AIR QUALITY FORECAST DATABASE AND ANALYSIS

EPA Science Inventory

In 2003, NOAA and EPA signed a Memorandum of Agreement to collaborate on the design and implementation of a capability to produce daily air quality modeling forecast information for the U.S. NOAA's ETA meteorological model and EPA's Community Multiscale Air Quality (CMAQ) model ...

Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods

NASA Astrophysics Data System (ADS)

Vanrolleghem, Peter A.; Mannina, Giorgio; Cosenza, Alida; Neumann, Marc B.

2015-03-01

Sensitivity analysis represents an important step in improving the understanding and use of environmental models. Indeed, by means of global sensitivity analysis (GSA), modellers may identify both important (factor prioritisation) and non-influential (factor fixing) model factors. No general rule has yet been defined for verifying the convergence of the GSA methods. In order to fill this gap this paper presents a convergence analysis of three widely used GSA methods (SRC, Extended FAST and Morris screening) for an urban drainage stormwater quality-quantity model. After the convergence was achieved the results of each method were compared. In particular, a discussion on peculiarities, applicability, and reliability of the three methods is presented. Moreover, a graphical Venn diagram based classification scheme and a precise terminology for better identifying important, interacting and non-influential factors for each method is proposed. In terms of convergence, it was shown that sensitivity indices related to factors of the quantity model achieve convergence faster. Results for the Morris screening method deviated considerably from the other methods. Factors related to the quality model require a much higher number of simulations than the number suggested in literature for achieving convergence with this method. In fact, the results have shown that the term "screening" is improperly used as the method may exclude important factors from further analysis. Moreover, for the presented application the convergence analysis shows more stable sensitivity coefficients for the Extended-FAST method compared to SRC and Morris screening. Substantial agreement in terms of factor fixing was found between the Morris screening and Extended FAST methods. In general, the water quality related factors exhibited more important interactions than factors related to water quantity. Furthermore, in contrast to water quantity model outputs, water quality model outputs were found to be characterised by high non-linearity.

A Design Quality Learning Unit in Relational Data Modeling Based on Thriving Systems Properties

ERIC Educational Resources Information Center

Waguespack, Leslie J.

2013-01-01

This paper presents a learning unit that addresses quality design in relational data models. The focus on modeling allows the learning to span analysis, design, and implementation enriching pedagogy across the systems development life cycle. Thriving Systems Theory presents fifteen choice properties that convey design quality in models integrating…

Root Cause Analysis of Quality Defects Using HPLC-MS Fingerprint Knowledgebase for Batch-to-batch Quality Control of Herbal Drugs.

PubMed

Yan, Binjun; Fang, Zhonghua; Shen, Lijuan; Qu, Haibin

2015-01-01

The batch-to-batch quality consistency of herbal drugs has always been an important issue. To propose a methodology for batch-to-batch quality control based on HPLC-MS fingerprints and process knowledgebase. The extraction process of Compound E-jiao Oral Liquid was taken as a case study. After establishing the HPLC-MS fingerprint analysis method, the fingerprints of the extract solutions produced under normal and abnormal operation conditions were obtained. Multivariate statistical models were built for fault detection and a discriminant analysis model was built using the probabilistic discriminant partial-least-squares method for fault diagnosis. Based on multivariate statistical analysis, process knowledge was acquired and the cause-effect relationship between process deviations and quality defects was revealed. The quality defects were detected successfully by multivariate statistical control charts and the type of process deviations were diagnosed correctly by discriminant analysis. This work has demonstrated the benefits of combining HPLC-MS fingerprints, process knowledge and multivariate analysis for the quality control of herbal drugs. Copyright © 2015 John Wiley & Sons, Ltd.

Data-base development for water-quality modeling of the Patuxent River basin, Maryland

USGS Publications Warehouse

Fisher, G.T.; Summers, R.M.

1987-01-01

Procedures and rationale used to develop a data base and data management system for the Patuxent Watershed Nonpoint Source Water Quality Monitoring and Modeling Program of the Maryland Department of the Environment and the U.S. Geological Survey are described. A detailed data base and data management system has been developed to facilitate modeling of the watershed for water quality planning purposes; statistical analysis; plotting of meteorologic, hydrologic and water quality data; and geographic data analysis. The system is Maryland 's prototype for development of a basinwide water quality management program. A key step in the program is to build a calibrated and verified water quality model of the basin using the Hydrological Simulation Program--FORTRAN (HSPF) hydrologic model, which has been used extensively in large-scale basin modeling. The compilation of the substantial existing data base for preliminary calibration of the basin model, including meteorologic, hydrologic, and water quality data from federal and state data bases and a geographic information system containing digital land use and soils data is described. The data base development is significant in its application of an integrated, uniform approach to data base management and modeling. (Lantz-PTT)

Diagnostic Analysis of Ozone Concentrations Simulated by Two Regional-Scale Air Quality Models

EPA Science Inventory

Since the Community Multiscale Air Quality modeling system (CMAQ) and the Weather Research and Forecasting with Chemistry model (WRF/Chem) use different approaches to simulate the interaction of meteorology and chemistry, this study compares the CMAQ and WRF/Chem air quality simu...

Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

ERIC Educational Resources Information Center

Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan

2016-01-01

Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…

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.

Predicting soil quality indices with near infrared analysis in a wildfire chronosequence.

PubMed

Cécillon, Lauric; Cassagne, Nathalie; Czarnes, Sonia; Gros, Raphaël; Vennetier, Michel; Brun, Jean-Jacques

2009-01-15

We investigated the power of near infrared (NIR) analysis for the quantitative assessment of soil quality in a wildfire chronosequence. The effect of wildfire disturbance and soil engineering activity of earthworms on soil organic matter quality was first assessed with principal component analysis of NIR spectra. Three soil quality indices were further calculated using an adaptation of the method proposed by Velasquez et al. [Velasquez, E., Lavelle, P., Andrade, M. GISQ, a multifunctional indicator of soil quality. Soil Biol Biochem 2007; 39: 3066-3080.], each one addressing an ecosystem service provided by soils: organic matter storage, nutrient supply and biological activity. Partial least squares regression models were developed to test the predicting ability of NIR analysis for these soil quality indices. All models reached coefficients of determination above 0.90 and ratios of performance to deviation above 2.8. This finding provides new opportunities for the monitoring of soil quality, using NIR scanning of soil samples.

DRAINMOD-GIS: a lumped parameter watershed scale drainage and water quality model

Treesearch

G.P. Fernandez; G.M. Chescheir; R.W. Skaggs; D.M. Amatya

2006-01-01

A watershed scale lumped parameter hydrology and water quality model that includes an uncertainty analysis component was developed and tested on a lower coastal plain watershed in North Carolina. Uncertainty analysis was used to determine the impacts of uncertainty in field and network parameters of the model on the predicted outflows and nitrate-nitrogen loads at the...

Stormwater quality modelling in combined sewers: calibration and uncertainty analysis.

PubMed

Kanso, A; Chebbo, G; Tassin, B

2005-01-01

Estimating the level of uncertainty in urban stormwater quality models is vital for their utilization. This paper presents the results of application of a Monte Carlo Markov Chain method based on the Bayesian theory for the calibration and uncertainty analysis of a storm water quality model commonly used in available software. The tested model uses a hydrologic/hydrodynamic scheme to estimate the accumulation, the erosion and the transport of pollutants on surfaces and in sewers. It was calibrated for four different initial conditions of in-sewer deposits. Calibration results showed large variability in the model's responses in function of the initial conditions. They demonstrated that the model's predictive capacity is very low.

Quality Management in Schools: Analysis of Mediating Factors

ERIC Educational Resources Information Center

Díez, Fernando; Iraurgi, Ioseba; Sanchez, Aurelio Villa

2018-01-01

The objective of this study is to contribute to Quality Management Systems (QMS) and their impact on schools in the Basque Country, Spain. Specifically, it analyses two models: the EFQM Excellence Model, which originated in the business world, and the Integrated Quality Project (IQP) Model, which has a humanistic focus and arose from an…

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...

WASP TRANSPORT MODELING AND WASP ECOLOGICAL MODELING

EPA Science Inventory

A combination of lectures, demonstrations, and hands-on excercises will be used to introduce pollutant transport modeling with the U.S. EPA's general water quality model, WASP (Water Quality Analysis Simulation Program). WASP features include a user-friendly Windows-based interfa...

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

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.

Quality Control Analysis of Selected Aspects of Programs Administered by the Bureau of Student Financial Assistance. Task 1 and Quality Control Sample; Error-Prone Modeling Analysis Plan.

ERIC Educational Resources Information Center

Saavedra, Pedro; And Others

Parameters and procedures for developing an error-prone model (EPM) to predict financial aid applicants who are likely to misreport on Basic Educational Opportunity Grant (BEOG) applications are introduced. Specifications to adapt these general parameters to secondary data analysis of the Validation, Edits, and Applications Processing Systems…

Meeting in Turkey: WASP Transport Modeling and WASP Ecological Modeling

EPA Science Inventory

A combination of lectures, demonstrations, and hands-on excercises will be used to introduce pollutant transport modeling with the U.S. EPA's general water quality model, WASP (Water Quality Analysis Simulation Program). WASP features include a user-friendly Windows-based interfa...

Meeting in Korea: WASP Transport Modeling and WASP Ecological Modeling

EPA Science Inventory

A combination of lectures, demonstrations, and hands-on excercises will be used to introduce pollutant transport modeling with the U.S. EPA's general water quality model, WASP (Water Quality Analysis Simulation Program). WASP features include a user-friendly Windows-based interfa...

Analysis of aircraft longitudinal handling qualities

NASA Technical Reports Server (NTRS)

Hess, R. A.

1981-01-01

The optimal control model (OCM) of the human pilot is applied to the study of aircraft handling qualities. Attention is focused primarily on longitudinal tasks. The modeling technique differs from previous applications of the OCM in that considerable effort is expended in simplifying the pilot/vehicle analysis. After briefly reviewing the OCM, a technique for modeling the pilot controlling higher order systems is introduced. Following this, a simple criterion for determining the susceptibility of an aircraft to pilot induced oscillations (PIO) is formulated. Finally, a model-based metric for pilot rating prediction is discussed. The resulting modeling procedure provides a relatively simple, yet unified approach to the study of a variety of handling qualities problems.

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.

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.

[Real-time detection of quality of Chinese materia medica: strategy of NIR model evaluation].

PubMed

Wu, Zhi-sheng; Shi, Xin-yuan; Xu, Bing; Dai, Xing-xing; Qiao, Yan-jiang

2015-07-01

The definition of critical quality attributes of Chinese materia medica ( CMM) was put forward based on the top-level design concept. Nowadays, coupled with the development of rapid analytical science, rapid assessment of critical quality attributes of CMM was firstly carried out, which was the secondary discipline branch of CMM. Taking near infrared (NIR) spectroscopy as an example, which is a rapid analytical technology in pharmaceutical process over the past decade, systematic review is the chemometric parameters in NIR model evaluation. According to the characteristics of complexity of CMM and trace components analysis, a multi-source information fusion strategy of NIR model was developed for assessment of critical quality attributes of CMM. The strategy has provided guideline for NIR reliable analysis in critical quality attributes of CMM.

Long-term behaviour and cross-correlation water quality analysis of the River Elbe, Germany.

PubMed

Lehmann, A; Rode, M

2001-06-01

This study analyses weekly data samples from the river Elbe at Magdeburg between 1984 and 1996 to investigate the changes in metabolism and water quality in the river Elbe since the German reunification in 1990. Modelling water quality variables by autoregressive component models and ARIMA models reveals the improvement of water quality due to the reduction of waste water emissions since 1990. The models are used to determine the long-term and seasonal behaviour of important water quality variables. Organic and heavy metal pollution parameters showed a significant decrease since 1990, however, no significant change of chlorophyll-a as a measure for primary production could be found. A new procedure for testing the significance of a sample correlation coefficient is discussed, which is able to detect spurious sample correlation coefficients without making use of time-consuming prewhitening. The cross-correlation analysis is applied to hydrophysical, biological, and chemical water quality variables of the river Elbe since 1984. Special emphasis is laid on the detection of spurious sample correlation coefficients.

Assessing the effects of regional payment for watershed services program on water quality using an intervention analysis model.

PubMed

Lu, Yan; He, Tian

2014-09-15

Much attention has been recently paid to ex-post assessments of socioeconomic and environmental benefits of payment for ecosystem services (PES) programs on poverty reduction, water quality, and forest protection. To evaluate the effects of a regional PES program on water quality, we selected chemical oxygen demand (COD) and ammonia-nitrogen (NH3-N) as indicators of water quality. Statistical methods and an intervention analysis model were employed to assess whether the PES program produced substantial changes in water quality at 10 water-quality sampling stations in the Shaying River watershed, China during 2006-2011. Statistical results from paired-sample t-tests and box plots of COD and NH3-N concentrations at the 10 stations showed that the PES program has played a positive role in improving water quality and reducing trans-boundary water pollution in the Shaying River watershed. Using the intervention analysis model, we quantitatively evaluated the effects of the intervention policy, i.e., the watershed PES program, on water quality at the 10 stations. The results suggest that this method could be used to assess the environmental benefits of watershed or water-related PES programs, such as improvements in water quality, seasonal flow regulation, erosion and sedimentation, and aquatic habitat. Copyright © 2014 Elsevier B.V. All rights reserved.

pcr: an R package for quality assessment, analysis and testing of qPCR data

PubMed Central

Ahmed, Mahmoud

2018-01-01

Background Real-time quantitative PCR (qPCR) is a broadly used technique in the biomedical research. Currently, few different analysis models are used to determine the quality of data and to quantify the mRNA level across the experimental conditions. Methods We developed an R package to implement methods for quality assessment, analysis and testing qPCR data for statistical significance. Double Delta CT and standard curve models were implemented to quantify the relative expression of target genes from CT in standard qPCR control-group experiments. In addition, calculation of amplification efficiency and curves from serial dilution qPCR experiments are used to assess the quality of the data. Finally, two-group testing and linear models were used to test for significance of the difference in expression control groups and conditions of interest. Results Using two datasets from qPCR experiments, we applied different quality assessment, analysis and statistical testing in the pcr package and compared the results to the original published articles. The final relative expression values from the different models, as well as the intermediary outputs, were checked against the expected results in the original papers and were found to be accurate and reliable. Conclusion The pcr package provides an intuitive and unified interface for its main functions to allow biologist to perform all necessary steps of qPCR analysis and produce graphs in a uniform way. PMID:29576953

Bayesian Analysis of a Reduced-Form Air Quality Model

EPA Science Inventory

Numerical air quality models are being used for assessing emission control strategies for improving ambient pollution levels across the globe. This paper applies probabilistic modeling to evaluate the effectiveness of emission reduction scenarios aimed at lowering ground-level oz...

Water quality management using statistical analysis and time-series prediction model

NASA Astrophysics Data System (ADS)

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2014-12-01

This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.

Development of the High-Order Decoupled Direct Method in Three Dimensions for Particulate Matter: Enabling Advanced Sensitivity Analysis in Air Quality Models

EPA Science Inventory

The high-order decoupled direct method in three dimensions for particular matter (HDDM-3D/PM) has been implemented in the Community Multiscale Air Quality (CMAQ) model to enable advanced sensitivity analysis. The major effort of this work is to develop high-order DDM sensitivity...

Testing a healthcare provider-patient communicative relationship quality model of pharmaceutical care in hospitals.

PubMed

Wang, Dan; Liu, Chenxi; Zhang, Zinan; Ye, Liping; Zhang, Xinping

2018-06-01

Background Patient-centeredness and participatory care is increasingly regarded as a proxy for high-quality interpersonal care. Considering the development of patient-centeredness and participatory care relationship model in pharmacist-patient domain, it is of great significance to explore the mechanism of how pharmacist and patient participative behaviors influence relationship quality and patient outcomes. Objective To validate pharmacist-patient relationship quality model in Chinese hospitals. Four tertiary hospitals in 2017. Methods The provision of pharmaceutical care was investigated. A cross-sectional questionnaire survey covering different constructs of communicative relationship quality model was conducted and the associations among pairs of the study constructs were explored. Based on the results of confirmatory factor analysis, path analysis was conducted to validate the proposed communicative relationship quality model. Main outcome measure Model fit indicators including Tucker-Lewis index (TLI), comparative fit index (CFI), root mean square error of approximation (RMSEA) and weighted root mean square residual(WRMR). Results There were 589 patients included in our study. The final path model had an excellent fit (TLI = 0.98, CFI = 0.98, RMSEA = 0.05; WRMR = 1.06). HCP participative behavior/patient-centeredness (β = 0.79, p < 0.001) and interpersonal communication (β = 0.13, p < 0.001) directly impact the communicative relationship quality. But patient participative behavior was not a predictor of either communicative relationship quality or patient satisfaction. Conclusion HCP participative behavior/patient-centeredness and interpersonal communication are positively related to relationship quality, and relationship quality is mediator between HCP participative behavior and interpersonal communication with patient satisfaction.

Linking Air Quality and Watershed Models for Environmental Assessments: Analysis of the Effects of Model-Specific Precipitation Estimates on Calculated Water Flux

EPA Science Inventory

Directly linking air quality and watershed models could provide an effective method for estimating spatially-explicit inputs of atmospheric contaminants to watershed biogeochemical models. However, to adequately link air and watershed models for wet deposition estimates, each mod...

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

EPA Science Inventory

This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...

Retrospective analysis of the quality of reports by author-suggested and non-author-suggested reviewers in journals operating on open or single-blind peer review models

PubMed Central

Kowalczuk, Maria K; Dudbridge, Frank; Nanda, Shreeya; Harriman, Stephanie L; Patel, Jigisha; Moylan, Elizabeth C

2015-01-01

Objectives To assess whether reports from reviewers recommended by authors show a bias in quality and recommendation for editorial decision, compared with reviewers suggested by other parties, and whether reviewer reports for journals operating on open or single-blind peer review models differ with regard to report quality and reviewer recommendations. Design Retrospective analysis of the quality of reviewer reports using an established Review Quality Instrument, and analysis of reviewer recommendations and author satisfaction surveys. Setting BioMed Central biology and medical journals. BMC Infectious Diseases and BMC Microbiology are similar in size, rejection rates, impact factors and editorial processes, but the former uses open peer review while the latter uses single-blind peer review. The Journal of Inflammation has operated under both peer review models. Sample Two hundred reviewer reports submitted to BMC Infectious Diseases, 200 reviewer reports submitted to BMC Microbiology and 400 reviewer reports submitted to the Journal of Inflammation. Results For each journal, author-suggested reviewers provided reports of comparable quality to non-author-suggested reviewers, but were significantly more likely to recommend acceptance, irrespective of the peer review model (p<0.0001 for BMC Infectious Diseases, BMC Microbiology and the Journal of Inflammation). For BMC Infectious Diseases, the overall quality of reviewer reports measured by the Review Quality Instrument was 5% higher than for BMC Microbiology (p=0.042). For the Journal of Inflammation, the quality of reports was the same irrespective of the peer review model used. Conclusions Reviewers suggested by authors provide reports of comparable quality to non-author-suggested reviewers, but are significantly more likely to recommend acceptance. Open peer review reports for BMC Infectious Diseases were of higher quality than single-blind reports for BMC Microbiology. There was no difference in quality of peer review in the Journal of Inflammation under open peer review compared with single blind. PMID:26423855

Modelling of groundwater quality using bicarbonate chemical parameter in Netravathi and Gurpur river confluence, India

NASA Astrophysics Data System (ADS)

Sylus, K. J.; H., Ramesh

2018-04-01

In the coastal aquifer, seawater intrusion considered the major problem which contaminates freshwater and reduces its quality for domestic use. In order to find seawater intrusion, the groundwater quality analysis for the different chemical parameter was considered as the basic method to find out contamination. This analysis was carried out as per Bureau of Indian standards (2012) and World Health Organisations (1996). In this study, Bicarbonate parameter was considered for groundwater quality analysis which ranges the permissible limit in between 200-600 mg/l. The groundwater system was modelled using Groundwater modelling software (GMS) in which the FEMWATER package used for flow and transport. The FEMWATER package works in the principle of finite element method. The base input data of model include elevation, Groundwater head, First bottom and second bottom of the study area. The modelling results show the spatial occurrence of contamination in the study area of Netravathi and Gurpur river confluence at the various time period. Further, the results of the modelling also show that the contamination occurs up to a distance of 519m towards the freshwater zone of the study area.

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.

A compilation and analysis of helicopter handling qualities data. Volume 2: Data analysis

NASA Technical Reports Server (NTRS)

Heffley, R. K.

1979-01-01

A compilation and an analysis of helicopter handling qualities data are presented. Multiloop manual control methods are used to analyze the descriptive data, stability derivatives, and transfer functions for a six degrees of freedom, quasi static model. A compensatory loop structure is applied to coupled longitudinal, lateral and directional equations in such a way that key handling qualities features are examined directly.

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.

Near infrared spectrometric technique for testing fruit quality: optimisation of regression models using genetic algorithms

NASA Astrophysics Data System (ADS)

Isingizwe Nturambirwe, J. Frédéric; Perold, Willem J.; Opara, Umezuruike L.

2016-02-01

Near infrared (NIR) spectroscopy has gained extensive use in quality evaluation. It is arguably one of the most advanced spectroscopic tools in non-destructive quality testing of food stuff, from measurement to data analysis and interpretation. NIR spectral data are interpreted through means often involving multivariate statistical analysis, sometimes associated with optimisation techniques for model improvement. The objective of this research was to explore the extent to which genetic algorithms (GA) can be used to enhance model development, for predicting fruit quality. Apple fruits were used, and NIR spectra in the range from 12000 to 4000 cm-1 were acquired on both bruised and healthy tissues, with different degrees of mechanical damage. GAs were used in combination with partial least squares regression methods to develop bruise severity prediction models, and compared to PLS models developed using the full NIR spectrum. A classification model was developed, which clearly separated bruised from unbruised apple tissue. GAs helped improve prediction models by over 10%, in comparison with full spectrum-based models, as evaluated in terms of error of prediction (Root Mean Square Error of Cross-validation). PLS models to predict internal quality, such as sugar content and acidity were developed and compared to the versions optimized by genetic algorithm. Overall, the results highlighted the potential use of GA method to improve speed and accuracy of fruit quality prediction.

A three-model comparison of the relationship between quality, satisfaction and loyalty: an empirical study of the Chinese healthcare system.

PubMed

Lei, Ping; Jolibert, Alain

2012-11-30

Previous research has addressed the relationship between customer satisfaction, perceived quality and customer loyalty intentions in consumer markets. In this study, we test and compare three theoretical models of the quality-satisfaction-loyalty relationship in the Chinese healthcare system. This research focuses on hospital patients as participants in the process of healthcare procurement. Empirical data were obtained from six Chinese public hospitals in Shanghai. A total of 630 questionnaires were collected in two studies. Study 1 tested the research instruments, and Study 2 tested the three models. Confirmatory factor analysis was used to assess the scales' construct validity by testing convergent and discriminant validity. A structural equation model (SEM) specified the distinctions between each construct. A comparison of the three theoretical models was conducted via AMOS analysis. The results of the SEM demonstrate that quality and satisfaction are distinct concepts and that the first model (satisfaction mediates quality and loyalty) is the most appropriate one in the context of the Chinese healthcare environment. In this study, we test and compare three theoretical models of the quality-satisfaction-loyalty relationship in the Chinese healthcare system. Findings show that perceived quality improvement does not lead directly to customer loyalty. The strategy of using quality improvement to maintain patient loyalty depends on the level of patient satisfaction. This implies that the measurement of patient experiences should include topics of importance for patients' satisfaction with health care services.

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

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

40 CFR 93.152 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... official charged with direct responsibility for management of an area designated as Class I under the Act.... Areawide air quality modeling analysis means an assessment on a scale that includes the entire nonattainment or maintenance area using an air quality dispersion model or photochemical grid model to determine...

Analysis and enhancement of country singing

NASA Astrophysics Data System (ADS)

Lee, Matthew; Smith, Mark J. T.

2003-04-01

The study of human singing has focused extensively on the analysis of voice characteristics. At the same time, a substantial body of work has been under study aimed at modeling and synthesizing the human voice. The work on which we report brings together some key analysis and synthesis principles to create a new model for digitally improving the perceived quality of an average singing voice. The model presented employs an analysis-by-synthesis overlap-add (ABS-OLA) sinusoidal model, which in the past has been used for the analysis and synthesis of speech, in combination with a spectral model of the vocal tract. The ABS-OLA sinusoidal model for speech has been shown to be a flexible, accurate, and computationally efficient representation capable of producing a natural-sounding singing voice [E. B. George and M. J. T. Smith, Trans. Speech Audio Processing 5, 389-406 (1997)]. A spectral model infused in the ABS-OLA uses Generalized Gaussian functions to provide a simple framework which enables the precise modification of spectral characteristics while maintaining the quality and naturalness of the original voice. Furthermore, it is shown that the parameters of the new ABS-OLA can accommodate pitch corrections and vocal quality enhancements while preserving naturalness and singer identity. Examples of enhanced country singing will be presented.

ANALYSIS OF AIR QUALITY DATA NEAR ROADWAYS USING A DISPERSION MODEL

EPA Science Inventory

A dispersion model was used to analyze measurements made during a field study conducted by the U.S. EPA in July and August 2006, to estimate the impact of highway emissions on air quality at distances of tens of meters from an eight-lane highway. The air quality measurements con...

Modeling the impacts of green infrastructure land use changes on air quality and meteorology case study and sensitivity analysis in Kansas City

EPA Science Inventory

Changes in vegetation cover associated with urban planning efforts may affect regional meteorology and air quality. Here we use a comprehensive coupled meteorology-air quality model (WRF-CMAQ) to simulate the influence of planned land use changes from green infrastructure impleme...

DEVELOPMENT OF AN AGGREGATION AND EPISODE SELECTION SCHEME TO SUPPORT THE MODELS-3 COMMUNITY MULTISCALE AIR QUALITY MODEL

EPA Science Inventory

The development of an episode selection and aggregation approach, designed to support distributional estimation of use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700-hPa east-west and north-south...

Construction of a 3D model of nattokinase, a novel fibrinolytic enzyme from Bacillus natto. A novel nucleophilic catalytic mechanism for nattokinase.

PubMed

Zheng, Zhong-liang; Zuo, Zhen-yu; Liu, Zhi-gang; Tsai, Keng-chang; Liu, Ai-fu; Zou, Guo-lin

2005-01-01

A three-dimensional structural model of nattokinase (NK) from Bacillus natto was constructed by homology modeling. High-resolution X-ray structures of Subtilisin BPN' (SB), Subtilisin Carlsberg (SC), Subtilisin E (SE) and Subtilisin Savinase (SS), four proteins with sequential, structural and functional homology were used as templates. Initial models of NK were built by MODELLER and analyzed by the PROCHECK programs. The best quality model was chosen for further refinement by constrained molecular dynamics simulations. The overall quality of the refined model was evaluated. The refined model NKC1 was analyzed by different protein analysis programs including PROCHECK for the evaluation of Ramachandran plot quality, PROSA for testing interaction energies and WHATIF for the calculation of packing quality. This structure was found to be satisfactory and also stable at room temperature as demonstrated by a 300ps long unconstrained molecular dynamics (MD) simulation. Further docking analysis promoted the coming of a new nucleophilic catalytic mechanism for NK, which is induced by attacking of hydroxyl rich in catalytic environment and locating of S221.

An approach for quantitative image quality analysis for CT

NASA Astrophysics Data System (ADS)

Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

2016-03-01

An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

Water quality modeling for urban reach of Yamuna river, India (1999-2009), using QUAL2Kw

NASA Astrophysics Data System (ADS)

Sharma, Deepshikha; Kansal, Arun; Pelletier, Greg

2017-06-01

The study was to characterize and understand the water quality of the river Yamuna in Delhi (India) prior to an efficient restoration plan. A combination of collection of monitored data, mathematical modeling, sensitivity, and uncertainty analysis has been done using the QUAL2Kw, a river quality model. The model was applied to simulate DO, BOD, total coliform, and total nitrogen at four monitoring stations, namely Palla, Old Delhi Railway Bridge, Nizamuddin, and Okhla for 10 years (October 1999-June 2009) excluding the monsoon seasons (July-September). The study period was divided into two parts: monthly average data from October 1999-June 2004 (45 months) were used to calibrate the model and monthly average data from October 2005-June 2009 (45 months) were used to validate the model. The R2 for CBODf and TN lies within the range of 0.53-0.75 and 0.68-0.83, respectively. This shows that the model has given satisfactory results in terms of R2 for CBODf, TN, and TC. Sensitivity analysis showed that DO, CBODf, TN, and TC predictions are highly sensitive toward headwater flow and point source flow and quality. Uncertainty analysis using Monte Carlo showed that the input data have been simulated in accordance with the prevalent river conditions.

Global ozone and air quality: a multi-model assessment of risks to human health and crops

NASA Astrophysics Data System (ADS)

Ellingsen, K.; Gauss, M.; van Dingenen, R.; Dentener, F. J.; Emberson, L.; Fiore, A. M.; Schultz, M. G.; Stevenson, D. S.; Ashmore, M. R.; Atherton, C. S.; Bergmann, D. J.; Bey, I.; Butler, T.; Drevet, J.; Eskes, H.; Hauglustaine, D. A.; Isaksen, I. S. A.; Horowitz, L. W.; Krol, M.; Lamarque, J. F.; Lawrence, M. G.; van Noije, T.; Pyle, J.; Rast, S.; Rodriguez, J.; Savage, N.; Strahan, S.; Sudo, K.; Szopa, S.; Wild, O.

2008-02-01

Within ACCENT, a European Network of Excellence, eighteen atmospheric models from the U.S., Europe, and Japan calculated present (2000) and future (2030) concentrations of ozone at the Earth's surface with hourly temporal resolution. Comparison of model results with surface ozone measurements in 14 world regions indicates that levels and seasonality of surface ozone in North America and Europe are characterized well by global models, with annual average biases typically within 5-10 nmol/mol. However, comparison with rather sparse observations over some regions suggest that most models overestimate annual ozone by 15-20 nmol/mol in some locations. Two scenarios from the International Institute for Applied Systems Analysis (IIASA) and one from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) have been implemented in the models. This study focuses on changes in near-surface ozone and their effects on human health and vegetation. Different indices and air quality standards are used to characterise air quality. We show that often the calculated changes in the different indices are closely inter-related. Indices using lower thresholds are more consistent between the models, and are recommended for global model analysis. Our analysis indicates that currently about two-thirds of the regions considered do not meet health air quality standards, whereas only 2-4 regions remain below the threshold. Calculated air quality exceedances show moderate deterioration by 2030 if current emissions legislation is followed and slight improvements if current emissions reduction technology is used optimally. For the "business as usual" scenario severe air quality problems are predicted. We show that model simulations of air quality indices are particularly sensitive to how well ozone is represented, and improved accuracy is needed for future projections. Additional measurements are needed to allow a more quantitative assessment of the risks to human health and vegetation from changing levels of surface ozone.

Uncertainty analyses of the calibrated parameter values of a water quality model

NASA Astrophysics Data System (ADS)

Rode, M.; Suhr, U.; Lindenschmidt, K.-E.

2003-04-01

For river basin management water quality models are increasingly used for the analysis and evaluation of different management measures. However substantial uncertainties exist in parameter values depending on the available calibration data. In this paper an uncertainty analysis for a water quality model is presented, which considers the impact of available model calibration data and the variance of input variables. The investigation was conducted based on four extensive flowtime related longitudinal surveys in the River Elbe in the years 1996 to 1999 with varying discharges and seasonal conditions. For the model calculations the deterministic model QSIM of the BfG (Germany) was used. QSIM is a one dimensional water quality model and uses standard algorithms for hydrodynamics and phytoplankton dynamics in running waters, e.g. Michaelis Menten/Monod kinetics, which are used in a wide range of models. The multi-objective calibration of the model was carried out with the nonlinear parameter estimator PEST. The results show that for individual flow time related measuring surveys very good agreements between model calculation and measured values can be obtained. If these parameters are applied to deviating boundary conditions, substantial errors in model calculation can occur. These uncertainties can be decreased with an increased calibration database. More reliable model parameters can be identified, which supply reasonable results for broader boundary conditions. The extension of the application of the parameter set on a wider range of water quality conditions leads to a slight reduction of the model precision for the specific water quality situation. Moreover the investigations show that highly variable water quality variables like the algal biomass always allow a smaller forecast accuracy than variables with lower coefficients of variation like e.g. nitrate.

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

The model of flood control using servqual method and importance performance analysis in Surakarta City – Indonesia

NASA Astrophysics Data System (ADS)

Titi Purwantini, V.; Sutanto, Yusuf

2018-05-01

This research is to create a model of flood control in the city of Surakarta using Servqual method and Importance Performance Analysis. Service quality is generally defined as the overall assessment of a service by the customersor the extent to which a service meets customer’s needs or expectations. The purpose of this study is to find the first model of flood control that is appropriate to the condition of the community. Surakarta This means looking for a model that can provide satisfactory service for the people of Surakarta who are in the location of the flood. The second is to find the right model to improve service performance of Surakarta City Government in serving the people in flood location. The method used to determine the satisfaction of the public on the quality of service is to see the difference in the quality of service expected by the community with the reality. This method is Servqual Method While to assess the performance of city government officials is by comparing the actual performance with the quality of services provided, this method is This means looking for a model that can provide satisfactory service for the people of Surakarta who are in the location of the flood.The second is to find the right model to improve service performance of Surakarta City Government in serving the people in flood location. The method used to determine the satisfaction of the public on the quality of service is to see the difference in the quality of service expected by the community with the reality. This method is Servqual Method While to assess the performance of city government officials is by comparing the actual performance with the quality of services provided, this method is Importance Performance Analysis. Samples were people living in flooded areas in the city of Surakarta. Result this research is Satisfaction = Responsiveness+ Realibility + Assurance + Empathy+ Tangible (Servqual Model) and Importance Performance Analysis is From Cartesian diagram can be made Flood Control Formula as follow: Food Control = High performance

Understanding Intention to Use Electronic Information Resources: A Theoretical Extension of the Technology Acceptance Model (TAM)

PubMed Central

Tao, Donghua

2008-01-01

This study extended the Technology Acceptance Model (TAM) by examining the roles of two aspects of e-resource characteristics, namely, information quality and system quality, in predicting public health students’ intention to use e-resources for completing research paper assignments. Both focus groups and a questionnaire were used to collect data. Descriptive analysis, data screening, and Structural Equation Modeling (SEM) techniques were used for data analysis. The study found that perceived usefulness played a major role in determining students’ intention to use e-resources. Perceived usefulness and perceived ease of use fully mediated the impact that information quality and system quality had on behavior intention. The research model enriches the existing technology acceptance literature by extending TAM. Representing two aspects of e-resource characteristics provides greater explanatory information for diagnosing problems of system design, development, and implementation. PMID:18999300

Understanding intention to use electronic information resources: A theoretical extension of the technology acceptance model (TAM).

PubMed

Tao, Donghua

2008-11-06

This study extended the Technology Acceptance Model (TAM) by examining the roles of two aspects of e-resource characteristics, namely, information quality and system quality, in predicting public health students' intention to use e-resources for completing research paper assignments. Both focus groups and a questionnaire were used to collect data. Descriptive analysis, data screening, and Structural Equation Modeling (SEM) techniques were used for data analysis. The study found that perceived usefulness played a major role in determining students' intention to use e-resources. Perceived usefulness and perceived ease of use fully mediated the impact that information quality and system quality had on behavior intention. The research model enriches the existing technology acceptance literature by extending TAM. Representing two aspects of e-resource characteristics provides greater explanatory information for diagnosing problems of system design, development, and implementation.

An international study of hospitalized cancer patients' health status, nursing care quality, perceived individuality in care and trust in nurses: A path analysis.

PubMed

Charalambous, Andreas; Radwin, Laurel; Berg, Agneta; Sjovall, Katarina; Patiraki, Elisabeth; Lemonidou, Chryssoula; Katajisto, Jouko; Suhonen, Riitta

2016-09-01

Providing high quality nursing care for patients with malignancies is complex and driven by many factors. Many of the associations between nursing care quality, trust, health status and individualized care remain obscure. To empirically test a model of association linking hospitalized cancer patients' health status, nursing care quality, perceived individuality in care and trust in nurses. A cross-sectional, exploratory and correlational study design was used. This multi-site study was conducted in cancer care clinics, in-patient wards of five tertiary care hospitals in Cyprus, Finland, Greece and Sweden. Out of 876 hospitalized patients with a confirmed histopathological diagnosis of cancer approached to participate in the study in consecutive order, 599 (response rate 68%) agreed to participate and the data from 590 were used for path analysis. Data were collected in 2012-2013 with the Individualized Care Scale-Patient (ICS-Patient), the Oncology Patients' Perceptions of Quality Nursing Care Scale (OPPQNCS), the Euro-Qol (EQ-5D-3L) and the Trust in Nurses Scale. Data were analysed statistically using descriptive and inferential statistics. Mplus version 7.11 was used to determine the best Trust model with path analysis. Although the model fit indices suggested that the hypothesized model did not perfectly to the data, a slightly modified model which includes the reciprocal path between individualized care and nursing care quality demonstrated a good fit. A model of trust in nurses was developed. Health status, individualized care, and nursing care quality were found to be associated with trust. The model highlights the complexity of caring for cancer patients. Trust in nurses is influenced by the provision of individualized care. Generating and promoting trust requires interventions, which promote nursing care quality, individuality and patients' health status. Copyright © 2016 Elsevier Ltd. All rights reserved.

The business process management software for successful quality management and organization: A case study from the University of Split School of Medicine.

PubMed

Sapunar, Damir; Grković, Ivica; Lukšić, Davor; Marušić, Matko

2016-05-01

Our aim was to describe a comprehensive model of internal quality management (QM) at a medical school founded on the business process analysis (BPA) software tool. BPA software tool was used as the core element for description of all working processes in our medical school, and subsequently the system served as the comprehensive model of internal QM. The quality management system at the University of Split School of Medicine included the documentation and analysis of all business processes within the School. The analysis revealed 80 weak points related to one or several business processes. A precise analysis of medical school business processes allows identification of unfinished, unclear and inadequate points in these processes, and subsequently the respective improvements and increase of the QM level and ultimately a rationalization of the institution's work. Our approach offers a potential reference model for development of common QM framework allowing a continuous quality control, i.e. the adjustments and adaptation to contemporary educational needs of medical students. Copyright © 2016 by Academy of Sciences and Arts of Bosnia and Herzegovina.

A Conceptual Framework for Quality of Care

PubMed Central

Mosadeghrad, Ali Mohammad

2012-01-01

Despite extensive research on defining and measuring health care quality, little attention has been given to different stakeholders’ perspectives of high-quality health care services. The main purpose of this study was to explore the attributes of quality healthcare in the Iranian context. Exploratory in-depth individual and focus group interviews were conducted with key healthcare stakeholders including clients, providers, managers, policy makers, payers, suppliers and accreditation panel members to identify the healthcare service quality attributes and dimensions. Data analysis was carried out by content analysis, with the constant comparative method. Over 100 attributes of quality healthcare service were elicited and grouped into five categories. The dimensions were: efficacy, effectiveness, efficiency, empathy, and environment. Consequently, a comprehensive model of service quality was developed for health care context. The findings of the current study led to a conceptual framework of healthcare quality. This model leads to a better understanding of the different aspects of quality in health care and provides a better basis for defining, measuring and controlling quality of health care services. PMID:23922534

A modern approach to the authentication and quality assessment of thyme using UV spectroscopy and chemometric analysis.

PubMed

Gad, Haidy A; El-Ahmady, Sherweit H; Abou-Shoer, Mohamed I; Al-Azizi, Mohamed M

2013-01-01

Recently, the fields of chemometrics and multivariate analysis have been widely implemented in the quality control of herbal drugs to produce precise results, which is crucial in the field of medicine. Thyme represents an essential medicinal herb that is constantly adulterated due to its resemblance to many other plants with similar organoleptic properties. To establish a simple model for the quality assessment of Thymus species using UV spectroscopy together with known chemometric techniques. The success of this model may also serve as a technique for the quality control of other herbal drugs. The model was constructed using 30 samples of authenticated Thymus vulgaris and challenged with 20 samples of different botanical origins. The methanolic extracts of all samples were assessed using UV spectroscopy together with chemometric techniques: principal component analysis (PCA), soft independent modeling of class analogy (SIMCA) and hierarchical cluster analysis (HCA). The model was able to discriminate T. vulgaris from other Thymus, Satureja, Origanum, Plectranthus and Eriocephalus species, all traded in the Egyptian market as different types of thyme. The model was also able to classify closely related species in clusters using PCA and HCA. The model was finally used to classify 12 commercial thyme varieties into clusters of species incorporated in the model as thyme or non-thyme. The model constructed is highly recommended as a simple and efficient method for distinguishing T. vulgaris from other related species as well as the classification of marketed herbs as thyme or non-thyme. Copyright © 2013 John Wiley & Sons, Ltd.

Variation in Estimated Ozone-Related Health Impacts of Climate Change due to Modeling Choices and Assumptions

PubMed Central

Post, Ellen S.; Grambsch, Anne; Weaver, Chris; Morefield, Philip; Leung, Lai-Yung; Nolte, Christopher G.; Adams, Peter; Liang, Xin-Zhong; Zhu, Jin-Hong; Mahoney, Hardee

2012-01-01

Background: Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices. Objectives: Our goal was to assess the sensitivity of estimated ozone-related human health impacts of climate change to key modeling choices. Methods: Our analysis included seven modeling systems in which a climate change model is linked to an air quality model, five population projections, and multiple concentration–response functions. Using the U.S. Environmental Protection Agency’s (EPA’s) Environmental Benefits Mapping and Analysis Program (BenMAP), we estimated future ozone (O3)-related health effects in the United States attributable to simulated climate change between the years 2000 and approximately 2050, given each combination of modeling choices. Health effects and concentration–response functions were chosen to match those used in the U.S. EPA’s 2008 Regulatory Impact Analysis of the National Ambient Air Quality Standards for O3. Results: Different combinations of methodological choices produced a range of estimates of national O3-related mortality from roughly 600 deaths avoided as a result of climate change to 2,500 deaths attributable to climate change (although the large majority produced increases in mortality). The choice of the climate change and the air quality model reflected the greatest source of uncertainty, with the other modeling choices having lesser but still substantial effects. Conclusions: Our results highlight the need to use an ensemble approach, instead of relying on any one set of modeling choices, to assess the potential risks associated with O3-related human health effects resulting from climate change. PMID:22796531

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...

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.

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.

Quality Control Analysis of Selected Aspects of Programs Administered by the Bureau of Student Financial Assistance. Error-Prone Model Derived from 1978-1979 Quality Control Study. Data Report. [Task 3.

ERIC Educational Resources Information Center

Saavedra, Pedro; Kuchak, JoAnn

An error-prone model (EPM) to predict financial aid applicants who are likely to misreport on Basic Educational Opportunity Grant (BEOG) applications was developed, based on interviews conducted with a quality control sample of 1,791 students during 1978-1979. The model was designed to identify corrective methods appropriate for different types of…

Urban air quality estimation study, phase 1

NASA Technical Reports Server (NTRS)

Diamante, J. M.; Englar, T. S., Jr.; Jazwinski, A. H.

1976-01-01

Possibilities are explored for applying estimation theory to the analysis, interpretation, and use of air quality measurements in conjunction with simulation models to provide a cost effective method of obtaining reliable air quality estimates for wide urban areas. The physical phenomenology of real atmospheric plumes from elevated localized sources is discussed. A fluctuating plume dispersion model is derived. Individual plume parameter formulations are developed along with associated a priori information. Individual measurement models are developed.

Incorporating principal component analysis into air quality model evaluation

EPA Science Inventory

The efficacy of standard air quality model evaluation techniques is becoming compromised as the simulation periods continue to lengthen in response to ever increasing computing capacity. Accordingly, the purpose of this paper is to demonstrate a statistical approach called Princi...

[Review on HSPF model for simulation of hydrology and water quality processes].

PubMed

Li, Zhao-fu; Liu, Hong-Yu; Li, Yan

2012-07-01

Hydrological Simulation Program-FORTRAN (HSPF), written in FORTRAN, is one ol the best semi-distributed hydrology and water quality models, which was first developed based on the Stanford Watershed Model. Many studies on HSPF model application were conducted. It can represent the contributions of sediment, nutrients, pesticides, conservatives and fecal coliforms from agricultural areas, continuously simulate water quantity and quality processes, as well as the effects of climate change and land use change on water quantity and quality. HSPF consists of three basic application components: PERLND (Pervious Land Segment) IMPLND (Impervious Land Segment), and RCHRES (free-flowing reach or mixed reservoirs). In general, HSPF has extensive application in the modeling of hydrology or water quality processes and the analysis of climate change and land use change. However, it has limited use in China. The main problems with HSPF include: (1) some algorithms and procedures still need to revise, (2) due to the high standard for input data, the accuracy of the model is limited by spatial and attribute data, (3) the model is only applicable for the simulation of well-mixed rivers, reservoirs and one-dimensional water bodies, it must be integrated with other models to solve more complex problems. At present, studies on HSPF model development are still undergoing, such as revision of model platform, extension of model function, method development for model calibration, and analysis of parameter sensitivity. With the accumulation of basic data and imorovement of data sharing, the HSPF model will be applied more extensively in China.

Short-term effects of air quality and thermal stress on non-accidental morbidity-a multivariate meta-analysis comparing indices to single measures.

PubMed

Lokys, Hanna Leona; Junk, Jürgen; Krein, Andreas

2018-01-01

Air quality and thermal stress lead to increased morbidity and mortality. Studies on morbidity and the combined impact of air pollution and thermal stress are still rare. To analyse the correlations between air quality, thermal stress and morbidity, we used a two-stage meta-analysis approach, consisting of a Poisson regression model combined with distributed lag non-linear models (DLNMs) and a meta-analysis investigating whether latitude or the number of inhabitants significantly influence the correlations. We used air pollution, meteorological and hospital admission data from 28 administrative districts along a north-south gradient in western Germany from 2001 to 2011. We compared the performance of the single measure particulate matter (PM10) and air temperature to air quality indices (MPI and CAQI) and the biometeorological index UTCI. Based on the Akaike information criterion (AIC), it can be shown that using air quality indices instead of single measures increases the model strength. However, using the UTCI in the model does not give additional information compared to mean air temperature. Interaction between the 3-day average of air quality (max PM10, max CAQI and max MPI) and meteorology (mean air temperature and mean UTCI) did not improve the models. Using the mean air temperature, we found immediate effects of heat stress (RR 1.0013, 95% CI: 0.9983-1.0043) and by 3 days delayed effects of cold stress (RR: 1.0184, 95% CI: 1.0117-1.0252). The results for air quality differ between both air quality indices and PM10. CAQI and MPI show a delayed impact on morbidity with a maximum RR after 2 days (MPI 1.0058, 95% CI: 1.0013-1.0102; CAQI 1.0068, 95% CI: 1.0030-1.0107). Latitude was identified as a significant meta-variable, whereas the number of inhabitants was not significant in the model.

Short-term effects of air quality and thermal stress on non-accidental morbidity—a multivariate meta-analysis comparing indices to single measures

NASA Astrophysics Data System (ADS)

Lokys, Hanna Leona; Junk, Jürgen; Krein, Andreas

2018-01-01

Air quality and thermal stress lead to increased morbidity and mortality. Studies on morbidity and the combined impact of air pollution and thermal stress are still rare. To analyse the correlations between air quality, thermal stress and morbidity, we used a two-stage meta-analysis approach, consisting of a Poisson regression model combined with distributed lag non-linear models (DLNMs) and a meta-analysis investigating whether latitude or the number of inhabitants significantly influence the correlations. We used air pollution, meteorological and hospital admission data from 28 administrative districts along a north-south gradient in western Germany from 2001 to 2011. We compared the performance of the single measure particulate matter (PM10) and air temperature to air quality indices (MPI and CAQI) and the biometeorological index UTCI. Based on the Akaike information criterion (AIC), it can be shown that using air quality indices instead of single measures increases the model strength. However, using the UTCI in the model does not give additional information compared to mean air temperature. Interaction between the 3-day average of air quality (max PM10, max CAQI and max MPI) and meteorology (mean air temperature and mean UTCI) did not improve the models. Using the mean air temperature, we found immediate effects of heat stress (RR 1.0013, 95% CI: 0.9983-1.0043) and by 3 days delayed effects of cold stress (RR: 1.0184, 95% CI: 1.0117-1.0252). The results for air quality differ between both air quality indices and PM10. CAQI and MPI show a delayed impact on morbidity with a maximum RR after 2 days (MPI 1.0058, 95% CI: 1.0013-1.0102; CAQI 1.0068, 95% CI: 1.0030-1.0107). Latitude was identified as a significant meta-variable, whereas the number of inhabitants was not significant in the model.

Modeling and Analysis of Process Parameters for Evaluating Shrinkage Problems During Plastic Injection Molding of a DVD-ROM Cover

NASA Astrophysics Data System (ADS)

Öktem, H.

2012-01-01

Plastic injection molding plays a key role in the production of high-quality plastic parts. Shrinkage is one of the most significant problems of a plastic part in terms of quality in the plastic injection molding. This article focuses on the study of the modeling and analysis of the effects of process parameters on the shrinkage by evaluating the quality of the plastic part of a DVD-ROM cover made with Acrylonitrile Butadiene Styrene (ABS) polymer material. An effective regression model was developed to determine the mathematical relationship between the process parameters (mold temperature, melt temperature, injection pressure, injection time, and cooling time) and the volumetric shrinkage by utilizing the analysis data. Finite element (FE) analyses designed by Taguchi (L27) orthogonal arrays were run in the Moldflow simulation program. Analysis of variance (ANOVA) was then performed to check the adequacy of the regression model and to determine the effect of the process parameters on the shrinkage. Experiments were conducted to control the accuracy of the regression model with the FE analyses obtained from Moldflow. The results show that the regression model agrees very well with the FE analyses and the experiments. From this, it can be concluded that this study succeeded in modeling the shrinkage problem in our application.

Retrospective analysis of the quality of reports by author-suggested and non-author-suggested reviewers in journals operating on open or single-blind peer review models.

PubMed

Kowalczuk, Maria K; Dudbridge, Frank; Nanda, Shreeya; Harriman, Stephanie L; Patel, Jigisha; Moylan, Elizabeth C

2015-09-29

To assess whether reports from reviewers recommended by authors show a bias in quality and recommendation for editorial decision, compared with reviewers suggested by other parties, and whether reviewer reports for journals operating on open or single-blind peer review models differ with regard to report quality and reviewer recommendations. Retrospective analysis of the quality of reviewer reports using an established Review Quality Instrument, and analysis of reviewer recommendations and author satisfaction surveys. BioMed Central biology and medical journals. BMC Infectious Diseases and BMC Microbiology are similar in size, rejection rates, impact factors and editorial processes, but the former uses open peer review while the latter uses single-blind peer review. The Journal of Inflammation has operated under both peer review models. Two hundred reviewer reports submitted to BMC Infectious Diseases, 200 reviewer reports submitted to BMC Microbiology and 400 reviewer reports submitted to the Journal of Inflammation. For each journal, author-suggested reviewers provided reports of comparable quality to non-author-suggested reviewers, but were significantly more likely to recommend acceptance, irrespective of the peer review model (p<0.0001 for BMC Infectious Diseases, BMC Microbiology and the Journal of Inflammation). For BMC Infectious Diseases, the overall quality of reviewer reports measured by the Review Quality Instrument was 5% higher than for BMC Microbiology (p=0.042). For the Journal of Inflammation, the quality of reports was the same irrespective of the peer review model used. Reviewers suggested by authors provide reports of comparable quality to non-author-suggested reviewers, but are significantly more likely to recommend acceptance. Open peer review reports for BMC Infectious Diseases were of higher quality than single-blind reports for BMC Microbiology. There was no difference in quality of peer review in the Journal of Inflammation under open peer review compared with single blind. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

[Environmental quality assessment of regional agro-ecosystem in Loess Plateau].

PubMed

Wang, Limei; Meng, Fanping; Zheng, Jiyong; Wang, Zhonglin

2004-03-01

Based on the detection and analysis of the contamination status of agro-ecosystem with apple-crops intercropping as the dominant cropping model in Loess Plateau, the individual factor and comprehensive environmental quality were assessed by multilevel fuzzy synthetic evaluation model, analytical hierarchy process(AHP), and improved standard weight deciding method. The results showed that the quality of soil, water and agricultural products was grade I, the social economical environmental quality was grade II, the ecological environmental quality was grade III, and the comprehensive environmental quality was grade I. The regional agro-ecosystem dominated by apple-crops intercropping was not the best model for the ecological benefits, but had the better social economical benefits.

