Deep learning architecture for air quality predictions.

PubMed

Li, Xiang; Peng, Ling; Hu, Yuan; Shao, Jing; Chi, Tianhe

2016-11-01

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.

A fuzzy-logic based decision-making approach for identification of groundwater quality based on groundwater quality indices.

PubMed

Vadiati, M; Asghari-Moghaddam, A; Nakhaei, M; Adamowski, J; Akbarzadeh, A H

2016-12-15

Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, specifically fuzzy inference systems, have proven useful in evaluating groundwater quality in uncertain and complex hydrogeological systems. In the present study, a Mamdani fuzzy-logic-based decision-making approach was developed to assess groundwater quality based on relevant indices. In an effort to develop a set of new hybrid fuzzy indices for groundwater quality assessment, a Mamdani fuzzy inference model was developed with widely-accepted groundwater quality indices: the Groundwater Quality Index (GQI), the Water Quality Index (WQI), and the Ground Water Quality Index (GWQI). In an effort to present generalized hybrid fuzzy indices a significant effort was made to employ well-known groundwater quality index acceptability ranges as fuzzy model output ranges rather than employing expert knowledge in the fuzzification of output parameters. The proposed approach was evaluated for its ability to assess the drinking water quality of 49 samples collected seasonally from groundwater resources in Iran's Sarab Plain during 2013-2014. Input membership functions were defined as "desirable", "acceptable" and "unacceptable" based on expert knowledge and the standard and permissible limits prescribed by the World Health Organization. Output data were categorized into multiple categories based on the GQI (5 categories), WQI (5 categories), and GWQI (3 categories). Given the potential of fuzzy models to minimize uncertainties, hybrid fuzzy-based indices produce significantly more accurate assessments of groundwater quality than traditional indices. The developed models' accuracy was assessed and a comparison of the performance indices demonstrated the Fuzzy Groundwater Quality Index model to be more accurate than both the Fuzzy Water Quality Index and Fuzzy Ground Water Quality Index models. This suggests that the new hybrid fuzzy indices developed in this research are reliable and flexible when used in groundwater quality assessment for drinking purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.…

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.

An examination of data quality on QSAR Modeling in regards to the environmental sciences (UNC-CH talk)

EPA Science Inventory

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...

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.

Development and Validation of a Consumer Quality Assessment Instrument for Dentistry.

ERIC Educational Resources Information Center

Johnson, Jeffrey D.; And Others

1990-01-01

This paper reviews the literature on consumer involvement in dental quality assessment, argues for inclusion of this information in quality assessment measures, outlines a conceptual model for measuring dental consumer quality assessment, and presents data relating to the development and validation of an instrument based on the conceptual model.…

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.

Developing and Transitioning Numerical Air Quality Models to Improve Air Quality and Public Health Decision-Making in El Salvador and Costa Rica As Part of the Servir Applied Sciences Team

NASA Astrophysics Data System (ADS)

Thomas, A.; Huff, A. K.; Gomori, S. G.; Sadoff, N.

2014-12-01

In order to enhance the capacity for air quality modeling and improve air quality monitoring and management in the SERVIR Mesoamerica region, members of SERVIR's Applied Sciences Team (AST) are developing national numerical air quality models for El Salvador and Costa Rica. We are working with stakeholders from the El Salvador Ministry of the Environment and Natural Resources (MARN); National University of Costa Rica (UNA); the Costa Rica Ministry of the Environment, Energy, and Telecommunications (MINAET); and Costa Rica National Meteorological Institute (IMN), who are leaders in air quality monitoring and management in the Mesoamerica region. Focusing initially on these institutions will build sustainability in regional modeling activities by developing air quality modeling capability that can be shared with other countries in Mesoamerica. The air quality models are based on the Community Multi-scale Air Quality (CMAQ) model and incorporate meteorological inputs from the Weather Research and Forecasting (WRF) model, as well as national emissions inventories from El Salvador and Costa Rica. The models are being optimized for urban air quality, which is a priority of decision-makers in Mesoamerica. Once experimental versions of the modeling systems are complete, they will be transitioned to servers run by stakeholders in El Salvador and Costa Rica. The numerical air quality models will provide decision support for stakeholders to identify 1) high-priority areas for expanding national ambient air monitoring networks, 2) needed revisions to national air quality regulations, and 3) gaps in national emissions inventories. This project illustrates SERVIR's goal of the transition of science to support decision-making through capacity building in Mesoamerica, and it aligns with the Group on Earth Observations' health societal benefit theme. This presentation will describe technical aspects of the development of the models and outline key steps in our successful collaboration with the Mesoamerican stakeholders, including the processes of identifying and engaging decision-makers, understanding their requirements and limitations, communicating status updates on a regular basis, and providing sufficient training for end users to be able to utilize the models in a decision-making context.

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.

Projecting manpower to attain quality

NASA Technical Reports Server (NTRS)

Rone, K. Y.

1983-01-01

The resulting model is useful as a projection tool but must be validated in order to be used as an on-going software cost engineering tool. A procedure is developed to facilitate the tracking of model projections and actual data to allow the model to be tuned. Finally, since the model must be used in an environment of overlapping development activities on a progression of software elements in development and maintenance, a manpower allocation model is developed for use in a steady state development/maintenance environment. In these days of soaring software costs it becomes increasingly important to properly manage a software development project. One element of the management task is the projection and tracking of manpower required to perform the task. In addition, since the total cost of the task is directly related to the initial quality built into the software, it becomes a necessity to project the development manpower in a way to attain that quality. An approach to projecting and tracking manpower with quality in mind is described.

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…

Enhanced data validation strategy of air quality monitoring network.

PubMed

Harkat, Mohamed-Faouzi; Mansouri, Majdi; Nounou, Mohamed; Nounou, Hazem

2018-01-01

Quick validation and detection of faults in measured air quality data is a crucial step towards achieving the objectives of air quality networks. Therefore, the objectives of this paper are threefold: (i) to develop a modeling technique that can be used to predict the normal behavior of air quality variables and help provide accurate reference for monitoring purposes; (ii) to develop fault detection method that can effectively and quickly detect any anomalies in measured air quality data. For this purpose, a new fault detection method that is based on the combination of generalized likelihood ratio test (GLRT) and exponentially weighted moving average (EWMA) will be developed. GLRT is a well-known statistical fault detection method that relies on maximizing the detection probability for a given false alarm rate. In this paper, we propose to develop GLRT-based EWMA fault detection method that will be able to detect the changes in the values of certain air quality variables; (iii) to develop fault isolation and identification method that allows defining the fault source(s) in order to properly apply appropriate corrective actions. In this paper, reconstruction approach that is based on Midpoint-Radii Principal Component Analysis (MRPCA) model will be developed to handle the types of data and models associated with air quality monitoring networks. All air quality modeling, fault detection, fault isolation and reconstruction methods developed in this paper will be validated using real air quality data (such as particulate matter, ozone, nitrogen and carbon oxides measurement). Copyright © 2017 Elsevier Inc. All rights reserved.

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...

Requirements model for an e-Health awareness portal

NASA Astrophysics Data System (ADS)

Hussain, Azham; Mkpojiogu, Emmanuel O. C.; Nawi, Mohd Nasrun M.

2016-08-01

Requirements engineering is at the heart and foundation of software engineering process. Poor quality requirements inevitably lead to poor quality software solutions. Also, poor requirement modeling is tantamount to designing a poor quality product. So, quality assured requirements development collaborates fine with usable products in giving the software product the needed quality it demands. In the light of the foregoing, the requirements for an e-Ebola Awareness Portal were modeled with a good attention given to these software engineering concerns. The requirements for the e-Health Awareness Portal are modeled as a contribution to the fight against Ebola and helps in the fulfillment of the United Nation's Millennium Development Goal No. 6. In this study requirements were modeled using UML 2.0 modeling technique.

The Development of Evaluation Model for Internal Quality Assurance System of Dramatic Arts College of Bunditpattanasilpa Institute

ERIC Educational Resources Information Center

Sinthukhot, Kittisak; Srihamongkol, Yannapat; Luanganggoon, Nuchwana; Suwannoi, Paisan

2013-01-01

The research purpose was to develop an evaluation model for the internal quality assurance system of the dramatic arts College of Bunditpattanasilpa Institute. The Research and Development method was used as research methodology which was divided into three phases; "developing the model and its guideline", "trying out the actual…

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

PubMed Central

2010-01-01

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

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.

Development of the Next Generation Air Quality Modeling System (20th Joint Conference on the Applications of Air Pollution Meteorology with the A&WMA)

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...

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.

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…

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…

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

PubMed

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

2010-01-01

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

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

EPA Pesticide Factsheets

We have developed new canopy emission algorithms and land use data for BEIS. Simulations with BEIS v3.4 and these updates in CMAQ v5.0.2 are compared these changes to the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and evaluated the simulations against observations. This has resulted in improvements in model evaluations of modeled isoprene, NOx, and O3. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.

Predicting the Overall Spatial Quality of Automotive Audio Systems

NASA Astrophysics Data System (ADS)

Koya, Daisuke

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

U.S. EPA MODELS-3/CMAQ - STATUS AND APPLICATIONS

EPA Science Inventory

An advanced third-generation air quality modeling system has been developed by the Atmospheric Modeling Division of the U.S. EPA. The air quality simulation model at the heart of the system is known as the Community Multiscale Air Quality (CMAQ) Model. It is comprehensive in ...

[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.

Measuring Service Quality in Higher Education: Development of a Hierarchical Model (HESQUAL)

ERIC Educational Resources Information Center

Teeroovengadum, Viraiyan; Kamalanabhan, T. J.; Seebaluck, Ashley Keshwar

2016-01-01

Purpose: This paper aims to develop and empirically test a hierarchical model for measuring service quality in higher education. Design/methodology/approach: The first phase of the study consisted of qualitative research methods and a comprehensive literature review, which allowed the development of a conceptual model comprising 53 service quality…

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...

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...

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…

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

DTIC Science & Technology

2016-07-27

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

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...

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

NASA Astrophysics Data System (ADS)

Koshkina, S.; Ostrinskaya, L.

2018-04-01

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

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

A Systematic Process for Developing High Quality SaaS Cloud Services

NASA Astrophysics Data System (ADS)

La, Hyun Jung; Kim, Soo Dong

Software-as-a-Service (SaaS) is a type of cloud service which provides software functionality through Internet. Its benefits are well received in academia and industry. To fully utilize the benefits, there should be effective methodologies to support the development of SaaS services which provide high reusability and applicability. Conventional approaches such as object-oriented methods do not effectively support SaaS-specific engineering activities such as modeling common features, variability, and designing quality services. In this paper, we present a systematic process for developing high quality SaaS and highlight the essentiality of commonality and variability (C&V) modeling to maximize the reusability. We first define criteria for designing the process model and provide a theoretical foundation for SaaS; its meta-model and C&V model. We clarify the notion of commonality and variability in SaaS, and propose a SaaS development process which is accompanied with engineering instructions. Using the proposed process, SaaS services with high quality can be effectively developed.

Development of Knowledge Management Model for Developing the Internal Quality Assurance in Educational Opportunity Expansion Schools

ERIC Educational Resources Information Center

Pradabpech, Pipat; Chantarasombat, Chalard; Sriampai, Anan

2015-01-01

This research for: 1) to study the current situation and problem in KM, 2) to develop the KM Model, and 3) to evaluate the finding usage of the KM Model for developing the Internal Quality Assurance of Educational Opportunity Expansion Schools. There were 3 Phases of research implementation. Phase 1: the current situation and problem in KM, was…

DEVELOPING EMISSION INVENTORIES FOR BIOMASS BURNING FOR REAL-TIME AND RETROSPECTIVE MODELING

EPA Science Inventory

The EPA uses chemical transport models to simulate historic meteorological episodes for developing air quality management strategies. In addition, chemical transport models are now being used operationally to create air quality forecasts. There are currently a number of methods a...

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.

Development of Techniques and Data for Evaluating Ride Quality, Volume III : Guidelines for Development of Ride-Quality Models and Their Applications

DOT National Transportation Integrated Search

1978-02-01

Ride-quality models for city buses and intercity trains are presented and discussed in terms of their ability to predict passenger comfort and ride acceptability. The report, the last of three volumes, contains procedural guidelines to be employed by...

Performance-Based Service Quality Model: An Empirical Study on Japanese Universities

ERIC Educational Resources Information Center

Sultan, Parves; Wong, Ho

2010-01-01

Purpose: This paper aims to develop and empirically test the performance-based higher education service quality model. Design/methodology/approach: The study develops 67-item instrument for measuring performance-based service quality with a particular focus on the higher education sector. Scale reliability is confirmed using the Cronbach's alpha.…

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

EPA Science Inventory

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

A measurement system for large, complex software programs

NASA Technical Reports Server (NTRS)

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

1994-01-01

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

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.

Preface to QoIS 2009

NASA Astrophysics Data System (ADS)

Comyn-Wattiau, Isabelle; Thalheim, Bernhard

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

PROJECT SUMMARY: DEVELOPMENT OF THE VIRTUAL BEACH MODEL, PHASE I: AN EMPIRICAL MODEL

EPA Science Inventory

Mathematical models based on water-quality and other environmental surrogates may help to provide water quality assessment within a few hours and potentially provide one to three day forecasts, providing beach managers and public-health officials a tool for developing beach-speci...

Quality tracing in meat supply chains

PubMed Central

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

2014-01-01

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

Quality tracing in meat supply chains.

PubMed

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

2014-06-13

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

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.

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.

Implementation of a Quality Assurance Review System for the Scalable Development of Online Courses

ERIC Educational Resources Information Center

Ozdemir, Devrim; Loose, Rich

2014-01-01

With the growing demand for quality online education in the US, developing quality online courses and online programs, and more importantly maintaining this quality, have been an inevitable concern for higher education institutes. Current literature on quality assurance in online education mostly focuses on the development of review models and…

Urban air quality estimation study, phase 1

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

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...

Matrix population models as a tool in development of habitat models

Treesearch

Gregory D. Hayward; David B. McDonald

1997-01-01

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

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

PubMed

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

2015-10-01

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

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.

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.

[Quality process control system of Chinese medicine preparation based on "holistic view"].

PubMed

Wang, Ya-Qi; Jiao, Jiao-Jiao; Wu, Zhen-Feng; Zheng, Qin; Yang, Ming

2018-01-01

"High quality, safety and effectiveness" are the primary principles for the pharmaceutical research and development process in China. The quality of products relies not only on the inspection method, but also on the design and development, process control and standardized management. The quality depends on the process control level. In this paper, the history and current development of quality control of traditional Chinese medicine (TCM) preparations are reviewed systematically. Based on the development model of international drug quality control and the misunderstanding of quality control of TCM preparations, the reasons for impacting the homogeneity of TCM preparations are analyzed and summarized. According to TCM characteristics, efforts were made to control the diversity of TCM, make "unstable" TCM into "stable" Chinese patent medicines, put forward the concepts of "holistic view" and "QbD (quality by design)", so as to create the "holistic, modular, data, standardized" model as the core of TCM preparation quality process control model. Scientific studies shall conform to the actual production of TCM preparations, and be conducive to supporting advanced equipment and technology upgrade, thoroughly applying the scientific research achievements in Chinese patent medicines, and promoting the cluster application and transformation application of TCM pharmaceutical technology, so as to improve the quality and effectiveness of the TCM industry and realize the green development. Copyright© by the Chinese Pharmaceutical Association.

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

EPA Pesticide Factsheets

This presentation provides an example of doing additional work for preprocessing global climate model data for use in regional climate modeling simulations with the Weather Research and Forecasting (WRF) model. In this presentation, results from 15 months of downscaling the Community Earth System Model (CESM) were shown, both using the out-of-the-box downscaling of CESM and also with a modification to setting the inland lake temperatures. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.

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…

Evaluation of future base-flow water-quality conditions in the Hillsborough River, Florida

USGS Publications Warehouse

Fernandez, Mario; Goetz, C.L.; Miller, J.E.

1984-01-01

A one-dimensional, steady-state, water-quality model was developed for a 30.0 mile reach of the Hillsborough River to evaluate water-quality conditions to be expected from future development. The model was calibrated and verified using data collected under critical base-flow conditions in April and December 1978. Dissolved organic nitrogen, nitrate nitrogen, and total and fecal coliforms were modeled for most of the study reach. Model results were used to evaluate the impacts of two typical housing developments on water-quality conditions in Tampa Reservoir. One development is located in the Cypress Creek basin and the other near the upper end of the study reach. Model results show development in the Hillsborough River basin may cause increased total and fecal coliform conditions. Simulated total coliforms at the Tampa water treatment plant for 1-, 3-, and 5-square-mile developments located in the Cypress Creek basin were 3,000, 5,400, and 8,300 colonies per 100 milliliters. Similar developments, however, located near the upper end of the study reach were 2,000, 3,600, and 5,100 colonies per 100 milliliters. Simulated fecal coliforms were 360, 700, and 100 and 180, 350, and 510 colonies per 100 milliliters, respectively. Other constituents modeled showed only minor increases in concentrations. (USGS)

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

PubMed

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

2018-04-01

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

A 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 Institute of Marine Sciences, and the U.S. Geological Survey. Limitations in the modeling framework were clearly identified. These limitations formed the basis for a set of suggestions to refine the Neuse River estuary water-quality model.

