that would merit plan quality assessment in lung stereotactic body radiation therapy (SBRT) dose distributions. Treatment plans of 90 lung SBRT patients, comprising 91 targets, treated in our institution were retrospectively reviewed. Dose calculations were performed using anisotropic analytical algorithm (AAA) with heterogeneity correction. A literature review on published plan quality metrics in the categories-coverage, homogeneity, conformity and gradient was performed. For each patient, using dose-volume histogram data, plan quality metric values were quantified and analysed. For the study, the radiation therapy oncology group (RTOG) defined plan quality metrics were: coverage (0.90 ± 0.08); homogeneity (1.27 ± 0.07); conformity (1.03 ± 0.07) and gradient (4.40 ± 0.80). Geometric conformity strongly correlated with conformity index (p < 0.0001). Gradient measures strongly correlated with target volume (p < 0.0001). The RTOG lung SBRT protocol advocated conformity guidelines for prescribed dose in all categories were met in ≥94% of cases. The proportion of total lung volume receiving doses of 20 Gy and 5 Gy (V 20 and V 5 ) were mean 4.8% (±3.2) and 16.4% (±9.2), respectively. Based on our study analyses, we recommend the following metrics as appropriate surrogates for establishing SBRT lung plan quality guidelines-coverage % (ICRU 62), conformity (CN or CI Paddick ) and gradient (R 50% ). Furthermore, we strongly recommend that RTOG lung SBRT protocols adopt either CN or CI Padddick in place of prescription isodose to target volume ratio for conformity index evaluation. Advances in knowledge: Our study metrics are valuable tools for establishing lung SBRT plan quality guidelines.

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.

Perceived assessment metrics for visible and infrared color fused image quality without reference image

NASA Astrophysics Data System (ADS)

Yu, Xuelian; Chen, Qian; Gu, Guohua; Ren, Jianle; Sui, Xiubao

2015-02-01

Designing objective quality assessment of color-fused image is a very demanding and challenging task. We propose four no-reference metrics based on human visual system characteristics for objectively evaluating the quality of false color fusion image. The perceived edge metric (PEM) is defined based on visual perception model and color image gradient similarity between the fused image and the source images. The perceptual contrast metric (PCM) is established associating multi-scale contrast and varying contrast sensitivity filter (CSF) with color components. The linear combination of the standard deviation and mean value over the fused image construct the image colorfulness metric (ICM). The color comfort metric (CCM) is designed by the average saturation and the ratio of pixels with high and low saturation. The qualitative and quantitative experimental results demonstrate that the proposed metrics have a good agreement with subjective perception.

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

The compressed average image intensity metric for stereoscopic video quality assessment

NASA Astrophysics Data System (ADS)

Wilczewski, Grzegorz

2016-09-01

The following article depicts insights towards design, creation and testing of a genuine metric designed for a 3DTV video quality evaluation. The Compressed Average Image Intensity (CAII) mechanism is based upon stereoscopic video content analysis, setting its core feature and functionality to serve as a versatile tool for an effective 3DTV service quality assessment. Being an objective type of quality metric it may be utilized as a reliable source of information about the actual performance of a given 3DTV system, under strict providers evaluation. Concerning testing and the overall performance analysis of the CAII metric, the following paper presents comprehensive study of results gathered across several testing routines among selected set of samples of stereoscopic video content. As a result, the designed method for stereoscopic video quality evaluation is investigated across the range of synthetic visual impairments injected into the original video stream.

Performance evaluation of no-reference image quality metrics for face biometric images

NASA Astrophysics Data System (ADS)

Liu, Xinwei; Pedersen, Marius; Charrier, Christophe; Bours, Patrick

2018-03-01

The accuracy of face recognition systems is significantly affected by the quality of face sample images. The recent established standardization proposed several important aspects for the assessment of face sample quality. There are many existing no-reference image quality metrics (IQMs) that are able to assess natural image quality by taking into account similar image-based quality attributes as introduced in the standardization. However, whether such metrics can assess face sample quality is rarely considered. We evaluate the performance of 13 selected no-reference IQMs on face biometrics. The experimental results show that several of them can assess face sample quality according to the system performance. We also analyze the strengths and weaknesses of different IQMs as well as why some of them failed to assess face sample quality. Retraining an original IQM by using face database can improve the performance of such a metric. In addition, the contribution of this paper can be used for the evaluation of IQMs on other biometric modalities; furthermore, it can be used for the development of multimodality biometric IQMs.

A Validation of Object-Oriented Design Metrics as Quality Indicators

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Briand, Lionel C.; Melo, Walcelio

1997-01-01

This paper presents the results of a study in which we empirically investigated the suits of object-oriented (00) design metrics introduced in another work. More specifically, our goal is to assess these metrics as predictors of fault-prone classes and, therefore, determine whether they can be used as early quality indicators. This study is complementary to the work described where the same suite of metrics had been used to assess frequencies of maintenance changes to classes. To perform our validation accurately, we collected data on the development of eight medium-sized information management systems based on identical requirements. All eight projects were developed using a sequential life cycle model, a well-known 00 analysis/design method and the C++ programming language. Based on empirical and quantitative analysis, the advantages and drawbacks of these 00 metrics are discussed. Several of Chidamber and Kamerer's 00 metrics appear to be useful to predict class fault-proneness during the early phases of the life-cycle. Also, on our data set, they are better predictors than 'traditional' code metrics, which can only be collected at a later phase of the software development processes.

Evaluation of cassette-based digital radiography detectors using standardized image quality metrics: AAPM TG-150 Draft Image Detector Tests.

PubMed

Li, Guang; Greene, Travis C; Nishino, Thomas K; Willis, Charles E

2016-09-08

The purpose of this study was to evaluate several of the standardized image quality metrics proposed by the American Association of Physics in Medicine (AAPM) Task Group 150. The task group suggested region-of-interest (ROI)-based techniques to measure nonuniformity, minimum signal-to-noise ratio (SNR), number of anomalous pixels, and modulation transfer function (MTF). This study evaluated the effects of ROI size and layout on the image metrics by using four different ROI sets, assessed result uncertainty by repeating measurements, and compared results with two commercially available quality control tools, namely the Carestream DIRECTVIEW Total Quality Tool (TQT) and the GE Healthcare Quality Assurance Process (QAP). Seven Carestream DRX-1C (CsI) detectors on mobile DR systems and four GE FlashPad detectors in radiographic rooms were tested. Images were analyzed using MATLAB software that had been previously validated and reported. Our values for signal and SNR nonuniformity and MTF agree with values published by other investigators. Our results show that ROI size affects nonuniformity and minimum SNR measurements, but not detection of anomalous pixels. Exposure geometry affects all tested image metrics except for the MTF. TG-150 metrics in general agree with the TQT, but agree with the QAP only for local and global signal nonuniformity. The difference in SNR nonuniformity and MTF values between the TG-150 and QAP may be explained by differences in the calculation of noise and acquisition beam quality, respectively. TG-150's SNR nonuniformity metrics are also more sensitive to detector nonuniformity compared to the QAP. Our results suggest that fixed ROI size should be used for consistency because nonuniformity metrics depend on ROI size. Ideally, detector tests should be performed at the exact calibration position. If not feasible, a baseline should be established from the mean of several repeated measurements. Our study indicates that the TG-150 tests can be

Evaluation of cassette‐based digital radiography detectors using standardized image quality metrics: AAPM TG‐150 Draft Image Detector Tests

PubMed Central

Greene, Travis C.; Nishino, Thomas K.; Willis, Charles E.

2016-01-01

The purpose of this study was to evaluate several of the standardized image quality metrics proposed by the American Association of Physics in Medicine (AAPM) Task Group 150. The task group suggested region‐of‐interest (ROI)‐based techniques to measure nonuniformity, minimum signal‐to‐noise ratio (SNR), number of anomalous pixels, and modulation transfer function (MTF). This study evaluated the effects of ROI size and layout on the image metrics by using four different ROI sets, assessed result uncertainty by repeating measurements, and compared results with two commercially available quality control tools, namely the Carestream DIRECTVIEW Total Quality Tool (TQT) and the GE Healthcare Quality Assurance Process (QAP). Seven Carestream DRX‐1C (CsI) detectors on mobile DR systems and four GE FlashPad detectors in radiographic rooms were tested. Images were analyzed using MATLAB software that had been previously validated and reported. Our values for signal and SNR nonuniformity and MTF agree with values published by other investigators. Our results show that ROI size affects nonuniformity and minimum SNR measurements, but not detection of anomalous pixels. Exposure geometry affects all tested image metrics except for the MTF. TG‐150 metrics in general agree with the TQT, but agree with the QAP only for local and global signal nonuniformity. The difference in SNR nonuniformity and MTF values between the TG‐150 and QAP may be explained by differences in the calculation of noise and acquisition beam quality, respectively. TG‐150's SNR nonuniformity metrics are also more sensitive to detector nonuniformity compared to the QAP. Our results suggest that fixed ROI size should be used for consistency because nonuniformity metrics depend on ROI size. Ideally, detector tests should be performed at the exact calibration position. If not feasible, a baseline should be established from the mean of several repeated measurements. Our study indicates that the TG�

Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale

PubMed Central

Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Overview Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms—Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. Cluster Quality Metrics We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Network Clustering Algorithms Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large

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

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

Quantitative metrics for assessment of chemical image quality and spatial resolution

DOE PAGES

Kertesz, Vilmos; Cahill, John F.; Van Berkel, Gary J.

2016-02-28

Rationale: Currently objective/quantitative descriptions of the quality and spatial resolution of mass spectrometry derived chemical images are not standardized. Development of these standardized metrics is required to objectively describe chemical imaging capabilities of existing and/or new mass spectrometry imaging technologies. Such metrics would allow unbiased judgment of intra-laboratory advancement and/or inter-laboratory comparison for these technologies if used together with standardized surfaces. Methods: We developed two image metrics, viz., chemical image contrast (ChemIC) based on signal-to-noise related statistical measures on chemical image pixels and corrected resolving power factor (cRPF) constructed from statistical analysis of mass-to-charge chronograms across features of interest inmore » an image. These metrics, quantifying chemical image quality and spatial resolution, respectively, were used to evaluate chemical images of a model photoresist patterned surface collected using a laser ablation/liquid vortex capture mass spectrometry imaging system under different instrument operational parameters. Results: The calculated ChemIC and cRPF metrics determined in an unbiased fashion the relative ranking of chemical image quality obtained with the laser ablation/liquid vortex capture mass spectrometry imaging system. These rankings were used to show that both chemical image contrast and spatial resolution deteriorated with increasing surface scan speed, increased lane spacing and decreasing size of surface features. Conclusions: ChemIC and cRPF, respectively, were developed and successfully applied for the objective description of chemical image quality and spatial resolution of chemical images collected from model surfaces using a laser ablation/liquid vortex capture mass spectrometry imaging system.« less

Quantitative metrics for assessment of chemical image quality and spatial resolution

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

Kertesz, Vilmos; Cahill, John F.; Van Berkel, Gary J.

Rationale: Currently objective/quantitative descriptions of the quality and spatial resolution of mass spectrometry derived chemical images are not standardized. Development of these standardized metrics is required to objectively describe chemical imaging capabilities of existing and/or new mass spectrometry imaging technologies. Such metrics would allow unbiased judgment of intra-laboratory advancement and/or inter-laboratory comparison for these technologies if used together with standardized surfaces. Methods: We developed two image metrics, viz., chemical image contrast (ChemIC) based on signal-to-noise related statistical measures on chemical image pixels and corrected resolving power factor (cRPF) constructed from statistical analysis of mass-to-charge chronograms across features of interest inmore » an image. These metrics, quantifying chemical image quality and spatial resolution, respectively, were used to evaluate chemical images of a model photoresist patterned surface collected using a laser ablation/liquid vortex capture mass spectrometry imaging system under different instrument operational parameters. Results: The calculated ChemIC and cRPF metrics determined in an unbiased fashion the relative ranking of chemical image quality obtained with the laser ablation/liquid vortex capture mass spectrometry imaging system. These rankings were used to show that both chemical image contrast and spatial resolution deteriorated with increasing surface scan speed, increased lane spacing and decreasing size of surface features. Conclusions: ChemIC and cRPF, respectively, were developed and successfully applied for the objective description of chemical image quality and spatial resolution of chemical images collected from model surfaces using a laser ablation/liquid vortex capture mass spectrometry imaging system.« less

Defining quality metrics and improving safety and outcome in allergy care.

PubMed

Lee, Stella; Stachler, Robert J; Ferguson, Berrylin J

2014-04-01

The delivery of allergy immunotherapy in the otolaryngology office is variable and lacks standardization. Quality metrics encompasses the measurement of factors associated with good patient-centered care. These factors have yet to be defined in the delivery of allergy immunotherapy. We developed and applied quality metrics to 6 allergy practices affiliated with an academic otolaryngic allergy center. This work was conducted at a tertiary academic center providing care to over 1500 patients. We evaluated methods and variability between 6 sites. Tracking of errors and anaphylaxis was initiated across all sites. A nationwide survey of academic and private allergists was used to collect data on current practice and use of quality metrics. The most common types of errors recorded were patient identification errors (n = 4), followed by vial mixing errors (n = 3), and dosing errors (n = 2). There were 7 episodes of anaphylaxis of which 2 were secondary to dosing errors for a rate of 0.01% or 1 in every 10,000 injection visits/year. Site visits showed that 86% of key safety measures were followed. Analysis of nationwide survey responses revealed that quality metrics are still not well defined by either medical or otolaryngic allergy practices. Academic practices were statistically more likely to use quality metrics (p = 0.021) and perform systems reviews and audits in comparison to private practices (p = 0.005). Quality metrics in allergy delivery can help improve safety and quality care. These metrics need to be further defined by otolaryngic allergists in the changing health care environment. © 2014 ARS-AAOA, LLC.

Analysis of Network Clustering Algorithms and Cluster Quality Metrics at Scale.

PubMed

Emmons, Scott; Kobourov, Stephen; Gallant, Mike; Börner, Katy

2016-01-01

Notions of community quality underlie the clustering of networks. While studies surrounding network clustering are increasingly common, a precise understanding of the realtionship between different cluster quality metrics is unknown. In this paper, we examine the relationship between stand-alone cluster quality metrics and information recovery metrics through a rigorous analysis of four widely-used network clustering algorithms-Louvain, Infomap, label propagation, and smart local moving. We consider the stand-alone quality metrics of modularity, conductance, and coverage, and we consider the information recovery metrics of adjusted Rand score, normalized mutual information, and a variant of normalized mutual information used in previous work. Our study includes both synthetic graphs and empirical data sets of sizes varying from 1,000 to 1,000,000 nodes. We find significant differences among the results of the different cluster quality metrics. For example, clustering algorithms can return a value of 0.4 out of 1 on modularity but score 0 out of 1 on information recovery. We find conductance, though imperfect, to be the stand-alone quality metric that best indicates performance on the information recovery metrics. Additionally, our study shows that the variant of normalized mutual information used in previous work cannot be assumed to differ only slightly from traditional normalized mutual information. Smart local moving is the overall best performing algorithm in our study, but discrepancies between cluster evaluation metrics prevent us from declaring it an absolutely superior algorithm. Interestingly, Louvain performed better than Infomap in nearly all the tests in our study, contradicting the results of previous work in which Infomap was superior to Louvain. We find that although label propagation performs poorly when clusters are less clearly defined, it scales efficiently and accurately to large graphs with well-defined clusters.

Spatial-temporal distortion metric for in-service quality monitoring of any digital video system

NASA Astrophysics Data System (ADS)

Wolf, Stephen; Pinson, Margaret H.

1999-11-01

Many organizations have focused on developing digital video quality metrics which produce results that accurately emulate subjective responses. However, to be widely applicable a metric must also work over a wide range of quality, and be useful for in-service quality monitoring. The Institute for Telecommunication Sciences (ITS) has developed spatial-temporal distortion metrics that meet all of these requirements. These objective metrics are described in detail and have a number of interesting properties, including utilization of (1) spatial activity filters which emphasize long edges on the order of 10 arc min while simultaneously performing large amounts of noise suppression, (2) the angular direction of the spatial gradient, (3) spatial-temporal compression factors of at least 384:1 (spatial compression of at least 64:1 and temporal compression of at least 6:1, and 4) simple perceptibility thresholds and spatial-temporal masking functions. Results are presented that compare the objective metric values with mean opinion scores from a wide range of subjective data bases spanning many different scenes, systems, bit-rates, and applications.

National Quality Forum Colon Cancer Quality Metric Performance: How Are Hospitals Measuring Up?

PubMed

Mason, Meredith C; Chang, George J; Petersen, Laura A; Sada, Yvonne H; Tran Cao, Hop S; Chai, Christy; Berger, David H; Massarweh, Nader N

2017-12-01

To evaluate the impact of care at high-performing hospitals on the National Quality Forum (NQF) colon cancer metrics. The NQF endorses evaluating ≥12 lymph nodes (LNs), adjuvant chemotherapy (AC) for stage III patients, and AC within 4 months of diagnosis as colon cancer quality indicators. Data on hospital-level metric performance and the association with survival are unclear. Retrospective cohort study of 218,186 patients with resected stage I to III colon cancer in the National Cancer Data Base (2004-2012). High-performing hospitals (>75% achievement) were identified by the proportion of patients achieving each measure. The association between hospital performance and survival was evaluated using Cox shared frailty modeling. Only hospital LN performance improved (15.8% in 2004 vs 80.7% in 2012; trend test, P < 0.001), with 45.9% of hospitals performing well on all 3 measures concurrently in the most recent study year. Overall, 5-year survival was 75.0%, 72.3%, 72.5%, and 69.5% for those treated at hospitals with high performance on 3, 2, 1, and 0 metrics, respectively (log-rank, P < 0.001). Care at hospitals with high metric performance was associated with lower risk of death in a dose-response fashion [0 metrics, reference; 1, hazard ratio (HR) 0.96 (0.89-1.03); 2, HR 0.92 (0.87-0.98); 3, HR 0.85 (0.80-0.90); 2 vs 1, HR 0.96 (0.91-1.01); 3 vs 1, HR 0.89 (0.84-0.93); 3 vs 2, HR 0.95 (0.89-0.95)]. Performance on metrics in combination was associated with lower risk of death [LN + AC, HR 0.86 (0.78-0.95); AC + timely AC, HR 0.92 (0.87-0.98); LN + AC + timely AC, HR 0.85 (0.80-0.90)], whereas individual measures were not [LN, HR 0.95 (0.88-1.04); AC, HR 0.95 (0.87-1.05)]. Less than half of hospitals perform well on these NQF colon cancer metrics concurrently, and high performance on individual measures is not associated with improved survival. Quality improvement efforts should shift focus from individual measures to defining composite measures

The use of vision-based image quality metrics to predict low-light performance of camera phones

NASA Astrophysics Data System (ADS)

Hultgren, B.; Hertel, D.

2010-01-01

Small digital camera modules such as those in mobile phones have become ubiquitous. Their low-light performance is of utmost importance since a high percentage of images are made under low lighting conditions where image quality failure may occur due to blur, noise, and/or underexposure. These modes of image degradation are not mutually exclusive: they share common roots in the physics of the imager, the constraints of image processing, and the general trade-off situations in camera design. A comprehensive analysis of failure modes is needed in order to understand how their interactions affect overall image quality. Low-light performance is reported for DSLR, point-and-shoot, and mobile phone cameras. The measurements target blur, noise, and exposure error. Image sharpness is evaluated from three different physical measurements: static spatial frequency response, handheld motion blur, and statistical information loss due to image processing. Visual metrics for sharpness, graininess, and brightness are calculated from the physical measurements, and displayed as orthogonal image quality metrics to illustrate the relative magnitude of image quality degradation as a function of subject illumination. The impact of each of the three sharpness measurements on overall sharpness quality is displayed for different light levels. The power spectrum of the statistical information target is a good representation of natural scenes, thus providing a defined input signal for the measurement of power-spectrum based signal-to-noise ratio to characterize overall imaging performance.

Automatic red eye correction and its quality metric

NASA Astrophysics Data System (ADS)

Safonov, Ilia V.; Rychagov, Michael N.; Kang, KiMin; Kim, Sang Ho

2008-01-01

The red eye artifacts are troublesome defect of amateur photos. Correction of red eyes during printing without user intervention and making photos more pleasant for an observer are important tasks. The novel efficient technique of automatic correction of red eyes aimed for photo printers is proposed. This algorithm is independent from face orientation and capable to detect paired red eyes as well as single red eyes. The approach is based on application of 3D tables with typicalness levels for red eyes and human skin tones and directional edge detection filters for processing of redness image. Machine learning is applied for feature selection. For classification of red eye regions a cascade of classifiers including Gentle AdaBoost committee from Classification and Regression Trees (CART) is applied. Retouching stage includes desaturation, darkening and blending with initial image. Several versions of approach implementation using trade-off between detection and correction quality, processing time, memory volume are possible. The numeric quality criterion of automatic red eye correction is proposed. This quality metric is constructed by applying Analytic Hierarchy Process (AHP) for consumer opinions about correction outcomes. Proposed numeric metric helped to choose algorithm parameters via optimization procedure. Experimental results demonstrate high accuracy and efficiency of the proposed algorithm in comparison with existing solutions.

Comparison of macroinvertebrate-derived stream quality metrics between snag and riffle habitats

USGS Publications Warehouse

Stepenuck, K.F.; Crunkilton, R.L.; Bozek, Michael A.; Wang, L.

2008-01-01

We compared benthic macroinvertebrate assemblage structure at snag and riffle habitats in 43 Wisconsin streams across a range of watershed urbanization using a variety of stream quality metrics. Discriminant analysis indicated that dominant taxa at riffles and snags differed; Hydropsychid caddisflies (Hydropsyche betteni and Cheumatopsyche spp.) and elmid beetles (Optioservus spp. and Stenemlis spp.) typified riffles, whereas isopods (Asellus intermedius) and amphipods (Hyalella azteca and Gammarus pseudolimnaeus) predominated in snags. Analysis of covariance indicated that samples from snag and riffle habitats differed significantly in their response to the urbanization gradient for the Hilsenhoff biotic index (BI), Shannon's diversity index, and percent of filterers, shredders, and pollution intolerant Ephemeroptera, Plecoptera, and Trichoptera (EPT) at each stream site (p ??? 0.10). These differences suggest that although macroinvertebrate assemblages present in either habitat type are sensitive to detecting the effects of urbanization, metrics derived from different habitats should not be intermixed when assessing stream quality through biomonitoring. This can be a limitation to resource managers who wish to compare water quality among streams where the same habitat type is not available at all stream locations, or where a specific habitat type (i.e., a riffle) is required to determine a metric value (i.e., BI). To account for differences in stream quality at sites lacking riffle habitat, snag-derived metric values can be adjusted based on those obtained from riffles that have been exposed to the same level of urbanization. Comparison of nonlinear regression equations that related stream quality metric values from the two habitat types to percent watershed urbanization indicated that snag habitats had on average 30.2 fewer percent EPT individuals, a lower diversity index value than riffles, and a BI value of 0.29 greater than riffles. ?? 2008 American Water

Software metrics: The key to quality software on the NCC project

NASA Technical Reports Server (NTRS)

Burns, Patricia J.

1993-01-01

Network Control Center (NCC) Project metrics are captured during the implementation and testing phases of the NCCDS software development lifecycle. The metrics data collection and reporting function has interfaces with all elements of the NCC project. Close collaboration with all project elements has resulted in the development of a defined and repeatable set of metrics processes. The resulting data are used to plan and monitor release activities on a weekly basis. The use of graphical outputs facilitates the interpretation of progress and status. The successful application of metrics throughout the NCC project has been instrumental in the delivery of quality software. The use of metrics on the NCC Project supports the needs of the technical and managerial staff. This paper describes the project, the functions supported by metrics, the data that are collected and reported, how the data are used, and the improvements in the quality of deliverable software since the metrics processes and products have been in use.

Modulated evaluation metrics for drug-based ontologies.

PubMed

Amith, Muhammad; Tao, Cui

2017-04-24

Research for ontology evaluation is scarce. If biomedical ontological datasets and knowledgebases are to be widely used, there needs to be quality control and evaluation for the content and structure of the ontology. This paper introduces how to effectively utilize a semiotic-inspired approach to ontology evaluation, specifically towards drug-related ontologies hosted on the National Center for Biomedical Ontology BioPortal. Using the semiotic-based evaluation framework for drug-based ontologies, we adjusted the quality metrics based on the semiotic features of drug ontologies. Then, we compared the quality scores before and after tailoring. The scores revealed a more precise measurement and a closer distribution compared to the before-tailoring. The results of this study reveal that a tailored semiotic evaluation produced a more meaningful and accurate assessment of drug-based ontologies, lending to the possible usefulness of semiotics in ontology evaluation.

Testing, Requirements, and Metrics

NASA Technical Reports Server (NTRS)

Rosenberg, Linda; Hyatt, Larry; Hammer, Theodore F.; Huffman, Lenore; Wilson, William

1998-01-01

The criticality of correct, complete, testable requirements is a fundamental tenet of software engineering. Also critical is complete requirements based testing of the final product. Modern tools for managing requirements allow new metrics to be used in support of both of these critical processes. Using these tools, potential problems with the quality of the requirements and the test plan can be identified early in the life cycle. Some of these quality factors include: ambiguous or incomplete requirements, poorly designed requirements databases, excessive or insufficient test cases, and incomplete linkage of tests to requirements. This paper discusses how metrics can be used to evaluate the quality of the requirements and test to avoid problems later. Requirements management and requirements based testing have always been critical in the implementation of high quality software systems. Recently, automated tools have become available to support requirements management. At NASA's Goddard Space Flight Center (GSFC), automated requirements management tools are being used on several large projects. The use of these tools opens the door to innovative uses of metrics in characterizing test plan quality and assessing overall testing risks. In support of these projects, the Software Assurance Technology Center (SATC) is working to develop and apply a metrics program that utilizes the information now available through the application of requirements management tools. Metrics based on this information provides real-time insight into the testing of requirements and these metrics assist the Project Quality Office in its testing oversight role. This paper discusses three facets of the SATC's efforts to evaluate the quality of the requirements and test plan early in the life cycle, thus preventing costly errors and time delays later.

Pragmatic quality metrics for evolutionary software development models

NASA Technical Reports Server (NTRS)

Royce, Walker

1990-01-01

Due to the large number of product, project, and people parameters which impact large custom software development efforts, measurement of software product quality is a complex undertaking. Furthermore, the absolute perspective from which quality is measured (customer satisfaction) is intangible. While we probably can't say what the absolute quality of a software product is, we can determine the relative quality, the adequacy of this quality with respect to pragmatic considerations, and identify good and bad trends during development. While no two software engineers will ever agree on an optimum definition of software quality, they will agree that the most important perspective of software quality is its ease of change. We can call this flexibility, adaptability, or some other vague term, but the critical characteristic of software is that it is soft. The easier the product is to modify, the easier it is to achieve any other software quality perspective. This paper presents objective quality metrics derived from consistent lifecycle perspectives of rework which, when used in concert with an evolutionary development approach, can provide useful insight to produce better quality per unit cost/schedule or to achieve adequate quality more efficiently. The usefulness of these metrics is evaluated by applying them to a large, real world, Ada project.

Specification-based software sizing: An empirical investigation of function metrics

NASA Technical Reports Server (NTRS)

Jeffery, Ross; Stathis, John

1993-01-01

For some time the software industry has espoused the need for improved specification-based software size metrics. This paper reports on a study of nineteen recently developed systems in a variety of application domains. The systems were developed by a single software services corporation using a variety of languages. The study investigated several metric characteristics. It shows that: earlier research into inter-item correlation within the overall function count is partially supported; a priori function counts, in themself, do not explain the majority of the effort variation in software development in the organization studied; documentation quality is critical to accurate function identification; and rater error is substantial in manual function counting. The implication of these findings for organizations using function based metrics are explored.

A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

USGS Publications Warehouse

Nicol, Sam; Wiederholt, Ruscena; Diffendorfer, James E.; Mattsson, Brady; Thogmartin, Wayne E.; Semmens, Darius J.; Laura Lopez-Hoffman,; Norris, Ryan

2016-01-01

Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.

qcML: An Exchange Format for Quality Control Metrics from Mass Spectrometry Experiments*

PubMed Central

Walzer, Mathias; Pernas, Lucia Espona; Nasso, Sara; Bittremieux, Wout; Nahnsen, Sven; Kelchtermans, Pieter; Pichler, Peter; van den Toorn, Henk W. P.; Staes, An; Vandenbussche, Jonathan; Mazanek, Michael; Taus, Thomas; Scheltema, Richard A.; Kelstrup, Christian D.; Gatto, Laurent; van Breukelen, Bas; Aiche, Stephan; Valkenborg, Dirk; Laukens, Kris; Lilley, Kathryn S.; Olsen, Jesper V.; Heck, Albert J. R.; Mechtler, Karl; Aebersold, Ruedi; Gevaert, Kris; Vizcaíno, Juan Antonio; Hermjakob, Henning; Kohlbacher, Oliver; Martens, Lennart

2014-01-01

Quality control is increasingly recognized as a crucial aspect of mass spectrometry based proteomics. Several recent papers discuss relevant parameters for quality control and present applications to extract these from the instrumental raw data. What has been missing, however, is a standard data exchange format for reporting these performance metrics. We therefore developed the qcML format, an XML-based standard that follows the design principles of the related mzML, mzIdentML, mzQuantML, and TraML standards from the HUPO-PSI (Proteomics Standards Initiative). In addition to the XML format, we also provide tools for the calculation of a wide range of quality metrics as well as a database format and interconversion tools, so that existing LIMS systems can easily add relational storage of the quality control data to their existing schema. We here describe the qcML specification, along with possible use cases and an illustrative example of the subsequent analysis possibilities. All information about qcML is available at http://code.google.com/p/qcml. PMID:24760958

qcML: an exchange format for quality control metrics from mass spectrometry experiments.

PubMed

Walzer, Mathias; Pernas, Lucia Espona; Nasso, Sara; Bittremieux, Wout; Nahnsen, Sven; Kelchtermans, Pieter; Pichler, Peter; van den Toorn, Henk W P; Staes, An; Vandenbussche, Jonathan; Mazanek, Michael; Taus, Thomas; Scheltema, Richard A; Kelstrup, Christian D; Gatto, Laurent; van Breukelen, Bas; Aiche, Stephan; Valkenborg, Dirk; Laukens, Kris; Lilley, Kathryn S; Olsen, Jesper V; Heck, Albert J R; Mechtler, Karl; Aebersold, Ruedi; Gevaert, Kris; Vizcaíno, Juan Antonio; Hermjakob, Henning; Kohlbacher, Oliver; Martens, Lennart

2014-08-01

Quality control is increasingly recognized as a crucial aspect of mass spectrometry based proteomics. Several recent papers discuss relevant parameters for quality control and present applications to extract these from the instrumental raw data. What has been missing, however, is a standard data exchange format for reporting these performance metrics. We therefore developed the qcML format, an XML-based standard that follows the design principles of the related mzML, mzIdentML, mzQuantML, and TraML standards from the HUPO-PSI (Proteomics Standards Initiative). In addition to the XML format, we also provide tools for the calculation of a wide range of quality metrics as well as a database format and interconversion tools, so that existing LIMS systems can easily add relational storage of the quality control data to their existing schema. We here describe the qcML specification, along with possible use cases and an illustrative example of the subsequent analysis possibilities. All information about qcML is available at http://code.google.com/p/qcml. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

Sigma metrics used to assess analytical quality of clinical chemistry assays: importance of the allowable total error (TEa) target.

PubMed

Hens, Koen; Berth, Mario; Armbruster, Dave; Westgard, Sten

2014-07-01

Six Sigma metrics were used to assess the analytical quality of automated clinical chemistry and immunoassay tests in a large Belgian clinical laboratory and to explore the importance of the source used for estimation of the allowable total error. Clinical laboratories are continually challenged to maintain analytical quality. However, it is difficult to measure assay quality objectively and quantitatively. The Sigma metric is a single number that estimates quality based on the traditional parameters used in the clinical laboratory: allowable total error (TEa), precision and bias. In this study, Sigma metrics were calculated for 41 clinical chemistry assays for serum and urine on five ARCHITECT c16000 chemistry analyzers. Controls at two analyte concentrations were tested and Sigma metrics were calculated using three different TEa targets (Ricos biological variability, CLIA, and RiliBÄK). Sigma metrics varied with analyte concentration, the TEa target, and between/among analyzers. Sigma values identified those assays that are analytically robust and require minimal quality control rules and those that exhibit more variability and require more complex rules. The analyzer to analyzer variability was assessed on the basis of Sigma metrics. Six Sigma is a more efficient way to control quality, but the lack of TEa targets for many analytes and the sometimes inconsistent TEa targets from different sources are important variables for the interpretation and the application of Sigma metrics in a routine clinical laboratory. Sigma metrics are a valuable means of comparing the analytical quality of two or more analyzers to ensure the comparability of patient test results.

Improvement of impact noise in a passenger car utilizing sound metric based on wavelet transform

NASA Astrophysics Data System (ADS)

Lee, Sang-Kwon; Kim, Ho-Wuk; Na, Eun-Woo

2010-08-01

A new sound metric for impact sound is developed based on the continuous wavelet transform (CWT), a useful tool for the analysis of non-stationary signals such as impact noise. Together with new metric, two other conventional sound metrics related to sound modulation and fluctuation are also considered. In all, three sound metrics are employed to develop impact sound quality indexes for several specific impact courses on the road. Impact sounds are evaluated subjectively by 25 jurors. The indexes are verified by comparing the correlation between the index output and results of a subjective evaluation based on a jury test. These indexes are successfully applied to an objective evaluation for improvement of the impact sound quality for cases where some parts of the suspension system of the test car are modified.

New Quality Metrics for Web Search Results

NASA Astrophysics Data System (ADS)

Metaxas, Panagiotis Takis; Ivanova, Lilia; Mustafaraj, Eni

Web search results enjoy an increasing importance in our daily lives. But what can be said about their quality, especially when querying a controversial issue? The traditional information retrieval metrics of precision and recall do not provide much insight in the case of web information retrieval. In this paper we examine new ways of evaluating quality in search results: coverage and independence. We give examples on how these new metrics can be calculated and what their values reveal regarding the two major search engines, Google and Yahoo. We have found evidence of low coverage for commercial and medical controversial queries, and high coverage for a political query that is highly contested. Given the fact that search engines are unwilling to tune their search results manually, except in a few cases that have become the source of bad publicity, low coverage and independence reveal the efforts of dedicated groups to manipulate the search results.

Value-based metrics and Internet-based enterprises

NASA Astrophysics Data System (ADS)

Gupta, Krishan M.

2001-10-01

Within the last few years, a host of value-based metrics like EVA, MVA, TBR, CFORI, and TSR have evolved. This paper attempts to analyze the validity and applicability of EVA and Balanced Scorecard for Internet based organizations. Despite the collapse of the dot-com model, the firms engaged in e- commerce continue to struggle to find new ways to account for customer-base, technology, employees, knowledge, etc, as part of the value of the firm. While some metrics, like the Balance Scorecard are geared towards internal use, others like EVA are for external use. Value-based metrics are used for performing internal audits as well as comparing firms against one another; and can also be effectively utilized by individuals outside the firm looking to determine if the firm is creating value for its stakeholders.

A Novel Scoring Metrics for Quality Assurance of Ocean Color Observations

NASA Astrophysics Data System (ADS)

Wei, J.; Lee, Z.

2016-02-01

Interpretation of the ocean bio-optical properties from ocean color observations depends on the quality of the ocean color data, specifically the spectrum of remote sensing reflectance (Rrs). The in situ and remotely measured Rrs spectra are inevitably subject to errors induced by instrument calibration, sea-surface correction and atmospheric correction, and other environmental factors. Great efforts have been devoted to the ocean color calibration and validation. Yet, there exist no objective and consensus criteria for assessment of the ocean color data quality. In this study, the gap is filled by developing a novel metrics for such data quality assurance and quality control (QA/QC). This new QA metrics is not intended to discard "suspicious" Rrs spectra from available datasets. Rather, it takes into account the Rrs spectral shapes and amplitudes as a whole and grades each Rrs spectrum. This scoring system is developed based on a large ensemble of in situ hyperspectral remote sensing reflectance data measured from various aquatic environments and processed with robust procedures. This system is further tested with the NASA bio-Optical Marine Algorithm Data set (NOMAD), with results indicating significant improvements in the estimation of bio-optical properties when Rrs spectra marked with higher quality assurance are used. This scoring system is further verified with simulated data and satellite ocean color data in various regions, and we envision higher quality ocean color products with the implementation of such a quality screening system.

Development of quality metrics for ambulatory care in pediatric patients with tetralogy of Fallot.

PubMed

Villafane, Juan; Edwards, Thomas C; Diab, Karim A; Satou, Gary M; Saarel, Elizabeth; Lai, Wyman W; Serwer, Gerald A; Karpawich, Peter P; Cross, Russell; Schiff, Russell; Chowdhury, Devyani; Hougen, Thomas J

2017-12-01

The objective of this study was to develop quality metrics (QMs) relating to the ambulatory care of children after complete repair of tetralogy of Fallot (TOF). A workgroup team (WT) of pediatric cardiologists with expertise in all aspects of ambulatory cardiac management was formed at the request of the American College of Cardiology (ACC) and the Adult Congenital and Pediatric Cardiology Council (ACPC), to review published guidelines and consensus data relating to the ambulatory care of repaired TOF patients under the age of 18 years. A set of quality metrics (QMs) was proposed by the WT. The metrics went through a two-step evaluation process. In the first step, the RAND-UCLA modified Delphi methodology was employed and the metrics were voted on feasibility and validity by an expert panel. In the second step, QMs were put through an "open comments" process where feedback was provided by the ACPC members. The final QMs were approved by the ACPC council. The TOF WT formulated 9 QMs of which only 6 were submitted to the expert panel; 3 QMs passed the modified RAND-UCLA and went through the "open comments" process. Based on the feedback through the open comment process, only 1 metric was finally approved by the ACPC council. The ACPC Council was able to develop QM for ambulatory care of children with repaired TOF. These patients should have documented genetic testing for 22q11.2 deletion. However, lack of evidence in the literature made it a challenge to formulate other evidence-based QMs. © 2017 Wiley Periodicals, Inc.

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.

A Metric-Based Validation Process to Assess the Realism of Synthetic Power Grids

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

Birchfield, Adam; Schweitzer, Eran; Athari, Mir

Public power system test cases that are of high quality benefit the power systems research community with expanded resources for testing, demonstrating, and cross-validating new innovations. Building synthetic grid models for this purpose is a relatively new problem, for which a challenge is to show that created cases are sufficiently realistic. This paper puts forth a validation process based on a set of metrics observed from actual power system cases. These metrics follow the structure, proportions, and parameters of key power system elements, which can be used in assessing and validating the quality of synthetic power grids. Though wide diversitymore » exists in the characteristics of power systems, the paper focuses on an initial set of common quantitative metrics to capture the distribution of typical values from real power systems. The process is applied to two new public test cases, which are shown to meet the criteria specified in the metrics of this paper.« less

A Metric-Based Validation Process to Assess the Realism of Synthetic Power Grids

DOE PAGES

Birchfield, Adam; Schweitzer, Eran; Athari, Mir; ...

2017-08-19

Public power system test cases that are of high quality benefit the power systems research community with expanded resources for testing, demonstrating, and cross-validating new innovations. Building synthetic grid models for this purpose is a relatively new problem, for which a challenge is to show that created cases are sufficiently realistic. This paper puts forth a validation process based on a set of metrics observed from actual power system cases. These metrics follow the structure, proportions, and parameters of key power system elements, which can be used in assessing and validating the quality of synthetic power grids. Though wide diversitymore » exists in the characteristics of power systems, the paper focuses on an initial set of common quantitative metrics to capture the distribution of typical values from real power systems. The process is applied to two new public test cases, which are shown to meet the criteria specified in the metrics of this paper.« less

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.

Fusion set selection with surrogate metric in multi-atlas based image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Tingting; Ruan, Dan

2016-02-01

Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation.

Neural decoding with kernel-based metric learning.

PubMed

Brockmeier, Austin J; Choi, John S; Kriminger, Evan G; Francis, Joseph T; Principe, Jose C

2014-06-01

In studies of the nervous system, the choice of metric for the neural responses is a pivotal assumption. For instance, a well-suited distance metric enables us to gauge the similarity of neural responses to various stimuli and assess the variability of responses to a repeated stimulus-exploratory steps in understanding how the stimuli are encoded neurally. Here we introduce an approach where the metric is tuned for a particular neural decoding task. Neural spike train metrics have been used to quantify the information content carried by the timing of action potentials. While a number of metrics for individual neurons exist, a method to optimally combine single-neuron metrics into multineuron, or population-based, metrics is lacking. We pose the problem of optimizing multineuron metrics and other metrics using centered alignment, a kernel-based dependence measure. The approach is demonstrated on invasively recorded neural data consisting of both spike trains and local field potentials. The experimental paradigm consists of decoding the location of tactile stimulation on the forepaws of anesthetized rats. We show that the optimized metrics highlight the distinguishing dimensions of the neural response, significantly increase the decoding accuracy, and improve nonlinear dimensionality reduction methods for exploratory neural analysis.

Development of Quality Metrics in Ambulatory Pediatric Cardiology.

PubMed

Chowdhury, Devyani; Gurvitz, Michelle; Marelli, Ariane; Anderson, Jeffrey; Baker-Smith, Carissa; Diab, Karim A; Edwards, Thomas C; Hougen, Tom; Jedeikin, Roy; Johnson, Jonathan N; Karpawich, Peter; Lai, Wyman; Lu, Jimmy C; Mitchell, Stephanie; Newburger, Jane W; Penny, Daniel J; Portman, Michael A; Satou, Gary; Teitel, David; Villafane, Juan; Williams, Roberta; Jenkins, Kathy

2017-02-07

The American College of Cardiology Adult Congenital and Pediatric Cardiology (ACPC) Section had attempted to create quality metrics (QM) for ambulatory pediatric practice, but limited evidence made the process difficult. The ACPC sought to develop QMs for ambulatory pediatric cardiology practice. Five areas of interest were identified, and QMs were developed in a 2-step review process. In the first step, an expert panel, using the modified RAND-UCLA methodology, rated each QM for feasibility and validity. The second step sought input from ACPC Section members; final approval was by a vote of the ACPC Council. Work groups proposed a total of 44 QMs. Thirty-one metrics passed the RAND process and, after the open comment period, the ACPC council approved 18 metrics. The project resulted in successful development of QMs in ambulatory pediatric cardiology for a range of ambulatory domains. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Decomposition-based transfer distance metric learning for image classification.

PubMed

Luo, Yong; Liu, Tongliang; Tao, Dacheng; Xu, Chao

2014-09-01

Distance metric learning (DML) is a critical factor for image analysis and pattern recognition. To learn a robust distance metric for a target task, we need abundant side information (i.e., the similarity/dissimilarity pairwise constraints over the labeled data), which is usually unavailable in practice due to the high labeling cost. This paper considers the transfer learning setting by exploiting the large quantity of side information from certain related, but different source tasks to help with target metric learning (with only a little side information). The state-of-the-art metric learning algorithms usually fail in this setting because the data distributions of the source task and target task are often quite different. We address this problem by assuming that the target distance metric lies in the space spanned by the eigenvectors of the source metrics (or other randomly generated bases). The target metric is represented as a combination of the base metrics, which are computed using the decomposed components of the source metrics (or simply a set of random bases); we call the proposed method, decomposition-based transfer DML (DTDML). In particular, DTDML learns a sparse combination of the base metrics to construct the target metric by forcing the target metric to be close to an integration of the source metrics. The main advantage of the proposed method compared with existing transfer metric learning approaches is that we directly learn the base metric coefficients instead of the target metric. To this end, far fewer variables need to be learned. We therefore obtain more reliable solutions given the limited side information and the optimization tends to be faster. Experiments on the popular handwritten image (digit, letter) classification and challenge natural image annotation tasks demonstrate the effectiveness of the proposed method.