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

A Latent Profile Analysis and Structural Equation Modeling of the Instructional Quality of Mathematics Classrooms Based on the PISA 2012 Results of Korea and Singapore

ERIC Educational Resources Information Center

Yi, Hyun Sook; Lee, Yuree

2017-01-01

Teachers' classroom behaviors and their effects on student learning have received significant attention from educators, because the quality of instruction is a critical factor closely tied to students' learning experiences. Based on a theoretical model conceptualizing the quality of instruction, this study examined the characteristics of…

Spatial Double Generalized Beta Regression Models: Extensions and Application to Study Quality of Education in Colombia

ERIC Educational Resources Information Center

Cepeda-Cuervo, Edilberto; Núñez-Antón, Vicente

2013-01-01

In this article, a proposed Bayesian extension of the generalized beta spatial regression models is applied to the analysis of the quality of education in Colombia. We briefly revise the beta distribution and describe the joint modeling approach for the mean and dispersion parameters in the spatial regression models' setting. Finally, we motivate…

Perceived service quality's effect on patient satisfaction and behavioural compliance.

PubMed

Mohamed, Bahari; Azizan, Noor Azlinna

2015-01-01

The purpose of this paper is to advance healthcare service quality research using hierarchical component models. This study used a quantitative approach with cross-sectional design as a survey method, combining cluster and convenience sampling and partial least square structural equation modelling (PLS-SEM) to validate the research model and test the hypotheses. The study extends health service quality literature by showing that: patient satisfaction (PS) is dominant, significant and indirect determinant of behavioural compliance (BC); perceived service quality has the strongest effect on BC via PS. Only one hospital was evaluated. The study provides managers with a service quality model for conducting integrated service delivery systems analysis and design. Overall, the study makes a significant contribution to healthcare organizations, better health outcomes for patients and better quality of life for the community.

Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

PubMed

Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

2017-07-01

Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

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...

Private healthcare quality: applying a SERVQUAL model.

PubMed

Butt, Mohsin Muhammad; de Run, Ernest Cyril

2010-01-01

This paper seeks to develop and test the SERVQUAL model scale for measuring Malaysian private health service quality. The study consists of 340 randomly selected participants visiting a private healthcare facility during a three-month data collection period. Data were analyzed using means, correlations, principal component and confirmatory factor analysis to establish the modified SERVQUAL scale's reliability, underlying dimensionality and convergent, discriminant validity. Results indicate a moderate negative quality gap for overall Malaysian private healthcare service quality. Results also indicate a moderate negative quality gap on each service quality scale dimension. However, scale development analysis yielded excellent results, which can be used in wider healthcare policy and practice. Respondents were skewed towards a younger population, causing concern that the results might not represent all Malaysian age groups. The study's major contribution is that it offers a way to assess private healthcare service quality. Second, it successfully develops a scale that can be used to measure health service quality in Malaysian contexts.

Scan-To Output Validation: Towards a Standardized Geometric Quality Assessment of Building Information Models Based on Point Clouds

NASA Astrophysics Data System (ADS)

Bonduel, M.; Bassier, M.; Vergauwen, M.; Pauwels, P.; Klein, R.

2017-11-01

The use of Building Information Modeling (BIM) for existing buildings based on point clouds is increasing. Standardized geometric quality assessment of the BIMs is needed to make them more reliable and thus reusable for future users. First, available literature on the subject is studied. Next, an initial proposal for a standardized geometric quality assessment is presented. Finally, this method is tested and evaluated with a case study. The number of specifications on BIM relating to existing buildings is limited. The Levels of Accuracy (LOA) specification of the USIBD provides definitions and suggestions regarding geometric model accuracy, but lacks a standardized assessment method. A deviation analysis is found to be dependent on (1) the used mathematical model, (2) the density of the point clouds and (3) the order of comparison. Results of the analysis can be graphical and numerical. An analysis on macro (building) and micro (BIM object) scale is necessary. On macro scale, the complete model is compared to the original point cloud and vice versa to get an overview of the general model quality. The graphical results show occluded zones and non-modeled objects respectively. Colored point clouds are derived from this analysis and integrated in the BIM. On micro scale, the relevant surface parts are extracted per BIM object and compared to the complete point cloud. Occluded zones are extracted based on a maximum deviation. What remains is classified according to the LOA specification. The numerical results are integrated in the BIM with the use of object parameters.

Verification and Evaluation of Aquatic Contaminant Simulation Module (CSM)

DTIC Science & Technology

2016-08-01

RECOVERY model (Boyer et al. 1994, Ruiz et al. 2000) and Water- quality Analysis Simulation Program (WASP) model (Wool et al. 2006). This technical note (TN...bacteria, and detritus). Natural waters can contain a mixture of solid particles ranging from gravel (2 mm to 20 mm) or sand (0.07 mm to 2 mm) down to... quality perspective, cohesive sediments are usually of greater importance in water quality modeling. The chemical species in the active sediment

Project ATLANTA (Atlanta Land use Analysis: Temperature and Air Quality): Use of Remote Sensing and Modeling to Analyze How Urban Land Use Change Affects Meteorology and Air Quality Through Time

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Luvall, Jeffrey C.; Estes, Maurice G., Jr.

1999-01-01

This paper presents an overview of Project ATLANTA (ATlanta Land use ANalysis: Temperature and Air-quality) which is an investigation that seeks to observe, measure, model, and analyze how the rapid growth of the Atlanta, Georgia metropolitan area since the early 1970's has impacted the region's climate and air quality. The primary objectives for this research effort are: (1) To investigate and model the relationships between land cover change in the Atlanta metropolitan, and the development of the urban heat island phenomenon through time; (2) To investigate and model the temporal relationships between Atlanta urban growth and land cover change on air quality; and (3) To model the overall effects of urban development on surface energy budget characteristics across the Atlanta urban landscape through time. Our key goal is to derive a better scientific understanding of how land cover changes associated with urbanization in the Atlanta area, principally in transforming forest lands to urban land covers through time, has, and will, effect local and regional climate, surface energy flux, and air quality characteristics. Allied with this goal is the prospect that the results from this research can be applied by urban planners, environmental managers and other decision-makers, for determining how urbanization has impacted the climate and overall environment of the Atlanta area. Multiscaled remote sensing data, particularly high resolution thermal infrared data, are integral to this study for the analysis of thermal energy fluxes across the Atlanta urban landscape.

Weighted analysis of paired microarray experiments.

PubMed

Kristiansson, Erik; Sjögren, Anders; Rudemo, Mats; Nerman, Olle

2005-01-01

In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.

Economic production quantity model for items with continuous quality characteristic, rework and reject

NASA Astrophysics Data System (ADS)

Tsou, Jia-Chi; Hejazi, Seyed Reza; Rasti Barzoki, Morteza

2012-12-01

The economic production quantity (EPQ) model is a well-known and commonly used inventory control technique. However, the model is built on an unrealistic assumption that all the produced items need to be of perfect quality. Having relaxed this assumption, some researchers have studied the effects of the imperfect products on the inventory control techniques. This article, thus, attempts to develop an EPQ model with continuous quality characteristic and rework. To this end, this study assumes that a produced item follows a general distribution pattern, with its quality being perfect, imperfect or defective. The analysis of the model developed indicates that there is an optimal lot size, which generates minimum total cost. Moreover, the results show that the optimal lot size of the model equals that of the classical EPQ model in case imperfect quality percentage is zero or even close to zero.

Trend analysis of salt load and evaluation of the frequency of water-quality measurements for the Gunnison, the Colorado, and the Dolores rivers in Colorado and Utah

USGS Publications Warehouse

Kircher, J.E.; Dinicola, Richard S.; Middelburg, R.F.

1984-01-01

Monthly values were computed for water-quality constituents at four streamflow gaging stations in the Upper Colorado River basin for the determination of trends. Seasonal regression and seasonal Kendall trend analysis techniques were applied to two monthly data sets at each station site for four different time periods. A recently developed method for determining optimal water-discharge data-collection frequency was also applied to the monthly water-quality data. Trend analysis results varied with each monthly load computational method, period of record, and trend detection model used. No conclusions could be reached regarding which computational method was best to use in trend analysis. Time-period selection for analysis was found to be important with regard to intended use of the results. Seasonal Kendall procedures were found to be applicable to most data sets. Seasonal regression models were more difficult to apply and were sometimes of questionable validity; however, those results were more informative than seasonal Kendall results. The best model to use depends upon the characteristics of the data and the amount of trend information needed. The measurement-frequency optimization method had potential for application to water-quality data, but refinements are needed. (USGS)

On the Use of Principal Component and Spectral Density Analysis to Evaluate the Community Multiscale Air Quality (CMAQ) Model

EPA Science Inventory

A 5 year (2002-2006) simulation of CMAQ covering the eastern United States is evaluated using principle component analysis in order to identify and characterize statistically significant patterns of model bias. Such analysis is useful in that in can identify areas of poor model ...

F-15 inlet/engine test techniques and distortion methodologies studies. Volume 2: Time variant data quality analysis plots

NASA Technical Reports Server (NTRS)

Stevens, C. H.; Spong, E. D.; Hammock, M. S.

1978-01-01

Time variant data quality analysis plots were used to determine if peak distortion data taken from a subscale inlet model can be used to predict peak distortion levels for a full scale flight test vehicle.

Factor analytical study of the short version of the World Health Organization Quality of Life Instrument.

PubMed

Ohaeri, Jude U; Olusina, Adewunmi K; Al-Abassi, Abdul-Hamid M

2004-01-01

The domains of the 26-item World Health Organization Quality of Life Instrument (WHOQOL-Bref) contain heterogeneous items and do not encompass the logical constructs of subjective quality of life (QOL). We compared the WHO 4-domain and 6-domain models of the WHOQOL-Bref with the 8-domain model that we obtained from factor analysis (FA). Data from 118 recently recovered Nigerian psychotic patients were used in confirmatory factor analysis (CFA) to assess goodness of fit and clarity of concept. Our FA model had superior goodness of fit for CFA and provided clarity of concept. Analysis of the WHOQOL-Bref should consider the domains from FA and include 'overall QOL' as an item and dependent variable. Subjective QOL is an aggregate of the following constructs: satisfaction with life circumstances; fulfillment of needs, and opportunity for experience in the milieu.

Information security system quality assessment through the intelligent tools

NASA Astrophysics Data System (ADS)

Trapeznikov, E. V.

2018-04-01

The technology development has shown the automated system information security comprehensive analysis necessity. The subject area analysis indicates the study relevance. The research objective is to develop the information security system quality assessment methodology based on the intelligent tools. The basis of the methodology is the information security assessment model in the information system through the neural network. The paper presents the security assessment model, its algorithm. The methodology practical implementation results in the form of the software flow diagram are represented. The practical significance of the model being developed is noted in conclusions.

Estimating short-period dynamics using an extended Kalman filter

NASA Technical Reports Server (NTRS)

Bauer, Jeffrey E.; Andrisani, Dominick

1990-01-01

An extended Kalman filter (EKF) is used to estimate the parameters of a low-order model from aircraft transient response data. The low-order model is a state space model derived from the short-period approximation of the longitudinal aircraft dynamics. The model corresponds to the pitch rate to stick force transfer function currently used in flying qualities analysis. Because of the model chosen, handling qualities information is also obtained. The parameters are estimated from flight data as well as from a six-degree-of-freedom, nonlinear simulation of the aircraft. These two estimates are then compared and the discrepancies noted. The low-order model is able to satisfactorily match both flight data and simulation data from a high-order computer simulation. The parameters obtained from the EKF analysis of flight data are compared to those obtained using frequency response analysis of the flight data. Time delays and damping ratios are compared and are in agreement. This technique demonstrates the potential to determine, in near real time, the extent of differences between computer models and the actual aircraft. Precise knowledge of these differences can help to determine the flying qualities of a test aircraft and lead to more efficient envelope expansion.

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin

PubMed Central

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency’s model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program—Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes. PMID:29162976

Linking Air Quality and Human Health Effects Models: An Application to the Los Angeles Air Basin.

PubMed

Stewart, Devoun R; Saunders, Emily; Perea, Roberto A; Fitzgerald, Rosa; Campbell, David E; Stockwell, William R

2017-01-01

Proposed emission control strategies for reducing ozone and particulate matter are evaluated better when air quality and health effects models are used together. The Community Multiscale Air Quality (CMAQ) model is the US Environmental Protection Agency's model for determining public policy and forecasting air quality. CMAQ was used to forecast air quality changes due to several emission control strategies that could be implemented between 2008 and 2030 for the South Coast Air Basin that includes Los Angeles. The Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) was used to estimate health and economic impacts of the different emission control strategies based on CMAQ simulations. BenMAP-CE is a computer program based on epidemiologic studies that link human health and air quality. This modeling approach is better for determining optimum public policy than approaches that only examine concentration changes.

Applications of MIDAS regression in analysing trends in water quality

NASA Astrophysics Data System (ADS)

Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

2014-04-01

We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

SBKF Modeling and Analysis Plan: Buckling Analysis of Compression-Loaded Orthogrid and Isogrid Cylinders

NASA Technical Reports Server (NTRS)

Lovejoy, Andrew E.; Hilburger, Mark W.

2013-01-01

This document outlines a Modeling and Analysis Plan (MAP) to be followed by the SBKF analysts. It includes instructions on modeling and analysis formulation and execution, model verification and validation, identifying sources of error and uncertainty, and documentation. The goal of this MAP is to provide a standardized procedure that ensures uniformity and quality of the results produced by the project and corresponding documentation.

40 CFR 51.852 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... manager means the Federal agency or the Federal official charged with direct responsibility for management... requirements of the Act. Areawide air quality modeling analysis means an assessment on a scale that includes the entire nonattainment or maintenance area which uses an air quality dispersion model to determine...

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...

Land Surface Process and Air Quality Research and Applications at MSFC

NASA Technical Reports Server (NTRS)

Quattrochi, Dale; Khan, Maudood

2007-01-01

This viewgraph presentation provides an overview of land surface process and air quality research at MSFC including atmospheric modeling and ongoing research whose objective is to undertake a comprehensive spatiotemporal analysis of the effects of accurate land surface characterization on atmospheric modeling results, and public health applications. Land use maps as well as 10 meter air temperature, surface wind, PBL mean difference heights, NOx, ozone, and O3+NO2 plots as well as spatial growth model outputs are included. Emissions and general air quality modeling are also discussed.

Quality Inspection and Analysis of Three-Dimensional Geographic Information Model Based on Oblique Photogrammetry

NASA Astrophysics Data System (ADS)

Dong, S.; Yan, Q.; Xu, Y.; Bai, J.

2018-04-01

In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

Modeling the relationship between landscape characteristics and water quality in a typical highly intensive agricultural small watershed, Dongting lake basin, south central China.

PubMed

Li, Hongqing; Liu, Liming; Ji, Xiang

2015-03-01

Understanding the relationship between landscape characteristics and water quality is critically important for estimating pollution potential and reducing pollution risk. Therefore, this study examines the relationship between landscape characteristics and water quality at both spatial and temporal scales. The study took place in the Jinjing River watershed in 2010; seven landscape types and four water quality pollutions were chosen as analysis parameters. Three different buffer areas along the river were drawn to analyze the relationship as a function of spatial scale. The results of a Pearson's correlation coefficient analysis suggest that "source" landscape, namely, tea gardens, residential areas, and paddy lands, have positive effects on water quality parameters, while forests exhibit a negative influence on water quality parameters because they represent a "sink" landscape and the sub-watershed level is identified as a suitable scale. Using the principal component analysis, tea gardens, residential areas, paddy lands, and forests were identified as the main landscape index. A stepwise multiple regression analysis was employed to model the relationship between landscape characteristics and water quality for each season. The results demonstrate that both landscape composition and configuration affect water quality. In summer and winter, the landscape metrics explained approximately 80.7 % of the variance in the water quality variables, which was higher than that for spring and fall (60.3 %). This study can help environmental managers to understand the relationships between landscapes and water quality and provide landscape ecological approaches for water quality control and land use management.

A three-model comparison of the relationship between quality, satisfaction and loyalty: an empirical study of the Chinese healthcare system

PubMed Central

2012-01-01

Background Previous research has addressed the relationship between customer satisfaction, perceived quality and customer loyalty intentions in consumer markets. In this study, we test and compare three theoretical models of the quality–satisfaction–loyalty relationship in the Chinese healthcare system. Methods This research focuses on hospital patients as participants in the process of healthcare procurement. Empirical data were obtained from six Chinese public hospitals in Shanghai. A total of 630 questionnaires were collected in two studies. Study 1 tested the research instruments, and Study 2 tested the three models. Confirmatory factor analysis was used to assess the scales’ construct validity by testing convergent and discriminant validity. A structural equation model (SEM) specified the distinctions between each construct. A comparison of the three theoretical models was conducted via AMOS analysis. Results The results of the SEM demonstrate that quality and satisfaction are distinct concepts and that the first model (satisfaction mediates quality and loyalty) is the most appropriate one in the context of the Chinese healthcare environment. Conclusions In this study, we test and compare three theoretical models of the quality–satisfaction–loyalty relationship in the Chinese healthcare system. Findings show that perceived quality improvement does not lead directly to customer loyalty. The strategy of using quality improvement to maintain patient loyalty depends on the level of patient satisfaction. This implies that the measurement of patient experiences should include topics of importance for patients’ satisfaction with health care services. PMID:23198824

Analysis of wind-tunnel stability and control tests in terms of flying qualities of full-scale airplanes

NASA Technical Reports Server (NTRS)

Kayten, Gerald G

1945-01-01

The analysis of results of wind-tunnel stability and control tests of powered airplane models in terms of the flying qualities of full-scale airplanes is advocated. In order to indicated the topics upon which comments are considered desirable in the report of a wind-tunnel stability and control investigation and to demonstrate the nature of the suggested analysis, the present NACA flying-qualities requirements are discussed in relation to wind-tunnel tests. General procedures for the estimation of flying qualities from wind-tunnel tests are outlined.

Quality transitivity and traceability system of herbal medicine products based on quality markers.

PubMed

Liu, Changxiao; Guo, De-An; Liu, Liang

2018-05-15

Due to a variety of factors to affect the herb quality, the existing quality management model is unable to evaluate the process control. The development of the concept of "quality marker" (Q-marker) lays basis for establishing an independent process quality control system for herbal products. To ensure the highest degree of safety, effectiveness and quality process control of herbal products, it is aimed to establish a quality transitivity and traceability system of quality and process control from raw materials to finished herbal products. Based on the key issues and challenges of quality assessment, the current status of quality and process controls from raw materials to herbal medicinal products listed in Pharmacopoeia were analyzed and the research models including discovery and identification of Q-markers, analysis and quality management of risk evaluation were designed. Authors introduced a few new technologies and methodologies, such as DNA barcoding, chromatographic technologies, fingerprint analysis, chemical markers, bio-responses, risk management and solution for quality process control. The quality and process control models for herbal medicinal products were proposed and the transitivity and traceability system from raw materials to the finished products was constructed to improve the herbal quality from the entire supply and production chain. The transitivity and traceability system has been established based on quality markers, especially on how to control the production process under Good Engineering Practices, as well as to implement the risk management for quality and process control in herbal medicine production. Copyright © 2018 Elsevier GmbH. All rights reserved.

Structural dynamic model obtained from flight use with piloted simulation and handling qualities analysis

NASA Technical Reports Server (NTRS)

Powers, Bruce G.

1996-01-01

The ability to use flight data to determine an aircraft model with structural dynamic effects suitable for piloted simulation. and handling qualities analysis has been developed. This technique was demonstrated using SR-71 flight test data. For the SR-71 aircraft, the most significant structural response is the longitudinal first-bending mode. This mode was modeled as a second-order system, and the other higher order modes were modeled as a time delay. The distribution of the modal response at various fuselage locations was developed using a uniform beam solution, which can be calibrated using flight data. This approach was compared to the mode shape obtained from the ground vibration test, and the general form of the uniform beam solution was found to be a good representation of the mode shape in the areas of interest. To calibrate the solution, pitch-rate and normal-acceleration instrumentation is required for at least two locations. With the resulting structural model incorporated into the simulation, a good representation of the flight characteristics was provided for handling qualities analysis and piloted simulation.

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.

A Longitudinal Examination of Middle School Science Learners' Use of Scaffolding In and Around a Dynamic Modeling Tool

NASA Astrophysics Data System (ADS)

Fretz, Eric Bruce

Scaffolding is a term rooted in multiple research communities over decades of development. Customized, contingent support can be provided to learners to enable performances beyond what they can do alone. This dissertation seeks to examine how effectively scaffolds designed to promote articulation (written expressions of learner understanding) actually work, and if this effectiveness and/or the quality of the resulting models changes over time. It longitudinally examines the use of scaffolds designed into a dynamic modeling tool, as it is used by middle school science learners to create, test, and revise models of complex science phenomena like stream ecosystems. This dissertation also reviews the origins of the scaffolding construct, and summarizes conceptions of scaffolding from various lines of research. Scaffolding can be provided by both human and non-human agents, such as computers, which require specialized interface design to ensure maximum effectiveness. In the study, learners created models in four curriculum units over the seventh and eighth grade school years. Additionally, this dissertation examines the nature of the discussion learners have while using these scaffolds and the frequency and types of interpersonal scaffolds employed during the creation of models. Model quality is also examined using a rubric developed through review of prior research on assessing models and concept maps. Learner pairs' model creation sessions on a computer are captured with screen video and learner audio, and then distilled to transcripts for subsequent coding and analysis, supported by qualitative analysis software. Articulation scaffolds were found to succeed in promoting articulations and the quality of those articulations improved over time. Learner dialog associated with these written articulations is of reasonable quality but did not improve over time. Quality of model artifacts did improve over time. The overall use of scaffolding by each learner pair was contrasted with that pairs model quality, but no relationship was found. Software design and classroom implementation implications of these findings are discussed. The frequency of interpersonal scaffolding provided by teachers highlights the need to consider scaffolding holistically and synergistically, with design decisions for software tools made in light of careful analysis as to what human and non-human agents can and should each provide.

Analysis of apple beverages treated with high-power ultrasound: a quality function deployment approach.

PubMed

Režek Jambrak, Anet; Šimunek, Marina; Grbeš, Franjo; Mandura, Ana; Djekic, Ilija

2018-04-01

The objective of this paper was to demonstrate application of quality function deployment in analysing effects of high power ultrasound on quality properties of apple juices and nectars. In order to develop a quality function deployment model, joint with instrumental analysis of treated samples, a field survey was performed to identify consumer preferences towards quality characteristics of juices/nectar. Based on field research, the three most important characteristics were 'taste' and 'aroma' with 28.5% of relative absolute weight importance, followed by 'odour' (16.9%). The quality function deployment model showed that the top three 'quality scores' for apple juice were treatments with amplitude 90 µm, 9 min treatment time and sample temperature 40 °C; 60 µm, 9 min, 60 °C; and 90 µm, 6 min, 40 °C. For nectars, the top three were treatments 120 µm, 9 min, 20 °C; 60 µm, 9 min, 60 °C; and A2.16 60 µm, 9 min, 20 °C. This type of quality model enables a more complex measure of large scale of different quality parameters. Its simplicity should be understood as its practical advantage and, as such, this tool can be a part of design quality when using novel preservation technologies. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

A Conceptual Analysis of Quality in Quality Function Deployment-Based Contexts of Higher Education

ERIC Educational Resources Information Center

Matorera, Douglas

2015-01-01

The purpose of this paper is to assess and evaluate how higher education institutions (HEIs) using Quality Function Deployment draw out the relevancy and potential of the model in shaping their concept of "Quality" and how that Quality can be assured in higher education institutions' (HEIs') programmes. An intensive literature review was…

Quality Tools for Professional Higher Education Review and Improvement. PHExcel Report

ERIC Educational Resources Information Center

Jørgensen, Malene Dahl; Sparre Kristensen, Regitze; Wimpf, Alexandre; Delplace, Stefan

2014-01-01

The report is the project's first outcome, and provides an overview of quality tools, quality models and quality labels, currently in use in (professional) higher education. It is followed by a gap analysis as regards the Standards and Guidelines for quality assurance in the European Higher Education Area (ESG), and the identified characteristics…

Air Quality Analysis of a Multilevel Complex Interchange : Case Study Using the Improved TSC/EPA Model

DOT National Transportation Integrated Search

1976-12-01

This report describes a case study of an air quality analysis prepared by the U.S. Department of Transportation (DOT), Transportation Systems Center (TSC). The site analyzed was the proposed I-83/I-95 interchange in Baltimore, Maryland. This intercha...

Comprehensive School Reform and Achievement: A Meta-Analysis

ERIC Educational Resources Information Center

Borman, Geoffrey D.; Hewes, Gina M.; Overman, Laura T.; Brown, Shelly

2003-01-01

This meta-analysis reviews research on the achievement effects of comprehensive school reform (CSR) and summarizes the specific effects of 29 widely implemented models. There are limitations on the overall quantity and quality of the research base, but the overall effects of CSR appear promising. The combined quantity, quality, and statistical…

Improving quality-of-life outcomes for patients with cancer through mediating effects of depressive symptoms and functional status: a three-path mediation model.

PubMed

Hsu, Mei-Chi; Tu, Chun-Hsien

2014-09-01

To test a hypothetical three-path mediation model evaluating the effects of functional status and depressive symptoms on the relationship between fatigue and quality of life in patients with cancer on the basis of the Theory of Unpleasant Symptoms. Patients with cancer often experience two or more concurrent, interrelated, mutually influential symptoms. Multiple unpleasant symptoms that have been proposed as mediating variables affecting quality of life in a model proposed in recent cancer studies are scanty. This study was a cross-sectional, descriptive, correlational design. Three hundred and twenty-six patients with cancer from oncology clinics were recruited in Taiwan between 2010-2011. Mediation models were tested and confirmed by applying structural modelling using Analysis of Moment Structures and the joint significance test. Fatigue affects patient quality of life directly or indirectly through functional status and depressive symptoms. These two mediating variables exhibited direct effects on quality of life. A path analysis approach revealed that 47·28 and 67·70% of the total effects of functional status and depressive symptoms, respectively, on the quality-of-life mediation models are attributable to 29·6 and 44·7% of the total effects between fatigue and quality of life, which mediated through two mediators, respectively. Quality of life may be enhanced by simultaneously improving physiological and psychological factors. An understanding of mediating effects is valuable in nursing care of patients with cancer, particularly in the early phase of treatment or in newly diagnosed stages I-III or recently treated patients with cancer in different disease stages. © 2013 John Wiley & Sons Ltd.

Do written mandatory accreditation standards for residential care positively model learning organizations? Textual and critical discourse analysis.

PubMed

Bell, Erica; Robinson, Andrew; See, Catherine

2013-11-01

Unprecedented global population ageing accompanied by increasing complexity of aged care present major challenges of quality in aged care. In the business literature, Senge's theory of adaptive learning organisations offers a model of organisational quality. However, while accreditation of national standards is an increasing mechanism for achieving quality in aged care, there are anecdotal concerns it creates a 'minimum standards compliance mentality' and no evidence about whether it reinforces learning organisations. The research question was 'Do mandatory national accreditation standards for residential aged care, as they are written, positively model learning organisations?'. Automatic text analysis was combined with critical discourse analysis to analyse the presence of learning concepts from Senge's learning organisation theory in an exhaustive sample of national accreditation standards from 7 countries. The two stages of analysis were: (1) quantitative mapping of the presence of learning organisation concepts in standards using Bayesian-based textual analytics software and (2) qualitative critical discourse analysis to further examine how the language of standards so identified may be modelling learning organisation concepts. The learning concepts 'training', 'development', 'knowledge', and 'systems' are present with relative frequencies of 19%, 11%, 10%, and 10% respectively in the 1944 instances, in paragraph-sized text blocks, considered. Concepts such as 'team', 'integration', 'learning', 'change' and 'innovation' occur with 7%, 6%, 5%, 5%, and 1% relative frequencies respectively. Learning concepts tend to co-occur with negative rather than positive sentiment language in the 3176 instances in text blocks containing sentiment language. Critical discourse analysis suggested that standards generally use the language of organisational change and learning in limited ways that appear to model 'learning averse' communities of practice and organisational cultures. The aged care quality challenge and the role of standards need rethinking. All standards implicitly or explicitly model an organisation of some type. If standards can model a limited and negative learning organisation language, they could model a well-developed and positive learning organisation language. In the context of the global aged care crisis, the modelling of learning organisations is probably critical for minimal competence in residential aged care and certainly achievable in the language of standards. Copyright © 2013 Elsevier Ltd. All rights reserved.

Measuring Student Course Evaluations: The Use of a Loglinear Model

ERIC Educational Resources Information Center

Ting, Ding Hooi; Abella, Mireya Sosa

2007-01-01

In this paper, the researchers attempt to incorporate the marketing theory (specifically the service quality model) into the education system. The service quality measurements have been employed to investigate its applicability in the education environment. Most of previous studies employ the regression-based analysis to test the effectiveness of…

An Analytical Hierarchy Process Model for the Evaluation of College Experimental Teaching Quality

ERIC Educational Resources Information Center

Yin, Qingli

2013-01-01

Taking into account the characteristics of college experimental teaching, through investigaton and analysis, evaluation indices and an Analytical Hierarchy Process (AHP) model of experimental teaching quality have been established following the analytical hierarchy process method, and the evaluation indices have been given reasonable weights. An…

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...

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

2017-10-01

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

A modeling analysis program for the JPL Table Mountain Io sodium cloud data

NASA Technical Reports Server (NTRS)

Smyth, W. H.; Goldberg, B. A.

1986-01-01

Progress and achievements in the second year are discussed in three main areas: (1) data quality review of the 1981 Region B/C images; (2) data processing activities; and (3) modeling activities. The data quality review revealed that almost all 1981 Region B/C images are of sufficient quality to be valuable in the analyses of the JPL data set. In the second area, the major milestone reached was the successful development and application of complex image-processing software required to render the original image data suitable for modeling analysis studies. In the third area, the lifetime description of sodium atoms in the planet magnetosphere was improved in the model to include the offset dipole nature of the magnetic field as well as an east-west electric field. These improvements are important in properly representing the basic morphology as well as the east-west asymmetries of the sodium cloud.

Receiving water quality assessment: comparison between simplified and detailed integrated urban modelling approaches.

PubMed

Mannina, Giorgio; Viviani, Gaspare

2010-01-01

Urban water quality management often requires use of numerical models allowing the evaluation of the cause-effect relationship between the input(s) (i.e. rainfall, pollutant concentrations on catchment surface and in sewer system) and the resulting water quality response. The conventional approach to the system (i.e. sewer system, wastewater treatment plant and receiving water body), considering each component separately, does not enable optimisation of the whole system. However, recent gains in understanding and modelling make it possible to represent the system as a whole and optimise its overall performance. Indeed, integrated urban drainage modelling is of growing interest for tools to cope with Water Framework Directive requirements. Two different approaches can be employed for modelling the whole urban drainage system: detailed and simplified. Each has its advantages and disadvantages. Specifically, detailed approaches can offer a higher level of reliability in the model results, but can be very time consuming from the computational point of view. Simplified approaches are faster but may lead to greater model uncertainty due to an over-simplification. To gain insight into the above problem, two different modelling approaches have been compared with respect to their uncertainty. The first urban drainage integrated model approach uses the Saint-Venant equations and the 1D advection-dispersion equations, for the quantity and for the quality aspects, respectively. The second model approach consists of the simplified reservoir model. The analysis used a parsimonious bespoke model developed in previous studies. For the uncertainty analysis, the Generalised Likelihood Uncertainty Estimation (GLUE) procedure was used. Model reliability was evaluated on the basis of capacity of globally limiting the uncertainty. Both models have a good capability to fit the experimental data, suggesting that all adopted approaches are equivalent both for quantity and quality. The detailed model approach is more robust and presents less uncertainty in terms of uncertainty bands. On the other hand, the simplified river water quality model approach shows higher uncertainty and may be unsuitable for receiving water body quality assessment.

Simulation of in-stream water quality on global scale under changing climate and anthropogenic conditions

NASA Astrophysics Data System (ADS)

Voss, Anja; Bärlund, Ilona; Punzet, Manuel; Williams, Richard; Teichert, Ellen; Malve, Olli; Voß, Frank

2010-05-01

Although catchment scale modelling of water and solute transport and transformations is a widely used technique to study pollution pathways and effects of natural changes, policies and mitigation measures there are only a few examples of global water quality modelling. This work will provide a description of the new continental-scale model of water quality WorldQual and the analysis of model simulations under changed climate and anthropogenic conditions with respect to changes in diffuse and point loading as well as surface water quality. BOD is used as an indicator of the level of organic pollution and its oxygen-depleting potential, and for the overall health of aquatic ecosystems. The first application of this new water quality model is to river systems of Europe. The model itself is being developed as part of the EU-funded SCENES Project which has the principal goal of developing new scenarios of the future of freshwater resources in Europe. The aim of the model is to determine chemical fluxes in different pathways combining analysis of water quantity with water quality. Simple equations, consistent with the availability of data on the continental scale, are used to simulate the response of in-stream BOD concentrations to diffuse and anthropogenic point loadings as well as flow dilution. Point sources are divided into manufacturing, domestic and urban loadings, whereas diffuse loadings come from scattered settlements, agricultural input (for instance livestock farming), and also from natural background sources. The model is tested against measured longitudinal gradients and time series data at specific river locations with different loading characteristics like the Thames that is driven by domestic loading and Ebro with relative high share of diffuse loading. With scenario studies the influence of climate and anthropogenic changes on European water resources shall be investigated with the following questions: 1. What percentage of river systems will have degraded water quality due to different driving forces? 2. How will climate change and changes in wastewater discharges affect water quality? For the analysis these scenario aspects are included: 1. climate with changed runoff (affecting diffuse pollution and loading from sealed areas), river discharge (causing dilution or concentration of point source pollution) and water temperature (affecting BOD degradation). 2. Point sources with changed population (affecting domestic pollution), connectivity to treatment plants (influencing domestic and manufacturing pollution as well as input from sealed areas and scattered settlements).

Analysis of Moisture Content in Beetroot using Fourier Transform Infrared Spectroscopy and by Principal Component Analysis.

PubMed

Nesakumar, Noel; Baskar, Chanthini; Kesavan, Srinivasan; Rayappan, John Bosco Balaguru; Alwarappan, Subbiah

2018-05-22

The moisture content of beetroot varies during long-term cold storage. In this work, we propose a strategy to identify the moisture content and age of beetroot using principal component analysis coupled Fourier transform infrared spectroscopy (FTIR). Frequent FTIR measurements were recorded directly from the beetroot sample surface over a period of 34 days for analysing its moisture content employing attenuated total reflectance in the spectral ranges of 2614-4000 and 1465-1853 cm -1 with a spectral resolution of 8 cm -1 . In order to estimate the transmittance peak height (T p ) and area under the transmittance curve [Formula: see text] over the spectral ranges of 2614-4000 and 1465-1853 cm -1 , Gaussian curve fitting algorithm was performed on FTIR data. Principal component and nonlinear regression analyses were utilized for FTIR data analysis. Score plot over the ranges of 2614-4000 and 1465-1853 cm -1 allowed beetroot quality discrimination. Beetroot quality predictive models were developed by employing biphasic dose response function. Validation experiment results confirmed that the accuracy of the beetroot quality predictive model reached 97.5%. This research work proves that FTIR spectroscopy in combination with principal component analysis and beetroot quality predictive models could serve as an effective tool for discriminating moisture content in fresh, half and completely spoiled stages of beetroot samples and for providing status alerts.

Development of urban runoff model FFC-QUAL for first-flush water-quality analysis in urban drainage basins.

PubMed

Hur, Sungchul; Nam, Kisung; Kim, Jungsoo; Kwak, Changjae

2018-01-01

An urban runoff model that is able to compute the runoff, the pollutant loadings, and the concentrations of water-quality constituents in urban drainages during the first flush was developed. This model, which is referred to as FFC-QUAL, was modified from the existing ILLUDAS model and added for use during the water-quality analysis process for dry and rainy periods. For the dry period, the specifications of the coefficients for the discharge and water quality were used. During rainfall, we used the Clark and time-area methods for the runoff analyses of pervious and impervious areas to consider the effects of the subbasin shape; moreover, four pollutant accumulation methods and the washoff equation for computing the water quality each time were used. According to the verification results, FFC-QUAL provides generally similar output as the measured data for the peak flow, total runoff volume, total loadings, peak concentration, and time of peak concentration for three rainfall events in the Gunja subbasin. In comparison with the ILLUDAS, SWMM, and MOUSE models, there is little difference between these models and the model developed in this study. The proposed model should be useful in urban watersheds because of its simplicity and its capacity to model common pollutants (e.g., biological oxygen demand, chemical oxygen demand, Escherichia coli, suspended solids, and total nitrogen and phosphorous) in runoff. The proposed model can also be used in design studies to determine how changes in infrastructure will affect the runoff and pollution loads. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Multi-criteria analysis for PM10 planning

NASA Astrophysics Data System (ADS)

Pisoni, Enrico; Carnevale, Claudio; Volta, Marialuisa

To implement sound air quality policies, Regulatory Agencies require tools to evaluate outcomes and costs associated to different emission reduction strategies. These tools are even more useful when considering atmospheric PM10 concentrations due to the complex nonlinear processes that affect production and accumulation of the secondary fraction of this pollutant. The approaches presented in the literature (Integrated Assessment Modeling) are mainly cost-benefit and cost-effective analysis. In this work, the formulation of a multi-objective problem to control particulate matter is proposed. The methodology defines: (a) the control objectives (the air quality indicator and the emission reduction cost functions); (b) the decision variables (precursor emission reductions); (c) the problem constraints (maximum feasible technology reductions). The cause-effect relations between air quality indicators and decision variables are identified tuning nonlinear source-receptor models. The multi-objective problem solution provides to the decision maker a set of not-dominated scenarios representing the efficient trade-off between the air quality benefit and the internal costs (emission reduction technology costs). The methodology has been implemented for Northern Italy, often affected by high long-term exposure to PM10. The source-receptor models used in the multi-objective analysis are identified processing long-term simulations of GAMES multiphase modeling system, performed in the framework of CAFE-Citydelta project.

Evaluation and error apportionment of an ensemble of ...

EPA Pesticide Factsheets

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) helping to detect causes of models error, and iii) identifying the processes and scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance and covariance) can help to 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 former phases of AQMEII.The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact

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

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.

Parallel Computing and Model Evaluation for Environmental Systems: An Overview of the Supermuse and Frames Software Technologies

EPA Science Inventory

ERD’s Supercomputer for Model Uncertainty and Sensitivity Evaluation (SuperMUSE) is a key to enhancing quality assurance in environmental models and applications. Uncertainty analysis and sensitivity analysis remain critical, though often overlooked steps in the development and e...

Prediction of aircraft handling qualities using analytical models of the human pilot

NASA Technical Reports Server (NTRS)

Hess, R. A.

1982-01-01

The optimal control model (OCM) of the human pilot is applied to the study of aircraft handling qualities. Attention is focused primarily on longitudinal tasks. The modeling technique differs from previous applications of the OCM in that considerable effort is expended in simplifying the pilot/vehicle analysis. After briefly reviewing the OCM, a technique for modeling the pilot controlling higher order systems is introduced. Following this, a simple criterion for determining the susceptibility of an aircraft to pilot-induced oscillations (PIO) is formulated. Finally, a model-based metric for pilot rating prediction is discussed. The resulting modeling procedure provides a relatively simple, yet unified approach to the study of a variety of handling qualities problems.

Prediction of aircraft handling qualities using analytical models of the human pilot

NASA Technical Reports Server (NTRS)

Hess, R. A.

1982-01-01

The optimal control model (OCM) of the human pilot is applied to the study of aircraft handling qualities. Attention is focused primarily on longitudinal tasks. The modeling technique differs from previous applications of the OCM in that considerable effort is expended in simplifying the pilot/vehicle analysis. After briefly reviewing the OCM, a technique for modeling the pilot controlling higher order systems is introduced. Following this, a simple criterion for determining the susceptibility of an aircraft to pilot induced oscillations is formulated. Finally, a model based metric for pilot rating prediction is discussed. The resulting modeling procedure provides a relatively simple, yet unified approach to the study of a variety of handling qualities problems.

Knowledge work productivity effect on quality of knowledge work in software development process in SME

NASA Astrophysics Data System (ADS)

Yusoff, Mohd Zairol; Mahmuddin, Massudi; Ahmad, Mazida

2016-08-01

Knowledge and skill are necessary to develop the capability of knowledge workers. However, there is very little understanding of what the necessary knowledge work (KW) is, and how they influence the quality of knowledge work or knowledge work productivity (KWP) in software development process, including that in small and medium-sized (SME) enterprise. The SME constitutes a major part of the economy and it has been relatively unsuccessful in developing KWP. Accordingly, this paper seeks to explore the influencing dimensions of KWP that effect on the quality of KW in SME environment. First, based on the analysis of the existing literatures, the key characteristics of KW productivity are defined. Second, the conceptual model is proposed, which explores the dimensions of the KWP and its quality. This study analyses data collected from 150 respondents (based on [1], who involve in SME in Malaysia and validates the models by using structural equation modeling (SEM). The results provide an analysis of the effect of KWP on the quality of KW and business success, and have a significant relevance for both research and practice in the SME

Using Data From Ontario's Episode-Based Funding Model to Assess Quality of Chemotherapy.

PubMed

Kaizer, Leonard; Simanovski, Vicky; Lalonde, Carlin; Tariq, Huma; Blais, Irene; Evans, William K

2016-10-01

A new episode-based funding model for ambulatory systemic therapy was implemented in Ontario, Canada on April 1, 2014, after a comprehensive knowledge transfer and exchange strategy with providers and administrators. An analysis of the data from the first year of the new funding model provided an opportunity to assess the quality of chemotherapy, which was not possible under the old funding model. Options for chemotherapy regimens given with adjuvant/curative intent or palliative intent were informed by input from disease site groups. Bundles were developed and priced to enable evidence-informed best practice. Analysis of systemic therapy utilization after model implementation was performed to assess the concordance rate of the treatments chosen with recommended practice. The actual number of cycles of treatment delivered was also compared with expert recommendations. Significant improvement compared with baseline was seen in the proportion of adjuvant/curative regimens that aligned with disease site group-recommended options (98% v 90%). Similar improvement was seen for palliative regimens (94% v 89%). However, overall, the number of cycles of adjuvant/curative therapy delivered was lower than recommended best practice in 57.5% of patients. There was significant variation by disease site and between facilities. Linking funding to quality, supported by knowledge transfer and exchange, resulted in a rapid improvement in the quality of systemic treatment in Ontario. This analysis has also identified further opportunities for improvement and the need for model refinement.

“Skill of Generalized Additive Model to Detect PM2.5 Health Signal in the Presence of Confounding Variables”

EPA Science Inventory

Summary. Measures of health outcomes are collinear with meteorology and air quality, making analysis of connections between human health and air quality difficult. The purpose of this analysis was to determine time scales and periods shared by the variables of interest (and...

Evaluative methodology for comprehensive water quality management planning

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

Dyer, H. L.

Computer-based evaluative methodologies have been developed to provide for the analysis of coupled phenomena associated with natural resource comprehensive planning requirements. Provisions for planner/computer interaction have been included. Each of the simulation models developed is described in terms of its coded procedures. An application of the models for water quality management planning is presented; and the data requirements for each of the models are noted.

Cost-effectiveness analysis of a patient-centered care model for management of psoriasis.

PubMed

Parsi, Kory; Chambers, Cindy J; Armstrong, April W

2012-04-01

Cost-effectiveness analyses help policymakers make informed decisions regarding funding allocation of health care resources. Cost-effectiveness analysis of technology-enabled models of health care delivery is necessary to assess sustainability of novel online, patient-centered health care models. We sought to compare cost-effectiveness of conventional in-office care with a patient-centered, online model for follow-up treatment of patients with psoriasis. Cost-effectiveness analysis was performed from a societal perspective on a randomized controlled trial comparing a patient-centered online model with in-office visits for treatment of patients with psoriasis during a 24-week period. Quality-adjusted life expectancy was calculated using the life table method. Costs were generated from the original study parameters and national averages for salaries and services. No significant difference existed in the mean change in Dermatology Life Quality Index scores between the two groups (online: 3.51 ± 4.48 and in-office: 3.88 ± 6.65, P value = .79). Mean improvement in quality-adjusted life expectancy was not significantly different between the groups (P value = .93), with a gain of 0.447 ± 0.48 quality-adjusted life years for the online group and a gain of 0.463 ± 0.815 quality-adjusted life years for the in-office group. The cost of follow-up psoriasis care with online visits was 1.7 times less than the cost of in-person visits ($315 vs $576). Variations in travel time existed among patients depending on their distance from the dermatologist's office. From a societal perspective, the patient-centered online care model appears to be cost saving, while maintaining similar effectiveness to standard in-office care. Copyright © 2011 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

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.

Analysis of parameter sensitivity and identifiability of root zone water quality model (RZWQM) for dryland sugerbeet modeling

USDA-ARS?s Scientific Manuscript database

Sugarbeet is being considered as one of the most viable feedstock alternatives to corn for biofuel production since herbicide resistant energy beets were deregulated by USDA in 2012. Growing sugarbeets for biofuel production may have significant impacts on soil health and water quality in the north-...

Water quality modeling based on landscape analysis: Importance of riparian hydrology

Treesearch

Thomas Grabs

2010-01-01

Several studies in high-latitude catchments have demonstrated the importance of near-stream riparian zones as hydrogeochemical hotspots with a substantial influence on stream chemistry. An adequate representation of the spatial variability of riparian-zone processes and characteristics is the key for modeling spatiotemporal variations of stream-water quality. This...

Enhancing E-Learning Quality through the Application of the AKUE Procedure Model

ERIC Educational Resources Information Center

Bremer, C.

2012-01-01

The paper describes the procedure model AKUE, which aims at the improvement and assurance of quality and cost efficiency in the context of the introduction of e-learning and the development of digital learning material. AKUE divides the whole planning and implementation process into four different phases: analysis, conception, implementation, and…

Water Quality Assessment Simulation Program (WASP8): Upgrades to the Advanced Toxicant Module for Simulating Dissolved Chemicals, Nanomaterials, and Solids

EPA Science Inventory

The Water Quality Analysis Simulation Program (WASP) is a dynamic, spatially-resolved, differential mass balance fate and transport modeling framework. WASP is used to develop models to simulate concentrations of environmental contaminants in surface waters and sediments. As a mo...

(AMD) ANALYSIS OF AIR QUALITY DATA NEAR ROADWAYS USING A DISPERSION MODEL

EPA Science Inventory

We used a dispersion model to analyze measurements made during a field study conducted by the U.S. EPA in July-August 2006, to estimate the impact of traffic emissions on air quality at distances of tens of meters from an 8 lane highway located in Raleigh, North Carolina. The air...

Colonoscopy video quality assessment using hidden Markov random fields

NASA Astrophysics Data System (ADS)

Park, Sun Young; Sargent, Dusty; Spofford, Inbar; Vosburgh, Kirby

2011-03-01

With colonoscopy becoming a common procedure for individuals aged 50 or more who are at risk of developing colorectal cancer (CRC), colon video data is being accumulated at an ever increasing rate. However, the clinically valuable information contained in these videos is not being maximally exploited to improve patient care and accelerate the development of new screening methods. One of the well-known difficulties in colonoscopy video analysis is the abundance of frames with no diagnostic information. Approximately 40% - 50% of the frames in a colonoscopy video are contaminated by noise, acquisition errors, glare, blur, and uneven illumination. Therefore, filtering out low quality frames containing no diagnostic information can significantly improve the efficiency of colonoscopy video analysis. To address this challenge, we present a quality assessment algorithm to detect and remove low quality, uninformative frames. The goal of our algorithm is to discard low quality frames while retaining all diagnostically relevant information. Our algorithm is based on a hidden Markov model (HMM) in combination with two measures of data quality to filter out uninformative frames. Furthermore, we present a two-level framework based on an embedded hidden Markov model (EHHM) to incorporate the proposed quality assessment algorithm into a complete, automated diagnostic image analysis system for colonoscopy video.

Python tools for rapid development, calibration, and analysis of generalized groundwater-flow models

NASA Astrophysics Data System (ADS)

Starn, J. J.; Belitz, K.

2014-12-01

National-scale water-quality data sets for the United States have been available for several decades; however, groundwater models to interpret these data are available for only a small percentage of the country. Generalized models may be adequate to explain and project groundwater-quality trends at the national scale by using regional scale models (defined as watersheds at or between the HUC-6 and HUC-8 levels). Coast-to-coast data such as the National Hydrologic Dataset Plus (NHD+) make it possible to extract the basic building blocks for a model anywhere in the country. IPython notebooks have been developed to automate the creation of generalized groundwater-flow models from the NHD+. The notebook format allows rapid testing of methods for model creation, calibration, and analysis. Capabilities within the Python ecosystem greatly speed up the development and testing of algorithms. GeoPandas is used for very efficient geospatial processing. Raster processing includes the Geospatial Data Abstraction Library and image processing tools. Model creation is made possible through Flopy, a versatile input and output writer for several MODFLOW-based flow and transport model codes. Interpolation, integration, and map plotting included in the standard Python tool stack also are used, making the notebook a comprehensive platform within on to build and evaluate general models. Models with alternative boundary conditions, number of layers, and cell spacing can be tested against one another and evaluated by using water-quality data. Novel calibration criteria were developed by comparing modeled heads to land-surface and surface-water elevations. Information, such as predicted age distributions, can be extracted from general models and tested for its ability to explain water-quality trends. Groundwater ages then can be correlated with horizontal and vertical hydrologic position, a relation that can be used for statistical assessment of likely groundwater-quality conditions. Convolution with age distributions can be used to quickly ascertain likely future water-quality conditions. Although these models are admittedly very general and are still being tested, the hope is that they will be useful for answering questions related to water quality at the regional scale.

Application of receptor models on water quality data in source apportionment in Kuantan River Basin

PubMed Central

2012-01-01

Recent techniques in the management of surface river water have been expanding the demand on the method that can provide more representative of multivariate data set. A proper technique of the architecture of artificial neural network (ANN) model and multiple linear regression (MLR) provides an advance tool for surface water modeling and forecasting. The development of receptor model was applied in order to determine the major sources of pollutants at Kuantan River Basin, Malaysia. Thirteen water quality parameters were used in principal component analysis (PCA) and new variables of fertilizer waste, surface runoff, anthropogenic input, chemical and mineral changes and erosion are successfully developed for modeling purposes. Two models were compared in terms of efficiency and goodness-of-fit for water quality index (WQI) prediction. The results show that APCS-ANN model gives better performance with high R2 value (0.9680) and small root mean square error (RMSE) value (2.6409) compared to APCS-MLR model. Meanwhile from the sensitivity analysis, fertilizer waste acts as the dominant pollutant contributor (59.82%) to the basin studied followed by anthropogenic input (22.48%), surface runoff (13.42%), erosion (2.33%) and lastly chemical and mineral changes (1.95%). Thus, this study concluded that receptor modeling of APCS-ANN can be used to solve various constraints in environmental problem that exist between water distribution variables toward appropriate water quality management. PMID:23369363

Development of the information model for consumer assessment of key quality indicators by goods labelling

NASA Astrophysics Data System (ADS)

Koshkina, S.; Ostrinskaya, L.

2018-04-01

An information model for “key” quality indicators of goods has been developed. This model is based on the assessment of f standardization existing state and the product labeling quality. According to the authors’ opinion, the proposed “key” indicators are the most significant for purchasing decision making. Customers will be able to use this model through their mobile technical devices. The developed model allows to decompose existing processes in data flows and to reveal the levels of possible architectural solutions. In-depth analysis of the presented information model decomposition levels will allow determining the stages of its improvement and to reveal additional indicators of the goods quality that are of interest to customers in the further research. Examining the architectural solutions for the customer’s information environment functioning when integrating existing databases will allow us to determine the boundaries of the model flexibility and customizability.

Analysis of trends in water-quality data for water conservation area 3A, the Everglades, Florida

USGS Publications Warehouse

Mattraw, H.C.; Scheidt, D.J.; Federico, A.C.

1987-01-01

Rainfall and water quality data bases from the South Florida Water Management District were used to evaluate water quality trends at 10 locations near or in Water Conservation Area 3A in The Everglades. The Seasonal Kendall test was applied to specific conductance, orthophosphate-phosphorus, nitrate-nitrogen, total Kjeldahl nitrogen, and total nitrogen regression residuals for the period 1978-82. Residuals of orthophosphate and nitrate quadratic models, based on antecedent 7-day rainfall at inflow gate S-11B, were the only two constituent-structure pairs that showed apparent significant (p < 0.05) increases in constituent concentrations. Elimination of regression models with distinct residual patterns and data outlines resulted in 17 statistically significant station water quality combinations for trend analysis. No water quality trends were observed. The 1979 Memorandum of Agreement outlining the water quality monitoring program between the Everglades National Park and the U.S. Army Corps of Engineers stressed collection four times a year at three stations, and extensive coverage of water quality properties. Trend analysis and other rigorous statistical evaluation programs are better suited to data monitoring programs that include more frequent sampling and that are organized in a water quality data management system. Pronounced areal differences in water quality suggest that a water quality monitoring system for Shark River Slough in Everglades National Park include collection locations near the source of inflow to Water Conservation Area 3A. (Author 's abstract)

Practice and payment preferences of newly practising family physicians in British Columbia

PubMed Central

Brcic, Vanessa; McGregor, Margaret J.; Kaczorowski, Janusz; Dharamsi, Shafik; Verma, Serena

2012-01-01

Abstract Objective To examine the remuneration model preferences of newly practising family physicians. Design Mixed-methods study comprising a cross-sectional, Web-based survey, as well as qualitative content analysis of answers to open-ended questions. Setting British Columbia. Participants University of British Columbia family practice residents who graduated between 2000 and 2009. Main outcome measures Preferred remuneration models of newly practising physicians. Results The survey response rate was 31% (133 of 430). Of respondents, 71% (93 of 132) preferred non–fee-for-service practice models and 86% (110 of 132) identified the payment model as very or somewhat important in their choice of future practice. Three principal themes were identified from content analysis of respondents’ open-ended comments: frustrations with fee-for-service billing, which encompassed issues related to aggravations with “the business side of things” and was seen as impeding “the freedom to focus on medicine”; quality of patient care, which embraced the importance of a payment model that supported “comprehensive patient care” and “quality rather than quantity”; and freedom to choose, which supported the plurality of practice preferences among providers who strived to provide quality care for patients, “whatever model you happen to be working in.” Conclusion Newly practising physicians in British Columbia preferred alternatives to fee-for-service payment models, which were perceived as contributing to fewer frustrations with billing systems, improved quality of work life, and better quality of patient care. PMID:22586205

An Integrated Modeling Framework Forecasting Ecosystem Exposure-- A Systems Approach to the Cumulative Impacts of Multiple Stressors

NASA Astrophysics Data System (ADS)

Johnston, J. M.

