Sample records for quality model results

  1. FIRST RESULTS FROM OPERATIONAL TESTING OF THE U.S. EPA MODELS-3 COMMUNITY MULTISCALE MODEL FOR AIR QUALITY (CMAQ)

    EPA Science Inventory

    The Models 3 / Community Multiscale Model for Air Quality (CMAQ) has been designed for one-atmosphere assessments for multiple pollutants including ozone (O3), particulate matter (PM10, PM2.5), and acid / nutrient deposition. In this paper we report initial results of our evalu...

  2. Cost-effective water quality assessment through the integration of monitoring data and modeling results

    NASA Astrophysics Data System (ADS)

    Lobuglio, Joseph N.; Characklis, Gregory W.; Serre, Marc L.

    2007-03-01

    Sparse monitoring data and error inherent in water quality models make the identification of waters not meeting regulatory standards uncertain. Additional monitoring can be implemented to reduce this uncertainty, but it is often expensive. These costs are currently a major concern, since developing total maximum daily loads, as mandated by the Clean Water Act, will require assessing tens of thousands of water bodies across the United States. This work uses the Bayesian maximum entropy (BME) method of modern geostatistics to integrate water quality monitoring data together with model predictions to provide improved estimates of water quality in a cost-effective manner. This information includes estimates of uncertainty and can be used to aid probabilistic-based decisions concerning the status of a water (i.e., impaired or not impaired) and the level of monitoring needed to characterize the water for regulatory purposes. This approach is applied to the Catawba River reservoir system in western North Carolina as a means of estimating seasonal chlorophyll a concentration. Mean concentration and confidence intervals for chlorophyll a are estimated for 66 reservoir segments over an 11-year period (726 values) based on 219 measured seasonal averages and 54 model predictions. Although the model predictions had a high degree of uncertainty, integration of modeling results via BME methods reduced the uncertainty associated with chlorophyll estimates compared with estimates made solely with information from monitoring efforts. Probabilistic predictions of future chlorophyll levels on one reservoir are used to illustrate the cost savings that can be achieved by less extensive and rigorous monitoring methods within the BME framework. While BME methods have been applied in several environmental contexts, employing these methods as a means of integrating monitoring and modeling results, as well as application of this approach to the assessment of surface water monitoring networks

  3. Modelled air pollution levels versus EC air quality legislation - results from high resolution simulation.

    PubMed

    Chervenkov, Hristo

    2013-12-01

    An appropriate method for evaluating the air quality of a certain area is to contrast the actual air pollution levels to the critical ones, prescribed in the legislative standards. The application of numerical simulation models for assessing the real air quality status is allowed by the legislation of the European Community (EC). This approach is preferable, especially when the area of interest is relatively big and/or the network of measurement stations is sparse, and the available observational data are scarce, respectively. Such method is very efficient for similar assessment studies due to continuous spatio-temporal coverage of the obtained results. In the study the values of the concentration of the harmful substances sulphur dioxide, (SO2), nitrogen dioxide (NO2), particulate matter - coarse (PM10) and fine (PM2.5) fraction, ozone (O3), carbon monoxide (CO) and ammonia (NH3) in the surface layer obtained from modelling simulations with resolution 10 km on hourly bases are taken to calculate the necessary statistical quantities which are used for comparison with the corresponding critical levels, prescribed in the EC directives. For part of them (PM2.5, CO and NH3) this is done for first time with such resolution. The computational grid covers Bulgaria entirely and some surrounding territories and the calculations are made for every year in the period 1991-2000. The averaged over the whole time slice results can be treated as representative for the air quality situation of the last decade of the former century.

  4. Evaluation of Observation-Fused Regional Air Quality Model Results for Population Air Pollution Exposure Estimation

    PubMed Central

    Chen, Gang; Li, Jingyi; Ying, Qi; Sherman, Seth; Perkins, Neil; Rajeshwari, Sundaram; Mendola, Pauline

    2014-01-01

    In this study, Community Multiscale Air Quality (CMAQ) model was applied to predict ambient gaseous and particulate concentrations during 2001 to 2010 in 15 hospital referral regions (HRRs) using a 36-km horizontal resolution domain. An inverse distance weighting based method was applied to produce exposure estimates based on observation-fused regional pollutant concentration fields using the differences between observations and predictions at grid cells where air quality monitors were located. Although the raw CMAQ model is capable of producing satisfying results for O3 and PM2.5 based on EPA guidelines, using the observation data fusing technique to correct CMAQ predictions leads to significant improvement of model performance for all gaseous and particulate pollutants. Regional average concentrations were calculated using five different methods: 1) inverse distance weighting of observation data alone, 2) raw CMAQ results, 3) observation-fused CMAQ results, 4) population-averaged raw CMAQ results and 5) population-averaged fused CMAQ results. It shows that while O3 (as well as NOx) monitoring networks in the HRR regions are dense enough to provide consistent regional average exposure estimation based on monitoring data alone, PM2.5 observation sites (as well as monitors for CO, SO2, PM10 and PM2.5 components) are usually sparse and the difference between the average concentrations estimated by the inverse distance interpolated observations, raw CMAQ and fused CMAQ results can be significantly different. Population-weighted average should be used to account spatial variation in pollutant concentration and population density. Using raw CMAQ results or observations alone might lead to significant biases in health outcome analyses. PMID:24747248

  5. Evaluating and improving the results of air quality models in Texas using TES, AIRS and other satellite data

    NASA Astrophysics Data System (ADS)

    Osterman, G.; Harper, C.; Estes, M.; Zhao, W.; Bowman, K.; Pierce, B.; Irion, B.; Kahn, B.; Al-Saadi, J.

    2008-05-01

    The Houston/Galveston/Brazoria (HGB) area of Texas has been classified as in moderate nonattainment of the Environmental Protection Agency (EPA) 8-hour standard for ground level ozone since April 30, 2004. The Texas Commission on Environmental Quality uses photochemical model results as one of its primary tools to develop strategies to bring the HGB area into attainment with the EPA standard. The state of Texas then includes the strategies into a revised version of its State Implementation Plan (SIP). We will discuss efforts that have been or soon will be underway to use satellite data to evaluate and improve the meteorological and photochemical modeling efforts at TCEQ. In particular we will show the use of GOES, AIRS and TES data to improve the ability to model, using the MM5 model, the meteorological conditions over Texas and the Gulf of Mexico. The meteorological fields are then used as one of the inputs to the CAMx air quality model used at TCEQ. We will discuss the use of chemical transport model results as initial and boundary conditions which are a key uncertainty in the modeling of the air above Houston. We will also discuss the use of TES data to assist in the evaluation of preliminary model results generated by TCEQ for time periods in 2005. The satellite data will provide key information on ozone and carbon monoxide concentrations away from surface monitors in the troposphere. We will show how satellite data is becoming a key tool in the effort to improve air quality in the HGB area and one that can easily applied for use in other regions of the country.

  6. A Review of Surface Water Quality Models

    PubMed Central

    Li, Shibei; Jia, Peng; Qi, Changjun; Ding, Feng

    2013-01-01

    Surface water quality models can be useful tools to simulate and predict the levels, distributions, and risks of chemical pollutants in a given water body. The modeling results from these models under different pollution scenarios are very important components of environmental impact assessment and can provide a basis and technique support for environmental management agencies to make right decisions. Whether the model results are right or not can impact the reasonability and scientificity of the authorized construct projects and the availability of pollution control measures. We reviewed the development of surface water quality models at three stages and analyzed the suitability, precisions, and methods among different models. Standardization of water quality models can help environmental management agencies guarantee the consistency in application of water quality models for regulatory purposes. We concluded the status of standardization of these models in developed countries and put forward available measures for the standardization of these surface water quality models, especially in developing countries. PMID:23853533

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

    PubMed Central

    Mlakar, Mitja

    2016-01-01

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

  8. Innovations in projecting emissions for air quality modeling

    EPA Science Inventory

    Air quality modeling is used in setting air quality standards and in evaluating their costs and benefits. Historically, modeling applications have projected emissions and the resulting air quality only 5 to 10 years into the future. Recognition that the choice of air quality mana...

  9. 3D Air Quality and the Clean Air Interstate Rule: Lagrangian Sampling of CMAQ Model Results to Aid Regional Accountability Metrics

    NASA Technical Reports Server (NTRS)

    Fairlie, T. D.; Szykman, Jim; Pierce, Robert B.; Gilliland, A. B.; Engel-Cox, Jill; Weber, Stephanie; Kittaka, Chieko; Al-Saadi, Jassim A.; Scheffe, Rich; Dimmick, Fred; hide

    2008-01-01

    The Clean Air Interstate Rule (CAIR) is expected to reduce transport of air pollutants (e.g. fine sulfate particles) in nonattainment areas in the Eastern United States. CAIR highlights the need for an integrated air quality observational and modeling system to understand sulfate as it moves in multiple dimensions, both spatially and temporally. Here, we demonstrate how results from an air quality model can be combined with a 3d monitoring network to provide decision makers with a tool to help quantify the impact of CAIR reductions in SO2 emissions on regional transport contributions to sulfate concentrations at surface monitors in the Baltimore, MD area, and help improve decision making for strategic implementation plans (SIPs). We sample results from the Community Multiscale Air Quality (CMAQ) model using ensemble back trajectories computed with the NASA Langley Research Center trajectory model to provide Lagrangian time series and vertical profile information, that can be compared with NASA satellite (MODIS), EPA surface, and lidar measurements. Results are used to assess the regional transport contribution to surface SO4 measurements in the Baltimore MSA, and to characterize the dominant source regions for low, medium, and high SO4 episodes.

  10. Modeling Quality-Adjusted Life Expectancy Loss Resulting from Tobacco Use in the United States

    ERIC Educational Resources Information Center

    Kaplan, Robert M.; Anderson, John P.; Kaplan, Cameron M.

    2007-01-01

    Purpose: To describe the development of a model for estimating the effects of tobacco use upon Quality Adjusted Life Years (QALYs) and to estimate the impact of tobacco use on health outcomes for the United States (US) population using the model. Method: We obtained estimates of tobacco consumption from 6 years of the National Health Interview…

  11. Southern P indices, water quality data, and modeling results: a comparison

    USDA-ARS?s Scientific Manuscript database

    Phosphorus (P) indices in the south frequently produce different results for similar conditions. After collecting data from benchmark sites throughout the south (6 Arkansas, 1 Georgia, 2 Mississippi, 4 North Carolina, 4 Oklahoma, and 4 Texas site/treatment water quality and land treatment data sets...

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

    PubMed

    Petek, Davorina; Mlakar, Mitja

    2016-09-01

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

  13. 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

  14. Evaluation of data assimilation techniques for a mesoscale meteorological model and their effects on air quality model results

    NASA Astrophysics Data System (ADS)

    Amicarelli, A.; Gariazzo, C.; Finardi, S.; Pelliccioni, A.; Silibello, C.

    2008-05-01

    Data assimilation techniques are methods to limit the growth of errors in a dynamical model by allowing observations distributed in space and time to force (nudge) model solutions. They have become common for meteorological model applications in recent years, especially to enhance weather forecast and to support air-quality studies. In order to investigate the influence of different data assimilation techniques on the meteorological fields produced by RAMS model, and to evaluate their effects on the ozone and PM10 concentrations predicted by FARM model, several numeric experiments were conducted over the urban area of Rome, Italy, during a summer episode.

  15. A quality score for coronary artery tree extraction results

    NASA Astrophysics Data System (ADS)

    Cao, Qing; Broersen, Alexander; Kitslaar, Pieter H.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke

    2018-02-01

    Coronary artery trees (CATs) are often extracted to aid the fully automatic analysis of coronary artery disease on coronary computed tomography angiography (CCTA) images. Automatically extracted CATs often miss some arteries or include wrong extractions which require manual corrections before performing successive steps. For analyzing a large number of datasets, a manual quality check of the extraction results is time-consuming. This paper presents a method to automatically calculate quality scores for extracted CATs in terms of clinical significance of the extracted arteries and the completeness of the extracted CAT. Both right dominant (RD) and left dominant (LD) anatomical statistical models are generated and exploited in developing the quality score. To automatically determine which model should be used, a dominance type detection method is also designed. Experiments are performed on the automatically extracted and manually refined CATs from 42 datasets to evaluate the proposed quality score. In 39 (92.9%) cases, the proposed method is able to measure the quality of the manually refined CATs with higher scores than the automatically extracted CATs. In a 100-point scale system, the average scores for automatically and manually refined CATs are 82.0 (+/-15.8) and 88.9 (+/-5.4) respectively. The proposed quality score will assist the automatic processing of the CAT extractions for large cohorts which contain both RD and LD cases. To the best of our knowledge, this is the first time that a general quality score for an extracted CAT is presented.

  16. 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.

  17. 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.

  18. Quality models for audiovisual streaming

    NASA Astrophysics Data System (ADS)

    Thang, Truong Cong; Kim, Young Suk; Kim, Cheon Seog; Ro, Yong Man

    2006-01-01

    Quality is an essential factor in multimedia communication, especially in compression and adaptation. Quality metrics can be divided into three categories: within-modality quality, cross-modality quality, and multi-modality quality. Most research has so far focused on within-modality quality. Moreover, quality is normally just considered from the perceptual perspective. In practice, content may be drastically adapted, even converted to another modality. In this case, we should consider the quality from semantic perspective as well. In this work, we investigate the multi-modality quality from the semantic perspective. To model the semantic quality, we apply the concept of "conceptual graph", which consists of semantic nodes and relations between the nodes. As an typical of multi-modality example, we focus on audiovisual streaming service. Specifically, we evaluate the amount of information conveyed by a audiovisual content where both video and audio channels may be strongly degraded, even audio are converted to text. In the experiments, we also consider the perceptual quality model of audiovisual content, so as to see the difference with semantic quality model.

  19. 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.

  20. One multi-media environmental system with linkage between meteorology/ hydrology/ air quality models and water quality model

    NASA Astrophysics Data System (ADS)

    Tang, C.; Lynch, J. A.; Dennis, R. L.

    2016-12-01

    The biogeochemical processing of nitrogen and associated pollutants is driven by meteorological and hydrological processes in conjunction with pollutant loading. There are feedbacks between meteorology and hydrology that will be affected by land-use change and climate change. Changes in meteorology will affect pollutant deposition. It is important to account for those feedbacks and produce internally consistent simulations of meteorology, hydrology, and pollutant loading to drive the (watershed/water quality) biogeochemical models. In this study, the ecological response to emission reductions in streams in the Potomac watershed was evaluated. Firstly, we simulated the deposition by using the fully coupled Weather Research & Forecasting (WRF) model and the Community Multiscale Air Quality (CAMQ) model; secondly, we created the hydrological data by the offline linked Variable Infiltration Capacity (VIC) model and the WRF model. Lastly, we investigated the water quality by one comprehensive/environment model, namely the linkage of CMAQ, WRF, VIC and the Model of Acidification of Groundwater In Catchment (MAGIC) model from 2002 to 2010.The simulated results (such as NO3, SO4, and SBC) fit well to the observed values. The linkage provides a generally accurate, well-tested tool for evaluating sensitivities to varying meteorology and environmental changes on acidification and other biogeochemical processes, with capability to comprehensively explore strategic policy and management design.

  1. Collaborative problem solving with a total quality model.

    PubMed

    Volden, C M; Monnig, R

    1993-01-01

    A collaborative problem-solving system committed to the interests of those involved complies with the teachings of the total quality management movement in health care. Deming espoused that any quality system must become an integral part of routine activities. A process that is used consistently in dealing with problems, issues, or conflicts provides a mechanism for accomplishing total quality improvement. The collaborative problem-solving process described here results in quality decision-making. This model incorporates Ishikawa's cause-and-effect (fishbone) diagram, Moore's key causes of conflict, and the steps of the University of North Dakota Conflict Resolution Center's collaborative problem solving model.

  2. 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.

  3. Klang River water quality modelling using music

    NASA Astrophysics Data System (ADS)

    Zahari, Nazirul Mubin; Zawawi, Mohd Hafiz; Muda, Zakaria Che; Sidek, Lariyah Mohd; Fauzi, Nurfazila Mohd; Othman, Mohd Edzham Fareez; Ahmad, Zulkepply

    2017-09-01

    Water is an essential resource that sustains life on earth; changes in the natural quality and distribution of water have ecological impacts that can sometimes be devastating. Recently, Malaysia is facing many environmental issues regarding water pollution. The main causes of river pollution are rapid urbanization, arising from the development of residential, commercial, industrial sites, infrastructural facilities and others. The purpose of the study was to predict the water quality of the Connaught Bridge Power Station (CBPS), Klang River. Besides that, affects to the low tide and high tide and. to forecast the pollutant concentrations of the Biochemical Oxygen Demand (BOD) and Total Suspended Solid (TSS) for existing land use of the catchment area through water quality modeling (by using the MUSIC software). Besides that, to identifying an integrated urban stormwater treatment system (Best Management Practice or BMPs) to achieve optimal performance in improving the water quality of the catchment using the MUSIC software in catchment areas having tropical climates. Result from MUSIC Model such as BOD5 at station 1 can be reduce the concentration from Class IV to become Class III. Whereas, for TSS concentration from Class III to become Class II at the station 1. The model predicted a mean TSS reduction of 0.17%, TP reduction of 0.14%, TN reduction of 0.48% and BOD5 reduction of 0.31% for Station 1 Thus, from the result after purposed BMPs the water quality is safe to use because basically water quality monitoring is important due to threat such as activities are harmful to aquatic organisms and public health.

  4. [Autism: educational models for a quality life].

    PubMed

    Tamarit, J

    2005-01-15

    Our aim is to describe the change that is taking place in the field of education in developmental disabilities from models centred on the clinical symptoms and on the limitations in the adaptive skills to models that focus on valuable personal results in terms of quality of life. In order to understand these changes, we outline some of the key points that have given rise to a particular cultural construction of disability and we also discuss how the situation is changing towards models aimed at achieving important personal results. In autism, as in the other developmental disorders, special emphasis has traditionally been placed on an education focusing on symptoms and on skills, and, although things are now beginning to head in that direction, little attention has been given to education based on the person and his or her quality of life. These changes imply new roles for the professionals attending these people. These roles involve combining technique with empathy and ethics, and they are more firmly based on the active role of individuals with autism, together with their rights, interests and opinions. Models of intervention must pay special attention to the pursuit of valuable personal results, which are oriented towards living a quality life and must involve the active participation of the individuals themselves as well as their relatives.

  5. Air Quality Modeling | Air Quality Planning & Standards | US ...

    EPA Pesticide Factsheets

    2016-06-08

    The basic mission of the Office of Air Quality Planning and Standards is to preserve and improve the quality of our nation's air. One facet of accomplishing this goal requires that new and existing air pollution sources be modeled for compliance with the National Ambient Air Quality Standards (NAAQS).

  6. 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.

  7. Modelling End-User of Electronic-Government Service: The Role of Information quality, System Quality and Trust

    NASA Astrophysics Data System (ADS)

    Witarsyah Jacob, Deden; Fudzee, Mohd Farhan Md; Aizi Salamat, Mohamad; Kasim, Shahreen; Mahdin, Hairulnizam; Azhar Ramli, Azizul

    2017-08-01

    Many governments around the world increasingly use internet technologies such as electronic government to provide public services. These services range from providing the most basic informational website to deploying sophisticated tools for managing interactions between government agencies and beyond government. Electronic government (e-government) aims to provide a more accurate, easily accessible, cost-effective and time saving for the community. In this study, we develop a new model of e-government adoption service by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) through the incorporation of some variables such as System Quality, Information Quality and Trust. The model is then tested using a large-scale, multi-site survey research of 237 Indonesian citizens. This model will be validated by using Structural Equation Modeling (SEM). The result indicates that System Quality, Information Quality and Trust variables proven to effect user behavior. This study extends the current understanding on the influence of System Quality, Information Quality and Trust factors to researchers, practitioners, and policy makers.

  8. Model-based monitoring of stormwater runoff quality.

    PubMed

    Birch, Heidi; Vezzaro, Luca; Mikkelsen, Peter Steen

    2013-01-01

    Monitoring of micropollutants (MP) in stormwater is essential to evaluate the impacts of stormwater on the receiving aquatic environment. The aim of this study was to investigate how different strategies for monitoring of stormwater quality (combining a model with field sampling) affect the information obtained about MP discharged from the monitored system. A dynamic stormwater quality model was calibrated using MP data collected by automatic volume-proportional sampling and passive sampling in a storm drainage system on the outskirts of Copenhagen (Denmark) and a 10-year rain series was used to find annual average (AA) and maximum event mean concentrations. Use of this model reduced the uncertainty of predicted AA concentrations compared to a simple stochastic method based solely on data. The predicted AA concentration, obtained by using passive sampler measurements (1 month installation) for calibration of the model, resulted in the same predicted level but with narrower model prediction bounds than by using volume-proportional samples for calibration. This shows that passive sampling allows for a better exploitation of the resources allocated for stormwater quality monitoring.

  9. Higher Education Quality Assessment Model: Towards Achieving Educational Quality Standard

    ERIC Educational Resources Information Center

    Noaman, Amin Y.; Ragab, Abdul Hamid M.; Madbouly, Ayman I.; Khedra, Ahmed M.; Fayoumi, Ayman G.

    2017-01-01

    This paper presents a developed higher education quality assessment model (HEQAM) that can be applied for enhancement of university services. This is because there is no universal unified quality standard model that can be used to assess the quality criteria of higher education institutes. The analytical hierarchy process is used to identify the…

  10. Putting people into water quality modelling.

    NASA Astrophysics Data System (ADS)

    Strickert, G. E.; Hassanzadeh, E.; Noble, B.; Baulch, H. M.; Morales-Marin, L. A.; Lindenschmidt, K. E.

    2017-12-01

    Water quality in the Qu'Appelle River Basin, Saskatchewan is under pressure due to nutrient pollution entering the river system from major cities, industrial zones and agricultural areas. Among these stressors, agricultural activities are basin-wide; therefore, they are the largest non-point source of water pollution in this region. The dynamics of agricultural impacts on water quality are complex and stem from decisions and activities of two distinct stakeholder groups, namely grain farmers and cattle producers, which have different business plans, values, and attitudes towards water quality. As a result, improving water quality in this basin requires engaging with stakeholders to: (1) understand their perspectives regarding a range of agricultural Beneficial Management Practices (BMPs) that can improve water quality in the region, (2) show them the potential consequences of their selected BMPs, and (3) work with stakeholders to better understand the barriers and incentives to implement the effective BMPs. In this line, we held a series of workshops in the Qu'Appelle River Basin with both groups of stakeholders to understand stakeholders' viewpoints about alternative agricultural BMPs and their impact on water quality. Workshop participants were involved in the statement sorting activity (Q-sorts), group discussions, as well as mapping activity. The workshop outcomes show that stakeholder had four distinct viewpoints about the BMPs that can improve water quality, i.e., flow and erosion control, fertilizer management, cattle site management, as well as mixed cattle and wetland management. Accordingly, to simulate the consequences of stakeholder selected BMPs, a conceptual water quality model was developed using System Dynamics (SD). The model estimates potential changes in water quality at the farm, tributary and regional scale in the Qu'Appelle River Basin under each and/or combination of stakeholder selected BMPs. The SD model was then used for real

  11. [Risk adjusted assessment of quality of perinatal centers - results of perinatal/neonatal quality surveillance in Saxonia].

    PubMed

    Koch, R; Gmyrek, D; Vogtmann, Ch

    2005-12-01

    The weak point of the country-wide perinatal/neonatal quality surveillance as a tool for evaluation of achievements of a distinct clinic, is the ignorance of interhospital differences in the case-mix of patients. Therefore, that approach can not result in a reliable bench marking. To adjust the results of quality assessment of different hospitals according to their risk profile of patients by multivariate analysis. The perinatal/neonatal data base of 12.783 newborns of the saxonian quality surveillance from 1998 to 2000 was analyzed. 4 relevant quality indicators of newborn outcome -- a) severe intraventricular hemorrhage in preterm infants < 1500 g, b) death in hospital of preterm infants < 1500 g, c) death in newborns with birth weight > 2500 g and d) hypoxic-ischemic encephalopathy -- were targeted to find out specific risk predictors by considering 26 risk factors. A logistic regression model was used to develop the risk predictors. Risk predictors for the 4 quality indicators could be described by 3 - 9 out of 26 analyzed risk factors. The AUC (ROC)-values for these quality indicators were 82, 89, 89 and 89 %, what signifies their reliability. Using the new specific predictors for calculation the risk adjusted incidence rates of quality indicator yielded in some remarkable changes. The apparent differences in the outcome criteria of analyzed hospitals were found to be much less pronounced. The application of the proposed method for risk adjustment of quality indicators makes it possible to perform a more objective comparison of neonatal outcome criteria between different hospitals or regions.

  12. The impact of working memory and the "process of process modelling" on model quality: Investigating experienced versus inexperienced modellers.

    PubMed

    Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R; Weber, Barbara

    2016-05-09

    A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling.

  13. Institutional Response to the Swedish Model of Quality Assurance.

    ERIC Educational Resources Information Center

    Nilsson, Karl-Axel; Wahlen, Staffan

    2000-01-01

    Evaluates the Swedish model of quality assurance of higher education by examining the response of institutions to 27 quality audits and 19 follow-up interviews. Discusses the relationship between top-down and bottom-up approaches to internal quality assurance and suggests that, with growing professionalization, more limited result-oriented audits…

  14. Information quality-control model

    NASA Technical Reports Server (NTRS)

    Vincent, D. A.

    1971-01-01

    Model serves as graphic tool for estimating complete product objectives from limited input information, and is applied to cost estimations, product-quality evaluations, and effectiveness measurements for manpower resources allocation. Six product quality levels are defined.

  15. Voice Quality Modelling for Expressive Speech Synthesis

    PubMed Central

    Socoró, Joan Claudi

    2014-01-01

    This paper presents the perceptual experiments that were carried out in order to validate the methodology of transforming expressive speech styles using voice quality (VoQ) parameters modelling, along with the well-known prosody (F 0, duration, and energy), from a neutral style into a number of expressive ones. The main goal was to validate the usefulness of VoQ in the enhancement of expressive synthetic speech in terms of speech quality and style identification. A harmonic plus noise model (HNM) was used to modify VoQ and prosodic parameters that were extracted from an expressive speech corpus. Perception test results indicated the improvement of obtained expressive speech styles using VoQ modelling along with prosodic characteristics. PMID:24587738

  16. 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.

  17. A model for predicting air quality along highways.

    DOT National Transportation Integrated Search

    1973-01-01

    The subject of this report is an air quality prediction model for highways, AIRPOL Version 2, July 1973. AIRPOL has been developed by modifying the basic Gaussian approach to gaseous dispersion. The resultant model is smooth and continuous throughout...

  18. A simple parametric model observer for quality assurance in computer tomography

    NASA Astrophysics Data System (ADS)

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

    2018-04-01

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

  19. Reflexion on linear regression trip production modelling method for ensuring good model quality

    NASA Astrophysics Data System (ADS)

    Suprayitno, Hitapriya; Ratnasari, Vita

    2017-11-01

    Transport Modelling is important. For certain cases, the conventional model still has to be used, in which having a good trip production model is capital. A good model can only be obtained from a good sample. Two of the basic principles of a good sampling is having a sample capable to represent the population characteristics and capable to produce an acceptable error at a certain confidence level. It seems that this principle is not yet quite understood and used in trip production modeling. Therefore, investigating the Trip Production Modelling practice in Indonesia and try to formulate a better modeling method for ensuring the Model Quality is necessary. This research result is presented as follows. Statistics knows a method to calculate span of prediction value at a certain confidence level for linear regression, which is called Confidence Interval of Predicted Value. The common modeling practice uses R2 as the principal quality measure, the sampling practice varies and not always conform to the sampling principles. An experiment indicates that small sample is already capable to give excellent R2 value and sample composition can significantly change the model. Hence, good R2 value, in fact, does not always mean good model quality. These lead to three basic ideas for ensuring good model quality, i.e. reformulating quality measure, calculation procedure, and sampling method. A quality measure is defined as having a good R2 value and a good Confidence Interval of Predicted Value. Calculation procedure must incorporate statistical calculation method and appropriate statistical tests needed. A good sampling method must incorporate random well distributed stratified sampling with a certain minimum number of samples. These three ideas need to be more developed and tested.

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

    PubMed

    Cao, Renzhi; Cheng, Jianlin

    2016-04-04

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

  1. The Impact of Applying Quality Management Practices on Patient Centeredness in Jordanian Public Hospitals: Results of Predictive Modeling

    PubMed Central

    Hijazi, Heba H.; Harvey, Heather L.; Alyahya, Mohammad S.; Alshraideh, Hussam A.; Al abdi, Rabah M.; Parahoo, Sanjai K.

    2018-01-01

    Targeting the patient’s needs and preferences has become an important contributor for improving care delivery, enhancing patient satisfaction, and achieving better clinical outcomes. This study aimed to examine the impact of applying quality management practices on patient centeredness within the context of health care accreditation and to explore the differences in the views of various health care workers regarding the attributes affecting patient-centered care. Our study followed a cross-sectional survey design wherein 4 Jordanian public hospitals were investigated several months after accreditation was obtained. Total 829 clinical/nonclinical hospital staff members consented for study participation. This sample was divided into 3 main occupational categories to represent the administrators, nurses, as well as doctors and other health professionals. Using a structural equation modeling, our results indicated that the predictors of patient-centered care for both administrators and those providing clinical care were participation in the accreditation process, leadership commitment to quality improvement, and measurement of quality improvement outcomes. In particular, perceiving the importance of the hospital’s engagement in the accreditation process was shown to be relevant to the administrators (gamma = 0.96), nurses (gamma = 0.80), as well as to doctors and other health professionals (gamma = 0.71). However, the administrator staff (gamma = 0.31) was less likely to perceive the influence of measuring the quality improvement outcomes on the delivery of patient-centered care than nurses (gamma = 0.59) as well as doctors and other health care providers (gamma = 0.55). From the nurses’ perspectives only, patient centeredness was found to be driven by building an institutional framework that supports quality assurance in hospital settings (gamma = 0.36). In conclusion, accreditation is a leading factor for delivering patient-centered care and should be on a

  2. The Impact of Applying Quality Management Practices on Patient Centeredness in Jordanian Public Hospitals: Results of Predictive Modeling.

    PubMed

    Hijazi, Heba H; Harvey, Heather L; Alyahya, Mohammad S; Alshraideh, Hussam A; Al Abdi, Rabah M; Parahoo, Sanjai K

    2018-01-01

    Targeting the patient's needs and preferences has become an important contributor for improving care delivery, enhancing patient satisfaction, and achieving better clinical outcomes. This study aimed to examine the impact of applying quality management practices on patient centeredness within the context of health care accreditation and to explore the differences in the views of various health care workers regarding the attributes affecting patient-centered care. Our study followed a cross-sectional survey design wherein 4 Jordanian public hospitals were investigated several months after accreditation was obtained. Total 829 clinical/nonclinical hospital staff members consented for study participation. This sample was divided into 3 main occupational categories to represent the administrators, nurses, as well as doctors and other health professionals. Using a structural equation modeling, our results indicated that the predictors of patient-centered care for both administrators and those providing clinical care were participation in the accreditation process, leadership commitment to quality improvement, and measurement of quality improvement outcomes. In particular, perceiving the importance of the hospital's engagement in the accreditation process was shown to be relevant to the administrators (gamma = 0.96), nurses (gamma = 0.80), as well as to doctors and other health professionals (gamma = 0.71). However, the administrator staff (gamma = 0.31) was less likely to perceive the influence of measuring the quality improvement outcomes on the delivery of patient-centered care than nurses (gamma = 0.59) as well as doctors and other health care providers (gamma = 0.55). From the nurses' perspectives only, patient centeredness was found to be driven by building an institutional framework that supports quality assurance in hospital settings (gamma = 0.36). In conclusion, accreditation is a leading factor for delivering patient-centered care and should be on a hospital

  3. Four-dimensional evaluation of regional air quality models

    EPA Science Inventory

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

  4. 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

  5. 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.

  6. Data Quality in Institutional Arthroplasty Registries: Description of a Model of Validation and Report of Preliminary Results.

    PubMed

    Bautista, Maria P; Bonilla, Guillermo A; Mieth, Klaus W; Llinás, Adolfo M; Rodríguez, Fernanda; Cárdenas, Laura L

    2017-07-01

    Arthroplasty registries are a relevant source of information for research and quality improvement in patient care and its value depends on the quality of the recorded data. The purpose of this study is to describe a model of validation and present the findings of validation of an Institutional Arthroplasty Registry (IAR). Information from 209 primary arthroplasties and revision surgeries of the hip, knee, and shoulder recorded in the IAR between March and September 2015 were analyzed in the following domains. Adherence is defined as the proportion of patients included in the registry, completeness is defined as the proportion of data effectively recorded, and accuracy is defined as the proportion of data consistent with medical records. A random sample of 53 patients (25.4%) was selected to assess the latest 2 domains. A direct comparison between the registry's database and medical records was performed. In total, 324 variables containing information on demographic data, surgical procedure, clinical outcomes, and key performance indicators were analyzed. Two hundred nine of 212 patients who underwent surgery during the study period were included in the registry, accounting for an adherence of 98.6%. Completeness was 91.7% and accuracy was 85.8%. Most errors were found in the preoperative range of motion and timely administration of prophylactic antibiotics and thromboprophylaxis. This model provides useful information regarding the quality of the recorded data since it identified deficient areas within the IAR. We recommend that institutional arthroplasty registries be constantly monitored for data quality before using their information for research or quality improvement purposes. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Air Quality Modeling

    EPA Pesticide Factsheets

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

  8. 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.

  9. Operation quality assessment model for video conference system

    NASA Astrophysics Data System (ADS)

    Du, Bangshi; Qi, Feng; Shao, Sujie; Wang, Ying; Li, Weijian

    2018-01-01

    Video conference system has become an important support platform for smart grid operation and management, its operation quality is gradually concerning grid enterprise. First, the evaluation indicator system covering network, business and operation maintenance aspects was established on basis of video conference system's operation statistics. Then, the operation quality assessment model combining genetic algorithm with regularized BP neural network was proposed, which outputs operation quality level of the system within a time period and provides company manager with some optimization advice. The simulation results show that the proposed evaluation model offers the advantages of fast convergence and high prediction accuracy in contrast with regularized BP neural network, and its generalization ability is superior to LM-BP neural network and Bayesian BP neural network.

  10. Comparative evaluation of urban storm water quality models

    NASA Astrophysics Data System (ADS)

    Vaze, J.; Chiew, Francis H. S.

    2003-10-01

    The estimation of urban storm water pollutant loads is required for the development of mitigation and management strategies to minimize impacts to receiving environments. Event pollutant loads are typically estimated using either regression equations or "process-based" water quality models. The relative merit of using regression models compared to process-based models is not clear. A modeling study is carried out here to evaluate the comparative ability of the regression equations and process-based water quality models to estimate event diffuse pollutant loads from impervious surfaces. The results indicate that, once calibrated, both the regression equations and the process-based model can estimate event pollutant loads satisfactorily. In fact, the loads estimated using the regression equation as a function of rainfall intensity and runoff rate are better than the loads estimated using the process-based model. Therefore, if only estimates of event loads are required, regression models should be used because they are simpler and require less data compared to process-based models.

  11. A linked hydrodynamic and water quality model for the Salton Sea

    USGS Publications Warehouse

    Chung, E.G.; Schladow, S.G.; Perez-Losada, J.; Robertson, Dale M.

    2008-01-01

    A linked hydrodynamic and water quality model was developed and applied to the Salton Sea. The hydrodynamic component is based on the one-dimensional numerical model, DLM. The water quality model is based on a new conceptual model for nutrient cycling in the Sea, and simulates temperature, total suspended sediment concentration, nutrient concentrations, including PO4-3, NO3-1 and NH4+1, DO concentration and chlorophyll a concentration as functions of depth and time. Existing water temperature data from 1997 were used to verify that the model could accurately represent the onset and breakup of thermal stratification. 1999 is the only year with a near-complete dataset for water quality variables for the Salton Sea. The linked hydrodynamic and water quality model was run for 1999, and by adjustment of rate coefficients and other water quality parameters, a good match with the data was obtained. In this article, the model is fully described and the model results for reductions in external phosphorus load on chlorophyll a distribution are presented. ?? 2008 Springer Science+Business Media B.V.

  12. 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.

  13. Quality circles: Organizational adaptations, improvements and results

    NASA Technical Reports Server (NTRS)

    Tortorich, R.

    1985-01-01

    The effective application in industry and government of quality circles work was demonstrated. The results achieved in quality and productivity improvements and cost savings are impressive. The circle process should be institutionalized within industry and government. The stages of circle program growth, innovations that help achieve circle process institutionalization, and the result achieved at Martin Marietta's Michoud Division and within the National Aeronautics and Space Administration (NASA) are addressed.

  14. A comparison of different functions for predicted protein model quality assessment.

    PubMed

    Li, Juan; Fang, Huisheng

    2016-07-01

    In protein structure prediction, a considerable number of models are usually produced by either the Template-Based Method (TBM) or the ab initio prediction. The purpose of this study is to find the critical parameter in assessing the quality of the predicted models. A non-redundant template library was developed and 138 target sequences were modeled. The target sequences were all distant from the proteins in the template library and were aligned with template library proteins on the basis of the transformation matrix. The quality of each model was first assessed with QMEAN and its six parameters, which are C_β interaction energy (C_beta), all-atom pairwise energy (PE), solvation energy (SE), torsion angle energy (TAE), secondary structure agreement (SSA), and solvent accessibility agreement (SAE). Finally, the alignment score (score) was also used to assess the quality of model. Hence, a total of eight parameters (i.e., QMEAN, C_beta, PE, SE, TAE, SSA, SAE, score) were independently used to assess the quality of each model. The results indicate that SSA is the best parameter to estimate the quality of the model.

  15. COMMUNITY MULTISCALE AIR QUALITY ( CMAQ ) MODEL - QUALITY ASSURANCE AND VERSION CONTROL

    EPA Science Inventory

    This presentation will be given to the EPA Exposure Modeling Workgroup on January 24, 2006. The quality assurance and version control procedures for the Community Multiscale Air Quality (CMAQ) Model are presented. A brief background of CMAQ is given, then issues related to qual...

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

    PubMed Central

    2012-01-01

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

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

    PubMed

    Westgard, James O

    2016-02-01

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

  18. Modelling rainfall erosion resulting from climate change

    NASA Astrophysics Data System (ADS)

    Kinnell, Peter

    2016-04-01

    It is well known that soil erosion leads to agricultural productivity decline and contributes to water quality decline. The current widely used models for determining soil erosion for management purposes in agriculture focus on long term (~20 years) average annual soil loss and are not well suited to determining variations that occur over short timespans and as a result of climate change. Soil loss resulting from rainfall erosion is directly dependent on the product of runoff and sediment concentration both of which are likely to be influenced by climate change. This presentation demonstrates the capacity of models like the USLE, USLE-M and WEPP to predict variations in runoff and erosion associated with rainfall events eroding bare fallow plots in the USA with a view to modelling rainfall erosion in areas subject to climate change.

  19. An assessment model for quality management

    NASA Astrophysics Data System (ADS)

    Völcker, Chr.; Cass, A.; Dorling, A.; Zilioli, P.; Secchi, P.

    2002-07-01

    SYNSPACE together with InterSPICE and Alenia Spazio is developing an assessment method to determine the capability of an organisation in the area of quality management. The method, sponsored by the European Space Agency (ESA), is called S9kS (SPiCE- 9000 for SPACE). S9kS is based on ISO 9001:2000 with additions from the quality standards issued by the European Committee for Space Standardization (ECSS) and ISO 15504 - Process Assessments. The result is a reference model that supports the expansion of the generic process assessment framework provided by ISO 15504 to nonsoftware areas. In order to be compliant with ISO 15504, requirements from ISO 9001 and ECSS-Q-20 and Q-20-09 have been turned into process definitions in terms of Purpose and Outcomes, supported by a list of detailed indicators such as Practices, Work Products and Work Product Characteristics. In coordination with this project, the capability dimension of ISO 15504 has been revised to be consistent with ISO 9001. As contributions from ISO 9001 and the space quality assurance standards are separable, the stripped down version S9k offers organisations in all industries an assessment model based solely on ISO 9001, and is therefore interesting to all organisations, which intend to improve their quality management system based on ISO 9001.

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

    PubMed

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

    2015-01-01

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

  1. 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.

  2. Indicators to support the dynamic evaluation of air quality models

    NASA Astrophysics Data System (ADS)

    Thunis, P.; Clappier, A.

    2014-12-01

    Air quality models are useful tools for the assessment and forecast of pollutant concentrations in the atmosphere. Most of the evaluation process relies on the “operational phase” or in other words the comparison of model results with available measurements which provides insight on the model capability to reproduce measured concentrations for a given application. But one of the key advantages of air quality models lies in their ability to assess the impact of precursor emission reductions on air quality levels. Models are then used in a dynamic mode (i.e. response to a change in a given model input data) for which evaluation of the model performances becomes a challenge. The objective of this work is to propose common indicators and diagrams to facilitate the understanding of model responses to emission changes when models are to be used for policy support. These indicators are shown to be useful to retrieve information on the magnitude of the locally produced impacts of emission reductions on concentrations with respect to the “external to the domain” contribution but also to identify, distinguish and quantify impacts arising from different factors (different precursors). In addition information about the robustness of the model results is provided. As such these indicators might reveal useful as first screening methodology to identify the feasibility of a given action as well as to prioritize the factors on which to act for an increased efficiency. Finally all indicators are made dimensionless to facilitate the comparison of results obtained with different models, different resolutions, or on different geographical areas.

  3. Implications of Modeling Uncertainty for Water Quality Decision Making

    NASA Astrophysics Data System (ADS)

    Shabman, L.

    2002-05-01

    The report, National Academy of Sciences report, "Assessing the TMDL Approach to Water Quality Management" endorsed the "watershed" and "ambient water quality focused" approach" to water quality management called for in the TMDL program. The committee felt that available data and models were adequate to move such a program forward, if the EPA and all stakeholders better understood the nature of the scientific enterprise and its application to the TMDL program. Specifically, the report called for a greater acknowledgement of model prediction uncertinaity in making and implementing TMDL plans. To assure that such uncertinaity was addressed in water quality decision making the committee called for a commitment to "adaptive implementation" of water quality management plans. The committee found that the number and complexity of the interactions of multiple stressors, combined with model prediction uncertinaity means that we need to avoid the temptation to make assurances that specific actions will result in attainment of particular water quality standards. Until the work on solving a water quality problem begins, analysts and decision makers cannot be sure what the correct solutions are, or even what water quality goals a community should be seeking. In complex systems we need to act in order to learn; adaptive implementation is a concurrent process of action and learning. Learning requires (1) continued monitoring of the waterbody to determine how it responds to the actions taken and (2) carefully designed experiments in the watershed. If we do not design learning into what we attempt we are not doing adaptive implementation. Therefore, there needs to be an increased commitment to monitoring and experiments in watersheds that will lead to learning. This presentation will 1) explain the logic for adaptive implementation; 2) discuss the ways that water quality modelers could characterize and explain model uncertinaity to decision makers; 3) speculate on the implications

  4. 42 CFR 438.364 - External quality review results.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 4 2011-10-01 2011-10-01 false External quality review results. 438.364 Section 438.364 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... quality review results. (a) Information that must be produced. The State must ensure that the EQR produces...

  5. 42 CFR 438.364 - External quality review results.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 4 2013-10-01 2013-10-01 false External quality review results. 438.364 Section 438.364 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... quality review results. (a) Information that must be produced. The State must ensure that the EQR produces...

  6. 42 CFR 438.364 - External quality review results.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 4 2014-10-01 2014-10-01 false External quality review results. 438.364 Section 438.364 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... quality review results. (a) Information that must be produced. The State must ensure that the EQR produces...

  7. 42 CFR 438.364 - External quality review results.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 4 2012-10-01 2012-10-01 false External quality review results. 438.364 Section 438.364 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... quality review results. (a) Information that must be produced. The State must ensure that the EQR produces...

  8. 42 CFR 438.364 - External quality review results.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 4 2010-10-01 2010-10-01 false External quality review results. 438.364 Section 438.364 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... quality review results. (a) Information that must be produced. The State must ensure that the EQR produces...

  9. Relationship between soybean yield/quality and soil quality in a major soybean-producing area based on a 2D-QSAR model

    NASA Astrophysics Data System (ADS)

    Gao, Ming; Li, Shiwei

    2017-05-01

    Based on experimental data of the soybean yield and quality from 30 sampling points, a quantitative structure-activity relationship model (2D-QSAR) was established using the soil quality (elements, pH, organic matter content and cation exchange capacity) as independent variables and soybean yield or quality as the dependent variable, with SPSS software. During the modeling, the full data set (30 and 14 compounds) was divided into a training set (24 and 11 compounds) for model generation and a test set (6 and 3 compounds) for model validation. The R2 values of the resulting models and data were 0.826 and 0.808 for soybean yield and quality, respectively, and all regression coefficients were significant (P < 0.05). The correlation coefficient R2pred of observed values and predicted values of the soybean yield and soybean quality in the test set were 0.961 and 0.956, respectively, indicating that the models had a good predictive ability. Moreover, the Mo, Se, K, N and organic matter contents and the cation exchange capacity of soil had a positive effect on soybean production, and the B, Mo, Se, K and N contents and cation exchange coefficient had a positive effect on soybean quality. The results are instructive for enhancing soils to improve the yield and quality of soybean, and this method can also be used to study other crops or regions, providing a theoretical basis to improving the yield and quality of crops.