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.

Development of Water Quality Forecasting Models Based on the SOM-ANN on TMDL Unit Watershed in Nakdong River

NASA Astrophysics Data System (ADS)

KIM, M.; Kim, J.; Baek, J.; Kim, C.; Shin, H.

2013-12-01

It has being happened as flush flood or red/green tide in various natural phenomena due to climate change and indiscreet development of river or land. Especially, water being very important to man should be protected and managed from water quality pollution, and in water resources management, real-time watershed monitoring system is being operated with the purpose of keeping watch and managing on rivers. It is especially important to monitor and forecast water quality in watershed. A study area selected Nak_K as one site among TMDL unit watershed in Nakdong River. This study is to develop a water quality forecasting model connected with making full use of observed data of 8 day interval from Nakdong River Environment Research Center. When forecasting models for each of the BOD, DO, COD, and chlorophyll-a are established considering correlation of various water quality factors, it is needed to select water quality factors showing highly considerable correlation with each water quality factor which is BOD, DO, COD, and chlorophyll-a. For analyzing the correlation of the factors (reservoir discharge, precipitation, air temperature, DO, BOD, COD, Tw, TN, TP, chlorophyll-a), in this study, self-organizing map was used and cross correlation analysis method was also used for comparing results drawn. Based on the results, each forecasting model for BOD, DO, COD, and chlorophyll-a was developed during the short period as 8, 16, 24, 32 days at 8 day interval. The each forecasting model is based on neural network with back propagation algorithm. That is, the study is connected with self-organizing map for analyzing correlation among various factors and neural network model for forecasting of water quality. It is considerably effective to manage the water quality in plenty of rivers, then, it specially is possible to monitor a variety of accidents in water quality. It will work well to protect water quality and to prevent destruction of the environment becoming more and more serious before occurring.

Gulf of Mexico dissolved oxygen model (GoMDOM) research and quality assurance project plan

EPA Science Inventory

An integrated high resolution mathematical modeling framework is being developed that will link hydrodynamic, atmospheric, and water quality models for the northern Gulf of Mexico. This Research and Quality Assurance Project Plan primarily focuses on the deterministic Gulf of Me...

Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015

USGS Publications Warehouse

Foster, Guy M.; Graham, Jennifer L.

2016-04-06

The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Source-water supplies are treated by a combination of chemical and physical processes to remove contaminants before distribution. Advanced notification of changing water-quality conditions and cyanobacteria and associated toxin and taste-and-odor compounds provides drinking-water treatment facilities time to develop and implement adequate treatment strategies. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas State Water Plan Fund), and the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One, began a study in July 2012 to develop statistical models at two Kansas River sites located upstream from drinking-water intakes. Continuous water-quality monitors have been operated and discrete-water quality samples have been collected on the Kansas River at Wamego (USGS site number 06887500) and De Soto (USGS site number 06892350) since July 2012. Continuous and discrete water-quality data collected during July 2012 through June 2015 were used to develop statistical models for constituents of interest at the Wamego and De Soto sites. Logistic models to continuously estimate the probability of occurrence above selected thresholds were developed for cyanobacteria, microcystin, and geosmin. Linear regression models to continuously estimate constituent concentrations were developed for major ions, dissolved solids, alkalinity, nutrients (nitrogen and phosphorus species), suspended sediment, indicator bacteria (Escherichia coli, fecal coliform, and enterococci), and actinomycetes bacteria. These models will be used to provide real-time estimates of the probability that cyanobacteria and associated compounds exceed thresholds and of the concentrations of other water-quality constituents in the Kansas River. The models documented in this report are useful for characterizing changes in water-quality conditions through time, characterizing potentially harmful cyanobacterial events, and indicating changes in water-quality conditions that may affect drinking-water treatment processes.

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

EPA Pesticide Factsheets

Presentation on the results from the 3 linked models, EPIC (USDA), CMAQ and NEWS to analyze a scenario of increased corn production related to biofuels together with Clean Air Act emission reductions across the US and the resultant effect on nitrogen loading to the Gulf of Mexico from the Mississippi River Basin. This is a demonstration of a capability to connect the N cascade bringing air, land, water together. EPIC = Environmental Policy Integrated Climate model, CMAQ = Community Multiscale Air Quality model, NEWS = Nutrient Export of WaterSheds model. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

EPA Science Inventory

The second phase of the MicroArray Quality Control (MAQC-II) project evaluated common practices for developing and validating microarray-based models aimed at predicting toxicological and clinical endpoints. Thirty-six teams developed classifiers for 13 endpoints - some easy, som...

Defining Strategic and Excellence Bases for the Development of Portuguese Higher Education

ERIC Educational Resources Information Center

Rosa, Maria Joao; Saraiva, Pedro M.; Diz, Henrique

2005-01-01

A self-assessment model was developed for the Portuguese higher education institutions (HEIs) which was based on an empirical study aiming at better understanding their strategic and quality management and innovation practices and tools and on the study of several quality assessment models developed both for HEIs and business organisations. From…

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.)

Comparison of computer models for estimating hydrology and water quality in an agricultural watershed

USDA-ARS?s Scientific Manuscript database

Various computer models, ranging from simple to complex, have been developed to simulate hydrology and water quality from field to watershed scales. However, many users are uncertain about which model to choose when estimating water quantity and quality conditions in a watershed. This study compared...

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).

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…

Prediction of wastewater quality indicators at the inflow to the wastewater treatment plant using data mining methods

NASA Astrophysics Data System (ADS)

Szeląg, Bartosz; Barbusiński, Krzysztof; Studziński, Jan; Bartkiewicz, Lidia

2017-11-01

In the study, models developed using data mining methods are proposed for predicting wastewater quality indicators: biochemical and chemical oxygen demand, total suspended solids, total nitrogen and total phosphorus at the inflow to wastewater treatment plant (WWTP). The models are based on values measured in previous time steps and daily wastewater inflows. Also, independent prediction systems that can be used in case of monitoring devices malfunction are provided. Models of wastewater quality indicators were developed using MARS (multivariate adaptive regression spline) method, artificial neural networks (ANN) of the multilayer perceptron type combined with the classification model (SOM) and cascade neural networks (CNN). The lowest values of absolute and relative errors were obtained using ANN+SOM, whereas the MARS method produced the highest error values. It was shown that for the analysed WWTP it is possible to obtain continuous prediction of selected wastewater quality indicators using the two developed independent prediction systems. Such models can ensure reliable WWTP work when wastewater quality monitoring systems become inoperable, or are under maintenance.

Prediction of specialty coffee cup quality based on near infrared spectra of green coffee beans.

PubMed

Tolessa, Kassaye; Rademaker, Michael; De Baets, Bernard; Boeckx, Pascal

2016-04-01

The growing global demand for specialty coffee increases the need for improved coffee quality assessment methods. Green bean coffee quality analysis is usually carried out by physical (e.g. black beans, immature beans) and cup quality (e.g. acidity, flavour) evaluation. However, these evaluation methods are subjective, costly, time consuming, require sample preparation and may end up in poor grading systems. This calls for the development of a rapid, low-cost, reliable and reproducible analytical method to evaluate coffee quality attributes and eventually chemical compounds of interest (e.g. chlorogenic acid) in coffee beans. The aim of this study was to develop a model able to predict coffee cup quality based on NIR spectra of green coffee beans. NIR spectra of 86 samples of green Arabica beans of varying quality were analysed. Partial least squares (PLS) regression method was used to develop a model correlating spectral data to cupping score data (cup quality). The selected PLS model had a good predictive power for total specialty cup quality and its individual quality attributes (overall cup preference, acidity, body and aftertaste) showing a high correlation coefficient with r-values of 90, 90,78, 72 and 72, respectively, between measured and predicted cupping scores for 20 out of 86 samples. The corresponding root mean square error of prediction (RMSEP) was 1.04, 0.22, 0.27, 0.24 and 0.27 for total specialty cup quality, overall cup preference, acidity, body and aftertaste, respectively. The results obtained suggest that NIR spectra of green coffee beans are a promising tool for fast and accurate prediction of coffee quality and for classifying green coffee beans into different specialty grades. However, the model should be further tested for coffee samples from different regions in Ethiopia and test if one generic or region-specific model should be developed. Copyright © 2015 Elsevier B.V. All rights reserved.

The influence of data curation on QSAR Modeling - examining issues of quality versus quantity of data (American Chemical Society)

EPA Science Inventory

This presentation will examine the impact of data quality on the construction of QSAR models being developed within the EPA‘s National Center for Computational Toxicology. We have developed a public-facing platform to provide access to predictive models. As part of the work we ha...

Quality-by-design III: application of near-infrared spectroscopy to monitor roller compaction in-process and product quality attributes of immediate release tablets.

PubMed

Kona, Ravikanth; Fahmy, Raafat M; Claycamp, Gregg; Polli, James E; Martinez, Marilyn; Hoag, Stephen W

2015-02-01

The objective of this study is to use near-infrared spectroscopy (NIRS) coupled with multivariate chemometric models to monitor granule and tablet quality attributes in the formulation development and manufacturing of ciprofloxacin hydrochloride (CIP) immediate release tablets. Critical roller compaction process parameters, compression force (CFt), and formulation variables identified from our earlier studies were evaluated in more detail. Multivariate principal component analysis (PCA) and partial least square (PLS) models were developed during the development stage and used as a control tool to predict the quality of granules and tablets. Validated models were used to monitor and control batches manufactured at different sites to assess their robustness to change. The results showed that roll pressure (RP) and CFt played a critical role in the quality of the granules and the finished product within the range tested. Replacing binder source did not statistically influence the quality attributes of the granules and tablets. However, lubricant type has significantly impacted the granule size. Blend uniformity, crushing force, disintegration time during the manufacturing was predicted using validated PLS regression models with acceptable standard error of prediction (SEP) values, whereas the models resulted in higher SEP for batches obtained from different manufacturing site. From this study, we were able to identify critical factors which could impact the quality attributes of the CIP IR tablets. In summary, we demonstrated the ability of near-infrared spectroscopy coupled with chemometrics as a powerful tool to monitor critical quality attributes (CQA) identified during formulation development.

“Summary of the Emission Inventories compiled for the ...

EPA Pesticide Factsheets

We present a summary of the emission inventories from the US, Canada, and Mexico developed for the second phase of the Air Quality Model Evaluation International Initiative (AQMEII). Activities in this second phase are focused on the application and evaluation of coupled meteorology-chemistry models over both North America and Europe using common emissions and boundary conditions for all modeling groups for the years of 2006 and 2010. We will compare the emission inventories developed for these two years focusing on the SO2 and NOx reductions over these years and compare with socio-economic data. In addition we will highlight the differences in the inventories for the US and Canada compared with the inventories used in the phase 1 of this project. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollut

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...

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.

CHOOSING A CHEMICAL MECHANISM FOR REGULATORY AND RESEARCH AIR QUALITY MODELING APPLICATIONS

EPA Science Inventory

There are numerous, different chemical mechanisms currently available for use in air quality models, and new mechanisms and versions of mechanisms are continually being developed. The development of Morphecule-type mechanisms will add a near-infinite number of additional mecha...

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

NASA Astrophysics Data System (ADS)

Cobourn, W. Geoffrey

2010-08-01

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

Cost Models for MMC Manufacturing Processes

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

The influence of data curation on QSAR Modeling – examining issues of quality versus quantity of data (SOT)

EPA Science Inventory

The construction 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 ...

Enhancing mathematics teachers' quality through Lesson Study.

PubMed

Lomibao, Laila S

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Starn, J. J.; Belitz, K.

2014-12-01

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

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.

[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.

Cost Estimation of Software Development and the Implications for the Program Manager

DTIC Science & Technology

1992-06-01

Software Lifecycle Model (SLIM), the Jensen System-4 model, the Software Productivity, Quality, and Reliability Estimator ( SPQR \\20), the Constructive...function models in current use are the Software Productivity, Quality, and Reliability Estimator ( SPQR /20) and the Software Architecture Sizing and...Estimator ( SPQR /20) was developed by T. Capers Jones of Software Productivity Research, Inc., in 1985. The model is intended to estimate the outcome

ERD WATERSHED AND WATER QUALITY MODEL DEVELOPMENT AND TECHNICAL SUPPORT PROGRAM

EPA Science Inventory

The ERD has a long history in providing model research and development and technical support to Regions, States and the Office of Water for watersheds/water quality ecosystem research. The ERD efforts are described in major subtasks comprising the Program. Briefly, these are:

Fragmentation of urban forms and the environmental consequences: results from a high-spatial resolution model system

NASA Astrophysics Data System (ADS)

Tang, U. W.; Wang, Z. S.

2008-10-01

Each city has its unique urban form. The importance of urban form on sustainable development has been recognized in recent years. Traditionally, air quality modelling in a city is in a mesoscale with grid resolution of kilometers, regardless of its urban form. This paper introduces a GIS-based air quality and noise model system developed to study the built environment of highly compact urban forms. Compared with traditional mesoscale air quality model system, the present model system has a higher spatial resolution down to individual buildings along both sides of the street. Applying the developed model system in the Macao Peninsula with highly compact urban forms, the average spatial resolution of input and output data is as high as 174 receptor points per km2. Based on this input/output dataset with a high spatial resolution, this study shows that even the highly compact urban forms can be fragmented into a very small geographic scale of less than 3 km2. This is due to the significant temporal variation of urban development. The variation of urban form in each fragment in turn affects air dispersion, traffic condition, and thus air quality and noise in a measurable scale.

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

PubMed

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

2015-01-01

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

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...

EMISSION AND SURFACE EXCHANGE PROCESS

EPA Science Inventory

This task supports the development, evaluation, and application of emission and dry deposition algorithms in air quality simulation models, such as the Models-3/Community Multiscale Air Quality (CMAQ) modeling system. Emission estimates influence greatly the accuracy of air qual...

Development of models to estimate the subgrade and subbase layers' resilient modulus from in situ devices test results for construction control.

DOT National Transportation Integrated Search

2008-04-01

The objective of this study was to develop resilient modulus prediction models for possible application in the quality control/quality assurance (QC/QA) procedures during and after the construction of pavement layers. Field and laboratory testing pro...

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

PubMed

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

2012-07-01

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

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

PubMed

Chuang, Sheuwen; Inder, Kerry

2009-10-24

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

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

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.

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

PubMed

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

2017-03-01

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

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

PubMed

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

2014-01-01

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

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...

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....

DEVELOPMENT OF GUIDELINES FOR CALIBRATING, VALIDATING, AND EVALUATING HYDROLOGIC AND WATER QUALITY MODELS: ASABE ENGINEERING PRACTICE 621

USDA-ARS?s Scientific Manuscript database

Information to support application of hydrologic and water quality (H/WQ) models abounds, yet modelers commonly use arbitrary, ad hoc methods to conduct, document, and report model calibration, validation, and evaluation. Consistent methods are needed to improve model calibration, validation, and e...

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)

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.

MODEL DEVELOPMENT AND TESTING FOR SEMI-VOLATILES (ATRAZINE)

EPA Science Inventory

The Community Multi-Scale Air Quality (CMAQ) model, air quality model within EPA's Models-3 system, can be adapted to simulate the fate of semi-volatile compounds that are emitted into the atmosphere. "Semi-volatile" refers to compounds that partition their mass between two ph...

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.

Emissions and dispersion modeling system (EDMS). Its development and application at airports and airbases

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

Moss, M.T.; Segal, H.M.

1994-06-01

A new complex source microcomputer model has been developed for use at civil airports and Air Force bases. This paper describes both the key features of this model and its application in evaluating the air quality impact of new construction projects at three airports: one in the United States and two in Canada. The single EDMS model replaces the numerous models previously required to assess the air quality impact of pollution sources at airports. EDMS also employs a commercial data base to reduce the time and manpower required to accurately assess and document the air quality impact of airfield operations.more » On July 20, 1993, the U.S. Environmental Protection Agency (EPA) issued the final rule (Federal Register, 7/20/93, page 38816) to add new models to the Guideline on Air Quality Models. At that time EDMS was incorporated into the Guideline as an Appendix A model. 12 refs., 4 figs., 1 tab.« less

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

PubMed

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

2015-07-01

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

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

EPA Pesticide Factsheets

The presentation provides an update on the use of a hybrid methodology that relies on measured values from national monitoring networks and modeled values from CMAQ to produce of maps of total deposition for use in critical loads and other ecological assessments. Additionally, comparisons of the deposition values from the hybrid approach are compared with deposition estimates from other methodologies. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.

Evaluative methodology for comprehensive water quality management planning

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

Dyer, H. L.

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

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...

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.

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.

Environmental Flow for Sungai Johor Estuary

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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.

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.

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.