2013-12-01

Freshwater habitats provide fishable, swimmable and drinkable resources and are a nexus of geophysical and biological processes. These processes in turn influence the persistence and sustainability of populations, communities and ecosystems. Climate change and landuse change encompass numerous stressors of potential exposure, including the introduction of toxic contaminants, invasive species, and disease in addition to physical drivers such as temperature and hydrologic regime. A systems approach that includes the scientific and technologic basis of assessing the health of ecosystems is needed to effectively protect human health and the environment. The Integrated Environmental Modeling Framework 'iemWatersheds' has been developed as a consistent and coherent means of forecasting the cumulative impact of co-occurring stressors. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standardization of input data; the Framework for Risk Assessment of Multimedia Environmental Systems (FRAMES) that manages the flow of information between linked models; and the Supercomputer for Model Uncertainty and Sensitivity Evaluation (SuperMUSE) that provides post-processing and analysis of model outputs, including uncertainty and sensitivity analysis. Five models are linked within the Framework to provide multimedia simulation capabilities for hydrology and water quality processes: the Soil Water Assessment Tool (SWAT) predicts surface water and sediment runoff and associated contaminants; the Watershed Mercury Model (WMM) predicts mercury runoff and loading to streams; the Water quality Analysis and Simulation Program (WASP) predicts water quality within the stream channel; the Habitat Suitability Index (HSI) model scores physicochemical habitat quality for individual fish species; and the Bioaccumulation and Aquatic System Simulator (BASS) predicts fish growth, population dynamics and bioaccumulation of toxic substances. The capability of the Framework to address cumulative impacts will be demonstrated for freshwater ecosystem services and mountaintop mining.

Geospatial distribution modeling and determining suitability of groundwater quality for irrigation purpose using geospatial methods and water quality index (WQI) in Northern Ethiopia

NASA Astrophysics Data System (ADS)

Gidey, Amanuel

2018-06-01

Determining suitability and vulnerability of groundwater quality for irrigation use is a key alarm and first aid for careful management of groundwater resources to diminish the impacts on irrigation. This study was conducted to determine the overall suitability of groundwater quality for irrigation use and to generate their spatial distribution maps in Elala catchment, Northern Ethiopia. Thirty-nine groundwater samples were collected to analyze and map the water quality variables. Atomic absorption spectrophotometer, ultraviolet spectrophotometer, titration and calculation methods were used for laboratory groundwater quality analysis. Arc GIS, geospatial analysis tools, semivariogram model types and interpolation methods were used to generate geospatial distribution maps. Twelve and eight water quality variables were used to produce weighted overlay and irrigation water quality index models, respectively. Root-mean-square error, mean square error, absolute square error, mean error, root-mean-square standardized error, measured values versus predicted values were used for cross-validation. The overall weighted overlay model result showed that 146 km2 areas are highly suitable, 135 km2 moderately suitable and 60 km2 area unsuitable for irrigation use. The result of irrigation water quality index confirms 10.26% with no restriction, 23.08% with low restriction, 20.51% with moderate restriction, 15.38% with high restriction and 30.76% with the severe restriction for irrigation use. GIS and irrigation water quality index are better methods for irrigation water resources management to achieve a full yield irrigation production to improve food security and to sustain it for a long period, to avoid the possibility of increasing environmental problems for the future generation.

LAKE DATA ANALYSIS AND NUTRIENT BUDGET MODELING

EPA Science Inventory

Several quantitative methods that may be useful for lake trophic quality management planning are discussed and illustrated. An emphasis is placed on scientific methods in research, data analysis, and modeling. Proper use of statistical methods is also stressed, along with conside...

Course for undergraduate students: analysis of the retinal image quality of a human eye model

NASA Astrophysics Data System (ADS)

del Mar Pérez, Maria; Yebra, Ana; Fernández-Oliveras, Alicia; Ghinea, Razvan; Ionescu, Ana M.; Cardona, Juan C.

2014-07-01

In teaching of Vision Physics or Physiological Optics, the knowledge and analysis of the aberration that the human eye presents are of great interest, since this information allows a proper evaluation of the quality of the retinal image. The objective of the present work is that the students acquire the required competencies which will allow them to evaluate the optical quality of the human visual system for emmetropic and ammetropic eye, both with and without the optical compensation. For this purpose, an optical system corresponding to the Navarro-Escudero eye model, which allows calculating and evaluating the aberration of this eye model in different ammetropic conditions, was developed employing the OSLO LT software. The optical quality of the visual system will be assessed through determinations of the third and fifth order aberration coefficients, the impact diagram, wavefront analysis, calculation of the Point Spread Function and the Modulation Transfer Function for ammetropic individuals, with myopia or hyperopia, both with or without the optical compensation. This course is expected to be of great interest for student of Optics and Optometry Sciences, last courses of Physics or medical sciences related with human vision.

Modeling the ecological trap hypothesis: a habitat and demographic analysis for migrant songbirds

Treesearch

Therese M. Donovan; Frank R, III Thompson

2001-01-01

Most species occupy both high- and low-quality habitats throughout their ranges. As habitats become modified through anthropogenic change, low-quality habitat may become a more dominant component of the landscape for some species. To conserve species, information on how to assess habitat quality and guidelines for maintaining or eliminating low-quality habitats are...

A parsimonious dynamic model for river water quality assessment.

PubMed

Mannina, Giorgio; Viviani, Gaspare

2010-01-01

Water quality modelling is of crucial importance for the assessment of physical, chemical, and biological changes in water bodies. Mathematical approaches to water modelling have become more prevalent over recent years. Different model types ranging from detailed physical models to simplified conceptual models are available. Actually, a possible middle ground between detailed and simplified models may be parsimonious models that represent the simplest approach that fits the application. The appropriate modelling approach depends on the research goal as well as on data available for correct model application. When there is inadequate data, it is mandatory to focus on a simple river water quality model rather than detailed ones. The study presents a parsimonious river water quality model to evaluate the propagation of pollutants in natural rivers. The model is made up of two sub-models: a quantity one and a quality one. The model employs a river schematisation that considers different stretches according to the geometric characteristics and to the gradient of the river bed. Each stretch is represented with a conceptual model of a series of linear channels and reservoirs. The channels determine the delay in the pollution wave and the reservoirs cause its dispersion. To assess the river water quality, the model employs four state variables: DO, BOD, NH(4), and NO. The model was applied to the Savena River (Italy), which is the focus of a European-financed project in which quantity and quality data were gathered. A sensitivity analysis of the model output to the model input or parameters was done based on the Generalised Likelihood Uncertainty Estimation methodology. The results demonstrate the suitability of such a model as a tool for river water quality management.

Development of Innovative Business Model of Modern Manager's Qualities

ERIC Educational Resources Information Center

Yashkova, Elena V.; Sineva, Nadezda L.; Shkunova, Angelika A.; Bystrova, Natalia V.; Smirnova, Zhanna V.; Kolosova, Tatyana V.

2016-01-01

The paper defines a complex of manager's qualities based on theoretical and methodological analysis and synthesis methods, available national and world literature, research papers and publications. The complex approach methodology was used, which provides an innovative view of the development of modern manager's qualities. The methodological…

Statistical Approaches to Interpretation of Local, Regional, and National Highway-Runoff and Urban-Stormwater Data

USGS Publications Warehouse

Tasker, Gary D.; Granato, Gregory E.

2000-01-01

Decision makers need viable methods for the interpretation of local, regional, and national-highway runoff and urban-stormwater data including flows, concentrations and loads of chemical constituents and sediment, potential effects on receiving waters, and the potential effectiveness of various best management practices (BMPs). Valid (useful for intended purposes), current, and technically defensible stormwater-runoff models are needed to interpret data collected in field studies, to support existing highway and urban-runoffplanning processes, to meet National Pollutant Discharge Elimination System (NPDES) requirements, and to provide methods for computation of Total Maximum Daily Loads (TMDLs) systematically and economically. Historically, conceptual, simulation, empirical, and statistical models of varying levels of detail, complexity, and uncertainty have been used to meet various data-quality objectives in the decision-making processes necessary for the planning, design, construction, and maintenance of highways and for other land-use applications. Water-quality simulation models attempt a detailed representation of the physical processes and mechanisms at a given site. Empirical and statistical regional water-quality assessment models provide a more general picture of water quality or changes in water quality over a region. All these modeling techniques share one common aspect-their predictive ability is poor without suitable site-specific data for calibration. To properly apply the correct model, one must understand the classification of variables, the unique characteristics of water-resources data, and the concept of population structure and analysis. Classifying variables being used to analyze data may determine which statistical methods are appropriate for data analysis. An understanding of the characteristics of water-resources data is necessary to evaluate the applicability of different statistical methods, to interpret the results of these techniques, and to use tools and techniques that account for the unique nature of water-resources data sets. Populations of data on stormwater-runoff quantity and quality are often best modeled as logarithmic transformations. Therefore, these factors need to be considered to form valid, current, and technically defensible stormwater-runoff models. Regression analysis is an accepted method for interpretation of water-resources data and for prediction of current or future conditions at sites that fit the input data model. Regression analysis is designed to provide an estimate of the average response of a system as it relates to variation in one or more known variables. To produce valid models, however, regression analysis should include visual analysis of scatterplots, an examination of the regression equation, evaluation of the method design assumptions, and regression diagnostics. A number of statistical techniques are described in the text and in the appendixes to provide information necessary to interpret data by use of appropriate methods. Uncertainty is an important part of any decisionmaking process. In order to deal with uncertainty problems, the analyst needs to know the severity of the statistical uncertainty of the methods used to predict water quality. Statistical models need to be based on information that is meaningful, representative, complete, precise, accurate, and comparable to be deemed valid, up to date, and technically supportable. To assess uncertainty in the analytical tools, the modeling methods, and the underlying data set, all of these components need be documented and communicated in an accessible format within project publications.

Uncertainty estimation of a complex water quality model: The influence of Box-Cox transformation on Bayesian approaches and comparison with a non-Bayesian method

NASA Astrophysics Data System (ADS)

Freni, Gabriele; Mannina, Giorgio

In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised Likelihood Uncertainty Estimation (GLUE). One crucial point in the application of Bayesian method is the formulation of a likelihood function that is conditioned by the hypotheses made regarding model residuals. Statistical transformations, such as the use of Box-Cox equation, are generally used to ensure the homoscedasticity of residuals. However, this practice may affect the reliability of the analysis leading to a wrong uncertainty estimation. The present paper aims to explore the influence of the Box-Cox equation for environmental water quality models. To this end, five cases were considered one of which was the “real” residuals distributions (i.e. drawn from available data). The analysis was applied to the Nocella experimental catchment (Italy) which is an agricultural and semi-urbanised basin where two sewer systems, two wastewater treatment plants and a river reach were monitored during both dry and wet weather periods. The results show that the uncertainty estimation is greatly affected by residual transformation and a wrong assumption may also affect the evaluation of model uncertainty. The use of less formal methods always provide an overestimation of modelling uncertainty with respect to Bayesian method but such effect is reduced if a wrong assumption is made regarding the residuals distribution. If residuals are not normally distributed, the uncertainty is over-estimated if Box-Cox transformation is not applied or non-calibrated parameter is used.

A value-based medicine analysis of ranibizumab for the treatment of subfoveal neovascular macular degeneration.

PubMed

Brown, Melissa M; Brown, Gary C; Brown, Heidi C; Peet, Jonathan

2008-06-01

To assess the conferred value and average cost-utility (cost-effectiveness) for intravitreal ranibizumab used to treat occult/minimally classic subfoveal choroidal neovascularization associated with age-related macular degeneration (AMD). Value-based medicine cost-utility analysis. MARINA (Minimally Classic/Occult Trial of the Anti-Vascular Endothelial Growth Factor Antibody Ranibizumab in the Treatment of Neovascular AMD) Study patients utilizing published primary data. Reference case, third-party insurer perspective, cost-utility analysis using 2006 United States dollars. Conferred value in the forms of (1) quality-adjusted life-years (QALYs) and (2) percent improvement in health-related quality of life. Cost-utility is expressed in terms of dollars expended per QALY gained. All outcomes are discounted at a 3% annual rate, as recommended by the Panel on Cost-effectiveness in Health and Medicine. Data are presented for the second-eye model, first-eye model, and combined model. Twenty-two intravitreal injections of 0.5 mg of ranibizumab administered over a 2-year period confer 1.039 QALYs, or a 15.8% improvement in quality of life for the 12-year period of the second-eye model reference case of occult/minimally classic age-related subfoveal choroidal neovascularization. The reference case treatment cost is $52652, and the cost-utility for the second-eye model is $50691/QALY. The quality-of-life gain from the first-eye model is 6.4% and the cost-utility is $123887, whereas the most clinically simulating combined model yields a quality-of-life gain of 10.4% and cost-utility of $74169. By conventional standards and the most commonly used second-eye and combined models, intravitreal ranibizumab administered for occult/minimally classic subfoveal choroidal neovascularization is a cost-effective therapy. Ranibizumab treatment confers considerably greater value than other neovascular macular degeneration pharmaceutical therapies that have been studied in randomized clinical trials.

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.

Development and case study of a science-based software platform to support policy making on air quality.

PubMed

Zhu, Yun; Lao, Yanwen; Jang, Carey; Lin, Chen-Jen; Xing, Jia; Wang, Shuxiao; Fu, Joshua S; Deng, Shuang; Xie, Junping; Long, Shicheng

2015-01-01

This article describes the development and implementations of a novel software platform that supports real-time, science-based policy making on air quality through a user-friendly interface. The software, RSM-VAT, uses a response surface modeling (RSM) methodology and serves as a visualization and analysis tool (VAT) for three-dimensional air quality data obtained by atmospheric models. The software features a number of powerful and intuitive data visualization functions for illustrating the complex nonlinear relationship between emission reductions and air quality benefits. The case study of contiguous U.S. demonstrates that the enhanced RSM-VAT is capable of reproducing the air quality model results with Normalized Mean Bias <2% and assisting in air quality policy making in near real time. Copyright © 2014. Published by Elsevier B.V.

Panning for the gold in health research: incorporating studies' methodological quality in meta-analysis.

PubMed

Johnson, Blair T; Low, Robert E; MacDonald, Hayley V

2015-01-01

Systematic reviews now routinely assess methodological quality to gauge the validity of the included studies and of the synthesis as a whole. Although trends from higher quality studies should be clearer, it is uncertain how often meta-analyses incorporate methodological quality in models of study results either as predictors, or, more interestingly, in interactions with theoretical moderators. We survey 200 meta-analyses in three health promotion domains to examine when and how meta-analyses incorporate methodological quality. Although methodological quality assessments commonly appear in contemporary meta-analyses (usually as scales), they are rarely incorporated in analyses, and still more rarely analysed in interaction with theoretical determinants of the success of health promotions. The few meta-analyses (2.5%) that did include such an interaction analysis showed that moderator results remained significant in higher quality studies or were present only among higher quality studies. We describe how to model quality interactively with theoretically derived moderators and discuss strengths and weaknesses of this approach and in relation to current meta-analytic practice. In large literatures exhibiting heterogeneous effects, meta-analyses can incorporate methodological quality and generate conclusions that enable greater confidence not only about the substantive phenomenon but also about the role that methodological quality itself plays.

77 FR 21896 - Approval and Promulgation of Air Quality Implementation Plans; State of Nevada; Regional Haze...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-12

... proposed approval, including specific comments on NDEP's modeling and cost analysis of the RGGS BART Determination for NO X . See Modeling for the Reid Gardner Generating Station: Visibility Impacts in Class I... independent modeling analysis to evaluate the incremental visibility improvement attributable to the NO X...

[A measure of the efficiency of primary care in Barcelona (Spain) incorporating quality indicators].

PubMed

Romano, José; Choi, Álvaro

2016-01-01

To demonstrate the impact of the incorporation of quality indicators in assessing the technical efficiency of primary healthcare teams. The processes through which primary healthcare resources have been allocated since the onset of the financial crisis in 2008 have focussed on quantitative rather than qualitative indicators. This study applies data envelopment analysis (DEA) techniques to 58 primary healthcare teams from three different primary healthcare services from the province of Barcelona (Spain). We combine publicly available information from the regional government of Catalonia with data requested from the Catalan Health System Observatory. The analysis compares the results of three models, thereby allowing shifts in the efficiency of primary healthcare teams to be identified in terms of the (lack of) consideration for healthcare quality indicators. Only 16% of the primary healthcare teams were found to be efficient according to the baseline models, which only incorporated input and output quantity indicators. However, once proxies for healthcare quality are included in the analysis, this percentage increases to 58.6%. No meaningful differences in primary healthcare team efficiency were found between public and privately owned centres, between regional primary care services and organisational models, or between rural and urban teams. The results suggest the need to incorporate healthcare quality indicators as outputs when considering criteria for the streamlining of primary healthcare services. Failure to incorporate quality indicators is associated with various primary healthcare concepts. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Application-Driven No-Reference Quality Assessment for Dermoscopy Images With Multiple Distortions.

PubMed

Xie, Fengying; Lu, Yanan; Bovik, Alan C; Jiang, Zhiguo; Meng, Rusong

2016-06-01

Dermoscopy images often suffer from blur and uneven illumination distortions that occur during acquisition, which can adversely influence consequent automatic image analysis results on potential lesion objects. The purpose of this paper is to deploy an algorithm that can automatically assess the quality of dermoscopy images. Such an algorithm could be used to direct image recapture or correction. We describe an application-driven no-reference image quality assessment (IQA) model for dermoscopy images affected by possibly multiple distortions. For this purpose, we created a multiple distortion dataset of dermoscopy images impaired by varying degrees of blur and uneven illumination. The basis of this model is two single distortion IQA metrics that are sensitive to blur and uneven illumination, respectively. The outputs of these two metrics are combined to predict the quality of multiply distorted dermoscopy images using a fuzzy neural network. Unlike traditional IQA algorithms, which use human subjective score as ground truth, here ground truth is driven by the application, and generated according to the degree of influence of the distortions on lesion analysis. The experimental results reveal that the proposed model delivers accurate and stable quality prediction results for dermoscopy images impaired by multiple distortions. The proposed model is effective for quality assessment of multiple distorted dermoscopy images. An application-driven concept for IQA is introduced, and at the same time, a solution framework for the IQA of multiple distortions is proposed.

Developments to the Sylvan stand structure model to describe wood quality changes in southern bottomland hardwood forests because of forest management

Treesearch

Ian R. Scott

2009-01-01

Growth models can produce a wealth of detailed information that is often very difficult to perceive because it is frequently presented either as summary tables, stand view or landscape view visualizations. We have developed new tools for use with the Sylvan model (Larsen 1994) that allow the analysis of wood-quality changes as a consequence of forest management....

Class Model Development Using Business Rules

NASA Astrophysics Data System (ADS)

Skersys, Tomas; Gudas, Saulius

New developments in the area of computer-aided system engineering (CASE) greatly improve processes of the information systems development life cycle (ISDLC). Much effort is put into the quality improvement issues, but IS development projects still suffer from the poor quality of models during the system analysis and design cycles. At some degree, quality of models that are developed using CASE tools can be assured using various. automated. model comparison, syntax. checking procedures. It. is also reasonable to check these models against the business domain knowledge, but the domain knowledge stored in the repository of CASE tool (enterprise model) is insufficient (Gudas et al. 2004). Involvement of business domain experts into these processes is complicated because non- IT people often find it difficult to understand models that were developed by IT professionals using some specific modeling language.

Applying Argumentation Analysis To Assess the Quality of University Oceanography Students' Scientific Writing.

ERIC Educational Resources Information Center

Takao, Allison Y.; Prothero, William A.; Kelly, Gregory J.

2002-01-01

Presents the methods and results of an assessment of students' scientific writing. Studies an introductory oceanography course in a large public university that used an interactive CD-ROM, "Our Dynamic Planet". Analyzes the quality of students' written arguments by using a grading rubric and an argumentation analysis model. Includes 18…

Assessing the Quality of Academic Libraries on the Web: The Development and Testing of Criteria.

ERIC Educational Resources Information Center

Chao, Hungyune

2002-01-01

This study develops and tests an instrument useful for evaluating the quality of academic library Web sites. Discusses criteria for print materials and human-computer interfaces; user-based perspectives; the use of factor analysis; a survey of library experts; testing reliability through analysis of variance; and regression models. (Contains 53…

The Study of an Integrated Rating System for Supplier Quality Performance in the Semiconductor Industry

NASA Astrophysics Data System (ADS)

Lee, Yu-Cheng; Yen, Tieh-Min; Tsai, Chih-Hung

This study provides an integrated model of Supplier Quality Performance Assesment (SQPA) activity for the semiconductor industry through introducing the ISO 9001 management framework, Importance-Performance Analysis (IPA) Supplier Quality Performance Assesment and Taguchi`s Signal-to-Noise Ratio (S/N) techniques. This integrated model provides a SQPA methodology to create value for all members under mutual cooperation and trust in the supply chain. This method helps organizations build a complete SQPA framework, linking organizational objectives and SQPA activities to optimize rating techniques to promote supplier quality improvement. The techniques used in SQPA activities are easily understood. A case involving a design house is illustrated to show our model.

Articulation of Quality Teaching: A Comparative Study

ERIC Educational Resources Information Center

Sakarneh, Mohammad

2015-01-01

The aim of this study is to describe and then contrast the New South Wales Department of Education and Training's model of quality teaching with the Jordanian Ministry of Education's conception of quality teaching, looking particularly at potential differences in interpretation. A content analysis methodology was used. Each perspective has been…

Educational Quality, Outcomes Assessment, and Policy Change: The Virginia Example

ERIC Educational Resources Information Center

Culver, Steve

2010-01-01

The higher education system in the Commonwealth of Virginia in the United States provides a case model for how discussions regarding educational quality and assessment of that quality have affected institutions' policy decisions and implementation. Using Levin's (1998) policy analysis framework, this essay explores how assessment of student…

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...

Air Quality Response Modeling for Decision Support | Science ...

EPA Pesticide Factsheets

Air quality management relies on photochemical models to predict the responses of pollutant concentrations to changes in emissions. Such modeling is especially important for secondary pollutants such as ozone and fine particulate matter which vary nonlinearly with changes in emissions. Numerous techniques for probing pollutant-emission relationships within photochemical models have been developed and deployed for a variety of decision support applications. However, atmospheric response modeling remains complicated by the challenge of validating sensitivity results against observable data. This manuscript reviews the state of the science of atmospheric response modeling as well as efforts to characterize the accuracy and uncertainty of sensitivity results. 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 use

Structural equation model of factors related to quality of life for community-dwelling schizophrenic patients in Japan

PubMed Central

2014-01-01

Background This study aimed to clarify how community mental healthcare systems can be improved. Methods We included 79 schizophrenic patients, aged 20 to 80 years, residing in the Tokyo metropolitan area who regularly visited rehabilitation facilities offering assistance to psychiatric patients and were receiving treatment on an outpatient basis. No subjects had severe cognitive disorders or were taking medication with side effects that could prevent the completion of questionnaires. Questionnaires included items related to quality of life, self-efficacy, self-esteem, psychosis based on the Behavior and Symptom Identification Scale, health locus of control, and socio-demographic factors. We performed multiple linear regression analysis with quality of life as the dependent variable and, based on covariance structural analysis, evaluated the goodness of fit of the resulting structural equations models. Results Self-efficacy, self-esteem, and degree of psychosis significantly impacted quality of life. Marital status, age, and types of medications also influenced quality of life. Multiple linear regression analysis revealed psychiatric symptoms (Behavior and Symptom Identification Scale-32 [daily living and role functioning] (Beta = −0.537, p < 0.001) and self-efficacy (Beta = 0.249, p < 0.05) to be predictors of total quality of life score. Based on covariance structural analysis, the resulting model was found to exhibit reasonable goodness of fit. Conclusions Self-efficacy had an especially strong and direct impact on QOL. Therefore, it is important to provide more positive feedback to patients, provide social skills training based on cognitive behavioral therapy, and engage patients in role playing to improve self-efficacy and self-concept. PMID:25101143

A Review On Accuracy and Uncertainty of Spatial Data and Analyses with special reference to Urban and Hydrological Modelling

NASA Astrophysics Data System (ADS)

Devendran, A. A.; Lakshmanan, G.

2014-11-01

Data quality for GIS processing and analysis is becoming an increased concern due to the accelerated application of GIS technology for problem solving and decision making roles. Uncertainty in the geographic representation of the real world arises as these representations are incomplete. Identification of the sources of these uncertainties and the ways in which they operate in GIS based representations become crucial in any spatial data representation and geospatial analysis applied to any field of application. This paper reviews the articles on the various components of spatial data quality and various uncertainties inherent in them and special focus is paid to two fields of application such as Urban Simulation and Hydrological Modelling. Urban growth is a complicated process involving the spatio-temporal changes of all socio-economic and physical components at different scales. Cellular Automata (CA) model is one of the simulation models, which randomly selects potential cells for urbanisation and the transition rules evaluate the properties of the cell and its neighbour. Uncertainty arising from CA modelling is assessed mainly using sensitivity analysis including Monte Carlo simulation method. Likewise, the importance of hydrological uncertainty analysis has been emphasized in recent years and there is an urgent need to incorporate uncertainty estimation into water resources assessment procedures. The Soil and Water Assessment Tool (SWAT) is a continuous time watershed model to evaluate various impacts of land use management and climate on hydrology and water quality. Hydrological model uncertainties using SWAT model are dealt primarily by Generalized Likelihood Uncertainty Estimation (GLUE) method.

Artificial neural network modeling of the water quality index using land use areas as predictors.

PubMed

Gazzaz, Nabeel M; Yusoff, Mohd Kamil; Ramli, Mohammad Firuz; Juahir, Hafizan; Aris, Ahmad Zaharin

2015-02-01

This paper describes the design of an artificial neural network (ANN) model to predict the water quality index (WQI) using land use areas as predictors. Ten-year records of land use statistics and water quality data for Kinta River (Malaysia) were employed in the modeling process. The most accurate WQI predictions were obtained with the network architecture 7-23-1; the back propagation training algorithm; and a learning rate of 0.02. The WQI forecasts of this model had significant (p < 0.01), positive, very high correlation (ρs = 0.882) with the measured WQI values. Sensitivity analysis revealed that the relative importance of the land use classes to WQI predictions followed the order: mining > rubber > forest > logging > urban areas > agriculture > oil palm. These findings show that the ANNs are highly reliable means of relating water quality to land use, thus integrating land use development with river water quality management.

The Atlanta Urban Heat Island Mitigation and Air Quality Modeling Project: How High-Resoution Remote Sensing Data Can Improve Air Quality Models

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Estes, Maurice G., Jr.; Crosson, William L.; Khan, Maudood N.

2006-01-01

The Atlanta Urban Heat Island and Air Quality Project had its genesis in Project ATLANTA (ATlanta Land use Analysis: Temperature and Air quality) that began in 1996. Project ATLANTA examined how high-spatial resolution thermal remote sensing data could be used to derive better measurements of the Urban Heat Island effect over Atlanta. We have explored how these thermal remote sensing, as well as other imaged datasets, can be used to better characterize the urban landscape for improved air quality modeling over the Atlanta area. For the air quality modeling project, the National Land Cover Dataset and the local scale Landpro99 dataset at 30m spatial resolutions have been used to derive land use/land cover characteristics for input into the MM5 mesoscale meteorological model that is one of the foundations for the Community Multiscale Air Quality (CMAQ) model to assess how these data can improve output from CMAQ. Additionally, land use changes to 2030 have been predicted using a Spatial Growth Model (SGM). SGM simulates growth around a region using population, employment and travel demand forecasts. Air quality modeling simulations were conducted using both current and future land cover. Meteorological modeling simulations indicate a 0.5 C increase in daily maximum air temperatures by 2030. Air quality modeling simulations show substantial differences in relative contributions of individual atmospheric pollutant constituents as a result of land cover change. Enhanced boundary layer mixing over the city tends to offset the increase in ozone concentration expected due to higher surface temperatures as a result of urbanization.

Analysis of flexible aircraft longitudinal dynamics and handling qualities. Volume 1: Analysis methods

NASA Technical Reports Server (NTRS)

Waszak, M. R.; Schmidt, D. S.

1985-01-01

As aircraft become larger and lighter due to design requirements for increased payload and improved fuel efficiency, they will also become more flexible. For highly flexible vehicles, the handling qualities may not be accurately predicted by conventional methods. This study applies two analysis methods to a family of flexible aircraft in order to investigate how and when structural (especially dynamic aeroelastic) effects affect the dynamic characteristics of aircraft. The first type of analysis is an open loop model analysis technique. This method considers the effects of modal residue magnitudes on determining vehicle handling qualities. The second method is a pilot in the loop analysis procedure that considers several closed loop system characteristics. Volume 1 consists of the development and application of the two analysis methods described above.

Validity and reliability of Chinese version of Adult Carer Quality of Life questionnaire (AC-QoL) in family caregivers of stroke survivors

PubMed Central

Li, Yingshuang; Ding, Chunge

2017-01-01

The Adult Carer Quality of Life questionnaire (AC-QoL) is a reliable and valid instrument used to assess the quality of life (QoL) of adult family caregivers. We explored the psychometric properties and tested the reliability and validity of a Chinese version of the AC-QoL with reliability and validity testing in 409 Chinese stroke caregivers. We used item-total correlation and extreme group comparison to do item analysis. To evaluate its reliability, we used a test-retest reliability approach, intraclass correlation coefficient (ICC), together with Cronbach’s alpha and model-based internal consistency index; to evaluate its validity, we used scale content validity, confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) via principal component analysis with varimax rotation. We found that the CFA did not in fact confirm the original factor model and our EFA yielded a 31-item measure with a five-factor model. In conclusions, although some items performed differently in our analysis of the original English language version and our Chinese language version, our translated AC-QoL is a reliable and valid tool which can be used to assess the quality of life of stroke caregivers in mainland China. Chinese version AC-QoL is a comprehensive and good measurement to understand caregivers and has the potential to be a screening tool to assess QoL of caregiver. PMID:29131845

Flight-testing and frequency-domain analysis for rotorcraft handling qualities

NASA Technical Reports Server (NTRS)

Ham, Johnnie A.; Gardner, Charles K.; Tischler, Mark B.

1995-01-01

A demonstration of frequency-domain flight-testing techniques and analysis was performed on a U.S. Army OH-58D helicopter in support of the OH-58D Airworthiness and Flight Characteristics Evaluation and of the Army's development and ongoing review of Aeronautical Design Standard 33C, Handling Qualities Requirements for Military Rotorcraft. Hover and forward flight (60 kn) tests were conducted in 1 flight hour by Army experimental test pilots. Further processing of the hover data generated a complete database of velocity, angular-rate, and acceleration-frequency responses to control inputs. A joint effort was then undertaken by the Airworthiness Qualification Test Dirtectorate and the U.S. Army Aeroflightdynamics Directorate to derive handling-quality information from the frequency-domain database using a variety of approaches. This report documents numerous results that have been obtained from the simple frequency-domain tests; in many areas, these results provide more insight into the aircraft dynmamics that affect handling qualities than do traditional flight tests. The handling-quality results include ADS-33C bandwidth and phase-delay calculations, vibration spectral determinations, transfer-function models to examine single-axis results, and a six-degree-of-freedom fully coupled state-space model. The ability of this model to accurately predict responses was verified using data from pulse inputs. This report also documents the frequency-sweep flight-test technique and data analysis used to support the tests.

Intelligent Systems Approaches to Product Sound Quality Analysis

NASA Astrophysics Data System (ADS)

Pietila, Glenn M.

As a product market becomes more competitive, consumers become more discriminating in the way in which they differentiate between engineered products. The consumer often makes a purchasing decision based on the sound emitted from the product during operation by using the sound to judge quality or annoyance. Therefore, in recent years, many sound quality analysis tools have been developed to evaluate the consumer preference as it relates to a product sound and to quantify this preference based on objective measurements. This understanding can be used to direct a product design process in order to help differentiate the product from competitive products or to establish an impression on consumers regarding a product's quality or robustness. The sound quality process is typically a statistical tool that is used to model subjective preference, or merit score, based on objective measurements, or metrics. In this way, new product developments can be evaluated in an objective manner without the laborious process of gathering a sample population of consumers for subjective studies each time. The most common model used today is the Multiple Linear Regression (MLR), although recently non-linear Artificial Neural Network (ANN) approaches are gaining popularity. This dissertation will review publicly available published literature and present additional intelligent systems approaches that can be used to improve on the current sound quality process. The focus of this work is to address shortcomings in the current paired comparison approach to sound quality analysis. This research will propose a framework for an adaptive jury analysis approach as an alternative to the current Bradley-Terry model. The adaptive jury framework uses statistical hypothesis testing to focus on sound pairings that are most interesting and is expected to address some of the restrictions required by the Bradley-Terry model. It will also provide a more amicable framework for an intelligent systems approach. Next, an unsupervised jury clustering algorithm is used to identify and classify subgroups within a jury who have conflicting preferences. In addition, a nested Artificial Neural Network (ANN) architecture is developed to predict subjective preference based on objective sound quality metrics, in the presence of non-linear preferences. Finally, statistical decomposition and correlation algorithms are reviewed that can help an analyst establish a clear understanding of the variability of the product sounds used as inputs into the jury study and to identify correlations between preference scores and sound quality metrics in the presence of non-linearities.

A Hearing-Based, Frequency Domain Sound Quality Model for Combined Aerodynamic and Power Transmission Response with Application to Rotorcraft Interior Noise

NASA Astrophysics Data System (ADS)

Sondkar, Pravin B.

The severity of combined aerodynamics and power transmission response in high-speed, high power density systems such as a rotorcraft is still a major cause of annoyance in spite of recent advancement in passive, semi-active and active control. With further increase in the capacity and power of this class of machinery systems, the acoustic noise levels are expected to increase even more. To achieve further improvements in sound quality, a more refined understanding of the factors and attributes controlling human perception is needed. In the case of rotorcraft systems, the perceived quality of the interior sound field is a major determining factor of passenger comfort. Traditionally, this sound quality factor is determined by measuring the response of a chosen set of juries who are asked to compare their qualitative reactions to two or more sounds based on their subjective impressions. This type of testing is very time-consuming, costly, often inconsistent, and not useful for practical design purposes. Furthermore, there is no known universal model for sound quality. The primary aim of this research is to achieve significant improvements in quantifying the sound quality of combined aerodynamic and power transmission response in high-speed, high power density machinery systems such as a rotorcraft by applying relevant objective measures related to the spectral characteristics of the sound field. Two models have been proposed in this dissertation research. First, a classical multivariate regression analysis model based on currently known sound quality metrics as well some new metrics derived in this study is presented. Even though the analysis resulted in the best possible multivariate model as a measure of the acoustic noise quality, it lacks incorporation of human judgment mechanism. The regression model can change depending on specific application, nature of the sounds and types of juries used in the study. Also, it predicts only the averaged preference scores and does not explain why two jury members differ in their judgment. To address the above shortcoming of applying regression analysis, a new human judgment model is proposed to further improve the ability to predict the degree of subjective annoyance. The human judgment model involves extraction of subjective attributes and their values using a proposed artificial jury processor. In this approach, a set of ear transfer functions are employed to compute the characteristics of sound pressure waves as perceived subjectively by human. The resulting basilar membrane displacement data from this proposed model is then applied to analyze the attribute values. Using this proposed human judgment model, the human judgment mechanism, which is highly sophisticated, will be examined. Since the human judgment model is essentially based on jury attributes that are not expected to change significantly with application or nature of the sound field, it gives a more common basis to evaluate sound quality. This model also attempts to explain the inter-juror differences in opinion, which is critical in understanding the variability in human response.

Academic Coping, Friendship Quality, and Student Engagement Associated with Student Quality of School Life: A Partial Least Square Analysis

ERIC Educational Resources Information Center

Thien, Lei Mee; Razak, Nordin Abd

2013-01-01

This study aims to examine an untested research model that explains the direct- and indirect influences of Academic Coping, Friendship Quality, and Student Engagement on Student Quality of School Life. This study employed the quantitative-based cross-sectional survey method. The sample consisted of 2400 Malaysian secondary Form Four students…

Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

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

Wang, Feng, E-mail: fwang@unu.edu; Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft; Huisman, Jaco

2013-11-15

Highlights: • A multivariate Input–Output Analysis method for e-waste estimates is proposed. • Applying multivariate analysis to consolidate data can enhance e-waste estimates. • We examine the influence of model selection and data quality on e-waste estimates. • Datasets of all e-waste related variables in a Dutch case study have been provided. • Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lackmore » of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies.« less

The management of patients with T1 adenocarcinoma of the low rectum: a decision analysis.

PubMed

Johnston, Calvin F; Tomlinson, George; Temple, Larissa K; Baxter, Nancy N

2013-04-01

Decision making for patients with T1 adenocarcinoma of the low rectum, when treatment options are limited to a transanal local excision or abdominoperineal resection, is challenging. The aim of this study was to develop a contemporary decision analysis to assist patients and clinicians in balancing the goals of maximizing life expectancy and quality of life in this situation. We constructed a Markov-type microsimulation in open-source software. Recurrence rates and quality-of-life parameters were elicited by systematic literature reviews. Sensitivity analyses were performed on key model parameters. Our base case for analysis was a 65-year-old man with low-lying T1N0 rectal cancer. We determined the sensitivity of our model for sex, age up to 80, and T stage. The main outcome measured was quality-adjusted life-years. In the base case, selecting transanal local excision over abdominoperineal resection resulted in a loss of 0.53 years of life expectancy but a gain of 0.97 quality-adjusted life-years. One-way sensitivity analysis demonstrated a health state utility value threshold for permanent colostomy of 0.93. This value ranged from 0.88 to 1.0 based on tumor recurrence risk. There were no other model sensitivities. Some model parameter estimates were based on weak data. In our model, transanal local excision was found to be the preferable approach for most patients. An abdominoperineal resection has a 3.5% longer life expectancy, but this advantage is lost when the quality-of-life reduction reported by stoma patients is weighed in. The minority group in whom abdominoperineal resection is preferred are those who are unwilling to sacrifice 7% of their life expectancy to avoid a permanent stoma. This is estimated to be approximately 25% of all patients. The threshold increases to 12% of life expectancy in high-risk tumors. No other factors are found to be relevant to the decision.

Model-based quality assessment and base-calling for second-generation sequencing data.

PubMed

Bravo, Héctor Corrada; Irizarry, Rafael A

2010-09-01

Second-generation sequencing (sec-gen) technology can sequence millions of short fragments of DNA in parallel, making it capable of assembling complex genomes for a small fraction of the price and time of previous technologies. In fact, a recently formed international consortium, the 1000 Genomes Project, plans to fully sequence the genomes of approximately 1200 people. The prospect of comparative analysis at the sequence level of a large number of samples across multiple populations may be achieved within the next five years. These data present unprecedented challenges in statistical analysis. For instance, analysis operates on millions of short nucleotide sequences, or reads-strings of A,C,G, or T's, between 30 and 100 characters long-which are the result of complex processing of noisy continuous fluorescence intensity measurements known as base-calling. The complexity of the base-calling discretization process results in reads of widely varying quality within and across sequence samples. This variation in processing quality results in infrequent but systematic errors that we have found to mislead downstream analysis of the discretized sequence read data. For instance, a central goal of the 1000 Genomes Project is to quantify across-sample variation at the single nucleotide level. At this resolution, small error rates in sequencing prove significant, especially for rare variants. Sec-gen sequencing is a relatively new technology for which potential biases and sources of obscuring variation are not yet fully understood. Therefore, modeling and quantifying the uncertainty inherent in the generation of sequence reads is of utmost importance. In this article, we present a simple model to capture uncertainty arising in the base-calling procedure of the Illumina/Solexa GA platform. Model parameters have a straightforward interpretation in terms of the chemistry of base-calling allowing for informative and easily interpretable metrics that capture the variability in sequencing quality. Our model provides these informative estimates readily usable in quality assessment tools while significantly improving base-calling performance. © 2009, The International Biometric Society.

The Impact of Long-Term Climate Change on Nitrogen Runoff at the Watershed Scale.

NASA Astrophysics Data System (ADS)

Dorley, J.; Duffy, C.; Arenas Amado, A.

2017-12-01

The impact of agricultural runoff is a major concern for water quality of mid-western streams. This concern is largely due to excessive use of agricultural fertilizer, a major source of nutrients in many Midwestern watersheds. In order to improve water quality in these watersheds, understanding the long-term trends in nutrient concentration and discharge is an important water quality problem. This study attempts to analyze the role of long-term temperature and precipitation on nitrate runoff in an agriculturally dominated watershed in Iowa. The approach attempts to establish the concentration-discharge (C-Q) signature for the watershed using time series analysis, frequency analysis and model simulation. The climate data is from the Intergovernmental Panel on Climate Change (IPCC), model GFDL-CM3 (Geophysical Fluid Dynamic Laboratory Coupled Model 3). The historical water quality data was made available by the IIHR-Hydroscience & Engineering at the University of Iowa for the clear creek watershed (CCW). The CCW is located in east-central Iowa. The CCW is representative of many Midwestern watersheds with humid-continental climate with predominantly agricultural land use. The study shows how long-term climate changes in temperature and precipitation affects the C-Q dynamics and how a relatively simple approach to data analysis and model projections can be applied to best management practices at the site.

AQMEII3 evaluation of regional NA/EU simulations and ...

EPA Pesticide Factsheets

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) helping to detect causes of models error, and iii) identifying the processes and scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance and covariance) can help to 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 former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impac

Repeatability analysis of the K. J. Law Model 8300 Roughness Surveyor : final report.

DOT National Transportation Integrated Search

1991-04-01

The K.J. Law Model 8300 Roughness surveyor, is a ride-quality measurement device used to determine and analyze the longitudinal roadway profile. This paper describes an analysis of IRI data as collected with Louisiana's Roughness Surveyor to determin...

Integrated thermal disturbance analysis of optical system of astronomical telescope

NASA Astrophysics Data System (ADS)

Yang, Dehua; Jiang, Zibo; Li, Xinnan

2008-07-01

During operation, astronomical telescope will undergo thermal disturbance, especially more serious in solar telescope, which may cause degradation of image quality. As drives careful thermal load investigation and measure applied to assess its effect on final image quality during design phase. Integrated modeling analysis is boosting the process to find comprehensive optimum design scheme by software simulation. In this paper, we focus on the Finite Element Analysis (FEA) software-ANSYS-for thermal disturbance analysis and the optical design software-ZEMAX-for optical system design. The integrated model based on ANSYS and ZEMAX is briefed in the first from an overview of point. Afterwards, we discuss the establishment of thermal model. Complete power series polynomial with spatial coordinates is introduced to present temperature field analytically. We also borrow linear interpolation technique derived from shape function in finite element theory to interface the thermal model and structural model and further to apply the temperatures onto structural model nodes. Thereby, the thermal loads are transferred with as high fidelity as possible. Data interface and communication between the two softwares are discussed mainly on mirror surfaces and hence on the optical figure representation and transformation. We compare and comment the two different methods, Zernike polynomials and power series expansion, for representing and transforming deformed optical surface to ZEMAX. Additionally, these methods applied to surface with non-circular aperture are discussed. At the end, an optical telescope with parabolic primary mirror of 900 mm in diameter is analyzed to illustrate the above discussion. Finite Element Model with most interested parts of the telescope is generated in ANSYS with necessary structural simplification and equivalence. Thermal analysis is performed and the resulted positions and figures of the optics are to be retrieved and transferred to ZEMAX, and thus final image quality is evaluated with thermal disturbance.

Urban Stormwater Management Model and Tools for Designing Stormwater Management of Green Infrastructure Practices

NASA Astrophysics Data System (ADS)

Haris, H.; Chow, M. F.; Usman, F.; Sidek, L. M.; Roseli, Z. A.; Norlida, M. D.

2016-03-01

Urbanization is growing rapidly in Malaysia. Rapid urbanization has known to have several negative impacts towards hydrological cycle due to decreasing of pervious area and deterioration of water quality in stormwater runoff. One of the negative impacts of urbanization is the congestion of the stormwater drainage system and this situation leading to flash flood problem and water quality degradation. There are many urban stormwater management softwares available in the market such as Storm Water Drainage System design and analysis program (DRAINS), Urban Drainage and Sewer Model (MOUSE), InfoWorks River Simulation (InfoWork RS), Hydrological Simulation Program-Fortran (HSPF), Distributed Routing Rainfall-Runoff Model (DR3M), Storm Water Management Model (SWMM), XP Storm Water Management Model (XPSWMM), MIKE-SWMM, Quality-Quantity Simulators (QQS), Storage, Treatment, Overflow, Runoff Model (STORM), and Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS). In this paper, we are going to discuss briefly about several softwares and their functionality, accessibility, characteristics and components in the quantity analysis of the hydrological design software and compare it with MSMA Design Aid and Database. Green Infrastructure (GI) is one of the main topics that has widely been discussed all over the world. Every development in the urban area is related to GI. GI can be defined as green area build in the develop area such as forest, park, wetland or floodway. The role of GI is to improve life standard such as water filtration or flood control. Among the twenty models that have been compared to MSMA SME, ten models were selected to conduct a comprehensive review for this study. These are known to be widely accepted by water resource researchers. These ten tools are further classified into three major categories as models that address the stormwater management ability of GI in terms of quantity and quality, models that have the capability of conducting the economic analysis of GI and models that can address both stormwater management and economic aspects together.

Study of mechanism improving target course traceability in G-Vectoring Control

NASA Astrophysics Data System (ADS)

Yamakado, Makoto; Abe, Masato; Kano, Yoshio; Umetsu, Daisuke; Yoshioka, Thoru

2018-05-01

Production-type G-Vectoring Control vehicles are now being put on the market. Customers and reviewers have praised the handling quality and course traceability of these vehicles. This paper clarifies the mechanism behind this improvement in handling quality using a simple bicycle model and driver model analysis. It focuses on the residual yaw angular acceleration when the steering speed is zero and shows that GVC reduces its value. This result provides evidence for improved handling quality in GVC vehicles.

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.

Water Quality Variable Estimation using Partial Least Squares Regression and Multi-Scale Remote Sensing.

NASA Astrophysics Data System (ADS)

Peterson, K. T.; Wulamu, A.

2017-12-01

Water, essential to all living organisms, is one of the Earth's most precious resources. Remote sensing offers an ideal approach to monitor water quality over traditional in-situ techniques that are highly time and resource consuming. Utilizing a multi-scale approach, incorporating data from handheld spectroscopy, UAS based hyperspectal, and satellite multispectral images were collected in coordination with in-situ water quality samples for the two midwestern watersheds. The remote sensing data was modeled and correlated to the in-situ water quality variables including chlorophyll content (Chl), turbidity, and total dissolved solids (TDS) using Normalized Difference Spectral Indices (NDSI) and Partial Least Squares Regression (PLSR). The results of the study supported the original hypothesis that correlating water quality variables with remotely sensed data benefits greatly from the use of more complex modeling and regression techniques such as PLSR. The final results generated from the PLSR analysis resulted in much higher R2 values for all variables when compared to NDSI. The combination of NDSI and PLSR analysis also identified key wavelengths for identification that aligned with previous study's findings. This research displays the advantages and future for complex modeling and machine learning techniques to improve water quality variable estimation from spectral data.

Transparent Reporting of Data Quality in Distributed Data Networks

PubMed Central

Kahn, Michael G.; Brown, Jeffrey S.; Chun, Alein T.; Davidson, Bruce N.; Meeker, Daniella; Ryan, Patrick B.; Schilling, Lisa M.; Weiskopf, Nicole G.; Williams, Andrew E.; Zozus, Meredith Nahm

2015-01-01

Introduction: Poor data quality can be a serious threat to the validity and generalizability of clinical research findings. The growing availability of electronic administrative and clinical data is accompanied by a growing concern about the quality of these data for observational research and other analytic purposes. Currently, there are no widely accepted guidelines for reporting quality results that would enable investigators and consumers to independently determine if a data source is fit for use to support analytic inferences and reliable evidence generation. Model and Methods: We developed a conceptual model that captures the flow of data from data originator across successive data stewards and finally to the data consumer. This “data lifecycle” model illustrates how data quality issues can result in data being returned back to previous data custodians. We highlight the potential risks of poor data quality on clinical practice and research results. Because of the need to ensure transparent reporting of a data quality issues, we created a unifying data-quality reporting framework and a complementary set of 20 data-quality reporting recommendations for studies that use observational clinical and administrative data for secondary data analysis. We obtained stakeholder input on the perceived value of each recommendation by soliciting public comments via two face-to-face meetings of informatics and comparative-effectiveness investigators, through multiple public webinars targeted to the health services research community, and with an open access online wiki. Recommendations: Our recommendations propose reporting on both general and analysis-specific data quality features. The goals of these recommendations are to improve the reporting of data quality measures for studies that use observational clinical and administrative data, to ensure transparency and consistency in computing data quality measures, and to facilitate best practices and trust in the new clinical discoveries based on secondary use of observational data. PMID:25992385

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

Evaluation of outpatient service quality in Eastern Saudi Arabia

PubMed Central

Fraihi, Khalid J. Al; FAMCO, Dip; FAMCO, Fellow; Latif, Shahid A.

2016-01-01

Objectives: To investigate perceptions and expectations of patients regarding hospital outpatient services by using a service quality gap model and factors influencing such gaps. Methods: In this cross-sectional descriptive study conducted between October and November 2014 in the outpatient waiting areas of a hospital in the Eastern Province of Saudi Arabia, a sample of 306 patients was selected by convenience sampling technique. The data was collected through an Arabic version of the service quality (SERVQUAL) questionnaire consisting of 2 parts: patients’ demographic characteristics, and 22 items scales of patients’ expectations and perceptions of SERVQUAL. The data was analyzed by confirmatory factor analysis, independent, and paired t samples tests and one way analysis of variance test. Results: The results showed that the proposed model for service quality dimensions had a good fit by satisfying the recommended values. The patients’ expectations exceeded perceptions in all service quality dimensions indicating statistically significant service quality gaps (t=26.3, p<0.000). Findings revealed that the empathy dimension contributed most patients’ expectations (4.7 ± 0.5) and perceptions (3.7 ± 0.8) scores, and responsiveness contributed least to expectations (4.5 ± 0.6) and perceptions (3.2 ± 0.8) scores. Prompt services showed highest service quality gap, while observation of privacy showed the smallest service quality gap in the statements. The study showed a significant association between gender, age, education, multiple visits, and service quality dimensions. Conclusion: The proposed model is valid and reliable and significant service quality gaps of all 5 dimensions need to be prioritized and addressed by focused improvement efforts of hospital management. PMID:27052285

Evaluation of outpatient service quality in Eastern Saudi Arabia. Patient's expectations and perceptions.

PubMed

Al Fraihi, Khalid J; Latif, Shahid A

2016-04-01

To investigate perceptions and expectations of patients regarding hospital outpatient services by using a service quality gap model and factors influencing such gaps. In this cross-sectional descriptive study conducted between October and November 2014 in the outpatient waiting areas of a hospital in the Eastern Province of Saudi Arabia, a sample of 306 patients was selected by convenience sampling technique. The data was collected through an Arabic version of the service quality (SERVQUAL) questionnaire consisting of 2 parts: patients' demographic characteristics, and 22 items scales of patients' expectations and perceptions of SERVQUAL. The data was analyzed by confirmatory factor analysis, independent, and paired t samples tests and one way analysis of variance test The results showed that the proposed model for service quality dimensions had a good fit by satisfying the recommended values. The patients' expectations exceeded perceptions in all service quality dimensions indicating statistically significant service quality gaps (t=26.3, p less than 0.000). Findings revealed that the empathy dimension contributed most patients' expectations (4.7 ± 0.5) and perceptions (3.7 ± 0.8) scores, and responsiveness contributed least to expectations (4.5 ± 0.6) and perceptions (3.2 ± 0.8) scores. Prompt services showed highest service quality gap, while observation of privacy showed the smallest service quality gap in the statements. The study showed a significant association between gender, age, education, multiple visits, and service quality dimensions. The proposed model is valid and reliable and significant service quality gaps of all 5 dimensions need to be prioritized and addressed by focused improvement efforts of hospital management.

Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Kong, Shish-Jeng; Chang, Chih-Hua

2018-03-01

The turbidity (TB) of a water body varies with time and space. Water quality is traditionally estimated via linear regression based on satellite images. However, estimating and mapping water quality require a spatio-temporal nonstationary model, while TB mapping necessitates the use of geographically and temporally weighted regression (GTWR) and geographically weighted regression (GWR) models, both of which are more precise than linear regression. Given the temporal nonstationary models for mapping water quality, GTWR offers the best option for estimating regional water quality. Compared with GWR, GTWR provides highly reliable information for water quality mapping, boasts a relatively high goodness of fit, improves the explanation of variance from 44% to 87%, and shows a sufficient space-time explanatory power. The seasonal patterns of TB and the main spatial patterns of TB variability can be identified using the estimated TB maps from GTWR and by conducting an empirical orthogonal function (EOF) analysis.

Use of ocean color scanner data in water quality mapping

NASA Technical Reports Server (NTRS)

Khorram, S.

1981-01-01

Remotely sensed data, in combination with in situ data, are used in assessing water quality parameters within the San Francisco Bay-Delta. The parameters include suspended solids, chlorophyll, and turbidity. Regression models are developed between each of the water quality parameter measurements and the Ocean Color Scanner (OCS) data. The models are then extended to the entire study area for mapping water quality parameters. The results include a series of color-coded maps, each pertaining to one of the water quality parameters, and the statistical analysis of the OCS data and regression models. It is found that concurrently collected OCS data and surface truth measurements are highly useful in mapping the selected water quality parameters and locating areas having relatively high biological activity. In addition, it is found to be virtually impossible, at least within this test site, to locate such areas on U-2 color and color-infrared photography.

An evaluation method of power quality about electrified railways connected to power grid based on PSCAD/EMTDC

NASA Astrophysics Data System (ADS)

Liang, Weibin; Ouyang, Sen; Huang, Xiang; Su, Weijian

2017-05-01

The existing modeling process of power quality about electrified railways connected to power grid is complicated and the simulation scene is incomplete, so this paper puts forward a novel evaluation method of power quality based on PSCAD/ETMDC. Firstly, a model of power quality about electrified railways connected to power grid is established, which is based on testing report or measured data. The equivalent model of electrified locomotive contains power characteristic and harmonic characteristic, which are substituted by load and harmonic source. Secondly, in order to make evaluation more complete, an analysis scheme has been put forward. The scheme uses a combination of three-dimensions of electrified locomotive, which contains types, working conditions and quantity. At last, Shenmao Railway is taken as example to evaluate the power quality at different scenes, and the result shows electrified railways connected to power grid have significant effect on power quality.

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.

The relationship between quality management practices and organisational performance: A structural equation modelling approach

NASA Astrophysics Data System (ADS)

Jamaluddin, Z.; Razali, A. M.; Mustafa, Z.

2015-02-01

The purpose of this paper is to examine the relationship between the quality management practices (QMPs) and organisational performance for the manufacturing industry in Malaysia. In this study, a QMPs and organisational performance framework is developed according to a comprehensive literature review which cover aspects of hard and soft quality factors in manufacturing process environment. A total of 11 hypotheses have been put forward to test the relationship amongst the six constructs, which are management commitment, training, process management, quality tools, continuous improvement and organisational performance. The model is analysed using Structural Equation Modeling (SEM) with AMOS software version 18.0 using Maximum Likelihood (ML) estimation. A total of 480 questionnaires were distributed, and 210 questionnaires were valid for analysis. The results of the modeling analysis using ML estimation indicate that the fits statistics of QMPs and organisational performance model for manufacturing industry is admissible. From the results, it found that the management commitment have significant impact on the training and process management. Similarly, the training had significant effect to the quality tools, process management and continuous improvement. Furthermore, the quality tools have significant influence on the process management and continuous improvement. Likewise, the process management also has a significant impact to the continuous improvement. In addition the continuous improvement has significant influence the organisational performance. However, the results of the study also found that there is no significant relationship between management commitment and quality tools, and between the management commitment and continuous improvement. The results of the study can be used by managers to prioritize the implementation of QMPs. For instances, those practices that are found to have positive impact on organisational performance can be recommended to managers so that they can allocate resources to improve these practices to get better performance.

Mathematical 3D modelling and sensitivity analysis of multipolar radiofrequency ablation in the spine.

PubMed

Matschek, Janine; Bullinger, Eric; von Haeseler, Friedrich; Skalej, Martin; Findeisen, Rolf

2017-02-01

Radiofrequency ablation is a valuable tool in the treatment of many diseases, especially cancer. However, controlled heating up to apoptosis of the desired target tissue in complex situations, e.g. in the spine, is challenging and requires experienced interventionalists. For such challenging situations a mathematical model of radiofrequency ablation allows to understand, improve and optimise the outcome of the medical therapy. The main contribution of this work is the derivation of a tailored, yet expandable mathematical model, for the simulation, analysis, planning and control of radiofrequency ablation in complex situations. The dynamic model consists of partial differential equations that describe the potential and temperature distribution during intervention. To account for multipolar operation, time-dependent boundary conditions are introduced. Spatially distributed parameters, like tissue conductivity and blood perfusion, allow to describe the complex 3D environment representing diverse involved tissue types in the spine. To identify the key parameters affecting the prediction quality of the model, the influence of the parameters on the temperature distribution is investigated via a sensitivity analysis. Simulations underpin the quality of the derived model and the analysis approach. The proposed modelling and analysis schemes set the basis for intervention planning, state- and parameter estimation, and control. Copyright © 2016. Published by Elsevier Inc.

The response of numerical weather prediction analysis systems to FGGE 2b data

NASA Technical Reports Server (NTRS)

Hollingsworth, A.; Lorenc, A.; Tracton, S.; Arpe, K.; Cats, G.; Uppala, S.; Kallberg, P.

1985-01-01

An intercomparison of analyses of the main PGGE Level IIb data set is presented with three advanced analysis systems. The aims of the work are to estimate the extent and magnitude of the differences between the analyses, to identify the reasons for the differences, and finally to estimate the significance of the differences. Extratropical analyses only are considered. Objective evaluations of analysis quality, such as fit to observations, statistics of analysis differences, and mean fields are discussed. In addition, substantial emphasis is placed on subjective evaluation of a series of case studies that were selected to illustrate the importance of different aspects of the analysis procedures, such as quality control, data selection, resolution, dynamical balance, and the role of the assimilating forecast model. In some cases, the forecast models are used as selective amplifiers of analysis differences to assist in deciding which analysis was more nearly correct in the treatment of particular 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.

Analysis and optimization of dynamic model of eccentric shaft grinder

NASA Astrophysics Data System (ADS)

Gao, Yangjie; Han, Qiushi; Li, Qiguang; Peng, Baoying

2018-04-01

Eccentric shaft servo grinder is the core equipment in the process chain of machining eccentric shaft. The establishment of the movement model and the determination of the kinematic relation of the-axis in the grinding process directly affect the quality of the grinding process, and there are many error factors in grinding, and it is very important to analyze the influence of these factors on the work piece quality. The three-dimensional model of eccentric shaft grinder is drawn by Pro/E three-dimensional drawing software, the model is imported into ANSYS Workbench Finite element analysis software, and the finite element analysis is carried out, and then the variation and parameters of each component of the bed are obtained by the modal analysis result. The natural frequencies and formations of the first six steps of the eccentric shaft grinder are obtained by modal analysis, and the weak links of the parts of the grinder are found out, and a reference improvement method is proposed for the design of the eccentric shaft grinder in the future.

Analysis of various quality attributes of sunflower and soybean plants by near infra-red reflectance spectroscopy: Development and validation calibration models

USDA-ARS?s Scientific Manuscript database

Sunflower and soybean are summer annuals that can be grown as an alternative to corn and may be particularly useful in organic production systems. Rapid and low cost methods of analyzing plant quality would be helpful for crop management. We developed and validated calibration models for Near-infrar...

A Social Operational Model of Urban Adolescents' Tobacco and Substance Use: A Mediational Analysis

ERIC Educational Resources Information Center

Mason, Michael J.; Mennis, Jeremy; Schmidt, Christopher D.

2011-01-01

This study tested a mediation model of the relationship with tobacco use, social network quality (level of risk or protection in a network), and substance use (alcohol and/or illicit drugs) with a sample of 301 urban adolescents. It was theorized that social network quality would mediate the effect of tobacco use, accounting for PTSD symptoms and…

A model of service quality perceptions and health care consumer behavior.

PubMed

O'Connor, S J; Shewchuk, R M; Bowers, M R

1991-01-01

Analysis of covariance structures (LISREL) was used to examine the influence of consumer held perceptions of service quality on consumer satisfaction and intentions to return. Results indicate that service quality is a significant predictor of consumer satisfaction which, in turn, predicts intention to return. Health care marketing implications are discussed.

Pasta production: complexity in defining processing conditions for reference trials and quality assessment models

USDA-ARS?s Scientific Manuscript database

Pasta is a simple food made from water and durum wheat (Triticum turgidum subsp. durum) semolina. As pasta increases in popularity, studies have endeavored to analyze the attributes that contribute to high quality pasta. Despite being a simple food, the laboratory scale analysis of pasta quality is ...

Statistical Analysis of Regional Surface Water Quality in Southeastern Ontario.

ERIC Educational Resources Information Center

Bodo, Byron A.

1992-01-01

Historical records from Ontario's Provincial Water Quality Monitoring Network for rivers and streams were analyzed to assess the feasibility of mapping regional water quality patterns in southeastern Ontario, spanning the Precambrian Shield and the St. Lawrence Lowlands. The study served as a model for much of Ontario. (54 references) (Author/MDH)

A Strategic Quality Assurance Framework in an African Higher Education Context

ERIC Educational Resources Information Center

Ansah, Francis

2015-01-01

This study is based on a pragmatist analysis of selected international accounts on quality assurance in higher education. A pragmatist perspective was used to conceptualise a logical internal quality assurance model to embed and support the alignment of graduate competencies in curriculum and assessment of Ghanaian polytechnics. Through focus…

Early experiences building a software quality prediction model

NASA Technical Reports Server (NTRS)

Agresti, W. W.; Evanco, W. M.; Smith, M. C.

1990-01-01

Early experiences building a software quality prediction model are discussed. The overall research objective is to establish a capability to project a software system's quality from an analysis of its design. The technical approach is to build multivariate models for estimating reliability and maintainability. Data from 21 Ada subsystems were analyzed to test hypotheses about various design structures leading to failure-prone or unmaintainable systems. Current design variables highlight the interconnectivity and visibility of compilation units. Other model variables provide for the effects of reusability and software changes. Reported results are preliminary because additional project data is being obtained and new hypotheses are being developed and tested. Current multivariate regression models are encouraging, explaining 60 to 80 percent of the variation in error density of the subsystems.

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.

Analyzing the quality robustness of chemotherapy plans with respect to model uncertainties.

PubMed

Hoffmann, Anna; Scherrer, Alexander; Küfer, Karl-Heinz

2015-01-01

Mathematical models of chemotherapy planning problems contain various biomedical parameters, whose values are difficult to quantify and thus subject to some uncertainty. This uncertainty propagates into the therapy plans computed on these models, which poses the question of robustness to the expected therapy quality. This work introduces a combined approach for analyzing the quality robustness of plans in terms of dosing levels with respect to model uncertainties in chemotherapy planning. It uses concepts from multi-criteria decision making for studying parameters related to the balancing between the different therapy goals, and concepts from sensitivity analysis for the examination of parameters describing the underlying biomedical processes and their interplay. This approach allows for a profound assessment of a therapy plan, how stable its quality is with respect to parametric changes in the used mathematical model. Copyright © 2014 Elsevier Inc. All rights reserved.

Reduced-form air quality modeling for community-scale ...

EPA Pesticide Factsheets

Transportation plays an important role in modern society, but its impact on air quality has been shown to have significant adverse effects on public health. Numerous reviews (HEI, CDC, WHO) summarizing findings of hundreds of studies conducted mainly in the last decade, conclude that exposures to traffic emissions near roads are a public health concern. The Community LINE Source Model (C-LINE) is a web-based model designed to inform the community user of local air quality impacts due to roadway vehicles in their region of interest using a simplified modeling approach. Reduced-form air quality modeling is a useful tool for examining what-if scenarios of changes in emissions, such as those due to changes in traffic volume, fleet mix, or vehicle speed. Examining various scenarios of air quality impacts in this way can identify potentially at-risk populations located near roadways, and the effects that a change in traffic activity may have on them. C-LINE computes dispersion of primary mobile source pollutants using meteorological conditions for the region of interest and computes air-quality concentrations corresponding to these selected conditions. C-LINE functionality has been expanded to model emissions from port-related activities (e.g. ships, trucks, cranes, etc.) in a reduced-form modeling system for local-scale near-port air quality analysis. This presentation describes the Community modeling tools C-LINE and C-PORT that are intended to be used by local gove

Quality Analysis of Open Street Map Data

NASA Astrophysics Data System (ADS)

Wang, M.; Li, Q.; Hu, Q.; Zhou, M.

2013-05-01

Crowd sourcing geographic data is an opensource geographic data which is contributed by lots of non-professionals and provided to the public. The typical crowd sourcing geographic data contains GPS track data like OpenStreetMap, collaborative map data like Wikimapia, social websites like Twitter and Facebook, POI signed by Jiepang user and so on. These data will provide canonical geographic information for pubic after treatment. As compared with conventional geographic data collection and update method, the crowd sourcing geographic data from the non-professional has characteristics or advantages of large data volume, high currency, abundance information and low cost and becomes a research hotspot of international geographic information science in the recent years. Large volume crowd sourcing geographic data with high currency provides a new solution for geospatial database updating while it need to solve the quality problem of crowd sourcing geographic data obtained from the non-professionals. In this paper, a quality analysis model for OpenStreetMap crowd sourcing geographic data is proposed. Firstly, a quality analysis framework is designed based on data characteristic analysis of OSM data. Secondly, a quality assessment model for OSM data by three different quality elements: completeness, thematic accuracy and positional accuracy is presented. Finally, take the OSM data of Wuhan for instance, the paper analyses and assesses the quality of OSM data with 2011 version of navigation map for reference. The result shows that the high-level roads and urban traffic network of OSM data has a high positional accuracy and completeness so that these OSM data can be used for updating of urban road network database.

Relationship between Internal Quality Audit and Quality Culture toward Implementation Consistency of ISO 9000 in Private College of Sulawesi Province, Indonesia

ERIC Educational Resources Information Center

Mail, Abdul; Pratikto; Suparman, Sudjito; Purnomo; Santoso, Budi

2014-01-01

The study aims to find out the influence of internal quality process on the growth of quality culture in private college. This study is treated toward 178 lecturers of 25 private colleges in Sulawesi, Indonesia by means of questionnaire. Confirmatory factor analysis applied to assess the reliability of validity and measurement model. Relationship…

Improved first-order uncertainty method for water-quality modeling

USGS Publications Warehouse

Melching, C.S.; Anmangandla, S.

1992-01-01

Uncertainties are unavoidable in water-quality modeling and subsequent management decisions. Monte Carlo simulation and first-order uncertainty analysis (involving linearization at central values of the uncertain variables) have been frequently used to estimate probability distributions for water-quality model output due to their simplicity. Each method has its drawbacks: Monte Carlo simulation's is mainly computational time; and first-order analysis are mainly questions of accuracy and representativeness, especially for nonlinear systems and extreme conditions. An improved (advanced) first-order method is presented, where the linearization point varies to match the output level whose exceedance probability is sought. The advanced first-order method is tested on the Streeter-Phelps equation to estimate the probability distribution of critical dissolved-oxygen deficit and critical dissolved oxygen using two hypothetical examples from the literature. The advanced first-order method provides a close approximation of the exceedance probability for the Streeter-Phelps model output estimated by Monte Carlo simulation using less computer time - by two orders of magnitude - regardless of the probability distributions assumed for the uncertain model parameters.

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

USGS Publications Warehouse

Zajac, Zuzanna; Stith, Bradley M.; Bowling, Andrea C.; Langtimm, Catherine A.; Swain, Eric D.

2015-01-01

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust decisions.

A Review and Analysis of Remote Sensing Capability for Air Quality Measurements as a Potential Decision Support Tool Conducted by the NASA DEVELOP Program

NASA Technical Reports Server (NTRS)

Ross, A.; Richards, A.; Keith, K.; Frew, C.; Boseck, J.; Sutton, S.; Watts, C.; Rickman, D.

2007-01-01

This project focused on a comprehensive utilization of air quality model products as decision support tools (DST) needed for public health applications. A review of past and future air quality measurement methods and their uncertainty, along with the relationship of air quality to national and global public health, is vital. This project described current and future NASA satellite remote sensing and ground sensing capabilities and the potential for using these sensors to enhance the prediction, prevention, and control of public health effects that result from poor air quality. The qualitative uncertainty of current satellite remotely sensed air quality, the ground-based remotely sensed air quality, the air quality/public health model, and the decision making process is evaluated in this study. Current peer-reviewed literature suggests that remotely sensed air quality parameters correlate well with ground-based sensor data. A satellite remote-sensed and ground-sensed data complement is needed to enhance the models/tools used by policy makers for the protection of national and global public health communities

Trabecular bone analysis in CT and X-ray images of the proximal femur for the assessment of local bone quality.

PubMed

Fritscher, Karl; Grunerbl, Agnes; Hanni, Markus; Suhm, Norbert; Hengg, Clemens; Schubert, Rainer

2009-10-01

Currently, conventional X-ray and CT images as well as invasive methods performed during the surgical intervention are used to judge the local quality of a fractured proximal femur. However, these approaches are either dependent on the surgeon's experience or cannot assist diagnostic and planning tasks preoperatively. Therefore, in this work a method for the individual analysis of local bone quality in the proximal femur based on model-based analysis of CT- and X-ray images of femur specimen will be proposed. A combined representation of shape and spatial intensity distribution of an object and different statistical approaches for dimensionality reduction are used to create a statistical appearance model in order to assess the local bone quality in CT and X-ray images. The developed algorithms are tested and evaluated on 28 femur specimen. It will be shown that the tools and algorithms presented herein are highly adequate to automatically and objectively predict bone mineral density values as well as a biomechanical parameter of the bone that can be measured intraoperatively.

Reporting and methodological quality of survival analysis in articles published in Chinese oncology journals

PubMed Central

Zhu, Xiaoyan; Zhou, Xiaobin; Zhang, Yuan; Sun, Xiao; Liu, Haihua; Zhang, Yingying

2017-01-01

Abstract Survival analysis methods have gained widespread use in the filed of oncology. For achievement of reliable results, the methodological process and report quality is crucial. This review provides the first examination of methodological characteristics and reporting quality of survival analysis in articles published in leading Chinese oncology journals. To examine methodological and reporting quality of survival analysis, to identify some common deficiencies, to desirable precautions in the analysis, and relate advice for authors, readers, and editors. A total of 242 survival analysis articles were included to be evaluated from 1492 articles published in 4 leading Chinese oncology journals in 2013. Articles were evaluated according to 16 established items for proper use and reporting of survival analysis. The application rates of Kaplan–Meier, life table, log-rank test, Breslow test, and Cox proportional hazards model (Cox model) were 91.74%, 3.72%, 78.51%, 0.41%, and 46.28%, respectively, no article used the parametric method for survival analysis. Multivariate Cox model was conducted in 112 articles (46.28%). Follow-up rates were mentioned in 155 articles (64.05%), of which 4 articles were under 80% and the lowest was 75.25%, 55 articles were100%. The report rates of all types of survival endpoint were lower than 10%. Eleven of 100 articles which reported a loss to follow-up had stated how to treat it in the analysis. One hundred thirty articles (53.72%) did not perform multivariate analysis. One hundred thirty-nine articles (57.44%) did not define the survival time. Violations and omissions of methodological guidelines included no mention of pertinent checks for proportional hazard assumption; no report of testing for interactions and collinearity between independent variables; no report of calculation method of sample size. Thirty-six articles (32.74%) reported the methods of independent variable selection. The above defects could make potentially inaccurate, misleading of the reported results, or difficult to interpret. There are gaps in the conduct and reporting of survival analysis in studies published in Chinese oncology journals, severe deficiencies were noted. More endorsement by journals of the report guideline for survival analysis may improve articles quality, and the dissemination of reliable evidence to oncology clinicians. We recommend authors, readers, reviewers, and editors to consider survival analysis more carefully and cooperate more closely with statisticians and epidemiologists. PMID:29390340

A system framework of inter-enterprise machining quality control based on fractal theory

NASA Astrophysics Data System (ADS)

Zhao, Liping; Qin, Yongtao; Yao, Yiyong; Yan, Peng

2014-03-01

In order to meet the quality control requirement of dynamic and complicated product machining processes among enterprises, a system framework of inter-enterprise machining quality control based on fractal was proposed. In this system framework, the fractal-specific characteristic of inter-enterprise machining quality control function was analysed, and the model of inter-enterprise machining quality control was constructed by the nature of fractal structures. Furthermore, the goal-driven strategy of inter-enterprise quality control and the dynamic organisation strategy of inter-enterprise quality improvement were constructed by the characteristic analysis on this model. In addition, the architecture of inter-enterprise machining quality control based on fractal was established by means of Web service. Finally, a case study for application was presented. The result showed that the proposed method was available, and could provide guidance for quality control and support for product reliability in inter-enterprise machining processes.

Data assimilation and model evaluation experiment datasets

NASA Technical Reports Server (NTRS)

Lai, Chung-Cheng A.; Qian, Wen; Glenn, Scott M.

1994-01-01

The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

Using Data Mining for Wine Quality Assessment

NASA Astrophysics Data System (ADS)

Cortez, Paulo; Teixeira, Juliana; Cerdeira, António; Almeida, Fernando; Matos, Telmo; Reis, José

Certification and quality assessment are crucial issues within the wine industry. Currently, wine quality is mostly assessed by physicochemical (e.g alcohol levels) and sensory (e.g. human expert evaluation) tests. In this paper, we propose a data mining approach to predict wine preferences that is based on easily available analytical tests at the certification step. A large dataset is considered with white vinho verde samples from the Minho region of Portugal. Wine quality is modeled under a regression approach, which preserves the order of the grades. Explanatory knowledge is given in terms of a sensitivity analysis, which measures the response changes when a given input variable is varied through its domain. Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection and that is guided by the sensitivity analysis. The support vector machine achieved promising results, outperforming the multiple regression and neural network methods. Such model is useful for understanding how physicochemical tests affect the sensory preferences. Moreover, it can support the wine expert evaluations and ultimately improve the production.

Developing a quality by design approach to model tablet dissolution testing: an industrial case study.

PubMed

Yekpe, Ketsia; Abatzoglou, Nicolas; Bataille, Bernard; Gosselin, Ryan; Sharkawi, Tahmer; Simard, Jean-Sébastien; Cournoyer, Antoine

2018-07-01

This study applied the concept of Quality by Design (QbD) to tablet dissolution. Its goal was to propose a quality control strategy to model dissolution testing of solid oral dose products according to International Conference on Harmonization guidelines. The methodology involved the following three steps: (1) a risk analysis to identify the material- and process-related parameters impacting the critical quality attributes of dissolution testing, (2) an experimental design to evaluate the influence of design factors (attributes and parameters selected by risk analysis) on dissolution testing, and (3) an investigation of the relationship between design factors and dissolution profiles. Results show that (a) in the case studied, the two parameters impacting dissolution kinetics are active pharmaceutical ingredient particle size distributions and tablet hardness and (b) these two parameters could be monitored with PAT tools to predict dissolution profiles. Moreover, based on the results obtained, modeling dissolution is possible. The practicality and effectiveness of the QbD approach were demonstrated through this industrial case study. Implementing such an approach systematically in industrial pharmaceutical production would reduce the need for tablet dissolution testing.

"Going the Extra Mile in Downscaling: Why Downscaling is not ...

EPA Pesticide Factsheets

This presentation provides an example of doing additional work for preprocessing global climate model data for use in regional climate modeling simulations with the Weather Research and Forecasting (WRF) model. In this presentation, results from 15 months of downscaling the Community Earth System Model (CESM) were shown, both using the out-of-the-box downscaling of CESM and also with a modification to setting the inland lake temperatures. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the 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 pollution problem, but also in developing emission control policies and regulations for air quality improvements.

"Updates to Model Algorithms & Inputs for the Biogenic ...

EPA Pesticide Factsheets

We have developed new canopy emission algorithms and land use data for BEIS. Simulations with BEIS v3.4 and these updates in CMAQ v5.0.2 are compared these changes to the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and evaluated the simulations against observations. This has resulted in improvements in model evaluations of modeled isoprene, NOx, and O3. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the 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 pollution problem, but also in developing emission control policies and regulations for air quality improvements.

Combination of a Stressor-Response Model with a Conditional Probability Analysis Approach for Developing Candidate Criteria from MBSS

EPA Science Inventory

I show that a conditional probability analysis using a stressor-response model based on a logistic regression provides a useful approach for developing candidate water quality criteria from empirical data, such as the Maryland Biological Streams Survey (MBSS) data.

Aerodynamic Characteristics and Flying Qualities of a Tailless Triangular-wing Airplane Configuration as Obtained from Flights of Rocket-propelled Models at Transonic and Supersonic Speeds

NASA Technical Reports Server (NTRS)

Mitcham, Grady L; Stevens, Joseph E; Norris, Harry P

1956-01-01

A flight investigation of rocket-powered models of a tailless triangular-wing airplane configuration was made through the transonic and low supersonic speed range at the Langley Pilotless Aircraft Research Station at Wallops Island, Va. An analysis of the aerodynamic coefficients, stability derivatives, and flying qualities based on the results obtained from the successful flight tests of three models is presented.

Application of chemometric methods for assessment and modelling of microbiological quality data concerning coastal bathing water in Greece.

PubMed

Papaioannou, Agelos; Rigas, George; Papastergiou, Panagiotis; Hadjichristodoulou, Christos

2014-12-02

Worldwide, the aim of managing water is to safeguard human health whilst maintaining sustainable aquatic and associated terrestrial, ecosystems. Because human enteric viruses are the most likely pathogens responsible for waterborne diseases from recreational water use, but detection methods are complex and costly for routine monitoring, it is of great interest to determine the quality of coastal bathing water with a minimum cost and maximum safety. This study handles the assessment and modelling of the microbiological quality data of 2149 seawater bathing areas in Greece over 10-year period (1997-2006) by chemometric methods. Cluster analysis results indicated that the studied bathing beaches are classified in accordance with the seasonality in three groups. Factor analysis was applied to investigate possible determining factors in the groups resulted from the cluster analysis, and also two new parameters were created in each group; VF1 includes E. coli, faecal coliforms and total coliforms and VF2 includes faecal streptococci/enterococci. By applying the cluster analysis in each seasonal group, three new groups of coasts were generated, group A (ultraclean), group B (clean) and group C (contaminated). The above analysis is confirmed by the application of discriminant analysis, and proves that chemometric methods are useful tools for assessment and modeling microbiological quality data of coastal bathing water on a large scale, and thus could attribute to effective and economical monitoring of the quality of coastal bathing water in a country with a big number of bathing coasts, like Greece. Significance for public healthThe microbiological protection of coastal bathing water quality is of great interest for the public health authorities as well as for the economy. The present study proves that this protection can be achieved by monitoring only two microbiological parameters, E. coli and faecal streptococci/enterococci instead four microbiological parameters (the two mentioned above plus Total coliforms and Faecal coliforms) that are usually monitored today. As a consequence, countries, especially those with large quantities of coastal bathing sites, can perform microbiological monitoring of their bathing waters by checking only the mentioned two parameters, thus ensuring economies of scale. Thus, funds can be used in other actions to preserve the quality of coastal water and human health. This in turn, would aid in the assessment of the quality of coastal bathing waters and provide a more timely indication of bathing water quality, hence contributing to the immediate health protection of bathers.

Managing water quality under drought conditions in the Llobregat River Basin.

PubMed

Momblanch, Andrea; Paredes-Arquiola, Javier; Munné, Antoni; Manzano, Andreu; Arnau, Javier; Andreu, Joaquín

2015-01-15

The primary effects of droughts on river basins include both depleted quantity and quality of the available water resources, which can render water resources useless for human needs and simultaneously damage the environment. Isolated water quality analyses limit the action measures that can be proposed. Thus, an integrated evaluation of water management and quality is warranted. In this study, a methodology consisting of two coordinated models is used to combine aspects of water resource allocation and water quality assessment. Water management addresses water allocation issues by considering the storage, transport and consumption elements. Moreover, the water quality model generates time series of concentrations for several pollutants according to the water quality of the runoff and the demand discharges. These two modules are part of the AQUATOOL decision support system shell for water resource management. This tool facilitates the analysis of the effects of water management and quality alternatives and scenarios on the relevant variables in a river basin. This paper illustrates the development of an integrated model for the Llobregat River Basin. The analysis examines the drought from 2004 to 2008, which is an example of a period when the water system was quantitative and qualitatively stressed. The performed simulations encompass a wide variety of water management and water quality measures; the results provide data for making informed decisions. Moreover, the results demonstrated the importance of combining these measures depending on the evolution of a drought event and the state of the water resources system. Copyright © 2014 Elsevier B.V. All rights reserved.

Use of a Process Analysis Tool for Diagnostic Study on Fine Particulate Matter Predictions in the U.S.-Part II: Analysis and Sensitivity Simulations

EPA Science Inventory

Following the Part I paper that described an application of the U.S. EPA Models-3/Community Multiscale Air Quality (CMAQ) modeling system to the 1999 Southern Oxidants Study episode, this paper presents results from process analysis (PA) using the PA tool embedded in CMAQ and s...

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

Analysis of the longitudinal handling qualities and pilot-induced-oscillation tendencies of the High-Angle-of-Attack Research Vehicle (HARV)

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1994-01-01

The NASA High-Angle-of Attack Research Vehicle (HARV), a modified F-18 aircraft, experienced handling qualities problems in recent flight tests at NASA Dryden Research Center. Foremost in these problems was the tendency of the pilot-aircraft system to exhibit a potentially dangerous phenomenon known as a pilot-induced oscillation (PIO). When they occur, PIO's can severely restrict performance, sharply dimish mission capabilities, and can even result in aircraft loss. A pilot/vehicle analysis was undertaken with the goal of reducing these PIO tendencies and improving the overall vehicle handling qualities with as few changes as possible to the existing feedback/feedforward flight control laws. Utilizing a pair of analytical pilot models developed by the author, a pilot/vehicle analysis of the existing longitudinal flight control system was undertaken. The analysis included prediction of overall handling qualities levels and PIO susceptability. The analysis indicated that improvement in the flight control system was warranted and led to the formulation of a simple control stick command shaping filter. Analysis of the pilot/vehicle system with the shaping filter indicated significant improvements in handling qualities and PIO tendencies could be achieved. A non-real time simulation of the modified control system was undertaken with a realistic, nonlinear model of the current HARV. Special emphasis was placed upon those details of the command filter implementation which could effect safety of flight. The modified system is currently awaiting evaluation in the real-time, pilot-in-the-loop, Dual-Maneuvering-Simulator (DMS) facility at Langley.

Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a Systems Model

NASA Technical Reports Server (NTRS)

Cole, Bjorn; Chung, Seung

2012-01-01

One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must trade between time and cost for analysis quality and quantity. The quality often correlates with greater run time in multidisciplinary models and the quantity is associated with the number of alternatives that can be analyzed. The trade-off is due to the resource intensive process of creating a cohesive multidisciplinary systems model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than hand-written translation scripts between multi-disciplinary models and their analyses. The key is to work from a core systems model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query/View/Transformation (QVT), from the OMG community. SysML was designed to model multidisciplinary systems. The QVT standard was designed to transform SysML models into other models, including those leveraged by engineering analyses. The Europa Habitability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, symbolic analysis (supported by Wolfram Mathematica) is coordinated by data objects transformed from the systems model, enabling extremely flexible and powerful design exploration and analytical investigations of expected system performance.

Lucid dreaming incidence: A quality effects meta-analysis of 50years of research.

PubMed

Saunders, David T; Roe, Chris A; Smith, Graham; Clegg, Helen

2016-07-01

We report a quality effects meta-analysis on studies from the period 1966-2016 measuring either (a) lucid dreaming prevalence (one or more lucid dreams in a lifetime); (b) frequent lucid dreaming (one or more lucid dreams in a month) or both. A quality effects meta-analysis allows for the minimisation of the influence of study methodological quality on overall model estimates. Following sensitivity analysis, a heterogeneous lucid dreaming prevalence data set of 34 studies yielded a mean estimate of 55%, 95% C. I. [49%, 62%] for which moderator analysis showed no systematic bias for suspected sources of variability. A heterogeneous lucid dreaming frequency data set of 25 studies yielded a mean estimate of 23%, 95% C. I. [20%, 25%], moderator analysis revealed no suspected sources of variability. These findings are consistent with earlier estimates of lucid dreaming prevalence and frequent lucid dreaming in the population but are based on more robust evidence. Copyright © 2016 Elsevier Inc. All rights reserved.

[Effect of occupational stress and effort-reward imbalance on sleep quality of people's policeman].

PubMed

Wu, Hui; Gu, Guizhen; Yu, Shanfa

2014-04-01

To explore the effect of occupational stress and effort-reward imbalance on sleep quality of people's police. A cluster sampling survey of sleep quality and occupational stress correlated factors was conducted on 287 police from a city public security bureau by questionnaires in May, 2011; the relationship between sleep quality and occupational stress correlated factors was analyzed by one-way ANOVA and multivariate non-conditional logistic regression using effort-reward imbalance model (ERI) and demand-control-support model (DCS). And the subjects were divided into high tension group and low tension group using the 1.0 of ERI and DCS coefficients as the boundary. The sleep quality score of shift work police was higher than day work police (11.95 ± 6.54 vs 9.52 ± 6.43, t = 2.77, P < 0.05).In ERI model, the sleep quality score in high tension group was higher than low tension group (14.50 ± 6.41 vs 8.60 ± 5.53, t = -5.32, P < 0.01), and in DCS model, the sleep quality score in high tension group was also higher than low tension group (13.71 ± 6.62 vs 9.46 ± 6.04, t = -3.71, P < 0.01).For the regression analysis of ERI model as an argument, sex (OR = 3.0, 95%CI:1.16-7.73) , age for 30-39 years (OR = 3.48, 95%CI:1.32-9.16) , intrinsic effort (OR = 2.30, 95%CI:1.10-4.81) and daily hassles (OR = 2.15, 95%CI:1.06-4.33) were risk factors of low sleep quality, and reward (OR = 0.26, 95%CI:0.12-0.52) was the protective factor.For the regression analysis of DCS model as an argument , age for 30-39 years (OR = 2.55, 95%CI:1.02-6.37) , depressive symptom (OR = 2.10, 95%CI:1.14-3.89) and daily hassles (OR = 3.25, 95%CI:1.70-6.19) were risk factors of low sleep quality.While the ERI model and the DCS model were analyzed simultaneously, sex (OR = 3.03, 95%CI:1.15-7.98) , age for 30-39 years (OR = 3.71, 95%CI:1.38-9.98) and daily hassles (OR = 2.09, 95%CI:1.01-4.30) were the risk factors of low sleep quality, and reward (OR = 0.22, 95%CI:0.10-0.48) was the protective factor. Occupational stress and effort-reward imbalance affected the sleep quality to people's policeman.

Jointly modeling longitudinal proportional data and survival times with an application to the quality of life data in a breast cancer trial.

PubMed

Song, Hui; Peng, Yingwei; Tu, Dongsheng

2017-04-01

Motivated by the joint analysis of longitudinal quality of life data and recurrence free survival times from a cancer clinical trial, we present in this paper two approaches to jointly model the longitudinal proportional measurements, which are confined in a finite interval, and survival data. Both approaches assume a proportional hazards model for the survival times. For the longitudinal component, the first approach applies the classical linear mixed model to logit transformed responses, while the second approach directly models the responses using a simplex distribution. A semiparametric method based on a penalized joint likelihood generated by the Laplace approximation is derived to fit the joint model defined by the second approach. The proposed procedures are evaluated in a simulation study and applied to the analysis of breast cancer data motivated this research.

Researches of fruit quality prediction model based on near infrared spectrum

NASA Astrophysics Data System (ADS)

Shen, Yulin; Li, Lian

2018-04-01

With the improvement in standards for food quality and safety, people pay more attention to the internal quality of fruits, therefore the measurement of fruit internal quality is increasingly imperative. In general, nondestructive soluble solid content (SSC) and total acid content (TAC) analysis of fruits is vital and effective for quality measurement in global fresh produce markets, so in this paper, we aim at establishing a novel fruit internal quality prediction model based on SSC and TAC for Near Infrared Spectrum. Firstly, the model of fruit quality prediction based on PCA + BP neural network, PCA + GRNN network, PCA + BP adaboost strong classifier, PCA + ELM and PCA + LS_SVM classifier are designed and implemented respectively; then, in the NSCT domain, the median filter and the SavitzkyGolay filter are used to preprocess the spectral signal, Kennard-Stone algorithm is used to automatically select the training samples and test samples; thirdly, we achieve the optimal models by comparing 15 kinds of prediction model based on the theory of multi-classifier competition mechanism, specifically, the non-parametric estimation is introduced to measure the effectiveness of proposed model, the reliability and variance of nonparametric estimation evaluation of each prediction model to evaluate the prediction result, while the estimated value and confidence interval regard as a reference, the experimental results demonstrate that this model can better achieve the optimal evaluation of the internal quality of fruit; finally, we employ cat swarm optimization to optimize two optimal models above obtained from nonparametric estimation, empirical testing indicates that the proposed method can provide more accurate and effective results than other forecasting methods.

Identifying key sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2013-09-01

This study investigates sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment, through the use of local and global sensitivity analysis tools, and contributes to an in-depth understanding of wastewater treatment modelling by revealing critical parameters and parameter interactions. One-factor-at-a-time sensitivity analysis is used to screen model parameters and identify those with significant individual effects on three performance indicators: total greenhouse gas emissions, effluent quality and operational cost. Sobol's method enables identification of parameters with significant higher order effects and of particular parameter pairs to which model outputs are sensitive. Use of a variance-based global sensitivity analysis tool to investigate parameter interactions enables identification of important parameters not revealed in one-factor-at-a-time sensitivity analysis. These interaction effects have not been considered in previous studies and thus provide a better understanding wastewater treatment plant model characterisation. It was found that uncertainty in modelled nitrous oxide emissions is the primary contributor to uncertainty in total greenhouse gas emissions, due largely to the interaction effects of three nitrogen conversion modelling parameters. The higher order effects of these parameters are also shown to be a key source of uncertainty in effluent quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Radiation Quality Effects on Transcriptome Profiles in 3-D Cultures After Charged Particle Irradiation

NASA Technical Reports Server (NTRS)

Patel, Zarana S.; Kidane, Yared H.; Huff, Janice L.

2014-01-01

In this work, we evaluated the differential effects of low- and high-LET radiation on 3-D organotypic cultures in order to investigate radiation quality impacts on gene expression and cellular responses. Current risk models for assessment of space radiation-induced cancer have large uncertainties because the models for adverse health effects following radiation exposure are founded on epidemiological analyses of human populations exposed to low-LET radiation. Reducing these uncertainties requires new knowledge on the fundamental differences in biological responses (the so-called radiation quality effects) triggered by heavy ion particle radiation versus low-LET radiation associated with Earth-based exposures. In order to better quantify these radiation quality effects in biological systems, we are utilizing novel 3-D organotypic human tissue models for space radiation research. These models hold promise for risk assessment as they provide a format for study of human cells within a realistic tissue framework, thereby bridging the gap between 2-D monolayer culture and animal models for risk extrapolation to humans. To identify biological pathway signatures unique to heavy ion particle exposure, functional gene set enrichment analysis (GSEA) was used with whole transcriptome profiling. GSEA has been used extensively as a method to garner biological information in a variety of model systems but has not been commonly used to analyze radiation effects. It is a powerful approach for assessing the functional significance of radiation quality-dependent changes from datasets where the changes are subtle but broad, and where single gene based analysis using rankings of fold-change may not reveal important biological information.

Advances in the meta-analysis of heterogeneous clinical trials II: The quality effects model.

PubMed

Doi, Suhail A R; Barendregt, Jan J; Khan, Shahjahan; Thalib, Lukman; Williams, Gail M

2015-11-01

This article examines the performance of the updated quality effects (QE) estimator for meta-analysis of heterogeneous studies. It is shown that this approach leads to a decreased mean squared error (MSE) of the estimator while maintaining the nominal level of coverage probability of the confidence interval. Extensive simulation studies confirm that this approach leads to the maintenance of the correct coverage probability of the confidence interval, regardless of the level of heterogeneity, as well as a lower observed variance compared to the random effects (RE) model. The QE model is robust to subjectivity in quality assessment down to completely random entry, in which case its MSE equals that of the RE estimator. When the proposed QE method is applied to a meta-analysis of magnesium for myocardial infarction data, the pooled mortality odds ratio (OR) becomes 0.81 (95% CI 0.61-1.08) which favors the larger studies but also reflects the increased uncertainty around the pooled estimate. In comparison, under the RE model, the pooled mortality OR is 0.71 (95% CI 0.57-0.89) which is less conservative than that of the QE results. The new estimation method has been implemented into the free meta-analysis software MetaXL which allows comparison of alternative estimators and can be downloaded from www.epigear.com. Copyright © 2015 Elsevier Inc. All rights reserved.

Simulation based energy-resource efficient manufacturing integrated with in-process virtual management

NASA Astrophysics Data System (ADS)

Katchasuwanmanee, Kanet; Cheng, Kai; Bateman, Richard

2016-09-01

As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow (productivity) and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.

The relationship between advertising, price, and nursing home quality.

PubMed

Kash, Bita A; Miller, Thomas R

2009-01-01

Theoretically, nursing homes should engage in advertising for the following two reasons: (a) to improve awareness of the services offered in a particular market and (b) to signal high-quality services. In this study, we build upon results from prior studies of nursing home advertising activity, market competition, and quality. The purpose of this study was to examine the association between advertising expenses, price, and quality. We focused on answering the question: Do nursing homes use advertising and price to signal superior quality? The Texas Nursing Facilities Medicaid Cost Report, the Texas Quality Reporting System, and the Area Resource File were merged for the year 2003. We used three alternative measures of quality to improve the robustness of this exploratory analysis. Quality measures were examined using Bonferroni correlation coefficient analysis. Associations between advertising expenses and quality were evaluated using three regression models predicting quality. We also examined the association of the price of a private bed per day with quality. Advertising expenses were not associated with better nursing home quality as measured by three quality scales. The average price customers pay for one private bed per day was associated with better quality only in one of the three quality regression models. The price of nursing home care might be a better indicator of quality and necessary to increase as quality of care is improved in the nursing homes sector. Because more advertising expenditures are not necessarily associated with better quality, consumers could be mislead by advertisements and choose poor quality nursing homes. Nursing home administrators should focus on customer relationship management tools instead of expensive advertising. Relationship management tools are proven marketing techniques for the health services sector, usually less expensive than advertising, and help with staff retention and quality outcomes.

Guide to the Business Capability Lifecycle for Department of Defense ACAT III Programs

DTIC Science & Technology

2012-07-01

Cause and Effect matix SCAMPER Analysis Goal Quality Metrics Gap Analysis Bottlenecks Defects Goal Quality Metrics E2E Supported BPMN Q1/2 Q3 Q4 Q6 Q6...analysis a. Identify the root causes of the business problem b. Provide an as-is map, using Business Process Model and Notation ( BPMN ), of the...why they were eliminated from further consideration 8. To-be analysis a. Provide a to-be map, in BPMN , of the target process that illustrates the

The Operation Mechanisms of External Quality Assurance Frameworks of Foreign Higher Education and Implications for Graduate Education

ERIC Educational Resources Information Center

Lin, Mengquan; Chang, Kai; Gong, Le

2016-01-01

The higher education quality evaluation and assurance frameworks and their operating mechanisms of countries such as the United Kingdom, France, and the United States show that higher education systems, traditional culture, and social background all impact quality assurance operating mechanisms. A model analysis of these higher education quality…

A METHODOLOGY FOR ESTIMATING UNCERTAINTY OF A DISTRIBUTED HYDROLOGIC MODEL: APPLICATION TO POCONO CREEK WATERSHED

EPA Science Inventory

Utility of distributed hydrologic and water quality models for watershed management and sustainability studies should be accompanied by rigorous model uncertainty analysis. However, the use of complex watershed models primarily follows the traditional {calibrate/validate/predict}...

Impacts of Climate Policy on Regional Air Quality, Health, and Air Quality Regulatory Procedures

NASA Astrophysics Data System (ADS)

Thompson, T. M.; Selin, N. E.

2011-12-01

Both the changing climate, and the policy implemented to address climate change can impact regional air quality. We evaluate the impacts of potential selected climate policies on modeled regional air quality with respect to national pollution standards, human health and the sensitivity of health uncertainty ranges. To assess changes in air quality due to climate policy, we couple output from a regional computable general equilibrium economic model (the US Regional Energy Policy [USREP] model), with a regional air quality model (the Comprehensive Air Quality Model with Extensions [CAMx]). USREP uses economic variables to determine how potential future U.S. climate policy would change emissions of regional pollutants (CO, VOC, NOx, SO2, NH3, black carbon, and organic carbon) from ten emissions-heavy sectors of the economy (electricity, coal, gas, crude oil, refined oil, energy intensive industry, other industry, service, agriculture, and transportation [light duty and heavy duty]). Changes in emissions are then modeled using CAMx to determine the impact on air quality in several cities in the Northeast US. We first calculate the impact of climate policy by using regulatory procedures used to show attainment with National Ambient Air Quality Standards (NAAQS) for ozone and particulate matter. Building on previous work, we compare those results with the calculated results and uncertainties associated with human health impacts due to climate policy. This work addresses a potential disconnect between NAAQS regulatory procedures and the cost/benefit analysis required for and by the Clean Air Act.

Quality tracing in meat supply chains

PubMed Central

Mack, Miriam; Dittmer, Patrick; Veigt, Marius; Kus, Mehmet; Nehmiz, Ulfert; Kreyenschmidt, Judith

2014-01-01

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production. PMID:24797136

Quality tracing in meat supply chains.

PubMed

Mack, Miriam; Dittmer, Patrick; Veigt, Marius; Kus, Mehmet; Nehmiz, Ulfert; Kreyenschmidt, Judith

2014-06-13

The aim of this study was the development of a quality tracing model for vacuum-packed lamb that is applicable in different meat supply chains. Based on the development of relevant sensory parameters, the predictive model was developed by combining a linear primary model and the Arrhenius model as the secondary model. Then a process analysis was conducted to define general requirements for the implementation of the temperature-based model into a meat supply chain. The required hardware and software for continuous temperature monitoring were developed in order to use the model under practical conditions. Further on a decision support tool was elaborated in order to use the model as an effective tool in combination with the temperature monitoring equipment for the improvement of quality and storage management within the meat logistics network. Over the long term, this overall procedure will support the reduction of food waste and will improve the resources efficiency of food production.

Analysis of Indoor Environment in Classroom Based on Hygienic Requirements

NASA Astrophysics Data System (ADS)

Javorček, Miroslav; Sternová, Zuzana

2016-06-01

The article contains the analysis of experimental ventilation measurement in selected classrooms of the Elementary School Štrba. Mathematical model of selected classroom was prepared according to in-situ measurements and air exchange was calculated. Interior air temperature and quality influences the students ´ comfort. Evaluated data were compared to requirements of standard (STN EN 15251,2008) applicable to classroom indoor environment during lectures, highlighting the difference between required ambiance quality and actually measured values. CO2 concentration refers to one of the parameters indicating indoor environment quality.

Can integrative catchment management mitigate future water quality issues caused by climate change and socio-economic development?

NASA Astrophysics Data System (ADS)

Honti, Mark; Schuwirth, Nele; Rieckermann, Jörg; Stamm, Christian

2017-03-01

The design and evaluation of solutions for integrated surface water quality management requires an integrated modelling approach. Integrated models have to be comprehensive enough to cover the aspects relevant for management decisions, allowing for mapping of larger-scale processes such as climate change to the regional and local contexts. Besides this, models have to be sufficiently simple and fast to apply proper methods of uncertainty analysis, covering model structure deficits and error propagation through the chain of sub-models. Here, we present a new integrated catchment model satisfying both conditions. The conceptual iWaQa model was developed to support the integrated management of small streams. It can be used to predict traditional water quality parameters, such as nutrients and a wide set of organic micropollutants (plant and material protection products), by considering all major pollutant pathways in urban and agricultural environments. Due to its simplicity, the model allows for a full, propagative analysis of predictive uncertainty, including certain structural and input errors. The usefulness of the model is demonstrated by predicting future surface water quality in a small catchment with mixed land use in the Swiss Plateau. We consider climate change, population growth or decline, socio-economic development, and the implementation of management strategies to tackle urban and agricultural point and non-point sources of pollution. Our results indicate that input and model structure uncertainties are the most influential factors for certain water quality parameters. In these cases model uncertainty is already high for present conditions. Nevertheless, accounting for today's uncertainty makes management fairly robust to the foreseen range of potential changes in the next decades. The assessment of total predictive uncertainty allows for selecting management strategies that show small sensitivity to poorly known boundary conditions. The identification of important sources of uncertainty helps to guide future monitoring efforts and pinpoints key indicators, whose evolution should be closely followed to adapt management. The possible impact of climate change is clearly demonstrated by water quality substantially changing depending on single climate model chains. However, when all climate trajectories are combined, the human land use and management decisions have a larger influence on water quality against a time horizon of 2050 in the study.

Developing the Model of Fuel Injection Process Efficiency Analysis for Injector for Diesel Engines

NASA Astrophysics Data System (ADS)

Anisimov, M. Yu; Kayukov, S. S.; Gorshkalev, A. A.; Belousov, A. V.; Gallyamov, R. E.; Lysenko, Yu D.

2018-01-01

The article proposes an assessment option for analysing the quality of fuel injection by the injector constituting the development of calculation blocks in a common injector model within LMS Imagine.Lab AMESim. The parameters of the injector model in the article correspond to the serial injector Common Rail-type with solenoid. The possibilities of this approach are demonstrated with providing the results using the example of modelling the modified injector. Following the research results, the advantages of the proposed approach to analysing assessing the fuel injection quality were detected.

A Tentative Study on the Evaluation of Community Health Service Quality*

NASA Astrophysics Data System (ADS)

Ma, Zhi-qiang; Zhu, Yong-yue

Community health service is the key point of health reform in China. Based on pertinent studies, this paper constructed an indicator system for the community health service quality evaluation from such five perspectives as visible image, reliability, responsiveness, assurance and sympathy, according to service quality evaluation scale designed by Parasuraman, Zeithaml and Berry. A multilevel fuzzy synthetical evaluation model was constructed to evaluate community health service by fuzzy mathematics theory. The applicability and maneuverability of the evaluation indicator system and evaluation model were verified by empirical analysis.

Water quality and relation to taste-and-odor compounds in North Fork Ninnescah River and Cheney Reservoir, south-central Kansas, 1997-2003

USGS Publications Warehouse

Christensen, Victoria G.; Graham, Jennifer L.; Milligan, Chad R.; Pope, Larry M.; Ziegler, Andrew C.

2006-01-01

Regression models were developed between geosmin and the physical property measurements continuously recorded by water-quality monitors at each site. The geosmin regression model was applied to water-quality monitor measurements, providing a continuous estimate of geosmin for 2003. The city of Wichita will be able to use this type of analysis to determine the probability of when concentrations of geosmin are likely to be at or above the human detection level of 0.01 microgram per liter.

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.

The SCALE Verified, Archived Library of Inputs and Data - VALID

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

Marshall, William BJ J; Rearden, Bradley T

The Verified, Archived Library of Inputs and Data (VALID) at ORNL contains high quality, independently reviewed models and results that improve confidence in analysis. VALID is developed and maintained according to a procedure of the SCALE quality assurance (QA) plan. This paper reviews the origins of the procedure and its intended purpose, the philosophy of the procedure, some highlights of its implementation, and the future of the procedure and associated VALID library. The original focus of the procedure was the generation of high-quality models that could be archived at ORNL and applied to many studies. The review process associated withmore » model generation minimized the chances of errors in these archived models. Subsequently, the scope of the library and procedure was expanded to provide high quality, reviewed sensitivity data files for deployment through the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE). Sensitivity data files for approximately 400 such models are currently available. The VALID procedure and library continue fulfilling these multiple roles. The VALID procedure is based on the quality assurance principles of ISO 9001 and nuclear safety analysis. Some of these key concepts include: independent generation and review of information, generation and review by qualified individuals, use of appropriate references for design data and documentation, and retrievability of the models, results, and documentation associated with entries in the library. Some highlights of the detailed procedure are discussed to provide background on its implementation and to indicate limitations of data extracted from VALID for use by the broader community. Specifically, external users of data generated within VALID must take responsibility for ensuring that the files are used within the QA framework of their organization and that use is appropriate. The future plans for the VALID library include expansion to include additional experiments from the IHECSBE, to include experiments from areas beyond criticality safety, such as reactor physics and shielding, and to include application models. In the future, external SCALE users may also obtain qualification under the VALID procedure and be involved in expanding the library. The VALID library provides a pathway for the criticality safety community to leverage modeling and analysis expertise at ORNL.« less

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.