  10. Monitoring Quality Across Home Visiting Models: A Field Test of Michigan's Home Visiting Quality Assurance System.

    PubMed

    Heany, Julia; Torres, Jennifer; Zagar, Cynthia; Kostelec, Tiffany

    2018-06-05

    Introduction In order to achieve the positive outcomes with parents and children demonstrated by many home visiting models, home visiting services must be well implemented. The Michigan Home Visiting Initiative developed a tool and procedure for monitoring implementation quality across models referred to as Michigan's Home Visiting Quality Assurance System (MHVQAS). This study field tested the MHVQAS. This article focuses on one of the study's evaluation questions: Can the MHVQAS be applied across models? Methods Eight local implementing agencies (LIAs) from four home visiting models (Healthy Families America, Early Head Start-Home Based, Parents as Teachers, Maternal Infant Health Program) and five reviewers participated in the study by completing site visits, tracking their time and costs, and completing surveys about the process. LIAs also submitted their most recent review by their model developer. The researchers conducted participant observation of the review process. Results Ratings on the MHVQAS were not significantly different between models. There were some differences in interrater reliability and perceived reliability between models. There were no significant differences between models in perceived validity, satisfaction with the review process, or cost to participate. Observational data suggested that cross-model applicability could be improved by assisting sites in relating the requirements of the tool to the specifics of their model. Discussion The MHVQAS shows promise as a tool and process to monitor implementation quality of home visiting services across models. The results of the study will be used to make improvements before the MHVQAS is used in practice.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  12. [Service quality in health care: the application of the results of marketing research].

    PubMed

    Verheggen, F W; Harteloh, P P

    1993-01-01

    This paper deals with quality assurance in health care and its relation to quality assurance in trade and industry. We present the service quality model--a model of quality from marketing research--and discuss how it can be applied to health care. Traditional quality assurance appears to have serious flaws. It lacks a general theory of the sources of hazards in the complex process of patient care and tends to stagnate, for no real improvement takes place. Departing from this criticism, modern quality assurance in health care is marked by: defining quality in a preferential sense as "fitness for use"; the use of theories and models of trade and industry (process-control); an emphasis on analyzing the process, instead of merely inspecting it; use of the Deming problem solving technique (plan, do, check, act); improvement of the process of care by altering perceptions of parties involved. We present an experience of application and utilization of this method in the University Hospital Maastricht, The Netherlands. The successful application of this model requires a favorable corporate culture and motivation of the health care workers. This model provides a useful framework to uplift the traditional approach to quality assurance in health care.

  13. Aircraft model prototypes which have specified handling-quality time histories

    NASA Technical Reports Server (NTRS)

    Johnson, S. H.

    1978-01-01

    Several techniques for obtaining linear constant-coefficient airplane models from specified handling-quality time histories are discussed. The pseudodata method solves the basic problem, yields specified eigenvalues, and accommodates state-variable transfer-function zero suppression. The algebraic equations to be solved are bilinear, at worst. The disadvantages are reduced generality and no assurance that the resulting model will be airplane like in detail. The method is fully illustrated for a fourth-order stability-axis small motion model with three lateral handling quality time histories specified. The FORTRAN program which obtains and verifies the model is included and fully documented.

  14. Innovations in projecting emissions for air quality modeling ...

    EPA Pesticide Factsheets

    Air quality modeling is used in setting air quality standards and in evaluating their costs and benefits. Historically, modeling applications have projected emissions and the resulting air quality only 5 to 10 years into the future. Recognition that the choice of air quality management strategy has climate change implications is encouraging longer modeling time horizons. However, for multi-decadal time horizons, many questions about future conditions arise. For example, will current population, economic, and land use trends continue, or will we see shifts that may alter the spatial and temporal pattern of emissions? Similarly, will technologies such as building-integrated solar photovoltaics, battery storage, electric vehicles, and CO2 capture emerge as disruptive technologies - shifting how we produce and use energy - or will these technologies achieve only niche markets and have little impact? These are some of the questions that are being evaluated by researchers within the U.S. EPA’s Office of Research and Development. In this presentation, Dr. Loughlin will describe a range of analytical approaches that are being explored. These include: (i) the development of alternative scenarios of the future that can be used to evaluate candidate management strategies over wide-ranging conditions, (ii) the application of energy system models to project emissions decades into the future and to assess the environmental implications of new technologies, (iii) and methodo

  15. The air quality forecast in Beijing with Community Multi-scale Air Quality Modeling (CMAQ) System: model evaluation and improvement

    NASA Astrophysics Data System (ADS)

    Wu, Q.

    2013-12-01

    The MM5-SMOKE-CMAQ model system, which is developed by the United States Environmental Protection Agency(U.S. EPA) as the Models-3 system, has been used for the daily air quality forecast in the Beijing Municipal Environmental Monitoring Center(Beijing MEMC), as a part of the Ensemble Air Quality Forecast System for Beijing(EMS-Beijing) since the Olympic Games year 2008. In this study, we collect the daily forecast results of the CMAQ model in the whole year 2010 for the model evaluation. The results show that the model play a good model performance in most days but underestimate obviously in some air pollution episode. A typical air pollution episode from 11st - 20th January 2010 was chosen, which the air pollution index(API) of particulate matter (PM10) observed by Beijing MEMC reaches to 180 while the prediction of PM10-API is about 100. Taking in account all stations in Beijing, including urban and suburban stations, three numerical methods are used for model improvement: firstly, enhance the inner domain with 4km grids, the coverage from only Beijing to the area including its surrounding cities; secondly, update the Beijing stationary area emission inventory, from statistical county-level to village-town level, that would provide more detail spatial informance for area emissions; thirdly, add some industrial points emission in Beijing's surrounding cities, the latter two are both the improvement of emission. As the result, the peak of the nine national standard stations averaged PM10-API, which is simulated by CMAQ as daily hindcast PM10-API, reach to 160 and much near to the observation. The new results show better model performance, which the correlation coefficent is 0.93 in national standard stations average and 0.84 in all stations, the relative error is 15.7% in national standard stations averaged and 27% in all stations. The time series of 9 national standard in Beijing urban The scatter diagram of all stations in Beijing, the red is the forecast and

  16. A deterministic aggregate production planning model considering quality of products

    NASA Astrophysics Data System (ADS)

    Madadi, Najmeh; Yew Wong, Kuan

    2013-06-01

    Aggregate Production Planning (APP) is a medium-term planning which is concerned with the lowest-cost method of production planning to meet customers' requirements and to satisfy fluctuating demand over a planning time horizon. APP problem has been studied widely since it was introduced and formulated in 1950s. However, in several conducted studies in the APP area, most of the researchers have concentrated on some common objectives such as minimization of cost, fluctuation in the number of workers, and inventory level. Specifically, maintaining quality at the desirable level as an objective while minimizing cost has not been considered in previous studies. In this study, an attempt has been made to develop a multi-objective mixed integer linear programming model that serves those companies aiming to incur the minimum level of operational cost while maintaining quality at an acceptable level. In order to obtain the solution to the multi-objective model, the Fuzzy Goal Programming approach and max-min operator of Bellman-Zadeh were applied to the model. At the final step, IBM ILOG CPLEX Optimization Studio software was used to obtain the experimental results based on the data collected from an automotive parts manufacturing company. The results show that incorporating quality in the model imposes some costs, however a trade-off should be done between the cost resulting from producing products with higher quality and the cost that the firm may incur due to customer dissatisfaction and sale losses.

  17. Soil Quality Index Determination Models for Restinga Forest

    NASA Astrophysics Data System (ADS)

    Bonilha, R. M.; Casagrande, J. C.; Soares, R. M.

    2012-04-01

    The Restinga Forest is a set of plant communities in mosaic, determined by the characteristics of their substrates as a result of depositional processes and ages. In this complex mosaic are the physiognomies of restinga forests of high-stage regeneration (high restinga) and middle stage of regeneration (low restinga), each with its plant characteristics that differentiate them. Located on the coastal plains of the Brazilian coast, suffering internal influences both the continental slopes, as well as from the sea. Its soils come from the Quaternary and are subject to constant deposition of sediments. The climate in the coastal type is tropical (Köppen). This work was conducted in four locations: (1) Anchieta Island, Ubatuba, (2) Juréia-Itatins Ecological Station, Iguape, (3) Vila das Pedrinhas, Comprida Island; and (4) Cardoso Island, Cananeia. The soil samples were collect at a depths of 0 to 5, 0-10, 0-20, 20-40 and 40 to 60cm for the chemical and physical analysis. Were studied the additive and pondering additive models to evaluate soil quality. It was concluded: a) the comparative additive model produces quantitative results and the pondering additive model quantitative results; b) as the pondering additive model, the values of Soil Quality Index (SQI) for soils under forest of restinga are low and realistic, demonstrating the small plant biomass production potential of these soils, as well as their low resilience; c) the values of SQI similar to areas with and without restinga forest give quantitative demonstration of the restinga be considered as soil phase; d) restinga forest, probably, is maintained solely by the cycling of nutrients in a closed nutrient cycling; e) for the determination of IQS for soils under restinga vegetation the use of routine chemical analysis is adequate. Keywords: Model, restinga forest, Soil Quality Index (SQI).

  18. 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.

  19. Phase quality map based on local multi-unwrapped results for two-dimensional phase unwrapping.

    PubMed

    Zhong, Heping; Tang, Jinsong; Zhang, Sen

    2015-02-01

    The efficiency of a phase unwrapping algorithm and the reliability of the corresponding unwrapped result are two key problems in reconstructing the digital elevation model of a scene from its interferometric synthetic aperture radar (InSAR) or interferometric synthetic aperture sonar (InSAS) data. In this paper, a new phase quality map is designed and implemented in a graphic processing unit (GPU) environment, which greatly accelerates the unwrapping process of the quality-guided algorithm and enhances the correctness of the unwrapped result. In a local wrapped phase window, the center point is selected as the reference point, and then two unwrapped results are computed by integrating in two different simple ways. After the two local unwrapped results are computed, the total difference of the two unwrapped results is regarded as the phase quality value of the center point. In order to accelerate the computing process of the new proposed quality map, we have implemented it in a GPU environment. The wrapped phase data are first uploaded to the memory of a device, and then the kernel function is called in the device to compute the phase quality in parallel by blocks of threads. Unwrapping tests performed on the simulated and real InSAS data confirm the accuracy and efficiency of the proposed method.

  20. 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.

  1. Fox Valley Technical College Quality First Process Model.

    ERIC Educational Resources Information Center

    Fox Valley Technical Coll., Appleton, WI.

    An overview is provided of the Quality First Process Model developed by Fox Valley Technical College (FVTC), Wisconsin, to provide guidelines for quality instruction and service consistent with the highest educational standards. The 16-step model involves activities that should be adaptable to any organization. The steps of the quality model are…

  2. Evaluation of regional climate simulations for air quality modelling purposes

    NASA Astrophysics Data System (ADS)

    Menut, Laurent; Tripathi, Om P.; Colette, Augustin; Vautard, Robert; Flaounas, Emmanouil; Bessagnet, Bertrand

    2013-05-01

    In order to evaluate the future potential benefits of emission regulation on regional air quality, while taking into account the effects of climate change, off-line air quality projection simulations are driven using weather forcing taken from regional climate models. These regional models are themselves driven by simulations carried out using global climate models (GCM) and economical scenarios. Uncertainties and biases in climate models introduce an additional "climate modeling" source of uncertainty that is to be added to all other types of uncertainties in air quality modeling for policy evaluation. In this article we evaluate the changes in air quality-related weather variables induced by replacing reanalyses-forced by GCM-forced regional climate simulations. As an example we use GCM simulations carried out in the framework of the ERA-interim programme and of the CMIP5 project using the Institut Pierre-Simon Laplace climate model (IPSLcm), driving regional simulations performed in the framework of the EURO-CORDEX programme. In summer, we found compensating deficiencies acting on photochemistry: an overestimation by GCM-driven weather due to a positive bias in short-wave radiation, a negative bias in wind speed, too many stagnant episodes, and a negative temperature bias. In winter, air quality is mostly driven by dispersion, and we could not identify significant differences in either wind or planetary boundary layer height statistics between GCM-driven and reanalyses-driven regional simulations. However, precipitation appears largely overestimated in GCM-driven simulations, which could significantly affect the simulation of aerosol concentrations. The identification of these biases will help interpreting results of future air quality simulations using these data. Despite these, we conclude that the identified differences should not lead to major difficulties in using GCM-driven regional climate simulations for air quality projections.

  3. Changing physician incentives for affordable, quality cancer care: results of an episode payment model.

    PubMed

    Newcomer, Lee N; Gould, Bruce; Page, Ray D; Donelan, Sheila A; Perkins, Monica

    2014-09-01

    This study tested the combination of an episode payment coupled with actionable use and quality data as an incentive to improve quality and reduce costs. Medical oncologists were paid a single fee, in lieu of any drug margin, to treat their patients. Chemotherapy medications were reimbursed at the average sales price, a proxy for actual cost. Five volunteer medical groups were compared with a large national payer registry of fee-for-service patients with cancer to examine the difference in cost before and after the initiation of the payment change. Between October 2009 and December 2012, the five groups treated 810 patients with breast, colon, and lung cancer using the episode payments. The registry-predicted fee-for-service cost of the episodes cohort was $98,121,388, but the actual cost was $64,760,116. The predicted cost of chemotherapy drugs was $7,519,504, but the actual cost was $20,979,417. There was no difference between the groups on multiple quality measures. Modifying the current fee-for-service payment system for cancer therapy with feedback data and financial incentives that reward outcomes and cost efficiency resulted in a significant total cost reduction. Eliminating existing financial chemotherapy drug incentives paradoxically increased the use of chemotherapy. Copyright © 2014 by American Society of Clinical Oncology.

  4. Impacts of Megacities on Regional Air Quality from MOPITT Observations and MOZART Model Results

    NASA Astrophysics Data System (ADS)

    Emmons, L. K.; Edwards, D. P.; Hess, P. G.; Lamarque, J.; Pfister, G.; Wiedinmyer, C.; Clerbaux, C.

    2007-05-01

    The emissions from large cities, such as Mexico City, Los Angeles and Tokyo, as well as densely populated regions in India, China, etc., can clearly be seen in the CO retrievals from the Measurements of Pollution in the Troposphere (MOPITT) instrument on the Terra satellite and will be illustrated in this presentation. To assist in the flight planning and analysis of the MILAGRO field campaigns in Mexico during March 2006, MOPITT CO retrievals were assimilated in the global chemical transport model MOZART, using fire emissions based on satellite observations. To understand the impacts of Mexico City and other megacities on regional air quality, additional simulations of MOZART have been performed. The CO emissions from different types of sources (biomass burning, industry, etc.) are "tagged" in the model to show their relative contribution to the regional atmospheric composition. In addition, NO emissions from a single megacity or region are tagged to identify the contribution of ozone from a given source. The contribution from Mexico City pollution to the regional and global atmosphere will be compared to other megacities.

  5. Effects of Meteorological Data Quality on Snowpack Modeling

    NASA Astrophysics Data System (ADS)

    Havens, S.; Marks, D. G.; Robertson, M.; Hedrick, A. R.; Johnson, M.

    2017-12-01

    Detailed quality control of meteorological inputs is the most time-intensive component of running the distributed, physically-based iSnobal snow model, and the effect of data quality of the inputs on the model is unknown. The iSnobal model has been run operationally since WY2013, and is currently run in several basins in Idaho and California. The largest amount of user input during modeling is for the quality control of precipitation, temperature, relative humidity, solar radiation, wind speed and wind direction inputs. Precipitation inputs require detailed user input and are crucial to correctly model the snowpack mass. This research applies a range of quality control methods to meteorological input, from raw input with minimal cleaning, to complete user-applied quality control. The meteorological input cleaning generally falls into two categories. The first is global minimum/maximum and missing value correction that could be corrected and/or interpolated with automated processing. The second category is quality control for inputs that are not globally erroneous, yet are still unreasonable and generally indicate malfunctioning measurement equipment, such as temperature or relative humidity that remains constant, or does not correlate with daily trends observed at nearby stations. This research will determine how sensitive model outputs are to different levels of quality control and guide future operational applications.

  6. Motion-base simulator results of advanced supersonic transport handling qualities with active controls

    NASA Technical Reports Server (NTRS)

    Feather, J. B.; Joshi, D. S.

    1981-01-01

    Handling qualities of the unaugmented advanced supersonic transport (AST) are deficient in the low-speed, landing approach regime. Consequently, improvement in handling with active control augmentation systems has been achieved using implicit model-following techniques. Extensive fixed-based simulator evaluations were used to validate these systems prior to tests with full motion and visual capabilities on a six-axis motion-base simulator (MBS). These tests compared the handling qualities of the unaugmented AST with several augmented configurations to ascertain the effectiveness of these systems. Cooper-Harper ratings, tracking errors, and control activity data from the MBS tests have been analyzed statistically. The results show the fully augmented AST handling qualities have been improved to an acceptable level.

  7. AIR QUALITY MODELING OF AMMONIA: A REGIONAL MODELING PERSPECTIVE

    EPA Science Inventory

    The talk will address the status of modeling of ammonia from a regional modeling perspective, yet the observations and comments should have general applicability. The air quality modeling system components that are central to modeling ammonia will be noted and a perspective on ...

  8. Assessment of national dosimetry quality audits results for teletherapy machines from 1989 to 2015.

    PubMed

    Muhammad, Wazir; Ullah, Asad; Mahmood, Khalid; Matiullah

    2016-01-01

    The purpose of this study was to ensure accuracy in radiation dose delivery, external dosimetry quality audit has an equal importance with routine dosimetry performed at clinics. To do so, dosimetry quality audit was organized by the Secondary Standard Dosimetry Laboratory (SSDL) of Pakistan Institute of Nuclear Science and Technology (PINSTECH) at the national level to investigate and minimize uncertainties involved in the measurement of absorbed dose, and to improve the accuracy of dose measurement at different radiotherapy hospitals. A total of 181 dosimetry quality audits (i.e., 102 of Co-60 and 79 of linear accelerators) for teletherapy units installed at 22 different sites were performed from 1989 to 2015. The percent deviation between users’ calculated/stated dose and evaluated dose (in the result of on-site dosimetry visits) were calculated and the results were analyzed with respect to the limits of ± 2.5% (ICRU "optimal model") ± 3.0% (IAEA on-site dosimetry visits limit) and ± 5.0% (ICRU minimal or "lowest acceptable" model). The results showed that out of 181 total on-site dosimetry visits, 20.44%, 16.02%, and 4.42% were out of acceptable limits of ± 2.5% ± 3.0%, and ± 5.0%, respectively. The importance of a proper ongoing quality assurance program, recommendations of the followed protocols, and properly calibrated thermometers, pressure gauges, and humidity meters at radiotherapy hospitals are essential in maintaining consistency and uniformity of absorbed dose measurements for precision in dose delivery.

  9. STREAM WATER QUALITY MODEL

    EPA Science Inventory

    QUAL2K (or Q2K) is a river and stream water quality model that is intended to represent a modernized version of the QUAL2E (or Q2E) model (Brown and Barnwell 1987). Q2K is similar to Q2E in the following respects:

    • One dimensional. The channel is well-mixed vertically a...

    • Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model

      PubMed Central

      Xu, Shiguo; Wang, Tianxiang; Hu, Suduan

      2015-01-01

      Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results. PMID:25689998

    • Dynamic assessment of water quality based on a variable fuzzy pattern recognition model.

      PubMed

      Xu, Shiguo; Wang, Tianxiang; Hu, Suduan

      2015-02-16

      Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results.

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

      PubMed

      Sun, Siao; Bertrand-Krajewski, Jean-Luc

      2013-01-01

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

    • Comparison of results of an obstacle resolving microscale model with wind tunnel data

      NASA Astrophysics Data System (ADS)

      Grawe, David; Schlünzen, K. Heinke; Pascheke, Frauke

      2013-11-01

      The microscale transport and stream model MITRAS has been improved and a new technique has been implemented to improve numerical stability for complex obstacle configurations. Results of the updated version have been compared with wind tunnel data using an evaluation method that has been established for simple obstacle configurations. MITRAS is a part of the M-SYS model system for the assessment of ambient air quality. A comparison of model results for the flow field against quality ensured wind tunnel data has been carried out for both idealised and realistic test cases. Results of the comparison show a very good agreement of the wind field for most test cases and identify areas of possible improvement of the model. The evaluated MITRAS results can be used as input data for the M-SYS microscale chemistry model MICTM. This paper describes how such a comparison can be carried out for simple as well as realistic obstacle configurations and what difficulties arise.

    • The impact of working memory and the “process of process modelling” on model quality: Investigating experienced versus inexperienced modellers

      NASA Astrophysics Data System (ADS)

      Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R.; Weber, Barbara

      2016-05-01

      A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling.

    • The impact of working memory and the “process of process modelling” on model quality: Investigating experienced versus inexperienced modellers

      PubMed Central

      Martini, Markus; Pinggera, Jakob; Neurauter, Manuel; Sachse, Pierre; Furtner, Marco R.; Weber, Barbara

      2016-01-01

      A process model (PM) represents the graphical depiction of a business process, for instance, the entire process from online ordering a book until the parcel is delivered to the customer. Knowledge about relevant factors for creating PMs of high quality is lacking. The present study investigated the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension, modelling, and reconciliation) were related to PM quality. Our results show that the WM function of relational integration was positively related to PM quality in both modelling groups. The ratio of comprehension phases was negatively related to PM quality in inexperienced modellers and the ratio of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling. PMID:27157858

    • An Integrational Model of Quality of Life in Older Age. Results from the Esrc/mrc Hsrc Quality of Life Survey in Britain.(author Abstract)

      ERIC Educational Resources Information Center

      Bowling, Ann; Gabriel, Zahava

      2004-01-01

      This paper is based on the results of a national survey of the quality of life of 999 randomly sampled people aged 65 and over, living at home in Britain. The survey was semi-structured, and a sample of survey respondents was followed up and interviewed in-depth in order to explore their perceptions of quality of life in full. Comparisons are made…

    • 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.

    • Water quality assessment and meta model development in Melen watershed - Turkey.

      PubMed

      Erturk, Ali; Gurel, Melike; Ekdal, Alpaslan; Tavsan, Cigdem; Ugurluoglu, Aysegul; Seker, Dursun Zafer; Tanik, Aysegul; Ozturk, Izzet

      2010-07-01

      Istanbul, being one of the highly populated metropolitan areas of the world, has been facing water scarcity since the past decade. Water transfer from Melen Watershed was considered as the most feasible option to supply water to Istanbul due to its high water potential and relatively less degraded water quality. This study consists of two parts. In the first part, water quality data covering 26 parameters from 5 monitoring stations were analyzed and assessed due to the requirements of the "Quality Required of Surface Water Intended for the Abstraction of Drinking Water" regulation. In the second part, a one-dimensional stream water quality model with simple water quality kinetics was developed. It formed a basic design for more advanced water quality models for the watershed. The reason for assessing the water quality data and developing a model was to provide information for decision making on preliminary actions to prevent any further deterioration of existing water quality. According to the water quality assessment at the water abstraction point, Melen River has relatively poor water quality with regard to NH(4)(+), BOD(5), faecal streptococcus, manganese and phenol parameters, and is unsuitable for drinking water abstraction in terms of COD, PO(4)(3-), total coliform, total suspended solids, mercury and total chromium parameters. The results derived from the model were found to be consistent with the water quality assessment. It also showed that relatively high inorganic nitrogen and phosphorus concentrations along the streams are related to diffuse nutrient loads that should be managed together with municipal and industrial wastewaters. Copyright 2010 Elsevier Ltd. All rights reserved.

    • The Grand Challenge of Basin-Scale Groundwater Quality Management Modelling

      NASA Astrophysics Data System (ADS)

      Fogg, G. E.

      2017-12-01

      The last 50+ years of agricultural, urban and industrial land and water use practices have accelerated the degradation of groundwater quality in the upper portions of many major aquifer systems upon which much of the world relies for water supply. In the deepest and most extensive systems (e.g., sedimentary basins) that typically have the largest groundwater production rates and hold fresh groundwaters on decadal to millennial time scales, most of the groundwater is not yet contaminated. Predicting the long-term future groundwater quality in such basins is a grand scientific challenge. Moreover, determining what changes in land and water use practices would avert future, irreversible degradation of these massive freshwater stores is a grand challenge both scientifically and societally. It is naïve to think that the problem can be solved by eliminating or reducing enough of the contaminant sources, for human exploitation of land and water resources will likely always result in some contamination. The key lies in both reducing the contaminant sources and more proactively managing recharge in terms of both quantity and quality, such that the net influx of contaminants is sufficiently moderate and appropriately distributed in space and time to reverse ongoing groundwater quality degradation. Just as sustainable groundwater quantity management is greatly facilitated with groundwater flow management models, sustainable groundwater quality management will require the use of groundwater quality management models. This is a new genre of hydrologic models do not yet exist, partly because of the lack of modeling tools and the supporting research to model non-reactive as well as reactive transport on large space and time scales. It is essential that the contaminant hydrogeology community, which has heretofore focused almost entirely on point-source plume-scale problems, direct it's efforts toward the development of process-based transport modeling tools and analyses capable

    • Urban compaction or dispersion? An air quality modelling study

      NASA Astrophysics Data System (ADS)

      Martins, Helena

      2012-07-01

      Urban sprawl is altering the landscape, with current trends pointing to further changes in land use that will, in turn, lead to changes in population, energy consumption, atmospheric emissions and air quality. Urban planners have debated on the most sustainable urban structure, with arguments in favour and against urban compaction and dispersion. However, it is clear that other areas of expertise have to be involved. Urban air quality and human exposure to atmospheric pollutants as indicators of urban sustainability can contribute to the discussion, namely through the study of the relation between urban structure and air quality. This paper addresses the issue by analysing the impacts of alternative urban growth patterns on the air quality of Porto urban region in Portugal, through a 1-year simulation with the MM5-CAMx modelling system. This region has been experiencing one of the highest European rates of urban sprawl, and at the same time presents a poor air quality. As part of the modelling system setup, a sensitivity study was conducted regarding different land use datasets and spatial distribution of emissions. Two urban development scenarios were defined, SPRAWL and COMPACT, together with their new land use and emission datasets; then meteorological and air quality simulations were performed. Results reveal that SPRAWL land use changes resulted in an average temperature increase of 0.4 °C, with local increases reaching as high as 1.5 °C. SPRAWL results also show an aggravation of PM10 annual average values and an increase in the exceedances to the daily limit value. For ozone, differences between scenarios were smaller, with SPRAWL presenting larger concentration differences than COMPACT. Finally, despite the higher concentrations found in SPRAWL, population exposure to the pollutants is higher for COMPACT because more inhabitants are found in areas of highest concentration levels.

  1. [Hyperspectral Remote Sensing Estimation Models for Pasture Quality].

    PubMed

    Ma, Wei-wei; Gong, Cai-lan; Hu, Yong; Wei, Yong-lin; Li, Long; Liu, Feng-yi; Meng, Peng

    2015-10-01

    Crude protein (CP), crude fat (CFA) and crude fiber (CFI) are key indicators for evaluation of the quality and feeding value of pasture. Hence, identification of these biological contents is an essential practice for animal husbandry. As current approaches to pasture quality estimation are time-consuming and costly, and even generate hazardous waste, a real-time and non-destructive method is therefore developed in this study using pasture canopy hyperspectral data. A field campaign was carried out in August 2013 around Qinghai Lake in order to obtain field spectral properties of 19 types of natural pasture using the ASD Field Spec 3, a field spectrometer that works in the optical region (350-2 500 nm) of the electromagnetic spectrum. In additional to the spectral data, pasture samples were also collected from the field and examined in laboratory to measure the relative concentration of CP (%), CFA (%) and CFI (%). After spectral denoising and smoothing, the relationship of pasture quality parameters with the reflectance spectrum, the first derivatives of reflectance (FDR), band ratio and the wavelet coefficients (WCs) was analyzed respectively. The concentration of CP, CFA and CFI of pasture was found closely correlated with FDR with wavebands centered at 424, 1 668, and 918 nm as well as with the low-scale (scale = 2, 4) Morlet, Coiflets and Gassian WCs. Accordingly, the linear, exponential, and polynomial equations between each pasture variable and FDR or WCs were developed. Validation of the developed equations indicated that the polynomial model with an independent variable of Coiflets WCs (scale = 4, wavelength =1 209 nm), the polynomial model with an independent variable of FDR, and the exponential model with an independent variable of FDR were the optimal model for prediction of concentration of CP, CFA and CFI of pasture, respectively. The R2 of the pasture quality estimation models was between 0.646 and 0.762 at the 0.01 significance level. Results suggest

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

    PubMed

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

    2017-01-01

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

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

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

    2012-09-21

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

  5. Model of Auctioneer Estimation of Swordtip Squid (Loligo edulis) Quality

    NASA Astrophysics Data System (ADS)

    Nakamura, Makoto; Matsumoto, Keisuke; Morimoto, Eiji; Ezoe, Satoru; Maeda, Toshimichi; Hirano, Takayuki

    The knowledge of experienced auctioneers regarding the circulation of marine products is an essential skill and is necessary for evaluating product quality and managing aspects such as freshness. In the present study, the ability of an auctioneer to quickly evaluate the freshness of swordtip squid (Loligo edulis) at fish markets was analyzed. Evaluation characteristics used by an auctioneer were analyzed and developed using a fuzzy logic model. Forty boxes containing 247 swordtip squid with mantles measuring 220 mm that had been evaluated and assigned to one of five quality categories by an auctioneer were used for the analysis and the modeling. The relationships between the evaluations of appearance, body color, and muscle freshness were statistically analyzed. It was found that a total of four indexes of the epidermis color strongly reflected evaluations of appearance: dispersion ratio of the head, chroma on the head-end mantle and the difference in the chroma and brightness of the mantle. The fuzzy logic model used these indexes for the antecedent-part of the linguistic rules. The results of both simulation and evaluations demonstrate that the model is robust, with the predicted results corresponding with more than 96% of the quality assignments of the auctioneers.

  6. Modeling water quality, temperature, and flow in Link River, south-central Oregon

    USGS Publications Warehouse

    Sullivan, Annett B.; Rounds, Stewart A.

    2016-09-09

    The 2.1-km (1.3-mi) Link River connects Upper Klamath Lake to the Klamath River in south-central Oregon. A CE-QUAL-W2 flow and water-quality model of Link River was developed to provide a connection between an existing model of the upper Klamath River and any existing or future models of Upper Klamath Lake. Water-quality sampling at six locations in Link River was done during 2013–15 to support model development and to provide a better understanding of instream biogeochemical processes. The short reach and high velocities in Link River resulted in fast travel times and limited water-quality transformations, except for dissolved oxygen. Reaeration through the reach, especially at the falls in Link River, was particularly important in moderating dissolved oxygen concentrations that at times entered the reach at Link River Dam with marked supersaturation or subsaturation. This reaeration resulted in concentrations closer to saturation downstream at the mouth of Link River.

  7. Likelihood of achieving air quality targets under model uncertainties.

    PubMed

    Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

    2011-01-01

    Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

  8. Root Zone Water Quality Model (RZWQM2): Model use, calibration, and validation

    USDA-ARS?s Scientific Manuscript database

    The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model it has many desirable features for the modeling community. This paper outlines the principles of calibr...

  9. New Quality Metrics for Web Search Results

    NASA Astrophysics Data System (ADS)

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

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

  10. 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

  11. 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

  12. Production system with process quality control: modelling and application

    NASA Astrophysics Data System (ADS)

    Tsou, Jia-Chi

    2010-07-01

    Over the past decade, there has been a great deal of research dedicated to the study of quality and the economics of production. In this article, we develop a dynamic model which is based on the hypothesis of a traditional economic production quantity model. Taguchi's cost of poor quality is used to evaluate the cost of poor quality in the dynamic production system. A practical case from the automotive industry, which uses the Six-sigma DMAIC methodology, is discussed to verify the proposed model. This study shows that there is an optimal value of quality investment to make the production system reach a reasonable quality level and minimise the production cost. Based on our model, the management can adjust its investment in quality improvement to generate considerable financial return.

  13. 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.

  14. Better Insight Into Water Resources Management With Integrated Hydrodynamic And Water Quality Models

    NASA Astrophysics Data System (ADS)

    Debele, B.; Srinivasan, R.; Parlange, J.

    2004-12-01

    Models have long been used in water resources management to guide decision making and improve understanding of the system. Numerous models of different scales -spatial and temporal - are available. Yet, very few models manage to bridge simulations of hydrological and water quality parameters from both upland watershed and riverine system. Most water quality models, such as QUAL2E and EPD-RIV1 concentrate on the riverine system while CE-QUAL-W2 and WASP models focus on larger waterbodies, such as lakes and reservoirs. On the other hand, the original SWAT model, HSPF and other upland watershed hydrological models simulate agricultural (diffuse) pollution sources with limited number of processes incorporated to handle point source pollutions that emanate from industrial sectors. Such limitations, which are common in most hydrodynamic and water quality models undermine better understanding that otherwise could be uncovered by employing integrated hydrological and water quality models for both upland watershed and riverine system. The SWAT model is a well documented and verified hydrological and water quality model that has been developed to simulate the effects of various management scenarios on the health of the environment in terms of water quantity and quality. Recently, the SWAT model has been extended to include the simulation of hydrodynamic and water quality parameters in the river system. The extended SWAT model (ESWAT) has been further extended to run using diurnally varying (hourly) weather data and produce outputs at hourly timescales. This and other improvements in the ESWAT model have been documented in the current work. Besides, the results from two case studies in Texas will be reported.

  15. Refinement, Validation and Benchmarking of a Model for E-Government Service Quality

    NASA Astrophysics Data System (ADS)

    Magoutas, Babis; Mentzas, Gregoris

    This paper presents the refinement and validation of a model for Quality of e-Government Services (QeGS). We built upon our previous work where a conceptualized model was identified and put focus on the confirmatory phase of the model development process, in order to come up with a valid and reliable QeGS model. The validated model, which was benchmarked with very positive results with similar models found in the literature, can be used for measuring the QeGS in a reliable and valid manner. This will form the basis for a continuous quality improvement process, unleashing the full potential of e-government services for both citizens and public administrations.

  16. Value-added strategy models to provide quality services in senior health business.

    PubMed

    Yang, Ya-Ting; Lin, Neng-Pai; Su, Shyi; Chen, Ya-Mei; Chang, Yao-Mao; Handa, Yujiro; Khan, Hafsah Arshed Ali; Elsa Hsu, Yi-Hsin

    2017-06-20

    The rapid population aging is now a global issue. The increase in the elderly population will impact the health care industry and health enterprises; various senior needs will promote the growth of the senior health industry. Most senior health studies are focused on the demand side and scarcely on supply. Our study selected quality enterprises focused on aging health and analyzed different strategies to provide excellent quality services to senior health enterprises. We selected 33 quality senior health enterprises in Taiwan and investigated their excellent quality services strategies by face-to-face semi-structured in-depth interviews with CEO and managers of each enterprise in 2013. A total of 33 senior health enterprises in Taiwan. Overall, 65 CEOs and managers of 33 enterprises were interviewed individually. None. Core values and vision, organization structure, quality services provided, strategies for quality services. This study's results indicated four type of value-added strategy models adopted by senior enterprises to offer quality services: (i) residential care and co-residence model, (ii) home care and living in place model, (iii) community e-business experience model and (iv) virtual and physical portable device model. The common part in these four strategy models is that the services provided are elderly centered. These models offer virtual and physical integrations, and also offer total solutions for the elderly and their caregivers. Through investigation of successful strategy models for providing quality services to seniors, we identified opportunities to develop innovative service models and successful characteristics, also policy implications were summarized. The observations from this study will serve as a primary evidenced base for enterprises developing their senior market and, also for promoting the value co-creation possibility through dialogue between customers and those that deliver service. © The Author 2017. Published by Oxford

  17. United3D: a protein model quality assessment program that uses two consensus based methods.

    PubMed

    Terashi, Genki; Oosawa, Makoto; Nakamura, Yuuki; Kanou, Kazuhiko; Takeda-Shitaka, Mayuko

    2012-01-01

    In protein structure prediction, such as template-based modeling and free modeling (ab initio modeling), the step that assesses the quality of protein models is very important. We have developed a model quality assessment (QA) program United3D that uses an optimized clustering method and a simple Cα atom contact-based potential. United3D automatically estimates the quality scores (Qscore) of predicted protein models that are highly correlated with the actual quality (GDT_TS). The performance of United3D was tested in the ninth Critical Assessment of protein Structure Prediction (CASP9) experiment. In CASP9, United3D showed the lowest average loss of GDT_TS (5.3) among the QA methods participated in CASP9. This result indicates that the performance of United3D to identify the high quality models from the models predicted by CASP9 servers on 116 targets was best among the QA methods that were tested in CASP9. United3D also produced high average Pearson correlation coefficients (0.93) and acceptable Kendall rank correlation coefficients (0.68) between the Qscore and GDT_TS. This performance was competitive with the other top ranked QA methods that were tested in CASP9. These results indicate that United3D is a useful tool for selecting high quality models from many candidate model structures provided by various modeling methods. United3D will improve the accuracy of protein structure prediction.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  19. INDOOR AIR QUALITY MODELING (CHAPTER 58)

    EPA Science Inventory

    The chapter discussses indoor air quality (IAQ) modeling. Such modeling provides a way to investigate many IAQ problems without the expense of large field experiments. Where experiments are planned, IAQ models can be used to help design experiments by providing information on exp...

  20. Joint space-time geostatistical model for air quality surveillance

    NASA Astrophysics Data System (ADS)

    Russo, A.; Soares, A.; Pereira, M. J.

    2009-04-01

    Air pollution and peoples' generalized concern about air quality are, nowadays, considered to be a global problem. Although the introduction of rigid air pollution regulations has reduced pollution from industry and power stations, the growing number of cars on the road poses a new pollution problem. Considering the characteristics of the atmospheric circulation and also the residence times of certain pollutants in the atmosphere, a generalized and growing interest on air quality issues led to research intensification and publication of several articles with quite different levels of scientific depth. As most natural phenomena, air quality can be seen as a space-time process, where space-time relationships have usually quite different characteristics and levels of uncertainty. As a result, the simultaneous integration of space and time is not an easy task to perform. This problem is overcome by a variety of methodologies. The use of stochastic models and neural networks to characterize space-time dispersion of air quality is becoming a common practice. The main objective of this work is to produce an air quality model which allows forecasting critical concentration episodes of a certain pollutant by means of a hybrid approach, based on the combined use of neural network models and stochastic simulations. A stochastic simulation of the spatial component with a space-time trend model is proposed to characterize critical situations, taking into account data from the past and a space-time trend from the recent past. To identify near future critical episodes, predicted values from neural networks are used at each monitoring station. In this paper, we describe the design of a hybrid forecasting tool for ambient NO2 concentrations in Lisbon, Portugal.

  1. Quality Assurance Model for Digital Adult Education Materials

    ERIC Educational Resources Information Center

    Dimou, Helen; Kameas, Achilles

    2016-01-01

    Purpose: This paper aims to present a model for the quality assurance of digital educational material that is appropriate for adult education. The proposed model adopts the software quality standard ISO/IEC 9126 and takes into account adult learning theories, Bloom's taxonomy of learning objectives and two instructional design models: Kolb's model…

  2. 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).

  3. Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts

    NASA Astrophysics Data System (ADS)

    Irby, Isaac David

    Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research achieves that goal in three parts. First, a set of eight water quality models is used to establish a model mean and assess model skill. All models were found to exhibit similar skill in resolving dissolved oxygen concentrations as well as a number of dissolved oxygen-influencing variables (temperature, salinity, stratification, chlorophyll and nitrate) and the model mean exhibited the highest individual skill. The location of stratification within the water column was found to be a limiting factor in the models' ability to adequately simulate habitat compression resulting from low-oxygen conditions. Second, two of the previous models underwent the regulatory Chesapeake Bay pollution diet mandated by the Environmental Protection Agency. Both models exhibited a similar relative improvement in dissolved oxygen concentrations as a result of the reduction of nutrients stipulated in the pollution diet. A Confidence Index was developed to identify the locations of the Bay where the models are in agreement and disagreement regarding the impacts of the pollution diet. The models were least certain in the deep part of the upper main stem of the Bay and the uncertainty primarily stemmed from the post-processing methodology. Finally, by projecting the impacts of climate change in 2050 on the Bay, the potential success of the

  4. 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.

  5. Evaluating Predictive Models of Software Quality

    NASA Astrophysics Data System (ADS)

    Ciaschini, V.; Canaparo, M.; Ronchieri, E.; Salomoni, D.

    2014-06-01

    Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

  6. DockQ: A Quality Measure for Protein-Protein Docking Models

    PubMed Central

    Basu, Sankar

    2016-01-01

    The state-of-the-art to assess the structural quality of docking models is currently based on three related yet independent quality measures: Fnat, LRMS, and iRMS as proposed and standardized by CAPRI. These quality measures quantify different aspects of the quality of a particular docking model and need to be viewed together to reveal the true quality, e.g. a model with relatively poor LRMS (>10Å) might still qualify as 'acceptable' with a descent Fnat (>0.50) and iRMS (<3.0Å). This is also the reason why the so called CAPRI criteria for assessing the quality of docking models is defined by applying various ad-hoc cutoffs on these measures to classify a docking model into the four classes: Incorrect, Acceptable, Medium, or High quality. This classification has been useful in CAPRI, but since models are grouped in only four bins it is also rather limiting, making it difficult to rank models, correlate with scoring functions or use it as target function in machine learning algorithms. Here, we present DockQ, a continuous protein-protein docking model quality measure derived by combining Fnat, LRMS, and iRMS to a single score in the range [0, 1] that can be used to assess the quality of protein docking models. By using DockQ on CAPRI models it is possible to almost completely reproduce the original CAPRI classification into Incorrect, Acceptable, Medium and High quality. An average PPV of 94% at 90% Recall demonstrating that there is no need to apply predefined ad-hoc cutoffs to classify docking models. Since DockQ recapitulates the CAPRI classification almost perfectly, it can be viewed as a higher resolution version of the CAPRI classification, making it possible to estimate model quality in a more quantitative way using Z-scores or sum of top ranked models, which has been so valuable for the CASP community. The possibility to directly correlate a quality measure to a scoring function has been crucial for the development of scoring functions for protein structure

  7. Community Multiscale Air Quality Modeling System (CMAQ)

    EPA Pesticide Factsheets

    CMAQ is a computational tool used for air quality management. It models air pollutants including ozone, particulate matter and other air toxics to help determine optimum air quality management scenarios.

  8. Accelerating quality improvement within your organization: Applying the Model for Improvement.

    PubMed

    Crowl, Ashley; Sharma, Anita; Sorge, Lindsay; Sorensen, Todd

    2015-01-01

    To discuss the fundamentals of the Model for Improvement and how the model can be applied to quality improvement activities associated with medication use, including understanding the three essential questions that guide quality improvement, applying a process for actively testing change within an organization, and measuring the success of these changes on care delivery. PubMed from 1990 through April 2014 using the search terms quality improvement, process improvement, hospitals, and primary care. At the authors' discretion, studies were selected based on their relevance in demonstrating the quality improvement process and tests of change within an organization. Organizations are continuously seeking to enhance quality in patient care services, and much of this work focuses on improving care delivery processes. Yet change in these systems is often slow, which can lead to frustration or apathy among frontline practitioners. Adopting and applying the Model for Improvement as a core strategy for quality improvement efforts can accelerate the process. While the model is frequently well known in hospitals and primary care settings, it is not always familiar to pharmacists. In addition, while some organizations may be familiar with the "plan, do, study, act" (PDSA) cycles-one element of the Model for Improvement-many do not apply it effectively. The goal of the model is to combine a continuous process of small tests of change (PDSA cycles) within an overarching aim with a longitudinal measurement process. This process differs from other forms of improvement work that plan and implement large-scale change over an extended period, followed by months of data collection. In this scenario it may take months or years to determine whether an intervention will have a positive impact. By following the Model for Improvement, frontline practitioners and their organizational leaders quickly identify strategies that make a positive difference and result in a greater degree of

  9. 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

  10. COMMUNITY MULTISCALE AIR QUALITY MODELING SYSTEM (ONE ATMOSPHERE)

    EPA Science Inventory

    This task supports ORD's strategy by providing responsive technical support of EPA's mission and provides credible state of the art air quality models and guidance. This research effort is to develop and improve the Community Multiscale Air Quality (CMAQ) modeling system, a mu...

  11. Study on an Air Quality Evaluation Model for Beijing City Under Haze-Fog Pollution Based on New Ambient Air Quality Standards

    PubMed Central

    Li, Li; Liu, Dong-Jun

    2014-01-01

    Since 2012, China has been facing haze-fog weather conditions, and haze-fog pollution and PM2.5 have become hot topics. It is very necessary to evaluate and analyze the ecological status of the air environment of China, which is of great significance for environmental protection measures. In this study the current situation of haze-fog pollution in China was analyzed first, and the new Ambient Air Quality Standards were introduced. For the issue of air quality evaluation, a comprehensive evaluation model based on an entropy weighting method and nearest neighbor method was developed. The entropy weighting method was used to determine the weights of indicators, and the nearest neighbor method was utilized to evaluate the air quality levels. Then the comprehensive evaluation model was applied into the practical evaluation problems of air quality in Beijing to analyze the haze-fog pollution. Two simulation experiments were implemented in this study. One experiment included the indicator of PM2.5 and was carried out based on the new Ambient Air Quality Standards (GB 3095-2012); the other experiment excluded PM2.5 and was carried out based on the old Ambient Air Quality Standards (GB 3095-1996). Their results were compared, and the simulation results showed that PM2.5 was an important indicator for air quality and the evaluation results of the new Air Quality Standards were more scientific than the old ones. The haze-fog pollution situation in Beijing City was also analyzed based on these results, and the corresponding management measures were suggested. PMID:25170682

  12. Towards the Next Generation Air Quality Modeling System ...

    EPA Pesticide Factsheets

    The community multiscale air quality (CMAQ) model of the U.S. Environmental Protection Agency is one of the most widely used air quality model worldwide; it is employed for both research and regulatory applications at major universities and government agencies for improving understanding of the formation and transport of air pollutants. It is noted, however, that air quality issues and climate change assessments need to be addressed globally recognizing the linkages and interactions between meteorology and atmospheric chemistry across a wide range of scales. Therefore, an effort is currently underway to develop the next generation air quality modeling system (NGAQM) that will be based on a global integrated meteorology and chemistry system. The model for prediction across scales-atmosphere (MPAS-A), a global fully compressible non-hydrostatic model with seamlessly refined centroidal Voronoi grids, has been chosen as the meteorological driver of this modeling system. The initial step of adapting MPAS-A for the NGAQM was to implement and test the physics parameterizations and options that are preferred for retrospective air quality simulations (see the work presented by R. Gilliam, R. Bullock, and J. Herwehe at this workshop). The next step, presented herein, would be to link the chemistry from CMAQ to MPAS-A to build a prototype for the NGAQM. Furthermore, the techniques to harmonize transport processes between CMAQ and MPAS-A, methodologies to connect the chemis

  13. 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.