Evaluating Quality Metrics and Cost After Discharge: A Population-based Cohort Study of Value in Health Care Following Elective Major Vascular Surgery.

PubMed

de Mestral, Charles; Salata, Konrad; Hussain, Mohamad A; Kayssi, Ahmed; Al-Omran, Mohammed; Roche-Nagle, Graham

2018-04-18

Early readmission to hospital after surgery is an omnipresent quality metric across surgical fields. We sought to understand the relative importance of hospital readmission among all health services received after hospital discharge. The aim of this study was to characterize 30-day postdischarge cost and risk of an emergency department (ED) visit, readmission, or death after hospitalization for elective major vascular surgery. This is a population-based retrospective cohort study of patients who underwent elective major vascular surgery - carotid endarterectomy, EVAR, open AAA repair, bypass for lower extremity peripheral arterial disease - in Ontario, Canada, between 2004 and 2015. The outcomes of interest included quality metrics - ED visit, readmission, death - and cost to the Ministry of Health, within 30 days of discharge. Costs after discharge included those attributable to hospital readmission, ED visits, rehab, physician billing, outpatient nursing and allied health care, medications, interventions, and tests. Multivariable regression models characterized the association of pre-discharge characteristics with the above-mentioned postdischarge quality metrics and cost. A total of 30,752 patients were identified. Within 30 days of discharge, 2588 (8.4%) patients were readmitted to hospital and 13 patients died (0.04%). Another 4145 (13.5%) patients visited an ED without requiring admission. Across all patients, over half of 30-day postdischarge costs were attributable to outpatient care. Patients at an increased risk of an ED visit, readmission, or death within 30 days of discharge differed from those patients with relatively higher 30-day costs. Events occurring outside the hospital setting should be integral to the evaluation of quality of care and cost after hospitalization for major vascular surgery.

Energy-Based Metrics for Arthroscopic Skills Assessment.

PubMed

Poursartip, Behnaz; LeBel, Marie-Eve; McCracken, Laura C; Escoto, Abelardo; Patel, Rajni V; Naish, Michael D; Trejos, Ana Luisa

2017-08-05

Minimally invasive skills assessment methods are essential in developing efficient surgical simulators and implementing consistent skills evaluation. Although numerous methods have been investigated in the literature, there is still a need to further improve the accuracy of surgical skills assessment. Energy expenditure can be an indication of motor skills proficiency. The goals of this study are to develop objective metrics based on energy expenditure, normalize these metrics, and investigate classifying trainees using these metrics. To this end, different forms of energy consisting of mechanical energy and work were considered and their values were divided by the related value of an ideal performance to develop normalized metrics. These metrics were used as inputs for various machine learning algorithms including support vector machines (SVM) and neural networks (NNs) for classification. The accuracy of the combination of the normalized energy-based metrics with these classifiers was evaluated through a leave-one-subject-out cross-validation. The proposed method was validated using 26 subjects at two experience levels (novices and experts) in three arthroscopic tasks. The results showed that there are statistically significant differences between novices and experts for almost all of the normalized energy-based metrics. The accuracy of classification using SVM and NN methods was between 70% and 95% for the various tasks. The results show that the normalized energy-based metrics and their combination with SVM and NN classifiers are capable of providing accurate classification of trainees. The assessment method proposed in this study can enhance surgical training by providing appropriate feedback to trainees about their level of expertise and can be used in the evaluation of proficiency.

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.

Metrics for Radiologists in the Era of Value-based Health Care Delivery.

PubMed

Sarwar, Ammar; Boland, Giles; Monks, Annamarie; Kruskal, Jonathan B

2015-01-01

Accelerated by the Patient Protection and Affordable Care Act of 2010, health care delivery in the United States is poised to move from a model that rewards the volume of services provided to one that rewards the value provided by such services. Radiology department operations are currently managed by an array of metrics that assess various departmental missions, but many of these metrics do not measure value. Regulators and other stakeholders also influence what metrics are used to assess medical imaging. Metrics such as the Physician Quality Reporting System are increasingly being linked to financial penalties. In addition, metrics assessing radiology's contribution to cost or outcomes are currently lacking. In fact, radiology is widely viewed as a contributor to health care costs without an adequate understanding of its contribution to downstream cost savings or improvement in patient outcomes. The new value-based system of health care delivery and reimbursement will measure a provider's contribution to reducing costs and improving patient outcomes with the intention of making reimbursement commensurate with adherence to these metrics. The authors describe existing metrics and their application to the practice of radiology, discuss the so-called value equation, and suggest possible metrics that will be useful for demonstrating the value of radiologists' services to their patients. (©)RSNA, 2015.

Multivariate Analyses of Quality Metrics for Crystal Structures in the PDB Archive.

PubMed

Shao, Chenghua; Yang, Huanwang; Westbrook, John D; Young, Jasmine Y; Zardecki, Christine; Burley, Stephen K

2017-03-07

Following deployment of an augmented validation system by the Worldwide Protein Data Bank (wwPDB) partnership, the quality of crystal structures entering the PDB has improved. Of significance are improvements in quality measures now prominently displayed in the wwPDB validation report. Comparisons of PDB depositions made before and after introduction of the new reporting system show improvements in quality measures relating to pairwise atom-atom clashes, side-chain torsion angle rotamers, and local agreement between the atomic coordinate structure model and experimental electron density data. These improvements are largely independent of resolution limit and sample molecular weight. No significant improvement in the quality of associated ligands was observed. Principal component analysis revealed that structure quality could be summarized with three measures (Rfree, real-space R factor Z score, and a combined molecular geometry quality metric), which can in turn be reduced to a single overall quality metric readily interpretable by all PDB archive users. Copyright © 2017 Elsevier Ltd. All rights reserved.

Feasibility of and Rationale for the Collection of Orthopaedic Trauma Surgery Quality of Care Metrics.

PubMed

Miller, Anna N; Kozar, Rosemary; Wolinsky, Philip

2017-06-01

Reproducible metrics are needed to evaluate the delivery of orthopaedic trauma care, national care, norms, and outliers. The American College of Surgeons (ACS) is uniquely positioned to collect and evaluate the data needed to evaluate orthopaedic trauma care via the Committee on Trauma and the Trauma Quality Improvement Project. We evaluated the first quality metrics the ACS has collected for orthopaedic trauma surgery to determine whether these metrics can be appropriately collected with accuracy and completeness. The metrics include the time to administration of the first dose of antibiotics for open fractures, the time to surgical irrigation and débridement of open tibial fractures, and the percentage of patients who undergo stabilization of femoral fractures at trauma centers nationwide. These metrics were analyzed to evaluate for variances in the delivery of orthopaedic care across the country. The data showed wide variances for all metrics, and many centers had incomplete ability to collect the orthopaedic trauma care metrics. There was a large variability in the results of the metrics collected among different trauma center levels, as well as among centers of a particular level. The ACS has successfully begun tracking orthopaedic trauma care performance measures, which will help inform reevaluation of the goals and continued work on data collection and improvement of patient care. Future areas of research may link these performance measures with patient outcomes, such as long-term tracking, to assess nonunion and function. This information can provide insight into center performance and its effect on patient outcomes. The ACS was able to successfully collect and evaluate the data for three metrics used to assess the quality of orthopaedic trauma care. However, additional research is needed to determine whether these metrics are suitable for evaluating orthopaedic trauma care and cutoff values for each metric.

Systems Engineering Metrics: Organizational Complexity and Product Quality Modeling

NASA Technical Reports Server (NTRS)

Mog, Robert A.

1997-01-01

Innovative organizational complexity and product quality models applicable to performance metrics for NASA-MSFC's Systems Analysis and Integration Laboratory (SAIL) missions and objectives are presented. An intensive research effort focuses on the synergistic combination of stochastic process modeling, nodal and spatial decomposition techniques, organizational and computational complexity, systems science and metrics, chaos, and proprietary statistical tools for accelerated risk assessment. This is followed by the development of a preliminary model, which is uniquely applicable and robust for quantitative purposes. Exercise of the preliminary model using a generic system hierarchy and the AXAF-I architectural hierarchy is provided. The Kendall test for positive dependence provides an initial verification and validation of the model. Finally, the research and development of the innovation is revisited, prior to peer review. This research and development effort results in near-term, measurable SAIL organizational and product quality methodologies, enhanced organizational risk assessment and evolutionary modeling results, and 91 improved statistical quantification of SAIL productivity interests.

Environmental Quality and Aquatic Invertebrate Metrics Relationships at Patagonian Wetlands Subjected to Livestock Grazing Pressures.

PubMed

Epele, Luis Beltrán; Miserendino, María Laura

2015-01-01

Livestock grazing can compromise the biotic integrity and health of wetlands, especially in remotes areas like Patagonia, which provide habitat for several endemic terrestrial and aquatic species. Understanding the effects of these land use practices on invertebrate communities can help prevent the deterioration of wetlands and provide insights for restoration. In this contribution, we assessed the responses of 36 metrics based on the structural and functional attributes of invertebrates (130 taxa) at 30 Patagonian wetlands that were subject to different levels of livestock grazing intensity. These levels were categorized as low, medium and high based on eight features (livestock stock densities plus seven wetland measurements). Significant changes in environmental features were detected across the gradient of wetlands, mainly related to pH, conductivity, and nutrient values. Regardless of rainfall gradient, symptoms of eutrophication were remarkable at some highly disturbed sites. Seven invertebrate metrics consistently and accurately responded to livestock grazing on wetlands. All of them were negatively related to increased levels of grazing disturbance, with the number of insect families appearing as the most robust measure. A multivariate approach (RDA) revealed that invertebrate metrics were significantly affected by environmental variables related to water quality: in particular, pH, conductivity, dissolved oxygen, nutrient concentrations, and the richness and coverage of aquatic plants. Our results suggest that the seven aforementioned metrics could be used to assess ecological quality in the arid and semi-arid wetlands of Patagonia, helping to ensure the creation of protected areas and their associated ecological services.

Environmental Quality and Aquatic Invertebrate Metrics Relationships at Patagonian Wetlands Subjected to Livestock Grazing Pressures

PubMed Central

2015-01-01

Livestock grazing can compromise the biotic integrity and health of wetlands, especially in remotes areas like Patagonia, which provide habitat for several endemic terrestrial and aquatic species. Understanding the effects of these land use practices on invertebrate communities can help prevent the deterioration of wetlands and provide insights for restoration. In this contribution, we assessed the responses of 36 metrics based on the structural and functional attributes of invertebrates (130 taxa) at 30 Patagonian wetlands that were subject to different levels of livestock grazing intensity. These levels were categorized as low, medium and high based on eight features (livestock stock densities plus seven wetland measurements). Significant changes in environmental features were detected across the gradient of wetlands, mainly related to pH, conductivity, and nutrient values. Regardless of rainfall gradient, symptoms of eutrophication were remarkable at some highly disturbed sites. Seven invertebrate metrics consistently and accurately responded to livestock grazing on wetlands. All of them were negatively related to increased levels of grazing disturbance, with the number of insect families appearing as the most robust measure. A multivariate approach (RDA) revealed that invertebrate metrics were significantly affected by environmental variables related to water quality: in particular, pH, conductivity, dissolved oxygen, nutrient concentrations, and the richness and coverage of aquatic plants. Our results suggest that the seven aforementioned metrics could be used to assess ecological quality in the arid and semi-arid wetlands of Patagonia, helping to ensure the creation of protected areas and their associated ecological services. PMID:26448652

SU-E-T-776: Use of Quality Metrics for a New Hypo-Fractionated Pre-Surgical Mesothelioma Protocol

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

Richardson, S; Mehta, V

Purpose: The “SMART” (Surgery for Mesothelioma After Radiation Therapy) approach involves hypo-fractionated radiotherapy of the lung pleura to 25Gy over 5 days followed by surgical resection within 7. Early clinical results suggest that this approach is very promising, but also logistically challenging due to the multidisciplinary involvement. Due to the compressed schedule, high dose, and shortened planning time, the delivery of the planned doses were monitored for safety with quality metric software. Methods: Hypo-fractionated IMRT treatment plans were developed for all patients and exported to Quality Reports™ software. Plan quality metrics or PQMs™ were created to calculate an objective scoringmore » function for each plan. This allows for an objective assessment of the quality of the plan and a benchmark for plan improvement for subsequent patients. The priorities of various components were incorporated based on similar hypo-fractionated protocols such as lung SBRT treatments. Results: Five patients have been treated at our institution using this approach. The plans were developed, QA performed, and ready within 5 days of simulation. Plan Quality metrics utilized in scoring included doses to OAR and target coverage. All patients tolerated treatment well and proceeded to surgery as scheduled. Reported toxicity included grade 1 nausea (n=1), grade 1 esophagitis (n=1), grade 2 fatigue (n=3). One patient had recurrent fluid accumulation following surgery. No patients experienced any pulmonary toxicity prior to surgery. Conclusion: An accelerated course of pre-operative high dose radiation for mesothelioma is an innovative and promising new protocol. Without historical data, one must proceed cautiously and monitor the data carefully. The development of quality metrics and scoring functions for these treatments allows us to benchmark our plans and monitor improvement. If subsequent toxicities occur, these will be easy to investigate and incorporate into

Stability metrics for multi-source biomedical data based on simplicial projections from probability distribution distances.

PubMed

Sáez, Carlos; Robles, Montserrat; García-Gómez, Juan M

2017-02-01

Biomedical data may be composed of individuals generated from distinct, meaningful sources. Due to possible contextual biases in the processes that generate data, there may exist an undesirable and unexpected variability among the probability distribution functions (PDFs) of the source subsamples, which, when uncontrolled, may lead to inaccurate or unreproducible research results. Classical statistical methods may have difficulties to undercover such variabilities when dealing with multi-modal, multi-type, multi-variate data. This work proposes two metrics for the analysis of stability among multiple data sources, robust to the aforementioned conditions, and defined in the context of data quality assessment. Specifically, a global probabilistic deviation and a source probabilistic outlyingness metrics are proposed. The first provides a bounded degree of the global multi-source variability, designed as an estimator equivalent to the notion of normalized standard deviation of PDFs. The second provides a bounded degree of the dissimilarity of each source to a latent central distribution. The metrics are based on the projection of a simplex geometrical structure constructed from the Jensen-Shannon distances among the sources PDFs. The metrics have been evaluated and demonstrated their correct behaviour on a simulated benchmark and with real multi-source biomedical data using the UCI Heart Disease data set. The biomedical data quality assessment based on the proposed stability metrics may improve the efficiency and effectiveness of biomedical data exploitation and research.

Complexity metric based on fraction of penumbra dose - initial study

NASA Astrophysics Data System (ADS)

Bäck, A.; Nordström, F.; Gustafsson, M.; Götstedt, J.; Karlsson Hauer, A.

2017-05-01

Volumetric modulated arc therapy improve radiotherapy outcome for many patients compared to conventional three dimensional conformal radiotherapy but require a more extensive, most often measurement based, quality assurance. Multi leaf collimator (MLC) aperture-based complexity metrics have been suggested to be used to distinguish complex treatment plans unsuitable for treatment without time consuming measurements. This study introduce a spatially resolved complexity score that correlate to the fraction of penumbra dose and will give information on the spatial distribution and the clinical relevance of the calculated complexity. The complexity metric is described and an initial study on the correlation between the complexity score and the difference between measured and calculated dose for 30 MLC openings is presented. The result of an analysis of the complexity scores were found to correlate to differences between measurements and calculations with a Pearson’s r-value of 0.97.

Beyond metrics? Utilizing 'soft intelligence' for healthcare quality and safety.

PubMed

Martin, Graham P; McKee, Lorna; Dixon-Woods, Mary

2015-10-01

Formal metrics for monitoring the quality and safety of healthcare have a valuable role, but may not, by themselves, yield full insight into the range of fallibilities in organizations. 'Soft intelligence' is usefully understood as the processes and behaviours associated with seeking and interpreting soft data-of the kind that evade easy capture, straightforward classification and simple quantification-to produce forms of knowledge that can provide the basis for intervention. With the aim of examining current and potential practice in relation to soft intelligence, we conducted and analysed 107 in-depth qualitative interviews with senior leaders, including managers and clinicians, involved in healthcare quality and safety in the English National Health Service. We found that participants were in little doubt about the value of softer forms of data, especially for their role in revealing troubling issues that might be obscured by conventional metrics. Their struggles lay in how to access softer data and turn them into a useful form of knowing. Some of the dominant approaches they used risked replicating the limitations of hard, quantitative data. They relied on processes of aggregation and triangulation that prioritised reliability, or on instrumental use of soft data to animate the metrics. The unpredictable, untameable, spontaneous quality of soft data could be lost in efforts to systematize their collection and interpretation to render them more tractable. A more challenging but potentially rewarding approach involved processes and behaviours aimed at disrupting taken-for-granted assumptions about quality, safety, and organizational performance. This approach, which explicitly values the seeking out and the hearing of multiple voices, is consistent with conceptual frameworks of organizational sensemaking and dialogical understandings of knowledge. Using soft intelligence this way can be challenging and discomfiting, but may offer a critical defence against the

A condition metric for Eucalyptus woodland derived from expert evaluations.

PubMed

Sinclair, Steve J; Bruce, Matthew J; Griffioen, Peter; Dodd, Amanda; White, Matthew D

2018-02-01

The evaluation of ecosystem quality is important for land-management and land-use planning. Evaluation is unavoidably subjective, and robust metrics must be based on consensus and the structured use of observations. We devised a transparent and repeatable process for building and testing ecosystem metrics based on expert data. We gathered quantitative evaluation data on the quality of hypothetical grassy woodland sites from experts. We used these data to train a model (an ensemble of 30 bagged regression trees) capable of predicting the perceived quality of similar hypothetical woodlands based on a set of 13 site variables as inputs (e.g., cover of shrubs, richness of native forbs). These variables can be measured at any site and the model implemented in a spreadsheet as a metric of woodland quality. We also investigated the number of experts required to produce an opinion data set sufficient for the construction of a metric. The model produced evaluations similar to those provided by experts, as shown by assessing the model's quality scores of expert-evaluated test sites not used to train the model. We applied the metric to 13 woodland conservation reserves and asked managers of these sites to independently evaluate their quality. To assess metric performance, we compared the model's evaluation of site quality with the managers' evaluations through multidimensional scaling. The metric performed relatively well, plotting close to the center of the space defined by the evaluators. Given the method provides data-driven consensus and repeatability, which no single human evaluator can provide, we suggest it is a valuable tool for evaluating ecosystem quality in real-world contexts. We believe our approach is applicable to any ecosystem. © 2017 State of Victoria.

Metrics for the Evaluation the Utility of Air Quality Forecasting

NASA Astrophysics Data System (ADS)

Sumo, T. M.; Stockwell, W. R.

2013-12-01

Global warming is expected to lead to higher levels of air pollution and therefore the forecasting of both long-term and daily air quality is an important component for the assessment of the costs of climate change and its impact on human health. Some of the risks associated with poor air quality days (where the Air Pollution Index is greater than 100), include hospital visits and mortality. Accurate air quality forecasting has the potential to allow sensitive groups to take appropriate precautions. This research builds metrics for evaluating the utility of air quality forecasting in terms of its potential impacts. Our analysis of air quality models focuses on the Washington, DC/Baltimore, MD region over the summertime ozone seasons between 2010 and 2012. The metrics that are relevant to our analysis include: (1) The number of times that a high ozone or particulate matter (PM) episode is correctly forecasted, (2) the number of times that high ozone or PM episode is forecasted when it does not occur and (3) the number of times when the air quality forecast predicts a cleaner air episode when the air was observed to have high ozone or PM. Our evaluation of the performance of air quality forecasts include those forecasts of ozone and particulate matter and data available from the U.S. Environmental Protection Agency (EPA)'s AIRNOW. We also examined observational ozone and particulate matter data available from Clean Air Partners. Overall the forecast models perform well for our region and time interval.

MESUR: USAGE-BASED METRICS OF SCHOLARLY IMPACT

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

BOLLEN, JOHAN; RODRIGUEZ, MARKO A.; VAN DE SOMPEL, HERBERT

2007-01-30

The evaluation of scholarly communication items is now largely a matter of expert opinion or metrics derived from citation data. Both approaches can fail to take into account the myriad of factors that shape scholarly impact. Usage data has emerged as a promising complement to existing methods o fassessment but the formal groundwork to reliably and validly apply usage-based metrics of schlolarly impact is lacking. The Andrew W. Mellon Foundation funded MESUR project constitutes a systematic effort to define, validate and cross-validate a range of usage-based metrics of schlolarly impact by creating a semantic model of the scholarly communication process.more » The constructed model will serve as the basis of a creating a large-scale semantic network that seamlessly relates citation, bibliographic and usage data from a variety of sources. A subsequent program that uses the established semantic network as a reference data set will determine the characteristics and semantics of a variety of usage-based metrics of schlolarly impact. This paper outlines the architecture and methodology adopted by the MESUR project and its future direction.« less

The Nutrient Balance Concept: A New Quality Metric for Composite Meals and Diets

PubMed Central

Fern, Edward B; Watzke, Heribert; Barclay, Denis V.; Roulin, Anne; Drewnowski, Adam

2015-01-01

Background Combinations of foods that provide suitable levels of nutrients and energy are required for optimum health. Currently, however, it is difficult to define numerically what are ‘suitable levels’. Objective To develop new metrics based on energy considerations—the Nutrient Balance Concept (NBC)—for assessing overall nutrition quality when combining foods and meals. Method The NBC was developed using the USDA Food Composition Database (Release 27) and illustrated with their MyPlate 7-day sample menus for a 2000 calorie food pattern. The NBC concept is centered on three specific metrics for a given food, meal or diet—a Qualifying Index (QI), a Disqualifying Index (DI) and a Nutrient Balance (NB). The QI and DI were determined, respectively, from the content of 27 essential nutrients and 6 nutrients associated with negative health outcomes. The third metric, the Nutrient Balance (NB), was derived from the Qualifying Index (QI) and provided key information on the relative content of qualifying nutrients in the food. Because the Qualifying and Disqualifying Indices (QI and DI) were standardized to energy content, both become constants for a given food/meal/diet and a particular consumer age group, making it possible to develop algorithms for predicting nutrition quality when combining different foods. Results Combining different foods into composite meals and daily diets led to improved nutrition quality as seen by QI values closer to unity (indicating nutrient density was better equilibrated with energy density), DI values below 1.0 (denoting an acceptable level of consumption of disqualifying nutrients) and increased NB values (signifying complementarity of foods and better provision of qualifying nutrients). Conclusion The Nutrient Balance Concept (NBC) represents a new approach to nutrient profiling and the first step in the progression from the nutrient evaluation of individual foods to that of multiple foods in the context of meals and total

Using Qualitative and Quantitative Methods to Choose a Habitat Quality Metric for Air Pollution Policy Evaluation

PubMed Central

Ford, Adriana E. S.; Smart, Simon M.; Henrys, Peter A.; Ashmore, Mike R.

2016-01-01

Atmospheric nitrogen (N) deposition has had detrimental effects on species composition in a range of sensitive habitats, although N deposition can also increase agricultural productivity and carbon storage, and favours a few species considered of importance for conservation. Conservation targets are multiple, and increasingly incorporate services derived from nature as well as concepts of intrinsic value. Priorities vary. How then should changes in a set of species caused by drivers such as N deposition be assessed? We used a novel combination of qualitative semi-structured interviews and quantitative ranking to elucidate the views of conservation professionals specialising in grasslands, heathlands and mires. Although conservation management goals are varied, terrestrial habitat quality is mainly assessed by these specialists on the basis of plant species, since these are readily observed. The presence and abundance of plant species that are scarce, or have important functional roles, emerged as important criteria for judging overall habitat quality. However, species defined as ‘positive indicator-species’ (not particularly scarce, but distinctive for the habitat) were considered particularly important. Scarce species are by definition not always found, and the presence of functionally important species is not a sufficient indicator of site quality. Habitat quality as assessed by the key informants was rank-correlated with the number of positive indicator-species present at a site for seven of the nine habitat classes assessed. Other metrics such as species-richness or a metric of scarcity were inconsistently or not correlated with the specialists’ assessments. We recommend that metrics of habitat quality used to assess N pollution impacts are based on the occurrence of, or habitat-suitability for, distinctive species. Metrics of this type are likely to be widely applicable for assessing habitat change in response to different drivers. The novel combined

Getting started on metrics - Jet Propulsion Laboratory productivity and quality

NASA Technical Reports Server (NTRS)

Bush, M. W.

1990-01-01

A review is presented to describe the effort and difficulties of reconstructing fifteen years of JPL software history. In 1987 the collection and analysis of project data were started with the objective of creating laboratory-wide measures of quality and productivity for software development. As a result of this two-year Software Product Assurance metrics study, a rough measurement foundation for software productivity and software quality, and an order-of-magnitude quantitative baseline for software systems and subsystems are now available.

Sigma metrics as a tool for evaluating the performance of internal quality control in a clinical chemistry laboratory

PubMed Central

Kumar, B. Vinodh; Mohan, Thuthi

2018-01-01

OBJECTIVE: Six Sigma is one of the most popular quality management system tools employed for process improvement. The Six Sigma methods are usually applied when the outcome of the process can be measured. This study was done to assess the performance of individual biochemical parameters on a Sigma Scale by calculating the sigma metrics for individual parameters and to follow the Westgard guidelines for appropriate Westgard rules and levels of internal quality control (IQC) that needs to be processed to improve target analyte performance based on the sigma metrics. MATERIALS AND METHODS: This is a retrospective study, and data required for the study were extracted between July 2015 and June 2016 from a Secondary Care Government Hospital, Chennai. The data obtained for the study are IQC - coefficient of variation percentage and External Quality Assurance Scheme (EQAS) - Bias% for 16 biochemical parameters. RESULTS: For the level 1 IQC, four analytes (alkaline phosphatase, magnesium, triglyceride, and high-density lipoprotein-cholesterol) showed an ideal performance of ≥6 sigma level, five analytes (urea, total bilirubin, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level and for level 2 IQCs, same four analytes of level 1 showed a performance of ≥6 sigma level, and four analytes (urea, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level. For all analytes <6 sigma level, the quality goal index (QGI) was <0.8 indicating the area requiring improvement to be imprecision except cholesterol whose QGI >1.2 indicated inaccuracy. CONCLUSION: This study shows that sigma metrics is a good quality tool to assess the analytical performance of a clinical chemistry laboratory. Thus, sigma metric analysis provides a benchmark for the laboratory to design a protocol for IQC, address poor assay performance, and assess the efficiency of existing laboratory processes. PMID:29692587

Sigma metrics as a tool for evaluating the performance of internal quality control in a clinical chemistry laboratory.

PubMed

Kumar, B Vinodh; Mohan, Thuthi

2018-01-01

Six Sigma is one of the most popular quality management system tools employed for process improvement. The Six Sigma methods are usually applied when the outcome of the process can be measured. This study was done to assess the performance of individual biochemical parameters on a Sigma Scale by calculating the sigma metrics for individual parameters and to follow the Westgard guidelines for appropriate Westgard rules and levels of internal quality control (IQC) that needs to be processed to improve target analyte performance based on the sigma metrics. This is a retrospective study, and data required for the study were extracted between July 2015 and June 2016 from a Secondary Care Government Hospital, Chennai. The data obtained for the study are IQC - coefficient of variation percentage and External Quality Assurance Scheme (EQAS) - Bias% for 16 biochemical parameters. For the level 1 IQC, four analytes (alkaline phosphatase, magnesium, triglyceride, and high-density lipoprotein-cholesterol) showed an ideal performance of ≥6 sigma level, five analytes (urea, total bilirubin, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level and for level 2 IQCs, same four analytes of level 1 showed a performance of ≥6 sigma level, and four analytes (urea, albumin, cholesterol, and potassium) showed an average performance of <3 sigma level. For all analytes <6 sigma level, the quality goal index (QGI) was <0.8 indicating the area requiring improvement to be imprecision except cholesterol whose QGI >1.2 indicated inaccuracy. This study shows that sigma metrics is a good quality tool to assess the analytical performance of a clinical chemistry laboratory. Thus, sigma metric analysis provides a benchmark for the laboratory to design a protocol for IQC, address poor assay performance, and assess the efficiency of existing laboratory processes.

Beyond metrics? Utilizing ‘soft intelligence’ for healthcare quality and safety

PubMed Central

Martin, Graham P.; McKee, Lorna; Dixon-Woods, Mary

2015-01-01

Formal metrics for monitoring the quality and safety of healthcare have a valuable role, but may not, by themselves, yield full insight into the range of fallibilities in organizations. ‘Soft intelligence’ is usefully understood as the processes and behaviours associated with seeking and interpreting soft data—of the kind that evade easy capture, straightforward classification and simple quantification—to produce forms of knowledge that can provide the basis for intervention. With the aim of examining current and potential practice in relation to soft intelligence, we conducted and analysed 107 in-depth qualitative interviews with senior leaders, including managers and clinicians, involved in healthcare quality and safety in the English National Health Service. We found that participants were in little doubt about the value of softer forms of data, especially for their role in revealing troubling issues that might be obscured by conventional metrics. Their struggles lay in how to access softer data and turn them into a useful form of knowing. Some of the dominant approaches they used risked replicating the limitations of hard, quantitative data. They relied on processes of aggregation and triangulation that prioritised reliability, or on instrumental use of soft data to animate the metrics. The unpredictable, untameable, spontaneous quality of soft data could be lost in efforts to systematize their collection and interpretation to render them more tractable. A more challenging but potentially rewarding approach involved processes and behaviours aimed at disrupting taken-for-granted assumptions about quality, safety, and organizational performance. This approach, which explicitly values the seeking out and the hearing of multiple voices, is consistent with conceptual frameworks of organizational sensemaking and dialogical understandings of knowledge. Using soft intelligence this way can be challenging and discomfiting, but may offer a critical defence

Methods of Measurement the Quality Metrics in a Printing System

NASA Astrophysics Data System (ADS)

Varepo, L. G.; Brazhnikov, A. Yu; Nagornova, I. V.; Novoselskaya, O. A.

2018-04-01

One of the main criteria for choosing ink as a component of printing system is scumming ability of the ink. The realization of algorithm for estimating the quality metrics in a printing system is shown. The histograms of ink rate of various printing systems are presented. A quantitative estimation of stability of offset inks emulsifiability is given.

Evaluating hydrological model performance using information theory-based metrics

USDA-ARS?s Scientific Manuscript database

The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic m...

Effect of quality metric monitoring and colonoscopy performance.

PubMed

Razzak, Anthony; Smith, Dineen; Zahid, Maliha; Papachristou, Georgios; Khalid, Asif

2016-10-01

Background and aims: Adenoma detection rate (ADR) and cecal withdrawal time (CWT) have been identified as measures of colonoscopy quality. This study evaluates the impact of monitoring these measures on provider performance. Methods: Six blinded gastroenterologists practicing at a Veterans Affairs Medical Center were prospectively monitored over 9 months. Data for screening, adenoma surveillance, and fecal occult blood test positive (FOBT +) indicated colonoscopies were obtained, including exam preparation quality, cecal intubation rate, CWT, ADR, adenomas per colonoscopy (APC), and adverse events. Metrics were continuously monitored after a period of informed CWT monitoring and informed CWT + ADR monitoring. The primary outcome was impact on ADR and APC. Results: A total of 1671 colonoscopies were performed during the study period with 540 before informed monitoring, 528 during informed CWT monitoring, and 603 during informed CWT + ADR monitoring. No statistically significant impact on ADR was noted across each study phase. Multivariate regression revealed a trend towards fewer adenomas removed during the CWT monitoring phase (OR = 0.79; 95 %CI 0.62 - 1.02, P  = 0.065) and a trend towards more adenomas removed during the CWT + ADR monitoring phase when compared to baseline (OR = 1.26; 95 %CI 0.99 - 1.61, P  = 0.062). Indication for examination and provider were significant predictors for higher APC. Provider-specific data demonstrated a direct relationship between high ADR performers and increased CWT. Conclusions: Monitoring quality metrics did not significantly alter colonoscopy performance across a small heterogeneous group of providers. Non-significant trends towards higher APC were noted with CWT + ADR monitoring. Providers with a longer CWT had a higher ADR. Further studies are needed to determine the impact of monitoring on colonoscopy performance.

Macroinvertebrate and diatom metrics as indicators of water-quality conditions in connected depression wetlands in the Mississippi Alluvial Plain

USGS Publications Warehouse

Justus, Billy; Burge, David; Cobb, Jennifer; Marsico, Travis; Bouldin, Jennifer

2016-01-01

Methods for assessing wetland conditions must be established so wetlands can be monitored and ecological services can be protected. We evaluated biological indices compiled from macroinvertebrate and diatom metrics developed primarily for streams to assess their ability to indicate water quality in connected depression wetlands. We collected water-quality and biological samples at 24 connected depressions dominated by water tupelo (Nyssa aquatica) or bald cypress (Taxodium distichum) (water depths = 0.5–1.0 m). Water quality of the least-disturbed connected depressions was characteristic of swamps in the southeastern USA, which tend to have low specific conductance, nutrient concentrations, and pH. We compared 162 macroinvertebrate metrics and 123 diatom metrics with a water-quality disturbance gradient. For most metrics, we evaluated richness, % richness, abundance, and % relative abundance values. Three of the 4 macroinvertebrate metrics that were most beneficial for identifying disturbance in connected depressions decreased along the disturbance gradient even though they normally increase relative to stream disturbance. The negative relationship to disturbance of some taxa (e.g., dipterans, mollusks, and crustaceans) that are considered tolerant in streams suggests that the tolerance scale for some macroinvertebrates can differ markedly between streams and wetlands. Three of the 4 metrics chosen for the diatom index reflected published tolerances or fit the usual perception of metric response to disturbance. Both biological indices may be useful in connected depressions elsewhere in the Mississippi Alluvial Plain Ecoregion and could have application in other wetland types. Given the paradoxical relationship of some macroinvertebrate metrics to dissolved O2 (DO), we suggest that the diatom metrics may be easier to interpret and defend for wetlands with low DO concentrations in least-disturbed conditions.

A GPS Phase-Locked Loop Performance Metric Based on the Phase Discriminator Output

PubMed Central

Stevanovic, Stefan; Pervan, Boris

2018-01-01

We propose a novel GPS phase-lock loop (PLL) performance metric based on the standard deviation of tracking error (defined as the discriminator’s estimate of the true phase error), and explain its advantages over the popular phase jitter metric using theory, numerical simulation, and experimental results. We derive an augmented GPS phase-lock loop (PLL) linear model, which includes the effect of coherent averaging, to be used in conjunction with this proposed metric. The augmented linear model allows more accurate calculation of tracking error standard deviation in the presence of additive white Gaussian noise (AWGN) as compared to traditional linear models. The standard deviation of tracking error, with a threshold corresponding to half of the arctangent discriminator pull-in region, is shown to be a more reliable/robust measure of PLL performance under interference conditions than the phase jitter metric. In addition, the augmented linear model is shown to be valid up until this threshold, which facilitates efficient performance prediction, so that time-consuming direct simulations and costly experimental testing can be reserved for PLL designs that are much more likely to be successful. The effect of varying receiver reference oscillator quality on the tracking error metric is also considered. PMID:29351250

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream.

PubMed

Hong, Eun-Mi; Shelton, Daniel; Pachepsky, Yakov A; Nam, Won-Ho; Coppock, Cary; Muirhead, Richard

2017-02-01

Knowledge of the microbial quality of irrigation waters is extremely limited. For this reason, the US FDA has promulgated the Produce Rule, mandating the testing of irrigation water sources for many farms. The rule requires the collection and analysis of at least 20 water samples over two to four years to adequately evaluate the quality of water intended for produce irrigation. The objective of this work was to evaluate the effect of interannual weather variability on surface water microbial quality. We used the Soil and Water Assessment Tool model to simulate E. coli concentrations in the Little Cove Creek; this is a perennial creek located in an agricultural watershed in south-eastern Pennsylvania. The model performance was evaluated using the US FDA regulatory microbial water quality metrics of geometric mean (GM) and the statistical threshold value (STV). Using the 90-year time series of weather observations, we simulated and randomly sampled the time series of E. coli concentrations. We found that weather conditions of a specific year may strongly affect the evaluation of microbial quality and that the long-term assessment of microbial water quality may be quite different from the evaluation based on short-term observations. The variations in microbial concentrations and water quality metrics were affected by location, wetness of the hydrological years, and seasonality, with 15.7-70.1% of samples exceeding the regulatory threshold. The results of this work demonstrate the value of using modeling to design and evaluate monitoring protocols to assess the microbial quality of water used for produce irrigation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Questionable validity of the catheter-associated urinary tract infection metric used for value-based purchasing.

PubMed

Calderon, Lindsay E; Kavanagh, Kevin T; Rice, Mara K

2015-10-01

Catheter-associated urinary tract infections (CAUTIs) occur in 290,000 US hospital patients annually, with an estimated cost of $290 million. Two different measurement systems are being used to track the US health care system's performance in lowering the rate of CAUTIs. Since 2010, the Agency for Healthcare Research and Quality (AHRQ) metric has shown a 28.2% decrease in CAUTI, whereas the Centers for Disease Control and Prevention metric has shown a 3%-6% increase in CAUTI since 2009. Differences in data acquisition and the definition of the denominator may explain this discrepancy. The AHRQ metric analyzes chart-audited data and reflects both catheter use and care. The Centers for Disease Control and Prevention metric analyzes self-reported data and primarily reflects catheter care. Because analysis of the AHRQ metric showed a progressive change in performance over time and the scientific literature supports the importance of catheter use in the prevention of CAUTI, it is suggested that risk-adjusted catheter-use data be incorporated into metrics that are used for determining facility performance and for value-based purchasing initiatives. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Quality evaluation of extracted ion chromatograms and chromatographic peaks in liquid chromatography/mass spectrometry-based metabolomics data.

PubMed

Zhang, Wenchao; Zhao, Patrick X

2014-01-01

Extracted ion chromatogram (EIC) extraction and chromatographic peak detection are two important processing procedures in liquid chromatography/mass spectrometry (LC/MS)-based metabolomics data analysis. Most commonly, the LC/MS technique employs electrospray ionization as the ionization method. The EICs from LC/MS data are often noisy and contain high background signals. Furthermore, the chromatographic peak quality varies with respect to its location in the chromatogram and most peaks have zigzag shapes. Therefore, there is a critical need to develop effective metrics for quality evaluation of EICs and chromatographic peaks in LC/MS based metabolomics data analysis. We investigated a comprehensive set of potential quality evaluation metrics for extracted EICs and detected chromatographic peaks. Specifically, for EIC quality evaluation, we analyzed the mass chromatographic quality index (MCQ index) and propose a novel quality evaluation metric, the EIC-related global zigzag index, which is based on an EIC's first order derivatives. For chromatographic peak quality evaluation, we analyzed and compared six metrics: sharpness, Gaussian similarity, signal-to-noise ratio, peak significance level, triangle peak area similarity ratio and the local peak-related local zigzag index. Although the MCQ index is suited for selecting and aligning analyte components, it cannot fairly evaluate EICs with high background signals or those containing only a single peak. Our proposed EIC related global zigzag index is robust enough to evaluate EIC qualities in both scenarios. Of the six peak quality evaluation metrics, the sharpness, peak significance level, and zigzag index outperform the others due to the zigzag nature of LC/MS chromatographic peaks. Furthermore, using several peak quality metrics in combination is more efficient than individual metrics in peak quality evaluation.

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

Quality evaluation of extracted ion chromatograms and chromatographic peaks in liquid chromatography/mass spectrometry-based metabolomics data

PubMed Central

2014-01-01

Background Extracted ion chromatogram (EIC) extraction and chromatographic peak detection are two important processing procedures in liquid chromatography/mass spectrometry (LC/MS)-based metabolomics data analysis. Most commonly, the LC/MS technique employs electrospray ionization as the ionization method. The EICs from LC/MS data are often noisy and contain high background signals. Furthermore, the chromatographic peak quality varies with respect to its location in the chromatogram and most peaks have zigzag shapes. Therefore, there is a critical need to develop effective metrics for quality evaluation of EICs and chromatographic peaks in LC/MS based metabolomics data analysis. Results We investigated a comprehensive set of potential quality evaluation metrics for extracted EICs and detected chromatographic peaks. Specifically, for EIC quality evaluation, we analyzed the mass chromatographic quality index (MCQ index) and propose a novel quality evaluation metric, the EIC-related global zigzag index, which is based on an EIC's first order derivatives. For chromatographic peak quality evaluation, we analyzed and compared six metrics: sharpness, Gaussian similarity, signal-to-noise ratio, peak significance level, triangle peak area similarity ratio and the local peak-related local zigzag index. Conclusions Although the MCQ index is suited for selecting and aligning analyte components, it cannot fairly evaluate EICs with high background signals or those containing only a single peak. Our proposed EIC related global zigzag index is robust enough to evaluate EIC qualities in both scenarios. Of the six peak quality evaluation metrics, the sharpness, peak significance level, and zigzag index outperform the others due to the zigzag nature of LC/MS chromatographic peaks. Furthermore, using several peak quality metrics in combination is more efficient than individual metrics in peak quality evaluation. PMID:25350128

Ranking streamflow model performance based on Information theory metrics

NASA Astrophysics Data System (ADS)

Martinez, Gonzalo; Pachepsky, Yakov; Pan, Feng; Wagener, Thorsten; Nicholson, Thomas

2016-04-01

The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic model evaluation and selection. We simulated 10-year streamflow time series in five watersheds located in Texas, North Carolina, Mississippi, and West Virginia. Eight model of different complexity were applied. The information-theory based metrics were obtained after representing the time series as strings of symbols where different symbols corresponded to different quantiles of the probability distribution of streamflow. The symbol alphabet was used. Three metrics were computed for those strings - mean information gain that measures the randomness of the signal, effective measure complexity that characterizes predictability and fluctuation complexity that characterizes the presence of a pattern in the signal. The observed streamflow time series has smaller information content and larger complexity metrics than the precipitation time series. Watersheds served as information filters and and streamflow time series were less random and more complex than the ones of precipitation. This is reflected the fact that the watershed acts as the information filter in the hydrologic conversion process from precipitation to streamflow. The Nash Sutcliffe efficiency metric increased as the complexity of models increased, but in many cases several model had this efficiency values not statistically significant from each other. In such cases, ranking models by the closeness of the information-theory based parameters in simulated and measured streamflow time series can provide an additional criterion for the evaluation of hydrologic model performance.

Using Geometry-Based Metrics as Part of Fitness-for-Purpose Evaluations of 3D City Models

NASA Astrophysics Data System (ADS)

Wong, K.; Ellul, C.

2016-10-01

Three-dimensional geospatial information is being increasingly used in a range of tasks beyond visualisation. 3D datasets, however, are often being produced without exact specifications and at mixed levels of geometric complexity. This leads to variations within the models' geometric and semantic complexity as well as the degree of deviation from the corresponding real world objects. Existing descriptors and measures of 3D data such as CityGML's level of detail are perhaps only partially sufficient in communicating data quality and fitness-for-purpose. This study investigates whether alternative, automated, geometry-based metrics describing the variation of complexity within 3D datasets could provide additional relevant information as part of a process of fitness-for-purpose evaluation. The metrics include: mean vertex/edge/face counts per building; vertex/face ratio; minimum 2D footprint area and; minimum feature length. Each metric was tested on six 3D city models from international locations. The results show that geometry-based metrics can provide additional information on 3D city models as part of fitness-for-purpose evaluations. The metrics, while they cannot be used in isolation, may provide a complement to enhance existing data descriptors if backed up with local knowledge, where possible.

Objective evaluation of interior noise booming in a passenger car based on sound metrics and artificial neural networks.