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

EPA Science Inventory

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

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

COMPUTATIONAL ASPECTS OF THE AIR QUALITY FORECASTING VERSION OF CMAQ (CMAQ-F)

EPA Science Inventory

The air quality forecast version of the Community Modeling Air Quality (CMAQ) model (CMAQ-F) was developed from the public release version of CMAQ (available from http://www.cmascenter.org), and is running operationally at the National Weather Service's National Centers for Envir...

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.

A Completely Blind Video Integrity Oracle.

PubMed

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

2016-01-01

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

Measuring housing quality in the absence of a monetized real estate market.

PubMed

Rindfuss, Ronald R; Piotrowski, Martin; Thongthai, Varachai; Prasartkul, Pramote

2007-03-01

Measuring housing quality or value or both has been a weak component of demographic and development research in less developed countries that lack an active real estate (housing) market. We describe a new method based on a standardized subjective rating process. It is designed to be used in settings that do not have an active, monetized housing market. The method is applied in an ongoing longitudinal study in north-east Thailand and could be straightforwardly used in many other settings. We develop a conceptual model of the process whereby households come to reside in high-quality or low-quality housing units. We use this theoretical model in conjunction with longitudinal data to show that the new method of measuring housing quality behaves as theoretically expected, thus providing evidence of face validity.

Non-linear assessment and deficiency of linear relationship for healthcare industry

NASA Astrophysics Data System (ADS)

Nordin, N.; Abdullah, M. M. A. B.; Razak, R. C.

2017-09-01

This paper presents the development of the non-linear service satisfaction model that assumes patients are not necessarily satisfied or dissatisfied with good or poor service delivery. With that, compliment and compliant assessment is considered, simultaneously. Non-linear service satisfaction instrument called Kano-Q and Kano-SS is developed based on Kano model and Theory of Quality Attributes (TQA) to define the unexpected, hidden and unspoken patient satisfaction and dissatisfaction into service quality attribute. A new Kano-Q and Kano-SS algorithm for quality attribute assessment is developed based satisfaction impact theories and found instrumentally fit the reliability and validity test. The results were also validated based on standard Kano model procedure before Kano model and Quality Function Deployment (QFD) is integrated for patient attribute and service attribute prioritization. An algorithm of Kano-QFD matrix operation is developed to compose the prioritized complaint and compliment indexes. Finally, the results of prioritized service attributes are mapped to service delivery category to determine the most prioritized service delivery that need to be improved at the first place by healthcare service provider.

Developing a theoretical model and questionnaire survey instrument to measure the success of electronic health records in residential aged care.

PubMed

Yu, Ping; Qian, Siyu

2018-01-01

Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: system quality, information quality, service quality, use, user satisfaction and net benefits. Two variables training and self-efficacy were also incorporated into the model. A questionnaire survey instrument was designed to measure the eight variables in the model. After a pilot test, the measurement scale was used to collect data from 243 nursing staff members in 10 residential aged care homes belonging to three management groups in Australia. Partial least squares path modeling was conducted to validate the model. The validated EHR systems success model predicts the impact of the four antecedent variables-training, self-efficacy, system quality and information quality-on the net benefits, the indicator of EHR systems success, through the intermittent variables use and user satisfaction. A 24-item measurement scale was developed to quantitatively evaluate the performance of an EHR system. The parsimonious EHR systems success model and the measurement scale can be used to benchmark EHR systems success across organizations and units and over time.

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...

Quality of life as a cancer nursing outcome variable.

PubMed

Padilla, G V; Grant, M M

1985-10-01

A reliable and valid multidimensional instrument for measuring quality of life in cancer patients has been developed. Furthermore, a model has been offered that describes how quality of life works as an outcome variable. Using this model, predictions were made of how nursing interventions may directly or indirectly impact on quality of life. Initial testing of the model using data from 135 colostomy patients showed how satisfaction with nursing care and personal control act as cognitive mediators of self-worth, which then impacts on dimensions of quality of life.

Toward a food service quality management system for compliance with the Mediterranean dietary model.

PubMed

Grigoroudis, Evangelos; Psaroudaki, Antonia; Diakaki, Christina

2013-01-01

The traditional diet of Cretan people in the 1960s is the basis of the Mediterranean dietary model. This article investigates the potential of this model to inspire proposals of meals by food-serving businesses, and suggests a methodology for the development of a quality management system, which will certify the delivery of food service according to this dietary model. The proposed methodology is built upon the principles and structure of the ISO 9001:2008 quality standard to enable integration with other quality, environmental, and food safety management systems.

Measuring and Costing Quality in Education: Using Quality and Productivity Methods To Improve Schools.

ERIC Educational Resources Information Center

Spanbauer, Stanley J.

The Measurement and Costing Model (MCM) described in this book was developed and tested at Fox Valley Technical College (FVTC), Wisconsin, to enhance the college's quality improvement process and to serve as a guide to other institutions interested in improving their quality. The book presents a description of the model and outlines seven steps…

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.

Modeling the Effects of Conservation Tillage on Water Quality at the Field Scale

USDA-ARS?s Scientific Manuscript database

The development and application of predictive tools to quantitatively assess the effects of tillage and related management activities should be carefully tested against high quality field data. This study reports on: 1) the calibration and validation of the Root Zone Water Quality Model (RZWQM) to a...

Planning and design of studies for river-quality assessment in the Truckee and Carson River basins, California and Nevada

USGS Publications Warehouse

Nowlin, Jon O.; Brown, W.M.; Smith, L.H.; Hoffman, R.J.

1980-01-01

The objectives of the Geological Survey 's river-quality assessment in the Truckee and Carson River basins in California and Nevada are to identify the significant resource management problems; to develop techniques to assess the problems; and to effectively communicate results to responsible managers. Six major elements of the assessment to be completed by October 1981 are (1) a detailing of the legal, institutional, and structural development of water resources in the basins and the current problems and conflicts; (2) a compilation and synthesis of the physical hydrology of the basins; (3) development of a special workshop approach to involve local management in the direction and results of the study; (4) development of a comprehensive streamflow model emcompassing both basins to provide a quantitative hydrologic framework for water-quality analysis; (5) development of a water-quality transport model for selected constituents and characteristics on selected reaches of the Truckee River; and (6) a detailed examination of selected fish habitats for specified reaches of the Truckee River. Progress will be periodically reported in reports, maps, computer data files, mathematical models, a bibliography, and public presentations. In building a basic framework to develop techniques, the basins were viewed as a single hydrologic unit because of interconnecting diversion structures. The framework comprises 13 hydrographic subunits to facilitate modeling and sampling. Several significant issues beyond the scope of the assessment were considered as supplementary proposals; water-quality loadings in Truckee and Carson Rivers, urban runoff in Reno and management alternatives, and a model of limnological processes in Lahontan Reservoir. (USGS)

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

PubMed Central

2014-01-01

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

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

PubMed

Cao, Renzhi; Wang, Zheng; Cheng, Jianlin

2014-04-15

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

Linking Global and Regional Models to Simulate U.S. Air Quality in the Year 2050

EPA Science Inventory

The potential impact of global climate change on future air quality in the United States is investigated with global and regional-scale models. Regional climate model scenarios are developed by dynamically downscaling the outputs from a global chemistry and climate model and are...

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

EPA Science Inventory

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

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

Treesearch

Ian R. Scott

2009-01-01

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

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.

Combined effect of noise and vibration on passenger acceptance

NASA Technical Reports Server (NTRS)

Leatherwood, J. D.

1984-01-01

An extensive research program conducted at NASA Langley Research Center to develop a comprehensive model of passenger comfort response to combined noise and vibration environments has been completed. This model was developed for use in the prediction and/or assessment of vehicle ride quality and as a ride quality design tool. The model has the unique capability to transform individual elements of vehicle interior noise and vibration into subjective units and combining the subjective units to produce a total subjective discomfort index as well as the other useful subjective indices. This paper summarizes the basic approach used in the development of the NASA ride comfort model, presents some of the more fundamental results obtained, describes several application of the model to operational vehicles, and discusses a portable, self-contained ride quality meter system that is a direct hardware/software implementation of the NASA comfort algorithm.

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®.

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 prediction, and DockQ should be useful in a similar development in the protein docking field. DockQ is available at http://github.com/bjornwallner/DockQ/ PMID:27560519

A method of groundwater quality assessment based on fuzzy network-CANFIS and geographic information system (GIS)

NASA Astrophysics Data System (ADS)

Gholami, V.; Khaleghi, M. R.; Sebghati, M.

2017-11-01

The process of water quality testing is money/time-consuming, quite important and difficult stage for routine measurements. Therefore, use of models has become commonplace in simulating water quality. In this study, the coactive neuro-fuzzy inference system (CANFIS) was used to simulate groundwater quality. Further, geographic information system (GIS) was used as the pre-processor and post-processor tool to demonstrate spatial variation of groundwater quality. All important factors were quantified and groundwater quality index (GWQI) was developed. The proposed model was trained and validated by taking a case study of Mazandaran Plain located in northern part of Iran. The factors affecting groundwater quality were the input variables for the simulation, whereas GWQI index was the output. The developed model was validated to simulate groundwater quality. Network validation was performed via comparison between the estimated and actual GWQI values. In GIS, the study area was separated to raster format in the pixel dimensions of 1 km and also by incorporation of input data layers of the Fuzzy Network-CANFIS model; the geo-referenced layers of the effective factors in groundwater quality were earned. Therefore, numeric values of each pixel with geographical coordinates were entered to the Fuzzy Network-CANFIS model and thus simulation of groundwater quality was accessed in the study area. Finally, the simulated GWQI indices using the Fuzzy Network-CANFIS model were entered into GIS, and hence groundwater quality map (raster layer) based on the results of the network simulation was earned. The study's results confirm the high efficiency of incorporation of neuro-fuzzy techniques and GIS. It is also worth noting that the general quality of the groundwater in the most studied plain is fairly low.

Development of Innovative Business Model of Modern Manager's Qualities

ERIC Educational Resources Information Center

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

2016-01-01

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

Application of Wavelet Filters in an Evaluation of ...

EPA Pesticide Factsheets

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

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 transportation plans will affect fbture air quality.

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.

Development of an Interactive Computer-Based Learning Strategy to Assist in Teaching Water Quality Modelling

ERIC Educational Resources Information Center

Zigic, Sasha; Lemckert, Charles J.

2007-01-01

The following paper presents a computer-based learning strategy to assist in introducing and teaching water quality modelling to undergraduate civil engineering students. As part of the learning strategy, an interactive computer-based instructional (CBI) aid was specifically developed to assist students to set up, run and analyse the output from a…

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

EPA Science Inventory

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

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 University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

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.

Assessing Cumulative Impacts of Coal Bed Methane Development on Surface Water Quality and its Suitability for Irrigation in the Powder River Basin

NASA Astrophysics Data System (ADS)

Dawson, H. E.

2003-12-01

This paper presents a mass balance approach to assessing the cumulative impacts of discharge from Coal Bed Methane (CBM) wells on surface water quality and its suitability for irrigation in the Powder River Basin. Key water quality parameters for predicting potential effects of CBM development on irrigated agriculture are sodicity, expressed as sodium adsorption ratio (SAR) and salinity, expressed as electrical conductivity (EC). The assessment was performed with the aid of a spreadsheet model, which was designed to estimate steady-state SAR and EC at gauged stream locations after mixing with CBM produced water. Model input included ambient stream water quality and flow, CBM produced water quality and discharge rates, conveyance loss (quantity of water loss that may occur between the discharge point and the receiving streams), beneficial uses, regulatory thresholds, and discharge allocation at state-line boundaries. Historical USGS data were used to establish ambient stream water quality and flow conditions. The resultant water quality predicted for each stream station included the cumulative discharge of CBM produced water in all reaches upstream of the station. Model output was presented in both tabular and graphical formats, and indicated the suitability of pre- and post-mixing water quality for irrigation. Advantages and disadvantages of the spreadsheet model are discussed. This approach was used by federal agencies to support the development of the January 2003 Environmental Impact Statements (EIS) for the Wyoming and Montana portions of the Powder River Basin.

Doctors or technicians: assessing quality of medical education

PubMed Central

Hasan, Tayyab

2010-01-01

Medical education institutions usually adapt industrial quality management models that measure the quality of the process of a program but not the quality of the product. The purpose of this paper is to analyze the impact of industrial quality management models on medical education and students, and to highlight the importance of introducing a proper educational quality management model. Industrial quality management models can measure the training component in terms of competencies, but they lack the educational component measurement. These models use performance indicators to assess their process improvement efforts. Researchers suggest that the performance indicators used in educational institutions may only measure their fiscal efficiency without measuring the quality of the educational experience of the students. In most of the institutions, where industrial models are used for quality assurance, students are considered as customers and are provided with the maximum services and facilities possible. Institutions are required to fulfill a list of recommendations from the quality control agencies in order to enhance student satisfaction and to guarantee standard services. Quality of medical education should be assessed by measuring the impact of the educational program and quality improvement procedures in terms of knowledge base development, behavioral change, and patient care. Industrial quality models may focus on academic support services and processes, but educational quality models should be introduced in parallel to focus on educational standards and products. PMID:23745059

Doctors or technicians: assessing quality of medical education.

PubMed

Hasan, Tayyab

2010-01-01

Medical education institutions usually adapt industrial quality management models that measure the quality of the process of a program but not the quality of the product. The purpose of this paper is to analyze the impact of industrial quality management models on medical education and students, and to highlight the importance of introducing a proper educational quality management model. Industrial quality management models can measure the training component in terms of competencies, but they lack the educational component measurement. These models use performance indicators to assess their process improvement efforts. Researchers suggest that the performance indicators used in educational institutions may only measure their fiscal efficiency without measuring the quality of the educational experience of the students. In most of the institutions, where industrial models are used for quality assurance, students are considered as customers and are provided with the maximum services and facilities possible. Institutions are required to fulfill a list of recommendations from the quality control agencies in order to enhance student satisfaction and to guarantee standard services. Quality of medical education should be assessed by measuring the impact of the educational program and quality improvement procedures in terms of knowledge base development, behavioral change, and patient care. Industrial quality models may focus on academic support services and processes, but educational quality models should be introduced in parallel to focus on educational standards and products.

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.

Quality metrics for sensor images

NASA Technical Reports Server (NTRS)

Ahumada, AL

1993-01-01

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

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.…

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…

VOLATILE ORGANIC COMPOUND EMISSIONS FROM LATEX PAINT-PART 2. TEST HOUSE STUDIES AND INDOOR AIR QUALITY (IAQ) MODELING

EPA Science Inventory

Emission models developed using small chamber data were combined with an Indoor Air Quality (IAQ) model to analyze the impact of volatile organic compound (VOC) emissions from latex paint on indoor environments. Test house experiments were conducted to verify the IAQ model's pred...

The Meteorology-Chemistry Interface Processor (MCIP) for the CMAQ Modeling System: Updates through MCIPv3.4.1

EPA Science Inventory

The Community Multiscale Air Quality (CMAQ) modeling system is a state-of-the science regional air quality modeling system. The CMAQ modeling system has been primarily developed by the U.S. Environmental Protection Agency, and it has been publically and freely available for more...

APPLICATION OF THE MODELS-3 COMMUNITY MULTI-SCALE AIR QUALITY (CMAQ) MODEL SYSTEM TO SOS/NASHVILLE 1999

EPA Science Inventory

The Models-3 Community Multi-scale Air Quality (CMAQ) model, first released by the USEPA in 1999 (Byun and Ching. 1999), continues to be developed and evaluated. The principal components of the CMAQ system include a comprehensive emission processor known as the Sparse Matrix O...

Water quantity and quality model for the evaluation of water-management strategies in the Netherlands: application to the province of Friesland

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

Brinkman, J.J.; Griffioen, P.S.; Groot, S.

1987-03-01

The Netherlands have a rather complex water-management system consisting of a number of major rivers, canals, lakes and ditches. Water-quantity management on a regional scale is necessary for an effective water-quality policy. To support water management, a computer model was developed that includes both water quality and water quantity, based on three submodels: ABOPOL for the water movement, DELWAQ for the calculation of water quality variables and BLOOM-II for the phytoplankton growth. The northern province of Friesland was chosen as a test case for the integrated model to be developed, where water quality is highly related to the water distributionmore » and the main trade-off is minimizing the intake of (eutrophicated) alien water in order to minimize external nutrient load and maximizing the intake in order to flush channels and lakes. The results of the application of these models to this and to a number of hypothetical future situations are described.« less

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.

Information security system quality assessment through the intelligent tools

NASA Astrophysics Data System (ADS)

Trapeznikov, E. V.