  14. Software Quality Evaluation Models Applicable in Health Information and Communications Technologies. A Review of the Literature.

    PubMed

    Villamor Ordozgoiti, Alberto; Delgado Hito, Pilar; Guix Comellas, Eva María; Fernandez Sanchez, Carlos Manuel; Garcia Hernandez, Milagros; Lluch Canut, Teresa

    2016-01-01

    Information and Communications Technologies in healthcare has increased the need to consider quality criteria through standardised processes. The aim of this study was to analyse the software quality evaluation models applicable to healthcare from the perspective of ICT-purchasers. Through a systematic literature review with the keywords software, product, quality, evaluation and health, we selected and analysed 20 original research papers published from 2005-2016 in health science and technology databases. The results showed four main topics: non-ISO models, software quality evaluation models based on ISO/IEC standards, studies analysing software quality evaluation models, and studies analysing ISO standards for software quality evaluation. The models provide cost-efficiency criteria for specific software, and improve use outcomes. The ISO/IEC25000 standard is shown as the most suitable for evaluating the quality of ICTs for healthcare use from the perspective of institutional acquisition.

  15. Improved model quality assessment using ProQ2.

    PubMed

    Ray, Arjun; Lindahl, Erik; Wallner, Björn

    2012-09-10

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

  16. Urban Air Quality Modelling with AURORA: Prague and Bratislava

    NASA Astrophysics Data System (ADS)

    Veldeman, N.; Viaene, P.; De Ridder, K.; Peelaerts, W.; Lauwaet, D.; Muhammad, N.; Blyth, L.

    2012-04-01

    The European Commission, in its strategy to protect the health of the European citizens, states that in order to assess the impact of air pollution on public health, information on long-term exposure to air pollution should be available. Currently, indicators of air quality are often being generated using measured pollutant concentrations. While air quality monitoring stations data provide accurate time series information at specific locations, air quality models have the advantage of being able to assess the spatial variability of air quality (for different resolutions) and predict air quality in the future based on different scenarios. When running such air quality models at a high spatial and temporal resolution, one can simulate the actual situation as closely as possible, allowing for a detailed assessment of the risk of exposure to citizens from different pollutants. AURORA (Air quality modelling in Urban Regions using an Optimal Resolution Approach), a prognostic 3-dimensional Eulerian chemistry-transport model, is designed to simulate urban- to regional-scale atmospheric pollutant concentration and exposure fields. The AURORA model also allows to calculate the impact of changes in land use (e.g. planting of trees) or of emission reduction scenario's on air quality. AURORA is currently being applied within the ESA atmospheric GMES service, PASODOBLE (http://www.myair-eu.org), that delivers information on air quality, greenhouse gases, stratospheric ozone, … At present there are two operational AURORA services within PASODOBLE. Within the "Air quality forecast service" VITO delivers daily air quality forecasts for Belgium at a resolution of 5 km and for the major Belgian cities: Brussels, Ghent, Antwerp, Liege and Charleroi. Furthermore forecast services are provided for Prague, Czech Republic and Bratislava, Slovakia, both at a resolution of 1 km. The "Urban/regional air quality assessment service" provides urban- and regional-scale maps (hourly resolution

  17. Linking Meteorology, Air Quality Models and Observations to ...

    EPA Pesticide Factsheets

    Epidemiologic studies are critical in establishing the association between exposure to air pollutants and adverse health effects. Results of epidemiologic studies are used by U.S. EPA in developing air quality standards to protect the public from the health effects of air pollutants. A major challenge in environmental epidemiology is adequate exposure characterization. Numerous health studies have used measurements from a few central-site ambient monitors to characterize air pollution exposures. Relying solely on central-site ambient monitors does not account for the spatial-heterogeneity of ambient air pollution patterns, the temporal variability in ambient concentrations, nor the influence of infiltration and indoor sources. Central-site monitoring becomes even more problematic for certain air pollutants that exhibit significant spatial heterogeneity. Statistical interpolation techniques and passive monitoring methods can provide additional spatial resolution in ambient concentration estimates. In addition, spatio-temporal models, which integrate GIS data and other factors, such as meteorology, have also been developed to produce more resolved estimates of ambient concentrations. Models, such as the Community Multi-Scale Air Quality (CMAQ) model, estimate ambient concentrations by combining information on meteorology, source emissions, and chemical-fate and transport. Hybrid modeling approaches, which integrate regional scale models with local scale dispersion

  18. Modeling the Water - Quality Effects of Changes to the Klamath River Upstream of Keno Dam, Oregon

    USGS Publications Warehouse

    Sullivan, Annett B.; Sogutlugil, I. Ertugrul; Rounds, Stewart A.; Deas, Michael L.

    2013-01-01

    The Link River to Keno Dam (Link-Keno) reach of the Klamath River, Oregon, generally has periods of water-quality impairment during summer, including low dissolved oxygen, elevated concentrations of ammonia and algae, and high pH. Efforts are underway to improve water quality in this reach through a Total Maximum Daily Load (TMDL) program and other management and operational actions. To assist in planning, a hydrodynamic and water-quality model was used in this study to provide insight about how various actions could affect water quality in the reach. These model scenarios used a previously developed and calibrated CE-QUAL-W2 model of the Link-Keno reach developed by the U.S. Geological Survey (USGS), Watercourse Engineering Inc., and the Bureau of Reclamation for calendar years 2006-09 (referred to as the "USGS model" in this report). Another model of the same river reach was previously developed by Tetra Tech, Inc. and the Oregon Department of Environmental Quality for years 2000 and 2002 and was used in the TMDL process; that model is referred to as the "TMDL model" in this report. This report includes scenarios that (1) assess the effect of TMDL allocations on water quality, (2) provide insight on certain aspects of the TMDL model, (3) assess various methods to improve water quality in this reach, and (4) examine possible water-quality effects of a future warmer climate. Results presented in this report for the first 5 scenarios supersede or augment those that were previously published (scenarios 1 and 2 in Sullivan and others [2011], 3 through 5 in Sullivan and others [2012]); those previous results are still valid, but the results for those scenarios in this report are more current.

  19. Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

    PubMed

    Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

    2015-09-15

    The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2016-01-01

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

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

    EPA Science Inventory

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

  2. Instructor Quality and EMT Certification Examination Results

    ERIC Educational Resources Information Center

    Russ-Eft, Darlene; Dickison, Phil; Levine, Roger

    2007-01-01

    The Longitudinal Emergency Medical Technician Attributes and Demographics Study (LEADS) provides a representative sampling of EMTs throughout the United States. This study examines the relationship between instructor quality and National Registry of Emergency Medical Technicians certification examination outcomes. Results show significant…

  3. Make or buy decision model with multi-stage manufacturing process and supplier imperfect quality

    NASA Astrophysics Data System (ADS)

    Pratama, Mega Aria; Rosyidi, Cucuk Nur

    2017-11-01

    This research develops an make or buy decision model considering supplier imperfect quality. This model can be used to help companies make the right decision in case of make or buy component with the best quality and the least cost in multistage manufacturing process. The imperfect quality is one of the cost component that must be minimizing in this model. Component with imperfect quality, not necessarily defective. It still can be rework and used for assembly. This research also provide a numerical example and sensitivity analysis to show how the model work. We use simulation and help by crystal ball to solve the numerical problem. The sensitivity analysis result show that percentage of imperfect generally not affect to the model significantly, and the model is not sensitive to changes in these parameters. This is because the imperfect cost are smaller than overall total cost components.

  4. The Attributive Theory of Quality: A Model for Quality Measurement in Higher Education.

    ERIC Educational Resources Information Center

    Afshar, Arash

    A theoretical basis for defining and measuring the quality of institutions of higher education, namely for accreditation purposes, is developed. The theory, the Attributive Theory of Quality, is illustrated using a calculation model that is based on general systems theory. The theory postulates that quality only exists in relation to the…

  5. Evaluating Regional-Scale Air Quality Models

    EPA Science Inventory

    Numerical air quality models are being used to understand the complex interplay among emission loading meteorology, and atmospheric chemistry leading to the formation and accumulation of pollutants in the atmosphere. A model evaluation framework is presented here that considers ...

  6. 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.

  7. 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.

  8. Conceptual Models, Choices, and Benchmarks for Building Quality Work Cultures.

    ERIC Educational Resources Information Center

    Acker-Hocevar, Michele

    1996-01-01

    The two models in Florida's Educational Quality Benchmark System represent a new way of thinking about developing schools' work culture. The Quality Performance System Model identifies nine dimensions of work within a quality system. The Change Process Model provides a theoretical framework for changing existing beliefs, attitudes, and behaviors…

  9. Diagnostic Air Quality Model Evaluation of Source-Specific ...

    EPA Pesticide Factsheets

    Ambient measurements of 78 source-specific tracers of primary and secondary carbonaceous fine particulate matter collected at four midwestern United States locations over a full year (March 2004–February 2005) provided an unprecedented opportunity to diagnostically evaluate the results of a numerical air quality model. Previous analyses of these measurements demonstrated excellent mass closure for the variety of contributing sources. In this study, a carbon-apportionment version of the Community Multiscale Air Quality (CMAQ) model was used to track primary organic and elemental carbon emissions from 15 independent sources such as mobile sources and biomass burning in addition to four precursor-specific classes of secondary organic aerosol (SOA) originating from isoprene, terpenes, aromatics, and sesquiterpenes. Conversion of the source-resolved model output into organic tracer concentrations yielded a total of 2416 data pairs for comparison with observations. While emission source contributions to the total model bias varied by season and measurement location, the largest absolute bias of −0.55 μgC/m3 was attributed to insufficient isoprene SOA in the summertime CMAQ simulation. Biomass combustion was responsible for the second largest summertime model bias (−0.46 μgC/m3 on average). Several instances of compensating errors were also evident; model underpredictions in some sectors were masked by overpredictions in others. The National Exposure Research L

  10. Lean practices for quality results: a case illustration.

    PubMed

    Hwang, Pauline; Hwang, David; Hong, Paul

    2014-01-01

    Increasingly, healthcare providers are implementing lean practices to achieve quality results. Implementing lean healthcare practices is unique compared to manufacturing and other service industries. The purpose of this paper is to present a model that identifies and defines the lean implementation key success factors in healthcare organisations. The model is based on an extant literature review and a case illustration that explores actual lean implementation in a major USA hospital located in a Midwestern city (approximately 300,000 people). An exploratory/descriptive study using observation and follow-up interviews was conducted to identify lean practices in the hospital. Lean practice key drivers include growing elderly populations, rising medical expenses, decreasing insurance coverage and decreasing management support. Effectively implementing lean practices to increase bottom-line results and improve organisational integrity requires sharing goals and processes among healthcare managers and professionals. An illustration explains the model and the study provides a sound foundation for empirical work. Practical implications are included. Lean practices minimise waste and unnecessary hospital stays while simultaneously enhancing customer values and deploying resources in supply systems. Leadership requires clear project targets based on sound front-end planning because initial implementation steps involve uncertainty and ambiguity (i.e. fuzzy front-end planning). Since top management support is crucial for implementing lean practices successfully, a heavyweight manager, who communicates well both with top managers and project team members, is an important success factor when implementing lean practices. Increasingly, green orientation and sustainability initiatives are phrases that replaced lean practices. Effective results; e.g. waste reduction, employee satisfaction and customer values are applicable to bigger competitive challenges arising both in specific

  11. 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

  12. A dynamic water-quality modeling framework for the Neuse River estuary, North Carolina

    USGS Publications Warehouse

    Bales, Jerad D.; Robbins, Jeanne C.

    1999-01-01

    As a result of fish kills in the Neuse River estuary in 1995, nutrient reduction strategies were developed for point and nonpoint sources in the basin. However, because of the interannual variability in the natural system and the resulting complex hydrologic-nutrient inter- actions, it is difficult to detect through a short-term observational program the effects of management activities on Neuse River estuary water quality and aquatic health. A properly constructed water-quality model can be used to evaluate some of the potential effects of manage- ment actions on estuarine water quality. Such a model can be used to predict estuarine response to present and proposed nutrient strategies under the same set of meteorological and hydrologic conditions, thus removing the vagaries of weather and streamflow from the analysis. A two-dimensional, laterally averaged hydrodynamic and water-quality modeling framework was developed for the Neuse River estuary by using previously collected data. Development of the modeling framework consisted of (1) computational grid development, (2) assembly of data for model boundary conditions and model testing, (3) selection of initial values of model parameters, and (4) limited model testing. The model domain extends from Streets Ferry to Oriental, N.C., includes seven lateral embayments that have continual exchange with the main- stem of the estuary, three point-source discharges, and three tributary streams. Thirty-five computational segments represent the mainstem of the estuary, and the entire framework contains a total of 60 computa- tional segments. Each computational cell is 0.5 meter thick; segment lengths range from 500 meters to 7,125 meters. Data that were used to develop the modeling framework were collected during March through October 1991 and represent the most comprehensive data set available prior to 1997. Most of the data were collected by the North Carolina Division of Water Quality, the University of North Carolina

  13. Design and Establishment of Quality Model of Fundamental Geographic Information Database

    NASA Astrophysics Data System (ADS)

    Ma, W.; Zhang, J.; Zhao, Y.; Zhang, P.; Dang, Y.; Zhao, T.

    2018-04-01

    In order to make the quality evaluation for the Fundamental Geographic Information Databases(FGIDB) more comprehensive, objective and accurate, this paper studies and establishes a quality model of FGIDB, which formed by the standardization of database construction and quality control, the conformity of data set quality and the functionality of database management system, and also designs the overall principles, contents and methods of the quality evaluation for FGIDB, providing the basis and reference for carry out quality control and quality evaluation for FGIDB. This paper designs the quality elements, evaluation items and properties of the Fundamental Geographic Information Database gradually based on the quality model framework. Connected organically, these quality elements and evaluation items constitute the quality model of the Fundamental Geographic Information Database. This model is the foundation for the quality demand stipulation and quality evaluation of the Fundamental Geographic Information Database, and is of great significance on the quality assurance in the design and development stage, the demand formulation in the testing evaluation stage, and the standard system construction for quality evaluation technology of the Fundamental Geographic Information Database.

  14. HABSEED: a Simple Spatially Explicit Meta-Populations Model Using Remote Sensing Derived Habitat Quality Data

    NASA Astrophysics Data System (ADS)

    Heumann, B. W.; Guichard, F.; Seaquist, J. W.

    2005-05-01

    The HABSEED model uses remote sensing derived NPP as a surrogate for habitat quality as the driving mechanism for population growth and local seed dispersal. The model has been applied to the Sahel region of Africa. Results show that the functional response of plants to habitat quality alters population distribution. Plants more tolerant of medium quality habitat have greater distributions to the North while plants requiring only the best habitat are limited to the South. For all functional response types, increased seed production results in diminishing returns. Functional response types have been related to life history tradeoffs and r-K strategies based on the results. Results are compared to remote sensing derived vegetation land cover.

  15. Proteomics Quality Control: Quality Control Software for MaxQuant Results.

    PubMed

    Bielow, Chris; Mastrobuoni, Guido; Kempa, Stefan

    2016-03-04

    Mass spectrometry-based proteomics coupled to liquid chromatography has matured into an automatized, high-throughput technology, producing data on the scale of multiple gigabytes per instrument per day. Consequently, an automated quality control (QC) and quality analysis (QA) capable of detecting measurement bias, verifying consistency, and avoiding propagation of error is paramount for instrument operators and scientists in charge of downstream analysis. We have developed an R-based QC pipeline called Proteomics Quality Control (PTXQC) for bottom-up LC-MS data generated by the MaxQuant software pipeline. PTXQC creates a QC report containing a comprehensive and powerful set of QC metrics, augmented with automated scoring functions. The automated scores are collated to create an overview heatmap at the beginning of the report, giving valuable guidance also to nonspecialists. Our software supports a wide range of experimental designs, including stable isotope labeling by amino acids in cell culture (SILAC), tandem mass tags (TMT), and label-free data. Furthermore, we introduce new metrics to score MaxQuant's Match-between-runs (MBR) functionality by which peptide identifications can be transferred across Raw files based on accurate retention time and m/z. Last but not least, PTXQC is easy to install and use and represents the first QC software capable of processing MaxQuant result tables. PTXQC is freely available at https://github.com/cbielow/PTXQC .

  16. Development of an Instructional Quality Assurance Model in Nursing Science

    ERIC Educational Resources Information Center

    Ajpru, Haruthai; Pasiphol, Shotiga; Wongwanich, Suwimon

    2011-01-01

    The purpose of this study was to develop an instructional quality assurance model in nursing science. The study was divided into 3 phases; (1) to study the information for instructional quality assurance model development (2) to develop an instructional quality assurance model in nursing science and (3) to audit and the assessment of the developed…

  17. EPA RESEARCH HIGHLIGHTS -- MODELS-3/CMAQ OFFERS COMPREHENSIVE APPROACH TO AIR QUALITY MODELING

    EPA Science Inventory

    Regional and global coordinated efforts are needed to address air quality problems that are growing in complexity and scope. Models-3 CMAQ contains a community multi-scale air quality modeling system for simulating urban to regional scale pollution problems relating to troposphe...

  18. Quality Concerns in Technical Education in India: A Quantifiable Quality Enabled Model

    ERIC Educational Resources Information Center

    Gambhir, Victor; Wadhwa, N. C.; Grover, Sandeep

    2016-01-01

    Purpose: The paper aims to discuss current Technical Education scenarios in India. It proposes modelling the factors affecting quality in a technical institute and then applying a suitable technique for assessment, comparison and ranking. Design/methodology/approach: The paper chose graph theoretic approach for quantification of quality-enabled…

  19. Exploring the critical quality attributes and models of smart homes.

    PubMed

    Ted Luor, Tainyi; Lu, Hsi-Peng; Yu, Hueiju; Lu, Yinshiu

    2015-12-01

    Research on smart homes has significantly increased in recent years owing to their considerably improved affordability and simplicity. However, the challenge is that people have different needs (or attitudes toward smart homes), and provision should be tailored to individuals. A few studies have classified the functions of smart homes. Therefore, the Kano model is first adopted as a theoretical base to explore whether the functional classifications of smart homes are attractive or necessary, or both. Second, three models and test user attitudes toward three function types of smart homes are proposed. Based on the Kano model, the principal results, namely, two "Attractive Quality" and nine "Indifferent Quality" items, are found. Verification of the hypotheses also indicates that the entertainment, security, and automation functions are significantly correlated with the variables "perceive useful" and "attitude." Cost consideration is negatively correlated with attitudes toward entertainment and automation. Results suggest that smart home providers should survey user needs for their product instead of merely producing smart homes based on the design of the builder or engineer. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  20. Modeling water quality in an urban river using hydrological factors--data driven approaches.

    PubMed

    Chang, Fi-John; Tsai, Yu-Hsuan; Chen, Pin-An; Coynel, Alexandra; Vachaud, Georges

    2015-03-15

    Contrasting seasonal variations occur in river flow and water quality as a result of short duration, severe intensity storms and typhoons in Taiwan. Sudden changes in river flow caused by impending extreme events may impose serious degradation on river water quality and fateful impacts on ecosystems. Water quality is measured in a monthly/quarterly scale, and therefore an estimation of water quality in a daily scale would be of good help for timely river pollution management. This study proposes a systematic analysis scheme (SAS) to assess the spatio-temporal interrelation of water quality in an urban river and construct water quality estimation models using two static and one dynamic artificial neural networks (ANNs) coupled with the Gamma test (GT) based on water quality, hydrological and economic data. The Dahan River basin in Taiwan is the study area. Ammonia nitrogen (NH3-N) is considered as the representative parameter, a correlative indicator in judging the contamination level over the study. Key factors the most closely related to the representative parameter (NH3-N) are extracted by the Gamma test for modeling NH3-N concentration, and as a result, four hydrological factors (discharge, days w/o discharge, water temperature and rainfall) are identified as model inputs. The modeling results demonstrate that the nonlinear autoregressive with exogenous input (NARX) network furnished with recurrent connections can accurately estimate NH3-N concentration with a very high coefficient of efficiency value (0.926) and a low RMSE value (0.386 mg/l). Besides, the NARX network can suitably catch peak values that mainly occur in dry periods (September-April in the study area), which is particularly important to water pollution treatment. The proposed SAS suggests a promising approach to reliably modeling the spatio-temporal NH3-N concentration based solely on hydrological data, without using water quality sampling data. It is worth noticing that such estimation can be

  1. MQAPRank: improved global protein model quality assessment by learning-to-rank.

    PubMed

    Jing, Xiaoyang; Dong, Qiwen

    2017-05-25

    Protein structure prediction has achieved a lot of progress during the last few decades and a greater number of models for a certain sequence can be predicted. Consequently, assessing the qualities of predicted protein models in perspective is one of the key components of successful protein structure prediction. Over the past years, a number of methods have been developed to address this issue, which could be roughly divided into three categories: single methods, quasi-single methods and clustering (or consensus) methods. Although these methods achieve much success at different levels, accurate protein model quality assessment is still an open problem. Here, we present the MQAPRank, a global protein model quality assessment program based on learning-to-rank. The MQAPRank first sorts the decoy models by using single method based on learning-to-rank algorithm to indicate their relative qualities for the target protein. And then it takes the first five models as references to predict the qualities of other models by using average GDT_TS scores between reference models and other models. Benchmarked on CASP11 and 3DRobot datasets, the MQAPRank achieved better performances than other leading protein model quality assessment methods. Recently, the MQAPRank participated in the CASP12 under the group name FDUBio and achieved the state-of-the-art performances. The MQAPRank provides a convenient and powerful tool for protein model quality assessment with the state-of-the-art performances, it is useful for protein structure prediction and model quality assessment usages.

  2. Integrity Model Application: A Quality Support System for Decision-makers on Water Quality Assessment and Improvement

    NASA Astrophysics Data System (ADS)

    Mirauda, D.; Ostoich, M.; Di Maria, F.; Benacchio, S.; Saccardo, I.

    2018-03-01

    In this paper, a mathematical model has been applied to a river in North-East Italy to describe vulnerability scenarios due to environmental pollution phenomena. Such model, based on the influence diagrams theory, allowed identifying the extremely critical factors, such as wastewater discharges, drainage of diffuse pollution from agriculture and climate changes, which might affect the water quality of the river. The obtained results underlined how the water quality conditions have improved thanks to the continuous controls on the territory, following the application of Water Framework Directive 2000/60/EC. Nevertheless, some fluvial stretches did not reach the “good ecological status” by 2015, because of the increasing population in urban areas recorded in the last years and the high presence of tourists during the summer months, not balanced by a treatment plants upgrade.

  3. Design guidelines for an umbilical cord blood stem cell therapy quality assessment model

    NASA Astrophysics Data System (ADS)

    Januszewski, Witold S.; Michałek, Krzysztof; Yagensky, Oleksandr; Wardzińska, Marta

    The paper enlists the pivotal guidelines for producing an empirical umbilical cord blood stem cell therapy quality assessment model. The methodology adapted was single equation linear model with domain knowledge derived from MEDAFAR classification. The resulting model is ready for therapeutical application.

  4. Discrete State Change Model of Manufacturing Quality to Aid Assembly Process Design

    NASA Astrophysics Data System (ADS)

    Koga, Tsuyoshi; Aoyama, Kazuhiro

    This paper proposes a representation model of the quality state change in an assembly process that can be used in a computer-aided process design system. In order to formalize the state change of the manufacturing quality in the assembly process, the functions, operations, and quality changes in the assembly process are represented as a network model that can simulate discrete events. This paper also develops a design method for the assembly process. The design method calculates the space of quality state change and outputs a better assembly process (better operations and better sequences) that can be used to obtain the intended quality state of the final product. A computational redesigning algorithm of the assembly process that considers the manufacturing quality is developed. The proposed method can be used to design an improved manufacturing process by simulating the quality state change. A prototype system for planning an assembly process is implemented and applied to the design of an auto-breaker assembly process. The result of the design example indicates that the proposed assembly process planning method outputs a better manufacturing scenario based on the simulation of the quality state change.

  5. 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.

  6. The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

    NASA Astrophysics Data System (ADS)

    Schneider, Philipp; Stebel, Kerstin; Ajtai, Nicolae; Diamandi, Andrei; Horalek, Jan; Nemuc, Anca; Stachlewska, Iwona; Zehner, Claus

    2017-04-01

    We present a summary and some first results of a new ESA-funded project entitled Satellite based Monitoring Initiative for Regional Air quality (SAMIRA), which aims at improving regional and local air quality monitoring through synergetic use of data from present and upcoming satellite instruments, traditionally used in situ air quality monitoring networks and output from chemical transport models. Through collaborative efforts in four countries, namely Romania, Poland, the Czech Republic and Norway, all with existing air quality problems, SAMIRA intends to support the involved institutions and associated users in their national monitoring and reporting mandates as well as to generate novel research in this area. The primary goal of SAMIRA is to demonstrate the usefulness of existing and future satellite products of air quality for improving monitoring and mapping of air pollution at the regional scale. A total of six core activities are being carried out in order to achieve this goal: Firstly, the project is developing and optimizing algorithms for the retrieval of hourly aerosol optical depth (AOD) maps from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard of Meteosat Second Generation. As a second activity, SAMIRA aims to derive particulate matter (PM2.5) estimates from AOD data by developing robust algorithms for AOD-to-PM conversion with the support from model- and Lidar data. In a third activity, we evaluate the added value of satellite products of atmospheric composition for operational European-scale air quality mapping using geostatistics and auxiliary datasets. The additional benefit of satellite-based monitoring over existing monitoring techniques (in situ, models) is tested by combining these datasets using geostatistical methods and demonstrated for nitrogen dioxide (NO2), sulphur dioxide (SO2), and aerosol optical depth/particulate matter. As a fourth activity, the project is developing novel algorithms for downscaling coarse

  7. Manager personality, manager service quality orientation, and service climate: test of a model.

    PubMed

    Salvaggio, Amy Nicole; Schneider, Benjamin; Nishii, Lisa H; Mayer, David M; Ramesh, Anuradha; Lyon, Julie S

    2007-11-01

    This article conceptually and empirically explores the relationships among manager personality, manager service quality orientation, and climate for customer service. Data were collected from 1,486 employees and 145 managers in grocery store departments (N = 145) to test the authors' theoretical model. Largely consistent with hypotheses, results revealed that core self-evaluations were positively related to managers' service quality orientation, even after dimensions of the Big Five model of personality were controlled, and that service quality orientation fully mediated the relationship between personality and global service climate. Implications for personality and organizational climate research are discussed. (c) 2007 APA

  8. Application of uncertainty and sensitivity analysis to the air quality SHERPA modelling tool

    NASA Astrophysics Data System (ADS)

    Pisoni, E.; Albrecht, D.; Mara, T. A.; Rosati, R.; Tarantola, S.; Thunis, P.

    2018-06-01

    Air quality has significantly improved in Europe over the past few decades. Nonetheless we still find high concentrations in measurements mainly in specific regions or cities. This dimensional shift, from EU-wide to hot-spot exceedances, calls for a novel approach to regional air quality management (to complement EU-wide existing policies). The SHERPA (Screening for High Emission Reduction Potentials on Air quality) modelling tool was developed in this context. It provides an additional tool to be used in support to regional/local decision makers responsible for the design of air quality plans. It is therefore important to evaluate the quality of the SHERPA model, and its behavior in the face of various kinds of uncertainty. Uncertainty and sensitivity analysis techniques can be used for this purpose. They both reveal the links between assumptions and forecasts, help in-model simplification and may highlight unexpected relationships between inputs and outputs. Thus, a policy steered SHERPA module - predicting air quality improvement linked to emission reduction scenarios - was evaluated by means of (1) uncertainty analysis (UA) to quantify uncertainty in the model output, and (2) by sensitivity analysis (SA) to identify the most influential input sources of this uncertainty. The results of this study provide relevant information about the key variables driving the SHERPA output uncertainty, and advise policy-makers and modellers where to place their efforts for an improved decision-making process.

  9. Quality Improvement on the Acute Inpatient Psychiatry Unit Using the Model for Improvement

    PubMed Central

    Singh, Kuldeep; Sanderson, Joshua; Galarneau, David; Keister, Thomas; Hickman, Dean

    2013-01-01

    Background A need exists for constant evaluation and modification of processes within healthcare systems to achieve quality improvement. One common approach is the Model for Improvement that can be used to clearly define aims, measures, and changes that are then implemented through a plan-do-study-act (PDSA) cycle. This approach is a commonly used method for improving quality in a wide range of fields. The Model for Improvement allows for a systematic process that can be revised at set time intervals to achieve a desired result. Methods We used the Model for Improvement in an acute psychiatry unit (APU) to improve the screening incidence of abnormal involuntary movements in eligible patients—those starting or continuing on standing neuroleptics—with the Abnormal Involuntary Movement Scale (AIMS). Results After 8 weeks of using the Model for Improvement, both of the participating inpatient services in the APU showed substantial overall improvement in screening for abnormal involuntary movements using the AIMS. Conclusion Crucial aspects of a successful quality improvement initiative based on the Model for Improvement are well-defined goals, process measures, and structured PDSA cycles. Success also requires communication, organization, and participation of the entire team. PMID:24052768

  10. 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

  11. Advanced Computational Methods for High-accuracy Refinement of Protein Low-quality Models

    NASA Astrophysics Data System (ADS)

    Zang, Tianwu

    Predicting the 3-dimentional structure of protein has been a major interest in the modern computational biology. While lots of successful methods can generate models with 3˜5A root-mean-square deviation (RMSD) from the solution, the progress of refining these models is quite slow. It is therefore urgently needed to develop effective methods to bring low-quality models to higher-accuracy ranges (e.g., less than 2 A RMSD). In this thesis, I present several novel computational methods to address the high-accuracy refinement problem. First, an enhanced sampling method, named parallel continuous simulated tempering (PCST), is developed to accelerate the molecular dynamics (MD) simulation. Second, two energy biasing methods, Structure-Based Model (SBM) and Ensemble-Based Model (EBM), are introduced to perform targeted sampling around important conformations. Third, a three-step method is developed to blindly select high-quality models along the MD simulation. These methods work together to make significant refinement of low-quality models without any knowledge of the solution. The effectiveness of these methods is examined in different applications. Using the PCST-SBM method, models with higher global distance test scores (GDT_TS) are generated and selected in the MD simulation of 18 targets from the refinement category of the 10th Critical Assessment of Structure Prediction (CASP10). In addition, in the refinement test of two CASP10 targets using the PCST-EBM method, it is indicated that EBM may bring the initial model to even higher-quality levels. Furthermore, a multi-round refinement protocol of PCST-SBM improves the model quality of a protein to the level that is sufficient high for the molecular replacement in X-ray crystallography. Our results justify the crucial position of enhanced sampling in the protein structure prediction and demonstrate that a considerable improvement of low-accuracy structures is still achievable with current force fields.

  12. Quality control of the RMS US flood model

    NASA Astrophysics Data System (ADS)

    Jankowfsky, Sonja; Hilberts, Arno; Mortgat, Chris; Li, Shuangcai; Rafique, Farhat; Rajesh, Edida; Xu, Na; Mei, Yi; Tillmanns, Stephan; Yang, Yang; Tian, Ye; Mathur, Prince; Kulkarni, Anand; Kumaresh, Bharadwaj Anna; Chaudhuri, Chiranjib; Saini, Vishal

    2016-04-01

    The RMS US flood model predicts the flood risk in the US with a 30 m resolution for different return periods. The model is designed for the insurance industry to estimate the cost of flood risk for a given location. Different statistical, hydrological and hydraulic models are combined to develop the flood maps for different return periods. A rainfall-runoff and routing model, calibrated with observed discharge data, is run with 10 000 years of stochastic simulated precipitation to create time series of discharge and surface runoff. The 100, 250 and 500 year events are extracted from these time series as forcing for a two-dimensional pluvial and fluvial inundation model. The coupling of all the different models which are run on the large area of the US implies a certain amount of uncertainty. Therefore, special attention is paid to the final quality control of the flood maps. First of all, a thorough quality analysis of the Digital Terrain model and the river network was done, as the final quality of the flood maps depends heavily on the DTM quality. Secondly, the simulated 100 year discharge in the major river network (600 000 km) is compared to the 100 year discharge derived using extreme value distribution of all USGS gauges with more than 20 years of peak values (around 11 000 gauges). Thirdly, for each gauge the modelled flood depth is compared to the depth derived from the USGS rating curves. Fourthly, the modelled flood depth is compared to the base flood elevation given in the FEMA flood maps. Fifthly, the flood extent is compared to the FEMA flood extent. Then, for historic events we compare flood extents and flood depths at given locations. Finally, all the data and spatial layers are uploaded on geoserver to facilitate the manual investigation of outliers. The feedback from the quality control is used to improve the model and estimate its uncertainty.

  13. On Regional Modeling to Support Air Quality Policies

    EPA Science Inventory

    We examine the use of the Community Multiscale Air Quality (CMAQ) model in simulating the changes in the extreme values of air quality that are of interest to the regulatory agencies. Year-to-year changes in ozone air quality are attributable to variations in the prevailing mete...

  14. 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

  15. Development of Water Quality Modeling in the United States

    EPA Science Inventory

    This presentation describes historical trends in water quality model development in the United States, reviews current efforts, and projects promising future directions. Water quality modeling has a relatively long history in the United States. While its origins lie in the work...

  16. A coastal three-dimensional water quality model of nitrogen in Jiaozhou Bay linking field experiments with modelling.

    PubMed

    Lu, Dongliang; Li, Keqiang; Liang, Shengkang; Lin, Guohong; Wang, Xiulin

    2017-01-15

    With anthropogenic changes, the structure and quantity of nitrogen nutrients have changed in coastal ocean, which has dramatically influenced the water quality. Water quality modeling can contribute to the necessary scientific grounding of coastal management. In this paper, some of the dynamic functions and parameters of nitrogen were calibrated based on coastal field experiments covering the dynamic nitrogen processes in Jiaozhou Bay (JZB), including phytoplankton growth, respiration, and mortality; particulate nitrogen degradation; and dissolved organic nitrogen remineralization. The results of the field experiments and box model simulations showed good agreement (RSD=20%±2% and SI=0.77±0.04). A three-dimensional water quality model of nitrogen (3DWQMN) in JZB was improved and the dynamic parameters were updated according to field experiments. The 3DWQMN was validated based on observed data from 2012 to 2013, with good agreement (RSD=27±4%, SI=0.68±0.06, and K=0.48±0.04), which testifies to the model's credibility. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Water quality modeling using geographic information system (GIS) data

    NASA Technical Reports Server (NTRS)

    Engel, Bernard A

    1992-01-01

    Protection of the environment and natural resources at the Kennedy Space Center (KSC) is of great concern. The potential for surface and ground water quality problems resulting from non-point sources of pollution was examined using models. Since spatial variation of parameters required was important, geographic information systems (GIS) and their data were used. The potential for groundwater contamination was examined using the SEEPAGE (System for Early Evaluation of the Pollution Potential of Agricultural Groundwater Environments) model. A watershed near the VAB was selected to examine potential for surface water pollution and erosion using the AGNPS (Agricultural Non-Point Source Pollution) model.

  18. An Overview of Atmospheric Chemistry and Air Quality Modeling

    NASA Technical Reports Server (NTRS)

    Johnson, Matthew S.

    2017-01-01

    This presentation will include my personal research experience and an overview of atmospheric chemistry and air quality modeling to the participants of the NASA Student Airborne Research Program (SARP 2017). The presentation will also provide examples on ways to apply airborne observations for chemical transport (CTM) and air quality (AQ) model evaluation. CTM and AQ models are important tools in understanding tropospheric-stratospheric composition, atmospheric chemistry processes, meteorology, and air quality. This presentation will focus on how NASA scientist currently apply CTM and AQ models to better understand these topics. Finally, the importance of airborne observation in evaluating these topics and how in situ and remote sensing observations can be used to evaluate and improve CTM and AQ model predictions will be highlighted.

  19. THE ATMOSPHERIC MODEL EVALUATION TOOL (AMET); AIR QUALITY MODULE

    EPA Science Inventory

    This presentation reviews the development of the Atmospheric Model Evaluation Tool (AMET) air quality module. The AMET tool is being developed to aid in the model evaluation. This presentation focuses on the air quality evaluation portion of AMET. Presented are examples of the...

  20. AIR QUALITY SIMULATION MODEL PERFORMANCE FOR ONE-HOUR AVERAGES

    EPA Science Inventory

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

  1. Climate Change Impacts on US Water Quality using two Models: HAWQS and US Basins

    EPA Science Inventory

    Climate change and freshwater quality are well-linked. Changes in climate result in changes in streamflow and rising water temperatures, which impact biochemical reaction rates and increase stratification in lakes and reservoirs. Using two water quality modeling systems (the Hydr...

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

    NASA Technical Reports Server (NTRS)

    Canacci, Victor A.; Gonsalez, Jose C.

    1999-01-01

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

  3. Projection pursuit water quality evaluation model based on chicken swam algorithm

    NASA Astrophysics Data System (ADS)

    Hu, Zhe

    2018-03-01

    In view of the uncertainty and ambiguity of each index in water quality evaluation, in order to solve the incompatibility of evaluation results of individual water quality indexes, a projection pursuit model based on chicken swam algorithm is proposed. The projection index function which can reflect the water quality condition is constructed, the chicken group algorithm (CSA) is introduced, the projection index function is optimized, the best projection direction of the projection index function is sought, and the best projection value is obtained to realize the water quality evaluation. The comparison between this method and other methods shows that it is reasonable and feasible to provide decision-making basis for water pollution control in the basin.

  4. Community Multiscale Air Quality Model

    EPA Science Inventory

    The U.S. EPA developed the Community Multiscale Air Quality (CMAQ) system to apply a “one atmosphere” multiscale and multi-pollutant modeling approach based mainly on the “first principles” description of the atmosphere. The multiscale capability is supported by the governing di...

  5. Conceptual Model for Quality of Life among Adults With Congenital or Early Deafness

    PubMed Central

    Kushalnagar, P; McKee, M; Smith, SR; Hopper, M; Kavin, D; Atcherson, SR

    2015-01-01

    Background A conceptual model of health-related quality of life (QoL) is needed to describe key themes that impact perceived QoL in adults with congenital or early deafness. Objective: To revise University of Washington Center for Disability Policy and Research's conceptual model of health promotion and QoL, with suggestions for applying the model to improving programs or services that target deaf adults with early deafness. Methods Purposive and theoretical sampling of 35 adults who were born or became deaf early was planned in a 1-year study. In-depth semi-structured interviews probed deaf adult participants' perceptions about quality of life as a deaf individual. Data saturation was reached at the 17th interview with 2 additional interviews for validation, resulting in a total sample of 19 deaf adults. Coding and thematic analysis were conducted to develop the conceptual model. Results Our conceptual model delineates the relationships between health status (self-acceptance, coping with limitations), intrinsic (functional communication skills, navigating barriers/self-advocacy, resilience) and extrinsic (acceptance by others, access to information, educating others) factors in their influence on deaf adult quality of life outcomes at home, college, work, and in the community. Conclusions Findings demonstrate the need for the programs and services to consider not only factors intrinsic to the deaf individual but also extrinsic factors in enhancing perceived quality of life outcomes among people with a range of functional hearing and language preferences, including American Sign Language. PMID:24947577

  6. Better Data Quality for Better Healthcare Research Results - A Case Study.

    PubMed

    Hart, Robert; Kuo, Mu-Hsing

    2017-01-01

    Electronic Health Records (EHRs) have been identified as a key tool to collect data for healthcare research. However, EHR data must be of sufficient quality to support quality research results. Island Health, BC, Canada has invested and continues to invest in the development of solutions to address the quality of its EHR data and support high quality healthcare studies. This paper examines Island Health's data quality engine, its development and its successful implementation.

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

    PubMed

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

    2008-01-01

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

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

    PubMed Central

    2014-01-01

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

  9. Development of the Next Generation Air Quality Modeling System

    EPA Science Inventory

    A next generation air quality modeling system is being developed at the U.S. EPA to enable modeling of air quality from global to regional to (eventually) local scales. We envision that the system will have three configurations: 1. Global meteorology with seamless mesh refinemen...

  10. 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.

  11. A Total Quality Leadership Process Improvement Model

    DTIC Science & Technology

    1993-12-01

    Leadership Process Improvement Model by Archester Houston, Ph.D. and Steven L. Dockstader, Ph.D. DTICS ELECTE tleaese oand sale itsFeat ben proe 94-12058...tTl ’AND SIATE COVERID0 Z lits Z40 uerI’Ll12/93 IFinalS.FNR IM F A Total Quality Leadership Process Improvement Model M ARRhOW~ Archester Houston, Ph.D...and Steven L. Dockstader, Ph.D. ?. 7PEJORMING ORG-AN1:AION NAMEIS) AND 00-RESS(ES) L PERFORMIN4 ORAINIZATION Total Quality Leadership OfficeREOTNMR

  12. Atmospheric Model Evaluation Tool for meteorological and air quality simulations

    EPA Pesticide Factsheets

    The Atmospheric Model Evaluation Tool compares model predictions to observed data from various meteorological and air quality observation networks to help evaluate meteorological and air quality simulations.

  13. An Effect of the Co-Operative Network Model for Students' Quality in Thai Primary Schools

    ERIC Educational Resources Information Center

    Khanthaphum, Udomsin; Tesaputa, Kowat; Weangsamoot, Visoot

    2016-01-01

    This research aimed: 1) to study the current and desirable states of the co-operative network in developing the learners' quality in Thai primary schools, 2) to develop a model of the co-operative network in developing the learners' quality, and 3) to examine the results of implementation of the co-operative network model in the primary school.…

  14. Water quality modelling of an impacted semi-arid catchment using flow data from the WEAP model

    NASA Astrophysics Data System (ADS)

    Slaughter, Andrew R.; Mantel, Sukhmani K.

    2018-04-01

    The continuous decline in water quality in many regions is forcing a shift from quantity-based water resources management to a greater emphasis on water quality management. Water quality models can act as invaluable tools as they facilitate a conceptual understanding of processes affecting water quality and can be used to investigate the water quality consequences of management scenarios. In South Africa, the Water Quality Systems Assessment Model (WQSAM) was developed as a management-focussed water quality model that is relatively simple to be able to utilise the small amount of available observed data. Importantly, WQSAM explicitly links to systems (yield) models routinely used in water resources management in South Africa by using their flow output to drive water quality simulations. Although WQSAM has been shown to be able to represent the variability of water quality in South African rivers, its focus on management from a South African perspective limits its use to within southern African regions for which specific systems model setups exist. Facilitating the use of WQSAM within catchments outside of southern Africa and within catchments for which these systems model setups to not exist would require WQSAM to be able to link to a simple-to-use and internationally-applied systems model. One such systems model is the Water Evaluation and Planning (WEAP) model, which incorporates a rainfall-runoff component (natural hydrology), and reservoir storage, return flows and abstractions (systems modelling), but within which water quality modelling facilities are rudimentary. The aims of the current study were therefore to: (1) adapt the WQSAM model to be able to use as input the flow outputs of the WEAP model and; (2) provide an initial assessment of how successful this linkage was by application of the WEAP and WQSAM models to the Buffalo River for historical conditions; a small, semi-arid and impacted catchment in the Eastern Cape of South Africa. The simulations of

  15. Modelling the impacts of agricultural management practices on river water quality in Eastern England.

    PubMed

    Taylor, Sam D; He, Yi; Hiscock, Kevin M

    2016-09-15

    Agricultural diffuse water pollution remains a notable global pressure on water quality, posing risks to aquatic ecosystems, human health and water resources and as a result legislation has been introduced in many parts of the world to protect water bodies. Due to their efficiency and cost-effectiveness, water quality models have been increasingly applied to catchments as Decision Support Tools (DSTs) to identify mitigation options that can be introduced to reduce agricultural diffuse water pollution and improve water quality. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the River Wensum catchment in eastern England with the aim of quantifying the long-term impacts of potential changes to agricultural management practices on river water quality. Calibration and validation were successfully performed at a daily time-step against observations of discharge, nitrate and total phosphorus obtained from high-frequency water quality monitoring within the Blackwater sub-catchment, covering an area of 19.6 km(2). A variety of mitigation options were identified and modelled, both singly and in combination, and their long-term effects on nitrate and total phosphorus losses were quantified together with the 95% uncertainty range of model predictions. Results showed that introducing a red clover cover crop to the crop rotation scheme applied within the catchment reduced nitrate losses by 19.6%. Buffer strips of 2 m and 6 m width represented the most effective options to reduce total phosphorus losses, achieving reductions of 12.2% and 16.9%, respectively. This is one of the first studies to quantify the impacts of agricultural mitigation options on long-term water quality for nitrate and total phosphorus at a daily resolution, in addition to providing an estimate of the uncertainties of those impacts. The results highlighted the need to consider multiple pollutants, the degree of uncertainty associated with model predictions and the risk of

  16. The Educational Situation Quality Model: Recent Advances.

    PubMed

    Doménech-Betoret, Fernando

    2018-01-01

    The purpose of this work was to present an educational model developed in recent years entitled the "The Educational Situation Quality Model" (MOCSE, acronym in Spanish). MOCSE can be defined as an instructional model that simultaneously considers the teaching-learning process, where motivation plays a central role. It explains the functioning of an educational setting by organizing and relating the most important variables which, according to the literature, contribute to student learning. Besides being a conceptual framework, this model also provides a methodological procedure to guide research and to promote reflection in the classroom. It allows teachers to implement effective research-action programs to improve teacher-students satisfaction and learning outcomes in the classroom context. This work explains the model's characteristics and functioning, recent advances, and how teachers can use it in an educational setting with a specific subject. This proposal integrates approaches from several relevant psycho-educational theories and introduces a new perspective into the existing literature that will allow researchers to make progress in studying educational setting functioning. The initial MOCSE configuration has been refined over time in accordance with the empirical results obtained from previous research, carried out within the MOCSE framework and with the subsequent reflections that derived from these results. Finally, the contribution of the model to improve learning outcomes and satisfaction, and its applicability in the classroom, are also discussed.

