Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11

PubMed Central

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-01-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. PMID:26369671

Performance evaluation of air quality models for predicting PM10 and PM2.5 concentrations at urban traffic intersection during winter period.

PubMed

Gokhale, Sharad; Raokhande, Namita

2008-05-01

There are several models that can be used to evaluate roadside air quality. The comparison of the operational performance of different models pertinent to local conditions is desirable so that the model that performs best can be identified. Three air quality models, namely the 'modified General Finite Line Source Model' (M-GFLSM) of particulates, the 'California Line Source' (CALINE3) model, and the 'California Line Source for Queuing & Hot Spot Calculations' (CAL3QHC) model have been identified for evaluating the air quality at one of the busiest traffic intersections in the city of Guwahati. These models have been evaluated statistically with the vehicle-derived airborne particulate mass emissions in two sizes, i.e. PM10 and PM2.5, the prevailing meteorology and the temporal distribution of the measured daily average PM10 and PM2.5 concentrations in wintertime. The study has shown that the CAL3QHC model would make better predictions compared to other models for varied meteorology and traffic conditions. The detailed study reveals that the agreements between the measured and the modeled PM10 and PM2.5 concentrations have been reasonably good for CALINE3 and CAL3QHC models. Further detailed analysis shows that the CAL3QHC model performed well compared to the CALINE3. The monthly performance measures have also led to the similar results. These two models have also outperformed for a class of wind speed velocities except for low winds (<1 m s(-1)), for which, the M-GFLSM model has shown the tendency of better performance for PM10. Nevertheless, the CAL3QHC model has outperformed for both the particulate sizes and for all the wind classes, which therefore can be optional for air quality assessment at urban traffic intersections.

Preliminary Evaluation of Air Quality Model Performance Utilizing Measurements at the University of Houston Moody Tower and others during the TexAQS-II

NASA Astrophysics Data System (ADS)

Byun, D. W.; Rappenglueck, B.; Lefer, B.

2007-12-01

Accurate meteorological and photochemical modeling efforts are necessary to understand the measurements made during the Texas Air Quality Study (TexAQS-II). The main objective of the study is to understand the meteorological and chemical processes of high ozone and regional haze events in the Eastern Texas, including the Houston-Galveston metropolitan area. Real-time and retrospective meteorological and photochemical model simulations were performed to study key physical and chemical processes in the Houston Galveston Area. In particular, the Vertical Mixing Experiment (VME) at the University of Houston campus was performed on selected days during the TexAQS-II. Results of the MM5 meteorological model and CMAQ air quality model simulations were compared with the VME and other TexAQS-II measurements to understand the interaction of the boundary layer dynamics and photochemical evolution affecting Houston air quality.

Prediction of HDR quality by combining perceptually transformed display measurements with machine learning

NASA Astrophysics Data System (ADS)

Choudhury, Anustup; Farrell, Suzanne; Atkins, Robin; Daly, Scott

2017-09-01

We present an approach to predict overall HDR display quality as a function of key HDR display parameters. We first performed subjective experiments on a high quality HDR display that explored five key HDR display parameters: maximum luminance, minimum luminance, color gamut, bit-depth and local contrast. Subjects rated overall quality for different combinations of these display parameters. We explored two models | a physical model solely based on physically measured display characteristics and a perceptual model that transforms physical parameters using human vision system models. For the perceptual model, we use a family of metrics based on a recently published color volume model (ICT-CP), which consists of the PQ luminance non-linearity (ST2084) and LMS-based opponent color, as well as an estimate of the display point spread function. To predict overall visual quality, we apply linear regression and machine learning techniques such as Multilayer Perceptron, RBF and SVM networks. We use RMSE and Pearson/Spearman correlation coefficients to quantify performance. We found that the perceptual model is better at predicting subjective quality than the physical model and that SVM is better at prediction than linear regression. The significance and contribution of each display parameter was investigated. In addition, we found that combined parameters such as contrast do not improve prediction. Traditional perceptual models were also evaluated and we found that models based on the PQ non-linearity performed better.

Information system success model for customer relationship management system in health promotion centers.

PubMed

Choi, Wona; Rho, Mi Jung; Park, Jiyun; Kim, Kwang-Jum; Kwon, Young Dae; Choi, In Young

2013-06-01

Intensified competitiveness in the healthcare industry has increased the number of healthcare centers and propelled the introduction of customer relationship management (CRM) systems to meet diverse customer demands. This study aimed to develop the information system success model of the CRM system by investigating previously proposed indicators within the model. THE EVALUATION AREAS OF THE CRM SYSTEM INCLUDES THREE AREAS: the system characteristics area (system quality, information quality, and service quality), the user area (perceived usefulness and user satisfaction), and the performance area (personal performance and organizational performance). Detailed evaluation criteria of the three areas were developed, and its validity was verified by a survey administered to CRM system users in 13 nationwide health promotion centers. The survey data were analyzed by the structural equation modeling method, and the results confirmed that the model is feasible. Information quality and service quality showed a statistically significant relationship with perceived usefulness and user satisfaction. Consequently, the perceived usefulness and user satisfaction had significant influence on individual performance as well as an indirect influence on organizational performance. This study extends the research area on information success from general information systems to CRM systems in health promotion centers applying a previous information success model. This lays a foundation for evaluating health promotion center systems and provides a useful guide for successful implementation of hospital CRM systems.

Information System Success Model for Customer Relationship Management System in Health Promotion Centers

PubMed Central

Choi, Wona; Rho, Mi Jung; Park, Jiyun; Kim, Kwang-Jum; Kwon, Young Dae

2013-01-01

Objectives Intensified competitiveness in the healthcare industry has increased the number of healthcare centers and propelled the introduction of customer relationship management (CRM) systems to meet diverse customer demands. This study aimed to develop the information system success model of the CRM system by investigating previously proposed indicators within the model. Methods The evaluation areas of the CRM system includes three areas: the system characteristics area (system quality, information quality, and service quality), the user area (perceived usefulness and user satisfaction), and the performance area (personal performance and organizational performance). Detailed evaluation criteria of the three areas were developed, and its validity was verified by a survey administered to CRM system users in 13 nationwide health promotion centers. The survey data were analyzed by the structural equation modeling method, and the results confirmed that the model is feasible. Results Information quality and service quality showed a statistically significant relationship with perceived usefulness and user satisfaction. Consequently, the perceived usefulness and user satisfaction had significant influence on individual performance as well as an indirect influence on organizational performance. Conclusions This study extends the research area on information success from general information systems to CRM systems in health promotion centers applying a previous information success model. This lays a foundation for evaluating health promotion center systems and provides a useful guide for successful implementation of hospital CRM systems. PMID:23882416

Performance of ANFIS versus MLP-NN dissolved oxygen prediction models in water quality monitoring.

PubMed

Najah, A; El-Shafie, A; Karim, O A; El-Shafie, Amr H

2014-02-01

We discuss the accuracy and performance of the adaptive neuro-fuzzy inference system (ANFIS) in training and prediction of dissolved oxygen (DO) concentrations. The model was used to analyze historical data generated through continuous monitoring of water quality parameters at several stations on the Johor River to predict DO concentrations. Four water quality parameters were selected for ANFIS modeling, including temperature, pH, nitrate (NO3) concentration, and ammoniacal nitrogen concentration (NH3-NL). Sensitivity analysis was performed to evaluate the effects of the input parameters. The inputs with the greatest effect were those related to oxygen content (NO3) or oxygen demand (NH3-NL). Temperature was the parameter with the least effect, whereas pH provided the lowest contribution to the proposed model. To evaluate the performance of the model, three statistical indices were used: the coefficient of determination (R (2)), the mean absolute prediction error, and the correlation coefficient. The performance of the ANFIS model was compared with an artificial neural network model. The ANFIS model was capable of providing greater accuracy, particularly in the case of extreme events.

Assessment and prediction of air quality using fuzzy logic and autoregressive models

NASA Astrophysics Data System (ADS)

Carbajal-Hernández, José Juan; Sánchez-Fernández, Luis P.; Carrasco-Ochoa, Jesús A.; Martínez-Trinidad, José Fco.

2012-12-01

In recent years, artificial intelligence methods have been used for the treatment of environmental problems. This work, presents two models for assessment and prediction of air quality. First, we develop a new computational model for air quality assessment in order to evaluate toxic compounds that can harm sensitive people in urban areas, affecting their normal activities. In this model we propose to use a Sigma operator to statistically asses air quality parameters using their historical data information and determining their negative impact in air quality based on toxicity limits, frequency average and deviations of toxicological tests. We also introduce a fuzzy inference system to perform parameter classification using a reasoning process and integrating them in an air quality index describing the pollution levels in five stages: excellent, good, regular, bad and danger, respectively. The second model proposed in this work predicts air quality concentrations using an autoregressive model, providing a predicted air quality index based on the fuzzy inference system previously developed. Using data from Mexico City Atmospheric Monitoring System, we perform a comparison among air quality indices developed for environmental agencies and similar models. Our results show that our models are an appropriate tool for assessing site pollution and for providing guidance to improve contingency actions in urban areas.

Linking Quality and Spending to Measure Value for People with Serious Illness.

PubMed

Ryan, Andrew M; Rodgers, Phillip E

2018-03-01

Healthcare payment is rapidly evolving to reward value by measuring and paying for quality and spending performance. Rewarding value for the care of seriously ill patients presents unique challenges. To evaluate the state of current efforts to measure and reward value for the care of seriously ill patients. We performed a PubMed search of articles related to (1) measures of spending for people with serious illness and (2) linking spending and quality measures and rewarding performance for the care of people with serious illness. We limited our search to U.S.-based studies published in English between January 1, 1960, and March 31, 2017. We supplemented this search by identifying public programs and other known initiatives that linked quality and spending for the seriously ill and extracted key program elements. Our search related to linking spending and quality measures and rewarding performance for the care of people with serious illness yielded 277 articles. We identified three current public programs that currently link measures of quality and spending-or are likely to within the next few years-the Oncology Care Model; the Comprehensive End-Stage Renal Disease Model; and Home Health Value-Based Purchasing. Models that link quality and spending consist of four core components: (1) measuring quality, (2) measuring spending, (3) the payment adjustment model, and (4) the linking/incentive model. We found that current efforts to reward value for seriously ill patients are targeted for specific patient populations, do not broadly encourage the use of palliative care, and have not closely aligned quality and spending measures related to palliative care. We develop recommendations for policymakers and stakeholders about how measures of spending and quality can be balanced in value-based payment programs.

Linking Quality and Spending to Measure Value for People with Serious Illness

PubMed Central

Rodgers, Phillip E.

2018-01-01

Abstract Background: Healthcare payment is rapidly evolving to reward value by measuring and paying for quality and spending performance. Rewarding value for the care of seriously ill patients presents unique challenges. Objective: To evaluate the state of current efforts to measure and reward value for the care of seriously ill patients. Design: We performed a PubMed search of articles related to (1) measures of spending for people with serious illness and (2) linking spending and quality measures and rewarding performance for the care of people with serious illness. We limited our search to U.S.-based studies published in English between January 1, 1960, and March 31, 2017. We supplemented this search by identifying public programs and other known initiatives that linked quality and spending for the seriously ill and extracted key program elements. Results: Our search related to linking spending and quality measures and rewarding performance for the care of people with serious illness yielded 277 articles. We identified three current public programs that currently link measures of quality and spending—or are likely to within the next few years—the Oncology Care Model; the Comprehensive End-Stage Renal Disease Model; and Home Health Value-Based Purchasing. Models that link quality and spending consist of four core components: (1) measuring quality, (2) measuring spending, (3) the payment adjustment model, and (4) the linking/incentive model. We found that current efforts to reward value for seriously ill patients are targeted for specific patient populations, do not broadly encourage the use of palliative care, and have not closely aligned quality and spending measures related to palliative care. Conclusions: We develop recommendations for policymakers and stakeholders about how measures of spending and quality can be balanced in value-based payment programs. PMID:29091529

Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2016-09-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. Proteins 2016; 84(Suppl 1):247-259. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

AIR QUALITY SIMULATION MODEL PERFORMANCE FOR ONE-HOUR AVERAGES

EPA Science Inventory

If a one-hour standard for sulfur dioxide were promulgated, air quality dispersion modeling in the vicinity of major point sources would be an important air quality management tool. Would currently available dispersion models be suitable for use in demonstrating attainment of suc...

Using satellite observations in performance evaluation for regulatory air quality modeling: Comparison with ground-level measurements

NASA Astrophysics Data System (ADS)

Odman, M. T.; Hu, Y.; Russell, A.; Chai, T.; Lee, P.; Shankar, U.; Boylan, J.

2012-12-01

Regulatory air quality modeling, such as State Implementation Plan (SIP) modeling, requires that model performance meets recommended criteria in the base-year simulations using period-specific, estimated emissions. The goal of the performance evaluation is to assure that the base-year modeling accurately captures the observed chemical reality of the lower troposphere. Any significant deficiencies found in the performance evaluation must be corrected before any base-case (with typical emissions) and future-year modeling is conducted. Corrections are usually made to model inputs such as emission-rate estimates or meteorology and/or to the air quality model itself, in modules that describe specific processes. Use of ground-level measurements that follow approved protocols is recommended for evaluating model performance. However, ground-level monitoring networks are spatially sparse, especially for particulate matter. Satellite retrievals of atmospheric chemical properties such as aerosol optical depth (AOD) provide spatial coverage that can compensate for the sparseness of ground-level measurements. Satellite retrievals can also help diagnose potential model or data problems in the upper troposphere. It is possible to achieve good model performance near the ground, but have, for example, erroneous sources or sinks in the upper troposphere that may result in misleading and unrealistic responses to emission reductions. Despite these advantages, satellite retrievals are rarely used in model performance evaluation, especially for regulatory modeling purposes, due to the high uncertainty in retrievals associated with various contaminations, for example by clouds. In this study, 2007 was selected as the base year for SIP modeling in the southeastern U.S. Performance of the Community Multiscale Air Quality (CMAQ) model, at a 12-km horizontal resolution, for this annual simulation is evaluated using both recommended ground-level measurements and non-traditional satellite retrievals. Evaluation results are assessed against recommended criteria and peer studies in the literature. Further analysis is conducted, based upon these assessments, to discover likely errors in model inputs and potential deficiencies in the model itself. Correlations as well as differences in input errors and model deficiencies revealed by ground-level measurements versus satellite observations are discussed. Additionally, sensitivity analyses are employed to investigate errors in emission-rate estimates using either ground-level measurements or satellite retrievals, and the results are compared against each other considering observational uncertainties. Recommendations are made for how to effectively utilize satellite retrievals in regulatory air quality modeling.

A Multi-Resolution Assessment of the Community Multiscale Air Quality (CMAQ) Model v4.7 Wet Deposition Estimates for 2002 - 2006

EPA Science Inventory

This paper examines the operational performance of the Community Multiscale Air Quality (CMAQ) model simulations for 2002 - 2006 using both 36-km and 12-km horizontal grid spacing, with a primary focus on the performance of the CMAQ model in predicting wet deposition of sulfate (...

A simple parametric model observer for quality assurance in computer tomography

NASA Astrophysics Data System (ADS)

Anton, M.; Khanin, A.; Kretz, T.; Reginatto, M.; Elster, C.

2018-04-01

Model observers are mathematical classifiers that are used for the quality assessment of imaging systems such as computer tomography. The quality of the imaging system is quantified by means of the performance of a selected model observer. For binary classification tasks, the performance of the model observer is defined by the area under its ROC curve (AUC). Typically, the AUC is estimated by applying the model observer to a large set of training and test data. However, the recording of these large data sets is not always practical for routine quality assurance. In this paper we propose as an alternative a parametric model observer that is based on a simple phantom, and we provide a Bayesian estimation of its AUC. It is shown that a limited number of repeatedly recorded images (10–15) is already sufficient to obtain results suitable for the quality assessment of an imaging system. A MATLAB® function is provided for the calculation of the results. The performance of the proposed model observer is compared to that of the established channelized Hotelling observer and the nonprewhitening matched filter for simulated images as well as for images obtained from a low-contrast phantom on an x-ray tomography scanner. The results suggest that the proposed parametric model observer, along with its Bayesian treatment, can provide an efficient, practical alternative for the quality assessment of CT imaging systems.

Dynamic Evaluation of Long-Term Air Quality Model Simulations Over the Northeastern U.S.

EPA Science Inventory

Dynamic model evaluation assesses a modeling system's ability to reproduce changes in air quality induced by changes in meteorology and/or emissions. In this paper, we illustrate various approaches to dynamic mode evaluation utilizing 18 years of air quality simulations perform...

Regionalized PM2.5 Community Multiscale Air Quality model performance evaluation across a continuous spatiotemporal domain.

PubMed

Reyes, Jeanette M; Xu, Yadong; Vizuete, William; Serre, Marc L

2017-01-01

The regulatory Community Multiscale Air Quality (CMAQ) model is a means to understanding the sources, concentrations and regulatory attainment of air pollutants within a model's domain. Substantial resources are allocated to the evaluation of model performance. The Regionalized Air quality Model Performance (RAMP) method introduced here explores novel ways of visualizing and evaluating CMAQ model performance and errors for daily Particulate Matter ≤ 2.5 micrometers (PM2.5) concentrations across the continental United States. The RAMP method performs a non-homogenous, non-linear, non-homoscedastic model performance evaluation at each CMAQ grid. This work demonstrates that CMAQ model performance, for a well-documented 2001 regulatory episode, is non-homogeneous across space/time. The RAMP correction of systematic errors outperforms other model evaluation methods as demonstrated by a 22.1% reduction in Mean Square Error compared to a constant domain wide correction. The RAMP method is able to accurately reproduce simulated performance with a correlation of r = 76.1%. Most of the error coming from CMAQ is random error with only a minority of error being systematic. Areas of high systematic error are collocated with areas of high random error, implying both error types originate from similar sources. Therefore, addressing underlying causes of systematic error will have the added benefit of also addressing underlying causes of random error.

Preliminary evaluation of the Community Multiscale Air Quality model for 2002 over the Southeastern United States.

PubMed

Morris, Ralph E; McNally, Dennis E; Tesche, Thomas W; Tonnesen, Gail; Boylan, James W; Brewer, Patricia

2005-11-01

The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within +/-20%. Nitrate is overestimated in the winter by approximately +50% and underestimated in the summer by more than -100%. Organic carbon exhibits a large summer underestimation bias of approximately -100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within +/- 40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve nitrate performance and addressing missing processes in the secondary organic aerosol module to improve OC performance.

Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors.

PubMed

Heddam, Salim; Kisi, Ozgur

2017-07-01

In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme learning machine (OS-ELM), and optimally pruned extreme learning machine (OP-ELM), are newly applied for predicting dissolved oxygen concentration with and without water quality variables as predictors. Firstly, using data from eight United States Geological Survey (USGS) stations located in different rivers basins, USA, the S-ELM, R-ELM, OS-ELM, and OP-ELM were compared against the measured dissolved oxygen (DO) using four water quality variables, water temperature, specific conductance, turbidity, and pH, as predictors. For each station, we used data measured at an hourly time step for a period of 4 years. The dataset was divided into a training set (70%) and a validation set (30%). We selected several combinations of the water quality variables as inputs for each ELM model and six different scenarios were compared. Secondly, an attempt was made to predict DO concentration without water quality variables. To achieve this goal, we used the year numbers, 2008, 2009, etc., month numbers from (1) to (12), day numbers from (1) to (31) and hour numbers from (00:00) to (24:00) as predictors. Thirdly, the best ELM models were trained using validation dataset and tested with the training dataset. The performances of the four ELM models were evaluated using four statistical indices: the coefficient of correlation (R), the Nash-Sutcliffe efficiency (NSE), the root mean squared error (RMSE), and the mean absolute error (MAE). Results obtained from the eight stations indicated that: (i) the best results were obtained by the S-ELM, R-ELM, OS-ELM, and OP-ELM models having four water quality variables as predictors; (ii) out of eight stations, the OP-ELM performed better than the other three ELM models at seven stations while the R-ELM performed the best at one station. The OS-ELM models performed the worst and provided the lowest accuracy; (iii) for predicting DO without water quality variables, the R-ELM performed the best at seven stations followed by the S-ELM in the second place and the OP-ELM performed the worst with low accuracy; (iv) for the final application where training ELM models with validation dataset and testing with training dataset, the OP-ELM provided the best accuracy using water quality variables and the R-ELM performed the best at all eight stations without water quality variables. Fourthly, and finally, we compared the results obtained from different ELM models with those obtained using multiple linear regression (MLR) and multilayer perceptron neural network (MLPNN). Results obtained using MLPNN and MLR models reveal that: (i) using water quality variables as predictors, the MLR performed the worst and provided the lowest accuracy in all stations; (ii) MLPNN was ranked in the second place at two stations, in the third place at four stations, and finally, in the fourth place at two stations, (iii) for predicting DO without water quality variables, MLPNN is ranked in the second place at five stations, and ranked in the third, fourth, and fifth places in the remaining three stations, while MLR was ranked in the last place with very low accuracy at all stations. Overall, the results suggest that the ELM is more effective than the MLPNN and MLR for modelling DO concentration in river ecosystems.

DeepQA: improving the estimation of single protein model quality with deep belief networks.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

2016-12-05

Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

42 CFR § 510.300 - Determination of episode quality-adjusted target prices.

Code of Federal Regulations, 2010 CFR

2017-10-01

... OF HEALTH AND HUMAN SERVICES (CONTINUED) HEALTH CARE INFRASTRUCTURE AND MODEL PROGRAMS COMPREHENSIVE CARE FOR JOINT REPLACEMENT MODEL Pricing and Payment § 510.300 Determination of episode quality... hospitals for each performance year of the model as specified in this section. Episode quality-adjusted...

Dynamic Evaluation of a Regional Air Quality Model: Assessing the Emissions-Induced Weekly Ozone Cycle

EPA Science Inventory

Air quality models are used to predict changes in pollutant concentrations resulting from envisioned emission control policies. Recognizing the need to assess the credibility of air quality models in a policy-relevant context, we perform a dynamic evaluation of the community Mult...

Evaluating Performance Measurement Systems in Nonprofit Agencies: The Program Accountability Quality Scale (PAQS).

ERIC Educational Resources Information Center

Poole, Dennis L.; Nelson, Joan; Carnahan, Sharon; Chepenik, Nancy G.; Tubiak, Christine

2000-01-01

Developed and field tested the Performance Accountability Quality Scale (PAQS) on 191 program performance measurement systems developed by nonprofit agencies in central Florida. Preliminary findings indicate that the PAQS provides a structure for obtaining expert opinions based on a theory-driven model about the quality of proposed measurement…

NEIGHBORHOOD SCALE AIR QUALITY MODELING IN HOUSTON USING URBAN CANOPY PARAMETERS IN MM5 AND CMAQ WITH IMPROVED CHARACTERIZATION OF MESOSCALE LAKE-LAND BREEZE CIRCULATION

EPA Science Inventory

Advanced capability of air quality simulation models towards accurate performance at finer scales will be needed for such models to serve as tools for performing exposure and risk assessments in urban areas. It is recognized that the impact of urban features such as street and t...

Performance Summary of the 2006 Community Multiscale Air Quality (CMAQ) Simulation for the AQMEII Project: North American Application

EPA Science Inventory

The CMAQ modeling system has been used to simulate the CONUS using 12-km by 12-km horizontal grid spacing for the entire year of 2006 as part of the Air Quality Model Evaluation International initiative (AQMEII). The operational model performance for O₃ and PM_2.5<...

Influence of Boundary Conditions on Regional Air Quality Simulations—Analysis of AQMEII Phase 3 Results

EPA Science Inventory

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, performed during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), we perform annual simulations over North America with chemical boundary con...

Blind prediction of natural video quality.

PubMed

Saad, Michele A; Bovik, Alan C; Charrier, Christophe

2014-03-01

We propose a blind (no reference or NR) video quality evaluation model that is nondistortion specific. The approach relies on a spatio-temporal model of video scenes in the discrete cosine transform domain, and on a model that characterizes the type of motion occurring in the scenes, to predict video quality. We use the models to define video statistics and perceptual features that are the basis of a video quality assessment (VQA) algorithm that does not require the presence of a pristine video to compare against in order to predict a perceptual quality score. The contributions of this paper are threefold. 1) We propose a spatio-temporal natural scene statistics (NSS) model for videos. 2) We propose a motion model that quantifies motion coherency in video scenes. 3) We show that the proposed NSS and motion coherency models are appropriate for quality assessment of videos, and we utilize them to design a blind VQA algorithm that correlates highly with human judgments of quality. The proposed algorithm, called video BLIINDS, is tested on the LIVE VQA database and on the EPFL-PoliMi video database and shown to perform close to the level of top performing reduced and full reference VQA algorithms.

Comparing observed and predicted mortality among ICUs using different prognostic systems: why do performance assessments differ?

PubMed

Kramer, Andrew A; Higgins, Thomas L; Zimmerman, Jack E

2015-02-01

To compare ICU performance using standardized mortality ratios generated by the Acute Physiology and Chronic Health Evaluation IVa and a National Quality Forum-endorsed methodology and examine potential reasons for model-based standardized mortality ratio differences. Retrospective analysis of day 1 hospital mortality predictions at the ICU level using Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum models on the same patient cohort. Forty-seven ICUs at 36 U.S. hospitals from January 2008 to May 2013. Eighty-nine thousand three hundred fifty-three consecutive unselected ICU admissions. None. We assessed standardized mortality ratios for each ICU using data for patients eligible for Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum predictions in order to compare unit-level model performance, differences in ICU rankings, and how case-mix adjustment might explain standardized mortality ratio differences. Hospital mortality was 11.5%. Overall standardized mortality ratio was 0.89 using Acute Physiology and Chronic Health Evaluation IVa and 1.07 using National Quality Forum, the latter having a widely dispersed and multimodal standardized mortality ratio distribution. Model exclusion criteria eliminated mortality predictions for 10.6% of patients for Acute Physiology and Chronic Health Evaluation IVa and 27.9% for National Quality Forum. The two models agreed on the significance and direction of standardized mortality ratio only 45% of the time. Four ICUs had standardized mortality ratios significantly less than 1.0 using Acute Physiology and Chronic Health Evaluation IVa, but significantly greater than 1.0 using National Quality Forum. Two ICUs had standardized mortality ratios exceeding 1.75 using National Quality Forum, but nonsignificant performance using Acute Physiology and Chronic Health Evaluation IVa. Stratification by patient and institutional characteristics indicated that units caring for more severely ill patients and those with a higher percentage of patients on mechanical ventilation had the most discordant standardized mortality ratios between the two predictive models. Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum models yield different ICU performance assessments due to differences in case-mix adjustment. Given the growing role of outcomes in driving prospective payment patient referral and public reporting, performance should be assessed by models with fewer exclusions, superior accuracy, and better case-mix adjustment.

Data envelopment analysis in service quality evaluation: an empirical study

NASA Astrophysics Data System (ADS)

Najafi, Seyedvahid; Saati, Saber; Tavana, Madjid

2015-09-01

Service quality is often conceptualized as the comparison between service expectations and the actual performance perceptions. It enhances customer satisfaction, decreases customer defection, and promotes customer loyalty. Substantial literature has examined the concept of service quality, its dimensions, and measurement methods. We introduce the perceived service quality index (PSQI) as a single measure for evaluating the multiple-item service quality construct based on the SERVQUAL model. A slack-based measure (SBM) of efficiency with constant inputs is used to calculate the PSQI. In addition, a non-linear programming model based on the SBM is proposed to delineate an improvement guideline and improve service quality. An empirical study is conducted to assess the applicability of the method proposed in this study. A large number of studies have used DEA as a benchmarking tool to measure service quality. These models do not propose a coherent performance evaluation construct and consequently fail to deliver improvement guidelines for improving service quality. The DEA models proposed in this study are designed to evaluate and improve service quality within a comprehensive framework and without any dependency on external data.

Simulation of atmospheric oxidation capacity in Houston, Texas

EPA Science Inventory

Air quality model simulations are performed and evaluated for Houston using the Community Multiscale Air Quality (CMAQ) model. The simulations use two different emissions estimates: the EPA 2005 National Emissions Inventory (NEI) and the Texas Commission on Environmental Quality ...

Air Quality Modeling Technical Support Document for the Final Cross State Air Pollution Rule Update

EPA Pesticide Factsheets

In this technical support document (TSD) we describe the air quality modeling performed to support the final Cross State Air Pollution Rule for the 2008 ozone National Ambient Air Quality Standards (NAAQS).

Temporal evolution modeling of hydraulic and water quality performance of permeable pavements

NASA Astrophysics Data System (ADS)

Huang, Jian; He, Jianxun; Valeo, Caterina; Chu, Angus

2016-02-01

A mathematical model for predicting hydraulic and water quality performance in both the short- and long-term is proposed based on field measurements for three types of permeable pavements: porous asphalt (PA), porous concrete (PC), and permeable inter-locking concrete pavers (PICP). The model was applied to three field-scale test sites in Calgary, Alberta, Canada. The model performance was assessed in terms of hydraulic parameters including time to peak, peak flow and water balance and a water quality variable (the removal rate of total suspended solids). A total of 20 simulated storm events were used for model calibration and verification processes. The proposed model can simulate the outflow hydrographs with a coefficient of determination (R2) ranging from 0.762 to 0.907, and normalized root-mean-square deviation (NRMSD) ranging from 13.78% to 17.83%. Comparison of the time to peak flow, peak flow, runoff volume and TSS removal rates between the measured and modeled values in model verification phase had a maximum difference of 11%. The results demonstrate that the proposed model is capable of capturing the temporal dynamics of the pavement performance. Therefore, the model has great potential as a practical modeling tool for permeable pavement design and performance assessment.

A systematic literature review of open source software quality assessment models.

PubMed

Adewumi, Adewole; Misra, Sanjay; Omoregbe, Nicholas; Crawford, Broderick; Soto, Ricardo

2016-01-01

Many open source software (OSS) quality assessment models are proposed and available in the literature. However, there is little or no adoption of these models in practice. In order to guide the formulation of newer models so they can be acceptable by practitioners, there is need for clear discrimination of the existing models based on their specific properties. Based on this, the aim of this study is to perform a systematic literature review to investigate the properties of the existing OSS quality assessment models by classifying them with respect to their quality characteristics, the methodology they use for assessment, and their domain of application so as to guide the formulation and development of newer models. Searches in IEEE Xplore, ACM, Science Direct, Springer and Google Search is performed so as to retrieve all relevant primary studies in this regard. Journal and conference papers between the year 2003 and 2015 were considered since the first known OSS quality model emerged in 2003. A total of 19 OSS quality assessment model papers were selected. To select these models we have developed assessment criteria to evaluate the quality of the existing studies. Quality assessment models are classified into five categories based on the quality characteristics they possess namely: single-attribute, rounded category, community-only attribute, non-community attribute as well as the non-quality in use models. Our study reflects that software selection based on hierarchical structures is found to be the most popular selection method in the existing OSS quality assessment models. Furthermore, we found that majority (47%) of the existing models do not specify any domain of application. In conclusion, our study will be a valuable contribution to the community and helps the quality assessment model developers in formulating newer models and also to the practitioners (software evaluators) in selecting suitable OSS in the midst of alternatives.

Air Quality Modeling Technical Support Document for the 2008 Ozone NAAQS Cross-State Air Pollution Rule Proposal

EPA Pesticide Factsheets

In this technical support document (TSD) we describe the air quality modeling performed to support the proposed Cross-State Air Pollution Rule for the 2008 ozone National Ambient Air Quality Standards (NAAQS)

Air Quality Modeling Technical Support Document for the 2015 Ozone NAAQS Preliminary Interstate Transport Assessment

EPA Pesticide Factsheets

In this technical support document (TSD) EPA describes the air quality modeling performed to support the 2015 ozone National Ambient Air Quality Standards (NAAQS) preliminary interstate transport assessment Notice of Data Availability (NODA).

The Third Phase of AQMEII: Evaluation Strategy and Multi-Model Performance Analysis

EPA Science Inventory

AQMEII (Air Quality Model Evaluation International Initiative) is an extraordinary effort promoting policy-relevant research on regional air quality model evaluation across the European and North American atmospheric modelling communities, providing the ideal platform for advanci...

The Mediating Effect of Innovation between Total Quality Management (TQM) and Business Performance

NASA Astrophysics Data System (ADS)

Shan, Ang Wei; Fauzi Ahmad, Mohd; Hisyamudin Muhd Nor, Nik

2016-11-01

Both TQM and Innovation are the competitive key factors that intensely embedded into organizational products, service and process. In order to achieve higher business performance, organizations are needed to adopt both quality and innovation. Therefore, the main objective of this paper is to identify the relationship between TQM and business performance with a mediator's effect of Innovation. After detailed review the extensive literature, a new TQM model is presented. The proposed model integrates the TQM practices and different type of innovation attempt to develop a theoretical knowledge to help academician and manufacturer to understand the relationship that design quality in product and service and engaging innovation in the activities. To this end, the SEM-PLS (Structural Equation Modelling - Partial Least Squares Structural) is used to identify and evaluate the relationship among TQM, Innovation and business performance in establishing a new TQM model.

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.

Stochastic performance modeling and evaluation of obstacle detectability with imaging range sensors

NASA Technical Reports Server (NTRS)

Matthies, Larry; Grandjean, Pierrick

1993-01-01

Statistical modeling and evaluation of the performance of obstacle detection systems for Unmanned Ground Vehicles (UGVs) is essential for the design, evaluation, and comparison of sensor systems. In this report, we address this issue for imaging range sensors by dividing the evaluation problem into two levels: quality of the range data itself and quality of the obstacle detection algorithms applied to the range data. We review existing models of the quality of range data from stereo vision and AM-CW LADAR, then use these to derive a new model for the quality of a simple obstacle detection algorithm. This model predicts the probability of detecting obstacles and the probability of false alarms, as a function of the size and distance of the obstacle, the resolution of the sensor, and the level of noise in the range data. We evaluate these models experimentally using range data from stereo image pairs of a gravel road with known obstacles at several distances. The results show that the approach is a promising tool for predicting and evaluating the performance of obstacle detection with imaging range sensors.

Recent experience with the CQE{trademark}

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

Harrison, C.D.; Kehoe, D.B.; O`Connor, D.C.

1997-12-31

CQE (the Coal Quality Expert) is a software tool that brings a new level of sophistication to fuel decisions by seamlessly integrating the system-wide effects of fuel purchase decisions on power plant performance, emissions, and power generation costs. The CQE technology, which addresses fuel quality from the coal mine to the busbar and the stack, is an integration and improvement of predecessor software tools including: EPRI`s Coal Quality Information System, EPRI`s Coal Cleaning Cost Model, EPRI`s Coal Quality Impact Model, and EPRI and DOE models to predict slagging and fouling. CQE can be used as a stand-alone workstation or asmore » a network application for utilities, coal producers, and equipment manufacturers to perform detailed analyses of the impacts of coal quality, capital improvements, operational changes, and/or environmental compliance alternatives on power plant emissions, performance and production costs. It can be used as a comprehensive, precise and organized methodology for systematically evaluating all such impacts or it may be used in pieces with some default data to perform more strategic or comparative studies.« less

Modeling the effects of functional performance and post-transplant comorbidities on health-related quality of life after heart transplantation.

PubMed

Butler, Javed; McCoin, Nicole S; Feurer, Irene D; Speroff, Theodore; Davis, Stacy F; Chomsky, Don B; Wilson, John R; Merrill, Walter H; Drinkwater, Davis C; Pierson, Richard N; Pinson, C Wright

2003-10-01

Health-related quality of life and functional performance are important outcome measures following heart transplantation. This study investigates the impact of pre-transplant functional performance and post-transplant rejection episodes, obesity and osteopenia on post-transplant health-related quality of life and functional performance. Functional performance and health-related quality of life were measured in 70 adult heart transplant recipients. A composite health-related quality of life outcome measure was computed via principal component analysis. Iterative, multiple regression-based path analysis was used to develop an integrated model of variables that affect post-transplant functional performance and health-related quality of life. Functional performance, as measured by the Karnofsky scale, improved markedly during the first 6 months post-transplant and was then sustained for up to 3 years. Rejection Grade > or =2 was negatively associated with health-related quality of life, measured by Short Form-36 and reversed Psychosocial Adjustment to Illness Scale scores. Patients with osteopenia had lower Short Form-36 physical scores and obese patients had lower functional performance. Path analysis demonstrated a negative direct effect of obesity (beta = - 0.28, p < 0.05) on post-transplant functional performance. Post-transplant functional performance had a positive direct effect on the health-related quality of life composite score (beta = 0.48, p < 0.001), and prior rejection episodes grade > or =2 had a negative direct effect on this measure (beta = -0.29, p < 0.05). Either directly or through effects mediated by functional performance, moderate-to-severe rejection, obesity and osteopenia negatively impact health-related quality of life. These findings indicate that efforts should be made to devise immunosuppressive regimens that reduce the incidence of acute rejection, weight gain and osteopenia after heart transplantation.

Guiding Principles and Checklist for Population-Based Quality Metrics

PubMed Central

Brunelli, Steven M.; Maddux, Franklin W.; Parker, Thomas F.; Johnson, Douglas; Nissenson, Allen R.; Collins, Allan; Lacson, Eduardo

2014-01-01

The Centers for Medicare and Medicaid Services oversees the ESRD Quality Incentive Program to ensure that the highest quality of health care is provided by outpatient dialysis facilities that treat patients with ESRD. To that end, Centers for Medicare and Medicaid Services uses clinical performance measures to evaluate quality of care under a pay-for-performance or value-based purchasing model. Now more than ever, the ESRD therapeutic area serves as the vanguard of health care delivery. By translating medical evidence into clinical performance measures, the ESRD Prospective Payment System became the first disease-specific sector using the pay-for-performance model. A major challenge for the creation and implementation of clinical performance measures is the adjustments that are necessary to transition from taking care of individual patients to managing the care of patient populations. The National Quality Forum and others have developed effective and appropriate population-based clinical performance measures quality metrics that can be aggregated at the physician, hospital, dialysis facility, nursing home, or surgery center level. Clinical performance measures considered for endorsement by the National Quality Forum are evaluated using five key criteria: evidence, performance gap, and priority (impact); reliability; validity; feasibility; and usability and use. We have developed a checklist of special considerations for clinical performance measure development according to these National Quality Forum criteria. Although the checklist is focused on ESRD, it could also have broad application to chronic disease states, where health care delivery organizations seek to enhance quality, safety, and efficiency of their services. Clinical performance measures are likely to become the norm for tracking performance for health care insurers. Thus, it is critical that the methodologies used to develop such metrics serve the payer and the provider and most importantly, reflect what represents the best care to improve patient outcomes. PMID:24558050

Improving benchmarking by using an explicit framework for the development of composite indicators: an example using pediatric quality of care

PubMed Central

2010-01-01

Background The measurement of healthcare provider performance is becoming more widespread. Physicians have been guarded about performance measurement, in part because the methodology for comparative measurement of care quality is underdeveloped. Comprehensive quality improvement will require comprehensive measurement, implying the aggregation of multiple quality metrics into composite indicators. Objective To present a conceptual framework to develop comprehensive, robust, and transparent composite indicators of pediatric care quality, and to highlight aspects specific to quality measurement in children. Methods We reviewed the scientific literature on composite indicator development, health systems, and quality measurement in the pediatric healthcare setting. Frameworks were selected for explicitness and applicability to a hospital-based measurement system. Results We synthesized various frameworks into a comprehensive model for the development of composite indicators of quality of care. Among its key premises, the model proposes identifying structural, process, and outcome metrics for each of the Institute of Medicine's six domains of quality (safety, effectiveness, efficiency, patient-centeredness, timeliness, and equity) and presents a step-by-step framework for embedding the quality of care measurement model into composite indicator development. Conclusions The framework presented offers researchers an explicit path to composite indicator development. Without a scientifically robust and comprehensive approach to measurement of the quality of healthcare, performance measurement will ultimately fail to achieve its quality improvement goals. PMID:20181129

Air Quality Modeling

EPA Pesticide Factsheets

In this technical support document (TSD) EPA describes the air quality modeling performed to support the Environmental Protection Agency’s Transport Rule proposal (now known as the Cross-State Air Pollution Rule).

Quality and price--impact on patient satisfaction.

PubMed

Pantouvakis, Angelos; Bouranta, Nancy

2014-01-01

The purpose of this paper is to synthesize existing quality-measurement models and applies them to healthcare by combining a Nordic service-quality with an American service performance model. Results are based on a questionnaire survey of 1,298 respondents. Service quality dimensions were derived and related to satisfaction by employing a multinomial logistic model, which allows prediction and service improvement. Qualitative and empirical evidence indicates that customer satisfaction and service quality are multi-dimensional constructs, whose quality components, together with convenience and cost, influence the customer's overall satisfaction. The proposed model identifies important quality and satisfaction issues. It also enables transitions between different responses in different studies to be compared.

A Multi-Model Assessment for the 2006 and 2010 Simulations under the AirQuality Model Evaluation International Initiative (AQMEII) Phase 2 over North America: Part I. Indicators of the Sensitivity of O3 and PM2.5 Formation Regimes

EPA Science Inventory

Under the Air Quality Model Evaluation International Initiative, Phase 2 (AQMEII-2), three online coupled air quality model simulations, with six different configurations, are analyzed for their performance, inter-model agreement, and responses to emission and meteorological chan...

Sensitivity of Rainfall-runoff Model Parametrization and Performance to Potential Evaporation Inputs

NASA Astrophysics Data System (ADS)

Jayathilake, D. I.; Smith, T. J.

2017-12-01

Many watersheds of interest are confronted with insufficient data and poor process understanding. Therefore, understanding the relative importance of input data types and the impact of different qualities on model performance, parameterization, and fidelity is critically important to improving hydrologic models. In this paper, the change in model parameterization and performance are explored with respect to four different potential evapotranspiration (PET) products of varying quality. For each PET product, two widely used, conceptual rainfall-runoff models are calibrated with multiple objective functions to a sample of 20 basins included in the MOPEX data set and analyzed to understand how model behavior varied. Model results are further analyzed by classifying catchments as energy- or water-limited using the Budyko framework. The results demonstrated that model fit was largely unaffected by the quality of the PET inputs. However, model parameterizations were clearly sensitive to PET inputs, as their production parameters adjusted to counterbalance input errors. Despite this, changes in model robustness were not observed for either model across the four PET products, although robustness was affected by model structure.

Evaluation of model-based versus non-parametric monaural noise-reduction approaches for hearing aids.

PubMed

Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker

2012-08-01

Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.

Verification of a quality management theory: using a delphi study.

PubMed

Mosadeghrad, Ali Mohammad

2013-11-01

A model of quality management called Strategic Collaborative Quality Management (SCQM) model was developed based on the quality management literature review, the findings of a survey on quality management assessment in healthcare organisations, semi-structured interviews with healthcare stakeholders, and a Delphi study on healthcare quality management experts. The purpose of this study was to verify the SCQM model. The proposed model was further developed using feedback from thirty quality management experts using a Delphi method. Further, a guidebook for its implementation was prepared including a road map and performance measurement. The research led to the development of a context-specific model of quality management for healthcare organisations and a series of guidelines for its implementation. A proper model of quality management should be developed and implemented properly in healthcare organisations to achieve business excellence.

Verification of a Quality Management Theory: Using a Delphi Study

PubMed Central

Mosadeghrad, Ali Mohammad

2013-01-01

Background: A model of quality management called Strategic Collaborative Quality Management (SCQM) model was developed based on the quality management literature review, the findings of a survey on quality management assessment in healthcare organisations, semi-structured interviews with healthcare stakeholders, and a Delphi study on healthcare quality management experts. The purpose of this study was to verify the SCQM model. Methods: The proposed model was further developed using feedback from thirty quality management experts using a Delphi method. Further, a guidebook for its implementation was prepared including a road map and performance measurement. Results: The research led to the development of a context-specific model of quality management for healthcare organisations and a series of guidelines for its implementation. Conclusion: A proper model of quality management should be developed and implemented properly in healthcare organisations to achieve business excellence. PMID:24596883

Implementation of a WRF-CMAQ Air Quality Modeling System in Bogotá, Colombia

NASA Astrophysics Data System (ADS)

Nedbor-Gross, R.; Henderson, B. H.; Pachon, J. E.; Davis, J. R.; Baublitz, C. B.; Rincón, A.

2014-12-01

Due to a continuous economic growth Bogotá, Colombia has experienced air pollution issues in recent years. The local environmental authority has implemented several strategies to curb air pollution that have resulted in the decrease of PM10 concentrations since 2010. However, more activities are necessary in order to meet international air quality standards in the city. The University of Florida Air Quality and Climate group is collaborating with the Universidad de La Salle to prioritize regulatory strategies for Bogotá using air pollution simulations. To simulate pollution, we developed a modeling platform that combines the Weather Research and Forecasting Model (WRF), local emissions, and the Community Multi-scale Air Quality model (CMAQ). This platform is the first of its kind to be implemented in the megacity of Bogota, Colombia. The presentation will discuss development and evaluation of the air quality modeling system, highlight initial results characterizing photochemical conditions in Bogotá, and characterize air pollution under proposed regulatory strategies. The WRF model has been configured and applied to Bogotá, which resides in a tropical climate with complex mountainous topography. Developing the configuration included incorporation of local topography and land-use data, a physics sensitivity analysis, review, and systematic evaluation. The threshold, however, was set based on synthesis of model performance under less mountainous conditions. We will evaluate the impact that differences in autocorrelation contribute to the non-ideal performance. Air pollution predictions are currently under way. CMAQ has been configured with WRF meteorology, global boundary conditions from GEOS-Chem, and a locally produced emission inventory. Preliminary results from simulations show promising performance of CMAQ in Bogota. Anticipated results include a systematic performance evaluation of ozone and PM10, characterization of photochemical sensitivity, and air quality predictions under proposed regulatory scenarios.

Prediction of global and local model quality in CASP8 using the ModFOLD server.

PubMed

McGuffin, Liam J

2009-01-01

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0--an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/. Copyright 2009 Wiley-Liss, Inc.

A new method based on fuzzy logic to evaluate the contract service provider performance.

PubMed

Miguel, C A; Barr, C; Moreno, M J L

2008-01-01

This paper puts forward a fuzzy inference system for evaluating the service quality performance of service contract providers. An application service provider (ASP) model for computerized maintenance management was used in establishing common performance indicators of the quality of service. This model was implemented in 10 separate hospitals. As a result, inference produced a service cost/acquisition cost (SC/AC) ratio reduction from 16.14% to 6.09%, an increase of 20.9% in availability, with a maintained repair quality (NRR) in the period of December 2001 to January 2003.

MODELING ASSESSMENT OF THE IMPACT OF NITROGEN OXIDES EMISSION REDUCTIONS ON OZONE AIR QUALITY IN THE EASTERN UNITED STATES: OFFSETTING INCREASES IN ENERGY USE

EPA Science Inventory

The objective of this study is to examine changes in ambient ozone concentrations estimated by a photochemical air quality model in response to the NOx emission reductions imposed on the utility sector. To accomplish this task, CMAQ air quality model simulations were performe...

DAILY SIMULATIONS OF OZONE AND FINE PARTICULATES OVER THE NORTHEASTERN UNITED STATES: MODEL PERFORMANCE, SEASONAL DIFFERENCES, AND THE EFFECT OF MODEL UPDATES

EPA Science Inventory

This poster presents analysis of near-realtime air quality simulations over New York State for two summer and one winter season. Simulations were performed as a pilot study between the NOAA, EPA, and NYSDEC, utilizing resources from the national operational NOAA/EPA air quality f...

Preventive care quality of Medicare Accountable Care Organizations: Associations of organizational characteristics with performance

PubMed Central

Albright, Benjamin B.; Lewis, Valerie A.; Ross, Joseph S.; Colla, Carrie H.

2015-01-01

Background Accountable Care Organizations (ACOs) are a delivery and payment model aiming to coordinate care, control costs, and improve quality. Medicare ACOs are responsible for eight measures of preventive care quality. Objectives To create composite measures of preventive care quality and examine associations of ACO characteristics with performance. Design Cross-sectional study of Medicare Shared Savings Program and Pioneer participants. We linked quality performance to descriptive data from the National Survey of ACOs. We created composite measures using exploratory factor analysis, and used regression to assess associations with organizational characteristics. Results Of 252 eligible ACOs, 246 reported on preventive care quality, 177 of which completed the survey (response rate=72%). In their first year, ACOs lagged behind PPO performance on the majority of comparable measures. We identified two underlying factors among eight measures and created composites for each: disease prevention, driven by vaccines and cancer screenings, and wellness screening, driven by annual health screenings. Participation in the Advanced Payment Model, having fewer specialists, and having more Medicare ACO beneficiaries per primary care provider were associated with significantly better performance on both composites. Better performance on disease prevention was also associated with inclusion of a hospital, greater electronic health record capabilities, a larger primary care workforce, and fewer minority beneficiaries. Conclusions ACO preventive care quality performance is related to provider composition and benefitted by upfront investment. Vaccine and cancer screening quality performance is more dependent on organizational structure and characteristics than performance on annual wellness screenings, likely due to greater complexity in eligibility determination and service administration. PMID:26759974

Preventive Care Quality of Medicare Accountable Care Organizations: Associations of Organizational Characteristics With Performance.

PubMed

Albright, Benjamin B; Lewis, Valerie A; Ross, Joseph S; Colla, Carrie H

2016-03-01

Accountable Care Organizations (ACOs) are a delivery and payment model aiming to coordinate care, control costs, and improve quality. Medicare ACOs are responsible for 8 measures of preventive care quality. To create composite measures of preventive care quality and examine associations of ACO characteristics with performance. This is a cross-sectional study of Medicare Shared Savings Program and Pioneer participants. We linked quality performance to descriptive data from the National Survey of ACOs. We created composite measures using exploratory factor analysis, and used regression to assess associations with organizational characteristics. Of 252 eligible ACOs, 246 reported on preventive care quality, 177 of which completed the survey (response rate=72%). In their first year, ACOs lagged behind PPO performance on the majority of comparable measures. We identified 2 underlying factors among 8 measures and created composites for each: disease prevention, driven by vaccines and cancer screenings, and wellness screening, driven by annual health screenings. Participation in the Advanced Payment Model, having fewer specialists, and having more Medicare ACO beneficiaries per primary care provider were associated with significantly better performance on both composites. Better performance on disease prevention was also associated with inclusion of a hospital, greater electronic health record capabilities, a larger primary care workforce, and fewer minority beneficiaries. ACO preventive care quality performance is related to provider composition and benefitted by upfront investment. Vaccine and cancer screening quality performance is more dependent on organizational structure and characteristics than performance on annual wellness screenings, likely due to greater complexity in eligibility determination and service administration.

Medicaid plan, health centers reveal secrets to boosting HEDIS scores, quality of care.

PubMed

1999-07-01

How to do well on HEDIS measurement and boost quality of care for your Medicaid members. Neighborhood Health Plan in Boston, MA, attributes its top performance on Medicaid HEDIS measures to providers' care models, a commitment to quality, and the quest for performance data.

Environmental Flow for Sungai Johor Estuary

NASA Astrophysics Data System (ADS)

Adilah, A. Kadir; Zulkifli, Yusop; Zainura, Z. Noor; Bakhiah, Baharim N.

2018-03-01

Sungai Johor estuary is a vital water body in the south of Johor and greatly affects the water quality in the Johor Straits. In the development of the hydrodynamic and water quality models for Sungai Johor estuary, the Environmental Fluid Dynamics Code (EFDC) model was selected. In this application, the EFDC hydrodynamic model was configured to simulate time varying surface elevation, velocity, salinity, and water temperature. The EFDC water quality model was configured to simulate dissolved oxygen (DO), dissolved organic carbon (DOC), chemical oxygen demand (COD), ammoniacal nitrogen (NH3-N), nitrate nitrogen (NO3-N), phosphate (PO4), and Chlorophyll a. The hydrodynamic and water quality model calibration was performed utilizing a set of site specific data acquired in January 2008. The simulated water temperature, salinity and DO showed good and fairly good agreement with observations. The calculated correlation coefficients between computed and observed temperature and salinity were lower compared with the water level. Sensitivity analysis was performed on hydrodynamic and water quality models input parameters to quantify their impact on modeling results such as water surface elevation, salinity and dissolved oxygen concentration. It is anticipated and recommended that the development of this model be continued to synthesize additional field data into the modeling process.

Evaluation and intercomparison of air quality forecasts over Korea during the KORUS-AQ campaign

NASA Astrophysics Data System (ADS)

Lee, Seungun; Park, Rokjin J.; Kim, Soontae; Song, Chul H.; Kim, Cheol-Hee; Woo, Jung-Hun

2017-04-01

We evaluate and intercompare ozone and aerosol simulations over Korea during the KORUS-AQ campaign, which was conducted in May-June 2016. Four global and regional air quality models participated in the campaign and provided daily air quality forecasts over Korea to guide aircraft flight paths for detecting air pollution events over Korean peninsula and its nearby oceans. We first evaluate the model performance by comparing simulated and observed hourly surface ozone and PM2.5 concentrations at ground sites in Korea and find that the models successfully capture intermittent air pollution events and reproduce the daily variation of ozone and PM2.5 concentrations. However, significant underestimates of peak ozone concentrations in the afternoon are also found in most models. Among chemical constituents of PM2.5, the models typically overestimate observed nitrate aerosol concentrations and underestimate organic aerosol concentrations, although the observed mass concentrations of PM2.5 are seemingly reproduced by the models. In particular, all models used the same anthropogenic emission inventory (KU-CREATE) for daily air quality forecast, but they show a considerable discrepancy for ozone and aerosols. Compared to individual model results, the ensemble mean of all models shows the best performance with correlation coefficients of 0.73 for ozone and 0.57 for PM2.5. We here investigate contributing factors to the discrepancy, which will serve as a guidance to improve the performance of the air quality forecast.

Performance Effects of Measurement and Analysis: Perspectives from CMMI High Maturity Organizations and Appraisers

DTIC Science & Technology

2010-06-01

models 13 The Chi-Square test fails to reject the null hypothesis that there is no difference between 2008 and 2009 data (p-value = 0.601). This...attributed to process performance modeling 53 Table 4: Relationships between data quality and integrity activities and overall value attributed to... data quality and integrity; staffing and resources devoted to the work; pertinent training and coaching; and the alignment of the models with

PERFORMANCE AND DIAGNOSTIC EVALUATION OF OZONE PREDICTIONS BY THE ETA-COMMUNITY MULTISCALE AIR QUALITY FORECAST SYSTEM DURING THE 2002 NEW ENGLAND AIR QUALITY STUDY

EPA Science Inventory

A real-time air quality forecasting system (Eta-CMAQ model suite) has been developed by linking the NCEP Eta model to the U.S. EPA CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting O₃ over the northeastern U.S d...

QMEANclust: estimation of protein model quality by combining a composite scoring function with structural density information.

PubMed

Benkert, Pascal; Schwede, Torsten; Tosatto, Silvio Ce

2009-05-20

The selection of the most accurate protein model from a set of alternatives is a crucial step in protein structure prediction both in template-based and ab initio approaches. Scoring functions have been developed which can either return a quality estimate for a single model or derive a score from the information contained in the ensemble of models for a given sequence. Local structural features occurring more frequently in the ensemble have a greater probability of being correct. Within the context of the CASP experiment, these so called consensus methods have been shown to perform considerably better in selecting good candidate models, but tend to fail if the best models are far from the dominant structural cluster. In this paper we show that model selection can be improved if both approaches are combined by pre-filtering the models used during the calculation of the structural consensus. Our recently published QMEAN composite scoring function has been improved by including an all-atom interaction potential term. The preliminary model ranking based on the new QMEAN score is used to select a subset of reliable models against which the structural consensus score is calculated. This scoring function called QMEANclust achieves a correlation coefficient of predicted quality score and GDT_TS of 0.9 averaged over the 98 CASP7 targets and perform significantly better in selecting good models from the ensemble of server models than any other groups participating in the quality estimation category of CASP7. Both scoring functions are also benchmarked on the MOULDER test set consisting of 20 target proteins each with 300 alternatives models generated by MODELLER. QMEAN outperforms all other tested scoring functions operating on individual models, while the consensus method QMEANclust only works properly on decoy sets containing a certain fraction of near-native conformations. We also present a local version of QMEAN for the per-residue estimation of model quality (QMEANlocal) and compare it to a new local consensus-based approach. Improved model selection is obtained by using a composite scoring function operating on single models in order to enrich higher quality models which are subsequently used to calculate the structural consensus. The performance of consensus-based methods such as QMEANclust highly depends on the composition and quality of the model ensemble to be analysed. Therefore, performance estimates for consensus methods based on large meta-datasets (e.g. CASP) might overrate their applicability in more realistic modelling situations with smaller sets of models based on individual methods.

A Completely Blind Video Integrity Oracle.

PubMed

Mittal, Anish; Saad, Michele A; Bovik, Alan C

2016-01-01

Considerable progress has been made toward developing still picture perceptual quality analyzers that do not require any reference picture and that are not trained on human opinion scores of distorted images. However, there do not yet exist any such completely blind video quality assessment (VQA) models. Here, we attempt to bridge this gap by developing a new VQA model called the video intrinsic integrity and distortion evaluation oracle (VIIDEO). The new model does not require the use of any additional information other than the video being quality evaluated. VIIDEO embodies models of intrinsic statistical regularities that are observed in natural vidoes, which are used to quantify disturbances introduced due to distortions. An algorithm derived from the VIIDEO model is thereby able to predict the quality of distorted videos without any external knowledge about the pristine source, anticipated distortions, or human judgments of video quality. Even with such a paucity of information, we are able to show that the VIIDEO algorithm performs much better than the legacy full reference quality measure MSE on the LIVE VQA database and delivers performance comparable with a leading human judgment trained blind VQA model. We believe that the VIIDEO algorithm is a significant step toward making real-time monitoring of completely blind video quality possible.

GUIDANCE FOR THE PERFORMANCE EVALUATION OF THREE-DIMENSIONAL AIR QUALITY MODELING SYSTEMS FOR PARTICULATE MATTER AND VISIBILITY

EPA Science Inventory

The National Ambient Air Quality Standards for particulate matter (PM) and the federal regional haze regulations place some emphasis on the assessment of fine particle (PM; 5) concentrations. Current air quality models need to be improved and evaluated against observations to a...

Evaluating, interpreting, and communicating performance of hydrologic/water quality models considering intended use: A review and recommendations

USDA-ARS?s Scientific Manuscript database

Previous publications have outlined recommended practices for hydrologic and water quality (H/WQ) modeling, but none have formulated comprehensive guidelines for the final stage of modeling applications, namely evaluation, interpretation, and communication of model results and the consideration of t...

A proof-of-concept for linking the global meteorological model, MPAS-A with the air quality model, CMAQ

EPA Science Inventory

Researchers who perform air quality modeling studies usually do so on a regional scale. Typically, the boundary conditions are generated by another model which might have a different chemical mechanism, spatial resolution, and/or map projection. Hence, a necessary conversion/inte...

Modeling Canadian Quality Control Test Program for Steroid Hormone Receptors in Breast Cancer: Diagnostic Accuracy Study.

PubMed

Pérez, Teresa; Makrestsov, Nikita; Garatt, John; Torlakovic, Emina; Gilks, C Blake; Mallett, Susan

The Canadian Immunohistochemistry Quality Control program monitors clinical laboratory performance for estrogen receptor and progesterone receptor tests used in breast cancer treatment management in Canada. Current methods assess sensitivity and specificity at each time point, compared with a reference standard. We investigate alternative performance analysis methods to enhance the quality assessment. We used 3 methods of analysis: meta-analysis of sensitivity and specificity of each laboratory across all time points; sensitivity and specificity at each time point for each laboratory; and fitting models for repeated measurements to examine differences between laboratories adjusted by test and time point. Results show 88 laboratories participated in quality control at up to 13 time points using typically 37 to 54 histology samples. In meta-analysis across all time points no laboratories have sensitivity or specificity below 80%. Current methods, presenting sensitivity and specificity separately for each run, result in wide 95% confidence intervals, typically spanning 15% to 30%. Models of a single diagnostic outcome demonstrated that 82% to 100% of laboratories had no difference to reference standard for estrogen receptor and 75% to 100% for progesterone receptor, with the exception of 1 progesterone receptor run. Laboratories with significant differences to reference standard identified with Generalized Estimating Equation modeling also have reduced performance by meta-analysis across all time points. The Canadian Immunohistochemistry Quality Control program has a good design, and with this modeling approach has sufficient precision to measure performance at each time point and allow laboratories with a significantly lower performance to be targeted for advice.

Multilingual Twitter Sentiment Classification: The Role of Human Annotators

PubMed Central

Mozetič, Igor; Grčar, Miha; Smailović, Jasmina

2016-01-01

What are the limits of automated Twitter sentiment classification? We analyze a large set of manually labeled tweets in different languages, use them as training data, and construct automated classification models. It turns out that the quality of classification models depends much more on the quality and size of training data than on the type of the model trained. Experimental results indicate that there is no statistically significant difference between the performance of the top classification models. We quantify the quality of training data by applying various annotator agreement measures, and identify the weakest points of different datasets. We show that the model performance approaches the inter-annotator agreement when the size of the training set is sufficiently large. However, it is crucial to regularly monitor the self- and inter-annotator agreements since this improves the training datasets and consequently the model performance. Finally, we show that there is strong evidence that humans perceive the sentiment classes (negative, neutral, and positive) as ordered. PMID:27149621

High-performing trauma teams: frequency of behavioral markers of a shared mental model displayed by team leaders and quality of medical performance.