Quality evaluation of health information system's architectures developed using the HIS-DF methodology.

PubMed

López, Diego M; Blobel, Bernd; Gonzalez, Carolina

2010-01-01

Requirement analysis, design, implementation, evaluation, use, and maintenance of semantically interoperable Health Information Systems (HIS) have to be based on eHealth standards. HIS-DF is a comprehensive approach for HIS architectural development based on standard information models and vocabulary. The empirical validity of HIS-DF has not been demonstrated so far. Through an empirical experiment, the paper demonstrates that using HIS-DF and HL7 information models, semantic quality of HIS architecture can be improved, compared to architectures developed using traditional RUP process. Semantic quality of the architecture has been measured in terms of model's completeness and validity metrics. The experimental results demonstrated an increased completeness of 14.38% and an increased validity of 16.63% when using the HIS-DF and HL7 information models in a sample HIS development project. Quality assurance of the system architecture in earlier stages of HIS development presumes an increased quality of final HIS systems, which supposes an indirect impact on patient care.

[Satisfaction and perceived quality of people insured by the Social Health Protection in Mexico. Methodological foundations].

PubMed

Saturno-Hernández, Pedro J; Gutiérrez-Reyes, Juan Pablo; Vieyra-Romero, Waldo Ivan; Romero-Martínez, Martín; O'Shea-Cuevas, Gabriel Jaime; Lozano-Herrera, Javier; Tavera-Martínez, Sonia; Hernández-Ávila, Mauricio

2016-01-01

To describe the conceptual framework and methods for implementation and analysis of the satisfaction survey of the Mexican System for Social Protection in Health. We analyze the methodological elements of the 2013, 2014 and 2015 surveys, including the instrument, sampling method and study design, conceptual framework, and characteristics and indicators of the analysis. The survey captures information on perceived quality and satisfaction. Sampling has national and State representation. Simple and composite indicators (index of satisfaction and rate of reported quality problems) are built and described. The analysis is completed using Pareto diagrams, correlation between indicators and association with satisfaction by means of multivariate models. The measurement of satisfaction and perceived quality is a complex but necessary process to comply with regulations and to identify strategies for improvement. The described survey presents a design and rigorous analysis focused on its utility for improving.

Evaluating Individual Students' Perceptions of Instructional Quality: An Investigation of their Factor Structure, Measurement Invariance, and Relations to Educational Outcomes.

PubMed

Scherer, Ronny; Nilsen, Trude; Jansen, Malte

2016-01-01

Students' perceptions of instructional quality are among the most important criteria for evaluating teaching effectiveness. The present study evaluates different latent variable modeling approaches (confirmatory factor analysis, exploratory structural equation modeling, and bifactor modeling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance, and the relations to selected educational outcomes (achievement, self-concept, and motivation in mathematics). On the basis of the Programme for International Student Assessment (PISA) 2012 large-scale data sets of Australia, Canada, and the USA (N = 26,746 students), we find support for the distinction between three factors of individual students' perceptions and full measurement invariance across countries for all modeling approaches. In this regard, bifactor exploratory structural equation modeling outperformed alternative approaches with respect to model fit. Our findings reveal significant relations to the educational outcomes. This study synthesizes different modeling approaches of individual students' perceptions of instructional quality and provides insights into the nature of these perceptions from an individual differences perspective. Implications for the measurement and modeling of individually perceived instructional quality are discussed.

Do hospitals respond to rivals' quality and efficiency? A spatial panel econometric analysis.

PubMed

Longo, Francesco; Siciliani, Luigi; Gravelle, Hugh; Santos, Rita

2017-09-01

We investigate whether hospitals in the English National Health Service change their quality or efficiency in response to changes in quality or efficiency of neighbouring hospitals. We first provide a theoretical model that predicts that a hospital will not respond to changes in the efficiency of its rivals but may change its quality or efficiency in response to changes in the quality of rivals, though the direction of the response is ambiguous. We use data on eight quality measures (including mortality, emergency readmissions, patient reported outcome, and patient satisfaction) and six efficiency measures (including bed occupancy, cancelled operations, and costs) for public hospitals between 2010/11 and 2013/14 to estimate both spatial cross-sectional and spatial fixed- and random-effects panel data models. We find that although quality and efficiency measures are unconditionally spatially correlated, the spatial regression models suggest that a hospital's quality or efficiency does not respond to its rivals' quality or efficiency, except for a hospital's overall mortality that is positively associated with that of its rivals. The results are robust to allowing for spatially correlated covariates and errors and to instrumenting rivals' quality and efficiency. Copyright © 2017 John Wiley & Sons, Ltd.

Display Systems Dynamics Requirements for Flying Qualities

DTIC Science & Technology

1988-05-09

Schidtt. LodI Caser 13a. TYPE OP REPORT 1 &b TIME COVERED 14 DAEO EPOR Ywot.MDay)15. AGEWCUNT Finial Repart IFROM Oct.66o To DeB- 7lse may 9 178 16...e Di Spc Il .AI OF TABLE OF CONTENTS Section Page I INTRODUCTION 1 1 . Motivation and Objectives 1 2. Overview 3 3. Report Organization 4 II MODEL...BASED ANALYSIS FRAMEWORK 5 1 . Optimal Control Model Structure 5 2. OCM-Based Characterization of Flying Qualities 8 III MODELING THE PERCEPTUAL INTERFACE

State of the art in pathology business process analysis, modeling, design and optimization.

PubMed

Schrader, Thomas; Blobel, Bernd; García-Rojo, Marcial; Daniel, Christel; Słodkowska, Janina

2012-01-01

For analyzing current workflows and processes, for improving them, for quality management and quality assurance, for integrating hardware and software components, but also for education, training and communication between different domains' experts, modeling business process in a pathology department is inevitable. The authors highlight three main processes in pathology: general diagnostic, cytology diagnostic, and autopsy. In this chapter, those processes are formally modeled and described in detail. Finally, specialized processes such as immunohistochemistry and frozen section have been considered.

Development of the IBSAL-SimMOpt Method for the Optimization of Quality in a Corn Stover Supply Chain

DOE PAGES

Chavez, Hernan; Castillo-Villar, Krystel; Webb, Erin

2017-08-01

Variability on the physical characteristics of feedstock has a relevant effect on the reactor’s reliability and operating cost. Most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and preprocessing operations required to meet biomass specifications on overall cost and performance. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model estimates the harvesting, collection, transportation, and storage cost while considering the stochastic behavior of the field-to-biorefinery supply chain. This paper proposes an IBSAL-SimMOpt (Simulation-based Multi-Objective Optimization) method for optimizing the biomass quality and costs associated with the efforts needed to meetmore » conversion technology specifications. The method is developed in two phases. For the first phase, a SimMOpt tool that interacts with the extended IBSAL is developed. For the second phase, the baseline IBSAL model is extended so that the cost for meeting and/or penalization for failing in meeting specifications are considered. The IBSAL-SimMOpt method is designed to optimize quality characteristics of biomass, cost related to activities intended to improve the quality of feedstock, and the penalization cost. A case study based on 1916 farms in Ontario, Canada is considered for testing the proposed method. Analysis of the results demonstrates that this method is able to find a high-quality set of non-dominated solutions.« less

Development of the IBSAL-SimMOpt Method for the Optimization of Quality in a Corn Stover Supply Chain

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

Chavez, Hernan; Castillo-Villar, Krystel; Webb, Erin

Variability on the physical characteristics of feedstock has a relevant effect on the reactor’s reliability and operating cost. Most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and preprocessing operations required to meet biomass specifications on overall cost and performance. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model estimates the harvesting, collection, transportation, and storage cost while considering the stochastic behavior of the field-to-biorefinery supply chain. This paper proposes an IBSAL-SimMOpt (Simulation-based Multi-Objective Optimization) method for optimizing the biomass quality and costs associated with the efforts needed to meetmore » conversion technology specifications. The method is developed in two phases. For the first phase, a SimMOpt tool that interacts with the extended IBSAL is developed. For the second phase, the baseline IBSAL model is extended so that the cost for meeting and/or penalization for failing in meeting specifications are considered. The IBSAL-SimMOpt method is designed to optimize quality characteristics of biomass, cost related to activities intended to improve the quality of feedstock, and the penalization cost. A case study based on 1916 farms in Ontario, Canada is considered for testing the proposed method. Analysis of the results demonstrates that this method is able to find a high-quality set of non-dominated solutions.« less

Evaluation of physical activity programmes for elderly people - a descriptive study using the EFQM' criteria

PubMed Central

2011-01-01

Background In the past years, there has been a growing concern in designing physical activity (PA) programmes for elderly people, because evidence suggests that such health promotion interventions may reduce the deleterious effects of the ageing process. Quality is an important issue when designing a PA programme for older people. Some studies support the Excellence Model of the European Foundation for Quality Management (EFQM) as an operational framework for evaluating the quality of an organization. Within this context, the aim of this study was to characterize the quality management models of the PA programmes developed by Portuguese Local Administration to enhance quality of life for elderly people, according to the criteria of the EFQM Excellence Model. Methods A methodological triangulation was conducted in 26 PA programmes using questionnaire surveys, semi-structured interviews and document analysis. We used standard approaches to the statistical analysis of data including frequencies and percentages for the categorical data. Results Results showed that Processes (65,38%), Leadership (61,03%), Customer results (58,46) and People (51,28%) had high percentage occurrences of quality practices. In contrast, Partnerships and resources (45,77%), People results (41,03%), Policy and strategy (37,91%), Key performance results (19,23%) and Society results (19,23%) had lower percentage occurrences. Conclusions Our findings suggest that although there are some good practices in PA programmes, there are still relevant areas that require improvement. PMID:21338497

Assessing potential effects of highway runoff on receiving-water quality at selected sites in Oregon with the Stochastic Empirical Loading and Dilution Model (SELDM)

USGS Publications Warehouse

Risley, John C.; Granato, Gregory E.

2014-01-01

6. An analysis of the use of grab sampling and nonstochastic upstream modeling methods was done to evaluate the potential effects on modeling outcomes. Additional analyses using surrogate water-quality datasets for the upstream basin and highway catchment were provided for six Oregon study sites to illustrate the risk-based information that SELDM will produce. These analyses show that the potential effects of highway runoff on receiving-water quality downstream of the outfall depends on the ratio of drainage areas (dilution), the quality of the receiving water upstream of the highway, and the concentration of the criteria of the constituent of interest. These analyses also show that the probability of exceeding a water-quality criterion may depend on the input statistics used, thus careful selection of representative values is important.

Regression and multivariate models for predicting particulate matter concentration level.

PubMed

Nazif, Amina; Mohammed, Nurul Izma; Malakahmad, Amirhossein; Abualqumboz, Motasem S

2018-01-01

The devastating health effects of particulate matter (PM 10 ) exposure by susceptible populace has made it necessary to evaluate PM 10 pollution. Meteorological parameters and seasonal variation increases PM 10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM 10 concentration levels. The analyses were carried out using daily average PM 10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM 10 concentration levels having coefficient of determination (R 2 ) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

A Graphical Representation of Multiple Stressor Effects on River Eutrophication as Simulated by a Physics-Based River Quality Model

NASA Astrophysics Data System (ADS)

Hitt, O.; Hutchins, M.

2016-12-01

UK river waters face considerable future pressures, primarily from population growth and climate change. In understanding controls on river water quality, experimental studies have successfully identified response to single or paired stressors under controlled conditions. Generalised Linear Model (GLM) approaches are commonly used to quantify stressor-response relationships. To explore a wider variety of stressors physics-based models are used. Our objective is to evaluate how five different types of stressor influence the severity of river eutrophication and its impact on Dissolved Oxygen (DO) an integrated measure of river ecological health. This is done by applying a physics-based river quality model for 4 years at daily time step to a 92 km stretch in the 3445 km2 Thames (UK) catchment. To understand the impact of model structural uncertainty we present results from two alternative formulations of the biological response. Sensitivity analysis carried out using the QUESTOR model (QUality Evaluation and Simulation TOol for River systems) considered gradients of various stressors: river flow, water temperature, urbanisation (abstractions and sewage/industrial effluents), phosphate concentrations in effluents and tributaries and riparian tree shading (modifying the light input). Scalar modifiers applied to the 2009-12 time-series inputs define the gradients. The model has been run for each combination of the values of these 5 variables. Results are analysed using graphical methods in order to identify variation in the type of relationship between different pairs of stressors on the system response. The method allows for all outputs from each combination of stressors to be displayed in one graphic and so showing the results of hundreds of model runs simultaneously. This approach can be carried out for all stressor pairs, and many locations/determinands. Supporting statistical analysis (GLM) reinforces the findings from the graphical analysis. Analysis suggests that climate-driven variables (flow and river temperature) give strong explanation of variation in DO content. An indicator of low DO values typically seen in summer is chosen (10th percentile). Increasing temperature clearly has adverse effects lowering DO, and is illustrated in three example graphics.

Using a Data-Driven Approach to Understand the Interaction between Catchment Characteristics and Water Quality Responses

NASA Astrophysics Data System (ADS)

Western, A. W.; Lintern, A.; Liu, S.; Ryu, D.; Webb, J. A.; Leahy, P.; Wilson, P.; Waters, D.; Bende-Michl, U.; Watson, M.

2016-12-01

Many streams, lakes and estuaries are experiencing increasing concentrations and loads of nutrient and sediments. Models that can predict the spatial and temporal variability in water quality of aquatic systems are required to help guide the management and restoration of polluted aquatic systems. We propose that a Bayesian hierarchical modelling framework could be used to predict water quality responses over varying spatial and temporal scales. Stream water quality data and spatial data of catchment characteristics collected throughout Victoria and Queensland (in Australia) over two decades will be used to develop this Bayesian hierarchical model. In this paper, we present the preliminary exploratory data analysis required for the development of the Bayesian hierarchical model. Specifically, we present the results of exploratory data analysis of Total Nitrogen (TN) concentrations in rivers in Victoria (in South-East Australia) to illustrate the catchment characteristics that appear to be influencing spatial variability in (1) mean concentrations of TN; and (2) the relationship between discharge and TN throughout the state. These important catchment characteristics were identified using: (1) monthly TN concentrations measured at 28 water quality gauging stations and (2) climate, land use, topographic and geologic characteristics of the catchments of these 28 sites. Spatial variability in TN concentrations had a positive correlation to fertiliser use in the catchment and average temperature. There were negative correlations between TN concentrations and catchment forest cover, annual runoff, runoff perenniality, soil erosivity and catchment slope. The relationship between discharge and TN concentrations showed spatial variability, possibly resulting from climatic and topographic differences between the sites. The results of this study will feed into the hierarchical Bayesian model of river water quality.

Using aircraft and satellite observations to improve regulatory air quality models

NASA Astrophysics Data System (ADS)

Canty, T. P.; Vinciguerra, T.; Anderson, D. C.; Carpenter, S. F.; Goldberg, D. L.; Hembeck, L.; Montgomery, L.; Liu, X.; Salawitch, R. J.; Dickerson, R. R.

2014-12-01

Federal and state agencies rely on EPA approved models to develop attainment strategies that will bring states into compliance with the National Ambient Air Quality Standards (NAAQS). We will describe modifications to the Community Multi-Scale Air Quality (CMAQ) model and Comprehensive Air Quality Model with Extensions (CAMx) frameworks motivated by analysis of NASA satellite and aircraft measurements. Observations of tropospheric column NO2 from OMI have already led to the identification of an important deficiency in the chemical mechanisms used by models; data collected during the DISCOVER-AQ field campaign has been instrumental in devising an improved representation of the chemistry of nitrogen species. Our recent work has focused on the use of: OMI observations of tropospheric O3 to assess and improve the representation of boundary conditions used by AQ models, OMI NO2 to derive a top down NOx emission inventory from commercial shipping vessels that affect air quality in the Eastern U.S., and OMI HCHO to assess the C5H8 emission inventories provided by bioegenic emissions models. We will describe how these OMI-driven model improvements are being incorporated into the State Implementation Plans (SIPs) being prepared for submission to EPA in summer 2015 and how future modeling efforts may be impacted by our findings.

The Use of AMET and Automated Scripts for Model Evaluation

EPA Science Inventory

The Atmospheric Model Evaluation Tool (AMET) is a suite of software designed to facilitate the analysis and evaluation of meteorological and air quality models. AMET matches the model output for particular locations to the corresponding observed values from one or more networks ...

NEW DEVELOPMENTS IN THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL

EPA Science Inventory

CMAQ model research and development is currently following two tracks at the Atmospheric Modeling Division of the USEPA. Public releases of the community model system for research and policy analysis is continuing on an annual interval with the latest release scheduled for Augus...

Modelling the effect of wildfire on forested catchment water quality using the SWAT model

NASA Astrophysics Data System (ADS)

Yu, M.; Bishop, T.; van Ogtrop, F. F.; Bell, T.

2016-12-01

Wildfire removes the surface vegetation, releases ash, increase erosion and runoff, and therefore effects the hydrological cycle of a forested water catchment. It is important to understand chnage and how the catchment recovers. These processes are spatially sensitive and effected by interactions between fire severity and hillslope, soil type and surface vegetation conditions. Thus, a distributed hydrological modelling approach is required. In this study, the Soil and Water Analysis Tool (SWAT) is used to predict the effect of 2001/02 Sydney wild fire on catchment water quality. 10 years pre-fire data is used to create and calibrate the SWAT model. The calibrated model was then used to simulate the water quality for the 10 years post-fire period without fire effect. The simulated water quality data are compared with recorded water quality data provided by Sydney catchment authority. The mean change of flow, total suspended solid, total nitrate and total phosphate are compare on monthly, three month, six month and annual basis. Two control catchment and three burn catchment were analysed.

Multilevel Factor Analysis by Model Segregation: New Applications for Robust Test Statistics

ERIC Educational Resources Information Center

Schweig, Jonathan

2014-01-01

Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…

Bottom-Up Analysis of Single-Case Research Designs

ERIC Educational Resources Information Center

Parker, Richard I.; Vannest, Kimberly J.

2012-01-01

This paper defines and promotes the qualities of a "bottom-up" approach to single-case research (SCR) data analysis. Although "top-down" models, for example, multi-level or hierarchical linear models, are gaining momentum and have much to offer, interventionists should be cautious about analyses that are not easily understood, are not governed by…

Air quality and acute deaths in California, 2000-2012.

PubMed

Young, S Stanley; Smith, Richard L; Lopiano, Keneth K

2017-08-01

Many studies have shown an association between air quality and acute deaths, and such associations are widely interpreted as causal. Several factors call causation and even association into question, for example multiple testing and multiple modeling, publication bias and confirmation bias. Many published studies are difficult or impossible to reproduce because of lack of access to confidential data sources. Here we make publically available a dataset containing daily air quality levels, PM 2.5 and ozone, daily temperature levels, minimum and maximum and daily maximum relative humidity levels for the eight most populous California air basins, thirteen years, >2M deaths, over 37,000 exposure days. The data are analyzed using standard time series analysis, and a sensitivity analysis is computed varying model parameters, locations and years. Our analysis finds little evidence for association between air quality and acute deaths. These results are consistent with those for the widely cited NMMAPS dataset when the latter are restricted to California. The daily death variability was mostly explained by time of year or weather variables; Neither PM 2.5 nor ozone added appreciably to the prediction of daily deaths. These results call into question the widespread belief that association between air quality and acute deaths is causal/near-universal. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

“Nitrogen Budgets for the Mississippi River Basin using the ...

EPA Pesticide Factsheets

Presentation on the results from the 3 linked models, EPIC (USDA), CMAQ and NEWS to analyze a scenario of increased corn production related to biofuels together with Clean Air Act emission reductions across the US and the resultant effect on nitrogen loading to the Gulf of Mexico from the Mississippi River Basin. This is a demonstration of a capability to connect the N cascade bringing air, land, water together. EPIC = Environmental Policy Integrated Climate model, CMAQ = Community Multiscale Air Quality model, NEWS = Nutrient Export of WaterSheds model. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the 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 pollution problem, but also in developing emission control policies and regulations for air quality improvements.

Service quality, satisfaction, and behavioral intention in home delivered meals program

PubMed Central

Joung, Hyun-Woo; Yuan, Jingxue Jessica; Huffman, Lynn

2011-01-01

This study was conducted to evaluate recipients' perception of service quality, satisfaction, and behavioral intention in home delivered meals program in the US. Out of 398 questionnaires, 265 (66.6%) were collected, and 209 questionnaires (52.5%) were used for the statistical analysis. A Confirmatory Factor Analysis (CFA) with a maximum likelihood was first conducted to estimate the measurement model by verifying the underlying structure of constructs. The level of internal consistency in each construct was acceptable, with Cronbach's alpha estimates ranging from 0.7 to 0.94. All of the composite reliabilities of the constructs were over the cutoff value of 0.50, ensuring adequate internal consistency of multiple items for each construct. As a second step, a Meals-On-Wheels (MOW) recipient perception model was estimated. The model's fit as indicated by these indexes was satisfactory and path coefficients were analyzed. Two paths between (1) volunteer issues and behavioral intention and (2) responsiveness and behavioral intention were not significant. The path for predicting a positive relationship between food quality and satisfaction was supported. The results show that having high food quality may create recipient satisfaction. The findings suggest that food quality and responsiveness are significant predictors of positive satisfaction. Moreover, satisfied recipients have positive behavioral intention toward MOW programs. PMID:21556231

Service quality, satisfaction, and behavioral intention in home delivered meals program.

PubMed

Joung, Hyun-Woo; Kim, Hak-Seon; Yuan, Jingxue Jessica; Huffman, Lynn

2011-04-01

This study was conducted to evaluate recipients' perception of service quality, satisfaction, and behavioral intention in home delivered meals program in the US. Out of 398 questionnaires, 265 (66.6%) were collected, and 209 questionnaires (52.5%) were used for the statistical analysis. A Confirmatory Factor Analysis (CFA) with a maximum likelihood was first conducted to estimate the measurement model by verifying the underlying structure of constructs. The level of internal consistency in each construct was acceptable, with Cronbach's alpha estimates ranging from 0.7 to 0.94. All of the composite reliabilities of the constructs were over the cutoff value of 0.50, ensuring adequate internal consistency of multiple items for each construct. As a second step, a Meals-On-Wheels (MOW) recipient perception model was estimated. The model's fit as indicated by these indexes was satisfactory and path coefficients were analyzed. Two paths between (1) volunteer issues and behavioral intention and (2) responsiveness and behavioral intention were not significant. The path for predicting a positive relationship between food quality and satisfaction was supported. The results show that having high food quality may create recipient satisfaction. The findings suggest that food quality and responsiveness are significant predictors of positive satisfaction. Moreover, satisfied recipients have positive behavioral intention toward MOW programs.

A genome-wide longitudinal transcriptome analysis of the aging model Podospora anserina.

PubMed

Philipp, Oliver; Hamann, Andrea; Servos, Jörg; Werner, Alexandra; Koch, Ina; Osiewacz, Heinz D

2013-01-01

Aging of biological systems is controlled by various processes which have a potential impact on gene expression. Here we report a genome-wide transcriptome analysis of the fungal aging model Podospora anserina. Total RNA of three individuals of defined age were pooled and analyzed by SuperSAGE (serial analysis of gene expression). A bioinformatics analysis identified different molecular pathways to be affected during aging. While the abundance of transcripts linked to ribosomes and to the proteasome quality control system were found to decrease during aging, those associated with autophagy increase, suggesting that autophagy may act as a compensatory quality control pathway. Transcript profiles associated with the energy metabolism including mitochondrial functions were identified to fluctuate during aging. Comparison of wild-type transcripts, which are continuously down-regulated during aging, with those down-regulated in the long-lived, copper-uptake mutant grisea, validated the relevance of age-related changes in cellular copper metabolism. Overall, we (i) present a unique age-related data set of a longitudinal study of the experimental aging model P. anserina which represents a reference resource for future investigations in a variety of organisms, (ii) suggest autophagy to be a key quality control pathway that becomes active once other pathways fail, and (iii) present testable predictions for subsequent experimental investigations.

Impacts of Energy Sector Emissions on PM2.5 Air Quality in Northern India

NASA Astrophysics Data System (ADS)

Karambelas, A. N.; Kiesewetter, G.; Heyes, C.; Holloway, T.

2015-12-01

India experiences high concentrations of fine particulate matter (PM2.5), and several Indian cities currently rank among the world's most polluted cities. With ongoing urbanization and a growing economy, emissions from different energy sectors remain major contributors to air pollution in India. Emission sectors impact ambient air quality differently due to spatial distribution (typical urban vs. typical rural sources) as well as source height characteristics (low-level vs. high stack sources). This study aims to assess the impacts of emissions from three distinct energy sectors—transportation, domestic, and electricity—on ambient PM2.5­­ in northern India using an advanced air quality analysis framework based on the U.S. EPA Community Multi-Scale Air Quality (CMAQ) model. Present air quality conditions are simulated using 2010 emissions from the Greenhouse Gas-Air Pollution Interaction and Synergies (GAINS) model. Modeled PM2.5 concentrations are compared with satellite observations of aerosol optical depth (AOD) from the Moderate Imaging Spectroradiometer (MODIS) for 2010. Energy sector emissions impacts on future (2030) PM2.5 are evaluated with three sensitivity simulations, assuming maximum feasible reduction technologies for either transportation, domestic, or electricity sectors. These simulations are compared with a business as usual 2030 simulation to assess relative sectoral impacts spatially and temporally. CMAQ is modeled at 12km by 12km and include biogenic emissions from the Community Land Model coupled with the Model of Emissions of Gases and Aerosols in Nature (CLM-MEGAN), biomass burning emissions from the Global Fires Emissions Database (GFED), and ERA-Interim meteorology generated with the Weather Research and Forecasting (WRF) model for 2010 to quantify the impact of modified anthropogenic emissions on ambient PM2.5 concentrations. Energy sector emissions analysis supports decision-making to improve future air quality and public health in India.

A quality improvement management model for renal care.

PubMed

Vlchek, D L; Day, L M

1991-04-01

The purpose of this article is to explore the potential for applying the theory and tools of quality improvement (total quality management) in the renal care setting. We believe that the coupling of the statistical techniques used in the Deming method of quality improvement, with modern approaches to outcome and process analysis, will provide the renal care community with powerful tools, not only for improved quality (i.e., reduced morbidity and mortality), but also for technology evaluation and resource allocation.

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.

A modal analysis of flexible aircraft dynamics with handling qualities implications

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1983-01-01

A multivariable modal analysis technique is presented for evaluating flexible aircraft dynamics, focusing on meaningful vehicle responses to pilot inputs and atmospheric turbulence. Although modal analysis is the tool, vehicle time response is emphasized, and the analysis is performed on the linear, time-domain vehicle model. In evaluating previously obtained experimental pitch tracking data for a family of vehicle dynamic models, it is shown that flexible aeroelastic effects can significantly affect pitch attitude handling qualities. Consideration of the eigenvalues alone, of both rigid-body and aeroelastic modes, does not explain the simulation results. Modal analysis revealed, however, that although the lowest aeroelastic mode frequency was still three times greater than the short-period frequency, the rigid-body attitude response was dominated by this aeroelastic mode. This dominance was defined in terms of the relative magnitudes of the modal residues in selected vehicle responses.

A methodology model for quality management in a general hospital.

PubMed

Stern, Z; Naveh, E

1997-01-01

A reappraisal is made of the relevance of industrial modes of quality management to the issues of medical care. Analysis of the nature of medical care, which differentiates it from the supplier-client relationships of industry, presents the main intrinsic characteristics, which create problems in application of the industrial quality management approaches to medical care. Several examples are the complexity of the relationship between the medical action and the result obtained, the client's nonacceptance of economic profitability as a value in his medical care, and customer satisfaction biased by variable standards of knowledge. The real problems unique to hospitals are addressed, and a methodology model for their quality management is offered. Included is a sample of indicator vectors, measurements of quality care, cost of medical care, quality of service, and human resources. These are based on the trilogy of planning quality, quality control, and improving quality. The conclusions confirm the inadequacy of industrial quality management approaches for medical institutions and recommend investment in formulation of appropriate concepts.

Performance assessment of retrospective meteorological inputs for use in air quality modeling during TexAQS 2006

NASA Astrophysics Data System (ADS)

Ngan, Fong; Byun, Daewon; Kim, Hyuncheol; Lee, Daegyun; Rappenglück, Bernhard; Pour-Biazar, Arastoo

2012-07-01

To achieve more accurate meteorological inputs than was used in the daily forecast for studying the TexAQS 2006 air quality, retrospective simulations were conducted using objective analysis and 3D/surface analysis nudging with surface and upper observations. Model ozone using the assimilated meteorological fields with improved wind fields shows better agreement with the observation compared to the forecasting results. In the post-frontal conditions, important factors for ozone modeling in terms of wind patterns are the weak easterlies in the morning for bringing in industrial emissions to the city and the subsequent clockwise turning of the wind direction induced by the Coriolis force superimposing the sea breeze, which keeps pollutants in the urban area. Objective analysis and nudging employed in the retrospective simulation minimize the wind bias but are not able to compensate for the general flow pattern biases inherited from large scale inputs. By using an alternative analyses data for initializing the meteorological simulation, the model can re-produce the flow pattern and generate the ozone peak location closer to the reality. The inaccurate simulation of precipitation and cloudiness cause over-prediction of ozone occasionally. Since there are limitations in the meteorological model to simulate precipitation and cloudiness in the fine scale domain (less than 4-km grid), the satellite-based cloud is an alternative way to provide necessary inputs for the retrospective study of air quality.

Associations between Perceived HIV Stigma and Quality of Life at the Dyadic Lvel: The Actor-Partner Interdependence Model

PubMed Central

Liu, Hongjie; Xu, Yongfang; Lin, Xinjin; Shi, Jian; Chen, Shiyi

2013-01-01

Background Few studies have investigated the relationship between HIV-related stigma and quality life at the dyadic level. The objective of this study was to examine the actor and partner effects of stigma that was perceived by people living with HIV/AIDS (PLWHAs) and caregivers on quality of life at the dyadic level. Method A survey was conducted among 148 dyads consisting of one PLWHA and one caregiver (296 participants) in Nanning, China. The interdependent relationship between a pair of dyadic members that influences the associations between stigma and quality of life was analyzed, using an innovative dyadic analysis technique: the Actor-Partner Interdependence Model (APIM). Results We found in this dyadic analysis that (1) PLWHAs compared to their caregivers exhibited a higher level of perceived HIV stigma and lower level of quality of life measured in four domains; (2) both PLWHAs' and caregivers' perceived HIV stigma influenced their own quality of life; (3) The quality of life was not substantially influenced by their partners' perceived stigma; and (4) Both actor and partner effects of stigma on quality of life were similar among PLWHAs and their caregivers. Conclusion As HIV stigma and quality of life are complex phenomena rooted in cultures, intervention programs should be carefully planned based on social or cognitive theories and should be culturally adopted. PMID:23383343

Associations between perceived HIV stigma and quality of life at the dyadic level: the actor-partner interdependence model.

PubMed

Liu, Hongjie; Xu, Yongfang; Lin, Xinjin; Shi, Jian; Chen, Shiyi

2013-01-01

Few studies have investigated the relationship between HIV-related stigma and quality life at the dyadic level. The objective of this study was to examine the actor and partner effects of stigma that was perceived by people living with HIV/AIDS (PLWHAs) and caregivers on quality of life at the dyadic level. A survey was conducted among 148 dyads consisting of one PLWHA and one caregiver (296 participants) in Nanning, China. The interdependent relationship between a pair of dyadic members that influences the associations between stigma and quality of life was analyzed, using an innovative dyadic analysis technique: the Actor-Partner Interdependence Model (APIM). We found in this dyadic analysis that (1) PLWHAs compared to their caregivers exhibited a higher level of perceived HIV stigma and lower level of quality of life measured in four domains; (2) both PLWHAs' and caregivers' perceived HIV stigma influenced their own quality of life; (3) The quality of life was not substantially influenced by their partners' perceived stigma; and (4) Both actor and partner effects of stigma on quality of life were similar among PLWHAs and their caregivers. As HIV stigma and quality of life are complex phenomena rooted in cultures, intervention programs should be carefully planned based on social or cognitive theories and should be culturally adopted.

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

Spatial and temporal variations in the relationship between lake water surface temperatures and water quality - A case study of Dianchi Lake.

PubMed

Yang, Kun; Yu, Zhenyu; Luo, Yi; Yang, Yang; Zhao, Lei; Zhou, Xiaolu

2018-05-15

Global warming and rapid urbanization in China have caused a series of ecological problems. One consequence has involved the degradation of lake water environments. Lake surface water temperatures (LSWTs) significantly shape water ecological environments and are highly correlated with the watershed ecosystem features and biodiversity levels. Analysing and predicting spatiotemporal changes in LSWT and exploring the corresponding impacts on water quality is essential for controlling and improving the ecological water environment of watersheds. In this study, Dianchi Lake was examined through an analysis of 54 water quality indicators from 10 water quality monitoring sites from 2005 to 2016. Support vector regression (SVR), Principal Component Analysis (PCA) and Back Propagation Artificial Neural Network (BPANN) methods were applied to form a hybrid forecasting model. A geospatial analysis was conducted to observe historical LSWTs and water quality changes for Dianchi Lake from 2005 to 2016. Based on the constructed model, LSWTs and changes in water quality were simulated for 2017 to 2020. The relationship between LSWTs and water quality thresholds was studied. The results show limited errors and highly generalized levels of predictive performance. In addition, a spatial visualization analysis shows that from 2005 to 2020, the chlorophyll-a (Chla), chemical oxygen demand (COD) and total nitrogen (TN) diffused from north to south and that ammonia nitrogen (NH 3 -N) and total phosphorus (TP) levels are increases in the northern part of Dianchi Lake, where the LSWT levels exceed 17°C. The LSWT threshold is 17.6-18.53°C, which falls within the threshold for nutritional water quality, but COD and TN levels fall below V class water quality standards. Transparency (Trans), COD, biochemical oxygen demand (BOD) and Chla levels present a close relationship with LSWT, and LSWTs are found to fundamentally affect lake cyanobacterial blooms. Copyright © 2017 Elsevier B.V. All rights reserved.

Applying air pollution modelling within a multi-criteria decision analysis framework to evaluate UK air quality policies

NASA Astrophysics Data System (ADS)

Chalabi, Zaid; Milojevic, Ai; Doherty, Ruth M.; Stevenson, David S.; MacKenzie, Ian A.; Milner, James; Vieno, Massimo; Williams, Martin; Wilkinson, Paul

2017-10-01

A decision support system for evaluating UK air quality policies is presented. It combines the output from a chemistry transport model, a health impact model and other impact models within a multi-criteria decision analysis (MCDA) framework. As a proof-of-concept, the MCDA framework is used to evaluate and compare idealized emission reduction policies in four sectors (combustion in energy and transformation industries, non-industrial combustion plants, road transport and agriculture) and across six outcomes or criteria (mortality, health inequality, greenhouse gas emissions, biodiversity, crop yield and air quality legal compliance). To illustrate a realistic use of the MCDA framework, the relative importance of the criteria were elicited from a number of stakeholders acting as proxy policy makers. In the prototype decision problem, we show that reducing emissions from industrial combustion (followed very closely by road transport and agriculture) is more advantageous than equivalent reductions from the other sectors when all the criteria are taken into account. Extensions of the MCDA framework to support policy makers in practice are discussed.

Simulation-based optimization framework for reuse of agricultural drainage water in irrigation.

PubMed

Allam, A; Tawfik, A; Yoshimura, C; Fleifle, A

2016-05-01

A simulation-based optimization framework for agricultural drainage water (ADW) reuse has been developed through the integration of a water quality model (QUAL2Kw) and a genetic algorithm. This framework was applied to the Gharbia drain in the Nile Delta, Egypt, in summer and winter 2012. First, the water quantity and quality of the drain was simulated using the QUAL2Kw model. Second, uncertainty analysis and sensitivity analysis based on Monte Carlo simulation were performed to assess QUAL2Kw's performance and to identify the most critical variables for determination of water quality, respectively. Finally, a genetic algorithm was applied to maximize the total reuse quantity from seven reuse locations with the condition not to violate the standards for using mixed water in irrigation. The water quality simulations showed that organic matter concentrations are critical management variables in the Gharbia drain. The uncertainty analysis showed the reliability of QUAL2Kw to simulate water quality and quantity along the drain. Furthermore, the sensitivity analysis showed that the 5-day biochemical oxygen demand, chemical oxygen demand, total dissolved solids, total nitrogen and total phosphorous are highly sensitive to point source flow and quality. Additionally, the optimization results revealed that the reuse quantities of ADW can reach 36.3% and 40.4% of the available ADW in the drain during summer and winter, respectively. These quantities meet 30.8% and 29.1% of the drainage basin requirements for fresh irrigation water in the respective seasons. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rasch analysis of the carers quality of life questionnaire for parkinsonism.

PubMed

Pillas, Marios; Selai, Caroline; Schrag, Anette

2017-03-01

To assess the psychometric properties of the Carers Quality of Life Questionnaire for Parkinsonism using a Rasch modeling approach and determine the optimal cut-off score. We performed a Rasch analysis of the survey answers of 430 carers of patients with atypical parkinsonism. All of the scale items demonstrated acceptable goodness of fit to the Rasch model. The scale was unidimensional and no notable differential item functioning was detected in the items regarding age and disease type. Rating categories were functioning adequately in all scale items. The scale had high reliability (.95) and construct validity and a high degree of precision, distinguishing between 5 distinct groups of carers with different levels of quality of life. A cut-off score of 62 was found to have the optimal screening accuracy based on Hospital Anxiety and Depression Scale subscores. The results suggest that the Carers Quality of Life Questionnaire for Parkinsonism is a useful scale to assess carers' quality of life and allows analyses requiring interval scaling of variables. © 2016 International Parkinson and Movement Disorder Society. © 2016 International Parkinson and Movement Disorder Society.

“Skill of Generalized Additive Model to Detect PM2.5 Health ...

EPA Pesticide Factsheets

Summary. Measures of health outcomes are collinear with meteorology and air quality, making analysis of connections between human health and air quality difficult. The purpose of this analysis was to determine time scales and periods shared by the variables of interest (and by implication scales and periods that are not shared). Hospital admissions, meteorology (temperature and relative humidity), and air quality (PM2.5 and daily maximum ozone) for New York City during the period 2000-2006 were decomposed into temporal scales ranging from 2 days to greater than two years using a complex wavelet transform. Health effects were modeled as functions of the wavelet components of meteorology and air quality using the generalized additive model (GAM) framework. This simulation study showed that GAM is extremely successful at extracting and estimating a health effect embedded in a dataset. It also shows that, if the objective in mind is to estimate the health signal but not to fully explain this signal, a simple GAM model with a single confounder (calendar time) whose smooth representation includes a sufficient number of constraints is as good as a more complex model.Introduction. In the context of wavelet regression, confounding occurs when two or more independent variables interact with the dependent variable at the same frequency. Confounding also acts on a variety of time scales, changing the PM2.5 coefficient (magnitude and sign) and its significance ac

Simulation of Streamflow and Selected Water-Quality Constituents through a Model of the Onondaga Lake Basin, Onondaga County, New York - A Guide to Model Application

USGS Publications Warehouse

Coon, William F.

2008-01-01

A computer model of hydrologic and water-quality processes of the Onondaga Lake basin in Onondaga County, N.Y., was developed during 2003-07 to assist water-resources managers in making basin-wide management decisions that could affect peak flows and the water quality of tributaries to Onondaga Lake. The model was developed with the Hydrological Simulation Program-Fortran (HSPF) and was designed to allow simulation of proposed or hypothetical land-use changes, best-management practices (BMPs), and instream stormwater-detention basins such that their effects on flows and loads of suspended sediment, orthophosphate, total phosphorus, ammonia, organic nitrogen, and nitrate could be analyzed. Extreme weather conditions, such as intense storms and prolonged droughts, can be simulated through manipulation of the precipitation record. Model results obtained from different scenarios can then be compared and analyzed through an interactive computer program known as Generation and Analysis of Model Simulation Scenarios for Watersheds (GenScn). Background information on HSPF and GenScn is presented to familiarize the user with these two programs. Step-by-step examples are provided on (1) the creation of land-use, BMP, and stormflow-detention scenarios for simulation by the HSPF model, and (2) the analysis of simulation results through GenScn.

Examining the Influence of Selected Factors on Perceived Co-Op Work-Term Quality from a Student Perspective

ERIC Educational Resources Information Center

Drewery, David; Nevison, Colleen; Pretti, T. Judene; Cormier, Lauren; Barclay, Sage; Pennaforte, Antoine

2016-01-01

This study discusses and tests a conceptual model of co-op work-term quality from a student perspective. Drawing from an earlier exploration of co-op students' perceptions of work-term quality, variables related to role characteristics, interpersonal dynamics, and organizational elements were used in a multiple linear regression analysis to…

Tamoxifen for breast cancer risk reduction: impact of alternative approaches to quality-of-life adjustment on cost-effectiveness analysis.

PubMed

Melnikow, Joy; Birch, Stephen; Slee, Christina; McCarthy, Theodore J; Helms, L Jay; Kuppermann, Miriam

2008-09-01

In cost-effectiveness analysis (CEA), the effects of health-care interventions on multiple health dimensions typically require consideration of both quantity and quality of life. To explore the impact of alternative approaches to quality-of-life adjustment using patient preferences (utilities) on the outcome of a CEA on use of tamoxifen for breast cancer risk reduction. A state transition Markov model tracked hypothetical cohorts of women who did or did not take 5 years of tamoxifen for breast cancer risk reduction. Incremental quality-adjusted effectiveness and cost-effectiveness ratios (ICERs) for models including and excluding a utility adjustment for menopausal symptoms were compared with each other and to a global utility model. Two hundred fifty-five women aged 50 and over with estimated 5-year breast cancer risk >or=1.67% participated in utility assessment interviews. Standard gamble utilities were assessed for specified tamoxifen-related health outcomes, current health, and for a global assessment of possible outcomes of tamoxifen use. Inclusion of a utility for menopausal symptoms in the outcome-specific models substantially increased the ICER; at the threshold 5-year breast cancer risk of 1.67%, tamoxifen was dominated. When a global utility for tamoxifen was used in place of outcome-specific utilities, tamoxifen was dominated under all circumstances. CEAs may be profoundly affected by the types of outcomes considered for quality-of-life adjustment and how these outcomes are grouped for utility assessment. Comparisons of ICERs across analyses must consider effects of different approaches to using utilities for quality-of-life adjustment.

Variation of Water Quality Parameters with Siltation Depth for River Ichamati Along International Border with Bangladesh Using Multivariate Statistical Techniques

NASA Astrophysics Data System (ADS)

Roy, P. K.; Pal, S.; Banerjee, G.; Biswas Roy, M.; Ray, D.; Majumder, A.

2014-12-01

River is considered as one of the main sources of freshwater all over the world. Hence analysis and maintenance of this water resource is globally considered a matter of major concern. This paper deals with the assessment of surface water quality of the Ichamati river using multivariate statistical techniques. Eight distinct surface water quality observation stations were located and samples were collected. For the samples collected statistical techniques were applied to the physico-chemical parameters and depth of siltation. In this paper cluster analysis is done to determine the relations between surface water quality and siltation depth of river Ichamati. Multiple regressions and mathematical equation modeling have been done to characterize surface water quality of Ichamati river on the basis of physico-chemical parameters. It was found that surface water quality of the downstream river was different from the water quality of the upstream. The analysis of the water quality parameters of the Ichamati river clearly indicate high pollution load on the river water which can be accounted to agricultural discharge, tidal effect and soil erosion. The results further reveal that with the increase in depth of siltation, water quality degraded.

Preface to QoIS 2009

NASA Astrophysics Data System (ADS)

Comyn-Wattiau, Isabelle; Thalheim, Bernhard

Quality assurance is a growing research domain within the Information Systems (IS) and Conceptual Modeling (CM) disciplines. Ongoing research on quality in IS and CM is highly diverse and encompasses theoretical aspects including quality definition and quality models, and practical/empirical aspects such as the development of methods, approaches and tools for quality measurement and improvement. Current research on quality also includes quality characteristics definitions, validation instruments, methodological and development approaches to quality assurance during software and information systems development, quality monitors, quality assurance during information systems development processes and practices, quality assurance both for data and (meta)schemata, quality support for information systems data import and export, quality of query answering, and cost/benefit analysis of quality assurance processes. Quality assurance is also depending on the application area and the specific requirements in applications such as health sector, logistics, public sector, financial sector, manufacturing, services, e-commerce, software, etc. Furthermore, quality assurance must also be supported for data aggregation, ETL processes, web content management and other multi-layered applications. Quality assurance is typically requiring resources and has therefore beside its benefits a computational and economical trade-off. It is therefore also based on compromising between the value of quality data and the cost for quality assurance.

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.

Pharmaceutical Price Controls and Minimum Efficacy Regulation: Evidence from the United States and Italy

PubMed Central

Atella, Vincenzo; Bhattacharya, Jay; Carbonari, Lorenzo

2012-01-01

Objective This article examines the relationship between drug price and drug quality and how it varies across two of the most common regulatory regimes in the pharmaceutical market: minimum efficacy standards (MES) and a mix of MES and price control mechanisms (MES + PC). Data Sources Our primary data source is the Tufts-New England Medical Center-Cost Effectiveness Analysis Registry which have been merged with price data taken from MEPS (for the United States) and AIFA (for Italy). Study Design Through a simple model of adverse selection we model the interaction between firms, heterogeneous buyers, and the regulator. Principal Findings The theoretical analysis provides two results. First, an MES regime provides greater incentives to produce high-quality drugs. Second, an MES + PC mix reduces the difference in price between the highest and lowest quality drugs on the market. Conclusion The empirical analysis based on United States and Italian data corroborates these results. PMID:22091623

Integrating Kano’s Model into Quality Function Deployment for Product Design: A Comprehensive Review

NASA Astrophysics Data System (ADS)

Ginting, Rosnani; Hidayati, Juliza; Siregar, Ikhsan

2018-03-01

Many methods and techniques are adopted by some companies to improve the competitiveness through the fulfillment of customer satisfaction by enhancement and improvement the product design quality. Over the past few years, several researcher have studied extensively combining Quality Function Deployment and Kano’s model as design techniques by focusing on translating consumer desires into a product design. This paper presents a review and analysis of several literatures that associated to the integration methodology of Kano into the QFD process. Various of international journal articles were selected, collected and analyzed through a number of relevant scientific publications. In-depth analysis was performed, and focused in this paper on the results, advantages and drawbacks of its methodology. In addition, this paper also provides the analysis that acquired in this study related to the development of the methodology. It is hopedd this paper can be a reference for other researchers and manufacturing companies to implement the integration method of QFD- Kano for product design.

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

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)

A FAST BAYESIAN METHOD FOR UPDATING AND FORECASTING HOURLY OZONE LEVELS

EPA Science Inventory

A Bayesian hierarchical space-time model is proposed by combining information from real-time ambient AIRNow air monitoring data, and output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model. A model validation analysis shows...

Treatment strategies for pelvic organ prolapse: a cost-effectiveness analysis.

PubMed

Hullfish, Kathie L; Trowbridge, Elisa R; Stukenborg, George J

2011-05-01

To compare the relative cost effectiveness of treatment decision alternatives for post-hysterectomy pelvic organ prolapse (POP). A Markov decision analysis model was used to assess and compare the relative cost effectiveness of expectant management, use of a pessary, and surgery for obtaining months of quality-adjusted life over 1 year. Sensitivity analysis was conducted to determine whether the results depended on specific estimates of patient utilities for pessary use, probabilities for complications and other events, and estimated costs. Only two treatment alternatives were found to be efficient choices: initial pessary use and vaginal reconstructive surgery (VRS). Pessary use (including patients that eventually transitioned to surgery) achieved 10.4 quality-adjusted months, at a cost of $10,000 per patient, while VRS obtained 11.4 quality-adjusted months, at $15,000 per patient. Sensitivity analysis demonstrated that these baseline results depended on several key estimates in the model. This analysis indicates that pessary use and VRS are the most cost-effective treatment alternatives for treating post-hysterectomy vaginal prolapse. Additional research is needed to standardize POP outcomes and complications, so that healthcare providers can best utilize cost information in balancing the risks and benefits of their treatment decisions.

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.

Cost Models for MMC Manufacturing Processes

NASA Technical Reports Server (NTRS)

Elzey, Dana M.; Wadley, Haydn N. G.

1996-01-01

Processes for the manufacture of advanced metal matrix composites are rapidly approaching maturity in the research laboratory and there is growing interest in their transition to industrial production. However, research conducted to date has almost exclusively focused on overcoming the technical barriers to producing high-quality material and little attention has been given to the economical feasibility of these laboratory approaches and process cost issues. A quantitative cost modeling (QCM) approach was developed to address these issues. QCM are cost analysis tools based on predictive process models relating process conditions to the attributes of the final product. An important attribute, of the QCM approach is the ability to predict the sensitivity of material production costs to product quality and to quantitatively explore trade-offs between cost and quality. Applications of the cost models allow more efficient direction of future MMC process technology development and a more accurate assessment of MMC market potential. Cost models were developed for two state-of-the art metal matrix composite (MMC) manufacturing processes: tape casting and plasma spray deposition. Quality and Cost models are presented for both processes and the resulting predicted quality-cost curves are presented and discussed.

Technical efficiency of nursing homes: do five-star quality ratings matter?

PubMed

Dulal, Rajendra

2017-02-28

This study investigates associations between five-star quality ratings and technical efficiency of nursing homes. The sample consists of a balanced panel of 338 nursing homes in California from 2009 through 2013 and uses two-stage data envelopment (DEA) analysis. The first-stage applies an input oriented variable returns to scale DEA analysis. The second-stage uses a left censored random-effect Tobit regression model. The five-star quality ratings i.e., health inspections, quality measures, staffing available on the Nursing Home Compare website are divided into two categories: outcome and structure form of quality. Results show that quality measures ratings and health inspection ratings, used as outcome form of quality, are not associated with mean technical efficiency. These quality ratings, however, do affect the technical efficiency of a particular nursing home and hence alter the ranking of nursing homes based on efficiency scores. Staffing rating, categorized as a structural form of quality, is negatively associated with mean technical efficiency. These findings show that quality dimensions are associated with technical efficiency in different ways, suggesting that multiple dimensions of quality should be included in the efficiency analysis of nursing homes. They also suggest that patient care can be enhanced through investing more in improving care delivery rather than simply raising the number of staff per resident.

Multiphysical simulation analysis of the dislocation structure in germanium single crystals

NASA Astrophysics Data System (ADS)

Podkopaev, O. I.; Artemyev, V. V.; Smirnov, A. D.; Mamedov, V. M.; Sid'ko, A. P.; Kalaev, V. V.; Kravtsova, E. D.; Shimanskii, A. F.

2016-09-01

To grow high-quality germanium crystals is one of the most important problems of growth industry. The dislocation density is an important parameter of the quality of single crystals. The dislocation densities in germanium crystals 100 mm in diameter, which have various shapes of the side surface and are grown by the Czochralski technique, are experimentally measured. The crystal growth is numerically simulated using heat-transfer and hydrodynamics models and the Alexander-Haasen dislocation model in terms of the CGSim software package. A comparison of the experimental and calculated dislocation densities shows that the dislocation model can be applied to study lattice defects in germanium crystals and to improve their quality.

Applying Turbulence Models to Hydroturbine Flows: A Sensitivity Analysis Using the GAMM Francis Turbine

NASA Astrophysics Data System (ADS)

Lewis, Bryan; Cimbala, John; Wouden, Alex

2011-11-01

Turbulence models are generally developed to study common academic geometries, such as flat plates and channels. Creating quality computational grids for such geometries is trivial, and allows stringent requirements to be met for boundary layer grid refinement. However, engineering applications, such as flow through hydroturbines, require the analysis of complex, highly curved geometries. To produce body-fitted grids for such geometries, the mesh quality requirements must be relaxed. Relaxing these requirements, along with the complexity of rotating flows, forces turbulence models to be employed beyond their developed scope. This study explores the solution sensitivity to boundary layer grid quality for various turbulence models and boundary conditions currently implemented in OpenFOAM. The following models are resented: k-omega, k-omega SST, k-epsilon, realizable k-epsilon, and RNG k-epsilon. Standard wall functions, adaptive wall functions, and sub-grid integration are compared using various grid refinements. The chosen geometry is the GAMM Francis Turbine because experimental data and comparison computational results are available for this turbine. This research was supported by a grant from the DoE and a National Defense Science and Engineering Graduate Fellowship.

Study on a pattern classification method of soil quality based on simplified learning sample dataset

USGS Publications Warehouse

Zhang, Jiahua; Liu, S.; Hu, Y.; Tian, Y.