  17. Impact of inherent meteorology uncertainty on air quality model predictions

    EPA Science Inventory

    It is well established that there are a number of different classifications and sources of uncertainties in environmental modeling systems. Air quality models rely on two key inputs, namely, meteorology and emissions. When using air quality models for decision making, it is impor...

  18. Offline modeling for product quality prediction of mineral processing using modeling error PDF shaping and entropy minimization.

    PubMed

    Ding, Jinliang; Chai, Tianyou; Wang, Hong

    2011-03-01

    This paper presents a novel offline modeling for product quality prediction of mineral processing which consists of a number of unit processes in series. The prediction of the product quality of the whole mineral process (i.e., the mixed concentrate grade) plays an important role and the establishment of its predictive model is a key issue for the plantwide optimization. For this purpose, a hybrid modeling approach of the mixed concentrate grade prediction is proposed, which consists of a linear model and a nonlinear model. The least-squares support vector machine is adopted to establish the nonlinear model. The inputs of the predictive model are the performance indices of each unit process, while the output is the mixed concentrate grade. In this paper, the model parameter selection is transformed into the shape control of the probability density function (PDF) of the modeling error. In this context, both the PDF-control-based and minimum-entropy-based model parameter selection approaches are proposed. Indeed, this is the first time that the PDF shape control idea is used to deal with system modeling, where the key idea is to turn model parameters so that either the modeling error PDF is controlled to follow a target PDF or the modeling error entropy is minimized. The experimental results using the real plant data and the comparison of the two approaches are discussed. The results show the effectiveness of the proposed approaches.

  19. Indoor Air Quality Building Education and Assessment Model

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM), released in 2002, is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  20. Identification of water quality degradation hotspots in developing countries by applying large scale water quality modelling

    NASA Astrophysics Data System (ADS)

    Malsy, Marcus; Reder, Klara; Flörke, Martina

    2014-05-01

    Decreasing water quality is one of the main global issues which poses risks to food security, economy, and public health and is consequently crucial for ensuring environmental sustainability. During the last decades access to clean drinking water increased, but 2.5 billion people still do not have access to basic sanitation, especially in Africa and parts of Asia. In this context not only connection to sewage system is of high importance, but also treatment, as an increasing connection rate will lead to higher loadings and therefore higher pressure on water resources. Furthermore, poor people in developing countries use local surface waters for daily activities, e.g. bathing and washing. It is thus clear that water utilization and water sewerage are indispensable connected. In this study, large scale water quality modelling is used to point out hotspots of water pollution to get an insight on potential environmental impacts, in particular, in regions with a low observation density and data gaps in measured water quality parameters. We applied the global water quality model WorldQual to calculate biological oxygen demand (BOD) loadings from point and diffuse sources, as well as in-stream concentrations. Regional focus in this study is on developing countries i.e. Africa, Asia, and South America, as they are most affected by water pollution. Hereby, model runs were conducted for the year 2010 to draw a picture of recent status of surface waters quality and to figure out hotspots and main causes of pollution. First results show that hotspots mainly occur in highly agglomerated regions where population density is high. Large urban areas are initially loading hotspots and pollution prevention and control become increasingly important as point sources are subject to connection rates and treatment levels. Furthermore, river discharge plays a crucial role due to dilution potential, especially in terms of seasonal variability. Highly varying shares of BOD sources across

  1. The Plumbing of Land Surface Models: Is Poor Performance a Result of Methodology or Data Quality?

    NASA Technical Reports Server (NTRS)

    Haughton, Ned; Abramowitz, Gab; Pitman, Andy J.; Or, Dani; Best, Martin J.; Johnson, Helen R.; Balsamo, Gianpaolo; Boone, Aaron; Cuntz, Matthais; Decharme, Bertrand; hide

    2016-01-01

    The PALS Land sUrface Model Benchmarking Evaluation pRoject (PLUMBER) illustrated the value of prescribing a priori performance targets in model intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation. For latent heat flux, all land surface models were outperformed by a regression against downward shortwave, surface air temperature and relative humidity. These results are explored here in greater detail and possible causes are investigated. We examine whether particular metrics or sites unduly influence the collated results, whether results change according to time-scale aggregation and whether a lack of energy conservation in fluxtower data gives the empirical models an unfair advantage in the intercomparison. We demonstrate that energy conservation in the observational data is not responsible for these results. We also show that the partitioning between sensible and latent heat fluxes in LSMs, rather than the calculation of available energy, is the cause of the original findings. Finally, we present evidence suggesting that the nature of this partitioning problem is likely shared among all contributing LSMs. While we do not find a single candidate explanation forwhy land surface models perform poorly relative to empirical benchmarks in PLUMBER, we do exclude multiple possible explanations and provide guidance on where future research should focus.

  2. Ride qualities criteria validation/pilot performance study: Flight test results

    NASA Technical Reports Server (NTRS)

    Nardi, L. U.; Kawana, H. Y.; Greek, D. C.

    1979-01-01

    Pilot performance during a terrain following flight was studied for ride quality criteria validation. Data from manual and automatic terrain following operations conducted during low level penetrations were analyzed to determine the effect of ride qualities on crew performance. The conditions analyzed included varying levels of turbulence, terrain roughness, and mission duration with a ride smoothing system on and off. Limited validation of the B-1 ride quality criteria and some of the first order interactions between ride qualities and pilot/vehicle performance are highlighted. An earlier B-1 flight simulation program correlated well with the flight test results.

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

    NASA Astrophysics Data System (ADS)

    Miralha, L.; Kim, D.

    2017-12-01

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

  4. Southern Phosphorus Indices, Water Quality Data, and Modeling (APEX, APLE, and TBET) Results: A Comparison.

    PubMed

    Osmond, Deanna; Bolster, Carl; Sharpley, Andrew; Cabrera, Miguel; Feagley, Sam; Forsberg, Adam; Mitchell, Charles; Mylavarapu, Rao; Oldham, J Larry; Radcliffe, David E; Ramirez-Avila, John J; Storm, Dan E; Walker, Forbes; Zhang, Hailin

    2017-11-01

    Phosphorus (P) Indices in the southern United States frequently produce different recommendations for similar conditions. We compared risk ratings from 12 southern states (Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, North Carolina, Oklahoma, South Carolina, Tennessee, and Texas) using data collected from benchmark sites in the South (Arkansas, Georgia, Mississippi, North Carolina, Oklahoma, and Texas). Phosphorus Index ratings were developed using both measured erosion losses from each benchmark site and Revised Universal Soil Loss Equation 2 predictions; mostly, there was no difference in P Index outcome. The derived loss ratings were then compared with measured P loads at the benchmark sites by using equivalent USDA-NRCS P Index ratings and three water quality models (Annual P Loss Estimator [APLE], Agricultural Policy Environmental eXtender [APEX], and Texas Best Management Practice Evaluation Tool [TBET]). Phosphorus indices were finally compared against each other using USDA-NRCS loss ratings model estimate correspondence with USDA-NRCS loss ratings. Correspondence was 61% for APEX, 48% for APLE, and 52% for TBET, with overall P index correspondence at 55%. Additive P Indices (Alabama and Texas) had the lowest USDA-NRCS loss rating correspondence (31%), while the multiplicative (Arkansas, Florida, Louisiana, Mississippi, South Carolina, and Tennessee) and component (Georgia, Kentucky, and North Carolina) indices had similar USDA-NRCS loss rating correspondence-60 and 64%, respectively. Analysis using Kendall's modified Tau suggested that correlations between measured and calculated P-loss ratings were similar or better for most P Indices than the models. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  5. ONE-ATMOSPHERE DYNAMICS DESCRIPTION IN THE MODELS-3 COMMUNITY MULTI-SCALE QUALITY (CMAQ) MODELING SYSTEM

    EPA Science Inventory

    This paper proposes a general procedure to link meteorological data with air quality models, such as U.S. EPA's Models-3 Community Multi-scale Air Quality (CMAQ) modeling system. CMAQ is intended to be used for studying multi-scale (urban and regional) and multi-pollutant (ozon...

  6. Analysis of information quality attribute for SME towards adoption of research result

    NASA Astrophysics Data System (ADS)

    Febriani, E.; Dewobroto, W. S.; Anggraini, R. D.

    2017-12-01

    Small and Medium Enterprises (SME) holds significant role in fostering Indonesian economy. However, the research that is supposed to support the development of SMEs business has not yet fully adopted or utilized. Information attributes may be used as the benchmark to find the intention of SMEs from a research result and develop the strategy of quality information for all organizations both SMEs and the researcher. Therefore, because of the importance of information quality attribute required by SMEs, the research aims to analyses the information quality required by SMEs to clarify the information quality into the dimension of information quality. The research was started by distributing online questionnaire to SMEs. The questionnaire result showed that the content dimension is the most aspect required by SMEs, followed by time and form dimension, respectively. Quality information attribute required by SMEs from a research is that the result may be applied to the business.

  7. Modeling the Complex Photochemistry of Biomass Burning Plumes in Plume-Scale, Regional, and Global Air Quality Models

    NASA Astrophysics Data System (ADS)

    Alvarado, M. J.; Lonsdale, C. R.; Yokelson, R. J.; Travis, K.; Fischer, E. V.; Lin, J. C.

    2014-12-01

    Forecasting the impacts of biomass burning (BB) plumes on air quality is difficult due to the complex photochemistry that takes place in the concentrated young BB plumes. The spatial grid of global and regional scale Eulerian models is generally too large to resolve BB photochemistry, which can lead to errors in predicting the formation of secondary organic aerosol (SOA) and O3, as well as the partitioning of NOyspecies. AER's Aerosol Simulation Program (ASP v2.1) can be used within plume-scale Lagrangian models to simulate this complex photochemistry. We will present results of validation studies of the ASP model against aircraft observations of young BB smoke plumes. We will also present initial results from the coupling of ASP v2.1 into the Lagrangian particle dispersion model STILT-Chem in order to better examine the interactions between BB plume chemistry and dispersion. In addition, we have used ASP to develop a sub-grid scale parameterization of the near-source chemistry of BB plumes for use in regional and global air quality models. The parameterization takes inputs from the host model, such as solar zenith angle, temperature, and fire fuel type, and calculates enhancement ratios of O3, NOx, PAN, aerosol nitrate, and other NOy species, as well as organic aerosol (OA). We will present results from the ASP-based BB parameterization as well as its implementation into the global atmospheric composition model GEOS-Chem for the SEAC4RS campaign.

  8. A multi-model assessment of the co-benefits of climate mitigation for global air quality

    NASA Astrophysics Data System (ADS)

    Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana; Riahi, Keywan; van Dingenen, Rita; Aleluia Reis, Lara; Calvin, Katherine; Dentener, Frank; Drouet, Laurent; Fujimori, Shinichiro; Harmsen, Mathijs; Luderer, Gunnar; Heyes, Chris; Strefler, Jessica; Tavoni, Massimo; van Vuuren, Detlef P.

    2016-12-01

    We present a model comparison study that combines multiple integrated assessment models with a reduced-form global air quality model to assess the potential co-benefits of global climate mitigation policies in relation to the World Health Organization (WHO) goals on air quality and health. We include in our assessment, a range of alternative assumptions on the implementation of current and planned pollution control policies. The resulting air pollution emission ranges significantly extend those in the Representative Concentration Pathways. Climate mitigation policies complement current efforts on air pollution control through technology and fuel transformations in the energy system. A combination of stringent policies on air pollution control and climate change mitigation results in 40% of the global population exposed to PM levels below the WHO air quality guideline; with the largest improvements estimated for India, China, and Middle East. Our results stress the importance of integrated multisector policy approaches to achieve the Sustainable Development Goals.

  9. Integrating biomass quality variability in stochastic supply chain modeling and optimization for large-scale biofuel production

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

    Castillo-Villar, Krystel K.; Eksioglu, Sandra; Taherkhorsandi, Milad

    The production of biofuels using second-generation feedstocks has been recognized as an important alternative source of sustainable energy and its demand is expected to increase due to regulations such as the Renewable Fuel Standard. However, the pathway to biofuel industry maturity faces unique, unaddressed challenges. Here, to address this challenges, this article presents an optimization model which quantifies and controls the impact of biomass quality variability on supply chain related decisions and technology selection. We propose a two-stage stochastic programming model and associated efficient solution procedures for solving large-scale problems to (1) better represent the random nature of the biomassmore » quality (defined by moisture and ash contents) in supply chain modeling, and (2) assess the impact of these uncertainties on the supply chain design and planning. The proposed model is then applied to a case study in the state of Tennessee. Results show that high moisture and ash contents negatively impact the unit delivery cost since poor biomass quality requires the addition of quality control activities. Experimental results indicate that supply chain cost could increase as much as 27%–31% when biomass quality is poor. We assess the impact of the biomass quality on the topological supply chain. Our case study indicates that biomass quality impacts supply chain costs; thus, it is important to consider the impact of biomass quality in supply chain design and management decisions.« less

  10. Integrating biomass quality variability in stochastic supply chain modeling and optimization for large-scale biofuel production

    DOE PAGES

    Castillo-Villar, Krystel K.; Eksioglu, Sandra; Taherkhorsandi, Milad

    2017-02-20

    The production of biofuels using second-generation feedstocks has been recognized as an important alternative source of sustainable energy and its demand is expected to increase due to regulations such as the Renewable Fuel Standard. However, the pathway to biofuel industry maturity faces unique, unaddressed challenges. Here, to address this challenges, this article presents an optimization model which quantifies and controls the impact of biomass quality variability on supply chain related decisions and technology selection. We propose a two-stage stochastic programming model and associated efficient solution procedures for solving large-scale problems to (1) better represent the random nature of the biomassmore » quality (defined by moisture and ash contents) in supply chain modeling, and (2) assess the impact of these uncertainties on the supply chain design and planning. The proposed model is then applied to a case study in the state of Tennessee. Results show that high moisture and ash contents negatively impact the unit delivery cost since poor biomass quality requires the addition of quality control activities. Experimental results indicate that supply chain cost could increase as much as 27%–31% when biomass quality is poor. We assess the impact of the biomass quality on the topological supply chain. Our case study indicates that biomass quality impacts supply chain costs; thus, it is important to consider the impact of biomass quality in supply chain design and management decisions.« less

  11. Coastal Water Quality Modeling in Tidal Lake: Revisited with Groundwater Intrusion

    NASA Astrophysics Data System (ADS)

    Kim, C.

    2016-12-01

    A new method for predicting the temporal and spatial variation of water quality, with accounting for a groundwater effect, has been proposed and applied to a water body partially connected to macro-tidal coastal waters in Korea. The method consists of direct measurement of environmental parameters, and it indirectly incorporates a nutrients budget analysis to estimate the submarine groundwater fluxes. Three-dimensional numerical modeling of water quality has been used with the directly collected data and the indirectly estimated groundwater fluxes. The applied area is Saemangeum tidal lake that is enclosed by 33km-long sea dyke with tidal openings at two water gates. Many investigations of groundwater impact reveal that 10 50% of nutrient loading in coastal waters comes from submarine groundwater, particularly in the macro-tidal flat, as in the west coast of Korea. Long-term monitoring of coastal water quality signals the possibility of groundwater influence on salinity reversal and on the excess mass outbalancing the normal budget in Saemangeum tidal lake. In the present study, we analyze the observed data to examine the influence of submarine groundwater, and then a box model is demonstrated for quantifying the influx and efflux. A three-dimensional numerical model has been applied to reproduce the process of groundwater dispersal and its effect on the water quality of Saemangeum tidal lake. The results show that groundwater influx during the summer monsoon then contributes significantly, 20% more than during dry season, to water quality in the tidal lake.

  12. Designing Excellence and Quality Model for Training Centers of Primary Health Care: A Delphi Method Study.

    PubMed

    Tabrizi, Jafar-Sadegh; Farahbakhsh, Mostafa; Shahgoli, Javad; Rahbar, Mohammad Reza; Naghavi-Behzad, Mohammad; Ahadi, Hamid-Reza; Azami-Aghdash, Saber

    2015-10-01

    Excellence and quality models are comprehensive methods for improving the quality of healthcare. The aim of this study was to design excellence and quality model for training centers of primary health care using Delphi method. In this study, Delphi method was used. First, comprehensive information were collected using literature review. In extracted references, 39 models were identified from 34 countries and related sub-criteria and standards were extracted from 34 models (from primary 39 models). Then primary pattern including 8 criteria, 55 sub-criteria, and 236 standards was developed as a Delphi questionnaire and evaluated in four stages by 9 specialists of health care system in Tabriz and 50 specialists from all around the country. Designed primary model (8 criteria, 55 sub-criteria, and 236 standards) were concluded with 8 criteria, 45 sub-criteria, and 192 standards after 4 stages of evaluations by specialists. Major criteria of the model are leadership, strategic and operational planning, resource management, information analysis, human resources management, process management, costumer results, and functional results, where the top score was assigned as 1000 by specialists. Functional results had the maximum score of 195 whereas planning had the minimum score of 60. Furthermore the most and the least sub-criteria was for leadership with 10 sub-criteria and strategic planning with 3 sub-criteria, respectively. The model that introduced in this research has been designed following 34 reference models of the world. This model could provide a proper frame for managers of health system in improving quality.

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

    PubMed

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

    2014-06-01

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

  14. EVALUATING AND USING AIR QUALITY MODELS

    EPA Science Inventory

    Grid-based models are being used to assess the magnitude of the pollution problem and to design emission control strategies to achieve compliance with the relevant air quality standards in the United States.

  15. Spatial Allocator for air quality modeling

    EPA Pesticide Factsheets

    The Spatial Allocator is a set of tools that helps users manipulate and generate data files related to emissions and air quality modeling without requiring the use of a commercial Geographic Information System.

  16. Modelling of beef sensory quality for a better prediction of palatability.

    PubMed

    Hocquette, Jean-François; Van Wezemael, Lynn; Chriki, Sghaier; Legrand, Isabelle; Verbeke, Wim; Farmer, Linda; Scollan, Nigel D; Polkinghorne, Rod; Rødbotten, Rune; Allen, Paul; Pethick, David W

    2014-07-01

    Despite efforts by the industry to control the eating quality of beef, there remains a high level of variability in palatability, which is one reason for consumer dissatisfaction. In Europe, there is still no reliable on-line tool to predict beef quality and deliver consistent quality beef to consumers. Beef quality traits depend in part on the physical and chemical properties of the muscles. The determination of these properties (known as muscle profiling) will allow for more informed decisions to be made in the selection of individual muscles for the production of value-added products. Therefore, scientists and professional partners of the ProSafeBeef project have brought together all the data they have accumulated over 20 years. The resulting BIF-Beef (Integrated and Functional Biology of Beef) data warehouse contains available data of animal growth, carcass composition, muscle tissue characteristics and beef quality traits. This database is useful to determine the most important muscle characteristics associated with a high tenderness, a high flavour or generally a high quality. Another more consumer driven modelling tool was developed in Australia: the Meat Standards Australia (MSA) grading scheme that predicts beef quality for each individual muscle×specific cooking method combination using various information on the corresponding animals and post-slaughter processing factors. This system has also the potential to detect variability in quality within muscles. The MSA system proved to be effective in predicting beef palatability not only in Australia but also in many other countries. The results of the work conducted in Europe within the ProSafeBeef project indicate that it would be possible to manage a grading system in Europe similar to the MSA system. The combination of the different modelling approaches (namely muscle biochemistry and a MSA-like meat grading system adapted to the European market) is a promising area of research to improve the prediction

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

    PubMed

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

    2017-08-01

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

  18. Impact of influent data frequency and model structure on the quality of WWTP model calibration and uncertainty.

    PubMed

    Cierkens, Katrijn; Plano, Salvatore; Benedetti, Lorenzo; Weijers, Stefan; de Jonge, Jarno; Nopens, Ingmar

    2012-01-01

    Application of activated sludge models (ASMs) to full-scale wastewater treatment plants (WWTPs) is still hampered by the problem of model calibration of these over-parameterised models. This either requires expert knowledge or global methods that explore a large parameter space. However, a better balance in structure between the submodels (ASM, hydraulic, aeration, etc.) and improved quality of influent data result in much smaller calibration efforts. In this contribution, a methodology is proposed that links data frequency and model structure to calibration quality and output uncertainty. It is composed of defining the model structure, the input data, an automated calibration, confidence interval computation and uncertainty propagation to the model output. Apart from the last step, the methodology is applied to an existing WWTP using three models differing only in the aeration submodel. A sensitivity analysis was performed on all models, allowing the ranking of the most important parameters to select in the subsequent calibration step. The aeration submodel proved very important to get good NH(4) predictions. Finally, the impact of data frequency was explored. Lowering the frequency resulted in larger deviations of parameter estimates from their default values and larger confidence intervals. Autocorrelation due to high frequency calibration data has an opposite effect on the confidence intervals. The proposed methodology opens doors to facilitate and improve calibration efforts and to design measurement campaigns.

  19. Meteorological Processes Affecting Air Quality – Research and Model Development Needs

    EPA Science Inventory

    Meteorology modeling is an important component of air quality modeling systems that defines the physical and dynamical environment for atmospheric chemistry. The meteorology models used for air quality applications are based on numerical weather prediction models that were devel...

  20. Fuzzy intelligent quality monitoring model for X-ray image processing.

    PubMed

    Khalatbari, Azadeh; Jenab, Kouroush

    2009-01-01

    Today's imaging diagnosis needs to adapt modern techniques of quality engineering to maintain and improve its accuracy and reliability in health care system. One of the main factors that influences diagnostic accuracy of plain film X-ray on detecting pathology is the level of film exposure. If the level of film exposure is not adequate, a normal body structure may be interpretated as pathology and vice versa. This not only influences the patient management but also has an impact on health care cost and patient's quality of life. Therefore, providing an accurate and high quality image is the first step toward an excellent patient management in any health care system. In this paper, we study these techniques and also present a fuzzy intelligent quality monitoring model, which can be used to keep variables from degrading the image quality. The variables derived from chemical activity, cleaning procedures, maintenance, and monitoring may not be sensed, measured, or calculated precisely due to uncertain situations. Therefore, the gamma-level fuzzy Bayesian model for quality monitoring of an image processing is proposed. In order to apply the Bayesian concept, the fuzzy quality characteristics are assumed as fuzzy random variables. Using the fuzzy quality characteristics, the newly developed model calculates the degradation risk for image processing. A numerical example is also presented to demonstrate the application of the model.

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

    EPA Science Inventory

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

  2. 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.

  3. 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…

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  6. [Structural Equation Modeling of Quality of Work Life in Clinical Nurses based on the Culture-Work-Health Model].

    PubMed

    Kim, Miji; Ryu, Eunjung

    2015-12-01

    The purpose of this study was to construct and test a structural equation model of quality of work life for clinical nurses based on Peterson and Wilson's Culture-Work-Health model (CWHM). A structured questionnaire was completed by 523 clinical nurses to analyze the relationships between concepts of CWHM-organizational culture, social support, employee health, organizational health, and quality of work life. Among these conceptual variables of CWHM, employee health was measured by perceived health status, and organizational health was measured by presenteeism. SPSS21.0 and AMOS 21.0 programs were used to analyze the efficiency of the hypothesized model and calculate the direct and indirect effects of factors affecting quality of work life among clinical nurses. The goodness-of-fit statistics of the final modified hypothetical model are as follows: χ²=586.03, χ²/df=4.19, GFI=.89, AGFI=.85, CFI=.91, TLI=.90, NFI=.89, and RMSEA=.08. The results revealed that organizational culture, social support, organizational health, and employee health accounted for 69% of clinical nurses' quality of work life. The major findings of this study indicate that it is essential to create a positive organizational culture and provide adequate organizational support to maintain a balance between the health of clinical nurses and the organization. Further repeated and expanded studies are needed to explore the multidimensional aspects of clinical nurses' quality of work life in Korea, including various factors, such as work environment, work stress, and burnout.

  7. Optimum profit model considering production, quality and sale problem

    NASA Astrophysics Data System (ADS)

    Chen, Chung-Ho; Lu, Chih-Lun

    2011-12-01

    Chen and Liu ['Procurement Strategies in the Presence of the Spot Market-an Analytical Framework', Production Planning and Control, 18, 297-309] presented the optimum profit model between the producers and the purchasers for the supply chain system with a pure procurement policy. However, their model with a simple manufacturing cost did not consider the used cost of the customer. In this study, the modified Chen and Liu's model will be addressed for determining the optimum product and process parameters. The authors propose a modified Chen and Liu's model under the two-stage screening procedure. The surrogate variable having a high correlation with the measurable quality characteristic will be directly measured in the first stage. The measurable quality characteristic will be directly measured in the second stage when the product decision cannot be determined in the first stage. The used cost of the customer will be measured by adopting Taguchi's quadratic quality loss function. The optimum purchaser's order quantity, the producer's product price and the process quality level will be jointly determined by maximising the expected profit between them.

  8. THE EMERGENCE OF NUMERICAL AIR QUALITY FORECASTING MODELS AND THEIR APPLICATION

    EPA Science Inventory

    In recent years the U.S. and other nations have begun programs for short-term local through regional air quality forecasting based upon numerical three-dimensional air quality grid models. These numerical air quality forecast (NAQF) models and systems have been developed and test...

  9. THE EMERGENCE OF NUMERICAL AIR QUALITY FORCASTING MODELS AND THEIR APPLICATIONS

    EPA Science Inventory

    In recent years the U.S. and other nations have begun programs for short-term local through regional air quality forecasting based upon numerical three-dimensional air quality grid models. These numerical air quality forecast (NAQF) models and systems have been developed and test...

  10. Using climate models to estimate the quality of global observational data sets.

    PubMed

    Massonnet, François; Bellprat, Omar; Guemas, Virginie; Doblas-Reyes, Francisco J

    2016-10-28

    Observational estimates of the climate system are essential to monitoring and understanding ongoing climate change and to assessing the quality of climate models used to produce near- and long-term climate information. This study poses the dual and unconventional question: Can climate models be used to assess the quality of observational references? We show that this question not only rests on solid theoretical grounds but also offers insightful applications in practice. By comparing four observational products of sea surface temperature with a large multimodel climate forecast ensemble, we find compelling evidence that models systematically score better against the most recent, advanced, but also most independent product. These results call for generalized procedures of model-observation comparison and provide guidance for a more objective observational data set selection. Copyright © 2016, American Association for the Advancement of Science.

  11. 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.

  12. The choices, choosing model of quality of life: description and rationale.

    PubMed

    Gurland, Barry J; Gurland, Roni V

    2009-01-01

    This introductory paper offers a critical review of current models and measures of quality of life, and describes a choices and choosing (c-c) process as a new model of quality of life. Criteria are proposed for judging the relative merits of models of quality of life with preference being given to explicit mechanisms, linkages to a science base, a means of identifying deficits amenable to rational restorative interventions, and with embedded values of the whole person. A conjectured model, based on the processes of gaining access to choices and choosing among them, matches the proposed criteria. The c-c process is an evolved adaptive mechanism dedicated to the pursuit of quality of life, driven by specific biological and psychological systems, and influenced by social and environmental forces. This model strengthens the science base for the field of quality of life, unifies approaches to concept and measurement, and guides the evaluation of impairments of quality of life. Corresponding interventions can be aimed at relieving restrictions or distortions of the c-c process; thus helping people to preserve and improve their quality of life. RELATED WORK: Companion papers detail relevant aspects of the science base, present methods of identifying deficits and distortions of the c-c model so as to open opportunities for rational restorative interventions, and explore empirical analyses of the relationship between health imposed restrictions of c-c and conventional indicators of diminished quality of life. [corrected] (c) 2008 John Wiley & Sons, Ltd.

  13. Development and application of air quality models at the US ...

    EPA Pesticide Factsheets

    Overview of the development and application of air quality models at the U.S. EPA, particularly focused on the development and application of the Community Multiscale Air Quality (CMAQ) model developed within the Computation Exposure Division (CED) of the National Exposure Research Laboratory (NERL). This presentation will provide a simple overview of air quality model development and application geared toward a non-technical student audience. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

  14. Assessment of surgical discharge summaries and evaluation of a new quality improvement model.

    PubMed

    Stein, Ran; Neufeld, David; Shwartz, Ivan; Erez, Ilan; Haas, Ilana; Magen, Ada; Glassberg, Elon; Shmulevsky, Pavel; Paran, Haim

    2014-11-01

    Discharge summaries after hospitalization provide the most reliable description and implications of the hospitalization. A concise discharge summary is crucial for maintaining continuity of care through the transition from inpatient to ambulatory care. Discharge summaries often lack information and are imprecise. Errors and insufficient recommendations regarding changes in the medical regimen may harm the patient's health and may result in readmission. To evaluate a quality improvement model and training program for writing postoperative discharge summaries for three surgical procedures. Medical records and surgical discharge summaries were reviewed and scored. Essential points for communication between surgeons and family physicians were included in automated forms. Staff was briefed twice regarding required summary contents with an interim evaluation. Changes in quality were evaluated. Summaries from 61 cholecystectomies, 42 hernioplasties and 45 colectomies were reviewed. The average quality score of all discharge summaries increased from 72.1 to 78.3 after the first intervention (P < 0.0005) to 81.0 following the second intervention. As the discharge summary's quality improved, its length decreased significantly. Discharge summaries lack important information and are too long. Developing a model for discharge summaries and instructing surgical staff regarding their contents resulted in measurable improvement. Frequent interventions and supervision are needed to maintain the quality of the surgical discharge summary.

  15. Improved protein model quality assessments by changing the target function.

    PubMed

    Uziela, Karolis; Menéndez Hurtado, David; Shu, Nanjiang; Wallner, Björn; Elofsson, Arne

    2018-06-01

    Protein modeling quality is an important part of protein structure prediction. We have for more than a decade developed a set of methods for this problem. We have used various types of description of the protein and different machine learning methodologies. However, common to all these methods has been the target function used for training. The target function in ProQ describes the local quality of a residue in a protein model. In all versions of ProQ the target function has been the S-score. However, other quality estimation functions also exist, which can be divided into superposition- and contact-based methods. The superposition-based methods, such as S-score, are based on a rigid body superposition of a protein model and the native structure, while the contact-based methods compare the local environment of each residue. Here, we examine the effects of retraining our latest predictor, ProQ3D, using identical inputs but different target functions. We find that the contact-based methods are easier to predict and that predictors trained on these measures provide some advantages when it comes to identifying the best model. One possible reason for this is that contact based methods are better at estimating the quality of multi-domain targets. However, training on the S-score gives the best correlation with the GDT_TS score, which is commonly used in CASP to score the global model quality. To take the advantage of both of these features we provide an updated version of ProQ3D that predicts local and global model quality estimates based on different quality estimates. © 2018 Wiley Periodicals, Inc.

  16. Prediction of Groundwater Quality Trends Resulting from Anthropogenic Changes in Southeast Florida.

    PubMed

    Yi, Quanghee; Stewart, Mark

    2018-01-01

    The effects of surface water flow system changes caused by constructing water-conservation areas and canals in southeast Florida on groundwater quality under the Atlantic Coastal Ridge was investigated with numerical modeling. Water quality data were used to delineate a zone of groundwater with low total dissolved solids (TDS) within the Biscayne aquifer under the ridge. The delineated zone has the following characteristics. Its location generally coincides with an area where the Biscayne aquifer has high transmissivities, corresponds to a high recharge area of the ridge, and underlies a part of the groundwater mound formed under the ridge prior to completion of the canals. This low TDS groundwater appears to be the result of pre-development conditions rather than seepage from the canals constructed after the 1950s. Numerical simulation results indicate that the time for low TDS groundwater under the ridge to reach equilibrium with high TDS surface water in the water-conservation areas and Everglades National Park are approximately 70 and 60 years, respectively. The high TDS groundwater would be restricted to the water-conservation areas and the park due to its slow eastward movement caused by small hydraulic gradients in Rocky Glades and its mixing with the low TDS groundwater under the high-recharge area of the ridge. The flow or physical boundary conditions such as high recharge rates or low hydraulic conductivity layers may affect how the spatial distribution of groundwater quality in an aquifer will change when a groundwater flow system reaches equilibrium with an associated surface water flow system. © 2017, National Ground Water Association.

  17. Air quality modeling for effective environmental management in the mining region.

    PubMed

    Asif, Zunaira; Chen, Zhi; Han, Yi

    2018-04-18

    Air quality in the mining sector is a serious environmental concern and associated with many health issues. The air quality management in mining region has been facing many challenges due to lack of understanding of atmospheric factors and physical removal mechanism. A modeling approach called mining air dispersion model (MADM) is developed to predict air pollutants concentration in the mining region while considering the deposition effect. The model is taken into account through the planet's boundary conditions and assuming that the eddy diffusivity depends on the downwind distance. The developed MADM is applied to a mining site in Canada. The model provides values as the predicted concentrations of PM 10 , PM 2.5 , TSP, NO 2 and six heavy metals (As, Pb, Hg, Cd, Zn, Cr) at various receptor locations. The model shows that neutral stability conditions are dominant for the study site. The maximum mixing height is achieved (1280 m) during the evening of summer, and minimum mixing height (380 m) is attained during the evening of winter. The dust fall (PM coarse) deposition flux is maximum during February and March with the deposition velocity of 4.67 cm/s. The results are evaluated with the monitoring field values, revealing a good agreement for the target air pollutants with R-squared ranging from 0.72 to 0.96 for PM 2.5 ; 0.71 to 0.82 for PM 10 and from 0.71 to 0.89 for NO 2 . The analyses illustrate that presented algorithm in this model can be used to assess air quality for the mining site in a systematic way. The comparison of MADM and CALPUFF modeling values are made for four different pollutants (PM 2.5 , PM 10 , TSP, and NO 2 ) under three different atmospheric stability classes (stable, neutral and unstable). Further, MADM results are statistically tested against CALPUFF for the air pollutants and model performance is found satisfactory.

  18. 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.

  19. Quality assurance of weather data for agricultural system model input

    USDA-ARS?s Scientific Manuscript database

    It is well known that crop production and hydrologic variation on watersheds is weather related. Rarely, however, is meteorological data quality checks reported for agricultural systems model research. We present quality assurance procedures for agricultural system model weather data input. Problems...

  20. MODELED MESOSCALE METEOROLOGICAL FIELDS WITH FOUR-DIMENSIONAL DATA ASSIMILATION IN REGIONAL SCALE AIR QUALITY MODELS

    EPA Science Inventory

    This paper addresses the need to increase the temporal and spatial resolution of meteorological data currently used in air quality simulation models, AQSMs. ransport and diffusion parameters including mixing heights and stability used in regulatory air quality dispersion models a...

  1. ROLE OF MODELS IN AIR QUALITY MANAGEMENT DECISIONS

    EPA Science Inventory

    Within the frame of the US-India bilateral agreement on environmental cooperation, a team of US scientists have been helping India in designing emission control policies to address urban air quality problems. This presentation discusses how air quality models need to be used for ...

  2. ENHANCED STREAM WATER QUALITY MODEL (QUAL2EU)

    EPA Science Inventory

    The enhanced stream water quality model QUAL2E and QUAL2E-UNCAS (37) permits simulation of several water quality constituents in a branching stream system using a finite difference solution to the one-dimensional advective-dispersive mass transport and reaction equation. The con...

  3. First results from the International Urban Energy Balance Model Comparison: Model Complexity

    NASA Astrophysics Data System (ADS)

    Blackett, M.; Grimmond, S.; Best, M.

    2009-04-01

    A great variety of urban energy balance models has been developed. These vary in complexity from simple schemes that represent the city as a slab, through those which model various facets (i.e. road, walls and roof) to more complex urban forms (including street canyons with intersections) and features (such as vegetation cover and anthropogenic heat fluxes). Some schemes also incorporate detailed representations of momentum and energy fluxes distributed throughout various layers of the urban canopy layer. The models each differ in the parameters they require to describe the site and the in demands they make on computational processing power. Many of these models have been evaluated using observational datasets but to date, no controlled comparisons have been conducted. Urban surface energy balance models provide a means to predict the energy exchange processes which influence factors such as urban temperature, humidity, atmospheric stability and winds. These all need to be modelled accurately to capture features such as the urban heat island effect and to provide key information for dispersion and air quality modelling. A comparison of the various models available will assist in improving current and future models and will assist in formulating research priorities for future observational campaigns within urban areas. In this presentation we will summarise the initial results of this international urban energy balance model comparison. In particular, the relative performance of the models involved will be compared based on their degree of complexity. These results will inform us on ways in which we can improve the modelling of air quality within, and climate impacts of, global megacities. The methodology employed in conducting this comparison followed that used in PILPS (the Project for Intercomparison of Land-Surface Parameterization Schemes) which is also endorsed by the GEWEX Global Land Atmosphere System Study (GLASS) panel. In all cases, models were run

  4. Advanced Water Quality Modelling in Marine Systems: Application to the Wadden Sea, the Netherlands

    NASA Astrophysics Data System (ADS)

    Boon, J.; Smits, J. G.

    2006-12-01

    There is an increasing demand for knowledge and models that arise from water management in relation to water quality, sediment quality (ecology) and sediment accumulation (ecomorphology). Recently, models for sediment diagenesis and erosion developed or incorporated by Delft Hydraulics integrates the relevant physical, (bio)chemical and biological processes for the sediment-water exchange of substances. The aim of the diagenesis models is the prediction of both sediment quality and the return fluxes of substances such as nutrients and micropollutants to the overlying water. The resulting so-called DELWAQ-G model is a new, generic version of the water and sediment quality model of the DELFT3D framework. One set of generic water quality process formulations is used to calculate process rates in both water and sediment compartments. DELWAQ-G involves the explicit simulation of sediment layers in the water quality model with state-of-the-art process kinetics. The local conditions in a water layer or sediment layer such as the dissolved oxygen concentration determine if and how individual processes come to expression. New processes were added for sulphate, sulphide, methane and the distribution of the electron-acceptor demand over dissolved oxygen, nitrate, sulphate and carbon dioxide. DELWAQ-G also includes the dispersive and advective transport processes in the sediment and across the sediment-water interface. DELWAQ-G has been applied for the Wadden Sea. A very dynamic tidal and ecologically active estuary with a complex hydrodynamic behaviour located at the north of the Netherlands. The predicted profiles in the sediment reflect the typical interactions of diagenesis processes.

  5. Quality control of 3D Geological Models using an Attention Model based on Gaze

    NASA Astrophysics Data System (ADS)

    Busschers, Freek S.; van Maanen, Peter-Paul; Brouwer, Anne-Marie

    2014-05-01

    The Geological Survey of the Netherlands (GSN) produces 3D stochastic geological models of the upper 50 meters of the Dutch subsurface. The voxel models are regarded essential in answering subsurface questions on, for example, aggregate resources, groundwater flow, land subsidence studies and the planning of large-scale infrastructural works such as tunnels. GeoTOP is the most recent and detailed generation of 3D voxel models. This model describes 3D lithological variability up to a depth of 50 m using voxels of 100*100*0.5m. Due to the expected increase in data-flow, model output and user demands, the development of (semi-)automated quality control systems is getting more important in the near future. Besides numerical control systems, capturing model errors as seen from the expert geologist viewpoint is of increasing interest. We envision the use of eye gaze to support and speed up detection of errors in the geological voxel models. As a first step in this direction we explore gaze behavior of 12 geological experts from the GSN during quality control of part of the GeoTOP 3D geological model using an eye-tracker. Gaze is used as input of an attention model that results in 'attended areas' for each individual examined image of the GeoTOP model and each individual expert. We compared these attended areas to errors as marked by the experts using a mouse. Results show that: 1) attended areas as determined from experts' gaze data largely match with GeoTOP errors as indicated by the experts using a mouse, and 2) a substantial part of the match can be reached using only gaze data from the first few seconds of the time geologists spend to search for errors. These results open up the possibility of faster GeoTOP model control using gaze if geologists accept a small decrease of error detection accuracy. Attention data may also be used to make independent comparisons between different geologists varying in focus and expertise. This would facilitate a more effective use of

  6. 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.

  7. Integrating microbial physiology and enzyme traits in the quality model

    NASA Astrophysics Data System (ADS)

    Sainte-Marie, Julien; Barrandon, Matthieu; Martin, Francis; Saint-André, Laurent; Derrien, Delphine

    2017-04-01

    Microbe activity plays an undisputable role in soil carbon storage and there have been many calls to integrate microbial ecology in soil carbon (C) models. With regard to this challenge, a few trait-based microbial models of C dynamics have emerged during the past decade. They parameterize specific traits related to decomposer physiology (substrate use efficiency, growth and mortality rates...) and enzyme properties (enzyme production rate, catalytic properties of enzymes…). But these models are built on the premise that organic matter (OM) can be represented as one single entity or are divided into a few pools, while organic matter exists as a continuum of many different compounds spanning from intact plant molecules to highly oxidised microbial metabolites. In addition, a given molecule may also exist in different forms, depending on its stage of polymerization or on its interactions with other organic compounds or mineral phases of the soil. Here we develop a general theoretical model relating the evolution of soil organic matter, as a continuum of progressively decomposing compounds, with decomposer activity and enzyme traits. The model is based on the notion of quality developed by Agren and Bosatta (1998), which is a measure of molecule accessibility to degradation. The model integrates three major processes: OM depolymerisation by enzyme action, OM assimilation and OM biotransformation. For any enzyme, the model reports the quality range where this enzyme selectively operates and how the initial quality distribution of the OM subset evolves into another distribution of qualities under the enzyme action. The model also defines the quality range where the OM can be uptaken and assimilated by microbes. It finally describes how the quality of the assimilated molecules is transformed into another quality distribution, corresponding to the decomposer metabolites signature. Upon decomposer death, these metabolites return to the substrate. We explore here the how

  8. The Total Quality Management Model Department of Personnel State of Colorado,

    DTIC Science & Technology

    A panel of three members will present the Total Quality Management model recently designed for the Department of Personnel, State of Colorado. This model was selected to increase work quality and productivity of the Department and to exemplify Governor Romer’s commitment to quality work within state government.

  9. 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

  10. A software quality model and metrics for risk assessment

    NASA Technical Reports Server (NTRS)

    Hyatt, L.; Rosenberg, L.

    1996-01-01

    A software quality model and its associated attributes are defined and used as the model for the basis for a discussion on risk. Specific quality goals and attributes are selected based on their importance to a software development project and their ability to be quantified. Risks that can be determined by the model's metrics are identified. A core set of metrics relating to the software development process and its products is defined. Measurements for each metric and their usability and applicability are discussed.

  11. Improving the geomagnetic field modeling with a selection of high-quality archaeointensity data

    NASA Astrophysics Data System (ADS)

    Pavon-Carrasco, Francisco Javier; Gomez-Paccard, Miriam; Herve, Gwenael; Osete, Maria Luisa; Chauvin, Annick

    2014-05-01

    Geomagnetic field reconstructions for the last millennia are based on archeomagnetic data. However, the scatter of the archaeointensity data is very puzzling and clearly suggests that some of the intensity data might not be reliable. In this work we apply different selection criteria to the European and Western Asian archaeointensity data covering the last three millennia in order to investigate if the data selection affects geomagnetic field models results. Thanks to the recently developed archeomagnetic databases, new valuable information related to the methodology used to determine the archeointensity data is now available. We therefore used this information to rank the archaeointensity data in four quality categories depending on the methodology used during the laboratory treatment of the samples and on the number of specimens retained to calculate the mean intensities. Results show how the intensity geomagnetic field component given by the regional models hardly depends on the selected quality data used. When all the available data are used a different behavior of the geomagnetic field is observed in Western and Eastern Europe. However, when the regional model is obtained from a selection of high-quality intensity data the same features are observed at the European scale.