2018-04-01

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

Kinetics model development of cocoa bean fermentation

NASA Astrophysics Data System (ADS)

Kresnowati, M. T. A. P.; Gunawan, Agus Yodi; Muliyadini, Winny

2015-12-01

Although Indonesia is one of the biggest cocoa beans producers in the world, Indonesian cocoa beans are oftenly of low quality and thereby frequently priced low in the world market. In order to improve the quality, adequate post-harvest cocoa processing techniques are required. Fermentation is the vital stage in series of cocoa beans post harvest processing which could improve the quality of cocoa beans, in particular taste, aroma, and colours. During the fermentation process, combination of microbes grow producing metabolites that serve as the precursors for cocoa beans flavour. Microbial composition and thereby their activities will affect the fermentation performance and influence the properties of cocoa beans. The correlation could be reviewed using a kinetic model that includes unstructured microbial growth, substrate utilization and metabolic product formation. The developed kinetic model could be further used to design cocoa bean fermentation process to meet the expected quality. Further the development of kinetic model of cocoa bean fermentation also serve as a good case study of mixed culture solid state fermentation, that has rarely been studied. This paper presents the development of a kinetic model for solid-state cocoa beans fermentation using an empirical approach. Series of lab scale cocoa bean fermentations, either natural fermentations without starter addition or fermentations with mixed yeast and lactic acid bacteria starter addition, were used for model parameters estimation. The results showed that cocoa beans fermentation can be modelled mathematically and the best model included substrate utilization, microbial growth, metabolites production and its transport. Although the developed model still can not explain the dynamics in microbial population, this model can sufficiently explained the observed changes in sugar concentration as well as metabolic products in the cocoa bean pulp.

Forecasting relative impacts of land use on anadromous fish habitat to guide conservation planning.

PubMed

Lohse, Kathleen A; Newburn, David A; Opperman, Jeff J; Merenlender, Adina M

2008-03-01

Land use change can adversely affect water quality and freshwater ecosystems, yet our ability to predict how systems will respond to different land uses, particularly rural-residential development, is limited by data availability and our understanding of biophysical thresholds. In this study, we use spatially explicit parcel-level data to examine the influence of land use (including urban, rural-residential, and vineyard) on salmon spawning substrate quality in tributaries of the Russian River in California. We develop a land use change model to forecast the probability of losses in high-quality spawning habitat and recommend priority areas for incentive-based land conservation efforts. Ordinal logistic regression results indicate that all three land use types were negatively associated with spawning substrate quality, with urban development having the largest marginal impact. For two reasons, however, forecasted rural-residential and vineyard development have much larger influences on decreasing spawning substrate quality relative to urban development. First, the land use change model estimates 10 times greater land use conversion to both rural-residential and vineyard compared to urban. Second, forecasted urban development is concentrated in the most developed watersheds, which already have poor spawning substrate quality, such that the marginal response to future urban development is less significant. To meet the goals of protecting salmonid spawning habitat and optimizing investments in salmon recovery, we suggest investing in watersheds where future rural-residential development and vineyards threaten high-quality fish habitat, rather than the most developed watersheds, where land values are higher.

Integrating multiple data sources in species distribution modeling: A framework for data fusion

USGS Publications Warehouse

Pacifici, Krishna; Reich, Brian J.; Miller, David A.W.; Gardner, Beth; Stauffer, Glenn E.; Singh, Susheela; McKerrow, Alexa; Collazo, Jaime A.

2017-01-01

The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeoff between data quality and quantity. Recently several authors have developed approaches for jointly modeling two sources of data (one of high quality and one of lesser quality). We extend their work by allowing for explicit spatial autocorrelation in occurrence and detection error using a Multivariate Conditional Autoregressive (MVCAR) model and develop three models that share information in a less direct manner resulting in more robust performance when the auxiliary data is of lesser quality. We describe these three new approaches (“Shared,” “Correlation,” “Covariates”) for combining data sources and show their use in a case study of the Brown-headed Nuthatch in the Southeastern U.S. and through simulations. All three of the approaches which used the second data source improved out-of-sample predictions relative to a single data source (“Single”). When information in the second data source is of high quality, the Shared model performs the best, but the Correlation and Covariates model also perform well. When the information quality in the second data source is of lesser quality, the Correlation and Covariates model performed better suggesting they are robust alternatives when little is known about auxiliary data collected opportunistically or through citizen scientists. Methods that allow for both data types to be used will maximize the useful information available for estimating species distributions.

THE LAKE MICHIGAN MASS BALANCE PROJECT: QUALITY ASSURANCE PLAN FOR MATHEMATICAL MODELLING

EPA Science Inventory

This report documents the quality assurance process for the development and application of the Lake Michigan Mass Balance Models. The scope includes the overall modeling framework as well as the specific submodels that are linked to form a comprehensive synthesis of physical, che...

Development of Gridded Fields of Urban Canopy Parameters for Advanced Urban Meteorological and Air Quality Models

EPA Science Inventory

Urban dispersion and air quality simulation models applied at various horizontal scales require different levels of fidelity for specifying the characteristics of the underlying surfaces. As the modeling scales approach the neighborhood level (~1 km horizontal grid spacing), the...

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

EPA Science Inventory

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

Research on quality metrics of wireless adaptive video streaming

NASA Astrophysics Data System (ADS)

Li, Xuefei

2018-04-01

With the development of wireless networks and intelligent terminals, video traffic has increased dramatically. Adaptive video streaming has become one of the most promising video transmission technologies. For this type of service, a good QoS (Quality of Service) of wireless network does not always guarantee that all customers have good experience. Thus, new quality metrics have been widely studies recently. Taking this into account, the objective of this paper is to investigate the quality metrics of wireless adaptive video streaming. In this paper, a wireless video streaming simulation platform with DASH mechanism and multi-rate video generator is established. Based on this platform, PSNR model, SSIM model and Quality Level model are implemented. Quality Level Model considers the QoE (Quality of Experience) factors such as image quality, stalling and switching frequency while PSNR Model and SSIM Model mainly consider the quality of the video. To evaluate the performance of these QoE models, three performance metrics (SROCC, PLCC and RMSE) which are used to make a comparison of subjective and predicted MOS (Mean Opinion Score) are calculated. From these performance metrics, the monotonicity, linearity and accuracy of these quality metrics can be observed.

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

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

PubMed

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

2018-05-01

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

School Development Applications in Turkey

ERIC Educational Resources Information Center

Hosgörür, Vural

2014-01-01

This study aims to define and explain the establishment, functioning and problems of school development management teams (SDMTs), similar to quality circles used in total quality management practices, for the purposes of continuous development and improvement of schools on the basis of the planned school development model. This is a qualitative…

WILDFIRE EMISSION MODELING: INTEGRATING BLUESKY AND SMOKE

EPA Science Inventory

Atmospheric chemical transport models are used to simulate historic meteorological episodes for developing air quality management strategies. Wildland fire emissions need to be characterized accurately to achieve these air quality management goals. The temporal and spatial esti...

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

USDA-ARS?s Scientific Manuscript database

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

Nurturing Quality of Higher Education through National Ranking: A Potential Empowerment Model for Developing Countries

ERIC Educational Resources Information Center

Kusumastuti, Dyah; Idrus, Nirwan

2017-01-01

This paper reviews the recently introduced National Higher Education ranking system in Indonesia in order to evaluate its potential as a sustainable model to improve the quality of higher education in the country. It is a scaffold towards an established world-universities ranking system that may prove formidable for a developing country. This…

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.

Perceptions of Parent-Child Attachment Relationships and Friendship Qualities: Predictors of Romantic Relationship Involvement and Quality in Adolescence.

PubMed

Kochendorfer, Logan B; Kerns, Kathryn A

2017-05-01

Relationships with parents and friends are important contexts for developing romantic relationship skills. Parents and friends may influence both the timing of involvement and the quality of romantic relationships. Three models of the joint influence of parents and friends (direct effects model, mediation model, and moderator model) have been proposed. The present study uses data from a longitudinal study (n = 1012; 49.8% female; 81.1% Caucasian) to examine how attachment and friendship quality at age 10 years predict romantic relationship involvement and quality at ages 12 and 15 years. The results supported the direct effects model, with attachment and friendship quality uniquely predicting different romantic relationship outcomes. The findings provide further support for the important influence of family and friends on early romantic relationships.

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.

Mesh quality oriented 3D geometric vascular modeling based on parallel transport frame.

PubMed

Guo, Jixiang; Li, Shun; Chui, Yim Pan; Qin, Jing; Heng, Pheng Ann

2013-08-01

While a number of methods have been proposed to reconstruct geometrically and topologically accurate 3D vascular models from medical images, little attention has been paid to constantly maintain high mesh quality of these models during the reconstruction procedure, which is essential for many subsequent applications such as simulation-based surgical training and planning. We propose a set of methods to bridge this gap based on parallel transport frame. An improved bifurcation modeling method and two novel trifurcation modeling methods are developed based on 3D Bézier curve segments in order to ensure the continuous surface transition at furcations. In addition, a frame blending scheme is implemented to solve the twisting problem caused by frame mismatch of two successive furcations. A curvature based adaptive sampling scheme combined with a mesh quality guided frame tilting algorithm is developed to construct an evenly distributed, non-concave and self-intersection free surface mesh for vessels with distinct radius and high curvature. Extensive experiments demonstrate that our methodology can generate vascular models with better mesh quality than previous methods in terms of surface mesh quality criteria. Copyright © 2013 Elsevier Ltd. All rights reserved.

PREDICTIVE ORGANOPHOSPHORUS (OP) PESTICIDE QSARS AND PBPK/PD MODELS FOR RISK ASSESSMENT OF SUSCEPTIBLE SUB-POPULATIONS

EPA Science Inventory

Successful use of the Exposure Related Dose Estimating Model (ERDEM) in risk assessment of susceptible human sub-populations, e.g., infants and children, requires input of quality experimental data. In the clear absence of quality data, PBPK models can be developed and possibl...

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

EPA Science Inventory

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

Progress on Implementing Additional Physics Schemes into MPAS-A v5.1 for Next Generation Air Quality Modeling

EPA Science Inventory

The U.S. Environmental Protection Agency (USEPA) has a team of scientists developing a next generation air quality modeling system employing the Model for Prediction Across Scales – Atmosphere (MPAS-A) as its meteorological foundation. Several preferred physics schemes and ...

Three-dimensional numerical modeling of water quality and sediment-associated processes in natural lakes

USDA-ARS?s Scientific Manuscript database

This chapter presents the development and application of a three-dimensional water quality model for predicting the distributions of nutrients, phytoplankton, dissolved oxygen, etc., in natural lakes. In this model, the computational domain was divided into two parts: the water column and the bed se...

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.

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

ERIC Educational Resources Information Center

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

2000-01-01

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

Web 2.0--E-Learning 2.0--Quality 2.0? Quality for New Learning Cultures

ERIC Educational Resources Information Center

Ehlers, Ulf Daniel

2009-01-01

Purpose: The purpose of this paper is to analyse the changes taking place when learning moves from a transmissive learning model to a collaborative and reflective learning model and proposes consequences for quality development. Design/methodology/approach: The paper summarises relevant research in the field of e-learning to outline the…

Development Design Model of Academic Quality Assurance at Private Islamic University Jakarta Indonesia

ERIC Educational Resources Information Center

Suprihatin, Krebet; Bin Mohamad Yusof, Hj. Abdul Raheem

2015-01-01

This study aims to evaluate the practice of academic quality assurance in design model based on seven aspects of quality are: curriculum design, teaching and learning, student assessment, student selection, support services, learning resources, and continuous improvement. The design study was conducted in two stages. The first stage is to obtain…

DEVELOPMENT OF MESOSCALE AIR QUALITY SIMULATION MODELS. VOLUME 1. COMPARATIVE SENSITIVITY STUDIES OF PUFF, PLUME, AND GRID MODELS FOR LONG DISTANCE DISPERSION

EPA Science Inventory

This report provides detailed comparisons and sensitivity analyses of three candidate models, MESOPLUME, MESOPUFF, and MESOGRID. This was not a validation study; there was no suitable regional air quality data base for the Four Corners area. Rather, the models have been evaluated...

Overview and Evaluation of the Community Multiscale Air Quality (CMAQ) Modeling System Version 5.2

EPA Science Inventory

A new version of the Community Multiscale Air Quality (CMAQ) model, version 5.2 (CMAQv5.2), is currently being developed, with a planned release date in 2017. The new model includes numerous updates from the previous version of the model (CMAQv5.1). Specific updates include a new...

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.

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.

Linking service quality, customer satisfaction, and behavioral intention.

PubMed

Woodside, A G; Frey, L L; Daly, R T

1989-12-01

Based on the service quality and script theory literature, a framework of relationships among service quality, customer satisfaction, and behavioral intention for service purchases is proposed. Specific models are developed from the general framework and the models are applied and tested for the highly complex and divergent consumer service of overnight hospital care. Service quality, customer satisfaction, and behavioral intention data were collected from recent patients of two hospitals. The findings support the specific models and general framework. Implications for theory, service marketing, and future research are discussed.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Perceptual tools for quality-aware video networks

NASA Astrophysics Data System (ADS)

Bovik, A. C.

2014-01-01

Monitoring and controlling the quality of the viewing experience of videos transmitted over increasingly congested networks (especially wireless networks) is a pressing problem owing to rapid advances in video-centric mobile communication and display devices that are straining the capacity of the network infrastructure. New developments in automatic perceptual video quality models offer tools that have the potential to be used to perceptually optimize wireless video, leading to more efficient video data delivery and better received quality. In this talk I will review key perceptual principles that are, or could be used to create effective video quality prediction models, and leading quality prediction models that utilize these principles. The goal is to be able to monitor and perceptually optimize video networks by making them "quality-aware."

Global Environmental Multiscale model - a platform for integrated environmental predictions

NASA Astrophysics Data System (ADS)

Kaminski, Jacek W.; Struzewska, Joanna; Neary, Lori; Dearden, Frank

2017-04-01

The Global Environmental Multiscale model was developed by the Government of Canada as an operational weather prediction model in the mid-1990s. Subsequently, it was used as the host meteorological model for an on-line implementation of air quality chemistry and aerosols from global to the meso-gamma scale. Further model developments led to the vertical extension of the modelling domain to include stratospheric chemistry, aerosols, and formation of polar stratospheric clouds. In parallel, the modelling platform was used for planetary applications where dynamical, radiative transfer and chemical processes in the atmosphere of Mars were successfully simulated. Undoubtedly, the developed modelling platform can be classified as an example capable of the seamless and coupled modelling of the dynamics and chemistry of planetary atmospheres. We will present modelling results for global, regional, and local air quality episodes and the long-term air quality trends. Upper troposphere and lower stratosphere modelling results will be presented in terms of climate change and subsonic aviation emissions modelling. Model results for the atmosphere of Mars will be presented in the context of the 2016 ExoMars mission and the anticipated observations from the NOMAD instrument. Also, we will present plans and the design to extend the GEM model to the F region with further coupling with a magnetospheric model that extends to 15 Re.

Space shuttle flying qualities and criteria assessment

NASA Technical Reports Server (NTRS)

Myers, T. T.; Johnston, D. E.; Mcruer, Duane T.

1987-01-01

Work accomplished under a series of study tasks for the Flying Qualities and Flight Control Systems Design Criteria Experiment (OFQ) of the Shuttle Orbiter Experiments Program (OEX) is summarized. The tasks involved review of applicability of existing flying quality and flight control system specification and criteria for the Shuttle; identification of potentially crucial flying quality deficiencies; dynamic modeling of the Shuttle Orbiter pilot/vehicle system in the terminal flight phases; devising a nonintrusive experimental program for extraction and identification of vehicle dynamics, pilot control strategy, and approach and landing performance metrics, and preparation of an OEX approach to produce a data archive and optimize use of the data to develop flying qualities for future space shuttle craft in general. Analytic modeling of the Orbiter's unconventional closed-loop dynamics in landing, modeling pilot control strategies, verification of vehicle dynamics and pilot control strategy from flight data, review of various existent or proposed aircraft flying quality parameters and criteria in comparison with the unique dynamic characteristics and control aspects of the Shuttle in landing; and finally a summary of conclusions and recommendations for developing flying quality criteria and design guides for future Shuttle craft.

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

ERIC Educational Resources Information Center

Saavedra, Pedro; Kuchak, JoAnn

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

Unmix 6.0 Model for environmental data analyses

EPA Pesticide Factsheets

Unmix Model is a mathematical receptor model developed by EPA scientists that provides scientific support for the development and review of the air and water quality standards, exposure research, and environmental forensics.

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

USGS Publications Warehouse

Francy, Donna S.; Brady, Amie M.G.; Carvin, Rebecca B.; Corsi, Steven R.; Fuller, Lori M.; Harrison, John H.; Hayhurst, Brett A.; Lant, Jeremiah; Nevers, Meredith B.; Terrio, Paul J.; Zimmerman, Tammy M.

2013-01-01

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

A comparison of two types of neural network for weld quality prediction in small scale resistance spot welding

NASA Astrophysics Data System (ADS)

Wan, Xiaodong; Wang, Yuanxun; Zhao, Dawei; Huang, YongAn

2017-09-01

Our study aims at developing an effective quality monitoring system in small scale resistance spot welding of titanium alloy. The measured electrical signals were interpreted in combination with the nugget development. Features were extracted from the dynamic resistance and electrode voltage curve. A higher welding current generally indicated a lower overall dynamic resistance level. A larger electrode voltage peak and higher change rate of electrode voltage could be detected under a smaller electrode force or higher welding current condition. Variation of the extracted features and weld quality was found more sensitive to the change of welding current than electrode force. Different neural network model were proposed for weld quality prediction. The back propagation neural network was more proper in failure load estimation. The probabilistic neural network model was more appropriate to be applied in quality level classification. A real-time and on-line weld quality monitoring system may be developed by taking advantages of both methods.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Dimensions of service quality in healthcare: a systematic review of literature.