2011-01-01

Based on the massive soil information in current soil quality grade evaluation, this paper constructed an intelligent classification approach of soil quality grade depending on classical sampling techniques and disordered multiclassification Logistic regression model. As a case study to determine the learning sample capacity under certain confidence level and estimation accuracy, and use c-means algorithm to automatically extract the simplified learning sample dataset from the cultivated soil quality grade evaluation database for the study area, Long chuan county in Guangdong province, a disordered Logistic classifier model was then built and the calculation analysis steps of soil quality grade intelligent classification were given. The result indicated that the soil quality grade can be effectively learned and predicted by the extracted simplified dataset through this method, which changed the traditional method for soil quality grade evaluation. ?? 2011 IEEE.

Complementary effect of patient volume and quality of care on hospital cost efficiency.

PubMed

Choi, Jeong Hoon; Park, Imsu; Jung, Ilyoung; Dey, Asoke

2017-06-01

This study explores the direct effect of an increase in patient volume in a hospital and the complementary effect of quality of care on the cost efficiency of U.S. hospitals in terms of patient volume. The simultaneous equation model with three-stage least squares is used to measure the direct effect of patient volume and the complementary effect of quality of care and volume. Cost efficiency is measured with a data envelopment analysis method. Patient volume has a U-shaped relationship with hospital cost efficiency and an inverted U-shaped relationship with quality of care. Quality of care functions as a moderator for the relationship between patient volume and efficiency. This paper addresses the economically important question of the relationship of volume with quality of care and hospital cost efficiency. The three-stage least square simultaneous equation model captures the simultaneous effects of patient volume on hospital quality of care and cost efficiency.

ADVANCEMENTS IN SOURCE-TO-DOSE ANALYSIS OF POPULATION EXPOSURES TO OZONE

EPA Science Inventory

The current study takes advantage of the observations from regional air quality monitoring networks, the data from the NE-OPS (North East Oxidant and Particulate Study) Project in the Philadelphia region, and regional photochemical air quality model predictions to obtain and co...

The Use of Regulatory Air Quality Models to Develop Successful Ozone Attainment Strategies

NASA Astrophysics Data System (ADS)

Canty, T. P.; Salawitch, R. J.; Dickerson, R. R.; Ring, A.; Goldberg, D. L.; He, H.; Anderson, D. C.; Vinciguerra, T.

2015-12-01

The Environmental Protection Agency (EPA) recently proposed lowering the 8-hr ozone standard to between 65-70 ppb. Not all regions of the U.S. are in attainment of the current 75 ppb standard and it is expected that many regions currently in attainment will not meet the future, lower surface ozone standard. Ozone production is a nonlinear function of emissions, biological processes, and weather. Federal and state agencies rely on regulatory air quality models such as the Community Multi-Scale Air Quality (CMAQ) model and Comprehensive Air Quality Model with Extensions (CAMx) to test ozone precursor emission reduction strategies that will bring states into compliance with the National Ambient Air Quality Standards (NAAQS). We will describe various model scenarios that simulate how future limits on emission of ozone precursors (i.e. NOx and VOCs) from sources such as power plants and vehicles will affect air quality. These scenarios are currently being developed by states required to submit a State Implementation Plan to the EPA. Projections from these future case scenarios suggest that strategies intended to control local ozone may also bring upwind states into attainment of the new NAAQS. Ground based, aircraft, and satellite observations are used to ensure that air quality models accurately represent photochemical processes within the troposphere. We will highlight some of the improvements made to the CMAQ and CAMx model framework based on our analysis of NASA observations obtained by the OMI instrument on the Aura satellite and by the DISCOVER-AQ field campaign.

Determination of the optimal training principle and input variables in artificial neural network model for the biweekly chlorophyll-a prediction: a case study of the Yuqiao Reservoir, China.

PubMed

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang

2015-01-01

Predicting the levels of chlorophyll-a (Chl-a) is a vital component of water quality management, which ensures that urban drinking water is safe from harmful algal blooms. This study developed a model to predict Chl-a levels in the Yuqiao Reservoir (Tianjin, China) biweekly using water quality and meteorological data from 1999-2012. First, six artificial neural networks (ANNs) and two non-ANN methods (principal component analysis and the support vector regression model) were compared to determine the appropriate training principle. Subsequently, three predictors with different input variables were developed to examine the feasibility of incorporating meteorological factors into Chl-a prediction, which usually only uses water quality data. Finally, a sensitivity analysis was performed to examine how the Chl-a predictor reacts to changes in input variables. The results were as follows: first, ANN is a powerful predictive alternative to the traditional modeling techniques used for Chl-a prediction. The back program (BP) model yields slightly better results than all other ANNs, with the normalized mean square error (NMSE), the correlation coefficient (Corr), and the Nash-Sutcliffe coefficient of efficiency (NSE) at 0.003 mg/l, 0.880 and 0.754, respectively, in the testing period. Second, the incorporation of meteorological data greatly improved Chl-a prediction compared to models solely using water quality factors or meteorological data; the correlation coefficient increased from 0.574-0.686 to 0.880 when meteorological data were included. Finally, the Chl-a predictor is more sensitive to air pressure and pH compared to other water quality and meteorological variables.

Computer Analysis of Air Pollution from Highways, Streets, and Complex Interchanges

DOT National Transportation Integrated Search

1974-03-01

A detailed computer analysis of air quality for a complex highway interchange was prepared, using an in-house version of the Environmental Protection Agency's Gaussian Highway Line Source Model. This analysis showed that the levels of air pollution n...

Relevance of Regional Hydro-Climatic Projection Data for Hydrodynamics and Water Quality Modelling of the Baltic Sea

NASA Astrophysics Data System (ADS)

Goldenberg, R.; Vigouroux, G.; Chen, Y.; Bring, A.; Kalantari, Z.; Prieto, C.; Destouni, G.

2017-12-01

The Baltic Sea, located in Northern Europe, is one of the world's largest body of brackish water, enclosed and surrounded by nine different countries. The magnitude of climate change may be particularly large in northern regions, and identifying its impacts on vulnerable inland waters and their runoff and nutrient loading to the Baltic Sea is an important and complex task. Exploration of such hydro-climatic impacts is needed to understand potential future changes in physical, ecological and water quality conditions in the regional coastal and marine waters. In this study, we investigate hydro-climatic changes and impacts on the Baltic Sea by synthesizing multi-model climate projection data from the CORDEX regional downscaling initiative (EURO- and Arctic- CORDEX domains, http://www.cordex.org/). We identify key hydro-climatic variable outputs of these models and assess model performance with regard to their projected temporal and spatial change behavior and impacts on different scales and coastal-marine parts, up to the whole Baltic Sea. Model spreading, robustness and impact implications for the Baltic Sea system are investigated for and through further use in simulations of coastal-marine hydrodynamics and water quality based on these key output variables and their change projections. Climate model robustness in this context is assessed by inter-model spreading analysis and observation data comparisons, while projected change implications are assessed by forcing of linked hydrodynamic and water quality modeling of the Baltic Sea based on relevant hydro-climatic outputs for inland water runoff and waterborne nutrient loading to the Baltic sea, as well as for conditions in the sea itself. This focused synthesis and analysis of hydro-climatically relevant output data of regional climate models facilitates assessment of reliability and uncertainty in projections of driver-impact changes of key importance for Baltic Sea physical, water quality and ecological conditions and their future evolution.

Impacts of agricultural land use on biological integrity: A causal analysis

USGS Publications Warehouse

Riseng, C.M.; Wiley, M.J.; Black, R.W.; Munn, M.D.

2011-01-01

Agricultural land use has often been linked to nutrient enrichment, habitat degradation, hydrologic alteration, and loss of biotic integrity in streams. The U.S. Geological Survey's National Water Quality Assessment Program sampled 226 stream sites located in eight agriculture-dominated study units across the United States to investigate the geographic variability and causes of agricultural impacts on stream biotic integrity. In this analysis we used structural equation modeling (SEM) to develop a national and set of regional causal models linking agricultural land use to measured instream conditions. We then examined the direct, indirect, and total effects of agriculture on biotic integrity as it acted through multiple water quality and habitat pathways. In our nation-wide model, cropland affected benthic communities by both altering structural habitats and by imposing water quality-related stresses. Regionspecific modeling demonstrated that geographic context altered the relative importance of causal pathways through which agricultural activities affected stream biotic integrity. Cropland had strong negative total effects on the invertebrate community in the national, Midwest, and Western models, but a very weak effect in the Eastern Coastal Plain model. In theWestern Arid and Eastern Coastal Plain study regions, cropland impacts were transmitted primarily through dissolved water quality contaminants, but in the Midwestern region, they were transmitted primarily through particulate components of water quality. Habitat effects were important in the Western Arid model, but negligible in the Midwest and Eastern Coastal Plain models. The relative effects of riparian forested wetlands also varied regionally, having positive effects on biotic integrity in the Eastern Coastal Plain andWestern Arid region models, but no statistically significant effect in the Midwest. These differences in response to cropland and riparian cover suggest that best management practices and planning for the mitigation of agricultural land use impacts on stream ecosystems should be regionally focused. ?? 2011 by the Ecological Society of America.

Intercomparison of air quality data using principal component analysis, and forecasting of PM₁₀ and PM₂.₅ concentrations using artificial neural networks, in Thessaloniki and Helsinki.

PubMed

Voukantsis, Dimitris; Karatzas, Kostas; Kukkonen, Jaakko; Räsänen, Teemu; Karppinen, Ari; Kolehmainen, Mikko

2011-03-01

In this paper we propose a methodology consisting of specific computational intelligence methods, i.e. principal component analysis and artificial neural networks, in order to inter-compare air quality and meteorological data, and to forecast the concentration levels for environmental parameters of interest (air pollutants). We demonstrate these methods to data monitored in the urban areas of Thessaloniki and Helsinki in Greece and Finland, respectively. For this purpose, we applied the principal component analysis method in order to inter-compare the patterns of air pollution in the two selected cities. Then, we proceeded with the development of air quality forecasting models for both studied areas. On this basis, we formulated and employed a novel hybrid scheme in the selection process of input variables for the forecasting models, involving a combination of linear regression and artificial neural networks (multi-layer perceptron) models. The latter ones were used for the forecasting of the daily mean concentrations of PM₁₀ and PM₂.₅ for the next day. Results demonstrated an index of agreement between measured and modelled daily averaged PM₁₀ concentrations, between 0.80 and 0.85, while the kappa index for the forecasting of the daily averaged PM₁₀ concentrations reached 60% for both cities. Compared with previous corresponding studies, these statistical parameters indicate an improved performance of air quality parameters forecasting. It was also found that the performance of the models for the forecasting of the daily mean concentrations of PM₁₀ was not substantially different for both cities, despite the major differences of the two urban environments under consideration. Copyright © 2011 Elsevier B.V. All rights reserved.

Mid-tropospheric Spectral Length-scale Analysis of Many Constituents from Aircraft, Satellite and Model Results During the 2013 SENEX Field Study.

NASA Astrophysics Data System (ADS)

McKeen, S. A.; Angevine, W. M.; Ahmadov, R.; Frost, G. J.; Kim, S. W.; Cui, Y.; McDonald, B.; Trainer, M.; Holloway, J. S.; Ryerson, T. B.; Peischl, J.; Gambacorta, A.; Barnet, C. D.; Smith, N.; Pierce, R. B.

2016-12-01

This study presents preliminary comparisons of satellite, aircraft, and model variance spectra for meteorological, thermodynamic and gas-phase species collected during the 2013 Southeastern Nexus Air Quality Experiment (SENEX). Fourier analysis of 8 constituents collected at 1 Hz by the NOAA W-P3 aircraft in the 25 to 200 km length-scale range exhibit properties consistent with previous scale dependence studies: when spectra are averaged over several 500 mb flight legs, very linear dependence is found on log-log plots of spectral density versus inverse length-scale. Derived slopes for wind speed, temperature, H2O, CO, CO2, CH4, NOy and O3 all fall within ±30% and close to the slope of -5/3 predicted from dimensional scaling theory of isotropic turbulence. Qualitative differences are seen when a similar analysis, without quality control, is applied to a preliminary set of NUCAPS satellite retrievals over the continental U.S. during SENEX. While 500mb water vapor and column integrated water show slopes close to the -5/3 value in the 200 to 1000 km length-scale range, other quantities show significantly shallower slopes, suggesting the need for rigorous quality control. Results from WRF-Chem regional air quality model simulations at 500mb show the model is unable to account for variance on length-scales less than 6ΔX, where ΔX is the model horizontal resolution (12km). Comparisons with satellite data in the 200 to 1000km range show slopes consistent with the -5/3 power law for species such as CO, CH4 and CO2 that do not undergo reinitialization, suggesting potential for future application.

Meta-analysis genomewide association of pork quality traits: ultimate pH and shear force

USDA-ARS?s Scientific Manuscript database

It is common practice to perform genome-wide association analysis (GWA) using a genomic evaluation model of a single population. Joint analysis of several populations is more difficult. An alternative to joint analysis could be the meta-analysis (MA) of several GWA from independent genomic evaluatio...

Analysis of waste-load assimilative capacity of the Yampa River, Steamboat Springs to Hayden, Routt County, Colorado

USGS Publications Warehouse

Bauer, Daniel P.; Steele, Timothy Doak; Anderson, Richard D.

1978-01-01

An analysis of the waste-load assimilative capacity of the Yampa River from Steamboat Springs to Hayden, Colo., a distance of 38 miles, was made during September 1975 to obtain information on the effects of projected waste loadings on this stream reach. Simulations of effects of waste loadings on streamflow quality were made using a steady-state water-quality model. The simulations were based on 7-day low-flow values with a 10-year recurrence interval and population projections for 2010. Model results for December and September streamflow conditions indicated that the recommended 1978 Colorado and 1976 U.S. Environmental Protection Agency water-quality standard of 0.02 milligram per liter for nonionized ammonia concentration would be exceeded. Model simulations also included the effect of a flow augmentation of 20 cubic feet per second from a proposed upstream reservoir. The permissible ammonia loading in the study reach could be increased approximately 25 percent with this amount of flow augmentation. Simulations of concentrations of dissolved oxygen, fecal-coliform bacteria, and nitrate nitrogen indicated that the State 's water-quality goals proposed for 1978, 1983, or 1985 would not be exceeded. (Woodard-USGS)

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.

Influence of apple pomace inclusion on the process of animal feed pelleting.

PubMed

Maslovarić, Marijana D; Vukmirović, Đuro; Pezo, Lato; Čolović, Radmilo; Jovanović, Rade; Spasevski, Nedeljka; Tolimir, Nataša

2017-08-01

Apple pomace (AP) is the main by-product of apple juice production. Large amounts of this material disposed into landfills can cause serious environmental problems. One of the solutions is to utilise AP as animal feed. The aim of this study was to investigate the impact of dried AP inclusion into model mixtures made from conventional feedstuffs on pellet quality and pellet press performance. Three model mixtures, with different ratios of maize, sunflower meal and AP, were pelleted. Response surface methodology (RSM) was applied when designing the experiment. The simultaneous and interactive effects of apple pomace share (APS) in the mixtures, die thickness (DT) of the pellet press and initial moisture content of the mixtures (M), on pellet quality and production parameters were investigated. Principal component analysis (PCA) and standard score (SS) analysis were applied for comprehensive analysis of the experimental data. The increase in APS led to an improvement of pellet quality parameters: pellet durability index (PDI), hardness (H) and proportion of fines in pellets. The increase in DT and M resulted in pellet quality improvement. The increase in DT and APS resulted in higher energy consumption of the pellet press. APS was the most influential variable for PDI and H calculation, while APS and DT were the most influential variables in the calculation of pellet press energy consumption. PCA showed that the first two principal components could be considered sufficient for data representation. In conclusion, addition of dried AP to feed model mixtures significantly improved the quality of the pellets.

Investigating the Impact of a Metals Foundry on Neighborhood Air Quality through PM2.5 PMF Analysis and Mobile Environmental Odor Diaries App

NASA Astrophysics Data System (ADS)

Espinoza, D.; Clayton, I.; George, L. A.

2015-12-01

Chapman Elementary School in Portland, OR was identified by USA Today as being in the 2nd percentile of schools in the nation for poor air quality. This ranking was based on the EPA Risk-Screening Environmental Indicators (RSEI) model using the EPA's Toxics Release Inventory (TRI) program. The metals foundry identified in the report as the leading contributor to the poor air quality at Chapman currently meets its Title V permit and reports these permitted emissions to the TRI program. However, the poor air quality ranking is based on models that rely on emissions from permits and are not necessarily reflective of actual emissions. Several observational approaches were employed to assess the potential source contributors to air quality at Chapman. Two MiniVol Tactical Air Samplers (TAS) were co-located 1km from the facility at Chapman Elementary to sample according to the EPA six-day monitoring schedule for one year, filters were analyzed for mass and metals via XRF. Ogawa NO2 samplers were placed at various points around the Chapman neighborhood to develop an NO2 high-density measurement campaign to assess pollutant transport. In addition, a novel mobile environmental odor diaries app was developed and deployed to collect and geo-locate resident observation of odors. All observations were analyzed through mapping, dispersion modeling (AERMOD) and positive-matrix-factorization (PMF) analysis. This multi-dimensional analysis is designed to provide a framework for future studies to address increasing citizen concern about neighborhood level pollution.

[Perceived quality in hospitals of the Andalusia Healthcare System. The case of neurosurgery departments].

PubMed

Cordero Tous, N; Horcajadas Almansa, Á; Bermúdez González, G J; Tous Zamora, D

2014-01-01

To analyse the characteristics of the perceived quality in hospitals of the Andalusia healthcare system and compare this with that in Andalusian Neurosurgery departments. Randomised surveys, adjusted for working age, were performed in Andalusia using a telephone questionnaire based on the SERVQUAL model with the appropriate modification, with the subsequent selection of a subgroup associated with neurosurgery. Perceived quality was classified as; technical, functional and infrastructure quality. The overall satisfaction was 76.3%. Frequency analysis found that variables related to the technical quality (good doctors, successful operations, trained staff, etc.) obtained more favourable outcomes. Those related to time (wait, consulting, organizing schedules) obtained worse outcomes. The care of families variables obtained poor results. There was no difference between the overall Andalusian healthcare system and neurosurgery departments. In the mean analysis, women and older people gave more favourable responses, especially for variables related to infrastructure quality. In the "cluster" analysis, there were more favourable responses by elderly people, with no differences in gender (P<.009). There is no difference in perceived quality between the Andalusian healthcare system overall and neurosurgery departments. The perceived quality of the Andalusian healthcare system is higher in the elderly people. The analysis of perceived quality is useful for promoting projects to improve clinical management. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

Analysis of the impact of simulation model simplifications on the quality of low-energy buildings simulation results

NASA Astrophysics Data System (ADS)

Klimczak, Marcin; Bojarski, Jacek; Ziembicki, Piotr; Kęskiewicz, Piotr

2017-11-01

The requirements concerning energy performance of buildings and their internal installations, particularly HVAC systems, have been growing continuously in Poland and all over the world. The existing, traditional calculation methods following from the static heat exchange model are frequently not sufficient for a reasonable heating design of a building. Both in Poland and elsewhere in the world, methods and software are employed which allow a detailed simulation of the heating and moisture conditions in a building, and also an analysis of the performance of HVAC systems within a building. However, these systems are usually difficult in use and complex. In addition, the development of a simulation model that is sufficiently adequate to the real building requires considerable time involvement of a designer, is time-consuming and laborious. A simplification of the simulation model of a building renders it possible to reduce the costs of computer simulations. The paper analyses in detail the effect of introducing a number of different variants of the simulation model developed in Design Builder on the quality of final results obtained. The objective of this analysis is to find simplifications which allow obtaining simulation results which have an acceptable level of deviations from the detailed model, thus facilitating a quick energy performance analysis of a given building.

78 FR 15664 - Approval and Promulgation of Air Quality Implementation Plans; New Mexico; Interstate Transport...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-12

... technical analysis supporting New Mexico's conclusion as recommended by EPA's guidance memorandum that... modeling technical analyses are available, but EPA does not believe that modeling is necessarily required...)(2)(D)(i)(I) for the 2006 PM 2.5 NAAQS in several ways. It takes into account the technical analysis...

MODELS-3 INSTALLATION PROCEDURES FOR A PC WITH AN NT OPERATING SYSTEM (MODELS-3 VERSION 4.0)

EPA Science Inventory

Models-3 is a flexible software system designed to simplify the development and use of air quality models and other environmental decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of at...

MODELS-3 INSTALLATION PROCEDURES FOR A PERSONAL COMPUTER WITH A NT OPERATING SYSTEM (MODELS-3 VERSION 4.1)

EPA Science Inventory

Models-3 is a flexible system designed to simplify the development and use of air quality models and other environmental decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheric...

Reporting and methodological quality of survival analysis in articles published in Chinese oncology journals.

PubMed

Zhu, Xiaoyan; Zhou, Xiaobin; Zhang, Yuan; Sun, Xiao; Liu, Haihua; Zhang, Yingying

2017-12-01

Survival analysis methods have gained widespread use in the filed of oncology. For achievement of reliable results, the methodological process and report quality is crucial. This review provides the first examination of methodological characteristics and reporting quality of survival analysis in articles published in leading Chinese oncology journals.To examine methodological and reporting quality of survival analysis, to identify some common deficiencies, to desirable precautions in the analysis, and relate advice for authors, readers, and editors.A total of 242 survival analysis articles were included to be evaluated from 1492 articles published in 4 leading Chinese oncology journals in 2013. Articles were evaluated according to 16 established items for proper use and reporting of survival analysis.The application rates of Kaplan-Meier, life table, log-rank test, Breslow test, and Cox proportional hazards model (Cox model) were 91.74%, 3.72%, 78.51%, 0.41%, and 46.28%, respectively, no article used the parametric method for survival analysis. Multivariate Cox model was conducted in 112 articles (46.28%). Follow-up rates were mentioned in 155 articles (64.05%), of which 4 articles were under 80% and the lowest was 75.25%, 55 articles were100%. The report rates of all types of survival endpoint were lower than 10%. Eleven of 100 articles which reported a loss to follow-up had stated how to treat it in the analysis. One hundred thirty articles (53.72%) did not perform multivariate analysis. One hundred thirty-nine articles (57.44%) did not define the survival time. Violations and omissions of methodological guidelines included no mention of pertinent checks for proportional hazard assumption; no report of testing for interactions and collinearity between independent variables; no report of calculation method of sample size. Thirty-six articles (32.74%) reported the methods of independent variable selection. The above defects could make potentially inaccurate, misleading of the reported results, or difficult to interpret.There are gaps in the conduct and reporting of survival analysis in studies published in Chinese oncology journals, severe deficiencies were noted. More endorsement by journals of the report guideline for survival analysis may improve articles quality, and the dissemination of reliable evidence to oncology clinicians. We recommend authors, readers, reviewers, and editors to consider survival analysis more carefully and cooperate more closely with statisticians and epidemiologists. Copyright © 2017 The Authors. Published by Wolters Kluwer Health, Inc. All rights reserved.

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...

A systematic review of Markov models evaluating multicomponent disease management programs in diabetes.

PubMed

Kirsch, Florian

2015-01-01

Diabetes is the most expensive chronic disease; therefore, disease management programs (DMPs) were introduced. The aim of this review is to determine whether Markov models are adequate to evaluate the cost-effectiveness of complex interventions such as DMPs. Additionally, the quality of the models was evaluated using Philips and Caro quality appraisals. The five reviewed models incorporated the DMP into the model differently: two models integrated effectiveness rates derived from one clinical trial/meta-analysis and three models combined interventions from different sources into a DMP. The results range from cost savings and a QALY gain to costs of US$85,087 per QALY. The Spearman's rank coefficient assesses no correlation between the quality appraisals. With restrictions to the data selection process, Markov models are adequate to determine the cost-effectiveness of DMPs; however, to allow prioritization of medical services, more flexibility in the models is necessary to enable the evaluation of single additional interventions.

[Establishment of a 3D finite element model of human skull using MSCT images and mimics software].

PubMed

Huang, Ping; Li, Zheng-dong; Shao, Yu; Zou, Dong-hua; Liu, Ning-guo; Li, Li; Chen, Yuan-yuan; Wan, Lei; Chen, Yi-jiu

2011-02-01

To establish a human 3D finite element skull model, and to explore its value in biomechanics analysis. The cadaveric head was scanned and then 3D skull model was created using Mimics software based on 2D CT axial images. The 3D skull model was optimized by preprocessor along with creation of the surface and volume meshes. The stress changes, after the head was struck by an object or the head hit the ground directly, were analyzed using ANSYS software. The original 3D skull model showed a large number of triangles with a poor quality and high similarity with the real head, while the optimized model showed high quality surface and volume meshes with a small number of triangles comparatively. The model could show the local and global stress changes effectively. The human 3D skull model can be established using MSCT and Mimics software and provides a good finite element model for biomechanics analysis. This model may also provide a base for the study of head stress changes following different forces.

Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a System Model

NASA Technical Reports Server (NTRS)

Cole, Bjorn; Chung, Seung H.

2012-01-01

One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must tradeoff time and cost for analysis quality and quantity. The quality is associated with the fidelity of the multidisciplinary models and the quantity is associated with the design space that can be analyzed. The tradeoff is due to the resource intensive process of creating a cohesive multidisciplinary system model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than handwritten translation scripts or codes of multidisciplinary models and their analyses. The key is to work from a core system model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query-View- Transform (QVT), from the OMG community. SysML was designed to model multidisciplinary systems and analyses. The QVT standard was designed to transform SysML models. The Europa Hability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, a symbolic mathematical framework (supported by Wolfram Mathematica) is coordinated by data objects transformed from the system model, enabling extremely flexible and powerful tradespace exploration and analytical investigations of expected system performance.

SARTools: A DESeq2- and EdgeR-Based R Pipeline for Comprehensive Differential Analysis of RNA-Seq Data.

PubMed

Varet, Hugo; Brillet-Guéguen, Loraine; Coppée, Jean-Yves; Dillies, Marie-Agnès

2016-01-01

Several R packages exist for the detection of differentially expressed genes from RNA-Seq data. The analysis process includes three main steps, namely normalization, dispersion estimation and test for differential expression. Quality control steps along this process are recommended but not mandatory, and failing to check the characteristics of the dataset may lead to spurious results. In addition, normalization methods and statistical models are not exchangeable across the packages without adequate transformations the users are often not aware of. Thus, dedicated analysis pipelines are needed to include systematic quality control steps and prevent errors from misusing the proposed methods. SARTools is an R pipeline for differential analysis of RNA-Seq count data. It can handle designs involving two or more conditions of a single biological factor with or without a blocking factor (such as a batch effect or a sample pairing). It is based on DESeq2 and edgeR and is composed of an R package and two R script templates (for DESeq2 and edgeR respectively). Tuning a small number of parameters and executing one of the R scripts, users have access to the full results of the analysis, including lists of differentially expressed genes and a HTML report that (i) displays diagnostic plots for quality control and model hypotheses checking and (ii) keeps track of the whole analysis process, parameter values and versions of the R packages used. SARTools provides systematic quality controls of the dataset as well as diagnostic plots that help to tune the model parameters. It gives access to the main parameters of DESeq2 and edgeR and prevents untrained users from misusing some functionalities of both packages. By keeping track of all the parameters of the analysis process it fits the requirements of reproducible research.

The practice of quality-associated costing: application to transfusion manufacturing processes.

PubMed

Trenchard, P M; Dixon, R

1997-01-01

This article applies the new method of quality-associated costing (QAC) to the mixture of processes that create red cell and plasma products from whole blood donations. The article compares QAC with two commonly encountered but arbitrary models and illustrates the invalidity of clinical cost-benefit analysis based on these models. The first, an "isolated" cost model, seeks to allocate each whole process cost to only one product class. The other is a "shared" cost model, and it seeks to allocate an approximately equal share of all process costs to all associated products.

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

NASA Astrophysics Data System (ADS)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global search and Bayesian inference schemes.

Environmental and Water Quality Operational Studies: Proceedings of the DeGray Lake Symposium Held in Arkadelphia, Arkansas.

DTIC Science & Technology

1987-03-01

statistics for storm water quality variables and fractions of phosphorus, solids, and carbon are presented in Tables 7 and 8, respectively. The correlation...matrix and factor analysis (same method as used for baseflow) of storm water quality variables suggested three groups: Group I - TMG, TCA, TNA, TSI...models to predict storm water quality . The 11 static and 3 dynamic storm variables were used as potential dependent variables. All independent and

Importance of Dissolved Organic Nitrogen to Water Quality in Narragansett Bay

EPA Science Inventory

This preliminary analysis of the importance of the dissolved organic nitrogen (DON) pool in Narragansett Bay is being conducted as part of a five-year study of Narragansett Bay and its watershed. This larger study includes water quality and ecological modeling components that foc...

MODEL ANALYSIS OF RIPARIAN BUFFER EFFECTIVENESS FOR REDUCING NUTRIENT INPUTS TO STREAMS IN AGRICULTURAL LANDSCAPES

EPA Science Inventory

Federal and state agencies responsible for protecting water quality rely mainly on statistically-based methods to assess and manage risks to the nation's streams, lakes and estuaries. Although statistical approaches provide valuable information on current trends in water quality...

Additional Measurements and Analyses of H217O and H218O

NASA Astrophysics Data System (ADS)

Pearson, John; Yu, Shanshan; Walters, Adam; Daly, Adam M.

2015-06-01

Historically the analysis of the spectrum of water has been a balance between the quality of the data set and the applicability of the Hamiltonian to a highly non-rigid molecule. Recently, a number of different non-rigid analysis approaches have successfully been applied to 16O water resulting in a self-consistent set of transitions and energy levels to high J which allowed the spectrum to be modeled to experimental precision. The data set for 17O and 18O water was previously reviewed and many of the problematic measurements identified, but Hamiltonian modeling of the remaining data resulted in significantly poorer quality fits than that for the 16O parent. As a result, we have made additional microwave measurements and modeled the existing 17O and 18O data sets with an Euler series model. This effort has illuminated a number of additional problematic measurements in the previous data sets and has resulted in analyses of 17O and 18O water that are of similar quality to the 16O analysis. We report the new lines, the analyses and make recommendations on the quality of the experimental data sets. SS. Yu, J.C. Pearson, B.J. Drouin et al. J. Mol. Spectrosc. 279,~16-25 (2012) J. Tennyson, P.F. Bernath, L.R. Brown et al. J. Quant. Spectrosc. Rad. Trans. 117, 29-58 (2013) J. Tennyson, P.F. Bernath, L.R. Brown et al. J. Quant. Spectrosc. Rad. Trans. 110, 573-596 (2009) H.M. Pickett, J.C. Pearson, C.E. Miller J. Mol. Spectrosc. 233, 174-179 (2005)

Water quality assessment and apportionment of pollution sources using APCS-MLR and PMF receptor modeling techniques in three major rivers of South Florida.

PubMed

Haji Gholizadeh, Mohammad; Melesse, Assefa M; Reddi, Lakshmi

2016-10-01

In this study, principal component analysis (PCA), factor analysis (FA), and the absolute principal component score-multiple linear regression (APCS-MLR) receptor modeling technique were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, 15years (2000-2014) dataset of 12 water quality variables covering 16 monitoring stations, and approximately 35,000 observations was used. The PCA/FA method identified five and four potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules and causes were explained. The APCS-MLR apportioned their contributions to each water quality variable. Results showed that the point source pollution discharges from anthropogenic factors due to the discharge of agriculture waste and domestic and industrial wastewater were the major sources of river water contamination. Also, the studied variables were categorized into three groups of nutrients (total kjeldahl nitrogen, total phosphorus, total phosphate, and ammonia-N), water murkiness conducive parameters (total suspended solids, turbidity, and chlorophyll-a), and salt ions (magnesium, chloride, and sodium), and average contributions of different potential pollution sources to these categories were considered separately. The data matrix was also subjected to PMF receptor model using the EPA PMF-5.0 program and the two-way model described was performed for the PMF analyses. Comparison of the obtained results of PMF and APCS-MLR models showed that there were some significant differences in estimated contribution for each potential pollution source, especially in the wet season. Eventually, it was concluded that the APCS-MLR receptor modeling approach appears to be more physically plausible for the current study. It is believed that the results of apportionment could be very useful to the local authorities for the control and management of pollution and better protection of important riverine water quality. Copyright © 2016 Elsevier B.V. All rights reserved.

A simple, semi-prescriptive self-assessment model for TQM.

PubMed

Warwood, Stephen; Antony, Jiju

2003-01-01

This article presents a simple, semi-prescriptive self-assessment model for use in industry as part of a continuous improvement program such as Total Quality Management (TQM). The process by which the model was constructed started with a review of the available literature in order to research TQM success factors. Next, postal surveys were conducted by sending questionnaires to the winning organisations of the Baldrige and European Quality Awards and to a preselected group of enterprising UK organisations. From the analysis of this data, the self-assessment model was constructed to help organisations in their quest for excellence. This work confirmed the findings from the literature, that there are key factors that contribute to the successful implementation of TQM and these have different levels of importance. These key factors, in order of importance, are: effective leadership, the impact of other quality-related programs, measurement systems, organisational culture, education and training, the use of teams, efficient communications, active empowerment of the workforce, and a systems infrastructure to support the business and customer-focused processes. This analysis, in turn, enabled the design of a self-assessment model that can be applied within any business setting. Further work should include the testing and review of this model to ascertain its suitability and effectiveness within industry today.

Modeling of Micro Deval abrasion loss based on some rock properties

NASA Astrophysics Data System (ADS)

Capik, Mehmet; Yilmaz, Ali Osman

2017-10-01

Aggregate is one of the most widely used construction material. The quality of the aggregate is determined using some testing methods. Among these methods, the Micro Deval Abrasion Loss (MDAL) test is commonly used for the determination of the quality and the abrasion resistance of aggregate. The main objective of this study is to develop models for the prediction of MDAL from rock properties, including uniaxial compressive strength, Brazilian tensile strength, point load index, Schmidt rebound hardness, apparent porosity, void ratio Cerchar abrasivity index and Bohme abrasion test are examined. Additionally, the MDAL is modeled using simple regression analysis and multiple linear regression analysis based on the rock properties. The study shows that the MDAL decreases with the increase of uniaxial compressive strength, Brazilian tensile strength, point load index, Schmidt rebound hardness and Cerchar abrasivity index. It is also concluded that the MDAL increases with the increase of apparent porosity, void ratio and Bohme abrasion test. The modeling results show that the models based on Bohme abrasion test and L type Schmidt rebound hardness give the better forecasting performances for the MDAL. More models, including the uniaxial compressive strength, the apparent porosity and Cerchar abrasivity index, are developed for the rapid estimation of the MDAL of the rocks. The developed models were verified by statistical tests. Additionally, it can be stated that the proposed models can be used as a forecasting for aggregate quality.

A review of AirQ Models and their applications for forecasting the air pollution health outcomes.

PubMed

Oliveri Conti, Gea; Heibati, Behzad; Kloog, Itai; Fiore, Maria; Ferrante, Margherita

2017-03-01

Even though clean air is considered as a basic requirement for the maintenance of human health, air pollution continues to pose a significant health threat in developed and developing countries alike. Monitoring and modeling of classic and emerging pollutants is vital to our knowledge of health outcomes in exposed subjects and to our ability to predict them. The ability to anticipate and manage changes in atmospheric pollutant concentrations relies on an accurate representation of the chemical state of the atmosphere. The task of providing the best possible analysis of air pollution thus requires efficient computational tools enabling efficient integration of observational data into models. A number of air quality models have been developed and play an important role in air quality management. Even though a large number of air quality models have been discussed or applied, their heterogeneity makes it difficult to select one approach above the others. This paper provides a brief review on air quality models with respect to several aspects such as prediction of health effects.

Does competition improve health care quality?

PubMed

Scanlon, Dennis P; Swaminathan, Shailender; Lee, Woolton; Chernew, Michael

2008-12-01

To identify the effect of competition on health maintenance organizations' (HMOs) quality measures. Longitudinal analysis of a 5-year panel of the Healthcare Effectiveness Data and Information Set (HEDIS) and Consumer Assessment of Health Plans Survey(R) (CAHPS) data (calendar years 1998-2002). All plans submitting data to the National Committee for Quality Assurance (NCQA) were included regardless of their decision to allow NCQA to disclose their results publicly. NCQA, Interstudy, the Area Resource File, and the Bureau of Labor Statistics. Fixed-effects models were estimated that relate HMO competition to HMO quality controlling for an unmeasured, time-invariant plan, and market traits. Results are compared with estimates from models reliant on cross-sectional variation. Estimates suggest that plan quality does not improve with increased levels of HMO competition (as measured by either the Herfindahl index or the number of HMOs). Similarly, increased HMO penetration is generally not associated with improved quality. Cross-sectional models tend to suggest an inverse relationship between competition and quality. The strategies that promote competition among HMOs in the current market setting may not lead to improved HMO quality. It is possible that price competition dominates, with purchasers and consumers preferring lower premiums at the expense of improved quality, as measured by HEDIS and CAHPS. It is also possible that the fragmentation associated with competition hinders quality improvement.

The Role of Model and Initial Condition Error in Numerical Weather Forecasting Investigated with an Observing System Simulation Experiment

NASA Technical Reports Server (NTRS)

Prive, Nikki C.; Errico, Ronald M.

2013-01-01

A series of experiments that explore the roles of model and initial condition error in numerical weather prediction are performed using an observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO). The use of an OSSE allows the analysis and forecast errors to be explicitly calculated, and different hypothetical observing networks can be tested with ease. In these experiments, both a full global OSSE framework and an 'identical twin' OSSE setup are utilized to compare the behavior of the data assimilation system and evolution of forecast skill with and without model error. The initial condition error is manipulated by varying the distribution and quality of the observing network and the magnitude of observation errors. The results show that model error has a strong impact on both the quality of the analysis field and the evolution of forecast skill, including both systematic and unsystematic model error components. With a realistic observing network, the analysis state retains a significant quantity of error due to systematic model error. If errors of the analysis state are minimized, model error acts to rapidly degrade forecast skill during the first 24-48 hours of forward integration. In the presence of model error, the impact of observation errors on forecast skill is small, but in the absence of model error, observation errors cause a substantial degradation of the skill of medium range forecasts.

Management of common gastrointestinal disorders: quality criteria based on patients' views and practice guidelines

PubMed Central

Jones, Roger; Hunt, Claire; Stevens, Richard; Dalrymple, Jamie; Driscoll, Richard; Sleet, Sarah; Smith, Jonathan Blanchard

2009-01-01

Background Although gastrointestinal disorders are common in general practice, clinical guidelines are not always implemented, and few patient-generated quality criteria are available to guide management. Aim To develop quality criteria for the management of four common gastrointestinal disorders: coeliac disease, gastro-oesophageal reflux disease (GORD), inflammatory bowel disease, and irritable bowel syndrome. Design of study Qualitative study including thematic analysis of transcripts from patient focus groups and content analysis of published clinical practice guidelines. Emergent themes were synthesised by a consensus panel, into quality criteria for each condition. Setting Community-based practice in England, UK. Methods Fourteen focus groups were conducted (four for coeliac disease, irritable bowel syndrome, and inflammatory bowel disease, and two for GORD) involving a total of 93 patients (64 females, 29 males; mean age 55.4 years). Quality criteria were based on patients' views and expectations, synthesised with an analysis of clinical practice guidelines. Results A chronic disease management model was developed for each condition. Key themes included improving the timeliness and accuracy of diagnosis, appropriate use of investigations, better provision of information for patients, including access to patient organisations, better communication with, and access to, secondary care providers, and structured follow-up and regular review, particularly for coeliac disease and inflammatory bowel disease. Conclusion This study provides a model for the development of quality markers for chronic disease management in gastroenterology, which is likely to be applicable to other chronic conditions. PMID:19520018

Software reliability models for fault-tolerant avionics computers and related topics

NASA Technical Reports Server (NTRS)

Miller, Douglas R.

1987-01-01

Software reliability research is briefly described. General research topics are reliability growth models, quality of software reliability prediction, the complete monotonicity property of reliability growth, conceptual modelling of software failure behavior, assurance of ultrahigh reliability, and analysis techniques for fault-tolerant systems.

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL

EPA Science Inventory

The use of a fitted-parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can l...

Efficacy-mediated effects of spirituality and physical activity on quality of life: A path analysis

PubMed Central

2012-01-01

Background Physical activity has been established as an important determinant of quality of life, particularly among older adults. Previous research has suggested that physical activity’s influence on quality of life perceptions is mediated by changes in self-efficacy and health status. In the same vein, spirituality may be a salient quality of life determinant for many individuals. Methods In the current study, we used path analysis to test a model in which physical activity, spirituality, and social support were hypothesized to influence global quality of life in paths mediated by self-efficacy and health status. Cross-sectional data were collected from a sample of 215 adults (male, n = 51; female, n = 164) over the age of 50 (M age = 66.55 years). Results The analysis resulted in a model that provided acceptable fit to the data (χ2 = 33.10, df = 16, p < .01; RMSEA = .07; SRMR = .05; CFI = .94). Conclusions These results support previous findings of an efficacy-mediated relationship between physical activity and quality of life, with the exception that self-efficacy in the current study was moderately associated with physical health status (.38) but not mental health status. Our results further suggest that spirituality may influence health and well-being via a similar, efficacy-mediated path, with strongest effects on mental health status. These results suggest that those who are more spiritual and physically active report greater quality of life, and the effects of these factors on quality of life may be partially mediated by perceptions of self-efficacy. PMID:22642832

Development and assessment of an integrated ecological modelling framework to assess the effect of investments in wastewater treatment on water quality.

PubMed

Holguin-Gonzalez, Javier E; Boets, Pieter; Everaert, Gert; Pauwels, Ine S; Lock, Koen; Gobeyn, Sacha; Benedetti, Lorenzo; Amerlinck, Youri; Nopens, Ingmar; Goethals, Peter L M

2014-01-01

Worldwide, large investments in wastewater treatment are made to improve water quality. However, the impacts of these investments on river water quality are often not quantified. To assess water quality, the European Water Framework Directive (WFD) requires an integrated approach. The aim of this study was to develop an integrated ecological modelling framework for the River Drava (Croatia) that includes physical-chemical and hydromorphological characteristics as well as the ecological river water quality status. The developed submodels and the integrated model showed accurate predictions when comparing the modelled results to the observations. Dissolved oxygen and nitrogen concentrations (ammonium and organic nitrogen) were the most important variables in determining the ecological water quality (EWQ). The result of three potential investment scenarios of the wastewater treatment infrastructure in the city of Varaždin on the EWQ of the River Drava was assessed. From this scenario-based analysis, it was concluded that upgrading the existing wastewater treatment plant with nitrogen and phosphorus removal will be insufficient to reach a good EWQ. Therefore, other point and diffuse pollution sources in the area should also be monitored and remediated to meet the European WFD standards.

A measurement system for large, complex software programs

NASA Technical Reports Server (NTRS)

Rone, Kyle Y.; Olson, Kitty M.; Davis, Nathan E.

1994-01-01

This paper describes measurement systems required to forecast, measure, and control activities for large, complex software development and support programs. Initial software cost and quality analysis provides the foundation for meaningful management decisions as a project evolves. In modeling the cost and quality of software systems, the relationship between the functionality, quality, cost, and schedule of the product must be considered. This explicit relationship is dictated by the criticality of the software being developed. This balance between cost and quality is a viable software engineering trade-off throughout the life cycle. Therefore, the ability to accurately estimate the cost and quality of software systems is essential to providing reliable software on time and within budget. Software cost models relate the product error rate to the percent of the project labor that is required for independent verification and validation. The criticality of the software determines which cost model is used to estimate the labor required to develop the software. Software quality models yield an expected error discovery rate based on the software size, criticality, software development environment, and the level of competence of the project and developers with respect to the processes being employed.

The Social Distribution of Health: Estimating Quality-Adjusted Life Expectancy in England.

PubMed

Love-Koh, James; Asaria, Miqdad; Cookson, Richard; Griffin, Susan

2015-07-01

To model the social distribution of quality-adjusted life expectancy (QALE) in England by combining survey data on health-related quality of life with administrative data on mortality. Health Survey for England data sets for 2010, 2011, and 2012 were pooled (n = 35,062) and used to model health-related quality of life as a function of sex, age, and socioeconomic status (SES). Office for National Statistics mortality rates were used to construct life tables for age-sex-SES groups. These quality-of-life and length-of-life estimates were then combined to predict QALE as a function of these characteristics. Missing data were imputed, and Monte-Carlo simulation was used to estimate standard errors. Sensitivity analysis was conducted to explore alternative regression models and measures of SES. Socioeconomic inequality in QALE at birth was estimated at 11.87 quality-adjusted life-years (QALYs), with a sex difference of 1 QALY. When the socioeconomic-sex subgroups are ranked by QALE, a differential of 10.97 QALYs is found between the most and least healthy quintile groups. This differential can be broken down into a life expectancy difference of 7.28 years and a quality-of-life adjustment of 3.69 years. The methods proposed in this article refine simple binary quality-adjustment measures such as the widely used disability-free life expectancy, providing a more accurate picture of overall health inequality in society than has hitherto been available. The predictions also lend themselves well to the task of evaluating the health inequality impact of interventions in the context of cost-effectiveness analysis. Copyright © 2015 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Evaluating Individual Students' Perceptions of Instructional Quality: An Investigation of their Factor Structure, Measurement Invariance, and Relations to Educational Outcomes

PubMed Central

Scherer, Ronny; Nilsen, Trude; Jansen, Malte

2016-01-01

Students' perceptions of instructional quality are among the most important criteria for evaluating teaching effectiveness. The present study evaluates different latent variable modeling approaches (confirmatory factor analysis, exploratory structural equation modeling, and bifactor modeling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance, and the relations to selected educational outcomes (achievement, self-concept, and motivation in mathematics). On the basis of the Programme for International Student Assessment (PISA) 2012 large-scale data sets of Australia, Canada, and the USA (N = 26,746 students), we find support for the distinction between three factors of individual students' perceptions and full measurement invariance across countries for all modeling approaches. In this regard, bifactor exploratory structural equation modeling outperformed alternative approaches with respect to model fit. Our findings reveal significant relations to the educational outcomes. This study synthesizes different modeling approaches of individual students' perceptions of instructional quality and provides insights into the nature of these perceptions from an individual differences perspective. Implications for the measurement and modeling of individually perceived instructional quality are discussed. PMID:26903917

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

[Construction and application of economy-pollution-environment three-dimensional evaluation model for district].

PubMed

Fan, Xin-Gang; Mi, Wen-Bao; Ma, Zhen-Ning

2015-02-01

For deep analysis on the regional environmental economic system, the paper analyzes the mutual relation of regional economy development, environmental quality, environmental pollution, and builds the theoretical basis. Then, the economy-pollution-environment quality three-dimensional coupling evaluation model for district is constructed. It includes economic development level index, environmental pollution index, and environmental quality index. The model is a cube, which has spatialization and visualization characteristics. The model includes 8 sub cubes, which expresses 8 types of state, e. g. low pollution-inferior quality-low level of economic development etc. The model can be used to evaluate the status of region, divide development phase, analyze evolution trend etc. It has two ways including relative meaning evaluation (RME) and absolute meaning evaluation (AME). Based on the model, Yinchuan City in the Ningxia Hui Autonomous Region is used as an example for the empirical study. Using RME, compared with Guangzhou city, The result shows that the Yinchuan City has been a high pollution-low quality-low level of economic development state for a long period during 1996-2010. After 2007, the state changed to a high pollution-high quality-low level of economic development. Now, the environmental quality of Yinchuan city gets better, but pollutant discharge pressure is high, and tends to be the break point of high environment quality and low environment. With AME, using national standard, the Yinchuan City remains a high pollution-low quality-low level of economic development state during 1996-2010. Empirical research verifies that different target reference areas and relevant national standards have different main parameters, the evaluating result has an flexible range. The dimensionless data enhances the coupling of index. The data position in model increases the visibility to the environmental management decisions. The model improves mismatches of calculated data size, time asymmetry of spatial data, verification of the former multi-target coupling model.

HISTORICAL EMISSION AND OZONE TRENDS IN THE HOUSTON AREA

EPA Science Inventory

An analysis of historical trend data for emissions and air quality in Houston for period of 1974-78 is conducted for the purposes of checking the EKMA O3-predicting model and of exploring empirical relations between emission changes and O3 air quality in the Houston area. Results...

Judging the Quality of Peer-Led Student Dialogues.

ERIC Educational Resources Information Center

Keefer, Matthew W.; Zeitz, Colleen M.; Resnick, Lauren B.

2000-01-01

Compared the rational quality of fourth-graders' discussion of literary texts with an ideal model and over the course of the academic year. Analyzed the collaborative reasoning capabilities of 6 three-student groups using a graphical coding system with an analysis of the literary content of the students' argumentation. Identified important…

Insights into future air quality: Analysis of future emissions scenarios using the MARKAL model

EPA Science Inventory

This presentation will provide an update on the development and evaluation of four Air Quality Futures (AQF) scenarios. These scenarios represent widely different assumptions regarding the evolution of the U.S. energy system over the next 40 years. The primary differences between...

Quality effort decision in service supply chain with quality preference based on quantum game

NASA Astrophysics Data System (ADS)

Zhang, Cuihua; Xing, Peng; Wang, Jianwei

2015-04-01

Service quality preference behaviors of both members are considered in service supply chain (SSC) including a service integrator and a service provider with stochastic demand. Through analysis of service quality cost and revenue, the utility functions are established on service quality effort degree and service quality preference level in integrated and decentralized SSC. Nash equilibrium and quantum game are used to optimize the models. By comparing the different solutions, the optimal strategies are obtained in SSC with quality preference. Then some numerical examples are studied and the changing trend of service quality effort is further analyzed by the influence of the entanglement operator and quality preferences.

Synthesizing models useful for ecohydrology and ecohydraulic approaches: An emphasis on integrating models to address complex research questions

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

Brewer, Shannon K.; Worthington, Thomas A.; Mollenhauer, Robert

Ecohydrology combines empiricism, data analytics, and the integration of models to characterize linkages between ecological and hydrological processes. A challenge for practitioners is determining which models best generalizes heterogeneity in hydrological behaviour, including water fluxes across spatial and temporal scales, integrating environmental and socio–economic activities to determine best watershed management practices and data requirements. We conducted a literature review and synthesis of hydrologic, hydraulic, water quality, and ecological models designed for solving interdisciplinary questions. We reviewed 1,275 papers and identified 178 models that have the capacity to answer an array of research questions about ecohydrology or ecohydraulics. Of these models,more » 43 were commonly applied due to their versatility, accessibility, user–friendliness, and excellent user–support. Forty–one of 43 reviewed models were linked to at least 1 other model especially: Water Quality Analysis Simulation Program (linked to 21 other models), Soil and Water Assessment Tool (19), and Hydrologic Engineering Center's River Analysis System (15). However, model integration was still relatively infrequent. There was substantial variation in model applications, possibly an artefact of the regional focus of research questions, simplicity of use, quality of user–support efforts, or a limited understanding of model applicability. Simply increasing the interoperability of model platforms, transformation of models to user–friendly forms, increasing user–support, defining the reliability and risk associated with model results, and increasing awareness of model applicability may promote increased use of models across subdisciplines. Furthermore, the current availability of models allows an array of interdisciplinary questions to be addressed, and model choice relates to several factors including research objective, model complexity, ability to link to other models, and interface choice.« less

Synthesizing models useful for ecohydrology and ecohydraulic approaches: An emphasis on integrating models to address complex research questions

USGS Publications Warehouse

Brewer, Shannon K.; Worthington, Thomas; Mollenhauer, Robert; Stewart, David; McManamay, Ryan; Guertault, Lucie; Moore, Desiree

2018-01-01

Ecohydrology combines empiricism, data analytics, and the integration of models to characterize linkages between ecological and hydrological processes. A challenge for practitioners is determining which models best generalizes heterogeneity in hydrological behaviour, including water fluxes across spatial and temporal scales, integrating environmental and socio‐economic activities to determine best watershed management practices and data requirements. We conducted a literature review and synthesis of hydrologic, hydraulic, water quality, and ecological models designed for solving interdisciplinary questions. We reviewed 1,275 papers and identified 178 models that have the capacity to answer an array of research questions about ecohydrology or ecohydraulics. Of these models, 43 were commonly applied due to their versatility, accessibility, user‐friendliness, and excellent user‐support. Forty‐one of 43 reviewed models were linked to at least 1 other model especially: Water Quality Analysis Simulation Program (linked to 21 other models), Soil and Water Assessment Tool (19), and Hydrologic Engineering Center's River Analysis System (15). However, model integration was still relatively infrequent. There was substantial variation in model applications, possibly an artefact of the regional focus of research questions, simplicity of use, quality of user‐support efforts, or a limited understanding of model applicability. Simply increasing the interoperability of model platforms, transformation of models to user‐friendly forms, increasing user‐support, defining the reliability and risk associated with model results, and increasing awareness of model applicability may promote increased use of models across subdisciplines. Nonetheless, the current availability of models allows an array of interdisciplinary questions to be addressed, and model choice relates to several factors including research objective, model complexity, ability to link to other models, and interface choice.

Synthesizing models useful for ecohydrology and ecohydraulic approaches: An emphasis on integrating models to address complex research questions

DOE PAGES

Brewer, Shannon K.; Worthington, Thomas A.; Mollenhauer, Robert; ...