  12. Assessment of the Quality Management Models in Higher Education

    ERIC Educational Resources Information Center

    Basar, Gulsun; Altinay, Zehra; Dagli, Gokmen; Altinay, Fahriye

    2016-01-01

    This study involves the assessment of the quality management models in Higher Education by explaining the importance of quality in higher education and by examining the higher education quality assurance system practices in other countries. The qualitative study was carried out with the members of the Higher Education Planning, Evaluation,…

  13. Quality index of radiological devices: results of one year of use.

    PubMed

    Tofani, Alessandro; Imbordino, Patrizia; Lecci, Antonio; Bonannini, Claudia; Del Corona, Alberto; Pizzi, Stefano

    2003-01-01

    The physical quality index (QI) of radiological devices summarises in a single numerical value between 0 and 1 the results of constancy tests. The aim of this paper is to illustrate the results of the use of such an index on all public radiological devices in the Livorno province over one year. The quality index was calculated for 82 radiological devices of a wide range of types by implementing its algorithm in a spreadsheet-based software for the automatic handling of quality control data. The distribution of quality index values was computed together with the associated statistical quantities. This distribution is strongly asymmetrical, with a sharp peak near the highest QI values. The mean quality index values for the different types of device show some inhomogeneity: in particular, mammography and panoramic dental radiography devices show far lower quality than other devices. In addition, our analysis has identified the parameters that most frequently do not pass the quality tests for each type of device. Finally, we sought some correlation between quality and age of the device, but this was poorly significant. The quality index proved to be a useful tool providing an overview of the physical conditions of radiological devices. By selecting adequate QI threshold values for, it also helps to decide whether a given device should be upgraded or replaced. The identification of critical parameters for each type of device may be used to improve the definition of the QI by attributing greater weights to critical parameters, so as to better address the maintenance of radiological devices.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  15. The Educational Situation Quality Model: Recent Advances

    PubMed Central

    Doménech-Betoret, Fernando

    2018-01-01

    The purpose of this work was to present an educational model developed in recent years entitled the “The Educational Situation Quality Model” (MOCSE, acronym in Spanish). MOCSE can be defined as an instructional model that simultaneously considers the teaching-learning process, where motivation plays a central role. It explains the functioning of an educational setting by organizing and relating the most important variables which, according to the literature, contribute to student learning. Besides being a conceptual framework, this model also provides a methodological procedure to guide research and to promote reflection in the classroom. It allows teachers to implement effective research-action programs to improve teacher–students satisfaction and learning outcomes in the classroom context. This work explains the model’s characteristics and functioning, recent advances, and how teachers can use it in an educational setting with a specific subject. This proposal integrates approaches from several relevant psycho-educational theories and introduces a new perspective into the existing literature that will allow researchers to make progress in studying educational setting functioning. The initial MOCSE configuration has been refined over time in accordance with the empirical results obtained from previous research, carried out within the MOCSE framework and with the subsequent reflections that derived from these results. Finally, the contribution of the model to improve learning outcomes and satisfaction, and its applicability in the classroom, are also discussed. PMID:29593623

  16. Innovative model of delivering quality improvement education for trainees--a pilot project.

    PubMed

    Ramar, Kannan; Hale, Curt W; Dankbar, Eugene C

    2015-01-01

    After incorporating quality improvement (QI) education as a required curriculum for our trainees in 2010, a need arose to readdress our didactic sessions as they were too long, difficult to schedule, and resulting in a drop in attendance. A 'flipped classroom' (FC) model to deliver QI education was touted to be an effective delivery method as it allows the trainees to view didactic materials on videos, on their own time, and uses the classroom to clarify concepts and employ learned tools on case-based scenarios including workshops. The Mayo Quality Academy prepared 29 videos that incorporated the previously delivered 17 weekly didactic sessions, for a total duration of 135 min. The half-day session clarified questions related to the videos, followed by case examples and a hands-on workshop on how to perform and utilize a few commonly used QI tools and methods. Seven trainees participated. There was a significant improvement in knowledge as measured by pre- and post-FC model test results [improvement by 40.34% (SD 16.34), p<0.001]. The survey results were overall positive about the FC model with all trainees strongly agreeing that we should continue with this model to deliver QI education. The pilot project of using the FC model to deliver QI education was successful in a small sample of trainees.

  17. Indoor Air Quality Building Education and Assessment Model Forms

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  18. Measuring health care process quality with software quality measures.

    PubMed

    Yildiz, Ozkan; Demirörs, Onur

    2012-01-01

    Existing quality models focus on some specific diseases, clinics or clinical areas. Although they contain structure, process, or output type measures, there is no model which measures quality of health care processes comprehensively. In addition, due to the not measured overall process quality, hospitals cannot compare quality of processes internally and externally. To bring a solution to above problems, a new model is developed from software quality measures. We have adopted the ISO/IEC 9126 software quality standard for health care processes. Then, JCIAS (Joint Commission International Accreditation Standards for Hospitals) measurable elements were added to model scope for unifying functional requirements. Assessment (diagnosing) process measurement results are provided in this paper. After the application, it was concluded that the model determines weak and strong aspects of the processes, gives a more detailed picture for the process quality, and provides quantifiable information to hospitals to compare their processes with multiple organizations.

  19. Image quality assessment by preprocessing and full reference model combination

    NASA Astrophysics Data System (ADS)

    Bianco, S.; Ciocca, G.; Marini, F.; Schettini, R.

    2009-01-01

    This paper focuses on full-reference image quality assessment and presents different computational strategies aimed to improve the robustness and accuracy of some well known and widely used state of the art models, namely the Structural Similarity approach (SSIM) by Wang and Bovik and the S-CIELAB spatial-color model by Zhang and Wandell. We investigate the hypothesis that combining error images with a visual attention model could allow a better fit of the psycho-visual data of the LIVE Image Quality assessment Database Release 2. We show that the proposed quality assessment metric better correlates with the experimental data.

  20. Evaluation of the Community Multiscale Air Quality model version 5.1

    EPA Science Inventory

    The Community Multiscale Air Quality model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Atmospheric Modeling and Analysis Division (AMAD) of the U.S. Environment...

  1. The Feasibility of Quality Function Deployment (QFD) as an Assessment and Quality Assurance Model

    ERIC Educational Resources Information Center

    Matorera, D.; Fraser, W. J.

    2016-01-01

    Business schools are globally often seen as structured, purpose-driven, multi-sector and multi-perspective organisations. This article is based on the response of a graduate school to an innovative industrial Quality Function Deployment-based model (QFD), which was to be adopted initially in a Master's degree programme for quality assurance…

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

    PubMed

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

    2014-01-01

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

  3. McCook Reservoir Water Quality Model. Numerical Model Investigation

    DTIC Science & Technology

    1991-09-01

    REPT TYPE AND DATES COVERED ad September Cana Final report . LEAND SUBTITLE S. FUNDING NUERS Spinfild VA2261 ThcCook Reservoir Water Quality Model...oxygen injected by the aeration system Manufacturers of diffusers supply OTE information specific to gas flow rate and depth. The depths at which most

  4. 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

  5. APOLLO: a quality assessment service for single and multiple protein models.

    PubMed

    Wang, Zheng; Eickholt, Jesse; Cheng, Jianlin

    2011-06-15

    We built a web server named APOLLO, which can evaluate the absolute global and local qualities of a single protein model using machine learning methods or the global and local qualities of a pool of models using a pair-wise comparison approach. Based on our evaluations on 107 CASP9 (Critical Assessment of Techniques for Protein Structure Prediction) targets, the predicted quality scores generated from our machine learning and pair-wise methods have an average per-target correlation of 0.671 and 0.917, respectively, with the true model quality scores. Based on our test on 92 CASP9 targets, our predicted absolute local qualities have an average difference of 2.60 Å with the actual distances to native structure. http://sysbio.rnet.missouri.edu/apollo/. Single and pair-wise global quality assessment software is also available at the site.

  6. 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.

  7. [Economic efficiency of renal denervation in patients with resistant hypertension: results of Markov modeling].

    PubMed

    Kontsevaia, A V; Suvorova, E I; Khudiakov, M B

    2014-01-01

    Aim of this study was to evaluate the cost-effectiveness of renal denervation (RD) in resistant arterial hypertension (AH) in Russia. Modeling of Markov conducted economic impact of RD on the Russian population of patients with resistant hypertension in combination with optimal medical therapy (OMT) compared with OMT using a model developed by American researchers based on the results of international research. The model contains data on Russian mortality, and costs of major complications of hypertension. The simulation results showed a significant reduction in relative risk reduction of adverse outcomes in patients with resistant hypertension for 10 years (risk of stroke is reduced by 30%, myocardial infarction - 32%). RD saves 0.9 years of quality-adjusted life (QALY) by an average of 1 patient with resistant hypertension. Costs for 1 year stored in the application of quality of life amounted to RD 203 791.6 rubles. Which is below the 1 gross domestic product and therefore indicates the feasibility of this method in Russia.

  8. Monitoring And Modeling Environmental Water Quality To Support Environmental Water Purchase Decision-making

    NASA Astrophysics Data System (ADS)

    Null, S. E.; Elmore, L.; Mouzon, N. R.; Wood, J. R.

    2016-12-01

    More than 25 million cubic meters (20,000 acre feet) of water has been purchased from willing agricultural sellers for environmental flows in Nevada's Walker River to improve riverine habitat and connectivity with downstream Walker Lake. Reduced instream flows limit native fish populations, like Lahontan cutthroat trout, through warm daily stream temperatures and low dissolved oxygen concentrations. Environmental water purchases maintain instream flows, although effects on water quality are more varied. We use multi-year water quality monitoring and physically-based hydrodynamic and water quality modeling to estimate streamflow, water temperature, and dissolved oxygen concentrations with alternative environmental water purchases. We simulate water temperature and dissolved oxygen changes from increased streamflow to prioritize the time periods and locations that environmental water purchases most enhance trout habitat as a function of water quality. Monitoring results indicate stream temperature and dissolved oxygen limitations generally exist in the 115 kilometers upstream of Walker Lake (about 37% of the study area) from approximately May through September, and this reach acts as a water quality barrier for fish passage. Model results indicate that low streamflows generally coincide with critically warm stream temperatures, water quality refugia exist on a tributary of the Walker River, and environmental water purchases may improve stream temperature and dissolved oxygen conditions for some reaches and seasons, especially in dry years and prolonged droughts. This research supports environmental water purchase decision-making and allows water purchase decisions to be prioritized with other river restoration alternatives.

  9. 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...

  10. 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.

  11. Heuristic Model Of The Composite Quality Index Of Environmental Assessment

    NASA Astrophysics Data System (ADS)

    Khabarov, A. N.; Knyaginin, A. A.; Bondarenko, D. V.; Shepet, I. P.; Korolkova, L. N.

    2017-01-01

    The goal of the paper is to present the heuristic model of the composite environmental quality index based on the integrated application of the elements of utility theory, multidimensional scaling, expert evaluation and decision-making. The composite index is synthesized in linear-quadratic form, it provides higher adequacy of the results of the assessment preferences of experts and decision-makers.

  12. Quality improvement on the acute inpatient psychiatry unit using the model for improvement.

    PubMed

    Singh, Kuldeep; Sanderson, Joshua; Galarneau, David; Keister, Thomas; Hickman, Dean

    2013-01-01

    A need exists for constant evaluation and modification of processes within healthcare systems to achieve quality improvement. One common approach is the Model for Improvement that can be used to clearly define aims, measures, and changes that are then implemented through a plan-do-study-act (PDSA) cycle. This approach is a commonly used method for improving quality in a wide range of fields. The Model for Improvement allows for a systematic process that can be revised at set time intervals to achieve a desired result. We used the Model for Improvement in an acute psychiatry unit (APU) to improve the screening incidence of abnormal involuntary movements in eligible patients-those starting or continuing on standing neuroleptics-with the Abnormal Involuntary Movement Scale (AIMS). After 8 weeks of using the Model for Improvement, both of the participating inpatient services in the APU showed substantial overall improvement in screening for abnormal involuntary movements using the AIMS. Crucial aspects of a successful quality improvement initiative based on the Model for Improvement are well-defined goals, process measures, and structured PDSA cycles. Success also requires communication, organization, and participation of the entire team.

  13. A sound quality model for objective synthesis evaluation of vehicle interior noise based on artificial neural network

    NASA Astrophysics Data System (ADS)

    Wang, Y. S.; Shen, G. Q.; Xing, Y. F.

    2014-03-01

    Based on the artificial neural network (ANN) technique, an objective sound quality evaluation (SQE) model for synthesis annoyance of vehicle interior noises is presented in this paper. According to the standard named GB/T18697, firstly, the interior noises under different working conditions of a sample vehicle are measured and saved in a noise database. Some mathematical models for loudness, sharpness and roughness of the measured vehicle noises are established and performed by Matlab programming. Sound qualities of the vehicle interior noises are also estimated by jury tests following the anchored semantic differential (ASD) procedure. Using the objective and subjective evaluation results, furthermore, an ANN-based model for synthetical annoyance evaluation of vehicle noises, so-called ANN-SAE, is developed. Finally, the ANN-SAE model is proved by some verification tests with the leave-one-out algorithm. The results suggest that the proposed ANN-SAE model is accurate and effective and can be directly used to estimate sound quality of the vehicle interior noises, which is very helpful for vehicle acoustical designs and improvements. The ANN-SAE approach may be extended to deal with other sound-related fields for product quality evaluations in SQE engineering.

  14. Modeling Effects of Groundwater Basin Closure, and Reversal of Closure, on Groundwater Quality

    NASA Astrophysics Data System (ADS)

    Pauloo, R.; Guo, Z.; Fogg, G. E.

    2017-12-01

    Population growth, the expansion of agriculture, and climate uncertainties have accelerated groundwater pumping and overdraft in aquifers worldwide. In many agricultural basins, a water budget may be stable or not in overdraft, yet disconnected ground and surface water bodies can contribute to the formation of a "closed" basin, where water principally exits the basin as evapotranspiration. Although decreasing water quality associated with increases in Total Dissolved Solids (TDS) have been documented in aquifers across the United States in the past half century, connections between water quality declines and significant changes in hydrologic budgets leading to closed basin formation remain poorly understood. Preliminary results from an analysis with a regional-scale mixing model of the Tulare Lake Basin in California indicate that groundwater salinization resulting from open to closed basin conversion can operate on a decades-to-century long time scale. The only way to reverse groundwater salinization caused by basin closure is to refill the basin and change the hydrologic budget sufficiently for natural groundwater discharge to resume. 3D flow and transport modeling, including the effects of heterogeneity based on a hydrostratigraphic facies model, is used to explore rates and time scales of groundwater salinization and its reversal under different water and land management scenarios. The modeling is also used to ascertain the extent to which local and regional heterogeneity need to be included in order to appropriately upscale the advection-dispersion equation in a basin scale groundwater quality management model. Results imply that persistent managed aquifer recharge may slow groundwater salinization, and complete reversal may be possible at sufficiently high water tables.

  15. USING COMPUTER MODELS TO DETERMINE THE EFFECT OF STORAGE ON WATER QUALITY

    EPA Science Inventory

    Studies have indicated that water quality is degraded as a result of long residence times in storage tanks, highlighting the importance of tank design, location, and operation. Computer models, developed to explain some of the mixing and distrribution issues associated with tank...

  16. College quality and hourly wages: evidence from the self-revelation model, sibling models and instrumental variables.

    PubMed

    Borgen, Nicolai T

    2014-11-01

    This paper addresses the recent discussion on confounding in the returns to college quality literature using the Norwegian case. The main advantage of studying Norway is the quality of the data. Norwegian administrative data provide information on college applications, family relations and a rich set of control variables for all Norwegian citizens applying to college between 1997 and 2004 (N = 141,319) and their succeeding wages between 2003 and 2010 (676,079 person-year observations). With these data, this paper uses a subset of the models that have rendered mixed findings in the literature in order to investigate to what extent confounding biases the returns to college quality. I compare estimates obtained using standard regression models to estimates obtained using the self-revelation model of Dale and Krueger (2002), a sibling fixed effects model and the instrumental variable model used by Long (2008). Using these methods, I consistently find increasing returns to college quality over the course of students' work careers, with positive returns only later in students' work careers. I conclude that the standard regression estimate provides a reasonable estimate of the returns to college quality. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. Assessment of Reference Height Models on Quality of Tandem-X dem

    NASA Astrophysics Data System (ADS)

    Mirzaee, S.; Motagh, M.; Arefi, H.

    2015-12-01

    The aim of this study is to investigate the effect of various Global Digital Elevation Models (GDEMs) in producing high-resolution topography model using TanDEM-X (TDX) Coregistered Single Look Slant Range Complex (CoSSC) images. We selected an image acquired on Jun 12th, 2012 over Doroud region in Lorestan, west of Iran and used 4 external digital elevation models in our processing including DLR/ASI X-SAR DEM (SRTM-X, 30m resolution), ASTER GDEM Version 2 (ASTER-GDEMV2, 30m resolution), NASA SRTM Version 4 (SRTM-V4, 90m resolution), and a local photogrammetry-based DEM prepared by National Cartographic Center (NCC DEM, 10m resolution) of Iran. InSAR procedure for DEM generation was repeated four times with each of the four external height references. The quality of each external DEM was initially assessed using ICESat filtered points. Then, the quality of, each TDX-based DEM was assessed using the more precise external DEM selected in the previous step. Results showed that both local (NCC) DEM and SRTM X-band performed the best (RMSE< 9m) for TDX-DEM generation. In contrast, ASTER GDEM v2 and SRTM C-band v4 showed poorer quality.

  18. Uncertainty, ensembles and air quality dispersion modeling: applications and challenges

    NASA Astrophysics Data System (ADS)

    Dabberdt, Walter F.; Miller, Erik

    The past two decades have seen significant advances in mesoscale meteorological modeling research and applications, such as the development of sophisticated and now widely used advanced mesoscale prognostic models, large eddy simulation models, four-dimensional data assimilation, adjoint models, adaptive and targeted observational strategies, and ensemble and probabilistic forecasts. Some of these advances are now being applied to urban air quality modeling and applications. Looking forward, it is anticipated that the high-priority air quality issues for the near-to-intermediate future will likely include: (1) routine operational forecasting of adverse air quality episodes; (2) real-time high-level support to emergency response activities; and (3) quantification of model uncertainty. Special attention is focused here on the quantification of model uncertainty through the use of ensemble simulations. Application to emergency-response dispersion modeling is illustrated using an actual event that involved the accidental release of the toxic chemical oleum. Both surface footprints of mass concentration and the associated probability distributions at individual receptors are seen to provide valuable quantitative indicators of the range of expected concentrations and their associated uncertainty.

  19. Predictors of quality of life: A quantitative investigation of the stress-coping model in children with asthma

    PubMed Central

    Peeters, Yvette; Boersma, Sandra N; Koopman, Hendrik M

    2008-01-01

    Background Aim of this study is to further explore predictors of health related quality of life in children with asthma using factors derived from to the extended stress-coping model. While the stress-coping model has often been used as a frame of reference in studying health related quality of life in chronic illness, few have actually tested the model in children with asthma. Method In this survey study data were obtained by means of self-report questionnaires from seventy-eight children with asthma and their parents. Based on data derived from these questionnaires the constructs of the extended stress-coping model were assessed, using regression analysis and path analysis. Results The results of both regression analysis and path analysis reveal tentative support for the proposed relationships between predictors and health related quality of life in the stress-coping model. Moreover, as indicated in the stress-coping model, HRQoL is only directly predicted by coping. Both coping strategies 'emotional reaction' (significantly) and 'avoidance' are directly related to HRQoL. Conclusion In children with asthma, the extended stress-coping model appears to be a useful theoretical framework for understanding the impact of the illness on their quality of life. Consequently, the factors suggested by this model should be taken into account when designing optimal psychosocial-care interventions. PMID:18366753

  20. Water quality modeling in the systems impact assessment model for the Klamath River basin - Keno, Oregon to Seiad Valley, California

    USGS Publications Warehouse

    Hanna, R. Blair; Campbell, Sharon G.

    2000-01-01

    This report describes the water quality model developed for the Klamath River System Impact Assessment Model (SIAM). The Klamath River SIAM is a decision support system developed by the authors and other US Geological Survey (USGS), Midcontinent Ecological Science Center staff to study the effects of basin-wide water management decisions on anadromous fish in the Klamath River. The Army Corps of Engineersa?? HEC5Q water quality modeling software was used to simulate water temperature, dissolved oxygen and conductivity in 100 miles of the Klamath River Basin in Oregon and California. The water quality model simulated three reservoirs and the mainstem Klamath River influenced by the Shasta and Scott River tributaries. Model development, calibration and two validation exercises are described as well as the integration of the water quality model into the SIAM decision support system software. Within SIAM, data are exchanged between the water quantity model (MODSIM), the water quality model (HEC5Q), the salmon population model (SALMOD) and methods for evaluating ecosystem health. The overall predictive ability of the water quality model is described in the context of calibration and validation error statistics. Applications of SIAM and the water quality model are described.

  1. Model development for the assessment of terrestrial and aquatic habitat quality in conservation planning.

    PubMed

    Terrado, Marta; Sabater, Sergi; Chaplin-Kramer, Becky; Mandle, Lisa; Ziv, Guy; Acuña, Vicenç

    2016-01-01

    There is a growing pressure of human activities on natural habitats, which leads to biodiversity losses. To mitigate the impact of human activities, environmental policies are developed and implemented, but their effects are commonly not well understood because of the lack of tools to predict the effects of conservation policies on habitat quality and/or diversity. We present a straightforward model for the simultaneous assessment of terrestrial and aquatic habitat quality in river basins as a function of land use and anthropogenic threats to habitat that could be applied under different management scenarios to help understand the trade-offs of conservation actions. We modify the InVEST model for the assessment of terrestrial habitat quality and extend it to freshwater habitats. We assess the reliability of the model in a severely impaired basin by comparing modeled results to observed terrestrial and aquatic biodiversity data. Estimated habitat quality is significantly correlated with observed terrestrial vascular plant richness (R(2)=0.76) and diversity of aquatic macroinvertebrates (R(2)=0.34), as well as with ecosystem functions such as in-stream phosphorus retention (R(2)=0.45). After that, we analyze different scenarios to assess the suitability of the model to inform changes in habitat quality under different conservation strategies. We believe that the developed model can be useful to assess potential levels of biodiversity, and to support conservation planning given its capacity to forecast the effects of management actions in river basins. Copyright © 2015 Elsevier B.V. All rights reserved.

  2. What is a 'good' job? Modelling job quality for blue collar workers.

    PubMed

    Jones, Wendy; Haslam, Roger; Haslam, Cheryl

    2017-01-01

    This paper proposes a model of job quality, developed from interviews with blue collar workers: bus drivers, manufacturing operatives and cleaners (n  =  80). The model distinguishes between core features, important for almost all workers, and 'job fit' features, important to some but not others, or where individuals might have different preferences. Core job features found important for almost all interviewees included job security, personal safety and having enough pay to meet their needs. 'Job fit' features included autonomy and the opportunity to form close relationships. These showed more variation between participants; priorities were influenced by family commitments, stage of life and personal preference. The resulting theoretical perspective indicates the features necessary for a job to be considered 'good' by the person doing it, whilst not adversely affecting their health. The model should have utility as a basis for measuring and improving job quality and the laudable goal of creating 'good jobs'. Practitioner Summary: Good work can contribute positively to health and well-being, but there is a lack of agreement regarding the concept of a 'good' job. A model of job quality has been constructed based on semi-structured worker interviews (n  =  80). The model emphasises the need to take into account variation between individuals in their preferred work characteristics.

  3. EVALUATING THE USE OF OUTPUTS FROM COMPREHENSIVE METEOROLOGICAL MODELS IN AIR QUALITY MODELING APPLICATIONS

    EPA Science Inventory

    Currently used dispersion models, such as the AMS/EPA Regulatory Model (AERMOD), process routinely available meteorological observations to construct model inputs. Thus, model estimates of concentrations depend on the availability and quality of Meteorological observations, as we...

  4. Impacts of a Rural Subdivision on Groundwater Quality: Results of Long-Term Monitoring.

    PubMed

    Rayne, Todd W; Bradbury, Kenneth R; Krause, Jacob J

    2018-03-30

    A rural subdivision in south central Wisconsin was instrumented with monitoring wells and lysimeters before, during, and after its construction to examine the impacts of the unsewered subdivision on groundwater quality and quantity. Prior to construction, the 78-acre (32 ha) site was farmland. Sixteen homes were constructed beginning in 2003. Initial monitoring from 2002 to 2005 showed that groundwater beneath the site had been impacted by previous agricultural use, with nitrate-N values as high as 30 mg/L and some detections of the herbicide atrazine. Our 12-year study shows that the transition from agricultural to residential land use has changed groundwater quality in both negative and positive ways. Although groundwater elevations showed typical seasonal fluctuations each year, there were no measurable changes in groundwater levels or general flow directions during the 12-year study period. Chloride values increased in many wells, possibly as a result of road salting or water softener discharge. Nitrate concentrations varied spatially and temporally over the study period, with some initial concentrations substantially above the drinking water standard. In some wells, nitrate and atrazine levels have declined substantially since agriculture ceased. However, atrazine was still present at trace concentrations throughout the site in 2014. Wastewater tracers show there are small but detectable impacts from septic effluent on groundwater quality. Particle traces based on a groundwater flow model are consistent with the hypothesis that septic leachate has impacted groundwater quality. © 2018, National Ground Water Association.

  5. Development and application of new quality model for software projects.

    PubMed

    Karnavel, K; Dillibabu, R

    2014-01-01

    The IT industry tries to employ a number of models to identify the defects in the construction of software projects. In this paper, we present COQUALMO and its limitations and aim to increase the quality without increasing the cost and time. The computation time, cost, and effort to predict the residual defects are very high; this was overcome by developing an appropriate new quality model named the software testing defect corrective model (STDCM). The STDCM was used to estimate the number of remaining residual defects in the software product; a few assumptions and the detailed steps of the STDCM are highlighted. The application of the STDCM is explored in software projects. The implementation of the model is validated using statistical inference, which shows there is a significant improvement in the quality of the software projects.

  6. Stochastic Models of Quality Control on Test Misgrading.

    ERIC Educational Resources Information Center

    Wang, Jianjun

    Stochastic models are developed in this article to examine the rate of test misgrading in educational and psychological measurement. The estimation of inadvertent grading errors can serve as a basis for quality control in measurement. Limitations of traditional Poisson models have been reviewed to highlight the need to introduce new models using…

  7. Water-quality trends in the nation’s rivers and streams, 1972–2012—Data preparation, statistical methods, and trend results

    USGS Publications Warehouse

    Oelsner, Gretchen P.; Sprague, Lori A.; Murphy, Jennifer C.; Zuellig, Robert E.; Johnson, Henry M.; Ryberg, Karen R.; Falcone, James A.; Stets, Edward G.; Vecchia, Aldo V.; Riskin, Melissa L.; De Cicco, Laura A.; Mills, Taylor J.; Farmer, William H.

    2017-04-04

    Since passage of the Clean Water Act in 1972, Federal, State, and local governments have invested billions of dollars to reduce pollution entering rivers and streams. To understand the return on these investments and to effectively manage and protect the Nation’s water resources in the future, we need to know how and why water quality has been changing over time. As part of the National Water-Quality Assessment Project, of the U.S. Geological Survey’s National Water-Quality Program, data from the U.S. Geological Survey, along with multiple other Federal, State, Tribal, regional, and local agencies, have been used to support the most comprehensive assessment conducted to date of surface-water-quality trends in the United States. This report documents the methods used to determine trends in water quality and ecology because these methods are vital to ensuring the quality of the results. Specific objectives are to document (1) the data compilation and processing steps used to identify river and stream sites throughout the Nation suitable for water-quality, pesticide, and ecology trend analysis, (2) the statistical methods used to determine trends in target parameters, (3) considerations for water-quality, pesticide, and ecology data and streamflow data when modeling trends, (4) sensitivity analyses for selecting data and interpreting trend results with the Weighted Regressions on Time, Discharge, and Season method, and (5) the final trend results at each site. The scope of this study includes trends in water-quality concentrations and loads (nutrient, sediment, major ion, salinity, and carbon), pesticide concentrations and loads, and metrics for aquatic ecology (fish, invertebrates, and algae) for four time periods: (1) 1972–2012, (2) 1982–2012, (3) 1992–2012, and (4) 2002–12. In total, nearly 12,000 trends in concentration, load, and ecology metrics were evaluated in this study; there were 11,893 combinations of sites, parameters, and trend periods. The

  8. A manufacturing quality assessment model based-on two stages interval type-2 fuzzy logic

    NASA Astrophysics Data System (ADS)

    Purnomo, Muhammad Ridwan Andi; Helmi Shintya Dewi, Intan

    2016-01-01

    This paper presents the development of an assessment models for manufacturing quality using Interval Type-2 Fuzzy Logic (IT2-FL). The proposed model is developed based on one of building block in sustainable supply chain management (SSCM), which is benefit of SCM, and focuses more on quality. The proposed model can be used to predict the quality level of production chain in a company. The quality of production will affect to the quality of product. Practically, quality of production is unique for every type of production system. Hence, experts opinion will play major role in developing the assessment model. The model will become more complicated when the data contains ambiguity and uncertainty. In this study, IT2-FL is used to model the ambiguity and uncertainty. A case study taken from a company in Yogyakarta shows that the proposed manufacturing quality assessment model can work well in determining the quality level of production.

  9. Hydrological and water quality processes simulation by the integrated MOHID model

    NASA Astrophysics Data System (ADS)

    Epelde, Ane; Antiguedad, Iñaki; Brito, David; Eduardo, Jauch; Neves, Ramiro; Sauvage, Sabine; Sánchez-Pérez, José Miguel

    2016-04-01

    Different modelling approaches have been used in recent decades to study the water quality degradation caused by non-point source pollution. In this study, the MOHID fully distributed and physics-based model has been employed to simulate hydrological processes and nitrogen dynamics in a nitrate vulnerable zone: the Alegria River watershed (Basque Country, Northern Spain). The results of this study indicate that the MOHID code is suitable for hydrological processes simulation at the watershed scale, as the model shows satisfactory performance at simulating the discharge (with NSE: 0.74 and 0.76 during calibration and validation periods, respectively). The agronomical component of the code, allowed the simulation of agricultural practices, which lead to adequate crop yield simulation in the model. Furthermore, the nitrogen exportation also shows satisfactory performance (with NSE: 0.64 and 0.69 during calibration and validation periods, respectively). While the lack of field measurements do not allow to evaluate the nutrient cycling processes in depth, it has been observed that the MOHID model simulates the annual denitrification according to general ranges established for agricultural watersheds (in this study, 9 kg N ha-1 year-1). In addition, the model has simulated coherently the spatial distribution of the denitrification process, which is directly linked to the simulated hydrological conditions. Thus, the model has localized the highest rates nearby the discharge zone of the aquifer and also where the aquifer thickness is low. These results evidence the strength of this model to simulate watershed scale hydrological processes as well as the crop production and the agricultural activity derived water quality degradation (considering both nutrient exportation and nutrient cycling processes).

  10. Application of an IRT Polytomous Model for Measuring Health Related Quality of Life

    ERIC Educational Resources Information Center

    Tejada, Antonio J. Rojas; Rojas, Oscar M. Lozano

    2005-01-01

    Background: The Item Response Theory (IRT) has advantages for measuring Health Related Quality of Life (HRQOL) as opposed to the Classical Tests Theory (CTT). Objectives: To present the results of the application of a polytomous model based on IRT, specifically, the Rating Scale Model (RSM), to measure HRQOL with the EORTC QLQ-C30. Methods: 103…

  11. Urban scale air quality modelling using detailed traffic emissions estimates

    NASA Astrophysics Data System (ADS)

    Borrego, C.; Amorim, J. H.; Tchepel, O.; Dias, D.; Rafael, S.; Sá, E.; Pimentel, C.; Fontes, T.; Fernandes, P.; Pereira, S. R.; Bandeira, J. M.; Coelho, M. C.

    2016-04-01

    The atmospheric dispersion of NOx and PM10 was simulated with a second generation Gaussian model over a medium-size south-European city. Microscopic traffic models calibrated with GPS data were used to derive typical driving cycles for each road link, while instantaneous emissions were estimated applying a combined Vehicle Specific Power/Co-operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (VSP/EMEP) methodology. Site-specific background concentrations were estimated using time series analysis and a low-pass filter applied to local observations. Air quality modelling results are compared against measurements at two locations for a 1 week period. 78% of the results are within a factor of two of the observations for 1-h average concentrations, increasing to 94% for daily averages. Correlation significantly improves when background is added, with an average of 0.89 for the 24 h record. The results highlight the potential of detailed traffic and instantaneous exhaust emissions estimates, together with filtered urban background, to provide accurate input data to Gaussian models applied at the urban scale.

  12. WATER QUALITY MODELING IN THE RIO CHONE ESTUARY

    EPA Science Inventory

    Water quality in the Rio Chone Estuary, a seasonally inverse, tropical estuary, in Ecuador was characterized by modeling the distribution of biochemical oxygen demand (BOD) and dissolved inorganic nitrogen (DIN) within the water column. These two variables are modeled using modif...

  13. Green Pea and Garlic Puree Model Food Development for Thermal Pasteurization Process Quality Evaluation.

    PubMed

    Bornhorst, Ellen R; Tang, Juming; Sablani, Shyam S; Barbosa-Cánovas, Gustavo V; Liu, Fang

    2017-07-01

    Development and selection of model foods is a critical part of microwave thermal process development, simulation validation, and optimization. Previously developed model foods for pasteurization process evaluation utilized Maillard reaction products as the time-temperature integrators, which resulted in similar temperature sensitivity among the models. The aim of this research was to develop additional model foods based on different time-temperature integrators, determine their dielectric properties and color change kinetics, and validate the optimal model food in hot water and microwave-assisted pasteurization processes. Color, quantified using a * value, was selected as the time-temperature indicator for green pea and garlic puree model foods. Results showed 915 MHz microwaves had a greater penetration depth into the green pea model food than the garlic. a * value reaction rates for the green pea model were approximately 4 times slower than in the garlic model food; slower reaction rates were preferred for the application of model food in this study, that is quality evaluation for a target process of 90 °C for 10 min at the cold spot. Pasteurization validation used the green pea model food and results showed that there were quantifiable differences between the color of the unheated control, hot water pasteurization, and microwave-assisted thermal pasteurization system. Both model foods developed in this research could be utilized for quality assessment and optimization of various thermal pasteurization processes. © 2017 Institute of Food Technologists®.

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

    EPA Science Inventory

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

  15. Aircraft model prototypes which have specified handling-quality time histories

    NASA Technical Reports Server (NTRS)

    Johnson, S. H.

    1976-01-01

    Several techniques for obtaining linear constant-coefficient airplane models from specified handling-quality time histories are discussed. One technique, the pseudodata method, solves the basic problem, yields specified eigenvalues, and accommodates state-variable transfer-function zero suppression. The method is fully illustrated for a fourth-order stability-axis small-motion model with three lateral handling-quality time histories specified. The FORTRAN program which obtains and verifies the model is included and fully documented.

  16. Improvements to image quality using hybrid and model-based iterative reconstructions: a phantom study.

    PubMed

    Aurumskjöld, Marie-Louise; Ydström, Kristina; Tingberg, Anders; Söderberg, Marcus

    2017-01-01

    The number of computed tomography (CT) examinations is increasing and leading to an increase in total patient exposure. It is therefore important to optimize CT scan imaging conditions in order to reduce the radiation dose. The introduction of iterative reconstruction methods has enabled an improvement in image quality and a reduction in radiation dose. To investigate how image quality depends on reconstruction method and to discuss patient dose reduction resulting from the use of hybrid and model-based iterative reconstruction. An image quality phantom (Catphan® 600) and an anthropomorphic torso phantom were examined on a Philips Brilliance iCT. The image quality was evaluated in terms of CT numbers, noise, noise power spectra (NPS), contrast-to-noise ratio (CNR), low-contrast resolution, and spatial resolution for different scan parameters and dose levels. The images were reconstructed using filtered back projection (FBP) and different settings of hybrid (iDose 4 ) and model-based (IMR) iterative reconstruction methods. iDose 4 decreased the noise by 15-45% compared with FBP depending on the level of iDose 4 . The IMR reduced the noise even further, by 60-75% compared to FBP. The results are independent of dose. The NPS showed changes in the noise distribution for different reconstruction methods. The low-contrast resolution and CNR were improved with iDose 4 , and the improvement was even greater with IMR. There is great potential to reduce noise and thereby improve image quality by using hybrid or, in particular, model-based iterative reconstruction methods, or to lower radiation dose and maintain image quality. © The Foundation Acta Radiologica 2016.

  17. Conceptual model for quality of life among adults with congenital or early deafness.

    PubMed

    Kushalnagar, Poorna; McKee, Michael; Smith, Scott R; Hopper, Melinda; Kavin, Denise; Atcherson, Samuel R

    2014-07-01

    A conceptual model of health-related quality of life (QoL) is needed to describe key themes that impact perceived QoL in adults with congenital or early deafness. To revise University of Washington Center for Disability Policy and Research's conceptual model of health promotion and QoL, with suggestions for applying the model to improving programs or services that target deaf adults with early deafness. Purposive and theoretical sampling of 35 adults who were born or became deaf early was planned in a 1-year study. In-depth semi-structured interviews probed deaf adult participants' perceptions about quality of life as a deaf individual. Data saturation was reached at the 17th interview with 2 additional interviews for validation, resulting in a total sample of 19 deaf adults. Coding and thematic analysis were conducted to develop the conceptual model. Our conceptual model delineates the relationships between health status (self-acceptance, coping with limitations), intrinsic (functional communication skills, navigating barriers/self-advocacy, resilience) and extrinsic (acceptance by others, access to information, educating others) factors in their influence on deaf adult quality of life outcomes at home, college, work, and in the community. Findings demonstrate the need for the programs and services to consider not only factors intrinsic to the deaf individual but also extrinsic factors in enhancing perceived quality of life outcomes among people with a range of functional hearing and language preferences, including American Sign Language. Copyright © 2014 Elsevier Inc. All rights reserved.

  18. 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.

  19. ProQ3: Improved model quality assessments using Rosetta energy terms

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

  1. Fuel quality-processing study. Volume 1: Overview and results

    NASA Technical Reports Server (NTRS)

    Jones, G. E., Jr.

    1982-01-01

    The methods whereby the intermediate results were obtained are outlined, and the evaluation of the feasible paths from liquid fossil fuel sources to generated electricity is presented. The segments from which these paths were built are the results from the fuel upgrading schemes, on-site treatments, and exhaust gas treatments detailed in the subsequent volumes. The salient cost and quality parameters are included.

  2. Local-Scale Air Quality Modeling in Support of Human Health and Exposure Research (Invited)

    NASA Astrophysics Data System (ADS)

    Isakov, V.

    2010-12-01

    , regional-scale transport, and photochemical transformations. Since these needs are currently not met by a single model, hybrid air quality modeling has recently been developed to combine these capabilities. In this paper, we present the results of two studies where we applied the hybrid modeling approach to provide spatial and temporal details in air quality concentrations to support exposure and health studies: a) an urban-scale air quality accountability study involving near-source exposures to multiple ambient air pollutants, and b) an urban-scale epidemiological study involving human health data based on emergency department visits.

  3. Preparing the Model for Prediction Across Scales (MPAS) for global retrospective air quality modeling

    EPA Science Inventory

    The US EPA has a plan to leverage recent advances in meteorological modeling to develop a "Next-Generation" air quality modeling system that will allow consistent modeling of problems from global to local scale. The meteorological model of choice is the Model for Predic...

  4. CMAQ Involvement in Air Quality Model Evaluation International Initiative

    EPA Pesticide Factsheets

    Description of Air Quality Model Evaluation International Initiative (AQMEII). Different chemical transport models are applied by different groups over North America and Europe and evaluated against observations.

  5. Utility of NCEP Operational and Emerging Meteorological Models for Driving Air Quality Prediction

    NASA Astrophysics Data System (ADS)

    McQueen, J.; Huang, J.; Huang, H. C.; Shafran, P.; Lee, P.; Pan, L.; Sleinkofer, A. M.; Stajner, I.; Upadhayay, S.; Tallapragada, V.

    2017-12-01

    Operational air quality predictions for the United States (U. S.) are provided at NOAA by the National Air Quality Forecasting Capability (NAQFC). NAQFC provides nationwide operational predictions of ozone and particulate matter twice per day (at 06 and 12 UTC cycles) at 12 km resolution and 1 hour time intervals through 48 hours and distributed at http://airquality.weather.gov. The NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) 12 km weather prediction is used to drive the Community Multiscale Air Quality (CMAQ) model. In 2017, the NAM was upgraded in part to reduce a warm 2m temperature bias in Summer (V4). At the same time CMAQ was updated to V5.0.2. Both versions of the models were run in parallel for several months. Therefore the impact of improvements from the atmospheric chemistry model versus upgrades with the weather prediction model could be assessed. . Improvements to CMAQ were related to improvements to improvements in NAM 2 m temperature bias through increasing the opacity of clouds and reducing downward shortwave radiation resulted in reduced ozone photolysis. Higher resolution operational NWP models have recently been introduced as part of the NCEP modeling suite. These include the NAM CONUS Nest (3 km horizontal resolution) run four times per day through 60 hours and the High Resolution Rapid Refresh (HRRR, 3 km) run hourly out to 18 hours. In addition, NCEP with other NOAA labs has begun to develop and test the Next Generation Global Prediction System (NGGPS) based on the FV3 global model. This presentation also overviews recent developments with operational numerical weather prediction and evaluates the ability of these models for predicting low level temperatures, clouds and capturing boundary layer processes important for driving air quality prediction in complex terrain. The assessed meteorological model errors could help determine the magnitude of possible pollutant errors from CMAQ if used

  6. Developing a stochastic conflict resolution model for urban runoff quality management: Application of info-gap and bargaining theories

    NASA Astrophysics Data System (ADS)

    Ghodsi, Seyed Hamed; Kerachian, Reza; Estalaki, Siamak Malakpour; Nikoo, Mohammad Reza; Zahmatkesh, Zahra

    2016-02-01

    In this paper, two deterministic and stochastic multilateral, multi-issue, non-cooperative bargaining methodologies are proposed for urban runoff quality management. In the proposed methodologies, a calibrated Storm Water Management Model (SWMM) is used to simulate stormwater runoff quantity and quality for different urban stormwater runoff management scenarios, which have been defined considering several Low Impact Development (LID) techniques. In the deterministic methodology, the best management scenario, representing location and area of LID controls, is identified using the bargaining model. In the stochastic methodology, uncertainties of some key parameters of SWMM are analyzed using the info-gap theory. For each water quality management scenario, robustness and opportuneness criteria are determined based on utility functions of different stakeholders. Then, to find the best solution, the bargaining model is performed considering a combination of robustness and opportuneness criteria for each scenario based on utility function of each stakeholder. The results of applying the proposed methodology in the Velenjak urban watershed located in the northeastern part of Tehran, the capital city of Iran, illustrate its practical utility for conflict resolution in urban water quantity and quality management. It is shown that the solution obtained using the deterministic model cannot outperform the result of the stochastic model considering the robustness and opportuneness criteria. Therefore, it can be concluded that the stochastic model, which incorporates the main uncertainties, could provide more reliable results.

  7. On Regional Modeling to Support Air Quality Policies (book chapter)

    EPA Science Inventory

    We examine the use of the Community Multiscale Air Quality (CMAQ) model in simulating the changes in the extreme values of air quality that are of interest to the regulatory agencies. Year-to-year changes in ozone air quality are attributable to variations in the prevailing meteo...

  8. Development and Application of New Quality Model for Software Projects

    PubMed Central

    Karnavel, K.; Dillibabu, R.

    2014-01-01

    The IT industry tries to employ a number of models to identify the defects in the construction of software projects. In this paper, we present COQUALMO and its limitations and aim to increase the quality without increasing the cost and time. The computation time, cost, and effort to predict the residual defects are very high; this was overcome by developing an appropriate new quality model named the software testing defect corrective model (STDCM). The STDCM was used to estimate the number of remaining residual defects in the software product; a few assumptions and the detailed steps of the STDCM are highlighted. The application of the STDCM is explored in software projects. The implementation of the model is validated using statistical inference, which shows there is a significant improvement in the quality of the software projects. PMID:25478594

  9. Developing a Holistic Model for Quality in Higher Education.

    ERIC Educational Resources Information Center

    Srikanthan, G.; Dalrymple, John F.

    2002-01-01

    Proposes a holistic model for quality management in higher education which incorporates both service and academic functions. Discusses the crucial role played by organizational culture in implementation of any quality strategy, and asserts that ideal organizational behavior embodies the "learning communities" concept. (EV)

  10. Recent Advances in WRF Modeling for Air Quality Applications

    EPA Science Inventory

    The USEPA uses WRF in conjunction with the Community Multiscale Air Quality (CMAQ) for air quality regulation and research. Over the years we have added physics options and geophysical datasets to the WRF system to enhance model capabilities especially for extended retrospective...

  11. Microscale Obstacle Resolving Air Quality Model Evaluation with the Michelstadt Case

    PubMed Central

    Rakai, Anikó; Kristóf, Gergely

    2013-01-01

    Modelling pollutant dispersion in cities is challenging for air quality models as the urban obstacles have an important effect on the flow field and thus the dispersion. Computational Fluid Dynamics (CFD) models with an additional scalar dispersion transport equation are a possible way to resolve the flowfield in the urban canopy and model dispersion taking into consideration the effect of the buildings explicitly. These models need detailed evaluation with the method of verification and validation to gain confidence in their reliability and use them as a regulatory purpose tool in complex urban geometries. This paper shows the performance of an open source general purpose CFD code, OpenFOAM for a complex urban geometry, Michelstadt, which has both flow field and dispersion measurement data. Continuous release dispersion results are discussed to show the strengths and weaknesses of the modelling approach, focusing on the value of the turbulent Schmidt number, which was found to give best statistical metric results with a value of 0.7. PMID:24027450

  12. Microscale obstacle resolving air quality model evaluation with the Michelstadt case.

    PubMed

    Rakai, Anikó; Kristóf, Gergely

    2013-01-01

    Modelling pollutant dispersion in cities is challenging for air quality models as the urban obstacles have an important effect on the flow field and thus the dispersion. Computational Fluid Dynamics (CFD) models with an additional scalar dispersion transport equation are a possible way to resolve the flowfield in the urban canopy and model dispersion taking into consideration the effect of the buildings explicitly. These models need detailed evaluation with the method of verification and validation to gain confidence in their reliability and use them as a regulatory purpose tool in complex urban geometries. This paper shows the performance of an open source general purpose CFD code, OpenFOAM for a complex urban geometry, Michelstadt, which has both flow field and dispersion measurement data. Continuous release dispersion results are discussed to show the strengths and weaknesses of the modelling approach, focusing on the value of the turbulent Schmidt number, which was found to give best statistical metric results with a value of 0.7.