PubMed

Johnsen, Bjørn Helge; Westli, Heidi Kristina; Espevik, Roar; Wisborg, Torben; Brattebø, Guttorm

2017-11-10

High quality team leadership is important for the outcome of medical emergencies. However, the behavioral marker of leadership are not well defined. The present study investigated frequency of behavioral markers of shared mental models (SMM) on quality of medical management. Training video recordings of 27 trauma teams simulating emergencies were analyzed according to team -leader's frequency of shared mental model behavioral markers. The results showed a positive correlation of quality of medical management with leaders sharing information without an explicit demand for the information ("push" of information) and with leaders communicating their situational awareness (SA) and demonstrating implicit supporting behavior. When separating the sample into higher versus lower performing teams, the higher performing teams had leaders who displayed a greater frequency of "push" of information and communication of SA and supportive behavior. No difference was found for the behavioral marker of team initiative, measured as bringing up suggestions to other teammembers. The results of this study emphasize the team leader's role in initiating and updating a team's shared mental model. Team leaders should also set expectations for acceptable interaction patterns (e.g., promoting information exchange) and create a team climate that encourages behaviors, such as mutual performance monitoring, backup behavior, and adaptability to enhance SMM.

Four-dimensional evaluation of regional air quality models

EPA Science Inventory

We present highlights of the results obtained in the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3). Activities in AQMEII3 were focused on evaluating the performance of global, hemispheric and regional modeling systems over Europe and North Ame...

Quality of care for patients with diabetes mellitus type 2 in ‘model practices’ in Slovenia – first results

PubMed Central

Mlakar, Mitja

2016-01-01

Abstract Background A new organisation at the primary level, called model practices, introduces a 0.5 full-time equivalent nurse practitioner as a regular member of the team. Nurse practitioners are in charge of registers of chronic patients, and implement an active approach into medical care. Selected quality indicators define the quality of management. The majority of studies confirm the effectiveness of the extended team in the quality of care, which is similar or improved when compared to care performed by the physician alone. The aim of the study is to compare the quality of management of patients with diabetes mellitus type 2 before and after the introduction of model practices. Methods A cohort retrospective study was based on medical records from three practices. Process quality indicators, such as regularity of HbA1c measurement, blood pressure measurement, foot exam, referral to eye exam, performance of yearly laboratory tests and HbA1c level before and after the introduction of model practices were compared. Results The final sample consisted of 132 patients, whose diabetes care was exclusively performed at the primary care level. The process of care has significantly improved after the delivery of model practices. The most outstanding is the increase of foot exam and HbA1c testing. We could not prove better glycaemic control (p>0.1). Nevertheless, the proposed benchmark for the suggested quality process and outcome indicators were mostly exceeded in this cohort. Conclusion The introduction of a nurse into the team improves the process quality of care. Benchmarks for quality indicators are obtainable. Better outcomes of care need further confirmation. PMID:27703537

Quality of care for patients with diabetes mellitus type 2 in 'model practices' in Slovenia - first results.

PubMed

Petek, Davorina; Mlakar, Mitja

2016-09-01

A new organisation at the primary level, called model practices, introduces a 0.5 full-time equivalent nurse practitioner as a regular member of the team. Nurse practitioners are in charge of registers of chronic patients, and implement an active approach into medical care. Selected quality indicators define the quality of management. The majority of studies confirm the effectiveness of the extended team in the quality of care, which is similar or improved when compared to care performed by the physician alone. The aim of the study is to compare the quality of management of patients with diabetes mellitus type 2 before and after the introduction of model practices. A cohort retrospective study was based on medical records from three practices. Process quality indicators, such as regularity of HbA1c measurement, blood pressure measurement, foot exam, referral to eye exam, performance of yearly laboratory tests and HbA1c level before and after the introduction of model practices were compared. The final sample consisted of 132 patients, whose diabetes care was exclusively performed at the primary care level. The process of care has significantly improved after the delivery of model practices. The most outstanding is the increase of foot exam and HbA1c testing. We could not prove better glycaemic control (p>0.1). Nevertheless, the proposed benchmark for the suggested quality process and outcome indicators were mostly exceeded in this cohort. The introduction of a nurse into the team improves the process quality of care. Benchmarks for quality indicators are obtainable. Better outcomes of care need further confirmation.

The Evaluation of Teachers' Job Performance Based on Total Quality Management (TQM)

ERIC Educational Resources Information Center

Shahmohammadi, Nayereh

2017-01-01

This study aimed to evaluate teachers' job performance based on total quality management (TQM) model. This was a descriptive survey study. The target population consisted of all primary school teachers in Karaj (N = 2917). Using Cochran formula and simple random sampling, 340 participants were selected as sample. A total quality management…

A Flexible Modeling Framework For Hydraulic and Water Quality Performance Assessment of Stormwater Green Infrastructure

EPA Science Inventory

A flexible framework has been created for modeling multi-dimensional hydrological and water quality processes within stormwater green infrastructures (GIs). The framework models a GI system using a set of blocks (spatial features) and connectors (interfaces) representing differen...

Using the Many-Facet Rasch Model to Evaluate Standard-Setting Judgments: Setting Performance Standards for Advanced Placement® Examinations

ERIC Educational Resources Information Center

Kaliski, Pamela; Wind, Stefanie A.; Engelhard, George, Jr.; Morgan, Deanna; Plake, Barbara; Reshetar, Rosemary

2012-01-01

The Many-Facet Rasch (MFR) Model is traditionally used to evaluate the quality of ratings on constructed response assessments; however, it can also be used to evaluate the quality of judgments from panel-based standard setting procedures. The current study illustrates the use of the MFR Model by examining the quality of ratings obtained from a…

Hydrocarbon Fuel Thermal Performance Modeling based on Systematic Measurement and Comprehensive Chromatographic Analysis

DTIC Science & Technology

2016-07-27

is a common requirement for aircraft, rockets , and hypersonic vehicles. The Aerospace Fuels Quality Test and Model Development (AFQTMoDev) project...was initiated to mature fuel quality assurance practices for rocket grade kerosene, thereby ensuring operational readiness of conventional and...and reliability, is a common requirement for aircraft, rockets , and hypersonic vehicles. The Aerospace Fuels Quality Test and Model Development

Guiding principles and checklist for population-based quality metrics.

PubMed

Krishnan, Mahesh; Brunelli, Steven M; Maddux, Franklin W; Parker, Thomas F; Johnson, Douglas; Nissenson, Allen R; Collins, Allan; Lacson, Eduardo

2014-06-06

The Centers for Medicare and Medicaid Services oversees the ESRD Quality Incentive Program to ensure that the highest quality of health care is provided by outpatient dialysis facilities that treat patients with ESRD. To that end, Centers for Medicare and Medicaid Services uses clinical performance measures to evaluate quality of care under a pay-for-performance or value-based purchasing model. Now more than ever, the ESRD therapeutic area serves as the vanguard of health care delivery. By translating medical evidence into clinical performance measures, the ESRD Prospective Payment System became the first disease-specific sector using the pay-for-performance model. A major challenge for the creation and implementation of clinical performance measures is the adjustments that are necessary to transition from taking care of individual patients to managing the care of patient populations. The National Quality Forum and others have developed effective and appropriate population-based clinical performance measures quality metrics that can be aggregated at the physician, hospital, dialysis facility, nursing home, or surgery center level. Clinical performance measures considered for endorsement by the National Quality Forum are evaluated using five key criteria: evidence, performance gap, and priority (impact); reliability; validity; feasibility; and usability and use. We have developed a checklist of special considerations for clinical performance measure development according to these National Quality Forum criteria. Although the checklist is focused on ESRD, it could also have broad application to chronic disease states, where health care delivery organizations seek to enhance quality, safety, and efficiency of their services. Clinical performance measures are likely to become the norm for tracking performance for health care insurers. Thus, it is critical that the methodologies used to develop such metrics serve the payer and the provider and most importantly, reflect what represents the best care to improve patient outcomes. Copyright © 2014 by the American Society of Nephrology.

Minnesota's Nursing Facility Performance-Based Incentive Payment Program: An Innovative Model for Promoting Care Quality

ERIC Educational Resources Information Center

Cooke, Valerie; Arling, Greg; Lewis, Teresa; Abrahamson, Kathleen A.; Mueller, Christine; Edstrom, Lisa

2010-01-01

Purpose: Minnesota's Nursing Facility Performance-Based Incentive Payment Program (PIPP) supports provider-initiated projects aimed at improving care quality and efficiency. PIPP moves beyond conventional pay for performance. It seeks to promote implementation of evidence-based practices, encourage innovation and risk taking, foster collaboration…

Does adding clinical data to administrative data improve agreement among hospital quality measures?

PubMed

Hanchate, Amresh D; Stolzmann, Kelly L; Rosen, Amy K; Fink, Aaron S; Shwartz, Michael; Ash, Arlene S; Abdulkerim, Hassen; Pugh, Mary Jo V; Shokeen, Priti; Borzecki, Ann

2017-09-01

Hospital performance measures based on patient mortality and readmission have indicated modest rates of agreement. We examined if combining clinical data on laboratory tests and vital signs with administrative data leads to improved agreement with each other, and with other measures of hospital performance in the nation's largest integrated health care system. We used patient-level administrative and clinical data, and hospital-level data on quality indicators, for 2007-2010 from the Veterans Health Administration (VA). For patients admitted for acute myocardial infarction (AMI), heart failure (HF) and pneumonia we examined changes in hospital performance on 30-d mortality and 30-d readmission rates as a result of adding clinical data to administrative data. We evaluated whether this enhancement yielded improved measures of hospital quality, based on concordance with other hospital quality indicators. For 30-d mortality, data enhancement improved model performance, and significantly changed hospital performance profiles; for 30-d readmission, the impact was modest. Concordance between enhanced measures of both outcomes, and with other hospital quality measures - including Joint Commission process measures, VA Surgical Quality Improvement Program (VASQIP) mortality and morbidity, and case volume - remained poor. Adding laboratory tests and vital signs to measure hospital performance on mortality and readmission did not improve the poor rates of agreement across hospital quality indicators in the VA. Efforts to improve risk adjustment models should continue; however, evidence of validation should precede their use as reliable measures of quality. Published by Elsevier Inc.

Input variable selection and calibration data selection for storm water quality regression models.

PubMed

Sun, Siao; Bertrand-Krajewski, Jean-Luc

2013-01-01

Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.

Real-Time Bias-Adjusted O3 and PM2.5 Air Quality Index Forecasts and their Performance Evaluations over the Continental United States

EPA Science Inventory

The National Air Quality Forecast Capacity (NAQFC) system, which links NOAA's North American Mesoscale (NAM) meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, provided operational ozone (O₃) and experimental fine particular matter (PM_2...

Use of soft data for multi-criteria calibration and validation of APEX: Impact on model simulations

USDA-ARS?s Scientific Manuscript database

It is widely known that the use of soft data and multiple model performance criteria in model calibration and validation is critical to ensuring the model capture major hydrologic and water quality processes. The Agricultural Policy/Environmental eXtender (APEX) is a hydrologic and water quality mod...

77 FR 69399 - Approval and Promulgation of Air Quality Implementation Plans; Delaware; Attainment Plan for the...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-19

... results of speciation data analyses, air quality modeling studies, chemical tracer studies, emission... Demonstration 1. Pollutants Addressed 2. Emission Inventory Requirements 3. Modeling 4. Reasonably Available... modeling (40 CFR 51.1007) that is performed in accordance with EPA modeling guidance (EPA-454/B-07-002...

Flight-Test Validation and Flying Qualities Evaluation of a Rotorcraft UAV Flight Control System

NASA Technical Reports Server (NTRS)

Mettler, Bernard; Tuschler, Mark B.; Kanade, Takeo

2000-01-01

This paper presents a process of design and flight-test validation and flying qualities evaluation of a flight control system for a rotorcraft-based unmanned aerial vehicle (RUAV). The keystone of this process is an accurate flight-dynamic model of the aircraft, derived by using system identification modeling. The model captures the most relevant dynamic features of our unmanned rotorcraft, and explicitly accounts for the presence of a stabilizer bar. Using the identified model we were able to determine the performance margins of our original control system and identify limiting factors. The performance limitations were addressed and the attitude control system was 0ptimize.d for different three performance levels: slow, medium, fast. The optimized control laws will be implemented in our RUAV. We will first determine the validity of our control design approach by flight test validating our optimized controllers. Subsequently, we will fly a series of maneuvers with the three optimized controllers to determine the level of flying qualities that can be attained. The outcome enable us to draw important conclusions on the flying qualities requirements for small-scale RUAVs.

The AQMEII Two-Continent Regional Air Quality Model Evaluation Study: Fueling Ideas with Unprecedented Data

EPA Science Inventory

Although strong collaborations in the air pollution field have existed among the North American (NA) and European (EU) countries over the past five decades, regional-scale air quality model developments and model performance evaluations have been carried out independently unlike ...

Improving health systems performance in low- and middle-income countries: a system dynamics model of the pay-for-performance initiative in Afghanistan.

PubMed

Alonge, O; Lin, S; Igusa, T; Peters, D H

2017-12-01

System dynamics methods were used to explore effective implementation pathways for improving health systems performance through pay-for-performance (P4P) schemes. A causal loop diagram was developed to delineate primary causal relationships for service delivery within primary health facilities. A quantitative stock-and-flow model was developed next. The stock-and-flow model was then used to simulate the impact of various P4P implementation scenarios on quality and volume of services. Data from the Afghanistan national facility survey in 2012 was used to calibrate the model. The models show that P4P bonuses could increase health workers' motivation leading to higher levels of quality and volume of services. Gaming could reduce or even reverse this desired effect, leading to levels of quality and volume of services that are below baseline levels. Implementation issues, such as delays in the disbursement of P4P bonuses and low levels of P4P bonuses, also reduce the desired effect of P4P on quality and volume, but they do not cause the outputs to fall below baseline levels. Optimal effect of P4P on quality and volume of services is obtained when P4P bonuses are distributed per the health workers' contributions to the services that triggered the payments. Other distribution algorithms such as equal allocation or allocations proportionate to salaries resulted in quality and volume levels that were substantially lower, sometimes below baseline. The system dynamics models served to inform, with quantitative results, the theory of change underlying P4P intervention. Specific implementation strategies, such as prompt disbursement of adequate levels of performance bonus distributed per health workers' contribution to service, increase the likelihood of P4P success. Poorly designed P4P schemes, such as those without an optimal algorithm for distributing performance bonuses and adequate safeguards for gaming, can have a negative overall impact on health service delivery systems. © The Author 2017. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.

Impact of Expert Teaching Quality on Novice Academic Performance in the Jigsaw Cooperative Learning Method

ERIC Educational Resources Information Center

Berger, Roland; Hänze, Martin

2015-01-01

We assessed the impact of expert students' instructional quality on the academic performance of novice students in 12th-grade physics classes organized in an expert model of cooperative learning ("jigsaw classroom"). The instructional quality of 129 expert students was measured by a newly developed rating system. As expected, when…

An Investigation of Large Aircraft Handling Qualities

NASA Astrophysics Data System (ADS)

Joyce, Richard D.

An analytical technique for investigating transport aircraft handling qualities is exercised in a study using models of two such vehicles, a Boeing 747 and Lockheed C-5A. Two flight conditions are employed for climb and directional tasks, and a third included for a flare task. The analysis technique is based upon a "structural model" of the human pilot developed by Hess. The associated analysis procedure has been discussed previously in the literature, but centered almost exclusively on the characteristics of high-performance fighter aircraft. The handling qualities rating level (HQRL) and pilot induced oscillation tendencies rating level (PIORL) are predicted for nominal configurations of the aircraft and for "damaged" configurations where actuator rate limits are introduced as nonlinearites. It is demonstrated that the analysis can accommodate nonlinear pilot/vehicle behavior and do so in the context of specific flight tasks, yielding estimates of handling qualities, pilot-induced oscillation tendencies and upper limits of task performance. A brief human-in-the-loop tracking study was performed to provide a limited validation of the pilot model employed.

Comparative analysis of meteorological performance of coupled chemistry-meteorology models in the context of AQMEII phase 2

EPA Science Inventory

Air pollution simulations critically depend on the quality of the underlying meteorology. In phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII-2), thirteen modeling groups from Europe and four groups from North America operating eight different regional...

NEIGHBORHOOD SCALE MODELING OF PM 2.5 AND AIR TOXICS CONCENTRATION DISTRIBUTIONS TO DRIVE HUMAN EXPOSURE MODELS

EPA Science Inventory

Air quality (AQ) simulation models provide a basis for implementing the National Ambient Air Quality Standards (NAAQS) and are a tool for performing risk-based assessments and for developing environmental management strategies. Fine particulate matter (PM 2.5), its constituent...

Blind image quality assessment without training on human opinion scores

NASA Astrophysics Data System (ADS)

Mittal, Anish; Soundararajan, Rajiv; Muralidhar, Gautam S.; Bovik, Alan C.; Ghosh, Joydeep

2013-03-01

We propose a family of image quality assessment (IQA) models based on natural scene statistics (NSS), that can predict the subjective quality of a distorted image without reference to a corresponding distortionless image, and without any training results on human opinion scores of distorted images. These `completely blind' models compete well with standard non-blind image quality indices in terms of subjective predictive performance when tested on the large publicly available `LIVE' Image Quality database.

Predicting the Overall Spatial Quality of Automotive Audio Systems

NASA Astrophysics Data System (ADS)

Koya, Daisuke

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

The performance of fine-grained and coarse-grained elastic network models and its dependence on various factors.

PubMed

Na, Hyuntae; Song, Guang

2015-07-01

In a recent work we developed a method for deriving accurate simplified models that capture the essentials of conventional all-atom NMA and identified two best simplified models: ssNMA and eANM, both of which have a significantly higher correlation with NMA in mean square fluctuation calculations than existing elastic network models such as ANM and ANMr2, a variant of ANM that uses the inverse of the squared separation distances as spring constants. Here, we examine closely how the performance of these elastic network models depends on various factors, namely, the presence of hydrogen atoms in the model, the quality of input structures, and the effect of crystal packing. The study reveals the strengths and limitations of these models. Our results indicate that ssNMA and eANM are the best fine-grained elastic network models but their performance is sensitive to the quality of input structures. When the quality of input structures is poor, ANMr2 is a good alternative for computing mean-square fluctuations while ANM model is a good alternative for obtaining normal modes. © 2015 Wiley Periodicals, Inc.

EVALUATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL VERSION 4.5: UNCERTAINTIES AND SENSITIVITIES IMPACTING MODEL PERFORMANCE: PART II - PARTICULATE MATTER

EPA Science Inventory

This paper presents an analysis of the CMAQ v4.5 model performance for particulate matter and its chemical components for the simulated year 2001. This is part two is two part series of papers that examines the model performance of CMAQ v4.5.

Donabedian's structure-process-outcome quality of care model: Validation in an integrated trauma system.

PubMed

Moore, Lynne; Lavoie, André; Bourgeois, Gilles; Lapointe, Jean

2015-06-01

According to Donabedian's health care quality model, improvements in the structure of care should lead to improvements in clinical processes that should in turn improve patient outcome. This model has been widely adopted by the trauma community but has not yet been validated in a trauma system. The objective of this study was to assess the performance of an integrated trauma system in terms of structure, process, and outcome and evaluate the correlation between quality domains. Quality of care was evaluated for patients treated in a Canadian provincial trauma system (2005-2010; 57 centers, n = 63,971) using quality indicators (QIs) developed and validated previously. Structural performance was measured by transposing on-site accreditation visit reports onto an evaluation grid according to American College of Surgeons criteria. The composite process QI was calculated as the average sum of proportions of conformity to 15 process QIs derived from literature review and expert opinion. Outcome performance was measured using risk-adjusted rates of mortality, complications, and readmission as well as hospital length of stay (LOS). Correlation was assessed with Pearson's correlation coefficients. Statistically significant correlations were observed between structure and process QIs (r = 0.33), and process and outcome QIs (r = -0.33 for readmission, r = -0.27 for LOS). Significant positive correlations were also observed between outcome QIs (r = 0.37 for mortality-readmission; r = 0.39 for mortality-LOS and readmission-LOS; r = 0.45 for mortality-complications; r = 0.34 for readmission-complications; 0.63 for complications-LOS). Significant correlations between quality domains observed in this study suggest that Donabedian's structure-process-outcome model is a valid model for evaluating trauma care. Trauma centers that perform well in terms of structure also tend to perform well in terms of clinical processes, which in turn has a favorable influence on patient outcomes. Prognostic study, level III.

Matrix population models as a tool in development of habitat models

Treesearch

Gregory D. Hayward; David B. McDonald

1997-01-01

Building sophisticated habitat models for conservation of owls must stem from an understanding of the relative quality of habitats at a variety of geographic and temporal scales. Developing these models requires knowing the relationship between habitat conditions and owl performance. What measure should be used to compare the quality of habitats? Matrix population...

EVALUATION OF THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL VERSION 4.5: UNCERTAINTIES AND SENSITIVITIES IMPACTING MODEL PERFORMANCE: PART I - OZONE

EPA Science Inventory

This study examines ozone (O₃) predictions from the Community Multiscale Air Quality (CMAQ) model version 4.5 and discusses potential factors influencing the model results. Daily maximum 8-hr average O₃ levels are largely underpredicted when observed O_...

Evaluation of CMAQ and CAMx Ensemble Air Quality Forecasts during the 2015 MAPS-Seoul Field Campaign

NASA Astrophysics Data System (ADS)

Kim, E.; Kim, S.; Bae, C.; Kim, H. C.; Kim, B. U.

2015-12-01

The performance of Air quality forecasts during the 2015 MAPS-Seoul Field Campaign was evaluated. An forecast system has been operated to support the campaign's daily aircraft route decisions for airborne measurements to observe long-range transporting plume. We utilized two real-time ensemble systems based on the Weather Research and Forecasting (WRF)-Sparse Matrix Operator Kernel Emissions (SMOKE)-Comprehensive Air quality Model with extensions (CAMx) modeling framework and WRF-SMOKE- Community Multi_scale Air Quality (CMAQ) framework over northeastern Asia to simulate PM10 concentrations. Global Forecast System (GFS) from National Centers for Environmental Prediction (NCEP) was used to provide meteorological inputs for the forecasts. For an additional set of retrospective simulations, ERA Interim Reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF) was also utilized to access forecast uncertainties from the meteorological data used. Model Inter-Comparison Study for Asia (MICS-Asia) and National Institute of Environment Research (NIER) Clean Air Policy Support System (CAPSS) emission inventories are used for foreign and domestic emissions, respectively. In the study, we evaluate the CMAQ and CAMx model performance during the campaign by comparing the results to the airborne and surface measurements. Contributions of foreign and domestic emissions are estimated using a brute force method. Analyses on model performance and emissions will be utilized to improve air quality forecasts for the upcoming KORUS-AQ field campaign planned in 2016.

Paying for quality not quantity: a wisconsin health maintenance organization proposes an incentive model for reimbursement of chiropractic services.

PubMed

Pursel, Kevin J; Jacobson, Martin; Stephenson, Kathy

2012-07-01

The purpose of this study is to describe a reimbursement model that was developed by one Health Maintenance Organization (HMO) to transition from fee-for-service to add a combination of pay for performance and reporting model of reimbursement for chiropractic care. The previous incentive program used by the HMO provided best-practice education and additional reimbursement incentives for achieving the National Committee for Quality Assurance Back Pain Recognition Program (NCQA-BPRP) recognition status. However, this model had not leveled costs between doctors of chiropractic (DCs). Therefore, the HMO management aimed to develop a reimbursement model to incentivize providers to embrace existing best-practice models and report existing quality metrics. The development goals included the following: it should (1) be as financially predictable as the previous system, (2) cost no more on a per-member basis, (3) meet the coverage needs of its members, and (4) be able to be operationalized. The model should also reward DCs who embraced best practices with compensation, not simply tied to providing more procedures, the new program needed to (1) cause little or no disruption in current billing, (2) be grounded achievable and defined expectations for improvement in quality, and (3) be voluntary, without being unduly punitive, should the DC choose not to participate in the program. The generated model was named the Comprehensive Chiropractic Quality Reimbursement Methodology (CCQRM; pronounced "Quorum"). In this hybrid model, additional reimbursement, beyond pay-for-procedures will be based on unique payment interpretations reporting selected, existing Physician Quality Reporting System (PQRS) codes, meaningful use of electronic health records, and achieving NCQA-BPRP recognition. This model aims to compensate providers using pay-for-performance, pay-for-quality reporting, pay-for-procedure methods. The CCQRM reimbursement model was developed to address the current needs of one HMO that aims to transition from fee-for-service to a pay-for-performance and quality reporting for reimbursement for chiropractic care. This model is theoretically based on the combination of a fee-for-service payment, pay for participation (NCQA Back Pain Recognition Program payment), meaningful use of electronic health record payment, and pay for reporting (PQRS-BPMG payment). Evaluation of this model needs to be implemented to determine if it will achieve its intended goals. Copyright © 2012 National University of Health Sciences. Published by Mosby, Inc. All rights reserved.

Links among high-performance work environment, service quality, and customer satisfaction: an extension to the healthcare sector.

PubMed

Scotti, Dennis J; Harmon, Joel; Behson, Scott J

2007-01-01

Healthcare managers must deliver high-quality patient services that generate highly satisfied and loyal customers. In this article, we examine how a high-involvement approach to the work environment of healthcare employees may lead to exceptional service quality, satisfied patients, and ultimately to loyal customers. Specifically, we investigate the chain of events through which high-performance work systems (HPWS) and customer orientation influence employee and customer perceptions of service quality and patient satisfaction in a national sample of 113 Veterans Health Administration ambulatory care centers. We present a conceptual model for linking work environment to customer satisfaction and test this model using structural equations modeling. The results suggest that (1) HPWS is linked to employee perceptions of their ability to deliver high-quality customer service, both directly and through their perceptions of customer orientation; (2) employee perceptions of customer service are linked to customer perceptions of high-quality service; and (3) perceived service quality is linked with customer satisfaction. Theoretical and practical implications of our findings, including suggestions of how healthcare managers can implement changes to their work environments, are discussed.

Intelligent evaluation of color sensory quality of black tea by visible-near infrared spectroscopy technology: A comparison of spectra and color data information

NASA Astrophysics Data System (ADS)

Ouyang, Qin; Liu, Yan; Chen, Quansheng; Zhang, Zhengzhu; Zhao, Jiewen; Guo, Zhiming; Gu, Hang

2017-06-01

Instrumental test of black tea samples instead of human panel test is attracting massive attention recently. This study focused on an investigation of the feasibility for estimation of the color sensory quality of black tea samples using the VIS-NIR spectroscopy technique, comparing the performances of models based on the spectra and color information. In model calibration, the variables were first selected by genetic algorithm (GA); then the nonlinear back propagation-artificial neural network (BPANN) models were established based on the optimal variables. In comparison with the other models, GA-BPANN models from spectra data information showed the best performance, with the correlation coefficient of 0.8935, and the root mean square error of 0.392 in the prediction set. In addition, models based on the spectra information provided better performance than that based on the color parameters. Therefore, the VIS-NIR spectroscopy technique is a promising tool for rapid and accurate evaluation of the sensory quality of black tea samples.

Intelligent evaluation of color sensory quality of black tea by visible-near infrared spectroscopy technology: A comparison of spectra and color data information.

PubMed

Ouyang, Qin; Liu, Yan; Chen, Quansheng; Zhang, Zhengzhu; Zhao, Jiewen; Guo, Zhiming; Gu, Hang

2017-06-05

Instrumental test of black tea samples instead of human panel test is attracting massive attention recently. This study focused on an investigation of the feasibility for estimation of the color sensory quality of black tea samples using the VIS-NIR spectroscopy technique, comparing the performances of models based on the spectra and color information. In model calibration, the variables were first selected by genetic algorithm (GA); then the nonlinear back propagation-artificial neural network (BPANN) models were established based on the optimal variables. In comparison with the other models, GA-BPANN models from spectra data information showed the best performance, with the correlation coefficient of 0.8935, and the root mean square error of 0.392 in the prediction set. In addition, models based on the spectra information provided better performance than that based on the color parameters. Therefore, the VIS-NIR spectroscopy technique is a promising tool for rapid and accurate evaluation of the sensory quality of black tea samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Air quality assessment in the periurban area of Mexico Megacity during dry hot season in 2011 and 2012

NASA Astrophysics Data System (ADS)

Garcia-Reynoso, Agustin; Santos Garcia-Yee, Jose; Barrera-Huertas, Hugo; Gerardo Ruiz-Suárez, Luis

2016-04-01

Air quality is a human health threat not only in urbanized areas, it also affects the surrounding zones. Interaction between urban and rural areas can be evaluated by measurements and using models for regional areas that includes in its domain the peri-urban regions. The use of monitoring sites in remote areas is useful however it is not possible to cover all the region the use of models can provide valuable information about the source and fate of the pollution and its transformation. In order to evaluate the influence of the Mexico Megacity in the air quality of the region, two field campaigns were performed during the dry hot season during 2011 and 2012. Meterological and pollutant measurements were made during February and march 2011, in three sites towards the south east of Mexico Megacity, and from march to April 2012 towards the west after the Popocatepetl-Iztaccihuatl mountain range. Air quality modeling were performed by using the National Emissions Inventory 2008 during the studied periods, a comparison between measurements and the air quality model was performed. This type of studies can offer information about the pollutant distribution, the meteorological conditions and the exactness of emissions inventories. The latest can be useful for emissions inventory developers and policy makers.

Urban airshed modeling of air quality impacts of alternative transportation fuel use in Los Angeles and Atlanta

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

NONE

1997-12-01

The main objective of NREL in supporting this study is to determine the relative air quality impact of the use of compressed natural gas (CNG) as an alternative transportation fuel when compared to low Reid vapor pressure (RVP) gasoline and reformulated gasoline (RFG). A table lists the criteria, air toxic, and greenhouse gas pollutants for which emissions were estimated for the alternative fuel scenarios. Air quality impacts were then estimated by performing photochemical modeling of the alternative fuel scenarios using the Urban Airshed Model Version 6.21 and the Carbon Bond Mechanism Version IV (CBM-IV) (Geary et al., 1988) Using thismore » model, the authors examined the formation and transport of ozone under alternative fuel strategies for motor vehicle transportation sources for the year 2007. Photochemical modeling was performed for modeling domains in Los Angeles, California, and Atlanta, Georgia.« less

Accounting for and predicting the influence of spatial autocorrelation in water quality modeling

NASA Astrophysics Data System (ADS)

Miralha, L.; Kim, D.

2017-12-01

Although many studies have attempted to investigate the spatial trends of water quality, more attention is yet to be paid to the consequences of considering and ignoring the spatial autocorrelation (SAC) that exists in water quality parameters. Several studies have mentioned the importance of accounting for SAC in water quality modeling, as well as the differences in outcomes between models that account for and ignore SAC. However, the capacity to predict the magnitude of such differences is still ambiguous. In this study, we hypothesized that SAC inherently possessed by a response variable (i.e., water quality parameter) influences the outcomes of spatial modeling. We evaluated whether the level of inherent SAC is associated with changes in R-Squared, Akaike Information Criterion (AIC), and residual SAC (rSAC), after accounting for SAC during modeling procedure. The main objective was to analyze if water quality parameters with higher Moran's I values (inherent SAC measure) undergo a greater increase in R² and a greater reduction in both AIC and rSAC. We compared a non-spatial model (OLS) to two spatial regression approaches (spatial lag and error models). Predictor variables were the principal components of topographic (elevation and slope), land cover, and hydrological soil group variables. We acquired these data from federal online sources (e.g. USGS). Ten watersheds were selected, each in a different state of the USA. Results revealed that water quality parameters with higher inherent SAC showed substantial increase in R² and decrease in rSAC after performing spatial regressions. However, AIC values did not show significant changes. Overall, the higher the level of inherent SAC in water quality variables, the greater improvement of model performance. This indicates a linear and direct relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. Therefore, our study suggests that the inherent level of SAC in response variables can predict improvements in models even before performing spatial regression approaches. We also recognize the constraints of this research and suggest that further studies focus on better ways of defining spatial neighborhoods, considering the differences among stations set in tributaries near to each other and in upstream areas.

Identifying individual changes in performance with composite quality indicators while accounting for regression to the mean.

PubMed

Gajewski, Byron J; Dunton, Nancy

2013-04-01

Almost a decade ago Morton and Torgerson indicated that perceived medical benefits could be due to "regression to the mean." Despite this caution, the regression to the mean "effects on the identification of changes in institutional performance do not seem to have been considered previously in any depth" (Jones and Spiegelhalter). As a response, Jones and Spiegelhalter provide a methodology to adjust for regression to the mean when modeling recent changes in institutional performance for one-variable quality indicators. Therefore, in our view, Jones and Spiegelhalter provide a breakthrough methodology for performance measures. At the same time, in the interests of parsimony, it is useful to aggregate individual quality indicators into a composite score. Our question is, can we develop and demonstrate a methodology that extends the "regression to the mean" literature to allow for composite quality indicators? Using a latent variable modeling approach, we extend the methodology to the composite indicator case. We demonstrate the approach on 4 indicators collected by the National Database of Nursing Quality Indicators. A simulation study further demonstrates its "proof of concept."

Scale Issues in Air Quality Modeling Policy Support

EPA Science Inventory

This study examines the issues relating to the use of regional photochemical air quality models for evaluating their performance in reproducing the spatio-temporal features embedded in the observations and for designing emission control strategies needed to achieve compliance wit...

Identifying pollution sources and predicting urban air quality using ensemble learning methods

NASA Astrophysics Data System (ADS)

Singh, Kunwar P.; Gupta, Shikha; Rai, Premanjali

2013-12-01

In this study, principal components analysis (PCA) was performed to identify air pollution sources and tree based ensemble learning models were constructed to predict the urban air quality of Lucknow (India) using the air quality and meteorological databases pertaining to a period of five years. PCA identified vehicular emissions and fuel combustion as major air pollution sources. The air quality indices revealed the air quality unhealthy during the summer and winter. Ensemble models were constructed to discriminate between the seasonal air qualities, factors responsible for discrimination, and to predict the air quality indices. Accordingly, single decision tree (SDT), decision tree forest (DTF), and decision treeboost (DTB) were constructed and their generalization and predictive performance was evaluated in terms of several statistical parameters and compared with conventional machine learning benchmark, support vector machines (SVM). The DT and SVM models discriminated the seasonal air quality rendering misclassification rate (MR) of 8.32% (SDT); 4.12% (DTF); 5.62% (DTB), and 6.18% (SVM), respectively in complete data. The AQI and CAQI regression models yielded a correlation between measured and predicted values and root mean squared error of 0.901, 6.67 and 0.825, 9.45 (SDT); 0.951, 4.85 and 0.922, 6.56 (DTF); 0.959, 4.38 and 0.929, 6.30 (DTB); 0.890, 7.00 and 0.836, 9.16 (SVR) in complete data. The DTF and DTB models outperformed the SVM both in classification and regression which could be attributed to the incorporation of the bagging and boosting algorithms in these models. The proposed ensemble models successfully predicted the urban ambient air quality and can be used as effective tools for its management.

Performance improvement: the organization's quest.

PubMed

McKinley, C O; Parmer, D E; Saint-Amand, R A; Harbin, C B; Roulston, J C; Ellis, R A; Buchanan, J R; Leonard, R B

1999-01-01

In today's health care marketplace, quality has become an expectation. Stakeholders are demanding quality clinical outcomes, and accrediting bodies are requiring clinical performance data. The Roosevelt Institute's quest was to define and quantify quality outcomes, develop an organizational culture of performance improvement, and ensure customer satisfaction. Several of the organization's leaders volunteered to work as a team to develop a specific performance improvement approach tailored to the organization. To date, over 200 employees have received an orientation to the model and its philosophy and nine problem action and process improvement teams have been formed.

[Structural Equation Modeling for Public Hospital Quality of Care, Image, Role Performance, Satisfaction, Intent to (Re)visit, and Intent to Recommend Hospital as Perceived by Community Residents].

PubMed

Hwang, Eun Jeong; Sim, In Ok

2016-02-01

The study purposes were to construct and test structural equation modeling on the causal relationship of community residents' perceived quality of care, image, and role performance with satisfaction, intention to (re)visit and intention to recommend hospital. A cross-sectional survey was conducted with 3,900 community residents from 39 district public hospitals. The questionnaire was designed to collected information on personal characteristics and community awareness of public hospitals. Community awareness consisted of 6 factors and 18 items. The data were collected utilizing call-interview by a survey company. Research data were collected via questionnaires and analyzed using SPSS version 20.0 and AMOS version 20.0. Model fit indices for the hypothetical model were suitable for the recommended level: χ²=796.40 (df=79, p<.001), GFI=.93, AGFI=.90, RMSR=.08, NFI=.94. Quality of care, image, and role performance explained 68.1% of variance in community awareness. Total effect of quality of care process factors on satisfaction (path coefficients=3.67), intention to (re)visit (path coefficients=2.67) and intention to recommend hospital (coefficients=2.45) were higher than other factors. Findings show that public hospitals have to make an effort to improve community image through the provision of quality care, and excellent role performance. Support for these activities is available from both Central and Local Governments.

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment

PubMed Central

2014-01-01

Background Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. Results MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Conclusions Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy. PMID:24731387

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment.

PubMed

Cao, Renzhi; Wang, Zheng; Cheng, Jianlin

2014-04-15

Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy.

Impact of length of calibration period on the apex model output simulation performance

USDA-ARS?s Scientific Manuscript database

Datasets from long-term monitoring sites that can be used for calibration and validation of hydrologic and water quality models are rare due to resource constraints. As a result, hydrologic and water quality models are calibrated and, when possible, validated using short-term measured data. A previo...

Impact of length of calibration period on the APEX model water quantity and quality simulation performance

USDA-ARS?s Scientific Manuscript database

Availability of continuous long-term measured data for model calibration and validation is limited due to time and resources constraints. As a result, hydrologic and water quality models are calibrated and, if possible, validated when measured data is available. Past work reported on the impact of t...

The Effect of ISO 9001 and the EFQM Model on Improving Hospital Performance: A Systematic Review.

PubMed

Yousefinezhadi, Taraneh; Mohamadi, Efat; Safari Palangi, Hossein; Akbari Sari, Ali

2015-12-01

This study aimed to explore the effect of the International Organization for Standardization (ISO) ISO 9001 standard and the European foundation for quality management (EFQM) model on improving hospital performance. PubMed, Embase and the Cochrane Library databases were searched. In addition, Elsevier and Springer were searched as main publishers in the field of health sciences. We included empirical studies with any design that had used ISO 9001 or the EFQM model to improve the quality of healthcare. Data were collected and tabulated into a data extraction sheet that was specifically designed for this study. The collected data included authors' names, country, year of publication, intervention, improvement aims, setting, length of program, study design, and outcomes. Seven out of the 121 studies that were retrieved met the inclusion criteria. Three studies assessed the EFQM model and four studies assessed the ISO 9001 standard. Use of the EFQM model increased the degree of patient satisfaction and the number of hospital admissions and reduced the average length of stay, the delay on the surgical waiting list, and the number of emergency re-admissions. ISO 9001 also increased the degree of patient satisfaction and patient safety, increased cost-effectiveness, improved the hospital admissions process, and reduced the percentage of unscheduled returns to the hospital. Generally, there is a lack of robust and high quality empirical evidence regarding the effects of ISO 9001 and the EFQM model on the quality care provided by and the performance of hospitals. However, the limited evidence shows that ISO 9001 and the EFQM model might improve hospital performance.

Handling Qualities of Model Reference Adaptive Controllers with Varying Complexity for Pitch-Roll Coupled Failures

NASA Technical Reports Server (NTRS)

Schaefer, Jacob; Hanson, Curt; Johnson, Marcus A.; Nguyen, Nhan

2011-01-01

Three model reference adaptive controllers (MRAC) with varying levels of complexity were evaluated on a high performance jet aircraft and compared along with a baseline nonlinear dynamic inversion controller. The handling qualities and performance of the controllers were examined during failure conditions that induce coupling between the pitch and roll axes. Results from flight tests showed with a roll to pitch input coupling failure, the handling qualities went from Level 2 with the baseline controller to Level 1 with the most complex MRAC tested. A failure scenario with the left stabilator frozen also showed improvement with the MRAC. Improvement in performance and handling qualities was generally seen as complexity was incrementally added; however, added complexity usually corresponds to increased verification and validation effort required for certification. The tradeoff between complexity and performance is thus important to a controls system designer when implementing an adaptive controller on an aircraft. This paper investigates this relation through flight testing of several controllers of vary complexity.

Assessing the quality of digital elevation models obtained from mini unmanned aerial vehicles for overland flow modelling in urban areas

NASA Astrophysics Data System (ADS)

Leitão, João P.; Moy de Vitry, Matthew; Scheidegger, Andreas; Rieckermann, Jörg

2016-04-01

Precise and detailed digital elevation models (DEMs) are essential to accurately predict overland flow in urban areas. Unfortunately, traditional sources of DEM, such as airplane light detection and ranging (lidar) DEMs and point and contour maps, remain a bottleneck for detailed and reliable overland flow models, because the resulting DEMs are too coarse to provide DEMs of sufficient detail to inform urban overland flows. Interestingly, technological developments of unmanned aerial vehicles (UAVs) suggest that they have matured enough to be a competitive alternative to satellites or airplanes. However, this has not been tested so far. In this study we therefore evaluated whether DEMs generated from UAV imagery are suitable for urban drainage overland flow modelling. Specifically, 14 UAV flights were conducted to assess the influence of four different flight parameters on the quality of generated DEMs: (i) flight altitude, (ii) image overlapping, (iii) camera pitch, and (iv) weather conditions. In addition, we compared the best-quality UAV DEM to a conventional lidar-based DEM. To evaluate both the quality of the UAV DEMs and the comparison to lidar-based DEMs, we performed regression analysis on several qualitative and quantitative metrics, such as elevation accuracy, quality of object representation (e.g. buildings, walls and trees) in the DEM, which were specifically tailored to assess overland flow modelling performance, using the flight parameters as explanatory variables. Our results suggested that, first, as expected, flight altitude influenced the DEM quality most, where lower flights produce better DEMs; in a similar fashion, overcast weather conditions are preferable, but weather conditions and other factors influence DEM quality much less. Second, we found that for urban overland flow modelling, the UAV DEMs performed competitively in comparison to a traditional lidar-based DEM. An important advantage of using UAVs to generate DEMs in urban areas is their flexibility that enables more frequent, local, and affordable elevation data updates, allowing, for example, to capture different tree foliage conditions.

A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

EPA Science Inventory

Fine-scale Computational Fluid Dynamics (CFD) simulation of pollutant concentrations within roadway and building microenvironments is feasible using high performance computing. Unlike currently used regulatory air quality models, fine-scale CFD simulations are able to account rig...

A FEDERATED PARTNERSHIP FOR URBAN METEOROLOGICAL AND AIR QUALITY MODELING

EPA Science Inventory

Recently, applications of urban meteorological and air quality models have been performed at resolutions on the order of km grid sizes. This necessitated development and incorporation of high resolution landcover data and additional boundary layer parameters that serve to descri...

Sensitivity of the Community Multiscale Air Quality (CMAQ) Model v4.7 Results for the Eastern United States to MM5 and WRF Meteorological Drivers

EPA Science Inventory

This paper presents a comparison of the operational performance of two Community Multiscale Air Quality (CMAQ) model v4.7 simulations that utilize input data from the 5th generation Mesoscale Model MM5 and the Weather Research and Forecasting (WRF) meteorological models.

No-reference image quality assessment based on natural scene statistics and gradient magnitude similarity

NASA Astrophysics Data System (ADS)

Jia, Huizhen; Sun, Quansen; Ji, Zexuan; Wang, Tonghan; Chen, Qiang

2014-11-01

The goal of no-reference/blind image quality assessment (NR-IQA) is to devise a perceptual model that can accurately predict the quality of a distorted image as human opinions, in which feature extraction is an important issue. However, the features used in the state-of-the-art "general purpose" NR-IQA algorithms are usually natural scene statistics (NSS) based or are perceptually relevant; therefore, the performance of these models is limited. To further improve the performance of NR-IQA, we propose a general purpose NR-IQA algorithm which combines NSS-based features with perceptually relevant features. The new method extracts features in both the spatial and gradient domains. In the spatial domain, we extract the point-wise statistics for single pixel values which are characterized by a generalized Gaussian distribution model to form the underlying features. In the gradient domain, statistical features based on neighboring gradient magnitude similarity are extracted. Then a mapping is learned to predict quality scores using a support vector regression. The experimental results on the benchmark image databases demonstrate that the proposed algorithm correlates highly with human judgments of quality and leads to significant performance improvements over state-of-the-art methods.

Determining the Effectiveness and Evaluating the Implementation Process of a Quality/Performance Circles System Model to Assist in Institutional Decision Making and Problem Solving at Lakeshore Technical Institute.

ERIC Educational Resources Information Center

Ladwig, Dennis J.

During the 1982-83 school year, a quality/performance circles system model was implemented at Lakeshore Technical Institute (LTI) to promote greater participation by staff in decision making and problem solving. All management staff at the college (N=45) were invited to participate in the process, and 39 volunteered. Non-management staff (N=240)…

One-year simulation of ozone and particulate matter in China using WRF/CMAQ modeling system

NASA Astrophysics Data System (ADS)

Hu, Jianlin; Chen, Jianjun; Ying, Qi; Zhang, Hongliang

2016-08-01

China has been experiencing severe air pollution in recent decades. Although an ambient air quality monitoring network for criteria pollutants has been constructed in over 100 cities since 2013 in China, the temporal and spatial characteristics of some important pollutants, such as particulate matter (PM) components, remain unknown, limiting further studies investigating potential air pollution control strategies to improve air quality and associating human health outcomes with air pollution exposure. In this study, a yearlong (2013) air quality simulation using the Weather Research and Forecasting (WRF) model and the Community Multi-scale Air Quality (CMAQ) model was conducted to provide detailed temporal and spatial information of ozone (O3), total PM2.5, and chemical components. Multi-resolution Emission Inventory for China (MEIC) was used for anthropogenic emissions and observation data obtained from the national air quality monitoring network were collected to validate model performance. The model successfully reproduces the O3 and PM2.5 concentrations at most cities for most months, with model performance statistics meeting the performance criteria. However, overprediction of O3 generally occurs at low concentration range while underprediction of PM2.5 happens at low concentration range in summer. Spatially, the model has better performance in southern China than in northern China, central China, and Sichuan Basin. Strong seasonal variations of PM2.5 exist and wind speed and direction play important roles in high PM2.5 events. Secondary components have more boarder distribution than primary components. Sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and primary organic aerosol (POA) are the most important PM2.5 components. All components have the highest concentrations in winter except secondary organic aerosol (SOA). This study proves the ability of the CMAQ model to reproduce severe air pollution in China, identifies the directions where improvements are needed, and provides information for human exposure to multiple pollutants for assessing health effects.

Temporal performance assessment of wastewater treatment plants by using multivariate statistical analysis.

PubMed

Ebrahimi, Milad; Gerber, Erin L; Rockaway, Thomas D

2017-05-15

For most water treatment plants, a significant number of performance data variables are attained on a time series basis. Due to the interconnectedness of the variables, it is often difficult to assess over-arching trends and quantify operational performance. The objective of this study was to establish simple and reliable predictive models to correlate target variables with specific measured parameters. This study presents a multivariate analysis of the physicochemical parameters of municipal wastewater. Fifteen quality and quantity parameters were analyzed using data recorded from 2010 to 2016. To determine the overall quality condition of raw and treated wastewater, a Wastewater Quality Index (WWQI) was developed. The index summarizes a large amount of measured quality parameters into a single water quality term by considering pre-established quality limitation standards. To identify treatment process performance, the interdependencies between the variables were determined by using Principal Component Analysis (PCA). The five extracted components from the 15 variables accounted for 75.25% of total dataset information and adequately represented the organic, nutrient, oxygen demanding, and ion activity loadings of influent and effluent streams. The study also utilized the model to predict quality parameters such as Biological Oxygen Demand (BOD), Total Phosphorus (TP), and WWQI. High accuracies ranging from 71% to 97% were achieved for fitting the models with the training dataset and relative prediction percentage errors less than 9% were achieved for the testing dataset. The presented techniques and procedures in this paper provide an assessment framework for the wastewater treatment monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multi-year downscaling application of two-way coupled WRF v3.4 and CMAQ v5.0.2 over east Asia for regional climate and air quality modeling: model evaluation and aerosol direct effects

NASA Astrophysics Data System (ADS)

Hong, Chaopeng; Zhang, Qiang; Zhang, Yang; Tang, Youhua; Tong, Daniel; He, Kebin

2017-06-01

In this study, a regional coupled climate-chemistry modeling system using the dynamical downscaling technique was established by linking the global Community Earth System Model (CESM) and the regional two-way coupled Weather Research and Forecasting - Community Multi-scale Air Quality (WRF-CMAQ) model for the purpose of comprehensive assessments of regional climate change and air quality and their interactions within one modeling framework. The modeling system was applied over east Asia for a multi-year climatological application during 2006-2010, driven with CESM downscaling data under Representative Concentration Pathways 4.5 (RCP4.5), along with a short-term air quality application in representative months in 2013 that was driven with a reanalysis dataset. A comprehensive model evaluation was conducted against observations from surface networks and satellite observations to assess the model's performance. This study presents the first application and evaluation of the two-way coupled WRF-CMAQ model for climatological simulations using the dynamical downscaling technique. The model was able to satisfactorily predict major meteorological variables. The improved statistical performance for the 2 m temperature (T2) in this study (with a mean bias of -0.6 °C) compared with the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-models might be related to the use of the regional model WRF and the bias-correction technique applied for CESM downscaling. The model showed good ability to predict PM2. 5 in winter (with a normalized mean bias (NMB) of 6.4 % in 2013) and O3 in summer (with an NMB of 18.2 % in 2013) in terms of statistical performance and spatial distributions. Compared with global models that tend to underpredict PM2. 5 concentrations in China, WRF-CMAQ was able to capture the high PM2. 5 concentrations in urban areas. In general, the two-way coupled WRF-CMAQ model performed well for both climatological and air quality applications. The coupled modeling system with direct aerosol feedbacks predicted aerosol optical depth relatively well and significantly reduced the overprediction in downward shortwave radiation at the surface (SWDOWN) over polluted regions in China. The performance of cloud variables was not as good as other meteorological variables, and underpredictions of cloud fraction resulted in overpredictions of SWDOWN and underpredictions of shortwave and longwave cloud forcing. The importance of climate-chemistry interactions was demonstrated via the impacts of aerosol direct effects on climate and air quality. The aerosol effects on climate and air quality in east Asia (e.g., SWDOWN and T2 decreased by 21.8 W m-2 and 0.45 °C, respectively, and most pollutant concentrations increased by 4.8-9.5 % in January over China's major cities) were more significant than in other regions because of higher aerosol loadings that resulted from severe regional pollution, which indicates the need for applying online-coupled models over east Asia for regional climate and air quality modeling and to study the important climate-chemistry interactions. This work established a baseline for WRF-CMAQ simulations for a future period under the RCP4.5 climate scenario, which will be presented in a future paper.

A Public-Private Partnership Develops and Externally Validates a 30-Day Hospital Readmission Risk Prediction Model

PubMed Central

Choudhry, Shahid A.; Li, Jing; Davis, Darcy; Erdmann, Cole; Sikka, Rishi; Sutariya, Bharat

2013-01-01

Introduction: Preventing the occurrence of hospital readmissions is needed to improve quality of care and foster population health across the care continuum. Hospitals are being held accountable for improving transitions of care to avert unnecessary readmissions. Advocate Health Care in Chicago and Cerner (ACC) collaborated to develop all-cause, 30-day hospital readmission risk prediction models to identify patients that need interventional resources. Ideally, prediction models should encompass several qualities: they should have high predictive ability; use reliable and clinically relevant data; use vigorous performance metrics to assess the models; be validated in populations where they are applied; and be scalable in heterogeneous populations. However, a systematic review of prediction models for hospital readmission risk determined that most performed poorly (average C-statistic of 0.66) and efforts to improve their performance are needed for widespread usage. Methods: The ACC team incorporated electronic health record data, utilized a mixed-method approach to evaluate risk factors, and externally validated their prediction models for generalizability. Inclusion and exclusion criteria were applied on the patient cohort and then split for derivation and internal validation. Stepwise logistic regression was performed to develop two predictive models: one for admission and one for discharge. The prediction models were assessed for discrimination ability, calibration, overall performance, and then externally validated. Results: The ACC Admission and Discharge Models demonstrated modest discrimination ability during derivation, internal and external validation post-recalibration (C-statistic of 0.76 and 0.78, respectively), and reasonable model fit during external validation for utility in heterogeneous populations. Conclusions: The ACC Admission and Discharge Models embody the design qualities of ideal prediction models. The ACC plans to continue its partnership to further improve and develop valuable clinical models. PMID:24224068

Impact of Performance Obstacles on Intensive Care Nurses‘ Workload, Perceived Quality and Safety of Care, and Quality of Working Life

PubMed Central

Gurses, Ayse P; Carayon, Pascale; Wall, Melanie

2009-01-01

Objectives To study the impact of performance obstacles on intensive care nurses‘ workload, quality and safety of care, and quality of working life (QWL). Performance obstacles are factors that hinder nurses‘ capacity to perform their job and that are closely associated with their immediate work system. Data Sources/Study Setting Data were collected from 265 nurses in 17 intensive care units (ICUs) between February and August 2004 via a structured questionnaire, yielding a response rate of 80 percent. Study Design A cross-sectional study design was used. Data were analyzed by correlation analyses and structural equation modeling. Principal Findings Performance obstacles were found to affect perceived quality and safety of care and QWL of ICU nurses. Workload mediated the impact of performance obstacles with the exception of equipment-related issues on perceived quality and safety of care as well as QWL. Conclusions Performance obstacles in ICUs are a major determinant of nursing workload, perceived quality and safety of care, and QWL. In general, performance obstacles increase nursing workload, which in turn negatively affect perceived quality and safety of care and QWL. Redesigning the ICU work system to reduce performance obstacles may improve nurses‘ work. PMID:19207589

Evaluation of Performance of Laboratories and Manufacturers Within the Framework of the IFCC model for Quality Targets of HbA1c.

PubMed

Weykamp, Cas; Siebelder, Carla

2017-11-01

HbA1c is a key parameter in diabetes management. For years the test has been used exclusively for monitoring of long-term diabetic control. However, due to improvement of the performance, HbA1c is considered more and more for diagnosis and screening. With this new application, quality demands further increase. A task force of the International Federation of Clinical Chemistry and Laboratory Medicine developed a model to set and evaluate quality targets for HbA1c. The model is based on the concept of total error and takes into account the major sources of analytical errors in the medical laboratory: bias and imprecision. Performance criteria are derived from sigma-metrics and biological variation. This review shows 2 examples of the application of the model: at the level of single laboratories, and at the level of a group of laboratories. In the first example data of 125 individual laboratories of a recent external quality assessment program in the Netherlands are evaluated. Differences between laboratories as well as their relation to method principles are shown. The second example uses recent and 3-year-old data of the proficiency test of the College of American Pathologists. The differences in performance between 26 manufacturer-related groups of laboratories are shown. Over time these differences are quite consistent although some manufacturers improved substantially either by better standardization or by replacing a test. The IFCC model serves all who are involved in HbA1c testing in the ongoing process of better performance and better patient care.

DEVELOPMENT AND ANALYSIS OF AIR QUALITY MODELING SIMULATIONS FOR HAZARDOUS AIR POLLUTANTS

EPA Science Inventory

The concentrations of five hazardous air pollutants were simulated using the Community Multi Scale Air Quality (CMAQ) modeling system. Annual simulations were performed over the continental United States for the entire year of 2001 to support human exposure estimates. Results a...

OBJECTIVE REDUCTION OF THE SPACE-TIME DOMAIN DIMENSIONALITY FOR EVALUATING MODEL PERFORMANCE

EPA Science Inventory

In the United States, photochemical air quality models are the principal tools used by governmental agencies to develop emission reduction strategies aimed at achieving National Ambient Air Quality Standards (NAAQS). Before they can be applied with confidence in a regulatory sett...

Evaluation of atmospheric nitrogen deposition model performance in the context of U.S. critical load assessments

NASA Astrophysics Data System (ADS)

Williams, Jason J.; Chung, Serena H.; Johansen, Anne M.; Lamb, Brian K.; Vaughan, Joseph K.; Beutel, Marc

2017-02-01

Air quality models are widely used to estimate pollutant deposition rates and thereby calculate critical loads and critical load exceedances (model deposition > critical load). However, model operational performance is not always quantified specifically to inform these applications. We developed a performance assessment approach designed to inform critical load and exceedance calculations, and applied it to the Pacific Northwest region of the U.S. We quantified wet inorganic N deposition performance of several widely-used air quality models, including five different Community Multiscale Air Quality Model (CMAQ) simulations, the Tdep model, and 'PRISM x NTN' model. Modeled wet inorganic N deposition estimates were compared to wet inorganic N deposition measurements at 16 National Trends Network (NTN) monitoring sites, and to annual bulk inorganic N deposition measurements at Mount Rainier National Park. Model bias (model - observed) and error (|model - observed|) were expressed as a percentage of regional critical load values for diatoms and lichens. This novel approach demonstrated that wet inorganic N deposition bias in the Pacific Northwest approached or exceeded 100% of regional diatom and lichen critical load values at several individual monitoring sites, and approached or exceeded 50% of critical loads when averaged regionally. Even models that adjusted deposition estimates based on deposition measurements to reduce bias or that spatially-interpolated measurement data, had bias that approached or exceeded critical loads at some locations. While wet inorganic N deposition model bias is only one source of uncertainty that can affect critical load and exceedance calculations, results demonstrate expressing bias as a percentage of critical loads at a spatial scale consistent with calculations may be a useful exercise for those performing calculations. It may help decide if model performance is adequate for a particular calculation, help assess confidence in calculation results, and highlight cases where a non-deterministic approach may be needed.

Indonesian Private University Lecturer Performance Improvement Model to Improve a Sustainable Organization Performance

ERIC Educational Resources Information Center

Suryaman

2018-01-01

Lecturer performance will affect the quality and carrying capacity of the sustainability of an organization, in this case the university. There are many models developed to measure the performance of teachers, but not much to discuss the influence of faculty performance itself towards sustainability of an organization. This study was conducted in…

Comparison of CMAQ Modeling Study with Discover-AQ 2014 Aircraft Measurements over Colorado

NASA Astrophysics Data System (ADS)

Tang, Y.; Pan, L.; Lee, P.; Tong, D.; Kim, H. C.; Artz, R. S.

2014-12-01

NASA and NCAR jointly led a recent multiple platform-based (space, air and ground) measurement intensive to study air quality and to validate satellite data. The Discover-AQ/FRAPPE field experiment took place along the Colorado Front Range in July and August, 2014. The air quality modeling team of the NOAA Air Resources Laboratory was one of the three teams that provided real-time air quality forecasting for the campaign. The U.S. EPA Community Multi-scale Air Quality (CMAQ) Model was used with emission inventories based on the data set used by the NOAA National Air Quality Forecasting Capacity (NAQFC). By analyzing the forecast results calculated using aircraft measurements, it was found that CO emissions tended to be overestimated, while ethane emissions were underestimated. Biogenic VOCs were also underpredicted. Due to their relatively high altitude, ozone concentrations in Denver and the surrounding areas are affected by both local emissions and transported ozone. The modeled ozone was highly dependent on the meteorological predictions over this region. The complex terrain over the Rocky Mountains also contributed to the model uncertainty. This study discussed the causes of model biases, the forecast performance under different meteorology, and results from using different model grid resolutions. Several data assimilation techniques were further tested to improve the "post-analysis" performance of the modeling system for the period.

A new definition of pharmaceutical quality: assembly of a risk simulation platform to investigate the impact of manufacturing/product variability on clinical performance.

PubMed

Short, Steven M; Cogdill, Robert P; D'Amico, Frank; Drennen, James K; Anderson, Carl A

2010-12-01

The absence of a unanimous, industry-specific definition of quality is, to a certain degree, impeding the progress of ongoing efforts to "modernize" the pharmaceutical industry. This work was predicated on requests by Dr. Woodcock (FDA) to re-define pharmaceutical quality in terms of risk by linking production characteristics to clinical attributes. A risk simulation platform that integrates population statistics, drug delivery system characteristics, dosing guidelines, patient compliance estimates, production metrics, and pharmacokinetic, pharmacodynamic, and in vitro-in vivo correlation models to investigate the impact of manufacturing variability on clinical performance of a model extended-release theophylline solid oral dosage system was developed. Manufacturing was characterized by inter- and intra-batch content uniformity and dissolution variability metrics, while clinical performance was described by a probabilistic pharmacodynamic model that expressed the probability of inefficacy and toxicity as a function of plasma concentrations. Least-squares regression revealed that both patient compliance variables, percent of doses taken and dosing time variability, significantly impacted efficacy and toxicity. Additionally, intra-batch content uniformity variability elicited a significant change in risk scores for the two adverse events and, therefore, was identified as a critical quality attribute. The proposed methodology demonstrates that pharmaceutical quality can be recast to explicitly reflect clinical performance. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Impact of Expert Teaching Quality on Novice Academic Performance in the Jigsaw Cooperative Learning Method

NASA Astrophysics Data System (ADS)

Berger, Roland; Hänze, Martin

2015-01-01

We assessed the impact of expert students' instructional quality on the academic performance of novice students in 12th-grade physics classes organized in an expert model of cooperative learning ('jigsaw classroom'). The instructional quality of 129 expert students was measured by a newly developed rating system. As expected, when aggregating across all four subtopics taught, regression analysis revealed that academic performance of novice students increases with the quality of expert students' instruction. The difficulty of subtopics, however, moderates this effect: higher instructional quality of more difficult subtopics did not lead to better academic performance of novice students. We interpret this finding in the light of Cognitive Load Theory. Demanding tasks cause high intrinsic cognitive load and hindered the novice students' learning.