PubMed

Lee, Hyun-Ho; Lee, Sang-Kwon

2009-09-01

Booming sound is one of the important sounds in a passenger car. The aim of the paper is to develop the objective evaluation method of interior booming sound. The development method is based on the sound metrics and ANN (artificial neural network). The developed method is called the booming index. Previous work maintained that booming sound quality is related to loudness and sharpness--the sound metrics used in psychoacoustics--and that the booming index is developed by using the loudness and sharpness for a signal within whole frequency between 20 Hz and 20 kHz. In the present paper, the booming sound quality was found to be effectively related to the loudness at frequencies below 200 Hz; thus the booming index is updated by using the loudness of the signal filtered by the low pass filter at frequency under 200 Hz. The relationship between the booming index and sound metric is identified by an ANN. The updated booming index has been successfully applied to the objective evaluation of the booming sound quality of mass-produced passenger cars.

Development and evaluation of aperture-based complexity metrics using film and EPID measurements of static MLC openings

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

Götstedt, Julia; Karlsson Hauer, Anna; Bäck, Anna, E-mail: anna.back@vgregion.se

Purpose: Complexity metrics have been suggested as a complement to measurement-based quality assurance for intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT). However, these metrics have not yet been sufficiently validated. This study develops and evaluates new aperture-based complexity metrics in the context of static multileaf collimator (MLC) openings and compares them to previously published metrics. Methods: This study develops the converted aperture metric and the edge area metric. The converted aperture metric is based on small and irregular parts within the MLC opening that are quantified as measured distances between MLC leaves. The edge area metricmore » is based on the relative size of the region around the edges defined by the MLC. Another metric suggested in this study is the circumference/area ratio. Earlier defined aperture-based complexity metrics—the modulation complexity score, the edge metric, the ratio monitor units (MU)/Gy, the aperture area, and the aperture irregularity—are compared to the newly proposed metrics. A set of small and irregular static MLC openings are created which simulate individual IMRT/VMAT control points of various complexities. These are measured with both an amorphous silicon electronic portal imaging device and EBT3 film. The differences between calculated and measured dose distributions are evaluated using a pixel-by-pixel comparison with two global dose difference criteria of 3% and 5%. The extent of the dose differences, expressed in terms of pass rate, is used as a measure of the complexity of the MLC openings and used for the evaluation of the metrics compared in this study. The different complexity scores are calculated for each created static MLC opening. The correlation between the calculated complexity scores and the extent of the dose differences (pass rate) are analyzed in scatter plots and using Pearson’s r-values. Results: The complexity scores calculated by the

Evaluation techniques and metrics for assessment of pan+MSI fusion (pansharpening)

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

2015-05-01

Fusion of broadband panchromatic data with narrow band multispectral data - pansharpening - is a common and often studied problem in remote sensing. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. This study examines the output products of 4 commercial implementations with regard to their relative strengths and weaknesses for a set of defined image characteristics and analyst use-cases. Image characteristics used are spatial detail, spatial quality, spectral integrity, and composite color quality (hue and saturation), and analyst use-cases included a variety of object detection and identification tasks. The imagery comes courtesy of the RIT SHARE 2012 collect. Two approaches are used to evaluate the pansharpening methods, analyst evaluation or qualitative measure and image quality metrics or quantitative measures. Visual analyst evaluation results are compared with metric results to determine which metrics best measure the defined image characteristics and product use-cases and to support future rigorous characterization the metrics' correlation with the analyst results. Because pansharpening represents a trade between adding spatial information from the panchromatic image, and retaining spectral information from the MSI channels, the metrics examined are grouped into spatial improvement metrics and spectral preservation metrics. A single metric to quantify the quality of a pansharpening method would necessarily be a combination of weighted spatial and spectral metrics based on the importance of various spatial and spectral characteristics for the primary task of interest. Appropriate metrics and weights for such a combined metric are proposed here, based on the conducted analyst evaluation. Additionally, during this work, a metric was developed specifically focused on assessment of spatial structure improvement relative to a reference image and

Natural Language Processing As an Alternative to Manual Reporting of Colonoscopy Quality Metrics

PubMed Central

RAJU, GOTTUMUKKALA S.; LUM, PHILLIP J.; SLACK, REBECCA; THIRUMURTHI, SELVI; LYNCH, PATRICK M.; MILLER, ETHAN; WESTON, BRIAN R.; DAVILA, MARTA L.; BHUTANI, MANOOP S.; SHAFI, MEHNAZ A.; BRESALIER, ROBERT S.; DEKOVICH, ALEXANDER A.; LEE, JEFFREY H.; GUHA, SUSHOVAN; PANDE, MALA; BLECHACZ, BORIS; RASHID, ASIF; ROUTBORT, MARK; SHUTTLESWORTH, GLADIS; MISHRA, LOPA; STROEHLEIN, JOHN R.; ROSS, WILLIAM A.

2015-01-01

BACKGROUND & AIMS The adenoma detection rate (ADR) is a quality metric tied to interval colon cancer occurrence. However, manual extraction of data to calculate and track the ADR in clinical practice is labor-intensive. To overcome this difficulty, we developed a natural language processing (NLP) method to identify patients, who underwent their first screening colonoscopy, identify adenomas and sessile serrated adenomas (SSA). We compared the NLP generated results with that of manual data extraction to test the accuracy of NLP, and report on colonoscopy quality metrics using NLP. METHODS Identification of screening colonoscopies using NLP was compared with that using the manual method for 12,748 patients who underwent colonoscopies from July 2010 to February 2013. Also, identification of adenomas and SSAs using NLP was compared with that using the manual method with 2259 matched patient records. Colonoscopy ADRs using these methods were generated for each physician. RESULTS NLP correctly identified 91.3% of the screening examinations, whereas the manual method identified 87.8% of them. Both the manual method and NLP correctly identified examinations of patients with adenomas and SSAs in the matched records almost perfectly. Both NLP and manual method produce comparable values for ADR for each endoscopist as well as the group as a whole. CONCLUSIONS NLP can correctly identify screening colonoscopies, accurately identify adenomas and SSAs in a pathology database, and provide real-time quality metrics for colonoscopy. PMID:25910665

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.

Impact of artifact removal on ChIP quality metrics in ChIP-seq and ChIP-exo data

PubMed Central

Carroll, Thomas S.; Liang, Ziwei; Salama, Rafik; Stark, Rory; de Santiago, Ines

2014-01-01

With the advent of ChIP-seq multiplexing technologies and the subsequent increase in ChIP-seq throughput, the development of working standards for the quality assessment of ChIP-seq studies has received significant attention. The ENCODE consortium's large scale analysis of transcription factor binding and epigenetic marks as well as concordant work on ChIP-seq by other laboratories has established a new generation of ChIP-seq quality control measures. The use of these metrics alongside common processing steps has however not been evaluated. In this study, we investigate the effects of blacklisting and removal of duplicated reads on established metrics of ChIP-seq quality and show that the interpretation of these metrics is highly dependent on the ChIP-seq preprocessing steps applied. Further to this we perform the first investigation of the use of these metrics for ChIP-exo data and make recommendations for the adaptation of the NSC statistic to allow for the assessment of ChIP-exo efficiency. PMID:24782889

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.

On the performance of metrics to predict quality in point cloud representations

NASA Astrophysics Data System (ADS)

Alexiou, Evangelos; Ebrahimi, Touradj

2017-09-01

Point clouds are a promising alternative for immersive representation of visual contents. Recently, an increased interest has been observed in the acquisition, processing and rendering of this modality. Although subjective and objective evaluations are critical in order to assess the visual quality of media content, they still remain open problems for point cloud representation. In this paper we focus our efforts on subjective quality assessment of point cloud geometry, subject to typical types of impairments such as noise corruption and compression-like distortions. In particular, we propose a subjective methodology that is closer to real-life scenarios of point cloud visualization. The performance of the state-of-the-art objective metrics is assessed by considering the subjective scores as the ground truth. Moreover, we investigate the impact of adopting different test methodologies by comparing them. Advantages and drawbacks of every approach are reported, based on statistical analysis. The results and conclusions of this work provide useful insights that could be considered in future experimentation.

Quality measurement for rhinosinusitis: a review from the Quality Improvement Committee of the American Rhinologic Society.

PubMed

Rudmik, Luke; Mattos, Jose; Schneider, John; Manes, Peter R; Stokken, Janalee K; Lee, Jivianne; Higgins, Thomas S; Schlosser, Rodney J; Reh, Douglas D; Setzen, Michael; Soler, Zachary M

2017-09-01

Measuring quality outcomes is an important prerequisite to improve quality of care. Rhinosinusitis represents a high value target to improve quality of care because it has a high prevalence of disease, large economic burden, and large practice variation. In this study we review the current state of quality measurement for management of both acute (ARS) and chronic rhinosinusitis (CRS). The major national quality metric repositories and clearinghouses were queried. Additional searches included the American Academy of Otolaryngology-Head and Neck Surgery database, PubMed, and Google to attempt to capture any additional quality metrics. Seven quality metrics for ARS and 4 quality metrics for CRS were identified. ARS metrics focused on appropriateness of diagnosis (n = 1), antibiotic prescribing (n = 4), and radiologic imaging (n = 2). CRS quality metrics focused on appropriateness of diagnosis (n = 1), radiologic imaging (n = 1), and measurement of patient quality of life (n = 2). The Physician Quality Reporting System (PQRS) currently tracks 3 ARS quality metrics and 1 CRS quality metric. There are no outcome-based rhinosinusitis quality metrics and no metrics that assess domains of safety, patient-centeredness, and timeliness of care. The current status of quality measurement for rhinosinusitis has focused primarily on the quality domain of efficiency and process measures for ARS. More work is needed to develop, validate, and track outcome-based quality metrics along with CRS-specific metrics. Although there has been excellent work done to improve quality measurement for rhinosinusitis, there remain major gaps and challenges that need to be considered during the development of future metrics. © 2017 ARS-AAOA, LLC.

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.

Workshop summary: 'Integrating air quality and climate mitigation - is there a need for new metrics to support decision making?'

NASA Astrophysics Data System (ADS)

von Schneidemesser, E.; Schmale, J.; Van Aardenne, J.

2013-12-01

Air pollution and climate change are often treated at national and international level as separate problems under different regulatory or thematic frameworks and different policy departments. With air pollution and climate change being strongly linked with regard to their causes, effects and mitigation options, the integration of policies that steer air pollutant and greenhouse gas emission reductions might result in cost-efficient, more effective and thus more sustainable tackling of the two problems. To support informed decision making and to work towards an integrated air quality and climate change mitigation policy requires the identification, quantification and communication of present-day and potential future co-benefits and trade-offs. The identification of co-benefits and trade-offs requires the application of appropriate metrics that are well rooted in science, easy to understand and reflect the needs of policy, industry and the public for informed decision making. For the purpose of this workshop, metrics were loosely defined as a quantified measure of effect or impact used to inform decision-making and to evaluate mitigation measures. The workshop held on October 9 and 10 and co-organized between the European Environment Agency and the Institute for Advanced Sustainability Studies brought together representatives from science, policy, NGOs, and industry to discuss whether current available metrics are 'fit for purpose' or whether there is a need to develop alternative metrics or reassess the way current metrics are used and communicated. Based on the workshop outcome the presentation will (a) summarize the informational needs and current application of metrics by the end-users, who, depending on their field and area of operation might require health, policy, and/or economically relevant parameters at different scales, (b) provide an overview of the state of the science of currently used and newly developed metrics, and the scientific validity of these

A comparative study of multi-focus image fusion validation metrics

NASA Astrophysics Data System (ADS)

Giansiracusa, Michael; Lutz, Adam; Messer, Neal; Ezekiel, Soundararajan; Alford, Mark; Blasch, Erik; Bubalo, Adnan; Manno, Michael

2016-05-01

Fusion of visual information from multiple sources is relevant for applications security, transportation, and safety applications. One way that image fusion can be particularly useful is when fusing imagery data from multiple levels of focus. Different focus levels can create different visual qualities for different regions in the imagery, which can provide much more visual information to analysts when fused. Multi-focus image fusion would benefit a user through automation, which requires the evaluation of the fused images to determine whether they have properly fused the focused regions of each image. Many no-reference metrics, such as information theory based, image feature based and structural similarity-based have been developed to accomplish comparisons. However, it is hard to scale an accurate assessment of visual quality which requires the validation of these metrics for different types of applications. In order to do this, human perception based validation methods have been developed, particularly dealing with the use of receiver operating characteristics (ROC) curves and the area under them (AUC). Our study uses these to analyze the effectiveness of no-reference image fusion metrics applied to multi-resolution fusion methods in order to determine which should be used when dealing with multi-focus data. Preliminary results show that the Tsallis, SF, and spatial frequency metrics are consistent with the image quality and peak signal to noise ratio (PSNR).

Standardized reporting of functioning information on ICF-based common metrics.

PubMed

Prodinger, Birgit; Tennant, Alan; Stucki, Gerold

2018-02-01

In clinical practice and research a variety of clinical data collection tools are used to collect information on people's functioning for clinical practice and research and national health information systems. Reporting on ICF-based common metrics enables standardized documentation of functioning information in national health information systems. The objective of this methodological note on applying the ICF in rehabilitation is to demonstrate how to report functioning information collected with a data collection tool on ICF-based common metrics. We first specify the requirements for the standardized reporting of functioning information. Secondly, we introduce the methods needed for transforming functioning data to ICF-based common metrics. Finally, we provide an example. The requirements for standardized reporting are as follows: 1) having a common conceptual framework to enable content comparability between any health information; and 2) a measurement framework so that scores between two or more clinical data collection tools can be directly compared. The methods needed to achieve these requirements are the ICF Linking Rules and the Rasch measurement model. Using data collected incorporating the 36-item Short Form Health Survey (SF-36), the World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), and the Stroke Impact Scale 3.0 (SIS 3.0), the application of the standardized reporting based on common metrics is demonstrated. A subset of items from the three tools linked to common chapters of the ICF (d4 Mobility, d5 Self-care and d6 Domestic life), were entered as "super items" into the Rasch model. Good fit was achieved with no residual local dependency and a unidimensional metric. A transformation table allows for comparison between scales, and between a scale and the reporting common metric. Being able to report functioning information collected with commonly used clinical data collection tools with ICF-based common metrics enables clinicians

Recommendations for Mass Spectrometry Data Quality Metrics for Open Access Data (Corollary to the Amsterdam Principles)

PubMed Central

Kinsinger, Christopher R.; Apffel, James; Baker, Mark; Bian, Xiaopeng; Borchers, Christoph H.; Bradshaw, Ralph; Brusniak, Mi-Youn; Chan, Daniel W.; Deutsch, Eric W.; Domon, Bruno; Gorman, Jeff; Grimm, Rudolf; Hancock, William; Hermjakob, Henning; Horn, David; Hunter, Christie; Kolar, Patrik; Kraus, Hans-Joachim; Langen, Hanno; Linding, Rune; Moritz, Robert L.; Omenn, Gilbert S.; Orlando, Ron; Pandey, Akhilesh; Ping, Peipei; Rahbar, Amir; Rivers, Robert; Seymour, Sean L.; Simpson, Richard J.; Slotta, Douglas; Smith, Richard D.; Stein, Stephen E.; Tabb, David L.; Tagle, Danilo; Yates, John R.; Rodriguez, Henry

2011-01-01

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the U.S. National Cancer Institute (NCI) convened the “International Workshop on Proteomic Data Quality Metrics” in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: (1) an evolving list of comprehensive quality metrics and (2) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in the Journal of Proteome Research, Molecular and Cellular Proteomics, Proteomics, and Proteomics Clinical Applications as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals. PMID:22053864

Recommendations for Mass Spectrometry Data Quality Metrics for Open Access Data (Corollary to the Amsterdam Principles)*

PubMed Central

Kinsinger, Christopher R.; Apffel, James; Baker, Mark; Bian, Xiaopeng; Borchers, Christoph H.; Bradshaw, Ralph; Brusniak, Mi-Youn; Chan, Daniel W.; Deutsch, Eric W.; Domon, Bruno; Gorman, Jeff; Grimm, Rudolf; Hancock, William; Hermjakob, Henning; Horn, David; Hunter, Christie; Kolar, Patrik; Kraus, Hans-Joachim; Langen, Hanno; Linding, Rune; Moritz, Robert L.; Omenn, Gilbert S.; Orlando, Ron; Pandey, Akhilesh; Ping, Peipei; Rahbar, Amir; Rivers, Robert; Seymour, Sean L.; Simpson, Richard J.; Slotta, Douglas; Smith, Richard D.; Stein, Stephen E.; Tabb, David L.; Tagle, Danilo; Yates, John R.; Rodriguez, Henry

2011-01-01

Policies supporting the rapid and open sharing of proteomic data are being implemented by the leading journals in the field. The proteomics community is taking steps to ensure that data are made publicly accessible and are of high quality, a challenging task that requires the development and deployment of methods for measuring and documenting data quality metrics. On September 18, 2010, the United States National Cancer Institute convened the “International Workshop on Proteomic Data Quality Metrics” in Sydney, Australia, to identify and address issues facing the development and use of such methods for open access proteomics data. The stakeholders at the workshop enumerated the key principles underlying a framework for data quality assessment in mass spectrometry data that will meet the needs of the research community, journals, funding agencies, and data repositories. Attendees discussed and agreed up on two primary needs for the wide use of quality metrics: 1) an evolving list of comprehensive quality metrics and 2) standards accompanied by software analytics. Attendees stressed the importance of increased education and training programs to promote reliable protocols in proteomics. This workshop report explores the historic precedents, key discussions, and necessary next steps to enhance the quality of open access data. By agreement, this article is published simultaneously in the Journal of Proteome Research, Molecular and Cellular Proteomics, Proteomics, and Proteomics Clinical Applications as a public service to the research community. The peer review process was a coordinated effort conducted by a panel of referees selected by the journals. PMID:22052993

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.

Can state-of-the-art HVS-based objective image quality criteria be used for image reconstruction techniques based on ROI analysis?

NASA Astrophysics Data System (ADS)

Dostal, P.; Krasula, L.; Klima, M.

2012-06-01

Various image processing techniques in multimedia technology are optimized using visual attention feature of the human visual system. Spatial non-uniformity causes that different locations in an image are of different importance in terms of perception of the image. In other words, the perceived image quality depends mainly on the quality of important locations known as regions of interest. The performance of such techniques is measured by subjective evaluation or objective image quality criteria. Many state-of-the-art objective metrics are based on HVS properties; SSIM, MS-SSIM based on image structural information, VIF based on the information that human brain can ideally gain from the reference image or FSIM utilizing the low-level features to assign the different importance to each location in the image. But still none of these objective metrics utilize the analysis of regions of interest. We solve the question if these objective metrics can be used for effective evaluation of images reconstructed by processing techniques based on ROI analysis utilizing high-level features. In this paper authors show that the state-of-the-art objective metrics do not correlate well with subjective evaluation while the demosaicing based on ROI analysis is used for reconstruction. The ROI were computed from "ground truth" visual attention data. The algorithm combining two known demosaicing techniques on the basis of ROI location is proposed to reconstruct the ROI in fine quality while the rest of image is reconstructed with low quality. The color image reconstructed by this ROI approach was compared with selected demosaicing techniques by objective criteria and subjective testing. The qualitative comparison of the objective and subjective results indicates that the state-of-the-art objective metrics are still not suitable for evaluation image processing techniques based on ROI analysis and new criteria is demanded.

Landscape pattern metrics and regional assessment

USGS Publications Warehouse

O'Neill, R. V.; Riitters, K.H.; Wickham, J.D.; Jones, K.B.

1999-01-01

The combination of remote imagery data, geographic information systems software, and landscape ecology theory provides a unique basis for monitoring and assessing large-scale ecological systems. The unique feature of the work has been the need to develop and interpret quantitative measures of spatial pattern-the landscape indices. This article reviews what is known about the statistical properties of these pattern metrics and suggests some additional metrics based on island biogeography, percolation theory, hierarchy theory, and economic geography. Assessment applications of this approach have required interpreting the pattern metrics in terms of specific environmental endpoints, such as wildlife and water quality, and research into how to represent synergystic effects of many overlapping sources of stress.

Toward determining melt pool quality metrics via coaxial monitoring in laser powder bed fusion.

PubMed

Fisher, Brian A; Lane, Brandon; Yeung, Ho; Beuth, Jack

2018-01-01

The current industry trend in metal additive manufacturing is towards greater real time process monitoring capabilities during builds to ensure high quality parts. While the hardware implementations that allow for real time monitoring of the melt pool have advanced significantly, the knowledge required to correlate the generated data to useful metrics of interest are still lacking. This research presents promising results that aim to bridge this knowledge gap by determining a novel means to correlate easily obtainable sensor data (thermal emission) to key melt pool size metrics (e.g., melt pool cross sectional area).

Image-guided radiotherapy quality control: Statistical process control using image similarity metrics.

PubMed

Shiraishi, Satomi; Grams, Michael P; Fong de Los Santos, Luis E

2018-05-01

The purpose of this study was to demonstrate an objective quality control framework for the image review process. A total of 927 cone-beam computed tomography (CBCT) registrations were retrospectively analyzed for 33 bilateral head and neck cancer patients who received definitive radiotherapy. Two registration tracking volumes (RTVs) - cervical spine (C-spine) and mandible - were defined, within which a similarity metric was calculated and used as a registration quality tracking metric over the course of treatment. First, sensitivity to large misregistrations was analyzed for normalized cross-correlation (NCC) and mutual information (MI) in the context of statistical analysis. The distribution of metrics was obtained for displacements that varied according to a normal distribution with standard deviation of σ = 2 mm, and the detectability of displacements greater than 5 mm was investigated. Then, similarity metric control charts were created using a statistical process control (SPC) framework to objectively monitor the image registration and review process. Patient-specific control charts were created using NCC values from the first five fractions to set a patient-specific process capability limit. Population control charts were created using the average of the first five NCC values for all patients in the study. For each patient, the similarity metrics were calculated as a function of unidirectional translation, referred to as the effective displacement. Patient-specific action limits corresponding to 5 mm effective displacements were defined. Furthermore, effective displacements of the ten registrations with the lowest similarity metrics were compared with a three dimensional (3DoF) couch displacement required to align the anatomical landmarks. Normalized cross-correlation identified suboptimal registrations more effectively than MI within the framework of SPC. Deviations greater than 5 mm were detected at 2.8σ and 2.1σ from the mean for NCC and MI

Evaluation of the performance of a micromethod for measuring urinary iodine by using six sigma quality metrics.

PubMed

Hussain, Husniza; Khalid, Norhayati Mustafa; Selamat, Rusidah; Wan Nazaimoon, Wan Mohamud

2013-09-01

The urinary iodine micromethod (UIMM) is a modification of the conventional method and its performance needs evaluation. UIMM performance was evaluated using the method validation and 2008 Iodine Deficiency Disorders survey data obtained from four urinary iodine (UI) laboratories. Method acceptability tests and Sigma quality metrics were determined using total allowable errors (TEas) set by two external quality assurance (EQA) providers. UIMM obeyed various method acceptability test criteria with some discrepancies at low concentrations. Method validation data calculated against the UI Quality Program (TUIQP) TEas showed that the Sigma metrics were at 2.75, 1.80, and 3.80 for 51±15.50 µg/L, 108±32.40 µg/L, and 149±38.60 µg/L UI, respectively. External quality control (EQC) data showed that the performance of the laboratories was within Sigma metrics of 0.85-1.12, 1.57-4.36, and 1.46-4.98 at 46.91±7.05 µg/L, 135.14±13.53 µg/L, and 238.58±17.90 µg/L, respectively. No laboratory showed a calculated total error (TEcalc)Quality of UI Procedures (EQUIP) TEas, the performance of all laboratories was≤2.49 Sigma metrics at all concentrations. Only one laboratory had TEcalc

Evaluating the Good Ontology Design Guideline (GoodOD) with the Ontology Quality Requirements and Evaluation Method and Metrics (OQuaRE)

PubMed Central

Duque-Ramos, Astrid; Boeker, Martin; Jansen, Ludger; Schulz, Stefan; Iniesta, Miguela; Fernández-Breis, Jesualdo Tomás

2014-01-01

Objective To (1) evaluate the GoodOD guideline for ontology development by applying the OQuaRE evaluation method and metrics to the ontology artefacts that were produced by students in a randomized controlled trial, and (2) informally compare the OQuaRE evaluation method with gold standard and competency questions based evaluation methods, respectively. Background In the last decades many methods for ontology construction and ontology evaluation have been proposed. However, none of them has become a standard and there is no empirical evidence of comparative evaluation of such methods. This paper brings together GoodOD and OQuaRE. GoodOD is a guideline for developing robust ontologies. It was previously evaluated in a randomized controlled trial employing metrics based on gold standard ontologies and competency questions as outcome parameters. OQuaRE is a method for ontology quality evaluation which adapts the SQuaRE standard for software product quality to ontologies and has been successfully used for evaluating the quality of ontologies. Methods In this paper, we evaluate the effect of training in ontology construction based on the GoodOD guideline within the OQuaRE quality evaluation framework and compare the results with those obtained for the previous studies based on the same data. Results Our results show a significant effect of the GoodOD training over developed ontologies by topics: (a) a highly significant effect was detected in three topics from the analysis of the ontologies of untrained and trained students; (b) both positive and negative training effects with respect to the gold standard were found for five topics. Conclusion The GoodOD guideline had a significant effect over the quality of the ontologies developed. Our results show that GoodOD ontologies can be effectively evaluated using OQuaRE and that OQuaRE is able to provide additional useful information about the quality of the GoodOD ontologies. PMID:25148262

Evaluating the Good Ontology Design Guideline (GoodOD) with the ontology quality requirements and evaluation method and metrics (OQuaRE).

PubMed

Duque-Ramos, Astrid; Boeker, Martin; Jansen, Ludger; Schulz, Stefan; Iniesta, Miguela; Fernández-Breis, Jesualdo Tomás

2014-01-01

To (1) evaluate the GoodOD guideline for ontology development by applying the OQuaRE evaluation method and metrics to the ontology artefacts that were produced by students in a randomized controlled trial, and (2) informally compare the OQuaRE evaluation method with gold standard and competency questions based evaluation methods, respectively. In the last decades many methods for ontology construction and ontology evaluation have been proposed. However, none of them has become a standard and there is no empirical evidence of comparative evaluation of such methods. This paper brings together GoodOD and OQuaRE. GoodOD is a guideline for developing robust ontologies. It was previously evaluated in a randomized controlled trial employing metrics based on gold standard ontologies and competency questions as outcome parameters. OQuaRE is a method for ontology quality evaluation which adapts the SQuaRE standard for software product quality to ontologies and has been successfully used for evaluating the quality of ontologies. In this paper, we evaluate the effect of training in ontology construction based on the GoodOD guideline within the OQuaRE quality evaluation framework and compare the results with those obtained for the previous studies based on the same data. Our results show a significant effect of the GoodOD training over developed ontologies by topics: (a) a highly significant effect was detected in three topics from the analysis of the ontologies of untrained and trained students; (b) both positive and negative training effects with respect to the gold standard were found for five topics. The GoodOD guideline had a significant effect over the quality of the ontologies developed. Our results show that GoodOD ontologies can be effectively evaluated using OQuaRE and that OQuaRE is able to provide additional useful information about the quality of the GoodOD ontologies.

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.

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

PubMed Central

2011-01-01

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

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.

Applying Sigma Metrics to Reduce Outliers.

PubMed

Litten, Joseph

2017-03-01

Sigma metrics can be used to predict assay quality, allowing easy comparison of instrument quality and predicting which tests will require minimal quality control (QC) rules to monitor the performance of the method. A Six Sigma QC program can result in fewer controls and fewer QC failures for methods with a sigma metric of 5 or better. The higher the number of methods with a sigma metric of 5 or better, the lower the costs for reagents, supplies, and control material required to monitor the performance of the methods. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Adaptive distance metric learning for diffusion tensor image segmentation.

PubMed

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C N; Chu, Winnie C W

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.

Adaptive Distance Metric Learning for Diffusion Tensor Image Segmentation

PubMed Central

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C. N.; Chu, Winnie C. W.

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework. PMID:24651858

Evaluative Usage-Based Metrics for the Selection of E-Journals.

ERIC Educational Resources Information Center

Hahn, Karla L.; Faulkner, Lila A.

2002-01-01

Explores electronic journal usage statistics and develops three metrics and three benchmarks based on those metrics. Topics include earlier work that assessed the value of print journals and was modified for the electronic format; the evaluation of potential purchases; and implications for standards development, including the need for content…

Organ quality metrics are a poor predictor of costs and resource utilization in deceased donor kidney transplantation.

PubMed

Stahl, Christopher C; Wima, Koffi; Hanseman, Dennis J; Hoehn, Richard S; Ertel, Audrey; Midura, Emily F; Hohmann, Samuel F; Paquette, Ian M; Shah, Shimul A; Abbott, Daniel E

2015-12-01

The desire to provide cost-effective care has lead to an investigation of the costs of therapy for end-stage renal disease. Organ quality metrics are one way to attempt to stratify kidney transplants, although the ability of these metrics to predict costs and resource use is undetermined. The Scientific Registry of Transplant Recipients database was linked to the University HealthSystem Consortium Database to identify adult deceased donor kidney transplant recipients from 2009 to 2012. Patients were divided into cohorts by kidney criteria (standard vs expanded) or kidney donor profile index (KDPI) score (<85 vs 85+). Length of stay, 30-day readmission, discharge disposition, and delayed graft function were used as indicators of resource use. Cost was defined as reimbursement based on Medicare cost/charge ratios and included the costs of readmission when applicable. More than 19,500 patients populated the final dataset. Lower-quality kidneys (expanded criteria donor or KDPI 85+) were more likely to be transplanted in older (both P < .001) and diabetic recipients (both P < .001). After multivariable analysis controlling for recipient characteristics, we found that expanded criteria donor transplants were not associated with increased costs compared with standard criteria donor transplants (risk ratio [RR] 0.97, 95% confidence interval [CI] 0.93-1.00, P = .07). KDPI 85+ was associated with slightly lower costs than KDPI <85 transplants (RR 0.95, 95% CI 0.91-0.99, P = .02). When KDPI was considered as a continuous variable, the association was maintained (RR 0.9993, 95% CI 0.999-0.9998, P = .01). Organ quality metrics are less influential predictors of short-term costs than recipient factors. Future studies should focus on recipient characteristics as a way to discern high versus low cost transplantation procedures. Copyright © 2015 Elsevier Inc. All rights reserved.

A Metric and Workflow for Quality Control in the Analysis of Heterogeneity in Phenotypic Profiles and Screens

PubMed Central

Gough, Albert; Shun, Tongying; Taylor, D. Lansing; Schurdak, Mark

2016-01-01

Heterogeneity is well recognized as a common property of cellular systems that impacts biomedical research and the development of therapeutics and diagnostics. Several studies have shown that analysis of heterogeneity: gives insight into mechanisms of action of perturbagens; can be used to predict optimal combination therapies; and to quantify heterogeneity in tumors where heterogeneity is believed to be associated with adaptation and resistance. Cytometry methods including high content screening (HCS), high throughput microscopy, flow cytometry, mass spec imaging and digital pathology capture cell level data for populations of cells. However it is often assumed that the population response is normally distributed and therefore that the average adequately describes the results. A deeper understanding of the results of the measurements and more effective comparison of perturbagen effects requires analysis that takes into account the distribution of the measurements, i.e. the heterogeneity. However, the reproducibility of heterogeneous data collected on different days, and in different plates/slides has not previously been evaluated. Here we show that conventional assay quality metrics alone are not adequate for quality control of the heterogeneity in the data. To address this need, we demonstrate the use of the Kolmogorov-Smirnov statistic as a metric for monitoring the reproducibility of heterogeneity in an SAR screen, describe a workflow for quality control in heterogeneity analysis. One major challenge in high throughput biology is the evaluation and interpretation of heterogeneity in thousands of samples, such as compounds in a cell-based screen. In this study we also demonstrate that three heterogeneity indices previously reported, capture the shapes of the distributions and provide a means to filter and browse big data sets of cellular distributions in order to compare and identify distributions of interest. These metrics and methods are presented as a

The data quality analyzer: A quality control program for seismic data

NASA Astrophysics Data System (ADS)

Ringler, A. T.; Hagerty, M. T.; Holland, J.; Gonzales, A.; Gee, L. S.; Edwards, J. D.; Wilson, D.; Baker, A. M.

2015-03-01

The U.S. Geological Survey's Albuquerque Seismological Laboratory (ASL) has several initiatives underway to enhance and track the quality of data produced from ASL seismic stations and to improve communication about data problems to the user community. The Data Quality Analyzer (DQA) is one such development and is designed to characterize seismic station data quality in a quantitative and automated manner. The DQA consists of a metric calculator, a PostgreSQL database, and a Web interface: The metric calculator, SEEDscan, is a Java application that reads and processes miniSEED data and generates metrics based on a configuration file. SEEDscan compares hashes of metadata and data to detect changes in either and performs subsequent recalculations as needed. This ensures that the metric values are up to date and accurate. SEEDscan can be run as a scheduled task or on demand. The PostgreSQL database acts as a central hub where metric values and limited station descriptions are stored at the channel level with one-day granularity. The Web interface dynamically loads station data from the database and allows the user to make requests for time periods of interest, review specific networks and stations, plot metrics as a function of time, and adjust the contribution of various metrics to the overall quality grade of the station. 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

Using animation quality metric to improve efficiency of global illumination computation for dynamic environments

NASA Astrophysics Data System (ADS)

Myszkowski, Karol; Tawara, Takehiro; Seidel, Hans-Peter

2002-06-01

In this paper, we consider applications of perception-based video quality metrics to improve the performance of global lighting computations for dynamic environments. For this purpose we extend the Visible Difference Predictor (VDP) developed by Daly to handle computer animations. We incorporate into the VDP the spatio-velocity CSF model developed by Kelly. The CSF model requires data on the velocity of moving patterns across the image plane. We use the 3D image warping technique to compensate for the camera motion, and we conservatively assume that the motion of animated objects (usually strong attractors of the visual attention) is fully compensated by the smooth pursuit eye motion. Our global illumination solution is based on stochastic photon tracing and takes advantage of temporal coherence of lighting distribution, by processing photons both in the spatial and temporal domains. The VDP is used to keep noise inherent in stochastic methods below the sensitivity level of the human observer. As a result a perceptually-consistent quality across all animation frames is obtained.

Evaluation of image deblurring methods via a classification metric

NASA Astrophysics Data System (ADS)

Perrone, Daniele; Humphreys, David; Lamb, Robert A.; Favaro, Paolo

2012-09-01

The performance of single image deblurring algorithms is typically evaluated via a certain discrepancy measure between the reconstructed image and the ideal sharp image. The choice of metric, however, has been a source of debate and has also led to alternative metrics based on human visual perception. While fixed metrics may fail to capture some small but visible artifacts, perception-based metrics may favor reconstructions with artifacts that are visually pleasant. To overcome these limitations, we propose to assess the quality of reconstructed images via a task-driven metric. In this paper we consider object classification as the task and therefore use the rate of classification as the metric to measure deblurring performance. In our evaluation we use data with different types of blur in two cases: Optical Character Recognition (OCR), where the goal is to recognise characters in a black and white image, and object classification with no restrictions on pose, illumination and orientation. Finally, we show how off-the-shelf classification algorithms benefit from working with deblurred images.

Implementation of a Clinical Documentation Improvement Curriculum Improves Quality Metrics and Hospital Charges in an Academic Surgery Department.

PubMed

Reyes, Cynthia; Greenbaum, Alissa; Porto, Catherine; Russell, John C

2017-03-01

Accurate clinical documentation (CD) is necessary for many aspects of modern health care, including excellent communication, quality metrics reporting, and legal documentation. New requirements have mandated adoption of ICD-10-CM coding systems, adding another layer of complexity to CD. A clinical documentation improvement (CDI) and ICD-10 training program was created for health care providers in our academic surgery department. We aimed to assess the impact of our CDI curriculum by comparing quality metrics, coding, and reimbursement before and after implementation of our CDI program. A CDI/ICD-10 training curriculum was instituted in September 2014 for all members of our university surgery department. The curriculum consisted of didactic lectures, 1-on-1 provider training, case reviews, e-learning modules, and CD queries from nurse CDI staff and hospital coders. Outcomes parameters included monthly documentation completion rates, severity of illness (SOI), risk of mortality (ROM), case-mix index (CMI), all-payer refined diagnosis-related groups (APR-DRG), and Surgical Care Improvement Program (SCIP) metrics. Financial gain from responses to CDI queries was determined retrospectively. Surgery department delinquent documentation decreased by 85% after CDI implementation. Compliance with SCIP measures improved from 85% to 97%. Significant increases in surgical SOI, ROM, CMI, and APR-DRG (all p < 0.01) were found after CDI/ICD-10 training implementation. Provider responses to CDI queries resulted in an estimated $4,672,786 increase in charges. Clinical documentation improvement/ICD-10 training in an academic surgery department is an effective method to improve documentation rates, increase the hospital estimated reimbursement based on more accurate CD, and provide better compliance with surgical quality measures. Copyright © 2016 American College of Surgeons. All rights reserved.

EVALUATION OF METRIC PRECISION FOR A RIPARIAN FOREST SURVEY

EPA Science Inventory

This paper evaluates the performance of a protocol to monitor riparian forests in western Oregon based on the quality of the data obtained from a recent field survey. Precision and accuracy are the criteria used to determine the quality of 19 field metrics. The field survey con...

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.

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...

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.

Transfusion rate as a quality metric: is blood conservation a learnable skill?

PubMed

Paone, Gaetano; Brewer, Robert; Likosky, Donald S; Theurer, Patricia F; Bell, Gail F; Cogan, Chad M; Prager, Richard L

2013-10-01

Between January 2008 and December 2012, a multicenter quality collaborative initiated a focus on blood conservation as a quality metric, with educational presentations and quarterly reporting of institutional-level perioperative transfusion rates and outcomes. This prospective cohort study was undertaken to determine the effect of that initiative on transfusion rates after isolated coronary artery bypass grafting (CABG). Between January 1, 2008, and December 31, 2012, 30,271 patients underwent isolated CABG in Michigan. Evaluated were annual crude and adjusted trends in overall transfusion rates for red blood cells (RBCs), fresh frozen plasma (FFP), and platelets, and in operative death. Transfusion rates continuously decreased for all blood products. RBC use decreased from 56.4% in 2008 (baseline) to 38.3% in 2012, FFP use decreased from 14.8% to 9.1%, and platelet use decreased from 20.5% to 13.4% (ptrend < 0.001 for all). A significant reduction occurred in deep sternal wound infection, reoperation for bleeding, renal failure, prolonged ventilation, initial ventilator time, and intensive care unit duration. The percentage of patients discharged home significantly increased (ptrend < 0.001). Mortality rates did not differ significantly (ptrend = 0.11). In a multicenter quality collaborative, increased attention to transfusion-related outcomes and blood conservation techniques, coincident with regular reporting and review of perioperative transfusion rates as a quality metric, was associated with a significant decrease in blood product utilization. These reductions were concurrent with significant improvement in most perioperative outcomes. This intervention was also safe, as it was not associated with any increases in mortality. Copyright © 2013 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

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.

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.

MUSTANG: A Community-Facing Web Service to Improve Seismic Data Quality Awareness Through Metrics

NASA Astrophysics Data System (ADS)

Templeton, M. E.; Ahern, T. K.; Casey, R. E.; Sharer, G.; Weertman, B.; Ashmore, S.

2014-12-01

IRIS DMC is engaged in a new effort to provide broad and deep visibility into the quality of data and metadata found in its terabyte-scale geophysical data archive. Taking advantage of large and fast disk capacity, modern advances in open database technologies, and nimble provisioning of virtual machine resources, we are creating an openly accessible treasure trove of data measurements for scientists and the general public to utilize in providing new insights into the quality of this data. We have branded this statistical gathering system MUSTANG, and have constructed it as a component of the web services suite that IRIS DMC offers. MUSTANG measures over forty data metrics addressing issues with archive status, data statistics and continuity, signal anomalies, noise analysis, metadata checks, and station state of health. These metrics could potentially be used both by network operators to diagnose station problems and by data users to sort suitable data from unreliable or unusable data. Our poster details what MUSTANG is, how users can access it, what measurements they can find, and how MUSTANG fits into the IRIS DMC's data access ecosystem. Progress in data processing, approaches to data visualization, and case studies of MUSTANG's use for quality assurance will be presented. We want to illustrate what is possible with data quality assurance, the need for data quality assurance, and how the seismic community will benefit from this freely available analytics service.

The role of metrics and measurements in a software intensive total quality management environment

NASA Technical Reports Server (NTRS)

Daniels, Charles B.

1992-01-01

Paramax Space Systems began its mission as a member of the Rockwell Space Operations Company (RSOC) team which was the successful bidder on a massive operations consolidation contract for the Mission Operations Directorate (MOD) at JSC. The contract awarded to the team was the Space Transportation System Operations Contract (STSOC). Our initial challenge was to accept responsibility for a very large, highly complex and fragmented collection of software from eleven different contractors and transform it into a coherent, operational baseline. Concurrently, we had to integrate a diverse group of people from eleven different companies into a single, cohesive team. Paramax executives recognized the absolute necessity to develop a business culture based on the concept of employee involvement to execute and improve the complex process of our new environment. Our executives clearly understood that management needed to set the example and lead the way to quality improvement. The total quality management policy and the metrics used in this endeavor are presented.

Engineering performance metrics

NASA Astrophysics Data System (ADS)

Delozier, R.; Snyder, N.

1993-03-01

Implementation of a Total Quality Management (TQM) approach to engineering work required the development of a system of metrics which would serve as a meaningful management tool for evaluating effectiveness in accomplishing project objectives and in achieving improved customer satisfaction. A team effort was chartered with the goal of developing a system of engineering performance metrics which would measure customer satisfaction, quality, cost effectiveness, and timeliness. The approach to developing this system involved normal systems design phases including, conceptual design, detailed design, implementation, and integration. The lessons teamed from this effort will be explored in this paper. These lessons learned may provide a starting point for other large engineering organizations seeking to institute a performance measurement system accomplishing project objectives and in achieving improved customer satisfaction. To facilitate this effort, a team was chartered to assist in the development of the metrics system. This team, consisting of customers and Engineering staff members, was utilized to ensure that the needs and views of the customers were considered in the development of performance measurements. The development of a system of metrics is no different than the development of any type of system. It includes the steps of defining performance measurement requirements, measurement process conceptual design, performance measurement and reporting system detailed design, and system implementation and integration.

Metrics for Assessing the Quality of Groundwater Used for Public Supply, CA, USA: Equivalent-Population and Area.

PubMed

Belitz, Kenneth; Fram, Miranda S; Johnson, Tyler D

2015-07-21

Data from 11,000 public supply wells in 87 study areas were used to assess the quality of nearly all of the groundwater used for public supply in California. Two metrics were developed for quantifying groundwater quality: area with high concentrations (km(2) or proportion) and equivalent-population relying upon groundwater with high concentrations (number of people or proportion). Concentrations are considered high if they are above a human-health benchmark. When expressed as proportions, the metrics are area-weighted and population-weighted detection frequencies. On a statewide-scale, about 20% of the groundwater used for public supply has high concentrations for one or more constituents (23% by area and 18% by equivalent-population). On the basis of both area and equivalent-population, trace elements are more prevalent at high concentrations than either nitrate or organic compounds at the statewide-scale, in eight of nine hydrogeologic provinces, and in about three-quarters of the study areas. At a statewide-scale, nitrate is more prevalent than organic compounds based on area, but not on the basis of equivalent-population. The approach developed for this paper, unlike many studies, recognizes the importance of appropriately weighting information when changing scales, and is broadly applicable to other areas.

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

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.