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

    PubMed

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

    2013-01-01

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

  14. Regional photochemical air quality modeling in the Mexico-US border area

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

    Mendoza, A.; Russell, A.G.; Mejia, G.M.

    1998-12-31

    The Mexico-United States border area has become an increasingly important region due to its commercial, industrial and urban growth. As a result, environmental concerns have risen. Treaties like the North American Free Trade Agreement (NAFTA) have further motivated the development of environmental impact assessment in the area. Of particular concern are air quality, and how the activities on both sides of the border contribute to its degradation. This paper presents results of applying a three-dimensional photochemical airshed model to study air pollution dynamics along the Mexico-United States border. In addition, studies were conducted to assess how size resolution impacts themore » model performance. The model performed within acceptable statistic limits using 12.5 x 12.5 km{sup 2} grid cells, and the benefits using finer grids were limited. Results were further used to assess the influence of grid-cell size on the modeling of control strategies, where coarser grids lead to significant loss of information.« less

  15. Take the Reins on Model Quality with ModelCHECK and Gatekeeper

    NASA Technical Reports Server (NTRS)

    Jones, Corey

    2012-01-01

    Model quality and consistency has been an issue for us due to the diverse experience level and imaginative modeling techniques of our users. Fortunately, setting up ModelCHECK and Gatekeeper to enforce our best practices has helped greatly, but it wasn't easy. There were many challenges associated with setting up ModelCHECK and Gatekeeper including: limited documentation, restrictions within ModelCHECK, and resistance from end users. However, we consider ours a success story. In this presentation we will describe how we overcame these obstacles and present some of the details of how we configured them to work for us.

  16. MODELS-3 COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODEL AEROSOL COMPONENT 1: MODEL DESCRIPTION

    EPA Science Inventory

    The aerosol component of the Community Multiscale Air Quality (CMAQ) model is designed to be an efficient and economical depiction of aerosol dynamics in the atmosphere. The approach taken represents the particle size distribution as the superposition of three lognormal subdis...

  17. Gaia: automated quality assessment of protein structure models.

    PubMed

    Kota, Pradeep; Ding, Feng; Ramachandran, Srinivas; Dokholyan, Nikolay V

    2011-08-15

    Increasing use of structural modeling for understanding structure-function relationships in proteins has led to the need to ensure that the protein models being used are of acceptable quality. Quality of a given protein structure can be assessed by comparing various intrinsic structural properties of the protein to those observed in high-resolution protein structures. In this study, we present tools to compare a given structure to high-resolution crystal structures. We assess packing by calculating the total void volume, the percentage of unsatisfied hydrogen bonds, the number of steric clashes and the scaling of the accessible surface area. We assess covalent geometry by determining bond lengths, angles, dihedrals and rotamers. The statistical parameters for the above measures, obtained from high-resolution crystal structures enable us to provide a quality-score that points to specific areas where a given protein structural model needs improvement. We provide these tools that appraise protein structures in the form of a web server Gaia (http://chiron.dokhlab.org). Gaia evaluates the packing and covalent geometry of a given protein structure and provides quantitative comparison of the given structure to high-resolution crystal structures. dokh@unc.edu Supplementary data are available at Bioinformatics online.

  18. Urban Landscape Characterization Using Remote Sensing Data For Input into Air Quality Modeling

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

    The urban landscape is inherently complex and this complexity is not adequately captured in air quality models that are used to assess whether urban areas are in attainment of EPA air quality standards, particularly for ground level ozone. This inadequacy of air quality models to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well these models predict ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to meteorological and air quality models focusing on the Atlanta, Georgia metropolitan area as a case study. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the Community Multiscale Air Quality (CMAQ) modeling schemes. Use of these data have been found to better characterize low density/suburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality.

  19. Evolution of Air Quality Model at the US EPA

    EPA Science Inventory

    At the US EPA, we have developed an air quality model, CMAQ, in the past 20+ years. Throughout the years, the model has been upgraded with respect to advancement of science. We have extended the model from regional to hemispheric. We have coupled it with meteorological model, WR...

  20. 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.

  1. 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

    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.

  2. A task force model for statewide change in nursing education: building quality and safety.

    PubMed

    Mundt, Mary H; Clark, Margherita Procaccini; Klemczak, Jeanette Wrona

    2013-01-01

    The purpose of this article was to describe a statewide planning process to transform nursing education in Michigan to improve quality and safety of patient care. A task force model was used to engage diverse partners in issue identification, consensus building, and recommendations. An example of a statewide intervention in nursing education and practice that was executed was the Michigan Quality and Safety in Nursing Education Institute, which was held using an integrated approach to academic-practice partners from all state regions. This paper describes the unique advantage of leadership by the Michigan Chief Nurse Executive, the existence of a nursing strategic plan, and a funding model. An overview of the Task Force on Nursing Education is presented with a focus on the model's 10 process steps and resulting seven recommendations. The Michigan Nurse Education Council was established to implement the recommendations that included quality and safety. Copyright © 2013 Elsevier Inc. All rights reserved.

  3. Structural Model of psychological risk and protective factors affecting on quality of life in patients with coronary heart disease: A psychocardiology model

    PubMed Central

    Nekouei, Zohreh Khayyam; Yousefy, Alireza; Doost, Hamid Taher Neshat; Manshaee, Gholamreza; Sadeghei, Masoumeh

    2014-01-01

    Background: Conducted researches show that psychological factors may have a very important role in the etiology, continuity and consequences of coronary heart diseases. This study has drawn the psychological risk and protective factors and their effects in patients with coronary heart diseases (CHD) in a structural model. It aims to determine the structural relations between psychological risk and protective factors with quality of life in patients with coronary heart disease. Materials and Methods: The present cross-sectional and correlational studies were conducted using structural equation modeling. The study sample included 398 patients of coronary heart disease in the university referral Hospital, as well as other city health care centers in Isfahan city. They were selected based on random sampling method. Then, in case, they were executed the following questionnaires: Coping with stressful situations (CISS- 21), life orientation (LOT-10), general self-efficacy (GSE-10), depression, anxiety and stress (DASS-21), perceived stress (PSS-14), multidimensional social support (MSPSS-12), alexithymia (TAS-20), spiritual intelligence (SQ-23) and quality of life (WHOQOL-26). Results: The results showed that protective and risk factors could affect the quality of life in patients with CHD with factor loadings of 0.35 and −0.60, respectively. Moreover, based on the values of the framework of the model such as relative chi-square (CMIN/DF = 3.25), the Comparative Fit Index (CFI = 0.93), the Parsimony Comparative Fit Index (PCFI = 0.68), the Root Mean Square Error of Approximation (RMSEA = 0.07) and details of the model (significance of the relationships) it has been confirmed that the psychocardiological structural model of the study is the good fitting model. Conclusion: This study was among the first to research the different psychological risk and protective factors of coronary heart diseases in the form of a structural model. The results of this study have

  4. 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.

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

    PubMed

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

    2016-12-05

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

  6. Modelling postharvest quality of blueberry affected by biological variability using image and spectral data.

    PubMed

    Hu, Meng-Han; Dong, Qing-Li; Liu, Bao-Lin

    2016-08-01

    Hyperspectral reflectance and transmittance sensing as well as near-infrared (NIR) spectroscopy were investigated as non-destructive tools for estimating blueberry firmness, elastic modulus and soluble solid content (SSC). Least squares-support vector machine models were established from these three spectra based on samples from three cultivars viz. Bluecrop, Duke and M2 and two harvest years viz. 2014 and 2015 for predicting blueberry postharvest quality. One-cultivar reflectance models (establishing model using one cultivar) derived better results than the corresponding transmittance and NIR models for predicting blueberry firmness with few cultivar effects. Two-cultivar NIR models (establishing model using two cultivars) proved to be suitable for estimating blueberry SSC with correlations over 0.83. Rp (RMSEp ) values of the three-cultivar reflectance models (establishing model using 75% of three cultivars) were 0.73 (0.094) and 0.73 (0.186), respectively , for predicting blueberry firmness and elastic modulus. For SSC prediction, the three-cultivar NIR model was found to achieve an Rp (RMSEp ) value of 0.85 (0.090). Adding Bluecrop samples harvested in 2014 could enhance the three-cultivar model robustness for firmness and elastic modulus. The above results indicated the potential for using spatial and spectral techniques to develop robust models for predicting blueberry postharvest quality containing biological variability. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  7. 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)

  8. Frameworks for Assessing the Quality of Modeling and Simulation Capabilities

    NASA Astrophysics Data System (ADS)

    Rider, W. J.

    2012-12-01

    The importance of assuring quality in modeling and simulation has spawned several frameworks for structuring the examination of quality. The format and content of these frameworks provides an emphasis, completeness and flow to assessment activities. I will examine four frameworks that have been developed and describe how they can be improved and applied to a broader set of high consequence applications. Perhaps the first of these frameworks was known as CSAU [Boyack] (code scaling, applicability and uncertainty) used for nuclear reactor safety and endorsed the United States' Nuclear Regulatory Commission (USNRC). This framework was shaped by nuclear safety practice, and the practical structure needed after the Three Mile Island accident. It incorporated the dominant experimental program, the dominant analysis approach, and concerns about the quality of modeling. The USNRC gave it the force of law that made the nuclear industry take it seriously. After the cessation of nuclear weapons' testing the United States began a program of examining the reliability of these weapons without testing. This program utilizes science including theory, modeling, simulation and experimentation to replace the underground testing. The emphasis on modeling and simulation necessitated attention on the quality of these simulations. Sandia developed the PCMM (predictive capability maturity model) to structure this attention [Oberkampf]. PCMM divides simulation into six core activities to be examined and graded relative to the needs of the modeling activity. NASA [NASA] has built yet another framework in response to the tragedy of the space shuttle accidents. Finally, Ben-Haim and Hemez focus upon modeling robustness and predictive fidelity in another approach. These frameworks are similar, and applied in a similar fashion. The adoption of these frameworks at Sandia and NASA has been slow and arduous because the force of law has not assisted acceptance. All existing frameworks are

  9. Life course socio-economic position and quality of life in adulthood: a systematic review of life course models

    PubMed Central

    2012-01-01

    Background A relationship between current socio-economic position and subjective quality of life has been demonstrated, using wellbeing, life and needs satisfaction approaches. Less is known regarding the influence of different life course socio-economic trajectories on later quality of life. Several conceptual models have been proposed to help explain potential life course effects on health, including accumulation, latent, pathway and social mobility models. This systematic review aimed to assess whether evidence supported an overall relationship between life course socio-economic position and quality of life during adulthood and if so, whether there was support for one or more life course models. Methods A review protocol was developed detailing explicit inclusion and exclusion criteria, search terms, data extraction items and quality appraisal procedures. Literature searches were performed in 12 electronic databases during January 2012 and the references and citations of included articles were checked for additional relevant articles. Narrative synthesis was used to analyze extracted data and studies were categorized based on the life course model analyzed. Results Twelve studies met the eligibility criteria and used data from 10 datasets and five countries. Study quality varied and heterogeneity between studies was high. Seven studies assessed social mobility models, five assessed the latent model, two assessed the pathway model and three tested the accumulation model. Evidence indicated an overall relationship, but mixed results were found for each life course model. Some evidence was found to support the latent model among women, but not men. Social mobility models were supported in some studies, but overall evidence suggested little to no effect. Few studies addressed accumulation and pathway effects and study heterogeneity limited synthesis. Conclusions To improve potential for synthesis in this area, future research should aim to increase study

  10. Modeling white sturgeon movement in a reservoir: The effect of water quality and sturgeon density

    USGS Publications Warehouse

    Sullivan, A.B.; Jager, H.I.; Myers, R.

    2003-01-01

    We developed a movement model to examine the distribution and survival of white sturgeon (Acipenser transmontanus) in a reservoir subject to large spatial and temporal variation in dissolved oxygen and temperature. Temperature and dissolved oxygen were simulated by a CE-QUAL-W2 model of Brownlee Reservoir, Idaho for a typical wet, normal, and dry hydrologic year. We compared current water quality conditions to scenarios with reduced nutrient inputs to the reservoir. White sturgeon habitat quality was modeled as a function of temperature, dissolved oxygen and, in some cases, suitability for foraging and depth. We assigned a quality index to each cell along the bottom of the reservoir. The model simulated two aspects of daily movement. Advective movement simulated the tendency for animals to move toward areas with high habitat quality, and diffusion simulated density dependent movement away from areas with high sturgeon density in areas with non-lethal habitat conditions. Mortality resulted when sturgeon were unable to leave areas with lethal temperature or dissolved oxygen conditions. Water quality was highest in winter and early spring and lowest in mid to late summer. Limiting nutrient inputs reduced the area of Brownlee Reservoir with lethal conditions for sturgeon and raised the average habitat suitability throughout the reservoir. Without movement, simulated white sturgeon survival ranged between 45 and 89%. Allowing movement raised the predicted survival of sturgeon under all conditions to above 90% as sturgeon avoided areas with low habitat quality. ?? 2003 Elsevier B.V. All rights reserved.

  11. E-Learning Quality Assurance: A Process-Oriented Lifecycle Model

    ERIC Educational Resources Information Center

    Abdous, M'hammed

    2009-01-01

    Purpose: The purpose of this paper is to propose a process-oriented lifecycle model for ensuring quality in e-learning development and delivery. As a dynamic and iterative process, quality assurance (QA) is intertwined with the e-learning development process. Design/methodology/approach: After reviewing the existing literature, particularly…

  12. 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.

  13. Hydrodynamics and water quality models applied to Sepetiba Bay

    NASA Astrophysics Data System (ADS)

    Cunha, Cynara de L. da N.; Rosman, Paulo C. C.; Ferreira, Aldo Pacheco; Carlos do Nascimento Monteiro, Teófilo

    2006-10-01

    A coupled hydrodynamic and water quality model is used to simulate the pollution in Sepetiba Bay due to sewage effluent. Sepetiba Bay has a complicated geometry and bottom topography, and is located on the Brazilian coast near Rio de Janeiro. In the simulation, the dissolved oxygen (DO) concentration and biochemical oxygen demand (BOD) are used as indicators for the presence of organic matter in the body of water, and as parameters for evaluating the environmental pollution of the eastern part of Sepetiba Bay. Effluent sources in the model are taken from DO and BOD field measurements. The simulation results are consistent with field observations and demonstrate that the model has been correctly calibrated. The model is suitable for evaluating the environmental impact of sewage effluent on Sepetiba Bay from river inflows, assessing the feasibility of different treatment schemes, and developing specific monitoring activities. This approach has general applicability for environmental assessment of complicated coastal bays.

  14. Assessment and modeling of the groundwater hydrogeochemical quality parameters via geostatistical approaches

    NASA Astrophysics Data System (ADS)

    Karami, Shawgar; Madani, Hassan; Katibeh, Homayoon; Fatehi Marj, Ahmad

    2018-03-01

    Geostatistical methods are one of the advanced techniques used for interpolation of groundwater quality data. The results obtained from geostatistics will be useful for decision makers to adopt suitable remedial measures to protect the quality of groundwater sources. Data used in this study were collected from 78 wells in Varamin plain aquifer located in southeast of Tehran, Iran, in 2013. Ordinary kriging method was used in this study to evaluate groundwater quality parameters. According to what has been mentioned in this paper, seven main quality parameters (i.e. total dissolved solids (TDS), sodium adsorption ratio (SAR), electrical conductivity (EC), sodium (Na+), total hardness (TH), chloride (Cl-) and sulfate (SO4 2-)), have been analyzed and interpreted by statistical and geostatistical methods. After data normalization by Nscore method in WinGslib software, variography as a geostatistical tool to define spatial regression was compiled and experimental variograms were plotted by GS+ software. Then, the best theoretical model was fitted to each variogram based on the minimum RSS. Cross validation method was used to determine the accuracy of the estimated data. Eventually, estimation maps of groundwater quality were prepared in WinGslib software and estimation variance map and estimation error map were presented to evaluate the quality of estimation in each estimated point. Results showed that kriging method is more accurate than the traditional interpolation methods.

  15. Modeling crop residue burning experiments and assessing the fire impacts on air quality

    EPA Science Inventory

    Prescribed burning is a common land management practice that results in ambient emissions of a variety of primary and secondary pollutants with negative health impacts. The community Multiscale Air Quality (CMAQ) model is used to conduct 2 km grid resolution simulations of prescr...

  16. Elucidating hydraulic fracturing impacts on groundwater quality using a regional geospatial statistical modeling approach.

    PubMed

    Burton, Taylour G; Rifai, Hanadi S; Hildenbrand, Zacariah L; Carlton, Doug D; Fontenot, Brian E; Schug, Kevin A

    2016-03-01

    Hydraulic fracturing operations have been viewed as the cause of certain environmental issues including groundwater contamination. The potential for hydraulic fracturing to induce contaminant pathways in groundwater is not well understood since gas wells are completed while isolating the water table and the gas-bearing reservoirs lay thousands of feet below the water table. Recent studies have attributed ground water contamination to poor well construction and leaks in the wellbore annulus due to ruptured wellbore casings. In this paper, a geospatial model of the Barnett Shale region was created using ArcGIS. The model was used for spatial analysis of groundwater quality data in order to determine if regional variations in groundwater quality, as indicated by various groundwater constituent concentrations, may be associated with the presence of hydraulically fractured gas wells in the region. The Barnett Shale reservoir pressure, completions data, and fracture treatment data were evaluated as predictors of groundwater quality change. Results indicated that elevated concentrations of certain groundwater constituents are likely related to natural gas production in the study area and that beryllium, in this formation, could be used as an indicator variable for evaluating fracturing impacts on regional groundwater quality. Results also indicated that gas well density and formation pressures correlate to change in regional water quality whereas proximity to gas wells, by itself, does not. The results also provided indirect evidence supporting the possibility that micro annular fissures serve as a pathway transporting fluids and chemicals from the fractured wellbore to the overlying groundwater aquifers. Copyright © 2015 Elsevier B.V. All rights reserved.

  17. A framework for modeling contaminant impacts on reservoir water quality

    NASA Astrophysics Data System (ADS)

    Jeznach, Lillian C.; Jones, Christina; Matthews, Thomas; Tobiason, John E.; Ahlfeld, David P.

    2016-06-01

    This study presents a framework for using hydrodynamic and water quality models to understand the fate and transport of potential contaminants in a reservoir and to develop appropriate emergency response and remedial actions. In the event of an emergency situation, prior detailed modeling efforts and scenario evaluations allow for an understanding of contaminant plume behavior, including maximum concentrations that could occur at the drinking water intake and contaminant travel time to the intake. A case study assessment of the Wachusett Reservoir, a major drinking water supply for metropolitan Boston, MA, provides an example of an application of the framework and how hydrodynamic and water quality models can be used to quantitatively and scientifically guide management in response to varieties of contaminant scenarios. The model CE-QUAL-W2 was used to investigate the water quality impacts of several hypothetical contaminant scenarios, including hypothetical fecal coliform input from a sewage overflow as well as an accidental railway spill of ammonium nitrate. Scenarios investigated the impacts of decay rates, season, and inter-reservoir transfers on contaminant arrival times and concentrations at the drinking water intake. The modeling study highlights the importance of a rapid operational response by managers to contain a contaminant spill in order to minimize the mass of contaminant that enters the water column, based on modeled reservoir hydrodynamics. The development and use of hydrodynamic and water quality models for surface drinking water sources subject to the potential for contaminant entry can provide valuable guidance for making decisions about emergency response and remediation actions.

  18. SPARROW MODELING - Enhancing Understanding of the Nation's Water Quality

    USGS Publications Warehouse

    Preston, Stephen D.; Alexander, Richard B.; Woodside, Michael D.; Hamilton, Pixie A.

    2009-01-01

    The information provided here is intended to assist water-resources managers with interpretation of the U.S. Geological Survey (USGS) SPARROW model and its products. SPARROW models can be used to explain spatial patterns in monitored stream-water quality in relation to human activities and natural processes as defined by detailed geospatial information. Previous SPARROW applications have identified the sources and transport of nutrients in the Mississippi River basin, Chesapeake Bay watershed, and other major drainages of the United States. New SPARROW models with improved accuracy and interpretability are now being developed by the USGS National Water Quality Assessment (NAWQA) Program for six major regions of the conterminous United States. These new SPARROW models are based on updated geospatial data and stream-monitoring records from local, State, and other federal agencies.

  19. INDOOR AIR QUALITY MODEL VERSION 1.0 DOCUMENTATION

    EPA Science Inventory

    The report presents a multiroom model for estimating the impact of various sources on indoor air quality (IAQ). The model is written for use on IBM-PC and compatible microcomputers. It is easy to use with a menu-driven user interface. Data are entered using a fill-in-a-form inter...

  20. A Hybrid Interval–Robust Optimization Model for Water Quality Management

    PubMed Central

    Xu, Jieyu; Li, Yongping; Huang, Guohe

    2013-01-01

    Abstract In water quality management problems, uncertainties may exist in many system components and pollution-related processes (i.e., random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval–robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements. PMID:23922495

  1. A Hybrid Interval-Robust Optimization Model for Water Quality Management.

    PubMed

    Xu, Jieyu; Li, Yongping; Huang, Guohe

    2013-05-01

    In water quality management problems, uncertainties may exist in many system components and pollution-related processes ( i.e. , random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval-robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements.

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

    USDA-ARS?s Scientific Manuscript database

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

  3. A Rotational Blended Learning Model: Enhancement and Quality Assurance

    ERIC Educational Resources Information Center

    Ghoul, Said

    2013-01-01

    Research on blended learning theory and practice is growing nowadays with a focus on the development, evaluation, and quality assurance of case studies. However, the enhancement of blended learning existing models, the specification of their online parts, and the quality assurance related specifically to them have not received enough attention.…

  4. Evaluation models and criteria of the quality of hospital websites: a systematic review study

    PubMed Central

    Jeddi, Fatemeh Rangraz; Gilasi, Hamidreza; Khademi, Sahar

    2017-01-01

    Introduction Hospital websites are important tools in establishing communication and exchanging information between patients and staff, and thus should enjoy an acceptable level of quality. The aim of this study was to identify proper models and criteria to evaluate the quality of hospital websites. Methods This research was a systematic review study. The international databases such as Science Direct, Google Scholar, PubMed, Proquest, Ovid, Elsevier, Springer, and EBSCO together with regional database such as Magiran, Scientific Information Database, Persian Journal Citation Report (PJCR) and IranMedex were searched. Suitable keywords including website, evaluation, and quality of website were used. Full text papers related to the research were included. The criteria and sub criteria of the evaluation of website quality were extracted and classified. Results To evaluate the quality of the websites, various models and criteria were presented. The WEB-Q-IM, Mile, Minerva, Seruni Luci, and Web-Qual models were the designed models. The criteria of accessibility, content and apparent features of the websites, the design procedure, the graphics applied in the website, and the page’s attractions have been mentioned in the majority of studies. Conclusion The criteria of accessibility, content, design method, security, and confidentiality of personal information are the essential criteria in the evaluation of all websites. It is suggested that the ease of use, graphics, attractiveness and other apparent properties of websites are considered as the user-friendliness sub criteria. Further, the criteria of speed and accessibility of the website should be considered as sub criterion of efficiency. When determining the evaluation criteria of the quality of websites, attention to major differences in the specific features of any website is essential. PMID:28465807

  5. Prediction models for Arabica coffee beverage quality based on aroma analyses and chemometrics.

    PubMed

    Ribeiro, J S; Augusto, F; Salva, T J G; Ferreira, M M C

    2012-11-15

    In this work, soft modeling based on chemometric analyses of coffee beverage sensory data and the chromatographic profiles of volatile roasted coffee compounds is proposed to predict the scores of acidity, bitterness, flavor, cleanliness, body, and overall quality of the coffee beverage. A partial least squares (PLS) regression method was used to construct the models. The ordered predictor selection (OPS) algorithm was applied to select the compounds for the regression model of each sensory attribute in order to take only significant chromatographic peaks into account. The prediction errors of these models, using 4 or 5 latent variables, were equal to 0.28, 0.33, 0.35, 0.33, 0.34 and 0.41, for each of the attributes and compatible with the errors of the mean scores of the experts. Thus, the results proved the feasibility of using a similar methodology in on-line or routine applications to predict the sensory quality of Brazilian Arabica coffee. Copyright © 2012 Elsevier B.V. All rights reserved.

  6. Influence of air quality model resolution on uncertainty associated with health impacts

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

    We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx), we ran a modeling episode with meteorological inputs representing conditions as they occurred during August through September 2006, and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals) to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between 2, 4 and 12 km resolution runs, but 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements of the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer) resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2 and 4 km resolution. On average, when modeling at 36 km resolution, 7 deaths per ozone month were avoided because of ozone reductions resulting from the proposed emissions reductions (95% confidence interval was 2-9). When modeling at 2, 4 or 12 km finer scale resolution, on

  7. 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

  8. [Application of entropy-weight TOPSIS model in synthetical quality evaluation of Angelica sinensis growing in Gansu Province].

    PubMed

    Gu, Zhi-rong; Wang, Ya-li; Sun, Yu-jing; Dind, Jun-xia

    2014-09-01

    To investigate the establishment and application methods of entropy-weight TOPSIS model in synthetical quality evaluation of traditional Chinese medicine with Angelica sinensis growing in Gansu Province as an example. The contents of ferulic acid, 3-butylphthalide, Z-butylidenephthalide, Z-ligustilide, linolic acid, volatile oil, and ethanol soluble extractive were used as an evaluation index set. The weights of each evaluation index were determined by information entropy method. The entropyweight TOPSIS model was established to synthetically evaluate the quality of Angelica sinensis growing in Gansu Province by Euclid closeness degree. The results based on established model were in line with the daodi meaning and the knowledge of clinical experience. The established model was simple in calculation, objective, reliable, and can be applied to synthetical quality evaluation of traditional Chinese medicine.

  9. PconsD: ultra rapid, accurate model quality assessment for protein structure prediction.

    PubMed

    Skwark, Marcin J; Elofsson, Arne

    2013-07-15

    Clustering methods are often needed for accurately assessing the quality of modeled protein structures. Recent blind evaluation of quality assessment methods in CASP10 showed that there is little difference between many different methods as far as ranking models and selecting best model are concerned. When comparing many models, the computational cost of the model comparison can become significant. Here, we present PconsD, a fast, stream-computing method for distance-driven model quality assessment that runs on consumer hardware. PconsD is at least one order of magnitude faster than other methods of comparable accuracy. The source code for PconsD is freely available at http://d.pcons.net/. Supplementary benchmarking data are also available there. arne@bioinfo.se Supplementary data are available at Bioinformatics online.

  10. A database and tool for boundary conditions for regional air quality modeling: description and evaluation

    NASA Astrophysics Data System (ADS)

    Henderson, B. H.; Akhtar, F.; Pye, H. O. T.; Napelenok, S. L.; Hutzell, W. T.

    2013-09-01

    Transported air pollutants receive increasing attention as regulations tighten and global concentrations increase. The need to represent international transport in regional air quality assessments requires improved representation of boundary concentrations. Currently available observations are too sparse vertically to provide boundary information, particularly for ozone precursors, but global simulations can be used to generate spatially and temporally varying Lateral Boundary Conditions (LBC). This study presents a public database of global simulations designed and evaluated for use as LBC for air quality models (AQMs). The database covers the contiguous United States (CONUS) for the years 2000-2010 and contains hourly varying concentrations of ozone, aerosols, and their precursors. The database is complimented by a tool for configuring the global results as inputs to regional scale models (e.g., Community Multiscale Air Quality or Comprehensive Air quality Model with extensions). This study also presents an example application based on the CONUS domain, which is evaluated against satellite retrieved ozone vertical profiles. The results show performance is largely within uncertainty estimates for the Tropospheric Emission Spectrometer (TES) with some exceptions. The major difference shows a high bias in the upper troposphere along the southern boundary in January. This publication documents the global simulation database, the tool for conversion to LBC, and the fidelity of concentrations on the boundaries. This documentation is intended to support applications that require representation of long-range transport of air pollutants.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  12. In Pursuit of Teacher Quality: Three Models of Success.

    ERIC Educational Resources Information Center

    Dandy, Evelyn; O'Dell, Sandra; McKinney, Marilyn; Perkins, Peggy G.; Miller, Susan Peterson; Reiman, Alan; Peace, Sandra DeAngelis; Williams, Doris Terry; Duncan, JoAnn Hines

    This document is comprised of three papers by various authors, summarizing three different models of programs that successfully promote teacher quality that were introduced at the National Conference on Teacher Quality in January 2000, hosted by the U.S. Department of Education. The first program described, the Pathways to Teaching Program of…

  13. Hybrid Air Quality Modeling Approach For Use in the Near ...

    EPA Pesticide Factsheets

    The Near-road EXposures to Urban air pollutant Study (NEXUS) investigated whether children with asthma living in close proximity to major roadways in Detroit, MI, (particularly near roadways with high diesel traffic) have greater health impacts associated with exposure to air pollutants than those living farther away. A major challenge in such health and exposure studies is the lack of information regarding pollutant exposure characterization. Air quality modeling can provide spatially and temporally varying exposure estimates for examining relationships between traffic-related air pollutants and adverse health outcomes. This paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associated with local variations of emissions and meteorology, were estimated using a combination of the AERMOD and R-LINE dispersion models, local emission source information from the National Emissions Inventory, detailed road network locations and traffic activity, and meteorological data from the Detroit City Airport. The regional background contribution was estimated using a combination of the Community Multiscale Air Quality (CMAQ) model and the Space/Time Ordinary Kriging (STOK) model. To capture the near-road pollutant gradients, refined “mini-grids” of model recep

  14. Influence of raw milk quality on processed dairy products: How do raw milk quality test results relate to product quality and yield?

    PubMed

    Murphy, Steven C; Martin, Nicole H; Barbano, David M; Wiedmann, Martin

    2016-12-01

    This article provides an overview of the influence of raw milk quality on the quality of processed dairy products and offers a perspective on the merits of investing in quality. Dairy farmers are frequently offered monetary premium incentives to provide high-quality milk to processors. These incentives are most often based on raw milk somatic cell and bacteria count levels well below the regulatory public health-based limits. Justification for these incentive payments can be based on improved processed product quality and manufacturing efficiencies that provide the processor with a return on their investment for high-quality raw milk. In some cases, this return on investment is difficult to measure. Raw milks with high levels of somatic cells and bacteria are associated with increased enzyme activity that can result in product defects. Use of raw milk with somatic cell counts >100,000cells/mL has been shown to reduce cheese yields, and higher levels, generally >400,000 cells/mL, have been associated with textural and flavor defects in cheese and other products. Although most research indicates that fairly high total bacteria counts (>1,000,000 cfu/mL) in raw milk are needed to cause defects in most processed dairy products, receiving high-quality milk from the farm allows some flexibility for handling raw milk, which can increase efficiencies and reduce the risk of raw milk reaching bacterial levels of concern. Monitoring total bacterial numbers in regard to raw milk quality is imperative, but determining levels of specific types of bacteria present has gained increasing importance. For example, spores of certain spore-forming bacteria present in raw milk at very low levels (e.g., <1/mL) can survive pasteurization and grow in milk and cheese products to levels that result in defects. With the exception of meeting product specifications often required for milk powders, testing for specific spore-forming groups is currently not used in quality incentive programs in

  15. 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

  16. Daily air quality index forecasting with hybrid models: A case in China.

    PubMed

    Zhu, Suling; Lian, Xiuyuan; Liu, Haixia; Hu, Jianming; Wang, Yuanyuan; Che, Jinxing

    2017-12-01

    Air quality is closely related to quality of life. Air pollution forecasting plays a vital role in air pollution warnings and controlling. However, it is difficult to attain accurate forecasts for air pollution indexes because the original data are non-stationary and chaotic. The existing forecasting methods, such as multiple linear models, autoregressive integrated moving average (ARIMA) and support vector regression (SVR), cannot fully capture the information from series of pollution indexes. Therefore, new effective techniques need to be proposed to forecast air pollution indexes. The main purpose of this research is to develop effective forecasting models for regional air quality indexes (AQI) to address the problems above and enhance forecasting accuracy. Therefore, two hybrid models (EMD-SVR-Hybrid and EMD-IMFs-Hybrid) are proposed to forecast AQI data. The main steps of the EMD-SVR-Hybrid model are as follows: the data preprocessing technique EMD (empirical mode decomposition) is utilized to sift the original AQI data to obtain one group of smoother IMFs (intrinsic mode functions) and a noise series, where the IMFs contain the important information (level, fluctuations and others) from the original AQI series. LS-SVR is applied to forecast the sum of the IMFs, and then, S-ARIMA (seasonal ARIMA) is employed to forecast the residual sequence of LS-SVR. In addition, EMD-IMFs-Hybrid first separately forecasts the IMFs via statistical models and sums the forecasting results of the IMFs as EMD-IMFs. Then, S-ARIMA is employed to forecast the residuals of EMD-IMFs. To certify the proposed hybrid model, AQI data from June 2014 to August 2015 collected from Xingtai in China are utilized as a test case to investigate the empirical research. In terms of some of the forecasting assessment measures, the AQI forecasting results of Xingtai show that the two proposed hybrid models are superior to ARIMA, SVR, GRNN, EMD-GRNN, Wavelet-GRNN and Wavelet-SVR. Therefore, the

  17. 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.

  18. Differences in aquatic habitat quality as an impact of one- and two-dimensional hydrodynamic model simulated flow variables

    NASA Astrophysics Data System (ADS)

    Benjankar, R. M.; Sohrabi, M.; Tonina, D.; McKean, J. A.

    2013-12-01

    Aquatic habitat models utilize flow variables which may be predicted with one-dimensional (1D) or two-dimensional (2D) hydrodynamic models to simulate aquatic habitat quality. Studies focusing on the effects of hydrodynamic model dimensionality on predicted aquatic habitat quality are limited. Here we present the analysis of the impact of flow variables predicted with 1D and 2D hydrodynamic models on simulated spatial distribution of habitat quality and Weighted Usable Area (WUA) for fall-spawning Chinook salmon. Our study focuses on three river systems located in central Idaho (USA), which are a straight and pool-riffle reach (South Fork Boise River), small pool-riffle sinuous streams in a large meadow (Bear Valley Creek) and a steep-confined plane-bed stream with occasional deep forced pools (Deadwood River). We consider low and high flows in simple and complex morphologic reaches. Results show that 1D and 2D modeling approaches have effects on both the spatial distribution of the habitat and WUA for both discharge scenarios, but we did not find noticeable differences between complex and simple reaches. In general, the differences in WUA were small, but depended on stream type. Nevertheless, spatially distributed habitat quality difference is considerable in all streams. The steep-confined plane bed stream had larger differences between aquatic habitat quality defined with 1D and 2D flow models compared to results for streams with well defined macro-topographies, such as pool-riffle bed forms. KEY WORDS: one- and two-dimensional hydrodynamic models, habitat modeling, weighted usable area (WUA), hydraulic habitat suitability, high and low discharges, simple and complex reaches

  19. Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality

    NASA Astrophysics Data System (ADS)

    Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.

    2017-12-01

    Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.

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

    NASA Astrophysics Data System (ADS)

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

    2017-07-01

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

  1. Level of quality management in the Municipal Sports Services, contrast trough EFQM Excellence Model.

    PubMed

    Martínez-Moreno, Alfonso; Díaz Suárez, Arturo

    2016-01-01

    The quality management in the Municipal Sports Services is embedded in the servuction provided to the citizens, which are their internal customers who determine the quality improvement ensuring competitiveness with excellence criteria. The Model of the European Foundation for Quality Management enables the evaluation of organization progress towards achieving quality goals, from a structured, measurable and comparable methodology. The aim is to carry out a diagnosis of the level of implementation of quality in the Municipal Sports Services of the Region of Murcia, Spain. The sample of 287 workers of 30 sports services gets a high level of reliability at all scales, with a coefficient of variation of .985 (range .810-.943). The score in the criteria of Policy and Strategy, People Management, Alliances and Resources, Processes and People Results were significantly higher (p < .05) in the Municipalities with more than 25,000 inhabitants when compared with those less than 10,000 and with those from 10,000 to 25,000 inhabitants obtaining global ratings of 571 points, those less than 10,000, 590 points those from 10,000 to 25,000 and those higher than 25,000 reach 636, having a good level of quality in relation to the scale that determines the model.

  2. Optical aberrations, retinal image quality and eye growth: Experimentation and modeling

    NASA Astrophysics Data System (ADS)

    Tian, Yibin

    2007-12-01

    Retinal image quality is important for normal eye growth. Optical aberrations are of interest for two reasons: first, they degrade retinal images; second, they might provide some cues to defocus. Higher than normal ocular aberrations have been previously associated with human myopia. However, these studies were cross-sectional in design, and only reported aberrations in terms of root mean square (RMS) errors of Zernike coefficients, a poor metric of optical quality. This dissertation presents results from investigations of ocular optical aberrations, retinal image quality and eye growth in chicks and humans. A number of techniques were utilized, including Shack-Hartmann aberrometry, high-frequency A-scan ultrasonography, ciliary nerve section (CNX), photorefractive keratectomy (PRK) as well as computer simulations and modeling. A technique to extract light scatter information from Shack-Hartmann images was also developed. The main findings of the dissertation are summarized below. In young chicks, most ocular aberrations decreased with growth in both normal and CNX eyes, and there were diurnal fluctuations in some aberrations. Modeling suggested active reduction in higher order aberrations (HOAs) during early development. Although CNX eyes manifested greater than normal HOAs, they showed near normal growth. Retinal image degradation varied greatly among individual eyes post-PRK in young chicks. Including light scatter information into analyses of retinal image quality better estimated the latter. Albino eyes showed more severe retinal image degradation than normal eyes, due to increased optical aberrations and light scatter, but their growth was similar to those of normal eyes, implying that they are relatively insensitive to retina image quality. Although the above results questioned the influence of optical aberrations on early ocular growth, some optical quality metrics, derived from optical aberrations data, could predict how much the eyes of young chicks

  3. Quality assurance paradigms for artificial intelligence in modelling and simulation

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

    Oren, T.I.

    1987-04-01

    New classes of quality assurance concepts and techniques are required for the advanced knowledge-processing paradigms (such as artificial intelligence, expert systems, or knowledge-based systems) and the complex problems that only simulative systems can cope with. A systematization of quality assurance problems as well as examples are given to traditional and cognizant quality assurance techniques in traditional and cognizant modelling and simulation.

  4. Systems Modeling to Improve River, Riparian, and Wetland Habitat Quality and Area

    NASA Astrophysics Data System (ADS)

    Alafifi, A.

    2016-12-01

    The suitability of watershed habitat to support the livelihood of its biota primarily depends on managing flow. Ecological restoration requires finding opportunities to reallocate available water in a watershed to increase ecological benefits and maintain other beneficial uses. We present the Watershed Area of Suitable Habitat (WASH) systems model that recommends reservoir releases, streamflows, and water allocations throughout a watershed to maximize the ecosystem habitat quality. WASH embeds and aggregates area-weighted metrics for aquatic, floodplain, and wetland habitat components as an ecosystem objective to maximize, while maintaining water deliveries for domestic and agricultural uses, mass balance, and available budget for restoration actions. The metrics add spatial and temporal functionality and area coverage to traditional habitat quality indexes and can accommodate multiple species of concern. We apply the WASH model to the Utah portion of the Bear River watershed which includes 8 demand sites, 5 reservoirs and 37 nodes between the Utah-Idaho state line and the Great Salt Lake. We recommend water allocations to improve current conservation efforts and show tradeoffs between human and ecosystem uses of water. WASH results are displayed on an open-source web mapping application that allows stakeholders to access, visualize, and interact with the model data and results and compare current and model-recommended operations. Results show that the Bear River is largely developed and appropriated for human water uses. However, increasing reservoirs winter and early spring releases and minimizing late spring spill volumes can significantly improve habitat quality without harming agricultural or urban water users. The spatial and temporal reallocation of spring spills to environmental uses creates additional 70 thousand acres of suitable habitat in the watershed without harming human users. WASH also quantifies the potential environmental gains and losses from

  5. A systematic review of quality and cost-effectiveness derived from Markov models evaluating smoking cessation interventions in patients with chronic obstructive pulmonary disease.

    PubMed

    Kirsch, Florian

    2015-04-01

    Smoking cessation is the only strategy that has shown a lasting reduction in the decline of lung function in patients with chronic obstructive pulmonary disease. This study aims to evaluate the cost-effectiveness of smoking cessation interventions in patients with chronic obstructive pulmonary disease, to assess the quality of the Markov models and to estimate the consequences of model structure and input data on cost-effectiveness. A systematic literature search was conducted in PubMed, Embase, BusinessSourceComplete and Econlit on June 11, 2014. Data were extracted, and costs were inflated. Model quality was evaluated by a quality appraisal, and results were interpreted. Ten studies met the inclusion criteria. The results varied widely from cost savings to additional costs of €17,004 per quality adjusted life year. The models scored best in the category structure, followed by data and consistency. The quality of the models seems to rise over time, and regarding the results there is no economic reason to refuse the reimbursement of any smoking cessation intervention.

  6. Engineering Glass Passivation Layers -Model Results

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

    Skorski, Daniel C.; Ryan, Joseph V.; Strachan, Denis M.

    2011-08-08

    The immobilization of radioactive waste into glass waste forms is a baseline process of nuclear waste management not only in the United States, but worldwide. The rate of radionuclide release from these glasses is a critical measure of the quality of the waste form. Over long-term tests and using extrapolations of ancient analogues, it has been shown that well designed glasses exhibit a dissolution rate that quickly decreases to a slow residual rate for the lifetime of the glass. The mechanistic cause of this decreased corrosion rate is a subject of debate, with one of the major theories suggesting thatmore » the decrease is caused by the formation of corrosion products in such a manner as to present a diffusion barrier on the surface of the glass. Although there is much evidence of this type of mechanism, there has been no attempt to engineer the effect to maximize the passivating qualities of the corrosion products. This study represents the first attempt to engineer the creation of passivating phases on the surface of glasses. Our approach utilizes interactions between the dissolving glass and elements from the disposal environment to create impermeable capping layers. By drawing from other corrosion studies in areas where passivation layers have been successfully engineered to protect the bulk material, we present here a report on mineral phases that are likely have a morphological tendency to encrust the surface of the glass. Our modeling has focused on using the AFCI glass system in a carbonate, sulfate, and phosphate rich environment. We evaluate the minerals predicted to form to determine the likelihood of the formation of a protective layer on the surface of the glass. We have also modeled individual ions in solutions vs. pH and the addition of aluminum and silicon. These results allow us to understand the pH and ion concentration dependence of mineral formation. We have determined that iron minerals are likely to form a complete incrustation layer and

  7. 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...

  8. Sci-Fri AM: Quality, Safety, and Professional Issues 01: CPQR Technical Quality Control Suite Development including Quality Control Workload Results

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

    Malkoske, Kyle; Nielsen, Michelle; Brown, Erika

    A close partnership between the Canadian Partnership for Quality Radiotherapy (CPQR) and the Canadian Organization of Medical Physicist’s (COMP) Quality Assurance and Radiation Safety Advisory Committee (QARSAC) has resulted in the development of a suite of Technical Quality Control (TQC) Guidelines for radiation treatment equipment, that outline specific performance objectives and criteria that equipment should meet in order to assure an acceptable level of radiation treatment quality. The framework includes consolidation of existing guidelines and/or literature by expert reviewers, structured stages of public review, external field-testing and ratification by COMP. The adopted framework for the development and maintenance of themore » TQCs ensures the guidelines incorporate input from the medical physics community during development, measures the workload required to perform the QC tests outlined in each TQC, and remain relevant (i.e. “living documents”) through subsequent planned reviews and updates. This presentation will show the Multi-Leaf Linear Accelerator document as an example of how feedback and cross-national work to achieve a robust guidance document. During field-testing, each technology was tested at multiple centres in a variety of clinic environments. As part of the defined feedback, workload data was captured. This lead to average time associated with testing as defined in each TQC document. As a result, for a medium-sized centre comprising 6 linear accelerators and a comprehensive brachytherapy program, we evaluate the physics workload to 1.5 full-time equivalent physicist per year to complete all QC tests listed in this suite.« less

  9. New Methods for Air Quality Model Evaluation with Satellite Data

    NASA Astrophysics Data System (ADS)

    Holloway, T.; Harkey, M.

    2015-12-01

    Despite major advances in the ability of satellites to detect gases and aerosols in the atmosphere, there remains significant, untapped potential to apply space-based data to air quality regulatory applications. Here, we showcase research findings geared toward increasing the relevance of satellite data to support operational air quality management, focused on model evaluation. Particular emphasis is given to nitrogen dioxide (NO2) and formaldehyde (HCHO) from the Ozone Monitoring Instrument aboard the NASA Aura satellite, and evaluation of simulations from the EPA Community Multiscale Air Quality (CMAQ) model. This work is part of the NASA Air Quality Applied Sciences Team (AQAST), and is motivated by ongoing dialog with state and federal air quality management agencies. We present the response of satellite-derived NO2 to meteorological conditions, satellite-derived HCHO:NO2 ratios as an indicator of ozone production regime, and the ability of models to capture these sensitivities over the continental U.S. In the case of NO2-weather sensitivities, we find boundary layer height, wind speed, temperature, and relative humidity to be the most important variables in determining near-surface NO2 variability. CMAQ agreed with relationships observed in satellite data, as well as in ground-based data, over most regions. However, we find that the southwest U.S. is a problem area for CMAQ, where modeled NO2 responses to insolation, boundary layer height, and other variables are at odds with the observations. Our analyses utilize a software developed by our team, the Wisconsin Horizontal Interpolation Program for Satellites (WHIPS): a free, open-source program designed to make satellite-derived air quality data more usable. WHIPS interpolates level 2 satellite retrievals onto a user-defined fixed grid, in effect creating custom-gridded level 3 satellite product. Currently, WHIPS can process the following data products: OMI NO2 (NASA retrieval); OMI NO2 (KNMI retrieval); OMI

  10. A model for rotorcraft flying qualities studies

    NASA Technical Reports Server (NTRS)

    Mittal, Manoj; Costello, Mark F.