2018-04-06

Ecohydrology combines empiricism, data analytics, and the integration of models to characterize linkages between ecological and hydrological processes. A challenge for practitioners is determining which models best generalizes heterogeneity in hydrological behaviour, including water fluxes across spatial and temporal scales, integrating environmental and socio–economic activities to determine best watershed management practices and data requirements. We conducted a literature review and synthesis of hydrologic, hydraulic, water quality, and ecological models designed for solving interdisciplinary questions. We reviewed 1,275 papers and identified 178 models that have the capacity to answer an array of research questions about ecohydrology or ecohydraulics. Of these models,more » 43 were commonly applied due to their versatility, accessibility, user–friendliness, and excellent user–support. Forty–one of 43 reviewed models were linked to at least 1 other model especially: Water Quality Analysis Simulation Program (linked to 21 other models), Soil and Water Assessment Tool (19), and Hydrologic Engineering Center's River Analysis System (15). However, model integration was still relatively infrequent. There was substantial variation in model applications, possibly an artefact of the regional focus of research questions, simplicity of use, quality of user–support efforts, or a limited understanding of model applicability. Simply increasing the interoperability of model platforms, transformation of models to user–friendly forms, increasing user–support, defining the reliability and risk associated with model results, and increasing awareness of model applicability may promote increased use of models across subdisciplines. Furthermore, the current availability of models allows an array of interdisciplinary questions to be addressed, and model choice relates to several factors including research objective, model complexity, ability to link to other models, and interface choice.« less

Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging

PubMed Central

Lauzon, Carolyn B.; Asman, Andrew J.; Esparza, Michael L.; Burns, Scott S.; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W.; Davis, Nicole; Cutting, Laurie E.; Landman, Bennett A.

2013-01-01

Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible. PMID:23637895

Simultaneous analysis and quality assurance for diffusion tensor imaging.

PubMed

Lauzon, Carolyn B; Asman, Andrew J; Esparza, Michael L; Burns, Scott S; Fan, Qiuyun; Gao, Yurui; Anderson, Adam W; Davis, Nicole; Cutting, Laurie E; Landman, Bennett A

2013-01-01

Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural mapping of in vivo tissue microarchitecture through voxel-wise mathematical modeling of multiple magnetic resonance imaging (MRI) acquisitions, each differently sensitized to water diffusion. DTI computations are fundamentally estimation processes and are sensitive to noise and artifacts. Despite widespread adoption in the neuroimaging community, maintaining consistent DTI data quality remains challenging given the propensity for patient motion, artifacts associated with fast imaging techniques, and the possibility of hardware changes/failures. Furthermore, the quantity of data acquired per voxel, the non-linear estimation process, and numerous potential use cases complicate traditional visual data inspection approaches. Currently, quality inspection of DTI data has relied on visual inspection and individual processing in DTI analysis software programs (e.g. DTIPrep, DTI-studio). However, recent advances in applied statistical methods have yielded several different metrics to assess noise level, artifact propensity, quality of tensor fit, variance of estimated measures, and bias in estimated measures. To date, these metrics have been largely studied in isolation. Herein, we select complementary metrics for integration into an automatic DTI analysis and quality assurance pipeline. The pipeline completes in 24 hours, stores statistical outputs, and produces a graphical summary quality analysis (QA) report. We assess the utility of this streamlined approach for empirical quality assessment on 608 DTI datasets from pediatric neuroimaging studies. The efficiency and accuracy of quality analysis using the proposed pipeline is compared with quality analysis based on visual inspection. The unified pipeline is found to save a statistically significant amount of time (over 70%) while improving the consistency of QA between a DTI expert and a pool of research associates. Projection of QA metrics to a low dimensional manifold reveal qualitative, but clear, QA-study associations and suggest that automated outlier/anomaly detection would be feasible.

Assessing ecosystem effects of reservoir operations using food web-energy transfer and water quality models

USGS Publications Warehouse

Saito, L.; Johnson, B.M.; Bartholow, J.; Hanna, R.B.

2001-01-01

We investigated the effects on the reservoir food web of a new temperature control device (TCD) on the dam at Shasta Lake, California. We followed a linked modeling approach that used a specialized reservoir water quality model to forecast operation-induced changes in phytoplankton production. A food web–energy transfer model was also applied to propagate predicted changes in phytoplankton up through the food web to the predators and sport fishes of interest. The food web–energy transfer model employed a 10% trophic transfer efficiency through a food web that was mapped using carbon and nitrogen stable isotope analysis. Stable isotope analysis provided an efficient and comprehensive means of estimating the structure of the reservoir's food web with minimal sampling and background data. We used an optimization procedure to estimate the diet proportions of all food web components simultaneously from their isotopic signatures. Some consumers were estimated to be much more sensitive than others to perturbations to phytoplankton supply. The linked modeling approach demonstrated that interdisciplinary efforts enhance the value of information obtained from studies of managed ecosystems. The approach exploited the strengths of engineering and ecological modeling methods to address concerns that neither of the models could have addressed alone: (a) the water quality model could not have addressed quantitatively the possible impacts to fish, and (b) the food web model could not have examined how phytoplankton availability might change due to reservoir operations.

Air Quality Forecasts Using the NASA GEOS Model

NASA Technical Reports Server (NTRS)

Keller, Christoph A.; Knowland, K. Emma; Nielsen, Jon E.; Orbe, Clara; Ott, Lesley; Pawson, Steven; Saunders, Emily; Duncan, Bryan; Follette-Cook, Melanie; Liu, Junhua;

Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.

PubMed

Pratt, Bethany; Chang, Heejun

2012-03-30

The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants. Copyright © 2012 Elsevier B.V. All rights reserved.

"Total Deposition (TDEP) Maps" | Science Inventory | US EPA

EPA Pesticide Factsheets

The presentation provides an update on the use of a hybrid methodology that relies on measured values from national monitoring networks and modeled values from CMAQ to produce of maps of total deposition for use in critical loads and other ecological assessments. Additionally, comparisons of the deposition values from the hybrid approach are compared with deposition estimates from other methodologies. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the 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 pollution problem, but also in developing emission control policies and regulations for air quality improvements.

A supply chain model to improve the beef quality distribution using investment analysis: A case study

NASA Astrophysics Data System (ADS)

Lupita, Alessandra; Rangkuti, Sabrina Heriza; Sutopo, Wahyudi; Hisjam, Muh.

2017-11-01

There are significant differences related to the quality and price of the beef commodity in traditional market and modern market in Indonesia. Those are caused by very different treatments of the commodity. The different treatments are in the slaughter lines, the transportation from the abattoir to the outlet, the display system, and the control system. If the problem is not solved by the Government, the gap will result a great loss of the consumer regarding to the quality and sustainability of traditional traders business because of the declining interest in purchasing beef in the traditional markets. This article aims to improve the quality of beef in traditional markets. This study proposed A Supply Chain Model that involves the schemes of investment and government incentive for improving the distribution system. The supply chain model is can be formulated using the Mix Integer Linear Programming (MILP) and solved using the IBM®ILOG®CPLEX software. The results show that the proposed model can be used to determine the priority of programs for improving the quality and sustainability business of traditional beef merchants. By using the models, The Government can make a decision to consider incentives for improving the condition.

Propagating Water Quality Analysis Uncertainty Into Resource Management Decisions Through Probabilistic Modeling

NASA Astrophysics Data System (ADS)

Gronewold, A. D.; Wolpert, R. L.; Reckhow, K. H.

2007-12-01

Most probable number (MPN) and colony-forming-unit (CFU) are two estimates of fecal coliform bacteria concentration commonly used as measures of water quality in United States shellfish harvesting waters. The MPN is the maximum likelihood estimate (or MLE) of the true fecal coliform concentration based on counts of non-sterile tubes in serial dilution of a sample aliquot, indicating bacterial metabolic activity. The CFU is the MLE of the true fecal coliform concentration based on the number of bacteria colonies emerging on a growth plate after inoculation from a sample aliquot. Each estimating procedure has intrinsic variability and is subject to additional uncertainty arising from minor variations in experimental protocol. Several versions of each procedure (using different sized aliquots or different numbers of tubes, for example) are in common use, each with its own levels of probabilistic and experimental error and uncertainty. It has been observed empirically that the MPN procedure is more variable than the CFU procedure, and that MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the observed variability in, and discrepancy between, MPN and CFU measurements. We then explore how this variability and uncertainty might propagate into shellfish harvesting area management decisions through a two-phased modeling strategy. First, we apply our probabilistic model in a simulation-based analysis of future water quality standard violation frequencies under alternative land use scenarios, such as those evaluated under guidelines of the total maximum daily load (TMDL) program. Second, we apply our model to water quality data from shellfish harvesting areas which at present are closed (either conditionally or permanently) to shellfishing, to determine if alternative laboratory analysis procedures might have led to different management decisions. Our research results indicate that the (often large) observed differences between MPN and CFU values for the same water body are well within the ranges predicted by our probabilistic model. Our research also indicates that the probability of violating current water quality guidelines at specified true fecal coliform concentrations depends on the laboratory procedure used. As a result, quality-based management decisions, such as opening or closing a shellfishing area, may also depend on the laboratory procedure used.

Air Vehicles Division Computational Structural Analysis Facilities Policy and Guidelines for Users

DTIC Science & Technology

2005-05-01

34 Thermal " as appropriate and the tolerance set to "default". b) Create the model geometry. c) Create the finite elements. d) Create the...linear, non-linear, dynamic, thermal , acoustic analysis. The modelling of composite materials, creep, fatigue and plasticity are also covered...perform professional, high quality finite element analysis (FEA). FE analysts from many tasks within AVD are using the facilities to conduct FEA with

[Quality evaluation of rhubarb dispensing granules based on multi-component simultaneous quantitative analysis and bioassay].

PubMed

Tan, Peng; Zhang, Hai-Zhu; Zhang, Ding-Kun; Wu, Shan-Na; Niu, Ming; Wang, Jia-Bo; Xiao, Xiao-He

2017-07-01

This study attempts to evaluate the quality of Chinese formula granules by combined use of multi-component simultaneous quantitative analysis and bioassay. The rhubarb dispensing granules were used as the model drug for demonstrative study. The ultra-high performance liquid chromatography (UPLC) method was adopted for simultaneously quantitative determination of the 10 anthraquinone derivatives (such as aloe emodin-8-O-β-D-glucoside) in rhubarb dispensing granules; purgative biopotency of different batches of rhubarb dispensing granules was determined based on compound diphenoxylate tablets-induced mouse constipation model; blood activating biopotency of different batches of rhubarb dispensing granules was determined based on in vitro rat antiplatelet aggregation model; SPSS 22.0 statistical software was used for correlation analysis between 10 anthraquinone derivatives and purgative biopotency, blood activating biopotency. The results of multi-components simultaneous quantitative analysisshowed that there was a great difference in chemical characterizationand certain differences inpurgative biopotency and blood activating biopotency among 10 batches of rhubarb dispensing granules. The correlation analysis showed that the intensity of purgative biopotency was significantly correlated with the content of conjugated anthraquinone glycosides (P<0.01), and the intensity of blood activating biopotency was significantly correlated with the content of free anthraquinone (P<0.01). In summary, the combined use of multi-component simultaneous quantitative analysis and bioassay can achieve objective quantification and more comprehensive reflection on overall quality difference among different batches of rhubarb dispensing granules. Copyright© by the Chinese Pharmaceutical Association.

[Watershed water environment pollution models and their applications: a review].

PubMed

Zhu, Yao; Liang, Zhi-Wei; Li, Wei; Yang, Yi; Yang, Mu-Yi; Mao, Wei; Xu, Han-Li; Wu, Wei-Xiang

2013-10-01

Watershed water environment pollution model is the important tool for studying watershed environmental problems. Through the quantitative description of the complicated pollution processes of whole watershed system and its parts, the model can identify the main sources and migration pathways of pollutants, estimate the pollutant loadings, and evaluate their impacts on water environment, providing a basis for watershed planning and management. This paper reviewed the watershed water environment models widely applied at home and abroad, with the focuses on the models of pollutants loading (GWLF and PLOAD), water quality of received water bodies (QUAL2E and WASP), and the watershed models integrated pollutant loadings and water quality (HSPF, SWAT, AGNPS, AnnAGNPS, and SWMM), and introduced the structures, principles, and main characteristics as well as the limitations in practical applications of these models. The other models of water quality (CE-QUAL-W2, EFDC, and AQUATOX) and watershed models (GLEAMS and MIKE SHE) were also briefly introduced. Through the case analysis on the applications of single model and integrated models, the development trend and application prospect of the watershed water environment pollution models were discussed.

A verification procedure for MSC/NASTRAN Finite Element Models

NASA Technical Reports Server (NTRS)

Stockwell, Alan E.

1995-01-01

Finite Element Models (FEM's) are used in the design and analysis of aircraft to mathematically describe the airframe structure for such diverse tasks as flutter analysis and actively controlled landing gear design. FEM's are used to model the entire airplane as well as airframe components. The purpose of this document is to describe recommended methods for verifying the quality of the FEM's and to specify a step-by-step procedure for implementing the methods.

[AIDS prevention among adolescents in school: a systematic review of the efficacy of interventions].

PubMed

Juárez, O; Díez, E

1999-01-01

Preventive interventions are considered useful although poorly evaluated. Since 1990 there are growing evidences of effective school aids prevention interventions. This paper aims to identify school aids prevention programs among youngsters aged 13 to 19, published between 1990 and 1995, to analyze each evaluation and intervention quality, to assess their effectiveness as well as identifying the possible contributing factors. Location of reports by means of a Medline computerized search of published articles and reviews, which should include the following criteria: school aids prevention programs, addressed to youngsters aged 13 to 19, published in Spanish, French or English between 1990 and 1995 in scientific literature, and evaluating changes in behavior or its determinants through quantitative measures. Analysis of the evaluation quality through the assessment of the sample size, the use of a control group, the groups comparability, the drop out analysis and the time between the pretest and the posttest. Intervention quality analysis through the use of a psychological behavioral change model and the number of sessions. The effectiveness of the high quality interventions in changing behaviors, intentions, attitudes and knowledge was assessed. 29 studies were selected. Of these studies, relating the quality of evaluation criteria, a 28% was considered a high quality study, a 14% an intermediate quality study and a 58% a low quality one. In relation to intervention quality criteria, a 27% was found to be a high quality study, a 41% an intermediate quality study and 32% a low quality one. 38% (11 studies) showed high or intermediate quality criteria at the same time in intervention and in evaluation. All these studies modified knowledge and attitudes, an 80% modified the intention to behave and a 86% modified behavior. The increase in knowledge and attitudes was in general quite important, greater than 10%, and changes in intentions and behaviors were smaller than 10%, although relevant. Only 38% of the studies may be considered of high or intermediate quality. Preventive interventions correctly evaluated which rely on a theoretical model and offer 4 or more sessions show evidence of moderate but relevant reduction of aids risk practices, and important changes of the future behavior determinants.

Enhancing mathematics teachers' quality through Lesson Study.

PubMed

Lomibao, Laila S

2016-01-01

The efficiency and effectivity of the learning experience is dependent on the teacher quality, thus, enhancing teacher's quality is vital in improving the students learning outcome. Since, the usual top-down one-shot cascading model practice for teachers' professional development in Philippines has been observed to have much information dilution, and the Southeast Asian Ministers of Education Organization demanded the need to develop mathematics teachers' quality standards through the Southeast Asia Regional Standards for Mathematics Teachers (SEARS-MT), thus, an intensive, ongoing professional development model should be provided to teachers. This study was undertaken to determine the impact of Lesson Study on Bulua National High School mathematics teachers' quality level in terms of SEARS-MT dimensions. A mixed method of quantitative-qualitative research design was employed. Results of the analysis revealed that Lesson Study effectively enhanced mathematics teachers' quality and promoted teachers professional development. Teachers positively perceived Lesson Study to be beneficial for them to become a better mathematics teacher.

Divergent pathways to influence: Cognition and behavior differentially mediate the effects of optimism on physical and mental quality of life in Chinese university students.

PubMed

Ramsay, Jonathan E; Yang, Fang; Pang, Joyce S; Lai, Ching-Man; Ho, Roger Cm; Mak, Kwok-Kei

2015-07-01

Previous research has indicated that both cognitive and behavioral variables mediate the positive effect of optimism on quality of life; yet few attempts have been made to accommodate these constructs into a single explanatory framework. Adopting Fredrickson's broaden-and-build perspective, we examined the relationships between optimism, self-rated health, resilience, exercise, and quality of life in 365 Chinese university students using path analysis. For physical quality of life, a two-stage model, in which the effects of optimism were sequentially mediated by cognitive and behavioral variables, provided the best fit. A one-stage model, with full mediation by cognitive variables, provided the best fit for mental quality of life. This suggests that optimism influences physical and mental quality of life via different pathways. © The Author(s) 2013.

Aggregative Learning Method and Its Application for Communication Quality Evaluation

NASA Astrophysics Data System (ADS)

Akhmetov, Dauren F.; Kotaki, Minoru

2007-12-01

In this paper, so-called Aggregative Learning Method (ALM) is proposed to improve and simplify the learning and classification abilities of different data processing systems. It provides a universal basis for design and analysis of mathematical models of wide class. A procedure was elaborated for time series model reconstruction and analysis for linear and nonlinear cases. Data approximation accuracy (during learning phase) and data classification quality (during recall phase) are estimated from introduced statistic parameters. The validity and efficiency of the proposed approach have been demonstrated through its application for monitoring of wireless communication quality, namely, for Fixed Wireless Access (FWA) system. Low memory and computation resources were shown to be needed for the procedure realization, especially for data classification (recall) stage. Characterized with high computational efficiency and simple decision making procedure, the derived approaches can be useful for simple and reliable real-time surveillance and control system design.

[Risk management--a new aspect of quality assessment in intensive care medicine: first results of an analysis of the DIVI's interdisciplinary quality assessment research group].

PubMed

Stiletto, R; Röthke, M; Schäfer, E; Lefering, R; Waydhas, Ch

2006-10-01

Patient security has become one of the major aspects of clinical management in recent years. The crucial point in research was focused on malpractice. In contradiction to the economic process in non medical fields, the analysis of errors during the in-patient treatment time was neglected. Patient risk management can be defined as a structured procedure in a clinical unit with the aim to reduce harmful events. A risk point model was created based on a Delphi process and founded on the DIVI data register. The risk point model was evaluated in clinically working ICU departments participating in the register data base. The results of the risk point evaluation will be integrated in the next data base update. This might be a step to improve the reliability of the register to measure quality assessment in the ICU.

[Quality assurance of the renal applications software].

PubMed

del Real Núñez, R; Contreras Puertas, P I; Moreno Ortega, E; Mena Bares, L M; Maza Muret, F R; Latre Romero, J M

2007-01-01

The need for quality assurance of all technical aspects of nuclear medicine studies is widely recognised. However, little attention has been paid to the quality assurance of the applications software. Our work reported here aims at verifying the analysis software for processing of renal nuclear medicine studies (renograms). The software tools were used to build a synthetic dynamic model of renal system. The model consists of two phases: perfusion and function. The organs of interest (kidneys, bladder and aortic artery) were simple geometric forms. The uptake of the renal structures was described by mathematic functions. Curves corresponding to normal or pathological conditions were simulated for kidneys, bladder and aortic artery by appropriate selection of parameters. There was no difference between the parameters of the mathematic curves and the quantitative data produced by the renal analysis program. Our test procedure is simple to apply, reliable, reproducible and rapid to verify the renal applications software.

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.

Subsonic Wing Optimization for Handling Qualities Using ACSYNT

NASA Technical Reports Server (NTRS)

Soban, Danielle Suzanne

1996-01-01

The capability to accurately and rapidly predict aircraft stability derivatives using one comprehensive analysis tool has been created. The PREDAVOR tool has the following capabilities: rapid estimation of stability derivatives using a vortex lattice method, calculation of a longitudinal handling qualities metric, and inherent methodology to optimize a given aircraft configuration for longitudinal handling qualities, including an intuitive graphical interface. The PREDAVOR tool may be applied to both subsonic and supersonic designs, as well as conventional and unconventional, symmetric and asymmetric configurations. The workstation-based tool uses as its model a three-dimensional model of the configuration generated using a computer aided design (CAD) package. The PREDAVOR tool was applied to a Lear Jet Model 23 and the North American XB-70 Valkyrie.

Quantification of the effects of quality investment on the Cost of Poor Quality: A quasi-experimental study

NASA Astrophysics Data System (ADS)

Tamimi, Abdallah Ibrahim

Quality management is a fundamental challenge facing businesses. This research attempted to quantify the effect of quality investment on the Cost of Poor Quality (COPQ) in an aerospace company utilizing 3 years of quality data at United Launch Alliance, a Boeing -- Lockheed Martin Joint Venture Company. Statistical analysis tools, like multiple regressions, were used to quantify the relationship between quality investments and COPQ. Strong correlations were evident by the high correlation coefficient R2 and very small p-values in multiple regression analysis. The models in the study helped produce an Excel macro that based on preset constraints, optimized the level of quality spending to minimize COPQ. The study confirmed that as quality investments were increased, the COPQ decreased steadily until a point of diminishing return was reached. The findings may be used to develop an approach to reduce the COPQ and enhance product performance. Achieving superior quality in rocket launching enhances the accuracy, reliability, and mission success of delivering satellites to their precise orbits in pursuit of knowledge, peace, and freedom while assuring safety for the end user.

How do humans inspect BPMN models: an exploratory study.

PubMed

Haisjackl, Cornelia; Soffer, Pnina; Lim, Shao Yi; Weber, Barbara

2018-01-01

Even though considerable progress regarding the technical perspective on modeling and supporting business processes has been achieved, it appears that the human perspective is still often left aside. In particular, we do not have an in-depth understanding of how process models are inspected by humans, what strategies are taken, what challenges arise, and what cognitive processes are involved. This paper contributes toward such an understanding and reports an exploratory study investigating how humans identify and classify quality issues in BPMN process models. Providing preliminary answers to initial research questions, we also indicate other research questions that can be investigated using this approach. Our qualitative analysis shows that humans adapt different strategies on how to identify quality issues. In addition, we observed several challenges appearing when humans inspect process models. Finally, we present different manners in which classification of quality issues was addressed.

Understanding the mediating effects of relationship quality on technology acceptance: an empirical study of e-appointment system.

PubMed

Chen, Shih-Chih; Liu, Shih-Chi; Li, Shing-Han; Yen, David C

2013-12-01

This study extends the Technology Acceptance Model (TAM) by incorporating relationship quality as a mediator to construct a comprehensive framework for understanding the influence on continuance intention in the hospital e-appointment system. A survey of 334 Taiwanese citizens who were contacted via phone or the Internet and Structural Equation Modeling (SEM) is used for path analysis and hypothesis tests. The study shows that perceived ease of use (PEOU) and perceived usefulness (PU) have significant influence on continuance intention through the mediation of relationship quality, consisting of satisfaction and trust. The direct impact of relationship quality on continuance intention is also significant. The analytical results reveal that the relationship between the hospital, patients and e-appointment users can be improved via enhancing the continued usage of e-appointment. This paper also proposes a general model to synthesize the essence of PEOU, PU, and relationship quality for explaining users' continuous intention of e-appointment.

A Model of Risk Analysis in Analytical Methodology for Biopharmaceutical Quality Control.

PubMed

Andrade, Cleyton Lage; Herrera, Miguel Angel De La O; Lemes, Elezer Monte Blanco

2018-01-01

One key quality control parameter for biopharmaceutical products is the analysis of residual cellular DNA. To determine small amounts of DNA (around 100 pg) that may be in a biologically derived drug substance, an analytical method should be sensitive, robust, reliable, and accurate. In principle, three techniques have the ability to measure residual cellular DNA: radioactive dot-blot, a type of hybridization; threshold analysis; and quantitative polymerase chain reaction. Quality risk management is a systematic process for evaluating, controlling, and reporting of risks that may affects method capabilities and supports a scientific and practical approach to decision making. This paper evaluates, by quality risk management, an alternative approach to assessing the performance risks associated with quality control methods used with biopharmaceuticals, using the tool hazard analysis and critical control points. This tool provides the possibility to find the steps in an analytical procedure with higher impact on method performance. By applying these principles to DNA analysis methods, we conclude that the radioactive dot-blot assay has the largest number of critical control points, followed by quantitative polymerase chain reaction, and threshold analysis. From the analysis of hazards (i.e., points of method failure) and the associated method procedure critical control points, we conclude that the analytical methodology with the lowest risk for performance failure for residual cellular DNA testing is quantitative polymerase chain reaction. LAY ABSTRACT: In order to mitigate the risk of adverse events by residual cellular DNA that is not completely cleared from downstream production processes, regulatory agencies have required the industry to guarantee a very low level of DNA in biologically derived pharmaceutical products. The technique historically used was radioactive blot hybridization. However, the technique is a challenging method to implement in a quality control laboratory: It is laborious, time consuming, semi-quantitative, and requires a radioisotope. Along with dot-blot hybridization, two alternatives techniques were evaluated: threshold analysis and quantitative polymerase chain reaction. Quality risk management tools were applied to compare the techniques, taking into account the uncertainties, the possibility of circumstances or future events, and their effects upon method performance. By illustrating the application of these tools with DNA methods, we provide an example of how they can be used to support a scientific and practical approach to decision making and can assess and manage method performance risk using such tools. This paper discusses, considering the principles of quality risk management, an additional approach to the development and selection of analytical quality control methods using the risk analysis tool hazard analysis and critical control points. This tool provides the possibility to find the method procedural steps with higher impact on method reliability (called critical control points). Our model concluded that the radioactive dot-blot assay has the larger number of critical control points, followed by quantitative polymerase chain reaction and threshold analysis. Quantitative polymerase chain reaction is shown to be the better alternative analytical methodology in residual cellular DNA analysis. © PDA, Inc. 2018.

Applications of flight control system methods to an advanced combat rotorcraft

NASA Technical Reports Server (NTRS)

Tischler, Mark B.; Fletcher, Jay W.; Morris, Patrick M.; Tucker, George T.

1989-01-01

Advanced flight control system design, analysis, and testing methodologies developed at the Ames Research Center are applied in an analytical and flight test evaluation of the Advanced Digital Optical Control System (ADOCS) demonstrator. The primary objectives are to describe the knowledge gained about the implications of digital flight control system design for rotorcraft, and to illustrate the analysis of the resulting handling-qualities in the context of the proposed new handling-qualities specification for rotorcraft. Topics covered in-depth are digital flight control design and analysis methods, flight testing techniques, ADOCS handling-qualities evaluation results, and correlation of flight test results with analytical models and the proposed handling-qualities specification. The evaluation of the ADOCS demonstrator indicates desirable response characteristics based on equivalent damping and frequency, but undersirably large effective time-delays (exceeding 240 m sec in all axes). Piloted handling-qualities are found to be desirable or adequate for all low, medium, and high pilot gain tasks; but handling-qualities are inadequate for ultra-high gain tasks such as slope and running landings.

AN AGGREGATION AND EPISODE SELECTION SCHEME FOR EPA'S MODELS-3 CMAQ

EPA Science Inventory

The development of an episode selection and aggregation approach, designed to support distributional estimation for use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700 hPa u and v wind field compo...

MULTIVARIATE RECEPTOR MODELS-CURRENT PRACTICE AND FUTURE TRENDS. (R826238)

EPA Science Inventory

Multivariate receptor models have been applied to the analysis of air quality data for sometime. However, solving the general mixture problem is important in several other fields. This paper looks at the panoply of these models with a view of identifying common challenges and ...

Comparison of radar and gauge precipitation data in watershed models across varying spatial and temporal scales

EPA Science Inventory

Precipitation is a key control on watershed hydrologic modelling output, with errors in rainfall propagating through subsequent stages of water quantity and quality analysis. Most watershed models incorporate precipitation data from rain gauges; higher-resolution data sources are...

Creating quality improvement culture in public health agencies.

PubMed

Davis, Mary V; Mahanna, Elizabeth; Joly, Brenda; Zelek, Michael; Riley, William; Verma, Pooja; Fisher, Jessica Solomon

2014-01-01

We conducted case studies of 10 agencies that participated in early quality improvement efforts. The agencies participated in a project conducted by the National Association of County and City Health Officials (2007-2008). Case study participants included health directors and quality improvement team leaders and members. We implemented multiple qualitative analysis processes, including cross-case analysis and logic modeling. We categorized agencies according to the extent to which they had developed a quality improvement culture. Agencies were conducting informal quality improvement projects (n = 4), conducting formal quality improvement projects (n = 3), or creating a quality improvement culture (n = 4). Agencies conducting formal quality improvement and creating a quality improvement culture had leadership support for quality improvement, participated in national quality improvement initiatives, had a greater number of staff trained in quality improvement and quality improvement teams that met regularly with decision-making authority. Agencies conducting informal quality improvement were likely to report that accreditation is the major driver for quality improvement work. Agencies creating a quality improvement culture were more likely to have a history of evidence-based decision-making and use quality improvement to address emerging issues. Our findings support previous research and add the roles of national public health accreditation and emerging issues as factors in agencies' ability to create and sustain a quality improvement culture.

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.

Diagnostic Analysis of the Three-Dimensional Sulfur Distributions over the Eastern United States Using the CMAQ Model and Measurements from the ICARTT Field Experiment

EPA Science Inventory

Previous comparisons of air quality modeling results from various forecast models with aircraft measurements of sulfate aerosol collected during the ICARTT field experiment indicated that models that included detailed treatment of gas- and aqueous-phase atmospheric sulfate format...

Linking population viability, habitat suitability, and landscape simulation models for conservation planning

Treesearch

Michael A. Larson; Frank R., III Thompson; Joshua J. Millspaugh; William D. Dijak; Stephen R. Shifley

2004-01-01

Methods for habitat modeling based on landscape simulations and population viability modeling based on habitat quality are well developed, but no published study of which we are aware has effectively joined them in a single, comprehensive analysis. We demonstrate the application of a population viability model for ovenbirds (Seiurus aurocapillus)...

MODELS-3 INSTALLATION PROCEDURES FOR A SUN WORKSTATION WITH A UNIX-BASED OPERATING SYSTEM (MODELS-3 VERSION 4.1)

EPA Science Inventory

Models-3 is a flexible system designed to simplify the development and use of air quality models and other environmental decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheric...

A longitudinal study of clinical peer review's impact on quality and safety in U.S. hospitals.

PubMed

Edwards, Marc T

2013-01-01

Clinical peer review is the dominant method of event analysis in U.S. hospitals. It is pivotal to medical staff efforts to improve quality and safety, yet the quality assurance process model that has prevailed for the past 30 years evokes fear and is fundamentally antithetical to a culture of safety. Two prior national studies characterized a quality improvement model that corrects this dysfunction but failed to demonstrate progress toward its adoption despite a high rate of program change between 2007 and 2009. This study's online survey of 470 organizations participating in either of the prior studies further assessed relationships between clinical peer review program factors, including the degree of conformance to the quality improvement model (the QI model score), and subjectively measured program impact variables. Among the 300 hospitals (64%) that responded, the median QI model score was only 60 on a 100-point scale. Scores increased somewhat for the 2007 cohort (mean pair-wise difference of 5.9 [2-10]), but not for the 2009 cohort. The QI model is expanded as the result of the finding that self-reporting of adverse events, near misses, and hazardous conditions--an essential practice in high-reliability organizations--is no longer rare in hospitals. Self-reporting and the quality of case review are additional multivariate predictors of the perceived ongoing impact of clinical peer review on quality and safety, medical staff perceptions of the program, and medical staff engagement in quality and safety initiatives. Hospital leaders and trustees who seek to improve patient outcomes should facilitate the adoption of this best practice model for clinical peer review.

Impacts of crop growth dynamics on soil quality at the regional scale

NASA Astrophysics Data System (ADS)

Gobin, Anne

2014-05-01

Agricultural land use and in particular crop growth dynamics can greatly affect soil quality. Both the amount of soil lost from erosion by water and soil organic matter are key indicators for soil quality. The aim was to develop a modelling framework for quantifying the impacts of crop growth dynamics on soil quality at the regional scale with test case Flanders. A framework for modelling the impacts of crop growth on soil erosion and soil organic matter was developed by coupling the dynamic crop cover model REGCROP (Gobin, 2010) to the PESERA soil erosion model (Kirkby et al., 2009) and to the RothC carbon model (Coleman and Jenkinson, 1999). All three models are process-based, spatially distributed and intended as a regional diagnostic tool. A geo-database was constructed covering 10 years of crop rotation in Flanders using the IACS parcel registration (Integrated Administration and Control System). Crop allometric models were developed from variety trials to calculate crop residues for common crops in Flanders and subsequently derive stable organic matter fluxes to the soil. Results indicate that crop growth dynamics and crop rotations influence soil quality for a very large percentage. soil erosion mainly occurs in the southern part of Flanders, where silty to loamy soils and a hilly topography are responsible for soil loss rates of up to 40 t/ha. Parcels under maize, sugar beet and potatoes are most vulnerable to soil erosion. Crop residues of grain maize and winter wheat followed by catch crops contribute most to the total carbon sequestered in agricultural soils. For the same rotations carbon sequestration is highest on clay soils and lowest on sandy soils. This implies that agricultural policies that impact on agricultural land management influence soil quality for a large percentage. The coupled REGCROP-PESERA-ROTHC model allows for quantifying the impact of seasonal and year-to-year crop growth dynamics on soil quality. When coupled to a multi-annual crop rotation database both spatial and temporal analysis becomes possible and allows for decision support at both farm and regional level. The framework is therefore suited for further scenario analysis and impact assessment. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

A sediment resuspension and water quality model of Lake Okeechobee

USGS Publications Warehouse

James, R.T.; Martin, J.; Wool, T.; Wang, P.-F.

1997-01-01

The influence of sediment resuspension on the water quality of shallow lakes is well documented. However, a search of the literature reveals no deterministic mass-balance eutrophication models that explicitly include resuspension. We modified the Lake Okeeehobee water quality model - which uses the Water Analysis Simulation Package (WASP) to simulate algal dynamics and phosphorus, nitrogen, and oxygen cycles - to include inorganic suspended solids and algorithms that: (1) define changes in depth with changes in volume; (2) compute sediment resuspension based on bottom shear stress; (3) compute partition coefficients for ammonia and ortho-phosphorus to solids; and (4) relate light attenuation to solids concentrations. The model calibration and validation were successful with the exception of dissolved inorganic nitrogen species which did not correspond well to observed data in the validation phase. This could be attributed to an inaccurate formulation of algal nitrogen preference and/or the absence of nitrogen fixation in the model. The model correctly predicted that the lake is lightlimited from resuspended solids, and algae are primarily nitrogen limited. The model simulation suggested that biological fluxes greatly exceed external loads of dissolved nutrients; and sedimentwater interactions of organic nitrogen and phosphorus far exceed external loads. A sensitivity analysis demonstrated that parameters affecting resuspension, settling, sediment nutrient and solids concentrations, mineralization, algal productivity, and algal stoichiometry are factors requiring further study to improve our understanding of the Lake Okeechobee ecosystem.

Estimated Flying Qualities of the Martin Model 202 Airplane

NASA Technical Reports Server (NTRS)

Weil, Joseph; Spear, Margaret

1947-01-01

The flying qualities of the Martin model 202 airplane have been estimated chiefly from the results of tests of an 0.0875-scale complete model with power made in the Wright Brothers tunnel at the Massachusetts Institute of Technology and from partial span wing and isolated vertical tail tests made in the Georgia Tech Nine-Foot Tunnel. These estimated handling qualities have been compared with existing Army-Navy and CAA requirements for stability and control. The results of the analysis indicate that the Martin model 202 airplane will possess satisfactory handling qualities in all respects except possibly in the following: The amount of elevator control available for landing or maneuvering in the landing condition is either marginal or insufficient when using the adjustable stabilizer linked to the flaps . Moreover, indications are that the longitudinal trim changes will be neither large nor appreciably worse with a fixed stabilizer than with the contemplated arrangement utilizing the adjustable stabilizer in an attempt to reduce the magnitude of the trim changes caused by flap deflection.

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.

Water quality modelling of Jadro spring.

PubMed

Margeta, J; Fistanic, I

2004-01-01

Management of water quality in karst is a specific problem. Water generally moves very fast by infiltration processes but far more by concentrated flows through fissures and openings in karst. This enables the entire surface pollution to be transferred fast and without filtration into groundwater springs. A typical example is the Jadro spring. Changes in water quality at the spring are sudden, but short. Turbidity as a major water quality problem for the karst springs regularly exceeds allowable standards. Former practice in problem solving has been reduced to intensive water disinfection in periods of great turbidity without analyses of disinfection by-products risks for water users. The main prerequisite for water quality control and an optimization of water disinfection is the knowledge of raw water quality and nature of occurrence. The analysis of monitoring data and their functional relationship with hydrological parameters enables establishment of a stochastic model that will help obtain better information on turbidity in different periods of the year. Using the model a great number of average monthly and extreme daily values are generated. By statistical analyses of these data possibility of occurrence of high turbidity in certain months is obtained. This information can be used for designing expert system for water quality management of karst springs. Thus, the time series model becomes a valuable tool in management of drinking water quality of the Jadro spring.

Space Shuttle flying qualities and flight control system assessment study, phase 2

NASA Technical Reports Server (NTRS)

Myers, T. T.; Johnston, D. E.; Mcruer, D. T.

1983-01-01

A program of flying qualities experiments as part of the Orbiter Experiments Program (OEX) is defined. Phase 1, published as CR-170391, reviewed flying qualities criteria and shuttle data. The review of applicable experimental and shuttle data to further define the OEX plan is continued. An unconventional feature of this approach is the use of pilot strategy model identification to relate flight and simulator results. Instrumentation, software, and data analysis techniques for pilot model measurements are examined. The relationship between shuttle characteristics and superaugmented aircraft is established. STS flights 1 through 4 are reviewed from the point of view of flying qualities. A preliminary plan for a coordinated program of inflight and simulator research is presented.

Quantitative Prediction of Beef Quality Using Visible and NIR Spectroscopy with Large Data Samples Under Industry Conditions

NASA Astrophysics Data System (ADS)

Qiao, T.; Ren, J.; Craigie, C.; Zabalza, J.; Maltin, Ch.; Marshall, S.

2015-03-01

It is well known that the eating quality of beef has a significant influence on the repurchase behavior of consumers. There are several key factors that affect the perception of quality, including color, tenderness, juiciness, and flavor. To support consumer repurchase choices, there is a need for an objective measurement of quality that could be applied to meat prior to its sale. Objective approaches such as offered by spectral technologies may be useful, but the analytical algorithms used remain to be optimized. For visible and near infrared (VISNIR) spectroscopy, Partial Least Squares Regression (PLSR) is a widely used technique for meat related quality modeling and prediction. In this paper, a Support Vector Machine (SVM) based machine learning approach is presented to predict beef eating quality traits. Although SVM has been successfully used in various disciplines, it has not been applied extensively to the analysis of meat quality parameters. To this end, the performance of PLSR and SVM as tools for the analysis of meat tenderness is evaluated, using a large dataset acquired under industrial conditions. The spectral dataset was collected using VISNIR spectroscopy with the wavelength ranging from 350 to 1800 nm on 234 beef M. longissimus thoracis steaks from heifers, steers, and young bulls. As the dimensionality with the VISNIR data is very high (over 1600 spectral bands), the Principal Component Analysis (PCA) technique was applied for feature extraction and data reduction. The extracted principal components (less than 100) were then used for data modeling and prediction. The prediction results showed that SVM has a greater potential to predict beef eating quality than PLSR, especially for the prediction of tenderness. The infl uence of animal gender on beef quality prediction was also investigated, and it was found that beef quality traits were predicted most accurately in beef from young bulls.

Pregnancy care in Germany, France and Japan: an international comparison of quality and efficiency using structural equation modelling and data envelopment analysis.

PubMed

Rump, A; Schöffski, O

2018-07-01

Healthcare systems in developed countries may differ in financing and organisation. Maternity services and delivery are particularly influenced by culture and habits. In this study, we compared the pregnancy care quality and efficiency of the German, French and Japanese healthcare systems. Comparative healthcare data analysis. In an international comparison based mainly on Organisation for Economic Co-operation and Development (OECD) indicators, we analysed the health resources significantly affecting pregnancy care and quantified its quality using structural equation modelling. Pregnancy care efficiency was studied using data envelopment analysis. Pregnancy output was quantified overall or separately using indicators based on perinatal, neonatal or maternal mortality. The density of obstetricians, midwives, paediatricians and the average annual doctor's consultations were positively and the caesarean delivery rate negatively associated with pregnancy outcome. In the international comparison at an aggregate level, Japan ranked first for pregnancy care quality, whereas Germany and France were positioned in the second part of the ranking. Similarly, at an aggregate level, the Japanese system showed pure technical efficiency, whereas Germany and France revealed mediocre efficiency results. Perinatal, neonatal and maternal care quality and efficiency taken separately were quite similar and mediocre in Germany and France. In Japan, there was a marked difference between a highly effective and efficient care of the unborn and newborn baby, and a rather mediocre quality and efficiency of maternal care. Germany, France, and Japan have to struggle with quality and efficiency issues that are nevertheless different: in Germany and France, disappointing pregnancy care quality does not correspond to the high health care expenditures and lead to low technical efficiency. The Japanese system shows a high variability in outcomes and technical efficiency. Maternal care quality during delivery seems to be a particular issue that could possibly be addressed by legally implementing quality assurance systems with stricter rules for reimbursement in obstetrics. Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Stereotactic Body Radiotherapy Versus Surgery for Medically Operable Stage I Non-Small-Cell Lung Cancer: A Markov Model-Based Decision Analysis

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

Louie, Alexander V.; Rodrigues, George, E-mail: george.rodrigues@lhsc.on.ca; Department of Epidemiology/Biostatistics, University of Western Ontario, London, ON

Purpose: To compare the quality-adjusted life expectancy and overall survival in patients with Stage I non-small-cell lung cancer (NSCLC) treated with either stereotactic body radiation therapy (SBRT) or surgery. Methods and Materials: We constructed a Markov model to describe health states after either SBRT or lobectomy for Stage I NSCLC for a 5-year time frame. We report various treatment strategy survival outcomes stratified by age, sex, and pack-year history of smoking, and compared these with an external outcome prediction tool (Adjuvant{exclamation_point} Online). Results: Overall survival, cancer-specific survival, and other causes of death as predicted by our model correlated closely withmore » those predicted by the external prediction tool. Overall survival at 5 years as predicted by baseline analysis of our model is in favor of surgery, with a benefit ranging from 2.2% to 3.0% for all cohorts. Mean quality-adjusted life expectancy ranged from 3.28 to 3.78 years after surgery and from 3.35 to 3.87 years for SBRT. The utility threshold for preferring SBRT over surgery was 0.90. Outcomes were sensitive to quality of life, the proportion of local and regional recurrences treated with standard vs. palliative treatments, and the surgery- and SBRT-related mortalities. Conclusions: The role of SBRT in the medically operable patient is yet to be defined. Our model indicates that SBRT may offer comparable overall survival and quality-adjusted life expectancy as compared with surgical resection. Well-powered prospective studies comparing surgery vs. SBRT in early-stage lung cancer are warranted to further investigate the relative survival, quality of life, and cost characteristics of both treatment paradigms.« less

Bandwidth Allocation to Interactive Users in DBS-Based Hybrid Internet

DTIC Science & Technology

1998-01-01

policies 12 3.1 Framework for queuing analysis: ON/OFF source traffic model . 13 3.2 Service quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14...minimizing the queuing delay. In consequence, we were interested in ob- taining improvements in the service quality , as perceived by the users. A...the service quality as per- ceived by users. The merit of this approach, first introduced in [8], is the ability to capture the characteristics of the

3D Finite Element Modelling of Cutting Forces in Drilling Fibre Metal Laminates and Experimental Hole Quality Analysis

NASA Astrophysics Data System (ADS)

Giasin, Khaled; Ayvar-Soberanis, Sabino; French, Toby; Phadnis, Vaibhav

2017-02-01

Machining Glass fibre aluminium reinforced epoxy (GLARE) is cumbersome due to distinctively different mechanical and thermal properties of its constituents, which makes it challenging to achieve damage-free holes with the acceptable surface quality. The proposed work focuses on the study of the machinability of thin ( 2.5 mm) GLARE laminate. Drilling trials were conducted to analyse the effect of feed rate and spindle speed on the cutting forces and hole quality. The resulting hole quality metrics (surface roughness, hole size, circularity error, burr formation and delamination) were assessed using surface profilometry and optical scanning techniques. A three dimensional (3D) finite-element (FE) model of drilling GLARE laminate was also developed using ABAQUS/Explicit to help understand the mechanism of drilling GLARE. The homogenised ply-level response of GLARE laminate was considered in the FE model to predict cutting forces in the drilling process.

A statistical model for water quality predictions from a river discharge using coastal observations

NASA Astrophysics Data System (ADS)

Kim, S.; Terrill, E. J.

2007-12-01

Understanding and predicting coastal ocean water quality has benefits for reducing human health risks, protecting the environment, and improving local economies which depend on clean beaches. Continuous observations of coastal physical oceanography increase the understanding of the processes which control the fate and transport of a riverine plume which potentially contains high levels of contaminants from the upstream watershed. A data-driven model of the fate and transport of river plume water from the Tijuana River has been developed using surface current observations provided by a network of HF radar operated as part of a local coastal observatory that has been in place since 2002. The model outputs are compared with water quality sampling of shoreline indicator bacteria, and the skill of an alarm for low water quality is evaluated using the receiver operating characteristic (ROC) curve. In addition, statistical analysis of beach closures in comparison with environmental variables is also discussed.

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.

Development of the quality assessment model of EHR software in family medicine practices: research based on user satisfaction.

PubMed

Kralj, Damir; Kern, Josipa; Tonkovic, Stanko; Koncar, Miroslav

2015-09-09

Family medicine practices (FMPs) make the basis for the Croatian health care system. Use of electronic health record (EHR) software is mandatory and it plays an important role in running these practices, but important functional features still remain uneven and largely left to the will of the software developers. The objective of this study was to develop a novel and comprehensive model for functional evaluation of the EHR software in FMPs, based on current world standards, models and projects, as well as on actual user satisfaction and requirements. Based on previous theoretical and experimental research in this area, we made the initial framework model consisting of six basic categories as a base for online survey questionnaire. Family doctors assessed perceived software quality by using a five-point Likert-type scale. Using exploratory factor analysis and appropriate statistical methods over the collected data, the final optimal structure of the novel model was formed. Special attention was focused on the validity and quality of the novel model. The online survey collected a total of 384 cases. The obtained results indicate both the quality of the assessed software and the quality in use of the novel model. The intense ergonomic orientation of the novel measurement model was particularly emphasised. The resulting novel model is multiple validated, comprehensive and universal. It could be used to assess the user-perceived quality of almost all forms of the ambulatory EHR software and therefore useful to all stakeholders in this area of the health care informatisation.

The evaluation of a virtual education system based on the DeLone and McLean model:  A path analysis.

PubMed

Mahmoodi, Zohreh; Esmaelzadeh-Saeieh, Sara; Lotfi, Razieh; Baradaran Eftekhari, Monir; Akbari Kamrani, Mahnaz; Mehdizadeh Tourzani, Zahra; Salehi, Katayoun

2017-01-01

Background : The Internet has dramatically influenced the introduction of virtual education. Virtual education is a term that involves online education and e-learning. This study was conducted to evaluate a virtual education system based on the DeLone and McLean model. Methods : This descriptive analytical study was conducted using the census method on all the students of the Nursing and Midwifery Department of Alborz University of Medical Sciences who had taken at least one online course in 2016-2017. Data were collected using a researcher-made questionnaire based on the DeLone and McLean model in six domains and then analyzed in SPSS-16 and LISREL-8.8 using the path analysis. Results : The goodness of fit indices (GFI) of the model represent the desirability and good fit of the model, and the rational nature of the adjusted relationships between the variables based on a conceptual model (GFI = 0.98; RMSEA = 0.014).The results showed that system quality has the greatest impact on the net benefits of the system through both direct and indirect paths (β=0.52), service quality through the indirect path (β=0.03) and user satisfaction through the direct path (β=0.73). Conclusions : According to the results, system quality has the greatest overall impact on the net benefits of the system, both directly and indirectly by affecting user satisfaction and the intention to use. System quality should therefore be further emphasized, to use these systems more efficiently.

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

DOE PAGES

King, Zachary A.; Lu, Justin; Drager, Andreas; ...

2015-10-17

In this study, genome-scale metabolic models are mathematically structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scalemore » metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.« less

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

PubMed Central

King, Zachary A.; Lu, Justin; Dräger, Andreas; Miller, Philip; Federowicz, Stephen; Lerman, Joshua A.; Ebrahim, Ali; Palsson, Bernhard O.; Lewis, Nathan E.

2016-01-01

Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data. PMID:26476456

Statistical Downscaling of WRF-Chem Model: An Air Quality Analysis over Bogota, Colombia

NASA Astrophysics Data System (ADS)

Kumar, Anikender; Rojas, Nestor

2015-04-01

Statistical downscaling is a technique that is used to extract high-resolution information from regional scale variables produced by coarse resolution models such as Chemical Transport Models (CTMs). The fully coupled WRF-Chem (Weather Research and Forecasting with Chemistry) model is used to simulate air quality over Bogota. Bogota is a tropical Andean megacity located over a high-altitude plateau in the middle of very complex terrain. The WRF-Chem model was adopted for simulating the hourly ozone concentrations. The computational domains were chosen of 120x120x32, 121x121x32 and 121x121x32 grid points with horizontal resolutions of 27, 9 and 3 km respectively. The model was initialized with real boundary conditions using NCAR-NCEP's Final Analysis (FNL) and a 1ox1o (~111 km x 111 km) resolution. Boundary conditions were updated every 6 hours using reanalysis data. The emission rates were obtained from global inventories, namely the REanalysis of the TROpospheric (RETRO) chemical composition and the Emission Database for Global Atmospheric Research (EDGAR). Multiple linear regression and artificial neural network techniques are used to downscale the model output at each monitoring stations. The results confirm that the statistically downscaled outputs reduce simulated errors by up to 25%. This study provides a general overview of statistical downscaling of chemical transport models and can constitute a reference for future air quality modeling exercises over Bogota and other Colombian cities.

Pitfalls in velocity analysis for strongly contrasting, layered media - Example from the Chalk Group, North Sea

NASA Astrophysics Data System (ADS)

Montazeri, Mahboubeh; Uldall, Anette; Moreau, Julien; Nielsen, Lars

2018-02-01

Knowledge about the velocity structure of the subsurface is critical in key seismic processing sequences, for instance, migration, depth conversion, and construction of initial P- and S-wave velocity models for full-waveform inversion. Therefore, the quality of subsurface imaging is highly dependent upon the quality of the seismic velocity analysis. Based on a case study from the Danish part of the North Sea, we show how interference caused by multiples, converted waves, and thin-layer effects may lead to incorrect velocity estimation, if such effects are not accounted for. Seismic wave propagation inside finely layered reservoir rocks dominated by chalk is described by two-dimensional finite-difference wave field simulation. The rock physical properties used for the modeling are based on an exploration well from the Halfdan field in the Danish sector of the North Sea. The modeling results are compared to seismic data from the study area. The modeling shows that interference of primaries with multiples, converted waves and thin-bed effects can give rise to strong anomalies in standard velocity analysis plots. Consequently, root-mean-square (RMS) velocity profiles may be erroneously picked. In our study area, such mis-picking can introduce errors in, for example, the thickness estimation of the layers near the base of the studied sedimentary strata by 11% to 26%. Tests show that front muting and bandpass filtering cannot significantly improve the quality of velocity analysis in our study. However, we notice that spiking deconvolution applied before velocity analysis may to some extent reduce the impact of interference and, therefore, reduce the risk of erroneous picking of the velocity function.

Psychometrican analysis and dimensional structure of the Brazilian version of melasma quality of life scale (MELASQoL-BP)*

PubMed Central

Maranzatto, Camila Fernandes Pollo; Miot, Hélio Amante; Miot, Luciane Donida Bartoli; Meneguin, Silmara

2016-01-01

Background Although asymptomatic, melasma inflicts significant impact on quality of life. MELASQoL is the main instrument used to assess quality of life associated with melasma, it has been validated in several languages, but its latent dimensional structure and psychometric properties haven´t been fully explored. Objectives To evaluate psychometric characteristics, information and dimensional structure of the Brazilian version of MELASQoL. Methods Survey with patients with facial melasma through socio-demographic questionnaire, DLQI-BRA, MASI and MELASQoL-BP, exploratory and confirmatory factor analysis, internal consistency of MELASQoL and latent dimensions (Cronbach's alpha). The informativeness of the model and items were investigated by the Rasch model (ordinal data). Results We evaluated 154 patients, 134 (87%) were female, mean age (± SD) of 39 (± 8) years, the onset of melasma at 27 (± 8) years, median (p25-p75) of MASI scores , DLQI and MELASQoL 8 (5-15) 2 (1-6) and 30 (17-44). The correlation (rho) of MELASQoL with DLQI and MASI were: 0.70 and 0.36. Exploratory factor analysis identified two latent dimensions: Q1-Q3 and Q4-Q10, which had significantly more adjusted factor structure than the one-dimensional model: Χ2 / gl = 2.03, CFI = 0.95, AGFI = 0.94, RMSEA = 0.08. Cronbach's coefficient for the one-dimensional model and the factors were: 0.95, 0.92 and 0.93. Rasch analysis demonstrated that the use of seven alternatives per item resulted in no increase in the model informativeness. Conclusions MELASQoL-BP showed good psychometric performance and a latent structure of two dimensions. We also identified an oversizing of item alternatives to characterize the aggregate information to each dimension. PMID:27579735

[Association between sleep quality and life function among elderly community residents].