Investigation of Two Models to Set and Evaluate Quality Targets for HbA1c: Biological Variation and Sigma-metrics

PubMed Central

Weykamp, Cas; John, Garry; Gillery, Philippe; English, Emma; Ji, Linong; Lenters-Westra, Erna; Little, Randie R.; Roglic, Gojka; Sacks, David B.; Takei, Izumi

2016-01-01

Background A major objective of the IFCC Task Force on implementation of HbA1c standardization is to develop a model to define quality targets for HbA1c. Methods Two generic models, the Biological Variation and Sigma-metrics model, are investigated. Variables in the models were selected for HbA1c and data of EQA/PT programs were used to evaluate the suitability of the models to set and evaluate quality targets within and between laboratories. Results In the biological variation model 48% of individual laboratories and none of the 26 instrument groups met the minimum performance criterion. In the Sigma-metrics model, with a total allowable error (TAE) set at 5 mmol/mol (0.46% NGSP) 77% of the individual laboratories and 12 of 26 instrument groups met the 2 sigma criterion. Conclusion The Biological Variation and Sigma-metrics model were demonstrated to be suitable for setting and evaluating quality targets within and between laboratories. The Sigma-metrics model is more flexible as both the TAE and the risk of failure can be adjusted to requirements related to e.g. use for diagnosis/monitoring or requirements of (inter)national authorities. With the aim of reaching international consensus on advice regarding quality targets for HbA1c, the Task Force suggests the Sigma-metrics model as the model of choice with default values of 5 mmol/mol (0.46%) for TAE, and risk levels of 2 and 4 sigma for routine laboratories and laboratories performing clinical trials, respectively. These goals should serve as a starting point for discussion with international stakeholders in the field of diabetes. PMID:25737535

Survival As a Quality Metric of Cancer Care: Use of the National Cancer Data Base to Assess Hospital Performance.

PubMed

Shulman, Lawrence N; Palis, Bryan E; McCabe, Ryan; Mallin, Kathy; Loomis, Ashley; Winchester, David; McKellar, Daniel

2018-01-01

Survival is considered an important indicator of the quality of cancer care, but the validity of different methodologies to measure comparative survival rates is less well understood. We explored whether the National Cancer Data Base (NCDB) could serve as a source of unadjusted and risk-adjusted cancer survival data and whether these data could be used as quality indicators for individual hospitals or in the aggregate by hospital type. The NCDB, an aggregate of > 1,500 hospital cancer registries, was queried to analyze unadjusted and risk-adjusted hazards of death for patients with stage III breast cancer (n = 116,787) and stage IIIB or IV non-small-cell lung cancer (n = 252,392). Data were analyzed at the individual hospital level and by hospital type. At the hospital level, after risk adjustment, few hospitals had comparative risk-adjusted survival rates that were statistically better or worse. By hospital type, National Cancer Institute-designated comprehensive cancer centers had risk-adjusted survival ratios that were statistically significantly better than those of academic cancer centers and community hospitals. Using the NCDB as the data source, survival rates for patients with stage III breast cancer and stage IIIB or IV non-small-cell lung cancer were statistically better at National Cancer Institute-designated comprehensive cancer centers when compared with other hospital types. Compared with academic hospitals, risk-adjusted survival was lower in community hospitals. At the individual hospital level, after risk adjustment, few hospitals were shown to have statistically better or worse survival, suggesting that, using NCDB data, survival may not be a good metric to determine relative quality of cancer care at this level.

Empirical Assessment of the Impact of Low-Cost Generic Programs on Adherence-Based Quality Measures

PubMed Central

Pauly, Nathan J.; Talbert, Jeffery C.; Brown, Joshua D.

2017-01-01

In the United States, federally-funded health plans are mandated to measure the quality of care. Adherence-based medication quality metrics depend on completeness of administrative claims data for accurate measurement. Low-cost generic programs (LCGPs) cause medications fills to be missing from claims data as medications are not adjudicated through a patient’s insurance. This study sought to assess the magnitude of the impact of LCGPs on these quality measures. Data from the 2012–2013 Medical Expenditure Panel Survey (MEPS) were used. Medication fills for select medication classes were classified as LCGP fills and individuals were classified as never, sometimes, and always users of LCGPs. Individuals were classified based on insurance type (private, Medicare, Medicaid, dual-eligible). The proportion of days covered (PDC) was calculated for each medication class and the proportion of users with PDC ≥ 0.80 was reported as an observed metric for what would be calculated based on claims data and a true metric which included missing medication fills due to LCGPs. True measures of adherence were higher than the observed measures. The effect’s magnitude was highest for private insurance and for medication classes utilized more often through LCGPs. Thus, medication-based quality measures may be underestimated due to LCGPs. PMID:28970427

Calculation and use of an environment's characteristic software metric set

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Selby, Richard W., Jr.

1985-01-01

Since both cost/quality and production environments differ, this study presents an approach for customizing a characteristic set of software metrics to an environment. The approach is applied in the Software Engineering Laboratory (SEL), a NASA Goddard production environment, to 49 candidate process and product metrics of 652 modules from six (51,000 to 112,000 lines) projects. For this particular environment, the method yielded the characteristic metric set (source lines, fault correction effort per executable statement, design effort, code effort, number of I/O parameters, number of versions). The uses examined for a characteristic metric set include forecasting the effort for development, modification, and fault correction of modules based on historical data.

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

Construct validity of individual and summary performance metrics associated with a computer-based laparoscopic simulator.

PubMed

Rivard, Justin D; Vergis, Ashley S; Unger, Bertram J; Hardy, Krista M; Andrew, Chris G; Gillman, Lawrence M; Park, Jason

2014-06-01

Computer-based surgical simulators capture a multitude of metrics based on different aspects of performance, such as speed, accuracy, and movement efficiency. However, without rigorous assessment, it may be unclear whether all, some, or none of these metrics actually reflect technical skill, which can compromise educational efforts on these simulators. We assessed the construct validity of individual performance metrics on the LapVR simulator (Immersion Medical, San Jose, CA, USA) and used these data to create task-specific summary metrics. Medical students with no prior laparoscopic experience (novices, N = 12), junior surgical residents with some laparoscopic experience (intermediates, N = 12), and experienced surgeons (experts, N = 11) all completed three repetitions of four LapVR simulator tasks. The tasks included three basic skills (peg transfer, cutting, clipping) and one procedural skill (adhesiolysis). We selected 36 individual metrics on the four tasks that assessed six different aspects of performance, including speed, motion path length, respect for tissue, accuracy, task-specific errors, and successful task completion. Four of seven individual metrics assessed for peg transfer, six of ten metrics for cutting, four of nine metrics for clipping, and three of ten metrics for adhesiolysis discriminated between experience levels. Time and motion path length were significant on all four tasks. We used the validated individual metrics to create summary equations for each task, which successfully distinguished between the different experience levels. Educators should maintain some skepticism when reviewing the plethora of metrics captured by computer-based simulators, as some but not all are valid. We showed the construct validity of a limited number of individual metrics and developed summary metrics for the LapVR. The summary metrics provide a succinct way of assessing skill with a single metric for each task, but require further validation.

Objectively Quantifying Radiation Esophagitis With Novel Computed Tomography–Based Metrics

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: To study radiation-induced esophageal expansion as an objective measure of radiation esophagitis in patients with non-small cell lung cancer (NSCLC) treated with intensity modulated radiation therapy. Methods and Materials: Eighty-five patients had weekly intra-treatment CT imaging and esophagitis scoring according to Common Terminlogy Criteria for Adverse Events 4.0, (24 Grade 0, 45 Grade 2, and 16 Grade 3). Nineteen esophageal expansion metrics based on mean, maximum, spatial length, and volume of expansion were calculated as voxel-based relative volume change, using the Jacobian determinant from deformable image registration between the planning and weekly CTs. An anatomic variability correction method wasmore » validated and applied to these metrics to reduce uncertainty. An analysis of expansion metrics and radiation esophagitis grade was conducted using normal tissue complication probability from univariate logistic regression and Spearman rank for grade 2 and grade 3 esophagitis endpoints, as well as the timing of expansion and esophagitis grade. Metrics' performance in classifying esophagitis was tested with receiver operating characteristic analysis. Results: Expansion increased with esophagitis grade. Thirteen of 19 expansion metrics had receiver operating characteristic area under the curve values >0.80 for both grade 2 and grade 3 esophagitis endpoints, with the highest performance from maximum axial expansion (MaxExp1) and esophageal length with axial expansion ≥30% (LenExp30%) with area under the curve values of 0.93 and 0.91 for grade 2, 0.90 and 0.90 for grade 3 esophagitis, respectively. Conclusions: Esophageal expansion may be a suitable objective measure of esophagitis, particularly maximum axial esophageal expansion and esophageal length with axial expansion ≥30%, with 2.1 Jacobian value and 98.6 mm as the metric value for 50% probability of grade 3 esophagitis. The uncertainty in esophageal Jacobian calculations can be reduced

Efficacy of single and multi-metric fish-based indices in tracking anthropogenic pressures in estuaries: An 8-year case study.

PubMed

Martinho, Filipe; Nyitrai, Daniel; Crespo, Daniel; Pardal, Miguel A

2015-12-15

Facing a generalized increase in water degradation, several programmes have been implemented for protecting and enhancing the water quality and associated wildlife, which rely on ecological indicators to assess the degree of deviation from a pristine state. Here, single (species number, Shannon-Wiener H', Pielou J') and multi-metric (Estuarine Fish Assessment Index, EFAI) community-based ecological quality measures were evaluated in a temperate estuary over an 8-year period (2005-2012), and established their relationships with an anthropogenic pressure index (API). Single metric indices were highly variable and neither concordant amongst themselves nor with the EFAI. The EFAI was the only index significantly correlated with the API, indicating that higher ecological quality was associated with lower anthropogenic pressure. Pressure scenarios were related with specific fish community composition, as a result of distinct food web complexity and nursery functioning of the estuary. Results were discussed in the scope of the implementation of water protection programmes. Copyright © 2015 Elsevier Ltd. All rights reserved.

A neural net-based approach to software metrics

NASA Technical Reports Server (NTRS)

Boetticher, G.; Srinivas, Kankanahalli; Eichmann, David A.

1992-01-01

Software metrics provide an effective method for characterizing software. Metrics have traditionally been composed through the definition of an equation. This approach is limited by the fact that all the interrelationships among all the parameters be fully understood. This paper explores an alternative, neural network approach to modeling metrics. Experiments performed on two widely accepted metrics, McCabe and Halstead, indicate that the approach is sound, thus serving as the groundwork for further exploration into the analysis and design of software metrics.

Metric Conversion

Atmospheric Science Data Center

2013-03-12

Metric Weights and Measures The metric system is based on 10s.  For example, 10 millimeters = 1 centimeter, 10 ... Special Publications: NIST Guide to SI Units: Conversion Factors NIST Guide to SI Units: Conversion Factors listed ...

Essential metrics for assessing sex & gender integration in health research proposals involving human participants.

PubMed

Day, Suzanne; Mason, Robin; Tannenbaum, Cara; Rochon, Paula A

2017-01-01

Integrating sex and gender in health research is essential to produce the best possible evidence to inform health care. Comprehensive integration of sex and gender requires considering these variables from the very beginning of the research process, starting at the proposal stage. To promote excellence in sex and gender integration, we have developed a set of metrics to assess the quality of sex and gender integration in research proposals. These metrics are designed to assist both researchers in developing proposals and reviewers in making funding decisions. We developed this tool through an iterative three-stage method involving 1) review of existing sex and gender integration resources and initial metrics design, 2) expert review and feedback via anonymous online survey (Likert scale and open-ended questions), and 3) analysis of feedback data and collective revision of the metrics. We received feedback on the initial metrics draft from 20 reviewers with expertise in conducting sex- and/or gender-based health research. The majority of reviewers responded positively to questions regarding the utility, clarity and completeness of the metrics, and all reviewers provided responses to open-ended questions about suggestions for improvements. Coding and analysis of responses identified three domains for improvement: clarifying terminology, refining content, and broadening applicability. Based on this analysis we revised the metrics into the Essential Metrics for Assessing Sex and Gender Integration in Health Research Proposals Involving Human Participants, which outlines criteria for excellence within each proposal component and provides illustrative examples to support implementation. By enhancing the quality of sex and gender integration in proposals, the metrics will help to foster comprehensive, meaningful integration of sex and gender throughout each stage of the research process, resulting in better quality evidence to inform health care for all.

Essential metrics for assessing sex & gender integration in health research proposals involving human participants

PubMed Central

Mason, Robin; Tannenbaum, Cara; Rochon, Paula A.

2017-01-01

Integrating sex and gender in health research is essential to produce the best possible evidence to inform health care. Comprehensive integration of sex and gender requires considering these variables from the very beginning of the research process, starting at the proposal stage. To promote excellence in sex and gender integration, we have developed a set of metrics to assess the quality of sex and gender integration in research proposals. These metrics are designed to assist both researchers in developing proposals and reviewers in making funding decisions. We developed this tool through an iterative three-stage method involving 1) review of existing sex and gender integration resources and initial metrics design, 2) expert review and feedback via anonymous online survey (Likert scale and open-ended questions), and 3) analysis of feedback data and collective revision of the metrics. We received feedback on the initial metrics draft from 20 reviewers with expertise in conducting sex- and/or gender-based health research. The majority of reviewers responded positively to questions regarding the utility, clarity and completeness of the metrics, and all reviewers provided responses to open-ended questions about suggestions for improvements. Coding and analysis of responses identified three domains for improvement: clarifying terminology, refining content, and broadening applicability. Based on this analysis we revised the metrics into the Essential Metrics for Assessing Sex and Gender Integration in Health Research Proposals Involving Human Participants, which outlines criteria for excellence within each proposal component and provides illustrative examples to support implementation. By enhancing the quality of sex and gender integration in proposals, the metrics will help to foster comprehensive, meaningful integration of sex and gender throughout each stage of the research process, resulting in better quality evidence to inform health care for all. PMID:28854192

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.

Adding A Spending Metric To Medicare's Value-Based Purchasing Program Rewarded Low-Quality Hospitals.

PubMed

Das, Anup; Norton, Edward C; Miller, David C; Ryan, Andrew M; Birkmeyer, John D; Chen, Lena M

2016-05-01

In fiscal year 2015 the Centers for Medicare and Medicaid Services expanded its Hospital Value-Based Purchasing program by rewarding or penalizing hospitals for their performance on both spending and quality. This represented a sharp departure from the program's original efforts to incentivize hospitals for quality alone. How this change redistributed hospital bonuses and penalties was unknown. Using data from 2,679 US hospitals that participated in the program in fiscal years 2014 and 2015, we found that the new emphasis on spending rewarded not only low-spending hospitals but some low-quality hospitals as well. Thirty-eight percent of low-spending hospitals received bonuses in fiscal year 2014, compared to 100 percent in fiscal year 2015. However, low-quality hospitals also began to receive bonuses (0 percent in fiscal year 2014 compared to 17 percent in 2015). All high-quality hospitals received bonuses in both years. The Centers for Medicare and Medicaid Services should consider incorporating a minimum quality threshold into the Hospital Value-Based Purchasing program to avoid rewarding low-quality, low-spending hospitals. Project HOPE—The People-to-People Health Foundation, Inc.

Turbulence Hazard Metric Based on Peak Accelerations for Jetliner Passengers

NASA Technical Reports Server (NTRS)

Stewart, Eric C.

2005-01-01

Calculations are made of the approximate hazard due to peak normal accelerations of an airplane flying through a simulated vertical wind field associated with a convective frontal system. The calculations are based on a hazard metric developed from a systematic application of a generic math model to 1-cosine discrete gusts of various amplitudes and gust lengths. The math model simulates the three degree-of- freedom longitudinal rigid body motion to vertical gusts and includes (1) fuselage flexibility, (2) the lag in the downwash from the wing to the tail, (3) gradual lift effects, (4) a simplified autopilot, and (5) motion of an unrestrained passenger in the rear cabin. Airplane and passenger response contours are calculated for a matrix of gust amplitudes and gust lengths. The airplane response contours are used to develop an approximate hazard metric of peak normal accelerations as a function of gust amplitude and gust length. The hazard metric is then applied to a two-dimensional simulated vertical wind field of a convective frontal system. The variations of the hazard metric with gust length and airplane heading are demonstrated.

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

The software product assurance metrics study: JPL's software systems quality and productivity

NASA Technical Reports Server (NTRS)

Bush, Marilyn W.

1989-01-01

The findings are reported of the Jet Propulsion Laboratory (JPL)/Software Product Assurance (SPA) Metrics Study, conducted as part of a larger JPL effort to improve software quality and productivity. Until recently, no comprehensive data had been assembled on how JPL manages and develops software-intensive systems. The first objective was to collect data on software development from as many projects and for as many years as possible. Results from five projects are discussed. These results reflect 15 years of JPL software development, representing over 100 data points (systems and subsystems), over a third of a billion dollars, over four million lines of code and 28,000 person months. Analysis of this data provides a benchmark for gauging the effectiveness of past, present and future software development work. In addition, the study is meant to encourage projects to record existing metrics data and to gather future data. The SPA long term goal is to integrate the collection of historical data and ongoing project data with future project estimations.

SU-F-T-600: Influence of Acuros XB and AAA Dose Calculation Algorithms On Plan Quality Metrics and Normal Lung Doses in Lung SBRT

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

Yaparpalvi, R; Mynampati, D; Kuo, H

Purpose: To study the influence of superposition-beam model (AAA) and determinant-photon transport-solver (Acuros XB) dose calculation algorithms on the treatment plan quality metrics and on normal lung dose in Lung SBRT. Methods: Treatment plans of 10 Lung SBRT patients were randomly selected. Patients were prescribed to a total dose of 50-54Gy in 3–5 fractions (10?5 or 18?3). Doses were optimized accomplished with 6-MV using 2-arcs (VMAT). Doses were calculated using AAA algorithm with heterogeneity correction. For each plan, plan quality metrics in the categories- coverage, homogeneity, conformity and gradient were quantified. Repeat dosimetry for these AAA treatment plans was performedmore » using AXB algorithm with heterogeneity correction for same beam and MU parameters. Plan quality metrics were again evaluated and compared with AAA plan metrics. For normal lung dose, V{sub 20} and V{sub 5} to (Total lung- GTV) were evaluated. Results: The results are summarized in Supplemental Table 1. PTV volume was mean 11.4 (±3.3) cm{sup 3}. Comparing RTOG 0813 protocol criteria for conformality, AXB plans yielded on average, similar PITV ratio (individual PITV ratio differences varied from −9 to +15%), reduced target coverage (−1.6%) and increased R50% (+2.6%). Comparing normal lung doses, the lung V{sub 20} (+3.1%) and V{sub 5} (+1.5%) were slightly higher for AXB plans compared to AAA plans. High-dose spillage ((V105%PD - PTV)/ PTV) was slightly lower for AXB plans but the % low dose spillage (D2cm) was similar between the two calculation algorithms. Conclusion: AAA algorithm overestimates lung target dose. Routinely adapting to AXB for dose calculations in Lung SBRT planning may improve dose calculation accuracy, as AXB based calculations have been shown to be closer to Monte Carlo based dose predictions in accuracy and with relatively faster computational time. For clinical practice, revisiting dose-fractionation in Lung SBRT to correct for dose

Automating Software Design Metrics.

DTIC Science & Technology

1984-02-01

INTRODUCTION 1 ", ... 0..1 1.2 HISTORICAL PERSPECTIVE High quality software is of interest to both the software engineering com- munity and its users. As...contributions of many other software engineering efforts, most notably [MCC 77] and [Boe 83b], which have defined and refined a framework for quantifying...AUTOMATION OF DESIGN METRICS Software metrics can be useful within the context of an integrated soft- ware engineering environment. The purpose of this

NMF-Based Image Quality Assessment Using Extreme Learning Machine.

PubMed

Wang, Shuigen; Deng, Chenwei; Lin, Weisi; Huang, Guang-Bin; Zhao, Baojun

2017-01-01

Numerous state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage process: distortion description followed by distortion effects pooling. As for the first stage, the distortion descriptors or measurements are expected to be effective representatives of human visual variations, while the second stage should well express the relationship among quality descriptors and the perceptual visual quality. However, most of the existing quality descriptors (e.g., luminance, contrast, and gradient) do not seem to be consistent with human perception, and the effects pooling is often done in ad-hoc ways. In this paper, we propose a novel full-reference IQA metric. It applies non-negative matrix factorization (NMF) to measure image degradations by making use of the parts-based representation of NMF. On the other hand, a new machine learning technique [extreme learning machine (ELM)] is employed to address the limitations of the existing pooling techniques. Compared with neural networks and support vector regression, ELM can achieve higher learning accuracy with faster learning speed. Extensive experimental results demonstrate that the proposed metric has better performance and lower computational complexity in comparison with the relevant state-of-the-art approaches.

Coverage Metrics for Requirements-Based Testing: Evaluation of Effectiveness

NASA Technical Reports Server (NTRS)

Staats, Matt; Whalen, Michael W.; Heindahl, Mats P. E.; Rajan, Ajitha

2010-01-01

In black-box testing, the tester creates a set of tests to exercise a system under test without regard to the internal structure of the system. Generally, no objective metric is used to measure the adequacy of black-box tests. In recent work, we have proposed three requirements coverage metrics, allowing testers to objectively measure the adequacy of a black-box test suite with respect to a set of requirements formalized as Linear Temporal Logic (LTL) properties. In this report, we evaluate the effectiveness of these coverage metrics with respect to fault finding. Specifically, we conduct an empirical study to investigate two questions: (1) do test suites satisfying a requirements coverage metric provide better fault finding than randomly generated test suites of approximately the same size?, and (2) do test suites satisfying a more rigorous requirements coverage metric provide better fault finding than test suites satisfying a less rigorous requirements coverage metric? Our results indicate (1) only one coverage metric proposed -- Unique First Cause (UFC) coverage -- is sufficiently rigorous to ensure test suites satisfying the metric outperform randomly generated test suites of similar size and (2) that test suites satisfying more rigorous coverage metrics provide better fault finding than test suites satisfying less rigorous coverage metrics.

Grading the Metrics: Performance-Based Funding in the Florida State University System

ERIC Educational Resources Information Center

Cornelius, Luke M.; Cavanaugh, Terence W.

2016-01-01

A policy analysis of Florida's 10-factor Performance-Based Funding system for state universities. The focus of the article is on the system of performance metrics developed by the state Board of Governors and their impact on institutions and their missions. The paper also discusses problems and issues with the metrics, their ongoing evolution, and…

Requirement Metrics for Risk Identification

NASA Technical Reports Server (NTRS)

Hammer, Theodore; Huffman, Lenore; Wilson, William; Rosenberg, Linda; Hyatt, Lawrence

1996-01-01

The Software Assurance Technology Center (SATC) is part of the Office of Mission Assurance of the Goddard Space Flight Center (GSFC). The SATC's mission is to assist National Aeronautics and Space Administration (NASA) projects to improve the quality of software which they acquire or develop. The SATC's efforts are currently focused on the development and use of metric methodologies and tools that identify and assess risks associated with software performance and scheduled delivery. This starts at the requirements phase, where the SATC, in conjunction with software projects at GSFC and other NASA centers is working to identify tools and metric methodologies to assist project managers in identifying and mitigating risks. This paper discusses requirement metrics currently being used at NASA in a collaborative effort between the SATC and the Quality Assurance Office at GSFC to utilize the information available through the application of requirements management tools.

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…

WATER QUALITY VULNERABILITY IN THE OZARKS USING LANDSCAPE ECOLOGY METRICS: UPPER WHITE RIVER BROWSER (V2.0)

EPA Science Inventory

The principal focus of this project is the mapping and interpretation of landscape scale (i.e., broad scale) ecological metrics among contributing watersheds of the Upper White River, and the development of geospatial models of water quality vulnerability for several suspected no...

An Opportunistic Routing Mechanism Combined with Long-Term and Short-Term Metrics for WMN

PubMed Central

Piao, Xianglan; Qiu, Tie

2014-01-01

WMN (wireless mesh network) is a useful wireless multihop network with tremendous research value. The routing strategy decides the performance of network and the quality of transmission. A good routing algorithm will use the whole bandwidth of network and assure the quality of service of traffic. Since the routing metric ETX (expected transmission count) does not assure good quality of wireless links, to improve the routing performance, an opportunistic routing mechanism combined with long-term and short-term metrics for WMN based on OLSR (optimized link state routing) and ETX is proposed in this paper. This mechanism always chooses the highest throughput links to improve the performance of routing over WMN and then reduces the energy consumption of mesh routers. The simulations and analyses show that the opportunistic routing mechanism is better than the mechanism with the metric of ETX. PMID:25250379

An opportunistic routing mechanism combined with long-term and short-term metrics for WMN.

PubMed

Sun, Weifeng; Wang, Haotian; Piao, Xianglan; Qiu, Tie

2014-01-01

WMN (wireless mesh network) is a useful wireless multihop network with tremendous research value. The routing strategy decides the performance of network and the quality of transmission. A good routing algorithm will use the whole bandwidth of network and assure the quality of service of traffic. Since the routing metric ETX (expected transmission count) does not assure good quality of wireless links, to improve the routing performance, an opportunistic routing mechanism combined with long-term and short-term metrics for WMN based on OLSR (optimized link state routing) and ETX is proposed in this paper. This mechanism always chooses the highest throughput links to improve the performance of routing over WMN and then reduces the energy consumption of mesh routers. The simulations and analyses show that the opportunistic routing mechanism is better than the mechanism with the metric of ETX.

Promotion of Neurointervention to International Journal Based on Journal Metrics

PubMed Central

2016-01-01

Purpose The aim is to provide evidence of the internationalization of Neurointervention based on journal metrics for articles published from 2011 to 2015. Materials and Methods The following metrics and data were collected and analyzed with descriptive statistics: number of citable and non-citable articles; number of research articles (original papers) supported by grants; editorial board members' countries; authors' countries; citing authors' countries; source title of citing articles; two-year impact factor; total citations; and Hirsch index (h-index). Data were retrieved and analyzed from the journal homepage and Web of Science Core Collection in January 24, 2016. Results There were 80 citable and eight non-citable articles from 2011 to 2015. Out of 31 original articles, nine had research funds (29.0%). Editorial board members are from five countries. The authors are from six countries. The top-ranking countries of citing authors were USA, Korea, and China. The two-year impact factors were 1.125, 0.923, and 0.931 from 2013 to 2015. H-index was 7. Conclusion It was possible to confirm the internationalization of Neurointervention based on journal metrics. New digital standards should be adopted for more rapid dissemination of journal content. PMID:26958406

A method for the use of landscape metrics in freshwater research and management

USGS Publications Warehouse

Kearns, F.R.; Kelly, N.M.; Carter, J.L.; Resh, V.H.

2005-01-01

Freshwater research and management efforts could be greatly enhanced by a better understanding of the relationship between landscape-scale factors and water quality indicators. This is particularly true in urban areas, where land transformation impacts stream systems at a variety of scales. Despite advances in landscape quantification methods, several studies attempting to elucidate the relationship between land use/land cover (LULC) and water quality have resulted in mixed conclusions. However, these studies have largely relied on compositional landscape metrics. For urban and urbanizing watersheds in particular, the use of metrics that capture spatial pattern may further aid in distinguishing the effects of various urban growth patterns, as well as exploring the interplay between environmental and socioeconomic variables. However, to be truly useful for freshwater applications, pattern metrics must be optimized based on characteristic watershed properties and common water quality point sampling methods. Using a freely available LULC data set for the Santa Clara Basin, California, USA, we quantified landscape composition and configuration for subwatershed areas upstream of individual sampling sites, reducing the number of metrics based on: (1) sensitivity to changes in extent and (2) redundancy, as determined by a multivariate factor analysis. The first two factors, interpreted as (1) patch density and distribution and (2) patch shape and landscape subdivision, explained approximately 85% of the variation in the data set, and are highly reflective of the heterogeneous urban development pattern found in the study area. Although offering slightly less explanatory power, compositional metrics can provide important contextual information. ?? Springer 2005.

No-Reference Video Quality Assessment Based on Statistical Analysis in 3D-DCT Domain.

PubMed

Li, Xuelong; Guo, Qun; Lu, Xiaoqiang

2016-05-13

It is an important task to design models for universal no-reference video quality assessment (NR-VQA) in multiple video processing and computer vision applications. However, most existing NR-VQA metrics are designed for specific distortion types which are not often aware in practical applications. A further deficiency is that the spatial and temporal information of videos is hardly considered simultaneously. In this paper, we propose a new NR-VQA metric based on the spatiotemporal natural video statistics (NVS) in 3D discrete cosine transform (3D-DCT) domain. In the proposed method, a set of features are firstly extracted based on the statistical analysis of 3D-DCT coefficients to characterize the spatiotemporal statistics of videos in different views. These features are used to predict the perceived video quality via the efficient linear support vector regression (SVR) model afterwards. The contributions of this paper are: 1) we explore the spatiotemporal statistics of videos in 3DDCT domain which has the inherent spatiotemporal encoding advantage over other widely used 2D transformations; 2) we extract a small set of simple but effective statistical features for video visual quality prediction; 3) the proposed method is universal for multiple types of distortions and robust to different databases. The proposed method is tested on four widely used video databases. Extensive experimental results demonstrate that the proposed method is competitive with the state-of-art NR-VQA metrics and the top-performing FR-VQA and RR-VQA metrics.

A priori discretization quality metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan; Craig, James; Shafii, Mahyar; Basu, Nandita

2016-04-01

In distributed hydrologic modelling, a watershed is treated as a set of small homogeneous units that address the spatial heterogeneity of the watershed being simulated. The ability of models to reproduce observed spatial patterns firstly depends on the spatial discretization, which is the process of defining homogeneous units in the form of grid cells, subwatersheds, or hydrologic response units etc. It is common for hydrologic modelling studies to simply adopt a nominal or default discretization strategy without formally assessing alternative discretization levels. This approach lacks formal justifications and is thus problematic. More formalized discretization strategies are either a priori or a posteriori with respect to building and running a hydrologic simulation model. A posteriori approaches tend to be ad-hoc and compare model calibration and/or validation performance under various watershed discretizations. The construction and calibration of multiple versions of a distributed model can become a seriously limiting computational burden. Current a priori approaches are more formalized and compare overall heterogeneity statistics of dominant variables between candidate discretization schemes and input data or reference zones. While a priori approaches are efficient and do not require running a hydrologic model, they do not fully investigate the internal spatial pattern changes of variables of interest. Furthermore, the existing a priori approaches focus on landscape and soil data and do not assess impacts of discretization on stream channel definition even though its significance has been noted by numerous studies. The primary goals of this study are to (1) introduce new a priori discretization quality metrics considering the spatial pattern changes of model input data; (2) introduce a two-step discretization decision-making approach to compress extreme errors and meet user-specified discretization expectations through non-uniform discretization threshold

RNA-SeQC: RNA-seq metrics for quality control and process optimization.

PubMed

DeLuca, David S; Levin, Joshua Z; Sivachenko, Andrey; Fennell, Timothy; Nazaire, Marc-Danie; Williams, Chris; Reich, Michael; Winckler, Wendy; Getz, Gad

2012-06-01

RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-wide characterization of cellular activity. Assessment of sequencing performance and library quality is critical to the interpretation of RNA-seq data, yet few tools exist to address this issue. We introduce RNA-SeQC, a program which provides key measures of data quality. These metrics include yield, alignment and duplication rates; GC bias, rRNA content, regions of alignment (exon, intron and intragenic), continuity of coverage, 3'/5' bias and count of detectable transcripts, among others. The software provides multi-sample evaluation of library construction protocols, input materials and other experimental parameters. The modularity of the software enables pipeline integration and the routine monitoring of key measures of data quality such as the number of alignable reads, duplication rates and rRNA contamination. RNA-SeQC allows investigators to make informed decisions about sample inclusion in downstream analysis. In summary, RNA-SeQC provides quality control measures critical to experiment design, process optimization and downstream computational analysis. See www.genepattern.org to run online, or www.broadinstitute.org/rna-seqc/ for a command line tool.

Metrics and the effective computational scientist: process, quality and communication.

PubMed

Baldwin, Eric T

2012-09-01

Recent treatments of computational knowledge worker productivity have focused upon the value the discipline brings to drug discovery using positive anecdotes. While this big picture approach provides important validation of the contributions of these knowledge workers, the impact accounts do not provide the granular detail that can help individuals and teams perform better. I suggest balancing the impact-focus with quantitative measures that can inform the development of scientists. Measuring the quality of work, analyzing and improving processes, and the critical evaluation of communication can provide immediate performance feedback. The introduction of quantitative measures can complement the longer term reporting of impacts on drug discovery. These metric data can document effectiveness trends and can provide a stronger foundation for the impact dialogue. Copyright © 2012 Elsevier Ltd. All rights reserved.

Simulation of devices mobility to estimate wireless channel quality metrics in 5G networks

NASA Astrophysics Data System (ADS)

Orlov, Yu.; Fedorov, S.; Samuylov, A.; Gaidamaka, Yu.; Molchanov, D.

2017-07-01

The problem of channel quality estimation for devices in a wireless 5G network is formulated. As a performance metrics of interest we choose the signal-to-interference-plus-noise ratio, which depends essentially on the distance between the communicating devices. A model with a plurality of moving devices in a bounded three-dimensional space and a simulation algorithm to determine the distances between the devices for a given motion model are devised.

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

A laser beam quality definition based on induced temperature rise.

PubMed

Miller, Harold C

2012-12-17

Laser beam quality metrics like M(2) can be used to describe the spot sizes and propagation behavior of a wide variety of non-ideal laser beams. However, for beams that have been diffracted by limiting apertures in the near-field, or those with unusual near-field profiles, the conventional metrics can lead to an inconsistent or incomplete description of far-field performance. This paper motivates an alternative laser beam quality definition that can be used with any beam. The approach uses a consideration of the intrinsic ability of a laser beam profile to heat a material. Comparisons are made with conventional beam quality metrics. An analysis on an asymmetric Gaussian beam is used to establish a connection with the invariant beam propagation ratio.

Magic bases, metric ansaetze and generalized graph theories in the Virasoro master equation

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

Halpern, M.B.; Obers, N.A.

1991-11-15

The authors define a class of magic Lie group bases in which the Virasoro master equation admits a class of simple metric ansaetze (g{sub metric}), whose structure is visible in the high-level expansion. When a magic basis is real on compact g, the corresponding g{sub metric} is a large system of unitary, generically irrational conformal field theories. Examples in this class include the graph-theory ansatz SO(n){sub diag} in the Cartesian basis of So(n) and the ansatz SU(n){sub metric} in the Pauli-like basis of SU(n). A new phenomenon is observed in the high-level comparison of SU(n){sub metric}: Due to the trigonometricmore » structure constants of the Pauli-like basis, irrational central charge is clearly visible at finite order of the expansion. They also define the sine-area graphs of SU(n), which label the conformal field theories of SU(n){sub metric} and note that, in a similar fashion, each magic basis of g defines a generalize graph theory on g which labels the conformal field theories of g{sub metric}.« less

A Single Conjunction Risk Assessment Metric: the F-Value

NASA Technical Reports Server (NTRS)

Frigm, Ryan Clayton; Newman, Lauri K.

2009-01-01

The Conjunction Assessment Team at NASA Goddard Space Flight Center provides conjunction risk assessment for many NASA robotic missions. These risk assessments are based on several figures of merit, such as miss distance, probability of collision, and orbit determination solution quality. However, these individual metrics do not singly capture the overall risk associated with a conjunction, making it difficult for someone without this complete understanding to take action, such as an avoidance maneuver. The goal of this analysis is to introduce a single risk index metric that can easily convey the level of risk without all of the technical details. The proposed index is called the conjunction "F-value." This paper presents the concept of the F-value and the tuning of the metric for use in routine Conjunction Assessment operations.

Usability Evaluations of a Wearable Inertial Sensing System and Quality of Movement Metrics for Stroke Survivors by Care Professionals.

PubMed

Klaassen, Bart; van Beijnum, Bert-Jan F; Held, Jeremia P; Reenalda, Jasper; van Meulen, Fokke B; Veltink, Peter H; Hermens, Hermie J

2017-01-01

Inertial motion capture systems are used in many applications such as measuring the movement quality in stroke survivors. The absence of clinical effectiveness and usability evidence in these assistive technologies into rehabilitation has delayed the transition of research into clinical practice. Recently, a new inertial motion capture system was developed in a project, called INTERACTION, to objectively measure the quality of movement (QoM) in stroke survivors during daily-life activity. With INTERACTION, we are to be able to investigate into what happens with patients after discharge from the hospital. Resulting QoM metrics, where a metric is defined as a measure of some property, are subsequently presented to care professionals. Metrics include for example: reaching distance, walking speed, and hand distribution plots. The latter shows a density plot of the hand position in the transversal plane. The objective of this study is to investigate the opinions of care professionals in using these metrics obtained from INTERACTION and its usability. By means of a semi-structured interview, guided by a presentation, presenting two patient reports. Each report includes several QoM metric (like reaching distance, hand position density plots, shoulder abduction) results obtained during daily-life measurements and in clinic and were evaluated by care professionals not related to the project. The results were compared with care professionals involved within the INTERACTION project. Furthermore, two questionnaires (5-point Likert and open questionnaire) were handed over to rate the usability of the metrics and to investigate if they would like such a system in their clinic. Eleven interviews were conducted, where each interview included either two or three care professionals as a group, in Switzerland and The Netherlands. Evaluation of the case reports (CRs) by participants and INTERACTION members showed a high correlation for both lower and upper extremity metrics

Changing to the Metric System.

ERIC Educational Resources Information Center

Chambers, Donald L.; Dowling, Kenneth W.

This report examines educational aspects of the conversion to the metric system of measurement in the United States. Statements of positions on metrication and basic mathematical skills are given from various groups. Base units, symbols, prefixes, and style of the metric system are outlined. Guidelines for teaching metric concepts are given,…

Comparing image quality of print-on-demand books and photobooks from web-based vendors

NASA Astrophysics Data System (ADS)

Phillips, Jonathan; Bajorski, Peter; Burns, Peter; Fredericks, Erin; Rosen, Mitchell

2010-01-01

Because of the emergence of e-commerce and developments in print engines designed for economical output of very short runs, there are increased business opportunities and consumer options for print-on-demand books and photobooks. The current state of these printing modes allows for direct uploading of book files via the web, printing on nonoffset printers, and distributing by standard parcel or mail delivery services. The goal of this research is to assess the image quality of print-on-demand books and photobooks produced by various Web-based vendors and to identify correlations between psychophysical results and objective metrics. Six vendors were identified for one-off (single-copy) print-on-demand books, and seven vendors were identified for photobooks. Participants rank ordered overall quality of a subset of individual pages from each book, where the pages included text, photographs, or a combination of the two. Observers also reported overall quality ratings and price estimates for the bound books. Objective metrics of color gamut, color accuracy, accuracy of International Color Consortium profile usage, eye-weighted root mean square L*, and cascaded modulation transfer acutance were obtained and compared to the observer responses. We introduce some new methods for normalizing data as well as for strengthening the statistical significance of the results. Our approach includes the use of latent mixed-effect models. We found statistically significant correlation with overall image quality and some of the spatial metrics, but correlations between psychophysical results and other objective metrics were weak or nonexistent. Strong correlation was found between psychophysical results of overall quality assessment and estimated price associated with quality. The photobook set of vendors reached higher image-quality ratings than the set of print-on-demand vendors. However, the photobook set had higher image-quality variability.

Measuring economic complexity of countries and products: which metric to use?

NASA Astrophysics Data System (ADS)

Mariani, Manuel Sebastian; Vidmer, Alexandre; Medo, Matsúš; Zhang, Yi-Cheng

2015-11-01

Evaluating the economies of countries and their relations with products in the global market is a central problem in economics, with far-reaching implications to our theoretical understanding of the international trade as well as to practical applications, such as policy making and financial investment planning. The recent Economic Complexity approach aims to quantify the competitiveness of countries and the quality of the exported products based on the empirical observation that the most competitive countries have diversified exports, whereas developing countries only export few low quality products - typically those exported by many other countries. Two different metrics, Fitness-Complexity and the Method of Reflections, have been proposed to measure country and product score in the Economic Complexity framework. We use international trade data and a recent ranking evaluation measure to quantitatively compare the ability of the two metrics to rank countries and products according to their importance in the network. The results show that the Fitness-Complexity metric outperforms the Method of Reflections in both the ranking of products and the ranking of countries. We also investigate a generalization of the Fitness-Complexity metric and show that it can produce improved rankings provided that the input data are reliable.

Fish community-based measures of estuarine ecological quality and pressure-impact relationships

NASA Astrophysics Data System (ADS)

Fonseca, Vanessa F.; Vasconcelos, Rita P.; Gamito, Rita; Pasquaud, Stéphanie; Gonçalves, Catarina I.; Costa, José L.; Costa, Maria J.; Cabral, Henrique N.

2013-12-01

Community-based responses of fish fauna to anthropogenic pressures have been extensively used to assess the ecological quality of estuarine ecosystems. Several methodologies have been developed recently combining metrics reflecting community structure and function. A fish community facing significant environmental disturbances will be characterized by a simplified structure, with lower diversity and complexity. However, estuaries are naturally dynamic ecosystems exposed to numerous human pressures, making it difficult to distinguish between natural and anthropogenic-induced changes to the biological community. In the present work, the variability of several fish metrics was assessed in relation to different pressures in estuarine sites. The response of a multimetric index (Estuarine Fish Assessment Index) was also analysed. Overall, fish metrics and the multimetric index signalled anthropogenic stress, particularly environmental chemical pollution. The fish assemblage associated with this type of pressure was characterized by lower species diversity, lower number of functional guilds, lower abundance of marine migrants and of piscivorous individuals, and higher abundance of estuarine resident species. A decreased ecological quality status, based on the EFAI, was also determined for sites associated with this pressure group. Ultimately, the definition of each pressure groups favoured a stressor-specific analysis, evidencing pressure patterns and accounting for multiple factors in a highly dynamic environment.

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.

Development of a clinician reputation metric to identify appropriate problem-medication pairs in a crowdsourced knowledge base.

PubMed

McCoy, Allison B; Wright, Adam; Rogith, Deevakar; Fathiamini, Safa; Ottenbacher, Allison J; Sittig, Dean F

2014-04-01

Correlation of data within electronic health records is necessary for implementation of various clinical decision support functions, including patient summarization. A key type of correlation is linking medications to clinical problems; while some databases of problem-medication links are available, they are not robust and depend on problems and medications being encoded in particular terminologies. Crowdsourcing represents one approach to generating robust knowledge bases across a variety of terminologies, but more sophisticated approaches are necessary to improve accuracy and reduce manual data review requirements. We sought to develop and evaluate a clinician reputation metric to facilitate the identification of appropriate problem-medication pairs through crowdsourcing without requiring extensive manual review. We retrieved medications from our clinical data warehouse that had been prescribed and manually linked to one or more problems by clinicians during e-prescribing between June 1, 2010 and May 31, 2011. We identified measures likely to be associated with the percentage of accurate problem-medication links made by clinicians. Using logistic regression, we created a metric for identifying clinicians who had made greater than or equal to 95% appropriate links. We evaluated the accuracy of the approach by comparing links made by those physicians identified as having appropriate links to a previously manually validated subset of problem-medication pairs. Of 867 clinicians who asserted a total of 237,748 problem-medication links during the study period, 125 had a reputation metric that predicted the percentage of appropriate links greater than or equal to 95%. These clinicians asserted a total of 2464 linked problem-medication pairs (983 distinct pairs). Compared to a previously validated set of problem-medication pairs, the reputation metric achieved a specificity of 99.5% and marginally improved the sensitivity of previously described knowledge bases. A

Development of a clinician reputation metric to identify appropriate problem-medication pairs in a crowdsourced knowledge base

PubMed Central

McCoy, Allison B.; Wright, Adam; Rogith, Deevakar; Fathiamini, Safa; Ottenbacher, Allison J.; Sittig, Dean F.