    1993-01-01

    This paper outlines the development of a mathematical model that is expected to be useful for rotorcraft flying qualities research. A computer model is presented that can be applied to a range of different rotorcraft configurations. The algorithm computes vehicle trim and a linear state-space model of the aircraft. The trim algorithm uses non linear optimization theory to solve the nonlinear algebraic trim equations. The linear aircraft equations consist of an airframe model and a flight control system dynamic model. The airframe model includes coupled rotor and fuselage rigid body dynamics and aerodynamics. The aerodynamic model for the rotors utilizes blade element theory and a three state dynamic inflow model. Aerodynamics of the fuselage and fuselage empennages are included. The linear state-space description for the flight control system is developed using standard block diagram data.

  11. Systematic review of health-related quality of life models

    PubMed Central

    2012-01-01

    Background A systematic literature review was conducted to (a) identify the most frequently used health-related quality of life (HRQOL) models and (b) critique those models. Methods Online search engines were queried using pre-determined inclusion and exclusion criteria. We reviewed titles, abstracts, and then full-text articles for their relevance to this review. Then the most commonly used models were identified, reviewed in tables, and critiqued using published criteria. Results Of 1,602 titles identified, 100 articles from 21 countries met the inclusion criteria. The most frequently used HRQOL models were: Wilson and Cleary (16%), Ferrans and colleagues (4%), or World Health Organization (WHO) (5%). Ferrans and colleagues’ model was a revision of Wilson and Cleary’s model and appeared to have the greatest potential to guide future HRQOL research and practice. Conclusions Recommendations are for researchers to use one of the three common HRQOL models unless there are compelling and clearly delineated reasons for creating new models. Disease-specific models can be derived from one of the three commonly used HRQOL models. We recommend Ferrans and colleagues’ model because they added individual and environmental characteristics to the popular Wilson and Cleary model to better explain HRQOL. Using a common HRQOL model across studies will promote a coherent body of evidence that will more quickly advance the science in the area of HRQOL. PMID:23158687

  12. MEGAPOLI: concept and first results of multi-scale modelling of megacity impacts

    NASA Astrophysics Data System (ADS)

    Baklanov, A. A.; Lawrence, M.; Pandis, S.

    2009-09-01

    major city, Paris, performing detailed analysis for 12 megacities with existing air quality datasets and investigate the effects of all megacities on climate and global atmospheric chemistry. The project focuses on the multi-scale modelling of interacting meteorology and air quality, spanning the range from emissions to air quality, effects on climate, and feedbacks and mitigation potentials. Our hypothesis is that megacities around the world have an impact on air quality not only locally, but also regionally and globally and therefore can also influence the climate of our planet. Some of the links between megacities, air quality and climate are reasonably well-understood. However, a complete quantitative picture of these interactions is clearly missing. Understanding and quantifying these missing links is the focus of MEGAPOLI. The current status and modeling results after the first project year on examples of Paris and other European megacities are discussed.

  13. Application of water quality models to rivers in Johor

    NASA Astrophysics Data System (ADS)

    Chii, Puah Lih; Rahman, Haliza Abd.

    2017-08-01

    River pollution is one the most common hazard in many countries in the world, which includes Malaysia. Many rivers have been polluted because of the rapid growth in industrialization to support the country's growing population and economy. Domestic and industrial sewage, agricultural wastes have polluted the rivers and will affect the water quality. Based on the Malaysia Environment Quality Report 2007, the Department of Environment (DOE) has described that one of the major pollutants is Biochemical Oxygen Demand (BOD). Data from DOE in 2004, based on BOD, 18 river basins were classified polluted, 37 river basins were slightly polluted and 65 river basins were in clean condition. In this paper, two models are fitted the data of rivers in Johor state namely Streeter-Phelps model and nonlinear regression (NLR) model. The BOD concentration data for the two rivers in Johor state from year 1981 to year 1990 is analyzed. To estimate the parameters for the Streeter-Phelps model and NLR model, this study focuses on the weighted least squares and Gauss-Newton method respectively. Based on the value of Mean Square Error, NLR model is a better model compared to Streeter-Phelps model.

  14. Examining issues with water quality model configuration

    USDA-ARS?s Scientific Manuscript database

    Complex watershed–scale, water quality models require a considerable amount of data in order to be properly configured, especially in view of the scarcity of data in many regions due to temporal and economic constraints. In this study, we examined two different input issues incurred while building ...

  15. Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon

    DTIC Science & Technology

    2016-07-01

    was used to drive the transport and water quality kinetics for the simulation of 2007–2009. The sand berm, which controlled the opening/closure of...TECHNICAL REPORT 3015 July 2016 Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei...Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei-Fang Wang Chuck Katz Ripan Barua SSC Pacific James

  16. Evaluation of the Community Multiscale Air Quality (CMAQ) Model Version 5.2

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

  17. Evaluation of the Community Multi-scale Air Quality Model Version 5.2

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

  18. Development and application of air quality models at the U.S. EPA

    EPA Science Inventory

    Overview of the development and application of air quality models at the U.S. EPA, particularly focused on the development and application of the Community Multiscale Air Quality (CMAQ) model developed within the Computation Exposure Division (CED) of the National Exposure Resear...

  19. The Air Quality Model Evaluation International Initiative ...

    EPA Pesticide Factsheets

    This presentation provides an overview of the Air Quality Model Evaluation International Initiative (AQMEII). It contains a synopsis of the three phases of AQMEII, including objectives, logistics, and timelines. It also provides a number of examples of analyses conducted through AQMEII with a particular focus on past and future analyses of deposition. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.

  20. Nosocomial Infection Reduction in VLBW Infants With a Statewide Quality-Improvement Model

    PubMed Central

    Powers, Richard J.; Pettit, Janet S.; Lee, Henry C.; Boscardin, W. John; Ahmad Subeh, Mohammad; Gould, Jeffrey B.

    2011-01-01

    OBJECTIVE: To evaluate the effectiveness of the California Perinatal Quality Care Collaborative quality-improvement model using a toolkit supplemented by workshops and Web casts in decreasing nosocomial infections in very low birth weight infants. DESIGN: This was a retrospective cohort study of continuous California Perinatal Quality Care Collaborative members' data during the years 2002–2006. The primary dependent variable was nosocomial infection, defined as a late bacterial or coagulase-negative staphylococcal infection diagnosed after the age of 3 days by positive blood/cerebro-spinal fluid culture(s) and clinical criteria. The primary independent variable of interest was voluntary attendance at the toolkit's introductory event, a direct indicator that at least 1 member of an NICU team had been personally exposed to the toolkit's features rather than being only notified of its availability. The intervention's effects were assessed using a multivariable logistic regression model that risk adjusted for selected demographic and clinical factors. RESULTS: During the study period, 7733 eligible very low birth weight infants were born in 27 quality-improvement participant hospitals and 4512 very low birth weight infants were born in 27 non–quality-improvement participant hospitals. For the entire cohort, the rate of nosocomial infection decreased from 16.9% in 2002 to 14.5% in 2006. For infants admitted to NICUs participating in at least 1 quality-improvement event, there was an associated decreased risk of nosocomial infection (odds ratio: 0.81 [95% confidence interval: 0.68–0.96]) compared with those admitted to nonparticipating hospitals. CONCLUSIONS: The structured intervention approach to quality improvement in the NICU setting, using a toolkit along with attendance at a workshop and/or Web cast, is an effective means by which to improve care outcomes. PMID:21339273

  1. Combined comfort model of thermal comfort and air quality on buses in Hong Kong.

    PubMed

    Shek, Ka Wing; Chan, Wai Tin

    2008-01-25

    Air-conditioning settings are important factors in controlling the comfort of passengers on buses. The local bus operators control in-bus air quality and thermal environment by conforming to the prescribed levels stated in published standards. As a result, the settings are merely adjusted to fulfill the standards, rather than to satisfy the passengers' thermal comfort and air quality. Such "standard-oriented" practices are not appropriate; the passengers' preferences and satisfaction should be emphasized instead. Thus a "comfort-oriented" philosophy should be implemented to achieve a comfortable in-bus commuting environment. In this study, the achievement of a comfortable in-bus environment was examined with emphasis on thermal comfort and air quality. Both the measurement of physical parameters and subjective questionnaire surveys were conducted to collect practical in-bus thermal and air parameters data, as well as subjective satisfaction and sensation votes from the passengers. By analyzing the correlation between the objective and subjective data, a combined comfort models were developed. The models helped in evaluating the percentage of dissatisfaction under various combinations of passengers' sensation votes towards thermal comfort and air quality. An effective approach integrated the combined comfort model, hardware and software systems and the bus air-conditioning system could effectively control the transient in-bus environment. By processing and analyzing the data from the continuous monitoring system with the combined comfort model, air-conditioning setting adjustment commands could be determined and delivered to the hardware. This system adjusted air-conditioning settings depending on real-time commands along the bus journey. Therefore, a comfortable in-bus air quality and thermal environment could be achieved and efficiently maintained along the bus journey despite dynamic outdoor influences. Moreover, this model can help optimize air

  2. DESCRIPTION OF ATMOSPHERIC TRANSPORT PROCESSES IN EULERIAN AIR QUALITY MODELS

    EPA Science Inventory

    Key differences among many types of air quality models are the way atmospheric advection and turbulent diffusion processes are treated. Gaussian models use analytical solutions of the advection-diffusion equations. Lagrangian models use a hypothetical air parcel concept effecti...

  3. Quality prediction modeling for sintered ores based on mechanism models of sintering and extreme learning machine based error compensation

    NASA Astrophysics Data System (ADS)

    Tiebin, Wu; Yunlian, Liu; Xinjun, Li; Yi, Yu; Bin, Zhang

    2018-06-01

    Aiming at the difficulty in quality prediction of sintered ores, a hybrid prediction model is established based on mechanism models of sintering and time-weighted error compensation on the basis of the extreme learning machine (ELM). At first, mechanism models of drum index, total iron, and alkalinity are constructed according to the chemical reaction mechanism and conservation of matter in the sintering process. As the process is simplified in the mechanism models, these models are not able to describe high nonlinearity. Therefore, errors are inevitable. For this reason, the time-weighted ELM based error compensation model is established. Simulation results verify that the hybrid model has a high accuracy and can meet the requirement for industrial applications.

  4. Root zone water quality model (RZWQM2): Model use, calibration and validation

    USGS Publications Warehouse

    Ma, Liwang; Ahuja, Lajpat; Nolan, B.T.; Malone, Robert; Trout, Thomas; Qi, Z.

    2012-01-01

    The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model, it has many desirable features for the modeling community. This article outlines the principles of calibrating the model component by component with one or more datasets and validating the model with independent datasets. Users should consult the RZWQM2 user manual distributed along with the model and a more detailed protocol on how to calibrate RZWQM2 provided in a book chapter. Two case studies (or examples) are included in this article. One is from an irrigated maize study in Colorado to illustrate the use of field and laboratory measured soil hydraulic properties on simulated soil water and crop production. It also demonstrates the interaction between soil and plant parameters in simulated plant responses to water stresses. The other is from a maize-soybean rotation study in Iowa to show a manual calibration of the model for crop yield, soil water, and N leaching in tile-drained soils. Although the commonly used trial-and-error calibration method works well for experienced users, as shown in the second example, an automated calibration procedure is more objective, as shown in the first example. Furthermore, the incorporation of the Parameter Estimation Software (PEST) into RZWQM2 made the calibration of the model more efficient than a grid (ordered) search of model parameters. In addition, PEST provides sensitivity and uncertainty analyses that should help users in selecting the right parameters to calibrate.

  5. A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model

    NASA Astrophysics Data System (ADS)

    Abbaspour, K. C.; Rouholahnejad, E.; Vaghefi, S.; Srinivasan, R.; Yang, H.; Kløve, B.

    2015-05-01

    A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.

  6. 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.

  7. 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.

  8. Application of Water Quality Model of Jordan River to Evaluate Climate Change Effects on Eutrophication

    NASA Astrophysics Data System (ADS)

    Van Grouw, B.

    2016-12-01

    The Jordan River is a 51 mile long freshwater stream in Utah that provides drinking water to more than 50% of Utah's population. The various point and nonpoint sources introduce an excess of nutrients into the river. This excess induces eutrophication that results in an inhabitable environment for aquatic life is expected to be exacerbated due to climate change. Adaptive measures must be evaluated based on predictions of climate variation impacts on eutrophication and ecosystem processes in the Jordan River. A Water Quality Assessment Simulation Program (WASP) model was created to analyze the data results acquired from a Total Maximum Daily Load (TMDL) study conducted on the Jordan River. Eutrophication is modeled based on levels of phosphates and nitrates from point and nonpoint sources, temperature, and solar radiation. It will simulate the growth of phytoplankton and periphyton in the river. This model will be applied to assess how water quality in the Jordan River is affected by variations in timing and intensity of spring snowmelt and runoff during drought in the valley and the resulting effects on eutrophication in the river.

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

  11. The project MOHAVE tracer study: study design, data quality, and overview of results

    NASA Astrophysics Data System (ADS)

    Green, Mark C.

    In the winter and summer of 1992, atmospheric tracer studies were conducted in support of project MOHAVE, a visibility study in the southwestern United States. The primary goal of project MOHAVE is to determine the effects of the Mohave power plant and other sources upon visibility at Grand Canyon National Park. Perfluorocarbon tracers (PFTs) were released from the Mohave power plant and other locations and monitored at about 30 sites. The tracer data are being used for source attribution analysis and for evaluation of transport and dispersion models and receptor models. Collocated measurements showed the tracer data to be of high quality and suitable for source attribution analysis and model evaluation. The results showed strong influences of channeling by the Colorado River canyon during both winter and summer. Flow from the Mohave power plant was usually to the south, away from the Grand Canyon in winter and to the northeast, toward the Grand Canyon in summer. Tracer released at Lake Powell in winter was found to often travel downstream through the entire length of the Grand Canyon. Data from summer tracer releases in southern California demonstrated the existence of a convergence zone in the western Mohave Desert.

  12. Hydrologic and water quality terminology as applied to modeling

    USDA-ARS?s Scientific Manuscript database

    A survey of literature and examination in particular of terminology use in a previous special collection of modeling calibration and validation papers has been conducted to arrive at a list of consistent terminology recommended for writing about hydrologic and water quality model calibration and val...

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

    USDA-ARS?s Scientific Manuscript database

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

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

    PubMed

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

    2017-02-01

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

  15. Influence of air quality model resolution on uncertainty associated with health impacts

    NASA Astrophysics Data System (ADS)

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

    2012-10-01

    We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx), we ran a modeling episode with meteorological inputs simulating conditions as they occurred during August through September 2006 (a period representative of conditions leading to high ozone), and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals) to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between the 2, 4 and 12 km resolution runs, but the 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements motivated by Executive Order 12866 as it applies to the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer) resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2, 4 or 12 km resolution. On average, when modeling at 36 km resolution, an estimated 5 deaths per week during the May through September ozone season are avoided

  16. [Analysis of the results of the SEIMC External Quality Control Program. Year 2013].

    PubMed

    de Gopegui Bordes, Enrique Ruiz; Orta Mira, Nieves; Del Remedio Guna Serrano, M; Medina González, Rafael; Rosario Ovies, María; Poveda, Marta; Gimeno Cardona, Concepción

    2015-07-01

    The External Quality Control Program of the Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC) include controls for bacteriology, serology, mycology, parasitology, mycobacteria, virology, molecular microbiology and HIV-1, HCV and HBV viral loads. This manuscript presents the analysis of results obtained of the participants from the 2013 SEIMC External Quality Control Programme, except viral loads controls, that they are summarized in a manuscript abroad. As a whole, the results obtained in 2013 confirm the excellent skill and good technical standards found in previous editions. However, erroneous results can be obtained in any laboratory and in clinically relevant determinations. Once again, the results of this program highlighted the need to implement both internal and external controls in order to assure the maximal quality of the microbiological tests. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

  17. Quality assessment of Digital Elevation Model (DEM) in view of the Altiplano hydrological modeling

    NASA Astrophysics Data System (ADS)

    Satgé, F.; Arsen, A.; Bonnet, M.; Timouk, F.; Calmant, S.; Pilco, R.; Molina, J.; Lavado, W.; Crétaux, J.; HASM

    2013-05-01

    Topography is crucial data input for hydrological modeling but in many regions of the world, the only way to characterize topography is the use of satellite-based Digital Elevation Models (DEM). In some regions, the quality of these DEMs remains poor and induces modeling errors that may or not be compensated by model parameters tuning. In such regions, the evaluation of these data uncertainties is an important step in the modeling procedure. In this study, which focuses on the Altiplano region, we present the evaluation of the two freely available DEM. The shuttle radar topographic mission (SRTM), a product of the National Aeronautics and Space Administration (NASA) and the Advanced Space Born Thermal Emission and Reflection Global Digital Elevation Map (ASTER GDEM), data provided by the Ministry of Economy, Trade and Industry of Japan (MESI) in collaboration with the NASA, are widely used. While the first represents a resolution of 3 arc seconds (90m) the latter is 1 arc second (30m). In order to select the most reliable DEM, we compared the DEM elevation with high qualities control points elevation. Because of its large spatial coverture (track spaced of 30 km with a measure of each 172 m) and its high vertical accuracy which is less than 15 cm in good weather conditions, the Geoscience Laser Altimeter System (GLAS) on board on the Ice, Cloud and Land elevation Satellite of NASA (ICESat) represent the better solution to establish a high quality elevation database. After a quality check, more than 150 000 ICESat/GLAS measurements are suitable in terms of accuracy for the Altiplano watershed. This data base has been used to evaluate the vertical accuracy for each DEM. Regarding to the full spatial coverture; the comparison has been done for both, all kind of land coverture, range altitude and mean slope.

  18. An integrated bi-level optimization model for air quality management of Beijing's energy system under uncertainty.

    PubMed

    Jin, S W; Li, Y P; Nie, S

    2018-05-15

    In this study, an interval chance-constrained bi-level programming (ICBP) method is developed for air quality management of municipal energy system under uncertainty. ICBP can deal with uncertainties presented as interval values and probability distributions as well as examine the risk of violating constraints. Besides, a leader-follower decision strategy is incorporated into the optimization process where two decision makers with different goals and preferences are involved. To solve the proposed model, a bi-level interactive algorithm based on satisfactory degree is introduced into the decision-making processes. Then, an ICBP based energy and environmental systems (ICBP-EES) model is formulated for Beijing, in which air quality index (AQI) is used for evaluating the integrated air quality of multiple pollutants. Result analysis can help different stakeholders adjust their tolerances to achieve the overall satisfaction of EES planning for the study city. Results reveal that natural gas is the main source for electricity-generation and heating that could lead to a potentially increment of imported energy for Beijing in future. Results also disclose that PM 10 is the major contributor to AQI. These findings can help decision makers to identify desired alternatives for EES planning and provide useful information for regional air quality management under uncertainty. Copyright © 2018 Elsevier B.V. All rights reserved.

  19. Test of the efficiency of three storm water quality models with a rich set of data.

    PubMed

    Ahyerre, M; Henry, F O; Gogien, F; Chabanel, M; Zug, M; Renaudet, D

    2005-01-01

    The objective of this article is to test the efficiency of three different Storm Water Quality Model (SWQM) on the same data set (34 rain events, SS measurements) sampled on a 42 ha watershed in the center of Paris. The models have been calibrated at the scale of the rain event. Considering the mass of pollution calculated per event, the results on the models are satisfactory but that they are in the same order of magnitude as the simple hydraulic approach associated to a constant concentration. In a second time, the mass of pollutant at the outlet of the catchment at the global scale of the 34 events has been calculated. This approach shows that the simple hydraulic calculations gives better results than SWQM. Finally, the pollutographs are analysed, showing that storm water quality models are interesting tools to represent the shape of the pollutographs, and the dynamics of the phenomenon which can be useful in some projects for managers.

  20. The EFQM Excellence Model for Deploying Quality Management: A British-Russian Journey

    ERIC Educational Resources Information Center

    Steed, Carol; Maslow, Dmitry; Mazaletskaya, Anna

    2005-01-01

    This paper describes how the Excellence Model[R] developed by the European Foundation for Quality Management (EFQM) can be used and applied within higher education, with practical examples accompanying the Model in a Russian University to raise management quality. (Contains 5 figures, 2 tables, and 1 footnote.)

  1. AQA - Air Quality model for Austria - Evaluation and Developments

    NASA Astrophysics Data System (ADS)

    Hirtl, M.; Krüger, B. C.; Baumann-Stanzer, K.; Skomorowski, P.

    2009-04-01

    The regional weather forecast model ALADIN of the Central Institute for Meteorology and Geodynamics (ZAMG) is used in combination with the chemical transport model CAMx (www.camx.com) to conduct forecasts of gaseous and particulate air pollution over Europe. The forecasts which are done in cooperation with the University of Natural Resources and Applied Life Sciences in Vienna (BOKU) are supported by the regional governments since 2005 with the main interest on the prediction of tropospheric ozone. The daily ozone forecasts are evaluated for the summer 2008 with the observations of about 150 air quality stations in Austria. In 2008 the emission-model SMOKE was integrated into the modelling system to calculate the biogenic emissions. The anthropogenic emissions are based on the newest EMEP data set as well as on regional inventories for the core domain. The performance of SMOKE is shown for a summer period in 2007. In the frame of the COST-action 728 „Enhancing mesoscale meteorological modelling capabilities for air pollution and dispersion applications", multi-model ensembles are used to conduct an international model evaluation. The model calculations of meteorological- and concentration fields are compared to measurements on the ensemble platform at the Joint Research Centre (JRC) in Ispra. The results for 2 episodes in 2006 show the performance of the different models as well as of the model ensemble.

  2. Video quality assessment using a statistical model of human visual speed perception.

    PubMed

    Wang, Zhou; Li, Qiang

    2007-12-01

    Motion is one of the most important types of information contained in natural video, but direct use of motion information in the design of video quality assessment algorithms has not been deeply investigated. Here we propose to incorporate a recent model of human visual speed perception [Nat. Neurosci. 9, 578 (2006)] and model visual perception in an information communication framework. This allows us to estimate both the motion information content and the perceptual uncertainty in video signals. Improved video quality assessment algorithms are obtained by incorporating the model as spatiotemporal weighting factors, where the weight increases with the information content and decreases with the perceptual uncertainty. Consistent improvement over existing video quality assessment algorithms is observed in our validation with the video quality experts group Phase I test data set.

  3. LINKING ETA MODEL WITH THE COMMUNITY MULTISCALE AIR QUALITY (CMAQ) MODELING SYSTEM: OZONE BOUNDARY CONDITIONS

    EPA Science Inventory

    A prototype surface ozone concentration forecasting model system for the Eastern U.S. has been developed. The model system is consisting of a regional meteorological and a regional air quality model. It demonstrated a strong prediction dependence on its ozone boundary conditions....

  4. 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...

  5. Bibliography for the Indoor Air Quality Building Education and Assessment Model

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  6. Hydropower Optimization Using Artificial Neural Network Surrogate Models of a High-Fidelity Hydrodynamics and Water Quality Model

    NASA Astrophysics Data System (ADS)

    Shaw, Amelia R.; Smith Sawyer, Heather; LeBoeuf, Eugene J.; McDonald, Mark P.; Hadjerioua, Boualem

    2017-11-01

    Hydropower operations optimization subject to environmental constraints is limited by challenges associated with dimensionality and spatial and temporal resolution. The need for high-fidelity hydrodynamic and water quality models within optimization schemes is driven by improved computational capabilities, increased requirements to meet specific points of compliance with greater resolution, and the need to optimize operations of not just single reservoirs but systems of reservoirs. This study describes an important advancement for computing hourly power generation schemes for a hydropower reservoir using high-fidelity models, surrogate modeling techniques, and optimization methods. The predictive power of the high-fidelity hydrodynamic and water quality model CE-QUAL-W2 is successfully emulated by an artificial neural network, then integrated into a genetic algorithm optimization approach to maximize hydropower generation subject to constraints on dam operations and water quality. This methodology is applied to a multipurpose reservoir near Nashville, Tennessee, USA. The model successfully reproduced high-fidelity reservoir information while enabling 6.8% and 6.6% increases in hydropower production value relative to actual operations for dissolved oxygen (DO) limits of 5 and 6 mg/L, respectively, while witnessing an expected decrease in power generation at more restrictive DO constraints. Exploration of simultaneous temperature and DO constraints revealed capability to address multiple water quality constraints at specified locations. The reduced computational requirements of the new modeling approach demonstrated an ability to provide decision support for reservoir operations scheduling while maintaining high-fidelity hydrodynamic and water quality information as part of the optimization decision support routines.

  7. Hydropower Optimization Using Artificial Neural Network Surrogate Models of a High-Fidelity Hydrodynamics and Water Quality Model

    DOE PAGES

    Shaw, Amelia R.; Sawyer, Heather Smith; LeBoeuf, Eugene J.; ...

    2017-10-24

    Hydropower operations optimization subject to environmental constraints is limited by challenges associated with dimensionality and spatial and temporal resolution. The need for high-fidelity hydrodynamic and water quality models within optimization schemes is driven by improved computational capabilities, increased requirements to meet specific points of compliance with greater resolution, and the need to optimize operations of not just single reservoirs but systems of reservoirs. This study describes an important advancement for computing hourly power generation schemes for a hydropower reservoir using high-fidelity models, surrogate modeling techniques, and optimization methods. The predictive power of the high-fidelity hydrodynamic and water quality model CE-QUAL-W2more » is successfully emulated by an artificial neural network, then integrated into a genetic algorithm optimization approach to maximize hydropower generation subject to constraints on dam operations and water quality. This methodology is applied to a multipurpose reservoir near Nashville, Tennessee, USA. The model successfully reproduced high-fidelity reservoir information while enabling 6.8% and 6.6% increases in hydropower production value relative to actual operations for dissolved oxygen (DO) limits of 5 and 6 mg/L, respectively, while witnessing an expected decrease in power generation at more restrictive DO constraints. Exploration of simultaneous temperature and DO constraints revealed capability to address multiple water quality constraints at specified locations. Here, the reduced computational requirements of the new modeling approach demonstrated an ability to provide decision support for reservoir operations scheduling while maintaining high-fidelity hydrodynamic and water quality information as part of the optimization decision support routines.« less

  8. Hydropower Optimization Using Artificial Neural Network Surrogate Models of a High-Fidelity Hydrodynamics and Water Quality Model

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

    Shaw, Amelia R.; Sawyer, Heather Smith; LeBoeuf, Eugene J.

    Hydropower operations optimization subject to environmental constraints is limited by challenges associated with dimensionality and spatial and temporal resolution. The need for high-fidelity hydrodynamic and water quality models within optimization schemes is driven by improved computational capabilities, increased requirements to meet specific points of compliance with greater resolution, and the need to optimize operations of not just single reservoirs but systems of reservoirs. This study describes an important advancement for computing hourly power generation schemes for a hydropower reservoir using high-fidelity models, surrogate modeling techniques, and optimization methods. The predictive power of the high-fidelity hydrodynamic and water quality model CE-QUAL-W2more » is successfully emulated by an artificial neural network, then integrated into a genetic algorithm optimization approach to maximize hydropower generation subject to constraints on dam operations and water quality. This methodology is applied to a multipurpose reservoir near Nashville, Tennessee, USA. The model successfully reproduced high-fidelity reservoir information while enabling 6.8% and 6.6% increases in hydropower production value relative to actual operations for dissolved oxygen (DO) limits of 5 and 6 mg/L, respectively, while witnessing an expected decrease in power generation at more restrictive DO constraints. Exploration of simultaneous temperature and DO constraints revealed capability to address multiple water quality constraints at specified locations. Here, the reduced computational requirements of the new modeling approach demonstrated an ability to provide decision support for reservoir operations scheduling while maintaining high-fidelity hydrodynamic and water quality information as part of the optimization decision support routines.« less

  9. 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; hide

    2018-01-01

    We provide an introduction to a new high-resolution (0.25 degree) global composition forecast produced by NASA's Global Modeling and Assimilation office. The NASA Goddard Earth Observing System version 5 (GEOS-5) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (25 km). Previously, this combination of detailed chemistry and resolution was only provided by regional models. This system combines the operational GEOS-5 weather forecasting model with the state-of-the-science GEOS-Chem chemistry module (version 11) to provide detailed chemical analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). The resolution of the forecasts is the highest resolution compared to current, publically-available global composition forecasts. Evaluation and validation of modeled trace gases and aerosols compared to surface and satellite observations will be presented for constituents relative to health air quality standards. Comparisons of modeled trace gases and aerosols against satellite observations show that the model produces realistic concentrations of atmospheric constituents in the free troposphere. Model comparisons against surface observations highlight the model's capability to capture the diurnal variability of air pollutants under a variety of meteorological conditions. The GEOS-5 composition forecasting system offers a new tool for scientists and the public health community, and is being developed jointly with several government and non-profit partners. Potential applications include air quality warnings, flight campaign planning and exposure studies using the archived analysis fields.

  10. Evaluation of bone quality in osteoporosis model mice by Raman spectroscopy

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

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

  11. [Quality of life and job performance resulting from operatively treated tibial plateau fractures].

    PubMed

    Roßbach, B P; Faymonville, C; Müller, L P; Stützer, H; Isenberg, J

    2016-01-01

    The aim of this article is to present the functional results and the effect on quality of life of surgically treated tibial plateau fractures in physically active and working patients with multiple and serious injuries. In addition, the relationships between functional and radiological outcome were evaluated and compared with activity in daily and professional life. In all, 41 injured patients were followed up a mean of 47 months after surgical treatment and examined with radiological, functional, as well as quality of life score. In the radiological scoring, a mean value of 72 points (max 100 points) was achieved. In the activity score, there was an average of 63.5 points (max 100 points). When evaluating the health-related quality of life, an average score of 69.6 points was achieved. There was a significant relationship between radiological and activity scores and the radiological and life quality scores. Furthermore, the relationship between activity and quality of life scores was considered significant. Surgeon's influence on the functional outcome could be confirmed. The functional and the radiological results were moderate. Quality of life was permanently affected by the consequences of tibial plateau fracture in 12 patients; 11 patients were not re-employed. However, the quality of life was assessed as good or very good and 28 patients had returned to work. The quality of life was firmly linked to the radiological and functional parameters, which tended to be influenced by the quality of the primary surgical treatment when looking at the overall population.

  12. 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.

  13. Analyzing the efficiency of short-term air quality plans in European cities, using the CHIMERE air quality model.

    PubMed

    Thunis, P; Degraeuwe, B; Pisoni, E; Meleux, F; Clappier, A

    2017-01-01

    Regional and local authorities have the obligation to design air quality plans and assess their impacts when concentration levels exceed the limit values. Because these limit values cover both short- (day) and long-term (year) effects, air quality plans also follow these two formats. In this work, we propose a methodology to analyze modeled air quality forecast results, looking at emission reduction for different sectors (residential, transport, agriculture, etc.) with the aim of supporting policy makers in assessing the impact of short-term action plans. Regarding PM 10 , results highlight the diversity of responses across European cities, in terms of magnitude and type that raises the necessity of designing area-specific air quality plans. Action plans extended from 1 to 3 days (i.e., emissions reductions applied for 24 and 72 h, respectively) point to the added value of trans-city coordinated actions. The largest benefits are seen in central Europe (Vienna, Prague) while major cities (e.g., Paris) already solve a large part of the problem on their own. Eastern Europe would particularly benefit from plans based on emission reduction in the residential sectors; while in northern cities, agriculture seems to be the key sector on which to focus attention. Transport is playing a key role in most cities whereas the impact of industry is limited to a few cities in south-eastern Europe. For NO 2 , short-term action plans focusing on traffic emission reductions are efficient in all cities. This is due to the local character of this type of pollution. It is important, however, to stress that these results remain dependent on the selected months available for this study.

  14. Modeling procedures for handling qualities evaluation of flexible aircraft

    NASA Technical Reports Server (NTRS)

    Govindaraj, K. S.; Eulrich, B. J.; Chalk, C. R.

    1981-01-01

    This paper presents simplified modeling procedures to evaluate the impact of flexible modes and the unsteady aerodynamic effects on the handling qualities of Supersonic Cruise Aircraft (SCR). The modeling procedures involve obtaining reduced order transfer function models of SCR vehicles, including the important flexible mode responses and unsteady aerodynamic effects, and conversion of the transfer function models to time domain equations for use in simulations. The use of the modeling procedures is illustrated by a simple example.

  15. Hydrodynamic modelling of recreational water quality using Escherichia coli as an indicator of microbial contamination

    NASA Astrophysics Data System (ADS)

    Eregno, Fasil Ejigu; Tryland, Ingun; Tjomsland, Torulv; Kempa, Magdalena; Heistad, Arve

    2018-06-01

    Microbial contamination of recreational beaches is often at its worst after heavy rainfall events due to storm floods that carry fecal matter and other pollutants from the watershed. Similarly, overflows of untreated sewage from combined sewerage systems may discharge directly into coastal water or via rivers and streams. In order to understand the effect of rainfall events, wind-directions and tides on the recreational water quality, GEMSS, an integrated 3D hydrodynamic model was applied to assess the spreading of Escherichia coli (E. coli) at the Sandvika beaches, located in the Oslo fjord. The model was also used to theoretically investigate the effect of discharges from septic tanks from boats on the water quality at local beaches. The model make use of microbial decay rate as the main input representing the survival of microbial pathogens in the ocean, which vary widely depending on the type of pathogen and environmental stress. The predicted beach water quality was validated against observed data after a heavy rainfall event using Nash-Sutcliffe coefficient (E) and the overall result indicated that the model performed quite well and the simulation was in - good agreement with the observed E. coli concentrations for all beaches. The result of this study indicated that: 1) the bathing water quality was poor according to the EU bathing water directive up to two days after the heavy rainfall event depending on the location of the beach site. 2) The discharge from a boat at 300-meter distance to the beaches slightly increased the E. coli levels at the beaches. 3) The spreading of microbial pathogens from its source to the different beaches depended on the wind speed and the wind direction.

  16. 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

  17. Improving the Quality of Positive Datasets for the Establishment of Machine Learning Models for pre-microRNA Detection.

    PubMed

    Demirci, Müşerref Duygu Saçar; Allmer, Jens

    2017-07-28

    MicroRNAs (miRNAs) are involved in the post-transcriptional regulation of protein abundance and thus have a great impact on the resulting phenotype. It is, therefore, no wonder that they have been implicated in many diseases ranging from virus infections to cancer. This impact on the phenotype leads to a great interest in establishing the miRNAs of an organism. Experimental methods are complicated which led to the development of computational methods for pre-miRNA detection. Such methods generally employ machine learning to establish models for the discrimination between miRNAs and other sequences. Positive training data for model establishment, for the most part, stems from miRBase, the miRNA registry. The quality of the entries in miRBase has been questioned, though. This unknown quality led to the development of filtering strategies in attempts to produce high quality positive datasets which can lead to a scarcity of positive data. To analyze the quality of filtered data we developed a machine learning model and found it is well able to establish data quality based on intrinsic measures. Additionally, we analyzed which features describing pre-miRNAs could discriminate between low and high quality data. Both models are applicable to data from miRBase and can be used for establishing high quality positive data. This will facilitate the development of better miRNA detection tools which will make the prediction of miRNAs in disease states more accurate. Finally, we applied both models to all miRBase data and provide the list of high quality hairpins.

  18. Quality by control: Towards model predictive control of mammalian cell culture bioprocesses.

    PubMed

    Sommeregger, Wolfgang; Sissolak, Bernhard; Kandra, Kulwant; von Stosch, Moritz; Mayer, Martin; Striedner, Gerald

    2017-07-01

    The industrial production of complex biopharmaceuticals using recombinant mammalian cell lines is still mainly built on a quality by testing approach, which is represented by fixed process conditions and extensive testing of the end-product. In 2004 the FDA launched the process analytical technology initiative, aiming to guide the industry towards advanced process monitoring and better understanding of how critical process parameters affect the critical quality attributes. Implementation of process analytical technology into the bio-production process enables moving from the quality by testing to a more flexible quality by design approach. The application of advanced sensor systems in combination with mathematical modelling techniques offers enhanced process understanding, allows on-line prediction of critical quality attributes and subsequently real-time product quality control. In this review opportunities and unsolved issues on the road to a successful quality by design and dynamic control implementation are discussed. A major focus is directed on the preconditions for the application of model predictive control for mammalian cell culture bioprocesses. Design of experiments providing information about the process dynamics upon parameter change, dynamic process models, on-line process state predictions and powerful software environments seem to be a prerequisite for quality by control realization. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. [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.

  20. An innovative time-cost-quality tradeoff modeling of building construction project based on resource allocation.

    PubMed

    Hu, Wenfa; He, Xinhua

    2014-01-01

    The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated.

  1. [Practice report: the process-based indicator dashboard. Visualising quality assurance results in standardised processes].

    PubMed

    Petzold, Thomas; Hertzschuch, Diana; Elchlep, Frank; Eberlein-Gonska, Maria

    2014-01-01

    Process management (PM) is a valuable method for the systematic analysis and structural optimisation of the quality and safety of clinical treatment. PM requires a high motivation and willingness to implement changes of both employees and management. Definition of quality indicators is required to systematically measure the quality of the specified processes. One way to represent comparable quality results is the use of quality indicators of the external quality assurance in accordance with Sect. 137 SGB V—a method which the Federal Joint Committee (GBA) and the institutions commissioned by the GBA have employed and consistently enhanced for more than ten years. Information on the quality of inpatient treatment is available for 30 defined subjects throughout Germany. The combination of specified processes with quality indicators is beneficial for the information of employees. A process-based indicator dashboard provides essential information about the treatment process. These can be used for process analysis. In a continuous consideration of these indicator results values can be determined and errors will be remedied quickly. If due consideration is given to these indicators, they can be used for benchmarking to identify potential process improvements. Copyright © 2014. Published by Elsevier GmbH.

  2. Reliable results from stochastic simulation models

    Treesearch

    Donald L., Jr. Gochenour; Leonard R. Johnson

    1973-01-01

    Development of a computer simulation model is usually done without fully considering how long the model should run (e.g. computer time) before the results are reliable. However construction of confidence intervals (CI) about critical output parameters from the simulation model makes it possible to determine the point where model results are reliable. If the results are...

  3. A spatially distributed model for assessment of the effects of changing land use and climate on urban stream quality: Development of a Spatially Distributed Urban Water Quality Model

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

    Sun, Ning; Yearsley, John; Baptiste, Marisa

    While the effects of land use change in urban areas have been widely examined, the combined effects of climate and land use change on the quality of urban and urbanizing streams have received much less attention. We describe a modeling framework that is applicable to the evaluation of potential changes in urban water quality and associated hydrologic changes in response to ongoing climate and landscape alteration. The grid-based spatially distributed model, DHSVM-WQ, is an outgrowth of the Distributed Hydrology-Soil-Vegetation Model (DHSVM) that incorporates modules for assessing hydrology and water quality in urbanized watersheds at a high spatial and temporal resolution.more » DHSVM-WQ simulates surface runoff quality and in-stream processes that control the transport of nonpoint-source (NPS) pollutants into urban streams. We configure DHSVM-WQ for three partially urbanized catchments in the Puget Sound region to evaluate the water quality responses to current conditions and projected changes in climate and/or land use over the next century. Here we focus on total suspended solids (TSS) and total phosphorus (TP) from nonpoint sources (runoff), as well as stream temperature. The projection of future land use is characterized by a combination of densification in existing urban or partially urban areas, and expansion of the urban footprint. The climate change scenarios consist of individual and concurrent changes in temperature and precipitation. Future precipitation is projected to increase in winter and decrease in summer, while future temperature is projected to increase throughout the year. Our results show that urbanization has a much greater effect than climate change on both the magnitude and seasonal variability of streamflow, TSS and TP loads largely due to substantially increased streamflow, and particularly winter flow peaks. Water temperature is more sensitive to climate warming scenarios than to urbanization and precipitation changes. Future

  4. Ozone deposition modelling within the Air Quality Model Evaluation International Initiative (AQMEII)

    EPA Science Inventory

    This presentation provides an overview of the Air Quality Model Evaluation International Initiative (AQMEII). It contains a synopsis of the three phases of AQMEII, including objectives, logistics, and timelines. It also provides a number of examples of analyses conducted through ...

  5. Quality of maternity care and its determinants along the continuum in Kenya: A structural equation modeling analysis

    PubMed Central

    Mendez, Bomar Rojas

    2017-01-01

    Background Improving access to delivery services does not guarantee access to quality obstetric care and better survival, and therefore, concerns for quality of maternal and newborn care in low- and middle-income countries have been raised. Our study explored characteristics associated with the quality of initial assessment, intrapartum, and immediate postpartum and newborn care, and further assessed the relationships along the continuum of care. Methods The 2010 Service Provision Assessment data of Kenya for 627 routine deliveries of women aged 15–49 were used. Quality of care measures were assessed using recently validated quality of care measures during initial assessment, intrapartum, and postpartum periods. Data were analyzed with negative binomial regression and structural equation modeling technique. Results The negative binomial regression results identified a number of determinants of quality, such as the level of health facilities, managing authority, presence of delivery fee, central electricity supply and clinical guideline for maternal and neonatal care. Our structural equation modeling (SEM) further demonstrated that facility characteristics were important determinants of quality for initial assessment and postpartum care, while characteristics at the provider level became more important in shaping the quality of intrapartum care. Furthermore we also noted that quality of initial assessment had a positive association with quality of intrapartum care (β = 0.71, p < 0.001), which in turn was positively associated with the quality of newborn and immediate postpartum care (β = 1.29, p = 0.004). Conclusions A continued focus on quality of care along the continuum of maternity care is important not only to mothers but also their newborns. Policymakers should therefore ensure that required resources, as well as adequate supervision and emphasis on the quality of obstetric care, are available. PMID:28520771

  6. Statistical Methods for Quality Control of Steel Coils Manufacturing Process using Generalized Linear Models

    NASA Astrophysics Data System (ADS)

    García-Díaz, J. Carlos

    2009-11-01

    Fault detection and diagnosis is an important problem in process engineering. Process equipments are subject to malfunctions during operation. Galvanized steel is a value added product, furnishing effective performance by combining the corrosion resistance of zinc with the strength and formability of steel. Fault detection and diagnosis is an important problem in continuous hot dip galvanizing and the increasingly stringent quality requirements in automotive industry has also demanded ongoing efforts in process control to make the process more robust. When faults occur, they change the relationship among these observed variables. This work compares different statistical regression models proposed in the literature for estimating the quality of galvanized steel coils on the basis of short time histories. Data for 26 batches were available. Five variables were selected for monitoring the process: the steel strip velocity, four bath temperatures and bath level. The entire data consisting of 48 galvanized steel coils was divided into sets. The first training data set was 25 conforming coils and the second data set was 23 nonconforming coils. Logistic regression is a modeling tool in which the dependent variable is categorical. In most applications, the dependent variable is binary. The results show that the logistic generalized linear models do provide good estimates of quality coils and can be useful for quality control in manufacturing process.

  7. Atmospheric Boundary Layer Modeling for Combined Meteorology and Air Quality Systems

    EPA Science Inventory

    Atmospheric Eulerian grid models for mesoscale and larger applications require sub-grid models for turbulent vertical exchange processes, particularly within the Planetary Boundary Layer (PSL). In combined meteorology and air quality modeling systems consistent PSL modeling of wi...

  8. A NEW COMBINED LOCAL AND NON-LOCAL PBL MODEL FOR METEOROLOGY AND AIR QUALITY MODELING

    EPA Science Inventory

    A new version of the Asymmetric Convective Model (ACM) has been developed to describe sub-grid vertical turbulent transport in both meteorology models and air quality models. The new version (ACM2) combines the non-local convective mixing of the original ACM with local eddy diff...