The Automation of Nowcast Model Assessment Processes

DTIC Science & Technology

2016-09-01

that will automate real-time WRE-N model simulations, collect and quality control check weather observations for assimilation and verification, and...domains centered near White Sands Missile Range, New Mexico, where the Meteorological Sensor Array (MSA) will be located. The MSA will provide...observations and performing quality -control checks for the pre-forecast data assimilation period. 2. Run the WRE-N model to generate model forecast data

Where should Momma go? Current nursing home performance measurement strategies and a less ambitious approach.

PubMed

Phillips, Charles D; Hawes, Catherine; Lieberman, Trudy; Koren, Mary Jane

2007-06-25

Nursing home performance measurement systems are practically ubiquitous. The vast majority of these systems aspire to rank order all nursing homes based on quantitative measures of quality. However, the ability of such systems to identify homes differing in quality is hampered by the multidimensional nature of nursing homes and their residents. As a result, the authors doubt the ability of many nursing home performance systems to truly help consumers differentiate among homes providing different levels of quality. We also argue that, for consumers, performance measurement models are better at identifying problem facilities than potentially good homes. In response to these concerns we present a proposal for a less ambitious approach to nursing home performance measurement than previously used. We believe consumers can make better informed choice using a simpler system designed to pinpoint poor-quality nursing homes, rather than one designed to rank hundreds of facilities based on differences in quality-of-care indicators that are of questionable importance. The suggested performance model is based on five principles used in the development of the Consumers Union 2006 Nursing Home Quality Monitor. We can best serve policy-makers and consumers by eschewing nursing home reporting systems that present information about all the facilities in a city, a state, or the nation on a website or in a report. We argue for greater modesty in our efforts and a focus on identifying only the potentially poorest or best homes. In the end, however, it is important to remember that information from any performance measurement website or report is no substitute for multiple visits to a home at different times of the day to personally assess quality.

Research on the Establishment and Evaluation of End - to - End Service Quality Index System

NASA Astrophysics Data System (ADS)

Wei, Chen; Jing, Tao; Ji, Yutong

2018-01-01

From the perspective of power data networks, put forward the index system model to measure the quality of service, covering user experience, business performance, network capacity support, etc., and gives the establishment and use of each layer index in the model.

“Estimating Regional Background Air Quality using Space/Time Ordinary Kriging to Support Exposure Studies”

EPA Science Inventory

Local-scale dispersion models are increasingly being used to perform exposure assessments. These types of models, while able to characterize local-scale air quality at increasing spatial scale, however, lack the ability to include background concentration in their overall estimat...

Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The AMAD will performed two CMAQ model simulations, one with the current publically available version of the CMAQ model (v5.0.2) and the other with the new version of the CMAQ model (v5.1). The results of each model simulation are compared to observations and the performance of t...

The development of an integrated Indonesian health care model using Kano's model, quality function deployment and balanced scorecard

NASA Astrophysics Data System (ADS)

Jonny, Zagloed, Teuku Yuri M.

2017-11-01

This paper aims to present an integrated health care model for Indonesian health care industry. Based on previous researches, there are two health care models in the industry such as decease- and patient-centered care models. In their developments, the patient-centered care model is widely applied due to its capability in reducing cost and improving quality simultaneously. However, there is still no comprehensive model resulting in cost reduction, quality improvement, patient satisfaction and hospital profitability simultaneously. Therefore, this research is intended to develop that model. In doing so, first, a conceptual model using Kano's Model, Quality Function Deployment (QFD) and Balanced Scorecard (BSC) is developed to generate several important elements of the model as required by stakeholders. Then, a case study of an Indonesian hospital is presented to evaluate the validity of the model using correlation analysis. As a result, it can be concluded that the model is validated implying several managerial insights among its elements such as l) leadership (r=0.85) and context of the organization (r=0.77) improve operations; 2) planning (r=0.96), support process (r=0.87) and continual improvement (r=0.95) also improve operations; 3) operations improve customer satisfaction (r=0.89) and financial performance (r=0.93) and 4) customer satisfaction improves the financial performance (0.98).

Good quality sleep is associated with better academic performance among university students in Ethiopia.

PubMed

Lemma, Seblewengel; Berhane, Yemane; Worku, Alemayehu; Gelaye, Bizu; Williams, Michelle A

2014-05-01

This study assessed the association of sleep quality with academic performance among university students in Ethiopia. This cross-sectional study of 2,173 college students (471 female and 1,672 male) was conducted in two universities in Ethiopia. Students were selected into the study using a multistage sampling procedure, and data were collected through a self-administered questionnaire. Sleep quality was assessed using Pittsburgh Sleep Quality Index, and academic performance was based on self-reported cumulative grade point average. The Student's "t" test, analysis of variance, and multiple linear regression were used to evaluate associations. We found that students with better sleep quality score achieved better on their academic performance (P value = 0.001), while sleep duration was not associated with academic performance in the final model. Our study underscores the importance of sleep quality on better academic performance. Future studies need to identify the possible factors which influence sleep quality other than the academic environment repeatedly reported by other literature. It is imperative to design and implement appropriate interventions to improve sleep quality in light of the current body of evidence to enhance academic success in the study setting.

The Effect of ISO 9001 and the EFQM Model on Improving Hospital Performance: A Systematic Review

PubMed Central

Yousefinezhadi, Taraneh; Mohamadi, Efat; Safari Palangi, Hossein; Akbari Sari, Ali

2015-01-01

Context: This study aimed to explore the effect of the International Organization for Standardization (ISO) ISO 9001 standard and the European foundation for quality management (EFQM) model on improving hospital performance. Evidence Acquisition: PubMed, Embase and the Cochrane Library databases were searched. In addition, Elsevier and Springer were searched as main publishers in the field of health sciences. We included empirical studies with any design that had used ISO 9001 or the EFQM model to improve the quality of healthcare. Data were collected and tabulated into a data extraction sheet that was specifically designed for this study. The collected data included authors’ names, country, year of publication, intervention, improvement aims, setting, length of program, study design, and outcomes. Results: Seven out of the 121 studies that were retrieved met the inclusion criteria. Three studies assessed the EFQM model and four studies assessed the ISO 9001 standard. Use of the EFQM model increased the degree of patient satisfaction and the number of hospital admissions and reduced the average length of stay, the delay on the surgical waiting list, and the number of emergency re-admissions. ISO 9001 also increased the degree of patient satisfaction and patient safety, increased cost-effectiveness, improved the hospital admissions process, and reduced the percentage of unscheduled returns to the hospital. Conclusions: Generally, there is a lack of robust and high quality empirical evidence regarding the effects of ISO 9001 and the EFQM model on the quality care provided by and the performance of hospitals. However, the limited evidence shows that ISO 9001 and the EFQM model might improve hospital performance. PMID:26756012

Development and implementation of a regression model for predicting recreational water quality in the Cuyahoga River, Cuyahoga Valley National Park, Ohio 2009-11

USGS Publications Warehouse

Brady, Amie M.G.; Plona, Meg B.

2012-01-01

The Cuyahoga River within Cuyahoga Valley National Park (CVNP) is at times impaired for recreational use due to elevated concentrations of Escherichia coli (E. coli), a fecal-indicator bacterium. During the recreational seasons of mid-May through September during 2009–11, samples were collected 4 days per week and analyzed for E. coli concentrations at two sites within CVNP. Other water-quality and environ-mental data, including turbidity, rainfall, and streamflow, were measured and (or) tabulated for analysis. Regression models developed to predict recreational water quality in the river were implemented during the recreational seasons of 2009–11 for one site within CVNP–Jaite. For the 2009 and 2010 seasons, the regression models were better at predicting exceedances of Ohio's single-sample standard for primary-contact recreation compared to the traditional method of using the previous day's E. coli concentration. During 2009, the regression model was based on data collected during 2005 through 2008, excluding available 2004 data. The resulting model for 2009 did not perform as well as expected (based on the calibration data set) and tended to overestimate concentrations (correct responses at 69 percent). During 2010, the regression model was based on data collected during 2004 through 2009, including all of the available data. The 2010 model performed well, correctly predicting 89 percent of the samples above or below the single-sample standard, even though the predictions tended to be lower than actual sample concentrations. During 2011, the regression model was based on data collected during 2004 through 2010 and tended to overestimate concentrations. The 2011 model did not perform as well as the traditional method or as expected, based on the calibration dataset (correct responses at 56 percent). At a second site—Lock 29, approximately 5 river miles upstream from Jaite, a regression model based on data collected at the site during the recreational seasons of 2008–10 also did not perform as well as the traditional method or as well as expected (correct responses at 60 percent). Above normal precipitation in the region and a delayed start to the 2011 sampling season (sampling began mid-June) may have affected how well the 2011 models performed. With these new data, however, updated regression models may be better able to predict recreational water quality conditions due to the increased amount of diverse water quality conditions included in the calibration data. Daily recreational water-quality predictions for Jaite were made available on the Ohio Nowcast Web site at www.ohionowcast.info. Other public outreach included signage at trailheads in the park, articles in the park's quarterly-published schedule of events and volunteer newsletters. A U.S. Geological Survey Fact Sheet was also published to bring attention to water-quality issues in the park.

Useful measures and models for analytical quality management in medical laboratories.

PubMed

Westgard, James O

2016-02-01

The 2014 Milan Conference "Defining analytical performance goals 15 years after the Stockholm Conference" initiated a new discussion of issues concerning goals for precision, trueness or bias, total analytical error (TAE), and measurement uncertainty (MU). Goal-setting models are critical for analytical quality management, along with error models, quality-assessment models, quality-planning models, as well as comprehensive models for quality management systems. There are also critical underlying issues, such as an emphasis on MU to the possible exclusion of TAE and a corresponding preference for separate precision and bias goals instead of a combined total error goal. This opinion recommends careful consideration of the differences in the concepts of accuracy and traceability and the appropriateness of different measures, particularly TAE as a measure of accuracy and MU as a measure of traceability. TAE is essential to manage quality within a medical laboratory and MU and trueness are essential to achieve comparability of results across laboratories. With this perspective, laboratory scientists can better understand the many measures and models needed for analytical quality management and assess their usefulness for practical applications in medical laboratories.

Modeling subjective evaluation of soundscape quality in urban open spaces: An artificial neural network approach.

PubMed

Yu, Lei; Kang, Jian

2009-09-01

This research aims to explore the feasibility of using computer-based models to predict the soundscape quality evaluation of potential users in urban open spaces at the design stage. With the data from large scale field surveys in 19 urban open spaces across Europe and China, the importance of various physical, behavioral, social, demographical, and psychological factors for the soundscape evaluation has been statistically analyzed. Artificial neural network (ANN) models have then been explored at three levels. It has been shown that for both subjective sound level and acoustic comfort evaluation, a general model for all the case study sites is less feasible due to the complex physical and social environments in urban open spaces; models based on individual case study sites perform well but the application range is limited; and specific models for certain types of location/function would be reliable and practical. The performance of acoustic comfort models is considerably better than that of sound level models. Based on the ANN models, soundscape quality maps can be produced and this has been demonstrated with an example.

Comparison of the Mortality Probability Admission Model III, National Quality Forum, and Acute Physiology and Chronic Health Evaluation IV hospital mortality models: implications for national benchmarking*.

PubMed

Kramer, Andrew A; Higgins, Thomas L; Zimmerman, Jack E

2014-03-01

To examine the accuracy of the original Mortality Probability Admission Model III, ICU Outcomes Model/National Quality Forum modification of Mortality Probability Admission Model III, and Acute Physiology and Chronic Health Evaluation IVa models for comparing observed and risk-adjusted hospital mortality predictions. Retrospective paired analyses of day 1 hospital mortality predictions using three prognostic models. Fifty-five ICUs at 38 U.S. hospitals from January 2008 to December 2012. Among 174,001 intensive care admissions, 109,926 met model inclusion criteria and 55,304 had data for mortality prediction using all three models. None. We compared patient exclusions and the discrimination, calibration, and accuracy for each model. Acute Physiology and Chronic Health Evaluation IVa excluded 10.7% of all patients, ICU Outcomes Model/National Quality Forum 20.1%, and Mortality Probability Admission Model III 24.1%. Discrimination of Acute Physiology and Chronic Health Evaluation IVa was superior with area under receiver operating curve (0.88) compared with Mortality Probability Admission Model III (0.81) and ICU Outcomes Model/National Quality Forum (0.80). Acute Physiology and Chronic Health Evaluation IVa was better calibrated (lowest Hosmer-Lemeshow statistic). The accuracy of Acute Physiology and Chronic Health Evaluation IVa was superior (adjusted Brier score = 31.0%) to that for Mortality Probability Admission Model III (16.1%) and ICU Outcomes Model/National Quality Forum (17.8%). Compared with observed mortality, Acute Physiology and Chronic Health Evaluation IVa overpredicted mortality by 1.5% and Mortality Probability Admission Model III by 3.1%; ICU Outcomes Model/National Quality Forum underpredicted mortality by 1.2%. Calibration curves showed that Acute Physiology and Chronic Health Evaluation performed well over the entire risk range, unlike the Mortality Probability Admission Model and ICU Outcomes Model/National Quality Forum models. Acute Physiology and Chronic Health Evaluation IVa had better accuracy within patient subgroups and for specific admission diagnoses. Acute Physiology and Chronic Health Evaluation IVa offered the best discrimination and calibration on a large common dataset and excluded fewer patients than Mortality Probability Admission Model III or ICU Outcomes Model/National Quality Forum. The choice of ICU performance benchmarks should be based on a comparison of model accuracy using data for identical patients.

Comparison of exposure estimation methods for air pollutants: ambient monitoring data and regional air quality simulation.

PubMed

Bravo, Mercedes A; Fuentes, Montserrat; Zhang, Yang; Burr, Michael J; Bell, Michelle L

2012-07-01

Air quality modeling could potentially improve exposure estimates for use in epidemiological studies. We investigated this application of air quality modeling by estimating location-specific (point) and spatially-aggregated (county level) exposure concentrations of particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM(2.5)) and ozone (O(3)) for the eastern U.S. in 2002 using the Community Multi-scale Air Quality (CMAQ) modeling system and a traditional approach using ambient monitors. The monitoring approach produced estimates for 370 and 454 counties for PM(2.5) and O(3), respectively. Modeled estimates included 1861 counties, covering 50% more population. The population uncovered by monitors differed from those near monitors (e.g., urbanicity, race, education, age, unemployment, income, modeled pollutant levels). CMAQ overestimated O(3) (annual normalized mean bias=4.30%), while modeled PM(2.5) had an annual normalized mean bias of -2.09%, although bias varied seasonally, from 32% in November to -27% in July. Epidemiology may benefit from air quality modeling, with improved spatial and temporal resolution and the ability to study populations far from monitors that may differ from those near monitors. However, model performance varied by measure of performance, season, and location. Thus, the appropriateness of using such modeled exposures in health studies depends on the pollutant and metric of concern, acceptable level of uncertainty, population of interest, study design, and other factors. Copyright © 2012 Elsevier Inc. All rights reserved.

Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment.

PubMed

Shi, Yuan; Lau, Kevin Ka-Lun; Ng, Edward

2017-08-01

Urban air quality serves as an important function of the quality of urban life. Land use regression (LUR) modelling of air quality is essential for conducting health impacts assessment but more challenging in mountainous high-density urban scenario due to the complexities of the urban environment. In this study, a total of 21 LUR models are developed for seven kinds of air pollutants (gaseous air pollutants CO, NO 2 , NO x , O 3 , SO 2 and particulate air pollutants PM 2.5 , PM 10 ) with reference to three different time periods (summertime, wintertime and annual average of 5-year long-term hourly monitoring data from local air quality monitoring network) in Hong Kong. Under the mountainous high-density urban scenario, we improved the traditional LUR modelling method by incorporating wind availability information into LUR modelling based on surface geomorphometrical analysis. As a result, 269 independent variables were examined to develop the LUR models by using the "ADDRESS" independent variable selection method and stepwise multiple linear regression (MLR). Cross validation has been performed for each resultant model. The results show that wind-related variables are included in most of the resultant models as statistically significant independent variables. Compared with the traditional method, a maximum increase of 20% was achieved in the prediction performance of annual averaged NO 2 concentration level by incorporating wind-related variables into LUR model development. Copyright © 2017 Elsevier Inc. All rights reserved.

The use of quantile regression to forecast higher than expected respiratory deaths in a daily time series: a study of New York City data 1987-2000.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D

2013-01-01

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths. Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal/temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1). The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2) This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept.

The Use of Quantile Regression to Forecast Higher Than Expected Respiratory Deaths in a Daily Time Series: A Study of New York City Data 1987-2000

PubMed Central

Soyiri, Ireneous N.; Reidpath, Daniel D.

2013-01-01

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths. Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal / temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1). The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2) This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept. PMID:24147122

Bayesian Maximum Entropy Integration of Ozone Observations and Model Predictions: A National Application.

PubMed

Xu, Yadong; Serre, Marc L; Reyes, Jeanette; Vizuete, William

2016-04-19

To improve ozone exposure estimates for ambient concentrations at a national scale, we introduce our novel Regionalized Air Quality Model Performance (RAMP) approach to integrate chemical transport model (CTM) predictions with the available ozone observations using the Bayesian Maximum Entropy (BME) framework. The framework models the nonlinear and nonhomoscedastic relation between air pollution observations and CTM predictions and for the first time accounts for variability in CTM model performance. A validation analysis using only noncollocated data outside of a validation radius rv was performed and the R(2) between observations and re-estimated values for two daily metrics, the daily maximum 8-h average (DM8A) and the daily 24-h average (D24A) ozone concentrations, were obtained with the OBS scenario using ozone observations only in contrast with the RAMP and a Constant Air Quality Model Performance (CAMP) scenarios. We show that, by accounting for the spatial and temporal variability in model performance, our novel RAMP approach is able to extract more information in terms of R(2) increase percentage, with over 12 times for the DM8A and over 3.5 times for the D24A ozone concentrations, from CTM predictions than the CAMP approach assuming that model performance does not change across space and time.

Evaluation of Model Recognition for Grammar-Based Automatic 3d Building Model Reconstruction

NASA Astrophysics Data System (ADS)

Yu, Qian; Helmholz, Petra; Belton, David

2016-06-01

In recent years, 3D city models are in high demand by many public and private organisations, and the steadily growing capacity in both quality and quantity are increasing demand. The quality evaluation of these 3D models is a relevant issue both from the scientific and practical points of view. In this paper, we present a method for the quality evaluation of 3D building models which are reconstructed automatically from terrestrial laser scanning (TLS) data based on an attributed building grammar. The entire evaluation process has been performed in all the three dimensions in terms of completeness and correctness of the reconstruction. Six quality measures are introduced to apply on four datasets of reconstructed building models in order to describe the quality of the automatic reconstruction, and also are assessed on their validity from the evaluation point of view.

Development of visibility forecasting modeling framework for the Lower Fraser Valley of British Columbia using Canada's Regional Air Quality Deterministic Prediction System.

PubMed

So, Rita; Teakles, Andrew; Baik, Jonathan; Vingarzan, Roxanne; Jones, Keith

2018-05-01

Visibility degradation, one of the most noticeable indicators of poor air quality, can occur despite relatively low levels of particulate matter when the risk to human health is low. The availability of timely and reliable visibility forecasts can provide a more comprehensive understanding of the anticipated air quality conditions to better inform local jurisdictions and the public. This paper describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada's operational Regional Air Quality Deterministic Prediction System (RAQDPS) for the Lower Fraser Valley of British Columbia. A baseline model (GM-IMPROVE) was constructed using the revised IMPROVE algorithm based on unprocessed forecasts from the RAQDPS. Three additional prototypes (UMOS-HYB, GM-MLR, GM-RF) were also developed and assessed for forecast performance of up to 48 hr lead time during various air quality and meteorological conditions. Forecast performance was assessed by examining their ability to provide both numerical and categorical forecasts in the form of 1-hr total extinction and Visual Air Quality Ratings (VAQR), respectively. While GM-IMPROVE generally overestimated extinction more than twofold, it had skill in forecasting the relative species contribution to visibility impairment, including ammonium sulfate and ammonium nitrate. Both statistical prototypes, GM-MLR and GM-RF, performed well in forecasting 1-hr extinction during daylight hours, with correlation coefficients (R) ranging from 0.59 to 0.77. UMOS-HYB, a prototype based on postprocessed air quality forecasts without additional statistical modeling, provided reasonable forecasts during most daylight hours. In terms of categorical forecasts, the best prototype was approximately 75 to 87% correct, when forecasting for a condensed three-category VAQR. A case study, focusing on a poor visual air quality yet low Air Quality Health Index episode, illustrated that the statistical prototypes were able to provide timely and skillful visibility forecasts with lead time up to 48 hr. This study describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada's operational Regional Air Quality Deterministic Prediction System. The main applications include tourism and recreation planning, input into air quality management programs, and educational outreach. Visibility forecasts, when supplemented with the existing air quality and health based forecasts, can assist jurisdictions to anticipate the visual air quality impacts as perceived by the public, which can potentially assist in formulating the appropriate air quality bulletins and recommendations.

A Multi-Model Assessment for the 2006 and 2010 Simulations under the Air Quality Model Evaluation International Initiative (AQMEII) Phase 2 over North America: Part II. Evaluation of Column Variable Predictions Using Satellite Data

EPA Science Inventory

Within the context of the Air Quality Model Evaluation International Initiative phase 2 (AQMEII2) project, this part II paper performs a multi-model assessment of major column abundances of gases, radiation, aerosol, and cloud variables for 2006 and 2010 simulations with three on...

The impact of the board's strategy-setting role on board-management relations and hospital performance.

PubMed

Büchner, Vera Antonia; Schreyögg, Jonas; Schultz, Carsten

2014-01-01

The appropriate governance of hospitals largely depends on effective cooperation between governing boards and hospital management. Governing boards play an important role in strategy-setting as part of their support for hospital management. However, in certain situations, this active strategic role may also generate discord within this relationship. The objective of this study is to investigate the impact of the roles, attributes, and processes of governing boards on hospital performance. We examine the impact of the governing board's strategy-setting role on board-management collaboration quality and on financial performance while also analyzing the interaction effects of board diversity and board activity level. The data are derived from a survey that was sent simultaneously to German hospitals and their associated governing board, combined with objective performance information from annual financial statements and quality reports. We use a structural equation modeling approach to test the model. The results indicate that different board characteristics have a significant impact on hospital performance (R = .37). The strategy-setting role and board-management collaboration quality have a positive effect on hospital performance, whereas the impact of strategy-setting on collaboration quality is negative. We find that the positive effect of strategy-setting on performance increases with decreasing board diversity. When board members have more homogeneous backgrounds and exhibit higher board activity levels, the negative effect of the strategy-setting on collaboration quality also increases. Active strategy-setting by a governing board may generally improve hospital performance. Diverse members of governing boards should be involved in strategy-setting for hospitals. However, high board-management collaboration quality may be compromised if managerial autonomy is too highly restricted. Consequently, hospitals should support board-management collaboration about empowered contrasting board roles.

Annual Application and Evaluation of the Online Coupled WRF‐CMAQ System over North America under AQMEII Phase 2

EPA Science Inventory

We present an application of the online coupled WRF-CMAQ modeling system to two annual simulations over North America performed under Phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII). Operational evaluation shows that model performance is comparable t...

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.

Performance evaluation of public hospital information systems by the information system success model.

PubMed

Cho, Kyoung Won; Bae, Sung-Kwon; Ryu, Ji-Hye; Kim, Kyeong Na; An, Chang-Ho; Chae, Young Moon

2015-01-01

This study was to evaluate the performance of the newly developed information system (IS) implemented on July 1, 2014 at three public hospitals in Korea. User satisfaction scores of twelve key performance indicators of six IS success factors based on the DeLone and McLean IS Success Model were utilized to evaluate IS performance before and after the newly developed system was introduced. All scores increased after system introduction except for the completeness of medical records and impact on the clinical environment. The relationships among six IS factors were also analyzed to identify the important factors influencing three IS success factors (Intention to Use, User Satisfaction, and Net Benefits). All relationships were significant except for the relationships among Service Quality, Intention to Use, and Net Benefits. The results suggest that hospitals should not only focus on systems and information quality; rather, they should also continuously improve service quality to improve user satisfaction and eventually reach full the potential of IS performance.

[Pay for performance in dental care: A systematic narrative review of quality P4P models in dental care].

PubMed

Chenot, Regine

2017-11-01

Pay for performance (P4P) links reimbursement to the achievement of quality objectives. Experiences with P4P instruments and studies on their effects are available for the inpatient sector. A systematic narrative review brings together findings concerning the use and the effects of P4P, especially in dental care. A systematic literature search in PubMed and the Cochrane Library for reimbursement models using quality indicators provided 77 publications. Inclusion criteria were: year of publication not older than 2007, dental sector, models of quality-oriented remuneration, quality of care, quality indicators. 27 publications met the inclusion criteria and were evaluated with regard to the instruments and effects of P4P. The database search was supplemented by a free search on the Internet as well as a search in indicator databases and portals. The results of the included studies were extracted and summarized narratively. 27 studies were included in the review. Performance-oriented remuneration is an instrument of quality competition. In principle, P4P is embedded in an existing remuneration system, i.e., it does not occur in isolation. In the United States, England and Scandinavia, models are currently being tested for quality-oriented remuneration in dental care, based on quality indicators. The studies identified by the literature search are very heterogeneous and do not yield comparable endpoints. Difficulties are seen in the reproducibility of the quality of dental care with regard to certain characteristics which still have to be defined as quality-promoting properties. Risk selection cannot be ruled out, which may have an impact on structural quality (access to care, coordination). There were no long-term effects of P4P on the quality of care. In the short and medium term, adverse effects on the participants' motivation as well as shifting effects towards the private sector are described. A prerequisite for the functioning of P4P is the definition of clear targets and measuring parameters. Furthermore, evidence-based quality indicators have to be developed that validly depict quality differences. It is yet unknown whether P4P will have long-term effects or whether the quality of dental care will increase. Copyright © 2017. Published by Elsevier GmbH.

Sound quality indicators for urban places in Paris cross-validated by Milan data.

PubMed

Ricciardi, Paola; Delaitre, Pauline; Lavandier, Catherine; Torchia, Francesca; Aumond, Pierre

2015-10-01

A specific smartphone application was developed to collect perceptive and acoustic data in Paris. About 3400 questionnaires were analyzed, regarding the global sound environment characterization, the perceived loudness of some emergent sources and the presence time ratio of sources that do not emerge from the background. Sound pressure level was recorded each second from the mobile phone's microphone during a 10-min period. The aim of this study is to propose indicators of urban sound quality based on linear regressions with perceptive variables. A cross validation of the quality models extracted from Paris data was carried out by conducting the same survey in Milan. The proposed sound quality general model is correlated with the real perceived sound quality (72%). Another model without visual amenity and familiarity is 58% correlated with perceived sound quality. In order to improve the sound quality indicator, a site classification was performed by Kohonen's Artificial Neural Network algorithm, and seven specific class models were developed. These specific models attribute more importance on source events and are slightly closer to the individual data than the global model. In general, the Parisian models underestimate the sound quality of Milan environments assessed by Italian people.

Persistence of initial conditions in continental scale air quality simulations

EPA Science Inventory

This study investigates the effect of initial conditions (IC) for pollutant concentrations in the atmosphere and soil on simulated air quality for two continental-scale Community Multiscale Air Quality (CMAQ) model applications. One of these applications was performed for springt...

Improving cardiovascular care through outpatient cardiac rehabilitation: an analysis of payment models that would improve quality and promote use.

PubMed

Mead, Holly; Grantham, Sarah; Siegel, Bruce

2014-01-01

Much attention has been paid to improving the care of patients with cardiovascular disease by focusing attention on delivery system redesign and payment reforms that encompass the healthcare spectrum, from an acute episode to maintenance of care. However, 1 area of cardiovascular disease care that has received little attention in the advancement of quality is cardiac rehabilitation (CR), a comprehensive secondary prevention program that is significantly underused despite evidence-based guidelines that recommending its use. The purpose of this article was to analyze the applicability of 2 payment and reimbursement models-pay-for-performance and bundled payments for episodes of care--that can promote the use of CR. We conclude that a payment model combining elements of both pay-for-performance and episodes of care would increase the use of CR, which would both improve quality and increase efficiency in cardiac care. Specific elements would need to be clearly defined, however, including: (a) how an episode is defined, (b) how to hold providers accountable for the care they provider, (c) how to encourage participation among CR providers, and (d) how to determine an equitable distribution of payment. Demonstrations testing new payment models must be implemented to generate empirical evidence that a melded pay-for-performance and episode-based care payment model will improve quality and efficiency.

Sensitivity analyses of factors influencing CMAQ performance for fine particulate nitrate.

PubMed

Shimadera, Hikari; Hayami, Hiroshi; Chatani, Satoru; Morino, Yu; Mori, Yasuaki; Morikawa, Tazuko; Yamaji, Kazuyo; Ohara, Toshimasa

2014-04-01

Improvement of air quality models is required so that they can be utilized to design effective control strategies for fine particulate matter (PM2.5). The Community Multiscale Air Quality modeling system was applied to the Greater Tokyo Area of Japan in winter 2010 and summer 2011. The model results were compared with observed concentrations of PM2.5 sulfate (SO4(2-)), nitrate (NO3(-)) and ammonium, and gaseous nitric acid (HNO3) and ammonia (NH3). The model approximately reproduced PM2.5 SO4(2-) concentration, but clearly overestimated PM2.5 NO3(-) concentration, which was attributed to overestimation of production of ammonium nitrate (NH4NO3). This study conducted sensitivity analyses of factors associated with the model performance for PM2.5 NO3(-) concentration, including temperature and relative humidity, emission of nitrogen oxides, seasonal variation of NH3 emission, HNO3 and NH3 dry deposition velocities, and heterogeneous reaction probability of dinitrogen pentoxide. Change in NH3 emission directly affected NH3 concentration, and substantially affected NH4NO3 concentration. Higher dry deposition velocities of HNO3 and NH3 led to substantial reductions of concentrations of the gaseous species and NH4NO3. Because uncertainties in NH3 emission and dry deposition processes are probably large, these processes may be key factors for improvement of the model performance for PM2.5 NO3(-). The Community Multiscale Air Quality modeling system clearly overestimated the concentration of fine particulate nitrate in the Greater Tokyo Area of Japan, which was attributed to overestimation of production of ammonium nitrate. Sensitivity analyses were conducted for factors associated with the model performance for nitrate. Ammonia emission and dry deposition of nitric acid and ammonia may be key factors for improvement of the model performance.

[THE EMPIRICAL DISTINCTIVENESS OF WORK ENGAGEMENT AND WORKAHOLISM AMONG HOSPITAL NURSES IN JAPAN : THE EFFECT ON SLEEP QUALITY AND JOB PERFORMANCE].

PubMed

Kubota, Kazumi; Shimazu, Akihito; Kawakami, Norito; Takahashi, Masaya; Nakata, Akinori; Schaufeli, Wilmar B

2011-01-01

The aim of the present study is to demonstrate the distinctiveness of work engagement and workaholism by examining their relationships with sleep quality and job performance. A total of 447 nurses from 3 hospitals in Japan were surveyed using a self-administrated questionnaire including Utrecht Work Engagement Scale (UWES), the Dutch Workaholism Scale (DUWAS), questions on sleep quality (7 items) regarding (1) difficulty initiating sleep, (2) difficulty maintaining sleep, (3) early morning awakening, (4) dozing off or napping in daytime, (5) excessive daytime sleepiness at work, (6) difficulty awakening in the morning, and (7) tiredness awakening in the morning, and the World Health Organization Health Work Performance Questionnaire. The Structural Equation Modeling showed that, work engagement was positively related to sleep quality and job performance whereas workaholism negatively to sleep quality and job performance. The findings suggest that work engagement and workaholism are conceptually distinctive and that the former is positively and the latter is negatively related to well-being (i.e., good sleep quality and job performance).

Status of Air Quality in Central California and Needs for Further Study

NASA Astrophysics Data System (ADS)

Tanrikulu, S.; Beaver, S.; Soong, S.; Tran, C.; Jia, Y.; Matsuoka, J.; McNider, R. T.; Biazar, A. P.; Palazoglu, A.; Lee, P.; Wang, J.; Kang, D.; Aneja, V. P.

2012-12-01

Ozone and PM2.5 levels frequently exceed NAAQS in central California (CC). Additional emission reductions are needed to attain and maintain the standards there. Agencies are developing cost-effective emission control strategies along with complementary incentive programs to reduce emissions when exceedances are forecasted. These approaches require accurate modeling and forecasting capabilities. A variety of models have been rigorously applied (MM5, WRF, CMAQ, CAMx) over CC. Despite the vast amount of land-based measurements from special field programs and significant effort, models have historically exhibited marginal performance. Satellite data may improve model performance by: establishing IC/BC over outlying areas of the modeling domain having unknown conditions; enabling FDDA over the Pacific Ocean to characterize important marine inflows and pollutant outflows; and filling in the gaps of the land-based monitoring network. BAAQMD, in collaboration with the NASA AQAST, plans to conduct four studies that include satellite-based data in CC air quality analysis and modeling: The first project enhances and refines weather patterns, especially aloft, impacting summer ozone formation. Surface analyses were unable to characterize the strong attenuating effect of the complex terrain to steer marine winds impinging on the continent. The dense summer clouds and fog over the Pacific Ocean form spatial patterns that can be related to the downstream air flows through polluted areas. The goal of this project is to explore, characterize, and quantify these relationships using cloud cover data. Specifically, cloud agreement statistics will be developed using satellite data and model clouds. Model skin temperature predictions will be compared to both MODIS and GOES skin temperatures. The second project evaluates and improves the initial and simulated fields of meteorological models that provide inputs to air quality models. The study will attempt to determine whether a cloud dynamical adjustment developed by UAHuntsville can improve model performance for maritime stratus and whether a moisture adjustment scheme in the Pleim-Xiu boundary layer scheme can use satellite data in place of coarse surface air temperature measurements. The goal is to improve meteorological model performance that leads to improved air quality model performance. The third project evaluates and improves forecasting skills of the National Air Quality Forecasting Model in CC by using land-based routine measurements as well as satellite data. Local forecasts are mostly based on surface meteorological and air quality measurements and weather charts provided by NWS. The goal is to improve the average accuracy in forecasting exceedances, which is around 60%. The fourth project uses satellite data for monitoring trends in fine particulate matter (PM2.5) in the San Francisco Bay Area. It evaluates the effectiveness of a rule adopted in 2008 that restricts household wood burning on days forecasted to have high PM2.5 levels. The goal is to complement current analyses based on surface data covering the largest sub-regions and population centers. The overall goal is to use satellite data to overcome limitations of land-based measurements. The outcomes will be further conceptual understanding of pollutant formation, improved regulatory model performance, and better optimized forecasting programs.

Performance improvement CME for quality: challenges inherent to the process.

PubMed

Vakani, Farhan Saeed; O'Beirne, Ronan

2015-01-01

The purpose of this paper is to discuss the perspective debates upon the real-time challenges for a three-staged Performance Improvement Continuing Medical Education (PI-CME) model, an innovative and potential approach for future CME, to inform providers to think, prepare and to act proactively. In this discussion, the challenges associated for adopting the American Medical Association's three-staged PI-CME model are reported. Not many institutions in USA are using a three-staged performance improvement model and then customizing it to their own healthcare context for the specific targeted audience. They integrate traditional CME methods with performance and quality initiatives, and linking with CME credits. Overall the US health system is interested in a structured PI-CME model with the potential to improve physicians practicing behaviors. Knowing the dearth of evidence for applying this structured performance improvement methodology into the design of CME activities, and the lack of clarity on challenges inherent to the process that learners and providers encounter. This paper establishes all-important first step to render the set of challenges for a three-staged PI-CME model.

Heterogeneous sharpness for cross-spectral face recognition

NASA Astrophysics Data System (ADS)

Cao, Zhicheng; Schmid, Natalia A.

2017-05-01

Matching images acquired in different electromagnetic bands remains a challenging problem. An example of this type of comparison is matching active or passive infrared (IR) against a gallery of visible face images, known as cross-spectral face recognition. Among many unsolved issues is the one of quality disparity of the heterogeneous images. Images acquired in different spectral bands are of unequal image quality due to distinct imaging mechanism, standoff distances, or imaging environment, etc. To reduce the effect of quality disparity on the recognition performance, one can manipulate images to either improve the quality of poor-quality images or to degrade the high-quality images to the level of the quality of their heterogeneous counterparts. To estimate the level of discrepancy in quality of two heterogeneous images a quality metric such as image sharpness is needed. It provides a guidance in how much quality improvement or degradation is appropriate. In this work we consider sharpness as a relative measure of heterogeneous image quality. We propose a generalized definition of sharpness by first achieving image quality parity and then finding and building a relationship between the image quality of two heterogeneous images. Therefore, the new sharpness metric is named heterogeneous sharpness. Image quality parity is achieved by experimentally finding the optimal cross-spectral face recognition performance where quality of the heterogeneous images is varied using a Gaussian smoothing function with different standard deviation. This relationship is established using two models; one of them involves a regression model and the other involves a neural network. To train, test and validate the model, we use composite operators developed in our lab to extract features from heterogeneous face images and use the sharpness metric to evaluate the face image quality within each band. Images from three different spectral bands visible light, near infrared, and short-wave infrared are considered in this work. Both error of a regression model and validation error of a neural network are analyzed.

Workplace Violence and Job Performance among Community Healthcare Workers in China: The Mediator Role of Quality of Life.

PubMed

Lin, Wei-Quan; Wu, Jiang; Yuan, Le-Xin; Zhang, Sheng-Chao; Jing, Meng-Juan; Zhang, Hui-Shan; Luo, Jia-Li; Lei, Yi-Xiong; Wang, Pei-Xi

2015-11-20

To explore the impact of workplace violence on job performance and quality of life of community healthcare workers in China, especially the relationship of these three variables. From December 2013 to April 2014, a total of 1404 healthcare workers were recruited by using the random cluster sampling method from Community Health Centers in Guangzhou and Shenzhen. The workplace violence scale, the job performance scale and the quality of life scale (SF-36) were self-administered. The structural equation model constructed by Amos 17.0 was employed to assess the relationship among these variables. Our study found that 51.64% of the respondents had an experience of workplace violence. It was found that both job performance and quality of life had a negative correlation with workplace violence. A positive association was identified between job performance and quality of life. The path analysis showed the total effect (β = -0.243) of workplace violence on job performance consisted of a direct effect (β = -0.113) and an indirect effect (β = -0.130), which was mediated by quality of life. Workplace violence among community healthcare workers is prevalent in China. The workplace violence had negative effects on the job performance and quality of life of CHCs' workers. The study suggests that improvement in the quality of life may lead to an effective reduction of the damages in job performance caused by workplace violence.

A simple method for low-contrast detectability, image quality and dose optimisation with CT iterative reconstruction algorithms and model observers.

PubMed

Bellesi, Luca; Wyttenbach, Rolf; Gaudino, Diego; Colleoni, Paolo; Pupillo, Francesco; Carrara, Mauro; Braghetti, Antonio; Puligheddu, Carla; Presilla, Stefano

2017-01-01

The aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment. Images of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four-alternative forced-choice test) and model observers were performed across the various images. Compared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result. IR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low-contrast detection tasks and in dose optimisation.

Predicting Recreational Water Quality Using Turbidity in the Cuyahoga River, Cuyahoga Valley National Park, Ohio, 2004-7

USGS Publications Warehouse

Brady, Amie M.G.; Bushon, Rebecca N.; Plona, Meg B.

2009-01-01

The Cuyahoga River within Cuyahoga Valley National Park (CVNP) in Ohio is often impaired for recreational use because of elevated concentrations of bacteria, which are indicators of fecal contamination. During the recreational seasons (May through August) of 2004 through 2007, samples were collected at two river sites, one upstream of and one centrally-located within CVNP. Bacterial concentrations and turbidity were determined, and streamflow at time of sampling and rainfall amounts over the previous 24 hours prior to sampling were ascertained. Statistical models to predict Escherichia coli (E. coli) concentrations were developed for each site (with data from 2004 through 2006) and tested during an independent year (2007). At Jaite, a sampling site near the center of CVNP, the predictive model performed better than the traditional method of determining the current day's water quality using the previous day's E. coli concentration. During 2007, the Jaite model, based on turbidity, produced more correct responses (81 percent) and fewer false negatives (3.2 percent) than the traditional method (68 and 26 percent, respectively). At Old Portage, a sampling site just upstream from CVNP, a predictive model with turbidity and rainfall as explanatory variables did not perform as well as the traditional method. The Jaite model was used to estimate water quality at three other sites in the park; although it did not perform as well as the traditional method, it performed well - yielding between 68 and 91 percent correct responses. Further research would be necessary to determine whether using the Jaite model to predict recreational water quality elsewhere on the river would provide accurate results.

The Royal Australian and New Zealand College of Radiologists (RANZCR) relative value unit workload model, its limitations and the evolution to a safety, quality and performance framework.

PubMed

Pitman, A; Jones, D N; Stuart, D; Lloydhope, K; Mallitt, K; O'Rourke, P

2009-10-01

The study reports on the evolution of the Australian radiologist relative value unit (RVU) model of measuring radiologist reporting workloads in teaching hospital departments, and aims to outline a way forward for the development of a broad national safety, quality and performance framework that enables value mapping, measurement and benchmarking. The Radiology International Benchmarking Project of Queensland Health provided a suitable high-level national forum where the existing Pitman-Jones RVU model was applied to contemporaneous data, and its shortcomings and potential avenues for future development were analysed. Application of the Pitman-Jones model to Queensland data and also a Victorian benchmark showed that the original recommendation of 40,000 crude RVU per full-time equivalent consultant radiologist (97-98 baseline level) has risen only moderately, to now lie around 45,000 crude RVU/full-time equivalent. Notwithstanding this, the model has a number of weaknesses and is becoming outdated, as it cannot capture newer time-consuming examinations particularly in CT. A significant re-evaluation of the value of medical imaging is required, and is now occurring. We must rethink how we measure, benchmark, display and continually improve medical imaging safety, quality and performance, throughout the imaging care cycle and beyond. It will be necessary to ensure alignment with patient needs, as well as clinical and organisational objectives. Clear recommendations for the development of an updated national reporting workload RVU system are available, and an opportunity now exists for developing a much broader national model. A more sophisticated and balanced multidimensional safety, quality and performance framework that enables measurement and benchmarking of all important elements of health-care service is needed.

Hospital financial condition and the quality of patient care.

PubMed

Bazzoli, Gloria J; Chen, Hsueh-Fen; Zhao, Mei; Lindrooth, Richard C

2008-08-01

Concerns about deficiencies in the quality of care delivered in US hospitals grew during a time period when an increasing number of hospitals were experiencing financial problems. Our study examines a six-year longitudinal database of general acute care hospitals in 11 states to assess the relationship between hospital financial condition and quality of care. We evaluate two measures of financial performance: operating margin and a broader profitability measure that encompasses both operating and non-operating sources of income. Our model specification allows for gradual adjustments in quality-enhancing activities and recognizes that current realizations of patient quality may affect future financial performance. Empirical results suggest that there is a relationship between financial performance and quality of care, but not as strong as suggested in earlier research. Overall, our results suggest that deep financial problems that go beyond the patient care side of business may be important to prompting quality problems. Copyright (c) 2007 John Wiley & Sons, Ltd.

Multilayer perceptron neural network-based approach for modeling phycocyanin pigment concentrations: case study from lower Charles River buoy, USA.

PubMed

Heddam, Salim

2016-09-01

This paper proposes multilayer perceptron neural network (MLPNN) to predict phycocyanin (PC) pigment using water quality variables as predictor. In the proposed model, four water quality variables that are water temperature, dissolved oxygen, pH, and specific conductance were selected as the inputs for the MLPNN model, and the PC as the output. To demonstrate the capability and the usefulness of the MLPNN model, a total of 15,849 data measured at 15-min (15 min) intervals of time are used for the development of the model. The data are collected at the lower Charles River buoy, and available from the US Environmental Protection Agency (USEPA). For comparison purposes, a multiple linear regression (MLR) model that was frequently used for predicting water quality variables in previous studies is also built. The performances of the models are evaluated using a set of widely used statistical indices. The performance of the MLPNN and MLR models is compared with the measured data. The obtained results show that (i) the all proposed MLPNN models are more accurate than the MLR models and (ii) the results obtained are very promising and encouraging for the development of phycocyanin-predictive models.

Model fitting for small skin permeability data sets: hyperparameter optimisation in Gaussian Process Regression.

PubMed

Ashrafi, Parivash; Sun, Yi; Davey, Neil; Adams, Roderick G; Wilkinson, Simon C; Moss, Gary Patrick

2018-03-01

The aim of this study was to investigate how to improve predictions from Gaussian Process models by optimising the model hyperparameters. Optimisation methods, including Grid Search, Conjugate Gradient, Random Search, Evolutionary Algorithm and Hyper-prior, were evaluated and applied to previously published data. Data sets were also altered in a structured manner to reduce their size, which retained the range, or 'chemical space' of the key descriptors to assess the effect of the data range on model quality. The Hyper-prior Smoothbox kernel results in the best models for the majority of data sets, and they exhibited significantly better performance than benchmark quantitative structure-permeability relationship (QSPR) models. When the data sets were systematically reduced in size, the different optimisation methods generally retained their statistical quality, whereas benchmark QSPR models performed poorly. The design of the data set, and possibly also the approach to validation of the model, is critical in the development of improved models. The size of the data set, if carefully controlled, was not generally a significant factor for these models and that models of excellent statistical quality could be produced from substantially smaller data sets. © 2018 Royal Pharmaceutical Society.

Construction of anthropomorphic hybrid, dual-lattice voxel models for optimizing image quality and dose in radiography

NASA Astrophysics Data System (ADS)

Petoussi-Henss, Nina; Becker, Janine; Greiter, Matthias; Schlattl, Helmut; Zankl, Maria; Hoeschen, Christoph

2014-03-01

In radiography there is generally a conflict between the best image quality and the lowest possible patient dose. A proven method of dosimetry is the simulation of radiation transport in virtual human models (i.e. phantoms). However, while the resolution of these voxel models is adequate for most dosimetric purposes, they cannot provide the required organ fine structures necessary for the assessment of the imaging quality. The aim of this work is to develop hybrid/dual-lattice voxel models (called also phantoms) as well as simulation methods by which patient dose and image quality for typical radiographic procedures can be determined. The results will provide a basis to investigate by means of simulations the relationships between patient dose and image quality for various imaging parameters and develop methods for their optimization. A hybrid model, based on NURBS (Non Linear Uniform Rational B-Spline) and PM (Polygon Mesh) surfaces, was constructed from an existing voxel model of a female patient. The organs of the hybrid model can be then scaled and deformed in a non-uniform way i.e. organ by organ; they can be, thus, adapted to patient characteristics without losing their anatomical realism. Furthermore, the left lobe of the lung was substituted by a high resolution lung voxel model, resulting in a dual-lattice geometry model. "Dual lattice" means in this context the combination of voxel models with different resolution. Monte Carlo simulations of radiographic imaging were performed with the code EGS4nrc, modified such as to perform dual lattice transport. Results are presented for a thorax examination.

The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network.

PubMed

Dėdelė, Audrius; Miškinytė, Auksė

2015-09-01

In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations.

Evaluation of bone quality in osteoporosis model mice by Raman spectroscopy

NASA Astrophysics Data System (ADS)

Ishimaru, Yasumitsu; Oshima, Yusuke; Imai, Yuuki; Iimura, Tadahiro; Takanezawa, Sota; Hino, Kazunori; Miura, Hiromasa

2017-04-01

To evaluate the bone quality in the osteoporosis, we generated sciatic nerve resection (NX) mice as an osteoporosis model and analyzed by Raman spectroscopy. Raman spectra were measured in anterior cortical surface of the proximal tibia at 5 points in each bone. After that, the samples were fixed with 70% ethanol. We then performed DXA and μCT measurement. Raman peak intensity ratios were significantly different between NX and Control. Those changes in the Raman peak intensity ratios may reflect loss of bone quality in the osteoporosis model. Raman spectroscopy is a promising technique for measuring the bone quality and bone strength.

Modeling the BOD of Danube River in Serbia using spatial, temporal, and input variables optimized artificial neural network models.

PubMed

Šiljić Tomić, Aleksandra N; Antanasijević, Davor Z; Ristić, Mirjana Đ; Perić-Grujić, Aleksandra A; Pocajt, Viktor V

2016-05-01

This paper describes the application of artificial neural network models for the prediction of biological oxygen demand (BOD) levels in the Danube River. Eighteen regularly monitored water quality parameters at 17 stations on the river stretch passing through Serbia were used as input variables. The optimization of the model was performed in three consecutive steps: firstly, the spatial influence of a monitoring station was examined; secondly, the monitoring period necessary to reach satisfactory performance was determined; and lastly, correlation analysis was applied to evaluate the relationship among water quality parameters. Root-mean-square error (RMSE) was used to evaluate model performance in the first two steps, whereas in the last step, multiple statistical indicators of performance were utilized. As a result, two optimized models were developed, a general regression neural network model (labeled GRNN-1) that covers the monitoring stations from the Danube inflow to the city of Novi Sad and a GRNN model (labeled GRNN-2) that covers the stations from the city of Novi Sad to the border with Romania. Both models demonstrated good agreement between the predicted and actually observed BOD values.

A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring

NASA Astrophysics Data System (ADS)

Zimmerman, Naomi; Presto, Albert A.; Kumar, Sriniwasa P. N.; Gu, Jason; Hauryliuk, Aliaksei; Robinson, Ellis S.; Robinson, Allen L.; Subramanian, R.

2018-01-01

Low-cost sensing strategies hold the promise of denser air quality monitoring networks, which could significantly improve our understanding of personal air pollution exposure. Additionally, low-cost air quality sensors could be deployed to areas where limited monitoring exists. However, low-cost sensors are frequently sensitive to environmental conditions and pollutant cross-sensitivities, which have historically been poorly addressed by laboratory calibrations, limiting their utility for monitoring. In this study, we investigated different calibration models for the Real-time Affordable Multi-Pollutant (RAMP) sensor package, which measures CO, NO2, O3, and CO2. We explored three methods: (1) laboratory univariate linear regression, (2) empirical multiple linear regression, and (3) machine-learning-based calibration models using random forests (RF). Calibration models were developed for 16-19 RAMP monitors (varied by pollutant) using training and testing windows spanning August 2016 through February 2017 in Pittsburgh, PA, US. The random forest models matched (CO) or significantly outperformed (NO2, CO2, O3) the other calibration models, and their accuracy and precision were robust over time for testing windows of up to 16 weeks. Following calibration, average mean absolute error on the testing data set from the random forest models was 38 ppb for CO (14 % relative error), 10 ppm for CO2 (2 % relative error), 3.5 ppb for NO2 (29 % relative error), and 3.4 ppb for O3 (15 % relative error), and Pearson r versus the reference monitors exceeded 0.8 for most units. Model performance is explored in detail, including a quantification of model variable importance, accuracy across different concentration ranges, and performance in a range of monitoring contexts including the National Ambient Air Quality Standards (NAAQS) and the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. A key strength of the RF approach is that it accounts for pollutant cross-sensitivities. This highlights the importance of developing multipollutant sensor packages (as opposed to single-pollutant monitors); we determined this is especially critical for NO2 and CO2. The evaluation reveals that only the RF-calibrated sensors meet the US EPA Air Sensors Guidebook recommendations of minimum data quality for personal exposure measurement. We also demonstrate that the RF-model-calibrated sensors could detect differences in NO2 concentrations between a near-road site and a suburban site less than 1.5 km away. From this study, we conclude that combining RF models with carefully controlled state-of-the-art multipollutant sensor packages as in the RAMP monitors appears to be a very promising approach to address the poor performance that has plagued low-cost air quality sensors.

Investigating the Effect of Damage Progression Model Choice on Prognostics Performance

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Narasimhan, Sriram; Saha, Sankalita; Saha, Bhaskar; Goebel, Kai

2011-01-01

The success of model-based approaches to systems health management depends largely on the quality of the underlying models. In model-based prognostics, it is especially the quality of the damage progression models, i.e., the models describing how damage evolves as the system operates, that determines the accuracy and precision of remaining useful life predictions. Several common forms of these models are generally assumed in the literature, but are often not supported by physical evidence or physics-based analysis. In this paper, using a centrifugal pump as a case study, we develop different damage progression models. In simulation, we investigate how model changes influence prognostics performance. Results demonstrate that, in some cases, simple damage progression models are sufficient. But, in general, the results show a clear need for damage progression models that are accurate over long time horizons under varied loading conditions.

Mental models of audit and feedback in primary care settings.

PubMed

Hysong, Sylvia J; Smitham, Kristen; SoRelle, Richard; Amspoker, Amber; Hughes, Ashley M; Haidet, Paul

2018-05-30

Audit and feedback has been shown to be instrumental in improving quality of care, particularly in outpatient settings. The mental model individuals and organizations hold regarding audit and feedback can moderate its effectiveness, yet this has received limited study in the quality improvement literature. In this study we sought to uncover patterns in mental models of current feedback practices within high- and low-performing healthcare facilities. We purposively sampled 16 geographically dispersed VA hospitals based on high and low performance on a set of chronic and preventive care measures. We interviewed up to 4 personnel from each location (n = 48) to determine the facility's receptivity to audit and feedback practices. Interview transcripts were analyzed via content and framework analysis to identify emergent themes. We found high variability in the mental models of audit and feedback, which we organized into positive and negative themes. We were unable to associate mental models of audit and feedback with clinical performance due to high variance in facility performance over time. Positive mental models exhibit perceived utility of audit and feedback practices in improving performance; whereas, negative mental models did not. Results speak to the variability of mental models of feedback, highlighting how facilities perceive current audit and feedback practices. Findings are consistent with prior research  in that variability in feedback mental models is associated with lower performance.; Future research should seek to empirically link mental models revealed in this paper to high and low levels of clinical performance.

Performance measurement for people with multiple chronic conditions: conceptual model.

PubMed

Giovannetti, Erin R; Dy, Sydney; Leff, Bruce; Weston, Christine; Adams, Karen; Valuck, Tom B; Pittman, Aisha T; Blaum, Caroline S; McCann, Barbara A; Boyd, Cynthia M

2013-10-01

Improving quality of care for people with multiple chronic conditions (MCCs) requires performance measures reflecting the heterogeneity and scope of their care. Since most existing measures are disease specific, performance measures must be refined and new measures must be developed to address the complexity of care for those with MCCs. To describe development of the Performance Measurement for People with Multiple Chronic Conditions (PM-MCC) conceptual model. Framework development and a national stakeholder panel. We used reviews of existing conceptual frameworks of performance measurement, review of the literature on MCCs, input from experts in the multistakeholder Steering Committee, and public comment. The resulting model centers on the patient and family goals and preferences for care in the context of multiple care sites and providers, the type of care they are receiving, and the national priority domains for healthcare quality measurement. This model organizes measures into a comprehensive framework and identifies areas where measures are lacking. In this context, performance measures can be prioritized and implemented at different levels, in the context of patients' overall healthcare needs.

LOAD-ENHANCED MOVEMENT QUALITY SCREENING AND TACTICAL ATHLETICISM: AN EXTENSION OF EVIDENCE

PubMed Central

Schmitz, Randy J.; Rhea, Christopher K.; Ross, Scott E.

2017-01-01

Background Military organizations use movement quality screening for prediction of injury risk and performance potential. Currently, evidence of an association between movement quality and performance is limited. Recent work has demonstrated that external loading strengthens the relationship between movement screens and performance outcomes. Such loading may therefore steer us toward robust implementations of movement quality screens while maintaining their appeal as cost effective, field-expedient tools. Purpose The purpose of the current study was to quantify the effect of external load-bearing on the relationship between clinically rated movement quality and tactical performance outcomes while addressing the noted limitations. Study Design Crossover Trial. Methods Fifty young adults (25 male, 25 female, 22.98 ± 3.09 years, 171.95 ± 11.46 cm, 71.77 ± 14.03 kg) completed the Functional Movement Screen™ with (FMS™W) and without (FMS™C) a weight vest in randomized order. Following FMS™ testing, criterion measures of tactical performance were administered, including agility T-Tests, sprints, a 400-meter run, the Mobility for Battle (MOB) course, and a simulated casualty rescue. For each performance outcome, regression models were selected via group lasso with smoothed FMS™ item scores as candidate predictor variables. Results For all outcomes, proportion of variance accounted for was greater in FMS™W (R2 = ;0.22 [T-Test], 0.29 [Sprint], 0.17 [400 meter], 0.29 [MOB], and 0.11 [casualty rescue]) than in FMS™C (R2 = ;0.00 [T-Test], 0.11 [Sprint], 0.00 [400 meter], 0.19 [MOB], and 0.00 [casualty rescue]). From the FMS™W condition, beneficial performance effects (p<0.05) were observed for Deep Squat (sprint, casualty rescue), Hurdle Step (T-Agility, 400 meter run), Inline Lunge (sprint, MOB), and Trunk Stability Push Up (all models). Similar effects for FMS™C item scores were limited to Trunk Stability Push Up (p<0.05, all models). Conclusions The present study extends evidence supporting the validity of load-enhanced movement quality screening as a predictor of tactical performance ability. Future designs should seek to identify mechanisms explaining this effect. Level of Evidence 3 PMID:28593095

LOAD-ENHANCED MOVEMENT QUALITY SCREENING AND TACTICAL ATHLETICISM: AN EXTENSION OF EVIDENCE.

PubMed

Glass, Stephen M; Schmitz, Randy J; Rhea, Christopher K; Ross, Scott E

2017-06-01

Military organizations use movement quality screening for prediction of injury risk and performance potential. Currently, evidence of an association between movement quality and performance is limited. Recent work has demonstrated that external loading strengthens the relationship between movement screens and performance outcomes. Such loading may therefore steer us toward robust implementations of movement quality screens while maintaining their appeal as cost effective, field-expedient tools. The purpose of the current study was to quantify the effect of external load-bearing on the relationship between clinically rated movement quality and tactical performance outcomes while addressing the noted limitations. Crossover Trial. Fifty young adults (25 male, 25 female, 22.98 ± 3.09 years, 171.95 ± 11.46 cm, 71.77 ± 14.03 kg) completed the Functional Movement Screen™ with (FMS™W) and without (FMS™C) a weight vest in randomized order. Following FMS™ testing, criterion measures of tactical performance were administered, including agility T-Tests, sprints, a 400-meter run, the Mobility for Battle (MOB) course, and a simulated casualty rescue. For each performance outcome, regression models were selected via group lasso with smoothed FMS™ item scores as candidate predictor variables. For all outcomes, proportion of variance accounted for was greater in FMS™W (R 2 = ;0.22 [T-Test], 0.29 [Sprint], 0.17 [400 meter], 0.29 [MOB], and 0.11 [casualty rescue]) than in FMS™C (R 2 = ;0.00 [T-Test], 0.11 [Sprint], 0.00 [400 meter], 0.19 [MOB], and 0.00 [casualty rescue]). From the FMS™W condition, beneficial performance effects (p<0.05) were observed for Deep Squat (sprint, casualty rescue), Hurdle Step (T-Agility, 400 meter run), Inline Lunge (sprint, MOB), and Trunk Stability Push Up (all models). Similar effects for FMS™C item scores were limited to Trunk Stability Push Up (p<0.05, all models). The present study extends evidence supporting the validity of load-enhanced movement quality screening as a predictor of tactical performance ability. Future designs should seek to identify mechanisms explaining this effect. 3.

Performance specifications and six sigma theory: Clinical chemistry and industry compared.

PubMed

Oosterhuis, W P; Severens, M J M J

2018-04-11

Analytical performance specifications are crucial in test development and quality control. Although consensus has been reached on the use of biological variation to derive these specifications, no consensus has been reached which model should be preferred. The Six Sigma concept is widely applied in industry for quality specifications of products and can well be compared with Six Sigma models in clinical chemistry. However, the models for measurement specifications differ considerably between both fields: where the sigma metric is used in clinical chemistry, in industry the Number of Distinct Categories is used instead. In this study the models in both fields are compared and discussed. Copyright © 2018. Published by Elsevier Inc.

How do leader-member exchange quality and differentiation affect performance in teams? An integrated multilevel dual process model.