2014-01-01

previously described knowledge bases. Conclusion A reputation metric may be a valuable measure for identifying high quality clinician-entered, crowdsourced data. PMID:24321170

"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.

Multidisciplinary life cycle metrics and tools for green buildings.

PubMed

Helgeson, Jennifer F; Lippiatt, Barbara C

2009-07-01

Building sector stakeholders need compelling metrics, tools, data, and case studies to support major investments in sustainable technologies. Proponents of green building widely claim that buildings integrating sustainable technologies are cost effective, but often these claims are based on incomplete, anecdotal evidence that is difficult to reproduce and defend. The claims suffer from 2 main weaknesses: 1) buildings on which claims are based are not necessarily "green" in a science-based, life cycle assessment (LCA) sense and 2) measures of cost effectiveness often are not based on standard methods for measuring economic worth. Yet, the building industry demands compelling metrics to justify sustainable building designs. The problem is hard to solve because, until now, neither methods nor robust data supporting defensible business cases were available. The US National Institute of Standards and Technology (NIST) Building and Fire Research Laboratory is beginning to address these needs by developing metrics and tools for assessing the life cycle economic and environmental performance of buildings. Economic performance is measured with the use of standard life cycle costing methods. Environmental performance is measured by LCA methods that assess the "carbon footprint" of buildings, as well as 11 other sustainability metrics, including fossil fuel depletion, smog formation, water use, habitat alteration, indoor air quality, and effects on human health. Carbon efficiency ratios and other eco-efficiency metrics are established to yield science-based measures of the relative worth, or "business cases," for green buildings. Here, the approach is illustrated through a realistic building case study focused on different heating, ventilation, air conditioning technology energy efficiency. Additionally, the evolution of the Building for Environmental and Economic Sustainability multidisciplinary team and future plans in this area are described.

Comparison of the spatial and temporal variability of macroinvertebrate and periphyton-based metrics in a macrophyte-dominated shallow lake

NASA Astrophysics Data System (ADS)

Zhang, Lulu; Liu, Jingling; Li, Yi

2015-03-01

The influence of spatial differences, which are caused by different anthropogenic disturbances, and temporal changes, which are caused by natural conditions, on macroinvertebrates with periphyton communities in Baiyangdian Lake was compared. Periphyton and macrobenthos assemblage samples were simultaneously collected on four occasions during 2009 and 2010. Based on the physical and chemical attributes in the water and sediment, the 8 sampling sites can be divided into 5 habitat types by using cluster analysis. According to coefficients variation analysis (CV), three primary conclusions can be drawn: (1) the metrics of Hilsenhoff Biotic Index (HBI), Percent Tolerant Taxa (PTT), Percent dominant taxon (PDT), and community loss index (CLI), based on macroinvertebrates, and the metrics of algal density (AD), the proportion of chlorophyta (CHL), and the proportion of cyanophyta (CYA), based on periphytons, were mostly constant throughout our study; (2) in terms of spatial variation, the CV values in the macroinvertebratebased metrics were lower than the CV values in the periphyton-based metrics, and these findings may be caused by the effects of changes in environmental factors; whereas, the CV values in the macroinvertebrate-based metrics were higher than those in the periphyton-based metrics, and these results may be linked to the influences of phenology and life history patterns of the macroinvertebrate individuals; and (3) the CV values for the functionalbased metrics were higher than those for the structuralbased metrics. Therefore, spatial and temporal variation for metrics should be considered when assessing applying the biometrics.

Objective assessment based on motion-related metrics and technical performance in laparoscopic suturing.

PubMed

Sánchez-Margallo, Juan A; Sánchez-Margallo, Francisco M; Oropesa, Ignacio; Enciso, Silvia; Gómez, Enrique J

2017-02-01

The aim of this study is to present the construct and concurrent validity of a motion-tracking method of laparoscopic instruments based on an optical pose tracker and determine its feasibility as an objective assessment tool of psychomotor skills during laparoscopic suturing. A group of novice ([Formula: see text] laparoscopic procedures), intermediate (11-100 laparoscopic procedures) and experienced ([Formula: see text] laparoscopic procedures) surgeons performed three intracorporeal sutures on an ex vivo porcine stomach. Motion analysis metrics were recorded using the proposed tracking method, which employs an optical pose tracker to determine the laparoscopic instruments' position. Construct validation was measured for all 10 metrics across the three groups and between pairs of groups. Concurrent validation was measured against a previously validated suturing checklist. Checklists were completed by two independent surgeons over blinded video recordings of the task. Eighteen novices, 15 intermediates and 11 experienced surgeons took part in this study. Execution time and path length travelled by the laparoscopic dissector presented construct validity. Experienced surgeons required significantly less time ([Formula: see text]), travelled less distance using both laparoscopic instruments ([Formula: see text]) and made more efficient use of the work space ([Formula: see text]) compared with novice and intermediate surgeons. Concurrent validation showed strong correlation between both the execution time and path length and the checklist score ([Formula: see text] and [Formula: see text], [Formula: see text]). The suturing performance was successfully assessed by the motion analysis method. Construct and concurrent validity of the motion-based assessment method has been demonstrated for the execution time and path length metrics. This study demonstrates the efficacy of the presented method for objective evaluation of psychomotor skills in laparoscopic suturing

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

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

Zhang, J.; Hodge, B. M.; Florita, A.

2013-10-01

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The resultsmore » show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.« less

Validation of an image-based technique to assess the perceptual quality of clinical chest radiographs with an observer study

NASA Astrophysics Data System (ADS)

Lin, Yuan; Choudhury, Kingshuk R.; McAdams, H. Page; Foos, David H.; Samei, Ehsan

2014-03-01

We previously proposed a novel image-based quality assessment technique1 to assess the perceptual quality of clinical chest radiographs. In this paper, an observer study was designed and conducted to systematically validate this technique. Ten metrics were involved in the observer study, i.e., lung grey level, lung detail, lung noise, riblung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm-lung contrast, and subdiaphragm area. For each metric, three tasks were successively presented to the observers. In each task, six ROI images were randomly presented in a row and observers were asked to rank the images only based on a designated quality and disregard the other qualities. A range slider on the top of the images was used for observers to indicate the acceptable range based on the corresponding perceptual attribute. Five boardcertificated radiologists from Duke participated in this observer study on a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions. The observer data were analyzed in terms of the correlations between the observer ranking orders and the algorithmic ranking orders. Based on the collected acceptable ranges, quality consistency ranges were statistically derived. The observer study showed that, for each metric, the averaged ranking orders of the participated observers were strongly correlated with the algorithmic orders. For the lung grey level, the observer ranking orders completely accorded with the algorithmic ranking orders. The quality consistency ranges derived from this observer study were close to these derived from our previous study. The observer study indicates that the proposed image-based quality assessment technique provides a robust reflection of the perceptual image quality of the clinical chest radiographs. The derived quality consistency ranges can be used to automatically predict the acceptability of a clinical chest radiograph.

Hospital readiness for health information exchange: development of metrics associated with successful collaboration for quality improvement.

PubMed

Korst, Lisa M; Aydin, Carolyn E; Signer, Jordana M K; Fink, Arlene

2011-08-01

The development of readiness metrics for organizational participation in health information exchange is critical for monitoring progress toward, and achievement of, successful inter-organizational collaboration. In preparation for the development of a tool to measure readiness for data-sharing, we tested whether organizational capacities known to be related to readiness were associated with successful participation in an American data-sharing collaborative for quality improvement. Cross-sectional design, using an on-line survey of hospitals in a large, mature data-sharing collaborative organized for benchmarking and improvement in nursing care quality. Factor analysis was used to identify salient constructs, and identified factors were analyzed with respect to "successful" participation. "Success" was defined as the incorporation of comparative performance data into the hospital dashboard. The most important factor in predicting success included survey items measuring the strength of organizational leadership in fostering a culture of quality improvement (QI Leadership): (1) presence of a supportive hospital executive; (2) the extent to which a hospital values data; (3) the presence of leaders' vision for how the collaborative advances the hospital's strategic goals; (4) hospital use of the collaborative data to track quality outcomes; and (5) staff recognition of a strong mandate for collaborative participation (α=0.84, correlation with Success 0.68 [P<0.0001]). The data emphasize the importance of hospital QI Leadership in collaboratives that aim to share data for QI or safety purposes. Such metrics should prove useful in the planning and development of this complex form of inter-organizational collaboration. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Hospital readiness for health information exchange: development of metrics associated with successful collaboration for quality improvement

PubMed Central

Korst, Lisa M.; Aydin, Carolyn E.; Signer, Jordana M. K.; Fink, Arlene

2011-01-01

Objective The development of readiness metrics for organizational participation in health information exchange is critical for monitoring progress toward, and achievement of, successful inter-organizational collaboration. In preparation for the development of a tool to measure readiness for data-sharing, we tested whether organizational capacities known to be related to readiness were associated with successful participation in an American data-sharing collaborative for quality improvement. Design Cross-sectional design, using an on-line survey of hospitals in a large, mature data-sharing collaborative organized for benchmarking and improvement in nursing care quality. Measurements Factor analysis was used to identify salient constructs, and identified factors were analyzed with respect to “successful” participation. “Success” was defined as the incorporation of comparative performance data into the hospital dashboard. Results The most important factor in predicting success included survey items measuring the strength of organizational leadership in fostering a culture of quality improvement (QI Leadership): 1) presence of a supportive hospital executive; 2) the extent to which a hospital values data; 3) the presence of leaders’ vision for how the collaborative advances the hospital’s strategic goals; 4) hospital use of the collaborative data to track quality outcomes; and 5) staff recognition of a strong mandate for collaborative participation (α = 0.84, correlation with Success 0.68 [P < 0.0001]). Conclusion The data emphasize the importance of hospital QI Leadership in collaboratives that aim to share data for QI or safety purposes. Such metrics should prove useful in the planning and development of this complex form of inter-organizational collaboration. PMID:21330191

Health impact metrics for air pollution management strategies

PubMed Central

Martenies, Sheena E.; Wilkins, Donele; Batterman, Stuart A.

2015-01-01

Health impact assessments (HIAs) inform policy and decision making by providing information regarding future health concerns, and quantitative HIAs now are being used for local and urban-scale projects. HIA results can be expressed using a variety of metrics that differ in meaningful ways, and guidance is lacking with respect to best practices for the development and use of HIA metrics. This study reviews HIA metrics pertaining to air quality management and presents evaluative criteria for their selection and use. These are illustrated in a case study where PM2.5 concentrations are lowered from 10 to 8 µg/m3 in an urban area of 1.8 million people. Health impact functions are used to estimate the number of premature deaths, unscheduled hospitalizations and other morbidity outcomes. The most common metric in recent quantitative HIAs has been the number of cases of adverse outcomes avoided. Other metrics include time-based measures, e.g., disability-adjusted life years (DALYs), monetized impacts, functional-unit based measures, e.g., benefits per ton of emissions reduced, and other economic indicators, e.g., cost-benefit ratios. These metrics are evaluated by considering their comprehensiveness, the spatial and temporal resolution of the analysis, how equity considerations are facilitated, and the analysis and presentation of uncertainty. In the case study, the greatest number of avoided cases occurs for low severity morbidity outcomes, e.g., asthma exacerbations (n=28,000) and minor-restricted activity days (n=37,000); while DALYs and monetized impacts are driven by the severity, duration and value assigned to a relatively low number of premature deaths (n=190 to 230 per year). The selection of appropriate metrics depends on the problem context and boundaries, the severity of impacts, and community values regarding health. The number of avoided cases provides an estimate of the number of people affected, and monetized impacts facilitate additional economic analyses

Health impact metrics for air pollution management strategies.

PubMed

Martenies, Sheena E; Wilkins, Donele; Batterman, Stuart A

2015-12-01

Health impact assessments (HIAs) inform policy and decision making by providing information regarding future health concerns, and quantitative HIAs now are being used for local and urban-scale projects. HIA results can be expressed using a variety of metrics that differ in meaningful ways, and guidance is lacking with respect to best practices for the development and use of HIA metrics. This study reviews HIA metrics pertaining to air quality management and presents evaluative criteria for their selection and use. These are illustrated in a case study where PM2.5 concentrations are lowered from 10 to 8μg/m(3) in an urban area of 1.8 million people. Health impact functions are used to estimate the number of premature deaths, unscheduled hospitalizations and other morbidity outcomes. The most common metric in recent quantitative HIAs has been the number of cases of adverse outcomes avoided. Other metrics include time-based measures, e.g., disability-adjusted life years (DALYs), monetized impacts, functional-unit based measures, e.g., benefits per ton of emissions reduced, and other economic indicators, e.g., cost-benefit ratios. These metrics are evaluated by considering their comprehensiveness, the spatial and temporal resolution of the analysis, how equity considerations are facilitated, and the analysis and presentation of uncertainty. In the case study, the greatest number of avoided cases occurs for low severity morbidity outcomes, e.g., asthma exacerbations (n=28,000) and minor-restricted activity days (n=37,000); while DALYs and monetized impacts are driven by the severity, duration and value assigned to a relatively low number of premature deaths (n=190 to 230 per year). The selection of appropriate metrics depends on the problem context and boundaries, the severity of impacts, and community values regarding health. The number of avoided cases provides an estimate of the number of people affected, and monetized impacts facilitate additional economic analyses

A scalable kernel-based semisupervised metric learning algorithm with out-of-sample generalization ability.

PubMed

Yeung, Dit-Yan; Chang, Hong; Dai, Guang

2008-11-01

In recent years, metric learning in the semisupervised setting has aroused a lot of research interest. One type of semisupervised metric learning utilizes supervisory information in the form of pairwise similarity or dissimilarity constraints. However, most methods proposed so far are either limited to linear metric learning or unable to scale well with the data set size. In this letter, we propose a nonlinear metric learning method based on the kernel approach. By applying low-rank approximation to the kernel matrix, our method can handle significantly larger data sets. Moreover, our low-rank approximation scheme can naturally lead to out-of-sample generalization. Experiments performed on both artificial and real-world data show very promising results.

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.

The power metric: a new statistically robust enrichment-type metric for virtual screening applications with early recovery capability.

PubMed

Lopes, Julio Cesar Dias; Dos Santos, Fábio Mendes; Martins-José, Andrelly; Augustyns, Koen; De Winter, Hans

2017-01-01

A new metric for the evaluation of model performance in the field of virtual screening and quantitative structure-activity relationship applications is described. This metric has been termed the power metric and is defined as the fraction of the true positive rate divided by the sum of the true positive and false positive rates, for a given cutoff threshold. The performance of this metric is compared with alternative metrics such as the enrichment factor, the relative enrichment factor, the receiver operating curve enrichment factor, the correct classification rate, Matthews correlation coefficient and Cohen's kappa coefficient. The performance of this new metric is found to be quite robust with respect to variations in the applied cutoff threshold and ratio of the number of active compounds to the total number of compounds, and at the same time being sensitive to variations in model quality. It possesses the correct characteristics for its application in early-recognition virtual screening problems.

Relevance of motion-related assessment metrics in laparoscopic surgery.

PubMed

Oropesa, Ignacio; Chmarra, Magdalena K; Sánchez-González, Patricia; Lamata, Pablo; Rodrigues, Sharon P; Enciso, Silvia; Sánchez-Margallo, Francisco M; Jansen, Frank-Willem; Dankelman, Jenny; Gómez, Enrique J

2013-06-01

Motion metrics have become an important source of information when addressing the assessment of surgical expertise. However, their direct relationship with the different surgical skills has not been fully explored. The purpose of this study is to investigate the relevance of motion-related metrics in the evaluation processes of basic psychomotor laparoscopic skills and their correlation with the different abilities sought to measure. A framework for task definition and metric analysis is proposed. An explorative survey was first conducted with a board of experts to identify metrics to assess basic psychomotor skills. Based on the output of that survey, 3 novel tasks for surgical assessment were designed. Face and construct validation was performed, with focus on motion-related metrics. Tasks were performed by 42 participants (16 novices, 22 residents, and 4 experts). Movements of the laparoscopic instruments were registered with the TrEndo tracking system and analyzed. Time, path length, and depth showed construct validity for all 3 tasks. Motion smoothness and idle time also showed validity for tasks involving bimanual coordination and tasks requiring a more tactical approach, respectively. Additionally, motion smoothness and average speed showed a high internal consistency, proving them to be the most task-independent of all the metrics analyzed. Motion metrics are complementary and valid for assessing basic psychomotor skills, and their relevance depends on the skill being evaluated. A larger clinical implementation, combined with quality performance information, will give more insight on the relevance of the results shown in this study.

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

Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses*

PubMed Central

Rudnick, Paul A.; Clauser, Karl R.; Kilpatrick, Lisa E.; Tchekhovskoi, Dmitrii V.; Neta, Pedatsur; Blonder, Nikša; Billheimer, Dean D.; Blackman, Ronald K.; Bunk, David M.; Cardasis, Helene L.; Ham, Amy-Joan L.; Jaffe, Jacob D.; Kinsinger, Christopher R.; Mesri, Mehdi; Neubert, Thomas A.; Schilling, Birgit; Tabb, David L.; Tegeler, Tony J.; Vega-Montoto, Lorenzo; Variyath, Asokan Mulayath; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Carr, Steven A.; Fisher, Susan J.; Gibson, Bradford W.; Paulovich, Amanda G.; Regnier, Fred E.; Rodriguez, Henry; Spiegelman, Cliff; Tempst, Paul; Liebler, Daniel C.; Stein, Stephen E.

2010-01-01

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications. PMID:19837981

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.

Quality of service routing in the differentiated services framework

NASA Astrophysics Data System (ADS)

Oliveira, Marilia C.; Melo, Bruno; Quadros, Goncalo; Monteiro, Edmundo

2001-02-01

In this paper we present a quality of service routing strategy for network where traffic differentiation follows the class-based paradigm, as in the Differentiated Services framework. This routing strategy is based on a metric of quality of service. This metric represents the impact that delay and losses verified at each router in the network have in application performance. Based on this metric, it is selected a path for each class according to the class sensitivity to delay and losses. The distribution of the metric is triggered by a relative criterion with two thresholds, and the values advertised are the moving average of the last values measured.

Quality assessment of color images based on the measure of just noticeable color difference

NASA Astrophysics Data System (ADS)

Chou, Chun-Hsien; Hsu, Yun-Hsiang

2014-01-01

Accurate assessment on the quality of color images is an important step to many image processing systems that convey visual information of the reproduced images. An accurate objective image quality assessment (IQA) method is expected to give the assessment result highly agreeing with the subjective assessment. To assess the quality of color images, many approaches simply apply the metric for assessing the quality of gray scale images to each of three color channels of the color image, neglecting the correlation among three color channels. In this paper, a metric for assessing color images' quality is proposed, in which the model of variable just-noticeable color difference (VJNCD) is employed to estimate the visibility thresholds of distortion inherent in each color pixel. With the estimated visibility thresholds of distortion, the proposed metric measures the average perceptible distortion in terms of the quantized distortion according to the perceptual error map similar to that defined by National Bureau of Standards (NBS) for converting the color difference enumerated by CIEDE2000 to the objective score of perceptual quality assessment. The perceptual error map in this case is designed for each pixel according to the visibility threshold estimated by the VJNCD model. The performance of the proposed metric is verified by assessing the test images in the LIVE database, and is compared with those of many well-know IQA metrics. Experimental results indicate that the proposed metric is an effective IQA method that can accurately predict the image quality of color images in terms of the correlation between objective scores and subjective evaluation.

Future of the PCI Readmission Metric.

PubMed

Wasfy, Jason H; Yeh, Robert W

2016-03-01

Between 2013 and 2014, the Centers for Medicare and Medicaid Services and the National Cardiovascular Data Registry publically reported risk-adjusted 30-day readmission rates after percutaneous coronary intervention (PCI) as a pilot project. A key strength of this public reporting effort included risk adjustment with clinical rather than administrative data. Furthermore, because readmission after PCI is common, expensive, and preventable, this metric has substantial potential to improve quality and value in American cardiology care. Despite this, concerns about the metric exist. For example, few PCI readmissions are caused by procedural complications, limiting the extent to which improved procedural technique can reduce readmissions. Also, similar to other readmission measures, PCI readmission is associated with socioeconomic status and race. Accordingly, the metric may unfairly penalize hospitals that care for underserved patients. Perhaps in the context of these limitations, Centers for Medicare and Medicaid Services has not yet included PCI readmission among metrics that determine Medicare financial penalties. Nevertheless, provider organizations may still wish to focus on this metric to improve value for cardiology patients. PCI readmission is associated with low-risk chest discomfort and patient anxiety. Therefore, patient education, improved triage mechanisms, and improved care coordination offer opportunities to minimize PCI readmissions. Because PCI readmission is common and costly, reducing PCI readmission offers provider organizations a compelling target to improve the quality of care, and also performance in contracts involve shared financial risk. © 2016 American Heart Association, Inc.

Proposed Performance-Based Metrics for the Future Funding of Graduate Medical Education: Starting the Conversation.

PubMed

Caverzagie, Kelly J; Lane, Susan W; Sharma, Niraj; Donnelly, John; Jaeger, Jeffrey R; Laird-Fick, Heather; Moriarty, John P; Moyer, Darilyn V; Wallach, Sara L; Wardrop, Richard M; Steinmann, Alwin F

2017-12-12

Graduate medical education (GME) in the United States is financed by contributions from both federal and state entities that total over $15 billion annually. Within institutions, these funds are distributed with limited transparency to achieve ill-defined outcomes. To address this, the Institute of Medicine convened a committee on the governance and financing of GME to recommend finance reform that would promote a physician training system that meets society's current and future needs. The resulting report provided several recommendations regarding the oversight and mechanisms of GME funding, including implementation of performance-based GME payments, but did not provide specific details about the content and development of metrics for these payments. To initiate a national conversation about performance-based GME funding, the authors asked: What should GME be held accountable for in exchange for public funding? In answer to this question, the authors propose 17 potential performance-based metrics for GME funding that could inform future funding decisions. Eight of the metrics are described as exemplars to add context and to help readers obtain a deeper understanding of the inherent complexities of performance-based GME funding. The authors also describe considerations and precautions for metric implementation.

Cloud-based Computing and Applications of New Snow Metrics for Societal Benefit

NASA Astrophysics Data System (ADS)

Nolin, A. W.; Sproles, E. A.; Crumley, R. L.; Wilson, A.; Mar, E.; van de Kerk, M.; Prugh, L.

2017-12-01

Seasonal and interannual variability in snow cover affects socio-environmental systems including water resources, forest ecology, freshwater and terrestrial habitat, and winter recreation. We have developed two new seasonal snow metrics: snow cover frequency (SCF) and snow disappearance date (SDD). These metrics are calculated at 500-m resolution using NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover data (MOD10A1). SCF is the number of times snow is observed in a pixel over the user-defined observation period. SDD is the last date of observed snow in a water year. These pixel-level metrics are calculated rapidly and globally in the Google Earth Engine cloud-based environment. SCF and SDD can be interactively visualized in a map-based interface, allowing users to explore spatial and temporal snowcover patterns from 2000-present. These metrics are especially valuable in regions where snow data are sparse or non-existent. We have used these metrics in several ongoing projects. When SCF was linked with a simple hydrologic model in the La Laguna watershed in northern Chile, it successfully predicted summer low flows with a Nash-Sutcliffe value of 0.86. SCF has also been used to help explain changes in Dall sheep populations in Alaska where sheep populations are negatively impacted by late snow cover and low snowline elevation during the spring lambing season. In forest management, SCF and SDD appear to be valuable predictors of post-wildfire vegetation growth. We see a positive relationship between winter SCF and subsequent summer greening for several years post-fire. For western US winter recreation, we are exploring trends in SDD and SCF for regions where snow sports are economically important. In a world with declining snowpacks and increasing uncertainty, these metrics extend across elevations and fill data gaps to provide valuable information for decision-making. SCF and SDD are being produced so that anyone with Internet access and a Google

State of the art metrics for aspect oriented programming

NASA Astrophysics Data System (ADS)

Ghareb, Mazen Ismaeel; Allen, Gary

2018-04-01

The quality evaluation of software, e.g., defect measurement, gains significance with higher use of software applications. Metric measurements are considered as the primary indicator of imperfection prediction and software maintenance in various empirical studies of software products. However, there is no agreement on which metrics are compelling quality indicators for novel development approaches such as Aspect Oriented Programming (AOP). AOP intends to enhance programming quality, by providing new and novel constructs for the development of systems, for example, point cuts, advice and inter-type relationships. Hence, it is not evident if quality pointers for AOP can be derived from direct expansions of traditional OO measurements. Then again, investigations of AOP do regularly depend on established coupling measurements. Notwithstanding the late reception of AOP in empirical studies, coupling measurements have been adopted as useful markers of flaw inclination in this context. In this paper we will investigate the state of the art metrics for measurement of Aspect Oriented systems development.

Automated Assessment of Visual Quality of Digital Video

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Ellis, Stephen R. (Technical Monitor)

1997-01-01

The advent of widespread distribution of digital video creates a need for automated methods for evaluating visual quality of digital video. This is particularly so since most digital video is compressed using lossy methods, which involve the controlled introduction of potentially visible artifacts. Compounding the problem is the bursty nature of digital video, which requires adaptive bit allocation based on visual quality metrics. In previous work, we have developed visual quality metrics for evaluating, controlling, and optimizing the quality of compressed still images[1-4]. These metrics incorporate simplified models of human visual sensitivity to spatial and chromatic visual signals. The challenge of video quality metrics is to extend these simplified models to temporal signals as well. In this presentation I will discuss a number of the issues that must be resolved in the design of effective video quality metrics. Among these are spatial, temporal, and chromatic sensitivity and their interactions, visual masking, and implementation complexity. I will also touch on the question of how to evaluate the performance of these metrics.

MO-A-16A-01: QA Procedures and Metrics: In Search of QA Usability

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

Sathiaseelan, V; Thomadsen, B

Radiation therapy has undergone considerable changes in the past two decades with a surge of new technology and treatment delivery methods. The complexity of radiation therapy treatments has increased and there has been increased awareness and publicity about the associated risks. In response, there has been proliferation of guidelines for medical physicists to adopt to ensure that treatments are delivered safely. Task Group recommendations are copious, and clinical physicists' hours are longer, stretched to various degrees between site planning and management, IT support, physics QA, and treatment planning responsibilities.Radiation oncology has many quality control practices in place to ensure themore » delivery of high-quality, safe treatments. Incident reporting systems have been developed to collect statistics about near miss events at many radiation oncology centers. However, tools are lacking to assess the impact of these various control measures. A recent effort to address this shortcoming is the work of Ford et al (2012) who recently published a methodology enumerating quality control quantification for measuring the effectiveness of safety barriers. Over 4000 near-miss incidents reported from 2 academic radiation oncology clinics were analyzed using quality control quantification, and a profile of the most effective quality control measures (metrics) was identified.There is a critical need to identify a QA metric to help the busy clinical physicists to focus their limited time and resources most effectively in order to minimize or eliminate errors in the radiation treatment delivery processes. In this symposium the usefulness of workflows and QA metrics to assure safe and high quality patient care will be explored.Two presentations will be given:Quality Metrics and Risk Management with High Risk Radiation Oncology ProceduresStrategies and metrics for quality management in the TG-100 Era Learning Objectives: Provide an overview and the need for QA

Determination of a Screening Metric for High Diversity DNA Libraries.

PubMed

Guido, Nicholas J; Handerson, Steven; Joseph, Elaine M; Leake, Devin; Kung, Li A

2016-01-01

The fields of antibody engineering, enzyme optimization and pathway construction rely increasingly on screening complex variant DNA libraries. These highly diverse libraries allow researchers to sample a maximized sequence space; and therefore, more rapidly identify proteins with significantly improved activity. The current state of the art in synthetic biology allows for libraries with billions of variants, pushing the limits of researchers' ability to qualify libraries for screening by measuring the traditional quality metrics of fidelity and diversity of variants. Instead, when screening variant libraries, researchers typically use a generic, and often insufficient, oversampling rate based on a common rule-of-thumb. We have developed methods to calculate a library-specific oversampling metric, based on fidelity, diversity, and representation of variants, which informs researchers, prior to screening the library, of the amount of oversampling required to ensure that the desired fraction of variant molecules will be sampled. To derive this oversampling metric, we developed a novel alignment tool to efficiently measure frequency counts of individual nucleotide variant positions using next-generation sequencing data. Next, we apply a method based on the "coupon collector" probability theory to construct a curve of upper bound estimates of the sampling size required for any desired variant coverage. The calculated oversampling metric will guide researchers to maximize their efficiency in using highly variant libraries.

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.

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.

Quality Markers in Cardiology. Main Markers to Measure Quality of Results (Outcomes) and Quality Measures Related to Better Results in Clinical Practice (Performance Metrics). INCARDIO (Indicadores de Calidad en Unidades Asistenciales del Área del Corazón): A SEC/SECTCV Consensus Position Paper.

PubMed

López-Sendón, José; González-Juanatey, José Ramón; Pinto, Fausto; Cuenca Castillo, José; Badimón, Lina; Dalmau, Regina; González Torrecilla, Esteban; López-Mínguez, José Ramón; Maceira, Alicia M; Pascual-Figal, Domingo; Pomar Moya-Prats, José Luis; Sionis, Alessandro; Zamorano, José Luis

2015-11-01

Cardiology practice requires complex organization that impacts overall outcomes and may differ substantially among hospitals and communities. The aim of this consensus document is to define quality markers in cardiology, including markers to measure the quality of results (outcomes metrics) and quality measures related to better results in clinical practice (performance metrics). The document is mainly intended for the Spanish health care system and may serve as a basis for similar documents in other countries. Copyright © 2015 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Quality-of-life metrics with vagus nerve stimulation for epilepsy from provider survey data.

PubMed

Englot, Dario J; Hassnain, Kevin H; Rolston, John D; Harward, Stephen C; Sinha, Saurabh R; Haglund, Michael M

2017-01-01

Drug-resistant epilepsy is a devastating disorder associated with diminished quality of life (QOL). Surgical resection leads to seizure freedom and improved QOL in many epilepsy patients, but not all individuals are candidates for resection. In these cases, neuromodulation-based therapies such as vagus nerve stimulation (VNS) are often used, but most VNS studies focus exclusively on reduction of seizure frequency. QOL changes and predictors with VNS remain poorly understood. Using the VNS Therapy Patient Outcome Registry, we examined 7 metrics related to QOL after VNS for epilepsy in over 5000 patients (including over 3000 with ≥12months follow-up), as subjectively assessed by treating physicians. Trends and predictors of QOL changes were examined and related to post-operative seizure outcome and likelihood of VNS generator replacement. After VNS therapy, physicians reported patient improvement in alertness (58-63%, range over follow-up period), post-ictal state (55-62%), cluster seizures (48-56%), mood change (43-49%), verbal communication (38-45%), school/professional achievements (29-39%), and memory (29-38%). Predictors of net QOL improvement included shorter time to implant (odds ratio [OR], 1.3; 95% confidence interval [CI], 1.1-1.6), generalized seizure type (OR, 1.2; 95% CI, 1.0-1.4), female gender (OR, 1.2; 95% CI, 1.0-1.4), and Caucasian ethnicity (OR, 1.3; 95% CI, 1.0-1.5). No significant trends were observed over time. Patients with net QOL improvement were more likely to have favorable seizure outcomes (chi square [χ 2 ]=148.1, p<0.001) and more likely to undergo VNS generator replacement (χ 2 =68.9, p<0.001) than those with worsened/unchanged QOL. VNS for drug-resistant epilepsy is associated with improvement on various QOL metrics subjectively rated by physicians. QOL improvement is associated with favorable seizure outcome and a higher likelihood of generator replacement, suggesting satisfaction with therapy. It is important to consider QOL

Elementary Metric Curriculum - Project T.I.M.E. (Timely Implementation of Metric Education). Part I.

ERIC Educational Resources Information Center

Community School District 18, Brooklyn, NY.

This is a teacher's manual for an ISS-based elementary school course in the metric system. Behavioral objectives and student activities are included. The topics covered include: (1) linear measurement; (2) metric-decimal relationships; (3) metric conversions; (4) geometry; (5) scale drawings; and (6) capacity. This is the first of a two-part…

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.

Double metric, generalized metric, and α' -deformed double field theory

NASA Astrophysics Data System (ADS)

Hohm, Olaf; Zwiebach, Barton

2016-03-01

We relate the unconstrained "double metric" of the "α' -geometry" formulation of double field theory to the constrained generalized metric encoding the spacetime metric and b -field. This is achieved by integrating out auxiliary field components of the double metric in an iterative procedure that induces an infinite number of higher-derivative corrections. As an application, we prove that, to first order in α' and to all orders in fields, the deformed gauge transformations are Green-Schwarz-deformed diffeomorphisms. We also prove that to first order in α' the spacetime action encodes precisely the Green-Schwarz deformation with Chern-Simons forms based on the torsionless gravitational connection. This seems to be in tension with suggestions in the literature that T-duality requires a torsionful connection, but we explain that these assertions are ambiguous since actions that use different connections are related by field redefinitions.

Indicators and metrics for the assessment of climate engineering

NASA Astrophysics Data System (ADS)

Oschlies, A.; Held, H.; Keller, D.; Keller, K.; Mengis, N.; Quaas, M.; Rickels, W.; Schmidt, H.

2017-01-01

Selecting appropriate indicators is essential to aggregate the information provided by climate model outputs into a manageable set of relevant metrics on which assessments of climate engineering (CE) can be based. From all the variables potentially available from climate models, indicators need to be selected that are able to inform scientists and society on the development of the Earth system under CE, as well as on possible impacts and side effects of various ways of deploying CE or not. However, the indicators used so far have been largely identical to those used in climate change assessments and do not visibly reflect the fact that indicators for assessing CE (and thus the metrics composed of these indicators) may be different from those used to assess global warming. Until now, there has been little dedicated effort to identifying specific indicators and metrics for assessing CE. We here propose that such an effort should be facilitated by a more decision-oriented approach and an iterative procedure in close interaction between academia, decision makers, and stakeholders. Specifically, synergies and trade-offs between social objectives reflected by individual indicators, as well as decision-relevant uncertainties should be considered in the development of metrics, so that society can take informed decisions about climate policy measures under the impression of the options available, their likely effects and side effects, and the quality of the underlying knowledge base.

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.

On Learning: Metrics Based Systems for Countering Asymmetric Threats

DTIC Science & Technology

2006-05-25

of self- education . While this alone cannot guarantee organizational learning , no organization can learn without a spirit of individual learning ...held views on globalization and the impact of Information Age technology . The emerging environment conceptually links to the learning model as part...On Learning : Metrics Based Systems for Countering Asymmetric Threats A Monograph by MAJ Rafael Lopez U.S. Army School of Advanced Military

Backward Registration Based Aspect Ratio Similarity (ARS) for Image Retargeting Quality Assessment.

PubMed

Zhang, Yabin; Fang, Yuming; Lin, Weisi; Zhang, Xinfeng; Li, Leida

2016-06-28

During the past few years, there have been various kinds of content-aware image retargeting operators proposed for image resizing. However, the lack of effective objective retargeting quality assessment metrics limits the further development of image retargeting techniques. Different from traditional Image Quality Assessment (IQA) metrics, the quality degradation during image retargeting is caused by artificial retargeting modifications, and the difficulty for Image Retargeting Quality Assessment (IRQA) lies in the alternation of the image resolution and content, which makes it impossible to directly evaluate the quality degradation like traditional IQA. In this paper, we interpret the image retargeting in a unified framework of resampling grid generation and forward resampling. We show that the geometric change estimation is an efficient way to clarify the relationship between the images. We formulate the geometric change estimation as a Backward Registration problem with Markov Random Field (MRF) and provide an effective solution. The geometric change aims to provide the evidence about how the original image is resized into the target image. Under the guidance of the geometric change, we develop a novel Aspect Ratio Similarity metric (ARS) to evaluate the visual quality of retargeted images by exploiting the local block changes with a visual importance pooling strategy. Experimental results on the publicly available MIT RetargetMe and CUHK datasets demonstrate that the proposed ARS can predict more accurate visual quality of retargeted images compared with state-of-the-art IRQA metrics.

Developing a Metrics-Based Online Strategy for Libraries

ERIC Educational Resources Information Center

Pagano, Joe

2009-01-01

Purpose: The purpose of this paper is to provide an introduction to the various web metrics tools that are available, and to indicate how these might be used in libraries. Design/methodology/approach: The paper describes ways in which web metrics can be used to inform strategic decision making in libraries. Findings: A framework of possible web…

An optimization based sampling approach for multiple metrics uncertainty analysis using generalized likelihood uncertainty estimation

NASA Astrophysics Data System (ADS)

Zhou, Rurui; Li, Yu; Lu, Di; Liu, Haixing; Zhou, Huicheng

2016-09-01

This paper investigates the use of an epsilon-dominance non-dominated sorted genetic algorithm II (ɛ-NSGAII) as a sampling approach with an aim to improving sampling efficiency for multiple metrics uncertainty analysis using Generalized Likelihood Uncertainty Estimation (GLUE). The effectiveness of ɛ-NSGAII based sampling is demonstrated compared with Latin hypercube sampling (LHS) through analyzing sampling efficiency, multiple metrics performance, parameter uncertainty and flood forecasting uncertainty with a case study of flood forecasting uncertainty evaluation based on Xinanjiang model (XAJ) for Qing River reservoir, China. Results obtained demonstrate the following advantages of the ɛ-NSGAII based sampling approach in comparison to LHS: (1) The former performs more effective and efficient than LHS, for example the simulation time required to generate 1000 behavioral parameter sets is shorter by 9 times; (2) The Pareto tradeoffs between metrics are demonstrated clearly with the solutions from ɛ-NSGAII based sampling, also their Pareto optimal values are better than those of LHS, which means better forecasting accuracy of ɛ-NSGAII parameter sets; (3) The parameter posterior distributions from ɛ-NSGAII based sampling are concentrated in the appropriate ranges rather than uniform, which accords with their physical significance, also parameter uncertainties are reduced significantly; (4) The forecasted floods are close to the observations as evaluated by three measures: the normalized total flow outside the uncertainty intervals (FOUI), average relative band-width (RB) and average deviation amplitude (D). The flood forecasting uncertainty is also reduced a lot with ɛ-NSGAII based sampling. This study provides a new sampling approach to improve multiple metrics uncertainty analysis under the framework of GLUE, and could be used to reveal the underlying mechanisms of parameter sets under multiple conflicting metrics in the uncertainty analysis process.

Term Based Comparison Metrics for Controlled and Uncontrolled Indexing Languages

ERIC Educational Resources Information Center

Good, B. M.; Tennis, J. T.

2009-01-01

Introduction: We define a collection of metrics for describing and comparing sets of terms in controlled and uncontrolled indexing languages and then show how these metrics can be used to characterize a set of languages spanning folksonomies, ontologies and thesauri. Method: Metrics for term set characterization and comparison were identified and…

Figure of merit for macrouniformity based on image quality ruler evaluation and machine learning framework

NASA Astrophysics Data System (ADS)

Wang, Weibao; Overall, Gary; Riggs, Travis; Silveston-Keith, Rebecca; Whitney, Julie; Chiu, George; Allebach, Jan P.

2013-01-01

Assessment of macro-uniformity is a capability that is important for the development and manufacture of printer products. Our goal is to develop a metric that will predict macro-uniformity, as judged by human subjects, by scanning and analyzing printed pages. We consider two different machine learning frameworks for the metric: linear regression and the support vector machine. We have implemented the image quality ruler, based on the recommendations of the INCITS W1.1 macro-uniformity team. Using 12 subjects at Purdue University and 20 subjects at Lexmark, evenly balanced with respect to gender, we conducted subjective evaluations with a set of 35 uniform b/w prints from seven different printers with five levels of tint coverage. Our results suggest that the image quality ruler method provides a reliable means to assess macro-uniformity. We then defined and implemented separate features to measure graininess, mottle, large area variation, jitter, and large-scale non-uniformity. The algorithms that we used are largely based on ISO image quality standards. Finally, we used these features computed for a set of test pages and the subjects' image quality ruler assessments of these pages to train the two different predictors - one based on linear regression and the other based on the support vector machine (SVM). Using five-fold cross-validation, we confirmed the efficacy of our predictor.

A metric for success

NASA Astrophysics Data System (ADS)

Carver, Gary P.

1994-05-01

The federal agencies are working with industry to ease adoption of the metric system. The goal is to help U.S. industry compete more successfully in the global marketplace, increase exports, and create new jobs. The strategy is to use federal procurement, financial assistance, and other business-related activities to encourage voluntary conversion. Based upon the positive experiences of firms and industries that have converted, federal agencies have concluded that metric use will yield long-term benefits that are beyond any one-time costs or inconveniences. It may be time for additional steps to move the Nation out of its dual-system comfort zone and continue to progress toward metrication. This report includes 'Metric Highlights in U.S. History'.

Homogeneity and EPR metrics for assessment of regular grids used in CW EPR powder simulations.

PubMed

Crăciun, Cora

2014-08-01

CW EPR powder spectra may be approximated numerically using a spherical grid and a Voronoi tessellation-based cubature. For a given spin system, the quality of simulated EPR spectra depends on the grid type, size, and orientation in the molecular frame. In previous work, the grids used in CW EPR powder simulations have been compared mainly from geometric perspective. However, some grids with similar homogeneity degree generate different quality simulated spectra. This paper evaluates the grids from EPR perspective, by defining two metrics depending on the spin system characteristics and the grid Voronoi tessellation. The first metric determines if the grid points are EPR-centred in their Voronoi cells, based on the resonance magnetic field variations inside these cells. The second metric verifies if the adjacent Voronoi cells of the tessellation are EPR-overlapping, by computing the common range of their resonance magnetic field intervals. Beside a series of well known regular grids, the paper investigates a modified ZCW grid and a Fibonacci spherical code, which are new in the context of EPR simulations. For the investigated grids, the EPR metrics bring more information than the homogeneity quantities and are better related to the grids' EPR behaviour, for different spin system symmetries. The metrics' efficiency and limits are finally verified for grids generated from the initial ones, by using the original or magnetic field-constraint variants of the Spherical Centroidal Voronoi Tessellation method. Copyright © 2014 Elsevier Inc. All rights reserved.

Characterization of Pediatric In-Hospital Cardiopulmonary Resuscitation Quality Metrics Across an International Resuscitation Collaborative.

PubMed

Niles, Dana E; Duval-Arnould, Jordan; Skellett, Sophie; Knight, Lynda; Su, Felice; Raymond, Tia T; Sweberg, Todd; Sen, Anita I; Atkins, Dianne L; Friess, Stuart H; de Caen, Allan R; Kurosawa, Hiroshi; Sutton, Robert M; Wolfe, Heather; Berg, Robert A; Silver, Annemarie; Hunt, Elizabeth A; Nadkarni, Vinay M

2018-05-01

Pediatric in-hospital cardiac arrest cardiopulmonary resuscitation quality metrics have been reported in few children less than 8 years. Our objective was to characterize chest compression fraction, rate, depth, and compliance with 2015 American Heart Association guidelines across multiple pediatric hospitals. Retrospective observational study of data from a multicenter resuscitation quality collaborative from October 2015 to April 2017. Twelve pediatric hospitals across United States, Canada, and Europe. In-hospital cardiac arrest patients (age < 18 yr) with quantitative cardiopulmonary resuscitation data recordings. None. There were 112 events yielding 2,046 evaluable 60-second epochs of cardiopulmonary resuscitation (196,669 chest compression). Event cardiopulmonary resuscitation metric summaries (median [interquartile range]) by age: less than 1 year (38/112): chest compression fraction 0.88 (0.61-0.98), chest compression rate 119/min (110-129), and chest compression depth 2.3 cm (1.9-3.0 cm); for 1 to less than 8 years (42/112): chest compression fraction 0.94 (0.79-1.00), chest compression rate 117/min (110-124), and chest compression depth 3.8 cm (2.9-4.6 cm); for 8 to less than 18 years (32/112): chest compression fraction 0.94 (0.85-1.00), chest compression rate 117/min (110-123), chest compression depth 5.5 cm (4.0-6.5 cm). "Compliance" with guideline targets for 60-second chest compression "epochs" was predefined: chest compression fraction greater than 0.80, chest compression rate 100-120/min, and chest compression depth: greater than or equal to 3.4 cm in less than 1 year, greater than or equal to 4.4 cm in 1 to less than 8 years, and 4.5 to less than 6.6 cm in 8 to less than 18 years. Proportion of less than 1 year, 1 to less than 8 years, and 8 to less than 18 years events with greater than or equal to 60% of 60-second epochs meeting compliance (respectively): chest compression fraction was 53%, 81%, and 78%; chest compression rate

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…

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.