PubMed

Fatima, Iram; Humayun, Ayesha; Iqbal, Usman; Shafiq, Muhammad

2018-06-13

Various dimensions of healthcare service quality were used and discussed in literature across the globe. This study presents an updated meaningful review of the extensive research that has been conducted on measuring dimensions of healthcare service quality. Systematic review method in current study is based on PRISMA guidelines. We searched for literature using databases such as Google, Google Scholar, PubMed and Social Science, Citation Index. In this study, we screened 1921 identified papers using search terms/phrases. Snowball strategies were adopted to extract published articles from January 1997 till December 2016. Two-hundred and fourteen papers were identified as relevant for data extraction; completed by two researchers, double checked by the other two to develop agreement in discrepancies. In total, 74 studies fulfilled our pre-defined inclusion and exclusion criteria for data analysis. Service quality is mainly measured as technical and functional, incorporating many sub-dimensions. We synthesized the information about dimensions of healthcare service quality with reference to developed and developing countries. 'Tangibility' is found to be the most common contributing factor whereas 'SERVQUAL' as the most commonly used model to measure healthcare service quality. There are core dimensions of healthcare service quality that are commonly found in all models used in current reviewed studies. We found a little difference in these core dimensions while focusing dimensions in both developed and developing countries, as mostly SERVQUAL is being used as the basic model to either generate a new one or to add further contextual dimensions. The current study ranked the contributing factors based on their frequency in literature. Based on these priorities, if factors are addressed irrespective of any context, may lead to contribute to improve healthcare quality and may provide an important information for evidence-informed decision-making.

Evaluation of global water quality - the potential of a data- and model-driven analysis

NASA Astrophysics Data System (ADS)

Bärlund, Ilona; Flörke, Martina; Alcamo, Joseph; Völker, Jeanette; Malsy, Marcus; Kaus, Andrew; Reder, Klara; Büttner, Olaf; Katterfeld, Christiane; Dietrich, Désirée; Borchardt, Dietrich

2016-04-01

The ongoing socio-economic development presents a new challenge for water quality worldwide, especially in developing and emerging countries. It is estimated that due to population growth and the extension of water supply networks, the amount of waste water will rise sharply. This can lead to an increased risk of surface water quality degradation, if the wastewater is not sufficiently treated. This development has impacts on ecosystems and human health, as well as food security. The United Nations Member States have adopted targets for sustainable development. They include, inter alia, sustainable protection of water quality and sustainable use of water resources. To achieve these goals, appropriate monitoring strategies and the development of indicators for water quality are required. Within the pre-study for a 'World Water Quality Assessment' (WWQA) led by United Nations Environment Programme (UNEP), a methodology for assessing water quality, taking into account the above-mentioned objectives has been developed. The novelty of this methodology is the linked model- and data-driven approach. The focus is on parameters reflecting the key water quality issues, such as increased waste water pollution, salinization or eutrophication. The results from the pre-study show, for example, that already about one seventh of all watercourses in Latin America, Africa and Asia show high organic pollution. This is of central importance for inland fisheries and associated food security. In addition, it could be demonstrated that global water quality databases have large gaps. These must be closed in the future in order to obtain an overall picture of global water quality and to target measures more efficiently. The aim of this presentation is to introduce the methodology developed within the WWQA pre-study and to show selected examples of application in Latin America, Africa and Asia.

Developing a theoretical model and questionnaire survey instrument to measure the success of electronic health records in residential aged care

PubMed Central

Yu, Ping; Qian, Siyu

2018-01-01

Electronic health records (EHR) are introduced into healthcare organizations worldwide to improve patient safety, healthcare quality and efficiency. A rigorous evaluation of this technology is important to reduce potential negative effects on patient and staff, to provide decision makers with accurate information for system improvement and to ensure return on investment. Therefore, this study develops a theoretical model and questionnaire survey instrument to assess the success of organizational EHR in routine use from the viewpoint of nursing staff in residential aged care homes. The proposed research model incorporates six variables in the reformulated DeLone and McLean information systems success model: system quality, information quality, service quality, use, user satisfaction and net benefits. Two variables training and self-efficacy were also incorporated into the model. A questionnaire survey instrument was designed to measure the eight variables in the model. After a pilot test, the measurement scale was used to collect data from 243 nursing staff members in 10 residential aged care homes belonging to three management groups in Australia. Partial least squares path modeling was conducted to validate the model. The validated EHR systems success model predicts the impact of the four antecedent variables—training, self-efficacy, system quality and information quality—on the net benefits, the indicator of EHR systems success, through the intermittent variables use and user satisfaction. A 24-item measurement scale was developed to quantitatively evaluate the performance of an EHR system. The parsimonious EHR systems success model and the measurement scale can be used to benchmark EHR systems success across organizations and units and over time. PMID:29315323

Repositioning the knee joint in human body FE models using a graphics-based technique.

PubMed

Jani, Dhaval; Chawla, Anoop; Mukherjee, Sudipto; Goyal, Rahul; Vusirikala, Nataraju; Jayaraman, Suresh

2012-01-01

Human body finite element models (FE-HBMs) are available in standard occupant or pedestrian postures. There is a need to have FE-HBMs in the same posture as a crash victim or to be configured in varying postures. Developing FE models for all possible positions is not practically viable. The current work aims at obtaining a posture-specific human lower extremity model by reconfiguring an existing one. A graphics-based technique was developed to reposition the lower extremity of an FE-HBM by specifying the flexion-extension angle. Elements of the model were segregated into rigid (bones) and deformable components (soft tissues). The bones were rotated about the flexion-extension axis followed by rotation about the longitudinal axis to capture the twisting of the tibia. The desired knee joint movement was thus achieved. Geometric heuristics were then used to reposition the skin. A mapping defined over the space between bones and the skin was used to regenerate the soft tissues. Mesh smoothing was then done to augment mesh quality. The developed method permits control over the kinematics of the joint and maintains the initial mesh quality of the model. For some critical areas (in the joint vicinity) where element distortion is large, mesh smoothing is done to improve mesh quality. A method to reposition the knee joint of a human body FE model was developed. Repositions of a model from 9 degrees of flexion to 90 degrees of flexion in just a few seconds without subjective interventions was demonstrated. Because the mesh quality of the repositioned model was maintained to a predefined level (typically to the level of a well-made model in the initial configuration), the model was suitable for subsequent simulations.

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.

Development of alternative sulfur dioxide control strategies for a metropolitan area and its environs, utilizing a modified climatological dispersion model

Treesearch

K. J. Skipka; D. B. Smith

1977-01-01

Alternative control strategies were developed for achieving compliance with ambient air quality standards in Portland, Maine, and its environs, using a modified climatological dispersion model (CDM) and manipulating the sulfur content of the fuel oil consumed in four concentric zones. Strategies were evaluated for their impact on ambient air quality, economics, and...

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

Data Envelopment Analysis (DEA) Model in Operation Management

NASA Astrophysics Data System (ADS)

Malik, Meilisa; Efendi, Syahril; Zarlis, Muhammad

2018-01-01

Quality management is an effective system in operation management to develops, maintains, and improves quality from groups of companies that allow marketing, production, and service at the most economycal level as well as ensuring customer satisfication. Many companies are practicing quality management to improve their bussiness performance. One of performance measurement is through measurement of efficiency. One of the tools can be used to assess efficiency of companies performance is Data Envelopment Analysis (DEA). The aim of this paper is using Data Envelopment Analysis (DEA) model to assess efficiency of quality management. In this paper will be explained CCR, BCC, and SBM models to assess efficiency of quality management.

An evaluation of the NQF Quality Data Model for representing Electronic Health Record driven phenotyping algorithms.

PubMed

Thompson, William K; Rasmussen, Luke V; Pacheco, Jennifer A; Peissig, Peggy L; Denny, Joshua C; Kho, Abel N; Miller, Aaron; Pathak, Jyotishman

2012-01-01

The development of Electronic Health Record (EHR)-based phenotype selection algorithms is a non-trivial and highly iterative process involving domain experts and informaticians. To make it easier to port algorithms across institutions, it is desirable to represent them using an unambiguous formal specification language. For this purpose we evaluated the recently developed National Quality Forum (NQF) information model designed for EHR-based quality measures: the Quality Data Model (QDM). We selected 9 phenotyping algorithms that had been previously developed as part of the eMERGE consortium and translated them into QDM format. Our study concluded that the QDM contains several core elements that make it a promising format for EHR-driven phenotyping algorithms for clinical research. However, we also found areas in which the QDM could be usefully extended, such as representing information extracted from clinical text, and the ability to handle algorithms that do not consist of Boolean combinations of criteria.

DISCRETE VOLUME-ELEMENT METHOD FOR NETWORK WATER- QUALITY MODELS

EPA Science Inventory

An explicit dynamic water-quality modeling algorithm is developed for tracking dissolved substances in water-distribution networks. The algorithm is based on a mass-balance relation within pipes that considers both advective transport and reaction kinetics. Complete mixing of m...

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...

Methodologies for Evaluating Environmental Benefits of Intelligent Transportation Systems

DOT National Transportation Integrated Search

2001-05-01

This report provides an overview of the current state of practice in evaluation of air quality impacts and also in emissions modeling. This report also describes the recent developments in emissions modeling. The air quality impacts of various ITS st...

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

DOE PAGES

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

2017-08-01

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

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

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

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

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

Implementation of quality management in early stages of research and development projects at a university.

PubMed

Fiehe, Sandra; Wagner, Georg; Schlanstein, Peter; Rosefort, Christiane; Kopp, Rüdger; Bensberg, Ralf; Knipp, Peter; Schmitz-Rode, Thomas; Steinseifer, Ulrich; Arens, Jutta

2014-04-01

The ultimate objective of university research and development projects is usually to create knowledge, but also to successfully transfer results to industry for subsequent marketing. We hypothesized that the university technology transfer requires efficient measures to improve this important step. Besides good scientific practice, foresighted and industry-specific adapted documentation of research processes in terms of a quality management system might improve the technology transfer. In order to bridge the gap between research institute and cooperating industry, a model project has been accompanied by a project specific amount of quality management. However, such a system had to remain manageable and must not constrain the researchers' creativity. Moreover, topics and research team are strongly interdisciplinary, which entails difficulties regarding communication because of different perspectives and terminology. In parallel to the technical work of the model project, an adaptable quality management system with a quality manual, defined procedures, and forms and documents accompanying the research, development and validation was implemented. After process acquisition and analysis the appropriate amount of management for the model project was identified by a self-developed rating system considering project characteristics like size, innovation, stakeholders, interdisciplinarity, etc. Employees were trained according to their needs. The management was supported and the technical documentation was optimized. Finally, the quality management system has been transferred successfully to further projects.

Development of an Agricultural Fertilizer Modeling System for Bi-Directional Ammonia Fluxes in the Community Multiscale Air Quality (CMAQ) Model

EPA Science Inventory

Atmospheric ammonia (NH₃) plays an important role in fine-mode aerosol formation. Accurate estimates of ammonia from both human and natural emissions can reduce uncertainties in air quality modeling. The majority of ammonia anthropogenic emissions come from the agricul...

Opportunities to Practice What Is Locally Valued: An Ecocultural Perspective on Quality in Family Child Care Homes

ERIC Educational Resources Information Center

Tonyan, Holli A.

2017-01-01

Research Findings: Drawing from cultural approaches to human development (Rogoff, 2003; Weisner, 2002, 2005) and cognition (Quinn & Holland, 1987), this article presents a working model and theory of change for quality in family child care by defining quality as the alignment of children's opportunities for learning and development with…

Using Generalized Additive Modeling to Empirically Identify Thresholds within the ITERS in Relation to Toddlers' Cognitive Development

ERIC Educational Resources Information Center

Setodji, Claude Messan; Le, Vi-Nhuan; Schaack, Diana

2013-01-01

Research linking high-quality child care programs and children's cognitive development has contributed to the growing popularity of child care quality benchmarking efforts such as quality rating and improvement systems (QRIS). Consequently, there has been an increased interest in and a need for approaches to identifying thresholds, or cutpoints,…

An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers

USGS Publications Warehouse

Danielson, Thomas J.; Loftin, Cyndy; Tsomides, Leonidas; DiFranco, Jeanne L.; Connors, Beth; Courtemanch, David L.; Drummond, Francis; Davies, Susan

2012-01-01

State water-quality professionals developing new biological assessment methods often have difficulty relating assessment results to narrative criteria in water-quality standards. An alternative to selecting index thresholds arbitrarily is to include the Biological Condition Gradient (BCG) in the development of the assessment method. The BCG describes tiers of biological community condition to help identify and communicate the position of a water body along a gradient of water quality ranging from natural to degraded. Although originally developed for fish and macroinvertebrate communities of streams and rivers, the BCG is easily adapted to other habitats and taxonomic groups. We developed a discriminant analysis model with stream algal data to predict attainment of tiered aquatic-life uses in Maine's water-quality standards. We modified the BCG framework for Maine stream algae, related the BCG tiers to Maine's tiered aquatic-life uses, and identified appropriate algal metrics for describing BCG tiers. Using a modified Delphi method, 5 aquatic biologists independently evaluated algal community metrics for 230 samples from streams and rivers across the state and assigned a BCG tier (1–6) and Maine water quality class (AA/A, B, C, nonattainment of any class) to each sample. We used minimally disturbed reference sites to approximate natural conditions (Tier 1). Biologist class assignments were unanimous for 53% of samples, and 42% of samples differed by 1 class. The biologists debated and developed consensus class assignments. A linear discriminant model built to replicate a priori class assignments correctly classified 95% of 150 samples in the model training set and 91% of 80 samples in the model validation set. Locally derived metrics based on BCG taxon tolerance groupings (e.g., sensitive, intermediate, tolerant) were more effective than were metrics developed in other regions. Adding the algal discriminant model to Maine's existing macroinvertebrate discriminant model will broaden detection of biological impairment and further diagnose sources of impairment. The algal discriminant model is specific to Maine, but our approach of explicitly tying an assessment tool to tiered aquatic-life goals is widely transferrable to other regions, taxonomic groups, and waterbody types.

Outcomes-Balanced Framework for Emergency Management: A Predictive Model for Preparedness

DTIC Science & Technology

2013-09-01

Management Total Quality Management (TQM) was developed by W. Edwards Deming in the post-World War II reconstruction period in Japan. It ushered in a...FIGURES Figure 1. From Total Quality Management Principles ....................................................30 Figure 2. Outcomes Logic Model (After...THIRA Threat and Hazard Identification and Risk Assessment TQM Total Quality Management UTL Universal Task List xiv ACKNOWLEDGMENTS German

Measuring the impact of urbanization on scenic quality: land use change in the northeast

Treesearch

Robert O. Brush; James F. Palmer

1979-01-01

The changes in scenic quality resulting from urbanization are explored for a region in the Northeast. The relative contributions to scenic quality of certain landscape features are examined by developing regression models for the region and for town landscapes within that region. The models provide empirical evidence of the importance of trees for maintaining high...

Handbook for the Commonwealth of Learning Review and Improvement Model: Making Quality Work in Higher Education

ERIC Educational Resources Information Center

Commonwealth of Learning, 2010

2010-01-01

The Commonwealth of Learning Review and Improvement Model (COL RIM) was developed by the Commonwealth of Learning in response to two key drivers: (1) Increased global emphasis on the quality of higher education; and (2) Rising concern about the high cost and uncertain benefits of conventional approaches to external quality assurance. Any…

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.

Quality assessment for color reproduction using a blind metric

NASA Astrophysics Data System (ADS)

Bringier, B.; Quintard, L.; Larabi, M.-C.

2007-01-01

This paper deals with image quality assessment. This field plays nowadays an important role in various image processing applications. Number of objective image quality metrics, that correlate or not, with the subjective quality have been developed during the last decade. Two categories of metrics can be distinguished, the first with full-reference and the second with no-reference. Full-reference metric tries to evaluate the distortion introduced to an image with regards to the reference. No-reference approach attempts to model the judgment of image quality in a blind way. Unfortunately, the universal image quality model is not on the horizon and empirical models established on psychophysical experimentation are generally used. In this paper, we focus only on the second category to evaluate the quality of color reproduction where a blind metric, based on human visual system modeling is introduced. The objective results are validated by single-media and cross-media subjective tests.

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.

Sequentially Executed Model Evaluation Framework

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

2015-10-20

Provides a message passing framework between generic input, model and output drivers, and specifies an API for developing such drivers. Also provides batch and real-time controllers which step the model and I/O through the time domain (or other discrete domain), and sample I/O drivers. This is a library framework, and does not, itself, solve any problems or execute any modeling. The SeMe framework aids in development of models which operate on sequential information, such as time-series, where evaluation is based on prior results combined with new data for this iteration. Has applications in quality monitoring, and was developed as partmore » of the CANARY-EDS software, where real-time water quality data is being analyzed for anomalies.« less

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.