PubMed

Li, Alex Ning; Liao, Hui

2014-09-01

Integrating leader-member exchange (LMX) research with role engagement theory (Kahn, 1990) and role system theory (Katz & Kahn, 1978), we propose a multilevel, dual process model to understand the mechanisms through which LMX quality at the individual level and LMX differentiation at the team level simultaneously affect individual and team performance. With regard to LMX differentiation, we introduce a new configural approach focusing on the pattern of LMX differentiation to complement the traditional approach focusing on the degree of LMX differentiation. Results based on multiphase, multisource data from 375 employees of 82 teams revealed that, at the individual level, LMX quality positively contributed to customer-rated employee performance through enhancing employee role engagement. At the team level, LMX differentiation exerted negative influence on teams' financial performance through disrupting team coordination. In particular, teams with the bimodal form of LMX configuration (i.e., teams that split into 2 LMX-based subgroups with comparable size) suffered most in team performance because they experienced greatest difficulty in coordinating members' activities. Furthermore, LMX differentiation strengthened the relationship between LMX quality and role engagement, and team coordination strengthened the relationship between role engagement and employee performance. Theoretical and practical implications of the findings are discussed. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Air pollution and climate response to aerosol direct radiative effects: A modeling study of decadal trends across the northern hemisphere

EPA Science Inventory

Decadal hemispheric Weather Research and Forecast-Community Multiscale Air Quality simulations from 1990 to 2010 were conducted to examine the meteorology and air quality responses to the aerosol direct radiative effects. The model's performance for the simulation of hourly surfa...

Risk adjustment in the American College of Surgeons National Surgical Quality Improvement Program: a comparison of logistic versus hierarchical modeling.

PubMed

Cohen, Mark E; Dimick, Justin B; Bilimoria, Karl Y; Ko, Clifford Y; Richards, Karen; Hall, Bruce Lee

2009-12-01

Although logistic regression has commonly been used to adjust for risk differences in patient and case mix to permit quality comparisons across hospitals, hierarchical modeling has been advocated as the preferred methodology, because it accounts for clustering of patients within hospitals. It is unclear whether hierarchical models would yield important differences in quality assessments compared with logistic models when applied to American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) data. Our objective was to evaluate differences in logistic versus hierarchical modeling for identifying hospitals with outlying outcomes in the ACS-NSQIP. Data from ACS-NSQIP patients who underwent colorectal operations in 2008 at hospitals that reported at least 100 operations were used to generate logistic and hierarchical prediction models for 30-day morbidity and mortality. Differences in risk-adjusted performance (ratio of observed-to-expected events) and outlier detections from the two models were compared. Logistic and hierarchical models identified the same 25 hospitals as morbidity outliers (14 low and 11 high outliers), but the hierarchical model identified 2 additional high outliers. Both models identified the same eight hospitals as mortality outliers (five low and three high outliers). The values of observed-to-expected events ratios and p values from the two models were highly correlated. Results were similar when data were permitted from hospitals providing < 100 patients. When applied to ACS-NSQIP data, logistic and hierarchical models provided nearly identical results with respect to identification of hospitals' observed-to-expected events ratio outliers. As hierarchical models are prone to implementation problems, logistic regression will remain an accurate and efficient method for performing risk adjustment of hospital quality comparisons.

Aircrew coordination and decisionmaking: Peer ratings of video tapes made during a full mission simulation

NASA Technical Reports Server (NTRS)

Murphy, M. R.; Awe, C. A.

1986-01-01

Six professionally active, retired captains rated the coordination and decisionmaking performances of sixteen aircrews while viewing videotapes of a simulated commercial air transport operation. The scenario featured a required diversion and a probable minimum fuel situation. Seven point Likert-type scales were used in rating variables on the basis of a model of crew coordination and decisionmaking. The variables were based on concepts of, for example, decision difficulty, efficiency, and outcome quality; and leader-subordin ate concepts such as person and task-oriented leader behavior, and competency motivation of subordinate crewmembers. Five-front-end variables of the model were in turn dependent variables for a hierarchical regression procedure. The variance in safety performance was explained 46%, by decision efficiency, command reversal, and decision quality. The variance of decision quality, an alternative substantive dependent variable to safety performance, was explained 60% by decision efficiency and the captain's quality of within-crew communications. The variance of decision efficiency, crew coordination, and command reversal were in turn explained 78%, 80%, and 60% by small numbers of preceding independent variables. A principle component, varimax factor analysis supported the model structure suggested by regression analyses.

Motivating medical information system performance by system quality, service quality, and job satisfaction for evidence-based practice.

PubMed

Chang, Ching-Sheng; Chen, Su-Yueh; Lan, Yi-Ting

2012-11-21

No previous studies have addressed the integrated relationships among system quality, service quality, job satisfaction, and system performance; this study attempts to bridge such a gap with evidence-based practice study. The convenience sampling method was applied to the information system users of three hospitals in southern Taiwan. A total of 500 copies of questionnaires were distributed, and 283 returned copies were valid, suggesting a valid response rate of 56.6%. SPSS 17.0 and AMOS 17.0 (structural equation modeling) statistical software packages were used for data analysis and processing. The findings are as follows: System quality has a positive influence on service quality (γ11= 0.55), job satisfaction (γ21= 0.32), and system performance (γ31= 0.47). Service quality (β31= 0.38) and job satisfaction (β32= 0.46) will positively influence system performance. It is thus recommended that the information office of hospitals and developers take enhancement of service quality and user satisfaction into consideration in addition to placing b on system quality and information quality when designing, developing, or purchasing an information system, in order to improve benefits and gain more achievements generated by hospital information systems.

Validity and feasibility of the american college of surgeons colectomy composite outcome quality measure.

PubMed

Merkow, Ryan P; Hall, Bruce L; Cohen, Mark E; Wang, Xue; Adams, John L; Chow, Warren B; Lawson, Elise H; Bilimoria, Karl Y; Richards, Karen; Ko, Clifford Y

2013-03-01

To develop a reliable, robust, parsimonious, risk-adjusted 30-day composite colectomy outcome measure. A fundamental aspect in the pursuit of high-quality care is the development of valid and reliable performance measures in surgery. Colon resection is associated with appreciable morbidity and mortality and therefore is an ideal quality improvement target. From 2010 American College of Surgeons National Surgical Quality Improvement Program data, patients were identified who underwent colon resection for any indication. A composite outcome of death or any serious morbidity within 30 days of the index operation was established. A 6-predictor, parsimonious model was developed and compared with a more complex model with more variables. National caseload requirements were calculated on the basis of increasing reliability thresholds. From 255 hospitals, 22,346 patients were accrued who underwent a colon resection in 2010, most commonly for neoplasm (46.7%). A mortality or serious morbidity event occurred in 4461 patients (20.0%). At the hospital level, the median composite event rate was 20.7% (interquartile range: 15.8%-26.3%). The parsimonious model performed similarly to the full model (Akaike information criterion: 19,411 vs 18,988), and hospital-level performance comparisons were highly correlated (R = 0.97). At a reliability threshold of 0.4, 56 annual colon resections would be required and achievable at an estimated 42% of US and 69% of American College of Surgeons National Surgical Quality Improvement Program hospitals. This 42% of US hospitals performed approximately 84% of all colon resections in the country in 2008. It is feasible to design a measure with a composite outcome of death or serious morbidity after colon surgery that has a low burden for data collection, has substantial clinical importance, and has acceptable reliability.

Polyenergetic known-component reconstruction without prior shape models

NASA Astrophysics Data System (ADS)

Zhang, C.; Zbijewski, W.; Zhang, X.; Xu, S.; Stayman, J. W.

2017-03-01

Purpose: Previous work has demonstrated that structural models of surgical tools and implants can be integrated into model-based CT reconstruction to greatly reduce metal artifacts and improve image quality. This work extends a polyenergetic formulation of known-component reconstruction (Poly-KCR) by removing the requirement that a physical model (e.g. CAD drawing) be known a priori, permitting much more widespread application. Methods: We adopt a single-threshold segmentation technique with the help of morphological structuring elements to build a shape model of metal components in a patient scan based on initial filtered-backprojection (FBP) reconstruction. This shape model is used as an input to Poly-KCR, a formulation of known-component reconstruction that does not require a prior knowledge of beam quality or component material composition. An investigation of performance as a function of segmentation thresholds is performed in simulation studies, and qualitative comparisons to Poly-KCR with an a priori shape model are made using physical CBCT data of an implanted cadaver and in patient data from a prototype extremities scanner. Results: We find that model-free Poly-KCR (MF-Poly-KCR) provides much better image quality compared to conventional reconstruction techniques (e.g. FBP). Moreover, the performance closely approximates that of Poly- KCR with an a prior shape model. In simulation studies, we find that imaging performance generally follows segmentation accuracy with slight under- or over-estimation based on the shape of the implant. In both simulation and physical data studies we find that the proposed approach can remove most of the blooming and streak artifacts around the component permitting visualization of the surrounding soft-tissues. Conclusion: This work shows that it is possible to perform known-component reconstruction without prior knowledge of the known component. In conjunction with the Poly-KCR technique that does not require knowledge of beam quality or material composition, very little needs to be known about the metal implant and system beforehand. These generalizations will allow more widespread application of KCR techniques in real patient studies where the information of surgical tools and implants is limited or not available.

Control of maglev vehicles with aerodynamic and guideway disturbances

NASA Technical Reports Server (NTRS)

Flueckiger, Karl; Mark, Steve; Caswell, Ruth; Mccallum, Duncan

1994-01-01

A modeling, analysis, and control design methodology is presented for maglev vehicle ride quality performance improvement as measured by the Pepler Index. Ride quality enhancement is considered through active control of secondary suspension elements and active aerodynamic surfaces mounted on the train. To analyze and quantify the benefits of active control, the authors have developed a five degree-of-freedom lumped parameter model suitable for describing a large class of maglev vehicles, including both channel and box-beam guideway configurations. Elements of this modeling capability have been recently employed in studies sponsored by the U.S. Department of Transportation (DOT). A perturbation analysis about an operating point, defined by vehicle and average crosswind velocities, yields a suitable linearized state space model for multivariable control system analysis and synthesis. Neglecting passenger compartment noise, the ride quality as quantified by the Pepler Index is readily computed from the system states. A statistical analysis is performed by modeling the crosswind disturbances and guideway variations as filtered white noise, whereby the Pepler Index is established in closed form through the solution to a matrix Lyapunov equation. Data is presented which indicates the anticipated ride quality achieved through various closed-loop control arrangements.

Measuring Provider Performance for Physicians Participating in the Merit-Based Incentive Payment System.

PubMed

Squitieri, Lee; Chung, Kevin C

2017-07-01

In 2017, the Centers for Medicare and Medicaid Services began requiring all eligible providers to participate in the Quality Payment Program or face financial reimbursement penalty. The Quality Payment Program outlines two paths for provider participation: the Merit-Based Incentive Payment System and Advanced Alternative Payment Models. For the first performance period beginning in January of 2017, the Centers for Medicare and Medicaid Services estimates that approximately 83 to 90 percent of eligible providers will not qualify for participation in an Advanced Alternative Payment Model and therefore must participate in the Merit-Based Incentive Payment System program. The Merit-Based Incentive Payment System path replaces existing quality-reporting programs and adds several new measures to evaluate providers using four categories of data: (1) quality, (2) cost/resource use, (3) improvement activities, and (4) advancing care information. These categories will be combined to calculate a weighted composite score for each provider or provider group. Composite Merit-Based Incentive Payment System scores based on 2017 performance data will be used to adjust reimbursed payment in 2019. In this article, the authors provide relevant background for understanding value-based provider performance measurement. The authors also discuss Merit-Based Incentive Payment System reporting requirements and scoring methodology to provide plastic surgeons with the necessary information to critically evaluate their own practice capabilities in the context of current performance metrics under the Quality Payment Program.

Software cost/resource modeling: Software quality tradeoff measurement

NASA Technical Reports Server (NTRS)

Lawler, R. W.

1980-01-01

A conceptual framework for treating software quality from a total system perspective is developed. Examples are given to show how system quality objectives may be allocated to hardware and software; to illustrate trades among quality factors, both hardware and software, to achieve system performance objectives; and to illustrate the impact of certain design choices on software functionality.

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

Development and testing of a fast conceptual river water quality model.

PubMed

Keupers, Ingrid; Willems, Patrick

2017-04-15

Modern, model based river quality management strongly relies on river water quality models to simulate the temporal and spatial evolution of pollutant concentrations in the water body. Such models are typically constructed by extending detailed hydrodynamic models with a component describing the advection-diffusion and water quality transformation processes in a detailed, physically based way. This approach is too computational time demanding, especially when simulating long time periods that are needed for statistical analysis of the results or when model sensitivity analysis, calibration and validation require a large number of model runs. To overcome this problem, a structure identification method to set up a conceptual river water quality model has been developed. Instead of calculating the water quality concentrations at each water level and discharge node, the river branch is divided into conceptual reservoirs based on user information such as location of interest and boundary inputs. These reservoirs are modelled as Plug Flow Reactor (PFR) and Continuously Stirred Tank Reactor (CSTR) to describe advection and diffusion processes. The same water quality transformation processes as in the detailed models are considered but with adjusted residence times based on the hydrodynamic simulation results and calibrated to the detailed water quality simulation results. The developed approach allows for a much faster calculation time (factor 10 5 ) without significant loss of accuracy, making it feasible to perform time demanding scenario runs. Copyright © 2017 Elsevier Ltd. All rights reserved.

High-Performance Integrated Control of water quality and quantity in urban water reservoirs

NASA Astrophysics Data System (ADS)

Galelli, S.; Castelletti, A.; Goedbloed, A.

2015-11-01

This paper contributes a novel High-Performance Integrated Control framework to support the real-time operation of urban water supply storages affected by water quality problems. We use a 3-D, high-fidelity simulation model to predict the main water quality dynamics and inform a real-time controller based on Model Predictive Control. The integration of the simulation model into the control scheme is performed by a model reduction process that identifies a low-order, dynamic emulator running 4 orders of magnitude faster. The model reduction, which relies on a semiautomatic procedural approach integrating time series clustering and variable selection algorithms, generates a compact and physically meaningful emulator that can be coupled with the controller. The framework is used to design the hourly operation of Marina Reservoir, a 3.2 Mm3 storm-water-fed reservoir located in the center of Singapore, operated for drinking water supply and flood control. Because of its recent formation from a former estuary, the reservoir suffers from high salinity levels, whose behavior is modeled with Delft3D-FLOW. Results show that our control framework reduces the minimum salinity levels by nearly 40% and cuts the average annual deficit of drinking water supply by about 2 times the active storage of the reservoir (about 4% of the total annual demand).

Biomagnetic monitoring as a validation tool for local air quality models: a case study for an urban street canyon.

PubMed

Hofman, Jelle; Samson, Roeland

2014-09-01

Biomagnetic monitoring of tree leaf deposited particles has proven to be a good indicator of the ambient particulate concentration. The objective of this study is to apply this method to validate a local-scale air quality model (ENVI-met), using 96 tree crown sampling locations in a typical urban street canyon. To the best of our knowledge, the application of biomagnetic monitoring for the validation of pollutant dispersion modeling is hereby presented for the first time. Quantitative ENVI-met validation showed significant correlations between modeled and measured results throughout the entire in-leaf period. ENVI-met performed much better at the first half of the street canyon close to the ring road (r=0.58-0.79, RMSE=44-49%), compared to second part (r=0.58-0.64, RMSE=74-102%). The spatial model behavior was evaluated by testing effects of height, azimuthal position, tree position and distance from the main pollution source on the obtained model results and magnetic measurements. Our results demonstrate that biomagnetic monitoring seems to be a valuable method to evaluate the performance of air quality models. Due to the high spatial and temporal resolution of this technique, biomagnetic monitoring can be applied anywhere in the city (where urban green is present) to evaluate model performance at different spatial scales. Copyright © 2014 Elsevier Ltd. All rights reserved.

Improved model quality assessment using ProQ2.

PubMed

Ray, Arjun; Lindahl, Erik; Wallner, Björn

2012-09-10

Employing methods to assess the quality of modeled protein structures is now standard practice in bioinformatics. In a broad sense, the techniques can be divided into methods relying on consensus prediction on the one hand, and single-model methods on the other. Consensus methods frequently perform very well when there is a clear consensus, but this is not always the case. In particular, they frequently fail in selecting the best possible model in the hard cases (lacking consensus) or in the easy cases where models are very similar. In contrast, single-model methods do not suffer from these drawbacks and could potentially be applied on any protein of interest to assess quality or as a scoring function for sampling-based refinement. Here, we present a new single-model method, ProQ2, based on ideas from its predecessor, ProQ. ProQ2 is a model quality assessment algorithm that uses support vector machines to predict local as well as global quality of protein models. Improved performance is obtained by combining previously used features with updated structural and predicted features. The most important contribution can be attributed to the use of profile weighting of the residue specific features and the use features averaged over the whole model even though the prediction is still local. ProQ2 is significantly better than its predecessors at detecting high quality models, improving the sum of Z-scores for the selected first-ranked models by 20% and 32% compared to the second-best single-model method in CASP8 and CASP9, respectively. The absolute quality assessment of the models at both local and global level is also improved. The Pearson's correlation between the correct and local predicted score is improved from 0.59 to 0.70 on CASP8 and from 0.62 to 0.68 on CASP9; for global score to the correct GDT_TS from 0.75 to 0.80 and from 0.77 to 0.80 again compared to the second-best single methods in CASP8 and CASP9, respectively. ProQ2 is available at http://proq2.wallnerlab.org.

Protocol for Reliability Assessment of Structural Health Monitoring Systems Incorporating Model-assisted Probability of Detection (MAPOD) Approach

DTIC Science & Technology

2011-09-01

a quality evaluation with limited data, a model -based assessment must be...that affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a ...affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a wide range

Towards A Complete Model Of Photopic Visual Threshold Performance

NASA Astrophysics Data System (ADS)

Overington, I.

1982-02-01

Based on a wide variety of fragmentary evidence taken from psycho-physics, neurophysiology and electron microscopy, it has been possible to put together a very widely applicable conceptual model of photopic visual threshold performance. Such a model is so complex that a single comprehensive mathematical version is excessively cumbersome. It is, however, possible to set up a suite of related mathematical models, each of limited application but strictly known envelope of usage. Such models may be used for assessment of a variety of facets of visual performance when using display imagery, including effects and interactions of image quality, random and discrete display noise, viewing distance, image motion, etc., both for foveal interrogation tasks and for visual search tasks. The specific model may be selected from the suite according to the assessment task in hand. The paper discusses in some depth the major facets of preperceptual visual processing and their interaction with instrumental image quality and noise. It then highlights the statistical nature of visual performance before going on to consider a number of specific mathematical models of partial visual function. Where appropriate, these are compared with widely popular empirical models of visual function.

Indoor Air Quality and Energy Efficiency

EPA Pesticide Factsheets

EPA completed an extensive modeling study to assess the compatibilities and trade-offs between energy, indoor air quality, and thermal comfort objectives for HVAC systems and to formulate strategies for superior performance across all areas.

The Pennsylvania Trauma Outcomes Study Risk-Adjusted Mortality Model: Results of a Statewide Benchmarking Program

PubMed Central

WIEBE, DOUGLAS J.; HOLENA, DANIEL N.; DELGADO, M. KIT; McWILLIAMS, NATHAN; ALTENBURG, JULIET; CARR, BRENDAN G.

2018-01-01

Trauma centers need objective feedback on performance to inform quality improvement efforts. The Trauma Quality Improvement Program recently published recommended methodology for case mix adjustment and benchmarking performance. We tested the feasibility of applying this methodology to develop risk-adjusted mortality models for a statewide trauma system. We performed a retrospective cohort study of patients ≥16 years old at Pennsylvania trauma centers from 2011 to 2013 (n = 100,278). Our main outcome measure was observed-to-expected mortality ratios (overall and within blunt, penetrating, multisystem, isolated head, and geriatric subgroups). Patient demographic variables, physiology, mechanism of injury, transfer status, injury severity, and pre-existing conditions were included as predictor variables. The statistical model had excellent discrimination (area under the curve = 0.94). Funnel plots of observed-to-expected identified five centers with lower than expected mortality and two centers with higher than expected mortality. No centers were outliers for management of penetrating trauma, but five centers had lower and three had higher than expected mortality for blunt trauma. It is feasible to use Trauma Quality Improvement Program methodology to develop risk-adjusted models for statewide trauma systems. Even with smaller numbers of trauma centers that are available in national datasets, it is possible to identify high and low outliers in performance. PMID:28541852

The Pennsylvania Trauma Outcomes Study Risk-Adjusted Mortality Model: Results of a Statewide Benchmarking Program.

PubMed

Wiebe, Douglas J; Holena, Daniel N; Delgado, M Kit; McWilliams, Nathan; Altenburg, Juliet; Carr, Brendan G

2017-05-01

Trauma centers need objective feedback on performance to inform quality improvement efforts. The Trauma Quality Improvement Program recently published recommended methodology for case mix adjustment and benchmarking performance. We tested the feasibility of applying this methodology to develop risk-adjusted mortality models for a statewide trauma system. We performed a retrospective cohort study of patients ≥16 years old at Pennsylvania trauma centers from 2011 to 2013 (n = 100,278). Our main outcome measure was observed-to-expected mortality ratios (overall and within blunt, penetrating, multisystem, isolated head, and geriatric subgroups). Patient demographic variables, physiology, mechanism of injury, transfer status, injury severity, and pre-existing conditions were included as predictor variables. The statistical model had excellent discrimination (area under the curve = 0.94). Funnel plots of observed-to-expected identified five centers with lower than expected mortality and two centers with higher than expected mortality. No centers were outliers for management of penetrating trauma, but five centers had lower and three had higher than expected mortality for blunt trauma. It is feasible to use Trauma Quality Improvement Program methodology to develop risk-adjusted models for statewide trauma systems. Even with smaller numbers of trauma centers that are available in national datasets, it is possible to identify high and low outliers in performance.

The Role of Reliability, Vulnerability and Resilience in the Management of Water Quality Systems

NASA Astrophysics Data System (ADS)

Lence, B. J.; Maier, H. R.

2001-05-01

The risk based performance indicators reliability, vulnerability and resilience provide measures of the frequency, magnitude and duration of the failure of water resources systems, respectively. They have been applied primarily to water supply problems, including the assessment of the performance of reservoirs and water distribution systems. Applications to water quality case studies have been limited, although the need to consider the length and magnitude of violations of a particular water quality standard has been recognized for some time. In this research, the role of reliability, vulnerability and resilience in water quality management applications is investigated by examining their significance as performance measures for water quality systems and assessing their potential for assisting in decision making processes. The importance of each performance indicator is discussed and a framework for classifying such systems, based on the relative significance of each of these indicators, is introduced and illustrated qualitatively with various case studies. Quantitative examples drawn from both lake and river water quality modeling exercises are then provided.

Validating a model that predicts daily growth and feed quality of New Zealand dairy pastures.

PubMed

Woodward, S J

2001-09-01

The Pasture Quality (PQ) model is a simple, mechanistic, dynamical system model that was designed to capture the essential biological processes in grazed grass-clover pasture, and to be optimised to derive improved grazing strategies for New Zealand dairy farms. While the individual processes represented in the model (photosynthesis, tissue growth, flowering, leaf death, decomposition, worms) were based on experimental data, this did not guarantee that the assembled model would accurately predict the behaviour of the system as a whole (i.e., pasture growth and quality). Validation of the whole model was thus a priority, since any strategy derived from the model could impact a farm business in the order of thousands of dollars per annum if adopted. This paper describes the process of defining performance criteria for the model, obtaining suitable data to test the model, and carrying out the validation analysis. The validation process highlighted a number of weaknesses in the model, which will lead to the model being improved. As a result, the model's utility will be enhanced. Furthermore, validation was found to have an unexpected additional benefit, in that despite the model's poor initial performance, support was generated for the model among field scientists involved in the wider project.

Measuring, managing and maximizing refinery performance

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

Bascur, O.A.; Kennedy, J.P.

1996-01-01

Implementing continuous quality improvement is a confluence of total quality management, people empowerment, performance indicators and information engineering. Supporting information technologies allow a refiner to narrow the gap between management objectives and the process control level. Dynamic performance monitoring benefits come from production cost savings, improved communications and enhanced decision making. A refinery workgroup information flow model helps automate continuous improvement of processes, performance and the organization. The paper discusses the rethinking of refinery operations, dynamic performance monitoring, continuous process improvement, the knowledge coordinator and repository manager, an integrated plant operations workflow, and successful implementation.

Calibration of material models for estimating impact of construction quality on life cycle performance of pavements.

DOT National Transportation Integrated Search

2006-02-01

Constructing a pavement that will perform well throughout its expected design life is the main goal of any highway agency. The relationship between construction parameters and pavement life, defined by structural models, can be described using materi...

Development of a method for comprehensive water quality forecasting and its application in Miyun reservoir of Beijing, China.

PubMed

Zhang, Lei; Zou, Zhihong; Shan, Wei

2017-06-01

Water quality forecasting is an essential part of water resource management. Spatiotemporal variations of water quality and their inherent constraints make it very complex. This study explored a data-based method for short-term water quality forecasting. Prediction of water quality indicators including dissolved oxygen, chemical oxygen demand by KMnO 4 and ammonia nitrogen using support vector machine was taken as inputs of the particle swarm algorithm based optimal wavelet neural network to forecast the whole status index of water quality. Gubeikou monitoring section of Miyun reservoir in Beijing, China was taken as the study case to examine effectiveness of this approach. The experiment results also revealed that the proposed model has advantages of stability and time reduction in comparison with other data-driven models including traditional BP neural network model, wavelet neural network model and Gradient Boosting Decision Tree model. It can be used as an effective approach to perform short-term comprehensive water quality prediction. Copyright © 2016. Published by Elsevier B.V.

Quality Practices: An Open Distance Learning Perspective

ERIC Educational Resources Information Center

Ramdass, Kemlall; Nemavhola, Fulufhelo

2018-01-01

Global transformation in higher education over the past two decades has led to the implementation of national policies in order to measure the performance of institutions in South Africa. The Higher Education Quality Council (HEQC) adopted the quality assurance (QA) model for the purposes of accountability and governance in South African Higher…

[Economic Evaluation of Integrated Care Systems - Scientific Standard Specifications, Challenges, Best Practice Model].

PubMed

Pimperl, A; Schreyögg, J; Rothgang, H; Busse, R; Glaeske, G; Hildebrandt, H

2015-12-01

 Transparency of economic performance of integrated care systems (IV) is a basic requirement for the acceptance and further development of integrated care. Diverse evaluation methods are used but are seldom openly discussed because of the proprietary nature of the different business models. The aim of this article is to develop a generic model for measuring economic performance of IV interventions.  A catalogue of five quality criteria is used to discuss different evaluation methods -(uncontrolled before-after-studies, control group-based approaches, regression models). On this -basis a best practice model is proposed.  A regression model based on the German morbidity-based risk structure equalisation scheme (MorbiRSA) has some benefits in comparison to the other methods mentioned. In particular it requires less resources to be implemented and offers advantages concerning the relia-bility and the transparency of the method (=important for acceptance). Also validity is sound. Although RCTs and - also to a lesser -extent - complex difference-in-difference matching approaches can lead to a higher validity of the results, their feasibility in real life settings is limited due to economic and practical reasons. That is why central criticisms of a MorbiRSA-based model were addressed, adaptions proposed and incorporated in a best practice model: Population-oriented morbidity adjusted margin improvement model (P-DBV(MRSA)).  The P-DBV(MRSA) approach may be used as a standardised best practice model for the economic evaluation of IV. Parallel to the proposed approach for measuring economic performance a balanced, quality-oriented performance measurement system should be introduced. This should prevent incentivising IV-players to undertake short-term cost cutting at the expense of quality. © Georg Thieme Verlag KG Stuttgart · New York.

“Impact of CB6 and CB05TU chemical mechanisms on air quality”

EPA Science Inventory

“Impacts of CB6 and CB05TU chemical mechanisms on air quality”In this study, we incorporate the newly developed Carbon Bond chemical mechanism (CB6) into the Community Multiscale Air Quality modeling system (CMAQv5.0.1) and perform air quality model simulations with the CB6 and t...

Who Really Answers the Questions? Using Glasser's Quality School Model in an Undergraduate Classroom

ERIC Educational Resources Information Center

Logan, Jennifer; Plumlee, Gerald L.

2012-01-01

The authors discuss the effectiveness of the Quality School model and active learning in an undergraduate classroom setting. They compare performance levels of students in two course sections of Principles of Macroeconomics and two sections of Managerial Communications. Students are given an opportunity to help shape the structure of the…

77 FR 21690 - Approval and Promulgation of Air Quality Implementation Plan for 1997 8-Hour Ozone Standard; Arizona

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-11

... and emissions input data preparation, model performance evaluation, interpreting modeling results, and... standard based on ambient ozone monitoring data for the 2006- 2008 period. EPA has not yet acted on this... ppm) and years thereafter were at or below the standard. See EPA Air Quality System (AQS) data...

Performance of stochastic approaches for forecasting river water quality.

PubMed

Ahmad, S; Khan, I H; Parida, B P

2001-12-01

This study analysed water quality data collected from the river Ganges in India from 1981 to 1990 for forecasting using stochastic models. Initially the box and whisker plots and Kendall's tau test were used to identify the trends during the study period. For detecting the possible intervention in the data the time series plots and cusum charts were used. The three approaches of stochastic modelling which account for the effect of seasonality in different ways. i.e. multiplicative autoregressive integrated moving average (ARIMA) model. deseasonalised model and Thomas-Fiering model were used to model the observed pattern in water quality. The multiplicative ARIMA model having both nonseasonal and seasonal components were, in general, identified as appropriate models. In the deseasonalised modelling approach, the lower order ARIMA models were found appropriate for the stochastic component. The set of Thomas-Fiering models were formed for each month for all water quality parameters. These models were then used to forecast the future values. The error estimates of forecasts from the three approaches were compared to identify the most suitable approach for the reliable forecast. The deseasonalised modelling approach was recommended for forecasting of water quality parameters of a river.

Ergodicity and model quality in template-restrained canonical and temperature/Hamiltonian replica exchange coarse-grained molecular dynamics simulations of proteins.

PubMed

Karczyńska, Agnieszka S; Czaplewski, Cezary; Krupa, Paweł; Mozolewska, Magdalena A; Joo, Keehyoung; Lee, Jooyoung; Liwo, Adam

2017-12-05

Molecular simulations restrained to single or multiple templates are commonly used in protein-structure modeling. However, the restraints introduce additional barriers, thus impairing the ergodicity of simulations, which can affect the quality of the resulting models. In this work, the effect of restraint types and simulation schemes on ergodicity and model quality was investigated by performing template-restrained canonical molecular dynamics (MD), multiplexed replica-exchange molecular dynamics, and Hamiltonian replica exchange molecular dynamics (HREMD) simulations with the coarse-grained UNRES force field on nine selected proteins, with pseudo-harmonic log-Gaussian (unbounded) or Lorentzian (bounded) restraint functions. The best ergodicity was exhibited by HREMD. It has been found that non-ergodicity does not affect model quality if good templates are used to generate restraints. However, when poor-quality restraints not covering the entire protein are used, the improved ergodicity of HREMD can lead to significantly improved protein models. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A case study of a team-based, quality-focused compensation model for primary care providers.

PubMed

Greene, Jessica; Hibbard, Judith H; Overton, Valerie

2014-06-01

In 2011, Fairview Health Services began replacing their fee-for-service compensation model for primary care providers (PCPs), which included an annual pay-for-performance bonus, with a team-based model designed to improve quality of care, patient experience, and (eventually) cost containment. In-depth interviews and an online survey of PCPs early after implementation of the new model suggest that it quickly changed the way many PCPs practiced. Most PCPs reported a shift in orientation toward quality of care, working more collaboratively with their colleagues and focusing on their full panel of patients. The majority reported that their quality of care had improved because of the model and that their colleagues' quality had to. The comprehensive change did, however, result in lower fee-for-service billing and reductions in PCP satisfaction. While Fairview's compensation model is still a work in progress, their early experiences can provide lessons for other delivery systems seeking to reform PCP compensation.

Optimal quality control of bakers' yeast fed-batch culture using population dynamics.

PubMed

Dairaku, K; Izumoto, E; Morikawa, H; Shioya, S; Takamatsu, T

1982-12-01

An optimal quality control policy for the overall specific growth rate of bakers' yeast, which maximizes the fermentative activity in the making of bread, was obtained by direct searching based on the mathematical model proposed previously. The mathematical model had described the age distribution of bakers' yeast which had an essential relationship to the ability of fermentation in the making of bread. The mathematical model is a simple aging model with two periods: Nonbudding and budding. Based on the result obtained by direct searching, the quality control of bakers' yeast fed-batch culture was performed and confirmed to be experimentally valid.

Flow Quality Measurements in an Aerodynamic Model of NASA Lewis' Icing Research Tunnel

NASA Technical Reports Server (NTRS)

Canacci, Victor A.; Gonsalez, Jose C.

1999-01-01

As part of an ongoing effort to improve the aerodynamic flow characteristics of the Icing Research Tunnel (IRT), a modular scale model of the facility was fabricated. This 1/10th-scale model was used to gain further understanding of the flow characteristics in the IRT. The model was outfitted with instrumentation and data acquisition systems to determine pressures, velocities, and flow angles in the settling chamber and test section. Parametric flow quality studies involving the insertion and removal of a model of the IRT's distinctive heat exchanger (cooler) and/or of a honeycomb in the settling chamber were performed. These experiments illustrate the resulting improvement or degradation in flow quality.

A pilot modeling technique for handling-qualities research

NASA Technical Reports Server (NTRS)

Hess, R. A.

1980-01-01

A brief survey of the more dominant analysis techniques used in closed-loop handling-qualities research is presented. These techniques are shown to rely on so-called classical and modern analytical models of the human pilot which have their foundation in the analysis and design principles of feedback control. The optimal control model of the human pilot is discussed in some detail and a novel approach to the a priori selection of pertinent model parameters is discussed. Frequency domain and tracking performance data from 10 pilot-in-the-loop simulation experiments involving 3 different tasks are used to demonstrate the parameter selection technique. Finally, the utility of this modeling approach in handling-qualities research is discussed.

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.

Workplace Violence and Job Performance among Community Healthcare Workers in China: The Mediator Role of Quality of Life

PubMed Central

Lin, Wei-Quan; Wu, Jiang; Yuan, Le-Xin; Zhang, Sheng-Chao; Jing, Meng-Juan; Zhang, Hui-Shan; Luo, Jia-Li; Lei, Yi-Xiong; Wang, Pei-Xi

2015-01-01

Objective: To explore the impact of workplace violence on job performance and quality of life of community healthcare workers in China, especially the relationship of these three variables. Methods: From December 2013 to April 2014, a total of 1404 healthcare workers were recruited by using the random cluster sampling method from Community Health Centers in Guangzhou and Shenzhen. The workplace violence scale, the job performance scale and the quality of life scale (SF-36) were self-administered. The structural equation model constructed by Amos 17.0 was employed to assess the relationship among these variables. Results: Our study found that 51.64% of the respondents had an experience of workplace violence. It was found that both job performance and quality of life had a negative correlation with workplace violence. A positive association was identified between job performance and quality of life. The path analysis showed the total effect (β = −0.243) of workplace violence on job performance consisted of a direct effect (β = −0.113) and an indirect effect (β = −0.130), which was mediated by quality of life. Conclusions: Workplace violence among community healthcare workers is prevalent in China. The workplace violence had negative effects on the job performance and quality of life of CHCs’ workers. The study suggests that improvement in the quality of life may lead to an effective reduction of the damages in job performance caused by workplace violence. PMID:26610538

Improvements on NYMTC Data Products

DOT National Transportation Integrated Search

2009-11-11

Just like any other scientific research field, the value of data quality is undisputed in the field of transportation. From policy planning to performance evaluation, from model development to impact studies, good quality data is essential to generat...

Predicting non-stationary algal dynamics following changes in hydrometeorological conditions using data assimilation techniques

NASA Astrophysics Data System (ADS)

Kim, S.; Seo, D. J.

2017-12-01

When water temperature (TW) increases due to changes in hydrometeorological conditions, the overall ecological conditions change in the aquatic system. The changes can be harmful to human health and potentially fatal to fish habitat. Therefore, it is important to assess the impacts of thermal disturbances on in-stream processes of water quality variables and be able to predict effectiveness of possible actions that may be taken for water quality protection. For skillful prediction of in-stream water quality processes, it is necessary for the watershed water quality models to be able to reflect such changes. Most of the currently available models, however, assume static parameters for the biophysiochemical processes and hence are not able to capture nonstationaries seen in water quality observations. In this work, we assess the performance of the Hydrological Simulation Program-Fortran (HSPF) in predicting algal dynamics following TW increase. The study area is located in the Republic of Korea where waterway change due to weir construction and drought concurrently occurred around 2012. In this work we use data assimilation (DA) techniques to update model parameters as well as the initial condition of selected state variables for in-stream processes relevant to algal growth. For assessment of model performance and characterization of temporal variability, various goodness-of-fit measures and wavelet analysis are used.

Achieving performance breakthroughs in an HMO business process through quality planning.

PubMed

Hanan, K B

1993-01-01

Kaiser Permanente's Georgia Region commissioned a quality planning team to design a new process to improve payments to its suppliers and vendors. The result of the team's effort was a 73 percent reduction in cycle time. This team's experiences point to the advantages of process redesign as a quality planning model, as well as some general guidelines for its most effective use in teams. If quality planning project teams are carefully configured, sufficiently expert in the existing process, and properly supported by management, organizations can achieve potentially dramatic improvements in process performance using this approach.

Modified-BRISQUE as no reference image quality assessment for structural MR images.

PubMed

Chow, Li Sze; Rajagopal, Heshalini

2017-11-01

An effective and practical Image Quality Assessment (IQA) model is needed to assess the image quality produced from any new hardware or software in MRI. A highly competitive No Reference - IQA (NR - IQA) model called Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) initially designed for natural images were modified to evaluate structural MR images. The BRISQUE model measures the image quality by using the locally normalized luminance coefficients, which were used to calculate the image features. The modified-BRISQUE model trained a new regression model using MR image features and Difference Mean Opinion Score (DMOS) from 775 MR images. Two types of benchmarks: objective and subjective assessments were used as performance evaluators for both original and modified-BRISQUE models. There was a high correlation between the modified-BRISQUE with both benchmarks, and they were higher than those for the original BRISQUE. There was a significant percentage improvement in their correlation values. The modified-BRISQUE was statistically better than the original BRISQUE. The modified-BRISQUE model can accurately measure the image quality of MR images. It is a practical NR-IQA model for MR images without using reference images. Copyright © 2017 Elsevier Inc. All rights reserved.

An effectiveness analysis of healthcare systems using a systems theoretic approach.

PubMed

Chuang, Sheuwen; Inder, Kerry

2009-10-24

The use of accreditation and quality measurement and reporting to improve healthcare quality and patient safety has been widespread across many countries. A review of the literature reveals no association between the accreditation system and the quality measurement and reporting systems, even when hospital compliance with these systems is satisfactory. Improvement of health care outcomes needs to be based on an appreciation of the whole system that contributes to those outcomes. The research literature currently lacks an appropriate analysis and is fragmented among activities. This paper aims to propose an integrated research model of these two systems and to demonstrate the usefulness of the resulting model for strategic research planning. To achieve these aims, a systematic integration of the healthcare accreditation and quality measurement/reporting systems is structured hierarchically. A holistic systems relationship model of the administration segment is developed to act as an investigation framework. A literature-based empirical study is used to validate the proposed relationships derived from the model. Australian experiences are used as evidence for the system effectiveness analysis and design base for an adaptive-control study proposal to show the usefulness of the system model for guiding strategic research. Three basic relationships were revealed and validated from the research literature. The systemic weaknesses of the accreditation system and quality measurement/reporting system from a system flow perspective were examined. The approach provides a system thinking structure to assist the design of quality improvement strategies. The proposed model discovers a fourth implicit relationship, a feedback between quality performance reporting components and choice of accreditation components that is likely to play an important role in health care outcomes. An example involving accreditation surveyors is developed that provides a systematic search for improving the impact of accreditation on quality of care and hence on the accreditation/performance correlation. There is clear value in developing a theoretical systems approach to achieving quality in health care. The introduction of the systematic surveyor-based search for improvements creates an adaptive-control system to optimize health care quality. It is hoped that these outcomes will stimulate further research in the development of strategic planning using systems theoretic approach for the improvement of quality in health care.

Value-Based Payment Reform and the Medicare Access and Children's Health Insurance Program Reauthorization Act of 2015: A Primer for Plastic Surgeons.

PubMed

Squitieri, Lee; Chung, Kevin C

2017-07-01

In 2015, the U.S. Congress passed the Medicare Access and Children's Health Insurance Program Reauthorization Act, which effectively repealed the Centers for Medicare and Medicaid Services sustainable growth rate formula and established the Centers for Medicare and Medicaid Services Quality Payment Program. The Medicare Access and Children's Health Insurance Program Reauthorization Act represents an unparalleled acceleration toward value-based payment models and a departure from traditional volume-driven fee-for-service reimbursement. The Quality Payment Program includes two paths for provider participation: the Merit-Based Incentive Payment System and Advanced Alternative Payment Models. The Merit-Based Incentive Payment System pathway replaces existing quality reporting programs and adds several new measures to create a composite performance score for each provider (or provider group) that will be used to adjust reimbursed payment. The advanced alternative payment model pathway is available to providers who participate in qualifying Advanced Alternative Payment Models and is associated with an initial 5 percent payment incentive. The first performance period for the Merit-Based Incentive Payment System opens January 1, 2017, and closes on December 31, 2017, and is associated with payment adjustments in January of 2019. The Centers for Medicare and Medicaid Services estimates that the majority of providers will begin participation in 2017 through the Merit-Based Incentive Payment System pathway, but aims to have 50 percent of payments tied to quality or value through Advanced Alternative Payment Models by 2018. In this article, the authors describe key components of the Medicare Access and Children's Health Insurance Program Reauthorization Act to providers navigating through the Quality Payment Program and discuss how plastic surgeons may optimize their performance in this new value-based payment program.

Laying the foundation for successful team performance trajectories: The roles of team charters and performance strategies.

PubMed

Mathieu, John E; Rapp, Tammy L

2009-01-01

This study examined the influences of team charters and performance strategies on the performance trajectories of 32 teams of master's of business administration students competing in a business strategy simulation over time. The authors extended existing theory on team development by demonstrating that devoting time to laying a foundation for both teamwork (i.e., team charters) and taskwork (performance strategies) can pay dividends in terms of more effective team performance over time. Using random coefficients growth modeling techniques, they found that teams with high-quality performance strategies outperformed teams with poorer quality strategies. However, a significant interaction between quality of the charters of teams and their performance strategies was found, such that the highest sustained performances were exhibited by teams that were high on both features. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Modeling study of biomass burning plumes and their impact on urban air quality; a case study of Santiago de Chile

NASA Astrophysics Data System (ADS)

Cuchiara, G. C.; Rappenglück, B.; Rubio, M. A.; Lissi, E.; Gramsch, E.; Garreaud, R. D.

2017-10-01

On January 4, 2014, during the summer period in South America, an intense forest and dry pasture wildfire occurred nearby the city of Santiago de Chile. On that day the biomass-burning plume was transported by low-intensity winds towards the metropolitan area of Santiago and impacted the concentration of pollutants in this region. In this study, the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) is implemented to investigate the biomass-burning plume associated with these wildfires nearby Santiago, which impacted the ground-level ozone concentration and exacerbated Santiago's air quality. Meteorological variables simulated by WRF/Chem are compared against surface and radiosonde observations, and the results show that the model reproduces fairly well the observed wind speed, wind direction air temperature and relative humidity for the case studied. Based on an analysis of the transport of an inert tracer released over the locations, and at the time the wildfires were captured by the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS), the model reproduced reasonably well the transport of biomass burning plume towards the city of Santiago de Chile within a time delay of two hours as observed in ceilometer data. A six day air quality simulation was performed: the first three days were used to validate the anthropogenic and biogenic emissions, and the last three days (during and after the wildfire event) to analyze the performance of WRF/Chem plume-rise model within FINNv1 fire emission estimations. The model presented a satisfactory performance on the first days of the simulation when contrasted against data from the well-established air quality network over the city of Santiago de Chile. These days represent the urban air quality base case for Santiago de Chile unimpacted by fire emissions. However, for the last three simulation days, which were impacted by the fire emissions, the statistical indices showed a decrease in the model performance. While the model showed a satisfactory evidence that wildfires plumes that originated in the vicinity of Santiago de Chile were transported towards the urban area and impacted the air quality, the model still underpredicted some pollutants substantially, likely due to misrepresentation of fire emission sources during those days. Potential uncertainties may include to the land use/land cover classifications and its characteristics, such as type and density of vegetation assigned to the region, where the fire spots are detected. The variability of the ecosystem type during the fire event might also play a role.

Support vector machine-an alternative to artificial neuron network for water quality forecasting in an agricultural nonpoint source polluted river?

PubMed

Liu, Mei; Lu, Jun

2014-09-01

Water quality forecasting in agricultural drainage river basins is difficult because of the complicated nonpoint source (NPS) pollution transport processes and river self-purification processes involved in highly nonlinear problems. Artificial neural network (ANN) and support vector model (SVM) were developed to predict total nitrogen (TN) and total phosphorus (TP) concentrations for any location of the river polluted by agricultural NPS pollution in eastern China. River flow, water temperature, flow travel time, rainfall, dissolved oxygen, and upstream TN or TP concentrations were selected as initial inputs of the two models. Monthly, bimonthly, and trimonthly datasets were selected to train the two models, respectively, and the same monthly dataset which had not been used for training was chosen to test the models in order to compare their generalization performance. Trial and error analysis and genetic algorisms (GA) were employed to optimize the parameters of ANN and SVM models, respectively. The results indicated that the proposed SVM models performed better generalization ability due to avoiding the occurrence of overtraining and optimizing fewer parameters based on structural risk minimization (SRM) principle. Furthermore, both TN and TP SVM models trained by trimonthly datasets achieved greater forecasting accuracy than corresponding ANN models. Thus, SVM models will be a powerful alternative method because it is an efficient and economic tool to accurately predict water quality with low risk. The sensitivity analyses of two models indicated that decreasing upstream input concentrations during the dry season and NPS emission along the reach during average or flood season should be an effective way to improve Changle River water quality. If the necessary water quality and hydrology data and even trimonthly data are available, the SVM methodology developed here can easily be applied to other NPS-polluted rivers.

30 CFR 285.659 - What requirements must I include in my SAP, COP, or GAP regarding air quality?

Code of Federal Regulations, 2010 CFR

2010-07-01

..., or GAP regarding air quality? 285.659 Section 285.659 Mineral Resources MINERALS MANAGEMENT SERVICE... must I include in my SAP, COP, or GAP regarding air quality? (a) You must comply with the Clean Air Act...) For air quality modeling that you perform in support of the activities proposed in your plan, you...

Working under a clinic-level quality incentive: primary care clinicians' perceptions.

PubMed

Greene, Jessica; Kurtzman, Ellen T; Hibbard, Judith H; Overton, Valerie

2015-01-01

A key consideration in designing pay-for-performance programs is determining what entity the incentive should be awarded to-individual clinicians or to groups of clinicians working in teams. Some argue that team-level incentives, in which clinicians who are part of a team receive the same incentive based on the team's performance, are most effective; others argue for the efficacy of clinician-level incentives. This study examines primary care clinicians' perceptions of a team-based quality incentive awarded at the clinic level. This research was conducted with Fairview Health Services, where 40% of the primary care compensation model was based on clinic-level quality performance. We conducted 48 in-depth interviews to explore clinicians' perceptions of the clinic-level incentive, as well as an online survey of 150 clinicians (response rate 56%) to investigate which entity the clinicians would consider optimal to target for quality incentives. Clinicians reported the strengths of the clinic-based quality incentive were quality improvement for the team and less patient "dumping," or shifting patients with poor outcomes to other clinicians. The weaknesses were clinicians' lack of control and colleagues riding the coattails of higher performers. There were mixed reports on the model's impact on team dynamics. Although clinicians reported greater interaction with colleagues, some described an increase in tension. Most clinicians surveyed (73%) believed that there should be a mix of clinic and individual-level incentives to maintain collaboration and recognize individual performance. The study highlights the important advantages and disadvantages of using incentives based upon clinic-level performance. Future research should test whether hybrid incentives that mix group and individual incentives can maintain some of the best elements of each design while mitigating the negative impacts. © 2015 Annals of Family Medicine, Inc.

The Independent Associations of Physical Activity and Sleep with Cognitive Function in Older Adults.

PubMed

Falck, Ryan S; Best, John R; Davis, Jennifer C; Liu-Ambrose, Teresa

2018-01-01

Current evidence suggests physical activity (PA) and sleep are important for cognitive health; however, few studies examining the role of PA and sleep for cognitive health have measured these behaviors objectively. We cross-sectionally examined whether 1) higher PA is associated with better cognitive performance independently of sleep quality; 2) higher sleep quality is associated with better cognitive performance independently of PA; and 3) whether higher PA is associated with better sleep quality. We measured PA, subjective sleep quality using the Pittsburgh Sleep Quality Index (PSQI), and objective sleep quality (i.e., fragmentation, efficiency, duration, and latency) using the MotionWatch8© in community-dwelling adults (N = 137; aged 55+). Cognitive function was indexed using the Alzheimer's Disease Assessment Scale-Plus. Correlation analyses were performed to determine relationships between PA, sleep quality, and cognitive function. We then used latent variable modelling to examine the relationships of PA with cognitive function independently of sleep quality, sleep quality with cognitive function independently of PA, and PA with sleep quality. We found greater PA was associated with better cognitive performance independently of 1) PSQI (β= -0.03; p < 0.01); 2) sleep fragmentation (β= -0.02; p < 0.01); 3) sleep duration (β= -0.02; p < 0.01); and 4) sleep latency (β= -0.02; p < 0.01). In addition, better sleep efficiency was associated with better cognitive performance independently of PA (β= -0.01; p = 0.04). We did not find any associations between PA and sleep quality. PA is associated with better cognitive performance independently of sleep quality, and sleep efficiency is associated with better cognitive performance independently of PA. However, PA is not associated with sleep quality and thus PA and sleep quality may be related to cognitive performance through independent mechanisms.

Protein single-model quality assessment by feature-based probability density functions.

PubMed

Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

The Kubler-Ross model, physician distress, and performance reporting.

PubMed

Smaldone, Marc C; Uzzo, Robert G

2013-07-01

Physician performance reporting has been proposed as an essential component of health-care reform, with the aim of improving quality by providing transparency and accountability. Despite strong evidence demonstrating regional variation in practice patterns and lack of evidence-based care, public outcomes reporting has been met with resistance from medical professionals. Application of the Kubler-Ross 'five stages of grief' model--a conceptual framework consisting of a series of emotional stages (denial, anger, bargaining, depression, and acceptance) inspired by work with terminally ill patients--could provide some insight into why physicians are reluctant to accept emerging quality-reporting mechanisms. Physician-led quality-improvement initiatives are vital to contemporary health-care reform efforts and applications in urology, as well as other medical disciplines, are currently being explored.

A business case for quality improvement in addiction treatment: evidence from the NIATx collaborative.

PubMed

Quanbeck, Andrew R; Madden, Lynn; Edmundson, Eldon; Ford, James H; McConnell, K John; McCarty, Dennis; Gustafson, David H

2012-01-01

The Network for the Improvement of Addiction Treatment (NIATx) promotes treatment access and retention through a customer-focused quality improvement model. This paper explores the issue of the "business case" for quality improvement in addiction treatment from the provider's perspective. The business case model developed in this paper is based on case examples of early NIATx participants coupled with a review of the literature. Process inefficiencies indicated by long waiting times, high no-show rates, and low continuation rates cause underutilization of capacity and prevent optimal financial performance. By adopting customer-focused practices aimed at removing barriers to treatment access and retention, providers may be able to improve financial performance, increase staff retention, and gain long-term strategic advantage.

Evaluating Organic Aerosol Model Performance: Impact of two Embedded Assumptions

NASA Astrophysics Data System (ADS)

Jiang, W.; Giroux, E.; Roth, H.; Yin, D.

2004-05-01

Organic aerosols are important due to their abundance in the polluted lower atmosphere and their impact on human health and vegetation. However, modeling organic aerosols is a very challenging task because of the complexity of aerosol composition, structure, and formation processes. Assumptions and their associated uncertainties in both models and measurement data make model performance evaluation a truly demanding job. Although some assumptions are obvious, others are hidden and embedded, and can significantly impact modeling results, possibly even changing conclusions about model performance. This paper focuses on analyzing the impact of two embedded assumptions on evaluation of organic aerosol model performance. One assumption is about the enthalpy of vaporization widely used in various secondary organic aerosol (SOA) algorithms. The other is about the conversion factor used to obtain ambient organic aerosol concentrations from measured organic carbon. These two assumptions reflect uncertainties in the model and in the ambient measurement data, respectively. For illustration purposes, various choices of the assumed values are implemented in the evaluation process for an air quality model based on CMAQ (the Community Multiscale Air Quality Model). Model simulations are conducted for the Lower Fraser Valley covering Southwest British Columbia, Canada, and Northwest Washington, United States, for a historical pollution episode in 1993. To understand the impact of the assumed enthalpy of vaporization on modeling results, its impact on instantaneous organic aerosol yields (IAY) through partitioning coefficients is analysed first. The analysis shows that utilizing different enthalpy of vaporization values causes changes in the shapes of IAY curves and in the response of SOA formation capability of reactive organic gases to temperature variations. These changes are then carried into the air quality model and cause substantial changes in the organic aerosol modeling results. In another aspect, using different assumed factors to convert measured organic carbon to organic aerosol concentrations cause substantial variations in the processed ambient data themselves, which are normally used as performance targets for model evaluations. The combination of uncertainties in the modeling results and in the moving performance targets causes major uncertainties in the final conclusion about the model performance. Without further information, the best thing that a modeler can do is to choose a combination of the assumed values from the sensible parameter ranges available in the literature, based on the best match of the modeling results with the processed measurement data. However, the best match of the modeling results with the processed measurement data may not necessarily guarantee that the model itself is rigorous and the model performance is robust. Conclusions on the model performance can only be reached with sufficient understanding of the uncertainties and their impact.

Appraising Teacher Performance: A Quantitative Approach.

ERIC Educational Resources Information Center

Wingate, James G.; Bowers, Fred

Following a brief research review regarding the relationship between teacher behavior and student outcomes, a model is proposed for identifying those teaching behaviors that are significantly related to high-quality student performance. The model's stages include: (1) delineation of questions; (2) establishment of a framework; (3) selection of an…

Analysis of psychological factors for quality assessment of interactive multimodal service

NASA Astrophysics Data System (ADS)

Yamagishi, Kazuhisa; Hayashi, Takanori

2005-03-01

We proposed a subjective quality assessment model for interactive multimodal services. First, psychological factors of an audiovisual communication service were extracted by using the semantic differential (SD) technique and factor analysis. Forty subjects participated in subjective tests and performed point-to-point conversational tasks on a PC-based TV phone that exhibits various network qualities. The subjects assessed those qualities on the basis of 25 pairs of adjectives. Two psychological factors, i.e., an aesthetic feeling and a feeling of activity, were extracted from the results. Then, quality impairment factors affecting these two psychological factors were analyzed. We found that the aesthetic feeling is mainly affected by IP packet loss and video coding bit rate, and the feeling of activity depends on delay time and video frame rate. We then proposed an opinion model derived from the relationships among quality impairment factors, psychological factors, and overall quality. The results indicated that the estimation error of the proposed model is almost equivalent to the statistical reliability of the subjective score. Finally, using the proposed model, we discuss guidelines for quality design of interactive audiovisual communication services.

Performance Evaluation of Resource Management in Cloud Computing Environments.

PubMed

Batista, Bruno Guazzelli; Estrella, Julio Cezar; Ferreira, Carlos Henrique Gomes; Filho, Dionisio Machado Leite; Nakamura, Luis Hideo Vasconcelos; Reiff-Marganiec, Stephan; Santana, Marcos José; Santana, Regina Helena Carlucci

2015-01-01

Cloud computing is a computational model in which resource providers can offer on-demand services to clients in a transparent way. However, to be able to guarantee quality of service without limiting the number of accepted requests, providers must be able to dynamically manage the available resources so that they can be optimized. This dynamic resource management is not a trivial task, since it involves meeting several challenges related to workload modeling, virtualization, performance modeling, deployment and monitoring of applications on virtualized resources. This paper carries out a performance evaluation of a module for resource management in a cloud environment that includes handling available resources during execution time and ensuring the quality of service defined in the service level agreement. An analysis was conducted of different resource configurations to define which dimension of resource scaling has a real influence on client requests. The results were used to model and implement a simulated cloud system, in which the allocated resource can be changed on-the-fly, with a corresponding change in price. In this way, the proposed module seeks to satisfy both the client by ensuring quality of service, and the provider by ensuring the best use of resources at a fair price.

Performance Evaluation of Resource Management in Cloud Computing Environments

PubMed Central

Batista, Bruno Guazzelli; Estrella, Julio Cezar; Ferreira, Carlos Henrique Gomes; Filho, Dionisio Machado Leite; Nakamura, Luis Hideo Vasconcelos; Reiff-Marganiec, Stephan; Santana, Marcos José; Santana, Regina Helena Carlucci

2015-01-01

Cloud computing is a computational model in which resource providers can offer on-demand services to clients in a transparent way. However, to be able to guarantee quality of service without limiting the number of accepted requests, providers must be able to dynamically manage the available resources so that they can be optimized. This dynamic resource management is not a trivial task, since it involves meeting several challenges related to workload modeling, virtualization, performance modeling, deployment and monitoring of applications on virtualized resources. This paper carries out a performance evaluation of a module for resource management in a cloud environment that includes handling available resources during execution time and ensuring the quality of service defined in the service level agreement. An analysis was conducted of different resource configurations to define which dimension of resource scaling has a real influence on client requests. The results were used to model and implement a simulated cloud system, in which the allocated resource can be changed on-the-fly, with a corresponding change in price. In this way, the proposed module seeks to satisfy both the client by ensuring quality of service, and the provider by ensuring the best use of resources at a fair price. PMID:26555730

An enhanced PM 2.5 air quality forecast model based on nonlinear regression and back-trajectory concentrations

NASA Astrophysics Data System (ADS)

Cobourn, W. Geoffrey

2010-08-01

An enhanced PM 2.5 air quality forecast model based on nonlinear regression (NLR) and back-trajectory concentrations has been developed for use in the Louisville, Kentucky metropolitan area. The PM 2.5 air quality forecast model is designed for use in the warm season, from May through September, when PM 2.5 air quality is more likely to be critical for human health. The enhanced PM 2.5 model consists of a basic NLR model, developed for use with an automated air quality forecast system, and an additional parameter based on upwind PM 2.5 concentration, called PM24. The PM24 parameter is designed to be determined manually, by synthesizing backward air trajectory and regional air quality information to compute 24-h back-trajectory concentrations. The PM24 parameter may be used by air quality forecasters to adjust the forecast provided by the automated forecast system. In this study of the 2007 and 2008 forecast seasons, the enhanced model performed well using forecasted meteorological data and PM24 as input. The enhanced PM 2.5 model was compared with three alternative models, including the basic NLR model, the basic NLR model with a persistence parameter added, and the NLR model with persistence and PM24. The two models that included PM24 were of comparable accuracy. The two models incorporating back-trajectory concentrations had lower mean absolute errors and higher rates of detecting unhealthy PM2.5 concentrations compared to the other models.

[Integrated Quality Management System (IQMS): a model for improving the quality of reproductive health care in rural Kenya].

PubMed

Herrler, Claudia; Bramesfeld, Anke; Brodowski, Marc; Prytherch, Helen; Marx, Irmgard; Nafula, Maureen; Richter-Aairijoki, Heide; Musyoka, Lucy; Marx, Michael; Szecsenyi, Joachim

2015-01-01

To develop a model aiming to improve the quality of services for reproductive health care in rural Kenya and designed to measure the quality of reproductive health services in such a way that allows these services to identify measures for improving their performance. The Integrated Quality Management System (IQMS) was developed on the basis of a pre-existing and validated model for quality promotion, namely the European Practice Assessment (EPA). The methodology for quality assessment and feedback of assessment results to the service teams was adopted from the EPA model. Quality assessment methodology included data assessment through staff, patient surveys and service visitation. Quality is assessed by indicators, and so indicators had to be developed that were appropriate for assessing reproductive health care in rural Kenya. A search of the Kenyan and international literature was conducted to identify potential indicators. These were then rated for their relevance and clarity by a panel of Kenyan experts. 260 indicators were rated as relevant and assigned to 29 quality dimensions and 5 domains. The implementation of IQMS in ten facilities showed that IQMS is a feasible model for assessing the quality of reproductive health services in rural Kenya. IQMS enables these services to identify quality improvement targets and necessary improvement measures. Both strengths and limitations of IQMS will be discussed. Copyright © 2015. Published by Elsevier GmbH.