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

Metrication report to the Congress

NASA Technical Reports Server (NTRS)

1989-01-01

The major NASA metrication activity of 1988 concerned the Space Station. Although the metric system was the baseline measurement system for preliminary design studies, solicitations for final design and development of the Space Station Freedom requested use of the inch-pound system because of concerns with cost impact and potential safety hazards. Under that policy, however use of the metric system would be permitted through waivers where its use was appropriate. Late in 1987, several Department of Defense decisions were made to increase commitment to the metric system, thereby broadening the potential base of metric involvement in the U.S. industry. A re-evaluation of Space Station Freedom units of measure policy was, therefore, initiated in January 1988.

Visual salience metrics for image inpainting

NASA Astrophysics Data System (ADS)

Ardis, Paul A.; Singhal, Amit

2009-01-01

Quantitative metrics for successful image inpainting currently do not exist, with researchers instead relying upon qualitative human comparisons to evaluate their methodologies and techniques. In an attempt to rectify this situation, we propose two new metrics to capture the notions of noticeability and visual intent in order to evaluate inpainting results. The proposed metrics use a quantitative measure of visual salience based upon a computational model of human visual attention. We demonstrate how these two metrics repeatably correlate with qualitative opinion in a human observer study, correctly identify the optimum uses for exemplar-based inpainting (as specified in the original publication), and match qualitative opinion in published examples.

A Mixed Approach to Similarity Metric Selection in Affinity Propagation-Based WiFi Fingerprinting Indoor Positioning.

PubMed

Caso, Giuseppe; de Nardis, Luca; di Benedetto, Maria-Gabriella

2015-10-30

The weighted k-nearest neighbors (WkNN) algorithm is by far the most popular choice in the design of fingerprinting indoor positioning systems based on WiFi received signal strength (RSS). WkNN estimates the position of a target device by selecting k reference points (RPs) based on the similarity of their fingerprints with the measured RSS values. The position of the target device is then obtained as a weighted sum of the positions of the k RPs. Two-step WkNN positioning algorithms were recently proposed, in which RPs are divided into clusters using the affinity propagation clustering algorithm, and one representative for each cluster is selected. Only cluster representatives are then considered during the position estimation, leading to a significant computational complexity reduction compared to traditional, flat WkNN. Flat and two-step WkNN share the issue of properly selecting the similarity metric so as to guarantee good positioning accuracy: in two-step WkNN, in particular, the metric impacts three different steps in the position estimation, that is cluster formation, cluster selection and RP selection and weighting. So far, however, the only similarity metric considered in the literature was the one proposed in the original formulation of the affinity propagation algorithm. This paper fills this gap by comparing different metrics and, based on this comparison, proposes a novel mixed approach in which different metrics are adopted in the different steps of the position estimation procedure. The analysis is supported by an extensive experimental campaign carried out in a multi-floor 3D indoor positioning testbed. The impact of similarity metrics and their combinations on the structure and size of the resulting clusters, 3D positioning accuracy and computational complexity are investigated. Results show that the adoption of metrics different from the one proposed in the original affinity propagation algorithm and, in particular, the combination of different

A Mixed Approach to Similarity Metric Selection in Affinity Propagation-Based WiFi Fingerprinting Indoor Positioning

PubMed Central

Caso, Giuseppe; de Nardis, Luca; di Benedetto, Maria-Gabriella

2015-01-01

The weighted k-nearest neighbors (WkNN) algorithm is by far the most popular choice in the design of fingerprinting indoor positioning systems based on WiFi received signal strength (RSS). WkNN estimates the position of a target device by selecting k reference points (RPs) based on the similarity of their fingerprints with the measured RSS values. The position of the target device is then obtained as a weighted sum of the positions of the k RPs. Two-step WkNN positioning algorithms were recently proposed, in which RPs are divided into clusters using the affinity propagation clustering algorithm, and one representative for each cluster is selected. Only cluster representatives are then considered during the position estimation, leading to a significant computational complexity reduction compared to traditional, flat WkNN. Flat and two-step WkNN share the issue of properly selecting the similarity metric so as to guarantee good positioning accuracy: in two-step WkNN, in particular, the metric impacts three different steps in the position estimation, that is cluster formation, cluster selection and RP selection and weighting. So far, however, the only similarity metric considered in the literature was the one proposed in the original formulation of the affinity propagation algorithm. This paper fills this gap by comparing different metrics and, based on this comparison, proposes a novel mixed approach in which different metrics are adopted in the different steps of the position estimation procedure. The analysis is supported by an extensive experimental campaign carried out in a multi-floor 3D indoor positioning testbed. The impact of similarity metrics and their combinations on the structure and size of the resulting clusters, 3D positioning accuracy and computational complexity are investigated. Results show that the adoption of metrics different from the one proposed in the original affinity propagation algorithm and, in particular, the combination of different

Development and Implementation of a Design Metric for Systems Containing Long-Term Fluid Loops

NASA Technical Reports Server (NTRS)

Steele, John W.

2016-01-01

John Steele, a chemist and technical fellow from United Technologies Corporation, provided a water quality module to assist engineers and scientists with a metric tool to evaluate risks associated with the design of space systems with fluid loops. This design metric is a methodical, quantitative, lessons-learned based means to evaluate the robustness of a long-term fluid loop system design. The tool was developed by a cross-section of engineering disciplines who had decades of experience and problem resolution.

Leveraging multi-channel x-ray detector technology to improve quality metrics for industrial and security applications

NASA Astrophysics Data System (ADS)

Jimenez, Edward S.; Thompson, Kyle R.; Stohn, Adriana; Goodner, Ryan N.

2017-09-01

Sandia National Laboratories has recently developed the capability to acquire multi-channel radio- graphs for multiple research and development applications in industry and security. This capability allows for the acquisition of x-ray radiographs or sinogram data to be acquired at up to 300 keV with up to 128 channels per pixel. This work will investigate whether multiple quality metrics for computed tomography can actually benefit from binned projection data compared to traditionally acquired grayscale sinogram data. Features and metrics to be evaluated include the ability to dis- tinguish between two different materials with similar absorption properties, artifact reduction, and signal-to-noise for both raw data and reconstructed volumetric data. The impact of this technology to non-destructive evaluation, national security, and industry is wide-ranging and has to potential to improve upon many inspection methods such as dual-energy methods, material identification, object segmentation, and computer vision on radiographs.

Brief educational interventions to improve performance on novel quality metrics in ambulatory settings in Kenya: A multi-site pre-post effectiveness trial.

PubMed

Korom, Robert Ryan; Onguka, Stephanie; Halestrap, Peter; McAlhaney, Maureen; Adam, Mary

2017-01-01

The quality of primary care delivered in resource-limited settings is low. While some progress has been made using educational interventions, it is not yet clear how to sustainably improve care for common acute illnesses in the outpatient setting. Management of urinary tract infection is particularly important in resource-limited settings, where it is commonly diagnosed and associated with high levels of antimicrobial resistance. We describe an educational programme targeting non-physician health care providers and its effects on various clinical quality metrics for urinary tract infection. We used a series of educational interventions including 1) formal introduction of a clinical practice guideline, 2) peer-to-peer chart review, and 3) peer-reviewed literature describing local antimicrobial resistance patterns. Interventions were conducted for clinical officers (N = 24) at two outpatient centers near Nairobi, Kenya over a one-year period. The medical records of 474 patients with urinary tract infections were scored on five clinical quality metrics, with the primary outcome being the proportion of cases in which the guideline-recommended antibiotic was prescribed. The results at baseline and following each intervention were compared using chi-squared tests and unpaired two-tailed T-tests for significance. Logistic regression analysis was used to assess for possible confounders. Clinician adherence to the guideline-recommended antibiotic improved significantly during the study period, from 19% at baseline to 68% following all interventions (Χ2 = 150.7, p < 0.001). The secondary outcome of composite quality score also improved significantly from an average of 2.16 to 3.00 on a five-point scale (t = 6.58, p < 0.001). Interventions had different effects at different clinical sites; the primary outcome of appropriate antibiotic prescription was met 83% of the time at Penda Health, and 50% of the time at AICKH, possibly reflecting differences in onboarding and

Validation of sea ice models using an uncertainty-based distance metric for multiple model variables: NEW METRIC FOR SEA ICE MODEL VALIDATION

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

Urrego-Blanco, Jorge R.; Hunke, Elizabeth C.; Urban, Nathan M.

Here, we implement a variance-based distance metric (D n) to objectively assess skill of sea ice models when multiple output variables or uncertainties in both model predictions and observations need to be considered. The metric compares observations and model data pairs on common spatial and temporal grids improving upon highly aggregated metrics (e.g., total sea ice extent or volume) by capturing the spatial character of model skill. The D n metric is a gamma-distributed statistic that is more general than the χ 2 statistic commonly used to assess model fit, which requires the assumption that the model is unbiased andmore » can only incorporate observational error in the analysis. The D n statistic does not assume that the model is unbiased, and allows the incorporation of multiple observational data sets for the same variable and simultaneously for different variables, along with different types of variances that can characterize uncertainties in both observations and the model. This approach represents a step to establish a systematic framework for probabilistic validation of sea ice models. The methodology is also useful for model tuning by using the D n metric as a cost function and incorporating model parametric uncertainty as part of a scheme to optimize model functionality. We apply this approach to evaluate different configurations of the standalone Los Alamos sea ice model (CICE) encompassing the parametric uncertainty in the model, and to find new sets of model configurations that produce better agreement than previous configurations between model and observational estimates of sea ice concentration and thickness.« less

Validation of sea ice models using an uncertainty-based distance metric for multiple model variables: NEW METRIC FOR SEA ICE MODEL VALIDATION

DOE PAGES

Urrego-Blanco, Jorge R.; Hunke, Elizabeth C.; Urban, Nathan M.; ...

2017-04-01

Here, we implement a variance-based distance metric (D n) to objectively assess skill of sea ice models when multiple output variables or uncertainties in both model predictions and observations need to be considered. The metric compares observations and model data pairs on common spatial and temporal grids improving upon highly aggregated metrics (e.g., total sea ice extent or volume) by capturing the spatial character of model skill. The D n metric is a gamma-distributed statistic that is more general than the χ 2 statistic commonly used to assess model fit, which requires the assumption that the model is unbiased andmore » can only incorporate observational error in the analysis. The D n statistic does not assume that the model is unbiased, and allows the incorporation of multiple observational data sets for the same variable and simultaneously for different variables, along with different types of variances that can characterize uncertainties in both observations and the model. This approach represents a step to establish a systematic framework for probabilistic validation of sea ice models. The methodology is also useful for model tuning by using the D n metric as a cost function and incorporating model parametric uncertainty as part of a scheme to optimize model functionality. We apply this approach to evaluate different configurations of the standalone Los Alamos sea ice model (CICE) encompassing the parametric uncertainty in the model, and to find new sets of model configurations that produce better agreement than previous configurations between model and observational estimates of sea ice concentration and thickness.« less

DOE JGI Quality Metrics; Approaches to Scaling and Improving Metagenome Assembly (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

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

Copeland, Alex; Brown, C. Titus

2011-10-13

DOE JGI's Alex Copeland on "DOE JGI Quality Metrics" and Michigan State University's C. Titus Brown on "Approaches to Scaling and Improving Metagenome Assembly" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

DOE JGI Quality Metrics; Approaches to Scaling and Improving Metagenome Assembly (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Copeland, Alex; Brown, C. Titus

2018-04-27

DOE JGI's Alex Copeland on "DOE JGI Quality Metrics" and Michigan State University's C. Titus Brown on "Approaches to Scaling and Improving Metagenome Assembly" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Numerical Calabi-Yau metrics

NASA Astrophysics Data System (ADS)

Douglas, Michael R.; Karp, Robert L.; Lukic, Sergio; Reinbacher, René

2008-03-01

We develop numerical methods for approximating Ricci flat metrics on Calabi-Yau hypersurfaces in projective spaces. Our approach is based on finding balanced metrics and builds on recent theoretical work by Donaldson. We illustrate our methods in detail for a one parameter family of quintics. We also suggest several ways to extend our results.

Performance assessment of geospatial simulation models of land-use change--a landscape metric-based approach.

PubMed

Sakieh, Yousef; Salmanmahiny, Abdolrassoul

2016-03-01

Performance evaluation is a critical step when developing land-use and cover change (LUCC) models. The present study proposes a spatially explicit model performance evaluation method, adopting a landscape metric-based approach. To quantify GEOMOD model performance, a set of composition- and configuration-based landscape metrics including number of patches, edge density, mean Euclidean nearest neighbor distance, largest patch index, class area, landscape shape index, and splitting index were employed. The model takes advantage of three decision rules including neighborhood effect, persistence of change direction, and urbanization suitability values. According to the results, while class area, largest patch index, and splitting indices demonstrated insignificant differences between spatial pattern of ground truth and simulated layers, there was a considerable inconsistency between simulation results and real dataset in terms of the remaining metrics. Specifically, simulation outputs were simplistic and the model tended to underestimate number of developed patches by producing a more compact landscape. Landscape-metric-based performance evaluation produces more detailed information (compared to conventional indices such as the Kappa index and overall accuracy) on the model's behavior in replicating spatial heterogeneity features of a landscape such as frequency, fragmentation, isolation, and density. Finally, as the main characteristic of the proposed method, landscape metrics employ the maximum potential of observed and simulated layers for a performance evaluation procedure, provide a basis for more robust interpretation of a calibration process, and also deepen modeler insight into the main strengths and pitfalls of a specific land-use change model when simulating a spatiotemporal phenomenon.

Application of process mining to assess the data quality of routinely collected time-based performance data sourced from electronic health records by validating process conformance.

PubMed

Perimal-Lewis, Lua; Teubner, David; Hakendorf, Paul; Horwood, Chris

2016-12-01

Effective and accurate use of routinely collected health data to produce Key Performance Indicator reporting is dependent on the underlying data quality. In this research, Process Mining methodology and tools were leveraged to assess the data quality of time-based Emergency Department data sourced from electronic health records. This research was done working closely with the domain experts to validate the process models. The hospital patient journey model was used to assess flow abnormalities which resulted from incorrect timestamp data used in time-based performance metrics. The research demonstrated process mining as a feasible methodology to assess data quality of time-based hospital performance metrics. The insight gained from this research enabled appropriate corrective actions to be put in place to address the data quality issues. © The Author(s) 2015.

Accelerating Time-Varying Hardware Volume Rendering Using TSP Trees and Color-Based Error Metrics

NASA Technical Reports Server (NTRS)

Ellsworth, David; Chiang, Ling-Jen; Shen, Han-Wei; Kwak, Dochan (Technical Monitor)

2000-01-01

This paper describes a new hardware volume rendering algorithm for time-varying data. The algorithm uses the Time-Space Partitioning (TSP) tree data structure to identify regions within the data that have spatial or temporal coherence. By using this coherence, the rendering algorithm can improve performance when the volume data is larger than the texture memory capacity by decreasing the amount of textures required. This coherence can also allow improved speed by appropriately rendering flat-shaded polygons instead of textured polygons, and by not rendering transparent regions. To reduce the polygonization overhead caused by the use of the hierarchical data structure, we introduce an optimization method using polygon templates. The paper also introduces new color-based error metrics, which more accurately identify coherent regions compared to the earlier scalar-based metrics. By showing experimental results from runs using different data sets and error metrics, we demonstrate that the new methods give substantial improvements in volume rendering performance.

Development and application of a novel metric to assess effectiveness of biomedical data

PubMed Central

Bloom, Gregory C; Eschrich, Steven; Hang, Gang; Schabath, Matthew B; Bhansali, Neera; Hoerter, Andrew M; Morgan, Scott; Fenstermacher, David A

2013-01-01

Objective Design a metric to assess the comparative effectiveness of biomedical data elements within a study that incorporates their statistical relatedness to a given outcome variable as well as a measurement of the quality of their underlying data. Materials and methods The cohort consisted of 874 patients with adenocarcinoma of the lung, each with 47 clinical data elements. The p value for each element was calculated using the Cox proportional hazard univariable regression model with overall survival as the endpoint. An attribute or A-score was calculated by quantification of an element's four quality attributes; Completeness, Comprehensiveness, Consistency and Overall-cost. An effectiveness or E-score was obtained by calculating the conditional probabilities of the p-value and A-score within the given data set with their product equaling the effectiveness score (E-score). Results The E-score metric provided information about the utility of an element beyond an outcome-related p value ranking. E-scores for elements age-at-diagnosis, gender and tobacco-use showed utility above what their respective p values alone would indicate due to their relative ease of acquisition, that is, higher A-scores. Conversely, elements surgery-site, histologic-type and pathological-TNM stage were down-ranked in comparison to their p values based on lower A-scores caused by significantly higher acquisition costs. Conclusions A novel metric termed E-score was developed which incorporates standard statistics with data quality metrics and was tested on elements from a large lung cohort. Results show that an element's underlying data quality is an important consideration in addition to p value correlation to outcome when determining the element's clinical or research utility in a study. PMID:23975264

Can segmentation evaluation metric be used as an indicator of land cover classification accuracy?

NASA Astrophysics Data System (ADS)

Švab Lenarčič, Andreja; Đurić, Nataša; Čotar, Klemen; Ritlop, Klemen; Oštir, Krištof

2016-10-01

It is a broadly established belief that the segmentation result significantly affects subsequent image classification accuracy. However, the actual correlation between the two has never been evaluated. Such an evaluation would be of considerable importance for any attempts to automate the object-based classification process, as it would reduce the amount of user intervention required to fine-tune the segmentation parameters. We conducted an assessment of segmentation and classification by analyzing 100 different segmentation parameter combinations, 3 classifiers, 5 land cover classes, 20 segmentation evaluation metrics, and 7 classification accuracy measures. The reliability definition of segmentation evaluation metrics as indicators of land cover classification accuracy was based on the linear correlation between the two. All unsupervised metrics that are not based on number of segments have a very strong correlation with all classification measures and are therefore reliable as indicators of land cover classification accuracy. On the other hand, correlation at supervised metrics is dependent on so many factors that it cannot be trusted as a reliable classification quality indicator. Algorithms for land cover classification studied in this paper are widely used; therefore, presented results are applicable to a wider area.

Comparing masked target transform volume (MTTV) clutter metric to human observer evaluation of visual clutter

NASA Astrophysics Data System (ADS)

Camp, H. A.; Moyer, Steven; Moore, Richard K.

2010-04-01

The Night Vision and Electronic Sensors Directorate's current time-limited search (TLS) model, which makes use of the targeting task performance (TTP) metric to describe image quality, does not explicitly account for the effects of visual clutter on observer performance. The TLS model is currently based on empirical fits to describe human performance for a time of day, spectrum and environment. Incorporating a clutter metric into the TLS model may reduce the number of these empirical fits needed. The masked target transform volume (MTTV) clutter metric has been previously presented and compared to other clutter metrics. Using real infrared imagery of rural images with varying levels of clutter, NVESD is currently evaluating the appropriateness of the MTTV metric. NVESD had twenty subject matter experts (SME) rank the amount of clutter in each scene in a series of pair-wise comparisons. MTTV metric values were calculated and then compared to the SME observers rankings. The MTTV metric ranked the clutter in a similar manner to the SME evaluation, suggesting that the MTTV metric may emulate SME response. This paper is a first step in quantifying clutter and measuring the agreement to subjective human evaluation.

A Risk-based Assessment And Management Framework For Multipollutant Air Quality

PubMed Central

Frey, H. Christopher; Hubbell, Bryan

2010-01-01

The National Research Council recommended both a risk- and performance-based multipollutant approach to air quality management. Specifically, management decisions should be based on minimizing the exposure to, and risk of adverse effects from, multiple sources of air pollution and that the success of these decisions should be measured by how well they achieved this objective. We briefly describe risk analysis and its application within the current approach to air quality management. Recommendations are made as to how current practice could evolve to support a fully risk- and performance-based multipollutant air quality management system. The ability to implement a risk assessment framework in a credible and policy-relevant manner depends on the availability of component models and data which are scientifically sound and developed with an understanding of their application in integrated assessments. The same can be said about accountability assessments used to evaluate the outcomes of decisions made using such frameworks. The existing risk analysis framework, although typically applied to individual pollutants, is conceptually well suited for analyzing multipollutant management actions. Many elements of this framework, such as emissions and air quality modeling, already exist with multipollutant characteristics. However, the framework needs to be supported with information on exposure and concentration response relationships that result from multipollutant health studies. Because the causal chain that links management actions to emission reductions, air quality improvements, exposure reductions and health outcomes is parallel between prospective risk analyses and retrospective accountability assessments, both types of assessment should be placed within a single framework with common metrics and indicators where possible. Improvements in risk reductions can be obtained by adopting a multipollutant risk analysis framework within the current air quality management

Improving Quality Metric Adherence to Minimally Invasive Breast Biopsy among Surgeons Within a Multihospital Health Care System.

PubMed

Tjoe, Judy A; Greer, Danielle M; Ihde, Sue E; Bares, Diane A; Mikkelson, Wendy M; Weese, James L

2015-09-01

Minimally invasive breast biopsy (MIBB) is the procedure of choice for diagnosing breast lesions indeterminate for malignancy. Multihospital health care systems face challenges achieving systemwide adherence to standardized guidelines among surgeons with varying practice patterns. This study tested whether providing individual feedback about surgeons' use of MIBB to diagnose breast malignancies improved quality metric adherence across a large health care organization. We conducted a prospective matched-pairs study to test differences (or lack of agreement) between periods before and after intervention. All analytical cases of primary breast cancer diagnosed during 2011 (period 1) and from July 2012 to June 2013 (period 2) across a multihospital health care system were reviewed for initial diagnosis by MIBB or open surgical biopsy. Open surgical biopsy was considered appropriate care only if MIBB could not be performed for reasons listed in the American Society of Breast Surgeons' quality measure for preoperative diagnosis of breast cancer. Individual and systemwide results of adherence to the MIBB metric during period 1 were sent to each surgeon in June 2012 and were later compared with period 2 results using McNemar's test of marginal homogeneity for matched binary responses. Forty-six surgeons were evaluated on use of MIBB to diagnose breast cancer. In period 1, metric adherence for 100% of cases was achieved by 37 surgeons, for a systemwide 100% compliance rate of 80.4%. After notification of individual performance, 44 of 46 surgeons used MIBB solely or otherwise appropriate care to diagnose breast cancer, which improved systemwide compliance to 95.7%. Providing individual and systemwide performance results to surgeons can increase self-awareness of practice patterns when diagnosing breast cancer, leading to standardized best-practice care across a large health care organization. Copyright © 2015 American College of Surgeons. Published by Elsevier Inc. All

Development of quality metrics for ambulatory pediatric cardiology: Transposition of the great arteries after arterial switch operation.

PubMed

Baker-Smith, Carissa M; Carlson, Karina; Ettedgui, Jose; Tsuda, Takeshi; Jayakumar, K Anitha; Park, Matthew; Tede, Nikola; Uzark, Karen; Fleishman, Craig; Connuck, David; Likes, Maggie; Penny, Daniel J

2018-01-01

To develop quality metrics (QMs) for the ambulatory care of patients with transposition of the great arteries following arterial switch operation (TGA/ASO). Under the auspices of the American College of Cardiology Adult Congenital and Pediatric Cardiology (ACPC) Steering committee, the TGA/ASO team generated candidate QMs related to TGA/ASO ambulatory care. Candidate QMs were submitted to the ACPC Steering Committee and were reviewed for validity and feasibility using individual expert panel member scoring according to the RAND-UCLA methodology. QMs were then made available for review by the entire ACC ACPC during an "open comment period." Final approval of each QM was provided by a vote of the ACC ACPC Council. Patients with TGA who had undergone an ASO were included. Patients with complex transposition were excluded. Twelve candidate QMs were generated. Seven metrics passed the RAND-UCLA process. Four passed the "open comment period" and were ultimately approved by the Council. These included: (1) at least 1 echocardiogram performed during the first year of life reporting on the function, aortic dimension, degree of neoaortic valve insufficiency, the patency of the systemic and pulmonary outflows, the patency of the branch pulmonary arteries and coronary arteries, (2) neurodevelopmental (ND) assessment after ASO; (3) lipid profile by age 11 years; and (4) documentation of a transition of care plan to an adult congenital heart disease (CHD) provider by 18 years of age. Application of the RAND-UCLA methodology and linkage of this methodology to the ACPC approval process led to successful generation of 4 QMs relevant to the care of TGA/ASO pediatric patients in the ambulatory setting. These metrics have now been incorporated into the ACPC Quality Network providing guidance for the care of TGA/ASO patients across 30 CHD centers. © 2017 Wiley Periodicals, Inc.

WE-AB-209-07: Explicit and Convex Optimization of Plan Quality Metrics in Intensity-Modulated Radiation Therapy Treatment Planning

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

Engberg, L; KTH Royal Institute of Technology, Stockholm; Eriksson, K

Purpose: To formulate objective functions of a multicriteria fluence map optimization model that correlate well with plan quality metrics, and to solve this multicriteria model by convex approximation. Methods: In this study, objectives of a multicriteria model are formulated to explicitly either minimize or maximize a dose-at-volume measure. Given the widespread agreement that dose-at-volume levels play important roles in plan quality assessment, these objectives correlate well with plan quality metrics. This is in contrast to the conventional objectives, which are to maximize clinical goal achievement by relating to deviations from given dose-at-volume thresholds: while balancing the new objectives means explicitlymore » balancing dose-at-volume levels, balancing the conventional objectives effectively means balancing deviations. Constituted by the inherently non-convex dose-at-volume measure, the new objectives are approximated by the convex mean-tail-dose measure (CVaR measure), yielding a convex approximation of the multicriteria model. Results: Advantages of using the convex approximation are investigated through juxtaposition with the conventional objectives in a computational study of two patient cases. Clinical goals of each case respectively point out three ROI dose-at-volume measures to be considered for plan quality assessment. This is translated in the convex approximation into minimizing three mean-tail-dose measures. Evaluations of the three ROI dose-at-volume measures on Pareto optimal plans are used to represent plan quality of the Pareto sets. Besides providing increased accuracy in terms of feasibility of solutions, the convex approximation generates Pareto sets with overall improved plan quality. In one case, the Pareto set generated by the convex approximation entirely dominates that generated with the conventional objectives. Conclusion: The initial computational study indicates that the convex approximation outperforms the conventional

Resilience-based performance metrics for water resources management under uncertainty

NASA Astrophysics Data System (ADS)

Roach, Tom; Kapelan, Zoran; Ledbetter, Ralph

2018-06-01

This paper aims to develop new, resilience type metrics for long-term water resources management under uncertain climate change and population growth. Resilience is defined here as the ability of a water resources management system to 'bounce back', i.e. absorb and then recover from a water deficit event, restoring the normal system operation. Ten alternative metrics are proposed and analysed addressing a range of different resilience aspects including duration, magnitude, frequency and volume of related water deficit events. The metrics were analysed on a real-world case study of the Bristol Water supply system in the UK and compared with current practice. The analyses included an examination of metrics' sensitivity and correlation, as well as a detailed examination into the behaviour of metrics during water deficit periods. The results obtained suggest that multiple metrics which cover different aspects of resilience should be used simultaneously when assessing the resilience of a water resources management system, leading to a more complete understanding of resilience compared with current practice approaches. It was also observed that calculating the total duration of a water deficit period provided a clearer and more consistent indication of system performance compared to splitting the deficit periods into the time to reach and time to recover from the worst deficit events.

SIMPATIQCO: a server-based software suite which facilitates monitoring the time course of LC-MS performance metrics on Orbitrap instruments.

PubMed

Pichler, Peter; Mazanek, Michael; Dusberger, Frederico; Weilnböck, Lisa; Huber, Christian G; Stingl, Christoph; Luider, Theo M; Straube, Werner L; Köcher, Thomas; Mechtler, Karl

2012-11-02

While the performance of liquid chromatography (LC) and mass spectrometry (MS) instrumentation continues to increase, applications such as analyses of complete or near-complete proteomes and quantitative studies require constant and optimal system performance. For this reason, research laboratories and core facilities alike are recommended to implement quality control (QC) measures as part of their routine workflows. Many laboratories perform sporadic quality control checks. However, successive and systematic longitudinal monitoring of system performance would be facilitated by dedicated automatic or semiautomatic software solutions that aid an effortless analysis and display of QC metrics over time. We present the software package SIMPATIQCO (SIMPle AuTomatIc Quality COntrol) designed for evaluation of data from LTQ Orbitrap, Q-Exactive, LTQ FT, and LTQ instruments. A centralized SIMPATIQCO server can process QC data from multiple instruments. The software calculates QC metrics supervising every step of data acquisition from LC and electrospray to MS. For each QC metric the software learns the range indicating adequate system performance from the uploaded data using robust statistics. Results are stored in a database and can be displayed in a comfortable manner from any computer in the laboratory via a web browser. QC data can be monitored for individual LC runs as well as plotted over time. SIMPATIQCO thus assists the longitudinal monitoring of important QC metrics such as peptide elution times, peak widths, intensities, total ion current (TIC) as well as sensitivity, and overall LC-MS system performance; in this way the software also helps identify potential problems. The SIMPATIQCO software package is available free of charge.

SIMPATIQCO: A Server-Based Software Suite Which Facilitates Monitoring the Time Course of LC–MS Performance Metrics on Orbitrap Instruments

PubMed Central

2012-01-01

While the performance of liquid chromatography (LC) and mass spectrometry (MS) instrumentation continues to increase, applications such as analyses of complete or near-complete proteomes and quantitative studies require constant and optimal system performance. For this reason, research laboratories and core facilities alike are recommended to implement quality control (QC) measures as part of their routine workflows. Many laboratories perform sporadic quality control checks. However, successive and systematic longitudinal monitoring of system performance would be facilitated by dedicated automatic or semiautomatic software solutions that aid an effortless analysis and display of QC metrics over time. We present the software package SIMPATIQCO (SIMPle AuTomatIc Quality COntrol) designed for evaluation of data from LTQ Orbitrap, Q-Exactive, LTQ FT, and LTQ instruments. A centralized SIMPATIQCO server can process QC data from multiple instruments. The software calculates QC metrics supervising every step of data acquisition from LC and electrospray to MS. For each QC metric the software learns the range indicating adequate system performance from the uploaded data using robust statistics. Results are stored in a database and can be displayed in a comfortable manner from any computer in the laboratory via a web browser. QC data can be monitored for individual LC runs as well as plotted over time. SIMPATIQCO thus assists the longitudinal monitoring of important QC metrics such as peptide elution times, peak widths, intensities, total ion current (TIC) as well as sensitivity, and overall LC–MS system performance; in this way the software also helps identify potential problems. The SIMPATIQCO software package is available free of charge. PMID:23088386

Bayesian model evidence as a model evaluation metric

NASA Astrophysics Data System (ADS)

Guthke, Anneli; Höge, Marvin; Nowak, Wolfgang

2017-04-01

When building environmental systems models, we are typically confronted with the questions of how to choose an appropriate model (i.e., which processes to include or neglect) and how to measure its quality. Various metrics have been proposed that shall guide the modeller towards a most robust and realistic representation of the system under study. Criteria for evaluation often address aspects of accuracy (absence of bias) or of precision (absence of unnecessary variance) and need to be combined in a meaningful way in order to address the inherent bias-variance dilemma. We suggest using Bayesian model evidence (BME) as a model evaluation metric that implicitly performs a tradeoff between bias and variance. BME is typically associated with model weights in the context of Bayesian model averaging (BMA). However, it can also be seen as a model evaluation metric in a single-model context or in model comparison. It combines a measure for goodness of fit with a penalty for unjustifiable complexity. Unjustifiable refers to the fact that the appropriate level of model complexity is limited by the amount of information available for calibration. Derived in a Bayesian context, BME naturally accounts for measurement errors in the calibration data as well as for input and parameter uncertainty. BME is therefore perfectly suitable to assess model quality under uncertainty. We will explain in detail and with schematic illustrations what BME measures, i.e. how complexity is defined in the Bayesian setting and how this complexity is balanced with goodness of fit. We will further discuss how BME compares to other model evaluation metrics that address accuracy and precision such as the predictive logscore or other model selection criteria such as the AIC, BIC or KIC. Although computationally more expensive than other metrics or criteria, BME represents an appealing alternative because it provides a global measure of model quality. Even if not applicable to each and every case, we aim

An objective method for a video quality evaluation in a 3DTV service

NASA Astrophysics Data System (ADS)

Wilczewski, Grzegorz

2015-09-01

The following article describes proposed objective method for a 3DTV video quality evaluation, a Compressed Average Image Intensity (CAII) method. Identification of the 3DTV service's content chain nodes enables to design a versatile, objective video quality metric. It is based on an advanced approach to the stereoscopic videostream analysis. Insights towards designed metric mechanisms, as well as the evaluation of performance of the designed video quality metric, in the face of the simulated environmental conditions are herein discussed. As a result, created CAII metric might be effectively used in a variety of service quality assessment applications.

Metric-driven harm: an exploration of unintended consequences of performance measurement.

PubMed

Rambur, Betty; Vallett, Carol; Cohen, Judith A; Tarule, Jill Mattuck

2013-11-01

Performance measurement is an increasingly common element of the US health care system. Typically a proxy for high quality outcomes, there has been little systematic investigation of the potential negative unintended consequences of performance metrics, including metric-driven harm. This case study details an incidence of post-surgical metric-driven harm and offers Smith's 1995 work and a patient centered, context sensitive metric model for potential adoption by nurse researchers and clinicians. Implications for further research are discussed. © 2013.

Co-located perinatal psychiatry clinic: impact of adding a psychologist on clinical quality improvement metrics.

PubMed

Pawar, Deepa; Huang, Chiang-Ching; Wichman, Christina

2018-03-02

To describe the impact of adding a psychologist (the intervention) to a co-located perinatal psychiatry clinic (PPC) in terms of effects on clinical quality improvement (QI) metrics. Six-month pre- and postintervention study design with measurement of QI metrics: number of unique patients treated; number of new and established visits; percent no-shows for new and established visits; and mean wait time to new visit. Number of unique patients treated by the psychiatrist increased by 30%, from 90 preintervention to 118 postintervention (p = .06). Total number of visits completed by the psychiatrist increased by 20% from 174 preintervention to 208 postintervention. Mean wait time for new visits for a physician decreased from 20 days preintervention to 14 days postintervention, with a mean difference of 6.4 days (p = .0015). Percentage of no-shows for new visits increased slightly from 23% preintervention to 26% postintervention (p = .72). The percentage of no-shows for established visits decreased significantly from 22% preintervention to 10% postintervention (p < .005). By adding a psychologist to the co-located PPC, we improved quality of perinatal mental health care by improving efficiency, timeliness and patient-centered care. The psychiatrist saw a greater number of unique patients, decreased wait time to new visits and decreased no-show rates for established visits, likely by better matching patient needs with provider services. A psychologist could be a valuable addition to a PPC, given the shortage of psychiatrists in the United States.

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.

A proposed metric for assessing the measurement quality of individual microarrays

PubMed Central

Kim, Kyoungmi; Page, Grier P; Beasley, T Mark; Barnes, Stephen; Scheirer, Katherine E; Allison, David B

2006-01-01

Background High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface. Results We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets. Conclusion We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements. PMID:16430768

Metric analysis and data validation across FORTRAN projects

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Selby, Richard W., Jr.; Phillips, Tsai-Yun

1983-01-01

The desire to predict the effort in developing or explaining the quality of software has led to the proposal of several metrics. As a step toward validating these metrics, the Software Engineering Laboratory (SEL) has analyzed the software science metrics, cyclomatic complexity, and various standard program measures for their relation to effort (including design through acceptance testing), development errors (both discrete and weighted according to the amount of time to locate and fix), and one another. The data investigated are collected from a project FORTRAN environment and examined across several projects at once, within individual projects and by reporting accuracy checks demonstrating the need to validate a database. When the data comes from individual programmers or certain validated projects, the metrics' correlations with actual effort seem to be strongest. For modules developed entirely by individual programmers, the validity ratios induce a statistically significant ordering of several of the metrics' correlations. When comparing the strongest correlations, neither software science's E metric cyclomatic complexity not source lines of code appears to relate convincingly better with effort than the others.

Six Sigma Quality Management System and Design of Risk-based Statistical Quality Control.

PubMed

Westgard, James O; Westgard, Sten A

2017-03-01

Six sigma concepts provide a quality management system (QMS) with many useful tools for managing quality in medical laboratories. This Six Sigma QMS is driven by the quality required for the intended use of a test. The most useful form for this quality requirement is the allowable total error. Calculation of a sigma-metric provides the best predictor of risk for an analytical examination process, as well as a design parameter for selecting the statistical quality control (SQC) procedure necessary to detect medically important errors. Simple point estimates of sigma at medical decision concentrations are sufficient for laboratory applications. Copyright © 2016 Elsevier Inc. All rights reserved.

Reduced reference image quality assessment via sub-image similarity based redundancy measurement

NASA Astrophysics Data System (ADS)

Mou, Xuanqin; Xue, Wufeng; Zhang, Lei

2012-03-01

The reduced reference (RR) image quality assessment (IQA) has been attracting much attention from researchers for its loyalty to human perception and flexibility in practice. A promising RR metric should be able to predict the perceptual quality of an image accurately while using as few features as possible. In this paper, a novel RR metric is presented, whose novelty lies in two aspects. Firstly, it measures the image redundancy by calculating the so-called Sub-image Similarity (SIS), and the image quality is measured by comparing the SIS between the reference image and the test image. Secondly, the SIS is computed by the ratios of NSE (Non-shift Edge) between pairs of sub-images. Experiments on two IQA databases (i.e. LIVE and CSIQ databases) show that by using only 6 features, the proposed metric can work very well with high correlations between the subjective and objective scores. In particular, it works consistently well across all the distortion types.

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

A Comparison of the Performance of Efficient Data Analysis Versus Fine Particle Dose as Metrics for the Quality Control of Aerodynamic Particle Size Distributions of Orally Inhaled Pharmaceuticals.

PubMed

Tougas, Terrence P; Goodey, Adrian P; Hardwell, Gareth; Mitchell, Jolyon; Lyapustina, Svetlana

2017-02-01

The performance of two quality control (QC) tests for aerodynamic particle size distributions (APSD) of orally inhaled drug products (OIPs) is compared. One of the tests is based on the fine particle dose (FPD) metric currently expected by the European regulators. The other test, called efficient data analysis (EDA), uses the ratio of large particle mass to small particle mass (LPM/SPM), along with impactor sized mass (ISM), to detect changes in APSD for QC purposes. The comparison is based on analysis of APSD data from four products (two different pressurized metered dose inhalers (MDIs) and two dry powder inhalers (DPIs)). It is demonstrated that in each case, EDA is able to detect shifts and abnormalities that FPD misses. The lack of sensitivity on the part of FPD is due to its "aggregate" nature, since FPD is a univariate measure of all particles less than about 5 μm aerodynamic diameter, and shifts or changes within the range encompassed by this metric may go undetected. EDA is thus shown to be superior to FPD for routine control of OIP quality. This finding augments previously reported superiority of EDA compared with impactor stage groupings (favored by US regulators) for incorrect rejections (type I errors) when incorrect acceptances (type II errors) were adjusted to the same probability for both approaches. EDA is therefore proposed as a method of choice for routine quality control of OIPs in both European and US regulatory environments.

Resilience Metrics for the Electric Power System: A Performance-Based Approach.

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

Vugrin, Eric D.; Castillo, Andrea R; Silva-Monroy, Cesar Augusto

Grid resilience is a concept related to a power system's ability to continue operating and delivering power even in the event that low probability, high-consequence disruptions such as hurricanes, earthquakes, and cyber-attacks occur. Grid resilience objectives focus on managing and, ideally, minimizing potential consequences that occur as a result of these disruptions. Currently, no formal grid resilience definitions, metrics, or analysis methods have been universally accepted. This document describes an effort to develop and describe grid resilience metrics and analysis methods. The metrics and methods described herein extend upon the Resilience Analysis Process (RAP) developed by Watson et al. formore » the 2015 Quadrennial Energy Review. The extension allows for both outputs from system models and for historical data to serve as the basis for creating grid resilience metrics and informing grid resilience planning and response decision-making. This document describes the grid resilience metrics and analysis methods. Demonstration of the metrics and methods is shown through a set of illustrative use cases.« less

Metrics Handbook (Air Force Systems Command)

NASA Astrophysics Data System (ADS)

1991-08-01

The handbook is designed to help one develop and use good metrics. It is intended to provide sufficient information to begin developing metrics for objectives, processes, and tasks, and to steer one toward appropriate actions based on the data one collects. It should be viewed as a road map to assist one in arriving at meaningful metrics and to assist in continuous process improvement.

Quality Measurements in Radiology: A Systematic Review of the Literature and Survey of Radiology Benefit Management Groups.

PubMed

Narayan, Anand; Cinelli, Christina; Carrino, John A; Nagy, Paul; Coresh, Josef; Riese, Victoria G; Durand, Daniel J

2015-11-01

As the US health care system transitions toward value-based reimbursement, there is an increasing need for metrics to quantify health care quality. Within radiology, many quality metrics are in use, and still more have been proposed, but there have been limited attempts to systematically inventory these measures and classify them using a standard framework. The purpose of this study was to develop an exhaustive inventory of public and private sector imaging quality metrics classified according to the classic Donabedian framework (structure, process, and outcome). A systematic review was performed in which eligibility criteria included published articles (from 2000 onward) from multiple databases. Studies were double-read, with discrepancies resolved by consensus. For the radiology benefit management group (RBM) survey, the six known companies nationally were surveyed. Outcome measures were organized on the basis of standard categories (structure, process, and outcome) and reported using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The search strategy yielded 1,816 citations; review yielded 110 reports (29 included for final analysis). Three of six RBMs (50%) responded to the survey; the websites of the other RBMs were searched for additional metrics. Seventy-five unique metrics were reported: 35 structure (46%), 20 outcome (27%), and 20 process (27%) metrics. For RBMs, 35 metrics were reported: 27 structure (77%), 4 process (11%), and 4 outcome (11%) metrics. The most commonly cited structure, process, and outcome metrics included ACR accreditation (37%), ACR Appropriateness Criteria (85%), and peer review (95%), respectively. Imaging quality metrics are more likely to be structural (46%) than process (27%) or outcome (27%) based (P < .05). As national value-based reimbursement programs increasingly emphasize outcome-based metrics, radiologists must keep pace by developing the data infrastructure required to collect outcome-based

The Albuquerque Seismological Laboratory Data Quality Analyzer

NASA Astrophysics Data System (ADS)

Ringler, A. T.; Hagerty, M.; Holland, J.; Gee, L. S.; Wilson, D.