PubMed

Tanaka, Mika; Kusaga, Mari; Tagaya, Hirokuni; Miyoko, I; Oshima, Asami; Watanabe, Chiho

2012-01-01

To investigate the association between sleep quality and life function in an elderly Japanese population. A total of 563 residents of a village in Kumamoto Prefecture aged ≥65 years were asked to fill out a self-administered questionnaire survey from June to July 2010. Sleep quality and life function were respectively evaluated using the Pittsburgh Sleep Quality Index (PSQI) and Basics Check List, which is used to screen elderly individuals at high risk of needing long-term care in the future. As adjustment factors, age, sex, economic situation, residency status, medical history, depression status, and cognitive function were assessed. We examined the relationship between sleep quality and life function using multiple logistic regression analysis, with life function as a dependent variable. Subjects already receiving care or with psychiatric disorders or severe cognitive disturbance were excluded from analysis. Among the subjects (n=395), a significant relationship was found between poor sleep quality and impaired life function in all models. The odds ratio was 1.82 (95% confidence interval: 1.03-3.23) in the final model controlling for all adjustment factors. Our findings here suggest a significant relationship between poor sleep quality and impaired life function among elderly community residents. Given these findings, intervention to improve sleep may help delay or prevent the need for long-term care among elderly individuals.

Applying revised gap analysis model in measuring hotel service quality.

PubMed

Lee, Yu-Cheng; Wang, Yu-Che; Chien, Chih-Hung; Wu, Chia-Huei; Lu, Shu-Chiung; Tsai, Sang-Bing; Dong, Weiwei

2016-01-01

With the number of tourists coming to Taiwan growing by 10-20 % since 2010, the number has increased due to an increasing number of foreign tourists, particularly after deregulation allowed admitting tourist groups, followed later on by foreign individual tourists, from mainland China. The purpose of this study is to propose a revised gap model to evaluate and improve service quality in Taiwanese hotel industry. Thus, service quality could be clearly measured through gap analysis, which was more effective for offering direction in developing and improving service quality. The HOLSERV instrument was used to identify and analyze service gaps from the perceptions of internal and external customers. The sample for this study included three main categories of respondents: tourists, employees, and managers. The results show that five gaps influenced tourists' evaluations of service quality. In particular, the study revealed that Gap 1 (management perceptions vs. customer expectations) and Gap 9 (service provider perceptions of management perceptions vs. service delivery) were more critical than the others in affecting perceived service quality, making service delivery the main area of improvement. This study contributes toward an evaluation of the service quality of the Taiwanese hotel industry from the perspectives of customers, service providers, and managers, which is considerably valuable for hotel managers. It was the aim of this study to explore all of these together in order to better understand the possible gaps in the hotel industry in Taiwan.

[Associations between dormitory environment/other factors and sleep quality of medical students].

PubMed

Zheng, Bang; Wang, Kailu; Pan, Ziqi; Li, Man; Pan, Yuting; Liu, Ting; Xu, Dan; Lyu, Jun

2016-03-01

To investigate the sleep quality and related factors among medical students in China, understand the association between dormitory environment and sleep quality, and provide evidence and recommendations for sleep hygiene intervention. A total of 555 undergraduate students were selected from a medical school of an university in Beijing through stratified-cluster random-sampling to conduct a questionnaire survey by using Chinese version of Pittsburgh Sleep Quality Index (PSQI) and self-designed questionnaire. Analyses were performed by using multiple logistic regression model as well as multilevel linear regression model. The prevalence of sleep disorder was 29.1%(149/512), and 39.1%(200/512) of the students reported that the sleep quality was influenced by dormitory environment. PSQI score was negatively correlated with self-reported rating of dormitory environment (γs=-0.310, P<0.001). Logistic regression analysis showed the related factors of sleep disorder included grade, sleep regularity, self-rated health status, pressures of school work and employment, as well as dormitory environment. RESULTS of multilevel regression analysis also indicated that perception on dormitory environment (individual level) was associated with sleep quality with the dormitory level random effects under control (b=-0.619, P<0.001). The prevalence of sleep disorder was high in medical students, which was associated with multiple factors. Dormitory environment should be taken into consideration when the interventions are taken to improve the sleep quality of students.

10 CFR 503.34 - Inability to comply with applicable environmental requirements.

Code of Federal Regulations, 2014 CFR

2014-01-01

... environmental compliance of the facility, including an analysis of its ability to meet applicable standards and... will be based solely on an analysis of the petitioner's capacity to physically achieve applicable... exemption. All such analysis must be based on accepted analytical techniques, such as air quality modeling...

10 CFR 503.34 - Inability to comply with applicable environmental requirements.

Code of Federal Regulations, 2013 CFR

2013-01-01

... environmental compliance of the facility, including an analysis of its ability to meet applicable standards and... will be based solely on an analysis of the petitioner's capacity to physically achieve applicable... exemption. All such analysis must be based on accepted analytical techniques, such as air quality modeling...

Quality nursing care in the words of nurses.

PubMed

Burhans, Linda Maas; Alligood, Martha Raile

2010-08-01

This paper is a report of a study of the meaning of quality nursing care for practising nurses. Healthcare quality continues to be a subject of intense criticism and debate. Although quality nursing care is vital to patient outcomes and safety, meaningful improvements have been disturbingly slow. Analysis of quality care literature reveals that practising nurses are rarely involved in developing or defining improvement programs for quality nursing care. Therefore, two major study premises were that quality nursing care must be meaningful and relevant to nurses and that uncovering their meaning of quality nursing care could facilitate more effective improvement approaches. Using van Manen's hermeneutic phenomenology, meaning was revealed through analysis of interviews to answer the research question 'What is the lived meaning of quality nursing care for practising nurses?' Twelve nurses practising on medical or surgical adult units at general or intermediate levels of care within acute care hospitals in the United States of America were interviewed. Emerging themes were discovered through empirical and reflective analysis of audiotapes and transcripts. The data were collected in 2008. The revealed lived meaning of quality nursing care for practising nurses was meeting human needs through caring, empathetic, respectful interactions within which responsibility, intentionality and advocacy form an essential, integral foundation. Nurse managers could develop strategies that support nurses better in identifying and delivering quality nursing care reflective of responsibility, caring, intentionality, empathy, respect and advocacy. Nurse educators could modify education curricula to model and teach students the intrinsic qualities identified within these meanings of quality nursing care.

A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Borge, Rafael; Alexandrov, Vassil; José del Vas, Juan; Lumbreras, Julio; Rodríguez, Encarnacion

Meteorological inputs play a vital role on regional air quality modelling. An extensive sensitivity analysis of the Weather Research and Forecasting (WRF) model was performed, in the framework of the Integrated Assessment Modelling System for the Iberian Peninsula (SIMCA) project. Up to 23 alternative model configurations, including Planetary Boundary Layer schemes, Microphysics, Land-surface models, Radiation schemes, Sea Surface Temperature and Four-Dimensional Data Assimilation were tested in a 3 km spatial resolution domain. Model results for the most significant meteorological variables, were assessed through a series of common statistics. The physics options identified to produce better results (Yonsei University Planetary Boundary Layer, WRF Single-Moment 6-class microphysics, Noah Land-surface model, Eta Geophysical Fluid Dynamics Laboratory longwave radiation and MM5 shortwave radiation schemes) along with other relevant user settings (time-varying Sea Surface Temperature and combined grid-observational nudging) where included in a "best case" configuration. This setup was tested and found to produce more accurate estimation of temperature, wind and humidity fields at surface level than any other configuration for the two episodes simulated. Planetary Boundary Layer height predictions showed a reasonable agreement with estimations derived from routine atmospheric soundings. Although some seasonal and geographical differences were observed, the model showed an acceptable behaviour overall. Despite being useful to define the most appropriate setup of the WRF model for air quality modelling over the Iberian Peninsula, this study provides a general overview of WRF sensitivity and can constitute a reference for future mesoscale meteorological modelling exercises.

Using SERVQUAL and Kano research techniques in a patient service quality survey.

PubMed

Christoglou, Konstantinos; Vassiliadis, Chris; Sigalas, Ioakim

2006-01-01

This article presents the results of a service quality study. After an introduction to the SERVQUAL and the Kano research techniques, a Kano analysis of 75 patients from the General Hospital of Katerini in Greece is presented. The service quality criterion used satisfaction and dissatisfaction indices. The Kano statistical analysis process results strengthened the hypothesis of previous research regarding the importance of personal knowledge, the courtesy of the hospital employees and their ability to convey trust and confidence (assurance dimension). Managerial suggestions are made regarding the best way of acting and approaching hospital patients based on the basic SERVQUAL model.

Air quality and future energy system planning

NASA Astrophysics Data System (ADS)

Sobral Mourao, Zenaida; Konadu, Dennis; Lupton, Rick

2016-04-01

Ambient air pollution has been linked to an increasing number of premature deaths throughout the world. Projected increases in demand for food, energy resources and manufactured products will likely contribute to exacerbate air pollution with an increasing impact on human health, agricultural productivity and climate change. Current events such as tampering emissions tests by VW car manufacturers, failure to comply with EU Air Quality directives and WHO guidelines by many EU countries, the problem of smog in Chinese cities and new industrial emissions regulations represent unique challenges but also opportunities for regulators, local authorities and industry. However current models and practices of energy and resource use do not consider ambient air impacts as an integral part of the planing process. Furthermore the analysis of drivers, sources and impacts of air pollution is often fragmented, difficult to understand and lacks effective visualization tools that bring all of these components together. This work aims to develop a model that links impacts of air quality on human health and ecosystems to current and future developments in the energy system, industrial and agricultural activity and patterns of land use. The model will be added to the ForeseerTM tool, which is an integrated resource analysis platform that has been developed at the University of Cambridge initially with funding from BP and more recently through the EPSRC funded Whole Systems Energy Modeling (WholeSEM) project. The basis of the tool is a set of linked physical models for energy, water and land, including the technologies that are used to transform these resources into final services such as housing, food, transport and household goods. The new air quality model will explore different feedback effects between energy, land and atmospheric systems with the overarching goal of supporting better communication about the drivers of air quality and to incorporate concerns about air quality into energy system planning. Some example applications of this work are: (1) to discover conflicts and synergies between air quality regulations and future developments in the energy system and land use change; (2) to show the drivers of air quality in a given spatial context; (3) to explore effective ways to visualize impacts of different energy, land use and emissions control policies on air quality. An initial test case for the Bay Area in California will be presented, extending the scope of the existing California ForeseerTM tool to identify impacts of different policies within the water-energy-land nexus on local air quality.

Emulation and Sensitivity Analysis of the Community Multiscale Air Quality Model for a UK Ozone Pollution Episode.

PubMed

Beddows, Andrew V; Kitwiroon, Nutthida; Williams, Martin L; Beevers, Sean D

2017-06-06

Gaussian process emulation techniques have been used with the Community Multiscale Air Quality model, simulating the effects of input uncertainties on ozone and NO 2 output, to allow robust global sensitivity analysis (SA). A screening process ranked the effect of perturbations in 223 inputs, isolating the 30 most influential from emissions, boundary conditions (BCs), and reaction rates. Community Multiscale Air Quality (CMAQ) simulations of a July 2006 ozone pollution episode in the UK were made with input values for these variables plus ozone dry deposition velocity chosen according to a 576 point Latin hypercube design. Emulators trained on the output of these runs were used in variance-based SA of the model output to input uncertainties. Performing these analyses for every hour of a 21 day period spanning the episode and several days on either side allowed the results to be presented as a time series of sensitivity coefficients, showing how the influence of different input uncertainties changed during the episode. This is one of the most complex models to which these methods have been applied, and here, they reveal detailed spatiotemporal patterns of model sensitivities, with NO and isoprene emissions, NO 2 photolysis, ozone BCs, and deposition velocity being among the most influential input uncertainties.

Network hydraulics inclusion in water quality event detection using multiple sensor stations data.

PubMed

Oliker, Nurit; Ostfeld, Avi

2015-09-01

Event detection is one of the current most challenging topics in water distribution systems analysis: how regular on-line hydraulic (e.g., pressure, flow) and water quality (e.g., pH, residual chlorine, turbidity) measurements at different network locations can be efficiently utilized to detect water quality contamination events. This study describes an integrated event detection model which combines multiple sensor stations data with network hydraulics. To date event detection modelling is likely limited to single sensor station location and dataset. Single sensor station models are detached from network hydraulics insights and as a result might be significantly exposed to false positive alarms. This work is aimed at decreasing this limitation through integrating local and spatial hydraulic data understanding into an event detection model. The spatial analysis complements the local event detection effort through discovering events with lower signatures by exploring the sensors mutual hydraulic influences. The unique contribution of this study is in incorporating hydraulic simulation information into the overall event detection process of spatially distributed sensors. The methodology is demonstrated on two example applications using base runs and sensitivity analyses. Results show a clear advantage of the suggested model over single-sensor event detection schemes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Quantifying Co-benefits of Renewable Energy through Integrated Electricity and Air Quality Modeling

NASA Astrophysics Data System (ADS)

Abel, D.

2016-12-01

This work focuses on the coordination of electricity sector changes with air quality and health improvement strategies through the integration of electricity and air quality models. Two energy models are used to calculate emission perturbations associated with changes in generation technology (20% generation from solar photovoltaics) and demand (future electricity use under a warmer climate). Impacts from increased solar PV penetration are simulated with the electricity model GridView, in collaboration with the National Renewable Energy Laboratory (NREL). Generation results are used to scale power plant emissions from an inventory developed by the Lake Michigan Air Directors Consortium (LADCO). Perturbed emissions and are used to calculate secondary particulate matter with the Community Multiscale Air Quality (CMAQ) model. We find that electricity NOx and SO2 emissions decrease at a rate similar to the total fraction of electricity supplied by solar. Across the Eastern U.S. region, average PM2.5 is reduced 5% over the summer, with highest reduction in regions and on days of greater PM2.5. A similar approach evaluates the air quality impacts of elevated electricity demand under a warmer climate. Meteorology is selected from the North American Regional Climate Change Assessment Program (NARCCAP) and input to a building energy model, eQUEST, to assess electricity demand as a function of ambient temperature. The associated generation and emissions are calculated on a plant-by-plant basis by the MyPower power sector model. These emissions are referenced to the 2011 National Emissions Inventory to be modeled in CMAQ for the Eastern U.S. and extended to health impact evaluation with the Environmental Benefits Mapping and Analysis Program (BenMAP). All results focus on the air quality and health consequences of energy system changes, considering grid-level changes to meet climate and air quality goals.

An integrated fuzzy-based advanced eutrophication simulation model to develop the best management scenarios for a river basin.

PubMed

Srinivas, Rallapalli; Singh, Ajit Pratap

2018-03-01

Assessment of water quality status of a river with respect to its discharge has become prerequisite to sustainable river basin management. The present paper develops an integrated model for simulating and evaluating strategies for water quality management in a river basin management by controlling point source pollutant loadings and operations of multi-purpose projects. Water Quality Analysis and Simulation Program (WASP version 8.0) has been used for modeling the transport of pollutant loadings and their impact on water quality in the river. The study presents a novel approach of integrating fuzzy set theory with an "advanced eutrophication" model to simulate the transmission and distribution of several interrelated water quality variables and their bio-physiochemical processes in an effective manner in the Ganges river basin, India. After calibration, simulated values are compared with the observed values to validate the model's robustness. Fuzzy technique of order preference by similarity to ideal solution (F-TOPSIS) has been used to incorporate the uncertainty associated with the water quality simulation results. The model also simulates five different scenarios for pollution reduction, to determine the maximum pollutant loadings during monsoon and dry periods. The final results clearly indicate how modeled reduction in the rate of wastewater discharge has reduced impacts of pollutants in the downstream. Scenarios suggesting a river discharge rate of 1500 m 3 /s during the lean period, in addition to 25 and 50% reduction in the load rate, are found to be the most effective option to restore quality of river Ganges. Thus, the model serves as an important hydrologic tool to the policy makers by suggesting appropriate remediation action plans.

USER MANUAL FOR THE EPA THIRD-GENERATION AIR QUALITY MODELING SYSTEM (MODELS-3 VERSION 3.0)

EPA Science Inventory

Models-3 is a flexible software system designed to simplify the development and use of environmental assessment and other decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheri...

SYSTEM INSTALLATION AND OPERATION MANUAL FOR THE EPA THIRD-GENERATION AIR QUALITY MODELING SYSTEM (MODELS-3) VERSION 3.0

EPA Science Inventory

Models-3 is a flexible software system designed to simplify the development and use of environmental assessment and other decision support tools. It is designed for applications ranging from regulatory and policy analysis to understanding the complex interactions of atmospheri...

77 FR 41132 - Air Quality Implementation Plans; Alabama; Attainment Plan for the Alabama Portion of the...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-12

... modeling demonstration should include supporting technical analyses and descriptions of all relevant....5 and NO X . The attainment demonstration includes: Technical analyses that locate, identify, and... modeling analysis is a complex technical evaluation that began with selection of the modeling system. The...

Sensitivity Analysis of Dispersion Model Results in the NEXUS Health Study Due to Uncertainties in Traffic-Related Emissions Inputs

EPA Science Inventory

Dispersion modeling tools have traditionally provided critical information for air quality management decisions, but have been used recently to provide exposure estimates to support health studies. However, these models can be challenging to implement, particularly in near-road s...

Triple Value System Dynamics Modeling to Help Stakeholders Engage with Food-Energy-Water Problems

EPA Science Inventory

Triple Value (3V) Community scoping projects and Triple Value Simulation (3VS) models help decision makers and stakeholders apply systems-analysis methodology to complex problems related to food production, water quality, and energy use. 3VS models are decision support tools that...

Insights into the deterministic skill of air quality ensembles from the analysis of AQMEII data

EPA Science Inventory

Simulations from chemical weather models are subject to uncertainties in the input data (e.g. emission inventory, initial and boundary conditions) as well as those intrinsic to the model (e.g. physical parameterization, chemical mechanism). Multi-model ensembles can improve the f...

Estimation of contribution ratios of pollutant sources to a specific section based on an enhanced water quality model.

PubMed

Cao, Bibo; Li, Chuan; Liu, Yan; Zhao, Yue; Sha, Jian; Wang, Yuqiu

2015-05-01

Because water quality monitoring sections or sites could reflect the water quality status of rivers, surface water quality management based on water quality monitoring sections or sites would be effective. For the purpose of improving water quality of rivers, quantifying the contribution ratios of pollutant resources to a specific section is necessary. Because physical and chemical processes of nutrient pollutants are complex in water bodies, it is difficult to quantitatively compute the contribution ratios. However, water quality models have proved to be effective tools to estimate surface water quality. In this project, an enhanced QUAL2Kw model with an added module was applied to the Xin'anjiang Watershed, to obtain water quality information along the river and to assess the contribution ratios of each pollutant source to a certain section (the Jiekou state-controlled section). Model validation indicated that the results were reliable. Then, contribution ratios were analyzed through the added module. Results show that among the pollutant sources, the Lianjiang tributary contributes the largest part of total nitrogen (50.43%), total phosphorus (45.60%), ammonia nitrogen (32.90%), nitrate (nitrite + nitrate) nitrogen (47.73%), and organic nitrogen (37.87%). Furthermore, contribution ratios in different reaches varied along the river. Compared with pollutant loads ratios of different sources in the watershed, an analysis of contribution ratios of pollutant sources for each specific section, which takes the localized chemical and physical processes into consideration, was more suitable for local-regional water quality management. In summary, this method of analyzing the contribution ratios of pollutant sources to a specific section based on the QUAL2Kw model was found to support the improvement of the local environment.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zhu, Ying; Tan, Tuck Lee

2016-04-01

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects.

[Development of whole process quality control and management system of traditional Chinese medicine decoction pieces based on traditional Chinese medicine quality tree].

PubMed

Yu, Wen-Kang; Dong, Ling; Pei, Wen-Xuan; Sun, Zhi-Rong; Dai, Jun-Dong; Wang, Yun

2017-12-01

The whole process quality control and management of traditional Chinese medicine (TCM) decoction pieces is a system engineering, involving the base environment, seeds and seedlings, harvesting, processing and other multiple steps, so the accurate identification of factors in TCM production process that may induce the quality risk, as well as reasonable quality control measures are very important. At present, the concept of quality risk is mainly concentrated in the aspects of management and regulations, etc. There is no comprehensive analysis on possible risks in the quality control process of TCM decoction pieces, or analysis summary of effective quality control schemes. A whole process quality control and management system for TCM decoction pieces based on TCM quality tree was proposed in this study. This system effectively combined the process analysis method of TCM quality tree with the quality risk management, and can help managers to make real-time decisions while realizing the whole process quality control of TCM. By providing personalized web interface, this system can realize user-oriented information feedback, and was convenient for users to predict, evaluate and control the quality of TCM. In the application process, the whole process quality control and management system of the TCM decoction pieces can identify the related quality factors such as base environment, cultivation and pieces processing, extend and modify the existing scientific workflow according to their own production conditions, and provide different enterprises with their own quality systems, to achieve the personalized service. As a new quality management model, this paper can provide reference for improving the quality of Chinese medicine production and quality standardization. Copyright© by the Chinese Pharmaceutical Association.

A comparative analysis of two highly spatially resolved European atmospheric emission inventories

NASA Astrophysics Data System (ADS)

Ferreira, J.; Guevara, M.; Baldasano, J. M.; Tchepel, O.; Schaap, M.; Miranda, A. I.; Borrego, C.

2013-08-01

A reliable emissions inventory is highly important for air quality modelling applications, especially at regional or local scales, which require high resolutions. Consequently, higher resolution emission inventories have been developed that are suitable for regional air quality modelling. This research performs an inter-comparative analysis of different spatial disaggregation methodologies of atmospheric emission inventories. This study is based on two different European emission inventories with different spatial resolutions: 1) the EMEP (European Monitoring and Evaluation Programme) inventory and 2) an emission inventory developed by the TNO (Netherlands Organisation for Applied Scientific Research). These two emission inventories were converted into three distinct gridded emission datasets as follows: (i) the EMEP emission inventory was disaggregated by area (EMEParea) and (ii) following a more complex methodology (HERMES-DIS - High-Elective Resolution Modelling Emissions System - DISaggregation module) to understand and evaluate the influence of different disaggregation methods; and (iii) the TNO gridded emissions, which are based on different emission data sources and different disaggregation methods. A predefined common grid with a spatial resolution of 12 × 12 km2 was used to compare the three datasets spatially. The inter-comparative analysis was performed by source sector (SNAP - Selected Nomenclature for Air Pollution) with emission totals for selected pollutants. It included the computation of difference maps (to focus on the spatial variability of emission differences) and a linear regression analysis to calculate the coefficients of determination and to quantitatively measure differences. From the spatial analysis, greater differences were found for residential/commercial combustion (SNAP02), solvent use (SNAP06) and road transport (SNAP07). These findings were related to the different spatial disaggregation that was conducted by the TNO and HERMES-DIS for the first two sectors and to the distinct data sources that were used by the TNO and HERMES-DIS for road transport. Regarding the regression analysis, the greatest correlation occurred between the EMEParea and HERMES-DIS because the latter is derived from the first, which does not occur for the TNO emissions. The greatest correlations were encountered for agriculture NH3 emissions, due to the common use of the CORINE Land Cover database for disaggregation. The point source emissions (energy industries, industrial processes, industrial combustion and extraction/distribution of fossil fuels) resulted in the lowest coefficients of determination. The spatial variability of SOx differed among the emissions that were obtained from the different disaggregation methods. In conclusion, HERMES-DIS and TNO are two distinct emission inventories, both very well discretized and detailed, suitable for air quality modelling. However, the different databases and distinct disaggregation methodologies that were used certainly result in different spatial emission patterns. This fact should be considered when applying regional atmospheric chemical transport models. Future work will focus on the evaluation of air quality models performance and sensitivity to these spatial discrepancies in emission inventories. Air quality modelling will benefit from the availability of appropriate resolution, consistent and reliable emission inventories.

Model specification in oral health-related quality of life research.

PubMed

Kieffer, Jacobien M; Verrips, Erik; Hoogstraten, Johan

2009-10-01

The aim of this study was to analyze conventional wisdom regarding the construction and analysis of oral health-related quality of life (OHRQoL) questionnaires and to outline statistical complications. Most methods used for developing and analyzing questionnaires, such as factor analysis and Cronbach's alpha, presume psychological constructs to be latent, inferring a reflective measurement model with the underlying assumption of local independence. Local independence implies that the latent variable explains why the variables observed are related. Many OHRQoL questionnaires are analyzed as if they were based on a reflective measurement model; local independence is thus assumed. This assumption requires these questionnaires to consist solely of items that reflect, instead of determine, OHRQoL. The tenability of this assumption is the main topic of the present study. It is argued that OHRQoL questionnaires are a mix of both a formative measurement model and a reflective measurement model, thus violating the assumption of local independence. The implications are discussed.

Quality and provider choice: a multinomial logit-least-squares model with selectivity.

PubMed Central

Haas-Wilson, D; Savoca, E

1990-01-01

A Federal Trade Commission survey of contact lens wearers is used to estimate a multinomial logit-least-squares model of the joint determination of provider choice and quality of care in the contact lens industry. The effect of personal and industry characteristics on a consumer's choice among three types of providers--opticians, ophthalmologists, and optometrists--is estimated via multinomial logit. The regression model of the quality of care has two features that distinguish it from previous work in the area. First, it uses an outcome rather than a structural or process measure of quality. Quality is measured as an index of the presence of seven potentially pathological eye conditions caused by poorly fitted lenses. Second, the model controls for possible selection bias that may arise from the fact that the sample observations on quality are generated by consumers' nonrandom choices of providers. The multinomial logit estimates of provider choice indicate that professional regulations limiting the commercial practices of optometrists shift demand for contact lens services away from optometrists toward ophthalmologists. Further, consumers are more likely to have their lenses fitted by opticians in states that require the licensing of opticians. The regression analysis of variations in quality across provider types shows a strong positive selection bias in the estimate of the quality of care received by consumers of ophthalmologists' services. Failure to control for this selection bias results in an overestimate of the quality of care provided by ophthalmologists. PMID:2312308

Enhanced data validation strategy of air quality monitoring network.

PubMed

Harkat, Mohamed-Faouzi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem

2018-01-01

Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement). Copyright © 2017 Elsevier Inc. All rights reserved.

An analytical approach for predicting pilot induced oscillations

NASA Technical Reports Server (NTRS)

Hess, R. A.

1981-01-01

The optimal control model (OCM) of the human pilot is applied to the study of aircraft handling qualities. Attention is focused primarily on longitudinal tasks. The modeling technique differs from previous applications of the OCM in that considerable effort is expended in simplifying the pilot/vehicle analysis. After briefly reviewing the OCM, a technique for modeling the pilot controlling higher order systems is introduced. Following this, a simple criterion or determining the susceptability of an aircraft to pilot induced oscillations (PIO) is formulated. Finally, a model-based metric for pilot rating prediction is discussed. The resulting modeling procedure provides a relatively simple, yet unified approach to the study of a variety of handling qualities problems.

Instantaneous and time-averaged dispersion and measurement models for estimation theory applications with elevated point source plumes

NASA Technical Reports Server (NTRS)

Diamante, J. M.; Englar, T. S., Jr.; Jazwinski, A. H.

1977-01-01

Estimation theory, which originated in guidance and control research, is applied to the analysis of air quality measurements and atmospheric dispersion models to provide reliable area-wide air quality estimates. A method for low dimensional modeling (in terms of the estimation state vector) of the instantaneous and time-average pollutant distributions is discussed. In particular, the fluctuating plume model of Gifford (1959) is extended to provide an expression for the instantaneous concentration due to an elevated point source. Individual models are also developed for all parameters in the instantaneous and the time-average plume equations, including the stochastic properties of the instantaneous fluctuating plume.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

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).

Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?

NASA Technical Reports Server (NTRS)

Myers, Jerry G.; Young, M.; Goodenow, Debra A.; Keenan, A.; Walton, M.; Boley, L.

2015-01-01

Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.

[GIS and scenario analysis aid to water pollution control planning of river basin].

PubMed

Wang, Shao-ping; Cheng, Sheng-tong; Jia, Hai-feng; Ou, Zhi-dan; Tan, Bin

2004-07-01

The forward and backward algorithms for watershed water pollution control planning were summarized in this paper as well as their advantages and shortages. The spatial databases of water environmental function region, pollution sources, monitoring sections and sewer outlets were built with ARCGIS8.1 as the platform in the case study of Ganjiang valley, Jiangxi province. Based on the principles of the forward algorithm, four scenarios were designed for the watershed pollution control. Under these scenarios, ten sets of planning schemes were generated to implement cascade pollution source control. The investment costs of sewage treatment for these schemes were estimated by means of a series of cost-effective functions; with pollution source prediction, the water quality was modeled with CSTR model for each planning scheme. The modeled results of different planning schemes were visualized through GIS to aid decision-making. With the results of investment cost and water quality attainment as decision-making accords and based on the analysis of the economic endurable capacity for water pollution control in Ganjiang river basin, two optimized schemes were proposed. The research shows that GIS technology and scenario analysis can provide a good guidance to the synthesis, integrity and sustainability aspects for river basin water quality planning.

Development of Water Quality Forecasting Models Based on the SOM-ANN on TMDL Unit Watershed in Nakdong River

NASA Astrophysics Data System (ADS)

KIM, M.; Kim, J.; Baek, J.; Kim, C.; Shin, H.

2013-12-01

It has being happened as flush flood or red/green tide in various natural phenomena due to climate change and indiscreet development of river or land. Especially, water being very important to man should be protected and managed from water quality pollution, and in water resources management, real-time watershed monitoring system is being operated with the purpose of keeping watch and managing on rivers. It is especially important to monitor and forecast water quality in watershed. A study area selected Nak_K as one site among TMDL unit watershed in Nakdong River. This study is to develop a water quality forecasting model connected with making full use of observed data of 8 day interval from Nakdong River Environment Research Center. When forecasting models for each of the BOD, DO, COD, and chlorophyll-a are established considering correlation of various water quality factors, it is needed to select water quality factors showing highly considerable correlation with each water quality factor which is BOD, DO, COD, and chlorophyll-a. For analyzing the correlation of the factors (reservoir discharge, precipitation, air temperature, DO, BOD, COD, Tw, TN, TP, chlorophyll-a), in this study, self-organizing map was used and cross correlation analysis method was also used for comparing results drawn. Based on the results, each forecasting model for BOD, DO, COD, and chlorophyll-a was developed during the short period as 8, 16, 24, 32 days at 8 day interval. The each forecasting model is based on neural network with back propagation algorithm. That is, the study is connected with self-organizing map for analyzing correlation among various factors and neural network model for forecasting of water quality. It is considerably effective to manage the water quality in plenty of rivers, then, it specially is possible to monitor a variety of accidents in water quality. It will work well to protect water quality and to prevent destruction of the environment becoming more and more serious before occurring.

Incremental cost-effectiveness of laser therapy for choroidal neovascularization associated with histoplasmosis.

PubMed

Brown, G C; Brown, M M; Sharma, S; Busbee, B; Brown, H

2000-01-01

Laser photocoagulation has been shown in a large clinical trial to be efficacious in reducing the degree of vision loss occurring secondary to choroidal neovascularization (CNV) associated with ocular histoplasmosis. Nevertheless, data are lacking concerning the impact of the therapy on quality of life and its value to stakeholders in health care. Recently, information concerning the utility value of visual states has become available. Accordingly, the authors undertook to ascertain the cost-effectiveness of laser photocoagulation for the treatment of extrafoveal CNV occurring in eyes with ocular histoplasmosis. Design--A computer simulation, econometric model is presented to evaluate the incremental cost-effectiveness of laser photocoagulation therapy, as compared with the natural course of the disease, for the treatment of patients with extrafoveal CNV associated with ocular histoplasmosis. The model applies long-term visual data from previous clinical trials, utility analysis (which reflects patient perceptions of quality of life), decision analysis with Markov modeling, and present value analysis with discounting to account for the time value of money. Outcome measure--Cost per quality-adjusted life-year gained from treatment. Laser photocoagulation therapy for extrafoveal CNV associated with ocular histoplasmosis costs $4167 1999 US dollars (at a 3% discount rate) for each quality-adjusted life-year gained from treatment. Sensitivity analysis shows that changing the discount rate substantially alters the cost-effectiveness, with a value of $1339 at a 0% discount rate and $56,250 at a 10% discount rate. Compared with therapeutic modalities for other disease entities, laser therapy for the treatment of extrafoveal CNV associated with ocular histoplasmosis appears to be a cost-effective treatment from the patient preference-based point of view.

Mediators of the effects of rice intake on health in individuals consuming a traditional Japanese diet centered on rice

PubMed Central

Toyomaki, Atsuhito; Miyazaki, Akane; Nakai, Yukiei; Yamaguchi, Atsuko; Kubo, Chizuru; Suzuki, Junko; Ohkubo, Iwao; Shimizu, Mari; Musashi, Manabu; Kiso, Yoshinobu; Kusumi, Ichiro

2017-01-01

Although the Japanese diet is believed to be balanced and healthy, its benefits have been poorly investigated, especially in terms of effects on mental health. We investigated dietary patterns and physical and mental health in the Japanese population using an epidemiological survey to determine the health benefits of the traditional Japanese diet. Questionnaires to assess dietary habits, quality of life, sleep quality, impulsivity, and depression severity were distributed to 550 randomly selected middle-aged and elderly individuals. Participants with any physical or mental disease were excluded. Two-hundred and seventy-eight participants were selected for the final statistical analysis. We determined rice to be one of the most traditional foods in Japanese cuisine. Scores for each questionnaire were computed, and the correlations between rice intake and health indices were assessed. When analyzing the direct correlations between rice intake and health indices, we found only two correlations, namely those with quality of life (vitality) and sleep quality. Path analysis using structural equation modeling was performed to investigate the association between rice intake and health, with indirect effects included in the model. Additional associations between rice intake and health were explained using this model when compared to those using direct correlation analysis. Path analysis was used to identify mediators of the rice-health association. These mediators were miso (soybean paste) soup, green tea, and natto (fermented soybean) intake. Interestingly, these mediators have been major components of the Japanese diet since 1975, which has been considered one of the healthiest diets since the 1960s. Our results indicate that the combination of rice with other healthy foods, which is representative of the traditional Japanese diet, may contribute to improvements in physical and mental health. PMID:28968452

Rapid determination of sugar level in snack products using infrared spectroscopy.

PubMed

Wang, Ting; Rodriguez-Saona, Luis E

2012-08-01

Real-time spectroscopic methods can provide a valuable window into food manufacturing to permit optimization of production rate, quality and safety. There is a need for cutting edge sensor technology directed at improving efficiency, throughput and reliability of critical processes. The aim of the research was to evaluate the feasibility of infrared systems combined with chemometric analysis to develop rapid methods for determination of sugars in cereal products. Samples were ground and spectra were collected using a mid-infrared (MIR) spectrometer equipped with a triple-bounce ZnSe MIRacle attenuated total reflectance accessory or Fourier transform near infrared (NIR) system equipped with a diffuse reflection-integrating sphere. Sugar contents were determined using a reference HPLC method. Partial least squares regression (PLSR) was used to create cross-validated calibration models. The predictability of the models was evaluated on an independent set of samples and compared with reference techniques. MIR and NIR spectra showed characteristic absorption bands for sugars, and generated excellent PLSR models (sucrose: SEP < 1.7% and r > 0.96). Multivariate models accurately and precisely predicted sugar level in snacks allowing for rapid analysis. This simple technique allows for reliable prediction of quality parameters, and automation enabling food manufacturers for early corrective actions that will ultimately save time and money while establishing a uniform quality. The U.S. snack food industry generates billions of dollars in revenue each year and vibrational spectroscopic methods combined with pattern recognition analysis could permit optimization of production rate, quality, and safety of many food products. This research showed that infrared spectroscopy is a powerful technique for near real-time (approximately 1 min) assessment of sugar content in various cereal products. © 2012 Institute of Food Technologists®

Metrics for the Evaluation the Utility of Air Quality Forecasting

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Information Landscaping: Information Mapping, Charting, Querying and Reporting Techniques for Total Quality Knowledge Management.

ERIC Educational Resources Information Center

Tsai, Bor-sheng

2003-01-01

Total quality management and knowledge management are merged and used as a conceptual model to direct and develop information landscaping techniques through the coordination of information mapping, charting, querying, and reporting. Goals included: merge citation analysis and data mining, and apply data visualization and information architecture…

Writing Week-Journals to Improve the Writing Quality of Fourth-Graders' Compositions

ERIC Educational Resources Information Center

Rosário, Pedro; Högemann, Julia; Núñez, José Carlos; Vallejo, Guillermo; Cunha, Jennifer; Oliveira, Vera; Fuentes, Sonia; Rodrigues, Celestino

2017-01-01

Students' writing problems are a global educational concern and is in need of particular attention. This study aims to examine the impact of providing extra writing opportunities (i.e., writing journals) on the quality of writing compositions. A longitudinal cluster-randomized controlled design using a multilevel modeling analysis with 182 fourth…

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

EPA Science Inventory

This presentation focuses on the dynamic evaluation of the CMAQ model over the continental United States using multi-decadal simulations for the period from 1990 to 2010 to examine how well the changes in observed ozone air quality induced by variations in meteorology and/or emis...

Using AMLO to Improve the Quality of Teacher Education Outcomes

ERIC Educational Resources Information Center

Al-Shammari, Zaid

2012-01-01

This study aims to find ways to improve learning outcomes in teacher education courses by using an Analysis Model for Learning Outcomes (AMLO). It addresses the improvement of the quality of teacher education by analyzing learning outcomes and implementing curriculum modifications related to specific learning objectives and their effects on…

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…

Insights into future air quality: a multipollutant analysis of future scenarios using the MARKAL model

EPA Science Inventory

In this presentation, we will provide an update on the development and evaluation of the Air Quality Futures (AQF) scenarios. These scenarios represent widely different assumptions regarding the evolution of the U.S. energy system over the next 40 years. The four AQF scenarios di...

Modelling Student Satisfaction and Motivation in the Integrated Educational Environment: An Empirical study

ERIC Educational Resources Information Center

Stukalina, Yulia

2016-01-01

Purpose: The purpose of this paper is to explore some issues related to enhancing the quality of educational services provided by a university in the agenda of integrating quality assurance activities and strategic management procedures. Design/methodology/approach: Employing multiple regression analysis the author has examined some factors that…

Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis.

PubMed

Nespeca, Maurilio Gustavo; Hatanaka, Rafael Rodrigues; Flumignan, Danilo Luiz; de Oliveira, José Eduardo

2018-01-01

Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10), 50% (T50), and 85% (T85) recovery; cetane index; and biodiesel content) through attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and the multivariate regression method, partial least square (PLS). For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000-650 cm -1 . The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time.

Rapid and Simultaneous Prediction of Eight Diesel Quality Parameters through ATR-FTIR Analysis

PubMed Central

Hatanaka, Rafael Rodrigues; Flumignan, Danilo Luiz; de Oliveira, José Eduardo

2018-01-01

Quality assessment of diesel fuel is highly necessary for society, but the costs and time spent are very high while using standard methods. Therefore, this study aimed to develop an analytical method capable of simultaneously determining eight diesel quality parameters (density; flash point; total sulfur content; distillation temperatures at 10% (T10), 50% (T50), and 85% (T85) recovery; cetane index; and biodiesel content) through attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and the multivariate regression method, partial least square (PLS). For this purpose, the quality parameters of 409 samples were determined using standard methods, and their spectra were acquired in ranges of 4000–650 cm−1. The use of the multivariate filters, generalized least squares weighting (GLSW) and orthogonal signal correction (OSC), was evaluated to improve the signal-to-noise ratio of the models. Likewise, four variable selection approaches were tested: manual exclusion, forward interval PLS (FiPLS), backward interval PLS (BiPLS), and genetic algorithm (GA). The multivariate filters and variables selection algorithms generated more fitted and accurate PLS models. According to the validation, the FTIR/PLS models presented accuracy comparable to the reference methods and, therefore, the proposed method can be applied in the diesel routine monitoring to significantly reduce costs and analysis time. PMID:29629209

“Summary of the Emission Inventories compiled for the ...

EPA Pesticide Factsheets

We present a summary of the emission inventories from the US, Canada, and Mexico developed for the second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Activities in this second phase are focused on the application and evaluation of coupled meteorology-chemistry models over both North America and Europe using common emissions and boundary conditions for all modeling groups for the years of 2006 and 2010. We will compare the emission inventories developed for these two years focusing on the SO2 and NOx reductions over these years and compare with socio-economic data. In addition we will highlight the differences in the inventories for the US and Canada compared with the inventories used in the phase 1 of this project. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the 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 pollut

Proteomic analysis of early-stage embryos: implications for egg quality in hapuku (Polyprion oxygeneios).

PubMed

Kohn, Yair Y; Symonds, Jane E; Kleffmann, Torsten; Nakagawa, Shinichi; Lagisz, Malgorzata; Lokman, P Mark

2015-12-01

In order to develop biomarkers that may help predict the egg quality of captive hapuku (Polyprion oxygeneios) and provide potential avenues for its manipulation, the present study (1) sequenced the proteome of early-stage embryos using isobaric tag for relative and absolute quantification analysis, and (2) aimed to establish the predictive value of the abundance of identified proteins with regard to egg quality through regression analysis. Egg quality was determined for eight different egg batches by blastomere symmetry scores. In total, 121 proteins were identified and assigned to one of nine major groups according to their function/pathway. A mixed-effects model analysis revealed a decrease in relative protein abundance that correlated with (decreasing) egg quality in one major group (heat-shock proteins). No differences were found in the other protein groups. Linear regression analysis, performed for each identified protein separately, revealed seven proteins that showed a significant decrease in relative abundance with reduced blastomere symmetry: two correlates that have been named in other studies (vitellogenin, heat-shock protein-70) and a further five new candidate proteins (78 kDa glucose-regulated protein, elongation factor-2, GTP-binding nuclear protein Ran, iduronate 2-sulfatase and 6-phosphogluconate dehydrogenase). Notwithstanding issues associated with multiple statistical testing, we conclude that these proteins, and especially iduronate 2-sulfatase and the generic heat-shock protein group, could serve as biomarkers of egg quality in hapuku.

Environmetric data interpretation to assess the water quality of Maritsa River catchment.

PubMed

Papazova, Petia; Simeonova, Pavlina

2013-01-01

Maritsa River is one of the largest rivers flowing on Bulgarian territory. The quality of its waters is of substantial importance for irrigation, industrial, recreation and domestic use. Besides, part of the river is flowing on Turkish territory and the control and management of the Maritsa catchment is of mutual interst for the neighboring countires. Thus, performing interpretation and modeling of the river water quality is a major environmetric problem. Two multivariate statstical methods (Cluster analysis/CA/and Principal components analysis/PCA/) were applied for model assessment of the water quality of Maritsa River on Bulgarian territory. The study used long-term monitoring data from 21 sampling sites characterized by 8 surface water quality indicators. The application of CA to the indicators results in 3 significant clusters showing the impact of biological, anthropogenic and eutrophication sources. For further assessment of the monitoring data, PCA was implemented, which identified, again,three latent factors confirming, in principle, the clustering output. The latent factors were conditionally named "biologic", "anthropogenic" and "eutrophication" source. Their identification coinside correctly to the location of real pollution sources along the Maritsa River catchment. The linkage of the sampling sites along the river flow by CA identified four special patterns separated by specific tracers levels: biological and anthropogenic major impact for pattern 1, euthrophication major impact for pattern 2, background levels for pattern 3 and eutrophication and agricultural major impact for pattern 4. The apportionment models of the pollution determined the contribution of each one of identified pollution factors to the total concentration of each one of the water quality parameters. Thus, a better risk management of the surface water quality is achieved both on local and national level.

Testing a pharmacist-patient relationship quality model among older persons with diabetes.

PubMed

Worley, Marcia M

2006-03-01

Considering recent changes to the Medicare program, pharmacists will have unique opportunities to be reimbursed for providing Medication Therapy Management Services to older persons with diabetes. A high-quality pharmacist-patient relationship can lay the foundation for effective provision of Medication Therapy Management Services and improved care in this cohort. To test a pharmacist-patient relationship quality model in a group of older persons with diabetes from the patient's perspective. Antecedents to relationship quality were pharmacist participative behavior/patient-centeredness of relationship, patient participative behavior, and pharmacist-patient interpersonal communication. Pharmacist-patient relationship commitment was the outcome of relationship quality studied. Data were collected via mailed questionnaire from a random sample of 600 community-dwelling adults in the United States who (1) were 65 years of age and older, (2) had type 1 or type 2 diabetes, (3) used at least one prescription medication to treat their diabetes, and (4) used some type of nonmail order pharmacy as their primary source of obtaining prescription medications. Model relationships were tested using path analysis. The adjusted response rate was 41.6% (221/531). The models explained 47% and 49% of the variance in relationship quality and relationship commitment, respectively. In the relationship quality model, pharmacist participative behavior/patient-centeredness of relationship (beta=.51, P<.001) and pharmacist-patient interpersonal communication (beta=.17, P=.008) had direct effects on relationship quality. In the relationship commitment model, relationship quality had a direct effect on relationship commitment (beta=.60, P<.001). Pharmacist participative behavior/patient-centeredness and pharmacist-patient interpersonal communication had indirect effects on relationship commitment through their effects on relationship quality, which is a mediator in the model. Results affirm findings from previous research showing that patients' perceptions of pharmacist participative behavior/patient-centeredness of relationship and pharmacist-patient interpersonal communication are positively related to perceptions of relationship quality. Also, relationship quality is a strong mediator between pharmacist participative behavior/patient-centeredness of relationship and relationship commitment, as well as between pharmacist-patient interpersonal communication and relationship commitment.

A Comparison of Two Balance Calibration Model Building Methods

NASA Technical Reports Server (NTRS)

DeLoach, Richard; Ulbrich, Norbert

2007-01-01

Simulated strain-gage balance calibration data is used to compare the accuracy of two balance calibration model building methods for different noise environments and calibration experiment designs. The first building method obtains a math model for the analysis of balance calibration data after applying a candidate math model search algorithm to the calibration data set. The second building method uses stepwise regression analysis in order to construct a model for the analysis. Four balance calibration data sets were simulated in order to compare the accuracy of the two math model building methods. The simulated data sets were prepared using the traditional One Factor At a Time (OFAT) technique and the Modern Design of Experiments (MDOE) approach. Random and systematic errors were introduced in the simulated calibration data sets in order to study their influence on the math model building methods. Residuals of the fitted calibration responses and other statistical metrics were compared in order to evaluate the calibration models developed with different combinations of noise environment, experiment design, and model building method. Overall, predicted math models and residuals of both math model building methods show very good agreement. Significant differences in model quality were attributable to noise environment, experiment design, and their interaction. Generally, the addition of systematic error significantly degraded the quality of calibration models developed from OFAT data by either method, but MDOE experiment designs were more robust with respect to the introduction of a systematic component of the unexplained variance.

Environmental impact of geopressure - geothermal cogeneration facility on wetland resources and socioeconomic characteristics in Louisiana Gulf Coast region. Final report, October 10, 1983-September 31, 1984

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

Smalley, A.M.; Saleh, F.M.S.; Fontenot, M.

1984-08-01

Baseline data relevant to air quality are presented. The following are also included: geology and resource assessment, design well prospects in southwestern Louisiana, water quality monitoring, chemical analysis subsidence, microseismicity, geopressure-geothermal subsidence modeling, models of compaction and subsidence, sampling handling and preparation, brine chemistry, wetland resources, socioeconomic characteristics, impacts on wetlands, salinity, toxic metals, non-metal toxicants, temperature, subsidence, and socioeconomic impacts. (MHR)

The Effect of Orem's Self-Care Model on Quality of Life in Patients with Migraine: a Randomized Clinical Trial.

PubMed

Mahmoudzadeh Zarandi, Fatemeh; Raiesifar, Afsaneh; Ebadi, Abbas

2016-03-01

Many aspects of the lives of migraineurs are commonly affected by the condition, including occupational affairs, social and family life, responsibilities and ultimately the quality of life. This study was designed to determine the effect of orem's self-care nursing model on quality of life in patients with a migraine. This study was carried out in Tehran, Iran. According to the pre-post design of the randomized clinical trial, 88 patients were selected. After obtaining approval from the ethics committee of the Baqiyatallah Medical Sciences University's Research Deputy; Patients who signed the informed consent aged 20-55 years and without any more disease or disability affecting the quality of life were selected and randomly assigned to a group. Data collection tools were a demographic questionnaire, general health survey short form (SF36), and Orem cognition form and self-care checklist. Self-care model were held as four 30-45 minutes training sessions based on self-care deficit needs for the experimental group. The quality of life scores was measured in two stages, before and three months after intervention then were compared in both groups. Data were analyzed with statistical software SPSS and use of descriptive analysis tests, Chi-square, Mann-Whitney u and Wilcoxon. The final analysis was performed on 43 experimental and 40 controls. No significant difference was detected in the two groups in terms of demographic variables (P>0.05). All dimensions of quality of life including physical functioning, physical role limitation, body pain, general health, vitality, social functioning and emotional role limitation and mental health in the experimental group showed a significant increase after intervention compared to the control group (P<0.05). It was concluded that performing Orem's self-care nursing model improves function and overall quality of life and reduces the high cost of a migraine and migraine-related disability to individuals and society.

Using the HOMER Model in Air Quality Analysis

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

Not Available

2004-08-01

HOMER, the micropower optimization model created by the National Renewable Energy Laboratory (NREL), helps design and analyze off-grid and grid-connected power systems. One of HOMER's newest features is its enhanced ability to estimate air emissions for different micropower systems.

Preservation of protein clefts in comparative models.

PubMed

Piedra, David; Lois, Sergi; de la Cruz, Xavier

2008-01-16

Comparative, or homology, modelling of protein structures is the most widely used prediction method when the target protein has homologues of known structure. Given that the quality of a model may vary greatly, several studies have been devoted to identifying the factors that influence modelling results. These studies usually consider the protein as a whole, and only a few provide a separate discussion of the behaviour of biologically relevant features of the protein. Given the value of the latter for many applications, here we extended previous work by analysing the preservation of native protein clefts in homology models. We chose to examine clefts because of their role in protein function/structure, as they are usually the locus of protein-protein interactions, host the enzymes' active site, or, in the case of protein domains, can also be the locus of domain-domain interactions that lead to the structure of the whole protein. We studied how the largest cleft of a protein varies in comparative models. To this end, we analysed a set of 53507 homology models that cover the whole sequence identity range, with a special emphasis on medium and low similarities. More precisely we examined how cleft quality - measured using six complementary parameters related to both global shape and local atomic environment, depends on the sequence identity between target and template proteins. In addition to this general analysis, we also explored the impact of a number of factors on cleft quality, and found that the relationship between quality and sequence identity varies depending on cleft rank amongst the set of protein clefts (when ordered according to size), and number of aligned residues. We have examined cleft quality in homology models at a range of seq.id. levels. Our results provide a detailed view of how quality is affected by distinct parameters and thus may help the user of comparative modelling to determine the final quality and applicability of his/her cleft models. In addition, the large variability in model quality that we observed within each sequence bin, with good models present even at low sequence identities (between 20% and 30%), indicates that properly developed identification methods could be used to recover good cleft models in this sequence range.

Multisite Evaluation of a Data Quality Tool for Patient-Level Clinical Data Sets

PubMed Central

Huser, Vojtech; DeFalco, Frank J.; Schuemie, Martijn; Ryan, Patrick B.; Shang, Ning; Velez, Mark; Park, Rae Woong; Boyce, Richard D.; Duke, Jon; Khare, Ritu; Utidjian, Levon; Bailey, Charles

2016-01-01

Introduction: Data quality and fitness for analysis are crucial if outputs of analyses of electronic health record data or administrative claims data should be trusted by the public and the research community. Methods: We describe a data quality analysis tool (called Achilles Heel) developed by the Observational Health Data Sciences and Informatics Collaborative (OHDSI) and compare outputs from this tool as it was applied to 24 large healthcare datasets across seven different organizations. Results: We highlight 12 data quality rules that identified issues in at least 10 of the 24 datasets and provide a full set of 71 rules identified in at least one dataset. Achilles Heel is a freely available software that provides a useful starter set of data quality rules with the ability to add additional rules. We also present results of a structured email-based interview of all participating sites that collected qualitative comments about the value of Achilles Heel for data quality evaluation. Discussion: Our analysis represents the first comparison of outputs from a data quality tool that implements a fixed (but extensible) set of data quality rules. Thanks to a common data model, we were able to compare quickly multiple datasets originating from several countries in America, Europe and Asia. PMID:28154833