Monitoring Air Quality over China: Evaluation of the modeling system of the PANDA project

NASA Astrophysics Data System (ADS)

Bouarar, Idir; Katinka Petersen, Anna; Brasseur, Guy; Granier, Claire; Xie, Ying; Wang, Xuemei; Fan, Qi; Wang, Lili

2015-04-01

Air pollution has become a pressing problem in Asia and specifically in China due to rapid increase in anthropogenic emissions related to growth of China's economic activity and increasing demand for energy in the past decade. Observed levels of particulate matter and ozone regularly exceed World Health Organization (WHO) air quality guidelines in many parts of the country leading to increased risk of respiratory illnesses and other health problems. The EU-funded project PANDA aims to establish a team of European and Chinese scientists to monitor air pollution over China and elaborate air quality indicators in support of European and Chinese policies. PANDA combines state-of-the-art air pollution modeling with space and surface observations of chemical species to improve methods for monitoring air quality. The modeling system of the PANDA project follows a downscaling approach: global models such as MOZART and MACC system provide initial and boundary conditions to regional WRF-Chem and EMEP simulations over East Asia. WRF-Chem simulations at higher resolution (e.g. 20km) are then performed over a smaller domain covering East China and initial and boundary conditions from this run are used to perform simulations at a finer resolution (e.g. 5km) over specific megacities like Shanghai. Here we present results of model simulations for January and July 2010 performed during the first year of the project. We show an intercomparison of the global (MACC, EMEP) and regional (WRF-Chem) simulations and a comprehensive evaluation with satellite measurements (NO2, CO) and in-situ data (O3, CO, NOx, PM10 and PM2.5) at several surface stations. Using the WRF-Chem model, we demonstrate that model performance is influenced not only by the resolution (e.g. 60km, 20km) but also the emission inventories used (MACCity, HTAPv2), their resolution and diurnal variation, and the choice of initial and boundary conditions (e.g. MOZART, MACC analysis).

Understanding and development of manufacturable screen-printed contacts on high sheet-resistance emitters for low-cost silicon solar cells

NASA Astrophysics Data System (ADS)

Hilali, Mohamed M.

2005-11-01

A simple cost-effective approach was proposed and successfully employed to fabricate high-quality screen-printed (SP) contacts to high sheet-resistance emitters (100 O/sq) to improve the Si solar cell efficiency. Device modeling was used to quantify the performance enhancement possible from the high sheet-resistance emitter for various cell designs. It was found that for performance enhancement from the high sheet-resistance emitter, certain cell design criteria must be satisfied. Model calculations showed that in order to achieve any performance enhancement over the conventional ˜40 O/sq emitter, the high sheet resistance emitter solar cell must have a reasonably good (<120,000 cm/s) or low front-surface recombination velocity (FSRV). Model calculations were also performed to establish requirements for high fill factors (FFs). The results showed that the series resistance should be less than 0.8 O-cm2, the shunt resistance should be greater than 1000 O-cm2, and the junction leakage current should be less than 25 nA/cm2. Analytical microscopy and surface analysis techniques were used to study the Ag-Si contact interface of different SP Ag pastes. Physical and electrical properties of SP Ag thick-film contacts were studied and correlated to understand and achieve good-quality ohmic contacts to high sheet-resistance emitters for solar cells. This information was then used to define the criteria for high-quality screen-printed contacts. The role of paste constituents and firing scheme on contact quality were investigated to tailor the high-quality screen-printed contact interface structure that results in high performance solar cells. Results indicated that small particle size, high glass transition temperature, rapid firing and less aggressive glass frit help in producing high-quality contacts. Based on these results high-quality SP contacts with high FFs > 0.78 on high sheet-resistance emitters were achieved for the first time using a simple single-step firing process. This technology was applied to different substrates (monocrystalline and multicrystalline) and surfaces (textured and planar). Cell efficiencies of ˜16.2% on low-cost EFG ribbon substrates were achieved on high sheet-resistance emitters with SP contacts. A record high-efficiency SP solar cell of 19% with textured high sheet-resistance emitter was also fabricated and modeled.

Rapid performance modeling and parameter regression of geodynamic models

NASA Astrophysics Data System (ADS)

Brown, J.; Duplyakin, D.

2016-12-01

Geodynamic models run in a parallel environment have many parameters with complicated effects on performance and scientifically-relevant functionals. Manually choosing an efficient machine configuration and mapping out the parameter space requires a great deal of expert knowledge and time-consuming experiments. We propose an active learning technique based on Gaussion Process Regression to automatically select experiments to map out the performance landscape with respect to scientific and machine parameters. The resulting performance model is then used to select optimal experiments for improving the accuracy of a reduced order model per unit of computational cost. We present the framework and evaluate its quality and capability using popular lithospheric dynamics models.

Motivating medical information system performance by system quality, service quality, and job satisfaction for evidence-based practice

PubMed Central

2012-01-01

Background No previous studies have addressed the integrated relationships among system quality, service quality, job satisfaction, and system performance; this study attempts to bridge such a gap with evidence-based practice study. Methods The convenience sampling method was applied to the information system users of three hospitals in southern Taiwan. A total of 500 copies of questionnaires were distributed, and 283 returned copies were valid, suggesting a valid response rate of 56.6%. SPSS 17.0 and AMOS 17.0 (structural equation modeling) statistical software packages were used for data analysis and processing. Results The findings are as follows: System quality has a positive influence on service quality (γ11= 0.55), job satisfaction (γ21= 0.32), and system performance (γ31= 0.47). Service quality (β31= 0.38) and job satisfaction (β32= 0.46) will positively influence system performance. Conclusions It is thus recommended that the information office of hospitals and developers take enhancement of service quality and user satisfaction into consideration in addition to placing b on system quality and information quality when designing, developing, or purchasing an information system, in order to improve benefits and gain more achievements generated by hospital information systems. PMID:23171394

THE ATMOSPHERIC MODEL EVALUATION TOOL

EPA Science Inventory

This poster describes a model evaluation tool that is currently being developed and applied for meteorological and air quality model evaluation. The poster outlines the framework and provides examples of statistical evaluations that can be performed with the model evaluation tool...

A variation reduction allocation model for quality improvement to minimize investment and quality costs by considering suppliers’ learning curve

NASA Astrophysics Data System (ADS)

Rosyidi, C. N.; Jauhari, WA; Suhardi, B.; Hamada, K.

2016-02-01

Quality improvement must be performed in a company to maintain its product competitiveness in the market. The goal of such improvement is to increase the customer satisfaction and the profitability of the company. In current practice, a company needs several suppliers to provide the components in assembly process of a final product. Hence quality improvement of the final product must involve the suppliers. In this paper, an optimization model to allocate the variance reduction is developed. Variation reduction is an important term in quality improvement for both manufacturer and suppliers. To improve suppliers’ components quality, the manufacturer must invest an amount of their financial resources in learning process of the suppliers. The objective function of the model is to minimize the total cost consists of investment cost, and quality costs for both internal and external quality costs. The Learning curve will determine how the employee of the suppliers will respond to the learning processes in reducing the variance of the component.

Can Quality Improvement System Improve Childcare Site Performance in School Readiness?

ERIC Educational Resources Information Center

Ma, Xin; Shen, Jianping; Lu, Xuejin; Brandi, Karen; Goodman, Jeff; Watson, Grace

2013-01-01

The authors evaluated the effectiveness of the Quality Improvement System (QIS) developed and implemented by Children's Services Council of Palm Beach County (Florida) as a voluntary initiative to improve the quality of childcare and education. They adopted a growth model approach to investigate whether childcare sites that participated in QIS…

WRF/CMAQ AQMEII3 Simulations of U.S. Regional-Scale Ozone: Sensitivity to Processes and Inputs

EPA Science Inventory

Chemical boundary conditions are a key input to regional-scale photochemical models. In this study, performed during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), we perform annual simulations over North America with chemical boundary con...

Risk-adjusted hospital outcomes for children's surgery.

PubMed

Saito, Jacqueline M; Chen, Li Ern; Hall, Bruce L; Kraemer, Kari; Barnhart, Douglas C; Byrd, Claudia; Cohen, Mark E; Fei, Chunyuan; Heiss, Kurt F; Huffman, Kristopher; Ko, Clifford Y; Latus, Melissa; Meara, John G; Oldham, Keith T; Raval, Mehul V; Richards, Karen E; Shah, Rahul K; Sutton, Laura C; Vinocur, Charles D; Moss, R Lawrence

2013-09-01

BACKGROUND The American College of Surgeons National Surgical Quality Improvement Program-Pediatric was initiated in 2008 to drive quality improvement in children's surgery. Low mortality and morbidity in previous analyses limited differentiation of hospital performance. Participating institutions included children's units within general hospitals and free-standing children's hospitals. Cases selected by Current Procedural Terminology codes encompassed procedures within pediatric general, otolaryngologic, orthopedic, urologic, plastic, neurologic, thoracic, and gynecologic surgery. Trained personnel abstracted demographic, surgical profile, preoperative, intraoperative, and postoperative variables. Incorporating procedure-specific risk, hierarchical models for 30-day mortality and morbidities were developed with significant predictors identified by stepwise logistic regression. Reliability was estimated to assess the balance of information versus error within models. In 2011, 46 281 patients from 43 hospitals were accrued; 1467 codes were aggregated into 226 groupings. Overall mortality was 0.3%, composite morbidity 5.8%, and surgical site infection (SSI) 1.8%. Hierarchical models revealed outlier hospitals with above or below expected performance for composite morbidity in the entire cohort, pediatric abdominal subgroup, and spine subgroup; SSI in the entire cohort and pediatric abdominal subgroup; and urinary tract infection in the entire cohort. Based on reliability estimates, mortality discriminates performance poorly due to very low event rate; however, reliable model construction for composite morbidity and SSI that differentiate institutions is feasible. The National Surgical Quality Improvement Program-Pediatric expansion has yielded risk-adjusted models to differentiate hospital performance in composite and specific morbidities. However, mortality has low utility as a children's surgery performance indicator. Programmatic improvements have resulted in actionable data.

Vegetation Exposure to Ozone over the Continental United States: Assessment of Exposure Indices by the Eta-CMAQ Air Quality Forecast Model

EPA Science Inventory

This study presents the first evaluation of the performance of the Eta-CMAQ air quality forecast model to predict a variety of widely used seasonal mean and cumulative O₃ exposure indices associated with vegetation using the U.S. AIRNow O₃ observations.

Effect of attenuation correction on image quality in emission tomography

NASA Astrophysics Data System (ADS)

Denisova, N. V.; Ondar, M. M.

2017-10-01

In this paper, mathematical modeling and computer simulations of myocardial perfusion SPECT imaging are performed. The main factors affecting the quality of reconstructed images in SPECT are anatomical structures, the diastolic volume of a myocardium and attenuation of gamma rays. The purpose of the present work is to study the effect of attenuation correction on image quality in emission tomography. The basic 2D model describing a Tc-99m distribution in a transaxial slice of the thoracic part of a patient body was designed. This model was used to construct four phantoms simulated various anatomical shapes: 2 male and 2 female patients with normal, obese and subtle physique were included in the study. Data acquisition model which includes the effect of non-uniform attenuation, collimator-detector response and Poisson statistics was developed. The projection data were calculated for 60 views in accordance with the standard myocardial perfusion SPECT imaging protocol. Reconstructions of images were performed using the OSEM algorithm which is widely used in modern SPECT systems. Two types of patient's examination procedures were simulated: SPECT without attenuation correction and SPECT/CT with attenuation correction. The obtained results indicate a significant effect of the attenuation correction on the SPECT images quality.

Intelligent sensing sensory quality of Chinese rice wine using near infrared spectroscopy and nonlinear tools

NASA Astrophysics Data System (ADS)

Ouyang, Qin; Chen, Quansheng; Zhao, Jiewen

2016-02-01

The approach presented herein reports the application of near infrared (NIR) spectroscopy, in contrast with human sensory panel, as a tool for estimating Chinese rice wine quality; concretely, to achieve the prediction of the overall sensory scores assigned by the trained sensory panel. Back propagation artificial neural network (BPANN) combined with adaptive boosting (AdaBoost) algorithm, namely BP-AdaBoost, as a novel nonlinear algorithm, was proposed in modeling. First, the optimal spectra intervals were selected by synergy interval partial least square (Si-PLS). Then, BP-AdaBoost model based on the optimal spectra intervals was established, called Si-BP-AdaBoost model. These models were optimized by cross validation, and the performance of each final model was evaluated according to correlation coefficient (Rp) and root mean square error of prediction (RMSEP) in prediction set. Si-BP-AdaBoost showed excellent performance in comparison with other models. The best Si-BP-AdaBoost model was achieved with Rp = 0.9180 and RMSEP = 2.23 in the prediction set. It was concluded that NIR spectroscopy combined with Si-BP-AdaBoost was an appropriate method for the prediction of the sensory quality in Chinese rice wine.

Evaluating Air-Quality Models: Review and Outlook.

NASA Astrophysics Data System (ADS)

Weil, J. C.; Sykes, R. I.; Venkatram, A.

1992-10-01

Over the past decade, much attention has been devoted to the evaluation of air-quality models with emphasis on model performance in predicting the high concentrations that are important in air-quality regulations. This paper stems from our belief that this practice needs to be expanded to 1) evaluate model physics and 2) deal with the large natural or stochastic variability in concentration. The variability is represented by the root-mean- square fluctuating concentration (c about the mean concentration (C) over an ensemble-a given set of meteorological, source, etc. conditions. Most air-quality models used in applications predict C, whereas observations are individual realizations drawn from an ensemble. For cC large residuals exist between predicted and observed concentrations, which confuse model evaluations.This paper addresses ways of evaluating model physics in light of the large c the focus is on elevated point-source models. Evaluation of model physics requires the separation of the mean model error-the difference between the predicted and observed C-from the natural variability. A residual analysis is shown to be an elective way of doing this. Several examples demonstrate the usefulness of residuals as well as correlation analyses and laboratory data in judging model physics.In general, c models and predictions of the probability distribution of the fluctuating concentration (c), (c, are in the developmental stage, with laboratory data playing an important role. Laboratory data from point-source plumes in a convection tank show that (c approximates a self-similar distribution along the plume center plane, a useful result in a residual analysis. At pmsent,there is one model-ARAP-that predicts C, c, and (c for point-source plumes. This model is more computationally demanding than other dispersion models (for C only) and must be demonstrated as a practical tool. However, it predicts an important quantity for applications- the uncertainty in the very high and infrequent concentrations. The uncertainty is large and is needed in evaluating operational performance and in predicting the attainment of air-quality standards.

Assessment and Improvement of GOCE based Global Geopotential Models Using Wavelet Decomposition

NASA Astrophysics Data System (ADS)

Erol, Serdar; Erol, Bihter; Serkan Isik, Mustafa

2016-07-01

The contribution of recent Earth gravity field satellite missions, specifically GOCE mission, leads significant improvement in quality of gravity field models in both accuracy and resolution manners. However the performance and quality of each released model vary not only depending on the spatial location of the Earth but also the different bands of the spectral expansion. Therefore the assessment of the global model performances with validations using in situ-data in varying territories on the Earth is essential for clarifying their exact performances in local. Beside of this, their spectral evaluation and quality assessment of the signal in each part of the spherical harmonic expansion spectrum is essential to have a clear decision for the commission error content of the model and determining its optimal degree, revealed the best results, as well. The later analyses provide also a perspective and comparison on the global behavior of the models and opportunity to report the sequential improvement of the models depending on the mission developments and hence the contribution of the new data of missions. In this study a review on spectral assessment results of the recently released GOCE based global geopotential models DIR-R5, TIM-R5 with the enhancement using EGM2008, as reference model, in Turkey, versus the terrestrial data is provided. Beside of reporting the GOCE mission contribution to the models in Turkish territory, the possible improvement in the spectral quality of these models, via decomposition that are highly contaminated by noise, is purposed. In the analyses the motivation is on achieving an optimal amount of improvement that rely on conserving the useful component of the GOCE signal as much as possible, while fusing the filtered GOCE based models with EGM2008 in the appropriate spectral bands. The investigation also contain the assessment of the coherence and the correlation between the Earth gravity field parameters (free-air gravity anomalies and geoid undulations), derived from the validated geopotential models and terrestrial data (GPS/leveling, terrestrial gravity observations, DTM etc.), as well as the WGM2012 products. In the conclusion, with the numerical results, the performance of the assessed models are clarified in Turkish territory and the potential of the Wavelet decomposition in the improvement of the geopotential models is verified.

The influence of enterprise resource planning (ERP) systems' performance on earnings management

NASA Astrophysics Data System (ADS)

Tsai, Wen-Hsien; Lee, Kuen-Chang; Liu, Jau-Yang; Lin, Sin-Jin; Chou, Yu-Wei

2012-11-01

We analyse whether there is a linkage between performance measures of enterprise resource planning (ERP) systems and earnings management. We find that earnings management decreases with the higher performance of ERP systems. The empirical result is as expected. We further analyse how the dimension of the DeLone and McLean model of information systems success affects earnings management. We find that the relationship between the performance of ERP systems and earnings management depends on System Quality after ERP implementation. The more System Quality improves, the more earnings management is reduced.

Financial incentives for quality in breast cancer care.

PubMed

Tisnado, Diana M; Rose-Ash, Danielle E; Malin, Jennifer L; Adams, John L; Ganz, Patricia A; Kahn, Katherine L

2008-07-01

To examine the use of financial incentives related to performance on quality measures reported by oncologists and surgeons associated with a population-based cohort of patients with breast cancer in Los Angeles County, California, and to explore the physician and practice characteristics associated with the use of these incentives among breast cancer care providers. Cross-sectional observational study. Physician self-reported financial arrangements from a survey of 348 medical oncologists, radiation oncologists, and surgeons caring for patients with breast cancer in Los Angeles County (response rate, 76%). Physicians were asked whether they were subject to financial incentives for quality (ie, patient satisfaction surveys and adherence to practice guidelines). We examined the prevalence and correlates of incentives and performed multivariate logistic regression analyses to assess predictors of incentives, controlling for other covariates. Twenty percent of respondents reported incentives based on patient satisfaction, and 15% reported incentives based on guideline adherence. The use of incentives for quality in this cohort of oncologists and surgeons was modest and was primarily associated with staff- or group-model health maintenance organization (HMO) settings. In other settings, important predictors were partial physician ownership interest, large practice size, and capitation. Most cancer care providers in Los Angeles County outside of staff- or group-model HMOs are not subject to explicit financial incentives based on quality-of-care measures. Those who are, seem more likely to be associated with large practice settings. New approaches are needed to direct financial incentives for quality toward specialists outside of staff- or group-model HMOs if pay-for-performance programs are to succeed in influencing care.

30 CFR 285.659 - What requirements must I include in my SAP, COP, or GAP regarding air quality?

Code of Federal Regulations, 2011 CFR

2011-07-01

..., or GAP regarding air quality? 285.659 Section 285.659 Mineral Resources BUREAU OF OCEAN ENERGY... Pipeline Deviations § 285.659 What requirements must I include in my SAP, COP, or GAP regarding air quality..., according to the following table. ER29AP09.130 (b) For air quality modeling that you perform in support of...

Air Quality Science and Regulatory Efforts Require Geostationary Satellite Measurements

NASA Technical Reports Server (NTRS)

Pickering, Kenneth E.; Allen, D. J.; Stehr, J. W.

2006-01-01

Air quality scientists and regulatory agencies would benefit from the high spatial and temporal resolution trace gas and aerosol data that could be provided by instruments on a geostationary platform. More detailed time-resolved data from a geostationary platform could be used in tracking regional transport and in evaluating mesoscale air quality model performance in terms of photochemical evolution throughout the day. The diurnal cycle of photochemical pollutants is currently missing from the data provided by the current generation of atmospheric chemistry satellites which provide only one measurement per day. Often peak surface ozone mixing ratios are reached much earlier in the day during major regional pollution episodes than during local episodes due to downward mixing of ozone that had been transported above the boundary layer overnight. The regional air quality models often do not simulate this downward mixing well enough and underestimate surface ozone in regional episodes. Having high time-resolution geostationary data will make it possible to determine the magnitude of this lower-and mid-tropospheric transport that contributes to peak eight-hour average ozone and 24-hour average PM2.5 concentrations. We will show ozone and PM(sub 2.5) episodes from the CMAQ model and suggest ways in which geostationary satellite data would improve air quality forecasting. Current regulatory modeling is typically being performed at 12 km horizontal resolution. State and regional air quality regulators in regions with complex topography and/or land-sea breezes are anxious to move to 4-km or finer resolution simulations. Geostationary data at these or finer resolutions will be useful in evaluating such models.

Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P

NASA Astrophysics Data System (ADS)

Jackson-Blake, L. A.; Sample, J. E.; Wade, A. J.; Helliwell, R. C.; Skeffington, R. A.

2017-07-01

Catchment-scale water quality models are increasingly popular tools for exploring the potential effects of land management, land use change and climate change on water quality. However, the dynamic, catchment-scale nutrient models in common usage are complex, with many uncertain parameters requiring calibration, limiting their usability and robustness. A key question is whether this complexity is justified. To explore this, we developed a parsimonious phosphorus model, SimplyP, incorporating a rainfall-runoff model and a biogeochemical model able to simulate daily streamflow, suspended sediment, and particulate and dissolved phosphorus dynamics. The model's complexity was compared to one popular nutrient model, INCA-P, and the performance of the two models was compared in a small rural catchment in northeast Scotland. For three land use classes, less than six SimplyP parameters must be determined through calibration, the rest may be based on measurements, while INCA-P has around 40 unmeasurable parameters. Despite substantially simpler process-representation, SimplyP performed comparably to INCA-P in both calibration and validation and produced similar long-term projections in response to changes in land management. Results support the hypothesis that INCA-P is overly complex for the study catchment. We hope our findings will help prompt wider model comparison exercises, as well as debate among the water quality modeling community as to whether today's models are fit for purpose. Simpler models such as SimplyP have the potential to be useful management and research tools, building blocks for future model development (prototype code is freely available), or benchmarks against which more complex models could be evaluated.

Lower- Versus Higher-Income Populations In The Alternative Quality Contract: Improved Quality And Similar Spending

PubMed Central

Song, Zirui; Rose, Sherri; Chernew, Michael E.; Safran, Dana Gelb

2018-01-01

As population-based payment models become increasingly common, it is crucial to understand how such payment models affect health disparities. We evaluated health care quality and spending among enrollees in areas with lower versus higher socioeconomic status in Massachusetts before and after providers entered into the Alternative Quality Contract, a two-sided population-based payment model with substantial incentives tied to quality. We compared changes in process measures, outcome measures, and spending between enrollees in areas with lower and higher socioeconomic status from 2006 to 2012 (outcome measures were measured after the intervention only). Quality improved for all enrollees in the Alternative Quality Contract after their provider organizations entered the contract. Process measures improved 1.2 percentage points per year more among enrollees in areas with lower socioeconomic status than among those in areas with higher socioeconomic status. Outcome measure improvement was no different between the subgroups; neither were changes in spending. Larger or comparable improvements in quality among enrollees in areas with lower socioeconomic status suggest a potential narrowing of disparities. Strong pay-for-performance incentives within a population-based payment model could encourage providers to focus on improving quality for more disadvantaged populations. PMID:28069849

How motivation affects academic performance: a structural equation modelling analysis.

PubMed

Kusurkar, R A; Ten Cate, Th J; Vos, C M P; Westers, P; Croiset, G

2013-03-01

Few studies in medical education have studied effect of quality of motivation on performance. Self-Determination Theory based on quality of motivation differentiates between Autonomous Motivation (AM) that originates within an individual and Controlled Motivation (CM) that originates from external sources. To determine whether Relative Autonomous Motivation (RAM, a measure of the balance between AM and CM) affects academic performance through good study strategy and higher study effort and compare this model between subgroups: males and females; students selected via two different systems namely qualitative and weighted lottery selection. Data on motivation, study strategy and effort was collected from 383 medical students of VU University Medical Center Amsterdam and their academic performance results were obtained from the student administration. Structural Equation Modelling analysis technique was used to test a hypothesized model in which high RAM would positively affect Good Study Strategy (GSS) and study effort, which in turn would positively affect academic performance in the form of grade point averages. This model fit well with the data, Chi square = 1.095, df = 3, p = 0.778, RMSEA model fit = 0.000. This model also fitted well for all tested subgroups of students. Differences were found in the strength of relationships between the variables for the different subgroups as expected. In conclusion, RAM positively correlated with academic performance through deep strategy towards study and higher study effort. This model seems valid in medical education in subgroups such as males, females, students selected by qualitative and weighted lottery selection.

Effects of chronic shoulder pain on quality of life and occupational engagement in the population with chronic spinal cord injury: preparing for the best outcomes with occupational therapy.

PubMed

Silvestri, Jennifer

2017-01-01

Purpose To examine the implications of chronic shoulder pain on quality of life and occupational engagement in spinal cord injury (SCI). The Ecology of Human Performance Model and Self-Efficacy Theory will be used to further examine the interplay of shoulder pain, quality of life and engagement in this population. Method Analysis of literature. Results Persons with SCI have a high prevalence of shoulder pain and injury, affecting 37-84% of analysed studies; chronic pain limits occupational engagement and decreases quality of life. Remediation of pain provides improved occupational engagement, functional independence and quality of life in those with high self-efficacy and low depression. Conclusion Shoulder pain is a serious complication following SCI and the Ecology of Human Performance Model and Self-Efficacy Theory can be utilized in conjunction for a framework to evaluate, treat and prevent shoulder pain and its devastating effects on occupational engagement and quality of life in the spinal cord injured population. Thereafter, rehabilitation professionals will have a greater understanding of these interactions to serve as a guide for evaluation and intervention planning to promote optimal occupational engagement through limiting the experiences of occupational injustices for those with SCI and shoulder pain. Implications for Rehabilitation Musculoskeletal pain at the shoulder joint and depression are common complications following spinal cord injury that limit occupational engagement and decrease quality of life. To increase engagement and quality of life in this population, treatments need to address all factors including the under-lying psychosocial instead of task and environment modification alone. The Ecology of Human Performance Model and Self-efficacy Theory are effective frameworks that can be used for evaluation, treatment planning and outcome measurement to maximize occupational engagement and quality of life.

Centers for medicare and medicaid services: using an episode-based payment model to improve oncology care.

PubMed

Kline, Ronald M; Bazell, Carol; Smith, Erin; Schumacher, Heidi; Rajkumar, Rahul; Conway, Patrick H

2015-03-01

Cancer is a medically complex and expensive disease with costs projected to rise further as new treatment options increase and the United States population ages. Studies showing significant regional variation in oncology quality and costs and model tests demonstrating cost savings without adverse outcomes suggest there are opportunities to create a system of oncology care in the US that delivers higher quality care at lower cost. The Centers for Medicare and Medicaid Services (CMS) have designed an episode-based payment model centered around 6 month periods of chemotherapy treatment. Monthly per-patient care management payments will be made to practices to support practice transformation, including additional patient services and specific infrastructure enhancements. Quarterly reporting of quality metrics will drive continuous quality improvement and the adoption of best practices among participants. Practices achieving cost savings will also be eligible for performance-based payments. Savings are expected through improved care coordination and appropriately aligned payment incentives, resulting in decreased avoidable emergency department visits and hospitalizations and more efficient and evidence-based use of imaging, laboratory tests, and therapeutic agents, as well as improved end of life care. New therapies and better supportive care have significantly improved cancer survival in recent decades. This has come at a high cost, with cancer therapy consuming $124 billion in 2010. CMS has designed an episode-based model of oncology care that incorporates elements from several successful model tests. By providing care management and performance based payments in conjunction with quality metrics and a rapid learning environment, it is hoped that this model will demonstrate how oncology care in the US can transform into a high value, high quality system. Copyright © 2015 by American Society of Clinical Oncology.

Effects of interface pressure distribution on human sleep quality.

PubMed

Chen, Zongyong; Li, Yuqian; Liu, Rong; Gao, Dong; Chen, Quanhui; Hu, Zhian; Guo, Jiajun

2014-01-01

High sleep quality promotes efficient performance in the following day. Sleep quality is influenced by environmental factors, such as temperature, light, sound and smell. Here, we investigated whether differences in the interface pressure distribution on healthy individuals during sleep influenced sleep quality. We defined four types of pressure models by differences in the area distribution and the subjective feelings that occurred when participants slept on the mattresses. One type of model was showed "over-concentrated" distribution of pressure; one was displayed "over-evenly" distributed interface pressure while the other two models were displayed intermediate distribution of pressure. A polysomnography analysis demonstrated an increase in duration and proportion of non-rapid-eye-movement sleep stages 3 and 4, as well as decreased number of micro-arousals, in subjects sleeping on models with pressure intermediately distributed compared to models with over-concentrated or over-even distribution of pressure. Similarly, higher scores of self-reported sleep quality were obtained in subjects sleeping on the two models with intermediate pressure distribution. Thus, pressure distribution, at least to some degree, influences sleep quality and self-reported feelings of sleep-related events, though the underlying mechanisms remain unknown. The regulation of pressure models imposed by external sleep environment may be a new direction for improving sleep quality. Only an appropriate interface pressure distribution is beneficial for improving sleep quality, over-concentrated or -even distribution of pressure do not help for good sleep.

Using a gradient boosting model to improve the performance of low-cost aerosol monitors in a dense, heterogeneous urban environment

NASA Astrophysics Data System (ADS)

Johnson, Nicholas E.; Bonczak, Bartosz; Kontokosta, Constantine E.

2018-07-01

The increased availability and improved quality of new sensing technologies have catalyzed a growing body of research to evaluate and leverage these tools in order to quantify and describe urban environments. Air quality, in particular, has received greater attention because of the well-established links to serious respiratory illnesses and the unprecedented levels of air pollution in developed and developing countries and cities around the world. Though numerous laboratory and field evaluation studies have begun to explore the use and potential of low-cost air quality monitoring devices, the performance and stability of these tools has not been adequately evaluated in complex urban environments, and further research is needed. In this study, we present the design of a low-cost air quality monitoring platform based on the Shinyei PPD42 aerosol monitor and examine the suitability of the sensor for deployment in a dense heterogeneous urban environment. We assess the sensor's performance during a field calibration campaign from February 7th to March 25th 2017 with a reference instrument in New York City, and present a novel calibration approach using a machine learning method that incorporates publicly available meteorological data in order to improve overall sensor performance. We find that while the PPD42 performs well in relation to the reference instrument using linear regression (R2 = 0.36-0.51), a gradient boosting regression tree model can significantly improve device calibration (R2 = 0.68-0.76). We discuss the sensor's performance and reliability when deployed in a dense, heterogeneous urban environment during a period of significant variation in weather conditions, and important considerations when using machine learning techniques to improve the performance of low-cost air quality monitors.

Performance and diagnostic evaluation of ozone predictions by the Eta-Community Multiscale Air Quality Forecast System during the 2002 New England Air Quality Study.

PubMed

Yu, Shaocai; Mathur, Rohit; Kang, Daiwen; Schere, Kenneth; Eder, Brian; Pleim, Jonathan

2006-10-01

A real-time air quality forecasting system (Eta-Community Multiscale Air Quality [CMAQ] model suite) has been developed by linking the National Centers for Environmental Estimation Eta model to the U.S. Environmental Protection Agency (EPA) CMAQ model. This work presents results from the application of the Eta-CMAQ modeling system for forecasting ozone (O3) over the Northeastern United States during the 2002 New England Air Quality Study (NEAQS). Spatial and temporal performance of the Eta-CMAQ model for O3 was evaluated by comparison with observations from the EPA Air Quality System (AQS) network. This study also examines the ability of the model to simulate the processes governing the distributions of tropospheric O3 on the basis of the intensive datasets obtained at the four Atmospheric Investigation, Regional Modeling, Analysis, and Estimation (AIRMAP) and Harvard Forest (HF) surface sites. The episode analysis reveals that the model captured the buildup of O3 concentrations over the northeastern domain from August 11 and reproduced the spatial distributions of observed O3 very well for the daytime (8:00 p.m.) of both August 8 and 12 with most of normalized mean bias (NMB) within +/- 20%. The model reproduced 53.3% of the observed hourly O3 within a factor of 1.5 with NMB of 29.7% and normalized mean error of 46.9% at the 342 AQS sites. The comparison of modeled and observed lidar O3 vertical profiles shows that whereas the model reproduced the observed vertical structure, it tended to overestimate at higher altitude. The model reproduced 64-77% of observed NO2 photolysis rate values within a factor of 1.5 at the AIRMAP sites. At the HF site, comparison of modeled and observed O3/nitrogen oxide (NOx) ratios suggests that the site is mainly under strongly NOx-sensitive conditions (>53%). It was found that the modeled lower limits of the O3 production efficiency values (inferred from O3-CO correlation) are close to the observations.

Mediation analysis of severity of needs, service performance and outcomes for patients with mental disorders.

PubMed

Roux, Paul; Passerieux, Christine; Fleury, Marie-Josée

2016-12-01

Needs and service performance assessment are key components in improving recovery among individuals with mental disorders. To test the role of service performance as a mediating factor between severity of patients' needs and outcomes. A total of 339 adults with mental disorders were interviewed. A mediation analysis between severity of needs, service performance (adequacy of help, continuity of care and recovery orientation of services) and outcomes (personal recovery and quality of life) was carried out using structural equation modelling. The structural equation model provided a good fit with the data. An increase in needs was associated with lower service performance and worse outcomes, whereas higher service performance was associated with better outcomes. Service performance partially mediated the effect of patient needs on outcomes. Poorer service performance has a negative impact on outcomes for patients with the highest needs. Ensuring more efficient services for patients with high needs may help improve their recovery and quality of life. © The Royal College of Psychiatrists 2016.

Multiscale Methods for Accurate, Efficient, and Scale-Aware Models of the Earth System

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

Goldhaber, Steve; Holland, Marika

The major goal of this project was to contribute improvements to the infrastructure of an Earth System Model in order to support research in the Multiscale Methods for Accurate, Efficient, and Scale-Aware models of the Earth System project. In support of this, the NCAR team accomplished two main tasks: improving input/output performance of the model and improving atmospheric model simulation quality. Improvement of the performance and scalability of data input and diagnostic output within the model required a new infrastructure which can efficiently handle the unstructured grids common in multiscale simulations. This allows for a more computationally efficient model, enablingmore » more years of Earth System simulation. The quality of the model simulations was improved by reducing grid-point noise in the spectral element version of the Community Atmosphere Model (CAM-SE). This was achieved by running the physics of the model using grid-cell data on a finite-volume grid.« less

Genetic and Phenotypic Correlations between Performance Traits with Meat Quality and Carcass Characteristics in Commercial Crossbred Pigs

PubMed Central

Miar, Younes; Plastow, Graham; Bruce, Heather; Moore, Stephen; Manafiazar, Ghader; Kemp, Robert; Charagu, Patrick; Huisman, Abe; van Haandel, Benny; Zhang, Chunyan; McKay, Robert; Wang, Zhiquan

2014-01-01

Genetic correlations between performance traits with meat quality and carcass traits were estimated on 6,408 commercial crossbred pigs with performance traits recorded in production systems with 2,100 of them having meat quality and carcass measurements. Significant fixed effects (company, sex and batch), covariates (birth weight, cold carcass weight, and age), random effects (additive, litter and maternal) were fitted in the statistical models. A series of pairwise bivariate analyses were implemented in ASREML to estimate heritability, phenotypic, and genetic correlations between performance traits (n = 9) with meat quality (n = 25) and carcass (n = 19) traits. The animals had a pedigree compromised of 9,439 animals over 15 generations. Performance traits had low-to-moderate heritabilities (±SE), ranged from 0.07±0.13 to 0.45±0.07 for weaning weight, and ultrasound backfat depth, respectively. Genetic correlations between performance and carcass traits were moderate to high. The results indicate that: (a) selection for birth weight may increase drip loss, lightness of longissimus dorsi, and gluteus medius muscles but may reduce fat depth; (b) selection for nursery weight can be valuable for increasing both quantity and quality traits; (c) selection for increased daily gain may increase the carcass weight and most of the primal cuts. These findings suggest that deterioration of pork quality may have occurred over many generations through the selection for less backfat thickness, and feed efficiency, but selection for growth had no adverse effects on pork quality. Low-to-moderate heritabilities for performance traits indicate that they could be improved using traditional selection or genomic selection. The estimated genetic parameters for performance, carcass and meat quality traits may be incorporated into the breeding programs that emphasize product quality in these Canadian swine populations. PMID:25350845

Genetic and phenotypic correlations between performance traits with meat quality and carcass characteristics in commercial crossbred pigs.

PubMed

Miar, Younes; Plastow, Graham; Bruce, Heather; Moore, Stephen; Manafiazar, Ghader; Kemp, Robert; Charagu, Patrick; Huisman, Abe; van Haandel, Benny; Zhang, Chunyan; McKay, Robert; Wang, Zhiquan

2014-01-01

Genetic correlations between performance traits with meat quality and carcass traits were estimated on 6,408 commercial crossbred pigs with performance traits recorded in production systems with 2,100 of them having meat quality and carcass measurements. Significant fixed effects (company, sex and batch), covariates (birth weight, cold carcass weight, and age), random effects (additive, litter and maternal) were fitted in the statistical models. A series of pairwise bivariate analyses were implemented in ASREML to estimate heritability, phenotypic, and genetic correlations between performance traits (n = 9) with meat quality (n = 25) and carcass (n = 19) traits. The animals had a pedigree compromised of 9,439 animals over 15 generations. Performance traits had low-to-moderate heritabilities (±SE), ranged from 0.07±0.13 to 0.45±0.07 for weaning weight, and ultrasound backfat depth, respectively. Genetic correlations between performance and carcass traits were moderate to high. The results indicate that: (a) selection for birth weight may increase drip loss, lightness of longissimus dorsi, and gluteus medius muscles but may reduce fat depth; (b) selection for nursery weight can be valuable for increasing both quantity and quality traits; (c) selection for increased daily gain may increase the carcass weight and most of the primal cuts. These findings suggest that deterioration of pork quality may have occurred over many generations through the selection for less backfat thickness, and feed efficiency, but selection for growth had no adverse effects on pork quality. Low-to-moderate heritabilities for performance traits indicate that they could be improved using traditional selection or genomic selection. The estimated genetic parameters for performance, carcass and meat quality traits may be incorporated into the breeding programs that emphasize product quality in these Canadian swine populations.

Scale Issues in Air Quality Modeling

EPA Science Inventory

This presentation reviews past model evaluation studies investigating the impact of horizontal grid spacing on model performance. It also presents several examples of using a spectral decomposition technique to separate the forcings from processes operating on different time scal...

The Airport Performance Model

DOT National Transportation Integrated Search

1976-04-01

This report describes the development of a model and companion data base for evaluating levels and qualities of service provided to the public by Air Carrier Airports. The model is designed to translate changes in airport capabilities into public ser...

Multisite Evaluation of APEX for Water Quality: I. Best Professional Judgment Parameterization.

PubMed

Baffaut, Claire; Nelson, Nathan O; Lory, John A; Senaviratne, G M M M Anomaa; Bhandari, Ammar B; Udawatta, Ranjith P; Sweeney, Daniel W; Helmers, Matt J; Van Liew, Mike W; Mallarino, Antonio P; Wortmann, Charles S

2017-11-01

The Agricultural Policy Environmental eXtender (APEX) model is capable of estimating edge-of-field water, nutrient, and sediment transport and is used to assess the environmental impacts of management practices. The current practice is to fully calibrate the model for each site simulation, a task that requires resources and data not always available. The objective of this study was to compare model performance for flow, sediment, and phosphorus transport under two parameterization schemes: a best professional judgment (BPJ) parameterization based on readily available data and a fully calibrated parameterization based on site-specific soil, weather, event flow, and water quality data. The analysis was conducted using 12 datasets at four locations representing poorly drained soils and row-crop production under different tillage systems. Model performance was based on the Nash-Sutcliffe efficiency (NSE), the coefficient of determination () and the regression slope between simulated and measured annualized loads across all site years. Although the BPJ model performance for flow was acceptable (NSE = 0.7) at the annual time step, calibration improved it (NSE = 0.9). Acceptable simulation of sediment and total phosphorus transport (NSE = 0.5 and 0.9, respectively) was obtained only after full calibration at each site. Given the unacceptable performance of the BPJ approach, uncalibrated use of APEX for planning or management purposes may be misleading. Model calibration with water quality data prior to using APEX for simulating sediment and total phosphorus loss is essential. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Identifying Optimal Temporal Scale for the Correlation of AOD and Ground Measurements of PM2.5 to Improve the Model Performance in a Real-time Air Quality Estimation System

NASA Technical Reports Server (NTRS)

Li, Hui; Faruque, Fazlay; Williams, Worth; Al-Hamdan, Mohammad; Luvall, Jeffrey C.; Crosson, William; Rickman, Douglas; Limaye, Ashutosh

2009-01-01

Aerosol optical depth (AOD), an indirect estimate of particle matter using satellite observations, has shown great promise in improving estimates of PM 2.5 air quality surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM 2.5 surface estimation in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) the approach to integrate satellite measurements with ground measurements in the pollution estimation, and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect on the identifying the optimal temporal scale to correlate AOD with PM2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale of within the last 30 days displays the best model performance in this study area using 2004 and 2005 data sets.

An emission processing system for air quality modelling in the Mexico City metropolitan area: Evaluation and comparison of the MOBILE6.2-Mexico and MOVES-Mexico traffic emissions.

PubMed

Guevara, M; Tena, C; Soret, A; Serradell, K; Guzmán, D; Retama, A; Camacho, P; Jaimes-Palomera, M; Mediavilla, A

2017-04-15

This article describes the High-Elective Resolution Modelling Emission System for Mexico (HERMES-Mex) model, an emission processing tool developed to transform the official Mexico City Metropolitan Area (MCMA) emission inventory into hourly, gridded (up to 1km 2 ) and speciated emissions used to drive mesoscale air quality simulations with the Community Multi-scale Air Quality (CMAQ) model. The methods and ancillary information used for the spatial and temporal disaggregation and speciation of the emissions are presented and discussed. The resulting emission system is evaluated, and a case study on CO, NO 2 , O 3 , VOC and PM 2.5 concentrations is conducted to demonstrate its applicability. Moreover, resulting traffic emissions from the Mobile Source Emission Factor Model for Mexico (MOBILE6.2-Mexico) and the MOtor Vehicle Emission Simulator for Mexico (MOVES-Mexico) models are integrated in the tool to assess and compare their performance. NO x and VOC total emissions modelled are reduced by 37% and 26% in the MCMA when replacing MOBILE6.2-Mexico for MOVES-Mexico traffic emissions. In terms of air quality, the system composed by the Weather Research and Forecasting model (WRF) coupled with the HERMES-Mex and CMAQ models properly reproduces the pollutant levels and patterns measured in the MCMA. The system's performance clearly improves in urban stations with a strong influence of traffic sources when applying MOVES-Mexico emissions. Despite reducing estimations of modelled precursor emissions, O 3 peak averages are increased in the MCMA core urban area (up to 30ppb) when using MOVES-Mexico mobile emissions due to its VOC-limited regime, while concentrations in the surrounding suburban/rural areas decrease or increase depending on the meteorological conditions of the day. The results obtained suggest that the HERMES-Mex model can be used to provide model-ready emissions for air quality modelling in the MCMA. Copyright © 2017 Elsevier B.V. All rights reserved.

Case-Mix Adjustment of the Bereaved Family Survey.

PubMed

Kutney-Lee, Ann; Carpenter, Joan; Smith, Dawn; Thorpe, Joshua; Tudose, Alina; Ersek, Mary

2018-01-01

Surveys of bereaved family members are increasingly being used to evaluate end-of-life (EOL) care and to measure organizational performance in EOL care quality. The Bereaved Family Survey (BFS) is used to monitor EOL care quality and benchmark performance in the Veterans Affairs (VA) health-care system. The objective of this study was to develop a case-mix adjustment model for the BFS and to examine changes in facility-level scores following adjustment, in order to provide fair comparisons across facilities. We conducted a cross-sectional secondary analysis of medical record and survey data from veterans and their family members across 146 VA medical centers. Following adjustment using model-based propensity weighting, the mean change in the BFS-Performance Measure score across facilities was -0.6 with a range of -2.6 to 0.6. Fifty-five (38%) facilities changed within ±0.5 percentage points of their unadjusted score. On average, facilities that benefited most from adjustment cared for patients with greater comorbidity burden and were located in urban areas in the Northwest and Midwestern regions of the country. Case-mix adjustment results in minor changes to facility-level BFS scores but allows for fairer comparisons of EOL care quality. Case-mix adjustment of the BFS positions this National Quality Forum-endorsed measure for use in public reporting and internal quality dashboards for VA leadership and may inform the development and refinement of case-mix adjustment models for other surveys of bereaved family members.

Integrating Reliability Analysis with a Performance Tool

NASA Technical Reports Server (NTRS)

Nicol, David M.; Palumbo, Daniel L.; Ulrey, Michael

1995-01-01

A large number of commercial simulation tools support performance oriented studies of complex computer and communication systems. Reliability of these systems, when desired, must be obtained by remodeling the system in a different tool. This has obvious drawbacks: (1) substantial extra effort is required to create the reliability model; (2) through modeling error the reliability model may not reflect precisely the same system as the performance model; (3) as the performance model evolves one must continuously reevaluate the validity of assumptions made in that model. In this paper we describe an approach, and a tool that implements this approach, for integrating a reliability analysis engine into a production quality simulation based performance modeling tool, and for modeling within such an integrated tool. The integrated tool allows one to use the same modeling formalisms to conduct both performance and reliability studies. We describe how the reliability analysis engine is integrated into the performance tool, describe the extensions made to the performance tool to support the reliability analysis, and consider the tool's performance.

Prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy: a systematic review and external validation study.

PubMed

Hilkens, N A; Algra, A; Greving, J P

2016-01-01

ESSENTIALS: Prediction models may help to identify patients at high risk of bleeding on antiplatelet therapy. We identified existing prediction models for bleeding and validated them in patients with cerebral ischemia. Five prediction models were identified, all of which had some methodological shortcomings. Performance in patients with cerebral ischemia was poor. Background Antiplatelet therapy is widely used in secondary prevention after a transient ischemic attack (TIA) or ischemic stroke. Bleeding is the main adverse effect of antiplatelet therapy and is potentially life threatening. Identification of patients at increased risk of bleeding may help target antiplatelet therapy. This study sought to identify existing prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy and evaluate their performance in patients with cerebral ischemia. We systematically searched PubMed and Embase for existing prediction models up to December 2014. The methodological quality of the included studies was assessed with the CHARMS checklist. Prediction models were externally validated in the European Stroke Prevention Study 2, comprising 6602 patients with a TIA or ischemic stroke. We assessed discrimination and calibration of included prediction models. Five prediction models were identified, of which two were developed in patients with previous cerebral ischemia. Three studies assessed major bleeding, one studied intracerebral hemorrhage and one gastrointestinal bleeding. None of the studies met all criteria of good quality. External validation showed poor discriminative performance, with c-statistics ranging from 0.53 to 0.64 and poor calibration. A limited number of prediction models is available that predict intracranial hemorrhage or major bleeding in patients on antiplatelet therapy. The methodological quality of the models varied, but was generally low. Predictive performance in patients with cerebral ischemia was poor. In order to reliably predict the risk of bleeding in patients with cerebral ischemia, development of a prediction model according to current methodological standards is needed. © 2015 International Society on Thrombosis and Haemostasis.

Maximizing sinter plant operating flexibility through emissions trading and air modeling

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

Schewe, G.J.; Wagner, J.A.; Heron, T.

1998-12-31

This paper provides details on the dispersion modeling analysis performed to demonstrate air quality impacts associated with an emission trading scheme for a sintering operation in Youngstown, Ohio. The emission trade was proposed to allow the sinter plant to expand its current allowable sulfur dioxide (SO2) emissions while being offset with SO{sub 2} emissions from boilers at a nearby shutdown steel mill. While the emission trade itself was feasible and the emissions required for the offset were available (the boiler shutdown and their subsequent SO{sub 2} emission credits were never claimed, banked, or used elsewhere), the second criteria for determiningmore » compliance was a demonstration of minimal air quality impact. The air analysis combined the increased ambient SO{sub 2} concentrations of the relaxed sinter plant emissions with the offsetting air quality of the shutdown boilers to yield the net air quality impacts. To test this net air impact, dispersion modeling was performed treating the sinter plant SO{sub 2} emissions as positive and the shutdown boiler SO{sub 2} emissions as negative. The results of the modeling indicated that the ambient air concentrations due to the proposed emissions increase will be offset by the nearby boiler emissions to levels acceptable under EPA`s offset policy Level 2 significant impact concentrations. Therefore, the dispersion modeling demonstrated that the emission trading scheme would not result in significant air quality impacts and maximum operating flexibility was provided to the sintering facility.« less

Evaluation of Day and Nighttime Lower Tropospheric Ozone from Air Quality Models using TES and Ozonesondes

NASA Astrophysics Data System (ADS)

Osterman, G. B.; Neu, J. L.; Eldering, A.; Pinder, R. W.; Tang, Y.; McQueen, J.

2012-12-01

At night, ozone can be transported long distances above the surface inversion layer without chemical destruction or deposition. As the boundary layer breaks up in the morning, this nocturnal ozone can be mixed down to the surface and rapidly increase ozone concentrations at a rate that can rival chemical ozone production. Most regional scale models that are used for air quality forecasts and ozone source attribution do not adequately capture nighttime ozone concentrations and transport. We combine ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and other sensors, ozonesonde data collected during the INTEX Ozonesonde Network Study (IONS), EPA AirNow ground station ozone data, the Community Multi-Scale Air Quality (CMAQ) model, and the National Air Quality Forecast Capability (NAQFC) model to examine air quality events during August 2006. We present both aggregated statistics and case-study analyses that assess the relationship between the models' ability to reproduce surface air quality events and their ability to capture the vertical distribution of ozone both during the day and at night. We perform the comparisons looking at the geospatial dependence in the differences between the measurements and models under different surface ozone conditions.

Integrated Modelling on Flow and Water Quality Under the Impacts of Climate Change and Agricultural Activities

NASA Astrophysics Data System (ADS)

SHI, J.

2014-12-01

Climate change is expected to have a significant impact on flooding in the UK, inducing more intense and prolonged storms. Frequent flooding due to climate change already exacerbates catchment water quality. Land use is another contributing factor to poor water quality. For example, the move to intensive farming could cause an increase in faecal coliforms entering the water courses. In an effort to understand better the effects on water quality from land use and climate change, the hydrological and estuarine processes are being modelled using SWAT (Soil and Water Assessment Tool), linked to a 2-D hydrodynamic model DIVAST(Depth Integrated Velocity and Solute Transport). The coupled model is able to quantify how much of each pollutant from the catchment reaches the harbour and the impact on water quality within the harbour. The work is focused on the transportation and decay of faecal coliforms from agricultural runoff into the rivers Frome and Piddle in the UK. The impact from the agricultural land use and activities on the catchment river hydrology and water quality are evaluated. The coupled model calibration and validation showed the good model performance on flow and faecal coliform in the watershed and estuary.

Enhancing population pharmacokinetic modeling efficiency and quality using an integrated workflow.

PubMed

Schmidt, Henning; Radivojevic, Andrijana

2014-08-01

Population pharmacokinetic (popPK) analyses are at the core of Pharmacometrics and need to be performed regularly. Although these analyses are relatively standard, a large variability can be observed in both the time (efficiency) and the way they are performed (quality). Main reasons for this variability include the level of experience of a modeler, personal preferences and tools. This paper aims to examine how the process of popPK model building can be supported in order to increase its efficiency and quality. The presented approach to the conduct of popPK analyses is centered around three key components: (1) identification of most common and important popPK model features, (2) required information content and formatting of the data for modeling, and (3) methodology, workflow and workflow supporting tools. This approach has been used in several popPK modeling projects and a documented example is provided in the supplementary material. Efficiency of model building is improved by avoiding repetitive coding and other labor-intensive tasks and by putting the emphasis on a fit-for-purpose model. Quality is improved by ensuring that the workflow and tools are in alignment with a popPK modeling guidance which is established within an organization. The main conclusion of this paper is that workflow based approaches to popPK modeling are feasible and have significant potential to ameliorate its various aspects. However, the implementation of such an approach in a pharmacometric organization requires openness towards innovation and change-the key ingredient for evolution of integrative and quantitative drug development in the pharmaceutical industry.

Ensuring quality and safety.

PubMed

Reid, Jerry

2010-01-01

The certification model addresses quality and safety by directly targeting the qualifications of individuals. The practice accreditation model takes a more global approach to quality and safety and addresses the qualifications of individuals and standards for additional components of the quality chain. Although both certification and practice accreditation fundamentally are voluntary, the programs may become mandatory when enforcement mechanisms are linked to the programs via state or federal legislation or via private reimbursement policies, effectively resulting in mandatory standards. The CARE bill takes a certification approach to quality and safety by focusing on the qualifications of the individual. MIPPA takes an accreditation approach by focusing on the practice. MQSA is somewhat of a hybrid in that it takes an accreditation approach, but spells out standards for the individual that the accreditor must follow. If the practice accreditation standards require that all technologists employed in the practice be certified in the modalities performed, then the practice accreditation model and the certification model become functionally equivalent in terms of personnel qualifications. To the extent that practice accreditation models are less prescriptive regarding personnel standards, the certification model results in more stringent standards.

Deep supervised dictionary learning for no-reference image quality assessment

NASA Astrophysics Data System (ADS)

Huang, Yuge; Liu, Xuesong; Tian, Xiang; Zhou, Fan; Chen, Yaowu; Jiang, Rongxin

2018-03-01

We propose a deep convolutional neural network (CNN) for general no-reference image quality assessment (NR-IQA), i.e., accurate prediction of image quality without a reference image. The proposed model consists of three components such as a local feature extractor that is a fully CNN, an encoding module with an inherent dictionary that aggregates local features to output a fixed-length global quality-aware image representation, and a regression module that maps the representation to an image quality score. Our model can be trained in an end-to-end manner, and all of the parameters, including the weights of the convolutional layers, the dictionary, and the regression weights, are simultaneously learned from the loss function. In addition, the model can predict quality scores for input images of arbitrary sizes in a single step. We tested our method on commonly used image quality databases and showed that its performance is comparable with that of state-of-the-art general-purpose NR-IQA algorithms.

The Empirical Testing of a Musical Performance Assessment Paradigm

ERIC Educational Resources Information Center

Russell, Brian E.

2010-01-01

The purpose of this study was to test a hypothesized model of aurally perceived performer-controlled musical factors that influence assessments of performance quality. Previous research studies on musical performance constructs, musical achievement, musical expression, and scale construction were examined to identify the factors that influence…

Identify High-Quality Protein Structural Models by Enhanced K-Means.

PubMed

Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

Identify High-Quality Protein Structural Models by Enhanced K-Means

PubMed Central

Li, Haiou; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K-means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K-means clustering (SK-means), whereas the other employs squared distance to optimize the initial centroids (K-means++). Our results showed that SK-means and K-means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K-means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK-means and K-means++ demonstrated substantial improvements relative to results from SPICKER and classical K-means. PMID:28421198

Moving Towards Air Quality Models with Chemistry Linked to the Master Chemical Mechanism: CRI Performance in U.S. Regional Models

EPA Science Inventory

This presentation described implementation of the Common Representative Intermediate (CRI) atmospheric chemistry in CMAQ, a short analysis of its performance in CMAQ relative to other mechanisms and an example of the additional detail it gives us for understanding atmospheric che...

An Empirical Test of Five Prominent Explanations for the Black-White Academic Performance Gap

ERIC Educational Resources Information Center

Oates, Gary L. St. C.

2009-01-01

The viability of five prominent explanations for the black-white performance gap ("academic engagement," "cultural capital," "social capital," "school quality" and "biased treatment") is examined using NELS data and a LISREL model that adjusts for clustering of students within schools. Empirical models have typically assessed these factors…

Multi-objective models of waste load allocation toward a sustainable reuse of drainage water in irrigation.

PubMed

Allam, Ayman; Tawfik, Ahmed; Yoshimura, Chihiro; Fleifle, Amr

2016-06-01

The present study proposes a waste load allocation (WLA) framework for a sustainable quality management of agricultural drainage water (ADW). Two multi-objective models, namely, abatement-performance and abatement-equity-performance, were developed through the integration of a water quality model (QAUL2Kw) and a genetic algorithm, by considering (1) the total waste load abatement, and (2) the inequity among waste dischargers. For successfully accomplishing modeling tasks, we developed a comprehensive overall performance measure (E wla ) reflecting possible violations of Egyptian standards for ADW reuse in irrigation. This methodology was applied to the Gharbia drain in the Nile Delta, Egypt, during both summer and winter seasons of 2012. Abatement-performance modeling results for a target of E wla = 100 % corresponded to the abatement ratio of the dischargers ranging from 20.7 to 75.6 % and 29.5 to 78.5 % in summer and in winter, respectively, alongside highly shifting inequity values. Abatement-equity-performance modeling results for a target of E wla = 90 % unraveled the necessity of increasing treatment efforts in three out of five dischargers during summer, and four out of five in winter. The trade-off curves obtained from WLA models proved their reliability in selecting appropriate WLA procedures as a function of budget constraints, principles of social equity, and desired overall performance level. Hence, the proposed framework of methodologies is of great importance to decision makers working toward a sustainable reuse of the ADW in irrigation.

Real-time assessments of water quality: expanding nowcasting throughout the Great Lakes

USGS Publications Warehouse

,

2013-01-01

Nowcasts are systems that inform the public of current bacterial water-quality conditions at beaches on the basis of predictive models. During 2010–12, the U.S. Geological Survey (USGS) worked with 23 local and State agencies to improve existing operational beach nowcast systems at 4 beaches and expand the use of predictive models in nowcasts at an additional 45 beaches throughout the Great Lakes. The predictive models were specific to each beach, and the best model for each beach was based on a unique combination of environmental and water-quality explanatory variables. The variables used most often in models to predict Escherichia coli (E. coli) concentrations or the probability of exceeding a State recreational water-quality standard included turbidity, day of the year, wave height, wind direction and speed, antecedent rainfall for various time periods, and change in lake level over 24 hours. During validation of 42 beach models during 2012, the models performed better than the current method to assess recreational water quality (previous day's E. coli concentration). The USGS will continue to work with local agencies to improve nowcast predictions, enable technology transfer of predictive model development procedures, and implement more operational systems during 2013 and beyond.

The Relationship between Health Plan Performance Measures and Physician Network Overlap: Implications for Measuring Plan Quality

PubMed Central

Maeng, Daniel D; Scanlon, Dennis P; Chernew, Michael E; Gronniger, Tim; Wodchis, Walter P; McLaughlin, Catherine G

2010-01-01

Objective To examine the extent to which health plan quality measures capture physician practice patterns rather than plan characteristics. Data Source We gathered and merged secondary data from the following four sources: a private firm that collected information on individual physicians and their health plan affiliations, The National Committee for Quality Assurance, InterStudy, and the Dartmouth Atlas. Study Design We constructed two measures of physician network overlap for all health plans in our sample and linked them to selected measures of plan performance. Two linear regression models were estimated to assess the relationship between the measures of physician network overlap and the plan performance measures. Principal Findings The results indicate that in the presence of a higher degree of provider network overlap, plan performance measures tend to converge to a lower level of quality. Conclusions Standard health plan performance measures reflect physician practice patterns rather than plans' effort to improve quality. This implies that more provider-oriented measurement, such as would be possible with accountable care organizations or medical homes, may facilitate patient decision making and provide further incentives to improve performance. PMID:20403064

[Ventilation during cardiopulmonary resuscitation in the infant. Mouth to mouth and nose, or bag-valve-mask? A quasi-experimental study].

PubMed

Santos-Folgar, Myriam; Otero-Agra, Martín; Fernández-Méndez, Felipe; Hermo-Gonzalo, María Teresa; Barcala-Furelos, Roberto; Rodríguez-Núñez, Antonio

2018-02-08

It has been observed that health professionals have difficulty performing quality cardiopulmonary resuscitation (CPR). The aim of this study was to compare the quality of ventilations performed by Nursing students on an infant model using different methods (mouth-to-mouth-and-nose or bag-valve-mask). A quasi-experimental cross-sectional study was performed that included 46 second-year Nursing students. Two quantitative 4-minute tests of paediatric CPR were performed: a) mouth-to-mouth-and-nose ventilations, and b) ventilations with bag-valve-mask. A Resusci Baby QCPR Wireless SkillReporter® mannequin from Laerdal was used. The proportion of ventilations with adequate, excessive, and insufficient volume was recorded and analysed, as well as the overall quality of the CPR (ventilations and chest compressions). The students were able to give a higher number of ventilations with adequate volume using the mouth-to-mouth-and-nose method (55±22%) than with the bag-valve-mask (28±16%, P<.001). The overall quality of the CPR was also significantly higher when using the mouth-to-mouth-and-nose method (60±19 vs. 48±16%, P<.001). Mouth-to-mouth-and-nose ventilation method is more efficient than bag-valve-mask ventilations in CPR performed by nursing students with a simulated infant model. Copyright © 2018. Publicado por Elsevier España, S.L.U.

Dimethylsulfide Chemistry: Annual, Seasonal, and Spatial Impacts on Sulfate

EPA Science Inventory

We incorporated oceanic emissions and atmospheric chemistry of dimethylsulfide (DMS) into the hemispheric Community Multiscale Air Quality model and performed annual model simulations without and with DMS chemistry. The model without DMS chemistry predicts higher concentrations o...