2013-12-01

The U.S. Geological Survey's Albuquerque Seismological Laboratory (ASL) has several efforts underway to improve data quality at its stations. The Data Quality Analyzer (DQA) is one such development. The DQA is designed to characterize station data quality in a quantitative and automated manner. Station quality is based on the evaluation of various metrics, such as timing quality, noise levels, sensor coherence, and so on. These metrics are aggregated into a measurable grade for each station. The DQA consists of a website, a metric calculator (Seedscan), and a PostgreSQL database. The website allows the user to make requests for various time periods, review specific networks and stations, adjust weighting of the station's grade, and plot metrics as a function of time. The website dynamically loads all station data from a PostgreSQL database. The database is central to the application; it acts as a hub where metric values and limited station descriptions are stored. Data is stored at the level of one sensor's channel per day. The database is populated by Seedscan. Seedscan reads and processes miniSEED data, to generate metric values. Seedscan, written in Java, compares hashes of metadata and data to detect changes and perform subsequent recalculations. This ensures that the metric values are up to date and accurate. Seedscan can be run in a scheduled task or on demand by way of a config file. It will compute metrics specified in its configuration file. While many metrics are currently in development, some are completed and being actively used. These include: availability, timing quality, gap count, deviation from the New Low Noise Model, deviation from a station's noise baseline, inter-sensor coherence, and data-synthetic fits. In all, 20 metrics are planned, but any number could be added. ASL is actively using the DQA on a daily basis for station diagnostics and evaluation. As Seedscan is scheduled to run every night, data quality analysts are able to then use the

Foresters' Metric Conversions program (version 1.0). [Computer program

Treesearch

Jefferson A. Palmer

1999-01-01

The conversion of scientific measurements has become commonplace in the fields of - engineering, research, and forestry. Foresters? Metric Conversions is a Windows-based computer program that quickly converts user-defined measurements from English to metric and from metric to English. Foresters? Metric Conversions was derived from the publication "Metric...

Building structural similarity database for metric learning

NASA Astrophysics Data System (ADS)

Jin, Guoxin; Pappas, Thrasyvoulos N.

2015-03-01

We propose a new approach for constructing databases for training and testing similarity metrics for structurally lossless image compression. Our focus is on structural texture similarity (STSIM) metrics and the matched-texture compression (MTC) approach. We first discuss the metric requirements for structurally lossless compression, which differ from those of other applications such as image retrieval, classification, and understanding. We identify "interchangeability" as the key requirement for metric performance, and partition the domain of "identical" textures into three regions, of "highest," "high," and "good" similarity. We design two subjective tests for data collection, the first relies on ViSiProG to build a database of "identical" clusters, and the second builds a database of image pairs with the "highest," "high," "good," and "bad" similarity labels. The data for the subjective tests is generated during the MTC encoding process, and consist of pairs of candidate and target image blocks. The context of the surrounding image is critical for training the metrics to detect lighting discontinuities, spatial misalignments, and other border artifacts that have a noticeable effect on perceptual quality. The identical texture clusters are then used for training and testing two STSIM metrics. The labelled image pair database will be used in future research.

CUQI: cardiac ultrasound video quality index

PubMed Central

Razaak, Manzoor; Martini, Maria G.

2016-01-01

Abstract. Medical images and videos are now increasingly part of modern telecommunication applications, including telemedicinal applications, favored by advancements in video compression and communication technologies. Medical video quality evaluation is essential for modern applications since compression and transmission processes often compromise the video quality. Several state-of-the-art video quality metrics used for quality evaluation assess the perceptual quality of the video. For a medical video, assessing quality in terms of “diagnostic” value rather than “perceptual” quality is more important. We present a diagnostic-quality–oriented video quality metric for quality evaluation of cardiac ultrasound videos. Cardiac ultrasound videos are characterized by rapid repetitive cardiac motions and distinct structural information characteristics that are explored by the proposed metric. Cardiac ultrasound video quality index, the proposed metric, is a full reference metric and uses the motion and edge information of the cardiac ultrasound video to evaluate the video quality. The metric was evaluated for its performance in approximating the quality of cardiac ultrasound videos by testing its correlation with the subjective scores of medical experts. The results of our tests showed that the metric has high correlation with medical expert opinions and in several cases outperforms the state-of-the-art video quality metrics considered in our tests. PMID:27014715

On Information Metrics for Spatial Coding.

PubMed

Souza, Bryan C; Pavão, Rodrigo; Belchior, Hindiael; Tort, Adriano B L

2018-04-01

The hippocampal formation is involved in navigation, and its neuronal activity exhibits a variety of spatial correlates (e.g., place cells, grid cells). The quantification of the information encoded by spikes has been standard procedure to identify which cells have spatial correlates. For place cells, most of the established metrics derive from Shannon's mutual information (Shannon, 1948), and convey information rate in bits/s or bits/spike (Skaggs et al., 1993, 1996). Despite their widespread use, the performance of these metrics in relation to the original mutual information metric has never been investigated. In this work, using simulated and real data, we find that the current information metrics correlate less with the accuracy of spatial decoding than the original mutual information metric. We also find that the top informative cells may differ among metrics, and show a surrogate-based normalization that yields comparable spatial information estimates. Since different information metrics may identify different neuronal populations, we discuss current and alternative definitions of spatially informative cells, which affect the metric choice. Copyright © 2018 IBRO. Published by Elsevier Ltd. All rights reserved.

Evaluating Modeled Impact Metrics for Human Health, Agriculture Growth, and Near-Term Climate

NASA Astrophysics Data System (ADS)

Seltzer, K. M.; Shindell, D. T.; Faluvegi, G.; Murray, L. T.

2017-12-01

Simulated metrics that assess impacts on human health, agriculture growth, and near-term climate were evaluated using ground-based and satellite observations. The NASA GISS ModelE2 and GEOS-Chem models were used to simulate the near-present chemistry of the atmosphere. A suite of simulations that varied by model, meteorology, horizontal resolution, emissions inventory, and emissions year were performed, enabling an analysis of metric sensitivities to various model components. All simulations utilized consistent anthropogenic global emissions inventories (ECLIPSE V5a or CEDS), and an evaluation of simulated results were carried out for 2004-2006 and 2009-2011 over the United States and 2014-2015 over China. Results for O3- and PM2.5-based metrics featured minor differences due to the model resolutions considered here (2.0° × 2.5° and 0.5° × 0.666°) and model, meteorology, and emissions inventory each played larger roles in variances. Surface metrics related to O3 were consistently high biased, though to varying degrees, demonstrating the need to evaluate particular modeling frameworks before O3 impacts are quantified. Surface metrics related to PM2.5 were diverse, indicating that a multimodel mean with robust results are valuable tools in predicting PM2.5-related impacts. Oftentimes, the configuration that captured the change of a metric best over time differed from the configuration that captured the magnitude of the same metric best, demonstrating the challenge in skillfully simulating impacts. These results highlight the strengths and weaknesses of these models in simulating impact metrics related to air quality and near-term climate. With such information, the reliability of historical and future simulations can be better understood.

Barrier island morphodynamic classification based on lidar metrics for north Assateague Island, Maryland

USGS Publications Warehouse

Brock, John C.; Krabill, William; Sallenger, Asbury H.

2004-01-01

In order to reap the potential of airborne lidar surveys to provide geological information useful in understanding coastal sedimentary processes acting on various time scales, a new set of analysis methods are needed. This paper presents a multi-temporal lidar analysis of north Assateague Island, Maryland, and demonstrates the calculation of lidar metrics that condense barrier island morphology and morphological change into attributed linear features that may be used to analyze trends in coastal evolution. The new methods proposed in this paper are also of significant practical value, because lidar metric analysis reduces large volumes of point elevations into linear features attributed with essential morphological variables that are ideally suited for inclusion in Geographic Information Systems. A morphodynamic classification of north Assategue Island for a recent 10 month time period that is based on the recognition of simple patterns described by lidar change metrics is presented. Such morphodynamic classification reveals the relative magnitude and the fine scale alongshore variation in the importance of coastal changes over the study area during a defined time period. More generally, through the presentation of this morphodynamic classification of north Assateague Island, the value of lidar metrics in both examining large lidar data sets for coherent trends and in building hypotheses regarding processes driving barrier evolution is demonstrated

Developing a Security Metrics Scorecard for Healthcare Organizations.

PubMed

Elrefaey, Heba; Borycki, Elizabeth; Kushniruk, Andrea

2015-01-01

In healthcare, information security is a key aspect of protecting a patient's privacy and ensuring systems availability to support patient care. Security managers need to measure the performance of security systems and this can be achieved by using evidence-based metrics. In this paper, we describe the development of an evidence-based security metrics scorecard specific to healthcare organizations. Study participants were asked to comment on the usability and usefulness of a prototype of a security metrics scorecard that was developed based on current research in the area of general security metrics. Study findings revealed that scorecards need to be customized for the healthcare setting in order for the security information to be useful and usable in healthcare organizations. The study findings resulted in the development of a security metrics scorecard that matches the healthcare security experts' information requirements.

Development of a perceptually calibrated objective metric of noise

NASA Astrophysics Data System (ADS)

Keelan, Brian W.; Jin, Elaine W.; Prokushkin, Sergey

2011-01-01

A system simulation model was used to create scene-dependent noise masks that reflect current performance of mobile phone cameras. Stimuli with different overall magnitudes of noise and with varying mixtures of red, green, blue, and luminance noises were included in the study. Eleven treatments in each of ten pictorial scenes were evaluated by twenty observers using the softcopy ruler method. In addition to determining the quality loss function in just noticeable differences (JNDs) for the average observer and scene, transformations for different combinations of observer sensitivity and scene susceptibility were derived. The psychophysical results were used to optimize an objective metric of isotropic noise based on system noise power spectra (NPS), which were integrated over a visual frequency weighting function to yield perceptually relevant variances and covariances in CIE L*a*b* space. Because the frequency weighting function is expressed in terms of cycles per degree at the retina, it accounts for display pixel size and viewing distance effects, so application-specific predictions can be made. Excellent results were obtained using only L* and a* variances and L*a* covariance, with relative weights of 100, 5, and 12, respectively. The positive a* weight suggests that the luminance (photopic) weighting is slightly narrow on the long wavelength side for predicting perceived noisiness. The L*a* covariance term, which is normally negative, reflects masking between L* and a* noise, as confirmed in informal evaluations. Test targets in linear sRGB and rendered L*a*b* spaces for each treatment are available at http://www.aptina.com/ImArch/ to enable other researchers to test metrics of their own design and calibrate them to JNDs of quality loss without performing additional observer experiments. Such JND-calibrated noise metrics are particularly valuable for comparing the impact of noise and other attributes, and for computing overall image quality.

A lighting metric for quantitative evaluation of accent lighting systems

NASA Astrophysics Data System (ADS)

Acholo, Cyril O.; Connor, Kenneth A.; Radke, Richard J.

2014-09-01

Accent lighting is critical for artwork and sculpture lighting in museums, and subject lighting for stage, Film and television. The research problem of designing effective lighting in such settings has been revived recently with the rise of light-emitting-diode-based solid state lighting. In this work, we propose an easy-to-apply quantitative measure of the scene's visual quality as perceived by human viewers. We consider a well-accent-lit scene as one which maximizes the information about the scene (in an information-theoretic sense) available to the user. We propose a metric based on the entropy of the distribution of colors, which are extracted from an image of the scene from the viewer's perspective. We demonstrate that optimizing the metric as a function of illumination configuration (i.e., position, orientation, and spectral composition) results in natural, pleasing accent lighting. We use a photorealistic simulation tool to validate the functionality of our proposed approach, showing its successful application to two- and three-dimensional scenes.

Elementary Metric Curriculum - Project T.I.M.E. (Timely Implementation of Metric Education). Part II.

ERIC Educational Resources Information Center

Community School District 18, Brooklyn, NY.

This is the second part of a two-part teacher's manual for an ISS-based elementary school course in the metric system. Behavioral objectives and student activities are included. Topics include: (1) capacity; (2) calculation of volume and surface area of cylinders and cones; (3) mass; (4) temperature; and (5) metric conversions. (BB)

On Applying the Prognostic Performance Metrics

NASA Technical Reports Server (NTRS)

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

2009-01-01

Prognostics performance evaluation has gained significant attention in the past few years. As prognostics technology matures and more sophisticated methods for prognostic uncertainty management are developed, a standardized methodology for performance evaluation becomes extremely important to guide improvement efforts in a constructive manner. This paper is in continuation of previous efforts where several new evaluation metrics tailored for prognostics were introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. Several shortcomings identified, while applying these metrics to a variety of real applications, are also summarized along with discussions that attempt to alleviate these problems. Further, these metrics have been enhanced to include the capability of incorporating probability distribution information from prognostic algorithms as opposed to evaluation based on point estimates only. Several methods have been suggested and guidelines have been provided to help choose one method over another based on probability distribution characteristics. These approaches also offer a convenient and intuitive visualization of algorithm performance with respect to some of these new metrics like prognostic horizon and alpha-lambda performance, and also quantify the corresponding performance while incorporating the uncertainty information.

Evaluation of BLAST-based edge-weighting metrics used for homology inference with the Markov Clustering algorithm.

PubMed

Gibbons, Theodore R; Mount, Stephen M; Cooper, Endymion D; Delwiche, Charles F

2015-07-10

Clustering protein sequences according to inferred homology is a fundamental step in the analysis of many large data sets. Since the publication of the Markov Clustering (MCL) algorithm in 2002, it has been the centerpiece of several popular applications. Each of these approaches generates an undirected graph that represents sequences as nodes connected to each other by edges weighted with a BLAST-based metric. MCL is then used to infer clusters of homologous proteins by analyzing these graphs. The various approaches differ only by how they weight the edges, yet there has been very little direct examination of the relative performance of alternative edge-weighting metrics. This study compares the performance of four BLAST-based edge-weighting metrics: the bit score, bit score ratio (BSR), bit score over anchored length (BAL), and negative common log of the expectation value (NLE). Performance is tested using the Extended CEGMA KOGs (ECK) database, which we introduce here. All metrics performed similarly when analyzing full-length sequences, but dramatic differences emerged as progressively larger fractions of the test sequences were split into fragments. The BSR and BAL successfully rescued subsets of clusters by strengthening certain types of alignments between fragmented sequences, but also shifted the largest correct scores down near the range of scores generated from spurious alignments. This penalty outweighed the benefits in most test cases, and was greatly exacerbated by increasing the MCL inflation parameter, making these metrics less robust than the bit score or the more popular NLE. Notably, the bit score performed as well or better than the other three metrics in all scenarios. The results provide a strong case for use of the bit score, which appears to offer equivalent or superior performance to the more popular NLE. The insight that MCL-based clustering methods can be improved using a more tractable edge-weighting metric will greatly simplify future

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.

A priori discretization error metrics for distributed hydrologic modeling applications

NASA Astrophysics Data System (ADS)

Liu, Hongli; Tolson, Bryan A.; Craig, James R.; Shafii, Mahyar

2016-12-01

Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a subbasin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under

An Innovative Metric to Evaluate Satellite Precipitation's Spatial Distribution

NASA Astrophysics Data System (ADS)

Liu, H.; Chu, W.; Gao, X.; Sorooshian, S.

2011-12-01

Thanks to its capability to cover the mountains, where ground measurement instruments cannot reach, satellites provide a good means of estimating precipitation over mountainous regions. In regions with complex terrains, accurate information on high-resolution spatial distribution of precipitation is critical for many important issues, such as flood/landslide warning, reservoir operation, water system planning, etc. Therefore, in order to be useful in many practical applications, satellite precipitation products should possess high quality in characterizing spatial distribution. However, most existing validation metrics, which are based on point/grid comparison using simple statistics, cannot effectively measure satellite's skill of capturing the spatial patterns of precipitation fields. This deficiency results from the fact that point/grid-wised comparison does not take into account of the spatial coherence of precipitation fields. Furth more, another weakness of many metrics is that they can barely provide information on why satellite products perform well or poor. Motivated by our recent findings of the consistent spatial patterns of the precipitation field over the western U.S., we developed a new metric utilizing EOF analysis and Shannon entropy. The metric can be derived through two steps: 1) capture the dominant spatial patterns of precipitation fields from both satellite products and reference data through EOF analysis, and 2) compute the similarities between the corresponding dominant patterns using mutual information measurement defined with Shannon entropy. Instead of individual point/grid, the new metric treat the entire precipitation field simultaneously, naturally taking advantage of spatial dependence. Since the dominant spatial patterns are shaped by physical processes, the new metric can shed light on why satellite product can or cannot capture the spatial patterns. For demonstration, a experiment was carried out to evaluate a satellite

High resolution metric imaging payload

NASA Astrophysics Data System (ADS)

Delclaud, Y.

2017-11-01

Alcatel Space Industries has become Europe's leader in the field of high and very high resolution optical payloads, in the frame work of earth observation system able to provide military government with metric images from space. This leadership allowed ALCATEL to propose for the export market, within a French collaboration frame, a complete space based system for metric observation.

A Structure-Based Distance Metric for High-Dimensional Space Exploration with Multi-Dimensional Scaling

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

Lee, Hyun Jung; McDonnell, Kevin T.; Zelenyuk, Alla

2014-03-01

Although the Euclidean distance does well in measuring data distances within high-dimensional clusters, it does poorly when it comes to gauging inter-cluster distances. This significantly impacts the quality of global, low-dimensional space embedding procedures such as the popular multi-dimensional scaling (MDS) where one can often observe non-intuitive layouts. We were inspired by the perceptual processes evoked in the method of parallel coordinates which enables users to visually aggregate the data by the patterns the polylines exhibit across the dimension axes. We call the path of such a polyline its structure and suggest a metric that captures this structure directly inmore » high-dimensional space. This allows us to better gauge the distances of spatially distant data constellations and so achieve data aggregations in MDS plots that are more cognizant of existing high-dimensional structure similarities. Our MDS plots also exhibit similar visual relationships as the method of parallel coordinates which is often used alongside to visualize the high-dimensional data in raw form. We then cast our metric into a bi-scale framework which distinguishes far-distances from near-distances. The coarser scale uses the structural similarity metric to separate data aggregates obtained by prior classification or clustering, while the finer scale employs the appropriate Euclidean distance.« less

Comparison of task-based exposure metrics for an epidemiologic study of isocyanate inhalation exposures among autobody shop workers.

PubMed

Woskie, Susan R; Bello, Dhimiter; Gore, Rebecca J; Stowe, Meredith H; Eisen, Ellen A; Liu, Youcheng; Sparer, Judy A; Redlich, Carrie A; Cullen, Mark R

2008-09-01

Because many occupational epidemiologic studies use exposure surrogates rather than quantitative exposure metrics, the UMass Lowell and Yale study of autobody shop workers provided an opportunity to evaluate the relative utility of surrogates and quantitative exposure metrics in an exposure response analysis of cross-week change in respiratory function. A task-based exposure assessment was used to develop several metrics of inhalation exposure to isocyanates. The metrics included the surrogates, job title, counts of spray painting events during the day, counts of spray and bystander exposure events, and a quantitative exposure metric that incorporated exposure determinant models based on task sampling and a personal workplace protection factor for respirator use, combined with a daily task checklist. The result of the quantitative exposure algorithm was an estimate of the daily time-weighted average respirator-corrected total NCO exposure (microg/m(3)). In general, these four metrics were found to be variable in agreement using measures such as weighted kappa and Spearman correlation. A logistic model for 10% drop in FEV(1) from Monday morning to Thursday morning was used to evaluate the utility of each exposure metric. The quantitative exposure metric was the most favorable, producing the best model fit, as well as the greatest strength and magnitude of association. This finding supports the reports of others that reducing exposure misclassification can improve risk estimates that otherwise would be biased toward the null. Although detailed and quantitative exposure assessment can be more time consuming and costly, it can improve exposure-disease evaluations and is more useful for risk assessment purposes. The task-based exposure modeling method successfully produced estimates of daily time-weighted average exposures in the complex and changing autobody shop work environment. The ambient TWA exposures of all of the office workers and technicians and 57% of the

Orbit design and optimization based on global telecommunication performance metrics

NASA Technical Reports Server (NTRS)

Lee, Seungwon; Lee, Charles H.; Kerridge, Stuart; Cheung, Kar-Ming; Edwards, Charles D.

2006-01-01

The orbit selection of telecommunications orbiters is one of the critical design processes and should be guided by global telecom performance metrics and mission-specific constraints. In order to aid the orbit selection, we have coupled the Telecom Orbit Analysis and Simulation Tool (TOAST) with genetic optimization algorithms. As a demonstration, we have applied the developed tool to select an optimal orbit for general Mars telecommunications orbiters with the constraint of being a frozen orbit. While a typical optimization goal is to minimize tele-communications down time, several relevant performance metrics are examined: 1) area-weighted average gap time, 2) global maximum of local maximum gap time, 3) global maximum of local minimum gap time. Optimal solutions are found with each of the metrics. Common and different features among the optimal solutions as well as the advantage and disadvantage of each metric are presented. The optimal solutions are compared with several candidate orbits that were considered during the development of Mars Telecommunications Orbiter.

Measuring distance “as the horse runs”: Cross-scale comparison of terrain-based metrics

USGS Publications Warehouse

Buttenfield, Barbara P.; Ghandehari, M; Leyk, S; Stanislawski, Larry V.; Brantley, M E; Qiang, Yi

2016-01-01

Distance metrics play significant roles in spatial modeling tasks, such as flood inundation (Tucker and Hancock 2010), stream extraction (Stanislawski et al. 2015), power line routing (Kiessling et al. 2003) and analysis of surface pollutants such as nitrogen (Harms et al. 2009). Avalanche risk is based on slope, aspect, and curvature, all directly computed from distance metrics (Gutiérrez 2012). Distance metrics anchor variogram analysis, kernel estimation, and spatial interpolation (Cressie 1993). Several approaches are employed to measure distance. Planar metrics measure straight line distance between two points (“as the crow flies”) and are simple and intuitive, but suffer from uncertainties. Planar metrics assume that Digital Elevation Model (DEM) pixels are rigid and flat, as tiny facets of ceramic tile approximating a continuous terrain surface. In truth, terrain can bend, twist and undulate within each pixel.Work with Light Detection and Ranging (lidar) data or High Resolution Topography to achieve precise measurements present challenges, as filtering can eliminate or distort significant features (Passalacqua et al. 2015). The current availability of lidar data is far from comprehensive in developed nations, and non-existent in many rural and undeveloped regions. Notwithstanding computational advances, distance estimation on DEMs has never been systematically assessed, due to assumptions that improvements are so small that surface adjustment is unwarranted. For individual pixels inaccuracies may be small, but additive effects can propagate dramatically, especially in regional models (e.g., disaster evacuation) or global models (e.g., sea level rise) where pixels span dozens to hundreds of kilometers (Usery et al 2003). Such models are increasingly common, lending compelling reasons to understand shortcomings in the use of planar distance metrics. Researchers have studied curvature-based terrain modeling. Jenny et al. (2011) use curvature to generate

Real-time video quality monitoring

NASA Astrophysics Data System (ADS)

Liu, Tao; Narvekar, Niranjan; Wang, Beibei; Ding, Ran; Zou, Dekun; Cash, Glenn; Bhagavathy, Sitaram; Bloom, Jeffrey

2011-12-01

The ITU-T Recommendation G.1070 is a standardized opinion model for video telephony applications that uses video bitrate, frame rate, and packet-loss rate to measure the video quality. However, this model was original designed as an offline quality planning tool. It cannot be directly used for quality monitoring since the above three input parameters are not readily available within a network or at the decoder. And there is a great room for the performance improvement of this quality metric. In this article, we present a real-time video quality monitoring solution based on this Recommendation. We first propose a scheme to efficiently estimate the three parameters from video bitstreams, so that it can be used as a real-time video quality monitoring tool. Furthermore, an enhanced algorithm based on the G.1070 model that provides more accurate quality prediction is proposed. Finally, to use this metric in real-world applications, we present an example emerging application of real-time quality measurement to the management of transmitted videos, especially those delivered to mobile devices.

Sharp metric obstructions for quasi-Einstein metrics

NASA Astrophysics Data System (ADS)

Case, Jeffrey S.

2013-02-01

Using the tractor calculus to study smooth metric measure spaces, we adapt results of Gover and Nurowski to give sharp metric obstructions to the existence of quasi-Einstein metrics on suitably generic manifolds. We do this by introducing an analogue of the Weyl tractor W to the setting of smooth metric measure spaces. The obstructions we obtain can be realized as tensorial invariants which are polynomial in the Riemann curvature tensor and its divergence. By taking suitable limits of their tensorial forms, we then find obstructions to the existence of static potentials, generalizing to higher dimensions a result of Bartnik and Tod, and to the existence of potentials for gradient Ricci solitons.

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

Development of a mission-based funding model for undergraduate medical education: incorporation of quality.

PubMed

Stagnaro-Green, Alex; Roe, David; Soto-Greene, Maria; Joffe, Russell

2008-01-01

Increasing financial pressures, along with a desire to realign resources with institutional priorities, has resulted in the adoption of mission-based funding (MBF) at many medical schools. The lack of inclusion of quality and the time and expense in developing and implementing mission based funding are major deficiencies in the models reported to date. In academic year 2002-2003 New Jersey Medical School developed a model that included both quantity and quality in the education metric and that was departmentally based. Eighty percent of the undergraduate medical education allocation was based on the quantity of undergraduate medical education taught by the department ($7.35 million), and 20% ($1.89 million) was allocated based on the quality of the education delivered. Quality determinations were made by the educational leadership based on student evaluations and departmental compliance with educational administrative requirements. Evolution of the model has included the development of a faculty oversight committee and the integration of peer evaluation in the determination of educational quality. Six departments had a documented increase in quality over time, and one department had a transient decrease in quality. The MBF model has been well accepted by chairs, educational leaders, and faculty and has been instrumental in enhancing the stature of education at our institution.

Metric Madness

ERIC Educational Resources Information Center

Kroon, Cindy D.

2007-01-01

Created for a Metric Day activity, Metric Madness is a board game for two to four players. Students review and practice metric vocabulary, measurement, and calculations by playing the game. Playing time is approximately twenty to thirty minutes.

Make It Metric.

ERIC Educational Resources Information Center

Camilli, Thomas

Measurement is perhaps the most frequently used form of mathematics. This book presents activities for learning about the metric system designed for upper intermediate and junior high levels. Discussions include: why metrics, history of metrics, changing to a metric world, teaching tips, and formulas. Activities presented are: metrics all around…

Implicit Contractive Mappings in Modular Metric and Fuzzy Metric Spaces

PubMed Central

Hussain, N.; Salimi, P.

2014-01-01

The notion of modular metric spaces being a natural generalization of classical modulars over linear spaces like Lebesgue, Orlicz, Musielak-Orlicz, Lorentz, Orlicz-Lorentz, and Calderon-Lozanovskii spaces was recently introduced. In this paper we investigate the existence of fixed points of generalized α-admissible modular contractive mappings in modular metric spaces. As applications, we derive some new fixed point theorems in partially ordered modular metric spaces, Suzuki type fixed point theorems in modular metric spaces and new fixed point theorems for integral contractions. In last section, we develop an important relation between fuzzy metric and modular metric and deduce certain new fixed point results in triangular fuzzy metric spaces. Moreover, some examples are provided here to illustrate the usability of the obtained results. PMID:25003157

Quality of Information Approach to Improving Source Selection in Tactical Networks

DTIC Science & Technology

2017-02-01

consider the performance of this process based on metrics relating to quality of information: accuracy, timeliness, completeness and reliability. These...that are indicators of that the network is meeting these quality requirements. We study effective data rate, social distance, link integrity and the...utility of information as metrics within a multi-genre network to determine the quality of information of its available sources. This paper proposes a

A Novel Riemannian Metric Based on Riemannian Structure and Scaling Information for Fixed Low-Rank Matrix Completion.

PubMed

Mao, Shasha; Xiong, Lin; Jiao, Licheng; Feng, Tian; Yeung, Sai-Kit

2017-05-01

Riemannian optimization has been widely used to deal with the fixed low-rank matrix completion problem, and Riemannian metric is a crucial factor of obtaining the search direction in Riemannian optimization. This paper proposes a new Riemannian metric via simultaneously considering the Riemannian geometry structure and the scaling information, which is smoothly varying and invariant along the equivalence class. The proposed metric can make a tradeoff between the Riemannian geometry structure and the scaling information effectively. Essentially, it can be viewed as a generalization of some existing metrics. Based on the proposed Riemanian metric, we also design a Riemannian nonlinear conjugate gradient algorithm, which can efficiently solve the fixed low-rank matrix completion problem. By experimenting on the fixed low-rank matrix completion, collaborative filtering, and image and video recovery, it illustrates that the proposed method is superior to the state-of-the-art methods on the convergence efficiency and the numerical performance.

Reuse Metrics for Object Oriented Software

NASA Technical Reports Server (NTRS)

Bieman, James M.

1998-01-01

One way to increase the quality of software products and the productivity of software development is to reuse existing software components when building new software systems. In order to monitor improvements in reuse, the level of reuse must be measured. In this NASA supported project we (1) derived a suite of metrics which quantify reuse attributes for object oriented, object based, and procedural software, (2) designed prototype tools to take these measurements in Ada, C++, Java, and C software, (3) evaluated the reuse in available software, (4) analyzed the relationship between coupling, cohesion, inheritance, and reuse, (5) collected object oriented software systems for our empirical analyses, and (6) developed quantitative criteria and methods for restructuring software to improve reusability.

A new normalizing algorithm for BAC CGH arrays with quality control metrics.

PubMed

Miecznikowski, Jeffrey C; Gaile, Daniel P; Liu, Song; Shepherd, Lori; Nowak, Norma

2011-01-01

The main focus in pin-tip (or print-tip) microarray analysis is determining which probes, genes, or oligonucleotides are differentially expressed. Specifically in array comparative genomic hybridization (aCGH) experiments, researchers search for chromosomal imbalances in the genome. To model this data, scientists apply statistical methods to the structure of the experiment and assume that the data consist of the signal plus random noise. In this paper we propose "SmoothArray", a new method to preprocess comparative genomic hybridization (CGH) bacterial artificial chromosome (BAC) arrays and we show the effects on a cancer dataset. As part of our R software package "aCGHplus," this freely available algorithm removes the variation due to the intensity effects, pin/print-tip, the spatial location on the microarray chip, and the relative location from the well plate. removal of this variation improves the downstream analysis and subsequent inferences made on the data. Further, we present measures to evaluate the quality of the dataset according to the arrayer pins, 384-well plates, plate rows, and plate columns. We compare our method against competing methods using several metrics to measure the biological signal. With this novel normalization algorithm and quality control measures, the user can improve their inferences on datasets and pinpoint problems that may arise in their BAC aCGH technology.

Metrics for Performance Evaluation of Patient Exercises during Physical Therapy.

PubMed

Vakanski, Aleksandar; Ferguson, Jake M; Lee, Stephen

2017-06-01

The article proposes a set of metrics for evaluation of patient performance in physical therapy exercises. Taxonomy is employed that classifies the metrics into quantitative and qualitative categories, based on the level of abstraction of the captured motion sequences. Further, the quantitative metrics are classified into model-less and model-based metrics, in reference to whether the evaluation employs the raw measurements of patient performed motions, or whether the evaluation is based on a mathematical model of the motions. The reviewed metrics include root-mean square distance, Kullback Leibler divergence, log-likelihood, heuristic consistency, Fugl-Meyer Assessment, and similar. The metrics are evaluated for a set of five human motions captured with a Kinect sensor. The metrics can potentially be integrated into a system that employs machine learning for modelling and assessment of the consistency of patient performance in home-based therapy setting. Automated performance evaluation can overcome the inherent subjectivity in human performed therapy assessment, and it can increase the adherence to prescribed therapy plans, and reduce healthcare costs.

A Validation of Object-Oriented Design Metrics

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Briand, Lionel; Melo, Walcelio L.

1995-01-01

This paper presents the results of a study conducted at the University of Maryland in which we experimentally investigated the suite of Object-Oriented (00) design metrics introduced by [Chidamber and Kemerer, 1994]. In order to do this, we assessed these metrics as predictors of fault-prone classes. This study is complementary to [Lieand Henry, 1993] where the same suite of metrics had been used to assess frequencies of maintenance changes to classes. To perform our validation accurately, we collected data on the development of eight medium-sized information management systems based on identical requirements. All eight projects were developed using a sequential life cycle model, a well-known 00 analysis/design method and the C++ programming language. Based on experimental results, the advantages and drawbacks of these 00 metrics are discussed and suggestions for improvement are provided. Several of Chidamber and Kemerer's 00 metrics appear to be adequate to predict class fault-proneness during the early phases of the life-cycle. We also showed that they are, on our data set, better predictors than "traditional" code metrics, which can only be collected at a later phase of the software development processes.

Quality Measures for Dialysis: Time for a Balanced Scorecard.

PubMed

Kliger, Alan S

2016-02-05

Recent federal legislation establishes a merit-based incentive payment system for physicians, with a scorecard for each professional. The Centers for Medicare and Medicaid Services evaluate quality of care with clinical performance measures and have used these metrics for public reporting and payment to dialysis facilities. Similar metrics may be used for the future merit-based incentive payment system. In nephrology, most clinical performance measures measure processes and intermediate outcomes of care. These metrics were developed from population studies of best practice and do not identify opportunities for individualizing care on the basis of patient characteristics and individual goals of treatment. The In-Center Hemodialysis (ICH) Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey examines patients' perception of care and has entered the arena to evaluate quality of care. A balanced scorecard of quality performance should include three elements: population-based best clinical practice, patient perceptions, and individually crafted patient goals of care. Copyright © 2016 by the American Society of Nephrology.

Quality Measures for Dialysis: Time for a Balanced Scorecard

PubMed Central

2016-01-01

Recent federal legislation establishes a merit-based incentive payment system for physicians, with a scorecard for each professional. The Centers for Medicare and Medicaid Services evaluate quality of care with clinical performance measures and have used these metrics for public reporting and payment to dialysis facilities. Similar metrics may be used for the future merit-based incentive payment system. In nephrology, most clinical performance measures measure processes and intermediate outcomes of care. These metrics were developed from population studies of best practice and do not identify opportunities for individualizing care on the basis of patient characteristics and individual goals of treatment. The In-Center Hemodialysis (ICH) Consumer Assessment of Healthcare Providers and Systems (CAHPS) survey examines patients' perception of care and has entered the arena to evaluate quality of care. A balanced scorecard of quality performance should include three elements: population-based best clinical practice, patient perceptions, and individually crafted patient goals of care. PMID:26316622

Can metric-based approaches really improve multi-model climate projections? A perfect model framework applied to summer temperature change in France.

NASA Astrophysics Data System (ADS)

Boé, Julien; Terray, Laurent

2014-05-01

Ensemble approaches for climate change projections have become ubiquitous. Because of large model-to-model variations and, generally, lack of rationale for the choice of a particular climate model against others, it is widely accepted that future climate change and its impacts should not be estimated based on a single climate model. Generally, as a default approach, the multi-model ensemble mean (MMEM) is considered to provide the best estimate of climate change signals. The MMEM approach is based on the implicit hypothesis that all the models provide equally credible projections of future climate change. This hypothesis is unlikely to be true and ideally one would want to give more weight to more realistic models. A major issue with this alternative approach lies in the assessment of the relative credibility of future climate projections from different climate models, as they can only be evaluated against present-day observations: which present-day metric(s) should be used to decide which models are "good" and which models are "bad" in the future climate? Once a supposedly informative metric has been found, other issues arise. What is the best statistical method to combine multiple models results taking into account their relative credibility measured by a given metric? How to be sure in the end that the metric-based estimate of future climate change is not in fact less realistic than the MMEM? It is impossible to provide strict answers to those questions in the climate change context. Yet, in this presentation, we propose a methodological approach based on a perfect model framework that could bring some useful elements of answer to the questions previously mentioned. The basic idea is to take a random climate model in the ensemble and treat it as if it were the truth (results of this model, in both past and future climate, are called "synthetic observations"). Then, all the other members from the multi-model ensemble are used to derive thanks to a metric-based

Metrix Matrix: A Cloud-Based System for Tracking Non-Relative Value Unit Value-Added Work Metrics.

PubMed

Kovacs, Mark D; Sheafor, Douglas H; Thacker, Paul G; Hardie, Andrew D; Costello, Philip

2018-03-01

In the era of value-based medicine, it will become increasingly important for radiologists to provide metrics that demonstrate their value beyond clinical productivity. In this article the authors describe their institution's development of an easy-to-use system for tracking value-added but non-relative value unit (RVU)-based activities. Metrix Matrix is an efficient cloud-based system for tracking value-added work. A password-protected home page contains links to web-based forms created using Google Forms, with collected data populating Google Sheets spreadsheets. Value-added work metrics selected for tracking included interdisciplinary conferences, hospital committee meetings, consulting on nonbilled outside studies, and practice-based quality improvement. Over a period of 4 months, value-added work data were collected for all clinical attending faculty members in a university-based radiology department (n = 39). Time required for data entry was analyzed for 2 faculty members over the same time period. Thirty-nine faculty members (equivalent to 36.4 full-time equivalents) reported a total of 1,223.5 hours of value-added work time (VAWT). A formula was used to calculate "value-added RVUs" (vRVUs) from VAWT. VAWT amounted to 5,793.6 vRVUs or 6.0% of total work performed (vRVUs plus work RVUs [wRVUs]). Were vRVUs considered equivalent to wRVUs for staffing purposes, this would require an additional 2.3 full-time equivalents, on the basis of average wRVU calculations. Mean data entry time was 56.1 seconds per day per faculty member. As health care reimbursement evolves with an emphasis on value-based medicine, it is imperative that radiologists demonstrate the value they add to patient care beyond wRVUs. This free and easy-to-use cloud-based system allows the efficient quantification of value-added work activities. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Model-based metrics of human-automation function allocation in complex work environments

NASA Astrophysics Data System (ADS)

Kim, So Young

issues with function allocation. Then, based on the eight issues, eight types of metrics are established. The purpose of these metrics is to assess the extent to which each issue exists with a given function allocation. Specifically, the eight types of metrics assess workload, coherency of a function allocation, mismatches between responsibility and authority, interruptive automation, automation boundary conditions, human adaptation to context, stability of the human's work environment, and mission performance. Finally, to validate the modeling framework and the metrics, a case study was conducted modeling four different function allocations between a pilot and flight deck automation during the arrival and approach phases of flight. A range of pilot cognitive control modes and maximum human taskload limits were also included in the model. The metrics were assessed for these four function allocations and analyzed to validate capability of the metrics to identify important issues in given function allocations. In addition, the design insights provided by the metrics are highlighted. This thesis concludes with a discussion of mechanisms for further validating the modeling framework and function allocation metrics developed here, and highlights where these developments can be applied in research and in the design of function allocations in complex work environments such as aviation operations.

What Can Article-Level Metrics Do for You?

PubMed Central

Fenner, Martin

2013-01-01

Article-level metrics (ALMs) provide a wide range of metrics about the uptake of an individual journal article by the scientific community after publication. They include citations, usage statistics, discussions in online comments and social media, social bookmarking, and recommendations. In this essay, we describe why article-level metrics are an important extension of traditional citation-based journal metrics and provide a number of example from ALM data collected for PLOS Biology. PMID:24167445

What can article-level metrics do for you?

PubMed

Fenner, Martin

2013-10-01

Article-level metrics (ALMs) provide a wide range of metrics about the uptake of an individual journal article by the scientific community after publication. They include citations, usage statistics, discussions in online comments and social media, social bookmarking, and recommendations. In this essay, we describe why article-level metrics are an important extension of traditional citation-based journal metrics and provide a number of example from ALM data collected for PLOS Biology.

On use of image quality metrics for perceptual blur modeling: image/video compression case

NASA Astrophysics Data System (ADS)

Cha, Jae H.; Olson, Jeffrey T.; Preece, Bradley L.; Espinola, Richard L.; Abbott, A. Lynn

2018-02-01

Linear system theory is employed to make target acquisition performance predictions for electro-optical/infrared imaging systems where the modulation transfer function (MTF) may be imposed from a nonlinear degradation process. Previous research relying on image quality metrics (IQM) methods, which heuristically estimate perceived MTF has supported that an average perceived MTF can be used to model some types of degradation such as image compression. Here, we discuss the validity of the IQM approach by mathematically analyzing the associated heuristics from the perspective of reliability, robustness, and tractability. Experiments with standard images compressed by x.264 encoding suggest that the compression degradation can be estimated by a perceived MTF within boundaries defined by well-behaved curves with marginal error. Our results confirm that the IQM linearizer methodology provides a credible tool for sensor performance modeling.

The role of complexity metrics in a multi-institutional dosimetry audit of VMAT.

PubMed

McGarry, Conor K; Agnew, Christina E; Hussein, Mohammad; Tsang, Yatman; McWilliam, Alan; Hounsell, Alan R; Clark, Catharine H

2016-01-01

To demonstrate the benefit of complexity metrics such as the modulation complexity score (MCS) and monitor units (MUs) in multi-institutional audits of volumetric-modulated arc therapy (VMAT) delivery. 39 VMAT treatment plans were analysed using MCS and MU. A virtual phantom planning exercise was planned and independently measured using the PTW Octavius(®) phantom and seven29(®) 2D array (PTW-Freiburg GmbH, Freiburg, Germany). MCS and MU were compared with the median gamma index pass rates (2%/2 and 3%/3 mm) and plan quality. The treatment planning systems (TPS) were grouped by VMAT modelling being specifically designed for the linear accelerator manufacturer's own treatment delivery system (Type 1) or independent of vendor for VMAT delivery (Type 2). Differences in plan complexity (MCS and MU) between TPS types were compared. For Varian(®) linear accelerators (Varian(®) Medical Systems, Inc., Palo Alto, CA), MCS and MU were significantly correlated with gamma pass rates. Type 2 TPS created poorer quality, more complex plans with significantly higher MUs and MCS than Type 1 TPS. Plan quality was significantly correlated with MU for Type 2 plans. A statistically significant correlation was observed between MU and MCS for all plans (R = -0.84, p < 0.01). MU and MCS have a role in assessing plan complexity in audits along with plan quality metrics. Plan complexity metrics give some indication of plan deliverability but should be analysed with plan quality. Complexity metrics were investigated for a national rotational audit involving 34 institutions and they showed value. The metrics found that more complex plans were created for planning systems which were independent of vendor for VMAT delivery.