Numerical methods for assessing water quality in lakes and reservoirs

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

Mahamah, D.S.

1984-01-01

Water quality models are used as tools for predicting both short-term and long-term trends in water quality. They are generally classified into two groups based on the degree of empiricism. The two groups consists of the purely empirical types known as black-box models and the theoretical types called ecosystem models. This dissertation deals with both types of water quality models. The first part deals with empirical phosphorus models. The theory behind this class of models is discussed, leading to the development of an empirical phosphorus model using data from 79 western US lakes. A new approach to trophic state classificationmore » is introduced. The data used for the model was obtained from the Environmental Protection Agency National Eutrophication Study (EPA-NES) of western US lakes. The second portion of the dissertation discusses the development of an ecosystem model for culturally eutrophic Liberty Lake situated in eastern Washington State. The model is capable of simulating chlorophyll-a, phosphorus, and nitrogen levels in the lake on a weekly basis. For computing sediment release rates of phosphorus and nitrogen, equations based on laboratory bench-top studies using sediment samples from Liberty Lake are used. The model is used to simulate certain hypothetical nutrient control techniques such as phosphorus flushing, precipitation, and diversion.« less

Narrative meaning making and integration: Toward a better understanding of the way falling ill influences quality of life.

PubMed

Hartog, Iris; Scherer-Rath, Michael; Kruizinga, Renske; Netjes, Justine; Henriques, José; Nieuwkerk, Pythia; Sprangers, Mirjam; van Laarhoven, Hanneke

2017-09-01

Falling seriously ill is often experienced as a life event that causes conflict with people's personal goals and expectations in life and evokes existential questions. This article presents a new humanities approach to the way people make meaning of such events and how this influences their quality of life. Incorporating theories on contingency, narrative identity, and quality of life, we developed a theoretical model entailing the concepts life event, worldview, ultimate life goals, experience of contingency, narrative meaning making, narrative integration, and quality of life. We formulate testable hypotheses and describe the self-report questionnaire that was developed based on the model.

Land cover impacts on stream nutrients and fecal coliform in the lower Piedmont of West Georgia

NASA Astrophysics Data System (ADS)

Schoonover, Jon E.; Lockaby, B. Graeme

2006-12-01

SummaryAs urbanization infiltrates into rural areas, stream water quality is expected to decline as a result from increased impervious surface and greater sources for pollutants. Consequently, West Georgia's water quality is threatened by extensive development as well as other land uses such as livestock grazing and silvicultural activity. Maintenance of stream water quality, as land development occurs, is critical for the protection of drinking water and biotic integrity. A 2-phase, watershed-scale study was established to develop relationships among land cover and water quality within western Georgia. During phase 1, nutrient and fecal coliform data were collected within 18 mixed land use watersheds, ranging in size from 500 to 2500 ha. Regression models were developed that related land cover to stream water nutrient and fecal coliform concentrations. Nutrient and fecal coliform concentrations within watersheds having >24% impervious surface (IS) were often higher than those in nonurban watersheds (i.e., <5% IS) during both base flow (N: 1.64 mg/L versus 0.61 mg/L, and FC: 430 versus 120 MPN/100 ml) and storm flow (N: 1.93 mg/L versus 0.36 mg/L, and FC: 1600 versus 167 MPN/100 ml). Fecal coliform bacteria in urbanized areas consistently exceeded the US EPA's review criterion for recreational waters during both base flow and to a greater extent storm flow. During phase 2, regression models were tested based on data from six newly chosen watersheds with similar land use/cover patterns. Lastly, theoretical watersheds, based on land use percentages, were created to illustrate trends in water quality impairment as land development occurs. The models developed from this research could be used to forecast water quality changes under various land use scenarios in the developing Piedmont region of the US.

A FEDERATED PARTNERSHIP FOR URBAN METEOROLOGICAL AND AIR QUALITY MODELING

EPA Science Inventory

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

APPLICATION OF BAYESIAN MONTE CARLO ANALYSIS TO A LAGRANGIAN PHOTOCHEMICAL AIR QUALITY MODEL. (R824792)

EPA Science Inventory

Uncertainties in ozone concentrations predicted with a Lagrangian photochemical air quality model have been estimated using Bayesian Monte Carlo (BMC) analysis. Bayesian Monte Carlo analysis provides a means of combining subjective "prior" uncertainty estimates developed ...

Preface: Special issue of Atmospheric Environment for AQMEII

EPA Science Inventory

In December 2008, a handful of European and North American scientists got together to discuss a possible collaboration on the evaluation of regional-scale air quality models. This led to the development of the Air Quality Model Evaluation International Initiative (AQMEII) with th...

The importance of data curation on QSAR Modeling ...

EPA Pesticide Factsheets

During the last few decades many QSAR models and tools have been developed at the US EPA, including the widely used EPISuite. During this period the arsenal of computational capabilities supporting cheminformatics has broadened dramatically with multiple software packages. These modern tools allow for more advanced techniques in terms of chemical structure representation and storage, as well as enabling automated data-mining and standardization approaches to examine and fix data quality issues.This presentation will investigate the impact of data curation on the reliability of QSAR models being developed within the EPA‘s National Center for Computational Toxicology. As part of this work we have attempted to disentangle the influence of the quality versus quantity of data based on the Syracuse PHYSPROP database partly used by EPISuite software. We will review our automated approaches to examining key datasets related to the EPISuite data to validate across chemical structure representations (e.g., mol file and SMILES) and identifiers (chemical names and registry numbers) and approaches to standardize data into QSAR-ready formats prior to modeling procedures. Our efforts to quantify and segregate data into quality categories has allowed us to evaluate the resulting models that can be developed from these data slices and to quantify to what extent efforts developing high-quality datasets have the expected pay-off in terms of predicting performance. The most accur

A novel hybrid approach for estimating total deposition in the United States

NASA Astrophysics Data System (ADS)

Schwede, Donna B.; Lear, Gary G.

2014-08-01

Atmospheric deposition of nitrogen and sulfur causes many deleterious effects on ecosystems including acidification and excess eutrophication. Assessments to support development of strategies to mitigate these effects require spatially and temporally continuous values of nitrogen and sulfur deposition. In the U.S., national monitoring networks exist that provide values of wet and dry deposition at discrete locations. While wet deposition can be interpolated between the monitoring locations, dry deposition cannot. Additionally, monitoring networks do not measure the complete suite of chemicals that contribute to total sulfur and nitrogen deposition. Regional air quality models provide spatially continuous values of deposition of monitored species as well as important unmeasured species. However, air quality modeling values are not generally available for an extended continuous time period. Air quality modeling results may also be biased for some chemical species. We developed a novel approach for estimating dry deposition using data from monitoring networks such as the Clean Air Status and Trends Network (CASTNET), the National Atmospheric Deposition Program (NADP) Ammonia Monitoring Network (AMoN), and the Southeastern Aerosol Research and Characterization (SEARCH) network and modeled data from the Community Multiscale Air Quality (CMAQ) model. These dry deposition values estimates are then combined with wet deposition values from the NADP National Trends Network (NTN) to develop values of total deposition of sulfur and nitrogen. Data developed using this method are made available via the CASTNET website.

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.

How Clean is your Local Air? Here's an app for that

NASA Astrophysics Data System (ADS)

Maskey, M.; Yang, E.; Christopher, S. A.; Keiser, K.; Nair, U. S.; Graves, S. J.

2011-12-01

Air quality is a vital element of our environment. Accurate and localized air quality information is critical for characterizing environmental impacts at the local and regional levels. Advances in location-aware handheld devices and air quality modeling have enabled a group of UAHuntsville scientists to develop a mobile app, LocalAQI, that informs users of current conditions and forecasts of up to twenty-four hours, of air quality indices. The air quality index is based on Community Multiscale Air Quality Modeling System (CMAQ). UAHuntsville scientists have used satellite remote sensing products as inputs to CMAQ, resulting in forecast guidance for particulate matter air quality. The CMAQ output is processed to compute a standardized air quality index. Currently, the air quality index is available for the eastern half of the United States. LocalAQI consists of two main views: air quality index view and map view. The air quality index view displays current air quality for the zip code of a location of interest. Air quality index value is translated into a color-coded advisory system. In addition, users are able to cycle through available hourly forecasts for a location. This location-aware app defaults to the current air quality of user's location. The map view displays color-coded air quality information for the eastern US with an ability to animate through the available forecasts. The app is developed using a cross-platform native application development tool, appcelerator; hence LocalAQI is available for iOS and Android-based phones and pads.

Soldier Quality of Life Assessment

DTIC Science & Technology

2016-09-01

ABSTRACT This report documents survey research and modeling of Soldier quality of life (QoL) on contingency base camps by the U.S. Army Natick...Science and Technology Objective Demonstration, was to develop a way to quantify QoL for camps housing fewer than 1000 personnel. A discrete choice survey ... Survey results were analyzed using hierarchical Bayesian logistic regression to develop a quantitative model for estimating QoL based on base camp

Tracing the influence of land-use change on water quality and coral reefs using a Bayesian model.

PubMed

Brown, Christopher J; Jupiter, Stacy D; Albert, Simon; Klein, Carissa J; Mangubhai, Sangeeta; Maina, Joseph M; Mumby, Peter; Olley, Jon; Stewart-Koster, Ben; Tulloch, Vivitskaia; Wenger, Amelia

2017-07-06

Coastal ecosystems can be degraded by poor water quality. Tracing the causes of poor water quality back to land-use change is necessary to target catchment management for coastal zone management. However, existing models for tracing the sources of pollution require extensive data-sets which are not available for many of the world's coral reef regions that may have severe water quality issues. Here we develop a hierarchical Bayesian model that uses freely available satellite data to infer the connection between land-uses in catchments and water clarity in coastal oceans. We apply the model to estimate the influence of land-use change on water clarity in Fiji. We tested the model's predictions against underwater surveys, finding that predictions of poor water quality are consistent with observations of high siltation and low coverage of sediment-sensitive coral genera. The model thus provides a means to link land-use change to declines in coastal water quality.

Prototypic automated continuous recreational water quality monitoring of nine Chicago beaches

USGS Publications Warehouse

Dawn Shively,; Nevers, Meredith; Cathy Breitenbach,; Phanikumar, Mantha S.; Kasia Przybyla-Kelly,; Ashley M. Spoljaric,; Richard L. Whitman,

2015-01-01

Predictive empirical modeling is used in many locations worldwide as a rapid, alternative recreational water quality management tool to eliminate delayed notifications associated with traditional fecal indicator bacteria (FIB) culturing (referred to as the persistence model, PM) and to prevent errors in releasing swimming advisories. The goal of this study was to develop a fully automated water quality management system for multiple beaches using predictive empirical models (EM) and state-of-the-art technology. Many recent EMs rely on samples or data collected manually, which adds to analysis time and increases the burden to the beach manager. In this study, data from water quality buoys and weather stations were transmitted through cellular telemetry to a web hosting service. An executable program simultaneously retrieved and aggregated data for regression equations and calculated EM results each morning at 9:30 AM; results were transferred through RSS feed to a website, mapped to each beach, and received by the lifeguards to be posted at the beach. Models were initially developed for five beaches, but by the third year, 21 beaches were managed using refined and validated modeling systems. The adjusted R2 of the regressions relating Escherichia coli to hydrometeorological variables for the EMs were greater than those for the PMs, and ranged from 0.220 to 0.390 (2011) and 0.103 to 0.381 (2012). Validation results in 2013 revealed reduced predictive capabilities; however, three of the originally modeled beaches showed improvement in 2013 compared to 2012. The EMs generally showed higher accuracy and specificity than those of the PMs, and sensitivity was low for both approaches. In 2012 EM accuracy was 70–97%; specificity, 71–100%; and sensitivity, 0–64% and in 2013 accuracy was 68–97%; specificity, 73–100%; and sensitivity 0–36%. Factors that may have affected model capabilities include instrument malfunction, non-point source inputs, and sparse calibration data. The modeling system developed is the most extensive, fully-automated system for recreational water quality developed to date. Key insights for refining and improving large-scale empirical models for beach management have been developed through this multi-year effort.

Development of a Next Generation Air Quality Modeling System

EPA Science Inventory

In the presentation we will describe our modifications to MPAS to improve its suitability for retrospective air quality applications and show evaluations of global and regional meterological simulations. Our modifications include addition of physics schemes that we developed for...

An approach for quantitative image quality analysis for CT

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Systems Perspectives on External Quality Assurance: Implications for Micro-States

ERIC Educational Resources Information Center

Houston, Don; Maniku, Ahmed Ali

2005-01-01

Quality assurance in higher education is a mess: the "problem" of quality is embedded in complex sets of interacting issues that are of concern to many and varied stakeholders. Developing higher education systems that have responded to issues of quality through a "best practice" model of external quality assurance has produced…

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.

An integrated fuzzy-based advanced eutrophication simulation model to develop the best management scenarios for a river basin.

PubMed

Srinivas, Rallapalli; Singh, Ajit Pratap

2018-03-01

Assessment of water quality status of a river with respect to its discharge has become prerequisite to sustainable river basin management. The present paper develops an integrated model for simulating and evaluating strategies for water quality management in a river basin management by controlling point source pollutant loadings and operations of multi-purpose projects. Water Quality Analysis and Simulation Program (WASP version 8.0) has been used for modeling the transport of pollutant loadings and their impact on water quality in the river. The study presents a novel approach of integrating fuzzy set theory with an "advanced eutrophication" model to simulate the transmission and distribution of several interrelated water quality variables and their bio-physiochemical processes in an effective manner in the Ganges river basin, India. After calibration, simulated values are compared with the observed values to validate the model's robustness. Fuzzy technique of order preference by similarity to ideal solution (F-TOPSIS) has been used to incorporate the uncertainty associated with the water quality simulation results. The model also simulates five different scenarios for pollution reduction, to determine the maximum pollutant loadings during monsoon and dry periods. The final results clearly indicate how modeled reduction in the rate of wastewater discharge has reduced impacts of pollutants in the downstream. Scenarios suggesting a river discharge rate of 1500 m 3 /s during the lean period, in addition to 25 and 50% reduction in the load rate, are found to be the most effective option to restore quality of river Ganges. Thus, the model serves as an important hydrologic tool to the policy makers by suggesting appropriate remediation action plans.

Development strategy and process models for phased automation of design and digital manufacturing electronics

NASA Astrophysics Data System (ADS)

Korshunov, G. I.; Petrushevskaya, A. A.; Lipatnikov, V. A.; Smirnova, M. S.

2018-03-01

The strategy of quality of electronics insurance is represented as most important. To provide quality, the processes sequence is considered and modeled by Markov chain. The improvement is distinguished by simple database means of design for manufacturing for future step-by-step development. Phased automation of design and digital manufacturing electronics is supposed. The MatLab modelling results showed effectiveness increase. New tools and software should be more effective. The primary digital model is proposed to represent product in the processes sequence from several processes till the whole life circle.

Model documentation for relations between continuous real-time and discrete water-quality constituents in Cheney Reservoir near Cheney, Kansas, 2001--2009

USGS Publications Warehouse

Stone, Mandy L.; Graham, Jennifer L.; Gatotho, Jackline W.

2013-01-01

Cheney Reservoir, located in south-central Kansas, is one of the primary water supplies for the city of Wichita, Kansas. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station in Cheney Reservoir since 2001; continuously measured physicochemical properties include specific conductance, pH, water temperature, dissolved oxygen, turbidity, fluorescence (wavelength range 650 to 700 nanometers; estimate of total chlorophyll), and reservoir elevation. Discrete water-quality samples were collected during 2001 through 2009 and analyzed for sediment, nutrients, taste-and-odor compounds, cyanotoxins, phytoplankton community composition, actinomycetes bacteria, and other water-quality measures. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physicochemical properties to compute concentrations of constituents that are not easily measured in real time. The water-quality information in this report is important to the city of Wichita because it allows quantification and characterization of potential constituents of concern in Cheney Reservoir. This report updates linear regression models published in 2006 that were based on data collected during 2001 through 2003. The update uses discrete and continuous data collected during May 2001 through December 2009. Updated models to compute dissolved solids, sodium, chloride, and suspended solids were similar to previously published models. However, several other updated models changed substantially from previously published models. In addition to updating relations that were previously developed, models also were developed for four new constituents, including magnesium, dissolved phosphorus, actinomycetes bacteria, and the cyanotoxin microcystin. In addition, a conversion factor of 0.74 was established to convert the Yellow Springs Instruments (YSI) model 6026 turbidity sensor measurements to the newer YSI model 6136 sensor at the Cheney Reservoir site. Because a high percentage of geosmin and microcystin data were below analytical detection thresholds (censored data), multiple logistic regression was used to develop models that best explained the probability of geosmin and microcystin concentrations exceeding relevant thresholds. The geosmin and microcystin models are particularly important because geosmin is a taste-and-odor compound and microcystin is a cyanotoxin.

Developing quality indicators and auditing protocols from formal guideline models: knowledge representation and transformations.