Predicting the Accuracy of Protein–Ligand Docking on Homology Models

PubMed Central

BORDOGNA, ANNALISA; PANDINI, ALESSANDRO; BONATI, LAURA

2011-01-01

Ligand–protein docking is increasingly used in Drug Discovery. The initial limitations imposed by a reduced availability of target protein structures have been overcome by the use of theoretical models, especially those derived by homology modeling techniques. While this greatly extended the use of docking simulations, it also introduced the need for general and robust criteria to estimate the reliability of docking results given the model quality. To this end, a large-scale experiment was performed on a diverse set including experimental structures and homology models for a group of representative ligand–protein complexes. A wide spectrum of model quality was sampled using templates at different evolutionary distances and different strategies for target–template alignment and modeling. The obtained models were scored by a selection of the most used model quality indices. The binding geometries were generated using AutoDock, one of the most common docking programs. An important result of this study is that indeed quantitative and robust correlations exist between the accuracy of docking results and the model quality, especially in the binding site. Moreover, state-of-the-art indices for model quality assessment are already an effective tool for an a priori prediction of the accuracy of docking experiments in the context of groups of proteins with conserved structural characteristics. PMID:20607693

Importance and Challenges in Use and Uptake of Air Quality Modelling in Developing Countries: Use of CAMx for Air Quality Management in the City of Johannesburg.

NASA Astrophysics Data System (ADS)

Garland, R. M.; Naidoo, M.; Sibiya, B.; Naidoo, S.; Bird, T.; von Gruenewaldt, R.; Liebenberg-Enslin, H.; Nekhwalivhe, M.; Netshandama, J.; Mahlatji, M.

2017-12-01

Ambient air pollution levels are regulated in South Africa; however in many areas pollution concentrations exceed these levels. The South African Air Quality Act also stipulates that government across all levels must have Air Quality Management Plans (AQMP) in place that outline the current state of air quality and emissions, as well as the implementable plan to manage, and where necessary improve, air quality. Historically, dispersion models have been used to support air quality management decisions, including in AQMPs. However, with the focus of air quality management shifting from focusing on industrial point sources to a more integrated and holistic management of all sources, chemical transport models are needed. CAMx was used in the review and development of the City of Johannesburg's AQMP to simulate hot spots of air pollution, as well as to model intervention scenarios. As the pollutants of concern in Johannesburg are ozone and particulate matter, it is critical to use a model that can simulate chemistry. CAMx was run at 1 km with a locally derived emissions inventory for 2014. The sources of pollution in the City are diverse (including, industrial, vehicles, domestic burning, natural), and many sources have large uncertainties in estimating emissions due to lack of necessary data and local emission factors. These uncertainties, together with a lack of measurements to validate the model against, hinder the performance of the model to simulate air quality and thus inform air quality management. However, as air quality worsens in Africa, it is critical for decision makers to have a strong evidence base on the state of air quality and impact of interventions in order to improve air quality effectively. This presentation will highlight the findings from using a chemical transport model for air quality management in the largest city in South Africa, the use and limitations of these for decision-makers, and proposed way forward.

Flight simulator fidelity assessment in a rotorcraft lateral translation maneuver

NASA Technical Reports Server (NTRS)

Hess, R. A.; Malsbury, T.; Atencio, A., Jr.

1992-01-01

A model-based methodology for assessing flight simulator fidelity in closed-loop fashion is exercised in analyzing a rotorcraft low-altitude maneuver for which flight test and simulation results were available. The addition of a handling qualities sensitivity function to a previously developed model-based assessment criteria allows an analytical comparison of both performance and handling qualities between simulation and flight test. Model predictions regarding the existence of simulator fidelity problems are corroborated by experiment. The modeling approach is used to assess analytically the effects of modifying simulator characteristics on simulator fidelity.

Note on Professor Sizer's Paper.

ERIC Educational Resources Information Center

Balderston, Frederick E.

1979-01-01

Issues suggested by John Sizer's paper, an overview of the assessment of institutional performance, include: the efficient-frontier approach, multiple-criterion decision-making models, performance analysis approached as path analysis, and assessment of academic quality. (JMD)

Structural Model for the Effects of Environmental Elements on the Psychological Characteristics and Performance of the Employees of Manufacturing Systems

PubMed Central

Realyvásquez, Arturo; Maldonado-Macías, Aidé Aracely; García-Alcaraz, Jorge; Cortés-Robles, Guillermo; Blanco-Fernández, Julio

2016-01-01

This paper analyzes the effects of environmental elements on the psychological characteristics and performance of employees in manufacturing systems using structural equation modeling. Increasing the comprehension of these effects may help optimize manufacturing systems regarding their employees’ psychological characteristics and performance from a macroergonomic perspective. As the method, a new macroergonomic compatibility questionnaire (MCQ) was developed and statistically validated, and 158 respondents at four manufacture companies were considered. Noise, lighting and temperature, humidity and air quality (THAQ) were used as independent variables and psychological characteristics and employees’ performance as dependent variables. To propose and test the hypothetical causal model of significant relationships among the variables, a data analysis was deployed. Results found that the macroergonomic compatibility of environmental elements presents significant direct effects on employees’ psychological characteristics and either direct or indirect effects on the employees’ performance. THAQ had the highest direct and total effects on psychological characteristics. Regarding the direct and total effects on employees’ performance, the psychological characteristics presented the highest effects, followed by THAQ conditions. These results may help measure and optimize manufacturing systems’ performance by enhancing their macroergonomic compatibility and quality of life at work of the employees. PMID:26742054

Structural Model for the Effects of Environmental Elements on the Psychological Characteristics and Performance of the Employees of Manufacturing Systems.

PubMed

Realyvásquez, Arturo; Maldonado-Macías, Aidé Aracely; García-Alcaraz, Jorge; Cortés-Robles, Guillermo; Blanco-Fernández, Julio

2016-01-05

This paper analyzes the effects of environmental elements on the psychological characteristics and performance of employees in manufacturing systems using structural equation modeling. Increasing the comprehension of these effects may help optimize manufacturing systems regarding their employees' psychological characteristics and performance from a macroergonomic perspective. As the method, a new macroergonomic compatibility questionnaire (MCQ) was developed and statistically validated, and 158 respondents at four manufacture companies were considered. Noise, lighting and temperature, humidity and air quality (THAQ) were used as independent variables and psychological characteristics and employees' performance as dependent variables. To propose and test the hypothetical causal model of significant relationships among the variables, a data analysis was deployed. Results found that the macroergonomic compatibility of environmental elements presents significant direct effects on employees' psychological characteristics and either direct or indirect effects on the employees' performance. THAQ had the highest direct and total effects on psychological characteristics. Regarding the direct and total effects on employees' performance, the psychological characteristics presented the highest effects, followed by THAQ conditions. These results may help measure and optimize manufacturing systems' performance by enhancing their macroergonomic compatibility and quality of life at work of the employees.

Dynamical aspects of behavior generation under constraints

PubMed Central

Harter, Derek; Achunala, Srinivas

2007-01-01

Dynamic adaptation is a key feature of brains helping to maintain the quality of their performance in the face of increasingly difficult constraints. How to achieve high-quality performance under demanding real-time conditions is an important question in the study of cognitive behaviors. Animals and humans are embedded in and constrained by their environments. Our goal is to improve the understanding of the dynamics of the interacting brain–environment system by studying human behaviors when completing constrained tasks and by modeling the observed behavior. In this article we present results of experiments with humans performing tasks on the computer under variable time and resource constraints. We compare various models of behavior generation in order to describe the observed human performance. Finally we speculate on mechanisms how chaotic neurodynamics can contribute to the generation of flexible human behaviors under constraints. PMID:19003514

[Application of quality by design in granulation process for ginkgo leaf tablet (Ⅱ)： identification of critical quality attributes].

PubMed

Xu, Bing; Cui, Xiang-Long; Yang, Chan; Wang, Xin; Shi, Xin-Yuan; Qiao, Yan-Jiang

2017-03-01

Quality by design (QbD) highlights the concept of "begin with the end", which means to thoroughly understand the target product quality first, and then guide pharmaceutical process development and quality control throughout the whole manufacturing process. In this paper, the Ginkgo biloba granules intermediates were taken as the research object, and the requirements of the tensile strength of tablets were treated as the goals to establish the methods for identification of granules' critical quality attributes (CQAs) and establishment of CQAs' limits. Firstly, the orthogonal partial least square (OPLS) model was adopted to build the relationship between the micromeritic properties of 29 batches of granules and the tensile strength of ginkgo leaf tablets, and thereby the potential critical quality attributes (pCQAs) were screened by variable importance in the projection (VIP) indexes. Then, a series of OPLS models were rebuilt by reducing pCQAs variables one by one in view of the rule of VIP values from low to high in sequence. The model performance results demonstrated that calibration and predictive performance of the model had no decreasing trend after variables reduction. In consideration of the results from variables selection as well as the collinearity test and testability of the pCQAs, the median particle size (D₅₀) and the bulk density (Da) were identified as critical quality attributes (CQAs). The design space of CQAs was developed based on a multiple linear regression model established between the CQAs (D₅₀ and Da) and the tensile strength. The control constraints of the CQAs were determined as 170 μm< D₅₀<500 μm and 0.30 g•cm⁻³

Criteria for assessing problem solving and decision making in complex environments

NASA Technical Reports Server (NTRS)

Orasanu, Judith

1993-01-01

Training crews to cope with unanticipated problems in high-risk, high-stress environments requires models of effective problem solving and decision making. Existing decision theories use the criteria of logical consistency and mathematical optimality to evaluate decision quality. While these approaches are useful under some circumstances, the assumptions underlying these models frequently are not met in dynamic time-pressured operational environments. Also, applying formal decision models is both labor and time intensive, a luxury often lacking in operational environments. Alternate approaches and criteria are needed. Given that operational problem solving and decision making are embedded in ongoing tasks, evaluation criteria must address the relation between those activities and satisfaction of broader task goals. Effectiveness and efficiency become relevant for judging reasoning performance in operational environments. New questions must be addressed: What is the relation between the quality of decisions and overall performance by crews engaged in critical high risk tasks? Are different strategies most effective for different types of decisions? How can various decision types be characterized? A preliminary model of decision types found in air transport environments will be described along with a preliminary performance model based on an analysis of 30 flight crews. The performance analysis examined behaviors that distinguish more and less effective crews (based on performance errors). Implications for training and system design will be discussed.

Measuring Quality in Special Libraries: Lessons from Service Marketing.

ERIC Educational Resources Information Center

White, Marilyn Domas; Abels, Eileen G.

1995-01-01

Surveys the service marketing literature for models and data-gathering instruments measuring service quality, particularly the instruments SERVQUAL and SERVPERF, and assesses their applicability to special libraries and information centers. Topics include service characteristics and definitions of service; performance-minus-expectations and…

Develop nondestructive rapid pavement quality assurance/quality control evaluation test methods and supporting technology : project summary.

DOT National Transportation Integrated Search

2017-01-01

The findings from the proof of concept with mechanics-based models for flexible base suggest additional validation work should be performed, draft construction specification frameworks should be developed, and work extending the technology to stabili...

Develop nondestructive rapid pavement quality Assurance/quality control evaluation test methods and supporting technology : project summary.

DOT National Transportation Integrated Search

2017-01-01

The findings from the proof of concept with mechanics-based models for flexible base suggest additional validation work should be performed, draft construction specification frameworks should be developed, and work extending the technology to stabili...

Quality measurement and improvement in liver transplantation.

PubMed

Mathur, Amit K; Talwalkar, Jayant

2018-06-01

There is growing interest in the quality of health care delivery in liver transplantation. Multiple stakeholders, including patients, transplant providers and their hospitals, payers, and regulatory bodies have an interest in measuring and monitoring quality in the liver transplant process, and understanding differences in quality across centres. This article aims to provide an overview of quality measurement and regulatory issues in liver transplantation performed within the United States. We review how broader definitions of health care quality should be applied to liver transplant care models. We outline the status quo including the current regulatory agencies, public reporting mechanisms, and requirements around quality assurance and performance improvement (QAPI) activities. Additionally, we further discuss unintended consequences and opportunities for growth in quality measurement. Quality measurement and the integration of quality improvement strategies into liver transplant programmes hold significant promise, but multiple challenges to successful implementation must be addressed to optimise value. Copyright © 2018 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Defining quality in radiology.

PubMed

Blackmore, C Craig

2007-04-01

The introduction of pay for performance in medicine represents an opportunity for radiologists to define quality in radiology. Radiology quality can be defined on the basis of the production model that currently drives reimbursement, codifying the role of radiologists as being limited to the production of timely and accurate radiology reports produced in conditions of maximum patient safety and communicated in a timely manner. Alternately, quality in radiology can also encompass the professional role of radiologists as diagnostic imaging specialists responsible for the appropriate use, selection, interpretation, and application of imaging. Although potentially challenging to implement, the professional model for radiology quality is a comprehensive assessment of the ways in which radiologists add value to patient care. This essay is a discussion of the definition of radiology quality and the implications of that definition.

Land use change and conversion effects on ground water quality trends: An integration of land change modeler in GIS and a new Ground Water Quality Index developed by fuzzy multi-criteria group decision-making models.

PubMed

Shooshtarian, Mohammad Reza; Dehghani, Mansooreh; Margherita, Ferrante; Gea, Oliveri Conti; Mortezazadeh, Shima

2018-04-01

This study aggregated Land Change Modeller (LCM) as a useful model in GIS with an extended Groundwater Quality Index (GWQI) developed by fuzzy Multi-Criteria Group Decision-Making models to investigate the effect of land use change and conversion on groundwater quality being supplied for drinking. The model's performance was examined through an applied study in Shiraz, Iran, in a five year period (2011 to 2015). Four land use maps including urban, industrial, garden, and bare were employed in LCM model and the impact of change in area and their conversion to each other on GWQI changes was analysed. The correlation analysis indicated that increase in the urban land use area and conversion of bare to the residential/industrial land uses, had a relation with water quality decrease. Integration of LCM and GWQI can accurately and logically provide a numerical analysis of the possible impact of land use change and conversion, as one of the influencing factors, on the groundwater quality. Hence, the methodology could be used in urban development planning and management in macro level. Copyright © 2018. Published by Elsevier Ltd.

Quantitative Guidance for Stove Usage and Performance to Achieve Health and Environmental Targets.

PubMed

Johnson, Michael A; Chiang, Ranyee A

2015-08-01

Displacing the use of polluting and inefficient cookstoves in developing countries is necessary to achieve the potential health and environmental benefits sought through clean cooking solutions. Yet little quantitative context has been provided on how much displacement of traditional technologies is needed to achieve targets for household air pollutant concentrations or fuel savings. This paper provides instructive guidance on the usage of cooking technologies required to achieve health and environmental improvements. We evaluated different scenarios of displacement of traditional stoves with use of higher performing technologies. The air quality and fuel consumption impacts were estimated for these scenarios using a single-zone box model of indoor air quality and ratios of thermal efficiency. Stove performance and usage should be considered together, as lower performing stoves can result in similar or greater benefits than a higher performing stove if the lower performing stove has considerably higher displacement of the baseline stove. Based on the indoor air quality model, there are multiple performance-usage scenarios for achieving modest indoor air quality improvements. To meet World Health Organization guidance levels, however, three-stone fire and basic charcoal stove usage must be nearly eliminated to achieve the particulate matter target (< 1-3 hr/week), and substantially limited to meet the carbon monoxide guideline (< 7-9 hr/week). Moderate health gains may be achieved with various performance-usage scenarios. The greatest benefits are estimated to be achieved by near-complete displacement of traditional stoves with clean technologies, emphasizing the need to shift in the long term to near exclusive use of clean fuels and stoves. The performance-usage scenarios are also provided as a tool to guide technology selection and prioritize behavior change opportunities to maximize impact.

Application of Wavelet Filters in an Evaluation of ...

EPA Pesticide Factsheets

Air quality model evaluation can be enhanced with time-scale specific comparisons of outputs and observations. For example, high-frequency (hours to one day) time scale information in observed ozone is not well captured by deterministic models and its incorporation into model performance metrics lead one to devote resources to stochastic variations in model outputs. In this analysis, observations are compared with model outputs at seasonal, weekly, diurnal and intra-day time scales. Filters provide frequency specific information that can be used to compare the strength (amplitude) and timing (phase) of observations and model estimates. The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollu

Electroacoustics modeling of piezoelectric welders for ultrasonic additive manufacturing processes

NASA Astrophysics Data System (ADS)

Hehr, Adam; Dapino, Marcelo J.

2016-04-01

Ultrasonic additive manufacturing (UAM) is a recent 3D metal printing technology which utilizes ultrasonic vibrations from high power piezoelectric transducers to additively weld similar and dissimilar metal foils. CNC machining is used intermittent of welding to create internal channels, embed temperature sensitive components, sensors, and materials, and for net shaping parts. Structural dynamics of the welder and work piece influence the performance of the welder and part quality. To understand the impact of structural dynamics on UAM, a linear time-invariant model is used to relate system shear force and electric current inputs to the system outputs of welder velocity and voltage. Frequency response measurements are combined with in-situ operating measurements of the welder to identify model parameters and to verify model assumptions. The proposed LTI model can enhance process consistency, performance, and guide the development of improved quality monitoring and control strategies.

Assessing the multidimensional and hierarchical structure of SERVQUAL.

PubMed

Ma, Jun; Harvey, Milton E; Hu, Michael Y

2007-10-01

Parasuraman, Zeithaml, and Berry introduced SERVQUAL in 1998 as a scale to measure service quality. Since then, researchers have proposed several variations. This study examines the development of the tool. Marketing researchers have first challenged the conceptualization of a perceptions-expectations gap and have concluded that the performance-based measures are adequate to capture consumers' perception of service quality. Some researchers have argued that the five dimensions of the SERVQUAL scale only focus on the process of service delivery and have extended the SERVQUAL scale into six dimensions by including the service outcome dimension. Others have proposed that service quality is a multilevel construct and should be measured accordingly. From a sample of 467 undergraduate students data on service quality toward up-scale restaurants were collected. Using the structural equation approach, two measurement models of service quality were compared, the extended SERVQUAL model and the restructured multilevel SERVQUAL model. Analysis suggested that the latter model fits the data better than the extended one.

Modeling prescribed burning experiments and assessing the fire impacts on local to regional air quality

NASA Astrophysics Data System (ADS)

Zhou, L.; Baker, K. R.; Napelenok, S. L.; Elleman, R. A.; Urbanski, S. P.

2016-12-01

Biomass burning, including wildfires and prescribed burns, strongly impact the global carbon cycle and are of increasing concern due to the potential impacts on ambient air quality. This modelling study focuses on the evolution of carbonaceous compounds during a prescribed burning experiment and assesses the impacts of burning on local to regional air quality. The Community Multiscale Air Quality (CMAQ) model is used to conduct 4 and 2 km grid resolution simulations of prescribed burning experiments in southeast Washington state and western Idaho state in summer 2013. The ground and airborne measurements from the field experiment are used to evaluate the model performance in capturing surface and aloft impacts from the burning events. Phase partitioning of organic compounds in the plume are studied as it is a crucial step towards understanding the fate of carbonaceous compounds. The sensitivities of ambient concentrations and deposition to emissions are conducted for organic carbon, elemental carbon and ozone to estimate the impacts of fire on air quality.

The effect of intramuscular fat on skeletal muscle mechanics: implications for the elderly and obese

PubMed Central

Rahemi, Hadi; Nigam, Nilima; Wakeling, James M.

2015-01-01

Skeletal muscle accumulates intramuscular fat through age and obesity. Muscle quality, a measure of muscle strength per unit size, decreases in these conditions. It is not clear how fat influences this loss in performance. Changes to structural parameters (e.g. fibre pennation and connective tissue properties) affect the muscle quality. This study investigated the mechanisms that lead to deterioration in muscle performance due to changes in intramuscular fat, pennation and aponeurosis stiffness. A finite-element model of the human gastrocnemius was developed as a fibre-reinforced composite biomaterial containing contractile fibres within the base material. The base-material properties were modified to include intramuscular fat in five different ways. All these models with fat generated lower fibre stress and muscle quality than their lean counterparts. This effect is due to the higher stiffness of the tissue in the fatty models. The fibre deformations influence their interactions with the aponeuroses, and these change with fatty inclusions. Muscles with more compliant aponeuroses generated lower forces. The muscle quality was further reduced for muscles with lower pennation. This study shows that whole-muscle force is dependent on its base-material properties and changes to the base material due to fatty inclusions result in reductions to force and muscle quality. PMID:26156300

Next level of board accountability in health care quality.

PubMed

Pronovost, Peter J; Armstrong, C Michael; Demski, Renee; Peterson, Ronald R; Rothman, Paul B

2018-03-19

Purpose The purpose of this paper is to offer six principles that health system leaders can apply to establish a governance and management system for the quality of care and patient safety. Design/methodology/approach Leaders of a large academic health system set a goal of high reliability and formed a quality board committee in 2011 to oversee quality and patient safety everywhere care was delivered. Leaders of the health system and every entity, including inpatient hospitals, home care companies, and ambulatory services staff the committee. The committee works with the management for each entity to set and achieve quality goals. Through this work, the six principles emerged to address management structures and processes. Findings The principles are: ensure there is oversight for quality everywhere care is delivered under the health system; create a framework to organize and report the work; identify care areas where quality is ambiguous or underdeveloped (i.e. islands of quality) and work to ensure there is reporting and accountability for quality measures; create a consolidated quality statement similar to a financial statement; ensure the integrity of the data used to measure and report quality and safety performance; and transparently report performance and create an explicit accountability model. Originality/value This governance and management system for quality and safety functions similar to a finance system, with quality performance documented and reported, data integrity monitored, and accountability for performance from board to bedside. To the authors' knowledge, this is the first description of how a board has taken this type of systematic approach to oversee the quality of care.

[Professional quality of life in the clinical governance model of Asturias (Spain)].

PubMed

Díaz Corte, Carmen; Suárez Álvarez, Óscar; Fueyo Gutiérrez, Alejandra; Mola Caballero de Rodas, Pablo; Rancaño García, Iván; Sánchez Fernández, Ana María; Suárez Gutiérrez, Rebeca; Díaz Vázquez, Carlos

2013-01-01

To evaluate professional quality of life in our clinical governance model by comparing differences according to the time since the model's implementation (1-3 years) and the setting (primary or hospital care). A cross-sectional descriptive study was performed. The 35-item, anonymous, self-administered Professional Quality of Life Questionnaire, with three additional questions, was applied. A minimum sample size for each clinical governance unit/area (CGU/CGA) was calculated. Descriptive, univariate and bivariate analyses were performed using the 35 items separately. The subscales of « management support », « workload » and « intrinsic motivation » were used as dependant variables, and the setting and time since implementation of the CGU/CGA as independent variables. Of the study population of 2572 professionals, 1395 (54%) responded (67% in primary care and 51% in hospital care). A total of 87% had been working for 5 years or more in their positions. Thirty-three percent had worked for less than a year in clinical governance. The item with the highest score was job training (8.39 ± 1.42) and that with the lowest was conflicts with peers (3.23 ± 2.2). Primary healthcare professionals showed better results in management support and quality of life at work and hospital professionals in workload. The clinical governance model obtained the best scores at 3 years and the worst at 1 year. These differences were especially favorable for clinical governance in hospitals: professionals working longer perceived a lower workload and more intrinsic motivation and quality of life. A longer time working in the clinical governance model was associated with better perception of professional quality of life, especially in hospital care. Copyright © 2012 SESPAS. Published by Elsevier Espana. All rights reserved.

Dimethylsulfide chemistry: annual, seasonal, and spatial impacts on SO_4^(2-)

EPA Science Inventory

We incorporated oceanic emissions and atmospheric chemistry of dimethylsulfide (DMS) into the hemispheric Community Multiscale Air Quality model and performed annual model simulations without and with DMS chemistry. The model without DMS chemistry predicts higher concentrations o...

No-Reference Image Quality Assessment by Wide-Perceptual-Domain Scorer Ensemble Method.

PubMed

Liu, Tsung-Jung; Liu, Kuan-Hsien

2018-03-01

A no-reference (NR) learning-based approach to assess image quality is presented in this paper. The devised features are extracted from wide perceptual domains, including brightness, contrast, color, distortion, and texture. These features are used to train a model (scorer) which can predict scores. The scorer selection algorithms are utilized to help simplify the proposed system. In the final stage, the ensemble method is used to combine the prediction results from selected scorers. Two multiple-scale versions of the proposed approach are also presented along with the single-scale one. They turn out to have better performances than the original single-scale method. Because of having features from five different domains at multiple image scales and using the outputs (scores) from selected score prediction models as features for multi-scale or cross-scale fusion (i.e., ensemble), the proposed NR image quality assessment models are robust with respect to more than 24 image distortion types. They also can be used on the evaluation of images with authentic distortions. The extensive experiments on three well-known and representative databases confirm the performance robustness of our proposed model.

Evaluation of the Community Multi-scale Air Quality (CMAQ) ...

EPA Pesticide Factsheets

The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Protection Agency develops the CMAQ model and periodically releases new versions of the model that include bug fixes and various other improvements to the modeling system. In the fall of 2015, CMAQ version 5.1 was released. This new version of CMAQ will contain important bug fixes to several issues that were identified in CMAQv5.0.2 and additionally include updates to other portions of the code. Several annual, and numerous episodic, CMAQv5.1 simulations were performed to assess the impact of these improvements on the model results. These results will be presented, along with a base evaluation of the performance of the CMAQv5.1 modeling system against available surface and upper-air measurements available during the time period simulated. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, proces

Breast cancer screening services: trade-offs in quality, capacity, outreach, and centralization.

PubMed

Güneş, Evrim D; Chick, Stephen E; Akşin, O Zeynep

2004-11-01

This work combines and extends previous work on breast cancer screening models by explicitly incorporating, for the first time, aspects of the dynamics of health care states, program outreach, and the screening volume-quality relationship in a service system model to examine the effect of public health policy and service capacity decisions on public health outcomes. We consider the impact of increasing standards for minimum reading volume to improve quality, expanding outreach with or without decentralization of service facilities, and the potential of queueing due to stochastic effects and limited capacity. The results indicate a strong relation between screening quality and the cost of screening and treatment, and emphasize the importance of accounting for service dynamics when assessing the performance of health care interventions. For breast cancer screening, increasing outreach without improving quality and maintaining capacity results in less benefit than predicted by standard models.

An interval programming model for continuous improvement in micro-manufacturing

NASA Astrophysics Data System (ADS)

Ouyang, Linhan; Ma, Yizhong; Wang, Jianjun; Tu, Yiliu; Byun, Jai-Hyun

2018-03-01

Continuous quality improvement in micro-manufacturing processes relies on optimization strategies that relate an output performance to a set of machining parameters. However, when determining the optimal machining parameters in a micro-manufacturing process, the economics of continuous quality improvement and decision makers' preference information are typically neglected. This article proposes an economic continuous improvement strategy based on an interval programming model. The proposed strategy differs from previous studies in two ways. First, an interval programming model is proposed to measure the quality level, where decision makers' preference information is considered in order to determine the weight of location and dispersion effects. Second, the proposed strategy is a more flexible approach since it considers the trade-off between the quality level and the associated costs, and leaves engineers a larger decision space through adjusting the quality level. The proposed strategy is compared with its conventional counterparts using an Nd:YLF laser beam micro-drilling process.

The impact of primary care reform on health system performance in Canada: a systematic review.

PubMed

Carter, Renee; Riverin, Bruno; Levesque, Jean-Frédéric; Gariepy, Geneviève; Quesnel-Vallée, Amélie

2016-07-30

We aimed to synthesize the evidence of a causal effect and draw inferences about whether Canadian primary care reforms improved health system performance based on measures of health service utilization, processes of care, and physician productivity. We searched the Embase, PubMed and Web of Science databases for records from 2000 to September 2015. We based our risk of bias assessment on the Grading of Recommendations Assessment, Development and Evaluation guidelines. Full-text studies were synthesized and organized according to the three outcome categories: health service utilization, processes of care, and physician costs and productivity. We found moderate quality evidence that team-based models of care led to reductions in emergency department use, but the evidence was mixed for hospital admissions. We also found low quality evidence that team-based models, blended capitation models and pay-for-performance incentives led to small and sometimes non-significant improvements in processes of care. Studies examining new payment models on physician costs and productivity were of high methodological quality and provided a coherent body of evidence assessing enhanced fee-for-service and blended capitation payment models. A small number of studies suggested that team-based models contributed to reductions in emergency department use in Quebec and Alberta. Regarding processes of diabetes care, studies found higher rates of testing for blood glucose levels, retinopathy and cholesterol in Alberta's team-based primary care model and in practices eligible for pay-for-performance incentives in Ontario. However pay-for-performance in Ontario was found to have null to moderate effects on other prevention and screening activities. Although blended capitation payment in Ontario contributed to decreases in the number of services delivered and patients seen per day, the number of enrolled patients and number of days worked in a year was similar to that of enhanced fee-for-service practices.

Evaluation of a two-dimensional numerical model for air quality simulation in a street canyon

NASA Astrophysics Data System (ADS)

Okamoto, Shin `Ichi; Lin, Fu Chi; Yamada, Hiroaki; Shiozawa, Kiyoshige

For many urban areas, the most severe air pollution caused by automobile emissions appears along a road surrounded by tall buildings: the so=called street canyon. A practical two-dimensional numerical model has been developed to be applied to this kind of road structure. This model contains two submodels: a wind-field model and a diffusion model based on a Monte Carlo particle scheme. In order to evaluate the predictive performance of this model, an air quality simulation was carried out at three trunk roads in the Tokyo metropolitan area: Nishi-Shimbashi, Aoyama and Kanda-Nishikicho (using SF 6 as a tracer and NO x measurement). Since this model has two-dimensional properties and cannot be used for the parallel wind condition, the perpendicular wind condition was selected for the simulation. The correlation coefficients for the SF 6 and NO x data in Aoyama were 0.67 and 0.62, respectively. When predictive performance of this model is compared with other models, this model is comparable to the SRI model, and superior to the APPS three-dimensional numerical model.

Lower- Versus Higher-Income Populations In The Alternative Quality Contract: Improved Quality And Similar Spending.

PubMed

Song, Zirui; Rose, Sherri; Chernew, Michael E; Safran, Dana Gelb

2017-01-01

As population-based payment models become increasingly common, it is crucial to understand how such payment models affect health disparities. We evaluated health care quality and spending among enrollees in areas with lower versus higher socioeconomic status in Massachusetts before and after providers entered into the Alternative Quality Contract, a two-sided population-based payment model with substantial incentives tied to quality. We compared changes in process measures, outcome measures, and spending between enrollees in areas with lower and higher socioeconomic status from 2006 to 2012 (outcome measures were measured after the intervention only). Quality improved for all enrollees in the Alternative Quality Contract after their provider organizations entered the contract. Process measures improved 1.2 percentage points per year more among enrollees in areas with lower socioeconomic status than among those in areas with higher socioeconomic status. Outcome measure improvement was no different between the subgroups; neither were changes in spending. Larger or comparable improvements in quality among enrollees in areas with lower socioeconomic status suggest a potential narrowing of disparities. Strong pay-for-performance incentives within a population-based payment model could encourage providers to focus on improving quality for more disadvantaged populations. Project HOPE—The People-to-People Health Foundation, Inc.

Modeling and performance assessment in QinetiQ of EO and IR airborne reconnaissance systems

NASA Astrophysics Data System (ADS)

Williams, John W.; Potter, Gary E.

2002-11-01

QinetiQ are the technical authority responsible for specifying the performance requirements for the procurement of airborne reconnaissance systems, on behalf of the UK MoD. They are also responsible for acceptance of delivered systems, overseeing and verifying the installed system performance as predicted and then assessed by the contractor. Measures of functional capability are central to these activities. The conduct of these activities utilises the broad technical insight and wide range of analysis tools and models available within QinetiQ. This paper focuses on the tools, methods and models that are applicable to systems based on EO and IR sensors. The tools, methods and models are described, and representative output for systems that QinetiQ has been responsible for is presented. The principle capability applicable to EO and IR airborne reconnaissance systems is the STAR (Simulation Tools for Airborne Reconnaissance) suite of models. STAR generates predictions of performance measures such as GRD (Ground Resolved Distance) and GIQE (General Image Quality) NIIRS (National Imagery Interpretation Rating Scales). It also generates images representing sensor output, using the scene generation software CAMEO-SIM and the imaging sensor model EMERALD. The simulated image 'quality' is fully correlated with the predicted non-imaging performance measures. STAR also generates image and table data that is compliant with STANAG 7023, which may be used to test ground station functionality.

A Random Walk in the Park: An Individual-Based Null Model for Behavioral Thermoregulation.

PubMed

Vickers, Mathew; Schwarzkopf, Lin

2016-04-01

Behavioral thermoregulators leverage environmental temperature to control their body temperature. Habitat thermal quality therefore dictates the difficulty and necessity of precise thermoregulation, and the quality of behavioral thermoregulation in turn impacts organism fitness via the thermal dependence of performance. Comparing the body temperature of a thermoregulator with a null (non-thermoregulating) model allows us to estimate habitat thermal quality and the effect of behavioral thermoregulation on body temperature. We define a null model for behavioral thermoregulation that is a random walk in a temporally and spatially explicit thermal landscape. Predicted body temperature is also integrated through time, so recent body temperature history, environmental temperature, and movement influence current body temperature; there is no particular reliance on an organism's equilibrium temperature. We develop a metric called thermal benefit that equates body temperature to thermally dependent performance as a proxy for fitness. We measure thermal quality of two distinct tropical habitats as a temporally dynamic distribution that is an ergodic property of many random walks, and we compare it with the thermal benefit of real lizards in both habitats. Our simple model focuses on transient body temperature; as such, using it we observe such subtleties as shifts in the thermoregulatory effort and investment of lizards throughout the day, from thermoregulators to thermoconformers.

Santa Margarita Estuary Water Quality Monitoring Data

DTIC Science & Technology

2018-02-01

ADMINISTRATIVE INFORMATION The work described in this report was performed for the Water Quality Section of the Environmental Security Marine Corps Base...water quality model calibration given interest and the necessary resources. The dataset should also inform the stakeholders and Regional Board on...period. Several additional ancillary datasets were collected during the monitoring timeframe that provide key information though they were not collected

Citizen Perceptions of Government Service Quality: Evidence from Public Schools. Program on Education Policy and Governance Working Papers Series. PEPG 10-16

ERIC Educational Resources Information Center

Chingos, Matthew M.; Henderson, Michael; West, Martin R.

2010-01-01

Conventional models of democratic accountability hinge on citizens' ability to evaluate government performance accurately, yet there is little evidence on the degree to which citizen perceptions of the quality of government services correspond to actual service quality. Using nationally representative survey data, we find that citizens'…

Factors Influencing Team Performance in a Continuous Quality Improvement Process in the Wisconsin Technical College System

ERIC Educational Resources Information Center

Pietz, Victoria Lynn

2014-01-01

Continuous Quality Improvement (CQI) programs are growing in popularity in higher education settings and a key component is the use of work groups, which require active employee involvement. The problem addressed in this research was the lack of employee engagement in the Quality Review Process (QRP), which is a statewide CQI model developed by…

Video quality assessment method motivated by human visual perception

NASA Astrophysics Data System (ADS)

He, Meiling; Jiang, Gangyi; Yu, Mei; Song, Yang; Peng, Zongju; Shao, Feng

2016-11-01

Research on video quality assessment (VQA) plays a crucial role in improving the efficiency of video coding and the performance of video processing. It is well acknowledged that the motion energy model generates motion energy responses in a middle temporal area by simulating the receptive field of neurons in V1 for the motion perception of the human visual system. Motivated by the biological evidence for the visual motion perception, a VQA method is proposed in this paper, which comprises the motion perception quality index and the spatial index. To be more specific, the motion energy model is applied to evaluate the temporal distortion severity of each frequency component generated from the difference of Gaussian filter bank, which produces the motion perception quality index, and the gradient similarity measure is used to evaluate the spatial distortion of the video sequence to get the spatial quality index. The experimental results of the LIVE, CSIQ, and IVP video databases demonstrate that the random forests regression technique trained by the generated quality indices is highly correspondent to human visual perception and has many significant improvements than comparable well-performing methods. The proposed method has higher consistency with subjective perception and higher generalization capability.

A Five-Year CMAQ PM2.5 Model Performance for Wildfires and Prescribed Fires

NASA Astrophysics Data System (ADS)

Wilkins, J. L.; Pouliot, G.; Foley, K.; Rappold, A.; Pierce, T. E.

2016-12-01

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissions inventory. However, there is a large amount of uncertainty in the development of these emission inventory sectors. We have completed a 5 year set of CMAQ model simulations (2008-2012) in which we have simulated regional air quality with and without the wildfire and prescribed fire inventory. We will examine CMAQ model performance over regions with significant PM2.5 and Ozone contribution from prescribed fires and wildfires. We will also review plume rise to see how it affects model bias and compare CMAQ current fire emissions input to an hourly dataset from FLAMBE.

AQMEII3: the EU and NA regional scale program of the ...

EPA Pesticide Factsheets

The presentation builds on the work presented last year at the 14th CMAS meeting and it is applied to the work performed in the context of the AQMEII-HTAP collaboration. The analysis is conducted within the framework of the third phase of AQMEII (Air Quality Model Evaluation International Initiative) and encompasses the gauging of model performance through measurement-to-model comparison, error decomposition and time series analysis of the models biases. Through the comparison of several regional-scale chemistry transport modelling systems applied to simulate meteorology and air quality over two continental areas, this study aims at i) apportioning the error to the responsible processes through time-scale analysis, and ii) help detecting causes of models error, and iii) identify the processes and scales most urgently requiring dedicated investigations. The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while the apportioning of the error into its constituent parts (bias, variance and covariance) can help assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the previous phases of AQMEII. The National Exposure Research Laboratory (NERL) Computational Exposur

ProQ3: Improved model quality assessments using Rosetta energy terms

PubMed Central

Uziela, Karolis; Shu, Nanjiang; Wallner, Björn; Elofsson, Arne

2016-01-01

Quality assessment of protein models using no other information than the structure of the model itself has been shown to be useful for structure prediction. Here, we introduce two novel methods, ProQRosFA and ProQRosCen, inspired by the state-of-art method ProQ2, but using a completely different description of a protein model. ProQ2 uses contacts and other features calculated from a model, while the new predictors are based on Rosetta energies: ProQRosFA uses the full-atom energy function that takes into account all atoms, while ProQRosCen uses the coarse-grained centroid energy function. The two new predictors also include residue conservation and terms corresponding to the agreement of a model with predicted secondary structure and surface area, as in ProQ2. We show that the performance of these predictors is on par with ProQ2 and significantly better than all other model quality assessment programs. Furthermore, we show that combining the input features from all three predictors, the resulting predictor ProQ3 performs better than any of the individual methods. ProQ3, ProQRosFA and ProQRosCen are freely available both as a webserver and stand-alone programs at http://proq3.bioinfo.se/. PMID:27698390

Development of a simulation model of semi-active suspension for monorail

NASA Astrophysics Data System (ADS)

Hasnan, K.; Didane, D. H.; Kamarudin, M. A.; Bakhsh, Qadir; Abdulmalik, R. E.

2016-11-01

The new Kuala Lumpur Monorail Fleet Expansion Project (KLMFEP) uses semiactive technology in its suspension system. It is recognized that the suspension system influences the ride quality. Thus, among the way to further improve the ride quality is by fine- tuning the semi-active suspension system on the new KL Monorail. The semi-active suspension for the monorail specifically in terms of improving ride quality could be exploited further. Hence a simulation model which will act as a platform to test the design of a complete suspension system particularly to investigate the ride comfort performance is required. MSC Adams software was considered as the tool to develop the simulation platform, where all parameters and data are represented by mathematical equations; whereas the new KL Monorail being the reference model. In the simulation, the model went through step disturbance on the guideway for stability and ride comfort analysis. The model has shown positive results where the monorail is in stable condition as an outcome from stability analysis. The model also scores a Rating 1 classification in ISO 2631 Ride Comfort performance which is very comfortable as an overall outcome from ride comfort analysis. The model is also adjustable, flexibile and understandable by the engineers within the field for the purpose of further development.

Intelligent sensing sensory quality of Chinese rice wine using near infrared spectroscopy and nonlinear tools.

PubMed

Ouyang, Qin; Chen, Quansheng; Zhao, Jiewen

2016-02-05

The approach presented herein reports the application of near infrared (NIR) spectroscopy, in contrast with human sensory panel, as a tool for estimating Chinese rice wine quality; concretely, to achieve the prediction of the overall sensory scores assigned by the trained sensory panel. Back propagation artificial neural network (BPANN) combined with adaptive boosting (AdaBoost) algorithm, namely BP-AdaBoost, as a novel nonlinear algorithm, was proposed in modeling. First, the optimal spectra intervals were selected by synergy interval partial least square (Si-PLS). Then, BP-AdaBoost model based on the optimal spectra intervals was established, called Si-BP-AdaBoost model. These models were optimized by cross validation, and the performance of each final model was evaluated according to correlation coefficient (Rp) and root mean square error of prediction (RMSEP) in prediction set. Si-BP-AdaBoost showed excellent performance in comparison with other models. The best Si-BP-AdaBoost model was achieved with Rp=0.9180 and RMSEP=2.23 in the prediction set. It was concluded that NIR spectroscopy combined with Si-BP-AdaBoost was an appropriate method for the prediction of the sensory quality in Chinese rice wine. Copyright © 2015 Elsevier B.V. All rights reserved.

Numerical Simulation of Pollutants' Transport and Fate in AN Unsteady Flow in Lower Bear River, Box Elder County, Utah

NASA Astrophysics Data System (ADS)

Salha, A. A.; Stevens, D. K.

2013-12-01

This study presents numerical application and statistical development of Stream Water Quality Modeling (SWQM) as a tool to investigate, manage, and research the transport and fate of water pollutants in Lower Bear River, Box elder County, Utah. The concerned segment under study is the Bear River starting from Cutler Dam to its confluence with the Malad River (Subbasin HUC 16010204). Water quality problems arise primarily from high phosphorus and total suspended sediment concentrations that were caused by five permitted point source discharges and complex network of canals and ducts of varying sizes and carrying capacities that transport water (for farming and agriculture uses) from Bear River and then back to it. Utah Department of Environmental Quality (DEQ) has designated the entire reach of the Bear River between Cutler Reservoir and Great Salt Lake as impaired. Stream water quality modeling (SWQM) requires specification of an appropriate model structure and process formulation according to nature of study area and purpose of investigation. The current model is i) one dimensional (1D), ii) numerical, iii) unsteady, iv) mechanistic, v) dynamic, and vi) spatial (distributed). The basic principle during the study is using mass balance equations and numerical methods (Fickian advection-dispersion approach) for solving the related partial differential equations. Model error decreases and sensitivity increases as a model becomes more complex, as such: i) uncertainty (in parameters, data input and model structure), and ii) model complexity, will be under investigation. Watershed data (water quality parameters together with stream flow, seasonal variations, surrounding landscape, stream temperature, and points/nonpoint sources) were obtained majorly using the HydroDesktop which is a free and open source GIS enabled desktop application to find, download, visualize, and analyze time series of water and climate data registered with the CUAHSI Hydrologic Information System. Processing, assessment of validity, and distribution of time-series data was explored using the GNU R language (statistical computing and graphics environment). Physical, chemical, and biological processes equations were written in FORTRAN codes (High Performance Fortran) in order to compute and solve their hyperbolic and parabolic complexities. Post analysis of results conducted using GNU R language. High performance computing (HPC) will be introduced to expedite solving complex computational processes using parallel programming. It is expected that the model will assess nonpoint sources and specific point sources data to understand pollutants' causes, transfer, dispersion, and concentration in different locations of Bear River. Investigation the impact of reduction/removal in non-point nutrient loading to Bear River water quality management could be addressed. Keywords: computer modeling; numerical solutions; sensitivity analysis; uncertainty analysis; ecosystem processes; high Performance computing; water quality.

Preliminary simulation of an advanced, hingless rotor XV-15 tilt-rotor aircraft

NASA Technical Reports Server (NTRS)

Mcveigh, M. A.

1976-01-01

The feasibility of the tilt-rotor concept was verified through investigation of the performance, stability and handling qualities of the XV-15 tilt rotor. The rotors were replaced by advanced-technology fiberglass/composite hingless rotors of larger diameter, combined with an advanced integrated fly-by-wire control system. A parametric simulation model of the HRXV-15 was developed, model was used to define acceptable preliminary ranges of primary and secondary control schedules as functions of the flight parameters, to evaluate performance, flying qualities and structural loads, and to have a Boeing-Vertol pilot conduct a simulated flight test evaluation of the aircraft.

THE STORM WATER MANAGEMENT MODEL (SWMM) AND RELATED WATERSHED TOOLS DEVELOPMENT

EPA Science Inventory

The Storm Water Management Model (SWMM) is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. It is the only publicly available model capable of performing a comprehensiv...

Application of Wavelet Filters in an Evaluation of Photochemical Model Performance

EPA Science Inventory

Air quality model evaluation can be enhanced with time-scale specific comparisons of outputs and observations. For example, high-frequency (hours to one day) time scale information in observed ozone is not well captured by deterministic models and its incorporation into model pe...

The Mediating Effect of Kaizen between Total Quality Management (TQM) and Business Performance

NASA Astrophysics Data System (ADS)

Shan, Ang Wei; Fauzi Ahmad, Mohd; Hisyamudin Muhd Nor, Nik

2016-11-01

Every customer preference is different but yet important. The global market is shifting rapidly, organizations are needed to continuously identify new opportunity to obtain competitive advantages. Literature suggested that manufacturing companies are needed to differentiate themselves through emphasize on quality and continuous improvement in product and services as a crucial part to secure and success in the future. The Total Quality Management (TQM) practices has developed a strong bearing on growth and competitiveness in market. Therefore, a proper continuous improvement (Kaizen) practice is needed to eliminate waste and value added in production to remain competitiveness and retained the potential customer. However, based on the previous study it had indicated an inconsistent result between TQM and BP. Besides that, researcher also less emphasized on mediator in previous work. Therefore, the purpose of this paper is to recommend the relationship between TQM and business performance with a mediator's effect of Kaizen. This proposed model attempt to create knowledge to both academician and company players to acquire a better understanding among the TQM and Kaizen practices. Consequently, the Structural Equation Modelling (SEM) techniques is applying to identify and evaluate the relationship among TQM, Kaizen, and business performance in developing a new TQM model.

Quality assurance and organizational effectiveness in hospitals.

PubMed Central

Hetherington, R W

1982-01-01

The purpose of this paper is to explore some aspects of a general theoretical model within which research on the organizational impacts of quality assurance programs in hospitals may be examined. Quality assurance is conceptualized as an organizational control mechanism, operating primarily through increased formalization of structures and specification of procedures. Organizational effectiveness is discussed from the perspective of the problem-solving theory of organizations, wherein effective organizations are those which maintain at least average performance in all four system problem areas simultaneously (goal-attainment, integration, adaptation and pattern-maintenance). It is proposed that through the realization of mutual benefits for both professionals and the bureaucracy, quality assurance programs can maximize such effective performance in hospitals. PMID:7096096

Artificial neural network modeling of dissolved oxygen in reservoir.

PubMed

Chen, Wei-Bo; Liu, Wen-Cheng

2014-02-01

The water quality of reservoirs is one of the key factors in the operation and water quality management of reservoirs. Dissolved oxygen (DO) in water column is essential for microorganisms and a significant indicator of the state of aquatic ecosystems. In this study, two artificial neural network (ANN) models including back propagation neural network (BPNN) and adaptive neural-based fuzzy inference system (ANFIS) approaches and multilinear regression (MLR) model were developed to estimate the DO concentration in the Feitsui Reservoir of northern Taiwan. The input variables of the neural network are determined as water temperature, pH, conductivity, turbidity, suspended solids, total hardness, total alkalinity, and ammonium nitrogen. The performance of the ANN models and MLR model was assessed through the mean absolute error, root mean square error, and correlation coefficient computed from the measured and model-simulated DO values. The results reveal that ANN estimation performances were superior to those of MLR. Comparing to the BPNN and ANFIS models through the performance criteria, the ANFIS model is better than the BPNN model for predicting the DO values. Study results show that the neural network particularly using ANFIS model is able to predict the DO concentrations with reasonable accuracy, suggesting that the neural network is a valuable tool for reservoir management in Taiwan.

Empirical evaluation of humpback whale telomere length estimates; quality control and factors causing variability in the singleplex and multiplex qPCR methods.

PubMed

Olsen, Morten Tange; Bérubé, Martine; Robbins, Jooke; Palsbøll, Per J

2012-09-06

Telomeres, the protective cap of chromosomes, have emerged as powerful markers of biological age and life history in model and non-model species. The qPCR method for telomere length estimation is one of the most common methods for telomere length estimation, but has received recent critique for being too error-prone and yielding unreliable results. This critique coincides with an increasing awareness of the potentials and limitations of the qPCR technique in general and the proposal of a general set of guidelines (MIQE) for standardization of experimental, analytical, and reporting steps of qPCR. In order to evaluate the utility of the qPCR method for telomere length estimation in non-model species, we carried out four different qPCR assays directed at humpback whale telomeres, and subsequently performed a rigorous quality control to evaluate the performance of each assay. Performance differed substantially among assays and only one assay was found useful for telomere length estimation in humpback whales. The most notable factors causing these inter-assay differences were primer design and choice of using singleplex or multiplex assays. Inferred amplification efficiencies differed by up to 40% depending on assay and quantification method, however this variation only affected telomere length estimates in the worst performing assays. Our results suggest that seemingly well performing qPCR assays may contain biases that will only be detected by extensive quality control. Moreover, we show that the qPCR method for telomere length estimation can be highly precise and accurate, and thus suitable for telomere measurement in non-model species, if effort is devoted to optimization at all experimental and analytical steps. We conclude by highlighting a set of quality controls which may serve for further standardization of the qPCR method for telomere length estimation, and discuss some of the factors that may cause variation in qPCR experiments.

Empirical evaluation of humpback whale telomere length estimates; quality control and factors causing variability in the singleplex and multiplex qPCR methods

PubMed Central

2012-01-01

Background Telomeres, the protective cap of chromosomes, have emerged as powerful markers of biological age and life history in model and non-model species. The qPCR method for telomere length estimation is one of the most common methods for telomere length estimation, but has received recent critique for being too error-prone and yielding unreliable results. This critique coincides with an increasing awareness of the potentials and limitations of the qPCR technique in general and the proposal of a general set of guidelines (MIQE) for standardization of experimental, analytical, and reporting steps of qPCR. In order to evaluate the utility of the qPCR method for telomere length estimation in non-model species, we carried out four different qPCR assays directed at humpback whale telomeres, and subsequently performed a rigorous quality control to evaluate the performance of each assay. Results Performance differed substantially among assays and only one assay was found useful for telomere length estimation in humpback whales. The most notable factors causing these inter-assay differences were primer design and choice of using singleplex or multiplex assays. Inferred amplification efficiencies differed by up to 40% depending on assay and quantification method, however this variation only affected telomere length estimates in the worst performing assays. Conclusion Our results suggest that seemingly well performing qPCR assays may contain biases that will only be detected by extensive quality control. Moreover, we show that the qPCR method for telomere length estimation can be highly precise and accurate, and thus suitable for telomere measurement in non-model species, if effort is devoted to optimization at all experimental and analytical steps. We conclude by highlighting a set of quality controls which may serve for further standardization of the qPCR method for telomere length estimation, and discuss some of the factors that may cause variation in qPCR experiments. PMID:22954451

Research on Holographic Evaluation of Service Quality in Power Data Network

NASA Astrophysics Data System (ADS)

Wei, Chen; Jing, Tao; Ji, Yutong

2018-01-01

With the rapid development of power data network, the continuous development of the Power data application service system, more and more service systems are being put into operation. Following this, the higher requirements for network quality and service quality are raised, in the actual process for the network operation and maintenance. This paper describes the electricity network and data network services status. A holographic assessment model was presented to achieve a comprehensive intelligence assessment on the power data network and quality of service in the operation and maintenance on the power data network. This evaluation method avoids the problems caused by traditional means which performs a single assessment of network performance quality. This intelligent Evaluation method can improve the efficiency of network operation and maintenance guarantee the quality of real-time service in the power data network..

Quality assessment of protein model-structures based on structural and functional similarities.

PubMed

Konopka, Bogumil M; Nebel, Jean-Christophe; Kotulska, Malgorzata

2012-09-21

Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. GOBA--Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and one of CASP9, compared to the contest participants. Consequently, GOBA offers a novel single model quality assessment program that addresses the practical needs of biologists. In conjunction with other Model Quality Assessment Programs (MQAPs), it would prove useful for the evaluation of single protein models.

Near infrared spectroscopy based monitoring of extraction processes of raw material with the help of dynamic predictive modeling

NASA Astrophysics Data System (ADS)

Wang, Haixia; Suo, Tongchuan; Wu, Xiaolin; Zhang, Yue; Wang, Chunhua; Yu, Heshui; Li, Zheng

2018-03-01

The control of batch-to-batch quality variations remains a challenging task for pharmaceutical industries, e.g., traditional Chinese medicine (TCM) manufacturing. One difficult problem is to produce pharmaceutical products with consistent quality from raw material of large quality variations. In this paper, an integrated methodology combining the near infrared spectroscopy (NIRS) and dynamic predictive modeling is developed for the monitoring and control of the batch extraction process of licorice. With the spectra data in hand, the initial state of the process is firstly estimated with a state-space model to construct a process monitoring strategy for the early detection of variations induced by the initial process inputs such as raw materials. Secondly, the quality property of the end product is predicted at the mid-course during the extraction process with a partial least squares (PLS) model. The batch-end-time (BET) is then adjusted accordingly to minimize the quality variations. In conclusion, our study shows that with the help of the dynamic predictive modeling, NIRS can offer the past and future information of the process, which enables more accurate monitoring and control of process performance and product quality.

A fuzzy-logic based decision-making approach for identification of groundwater quality based on groundwater quality indices.

PubMed

Vadiati, M; Asghari-Moghaddam, A; Nakhaei, M; Adamowski, J; Akbarzadeh, A H

2016-12-15

Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, specifically fuzzy inference systems, have proven useful in evaluating groundwater quality in uncertain and complex hydrogeological systems. In the present study, a Mamdani fuzzy-logic-based decision-making approach was developed to assess groundwater quality based on relevant indices. In an effort to develop a set of new hybrid fuzzy indices for groundwater quality assessment, a Mamdani fuzzy inference model was developed with widely-accepted groundwater quality indices: the Groundwater Quality Index (GQI), the Water Quality Index (WQI), and the Ground Water Quality Index (GWQI). In an effort to present generalized hybrid fuzzy indices a significant effort was made to employ well-known groundwater quality index acceptability ranges as fuzzy model output ranges rather than employing expert knowledge in the fuzzification of output parameters. The proposed approach was evaluated for its ability to assess the drinking water quality of 49 samples collected seasonally from groundwater resources in Iran's Sarab Plain during 2013-2014. Input membership functions were defined as "desirable", "acceptable" and "unacceptable" based on expert knowledge and the standard and permissible limits prescribed by the World Health Organization. Output data were categorized into multiple categories based on the GQI (5 categories), WQI (5 categories), and GWQI (3 categories). Given the potential of fuzzy models to minimize uncertainties, hybrid fuzzy-based indices produce significantly more accurate assessments of groundwater quality than traditional indices. The developed models' accuracy was assessed and a comparison of the performance indices demonstrated the Fuzzy Groundwater Quality Index model to be more accurate than both the Fuzzy Water Quality Index and Fuzzy Ground Water Quality Index models. This suggests that the new hybrid fuzzy indices developed in this research are reliable and flexible when used in groundwater quality assessment for drinking purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

A method of groundwater quality assessment based on fuzzy network-CANFIS and geographic information system (GIS)

NASA Astrophysics Data System (ADS)

Gholami, V.; Khaleghi, M. R.; Sebghati, M.

2017-11-01

The process of water quality testing is money/time-consuming, quite important and difficult stage for routine measurements. Therefore, use of models has become commonplace in simulating water quality. In this study, the coactive neuro-fuzzy inference system (CANFIS) was used to simulate groundwater quality. Further, geographic information system (GIS) was used as the pre-processor and post-processor tool to demonstrate spatial variation of groundwater quality. All important factors were quantified and groundwater quality index (GWQI) was developed. The proposed model was trained and validated by taking a case study of Mazandaran Plain located in northern part of Iran. The factors affecting groundwater quality were the input variables for the simulation, whereas GWQI index was the output. The developed model was validated to simulate groundwater quality. Network validation was performed via comparison between the estimated and actual GWQI values. In GIS, the study area was separated to raster format in the pixel dimensions of 1 km and also by incorporation of input data layers of the Fuzzy Network-CANFIS model; the geo-referenced layers of the effective factors in groundwater quality were earned. Therefore, numeric values of each pixel with geographical coordinates were entered to the Fuzzy Network-CANFIS model and thus simulation of groundwater quality was accessed in the study area. Finally, the simulated GWQI indices using the Fuzzy Network-CANFIS model were entered into GIS, and hence groundwater quality map (raster layer) based on the results of the network simulation was earned. The study's results confirm the high efficiency of incorporation of neuro-fuzzy techniques and GIS. It is also worth noting that the general quality of the groundwater in the most studied plain is fairly low.

Combined risk assessment of nonstationary monthly water quality based on Markov chain and time-varying copula.

PubMed

Shi, Wei; Xia, Jun

2017-02-01

Water quality risk management is a global hot research linkage with the sustainable water resource development. Ammonium nitrogen (NH 3 -N) and permanganate index (COD Mn ) as the focus indicators in Huai River Basin, are selected to reveal their joint transition laws based on Markov theory. The time-varying moments model with either time or land cover index as explanatory variables is applied to build the time-varying marginal distributions of water quality time series. Time-varying copula model, which takes the non-stationarity in the marginal distribution and/or the time variation in dependence structure between water quality series into consideration, is constructed to describe a bivariate frequency analysis for NH 3 -N and COD Mn series at the same monitoring gauge. The larger first-order Markov joint transition probability indicates water quality state Class V w , Class IV and Class III will occur easily in the water body of Bengbu Sluice. Both marginal distribution and copula models are nonstationary, and the explanatory variable time yields better performance than land cover index in describing the non-stationarities in the marginal distributions. In modelling the dependence structure changes, time-varying copula has a better fitting performance than the copula with the constant or the time-trend dependence parameter. The largest synchronous encounter risk probability of NH 3 -N and COD Mn simultaneously reaching Class V is 50.61%, while the asynchronous encounter risk probability is largest when NH 3 -N and COD Mn is inferior to class V and class IV water quality standards, respectively.

Hospital implementation of health information technology and quality of care: are they related?

PubMed

Restuccia, Joseph D; Cohen, Alan B; Horwitt, Jedediah N; Shwartz, Michael

2012-09-27

Recently, there has been considerable effort to promote the use of health information technology (HIT) in order to improve health care quality. However, relatively little is known about the extent to which HIT implementation is associated with hospital patient care quality. We undertook this study to determine the association of various HITs with: hospital quality improvement (QI) practices and strategies; adherence to process of care measures; risk-adjusted inpatient mortality; patient satisfaction; and assessment of patient care quality by hospital quality managers and front-line clinicians. We conducted surveys of quality managers and front-line clinicians (physicians and nurses) in 470 short-term, general hospitals to obtain data on hospitals' extent of HIT implementation, QI practices and strategies, assessments of quality performance, commitment to quality, and sufficiency of resources for QI. Of the 470 hospitals, 401 submitted complete data necessary for analysis. We also developed measures of hospital performance from several publicly data available sources: Hospital Compare adherence to process of care measures; Medicare Provider Analysis and Review (MEDPAR) file; and Hospital Consumer Assessment of Healthcare Providers and Systems HCAHPS® survey. We used Poisson regression analysis to examine the association between HIT implementation and QI practices and strategies, and general linear models to examine the relationship between HIT implementation and hospital performance measures. Controlling for potential confounders, we found that hospitals with high levels of HIT implementation engaged in a statistically significant greater number of QI practices and strategies, and had significantly better performance on mortality rates, patient satisfaction measures, and assessments of patient care quality by hospital quality managers; there was weaker evidence of higher assessments of patient care quality by front-line clinicians. Hospital implementation of HIT was positively associated with activities intended to improve patient care quality and with higher performance on four of six performance measures.

Quality-based financial incentives in health care: can we improve quality by paying for it?

PubMed

Conrad, Douglas A; Perry, Lisa

2009-01-01

This article asks whether financial incentives can improve the quality of health care. A conceptual framework drawn from microeconomics, agency theory, behavioral economics, and cognitive psychology motivates a set of propositions about incentive effects on clinical quality. These propositions are evaluated through a synthesis of extant peer-reviewed empirical evidence. Comprehensive financial incentives--balancing rewards and penalties; blending structure, process, and outcome measures; emphasizing continuous, absolute performance standards; tailoring the size of incremental rewards to increasing marginal costs of quality improvement; and assuring certainty, frequency, and sustainability of incentive payoffs--offer the prospect of significantly enhancing quality beyond the modest impacts of prevailing pay-for-performance (P4P) programs. Such organizational innovations as the primary care medical home and accountable health care organizations are expected to catalyze more powerful quality incentive models: risk- and quality-adjusted capitation, episode of care payments, and enhanced fee-for-service payments for quality dimensions (e.g., prevention) most amenable to piece-rate delivery.