Attenuation-based size metric for estimating organ dose to patients undergoing tube current modulated CT exams

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

Bostani, Maryam, E-mail: mbostani@mednet.ucla.edu; McMillan, Kyle; Lu, Peiyun

2015-02-15

Purpose: Task Group 204 introduced effective diameter (ED) as the patient size metric used to correlate size-specific-dose-estimates. However, this size metric fails to account for patient attenuation properties and has been suggested to be replaced by an attenuation-based size metric, water equivalent diameter (D{sub W}). The purpose of this study is to investigate different size metrics, effective diameter, and water equivalent diameter, in combination with regional descriptions of scanner output to establish the most appropriate size metric to be used as a predictor for organ dose in tube current modulated CT exams. Methods: 101 thoracic and 82 abdomen/pelvis scans frommore » clinically indicated CT exams were collected retrospectively from a multidetector row CT (Sensation 64, Siemens Healthcare) with Institutional Review Board approval to generate voxelized patient models. Fully irradiated organs (lung and breasts in thoracic scans and liver, kidneys, and spleen in abdominal scans) were segmented and used as tally regions in Monte Carlo simulations for reporting organ dose. Along with image data, raw projection data were collected to obtain tube current information for simulating tube current modulation scans using Monte Carlo methods. Additionally, previously described patient size metrics [ED, D{sub W}, and approximated water equivalent diameter (D{sub Wa})] were calculated for each patient and reported in three different ways: a single value averaged over the entire scan, a single value averaged over the region of interest, and a single value from a location in the middle of the scan volume. Organ doses were normalized by an appropriate mAs weighted CTDI{sub vol} to reflect regional variation of tube current. Linear regression analysis was used to evaluate the correlations between normalized organ doses and each size metric. Results: For the abdominal organs, the correlations between normalized organ dose and size metric were overall slightly higher for

MO-D-213-06: Quantitative Image Quality Metrics Are for Physicists, Not Radiologists: How to Communicate to Your Radiologists Using Their Language

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

Szczykutowicz, T; Rubert, N; Ranallo, F

Purpose: A framework for explaining differences in image quality to non-technical audiences in medial imaging is needed. Currently, this task is something that is learned “on the job.” The lack of a formal methodology for communicating optimal acquisition parameters into the clinic effectively mitigates many technological advances. As a community, medical physicists need to be held responsible for not only advancing image science, but also for ensuring its proper use in the clinic. This work outlines a framework that bridges the gap between the results from quantitative image quality metrics like detectability, MTF, and NPS and their effect on specificmore » anatomical structures present in diagnostic imaging tasks. Methods: Specific structures of clinical importance were identified for a body, an extremity, a chest, and a temporal bone protocol. Using these structures, quantitative metrics were used to identify the parameter space that should yield optimal image quality constrained within the confines of clinical logistics and dose considerations. The reading room workflow for presenting the proposed changes for imaging each of these structures is presented. The workflow consists of displaying images for physician review consisting of different combinations of acquisition parameters guided by quantitative metrics. Examples of using detectability index, MTF, NPS, noise and noise non-uniformity are provided. During review, the physician was forced to judge the image quality solely on those features they need for diagnosis, not on the overall “look” of the image. Results: We found that in many cases, use of this framework settled mis-agreements between physicians. Once forced to judge images on the ability to detect specific structures inter reader agreement was obtained. Conclusion: This framework will provide consulting, research/industrial, or in-house physicists with clinically relevant imaging tasks to guide reading room image review. This framework

Improvement of Reliability of Diffusion Tensor Metrics in Thigh Skeletal Muscles.

PubMed

Keller, Sarah; Chhabra, Avneesh; Ahmed, Shaheen; Kim, Anne C; Chia, Jonathan M; Yamamura, Jin; Wang, Zhiyue J

2018-05-01

Quantitative diffusion tensor imaging (DTI) of skeletal muscles is challenging due to the bias in DTI metrics, such as fractional anisotropy (FA) and mean diffusivity (MD), related to insufficient signal-to-noise ratio (SNR). This study compares the bias of DTI metrics in skeletal muscles via pixel-based and region-of-interest (ROI)-based analysis. DTI of the thigh muscles was conducted on a 3.0-T system in N = 11 volunteers using a fat-suppressed single-shot spin-echo echo planar imaging (SS SE-EPI) sequence with eight repetitions (number of signal averages (NSA) = 4 or 8 for each repeat). The SNR was calculated for different NSAs and estimated for the composite images combining all data (effective NSA = 48) as standard reference. The bias of MD and FA derived by pixel-based and ROI-based quantification were compared at different NSAs. An "intra-ROI diffusion direction dispersion angle (IRDDDA)" was calculated to assess the uniformity of diffusion within the ROI. Using our standard reference image with NSA = 48, the ROI-based and pixel-based measurements agreed for FA and MD. Larger disagreements were observed for the pixel-based quantification at NSA = 4. MD was less sensitive than FA to the noise level. The IRDDDA decreased with higher NSA. At NSA = 4, ROI-based FA showed a lower average bias (0.9% vs. 37.4%) and narrower 95% limits of agreement compared to the pixel-based method. The ROI-based estimation of FA is less prone to bias than the pixel-based estimations when SNR is low. The IRDDDA can be applied as a quantitative quality measure to assess reliability of ROI-based DTI metrics. Copyright © 2018 Elsevier B.V. All rights reserved.

On the new metrics for IMRT QA verification.

PubMed

Garcia-Romero, Alejandro; Hernandez-Vitoria, Araceli; Millan-Cebrian, Esther; Alba-Escorihuela, Veronica; Serrano-Zabaleta, Sonia; Ortega-Pardina, Pablo

2016-11-01

The aim of this work is to search for new metrics that could give more reliable acceptance/rejection criteria on the IMRT verification process and to offer solutions to the discrepancies found among different conventional metrics. Therefore, besides conventional metrics, new ones are proposed and evaluated with new tools to find correlations among them. These new metrics are based on the processing of the dose-volume histogram information, evaluating the absorbed dose differences, the dose constraint fulfillment, or modified biomathematical treatment outcome models such as tumor control probability (TCP) and normal tissue complication probability (NTCP). An additional purpose is to establish whether the new metrics yield the same acceptance/rejection plan distribution as the conventional ones. Fifty eight treatment plans concerning several patient locations are analyzed. All of them were verified prior to the treatment, using conventional metrics, and retrospectively after the treatment with the new metrics. These new metrics include the definition of three continuous functions, based on dose-volume histograms resulting from measurements evaluated with a reconstructed dose system and also with a Monte Carlo redundant calculation. The 3D gamma function for every volume of interest is also calculated. The information is also processed to obtain ΔTCP or ΔNTCP for the considered volumes of interest. These biomathematical treatment outcome models have been modified to increase their sensitivity to dose changes. A robustness index from a radiobiological point of view is defined to classify plans in robustness against dose changes. Dose difference metrics can be condensed in a single parameter: the dose difference global function, with an optimal cutoff that can be determined from a receiver operating characteristics (ROC) analysis of the metric. It is not always possible to correlate differences in biomathematical treatment outcome models with dose difference metrics

A comparison of metrics to evaluate the effects of hydro-facility passage stressors on fish

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

Colotelo, Alison H.; Goldman, Amy E.; Wagner, Katie A.

Hydropower is the most common form of renewable energy, and countries worldwide are considering expanding hydropower to new areas. One of the challenges of hydropower deployment is mitigation of the environmental impacts including water quality, habitat alterations, and ecosystem connectivity. For fish species that inhabit river systems with hydropower facilities, passage through the facility to access spawning and rearing habitats can be particularly challenging. Fish moving downstream through a hydro-facility can be exposed to a number of stressors (e.g., rapid decompression, shear forces, blade strike and collision, and turbulence), which can all affect fish survival in direct and indirect ways.more » Many studies have investigated the effects of hydro-turbine passage on fish; however, the comparability among studies is limited by variation in the metrics and biological endpoints used. Future studies investigating the effects of hydro-turbine passage should focus on using metrics and endpoints that are easily comparable. This review summarizes four categories of metrics that are used in fisheries research and have application to hydro-turbine passage (i.e., mortality, injury, molecular metrics, behavior) and evaluates them based on several criteria (i.e., resources needed, invasiveness, comparability among stressors and species, and diagnostic properties). Additionally, these comparisons are put into context of study setting (i.e., laboratory vs. field). Overall, injury and molecular metrics are ideal for studies in which there is a need to understand the mechanisms of effect, whereas behavior and mortality metrics provide information on the whole body response of the fish. The study setting strongly influences the comparability among studies. In laboratory-based studies, stressors can be controlled by both type and magnitude, allowing for easy comparisons among studies. In contrast, field studies expose fish to realistic passage environments but the

Related Critical Psychometric Issues and Their Resolutions during Development of PE Metrics

ERIC Educational Resources Information Center

Fox, Connie; Zhu, Weimo; Park, Youngsik; Fisette, Jennifer L.; Graber, Kim C.; Dyson, Ben; Avery, Marybell; Franck, Marian; Placek, Judith H.; Rink, Judy; Raynes, De

2011-01-01

In addition to validity and reliability evidence, other psychometric qualities of the PE Metrics assessments needed to be examined. This article describes how those critical psychometric issues were addressed during the PE Metrics assessment bank construction. Specifically, issues included (a) number of items or assessments needed, (b) training…

Metrics for Offline Evaluation of Prognostic Performance

NASA Technical Reports Server (NTRS)

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

2010-01-01

Prognostic performance evaluation has gained significant attention in the past few years. Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end-user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.

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).

New wideband radar target classification method based on neural learning and modified Euclidean metric

NASA Astrophysics Data System (ADS)

Jiang, Yicheng; Cheng, Ping; Ou, Yangkui

2001-09-01

A new method for target classification of high-range resolution radar is proposed. It tries to use neural learning to obtain invariant subclass features of training range profiles. A modified Euclidean metric based on the Box-Cox transformation technique is investigated for Nearest Neighbor target classification improvement. The classification experiments using real radar data of three different aircraft have demonstrated that classification error can reduce 8% if this method proposed in this paper is chosen instead of the conventional method. The results of this paper have shown that by choosing an optimized metric, it is indeed possible to reduce the classification error without increasing the number of samples.

Assessing the quality of restored images in optical long-baseline interferometry

NASA Astrophysics Data System (ADS)

Gomes, Nuno; Garcia, Paulo J. V.; Thiébaut, Éric

2017-03-01

Assessing the quality of aperture synthesis maps is relevant for benchmarking image reconstruction algorithms, for the scientific exploitation of data from optical long-baseline interferometers, and for the design/upgrade of new/existing interferometric imaging facilities. Although metrics have been proposed in these contexts, no systematic study has been conducted on the selection of a robust metric for quality assessment. This article addresses the question: what is the best metric to assess the quality of a reconstructed image? It starts by considering several metrics and selecting a few based on general properties. Then, a variety of image reconstruction cases are considered. The observational scenarios are phase closure and phase referencing at the Very Large Telescope Interferometer (VLTI), for a combination of two, three, four and six telescopes. End-to-end image reconstruction is accomplished with the MIRA software, and several merit functions are put to test. It is found that convolution by an effective point spread function is required for proper image quality assessment. The effective angular resolution of the images is superior to naive expectation based on the maximum frequency sampled by the array. This is due to the prior information used in the aperture synthesis algorithm and to the nature of the objects considered. The ℓ1-norm is the most robust of all considered metrics, because being linear it is less sensitive to image smoothing by high regularization levels. For the cases considered, this metric allows the implementation of automatic quality assessment of reconstructed images, with a performance similar to human selection.

Performance metrics for the evaluation of hyperspectral chemical identification systems

NASA Astrophysics Data System (ADS)

Truslow, Eric; Golowich, Steven; Manolakis, Dimitris; Ingle, Vinay

2016-02-01

Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume's chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.

A Metric on Phylogenetic Tree Shapes

PubMed Central

Plazzotta, G.

2018-01-01

Abstract The shapes of evolutionary trees are influenced by the nature of the evolutionary process but comparisons of trees from different processes are hindered by the challenge of completely describing tree shape. We present a full characterization of the shapes of rooted branching trees in a form that lends itself to natural tree comparisons. We use this characterization to define a metric, in the sense of a true distance function, on tree shapes. The metric distinguishes trees from random models known to produce different tree shapes. It separates trees derived from tropical versus USA influenza A sequences, which reflect the differing epidemiology of tropical and seasonal flu. We describe several metrics based on the same core characterization, and illustrate how to extend the metric to incorporate trees’ branch lengths or other features such as overall imbalance. Our approach allows us to construct addition and multiplication on trees, and to create a convex metric on tree shapes which formally allows computation of average tree shapes. PMID:28472435

Metric Learning for Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Visual difference metric for realistic image synthesis

NASA Astrophysics Data System (ADS)

Bolin, Mark R.; Meyer, Gary W.

1999-05-01

An accurate and efficient model of human perception has been developed to control the placement of sample in a realistic image synthesis algorithm. Previous sampling techniques have sought to spread the error equally across the image plane. However, this approach neglects the fact that the renderings are intended to be displayed for a human observer. The human visual system has a varying sensitivity to error that is based upon the viewing context. This means that equivalent optical discrepancies can be very obvious in one situation and imperceptible in another. It is ultimately the perceptibility of this error that governs image quality and should be used as the basis of a sampling algorithm. This paper focuses on a simplified version of the Lubin Visual Discrimination Metric (VDM) that was developed for insertion into an image synthesis algorithm. The sampling VDM makes use of a Haar wavelet basis for the cortical transform and a less severe spatial pooling operation. The model was extended for color including the effects of chromatic aberration. Comparisons are made between the execution time and visual difference map for the original Lubin and simplified visual difference metrics. Results for the realistic image synthesis algorithm are also presented.

A scoring metric for multivariate data for reproducibility analysis using chemometric methods

PubMed Central

Sheen, David A.; de Carvalho Rocha, Werickson Fortunato; Lippa, Katrice A.; Bearden, Daniel W.

2017-01-01

Process quality control and reproducibility in emerging measurement fields such as metabolomics is normally assured by interlaboratory comparison testing. As a part of this testing process, spectral features from a spectroscopic method such as nuclear magnetic resonance (NMR) spectroscopy are attributed to particular analytes within a mixture, and it is the metabolite concentrations that are returned for comparison between laboratories. However, data quality may also be assessed directly by using binned spectral data before the time-consuming identification and quantification. Use of the binned spectra has some advantages, including preserving information about trace constituents and enabling identification of process difficulties. In this paper, we demonstrate the use of binned NMR spectra to conduct a detailed interlaboratory comparison and composition analysis. Spectra of synthetic and biologically-obtained metabolite mixtures, taken from a previous interlaboratory study, are compared with cluster analysis using a variety of distance and entropy metrics. The individual measurements are then evaluated based on where they fall within their clusters, and a laboratory-level scoring metric is developed, which provides an assessment of each laboratory’s individual performance. PMID:28694553

Sigma Routing Metric for RPL Protocol.

PubMed

Sanmartin, Paul; Rojas, Aldo; Fernandez, Luis; Avila, Karen; Jabba, Daladier; Valle, Sebastian

2018-04-21

This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX). However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption.

Sigma Routing Metric for RPL Protocol

PubMed Central

Rojas, Aldo; Fernandez, Luis

2018-01-01

This paper presents the adaptation of a specific metric for the RPL protocol in the objective function MRHOF. Among the functions standardized by IETF, we find OF0, which is based on the minimum hop count, as well as MRHOF, which is based on the Expected Transmission Count (ETX). However, when the network becomes denser or the number of nodes increases, both OF0 and MRHOF introduce long hops, which can generate a bottleneck that restricts the network. The adaptation is proposed to optimize both OFs through a new routing metric. To solve the above problem, the metrics of the minimum number of hops and the ETX are combined by designing a new routing metric called SIGMA-ETX, in which the best route is calculated using the standard deviation of ETX values between each node, as opposed to working with the ETX average along the route. This method ensures a better routing performance in dense sensor networks. The simulations are done through the Cooja simulator, based on the Contiki operating system. The simulations showed that the proposed optimization outperforms at a high margin in both OF0 and MRHOF, in terms of network latency, packet delivery ratio, lifetime, and power consumption. PMID:29690524

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks.

PubMed

Rehan, Waqas; Fischer, Stefan; Rehan, Maaz

2016-09-12

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end

Machine-Learning Based Channel Quality and Stability Estimation for Stream-Based Multichannel Wireless Sensor Networks

PubMed Central

Rehan, Waqas; Fischer, Stefan; Rehan, Maaz

2016-01-01

Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end

The role of complexity metrics in a multi-institutional dosimetry audit of VMAT

PubMed Central

Agnew, Christina E; Hussein, Mohammad; Tsang, Yatman; McWilliam, Alan; Hounsell, Alan R; Clark, Catharine H

2016-01-01

Objective: To demonstrate the benefit of complexity metrics such as the modulation complexity score (MCS) and monitor units (MUs) in multi-institutional audits of volumetric-modulated arc therapy (VMAT) delivery. Methods: 39 VMAT treatment plans were analysed using MCS and MU. A virtual phantom planning exercise was planned and independently measured using the PTW Octavius® phantom and seven29® 2D array (PTW-Freiburg GmbH, Freiburg, Germany). MCS and MU were compared with the median gamma index pass rates (2%/2 and 3%/3 mm) and plan quality. The treatment planning systems (TPS) were grouped by VMAT modelling being specifically designed for the linear accelerator manufacturer's own treatment delivery system (Type 1) or independent of vendor for VMAT delivery (Type 2). Differences in plan complexity (MCS and MU) between TPS types were compared. Results: For Varian® linear accelerators (Varian® Medical Systems, Inc., Palo Alto, CA), MCS and MU were significantly correlated with gamma pass rates. Type 2 TPS created poorer quality, more complex plans with significantly higher MUs and MCS than Type 1 TPS. Plan quality was significantly correlated with MU for Type 2 plans. A statistically significant correlation was observed between MU and MCS for all plans (R = −0.84, p < 0.01). Conclusion: MU and MCS have a role in assessing plan complexity in audits along with plan quality metrics. Plan complexity metrics give some indication of plan deliverability but should be analysed with plan quality. Advances in knowledge: Complexity metrics were investigated for a national rotational audit involving 34 institutions and they showed value. The metrics found that more complex plans were created for planning systems which were independent of vendor for VMAT delivery. PMID:26511276

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...

NASA metric transition plan

NASA Technical Reports Server (NTRS)

1992-01-01

NASA science publications have used the metric system of measurement since 1970. Although NASA has maintained a metric use policy since 1979, practical constraints have restricted actual use of metric units. In 1988, an amendment to the Metric Conversion Act of 1975 required the Federal Government to adopt the metric system except where impractical. In response to Public Law 100-418 and Executive Order 12770, NASA revised its metric use policy and developed this Metric Transition Plan. NASA's goal is to use the metric system for program development and functional support activities to the greatest practical extent by the end of 1995. The introduction of the metric system into new flight programs will determine the pace of the metric transition. Transition of institutional capabilities and support functions will be phased to enable use of the metric system in flight program development and operations. Externally oriented elements of this plan will introduce and actively support use of the metric system in education, public information, and small business programs. The plan also establishes a procedure for evaluating and approving waivers and exceptions to the required use of the metric system for new programs. Coordination with other Federal agencies and departments (through the Interagency Council on Metric Policy) and industry (directly and through professional societies and interest groups) will identify sources of external support and minimize duplication of effort.

Metric for evaluation of filter efficiency in spectral cameras.

PubMed

Nahavandi, Alireza Mahmoudi; Tehran, Mohammad Amani

2016-11-10

Although metric functions that show the performance of a colorimetric imaging device have been investigated, a metric for performance analysis of a set of filters in wideband filter-based spectral cameras has rarely been studied. Based on a generalization of Vora's Measure of Goodness (MOG) and the spanning theorem, a single function metric that estimates the effectiveness of a filter set is introduced. The improved metric, named MMOG, varies between one, for a perfect, and zero, for the worst possible set of filters. Results showed that MMOG exhibits a trend that is more similar to the mean square of spectral reflectance reconstruction errors than does Vora's MOG index, and it is robust to noise in the imaging system. MMOG as a single metric could be exploited for further analysis of manufacturing errors.

Early Warning Look Ahead Metrics: The Percent Milestone Backlog Metric

NASA Technical Reports Server (NTRS)

Shinn, Stephen A.; Anderson, Timothy P.

2017-01-01

All complex development projects experience delays and corresponding backlogs of their project control milestones during their acquisition lifecycles. NASA Goddard Space Flight Center (GSFC) Flight Projects Directorate (FPD) teamed with The Aerospace Corporation (Aerospace) to develop a collection of Early Warning Look Ahead metrics that would provide GSFC leadership with some independent indication of the programmatic health of GSFC flight projects. As part of the collection of Early Warning Look Ahead metrics, the Percent Milestone Backlog metric is particularly revealing, and has utility as a stand-alone execution performance monitoring tool. This paper describes the purpose, development methodology, and utility of the Percent Milestone Backlog metric. The other four Early Warning Look Ahead metrics are also briefly discussed. Finally, an example of the use of the Percent Milestone Backlog metric in providing actionable insight is described, along with examples of its potential use in other commodities.

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.

Optimal colour quality of LED clusters based on memory colours.

PubMed

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

2011-03-28

The spectral power distributions of tri- and tetrachromatic clusters of Light-Emitting-Diodes, composed of simulated and commercially available LEDs, were optimized with a genetic algorithm to maximize the luminous efficacy of radiation and the colour quality as assessed by the memory colour quality metric developed by the authors. The trade-off of the colour quality as assessed by the memory colour metric and the luminous efficacy of radiation was investigated by calculating the Pareto optimal front using the NSGA-II genetic algorithm. Optimal peak wavelengths and spectral widths of the LEDs were derived, and over half of them were found to be close to Thornton's prime colours. The Pareto optimal fronts of real LED clusters were always found to be smaller than those of the simulated clusters. The effect of binning on designing a real LED cluster was investigated and was found to be quite large. Finally, a real LED cluster of commercially available AlGaInP, InGaN and phosphor white LEDs was optimized to obtain a higher score on memory colour quality scale than its corresponding CIE reference illuminant.

Exploring s-CIELAB as a scanner metric for print uniformity

NASA Astrophysics Data System (ADS)

Hertel, Dirk W.

2005-01-01

The s-CIELAB color difference metric combines the standard CIELAB metric for perceived color difference with spatial contrast sensitivity filtering. When studying the performance of digital image processing algorithms, maps of spatial color difference between 'before' and 'after' images are a measure of perceived image difference. A general image quality metric can be obtained by modeling the perceived difference from an ideal image. This paper explores the s-CIELAB concept for evaluating the quality of digital prints. Prints present the challenge that the 'ideal print' which should serve as the reference when calculating the delta E* error map is unknown, and thus be estimated from the scanned print. A reasonable estimate of what the ideal print 'should have been' is possible at least for images of known content such as flat fields or continuous wedges, where the error map can be calculated against a global or local mean. While such maps showing the perceived error at each pixel are extremely useful when analyzing print defects, it is desirable to statistically reduce them to a more manageable dataset. Examples of digital print uniformity are given, and the effect of specific print defects on the s-CIELAB delta E* metric are discussed.

Digital Elevation Model from Non-Metric Camera in Uas Compared with LIDAR Technology

NASA Astrophysics Data System (ADS)

Dayamit, O. M.; Pedro, M. F.; Ernesto, R. R.; Fernando, B. L.

2015-08-01

Digital Elevation Model (DEM) data as a representation of surface topography is highly demanded for use in spatial analysis and modelling. Aimed to that issue many methods of acquisition data and process it are developed, from traditional surveying until modern technology like LIDAR. On the other hands, in a past four year the development of Unamend Aerial System (UAS) aimed to Geomatic bring us the possibility to acquire data about surface by non-metric digital camera on board in a short time with good quality for some analysis. Data collectors have attracted tremendous attention on UAS due to possibility of the determination of volume changes over time, monitoring of the breakwaters, hydrological modelling including flood simulation, drainage networks, among others whose support in DEM for proper analysis. The DEM quality is considered as a combination of DEM accuracy and DEM suitability so; this paper is aimed to analyse the quality of the DEM from non-metric digital camera on UAS compared with a DEM from LIDAR corresponding to same geographic space covering 4 km2 in Artemisa province, Cuba. This area is in a frame of urban planning whose need to know the topographic characteristics in order to analyse hydrology behaviour and decide the best place for make roads, building and so on. Base on LIDAR technology is still more accurate method, it offer us a pattern for test DEM from non-metric digital camera on UAS, whose are much more flexible and bring a solution for many applications whose needs DEM of detail.

Using Publication Metrics to Highlight Academic Productivity and Research Impact

PubMed Central

Carpenter, Christopher R.; Cone, David C.; Sarli, Cathy C.

2016-01-01

This article provides a broad overview of widely available measures of academic productivity and impact using publication data and highlights uses of these metrics for various purposes. Metrics based on publication data include measures such as number of publications, number of citations, the journal impact factor score, and the h-index, as well as emerging metrics based on document-level metrics. Publication metrics can be used for a variety of purposes for tenure and promotion, grant applications and renewal reports, benchmarking, recruiting efforts, and administrative purposes for departmental or university performance reports. The authors also highlight practical applications of measuring and reporting academic productivity and impact to emphasize and promote individual investigators, grant applications, or department output. PMID:25308141

Metrics-based assessments of research: incentives for 'institutional plagiarism'?

PubMed

Berry, Colin

2013-06-01

The issue of plagiarism--claiming credit for work that is not one's own, rightly, continues to cause concern in the academic community. An analysis is presented that shows the effects that may arise from metrics-based assessments of research, when credit for an author's outputs (chiefly publications) is given to an institution that did not support the research but which subsequently employs the author. The incentives for what is termed here "institutional plagiarism" are demonstrated with reference to the UK Research Assessment Exercise in which submitting units of assessment are shown in some instances to derive around twice the credit for papers produced elsewhere by new recruits, compared to papers produced 'in-house'.

High-quality cardiopulmonary resuscitation: current and future directions.

PubMed

Abella, Benjamin S

2016-06-01

Cardiopulmonary resuscitation (CPR) represents the cornerstone of cardiac arrest resuscitation care. Prompt delivery of high-quality CPR can dramatically improve survival outcomes; however, the definitions of optimal CPR have evolved over several decades. The present review will discuss the metrics of CPR delivery, and the evidence supporting the importance of CPR quality to improve clinical outcomes. The introduction of new technologies to quantify metrics of CPR delivery has yielded important insights into CPR quality. Investigations using CPR recording devices have allowed the assessment of specific CPR performance parameters and their relative importance regarding return of spontaneous circulation and survival to hospital discharge. Additional work has suggested new opportunities to measure physiologic markers during CPR and potentially tailor CPR delivery to patient requirements. Through recent laboratory and clinical investigations, a more evidence-based definition of high-quality CPR continues to emerge. Exciting opportunities now exist to study quantitative metrics of CPR and potentially guide resuscitation care in a goal-directed fashion. Concepts of high-quality CPR have also informed new approaches to training and quality improvement efforts for cardiac arrest care.

U50: A New Metric for Measuring Assembly Output Based on Non-Overlapping, Target-Specific Contigs.

PubMed

Castro, Christina J; Ng, Terry Fei Fan

2017-11-01

Advances in next-generation sequencing technologies enable routine genome sequencing, generating millions of short reads. A crucial step for full genome analysis is the de novo assembly, and currently, performance of different assembly methods is measured by a metric called N 50 . However, the N 50 value can produce skewed, inaccurate results when complex data are analyzed, especially for viral and microbial datasets. To provide a better assessment of assembly output, we developed a new metric called U 50 . The U 50 identifies unique, target-specific contigs by using a reference genome as baseline, aiming at circumventing some limitations that are inherent to the N 50 metric. Specifically, the U 50 program removes overlapping sequence of multiple contigs by utilizing a mask array, so the performance of the assembly is only measured by unique contigs. We compared simulated and real datasets by using U 50 and N 50 , and our results demonstrated that U 50 has the following advantages over N 50 : (1) reducing erroneously large N 50 values due to a poor assembly, (2) eliminating overinflated N 50 values caused by large measurements from overlapping contigs, (3) eliminating diminished N 50 values caused by an abundance of small contigs, and (4) allowing comparisons across different platforms or samples based on the new percentage-based metric UG 50 %. The use of the U 50 metric allows for a more accurate measure of assembly performance by analyzing only the unique, non-overlapping contigs. In addition, most viral and microbial sequencing have high background noise (i.e., host and other non-targets), which contributes to having a skewed, misrepresented N 50 value-this is corrected by U 50 . Also, the UG 50 % can be used to compare assembly results from different samples or studies, the cross-comparisons of which cannot be performed with N 50 .

It's A Metric World.

ERIC Educational Resources Information Center

Alabama State Dept. of Education, Montgomery. Div. of Instructional Services.

Topics covered in the first part of this document include eight advantages of the metric system; a summary of metric instruction; the International System of Units (SI) style and usage; metric decimal tables; the metric system; and conversion tables. An alphabetized list of organizations which market metric materials for educators is provided with…

How to measure ecosystem stability? An evaluation of the reliability of stability metrics based on remote sensing time series across the major global ecosystems.

PubMed

De Keersmaecker, Wanda; Lhermitte, Stef; Honnay, Olivier; Farifteh, Jamshid; Somers, Ben; Coppin, Pol

2014-07-01

Increasing frequency of extreme climate events is likely to impose increased stress on ecosystems and to jeopardize the services that ecosystems provide. Therefore, it is of major importance to assess the effects of extreme climate events on the temporal stability (i.e., the resistance, the resilience, and the variance) of ecosystem properties. Most time series of ecosystem properties are, however, affected by varying data characteristics, uncertainties, and noise, which complicate the comparison of ecosystem stability metrics (ESMs) between locations. Therefore, there is a strong need for a more comprehensive understanding regarding the reliability of stability metrics and how they can be used to compare ecosystem stability globally. The objective of this study was to evaluate the performance of temporal ESMs based on time series of the Moderate Resolution Imaging Spectroradiometer derived Normalized Difference Vegetation Index of 15 global land-cover types. We provide a framework (i) to assess the reliability of ESMs in function of data characteristics, uncertainties and noise and (ii) to integrate reliability estimates in future global ecosystem stability studies against climate disturbances. The performance of our framework was tested through (i) a global ecosystem comparison and (ii) an comparison of ecosystem stability in response to the 2003 drought. The results show the influence of data quality on the accuracy of ecosystem stability. White noise, biased noise, and trends have a stronger effect on the accuracy of stability metrics than the length of the time series, temporal resolution, or amount of missing values. Moreover, we demonstrate the importance of integrating reliability estimates to interpret stability metrics within confidence limits. Based on these confidence limits, other studies dealing with specific ecosystem types or locations can be put into context, and a more reliable assessment of ecosystem stability against environmental disturbances

Hydrologic metrics for status-and-trends monitoring in urban and urbanizing watersheds

USGS Publications Warehouse

Booth, Derek B.; Konrad, Christopher P.

2017-01-01

Local governmental agencies are increasingly undertaking potentially costly “status-and-trends” monitoring to evaluate the effectiveness of stormwater control measures and land-use planning strategies, or to satisfy regulatory requirements. Little guidance is presently available for such efforts, and so we have explored the application, interpretation, and temporal limitations of well-established hydrologic metrics of runoff changes from urbanization, making use of an unusually long-duration, high-quality data set from the Pacific Northwest (USA) with direct applicability to urban and urbanizing watersheds. Three metrics previously identified for their utility in identifying hydrologic conditions with biological importance that respond to watershed urbanization—TQmean (the fraction of time that flows exceed the mean annual discharge), the Richards-Baker Index (characterizing flashiness relative to the mean discharge), and the annual tally of wet-season day-to-day flow reversals (the total number of days that reverse the prior days’ increasing or decreasing trend)—are all successful in stratifying watersheds across a range of urbanization, as measured by total contributing area of urban development. All metrics respond with statistical significance to multi-decadal trends in urbanization, but none detect trends in watershed-scale urbanization over the course of a single decade. This suggests a minimum period over which dependable trends in hydrologic alteration (or improvement) can be detected with confidence. The metrics also prove less well suited to urbanizing watersheds in a semi-arid climate, with only flow reversals showing a response consistent with prior findings from more humid regions. We also explore the use of stage as a surrogate for discharge in calculating these metrics, recognizing potentially significant agency cost savings in data collection with minimal loss of information. This approach is feasible but cannot be implemented under

Sigma Metrics Across the Total Testing Process.

PubMed

Charuruks, Navapun

2017-03-01

Laboratory quality control has been developed for several decades to ensure patients' safety, from a statistical quality control focus on the analytical phase to total laboratory processes. The sigma concept provides a convenient way to quantify the number of errors in extra-analytical and analytical phases through the defect per million and sigma metric equation. Participation in a sigma verification program can be a convenient way to monitor analytical performance continuous quality improvement. Improvement of sigma-scale performance has been shown from our data. New tools and techniques for integration are needed. Copyright © 2016 Elsevier Inc. All rights reserved.

The Impact of Quality Assurance Assessment on Diffusion Tensor Imaging Outcomes in a Large-Scale Population-Based Cohort

PubMed Central

Roalf, David R.; Quarmley, Megan; Elliott, Mark A.; Satterthwaite, Theodore D.; Vandekar, Simon N.; Ruparel, Kosha; Gennatas, Efstathios D.; Calkins, Monica E.; Moore, Tyler M.; Hopson, Ryan; Prabhakaran, Karthik; Jackson, Chad T.; Verma, Ragini; Hakonarson, Hakon; Gur, Ruben C.; Gur, Raquel E.

2015-01-01

data. MAXVOX (AUC=0.88) best differentiated Good from Excellent DTI data. At the optimal threshold, 88% of Poor data and 91% Good/Excellent data were correctly identified. Use of these thresholds on a validation dataset (n=374) indicated high accuracy. In the validation sample 83% of Poor data and 94% of Excellent data was identified using thresholds derived from the training sample. Both FA and MD were affected by the inclusion of poor data in an analysis of age, sex and race in a matched comparison sample. In addition, we show that the inclusion of poor data results in significant attenuation of the correlation between diffusion metrics (FA and MD) and age during a critical neurodevelopmental period. We find higher correspondence between our QA method and DTIPrep for Poor data, but we find our method to be more robust for apparently high-quality images. Conclusion Automated QA of DTI can facilitate large-scale, high-throughput quality assurance by reliably identifying both scanner and subject induced imaging artifacts. The results present a practical example of the confounding effects of artifacts on DTI analysis in a large population-based sample, and suggest that estimates of data quality should not only be reported but also accounted for in data analysis, especially in studies of development. PMID:26520775

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.

A Metric on Phylogenetic Tree Shapes.

PubMed

Colijn, C; Plazzotta, G

2018-01-01

The shapes of evolutionary trees are influenced by the nature of the evolutionary process but comparisons of trees from different processes are hindered by the challenge of completely describing tree shape. We present a full characterization of the shapes of rooted branching trees in a form that lends itself to natural tree comparisons. We use this characterization to define a metric, in the sense of a true distance function, on tree shapes. The metric distinguishes trees from random models known to produce different tree shapes. It separates trees derived from tropical versus USA influenza A sequences, which reflect the differing epidemiology of tropical and seasonal flu. We describe several metrics based on the same core characterization, and illustrate how to extend the metric to incorporate trees' branch lengths or other features such as overall imbalance. Our approach allows us to construct addition and multiplication on trees, and to create a convex metric on tree shapes which formally allows computation of average tree shapes. © The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

Perceptual video quality assessment in H.264 video coding standard using objective modeling.

PubMed

Karthikeyan, Ramasamy; Sainarayanan, Gopalakrishnan; Deepa, Subramaniam Nachimuthu

2014-01-01

Since usage of digital video is wide spread nowadays, quality considerations have become essential, and industry demand for video quality measurement is rising. This proposal provides a method of perceptual quality assessment in H.264 standard encoder using objective modeling. For this purpose, quality impairments are calculated and a model is developed to compute the perceptual video quality metric based on no reference method. Because of the shuttle difference between the original video and the encoded video the quality of the encoded picture gets degraded, this quality difference is introduced by the encoding process like Intra and Inter prediction. The proposed model takes into account of the artifacts introduced by these spatial and temporal activities in the hybrid block based coding methods and an objective modeling of these artifacts into subjective quality estimation is proposed. The proposed model calculates the objective quality metric using subjective impairments; blockiness, blur and jerkiness compared to the existing bitrate only calculation defined in the ITU G 1070 model. The accuracy of the proposed perceptual video quality metrics is compared against popular full reference objective methods as defined by VQEG.

METRICS DEVELOPMENT FOR THE QUALIS OF SOFTWARE TECHNICAL PRODUCTION.

PubMed

Scarpi, Marinho Jorge

2015-01-01

To recommend metrics to qualify software production and to propose guidelines for the CAPES quadrennial evaluation of the Post-Graduation Programs of Medicine III about this issue. Identification of the development process quality features, of the product attributes and of the software use, determined by Brazilian Association of Technical Standards (ABNT), International Organization Standardization (ISO) and International Electrotechnical (IEC), important in the perspective of the CAPES Medicine III Area correlate users, basing the creation proposal of metrics aiming to be used on four-year evaluation of Medicine III. The in use software quality perception by the user results from the provided effectiveness, productivity, security and satisfaction that originate from its characteristics of functionality, reliability, usability, efficiency, maintainability and portability (in use metrics quality). This perception depends on the specific use scenario. The software metrics should be included in the intellectual production of the program, considering the system behavior measurements results obtained by users' performance evaluation through out the favorable responses punctuation sum for the six in use metrics quality (27 sub-items, 0 to 2 points each) and for quality perception proof (four items, 0 to 10 points each). It will be considered as very good (VG) 85 to 94 points; good (G) 75 to 84 points; regular (R) 65 to 74 points; weak (W) 55 to 64 points; poor (P) <55 points. Recomendar métrica para qualificar a produção de software propondo diretrizes para a avaliação dos Programas de Pós-Graduação da Medicina III. Identificação das características de qualidade para o processo de desenvolvimento, para os atributos do produto e para o uso de software, determinadas pela Associação Brasileira de Normas Técnicas (ABNT), International Organization Standardization (ISO) e International Electrotechnical (IEC), importantes na perspectiva dos usuários correlatos

Unsupervised Metric Fusion Over Multiview Data by Graph Random Walk-Based Cross-View Diffusion.

PubMed

Wang, Yang; Zhang, Wenjie; Wu, Lin; Lin, Xuemin; Zhao, Xiang

2017-01-01

Learning an ideal metric is crucial to many tasks in computer vision. Diverse feature representations may combat this problem from different aspects; as visual data objects described by multiple features can be decomposed into multiple views, thus often provide complementary information. In this paper, we propose a cross-view fusion algorithm that leads to a similarity metric for multiview data by systematically fusing multiple similarity measures. Unlike existing paradigms, we focus on learning distance measure by exploiting a graph structure of data samples, where an input similarity matrix can be improved through a propagation of graph random walk. In particular, we construct multiple graphs with each one corresponding to an individual view, and a cross-view fusion approach based on graph random walk is presented to derive an optimal distance measure by fusing multiple metrics. Our method is scalable to a large amount of data by enforcing sparsity through an anchor graph representation. To adaptively control the effects of different views, we dynamically learn view-specific coefficients, which are leveraged into graph random walk to balance multiviews. However, such a strategy may lead to an over-smooth similarity metric where affinities between dissimilar samples may be enlarged by excessively conducting cross-view fusion. Thus, we figure out a heuristic approach to controlling the iteration number in the fusion process in order to avoid over smoothness. Extensive experiments conducted on real-world data sets validate the effectiveness and efficiency of our approach.

In the pursuit of a semantic similarity metric based on UMLS annotations for articles in PubMed Central Open Access.

PubMed

Garcia Castro, Leyla Jael; Berlanga, Rafael; Garcia, Alexander

2015-10-01

Although full-text articles are provided by the publishers in electronic formats, it remains a challenge to find related work beyond the title and abstract context. Identifying related articles based on their abstract is indeed a good starting point; this process is straightforward and does not consume as many resources as full-text based similarity would require. However, further analyses may require in-depth understanding of the full content. Two articles with highly related abstracts can be substantially different regarding the full content. How similarity differs when considering title-and-abstract versus full-text and which semantic similarity metric provides better results when dealing with full-text articles are the main issues addressed in this manuscript. We have benchmarked three similarity metrics - BM25, PMRA, and Cosine, in order to determine which one performs best when using concept-based annotations on full-text documents. We also evaluated variations in similarity values based on title-and-abstract against those relying on full-text. Our test dataset comprises the Genomics track article collection from the 2005 Text Retrieval Conference. Initially, we used an entity recognition software to semantically annotate titles and abstracts as well as full-text with concepts defined in the Unified Medical Language System (UMLS®). For each article, we created a document profile, i.e., a set of identified concepts, term frequency, and inverse document frequency; we then applied various similarity metrics to those document profiles. We considered correlation, precision, recall, and F1 in order to determine which similarity metric performs best with concept-based annotations. For those full-text articles available in PubMed Central Open Access (PMC-OA), we also performed dispersion analyses in order to understand how similarity varies when considering full-text articles. We have found that the PubMed Related Articles similarity metric is the most suitable for

Development of quality metrics for ambulatory pediatric cardiology: Chest pain.

PubMed

Lu, Jimmy C; Bansal, Manish; Behera, Sarina K; Boris, Jeffrey R; Cardis, Brian; Hokanson, John S; Kakavand, Bahram; Jedeikin, Roy

2017-12-01

As part of the American College of Cardiology Adult Congenital and Pediatric Cardiology Section effort to develop quality metrics (QMs) for ambulatory pediatric practice, the chest pain subcommittee aimed to develop QMs for evaluation of chest pain. A group of 8 pediatric cardiologists formulated candidate QMs in the areas of history, physical examination, and testing. Consensus candidate QMs were submitted to an expert panel for scoring by the RAND-UCLA modified Delphi process. Recommended QMs were then available for open comments from all members. These QMs are intended for use in patients 5-18 years old, referred for initial evaluation of chest pain in an ambulatory pediatric cardiology clinic, with no known history of pediatric or congenital heart disease. A total of 10 candidate QMs were submitted; 2 were rejected by the expert panel, and 5 were removed after the open comment period. The 3 approved QMs included: (1) documentation of family history of cardiomyopathy, early coronary artery disease or sudden death, (2) performance of electrocardiogram in all patients, and (3) performance of an echocardiogram to evaluate coronary arteries in patients with exertional chest pain. Despite practice variation and limited prospective data, 3 QMs were approved, with measurable data points which may be extracted from the medical record. However, further prospective studies are necessary to define practice guidelines and to develop appropriate use criteria in this population. © 2017 Wiley Periodicals, Inc.

Blind image quality assessment based on aesthetic and statistical quality-aware features

NASA Astrophysics Data System (ADS)

Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi

2017-07-01

The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.

High-quality cardiopulmonary resuscitation.

PubMed

Nolan, Jerry P

2014-06-01

The quality of cardiopulmonary resuscitation (CPR) impacts on outcome after cardiac arrest. This review will explore the factors that contribute to high-quality CPR and the metrics that can be used to monitor performance. A recent consensus statement from North America defined five key components of high-quality CPR: minimizing interruptions in chest compressions, providing compressions of adequate rate and depth, avoiding leaning on the chest between compressions, and avoiding excessive ventilation. Studies have shown that real-time feedback devices improve the quality of CPR and, in one before-and-after study, outcome from out-of-hospital cardiac arrest. There is evidence for increasing survival rates following out-of-hospital cardiac arrest and this is associated with increasing rates of bystander CPR. The quality of CPR provided by healthcare professionals can be improved with real-time feedback devices. The components of high-quality CPR and the metrics that can be measured and fed back to healthcare professionals have been defined by expert consensus. In the future, real-time feedback based on the physiological responses to CPR may prove more effective.

Introduction to the special collection of papers on the San Luis Basin Sustainability Metrics Project: a methodology for evaluating regional sustainability.

PubMed

Heberling, Matthew T; Hopton, Matthew E

2012-11-30

This paper introduces a collection of four articles describing the San Luis Basin Sustainability Metrics Project. The Project developed a methodology for evaluating regional sustainability. This introduction provides the necessary background information for the project, description of the region, overview of the methods, and summary of the results. Although there are a multitude of scientifically based sustainability metrics, many are data intensive, difficult to calculate, and fail to capture all aspects of a system. We wanted to see if we could develop an approach that decision-makers could use to understand if their system was moving toward or away from sustainability. The goal was to produce a scientifically defensible, but straightforward and inexpensive methodology to measure and monitor environmental quality within a regional system. We initiated an interdisciplinary pilot project in the San Luis Basin, south-central Colorado, to test the methodology. The objectives were: 1) determine the applicability of using existing datasets to estimate metrics of sustainability at a regional scale; 2) calculate metrics through time from 1980 to 2005; and 3) compare and contrast the results to determine if the system was moving toward or away from sustainability. The sustainability metrics, chosen to represent major components of the system, were: 1) Ecological Footprint to capture the impact and human burden on the system; 2) Green Net Regional Product to represent economic welfare; 3) Emergy to capture the quality-normalized flow of energy through the system; and 4) Fisher information to capture the overall dynamic order and to look for possible regime changes. The methodology, data, and results of each metric are presented in the remaining four papers of the special collection. Based on the results of each metric and our criteria for understanding the sustainability trends, we find that the San Luis Basin is moving away from sustainability. Although we understand