PubMed

Advani, Aneel; Goldstein, Mary; Shahar, Yuval; Musen, Mark A

2003-01-01

Automated quality assessment of clinician actions and patient outcomes is a central problem in guideline- or standards-based medical care. In this paper we describe a model representation and algorithm for deriving structured quality indicators and auditing protocols from formalized specifications of guidelines used in decision support systems. We apply the model and algorithm to the assessment of physician concordance with a guideline knowledge model for hypertension used in a decision-support system. The properties of our solution include the ability to derive automatically context-specific and case-mix-adjusted quality indicators that can model global or local levels of detail about the guideline parameterized by defining the reliability of each indicator or element of the guideline.

Results of a modeling workshop concerning economic and environmental trends and concomitant resource management issues in the Mobile Bay area

USGS Publications Warehouse

Hamilton, David B.; Andrews, Austin K.; Auble, Gregor T.; Ellison, Richard A.; Johnson, Richard A.; Roelle, James E.; Staley, Michael J.

1982-01-01

During the past decade, the southern regions of the U.S. have experienced rapid change which is expected to continue into the foreseeable future. Growth in population, industry, and resource development has been attributed to a variety of advantages such as an abundant and inexpensive labor force, a mild climate, and the availability of energy, water, land, and other natural resources. While this growth has many benefits for the region, it also creates the potential for increased air, water, and solid waste pollution, and modification of natural habitats. A workshop was convened to consider the Mobile Bay area as a site-specific case of growth and its environmental consequences in the southern region. The objectives of the modeling workshop were to: (1) identify major factors of economic development as they relate to growth in the area over the immediate and longer term; (2) identify major environmental and resource management issues associated with this expected growth; and (3) identify and characterize the complex interrelationships among economic and environmental factors. This report summarizes the activities and results of a modeling workshop concerning economic growth and concomitant resource management issues in the Mobile Bay area. The workshop was organized around construction of a simulation model representing the relationships between a series of actions and indicators identified by participants. The workshop model had five major components. An Industry Submodel generated scenarios of growth in several industrial and transportation sectors. A Human Population/Economy Submodel calculated human population and economic variables in response to employment opportunities. A Land Use/Air Quality Submodel tabulated changes in land use, shoreline use, and air quality. A Water Submodel calculated indicators of water quality and quantity for fresh surface water, ground water, and Mobile Bay based on discharge information provided by the Industry and Human Population/Economy Submodels. Finally, a Fish Submodel calculated indicators of habitat quality for finfish and shellfish, utilizing information on water quality and wetlands acreage. The workshop was successful in identifying many of the critical interrelations between components of the Mobile area system. Not all of those interactions, such as the feedback of air quality as a limitation on development, could be incorporated into the workshop model because of the model's broad spatial scale and because of uncertainties or data gaps. Thus, the value of the modeling workshop was in the areas outlines below, rather than in the predictive power of the initial model developed at the workshop. First, participants developed a holistic perspective on the interactions which will determine future economic and environmental trends within the Mobile Bay area. Potential environmental consequences and limitations to grown identified at the workshop included: shoreline and water access; water quality of Mobile Bay; finfish and shellfish habitat quality with respect to dissolved oxygen and coliforms; air quality; and acreage of critical wetland habitat. Second, the model's requirements for specific, quantitative information stimulated supporting analyses, such as economic input-output calculations, which provide additional insight into the Mobile Bay area system. Third, the perspective of the Mobile area as an interacting system was developed in an open, cooperative forum which my provide a foundation for conflict resolution based on common understanding. Finally, the identification of model limitations and uncertainties should be useful in guiding the efficient allocation of future research effort.

Marketing and Quality of Life: A Model for Improving Perinatal Health Status

ERIC Educational Resources Information Center

Dever, G. E. Alan; Smith, Leah T.; Stamps, Bunnie V.

2005-01-01

Introduction: A marketing/business model using non-traditional Quality of Life measures was developed to assess perinatal health status on a micro-geographic level. This perinatal health status needs assessment study for Georgia South Central Region was conducted for the years 1994-1999. The model may be applied to any geographic unit in the…

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...

Protein model quality assessment prediction by combining fragment comparisons and a consensus Cα contact potential

PubMed Central

Zhou, Hongyi; Skolnick, Jeffrey

2009-01-01

In this work, we develop a fully automated method for the quality assessment prediction of protein structural models generated by structure prediction approaches such as fold recognition servers, or ab initio methods. The approach is based on fragment comparisons and a consensus Cα contact potential derived from the set of models to be assessed and was tested on CASP7 server models. The average Pearson linear correlation coefficient between predicted quality and model GDT-score per target is 0.83 for the 98 targets which is better than those of other quality assessment methods that participated in CASP7. Our method also outperforms the other methods by about 3% as assessed by the total GDT-score of the selected top models. PMID:18004783

Methodology and guidelines for regulating traffic flows under air quality constraints in metropolitan areas.

DOT National Transportation Integrated Search

2010-02-01

This project developed a methodology to couple a new pollutant dispersion model with a traffic : assignment process to contain air pollution while maximizing mobility. The overall objective of the air : quality modeling part of the project is to deve...

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...

Recent Enhancements to the Community Multiscale Air Quality Modeling System (CMAQ)

EPA Science Inventory

EPA’s Office of Research and Development, Computational Exposure Division held a webinar on January 31, 2017 to present the recent scientific and computational updates made by EPA to the Community Multi-Scale Air Quality Model (CMAQ). Topics covered included: (1) Improveme...

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

EPA Science Inventory

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

Watershed Regressions for Pesticides (WARP) for Predicting Annual Maximum and Annual Maximum Moving-Average Concentrations of Atrazine in Streams

USGS Publications Warehouse

Stone, Wesley W.; Gilliom, Robert J.; Crawford, Charles G.

2008-01-01

Regression models were developed for predicting annual maximum and selected annual maximum moving-average concentrations of atrazine in streams using the Watershed Regressions for Pesticides (WARP) methodology developed by the National Water-Quality Assessment Program (NAWQA) of the U.S. Geological Survey (USGS). The current effort builds on the original WARP models, which were based on the annual mean and selected percentiles of the annual frequency distribution of atrazine concentrations. Estimates of annual maximum and annual maximum moving-average concentrations for selected durations are needed to characterize the levels of atrazine and other pesticides for comparison to specific water-quality benchmarks for evaluation of potential concerns regarding human health or aquatic life. Separate regression models were derived for the annual maximum and annual maximum 21-day, 60-day, and 90-day moving-average concentrations. Development of the regression models used the same explanatory variables, transformations, model development data, model validation data, and regression methods as those used in the original development of WARP. The models accounted for 72 to 75 percent of the variability in the concentration statistics among the 112 sampling sites used for model development. Predicted concentration statistics from the four models were within a factor of 10 of the observed concentration statistics for most of the model development and validation sites. Overall, performance of the models for the development and validation sites supports the application of the WARP models for predicting annual maximum and selected annual maximum moving-average atrazine concentration in streams and provides a framework to interpret the predictions in terms of uncertainty. For streams with inadequate direct measurements of atrazine concentrations, the WARP model predictions for the annual maximum and the annual maximum moving-average atrazine concentrations can be used to characterize the probable levels of atrazine for comparison to specific water-quality benchmarks. Sites with a high probability of exceeding a benchmark for human health or aquatic life can be prioritized for monitoring.

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

EPA Science Inventory

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

Ground-water models for water resources planning

USGS Publications Warehouse

Moore, John E.

1980-01-01

In the past decade hydrologists have emphasized the development of computer-based mathematical models to aid in the understanding of flow, the transport of solutes, transport of heat, and deformation in the groundwater system. These models have been used to provide information and predictions for water managers. Too frequently, groundwater was neglected in water-resource planning because managers believed that it could not be adequately evaluated in terms of availability, quality, and effect of development on surface water supplies. Now, however, with newly developed digital groundwater models, effects of development can be predicted. Such models have been used to predict hydrologic and quality changes under different stresses. These models have grown in complexity over the last 10 years from simple one-layer flow models to three-dimensional simulations of groundwater flow which may include solute transport, heat transport, effects of land subsidence, and encroachment of salt water. This paper illustrates, through case histories, how predictive groundwater models have provided the information needed for the sound planning and management of water resources in the United States. (USGS)

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Quality Attribute Techniques Framework

NASA Astrophysics Data System (ADS)

Chiam, Yin Kia; Zhu, Liming; Staples, Mark

The quality of software is achieved during its development. Development teams use various techniques to investigate, evaluate and control potential quality problems in their systems. These “Quality Attribute Techniques” target specific product qualities such as safety or security. This paper proposes a framework to capture important characteristics of these techniques. The framework is intended to support process tailoring, by facilitating the selection of techniques for inclusion into process models that target specific product qualities. We use risk management as a theory to accommodate techniques for many product qualities and lifecycle phases. Safety techniques have motivated the framework, and safety and performance techniques have been used to evaluate the framework. The evaluation demonstrates the ability of quality risk management to cover the development lifecycle and to accommodate two different product qualities. We identify advantages and limitations of the framework, and discuss future research on the framework.

Social franchising primary healthcare clinics--a model for South African National Health Insurance?

PubMed

Robinson, Andrew Ken Lacey

2015-09-21

This article describes the first government social franchise initiative in the world to deliver a 'brand' of quality primary healthcare (PHC) clinic services. Quality and standards of care are not uniformly and reliably delivered across government PHC clinics in North West Province, South Africa, despite government support, numerous policies, guidelines and in-service training sessions provided to staff. Currently the strongest predictor of good-quality service is the skill and dedication of the facility manager. A project utilising the social franchising business model, harvesting best practices, has been implemented with the aim of developing a system to ensure reliably excellent healthcare service provision in every facility in North West. The services of social franchising consultants have been procured to develop the business model to drive this initiative. Best practices have been benchmarked, and policies, guidelines and clinic support systems have been reviewed, evaluated and assessed, and incorporated into the business plan. A pilot clinic has been selected to refine and develop a working social franchise model. This will then be replicated in one clinic to confirm proof of concept before further scale-up. The social franchise business model can provide solutions to a reliable and recognisable 'brand' of quality universal coverage of healthcare services.

Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?

NASA Technical Reports Server (NTRS)

Myers, Jerry G.; Young, M.; Goodenow, Debra A.; Keenan, A.; Walton, M.; Boley, L.

2015-01-01

Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.

Friendship Quality Scale: Conceptualization, Development and Validation

ERIC Educational Resources Information Center

Thien, Lei Mee; Razak, Nordin Abd; Jamil, Hazri

2012-01-01

The purpose of this study is twofold: (1) to initialize a new conceptualization of positive feature based Friendship Quality (FQUA) scale on the basis of four dimensions: Closeness, Help, Acceptance, and Safety; and (2) to develop and validate FQUA scale in the form of reflective measurement model. The scale development and validation procedures…

A Face-to-Face Professional Development Model to Enhance Teaching of Online Research Strategies

ERIC Educational Resources Information Center

Terrazas-Arellanes, Fatima E.; Knox, Carolyn; Strycker, Lisa A.; Walden, Emily

2016-01-01

To help students navigate the digital environment, teachers not only need access to the right technology tools but they must also engage in pedagogically sound, high-quality professional development. For teachers, quality professional development can mean the difference between merely using technology tools and creating transformative change in…

New Developments in Wildfire Pollution Forecasting at the Canadian Meteorological Centre

NASA Astrophysics Data System (ADS)

Pavlovic, Radenko; Chen, Jack; Munoz-Alpizar, Rodrigo; Davignon, Didier; Beaulieu, Paul-Andre; Landry, Hugo; Menard, Sylvain; Gravel, Sylvie; Moran, Michael

2017-04-01

Environment and Climate Change Canada's air quality forecast system with near-real-time wildfire emissions, named FireWork, was developed in 2012 and has been run by the Canadian Meteorological Centre Operations division (CMCO) since 2013. In June 2016 this system was upgraded to operational status and wildfire smoke forecasts for North America are now available to the general public. FireWork's ability to model the transport and diffusion of wildfire smoke plumes has proved to be valuable to regional air quality forecasters and emergency first responders. Some of the most challenging issues with wildfire pollution modelling concern the production of wildfire emission estimates and near-source dispersion within the air quality model. As a consequence, FireWork is undergoing constant development. During the massive Fort McMurray wildfire event in western Canada in May 2016, for example, different wildfire emissions processing approaches and wildfire emissions injection and dispersion schemes were tested within the air quality model. Work on various FireWork components will continue in order to deliver a new operational version of the forecasting system for the 2017 wildfire season. Some of the proposed improvements will be shown in this presentation along with current and planned FireWork post-processing products.

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

DOT National Transportation Integrated Search

2017-01-01

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

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

DOT National Transportation Integrated Search

2017-01-01

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

A design procedure for the handling qualities optimization of the X-29A aircraft

NASA Technical Reports Server (NTRS)

Bosworth, John T.; Cox, Timothy H.

1989-01-01

A design technique for handling qualities improvement was developed for the X-29A aircraft. As with any new aircraft, the X-29A control law designers were presented with a relatively high degree of uncertainty in their mathematical models. The presence of uncertainties, and the high level of static instability of the X-29A caused the control law designers to stress stability and robustness over handling qualities. During flight test, the mathematical models of the vehicle were validated or corrected to match the vehicle dynamic behavior. The updated models were then used to fine tune the control system to provide fighter-like handling characteristics. A design methodology was developed which works within the existing control system architecture to provide improved handling qualities and acceptable stability with a minimum of cost in both implementation as well as software verification and validation.

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.

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.

The experience factory: Can it make you a 5? or what is its relationship to other quality and improvement concepts?

NASA Technical Reports Server (NTRS)

Basili, Victor R.

1992-01-01

The concepts of quality improvements have permeated many businesses. It is clear that the nineties will be the quality era for software and there is a growing need to develop or adapt quality improvement approaches to the software business. Thus we must understand software as an artifact and software as a business. Since the business we are dealing with is software, we must understand the nature of software and software development. The software discipline is evolutionary and experimental; it is a laboratory science. Software is development not production. The technologies of the discipline are human based. There is a lack of models that allow us to reason about the process and the product. All software is not the same; process is a variable, goals are variable, etc. Packaged, reusable, experiences require additional resources in the form of organization, processes, people, etc. There have been a variety of organizational frameworks proposed to improve quality for various businesses. The ones discussed in this presentation include: Plan-Do-Check-Act, a quality improvement process based upon a feedback cycle for optimizing a single process model/production line; the Experience Factory/Quality Improvement Paradigm, continuous improvements through the experimentation, packaging, and reuse of experiences based upon a business's needs; Total Quality Management, a management approach to long term success through customer satisfaction based on the participation of all members of an organization; the SEI capability maturity model, a staged process improvement based upon assessment with regard to a set of key process areas until you reach a level 5 which represents a continuous process improvement; and Lean (software) Development, a principle supporting the concentration of the production on 'value added' activities and the elimination of reduction of 'not value added' activities.

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.

Development of the Quality of Australian Nursing Documentation in Aged Care (QANDAC) instrument to assess paper-based and electronic resident records.

PubMed

Wang, Ning; Björvell, Catrin; Hailey, David; Yu, Ping

2014-12-01

To develop an Australian nursing documentation in aged care (Quality of Australian Nursing Documentation in Aged Care (QANDAC)) instrument to measure the quality of paper-based and electronic resident records. The instrument was based on the nursing process model and on three attributes of documentation quality identified in a systematic review. The development process involved five phases following approaches to designing criterion-referenced measures. The face and content validities and the inter-rater reliability of the instrument were estimated using a focus group approach and consensus model. The instrument contains 34 questions in three sections: completion of nursing history and assessment, description of care process and meeting the requirements of data entry. Estimates of the validity and inter-rater reliability of the instrument gave satisfactory results. The QANDAC instrument may be a useful audit tool for quality improvement and research in aged care documentation. © 2013 ACOTA.

Air quality and future energy system planning

NASA Astrophysics Data System (ADS)

Sobral Mourao, Zenaida; Konadu, Dennis; Lupton, Rick

2016-04-01

Ambient air pollution has been linked to an increasing number of premature deaths throughout the world. Projected increases in demand for food, energy resources and manufactured products will likely contribute to exacerbate air pollution with an increasing impact on human health, agricultural productivity and climate change. Current events such as tampering emissions tests by VW car manufacturers, failure to comply with EU Air Quality directives and WHO guidelines by many EU countries, the problem of smog in Chinese cities and new industrial emissions regulations represent unique challenges but also opportunities for regulators, local authorities and industry. However current models and practices of energy and resource use do not consider ambient air impacts as an integral part of the planing process. Furthermore the analysis of drivers, sources and impacts of air pollution is often fragmented, difficult to understand and lacks effective visualization tools that bring all of these components together. This work aims to develop a model that links impacts of air quality on human health and ecosystems to current and future developments in the energy system, industrial and agricultural activity and patterns of land use. The model will be added to the ForeseerTM tool, which is an integrated resource analysis platform that has been developed at the University of Cambridge initially with funding from BP and more recently through the EPSRC funded Whole Systems Energy Modeling (WholeSEM) project. The basis of the tool is a set of linked physical models for energy, water and land, including the technologies that are used to transform these resources into final services such as housing, food, transport and household goods. The new air quality model will explore different feedback effects between energy, land and atmospheric systems with the overarching goal of supporting better communication about the drivers of air quality and to incorporate concerns about air quality into energy system planning. Some example applications of this work are: (1) to discover conflicts and synergies between air quality regulations and future developments in the energy system and land use change; (2) to show the drivers of air quality in a given spatial context; (3) to explore effective ways to visualize impacts of different energy, land use and emissions control policies on air quality. An initial test case for the Bay Area in California will be presented, extending the scope of the existing California ForeseerTM tool to identify impacts of different policies within the water-energy-land nexus on local air quality.