Quality-Related Monitoring and Grading of Granulated Products by Weibull-Distribution Modeling of Visual Images with Semi-Supervised Learning.

PubMed

Liu, Jinping; Tang, Zhaohui; Xu, Pengfei; Liu, Wenzhong; Zhang, Jin; Zhu, Jianyong

2016-06-29

The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products, fabric textiles, are comprised of a large number of independent particles or stochastically stacking locally homogeneous fragments, whose analysis and understanding remains challenging. A method of image statistical modeling-based OPQI for GP quality grading and monitoring by a Weibull distribution(WD) model with a semi-supervised learning classifier is presented. WD-model parameters (WD-MPs) of GP images' spatial structures, obtained with omnidirectional Gaussian derivative filtering (OGDF), which were demonstrated theoretically to obey a specific WD model of integral form, were extracted as the visual features. Then, a co-training-style semi-supervised classifier algorithm, named COSC-Boosting, was exploited for semi-supervised GP quality grading, by integrating two independent classifiers with complementary nature in the face of scarce labeled samples. Effectiveness of the proposed OPQI method was verified and compared in the field of automated rice quality grading with commonly-used methods and showed superior performance, which lays a foundation for the quality control of GP on assembly lines.

Objective Video Quality Assessment Based on Machine Learning for Underwater Scientific Applications

PubMed Central

Moreno-Roldán, José-Miguel; Luque-Nieto, Miguel-Ángel; Poncela, Javier; Otero, Pablo

2017-01-01

Video services are meant to be a fundamental tool in the development of oceanic research. The current technology for underwater networks (UWNs) imposes strong constraints in the transmission capacity since only a severely limited bitrate is available. However, previous studies have shown that the quality of experience (QoE) is enough for ocean scientists to consider the service useful, although the perceived quality can change significantly for small ranges of variation of video parameters. In this context, objective video quality assessment (VQA) methods become essential in network planning and real time quality adaptation fields. This paper presents two specialized models for objective VQA, designed to match the special requirements of UWNs. The models are built upon machine learning techniques and trained with actual user data gathered from subjective tests. Our performance analysis shows how both of them can successfully estimate quality as a mean opinion score (MOS) value and, for the second model, even compute a distribution function for user scores. PMID:28333123

Energy Auditor and Quality Control Inspector Competency Model

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

Head, Heather R.; Kurnik, Charles W.; Schroeder, Derek

The Energy Auditor (EA) and Quality Control Inspector (QCI) Competency model was developed to identify the soft skills, foundational competencies and define the levels of Knowledge, Skills, and Abilities (KSAs) required to successfully perform the tasks defined in the EA and QCI Job Task Analysis (JTAs), the U.S. Department of Energy (DOE) used the U.S. Department of Labor's (DOL) Competency Model Clearinghouse resources to develop a QCI and EA Competency Model. To keep the QCI and EA competency model consistent with other construction and energy management competency models, DOE and the National Renewable Energy Laboratory used the existing 'Residential Constructionmore » Competency Model' and the 'Advanced Commercial Building Competency Model' where appropriate.« less

The Relationship between Costs and Quality in Veterans Health Administration Community Living Centers: An Analysis Using Longitudinal Data.

PubMed

Burgess, James F; Shwartz, Michael; Stolzmann, Kelly; Sullivan, Jennifer L

2018-05-18

To examine the relationship between cost and quality in Veterans Health Administration (VA) nursing homes (called Community Living Centers, CLCs) using longitudinal data. One hundred and thirty CLCs over 13 quarters (from FY2009 to FY2012) were studied. Costs, resident days, and resident severity (RUGs score) were obtained from the VA Managerial Cost Accounting System. Clinical quality measures were obtained from the Minimum Data Set, and resident-centered care (RCC) was measured using the Artifacts of Culture Change Tool. We used a generalized estimating equation model with facilities included as fixed effects to examine the relationship between total cost and quality after controlling for resident days and severity. The model included linear and squared terms for all independent variables and interactions with resident days. With the exception of RCC, all other variables had a statistically significant relationship with total costs. For most poorer performing smaller facilities (lower size quartile), improvements in quality were associated with higher costs. For most larger facilities, improvements in quality were associated with lower costs. The relationship between cost and quality depends on facility size and current level of performance. © Published 2018. This article is a U.S. Government work and is in the public domain in the USA.

Chemical data assimilation of geostationary aerosol optical depth and PM surface observations on regional aerosol modeling over the Korean Peninsula during KORUS-AQ campaign

NASA Astrophysics Data System (ADS)

Jung, J.; Choi, Y.; Souri, A.; Jeon, W.

2017-12-01

Particle matter(PM) has played a significantly deleterious role in affecting human health and climate. Recently, continuous high concentrations of PM in Korea attracted public attention to this critical issue, and the Korea-United States Air Quality Study(KORUS-AQ) campaign in 2016 was conducted to investigate the causes. For this study, we adjusted the initial conditions in the chemical transport model(CTM) to improve its performance over Korean Peninsula during KORUS-AQ period, using the campaign data to evaluate our model performance. We used the Optimal Interpolation(OI) approach and used hourly surface air quality measurement data from the Air Quality Monitoring Station(AQMS) by NIER and the aerosol optical depth(AOD) measured by a GOCI sensor from the geostationary orbit onboard the Communication Ocean and Meteorological Satellite(COMS). The AOD at 550nm has a 6km spatial resolution and broad coverage over East Asia. After assimilating the surface air quality observation data, the model accuracy significantly improved compared to base model result (without assimilation). It reported very high correlation value (0.98) and considerably decreased mean bias. Especially, it well captured some high peaks which was underpredicted by the base model. To assimilate satellite data, we applied AOD scaling factors to quantify each specie's contribution to total PM concentration and find-mode fraction(FMF) to define vertical distribution. Finally, the improvement showed fairly good agreement.

Interactions of donor sources and media influence the histo-morphological quality of full-thickness skin models.

PubMed

Lange, Julia; Weil, Frederik; Riegler, Christoph; Groeber, Florian; Rebhan, Silke; Kurdyn, Szymon; Alb, Miriam; Kneitz, Hermann; Gelbrich, Götz; Walles, Heike; Mielke, Stephan

2016-10-01

Human artificial skin models are increasingly employed as non-animal test platforms for research and medical purposes. However, the overall histopathological quality of such models may vary significantly. Therefore, the effects of manufacturing protocols and donor sources on the quality of skin models built-up from fibroblasts and keratinocytes derived from juvenile foreskins is studied. Histo-morphological parameters such as epidermal thickness, number of epidermal cell layers, dermal thickness, dermo-epidermal adhesion and absence of cellular nuclei in the corneal layer are obtained and scored accordingly. In total, 144 full-thickness skin models derived from 16 different donors, built-up in triplicates using three different culture conditions were successfully generated. In univariate analysis both media and donor age affected the quality of skin models significantly. Both parameters remained statistically significant in multivariate analyses. Performing general linear model analyses we could show that individual medium-donor-interactions influence the quality. These observations suggest that the optimal choice of media may differ from donor to donor and coincides with findings where significant inter-individual variations of growth rates in keratinocytes and fibroblasts have been described. Thus, the consideration of individual medium-donor-interactions may improve the overall quality of human organ models thereby forming a reproducible test platform for sophisticated clinical research. Copyright © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Does Winning a Pay-for-Performance Bonus Improve Subsequent Quality Performance? Evidence from the Hospital Quality Incentive Demonstration

PubMed Central

Ryan, Andrew; Sutton, Matthew; Doran, Tim

2014-01-01

Objective To test whether receiving a financial bonus for quality in the Premier Hospital Quality Incentive Demonstration (HQID) stimulated subsequent quality improvement. Data Hospital-level data on process-of-care quality from Hospital Compare for the treatment of acute myocardial infarction (AMI), heart failure, and pneumonia for 260 hospitals participating in the HQID from 2004 to 2006; receipt of quality bonuses in the first 3 years of HQID from the Premier Inc. website; and hospital characteristics from the 2005 American Hospital Association Annual Survey. Study Design Under the HQID, hospitals received a 1 percent bonus on Medicare payments for scoring between the 80th and 90th percentiles on a composite quality measure, and a 2 percent bonus for scoring at the 90th percentile or above. We used a regression discontinuity design to evaluate whether hospitals with quality scores just above these payment thresholds improved more in the subsequent year than hospitals with quality scores just below the thresholds. In alternative specifications, we examined samples of hospitals scoring within 3, 5, and 10 percentage point “bandwidths” of the thresholds. We used a Generalized Linear Model to estimate whether the relationship between quality and lagged quality was discontinuous at the lagged thresholds required for quality bonuses. Principal Findings There were no statistically significant associations between receipt of a bonus and subsequent quality performance, with the exception of the 2 percent bonus for AMI in 2006 using the 5 percentage point bandwidth (0.8 percentage point increase, p < .01), and the 1 percent bonus for pneumonia in 2005 using all bandwidths (3.7 percentage point increase using the 3 percentage point bandwidth, p < .05). Conclusions We found little evidence that hospitals' receipt of quality bonuses was associated with subsequent improvement in performance. This raises questions about whether winning in pay-for-performance programs, such as Hospital Value-Based Purchasing, will lead to subsequent quality improvement. PMID:23909992

The effects of precipitation, river discharge, land use and coastal circulation on water quality in coastal Maine

PubMed Central

Tilburg, Charles E.; Jordan, Linda M.; Carlson, Amy E.; Zeeman, Stephan I.; Yund, Philip O.

2015-01-01

Faecal pollution in stormwater, wastewater and direct run-off can carry zoonotic pathogens to streams, rivers and the ocean, reduce water quality, and affect both recreational and commercial fishing areas of the coastal ocean. Typically, the closure of beaches and commercial fishing areas is governed by the testing for the presence of faecal bacteria, which requires an 18–24 h period for sample incubation. As water quality can change during this testing period, the need for accurate and timely predictions of coastal water quality has become acute. In this study, we: (i) examine the relationship between water quality, precipitation and river discharge at several locations within the Gulf of Maine, and (ii) use multiple linear regression models based on readily obtainable hydrometeorological measurements to predict water quality events at five coastal locations. Analysis of a 12 year dataset revealed that high river discharge and/or precipitation events can lead to reduced water quality; however, the use of only these two parameters to predict water quality can result in a number of errors. Analysis of a higher frequency, 2 year study using multiple linear regression models revealed that precipitation, salinity, river discharge, winds, seasonality and coastal circulation correlate with variations in water quality. Although there has been extensive development of regression models for freshwater, this is one of the first attempts to create a mechanistic model to predict water quality in coastal marine waters. Model performance is similar to that of efforts in other regions, which have incorporated models into water resource managers' decisions, indicating that the use of a mechanistic model in coastal Maine is feasible. PMID:26587258

An assessment technique for computer-socket manufacturing

PubMed Central

Sanders, Joan; Severance, Michael

2015-01-01

An assessment strategy is presented for testing the quality of carving and forming of individual computer aided manufacturing facilities. The strategy is potentially useful to facilities making sockets and companies marketing manufacturing equipment. To execute the strategy, an evaluator fabricates a collection of test models and sockets using the manufacturing suite under evaluation, and then measures their shapes using scanning equipment. Overall socket quality is assessed by comparing socket shapes with electronic file shapes. Then model shapes are compared with electronic file shapes to characterize carving performance. Socket shapes are compared with model shapes to characterize forming performance. The mean radial error (MRE), which is the average difference in radii between the two shapes being compared, provides insight into sizing quality. Inter-quartile range (IQR), the range of radial error for the best matched half of the points on the surfaces being compared, provides insight into shape quality. By determining MRE and IQR for carving and forming separately, the source(s) of socket shape error may be pinpointed. The developed strategy may provide a useful tool to the prosthetics community and industry to help identify problems and limitations in computer aided manufacturing and insight into appropriate modifications to overcome them. PMID:21938663

Quality of care and service trajectories for people with intellectual disabilities: defining the aspects of quality from the client's perspective.

PubMed

Barelds, Anna; van de Goor, Ien; van Heck, Guus; Schols, Jos

2010-03-01

Care and service trajectories for people with intellectual disabilities (i.e. people with mental retardations) are routes within the healthcare delivery system that consist of all the steps that people with intellectual disabilities and their families have to take in order to realise the needed care and services. This article aims to identify the quality aspects of trajectories that are considered important by people with intellectual disabilities and their parents/relatives. In addition, it examines how these aspects are related to quality determinants mentioned in the literature on integrated care and to authoritative models for quality assessment of care and service delivery. Quality aspects were collected during eight focus group discussions with people with intellectual disabilities or their parents/relatives. In addition, quality determinants of integrated care and authoritative models for quality assessment were selected by means of a thorough review of the literature. Finally, the quality aspects identified using focus groups were compared to the determinants and models found in the literature. The quality aspects presented by people with intellectual disabilities referred particularly to the immediate situation in receiving care and services, such as 'keeping appointments' and 'time and attention', whereas parents/relatives also referred to broader 'organisational issues', such as 'access to support' and 'problems with placement'. The quality aspects, however, are minimally related to the quality determinants of integrated care, probably because clients and their parents/relatives find it difficult to have an overview of the coherence between the various actions that have to be performed, when going through the trajectories. In contrast, the quality aspects seem to fit into the domains of the authoritative models for quality assessment, probably because of the minimal focus of the models on long-term aspects in care and service delivery.

Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin with Intensive Oil and Gas Production

NASA Astrophysics Data System (ADS)

Matichuk, R.; Tonnesen, G.; Luecken, D.; Roselle, S. J.; Napelenok, S. L.; Baker, K. R.; Gilliam, R. C.; Misenis, C.; Murphy, B.; Schwede, D. B.

2015-12-01

The western United States is an important source of domestic energy resources. One of the primary environmental impacts associated with oil and natural gas production is related to air emission releases of a number of air pollutants. Some of these pollutants are important precursors to the formation of ground-level ozone. To better understand ozone impacts and other air quality issues, photochemical air quality models are used to simulate the changes in pollutant concentrations in the atmosphere on local, regional, and national spatial scales. These models are important for air quality management because they assist in identifying source contributions to air quality problems and designing effective strategies to reduce harmful air pollutants. The success of predicting oil and natural gas air quality impacts depends on the accuracy of the input information, including emissions inventories, meteorological information, and boundary conditions. The treatment of chemical and physical processes within these models is equally important. However, given the limited amount of data collected for oil and natural gas production emissions in the past and the complex terrain and meteorological conditions in western states, the ability of these models to accurately predict pollution concentrations from these sources is uncertain. Therefore, this presentation will focus on understanding the Community Multiscale Air Quality (CMAQ) model's ability to predict air quality impacts associated with oil and natural gas production and its sensitivity to input uncertainties. The results will focus on winter ozone issues in the Uinta Basin, Utah and identify the factors contributing to model performance issues. The results of this study will help support future air quality model development, policy and regulatory decisions for the oil and gas sector.

OPERA: A free and open source QSAR tool for predicting physicochemical properties and environmental fate endpoints

EPA Science Inventory

Collecting the chemical structures and data for necessary QSAR modeling is facilitated by available public databases and open data. However, QSAR model performance is dependent on the quality of data and modeling methodology used. This study developed robust QSAR models for physi...

Global and Regional Modeling of Long-Range Transport and Intercontinental Source-Receptor Linkages

EPA Science Inventory

In this study, we compare air quality over North America simulated by the C-IFS global model and the CMAQ regional model driven by boundary conditions from C-IFS against surface and upper air observations. Results indicate substantial differences in model performance for surface ...

CFD MODELING OF FINE SCALE FLOW AND TRANSPORT IN THE HOUSTON METROPOLITAN AREA, TEXAS

EPA Science Inventory

Fine scale modeling of flows and air quality in Houston, Texas is being performed; the use of computational fluid dynamics (CFD) modeling is being applied to investigate the influence of morphologic structures on the within-grid transport and dispersion of sources in grid models ...

Total integrated performance excellence system (TIPES): A true north direction for a clinical trial support center.

PubMed

Sather, Mike R; Parsons, Sherry; Boardman, Kathy D; Warren, Stuart R; Davis-Karim, Anne; Griffin, Kevin; Betterton, Jane A; Jones, Mark S; Johnson, Stanley H; Vertrees, Julia E; Hickey, Jan H; Salazar, Thelma P; Huang, Grant D

2018-03-01

This paper presents the quality journey taken by a Federal organization over more than 20 years. These efforts have resulted in the implementation of a Total Integrated Performance Excellence System (TIPES) that combines key principles and practices of established quality systems. The Center has progressively integrated quality system frameworks including the Malcom Baldrige National Quality Award (MBNQA) Framework and Criteria for Performance Excellence, ISO 9001, and the Organizational Project Management Maturity Model (OPM3), as well as supplemental quality systems of ISO 15378 (packaging for medicinal products) and ISO 21500 (guide to project management) to systematically improve all areas of operations. These frameworks were selected for applicability to Center processes and systems, consistency and reinforcement of complimentary approaches, and international acceptance. External validations include the MBNQA, the highest quality award in the US, continued registration and conformance to ISO standards and guidelines, and multiple VA and state awards. With a focus on a holistic approach to quality involving processes, systems and personnel, this paper presents activities and lessons that were critical to building TIPES and establishing the quality environment for conducting clinical research in support of Veterans and national health care.

Evaluating the Relationship between Productivity and Quality in Emergency Departments

PubMed Central

Bastian, Nathaniel D.; Riordan, John P.

2017-01-01

Background In the United States, emergency departments (EDs) are constantly pressured to improve operational efficiency and quality in order to gain financial benefits and maintain a positive reputation. Objectives The first objective is to evaluate how efficiently EDs transform their input resources into quality outputs. The second objective is to investigate the relationship between the efficiency and quality performance of EDs and the factors affecting this relationship. Methods Using two data sources, we develop a data envelopment analysis (DEA) model to evaluate the relative efficiency of EDs. Based on the DEA result, we performed multinomial logistic regression to investigate the relationship between ED efficiency and quality performance. Results The DEA results indicated that the main source of inefficiencies was working hours of technicians. The multinomial logistic regression result indicated that the number of electrocardiograms and X-ray procedures conducted in the ED and the length of stay were significantly associated with the trade-offs between relative efficiency and quality. Structural ED characteristics did not influence the relationship between efficiency and quality. Conclusions Depending on the structural and operational characteristics of EDs, different factors can affect the relationship between efficiency and quality. PMID:29065673

Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework

EPA Science Inventory

The work here complements the overview analysis of the modelling systems participating in the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3) by focusing on the performance for hourly surface ozone by two modelling systems, Chimere for Europe an...

Optimizing construction quality management of pavements using mechanistic performance analysis.

DOT National Transportation Integrated Search

2004-08-01

This report presents a statistical-based algorithm that was developed to reconcile the results from several pavement performance models used in the state of practice with systematic process control techniques. These algorithms identify project-specif...

Projecting manpower to attain quality

NASA Technical Reports Server (NTRS)

Rone, K. Y.

1983-01-01

The resulting model is useful as a projection tool but must be validated in order to be used as an on-going software cost engineering tool. A procedure is developed to facilitate the tracking of model projections and actual data to allow the model to be tuned. Finally, since the model must be used in an environment of overlapping development activities on a progression of software elements in development and maintenance, a manpower allocation model is developed for use in a steady state development/maintenance environment. In these days of soaring software costs it becomes increasingly important to properly manage a software development project. One element of the management task is the projection and tracking of manpower required to perform the task. In addition, since the total cost of the task is directly related to the initial quality built into the software, it becomes a necessity to project the development manpower in a way to attain that quality. An approach to projecting and tracking manpower with quality in mind is described.

Small drinking water systems under spatiotemporal water quality variability: a risk-based performance benchmarking framework.

PubMed

Bereskie, Ty; Haider, Husnain; Rodriguez, Manuel J; Sadiq, Rehan

2017-08-23

Traditional approaches for benchmarking drinking water systems are binary, based solely on the compliance and/or non-compliance of one or more water quality performance indicators against defined regulatory guidelines/standards. The consequence of water quality failure is dependent on location within a water supply system as well as time of the year (i.e., season) with varying levels of water consumption. Conventional approaches used for water quality comparison purposes fail to incorporate spatiotemporal variability and degrees of compliance and/or non-compliance. This can lead to misleading or inaccurate performance assessment data used in the performance benchmarking process. In this research, a hierarchical risk-based water quality performance benchmarking framework is proposed to evaluate small drinking water systems (SDWSs) through cross-comparison amongst similar systems. The proposed framework (R WQI framework) is designed to quantify consequence associated with seasonal and location-specific water quality issues in a given drinking water supply system to facilitate more efficient decision-making for SDWSs striving for continuous performance improvement. Fuzzy rule-based modelling is used to address imprecision associated with measuring performance based on singular water quality guidelines/standards and the uncertainties present in SDWS operations and monitoring. This proposed R WQI framework has been demonstrated using data collected from 16 SDWSs in Newfoundland and Labrador and Quebec, Canada, and compared to the Canadian Council of Ministers of the Environment WQI, a traditional, guidelines/standard-based approach. The study found that the R WQI framework provides an in-depth state of water quality and benchmarks SDWSs more rationally based on the frequency of occurrence and consequence of failure events.

Evaluation of the impact of SO₂ and NO₂ emissions on the ambient air-quality in the Çan-Bayramiç region of northwest Turkey during 2007-2008.

PubMed

Ozkurt, Nesimi; Sari, Deniz; Akalin, Nuray; Hilmioglu, Bilgin

2013-07-01

The characterization and assessment of air-quality in this region are essential steps for the implementation of the "Clean Air Action Plan" as this is set by the Turkish Regulation on Ambient Air-Quality Assessment and Management. This study area intends to shed a light on use of modeling tools as an alternative method for the assessment of local atmospheric pollution and the determination of the importance of local emissions. This modeling approach can be also used for the consistent geographic representation of air-quality concentration as well as for assessing the future air-quality condition after the implementation of emission reduction measures in a certain area. With this article we evaluate the impact of sulfur dioxide and nitrogen dioxide emissions on the ambient air-quality in the Çan-Bayramiç region of Turkey. The emission rates of sulfur dioxide and nitrogen dioxide were calculated by using the CALPUFF model. The concentration of these pollutants had also been monitored at ten air-quality locations during 2007-2008 in the research area. The measured data were also utilized for testing the model performance. Results showed that the air-quality in this important rural region of Turkey can be evaluated effectively by using the current numerical modeling system. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

42 CFR § 414.1330 - Quality performance category.

Code of Federal Regulations, 2010 CFR

2017-10-01

... SERVICES (CONTINUED) MEDICARE PROGRAM (CONTINUED) PAYMENT FOR PART B MEDICAL AND OTHER HEALTH SERVICES Merit-Based Incentive Payment System and Alternative Payment Model Incentive § 414.1330 Quality... comprise: (1) 60 percent of a MIPS eligible clinician's final score for MIPS payment year 2019. (2) 50...

A comparative evaluation of risk-adjustment models for benchmarking amputation-free survival after lower extremity bypass.

PubMed

Simons, Jessica P; Goodney, Philip P; Flahive, Julie; Hoel, Andrew W; Hallett, John W; Kraiss, Larry W; Schanzer, Andres

2016-04-01

Providing patients and payers with publicly reported risk-adjusted quality metrics for the purpose of benchmarking physicians and institutions has become a national priority. Several prediction models have been developed to estimate outcomes after lower extremity revascularization for critical limb ischemia, but the optimal model to use in contemporary practice has not been defined. We sought to identify the highest-performing risk-adjustment model for amputation-free survival (AFS) at 1 year after lower extremity bypass (LEB). We used the national Society for Vascular Surgery Vascular Quality Initiative (VQI) database (2003-2012) to assess the performance of three previously validated risk-adjustment models for AFS. The Bypass versus Angioplasty in Severe Ischaemia of the Leg (BASIL), Finland National Vascular (FINNVASC) registry, and the modified Project of Ex-vivo vein graft Engineering via Transfection III (PREVENT III [mPIII]) risk scores were applied to the VQI cohort. A novel model for 1-year AFS was also derived using the VQI data set and externally validated using the PIII data set. The relative discrimination (Harrell c-index) and calibration (Hosmer-May goodness-of-fit test) of each model were compared. Among 7754 patients in the VQI who underwent LEB for critical limb ischemia, the AFS was 74% at 1 year. Each of the previously published models for AFS demonstrated similar discriminative performance: c-indices for BASIL, FINNVASC, mPIII were 0.66, 0.60, and 0.64, respectively. The novel VQI-derived model had improved discriminative ability with a c-index of 0.71 and appropriate generalizability on external validation with a c-index of 0.68. The model was well calibrated in both the VQI and PIII data sets (goodness of fit P = not significant). Currently available prediction models for AFS after LEB perform modestly when applied to national contemporary VQI data. Moreover, the performance of each model was inferior to that of the novel VQI-derived model. Because the importance of risk-adjusted outcome reporting continues to increase, national registries such as VQI should begin using this novel model for benchmarking quality of care. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

A sound quality model for objective synthesis evaluation of vehicle interior noise based on artificial neural network

NASA Astrophysics Data System (ADS)

Wang, Y. S.; Shen, G. Q.; Xing, Y. F.

2014-03-01

Based on the artificial neural network (ANN) technique, an objective sound quality evaluation (SQE) model for synthesis annoyance of vehicle interior noises is presented in this paper. According to the standard named GB/T18697, firstly, the interior noises under different working conditions of a sample vehicle are measured and saved in a noise database. Some mathematical models for loudness, sharpness and roughness of the measured vehicle noises are established and performed by Matlab programming. Sound qualities of the vehicle interior noises are also estimated by jury tests following the anchored semantic differential (ASD) procedure. Using the objective and subjective evaluation results, furthermore, an ANN-based model for synthetical annoyance evaluation of vehicle noises, so-called ANN-SAE, is developed. Finally, the ANN-SAE model is proved by some verification tests with the leave-one-out algorithm. The results suggest that the proposed ANN-SAE model is accurate and effective and can be directly used to estimate sound quality of the vehicle interior noises, which is very helpful for vehicle acoustical designs and improvements. The ANN-SAE approach may be extended to deal with other sound-related fields for product quality evaluations in SQE engineering.

Prediction of pilot opinion ratings using an optimal pilot model. [of aircraft handling qualities in multiaxis tasks

NASA Technical Reports Server (NTRS)

Hess, R. A.

1977-01-01

A brief review of some of the more pertinent applications of analytical pilot models to the prediction of aircraft handling qualities is undertaken. The relative ease with which multiloop piloting tasks can be modeled via the optimal control formulation makes the use of optimal pilot models particularly attractive for handling qualities research. To this end, a rating hypothesis is introduced which relates the numerical pilot opinion rating assigned to a particular vehicle and task to the numerical value of the index of performance resulting from an optimal pilot modeling procedure as applied to that vehicle and task. This hypothesis is tested using data from piloted simulations and is shown to be reasonable. An example concerning a helicopter landing approach is introduced to outline the predictive capability of the rating hypothesis in multiaxis piloting tasks.

Quality assessment of protein model-structures using evolutionary conservation.

PubMed

Kalman, Matan; Ben-Tal, Nir

2010-05-15

Programs that evaluate the quality of a protein structural model are important both for validating the structure determination procedure and for guiding the model-building process. Such programs are based on properties of native structures that are generally not expected for faulty models. One such property, which is rarely used for automatic structure quality assessment, is the tendency for conserved residues to be located at the structural core and for variable residues to be located at the surface. We present ConQuass, a novel quality assessment program based on the consistency between the model structure and the protein's conservation pattern. We show that it can identify problematic structural models, and that the scores it assigns to the server models in CASP8 correlate with the similarity of the models to the native structure. We also show that when the conservation information is reliable, the method's performance is comparable and complementary to that of the other single-structure quality assessment methods that participated in CASP8 and that do not use additional structural information from homologs. A perl implementation of the method, as well as the various perl and R scripts used for the analysis are available at http://bental.tau.ac.il/ConQuass/. nirb@tauex.tau.ac.il Supplementary data are available at Bioinformatics online.

How to Compare the Security Quality Requirements Engineering (SQUARE) Method with Other Methods

DTIC Science & Technology

2007-08-01

Attack Trees for Modeling and Analysis 10 2.8 Misuse and Abuse Cases 10 2.9 Formal Methods 11 2.9.1 Software Cost Reduction 12 2.9.2 Common...modern or efficient techniques. • Requirements analysis typically is either not performed at all (identified requirements are directly specified without...any analysis or modeling) or analysis is restricted to functional re- quirements and ignores quality requirements, other nonfunctional requirements

Quality of protection evaluation of security mechanisms.

PubMed

Ksiezopolski, Bogdan; Zurek, Tomasz; Mokkas, Michail

2014-01-01

Recent research indicates that during the design of teleinformatic system the tradeoff between the systems performance and the system protection should be made. The traditional approach assumes that the best way is to apply the strongest possible security measures. Unfortunately, the overestimation of security measures can lead to the unreasonable increase of system load. This is especially important in multimedia systems where the performance has critical character. In many cases determination of the required level of protection and adjustment of some security measures to these requirements increase system efficiency. Such an approach is achieved by means of the quality of protection models where the security measures are evaluated according to their influence on the system security. In the paper, we propose a model for QoP evaluation of security mechanisms. Owing to this model, one can quantify the influence of particular security mechanisms on ensuring security attributes. The methodology of our model preparation is described and based on it the case study analysis is presented. We support our method by the tool where the models can be defined and QoP evaluation can be performed. Finally, we have modelled TLS cryptographic protocol and presented the QoP security mechanisms evaluation for the selected versions of this protocol.

Application of OMI NO2 for Regional Air Quality Model Evaluation

NASA Astrophysics Data System (ADS)

Holloway, T.; Bickford, E.; Oberman, J.; Scotty, E.; Clifton, O. E.

2012-12-01

To support the application of satellite data for air quality analysis, we examine how column NO2 measurements from the Ozone Monitoring Instrument (OMI) aboard the NASA Aura satellite relate to ground-based and model estimates of NO2 and related species. Daily variability, monthly mean values, and spatial gradients in OMI NO2 from the Netherlands Royal Meteorological Institute (KNMI) are compared to ground-based measurements of NO2 from the EPA Air Quality System (AQS) database. Satellite data is gridded to two resolutions typical of regional air quality models - 36 km x 36 km over the continental U.S., and 12 km x 12 km over the Upper Midwestern U.S. Gridding is performed using the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS), a publicly available software to support gridding of satellite data to model grids. Comparing daily OMI retrievals (13:45 daytime local overpass time) with ground-based measurements (13:00), we find January and July 2007 correlation coefficients (r-values) generally positive, with values higher in the winter (January) than summer (July) for most sites. Incidences of anti-correlation or low-correlation are evaluated with model simulations from the U.S. EPA Community Multiscale Air Quality Model version 4.7 (CMAQ). OMI NO2 is also used to evaluate CMAQ output, and to compare performance metrics for CMAQ relative to AQS measurements. We compare simulated NO2 across both the U.S. and Midwest study domains with both OMI NO2 (total column CMAQ values, weighted with the averaging kernel) and with ground-based observations (lowest model layer CMAQ values). 2007 CMAQ simulations employ emissions from the Lake Michigan Air Directors Consortium (LADCO) and meteorology from the Weather Research and Forecasting (WRF) model. Over most of the U.S., CMAQ is too high in January relative to OMI NO2, but too low in January relative to AQS NO2. In contrast, CMAQ is too low in July relative to OMI NO2, but too high relative to AQS NO2. These biases are used to evaluate emission sources (and the importance of missing sources, such as lightning NOx), and to explain model performance for related secondary species, especially nitrate aerosol and ozone.

Client satisfaction with reproductive health-care quality: integrating business approaches to modeling and measurement.

PubMed

Alden, Dana L; Do, Mai Hoa; Bhawuk, Dharm

2004-12-01

Health-care managers are increasingly interested in client perceptions of clinic service quality and satisfaction. While tremendous progress has occurred, additional perspectives on the conceptualization, modeling and measurement of these constructs may further assist health-care managers seeking to provide high-quality care. To that end, this study draws on theories from business and health to develop an integrated model featuring antecedents to and consequences of reproductive health-care client satisfaction. In addition to developing a new model, this study contributes by testing how well Western-based theories of client satisfaction hold in a developing, Asian country. Applied to urban, reproductive health clinic users in Hanoi, Vietnam, test results suggest that hypothesized antecedents such as pre-visit expectations, perceived clinic performance and how much performance exceeds expectations impact client satisfaction. However, the relative importance of these predictors appears to vary depending on a client's level of service-related experience. Finally, higher levels of client satisfaction are positively related to future clinic use intentions. This study demonstrates the value of: (1) incorporating theoretical perspectives from multiple disciplines to model processes underlying health-care satisfaction and (2) field testing those models before implementation. It also furthers research designed to provide health-care managers with actionable measures of the complex processes related to their clients' satisfaction.

Space shuttle flying qualities and criteria assessment

NASA Technical Reports Server (NTRS)

Myers, T. T.; Johnston, D. E.; Mcruer, Duane T.

1987-01-01

Work accomplished under a series of study tasks for the Flying Qualities and Flight Control Systems Design Criteria Experiment (OFQ) of the Shuttle Orbiter Experiments Program (OEX) is summarized. The tasks involved review of applicability of existing flying quality and flight control system specification and criteria for the Shuttle; identification of potentially crucial flying quality deficiencies; dynamic modeling of the Shuttle Orbiter pilot/vehicle system in the terminal flight phases; devising a nonintrusive experimental program for extraction and identification of vehicle dynamics, pilot control strategy, and approach and landing performance metrics, and preparation of an OEX approach to produce a data archive and optimize use of the data to develop flying qualities for future space shuttle craft in general. Analytic modeling of the Orbiter's unconventional closed-loop dynamics in landing, modeling pilot control strategies, verification of vehicle dynamics and pilot control strategy from flight data, review of various existent or proposed aircraft flying quality parameters and criteria in comparison with the unique dynamic characteristics and control aspects of the Shuttle in landing; and finally a summary of conclusions and recommendations for developing flying quality criteria and design guides for future Shuttle craft.

A flexible framework for process-based hydraulic and water quality modeling of stormwater green infrastructure performance

EPA Science Inventory

Background Models that allow for design considerations of green infrastructure (GI) practices to control stormwater runoff and associated contaminants have received considerable attention in recent years. While popular, generally, the GI models are relatively simplistic. However,...

Does adoption of electronic health records improve the quality of care management in France? Results from the French e-SI (PREPS-SIPS) study.

PubMed

Plantier, Morgane; Havet, Nathalie; Durand, Thierry; Caquot, Nicolas; Amaz, Camille; Biron, Pierre; Philip, Irène; Perrier, Lionel

2017-06-01

Electronic health records (EHR) are increasingly being adopted by healthcare systems worldwide. In France, the "Hôpital numérique 2012-2017" program was implemented as part of a strategic plan to modernize health information technology (HIT), including the promotion of widespread EHR use. With significant upfront investment costs as well as ongoing operational expenses, it is important to assess this system in terms of its ability to result in improvements in hospital performances. The aim of this study was to evaluate the impact of EHR use on the quality of care management in acute care hospitals throughout France. This retrospective study was based on data derived from three national databases for the year 2011: IPAQSS (indicators of improvement in the quality and the management of healthcare, "IPAQSS"), Hospi-Diag (French hospital performance indicators), and the national accreditation database. Several multivariate models were used to examine the association between the use of EHRs and specific EHR features with four quality indicators: the quality of patient record, the delay in sending information at hospital discharge, the pain status evaluation, and the nutritional status evaluation, while also adjusting for hospital characteristics. The models revealed a significant positive impact of EHR use on the four quality indicators. Additionally, they showed a differential impact according to the functionality of the element of the health record that was computerized. All four quality indicators were also impacted by the type of hospital, the geographical region, and the severity of the pathology. These results suggest that, to improve the quality of care management in hospitals, EHR adoption represents an important lever. They complete previous work dealing with EHR and the organizational performance of hospital surgical units. Copyright © 2017 Elsevier B.V. All rights reserved.

Study on the influence of ground and satellite observations on the numerical air-quality for PM10 over Romanian territory

NASA Astrophysics Data System (ADS)

Dumitrache, Rodica Claudia; Iriza, Amalia; Maco, Bogdan Alexandru; Barbu, Cosmin Danut; Hirtl, Marcus; Mantovani, Simone; Nicola, Oana; Irimescu, Anisoara; Craciunescu, Vasile; Ristea, Alina; Diamandi, Andrei

2016-10-01

The numerical forecast of particulate matter concentrations in general, and PM10 in particular is a theme of high socio-economic relevance. The aim of this study was to investigate the impact of ground and satellite data assimilation of PM10 observations into the Weather Research and Forecasting model coupled with Chemistry (WRF-CHEM) numerical air quality model for Romanian territory. This is the first initiative of the kind for this domain of interest. Assimilation of satellite information - e.g. AOT's in air quality models is of interest due to the vast spatial coverage of the observations. Support Vector Regression (SVR) techniques are used to estimate the PM content from heterogeneous data sources, including EO products (Aerosol Optical Thickness), ground measurements and numerical model data (temperature, humidity, wind, etc.). In this study we describe the modeling framework employed and present the evaluation of the impact from the data assimilation of PM10 observations on the forecast of the WRF-CHEM model. Integrations of the WRF-CHEM model in data assimilation enabled/disabled configurations allowed the evaluation of satellite and ground data assimilation impact on the PM10 forecast performance for the Romanian territory. The model integration and evaluation were performed for two months, one in winter conditions (January 2013) and one in summer conditions (June 2013).

Using SCADA Data, Field Studies, and Real-Time Modeling to ...

EPA Pesticide Factsheets

EPA has been providing technical assistance to the City of Flint and the State of Michigan in response to the drinking water lead contamination incident. Responders quickly recognized the need for a water distribution system hydraulic model to provide insight on flow patterns and water quality as well as to evaluate changes being made to the system operation to enhance corrosion control and improve chlorine residuals. EPA partnered with the City of Flint and the Michigan Department of Environmental Quality to update and calibrate an existing hydraulic model. The City provided SCADA data, GIS data, customer billing data, valve status data, design diagrams, and information on operations. Team members visited all facilities and updated pump and valve types, sizes, settings, elevations, and pump discharge curves. Several technologies were used to support this work including the EPANET-RTX based Polaris real-time modeling software, WaterGEMS, ArcGIS, EPANET, and RTX:LINK. Field studies were conducted to collect pressure and flow data from more than 25 locations throughout the distribution system. An assessment of the model performance compared model predictions for flow, pressure, and tank levels to SCADA and field data, resulting in error measurements for each data stream over the time period analyzed. Now, the calibrated model can be used with a known confidence in its performance to evaluate hydraulic and water quality problems, and the model can be easily

Robust Decision Making to Support Water Quality Climate Adaptation: a Case Study in the Chesapeake Bay Watershed

NASA Astrophysics Data System (ADS)

Fischbach, J. R.; Lempert, R. J.; Molina-Perez, E.

2017-12-01

The U.S. Environmental Protection Agency (USEPA), together with state and local partners, develops watershed implementation plans designed to meet water quality standards. Climate uncertainty, along with uncertainty about future land use changes or the performance of water quality best management practices (BMPs), may make it difficult for these implementation plans to meet water quality goals. In this effort, we explored how decision making under deep uncertainty (DMDU) methods such as Robust Decision Making (RDM) could help USEPA and its partners develop implementation plans that are more robust to future uncertainty. The study focuses on one part of the Chesapeake Bay watershed, the Patuxent River, which is 2,479 sq km in area, highly urbanized, and has a rapidly growing population. We simulated the contribution of stormwater contaminants from the Patuxent to the overall Total Maximum Daily Load (TMDL) for the Chesapeake Bay under multiple scenarios reflecting climate and other uncertainties. Contaminants considered included nitrogen, phosphorus, and sediment loads. The assessment included a large set of scenario simulations using the USEPA Chesapeake Bay Program's Phase V watershed model. Uncertainties represented in the analysis included 18 downscaled climate projections (based on 6 general circulation models and 3 emissions pathways), 12 land use scenarios with different population projections and development patterns, and alternative assumptions about BMP performance standards and efficiencies associated with different suites of stormwater BMPs. Finally, we developed cost estimates for each of the performance standards and compared cost to TMDL performance as a key tradeoff for future water quality management decisions. In this talk, we describe how this research can help inform climate-related decision support at USEPA's Chesapeake Bay Program, and more generally how RDM and other DMDU methods can support improved water quality management under climate uncertainty.

Evaluation of COSMO-ART in the Framework of the Air Quality Model Evaluation International Initiative (AQMEII)

NASA Astrophysics Data System (ADS)

Giordano, Lea; Brunner, Dominik; Im, Ulas; Galmarini, Stefano

2014-05-01

The Air Quality Model Evaluation International Initiative (AQMEII) coordinated by the EC-JRC and US-EPA, promotes since 2008 research on regional air quality model evaluation across the atmospheric modelling communities of Europe and North America. AQMEII has now reached its Phase 2 that is dedicated to the evaluation of on-line coupled chemistry-meteorology models as opposed to Phase 1 where only off-line models were considered. At European level, AQMEII collaborates with the COST Action "European framework for on-line integrated air quality and meteorology modelling" (EuMetChem). All European groups participating in AQMEII performed simulations over the same spatial domain (Europe at a resolution of about 20 km) and using the same simulation strategy (e.g. no nudging allowed) and the same input data as much as possible. The initial and boundary conditions (IC/BC) were shared between all groups. Emissions were provided by the TNO-MACC database for anthropogenic emissions and the FMI database for biomass burning emissions. Chemical IC/BC data were taken from IFS-MOZART output, and meteorological IC/BC from the ECWMF global model. Evaluation data sets were collected by the Joint Research Center (JRC) and include measurements from surface in situ networks (AirBase and EMEP), vertical profiles from ozone sondes and aircraft (MOZAIC), and remote sensing (AERONET, satellites). Since Phase 2 focuses on on-line coupled models, a special effort is devoted to the detailed speciation of particulate matter components, with the goal of studying feedback processes. For the AQMEII exercise, COSMO-ART has been run with 40 levels of vertical resolution, and a chemical scheme that includes the SCAV module of Knote and Brunner (ACP 2013) for wet-phase chemistry and the SOA treatment according to VBS (volatility basis set) approach (Athanasopoulou et al., ACP 2013). The COSMO-ART evaluation shows that, next to a good performance in the meteorology, the gas phase chemistry is well captured throughout the year; the few cases showing a systematic underestimation of chemical concentrations arise as a consequence of the boundary conditions. Through this exercise we have identified the main critical issues in the COSMO-ART performance: sea salt and dust particulate matter components. The AQMEII exercise has provided an excellent platform to evaluate the COSMO-ART performance against both measurement data and other European regional on-line coupled models. From the analysis we have been able to identify specific model deficiencies and situations where the model cannot satisfactorily reproduce the data. Our future work will be focused on improving their modelling.

Biological and functional relevance of CASP predictions

PubMed Central

Liu, Tianyun; Ish‐Shalom, Shirbi; Torng, Wen; Lafita, Aleix; Bock, Christian; Mort, Matthew; Cooper, David N; Bliven, Spencer; Capitani, Guido; Mooney, Sean D.

2017-01-01

Abstract Our goal is to answer the question: compared with experimental structures, how useful are predicted models for functional annotation? We assessed the functional utility of predicted models by comparing the performances of a suite of methods for functional characterization on the predictions and the experimental structures. We identified 28 sites in 25 protein targets to perform functional assessment. These 28 sites included nine sites with known ligand binding (holo‐sites), nine sites that are expected or suggested by experimental authors for small molecule binding (apo‐sites), and Ten sites containing important motifs, loops, or key residues with important disease‐associated mutations. We evaluated the utility of the predictions by comparing their microenvironments to the experimental structures. Overall structural quality correlates with functional utility. However, the best‐ranked predictions (global) may not have the best functional quality (local). Our assessment provides an ability to discriminate between predictions with high structural quality. When assessing ligand‐binding sites, most prediction methods have higher performance on apo‐sites than holo‐sites. Some servers show consistently high performance for certain types of functional sites. Finally, many functional sites are associated with protein‐protein interaction. We also analyzed biologically relevant features from the protein assemblies of two targets where the active site spanned the protein‐protein interface. For the assembly targets, we find that the features in the models are mainly determined by the choice of template. PMID:28975675

Sparse representations via learned dictionaries for x-ray angiogram image denoising

NASA Astrophysics Data System (ADS)

Shang, Jingfan; Huang, Zhenghua; Li, Qian; Zhang, Tianxu

2018-03-01

X-ray angiogram image denoising is always an active research topic in the field of computer vision. In particular, the denoising performance of many existing methods had been greatly improved by the widely use of nonlocal similar patches. However, the only nonlocal self-similar (NSS) patch-based methods can be still be improved and extended. In this paper, we propose an image denoising model based on the sparsity of the NSS patches to obtain high denoising performance and high-quality image. In order to represent the sparsely NSS patches in every location of the image well and solve the image denoising model more efficiently, we obtain dictionaries as a global image prior by the K-SVD algorithm over the processing image; Then the single and effectively alternating directions method of multipliers (ADMM) method is used to solve the image denoising model. The results of widely synthetic experiments demonstrate that, owing to learned dictionaries by K-SVD algorithm, a sparsely augmented lagrangian image denoising (SALID) model, which perform effectively, obtains a state-of-the-art denoising performance and better high-quality images. Moreover, we also give some denoising results of clinical X-ray angiogram images.

A fuzzy inference system to evaluate contract service provider performance.

PubMed

Cruz, Antonio Miguel; Denis, Ernesto Rodriguez

2005-01-01

This paper puts forward a fuzzy inference system for evaluating the quality performance of service contract providers. An Application Service Provider was designed and put online, featuring surveys to establish the most useful indicators to evaluate the quality of the service. This model was implemented in 10 separate hospitals. As a result, the service cost-acquisition cost ratio in these cases was reduced from 16.14% to 6.09% in the period 2001-January 2003.

Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

NASA Astrophysics Data System (ADS)

Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

Modelling the photochemical pollution over the metropolitan area of Porto Alegre, Brazil

NASA Astrophysics Data System (ADS)

Borrego, C.; Monteiro, A.; Ferreira, J.; Moraes, M. R.; Carvalho, A.; Ribeiro, I.; Miranda, A. I.; Moreira, D. M.

2010-01-01

The main purpose of this study is to evaluate the photochemical pollution over the Metropolitan Area of Porto Alegre (MAPA), Brazil, where high concentrations of ozone have been registered during the past years. Due to the restricted spatial coverage of the monitoring air quality network, a numerical modelling technique was selected and applied to this assessment exercise. Two different chemistry-transport models - CAMx and CALGRID - were applied for a summer period, driven by the MM5 meteorological model. The meteorological model performance was evaluated comparing its results to available monitoring data measured at the Porto Alegre airport. Validation results point out a good model performance. It was not possible to evaluate the chemistry models performance due to the lack of adequate monitoring data. Nevertheless, the model intercomparison between CAMx and CALGRID shows a similar behaviour in what concerns the simulation of nitrogen dioxide, but some discrepancies concerning ozone. Regarding the fulfilment of the Brazilian air quality targets, the simulated ozone concentrations surpass the legislated value in specific periods, mainly outside the urban area of Porto Alegre. The ozone formation is influenced by the emission of pollutants that act as precursors (like the nitrogen oxides emitted at Porto Alegre urban area and coming from a large refinery complex) and by the meteorological conditions.

Screening bioactive quality control markers of QiShenYiQi dripping pills based on the relationship between the ultra-high performance liquid chromatography fingerprint and vascular protective activity.

PubMed

Zhuo, Limeng; Peng, Jingjing; Zhao, Yunli; Li, Dongxiang; Xie, Xiuman; Tong, Ling; Yu, Zhiguo

2017-10-01

Traditional Chinese medicine consists of complex phytochemical constituents. Selecting appropriate analytical markers of traditional Chinese medicine is a critical step in quality control. Currently, the combination of fingerprinting and efficacy evaluation is considered as a useful method for screening active ingredients in complex mixtures. This study was designed to develop an orthogonal partial least squares model for screening bioactive quality control markers of QishenYiqi dripping pills based on the fingerprint-efficacy relationship. First, the chemical fingerprints of 49 batches of QishenYiqi dripping pill samples were established by ultra-high performance liquid chromatography coupled with a photodiode array detector. Second, ultra-high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry was exploited to systematically investigate the 36 copossessing fingerprint components in QishenYiqi dripping pills. The vascular protective activity of QishenYiqi dripping pills was determined by using a cell counting kit-8 assay. Finally, fingerprint-efficacy relationship was established by orthogonal partial least squares model. The results indicated that ten components exhibited strong correlation with vascular protective activity, and these were preliminarily screened as quality control markers. The present study provided a novel idea for the study of the pharmacodynamic material basis and quality evaluation of QishenYiqi dripping pills. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

PubMed

Li, Qiongge; Chan, Maria F

2017-01-01

Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuous improvement of patient safety and quality of care. Cumulative longitudinal QA measurements are valuable for understanding the behavior of the Linac and allow physicists to identify trends in the output and take preventive actions. In this study, artificial neural networks (ANNs) and autoregressive moving average (ARMA) time-series prediction modeling techniques were both applied to 5-year daily Linac QA data. Verification tests and other evaluations were then performed for all models. Preliminary results showed that ANN time-series predictive modeling has more advantages over ARMA techniques for accurate and effective applicability in the dosimetry and QA field. © 2016 New York Academy of Sciences.

Systematically Evaluating the Effectiveness of Quality Assurance Programmes in Leading to Improvements in Institutional Performance

ERIC Educational Resources Information Center

Lillis, Deirdre

2012-01-01

Higher education institutions worldwide invest significant resources in their quality assurance systems. Little empirical evidence exists that demonstrates the effectiveness (or otherwise) of these systems. Methodological approaches for determining effectiveness are also underdeveloped. Self-study-with-peer-review is a widely used model for…

Simulating and Analyzing Long-Term Changes in Emissions, Air Quality, Aerosol Feedback Effects and Human Health

EPA Science Inventory

This presentation covers work performed by the authors to characterize changes in emissions over the 1990 – 2010 time period, quantify the effects of these emission changes on air quality and aerosol/radiation feedbacks using both observations and model simulations, and fin...

Joint Machine Learning and Game Theory for Rate Control in High Efficiency Video Coding.

PubMed

Gao, Wei; Kwong, Sam; Jia, Yuheng

2017-08-25

In this paper, a joint machine learning and game theory modeling (MLGT) framework is proposed for inter frame coding tree unit (CTU) level bit allocation and rate control (RC) optimization in High Efficiency Video Coding (HEVC). First, a support vector machine (SVM) based multi-classification scheme is proposed to improve the prediction accuracy of CTU-level Rate-Distortion (R-D) model. The legacy "chicken-and-egg" dilemma in video coding is proposed to be overcome by the learning-based R-D model. Second, a mixed R-D model based cooperative bargaining game theory is proposed for bit allocation optimization, where the convexity of the mixed R-D model based utility function is proved, and Nash bargaining solution (NBS) is achieved by the proposed iterative solution search method. The minimum utility is adjusted by the reference coding distortion and frame-level Quantization parameter (QP) change. Lastly, intra frame QP and inter frame adaptive bit ratios are adjusted to make inter frames have more bit resources to maintain smooth quality and bit consumption in the bargaining game optimization. Experimental results demonstrate that the proposed MLGT based RC method can achieve much better R-D performances, quality smoothness, bit rate accuracy, buffer control results and subjective visual quality than the other state-of-the-art one-pass RC methods, and the achieved R-D performances are very close to the performance limits from the FixedQP method.

A structural regression model for relationship between indoor air quality with dissatisfaction of occupants in education environment

NASA Astrophysics Data System (ADS)

Hosseini, Hamid Reza; Yunos, Mohd Yazid Mohd; Ismail, Sumarni; Yaman, Maheran

2017-12-01

This paper analysis the effects of indoor air elements on the dissatisfaction of occupants in education of environments. Tries to find the equation model for increasing the comprehension about these affects and optimizes satisfaction of occupants about indoor environment. Subsequently, increase performance of students, lecturers and staffs. As the method, a satisfaction questionnaire (SQ) and measuring environment elements (MEE) was conducted, 143 respondents at five classrooms, four staff rooms and five lectures rooms were considered. Temperature, air velocity and humidity (TVH) were used as independent variables and dissatisfaction as dependent variable. The hypothesis was tested for significant relationship between variables, and analysis was applied. Results found that indoor air quality presents direct effects on dissatisfaction of occupants and indirect effects on performance and the highest effects fallowed by temperature. These results may help to optimize the quality of efficiency and effectiveness in education environments.

Decadal application of WRF/Chem for regional air quality and climate modeling over the U.S. under the representative concentration pathways scenarios. Part 1: Model evaluation and impact of downscaling

NASA Astrophysics Data System (ADS)

Yahya, Khairunnisa; Wang, Kai; Campbell, Patrick; Chen, Ying; Glotfelty, Timothy; He, Jian; Pirhalla, Michael; Zhang, Yang

2017-03-01

An advanced online-coupled meteorology-chemistry model, i.e., the Weather Research and Forecasting Model with Chemistry (WRF/Chem), is applied for current (2001-2010) and future (2046-2055) decades under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios to examine changes in future climate, air quality, and their interactions. In this Part I paper, a comprehensive model evaluation is carried out for current decade to assess the performance of WRF/Chem and WRF under both scenarios and the benefits of downscaling the North Carolina State University's (NCSU) version of the Community Earth System Model (CESM_NCSU) using WRF/Chem. The evaluation of WRF/Chem shows an overall good performance for most meteorological and chemical variables on a decadal scale. Temperature at 2-m is overpredicted by WRF (by ∼0.2-0.3 °C) but underpredicted by WRF/Chem (by ∼0.3-0.4 °C), due to higher radiation from WRF. Both WRF and WRF/Chem show large overpredictions for precipitation, indicating limitations in their microphysics or convective parameterizations. WRF/Chem with prognostic chemical concentrations, however, performs much better than WRF with prescribed chemical concentrations for radiation variables, illustrating the benefit of predicting gases and aerosols and representing their feedbacks into meteorology in WRF/Chem. WRF/Chem performs much better than CESM_NCSU for most surface meteorological variables and O3 hourly mixing ratios. In addition, WRF/Chem better captures observed temporal and spatial variations than CESM_NCSU. CESM_NCSU performance for radiation variables is comparable to or better than WRF/Chem performance because of the model tuning in CESM_NCSU that is routinely made in global models.

Application of Six Sigma Model to Evaluate the Analytical Quality of Four HbA1c Analyzers.

PubMed

Maesa, Jos Eacute M; Fern Aacute Ndez-Riejos, Patricia; S Aacute Nchez-Mora, Catalina; Toro-Crespo, Mar Iacute A De; Gonz Aacute Lez-Rodriguez, Concepci Oacute N

2017-01-01

The Six Sigma Model is a global quality management system applicable to the determination of glycated hemoglobin (HbA1c). In addition, this model can ensure the three characteristics influencing the patient risk: the correct performance of the analytical method with low inaccuracy and bias, the quality control strategy used by the laboratory, and the necessary quality of the analyte. The aim of this study is to use the Six Sigma Model for evaluating quality criteria in the determination of glycated hemoglobin HbA1c and its application to assess four different HbA1c analyzers. Four HbA1c analyzers were evaluated: HA-8180V®, D-100®, G8®, and Variant II Turbo®. For 20 consecutive days, two levels of quality control (high and low) provided by the manufacturers were measured in each of the instruments. Imprecision (CV), bias, and Sigma values (σ) were calculated with the data obtained and a method decision chart was developed considering a range of quality requirements (allowable total error, TEa). For a TEa = 3%, HA-8180V = 1.54 σ, D-100 = 1.63 σ, G8 = 2.20 σ, and Variant II Turbo = -0.08 σ. For a TEa = 4%, HA-8180V = 2.34 σ, D-100 = 2.32 σ, G8 = 3.74 σ, and Variant II Turbo = 0.16 σ. For a TEa = 10%, HA8180V = 7.12 σ, D-100 = 6.46 σ, G8 = 13.0 σ, and Variant II Turbo = 1.56 σ. Applying the Stockholm consensus and its subsequent Milan review to the results: the maximum level in quality requirements for HbA1c is an allowable total error (TEa) = 3%, G8 is located in region 2 σ (2.20), which is a poor result, and HA-8180V and D-100 are both in region 1 σ (1.54 and 1.63, respectively), which is an unacceptable analytical performance.

Rehabilitation of compensable workplace injuries: effective payment models for quality vocational rehabilitation outcomes in a changing social landscape.

PubMed

Matthews, Lynda R; Hanley, Francine; Lewis, Virginia; Howe, Caroline

2015-01-01

With social and economic costs of workplace injury on the increase, efficient payment models that deliver quality rehabilitation outcomes are of increasing interest. This paper provides a perspective on the issue informed by both refereed literature and published research material not available commercially (gray literature). A review of payment models, workers' compensation and compensable injury identified relevant peer-reviewed and gray literature that informed our discussion. Fee-for-service and performance-based payment models dominate the health and rehabilitation literature, each described as having benefits and challenges to achieving quality outcomes for consumers. There appears to be a movement toward performance-based payments in compensable workplace injury settings as they are perceived to promote time-efficient services and support innovation in rehabilitation practice. However, it appears that the challenges that arise for workplace-based rehabilitation providers and professionals when working under the various payment models, such as staff retention and quality of client-practitioner relationship, are absent from the literature and this could lead to flawed policy decisions. Robust evidence of the benefits and costs associated with different payment models - from the perspectives of clients/consumers, funders and service providers - is needed to inform best practice in rehabilitation of compensable workplace injuries. Available but limited evidence suggests that payment models providing financial incentives for stakeholder-agreed vocational rehabilitation outcomes tend to improve service effectiveness in workers' compensation settings, although there is little evidence of service quality or client satisfaction. Working in a system that identifies payments for stakeholder-agreed outcomes may be more satisfying for rehabilitation practitioners in workers' compensation settings by allowing more clinical autonomy and innovative practice. Researchers need to work closely with the compensation and rehabilitation sector as well as governments to establish robust evidence of the benefits and costs of payment models, from the perspectives of clients/consumers, funders, service providers and rehabilitation professionals.

Image Quality Modeling and Characterization of Nyquist Sampled Framing Systems with Operational Considerations for Remote Sensing

NASA Astrophysics Data System (ADS)

Garma, Rey Jan D.

The trade between detector and optics performance is often conveyed through the Q metric, which is defined as the ratio of detector sampling frequency and optical cutoff frequency. Historically sensors have operated at Q ≈ 1, which introduces aliasing but increases the system modulation transfer function (MTF) and signal-to-noise ratio (SNR). Though mathematically suboptimal, such designs have been operationally ideal when considering system parameters such as pointing stability and detector performance. Substantial advances in read noise and quantum efficiency of modern detectors may compensate for the negative aspects associated with balancing detector/optics performance, presenting an opportunity to revisit the potential for implementing Nyquist-sampled (Q ≈ 2) sensors. A digital image chain simulation is developed and validated against a laboratory testbed using objective and subjective assessments. Objective assessments are accomplished by comparison of the modeled MTF and measurements from slant-edge photographs. Subjective assessments are carried out by performing a psychophysical study where subjects are asked to rate simulation and testbed imagery against a DeltaNIIRS scale with the aid of a marker set. Using the validated model, additional test cases are simulated to study the effects of increased detector sampling on image quality with operational considerations. First, a factorial experiment using Q-sampling, pointing stability, integration time, and detector performance is conducted to measure the main effects and interactions of each on the response variable, DeltaNIIRS. To assess the fidelity of current models, variants of the General Image Quality Equation (GIQE) are evaluated against subject-provided ratings and two modified GIQE versions are proposed. Finally, using the validated simulation and modified IQE, trades are conducted to ascertain the feasibility of implementing Q ≈ 2 designs in future systems.

Impact of Apex Model parameterization strategy on estimated benefit of conservation practices

USDA-ARS?s Scientific Manuscript database

Three parameterized Agriculture Policy Environmental eXtender (APEX) models for corn-soybean rotation on clay pan soils were developed with the objectives, 1. Evaluate model performance of three parameterization strategies on a validation watershed; and 2. Compare predictions of water quality benefi...

RESULTS OF PHOTOCHEMICAL SIMULATIONS OF SUBGRID SCALE POINT SOURCE EMISSIONS WITH THE MODELS-3 CMAQ MODELING SYSTEM

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) / Plume-in-Grid (PinG) model was applied on a domain encompassing the greater Nashville, Tennessee region. Model simulations were performed for selected days in July 1995 during the Southern Oxidant Study (SOS) field study program wh...

Preliminary Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.1

EPA Science Inventory

The AMAD will perform two annual CMAQ model simulations, one with the current publically available version of the CMAQ model (v5.0.2) and the other with the beta version of the new model (v5.1). The results of each model simulation will then be compared to observations and the pe...

Evaluation of regional climate simulations for air quality modelling purposes

NASA Astrophysics Data System (ADS)

Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

2013-05-01

In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

PubMed Central

2014-01-01

Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines.

PubMed

Cao, Renzhi; Wang, Zheng; Wang, Yiheng; Cheng, Jianlin

2014-04-28

It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/.