  9. Can training improve the quality of inferences made by raters in competency modeling? A quasi-experiment.

    PubMed

    Lievens, Filip; Sanchez, Juan I

    2007-05-01

    A quasi-experiment was conducted to investigate the effects of frame-of-reference training on the quality of competency modeling ratings made by consultants. Human resources consultants from a large consulting firm were randomly assigned to either a training or a control condition. The discriminant validity, interrater reliability, and accuracy of the competency ratings were significantly higher in the training group than in the control group. Further, the discriminant validity and interrater reliability of competency inferences were highest among an additional group of trained consultants who also had competency modeling experience. Together, these results suggest that procedural interventions such as rater training can significantly enhance the quality of competency modeling. 2007 APA, all rights reserved

  10. An integrated system dynamics model developed for managing lake water quality at the watershed scale.

    PubMed

    Liu, Hui; Benoit, Gaboury; Liu, Tao; Liu, Yong; Guo, Huaicheng

    2015-05-15

    A reliable system simulation to relate socioeconomic development with water environment and to comprehensively represent a watershed's dynamic features is important. In this study, after identifying lake watershed system processes, we developed a system dynamics modeling framework for managing lake water quality at the watershed scale. Two reinforcing loops (Development and Investment Promotion) and three balancing loops (Pollution, Resource Consumption, and Pollution Control) were constituted. Based on this work, we constructed Stock and Flow Diagrams that embedded a pollutant load model and a lake water quality model into a socioeconomic system dynamics model. The Dianchi Lake in Yunnan Province, China, which is the sixth largest and among the most severely polluted freshwater lakes in China, was employed as a case study to demonstrate the applicability of the model. Water quality parameters considered in the model included chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). The business-as-usual (BAU) scenario and three alternative management scenarios on spatial adjustment of industries and population (S1), wastewater treatment capacity construction (S2), and structural adjustment of agriculture (S3), were simulated to assess the effectiveness of certain policies in improving water quality. Results showed that S2 is most effective scenario, and the COD, TN, and TP concentrations in Caohai in 2030 are 52.5, 10.9, and 0.8 mg/L, while those in Waihai are 9.6, 1.2, and 0.08 mg/L, with sustained development in the watershed. Thus, the model can help support the decision making required in development and environmental protection strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

    PubMed

    Heddam, Salim; Kisi, Ozgur

    2017-07-01

    In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme learning machine (OS-ELM), and optimally pruned extreme learning machine (OP-ELM), are newly applied for predicting dissolved oxygen concentration with and without water quality variables as predictors. Firstly, using data from eight United States Geological Survey (USGS) stations located in different rivers basins, USA, the S-ELM, R-ELM, OS-ELM, and OP-ELM were compared against the measured dissolved oxygen (DO) using four water quality variables, water temperature, specific conductance, turbidity, and pH, as predictors. For each station, we used data measured at an hourly time step for a period of 4 years. The dataset was divided into a training set (70%) and a validation set (30%). We selected several combinations of the water quality variables as inputs for each ELM model and six different scenarios were compared. Secondly, an attempt was made to predict DO concentration without water quality variables. To achieve this goal, we used the year numbers, 2008, 2009, etc., month numbers from (1) to (12), day numbers from (1) to (31) and hour numbers from (00:00) to (24:00) as predictors. Thirdly, the best ELM models were trained using validation dataset and tested with the training dataset. The performances of the four ELM models were evaluated using four statistical indices: the coefficient of correlation (R), the Nash-Sutcliffe efficiency (NSE), the root mean squared error (RMSE), and the mean absolute error (MAE). Results obtained from the eight stations indicated that: (i) the best results were obtained by the S-ELM, R-ELM, OS-ELM, and OP-ELM models having four water quality variables as predictors; (ii) out of eight stations, the OP-ELM performed better than the other three ELM models at seven stations while the R

  12. 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.

  13. Estimating Lightning NOx Emissions for Regional Air Quality Modeling

    NASA Astrophysics Data System (ADS)

    Holloway, T.; Scotty, E.; Harkey, M.

    2014-12-01

    Lightning emissions have long been recognized as an important source of nitrogen oxides (NOx) on a global scale, and an essential emission component for global atmospheric chemistry models. However, only in recent years have regional air quality models incorporated lightning NOx emissions into simulations. The growth in regional modeling of lightning emissions has been driven in part by comparisons with satellite-derived estimates of column NO2, especially from the Ozone Monitoring Instrument (OMI) aboard the Aura satellite. We present and evaluate a lightning inventory for the EPA Community Multiscale Air Quality (CMAQ) model. Our approach follows Koo et al. [2010] in the approach to spatially and temporally allocating a given total value based on cloud-top height and convective precipitation. However, we consider alternate total NOx emission values (which translate into alternate lightning emission factors) based on a review of the literature and performance evaluation against OMI NO2 for July 2007 conditions over the U.S. and parts of Canada and Mexico. The vertical distribution of lightning emissions follow a bimodal distribution from Allen et al. [2012] calculated over 27 vertical model layers. Total lightning NO emissions for July 2007 show the highest above-land emissions in Florida, southeastern Texas and southern Louisiana. Although agreement with OMI NO2 across the domain varied significantly depending on lightning NOx assumptions, agreement among the simulations at ground-based NO2 monitors from the EPA Air Quality System database showed no meaningful sensitivity to lightning NOx. Emissions are compared with prior studies, which find similar distribution patterns, but a wide range of calculated magnitudes.

  14. Standards of care and quality indicators for multidisciplinary care models for psoriatic arthritis in Spain.

    PubMed

    Gratacós, Jordi; Luelmo, Jesús; Rodríguez, Jesús; Notario, Jaume; Marco, Teresa Navío; de la Cueva, Pablo; Busquets, Manel Pujol; Font, Mercè García; Joven, Beatriz; Rivera, Raquel; Vega, Jose Luis Alvarez; Álvarez, Antonio Javier Chaves; Parera, Ricardo Sánchez; Carrascosa, Jose Carlos Ruiz; Martínez, Fernando José Rodríguez; Sánchez, José Pardo; Olmos, Carlos Feced; Pujol, Conrad; Galindez, Eva; Barrio, Silvia Pérez; Arana, Ana Urruticoechea; Hergueta, Mercedes; Coto, Pablo; Queiro, Rubén

    2018-06-01

    To define and give priority to standards of care and quality indicators of multidisciplinary care for patients with psoriatic arthritis (PsA). A systematic literature review on PsA standards of care and quality indicators was performed. An expert panel of rheumatologists and dermatologists who provide multidisciplinary care was established. In a consensus meeting group, the experts discussed and developed the standards of care and quality indicators and graded their priority, agreement and also the feasibility (only for quality indicators) following qualitative methodology and a Delphi process. Afterwards, these results were discussed with 2 focus groups, 1 with patients, another with health managers. A descriptive analysis is presented. We obtained 25 standards of care (9 of structure, 9 of process, 7 of results) and 24 quality indicators (2 of structure, 5 of process, 17 of results). Standards of care include relevant aspects in the multidisciplinary care of PsA patients like an appropriate physical infrastructure and technical equipment, the access to nursing care, labs and imaging techniques, other health professionals and treatments, or the development of care plans. Regarding quality indicators, the definition of multidisciplinary care model objectives and referral criteria, the establishment of responsibilities and coordination among professionals and the active evaluation of patients and data collection were given a high priority. Patients considered all of them as important. This set of standards of care and quality indicators for the multidisciplinary care of patients with PsA should help improve quality of care in these patients.

  15. An examination of data quality on QSAR Modeling in regards ...

    EPA Pesticide Factsheets

    The development of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available to develop and validate QSAR models. We have focused our efforts on the widely used EPISuite software that was initially developed over two decades ago and, specifically, on the PHYSPROP dataset used to train the EPISuite prediction models. This presentation will review our approaches to examining key datasets, the delivery of curated data and the development of machine-learning models for thirteen separate property endpoints of interest to environmental science. We will also review how these data will be made freely accessible to the community via a new “chemistry dashboard”. This abstract does not reflect U.S. EPA policy. presentation at UNC-CH.

  16. The choices, choosing model of quality of life: linkages to a science base.

    PubMed

    Gurland, Barry J; Gurland, Roni V

    2009-01-01

    A previous paper began with a critical review of current models and measures of quality of life and then proposed criteria for judging the relative merits of alternative models: preference was given to finding a model with explicit mechanisms, linkages to a science base, a means of identifying deficits amenable to rational restorative interventions, and with embedded values of the whole person. A conjectured model, based on the processes of accessing choices and choosing among them, matched the proposed criteria. The choices and choosing (c-c) process is an evolved adaptive mechanism dedicated to the pursuit of quality of life, driven by specific biological and psychological systems, and influenced also by social and environmental forces. In this paper the c-c model is examined for its potential to strengthen the science base for the field of quality of life and thus to unify many approaches to concept and measurement. A third paper in this set will lay out a guide to applying the c-c model in evaluating impairments of quality of life and will tie this evaluation to corresponding interventions aimed at relieving restrictions or distortions of the c-c process; thus helping people to preserve and improve their quality of life. The fourth paper will demonstrate empirical analyses of the relationship between health imposed restrictions of options for living and conventional indicators of diminished quality of life. (c) 2008 John Wiley & Sons, Ltd.

  17. Modeling and Negotiating Service Quality

    NASA Astrophysics Data System (ADS)

    Benbernou, Salima; Brandic, Ivona; Cappiello, Cinzia; Carro, Manuel; Comuzzi, Marco; Kertész, Attila; Kritikos, Kyriakos; Parkin, Michael; Pernici, Barbara; Plebani, Pierluigi

    In this chapter the research problems of specifying and negotiating QoS and its corresponding quality documents are analyzed. For this reason, this chapter is separated into two main sections, Section 6.1 and 6.2, with each dedicated to one of the two problems, i.e., QoS specification and negotiation, respectively. Each section has a similar structure: they first introduce the problem and then, in the remaining subsections, review related work. Finally, the chapter ends with Section 6.3, which identifies research gaps and presents potential research challenges in QoS modelling, specification and negotiation.

  18. 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

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

    PubMed

    McGuffin, Liam J

    2009-01-01

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

  20. Predicting health-related quality of life in cancer patients receiving chemotherapy: a structural equation approach using the self-control model.

    PubMed

    Park, Yu-Ri; Park, Eun-Young; Kim, Jung-Hee

    2017-11-09

    According to the self-control model, self-control works as a protective factor and a psychological resource. Although an understanding of the effect(s) of peripheral neuropathy on quality of life is important to healthcare professionals, previous studies do not facilitate broad comprehension in this regard. The purpose of this cross-sectional study was to test the multidimensional assumptions of quality of life of patients with cancer, with focus on their self-control. A structural equation model was tested on patients with cancer at the oncology clinic of a university hospital where patients received chemotherapy. A model was tested using structural equation modeling, which allows the researcher to find the empirical evidence by testing a measurement model and a structural model. The model comprised three variables, self-control, health related quality of life, and chemotherapy-induced peripheral neuropathy. Among the variables, self-control was the endogenous and mediating variable. The proposed models showed good fit indices. Self-control partially mediated chemotherapy-induced peripheral neuropathy and quality of life. It was found that the physical symptoms of peripheral neuropathy influenced health-related quality of life both indirectly and directly. Self-control plays a significant role in the protection and promotion of physical and mental health in various stressful situations, and thus, as a psychological resource, it plays a significant role in quality of life. Our results can be used to develop a quality of life model for patients receiving chemotherapy and as a theoretical foundation for the development of appropriate nursing interventions.

  1. The Air Quality Model Evaluation International Initiative (AQMEII)

    EPA Science Inventory

    This presentation provides an overview of the Air Quality Model Evaluation International Initiative (AQMEII). It contains a synopsis of the three phases of AQMEII, including objectives, logistics, and timelines. It also provides a number of examples of analyses conducted through ...

  2. Scale Issues in Air Quality Modeling Policy Support

    EPA Science Inventory

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

  3. Experiments with data assimilation in comprehensive air quality models: Impacts on model predictions and observation requirements (Invited)

    NASA Astrophysics Data System (ADS)

    Mathur, R.

    2009-12-01

    Emerging regional scale atmospheric simulation models must address the increasing complexity arising from new model applications that treat multi-pollutant interactions. Sophisticated air quality modeling systems are needed to develop effective abatement strategies that focus on simultaneously controlling multiple criteria pollutants as well as use in providing short term air quality forecasts. In recent years the applications of such models is continuously being extended to address atmospheric pollution phenomenon from local to hemispheric spatial scales over time scales ranging from episodic to annual. The need to represent interactions between physical and chemical atmospheric processes occurring at these disparate spatial and temporal scales requires the use of observation data beyond traditional in-situ networks so that the model simulations can be reasonably constrained. Preliminary applications of assimilation of remote sensing and aloft observations within a comprehensive regional scale atmospheric chemistry-transport modeling system will be presented: (1) A methodology is developed to assimilate MODIS aerosol optical depths in the model to represent the impacts long-range transport associated with the summer 2004 Alaskan fires on surface-level regional fine particulate matter (PM2.5) concentrations across the Eastern U.S. The episodic impact of this pollution transport event on PM2.5 concentrations over the eastern U.S. during mid-July 2004, is quantified through the complementary use of the model with remotely-sensed, aloft, and surface measurements; (2) Simple nudging experiments with limited aloft measurements are performed to identify uncertainties in model representations of physical processes and assess the potential use of such measurements in improving the predictive capability of atmospheric chemistry-transport models. The results from these early applications will be discussed in context of uncertainties in the model and in the remote sensing

  4. An Innovative Time-Cost-Quality Tradeoff Modeling of Building Construction Project Based on Resource Allocation

    PubMed Central

    2014-01-01

    The time, quality, and cost are three important but contradictive objectives in a building construction project. It is a tough challenge for project managers to optimize them since they are different parameters. This paper presents a time-cost-quality optimization model that enables managers to optimize multiobjectives. The model is from the project breakdown structure method where task resources in a construction project are divided into a series of activities and further into construction labors, materials, equipment, and administration. The resources utilized in a construction activity would eventually determine its construction time, cost, and quality, and a complex time-cost-quality trade-off model is finally generated based on correlations between construction activities. A genetic algorithm tool is applied in the model to solve the comprehensive nonlinear time-cost-quality problems. Building of a three-storey house is an example to illustrate the implementation of the model, demonstrate its advantages in optimizing trade-off of construction time, cost, and quality, and help make a winning decision in construction practices. The computational time-cost-quality curves in visual graphics from the case study prove traditional cost-time assumptions reasonable and also prove this time-cost-quality trade-off model sophisticated. PMID:24672351

  5. A database and tool for boundary conditions for regional air quality modeling: description and evaluation

    NASA Astrophysics Data System (ADS)

    Henderson, B. H.; Akhtar, F.; Pye, H. O. T.; Napelenok, S. L.; Hutzell, W. T.

    2014-02-01

    Transported air pollutants receive increasing attention as regulations tighten and global concentrations increase. The need to represent international transport in regional air quality assessments requires improved representation of boundary concentrations. Currently available observations are too sparse vertically to provide boundary information, particularly for ozone precursors, but global simulations can be used to generate spatially and temporally varying lateral boundary conditions (LBC). This study presents a public database of global simulations designed and evaluated for use as LBC for air quality models (AQMs). The database covers the contiguous United States (CONUS) for the years 2001-2010 and contains hourly varying concentrations of ozone, aerosols, and their precursors. The database is complemented by a tool for configuring the global results as inputs to regional scale models (e.g., Community Multiscale Air Quality or Comprehensive Air quality Model with extensions). This study also presents an example application based on the CONUS domain, which is evaluated against satellite retrieved ozone and carbon monoxide vertical profiles. The results show performance is largely within uncertainty estimates for ozone from the Ozone Monitoring Instrument and carbon monoxide from the Measurements Of Pollution In The Troposphere (MOPITT), but there were some notable biases compared with Tropospheric Emission Spectrometer (TES) ozone. Compared with TES, our ozone predictions are high-biased in the upper troposphere, particularly in the south during January. This publication documents the global simulation database, the tool for conversion to LBC, and the evaluation of concentrations on the boundaries. This documentation is intended to support applications that require representation of long-range transport of air pollutants.

  6. Remote Sensing and Spatial Growth Modeling Coupled With Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

    NASA Astrophysics Data System (ADS)

    Quattrochi, D. A.; Estes, M. G.; Crosson, W. L.; Johnson, H.; Khan, M.

    2006-05-01

    The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world's population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as

  7. Impact of High Resolution Land-Use Data in Meteorology and Air Quality Modeling Systems

    EPA Science Inventory

    Accurate land use information is important in meteorology for land surface exchanges, in emission modeling for emission spatial allocation, and in air quality modeling for chemical surface fluxes. Currently, meteorology, emission, and air quality models often use outdated USGS Gl...

  8. The Model for Understanding Success in Quality (MUSIQ): building a theory of context in healthcare quality improvement.

    PubMed

    Kaplan, Heather C; Provost, Lloyd P; Froehle, Craig M; Margolis, Peter A

    2012-01-01

    BACKGROUND Quality improvement (QI) efforts have become widespread in healthcare, however there is significant variability in their success. Differences in context are thought to be responsible for some of the variability seen. To develop a conceptual model that can be used by organisations and QI researchers to understand and optimise contextual factors affecting the success of a QI project. 10 QI experts were provided with the results of a systematic literature review and then participated in two rounds of opinion gathering to identify and define important contextual factors. The experts subsequently met in person to identify relationships among factors and to begin to build the model. The Model for Understanding Success in Quality (MUSIQ) is organised based on the level of the healthcare system and identifies 25 contextual factors likely to influence QI success. Contextual factors within microsystems and those related to the QI team are hypothesised to directly shape QI success, whereas factors within the organisation and external environment are believed to influence success indirectly. The MUSIQ framework has the potential to guide the application of QI methods in healthcare and focus research. The specificity of MUSIQ and the explicit delineation of relationships among factors allows a deeper understanding of the mechanism of action by which context influences QI success. MUSIQ also provides a foundation to support further studies to test and refine the theory and advance the field of QI science.

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

    PubMed

    Cao, Renzhi; Wang, Zheng; Cheng, Jianlin

    2014-04-15

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

  10. Challenges in validating model results for first year ice

    NASA Astrophysics Data System (ADS)

    Melsom, Arne; Eastwood, Steinar; Xie, Jiping; Aaboe, Signe; Bertino, Laurent

    2017-04-01

    In order to assess the quality of model results for the distribution of first year ice, a comparison with a product based on observations from satellite-borne instruments has been performed. Such a comparison is not straightforward due to the contrasting algorithms that are used in the model product and the remote sensing product. The implementation of the validation is discussed in light of the differences between this set of products, and validation results are presented. The model product is the daily updated 10-day forecast from the Arctic Monitoring and Forecasting Centre in CMEMS. The forecasts are produced with the assimilative ocean prediction system TOPAZ. Presently, observations of sea ice concentration and sea ice drift are introduced in the assimilation step, but data for sea ice thickness and ice age (or roughness) are not included. The model computes the age of the ice by recording and updating the time passed after ice formation as sea ice grows and deteriorates as it is advected inside the model domain. Ice that is younger than 365 days is classified as first year ice. The fraction of first-year ice is recorded as a tracer in each grid cell. The Ocean and Sea Ice Thematic Assembly Centre in CMEMS redistributes a daily product from the EUMETSAT OSI SAF of gridded sea ice conditions which include "ice type", a representation of the separation of regions between those infested by first year ice, and those infested by multi-year ice. The ice type is parameterized based on data for the gradient ratio GR(19,37) from SSMIS observations, and from the ASCAT backscatter parameter. This product also includes information on ambiguity in the processing of the remote sensing data, and the product's confidence level, which have a strong seasonal dependency.

  11. 40 CFR Appendix W to Part 51 - Guideline on Air Quality Models

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 2 2010-07-01 2010-07-01 false Guideline on Air Quality Models W Appendix W to Part 51 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR PROGRAMS REQUIREMENTS FOR PREPARATION, ADOPTION, AND SUBMITTAL OF IMPLEMENTATION PLANS Pt. 51, App. W Appendix W to Part 51—Guideline on Air Quality Models...

  12. AIR QUALITY MODELING OF PM AND AIR TOXICS AT NEIGHBORHOOD SCALES

    EPA Science Inventory

    The current interest in fine particles and toxics pollutants provide an impetus for extending air quality modeling capability towards improving exposure modeling and assessments. Human exposure models require information on concentration derived from interpolation of observati...

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

    PubMed

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

    2017-12-05

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

  14. Implementing subgrid-scale cloudiness into the Model for Prediction Across Scales-Atmosphere (MPAS-A) for next generation global air quality modeling

    EPA Science Inventory

    A next generation air quality modeling system is being developed at the U.S. EPA to enable seamless modeling of air quality from global to regional to (eventually) local scales. State of the science chemistry and aerosol modules from the Community Multiscale Air Quality (CMAQ) mo...

  15. Validation of a digital mammographic unit model for an objective and highly automated clinical image quality assessment.

    PubMed

    Perez-Ponce, Hector; Daul, Christian; Wolf, Didier; Noel, Alain

    2013-08-01

    In mammography, image quality assessment has to be directly related to breast cancer indicator (e.g. microcalcifications) detectability. Recently, we proposed an X-ray source/digital detector (XRS/DD) model leading to such an assessment. This model simulates very realistic contrast-detail phantom (CDMAM) images leading to gold disc (representing microcalcifications) detectability thresholds that are very close to those of real images taken under the simulated acquisition conditions. The detection step was performed with a mathematical observer. The aim of this contribution is to include human observers into the disc detection process in real and virtual images to validate the simulation framework based on the XRS/DD model. Mathematical criteria (contrast-detail curves, image quality factor, etc.) are used to assess and to compare, from the statistical point of view, the cancer indicator detectability in real and virtual images. The quantitative results given in this paper show that the images simulated by the XRS/DD model are useful for image quality assessment in the case of all studied exposure conditions using either human or automated scoring. Also, this paper confirms that with the XRS/DD model the image quality assessment can be automated and the whole time of the procedure can be drastically reduced. Compared to standard quality assessment methods, the number of images to be acquired is divided by a factor of eight. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

  16. Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.1

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

  17. Overview and Evaluation of the Community Multiscale Air Quality Model Version 5.2

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

  18. Evaluation of the Community Multi-scale Air Quality (CMAQ) Model Version 5.2

    EPA Science Inventory

    The Community Multiscale Air Quality (CMAQ) model is a state-of-the-science air quality model that simulates the emission, transport and fate of numerous air pollutants, including ozone and particulate matter. The Computational Exposure Division (CED) of the U.S. Environmental Pr...

  19. 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...

  20. Monitoring the Quality of Medicines: Results from Africa, Asia, and South America

    PubMed Central

    Hajjou, Mustapha; Krech, Laura; Lane-Barlow, Christi; Roth, Lukas; Pribluda, Victor S.; Phanouvong, Souly; El-Hadri, Latifa; Evans, Lawrence; Raymond, Christopher; Yuan, Elaine; Siv, Lang; Vuong, Tuan-Anh; Boateng, Kwasi Poku; Okafor, Regina; Chibwe, Kennedy M.; Lukulay, Patrick H.

    2015-01-01

    Monitoring the quality of medicines plays a crucial role in an integrated medicines quality assurance system. In a publicly available medicines quality database (MQDB), the U.S. Pharmacopeial Convention (USP) reports results of data collected from medicines quality monitoring (MQM) activities spanning the period of 2003–2013 in 17 countries of Africa, Asia, and South America. The MQDB contains information on 15,063 samples collected and tested using Minilab® screening methods and/or pharmacopeial methods. Approximately 71% of the samples reported came from Asia, 23% from Africa, and 6% from South America. The samples collected and tested include mainly antibiotic, antimalarial, and antituberculosis medicines. A total of 848 samples, representing 5.6% of total samples, failed the quality test. The failure proportion per region was 11.5%, 10.4%, and 2.9% for South America, Africa, and Asia, respectively. Eighty-one counterfeit medicines were reported, 86.4% of which were found in Asia and 13.6% in Africa. Additional analysis of the data shows the distribution of poor-quality medicines per region and by therapeutic indication as well as possible trends of counterfeit medicines. PMID:25897073

  1. AIR QUALITY MODELING AT NEIGHBORHOOD SCALES TO IMPROVE HUMAN EXPOSURE ASSESSMENT

    EPA Science Inventory

    Air quality modeling is an integral component of risk assessment and of subsequent development of effective and efficient management of air quality. Urban areas introduce of fresh sources of pollutants into regional background producing significant spatial variability of the co...

  2. The Impact of 3D Data Quality on Improving GNSS Performance Using City Models Initial Simulations

    NASA Astrophysics Data System (ADS)

    Ellul, C.; Adjrad, M.; Groves, P.

    2016-10-01

    There is an increasing demand for highly accurate positioning information in urban areas, to support applications such as people and vehicle tracking, real-time air quality detection and navigation. However systems such as GPS typically perform poorly in dense urban areas. A number of authors have made use of 3D city models to enhance accuracy, obtaining good results, but to date the influence of the quality of the 3D city model on these results has not been tested. This paper addresses the following question: how does the quality, and in particular the variation in height, level of generalization and completeness and currency of a 3D dataset, impact the results obtained for the preliminary calculations in a process known as Shadow Matching, which takes into account not only where satellite signals are visible on the street but also where they are predicted to be absent. We describe initial simulations to address this issue, examining the variation in elevation angle - i.e. the angle above which the satellite is visible, for three 3D city models in a test area in London, and note that even within one dataset using different available height values could cause a difference in elevation angle of up to 29°. Missing or extra buildings result in an elevation variation of around 85°. Variations such as these can significantly influence the predicted satellite visibility which will then not correspond to that experienced on the ground, reducing the accuracy of the resulting Shadow Matching process.

  3. 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.

  4. 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.

  5. The Triangle Model for evaluating the effect of health information technology on healthcare quality and safety

    PubMed Central

    Kern, Lisa M; Abramson, Erika; Kaushal, Rainu

    2011-01-01

    With the proliferation of relatively mature health information technology (IT) systems with large numbers of users, it becomes increasingly important to evaluate the effect of these systems on the quality and safety of healthcare. Previous research on the effectiveness of health IT has had mixed results, which may be in part attributable to the evaluation frameworks used. The authors propose a model for evaluation, the Triangle Model, developed for designing studies of quality and safety outcomes of health IT. This model identifies structure-level predictors, including characteristics of: (1) the technology itself; (2) the provider using the technology; (3) the organizational setting; and (4) the patient population. In addition, the model outlines process predictors, including (1) usage of the technology, (2) organizational support for and customization of the technology, and (3) organizational policies and procedures about quality and safety. The Triangle Model specifies the variables to be measured, but is flexible enough to accommodate both qualitative and quantitative approaches to capturing them. The authors illustrate this model, which integrates perspectives from both health services research and biomedical informatics, with examples from evaluations of electronic prescribing, but it is also applicable to a variety of types of health IT systems. PMID:21857023

  6. 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.

  7. INTERCOMPARISON OF ALTERNATIVE VEGETATION DATABASES FOR REGIONAL AIR QUALITY MODELING

    EPA Science Inventory

    Vegetation cover data are used to characterize several regional air quality modeling processes, including the calculation of heat, moisture, and momentum fluxes with the Mesoscale Meteorological Model (MM5) and the estimate of biogenic volatile organic compound and nitric oxide...

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

    PubMed

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

    2005-11-01

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

  9. 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.

  10. A quality-based cost model for new electronic systems and products

    NASA Astrophysics Data System (ADS)

    Shina, Sammy G.; Saigal, Anil

    1998-04-01

    This article outlines a method for developing a quality-based cost model for the design of new electronic systems and products. The model incorporates a methodology for determining a cost-effective design margin allocation for electronic products and systems and its impact on manufacturing quality and cost. A spreadsheet-based cost estimating tool was developed to help implement this methodology in order for the system design engineers to quickly estimate the effect of design decisions and tradeoffs on the quality and cost of new products. The tool was developed with automatic spreadsheet connectivity to current process capability and with provisions to consider the impact of capital equipment and tooling purchases to reduce the product cost.

  11. Comparison of modelling accuracy with and without exploiting automated optical monitoring information in predicting the treated wastewater quality.

    PubMed

    Tomperi, Jani; Leiviskä, Kauko

    2018-06-01

    Traditionally the modelling in an activated sludge process has been based on solely the process measurements, but as the interest to optically monitor wastewater samples to characterize the floc morphology has increased, in the recent years the results of image analyses have been more frequently utilized to predict the characteristics of wastewater. This study shows that the traditional process measurements or the automated optical monitoring variables by themselves are not capable of developing the best predictive models for the treated wastewater quality in a full-scale wastewater treatment plant, but utilizing these variables together the optimal models, which show the level and changes in the treated wastewater quality, are achieved. By this early warning, process operation can be optimized to avoid environmental damages and economic losses. The study also shows that specific optical monitoring variables are important in modelling a certain quality parameter, regardless of the other input variables available.

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

    PubMed

    Woodward, S J

    2001-09-01

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

  13. POSNA Quality Safety Value Initiative: From Vision to Implementation to Early Results.

    PubMed

    Waters, Peter M; Flynn, John M

    2015-01-01

    The POSNA Quality, Safety and Value Initiative (QSVI) formally started with POSNA board approval in early 2011. The initial vision statement was: "To lead in defining our members' value based clinical care. To partner with hospital based and orthopedic organizational efforts to guarantee safe, high quality outcomes for our patients. To communicate our initiatives and results cooperatively with payer, credentialing, and compliance organizations to improve pediatric orthopedic care in North America."

  14. A slow fashion design model for bluejeans using house of quality approach

    NASA Astrophysics Data System (ADS)

    Nergis, B.; Candan, C.; Sarısaltık, S.; Seneloglu, N.; Bozuk, R.; Amzayev, K.

    2017-10-01

    The purpose of this study was to develop a slow fashion design model using the house of quality model (HOQ) to provide fashion designers a tool to improve the overall sustainability of denim jeans for Y generation consumers in Turkish market. In doing so, a survey was conducted to collect data on the design & performance expectations as well as the perception of slow fashion in design process of denim jeans of the targeted consumer group. The results showed that Y generation in the market gave the most importance to the sustainable production techniques when identifying slow fashion.

  15. 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.

  16. Water Quality and Quantity Modeling for Hydrologic and Policy Decision Making

    NASA Astrophysics Data System (ADS)

    Rubiano, J.; Giron, E.; Quintero, M.; O'Brien, R.

    2004-12-01

    This paper presents the results of a research project that elucidate the excesses of nitrogen and phosphorous using a spatial-temporal modeling approach. The project uses the approach of integrating biophysical and socio-economic knowledge to offer sound solution to multiple stakeholders within a watershed context. The aim is to promote rural development and solve environmental conflicts by focusing on the internalization of externalities derived from watershed management, triggering the transference of funding from urban to rural populations, making the city invest in environmental goods or services offered by rural environments. The integrated modeling is focused towards identifying causal relationships between land use and management on the one hand, and water quantity/quality and sedimentation downstream on the other. Estimation of the amount of contaminated sediments transported in the study area and its impact is also studied here. The soil runoff information within the study area is obtained considering the characteristics of erosion using a MUSLE model as a sub-model of SWAT model. Using regression analysis, mathematical relationships between rainfall and surface runoff and between land use or management practices and the measured nitrate and phosphate load are established. The methodology first integrates most of the key spatial information available for the site to facilitate envisioning different land use scenarios and their impacts upon water resources. Subsequently, selected alternatives scenarios regarding the identified externalities are analyzed using optimization models. Opportunities for and constraints to promoting co-operation among users are exposed with the aid of economic games in which more sustainable land use or management alternatives are suggested. Strategic alliances and collective action are promoted in order to implement those alternatives that are environmentally sound and economically feasible. Such options are supported by co

  17. 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.

  18. WATGIS: A GIS-Based Lumped Parameter Water Quality Model

    Treesearch

    Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

    2002-01-01

    A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...

  19. The Veterans Affairs National Quality Scholars program: a model for interprofessional education in quality and safety.

    PubMed

    Patrician, Patricia A; Dolansky, Mary A; Pair, Vincent; Bates, Mekeshia; Moore, Shirley M; Splaine, Mark; Gilman, Stuart C

    2013-01-01

    The Quality and Safety Education for Nurses (QSEN) project is enhancing the emphasis on quality care and patient safety content in nursing schools. A partnership between QSEN and the Veterans Affairs National Quality Scholars program resulted in a unique experiential, interdisciplinary fellowship for both nurses and physicians. This article introduces the Veterans Affairs National Quality Scholars program and provides examples of learning activities and fellows' accomplishments. Interprofessional quality and safety education at the doctoral and postdoctoral levels is germane to improving the quality of health care.

  20. 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.

  1. UNCERTAINTY ANALYSIS IN WATER QUALITY MODELING USING QUAL2E

    EPA Science Inventory

    A strategy for incorporating uncertainty analysis techniques (sensitivity analysis, first order error analysis, and Monte Carlo simulation) into the mathematical water quality model QUAL2E is described. The model, named QUAL2E-UNCAS, automatically selects the input variables or p...

  2. 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.

  3. Evaluation of the Community Multiscale Air Quality Model for Simulating Winter Ozone Formation in the Uinta Basin with Intensive Oil and Gas Production

    NASA Astrophysics Data System (ADS)

    Matichuk, R.; Tonnesen, G.; Luecken, D.; Roselle, S. J.; Napelenok, S. L.; Baker, K. R.; Gilliam, R. C.; Misenis, C.; Murphy, B.; Schwede, D. B.

    2015-12-01

    The western United States is an important source of domestic energy resources. One of the primary environmental impacts associated with oil and natural gas production is related to air emission releases of a number of air pollutants. Some of these pollutants are important precursors to the formation of ground-level ozone. To better understand ozone impacts and other air quality issues, photochemical air quality models are used to simulate the changes in pollutant concentrations in the atmosphere on local, regional, and national spatial scales. These models are important for air quality management because they assist in identifying source contributions to air quality problems and designing effective strategies to reduce harmful air pollutants. The success of predicting oil and natural gas air quality impacts depends on the accuracy of the input information, including emissions inventories, meteorological information, and boundary conditions. The treatment of chemical and physical processes within these models is equally important. However, given the limited amount of data collected for oil and natural gas production emissions in the past and the complex terrain and meteorological conditions in western states, the ability of these models to accurately predict pollution concentrations from these sources is uncertain. Therefore, this presentation will focus on understanding the Community Multiscale Air Quality (CMAQ) model's ability to predict air quality impacts associated with oil and natural gas production and its sensitivity to input uncertainties. The results will focus on winter ozone issues in the Uinta Basin, Utah and identify the factors contributing to model performance issues. The results of this study will help support future air quality model development, policy and regulatory decisions for the oil and gas sector.

  4. SMOQ: a tool for predicting the absolute residue-specific quality of a single protein model with support vector machines

    PubMed Central

    2014-01-01

    Background It is important to predict the quality of a protein structural model before its native structure is known. The method that can predict the absolute local quality of individual residues in a single protein model is rare, yet particularly needed for using, ranking and refining protein models. Results We developed a machine learning tool (SMOQ) that can predict the distance deviation of each residue in a single protein model. SMOQ uses support vector machines (SVM) with protein sequence and structural features (i.e. basic feature set), including amino acid sequence, secondary structures, solvent accessibilities, and residue-residue contacts to make predictions. We also trained a SVM model with two new additional features (profiles and SOV scores) on 20 CASP8 targets and found that including them can only improve the performance when real deviations between native and model are higher than 5Å. The SMOQ tool finally released uses the basic feature set trained on 85 CASP8 targets. Moreover, SMOQ implemented a way to convert predicted local quality scores into a global quality score. SMOQ was tested on the 84 CASP9 single-domain targets. The average difference between the residue-specific distance deviation predicted by our method and the actual distance deviation on the test data is 2.637Å. The global quality prediction accuracy of the tool is comparable to other good tools on the same benchmark. Conclusion SMOQ is a useful tool for protein single model quality assessment. Its source code and executable are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:24776231

  5. Process quality indicators in family medicine: results of an international comparison.

    PubMed

    Pavlič, Danica Rotar; Sever, Maja; Klemenc-Ketiš, Zalika; Švab, Igor

    2015-12-02

    The aim of our study was to describe variability in process quality in family medicine among 31 European countries plus Australia, New Zealand, and Canada. The quality of family medicine was measured in terms of continuity, coordination, community orientation, and comprehensiveness of care. The QUALICOPC study (Quality and Costs of Primary Care in Europe) was carried out among family physicians in 31 European countries (the EU 27 except for France, plus Macedonia, Iceland, Norway, Switzerland, and Turkey) and three non-European countries (Australia, Canada, and New Zealand). We used random sampling when national registers of practitioners were available. Regional registers or lists of facilities were used for some countries. A standardized questionnaire was distributed to the physicians, resulting in a sample of 6734 participants. Data collection took place between October 2011 and December 2013. Based on completed questionnaires, a three-dimensional framework was established to measure continuity, coordination, community orientation, and comprehensiveness of care. Multilevel linear regression analysis was performed to evaluate the variation of quality attributable to the family physician level and the country level. None of the 34 countries in this study consistently scored the best or worst in all categories. Continuity of care was perceived by family physicians as the most important dimension of quality. Some components of comprehensiveness of care, including medical technical procedures, preventive care and health care promotion, varied substantially between countries. Coordination of care was identified as the weakest part of quality. We found that physician-level characteristics contributed to the majority of variation. A comparison of process quality indicators in family medicine revealed similarities and differences within and between countries. The researchers found that the major proportion of variation can be explained by physicians' characteristics.

  6. Comparison of different uncertainty techniques in urban stormwater quantity and quality modelling.

    PubMed

    Dotto, Cintia B S; Mannina, Giorgio; Kleidorfer, Manfred; Vezzaro, Luca; Henrichs, Malte; McCarthy, David T; Freni, Gabriele; Rauch, Wolfgang; Deletic, Ana

    2012-05-15

    Urban drainage models are important tools used by both practitioners and scientists in the field of stormwater management. These models are often conceptual and usually require calibration using local datasets. The quantification of the uncertainty associated with the models is a must, although it is rarely practiced. The International Working Group on Data and Models, which works under the IWA/IAHR Joint Committee on Urban Drainage, has been working on the development of a framework for defining and assessing uncertainties in the field of urban drainage modelling. A part of that work is the assessment and comparison of different techniques generally used in the uncertainty assessment of the parameters of water models. This paper compares a number of these techniques: the Generalized Likelihood Uncertainty Estimation (GLUE), the Shuffled Complex Evolution Metropolis algorithm (SCEM-UA), an approach based on a multi-objective auto-calibration (a multialgorithm, genetically adaptive multi-objective method, AMALGAM) and a Bayesian approach based on a simplified Markov Chain Monte Carlo method (implemented in the software MICA). To allow a meaningful comparison among the different uncertainty techniques, common criteria have been set for the likelihood formulation, defining the number of simulations, and the measure of uncertainty bounds. Moreover, all the uncertainty techniques were implemented for the same case study, in which the same stormwater quantity and quality model was used alongside the same dataset. The comparison results for a well-posed rainfall/runoff model showed that the four methods provide similar probability distributions of model parameters, and model prediction intervals. For ill-posed water quality model the differences between the results were much wider; and the paper provides the specific advantages and disadvantages of each method. In relation to computational efficiency (i.e. number of iterations required to generate the probability

  7. Adding spatial flexibility to source-receptor relationships for air quality modeling.

    PubMed

    Pisoni, E; Clappier, A; Degraeuwe, B; Thunis, P

    2017-04-01

    To cope with computing power limitations, air quality models that are used in integrated assessment applications are generally approximated by simpler expressions referred to as "source-receptor relationships (SRR)". In addition to speed, it is desirable for the SRR also to be spatially flexible (application over a wide range of situations) and to require a "light setup" (based on a limited number of full Air Quality Models - AQM simulations). But "speed", "flexibility" and "light setup" do not naturally come together and a good compromise must be ensured that preserves "accuracy", i.e. a good comparability between SRR results and AQM. In this work we further develop a SRR methodology to better capture spatial flexibility. The updated methodology is based on a cell-to-cell relationship, in which a bell-shape function links emissions to concentrations. Maintaining a cell-to-cell relationship is shown to be the key element needed to ensure spatial flexibility, while at the same time the proposed approach to link emissions and concentrations guarantees a "light set-up" phase. Validation has been repeated on different areas and domain sizes (countries, regions, province throughout Europe) for precursors reduced independently or contemporarily. All runs showed a bias around 10% between the full AQM and the SRR. This methodology allows assessing the impact on air quality of emission scenarios applied over any given area in Europe (regions, set of regions, countries), provided that a limited number of AQM simulations are performed for training.

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

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

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

  9. An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation.

    PubMed

    Fan, Chihhao; Ko, Chun-Han; Wang, Wei-Shen

    2009-04-01

    Water quality modeling has been shown to be a useful tool in strategic water quality management. The present study combines the Qual2K model with the HEC-RAS model to assess the water quality of a tidal river in northern Taiwan. The contaminant loadings of biochemical oxygen demand (BOD), ammonia nitrogen (NH(3)-N), total phosphorus (TP), and sediment oxygen demand (SOD) are utilized in the Qual2K simulation. The HEC-RAS model is used to: (i) estimate the hydraulic constants for atmospheric re-aeration constant calculation; and (ii) calculate the water level profile variation to account for concentration changes as a result of tidal effect. The results show that HEC-RAS-assisted Qual2K simulations taking tidal effect into consideration produce water quality indices that, in general, agree with the monitoring data of the river. Comparisons of simulations with different combinations of contaminant loadings demonstrate that BOD is the most import contaminant. Streeter-Phelps simulation (in combination with HEC-RAS) is also performed for comparison, and the results show excellent agreement with the observed data. This paper is the first report of the innovative use of a combination of the HEC-RAS model and the Qual2K model (or Streeter-Phelps equation) to simulate water quality in a tidal river. The combination is shown to provide an alternative for water quality simulation of a tidal river when available dynamic-monitoring data are insufficient to assess the tidal effect of the river.

  10. 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…

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

    PubMed

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

    2009-12-01

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

  12. 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.

  13. Links Related to the Indoor Air Quality Building Education and Assessment Model

    EPA Pesticide Factsheets

    The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.

  14. Remote Sensing Characterization of the Urban Landscape for Improvement of Air Quality Modeling

    NASA Technical Reports Server (NTRS)

    Quattrochi, Dale A.; Estes, Maurice G., Jr.; Khan, Maudood

    2005-01-01

    The urban landscape is inherently complex and this complexity is not adequately captured in air quality models, particularly the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone pollutant levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban growth projections as improved inputs to the meteorology component of the CMAQ model focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include "business as usual" and "smart growth" scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, in moderating ground-level ozone and air temperature, compared to "business as usual" simulations in which heat island mitigation strategies are not applied. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the (CMAQ) modeling schemes. Use of these data has been found to better characterize low densityhburban development as compared with USGS 1 km land use/land cover data that have traditionally been used in modeling. Air quality prediction for fiture scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the state Environmental Protection agency to evaluate how these

  15. Sediment delivery estimates in water quality models altered by resolution and source of topographic data.

    PubMed

    Beeson, Peter C; Sadeghi, Ali M; Lang, Megan W; Tomer, Mark D; Daughtry, Craig S T

    2014-01-01

    Moderate-resolution (30-m) digital elevation models (DEMs) are normally used to estimate slope for the parameterization of non-point source, process-based water quality models. These models, such as the Soil and Water Assessment Tool (SWAT), use the Universal Soil Loss Equation (USLE) and Modified USLE to estimate sediment loss. The slope length and steepness factor, a critical parameter in USLE, significantly affects sediment loss estimates. Depending on slope range, a twofold difference in slope estimation potentially results in as little as 50% change or as much as 250% change in the LS factor and subsequent sediment estimation. Recently, the availability of much finer-resolution (∼3 m) DEMs derived from Light Detection and Ranging (LiDAR) data has increased. However, the use of these data may not always be appropriate because slope values derived from fine spatial resolution DEMs are usually significantly higher than slopes derived from coarser DEMs. This increased slope results in considerable variability in modeled sediment output. This paper addresses the implications of parameterizing models using slope values calculated from DEMs with different spatial resolutions (90, 30, 10, and 3 m) and sources. Overall, we observed over a 2.5-fold increase in slope when using a 3-m instead of a 90-m DEM, which increased modeled soil loss using the USLE calculation by 130%. Care should be taken when using LiDAR-derived DEMs to parameterize water quality models because doing so can result in significantly higher slopes, which considerably alter modeled sediment loss. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

  16. 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.

  17. Ensuring quality and safety.

    PubMed

    Reid, Jerry

    2010-01-01

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

  18. A description and evaluation of an air quality model nested within global and regional composition-climate models using MetUM

    NASA Astrophysics Data System (ADS)

    Neal, Lucy S.; Dalvi, Mohit; Folberth, Gerd; McInnes, Rachel N.; Agnew, Paul; O'Connor, Fiona M.; Savage, Nicholas H.; Tilbee, Marie

    2017-11-01

    There is a clear need for the development of modelling frameworks for both climate change and air quality to help inform policies for addressing these issues simultaneously. This paper presents an initial attempt to develop a single modelling framework, by introducing a greater degree of consistency in the meteorological modelling framework by using a two-step, one-way nested configuration of models, from a global composition-climate model (GCCM) (140 km resolution) to a regional composition-climate model covering Europe (RCCM) (50 km resolution) and finally to a high (12 km) resolution model over the UK (AQUM). The latter model is used to produce routine air quality forecasts for the UK. All three models are based on the Met Office's Unified Model (MetUM). In order to better understand the impact of resolution on the downscaling of projections of future climate and air quality, we have used this nest of models to simulate a 5-year period using present-day emissions and under present-day climate conditions. We also consider the impact of running the higher-resolution model with higher spatial resolution emissions, rather than simply regridding emissions from the RCCM. We present an evaluation of the models compared to in situ air quality observations over the UK, plus a comparison against an independent 1 km resolution gridded dataset, derived from a combination of modelling and observations, effectively producing an analysis of annual mean surface pollutant concentrations. We show that using a high-resolution model over the UK has some benefits in improving air quality modelling, but that the use of higher spatial resolution emissions is important to capture local variations in concentrations, particularly for primary pollutants such as nitrogen dioxide and sulfur dioxide. For secondary pollutants such as ozone and the secondary component of PM10, the benefits of a higher-resolution nested model are more limited and reasons for this are discussed. This study

  19. Performance measures and criteria for hydrologic and water quality models

    USDA-ARS?s Scientific Manuscript database

    Performance measures and criteria are essential for model calibration and validation. This presentation will include a summary of one of the papers that will be included in the 2014 Hydrologic and Water Quality Model Calibration & Validation Guidelines Special Collection of the ASABE Transactions. T...

  20. PREFACE SPECIAL ISSUE ON MODEL EVALUATION: EVALUATION OF URBAN AND REGIONAL EULERIAN AIR QUALITY MODELS

    EPA Science Inventory

    The "Preface to the Special Edition on Model Evaluation: Evaluation of Urban and Regional Eulerian Air Quality Models" is a brief introduction to the papers included in a special issue of Atmospheric Environment. The Preface provides a background for the papers, which have thei...