Information technology model for evaluating emergency medicine teaching

NASA Astrophysics Data System (ADS)

Vorbach, James; Ryan, James

1996-02-01

This paper describes work in progress to develop an Information Technology (IT) model and supporting information system for the evaluation of clinical teaching in the Emergency Medicine (EM) Department of North Shore University Hospital. In the academic hospital setting student physicians, i.e. residents, and faculty function daily in their dual roles as teachers and students respectively, and as health care providers. Databases exist that are used to evaluate both groups in either academic or clinical performance, but rarely has this information been integrated to analyze the relationship between academic performance and the ability to care for patients. The goal of the IT model is to improve the quality of teaching of EM physicians by enabling the development of integrable metrics for faculty and resident evaluation. The IT model will include (1) methods for tracking residents in order to develop experimental databases; (2) methods to integrate lecture evaluation, clinical performance, resident evaluation, and quality assurance databases; and (3) a patient flow system to monitor patient rooms and the waiting area in the Emergency Medicine Department, to record and display status of medical orders, and to collect data for analyses.

Sleep quantity, quality, and insomnia symptoms of medical students during clinical years. Relationship with stress and academic performance.

PubMed

Alsaggaf, Mohammed A; Wali, Siraj O; Merdad, Roah A; Merdad, Leena A

2016-02-01

To determine sleep habits and sleep quality in medical students during their clinical years using validated measures; and to investigate associations with academic performance and psychological stress. In this cross-sectional study, medical students (n=320) were randomly selected from a list of all enrolled clinical-year students in a Saudi medical school from 2011-2012. Students filled a questionnaire including demographic and lifestyle factors, Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and Perceived Stress Scale. Students acquired on average, 5.8 hours of sleep each night, with an average bedtime at 01:53. Approximately 8% reported acquiring sleep during the day, and not during nighttime. Poor sleep quality was present in 30%, excessive daytime sleepiness (EDS) in 40%, and insomnia symptoms in 33% of students. Multivariable regression models revealed significant associations between stress, poor sleep quality, and EDS. Poorer academic performance and stress were associated with symptoms of insomnia. Sleep deprivation, poor sleep quality, and EDS are common among clinical years medical students. High levels of stress and the pressure of maintaining grade point averages may be influencing their quality of sleep.

Optimum cooking conditions for shrimp and Atlantic salmon.

PubMed

Brookmire, Lauren; Mallikarjunan, P; Jahncke, M; Grisso, R

2013-02-01

The quality and safety of a cooked food product depends on many variables, including the cooking method and time-temperature combinations employed. The overall heating profile of the food can be useful in predicting the quality changes and microbial inactivation occurring during cooking. Mathematical modeling can be used to attain the complex heating profile of a food product during cooking. Studies were performed to monitor the product heating profile during the baking and boiling of shrimp and the baking and pan-frying of salmon. Product color, texture, moisture content, mass loss, and pressed juice were evaluated during the cooking processes as the products reached the internal temperature recommended by the FDA. Studies were also performed on the inactivation of Salmonella cocktails in shrimp and salmon. To effectively predict inactivation during cooking, the Bigelow, Fermi distribution, and Weibull distribution models were applied to the Salmonella thermal inactivation data. Minimum cooking temperatures necessary to destroy Salmonella in shrimp and salmon were determined. The heating profiles of the 2 products were modeled using the finite difference method. Temperature data directly from the modeled heating profiles were then used in the kinetic modeling of quality change and Salmonella inactivation during cooking. The optimum cooking times for a 3-log reduction of Salmonella and maintaining 95% of quality attributes are 100, 233, 159, 378, 1132, and 399 s for boiling extra jumbo shrimp, baking extra jumbo shrimp, boiling colossal shrimp, baking colossal shrimp, baking Atlantic salmon, and pan frying Atlantic Salmon, respectively. © 2013 Institute of Food Technologists®

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.

Pay-for-performance in disease management: a systematic review of the literature.

PubMed

de Bruin, Simone R; Baan, Caroline A; Struijs, Jeroen N

2011-10-14

Pay-for-performance (P4P) is increasingly implemented in the healthcare system to encourage improvements in healthcare quality. P4P is a payment model that rewards healthcare providers for meeting pre-established targets for delivery of healthcare services by financial incentives. Based on their performance, healthcare providers receive either additional or reduced payment. Currently, little is known about P4P schemes intending to improve delivery of chronic care through disease management. The objectives of this paper are therefore to provide an overview of P4P schemes used to stimulate delivery of chronic care through disease management and to provide insight into their effects on healthcare quality and costs. A systematic PubMed search was performed for English language papers published between 2000 and 2010 describing P4P schemes related to the implementation of disease management. Wagner's chronic care model was used to make disease management operational. Eight P4P schemes were identified, introduced in the USA (n = 6), Germany (n = 1), and Australia (n = 1). Five P4P schemes were part of a larger scheme of interventions to improve quality of care, whereas three P4P schemes were solely implemented. Most financial incentives were rewards, selective, and granted on the basis of absolute performance. More variation was found in incented entities and the basis for providing incentives. Information about motivation, certainty, size, frequency, and duration of the financial incentives was generally limited. Five studies were identified that evaluated the effects of P4P on healthcare quality. Most studies showed positive effects of P4P on healthcare quality. No studies were found that evaluated the effects of P4P on healthcare costs. The number of P4P schemes to encourage disease management is limited. Hardly any information is available about the effects of such schemes on healthcare quality and costs. © 2011 de Bruin et al; licensee BioMed Central Ltd.

Pay-for-performance in disease management: a systematic review of the literature

PubMed Central

2011-01-01

Background Pay-for-performance (P4P) is increasingly implemented in the healthcare system to encourage improvements in healthcare quality. P4P is a payment model that rewards healthcare providers for meeting pre-established targets for delivery of healthcare services by financial incentives. Based on their performance, healthcare providers receive either additional or reduced payment. Currently, little is known about P4P schemes intending to improve delivery of chronic care through disease management. The objectives of this paper are therefore to provide an overview of P4P schemes used to stimulate delivery of chronic care through disease management and to provide insight into their effects on healthcare quality and costs. Methods A systematic PubMed search was performed for English language papers published between 2000 and 2010 describing P4P schemes related to the implementation of disease management. Wagner's chronic care model was used to make disease management operational. Results Eight P4P schemes were identified, introduced in the USA (n = 6), Germany (n = 1), and Australia (n = 1). Five P4P schemes were part of a larger scheme of interventions to improve quality of care, whereas three P4P schemes were solely implemented. Most financial incentives were rewards, selective, and granted on the basis of absolute performance. More variation was found in incented entities and the basis for providing incentives. Information about motivation, certainty, size, frequency, and duration of the financial incentives was generally limited. Five studies were identified that evaluated the effects of P4P on healthcare quality. Most studies showed positive effects of P4P on healthcare quality. No studies were found that evaluated the effects of P4P on healthcare costs. Conclusion The number of P4P schemes to encourage disease management is limited. Hardly any information is available about the effects of such schemes on healthcare quality and costs. PMID:21999234

Performance evaluation of image-intensifier-TV fluoroscopy systems

NASA Astrophysics Data System (ADS)

van der Putten, Wilhelm J.; Bouley, Shawn

1995-05-01

Through use of a computer model and an aluminum low contrast phantom developed in-house, a method has been developed which is able to grade the imaging performance of fluoroscopy systems through use of a variable, K. This parameter was derived from Rose's model of image perception and is here used as a figure of merit to grade fluoroscopy systems. From Rose's model for an ideal system, a typical value of K for the perception of low contrast details should be between 3 and 7, assuming threshold vision by human observers. Thus, various fluoroscopy systems are graded with different values of K, with a lower value of K indicating better imaging performance of the system. A series of fluoroscopy systems have been graded where the best system produces a value in the low teens, while the poorest systems produce a value in the low twenties. Correlation with conventional image quality measurements is good and the method has the potential for automated assessment of image quality.

Evaluation of multivariate linear regression and artificial neural networks in prediction of water quality parameters

PubMed Central

2014-01-01

This paper examined the efficiency of multivariate linear regression (MLR) and artificial neural network (ANN) models in prediction of two major water quality parameters in a wastewater treatment plant. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as well as indirect indicators of organic matters are representative parameters for sewer water quality. Performance of the ANN models was evaluated using coefficient of correlation (r), root mean square error (RMSE) and bias values. The computed values of BOD and COD by model, ANN method and regression analysis were in close agreement with their respective measured values. Results showed that the ANN performance model was better than the MLR model. Comparative indices of the optimized ANN with input values of temperature (T), pH, total suspended solid (TSS) and total suspended (TS) for prediction of BOD was RMSE = 25.1 mg/L, r = 0.83 and for prediction of COD was RMSE = 49.4 mg/L, r = 0.81. It was found that the ANN model could be employed successfully in estimating the BOD and COD in the inlet of wastewater biochemical treatment plants. Moreover, sensitive examination results showed that pH parameter have more effect on BOD and COD predicting to another parameters. Also, both implemented models have predicted BOD better than COD. PMID:24456676

Routing UAVs to Co-Optimize Mission Effectiveness and Network Performance with Dynamic Programming

DTIC Science & Technology

2011-03-01

Heuristics on Hexagonal Connected Dominating Sets to Model Routing Dissemination," in Communication Theory, Reliability, and Quality of Service (CTRQ...24] Matthew Capt. USAF Compton, Improving the Quality of Service and Security of Military Networks with a Network Tasking Order Process, 2010. [25...Wesley, 2006. [32] James Haught, "Adaptive Quality of Service Engine with Dynamic Queue Control," Air Force Institute of Technology, Wright

On the use and the performance of software reliability growth models

NASA Technical Reports Server (NTRS)

Keiller, Peter A.; Miller, Douglas R.

1991-01-01

We address the problem of predicting future failures for a piece of software. The number of failures occurring during a finite future time interval is predicted from the number failures observed during an initial period of usage by using software reliability growth models. Two different methods for using the models are considered: straightforward use of individual models, and dynamic selection among models based on goodness-of-fit and quality-of-prediction criteria. Performance is judged by the relative error of the predicted number of failures over future finite time intervals relative to the number of failures eventually observed during the intervals. Six of the former models and eight of the latter are evaluated, based on their performance on twenty data sets. Many open questions remain regarding the use and the performance of software reliability growth models.

Mechanistic-Empirical Pavement Design Guide Flexible Pavement Performance Prediction Models Volume II Reference Manual

DOT National Transportation Integrated Search

2007-08-01

The objective of this research study was to develop performance characteristics or variables (e.g., ride quality, rutting, : fatigue cracking, transverse cracking) of flexible pavements in Montana, and to use these characteristics in the : implementa...

Identification of Long Bone Fractures in Radiology Reports Using Natural Language Processing to support Healthcare Quality Improvement.

PubMed

Grundmeier, Robert W; Masino, Aaron J; Casper, T Charles; Dean, Jonathan M; Bell, Jamie; Enriquez, Rene; Deakyne, Sara; Chamberlain, James M; Alpern, Elizabeth R

2016-11-09

Important information to support healthcare quality improvement is often recorded in free text documents such as radiology reports. Natural language processing (NLP) methods may help extract this information, but these methods have rarely been applied outside the research laboratories where they were developed. To implement and validate NLP tools to identify long bone fractures for pediatric emergency medicine quality improvement. Using freely available statistical software packages, we implemented NLP methods to identify long bone fractures from radiology reports. A sample of 1,000 radiology reports was used to construct three candidate classification models. A test set of 500 reports was used to validate the model performance. Blinded manual review of radiology reports by two independent physicians provided the reference standard. Each radiology report was segmented and word stem and bigram features were constructed. Common English "stop words" and rare features were excluded. We used 10-fold cross-validation to select optimal configuration parameters for each model. Accuracy, recall, precision and the F1 score were calculated. The final model was compared to the use of diagnosis codes for the identification of patients with long bone fractures. There were 329 unique word stems and 344 bigrams in the training documents. A support vector machine classifier with Gaussian kernel performed best on the test set with accuracy=0.958, recall=0.969, precision=0.940, and F1 score=0.954. Optimal parameters for this model were cost=4 and gamma=0.005. The three classification models that we tested all performed better than diagnosis codes in terms of accuracy, precision, and F1 score (diagnosis code accuracy=0.932, recall=0.960, precision=0.896, and F1 score=0.927). NLP methods using a corpus of 1,000 training documents accurately identified acute long bone fractures from radiology reports. Strategic use of straightforward NLP methods, implemented with freely available software, offers quality improvement teams new opportunities to extract information from narrative documents.

Quality-Related Monitoring and Grading of Granulated Products by Weibull-Distribution Modeling of Visual Images with Semi-Supervised Learning

PubMed Central

Liu, Jinping; Tang, Zhaohui; Xu, Pengfei; Liu, Wenzhong; Zhang, Jin; Zhu, Jianyong

2016-01-01

The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products, fabric textiles, are comprised of a large number of independent particles or stochastically stacking locally homogeneous fragments, whose analysis and understanding remains challenging. A method of image statistical modeling-based OPQI for GP quality grading and monitoring by a Weibull distribution(WD) model with a semi-supervised learning classifier is presented. WD-model parameters (WD-MPs) of GP images’ spatial structures, obtained with omnidirectional Gaussian derivative filtering (OGDF), which were demonstrated theoretically to obey a specific WD model of integral form, were extracted as the visual features. Then, a co-training-style semi-supervised classifier algorithm, named COSC-Boosting, was exploited for semi-supervised GP quality grading, by integrating two independent classifiers with complementary nature in the face of scarce labeled samples. Effectiveness of the proposed OPQI method was verified and compared in the field of automated rice quality grading with commonly-used methods and showed superior performance, which lays a foundation for the quality control of GP on assembly lines. PMID:27367703

Systematic void fraction studies with RELAP5, FRANCESCA and HECHAN

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

Stosic, Z.; Preusche, G.

1996-08-01

In enhancing the scope of standard thermal-hydraulic codes applications beyond its capabilities, i.e. coupling with a one and/or three-dimensional kinetics core model, the void fraction, transferred from thermal-hydraulics to the core model, plays a determining role in normal operating range and high core flow, as the generated heat and axial power profiles are direct functions of void distribution in the core. Hence, it is very important to know if the void quality models in the programs which have to be coupled are compatible to allow the interactive exchange of data which are based on these constitutive void-quality relations. The presentedmore » void fraction study is performed in order to give the basis for the conclusion whether a transient core simulation using the RELAP5 void fractions can calculate the axial power shapes adequately. Because of that, the void fractions calculated with RELAP5 are compared with those calculated by BWR safety code for licensing--FRANCESCA and the best estimate model for pre- and post-dryout calculation in BWR heated channel--HECHAN. In addition, a comparison with standard experimental void-quality benchmark tube data is performed for the HECHAN code.« less

Quality assessment of protein model-structures based on structural and functional similarities

PubMed Central

2012-01-01

Background Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. Results GOBA - Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. Conclusions The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and one of CASP9, compared to the contest participants. Consequently, GOBA offers a novel single model quality assessment program that addresses the practical needs of biologists. In conjunction with other Model Quality Assessment Programs (MQAPs), it would prove useful for the evaluation of single protein models. PMID:22998498

A pollution fate and transport model application in a semi-arid region: Is some number better than no number?

PubMed

Özcan, Zeynep; Başkan, Oğuz; Düzgün, H Şebnem; Kentel, Elçin; Alp, Emre

2017-10-01

Fate and transport models are powerful tools that aid authorities in making unbiased decisions for developing sustainable management strategies. Application of pollution fate and transport models in semi-arid regions has been challenging because of unique hydrological characteristics and limited data availability. Significant temporal and spatial variability in rainfall events, complex interactions between soil, vegetation and topography, and limited water quality and hydrological data due to insufficient monitoring network make it a difficult task to develop reliable models in semi-arid regions. The performances of these models govern the final use of the outcomes such as policy implementation, screening, economical analysis, etc. In this study, a deterministic distributed fate and transport model, SWAT, is applied in Lake Mogan Watershed, a semi-arid region dominated by dry agricultural practices, to estimate nutrient loads and to develop the water budget of the watershed. To minimize the discrepancy due to limited availability of historical water quality data extensive efforts were placed in collecting site-specific data for model inputs such as soil properties, agricultural practice information and land use. Moreover, calibration parameter ranges suggested in the literature are utilized during calibration in order to obtain more realistic representation of Lake Mogan Watershed in the model. Model performance is evaluated using comparisons of the measured data with 95%CI for the simulated data and comparison of unit pollution load estimations with those provided in the literature for similar catchments, in addition to commonly used evaluation criteria such as Nash-Sutcliffe simulation efficiency, coefficient of determination and percent bias. These evaluations demonstrated that even though the model prediction power is not high according to the commonly used model performance criteria, the calibrated model may provide useful information in the comparison of the effects of different management practices on diffuse pollution and water quality in Lake Mogan Watershed. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrated clinical and quality improvement coaching in Son La Province, Vietnam: a model of building public sector capacity for sustainable HIV care delivery.

PubMed

Cosimi, Lisa A; Dam, Huong V; Nguyen, Thai Q; Ho, Huyen T; Do, Phuong T; Duc, Duat N; Nguyen, Huong T; Gardner, Bridget; Libman, Howard; Pollack, Todd; Hirschhorn, Lisa R

2015-07-17

The global scale-up of antiretroviral therapy included extensive training and onsite support to build the capacity of HIV health care workers. However, traditional efforts aimed at strengthening knowledge and skills often are not successful at improving gaps in the key health systems required for sustaining high quality care. We trained and mentored existing staff of the Son La provincial health department and provincial HIV clinic to work as a provincial coaching team (PCT) to provide integrated coaching in clinical HIV skills and quality improvement (QI) to the HIV clinics in the province. Nine core indicators were measured through chart extraction by clinic and provincial staff at baseline and at 6 month intervals thereafter. Coaching from the team to each of the clinics, in both QI and clinical skills, was guided by results of performance measurements, gap analyses, and resulting QI plans. After 18 months, the PCT had successfully spread QI activities, and was independently providing regular coaching to the provincial general hospital clinic and six of the eight district clinics in the province. The frequency and type of coaching was determined by performance measurement results. Clinics completed a mean of five QI projects. Quality of HIV care was improved throughout all clinics with significant increases in seven of the indicators. Overall both the PCT activities and clinic performance were sustained after integration of the model into the Vietnam National QI Program. We successfully built capacity of a team of public sector health care workers to provide integrated coaching in both clinical skills and QI across a province. The PCT is a feasible and effective model to spread and sustain quality activities and improve HIV care services in a decentralized rural setting.

Improved Surgical Outcomes for ACS NSQIP Hospitals Over Time: Evaluation of Hospital Cohorts With up to 8 Years of Participation.

PubMed

Cohen, Mark E; Liu, Yaoming; Ko, Clifford Y; Hall, Bruce L

2016-02-01

The American College of Surgeons, National Surgical Quality Improvement Program (ACS NSQIP) surgical quality feedback models are recalibrated every 6 months, and each hospital is given risk-adjusted, hierarchical model, odds ratios that permit comparison to an estimated average NSQIP hospital at a particular point in time. This approach is appropriate for "relative" benchmarking, and for targeting quality improvement efforts, but does not permit evaluation of hospital or program-wide changes in quality over time. We report on long-term improvement in surgical outcomes associated with participation in ACS NSQIP. ACS NSQIP data (2006-2013) were used to create prediction models for mortality, morbidity (any of several distinct adverse outcomes), and surgical site infection (SSI). For each model, for each hospital, and for year of first participation (hospital cohort), hierarchical model observed/expected (O/E) ratios were computed. The primary performance metric was the within-hospital trend in logged O/E ratios over time (slope) for mortality, morbidity, and SSI. Hospital-averaged log O/E ratio slopes were generally negative, indicating improving performance over time. For all hospitals, 62%, 70%, and 65% of hospitals had negative slopes for mortality, morbidity, and any SSI, respectively. For hospitals currently in the program for at least 3 years, 69%, 79%, and 71% showed improvement in mortality, morbidity, and SSI, respectively. For these hospitals, we estimate 0.8%, 3.1%, and 2.6% annual reductions (with respect to prior year's rates) for mortality, morbidity, and SSI, respectively. Participation in ACS NSQIP is associated with reductions in adverse events after surgery. The magnitude of quality improvement increases with time in the program.

An airborne remote sensing system for urban air quality

NASA Technical Reports Server (NTRS)

Duncan, L. J.; Friedman, E. J.; Keitz, E. L.; Ward, E. A.

1974-01-01

Several NASA sponsored remote sensors and possible airborne platforms were evaluated. Outputs of dispersion models for SO2 and CO pollution in the Washington, D.C. area were used with ground station data to establish the expected performance and limitations of the remote sensors. Aircraft/sensor support requirements are discussed. A method of optimum flight plan determination was made. Cost trade offs were performed. Conclusions about the implementation of various instrument packages as parts of a comprehensive air quality monitoring system in Washington are presented.

Added value in health care with six sigma.

PubMed

Lenaz, Maria P

2004-06-01

Six sigma is the structured application of the tools and techniques of quality management applied on a project basis that can enable organizations to achieve superior performance and strategic business results. The Greek character sigma has been used as a statistical term that measures how much a process varies from perfection, based on the number of defects per million units. Health care organizations using this model proceed from the lower levels of quality performance to the highest level, in which the process is nearly error free.

Managers’ Compensation in a Mixed Ownership Industry: Evidence from Nursing Homes

PubMed Central

Huang, Sean Shenghsiu; Hirth, Richard A.; Smith, Dean G.

2016-01-01

An extensive literature is devoted to differences between for-profit and non-profit health-care providers’ prices, utilization, and quality. Less is known about for-profit and non-profit managers’ compensation and its relationship with financial and quality performance. The aim of this study is to examine whether for-profit and non-profit nursing homes place differential weights on financial and quality performance in determining managers’ compensation. Using a unique 8-year dataset on Ohio nursing homes, fixed-effect regression models of managers’ compensation include financial and quality performance as well as other explanatory variables concerning firm and market characteristics and manager qualifications. Among for-profit nursing homes, compensation of owner-managers and non-owner managers are compared. Compensation of for-profit managers is significantly positively associated with profit margin and return-on-assets, while compensation of non-profit managers does not exhibit any consistent relationship with financial measures. Compensation of neither for-profit nor non-profit managers is significantly related to quality measures. Nursing home size and managers’ years of experience are the only consistent determinants of compensation. Owner-managers earn significantly higher compensation than non-owner managers and their compensation is less related to nursing home performance. Finding that home size and experience are strong determinants of compensation, and the association with ownership and financial performance for for-profit nursing homes are as expected. The insignificant relationship between compensation and quality performance is potentially troublesome. PMID:28083528

Consideration of drainage ditches and sediment rating cure on SWAT model performance

USDA-ARS?s Scientific Manuscript database

Water quality models most often require a considerable amount of data to be properly configured and in some cases this requires additional procedural steps prior to model applications. We examined two different scenarios of such input issues in a small watershed using the Soil and Water Assessment ...

OPERA: A QSAR tool for physicochemical properties and environmental fate predictions (ACS Spring meeting)

EPA Science Inventory

The collection of chemical structures and associated experimental data for QSAR modeling is facilitated by the increasing number and size of public databases. However, the performance of QSAR models highly depends on the quality of the data used and the modeling methodology. The ...

Inexact hardware for modelling weather & climate

NASA Astrophysics Data System (ADS)

Düben, Peter D.; McNamara, Hugh; Palmer, Tim

2014-05-01

The use of stochastic processing hardware and low precision arithmetic in atmospheric models is investigated. Stochastic processors allow hardware-induced faults in calculations, sacrificing exact calculations in exchange for improvements in performance and potentially accuracy and a reduction in power consumption. A similar trade-off is achieved using low precision arithmetic, with improvements in computation and communication speed and savings in storage and memory requirements. As high-performance computing becomes more massively parallel and power intensive, these two approaches may be important stepping stones in the pursuit of global cloud resolving atmospheric modelling. The impact of both, hardware induced faults and low precision arithmetic is tested in the dynamical core of a global atmosphere model. Our simulations show that both approaches to inexact calculations do not substantially affect the quality of the model simulations, provided they are restricted to act only on smaller scales. This suggests that inexact calculations at the small scale could reduce computation and power costs without adversely affecting the quality of the simulations.

Regional photochemical air quality modeling in the Mexico-US border area

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

Mendoza, A.; Russell, A.G.; Mejia, G.M.

1998-12-31

The Mexico-United States border area has become an increasingly important region due to its commercial, industrial and urban growth. As a result, environmental concerns have risen. Treaties like the North American Free Trade Agreement (NAFTA) have further motivated the development of environmental impact assessment in the area. Of particular concern are air quality, and how the activities on both sides of the border contribute to its degradation. This paper presents results of applying a three-dimensional photochemical airshed model to study air pollution dynamics along the Mexico-United States border. In addition, studies were conducted to assess how size resolution impacts themore » model performance. The model performed within acceptable statistic limits using 12.5 x 12.5 km{sup 2} grid cells, and the benefits using finer grids were limited. Results were further used to assess the influence of grid-cell size on the modeling of control strategies, where coarser grids lead to significant loss of information.« less

A linear and non-linear polynomial neural network modeling of dissolved oxygen content in surface water: Inter- and extrapolation performance with inputs' significance analysis.

PubMed

Šiljić Tomić, Aleksandra; Antanasijević, Davor; Ristić, Mirjana; Perić-Grujić, Aleksandra; Pocajt, Viktor

2018-01-01

Accurate prediction of water quality parameters (WQPs) is an important task in the management of water resources. Artificial neural networks (ANNs) are frequently applied for dissolved oxygen (DO) prediction, but often only their interpolation performance is checked. The aims of this research, beside interpolation, were the determination of extrapolation performance of ANN model, which was developed for the prediction of DO content in the Danube River, and the assessment of relationship between the significance of inputs and prediction error in the presence of values which were of out of the range of training. The applied ANN is a polynomial neural network (PNN) which performs embedded selection of most important inputs during learning, and provides a model in the form of linear and non-linear polynomial functions, which can then be used for a detailed analysis of the significance of inputs. Available dataset that contained 1912 monitoring records for 17 water quality parameters was split into a "regular" subset that contains normally distributed and low variability data, and an "extreme" subset that contains monitoring records with outlier values. The results revealed that the non-linear PNN model has good interpolation performance (R 2 =0.82), but it was not robust in extrapolation (R 2 =0.63). The analysis of extrapolation results has shown that the prediction errors are correlated with the significance of inputs. Namely, the out-of-training range values of the inputs with low importance do not affect significantly the PNN model performance, but their influence can be biased by the presence of multi-outlier monitoring records. Subsequently, linear PNN models were successfully applied to study the effect of water quality parameters on DO content. It was observed that DO level is mostly affected by temperature, pH, biological oxygen demand (BOD) and phosphorus concentration, while in extreme conditions the importance of alkalinity and bicarbonates rises over pH and BOD. Copyright © 2017 Elsevier B.V. All rights reserved.

Do mobile clinics provide high-quality antenatal care? A comparison of care delivery, knowledge outcomes and perception of quality of care between fixed and mobile clinics in central Haiti.

PubMed

Phillips, Erica; Stoltzfus, Rebecca J; Michaud, Lesly; Pierre, Gracia Lionel Fils; Vermeylen, Francoise; Pelletier, David

2017-10-16

Antenatal care (ANC) is an important health service for women in developing countries, with numerous proven benefits. Global coverage of ANC has steadily increased over the past 30 years, in part due to increased community-based outreach. However, commensurate improvements in health outcomes such as reductions in the prevalence of maternal anemia and infants born small-for-gestational age have not been achieved, even with increased coverage, indicating that quality of care may be inadequate. Mobile clinics are one community-based strategy used to further improve coverage of ANC, but their quality of care delivery has rarely been evaluated. To determine the quality of care of ANC in central Haiti, we compared adherence to national guidelines between fixed and mobile clinics by performing direct observations of antenatal care consultations and exit interviews with recipients of care using a multi-stage random sampling procedure. Outcome variables were eight components of care, and women's knowledge and perception of care quality. There were significant differences in the predicted proportion or probability of recommended services for four of eight care components, including intake, laboratory examinations, infection control, and supplies, iron folic acid supplements and Tetanus Toxoid vaccine provided to women. These care components were more likely performed in fixed clinics, except for distribution of supplies, iron-folic acid supplements, and Tetanus Toxoid vaccine, more likely provided in mobile clinics. There were no differences between clinic type for the proportion of total physical exam procedures performed, health and communication messages delivered, provider communication or documentation. Women's knowledge about educational topics was poor, but women perceived extremely high quality of care in both clinic models. Although adherence to guidelines differed by clinic type for half of the care components, both clinics had a low percentage of overall services delivered. Efforts to improve provider performance and quality are therefore needed in both models. Mobile clinics must deliver high-quality ANC to improve health and nutrition outcomes.

Prediction on carbon dioxide emissions based on fuzzy rules

NASA Astrophysics Data System (ADS)

Pauzi, Herrini; Abdullah, Lazim

2014-06-01

There are several ways to predict air quality, varying from simple regression to models based on artificial intelligence. Most of the conventional methods are not sufficiently able to provide good forecasting performances due to the problems with non-linearity uncertainty and complexity of the data. Artificial intelligence techniques are successfully used in modeling air quality in order to cope with the problems. This paper describes fuzzy inference system (FIS) to predict CO2 emissions in Malaysia. Furthermore, adaptive neuro-fuzzy inference system (ANFIS) is used to compare the prediction performance. Data of five variables: energy use, gross domestic product per capita, population density, combustible renewable and waste and CO2 intensity are employed in this comparative study. The results from the two model proposed are compared and it is clearly shown that the ANFIS outperforms FIS in CO2 prediction.

Developing Staffing Models to Support Population Health Management And Quality Oucomes in Ambulatory Care Settings.

PubMed

Haas, Sheila A; Vlasses, Frances; Havey, Julia

2016-01-01

There are multiple demands and challenges inherent in establishing staffing models in ambulatory heath care settings today. If health care administrators establish a supportive physical and interpersonal health care environment, and develop high-performing interprofessional teams and staffing models and electronic documentation systems that track performance, patients will have more opportunities to receive safe, high-quality evidence-based care that encourages patient participation in decision making, as well as provision of their care. The health care organization must be aligned and responsive to the community within which it resides, fully invested in population health management, and continuously scanning the environment for competitive, regulatory, and external environmental risks. All of these challenges require highly competent providers willing to change attitudes and culture such as movement toward collaborative practice among the interprofessional team including the patient.

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.

Image aesthetic quality evaluation using convolution neural network embedded learning

NASA Astrophysics Data System (ADS)

Li, Yu-xin; Pu, Yuan-yuan; Xu, Dan; Qian, Wen-hua; Wang, Li-peng

2017-11-01

A way of embedded learning convolution neural network (ELCNN) based on the image content is proposed to evaluate the image aesthetic quality in this paper. Our approach can not only solve the problem of small-scale data but also score the image aesthetic quality. First, we chose Alexnet and VGG_S to compare for confirming which is more suitable for this image aesthetic quality evaluation task. Second, to further boost the image aesthetic quality classification performance, we employ the image content to train aesthetic quality classification models. But the training samples become smaller and only using once fine-tuning cannot make full use of the small-scale data set. Third, to solve the problem in second step, a way of using twice fine-tuning continually based on the aesthetic quality label and content label respective is proposed, the classification probability of the trained CNN models is used to evaluate the image aesthetic quality. The experiments are carried on the small-scale data set of Photo Quality. The experiment results show that the classification accuracy rates of our approach are higher than the existing image aesthetic quality evaluation approaches.

What are the similarities and differences in structure and function among the three main models of community health centers in China: a systematic review.

PubMed

Li, Haitao; Qian, Dongfu; Griffiths, Sian; Chung, Roger Yat-Nork; Wei, Xiaolin

2015-11-10

There are three major models of primary care providers (Community Health Centers, CHCs) in China, i.e., government managed, hospital managed and privately owned CHCs. We performed a systematic review of structures and health care delivery patterns of the three models of CHCs. Studies from relevant English and Chinese databases for the period of 1997-2011 were searched. Two independent researchers extracted data from the eligible studies using a standardized abstraction form. Methodological quality of included articles was assessed with the Mixed Methods Appraisal Tool (MMAT). A total of 13 studies was included in the final analysis. Compared with the other two models, private CHCs had a smaller health workforce and lower share of government funding in their total revenues. Private CHCs also had fewer training opportunities, were less recognized by health insurance schemes and tended to provide primary care services of poor quality. Hospital managed CHCs attracted patients through their higher quality of clinical care, while private CHCs attracted users through convenience and medical equipment. Our study suggested that government and hospital managed CHCs were more competent and provided better primary care than privately owned CHCs. Further studies are warranted to comprehensively compare performances among different models of CHCs.

Implementation of a channelized Hotelling observer model to assess image quality of x-ray angiography systems.

PubMed

Favazza, Christopher P; Fetterly, Kenneth A; Hangiandreou, Nicholas J; Leng, Shuai; Schueler, Beth A

2015-01-01

Evaluation of flat-panel angiography equipment through conventional image quality metrics is limited by the scope of standard spatial-domain image quality metric(s), such as contrast-to-noise ratio and spatial resolution, or by restricted access to appropriate data to calculate Fourier domain measurements, such as modulation transfer function, noise power spectrum, and detective quantum efficiency. Observer models have been shown capable of overcoming these limitations and are able to comprehensively evaluate medical-imaging systems. We present a spatial domain-based channelized Hotelling observer model to calculate the detectability index (DI) of our different sized disks and compare the performance of different imaging conditions and angiography systems. When appropriate, changes in DIs were compared to expectations based on the classical Rose model of signal detection to assess linearity of the model with quantum signal-to-noise ratio (SNR) theory. For these experiments, the estimated uncertainty of the DIs was less than 3%, allowing for precise comparison of imaging systems or conditions. For most experimental variables, DI changes were linear with expectations based on quantum SNR theory. DIs calculated for the smallest objects demonstrated nonlinearity with quantum SNR theory due to system blur. Two angiography systems with different detector element sizes were shown to perform similarly across the majority of the detection tasks.

Evaluation of the functional performance and technical quality of an Electronic Documentation System of the Nursing Process.

PubMed

de Oliveira, Neurilene Batista; Peres, Heloisa Helena Ciqueto

2015-01-01

To evaluate the functional performance and the technical quality of the Electronic Documentation System of the Nursing Process of the Teaching Hospital of the University of São Paulo. exploratory-descriptive study. The Quality Model of regulatory standard 25010 and the Evaluation Process defined under regulatory standard 25040, both of the International Organization for Standardization/International Electrotechnical Commission. The quality characteristics evaluated were: functional suitability, reliability, usability, performance efficiency, compatibility, security, maintainability and portability. The sample was made up of 37 evaluators. in the evaluation of the specialists in information technology, only the characteristic of usability obtained a rate of positive responses of less than 70%. For the nurse lecturers, all the quality characteristics obtained a rate of positive responses of over 70%. The staff nurses of the medical and surgical clinics with experience in using the system) and staff nurses from other units of the hospital and from other health institutions (without experience in using the system) obtained rates of positive responses of more than 70% referent to the functional suitability, usability, and security. However, performance efficiency, reliability and compatibility all obtained rates below the parameter established. the software achieved rates of positive responses of over 70% for the majority of the quality characteristics evaluated.

Exploring the effect of at-risk case management compensation on hospital pay-for-performance outcomes: tools for change.

PubMed

Granata, Randy L; Hamilton, Karen

2015-01-01

Acute care nurse case managers are charged with compliance oversight, managing throughput, and ensuring safe care transitions. Leveraging the roles of nurse case managers and social workers during care transitions translates into improved fiscal performance under the Affordable Care Act. This article aims to equip leaders in the field of case management with tools to facilitate the alignment of case management systems with hospital pay-for-performance measures. A quality improvement project was implemented at a hospital in south Alabama to examine the question: for acute care case managers, what is the effect of key performance indictors using an at-risk compensation model in comparison to past nonincentive models on hospital readmissions, lengths of stay, and patient satisfaction surrounding the discharge process. Inpatient acute care hospital. The implementation of an at-risk compensation model using key performance indicators, Lean Six Sigma methodology, and Creative Health Care Management's Relationship-Based Care framework demonstrated reduced length of stay, hospital readmissions, and improved patient experiences. Regulatory changes and new models of reimbursement in the acute care environment have created the perfect storm for case management leaders. Hospital fiscal performance is dependent on effective case management processes and the ability to optimize scarce resources. The quality improvement project aimed to further align case management systems and structures with hospital pay-for-performance measures. Tools for change were presented to assist leaders with the change acceleration process.

High Fidelity BWR Fuel Simulations

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

Yoon, Su Jong

This report describes the Consortium for Advanced Simulation of Light Water Reactors (CASL) work conducted for completion of the Thermal Hydraulics Methods (THM) Level 3 milestone THM.CFD.P13.03: High Fidelity BWR Fuel Simulation. High fidelity computational fluid dynamics (CFD) simulation for Boiling Water Reactor (BWR) was conducted to investigate the applicability and robustness performance of BWR closures. As a preliminary study, a CFD model with simplified Ferrule spacer grid geometry of NUPEC BWR Full-size Fine-mesh Bundle Test (BFBT) benchmark has been implemented. Performance of multiphase segregated solver with baseline boiling closures has been evaluated. Although the mean values of void fractionmore » and exit quality of CFD result for BFBT case 4101-61 agreed with experimental data, the local void distribution was not predicted accurately. The mesh quality was one of the critical factors to obtain converged result. The stability and robustness of the simulation was mainly affected by the mesh quality, combination of BWR closure models. In addition, the CFD modeling of fully-detailed spacer grid geometry with mixing vane is necessary for improving the accuracy of CFD simulation.« less

Geospatial Modelling for Micro Zonation of Groundwater Regime in Western Assam, India

NASA Astrophysics Data System (ADS)

Singh, R. P.

2016-12-01

Water, most precious natural resource on earth, is vital to sustain the natural system and human civilisation on the earth. The Assam state located in north-eastern part of India has a relatively good source of ground water due to their geographic and physiographic location but there is problem deterioration of groundwater quality causing major health problem in the area. In this study, I tried a integrated study of remote sensing and GIS and chemical analysis of groundwater samples to throw a light over groundwater regime and provides information for decision makers to make sustainable water resource management. The geospatial modelling performed by integrating hydrogeomorphic features. Geomorphology, lineament, Drainage, Landuse/landcover layer were generated through visual interpretation on satellite image (LISS III) based on tone, texture, shape, size, and arrangement of the features. Slope layer was prepared by using SRTM DEM data set .The LULC of the area were categories in to 6 classes of Agricultural field, Forest area ,River, Settlement , Tree-clad area and Wetlands. The geospatial modelling performed through weightage and rank method in GIS, depending on the influence of the features on ground water regime. To Assess the ground water quality of the area 45 groundwater samples have been collected from the field and chemical analysis performed through the standard method in the laboratory. The overall assessment of the ground water quality of the area analyse through Water Quality Index and found that about 70% samples are not potable for drinking purposes due to higher concentration Arsenic, Fluoride and Iron. It appears that, source of all these pollutants geologically and geomorphologically derived. Interpolated layer of Water Quality Index and geospatial modelled Groundwater potential layer provides a holistic view of groundwater scenario and provide direction for better planning and groundwater resource management. Study will be discussed in details during the conference.

A photosynthesis-based two-leaf canopy stomatal conductance model for meteorology and air quality modeling with WRF/CMAQ PX LSM

NASA Astrophysics Data System (ADS)

Ran, Limei; Pleim, Jonathan; Song, Conghe; Band, Larry; Walker, John T.; Binkowski, Francis S.

2017-02-01

A coupled photosynthesis-stomatal conductance model with single-layer sunlit and shaded leaf canopy scaling is implemented and evaluated in a diagnostic box model with the Pleim-Xiu land surface model (PX LSM) and ozone deposition model components taken directly from the meteorology and air quality modeling system - WRF/CMAQ (Weather Research and Forecast model and Community Multiscale Air Quality model). The photosynthesis-based model for PX LSM (PX PSN) is evaluated at a FLUXNET site for implementation against different parameterizations and the current PX LSM approach with a simple Jarvis function (PX Jarvis). Latent heat flux (LH) from PX PSN is further evaluated at five FLUXNET sites with different vegetation types and landscape characteristics. Simulated ozone deposition and flux from PX PSN are evaluated at one of the sites with ozone flux measurements. Overall, the PX PSN simulates LH as well as the PX Jarvis approach. The PX PSN, however, shows distinct advantages over the PX Jarvis approach for grassland that likely result from its treatment of C3 and C4 plants for CO2 assimilation. Simulations using Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) rather than LAI measured at each site assess how the model would perform with grid averaged data used in WRF/CMAQ. MODIS LAI estimates degrade model performance at all sites but one site having exceptionally old and tall trees. Ozone deposition velocity and ozone flux along with LH are simulated especially well by the PX PSN compared to significant overestimation by the PX Jarvis for a grassland site.

High-Performance Work Systems: American Models of Workplace Transformation.

ERIC Educational Resources Information Center

Appelbaum, Eileen; Batt, Rosemary

Rising competition in world and domestic markets for the past 2 decades has necessitated that U.S. companies undergo significant transformations to improve their performance with respect to a wide array of efficiency and quality indicators. Research on the transformations recently undertaken by some U.S. companies to boost performance revealed two…

Improved Fuzzy Modelling to Predict the Academic Performance of Distance Education Students

ERIC Educational Resources Information Center

Yildiz, Osman; Bal, Abdullah; Gulsecen, Sevinc

2013-01-01

It is essential to predict distance education students' year-end academic performance early during the course of the semester and to take precautions using such prediction-based information. This will, in particular, help enhance their academic performance and, therefore, improve the overall educational quality. The present study was on the…

A Five- Year CMAQ Model Performance for Wildfires and ...

EPA Pesticide Factsheets

Biomass burning has been identified as an important contributor to the degradation of air quality because of its impact on ozone and particulate matter. Two components of the biomass burning inventory, wildfires and prescribed fires are routinely estimated in the national emissions inventory. However, there is a large amount of uncertainty in the development of these emission inventory sectors. We have completed a 5 year set of CMAQ model simulations (2008-2012) in which we have simulated regional air quality with and without the wildfire and prescribed fire inventory. We will examine CMAQ model performance over regions with significant PM2.5 and Ozone contribution from prescribed fires and wildfires. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

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.

Hyperspectral water quality retrieval model: taking Malaysia inshore sea area as an example

NASA Astrophysics Data System (ADS)

Cui, Tingwei; Zhang, Jie; Ma, Yi; Li, Jing; Lim, Boonleong; Roslinah, Samad

2007-11-01

Remote sensing technique provides the possibility of rapid and synchronous monitoring in a large area of the water quality, which is an important element for the aquatic ecosystem quality assessment of islands and coastal zones, especially for the nearshore and tourism sea area. Tioman Island of Malaysia is regarded as one of ten of the best islands in the world and attracts tourists from all over the world for its clear sea, beautiful seashore and charming scenery. In this paper, on the basis of in situ dataset in the study area, distribution discipline of water quality parameters is analyzed to find that phytoplankton pigment, rather than suspended sediment is the main water quality parameter in the study area; seawater there is clean but not very oligotrophic; seawater spectra contains distinct features. Then water quality hyperspectral retrieval models are developed based on in situ data to calculate the chlorophyll a concentration ([chl-a]), transparency (SD) with satisfactory performance. It's suggested that model precision should be validated further using more in-situ data.

Mediator effect of statistical process control between Total Quality Management (TQM) and business performance in Malaysian Automotive Industry

NASA Astrophysics Data System (ADS)

Ahmad, M. F.; Rasi, R. Z.; Zakuan, N.; Hisyamudin, M. N. N.

2015-12-01

In today's highly competitive market, Total Quality Management (TQM) is vital management tool in ensuring a company can success in their business. In order to survive in the global market with intense competition amongst regions and enterprises, the adoption of tools and techniques are essential in improving business performance. There are consistent results between TQM and business performance. However, only few previous studies have examined the mediator effect namely statistical process control (SPC) between TQM and business performance. A mediator is a third variable that changes the association between an independent variable and an outcome variable. This study present research proposed a TQM performance model with mediator effect of SPC with structural equation modelling, which is a more comprehensive model for developing countries, specifically for Malaysia. A questionnaire was prepared and sent to 1500 companies from automotive industry and the related vendors in Malaysia, giving a 21.8 per cent rate. Attempts were made at findings significant impact of mediator between TQM practices and business performance showed that SPC is important tools and techniques in TQM implementation. The result concludes that SPC is partial correlation between and TQM and BP with indirect effect (IE) is 0.25 which can be categorised as high moderator effect.

Application of miniaturized near-infrared spectroscopy for quality control of extemporaneous orodispersible films.

PubMed

Foo, Wen Chin; Widjaja, Effendi; Khong, Yuet Mei; Gokhale, Rajeev; Chan, Sui Yung

2018-02-20

Extemporaneous oral preparations are routinely compounded in the pharmacy due to a lack of suitable formulations for special populations. Such small-scale pharmacy preparations also present an avenue for individualized pharmacotherapy. Orodispersible films (ODF) have increasingly been evaluated as a suitable dosage form for extemporaneous oral preparations. Nevertheless, as with all other extemporaneous preparations, safety and quality remain a concern. Although the United States Pharmacopeia (USP) recommends analytical testing of compounded preparations for quality assurance, pharmaceutical assays are typically not routinely performed for such non-sterile pharmacy preparations, due to the complexity and high cost of conventional assay methods such as high performance liquid chromatography (HPLC). Spectroscopic methods including Raman, infrared and near-infrared spectroscopy have been successfully applied as quality control tools in the industry. The state-of-art benchtop spectrometers used in those studies have the advantage of superior resolution and performance, but are not suitable for use in a small-scale pharmacy setting. In this study, we investigated the application of a miniaturized near infrared (NIR) spectrometer as a quality control tool for identification and quantification of drug content in extemporaneous ODFs. Miniaturized near infrared (NIR) spectroscopy is suitable for small-scale pharmacy applications in view of its small size, portability, simple user interface, rapid measurement and real-time prediction results. Nevertheless, the challenge with miniaturized NIR spectroscopy is its lower resolution compared to state-of-art benchtop equipment. We have successfully developed NIR spectroscopy calibration models for identification of ODFs containing five different drugs, and quantification of drug content in ODFs containing 2-10mg ondansetron (OND). The qualitative model for drug identification produced 100% prediction accuracy. The quantitative model to predict OND drug content in ODFs was divided into two calibrations for improved accuracy: Calibration I and II covered the 2-4mg and 4-10mg ranges respectively. Validation was performed for method accuracy, linearity and precision. In conclusion, this study demonstrates the feasibility of miniaturized NIR spectroscopy as a quality control tool for small-scale, pharmacy preparations. Due to its non-destructive nature, every dosage unit can be tested thus affording positive impact on patient safety. Copyright © 2017 Elsevier B.V. All rights reserved.

Effect of participating in Taiwan Quality Indicator Project on hospital efficiency in Taiwan.

PubMed

Chu, Hsuan-Lien; Wang, Chen-Chin; Shiu, Shu Fen

2009-01-01

To examine the effect of participating in Taiwan Quality Indicator Project (TQIP) on hospital efficiency and investigate why hospitals participate in TQIP. Our sample consists of 417 private not-for-profit hospitals in Taiwan during the 2001-2007 period. A simultaneous-equation model was performed to examine if hospitals that participated in TQIP were more efficient than hospitals that did not and investigate which variables affected the probabilities of hospitals' participation in the project. Our findings indicate that participating hospitals are more efficient than hospitals not participating in TQIP. In addition, hospital efficiency, hospital size, teaching status, and hospital age are positively related to participation in the project. These empirical results can be used as supporting evidence of success in improving performance through creating quality for hospitals that have participated in the project and offer insights into the value and strengths of the project. In addition, in recent years, reimbursement systems worldwide have partly moved payment methods to a pay-for-performance mechanism. In an attempt to control costs and improve quality, the policy makers should consider participating in Quality Indicator Project (QIP) as being one of the criteria to be reimbursed for performance.

The role of hospital managers in quality and patient safety: a systematic review

PubMed Central

Parand, Anam; Dopson, Sue; Renz, Anna; Vincent, Charles

2014-01-01

Objectives To review the empirical literature to identify the activities, time spent and engagement of hospital managers in quality of care. Design A systematic review of the literature. Methods A search was carried out on the databases MEDLINE, PSYCHINFO, EMBASE, HMIC. The search strategy covered three facets: management, quality of care and the hospital setting comprising medical subject headings and key terms. Reviewers screened 15 447 titles/abstracts and 423 full texts were checked against inclusion criteria. Data extraction and quality assessment were performed on 19 included articles. Results The majority of studies were set in the USA and investigated Board/senior level management. The most common research designs were interviews and surveys on the perceptions of managerial quality and safety practices. Managerial activities comprised strategy, culture and data-centred activities, such as driving improvement culture and promotion of quality, strategy/goal setting and providing feedback. Significant positive associations with quality included compensation attached to quality, using quality improvement measures and having a Board quality committee. However, there is an inconsistency and inadequate employment of these conditions and actions across the sample hospitals. Conclusions There is some evidence that managers’ time spent and work can influence quality and safety clinical outcomes, processes and performance. However, there is a dearth of empirical studies, further weakened by a lack of objective outcome measures and little examination of actual actions undertaken. We present a model to summarise the conditions and activities that affect quality performance. PMID:25192876

Relationship between quality of care and choice of clinical computing system: retrospective analysis of family practice performance under the UK's quality and outcomes framework.

PubMed

Kontopantelis, Evangelos; Buchan, Iain; Reeves, David; Checkland, Kath; Doran, Tim

2013-08-02

To investigate the relationship between performance on the UK Quality and Outcomes Framework pay-for-performance scheme and choice of clinical computer system. Retrospective longitudinal study. Data for 2007-2008 to 2010-2011, extracted from the clinical computer systems of general practices in England. All English practices participating in the pay-for-performance scheme: average 8257 each year, covering over 99% of the English population registered with a general practice. Levels of achievement on 62 quality-of-care indicators, measured as: reported achievement (levels of care after excluding inappropriate patients); population achievement (levels of care for all patients with the relevant condition) and percentage of available quality points attained. Multilevel mixed effects multiple linear regression models were used to identify population, practice and clinical computing system predictors of achievement. Seven clinical computer systems were consistently active in the study period, collectively holding approximately 99% of the market share. Of all population and practice characteristics assessed, choice of clinical computing system was the strongest predictor of performance across all three outcome measures. Differences between systems were greatest for intermediate outcomes indicators (eg, control of cholesterol levels). Under the UK's pay-for-performance scheme, differences in practice performance were associated with the choice of clinical computing system. This raises the question of whether particular system characteristics facilitate higher quality of care, better data recording or both. Inconsistencies across systems need to be understood and addressed, and researchers need to be cautious when generalising findings from samples of providers using a single computing system.

The Effects of a Model Developmental Mathematics Program on Elementary and Middle School Preservice Teachers

ERIC Educational Resources Information Center

Gerber, Lindsey N.

2012-01-01

Teacher quality is instrumental in improving student performance. Unfortunately, discrepancies between teacher preparation programs and national and state K-12 student standards have contributed to the difficult task of producing quality teachers. The contemporary mathematics education paradigm used at most colleges and universities relies on…

The Impact of Marketing Actions on Relationship Quality in the Higher Education Sector in Jordan

ERIC Educational Resources Information Center

Al-Alak, Basheer A. M.

2006-01-01

This field/analytical study examined the marketing actions (antecedents) and performance (consequences) of relationship quality in a higher education setting. To analyze data collected from a random sample of 271 undergraduate students at AL-Zaytoonah Private University of Jordan, the linear structural relationship (LISREL) model was used to…

Evaluation of near surface ozone and particulate matter in air quality simulations driven by dynamically downscaled historical meteorological fields

EPA Science Inventory

In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields witho...

Measuring Service Quality in a Nontraditional Institution Using Importance-Performance Gap Analysis

ERIC Educational Resources Information Center

Mugdh, Mrinal

2004-01-01

nd wants of these students, nontraditional colleges have adopted research strategies that take into account both student expectations as well as their perception of satisfaction to assess service quality at their institutions. As one of the model adult learner focused institutions, Empire State College used Noel-Levitz Adult Learner Inventory in…

(PRESENTED IN ALBERTA, CANADA) A PERFORMANCE EVALUATION OF THE 2004 RELEASE OF MODELS-3 CMAQ

EPA Science Inventory

The Clean Air Act and its Amendments require that the U.S. Environmental Protection Agency (EPA) establish National Ambient Air Quality Standards for O₃ and particulate matter and to assess current and future air quality regulations designed to protect human health and...

Is Bigger Better? Customer Base Expansion through Word-of-Mouth Reputation

ERIC Educational Resources Information Center

Rob, Rafael; Fishman, Arthur

2005-01-01

A model of gradual reputation formation through a process of continuous investment in product quality is developed. We assume that the ability to produce high-quality products requires continuous investment and that as a consequence of informational frictions, such as search costs, information about firms' past performance diffuses only gradually…

A Comparison of Growth Percentile and Value-Added Models of Teacher Performance. Working Paper #39

ERIC Educational Resources Information Center

Guarino, Cassandra M.; Reckase, Mark D.; Stacy, Brian W.; Wooldridge, Jeffrey M.

2014-01-01

School districts and state departments of education frequently must choose between a variety of methods to estimating teacher quality. This paper examines under what circumstances the decision between estimators of teacher quality is important. We examine estimates derived from student growth percentile measures and estimates derived from commonly…

A novel integrated modelling framework to assess the impacts of climate and socio-economic drivers on land use and water quality.

PubMed

Zessner, Matthias; Schönhart, Martin; Parajka, Juraj; Trautvetter, Helene; Mitter, Hermine; Kirchner, Mathias; Hepp, Gerold; Blaschke, Alfred Paul; Strenn, Birgit; Schmid, Erwin

2017-02-01

Changes in climatic conditions will directly affect the quality and quantity of water resources. Further on, they will affect them indirectly through adaptation in land use which ultimately influences diffuse nutrient emissions to rivers and therefore potentially the compliance with good ecological status according to the EU Water Framework Directive (WFD). We present an integrated impact modelling framework (IIMF) to track and quantify direct and indirect pollution impacts along policy-economy-climate-agriculture-water interfaces. The IIMF is applied to assess impacts of climatic and socio-economic drivers on agricultural land use (crop choices, farming practices and fertilization levels), river flows and the risk for exceedance of environmental quality standards for determination of the ecological water quality status in Austria. This article also presents model interfaces as well as validation procedures and results of single models and the IIMF with respect to observed state variables such as land use, river flow and nutrient river loads. The performance of the IIMF for calculations of river nutrient loads (120 monitoring stations) shows a Nash-Sutcliffe Efficiency of 0.73 for nitrogen and 0.51 for phosphorus. Most problematic is the modelling of phosphorus loads in the alpine catchments dominated by forests and mountainous landscape. About 63% of these catchments show a deviation between modelled and observed loads of 30% and more. In catchments dominated by agricultural production, the performance of the IIMF is much better as only 30% of cropland and 23% of permanent grassland dominated areas have a deviation of >30% between modelled and observed loads. As risk of exceedance of environmental quality standards is mainly recognized in catchments dominated by cropland, the IIMF is well suited for assessing the nutrient component of the WFD ecological status. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

ACO model should encourage efficient care delivery.

PubMed

Toussaint, John; Krueger, David; Shortell, Stephen M; Milstein, Arnold; Cutler, David M

2015-09-01

The independent Office of the Actuary for CMS certified that the Pioneer ACO model has met the stringent criteria for expansion to a larger population. Significant savings have accrued and quality targets have been met, so the program as a whole appears to be working. Ironically, 13 of the initial 32 enrollees have left. We attribute this to the design of the ACO models which inadequately support efficient care delivery. Using Bellin-ThedaCare Healthcare Partners as an example, we will focus on correctible flaws in four core elements of the ACO payment model: finance spending and targets, attribution, and quality performance. Copyright © 2015 Elsevier Inc. All rights reserved.

Climate Adaptation Capacity for Conventional Drinking Water Treatment Facilities

NASA Astrophysics Data System (ADS)

Levine, A.; Goodrich, J.; Yang, J.

2013-12-01

Water supplies are vulnerable to a host of climate- and weather-related stressors such as droughts, intense storms/flooding, snowpack depletion, sea level changes, and consequences from fires, landslides, and excessive heat or cold. Surface water resources (lakes, reservoirs, rivers, and streams) are especially susceptible to weather-induced changes in water availability and quality. The risks to groundwater systems may also be significant. Typically, water treatment facilities are designed with an underlying assumption that water quality from a given source is relatively predictable based on historical data. However, increasing evidence of the lack of stationarity is raising questions about the validity of traditional design assumptions, particularly since the service life of many facilities can exceed fifty years. Given that there are over 150,000 public water systems in the US that deliver drinking water to over 300 million people every day, it is important to evaluate the capacity for adapting to the impacts of a changing climate. Climate and weather can induce or amplify changes in physical, chemical, and biological water quality, reaction rates, the extent of water-sediment-air interactions, and also impact the performance of treatment technologies. The specific impacts depend on the watershed characteristics and local hydrological and land-use factors. Water quality responses can be transient, such as erosion-induced increases in sediment and runoff. Longer-term impacts include changes in the frequency and intensity of algal blooms, gradual changes in the nature and concentration of dissolved organic matter, dissolved solids, and modulation of the microbiological community structure, sources and survival of pathogens. In addition, waterborne contaminants associated with municipal, industrial, and agricultural activities can also impact water quality. This presentation evaluates relationships between climate and weather induced water quality variability and the capacity of treatment facilities and supporting water infrastructure to deliver safe drinking water consistently and reliably. Simulation models of water treatment facilities are used to evaluate the outcome of specific source water quality scenarios on treatment system performance and reliability. Modeling results are used to evaluate the process and operational capacity to respond to transient water quality changes and adapt to longer-term variability in water quality and availability. In some cases, changes in temperature and mineral content serve to improve the overall treatment performance. In addition, the integration of microbially enhanced treatment systems such as biological filtration can provide additional capacity. Conversely, changes in the nutrient and temperature dynamics can trigger algal and cyanobacterial blooms that can impair performance. Research needs are identified and the importance of developing more integrated modeling systems is highlighted.

Mechanistic-Empirical Pavement Design Guide Flexible Pavement Performance Prediction Models Volume I Executive Research Summary

DOT National Transportation Integrated Search

2007-08-01

The objective of this research study was to develop performance characteristics or variables (e.g., ride quality, rutting, : fatigue cracking, transverse cracking) of flexible pavements in Montana, and to use these characteristics in the : implementa...

Perceptual quality prediction on authentically distorted images using a bag of features approach

PubMed Central

Ghadiyaram, Deepti; Bovik, Alan C.

2017-01-01

Current top-performing blind perceptual image quality prediction models are generally trained on legacy databases of human quality opinion scores on synthetically distorted images. Therefore, they learn image features that effectively predict human visual quality judgments of inauthentic and usually isolated (single) distortions. However, real-world images usually contain complex composite mixtures of multiple distortions. We study the perceptually relevant natural scene statistics of such authentically distorted images in different color spaces and transform domains. We propose a “bag of feature maps” approach that avoids assumptions about the type of distortion(s) contained in an image and instead focuses on capturing consistencies—or departures therefrom—of the statistics of real-world images. Using a large database of authentically distorted images, human opinions of them, and bags of features computed on them, we train a regressor to conduct image quality prediction. We demonstrate the competence of the features toward improving automatic perceptual quality prediction by testing a learned algorithm using them on a benchmark legacy database as well as on a newly introduced distortion-realistic resource called the LIVE In the Wild Image Quality Challenge Database. We extensively evaluate the perceptual quality prediction model and algorithm and show that it is able to achieve good-quality prediction power that is better than other leading models. PMID:28129417

Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

NASA Astrophysics Data System (ADS)

Taylan, Osman

2017-02-01

High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.

An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation.

PubMed

Fan, Chihhao; Ko, Chun-Han; Wang, Wei-Shen

2009-04-01

Water quality modeling has been shown to be a useful tool in strategic water quality management. The present study combines the Qual2K model with the HEC-RAS model to assess the water quality of a tidal river in northern Taiwan. The contaminant loadings of biochemical oxygen demand (BOD), ammonia nitrogen (NH(3)-N), total phosphorus (TP), and sediment oxygen demand (SOD) are utilized in the Qual2K simulation. The HEC-RAS model is used to: (i) estimate the hydraulic constants for atmospheric re-aeration constant calculation; and (ii) calculate the water level profile variation to account for concentration changes as a result of tidal effect. The results show that HEC-RAS-assisted Qual2K simulations taking tidal effect into consideration produce water quality indices that, in general, agree with the monitoring data of the river. Comparisons of simulations with different combinations of contaminant loadings demonstrate that BOD is the most import contaminant. Streeter-Phelps simulation (in combination with HEC-RAS) is also performed for comparison, and the results show excellent agreement with the observed data. This paper is the first report of the innovative use of a combination of the HEC-RAS model and the Qual2K model (or Streeter-Phelps equation) to simulate water quality in a tidal river. The combination is shown to provide an alternative for water quality simulation of a tidal river when available dynamic-monitoring data are insufficient to assess the tidal effect of the river.