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.

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

NASA Technical Reports Server (NTRS)

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

2006-01-01

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 compared with USGS lkm 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, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

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 compared with USGS 1km 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, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta's growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Development and implementation of a remote-sensing and in situ data-assimilating version of CMAQ for operational PM2.5 forecasting. Part 1: MODIS aerosol optical depth (AOD) data-assimilation design and testing.

PubMed

McHenry, John N; Vukovich, Jeffery M; Hsu, N Christina

2015-12-01

This two-part paper reports on the development, implementation, and improvement of a version of the Community Multi-Scale Air Quality (CMAQ) model that assimilates real-time remotely-sensed aerosol optical depth (AOD) information and ground-based PM2.5 monitor data in routine prognostic application. The model is being used by operational air quality forecasters to help guide their daily issuance of state or local-agency-based air quality alerts (e.g. action days, health advisories). Part 1 describes the development and testing of the initial assimilation capability, which was implemented offline in partnership with NASA and the Visibility Improvement State and Tribal Association of the Southeast (VISTAS) Regional Planning Organization (RPO). In the initial effort, MODIS-derived aerosol optical depth (AOD) data are input into a variational data-assimilation scheme using both the traditional Dark Target and relatively new "Deep Blue" retrieval methods. Evaluation of the developmental offline version, reported in Part 1 here, showed sufficient promise to implement the capability within the online, prognostic operational model described in Part 2. In Part 2, the addition of real-time surface PM2.5 monitoring data to improve the assimilation and an initial evaluation of the prognostic modeling system across the continental United States (CONUS) is presented. Air quality forecasts are now routinely used to understand when air pollution may reach unhealthy levels. For the first time, an operational air quality forecast model that includes the assimilation of remotely-sensed aerosol optical depth and ground based PM2.5 observations is being used. The assimilation enables quantifiable improvements in model forecast skill, which improves confidence in the accuracy of the officially-issued forecasts. This helps air quality stakeholders be more effective in taking mitigating actions (reducing power consumption, ride-sharing, etc.) and avoiding exposures that could otherwise result in more serious air quality episodes or more deleterious health effects.

A Stirling engine for use with lower quality fuels

NASA Astrophysics Data System (ADS)

Paul, Christopher J.

There is increasing interest in using renewable fuels from biomass or alternative fuels such as municipal waste to reduce the need for fossil based fuels. Due to the lower heating values and higher levels of impurities, small scale electricity generation is more problematic. Currently, there are not many technologically mature options for small scale electricity generation using lower quality fuels. Even though there are few manufacturers of Stirling engines, the history of their development for two centuries offers significant guidance in developing a viable small scale generator set using lower quality fuels. The history, development, and modeling of Stirling engines were reviewed to identify possible model and engine configurations. A Stirling engine model based on the finite volume, ideal adiabatic model was developed. Flow dissipation losses are shown to need correcting as they increase significantly at low mean engine pressure and high engine speed. The complete engine including external components was developed. A simple yet effective method of evaluating the external heat transfer to the Stirling engine was created that can be used with any second order Stirling engine model. A derivative of the General Motors Ground Power Unit 3 was designed. By significantly increasing heater, cooler and regenerator size at the expense of increased dead volume, and adding a combustion gas recirculation, a generator set with good efficiency was designed.

Winter wheat quality monitoring and forecasting system based on remote sensing and environmental factors

NASA Astrophysics Data System (ADS)

Haiyang, Yu; Yanmei, Liu; Guijun, Yang; Xiaodong, Yang; Dong, Ren; Chenwei, Nie

2014-03-01

To achieve dynamic winter wheat quality monitoring and forecasting in larger scale regions, the objective of this study was to design and develop a winter wheat quality monitoring and forecasting system by using a remote sensing index and environmental factors. The winter wheat quality trend was forecasted before the harvest and quality was monitored after the harvest, respectively. The traditional quality-vegetation index from remote sensing monitoring and forecasting models were improved. Combining with latitude information, the vegetation index was used to estimate agronomy parameters which were related with winter wheat quality in the early stages for forecasting the quality trend. A combination of rainfall in May, temperature in May, illumination at later May, the soil available nitrogen content and other environmental factors established the quality monitoring model. Compared with a simple quality-vegetation index, the remote sensing monitoring and forecasting model used in this system get greatly improved accuracy. Winter wheat quality was monitored and forecasted based on the above models, and this system was completed based on WebGIS technology. Finally, in 2010 the operation process of winter wheat quality monitoring system was presented in Beijing, the monitoring and forecasting results was outputted as thematic maps.

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...

The Impact of the Developmental Training Model on Staff Development in Air Force Child Development Programs

ERIC Educational Resources Information Center

Bird, Candace Maria Edmonds

2010-01-01

In an effort to standardize training delivery and to individualize staff development based on observation and reflective practice, the Air Force implemented the Developmental Training Model (DTM) in its Child Development Programs. The goal of the Developmental Training Model is to enhance high quality programs through improvements in the training…

Facilitating the openEHR approach - organizational structures for defining high-quality archetypes.

PubMed

Kohl, Christian Dominik; Garde, Sebastian; Knaup, Petra

2008-01-01

Using openEHR archetypes to establish an electronic patient record promises rapid development and system interoperability by using or adopting existing archetypes. However, internationally accepted, high quality archetypes which enable a comprehensive semantic interoperability require adequate development and maintenance processes. Therefore, structures have to be created involving different health professions. In the following we present a model which facilitates and governs distributed but cooperative development and adoption of archetypes by different professionals including peer reviews. Our model consists of a hierarchical structure of professional committees and descriptions of the archetype development process considering these different committees.

Urban Quality Development and Management: Capacity Development and Continued Education for the Sustainable City

ERIC Educational Resources Information Center

Lehmann, Martin; Fryd, Ole

2008-01-01

Purpose: The purpose of this paper is to describe and discuss the development and the structure of a new international master on the subject of urban quality development and management (UQDM), and explore the potential of the process and the outcome in serving as models adoptable by faculty at other universities. Design/methodology/approach: The…

FEASIBILITY STUDY ON EXECUTIVE PROGRAM DEVELOPMENT FOR BASIN ECOSYSTEMS MODELING

EPA Science Inventory

The project was undertaken in order to provide a feasibility study in developing and implementing a complete executive program to interface automatically various basin-wide water quality models for use by relatively inexperienced modelers. This executive program should ultimately...

Real-time control of combined surface water quantity and quality: polder flushing.

PubMed

Xu, M; van Overloop, P J; van de Giesen, N C; Stelling, G S

2010-01-01

In open water systems, keeping both water depths and water quality at specified values is critical for maintaining a 'healthy' water system. Many systems still require manual operation, at least for water quality management. When applying real-time control, both quantity and quality standards need to be met. In this paper, an artificial polder flushing case is studied. Model Predictive Control (MPC) is developed to control the system. In addition to MPC, a 'forward estimation' procedure is used to acquire water quality predictions for the simplified model used in MPC optimization. In order to illustrate the advantages of MPC, classical control [Proportional-Integral control (PI)] has been developed for comparison in the test case. The results show that both algorithms are able to control the polder flushing process, but MPC is more efficient in functionality and control flexibility.

Photochemical Grid Modelling Study to Assess Potential Air Quality Impacts Associated with Energy Development in Colorado and Northern New Mexico.

NASA Astrophysics Data System (ADS)

Parker, L. K.; Morris, R. E.; Zapert, J.; Cook, F.; Koo, B.; Rasmussen, D.; Jung, J.; Grant, J.; Johnson, J.; Shah, T.; Pavlovic, T.

2015-12-01

The Colorado Air Resource Management Modeling Study (CARMMS) was funded by the Bureau of Land Management (BLM) to predict the impacts from future federal and non-federal energy development in Colorado and Northern New Mexico. The study used the Comprehensive Air Quality Model with extensions (CAMx) photochemical grid model (PGM) to quantify potential impacts from energy development from BLM field office planning areas. CAMx source apportionment technology was used to track the impacts from multiple (14) different emissions source regions (i.e. field office areas) within one simulation, as well as to assess the cumulative impact of emissions from all source regions combined. The energy development emissions estimates were for the year 2021 for three different development scenarios: (1) low; (2) high; (3) high with emissions mitigation. Impacts on air quality (AQ) including ozone, PM2.5, PM10, NO2, SO2, and air quality related values (AQRVs) such as atmospheric deposition, regional haze and changes in Acid Neutralizing Capacity (ANC) of lakes were quantified, and compared to establish threshold levels. In this presentation, we present a brief summary of the how the emission scenarios were developed, we compare the emission totals for each scenario, and then focus on the ozone impacts for each scenario to assess: (1). the difference in potential ozone impacts under the different development scenarios and (2). to establish the sensitivity of the ozone impacts to different emissions levels. Region-wide ozone impacts will be presented as well as impacts at specific locations with ozone monitors.

A multiresolution method for climate system modeling: application of spherical centroidal Voronoi tessellations

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

Ringler, Todd; Ju, Lili; Gunzburger, Max

2008-11-14

During the next decade and beyond, climate system models will be challenged to resolve scales and processes that are far beyond their current scope. Each climate system component has its prototypical example of an unresolved process that may strongly influence the global climate system, ranging from eddy activity within ocean models, to ice streams within ice sheet models, to surface hydrological processes within land system models, to cloud processes within atmosphere models. These new demands will almost certainly result in the develop of multiresolution schemes that are able, at least regionally, to faithfully simulate these fine-scale processes. Spherical centroidal Voronoimore » tessellations (SCVTs) offer one potential path toward the development of a robust, multiresolution climate system model components. SCVTs allow for the generation of high quality Voronoi diagrams and Delaunay triangulations through the use of an intuitive, user-defined density function. In each of the examples provided, this method results in high-quality meshes where the quality measures are guaranteed to improve as the number of nodes is increased. Real-world examples are developed for the Greenland ice sheet and the North Atlantic ocean. Idealized examples are developed for ocean–ice shelf interaction and for regional atmospheric modeling. In addition to defining, developing, and exhibiting SCVTs, we pair this mesh generation technique with a previously developed finite-volume method. Our numerical example is based on the nonlinear, shallow water equations spanning the entire surface of the sphere. This example is used to elucidate both the potential benefits of this multiresolution method and the challenges ahead.« less

a System Dynamics Model to Study the Importance of Infrastructure Facilities on Quality of Primary Education System in Developing Countries

NASA Astrophysics Data System (ADS)

Pedamallu, Chandra Sekhar; Ozdamar, Linet; Weber, Gerhard-Wilhelm; Kropat, Erik

2010-06-01

The system dynamics approach is a holistic way of solving problems in real-time scenarios. This is a powerful methodology and computer simulation modeling technique for framing, analyzing, and discussing complex issues and problems. System dynamics modeling and simulation is often the background of a systemic thinking approach and has become a management and organizational development paradigm. This paper proposes a system dynamics approach for study the importance of infrastructure facilities on quality of primary education system in developing nations. The model is proposed to be built using the Cross Impact Analysis (CIA) method of relating entities and attributes relevant to the primary education system in any given community. We offer a survey to build the cross-impact correlation matrix and, hence, to better understand the primary education system and importance of infrastructural facilities on quality of primary education. The resulting model enables us to predict the effects of infrastructural facilities on the access of primary education by the community. This may support policy makers to take more effective actions in campaigns.

Augmenting Species Diversity in Water Quality Criteria Derivation using Interspecies Correlation Models

EPA Science Inventory

The specific requirements for taxa diversity of the 1985 guidelines have limited the number of ambient water quality criteria (AWQC) developed for aquatic life protection. The EPA developed the Web-based Interspecies Correlation Estimation (Web-ICE) tool to allow extrapolation of...

Modeling Aircraft Emissions for Regional-scale Air Quality: Adapting a New Global Aircraft Emissions Database for the U.S

NASA Astrophysics Data System (ADS)

Arunachalam, S.; Baek, B. H.; Vennam, P. L.; Woody, M. C.; Omary, M.; Binkowski, F.; Fleming, G.

2012-12-01

Commercial aircraft emit substantial amounts of pollutants during their complete activity cycle that ranges from landing-and-takeoff (LTO) at airports to cruising in upper elevations of the atmosphere, and affect both air quality and climate. Since these emissions are not uniformly emitted over the earth, and have substantial temporal and spatial variability, it is vital to accurately evaluate and quantify the relative impacts of aviation emissions on ambient air quality. Regional-scale air quality modeling applications do not routinely include these aircraft emissions from all cycles. Federal Aviation Administration (FAA) has developed the Aviation Environmental Design Tool (AEDT), a software system that dynamically models aircraft performance in space and time to calculate fuel burn and emissions from gate-to-gate for all commercial aviation activity from all airports globally. To process in-flight aircraft emissions and to provide a realistic representation of these for treatment in grid-based air quality models, we have developed an interface processor called AEDTproc that accurately distributes full-flight chorded emissions in time and space to create gridded, hourly model-ready emissions input data. Unlike the traditional emissions modeling approach of treating aviation emissions as ground-level sources or processing emissions only from the LTO cycles in regional-scale air quality studies, AEDTproc distributes chorded inventories of aircraft emissions during LTO cycles and cruise activities into a time-variant 3-D gridded structure. We will present results of processed 2006 global emissions from AEDT over a continental U.S. modeling domain to support a national-scale air quality assessment of the incremental impacts of aircraft emissions on surface air quality. This includes about 13.6 million flights within the U.S. out of 31.2 million flights globally. We will focus on assessing spatio-temporal variability of these commercial aircraft emissions, and comparing upper tropospheric budgets of NOx from aircraft and lightning sources in the modeling domain.

Texas lignite and the visual resource: an objective approach to visual resource evaluation and management

Treesearch

Harlow C. Landphair

1979-01-01

This paper relates the evolution of an empirical model used to predict public response to scenic quality objectively. The text relates the methods used to develop the visual quality index model, explains the terms used in the equation and briefly illustrates how the model is applied and how it is tested. While the technical application of the model relies heavily on...

Modeling discharge, temperature, and water quality in the Tualatin River, Oregon

USGS Publications Warehouse

Rounds, Stewart A.; Wood, Tamara M.; Lynch, Dennis D.

1999-01-01

The discharge, water temperature, and water quality of the Tualatin River in northwestern Oregon was simulated with CE-QUAL-W2, a two-dimensional, laterally averaged model developed by the U.S. Army Corps of Engineers. The model was calibrated for May through October periods of 1991, 1992, and 1993. Nine hypothetical scenarios were tested with the model to provide insight for river managers and regulators.

Identifying models of delivery, care domains and quality indicators relevant to palliative day services: a scoping review protocol.

PubMed

O'Connor, Seán R; Dempster, Martin; McCorry, Noleen K

2017-05-16

With an ageing population and increasing numbers of people with life-limiting illness, there is a growing demand for palliative day services. There is a need to measure and demonstrate the quality of these services, but there is currently little agreement on which aspects of care should be used to do this. The aim of the scoping review will be to map the extent, range and nature of the evidence around models of delivery, care domains and existing quality indicators used to evaluate palliative day services. Electronic databases (MEDLINE, EMBASE, CINAHL, PsycINFO, Cochrane Central Register of Controlled Trials) will be searched for evidence using consensus development methods; randomised or quasi-randomised controlled trials; mixed methods; and prospective, longitudinal or retrospective case-control studies to develop or test quality indicators for evaluating palliative care within non-residential settings, including day hospices and community or primary care settings. At least two researchers will independently conduct all searches, study selection and data abstraction procedures. Meta-analyses and statistical methods of synthesis are not planned as part of the review. Results will be reported using numerical counts, including number of indicators in each care domain and by using qualitative approach to describe important indicator characteristics. A conceptual model will also be developed to summarise the impact of different aspects of quality in a palliative day service context. Methodological quality relating to indicator development will be assessed using the Appraisal of Indicators through Research and Evaluation (AIRE) tool. Overall strength of evidence will be assessed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system. Final decisions on quality assessment will be made via consensus between review authors. Identifying, developing and implementing evidence-based quality indicators is critical to the evaluation and continued improvement of palliative care. Review findings will be used to support clinicians and policymakers make decisions on which quality indicators are most appropriate for evaluating day services at the patient and service level, and to identify areas for further research.

Validating archetypes for the Multiple Sclerosis Functional Composite.

PubMed

Braun, Michael; Brandt, Alexander Ulrich; Schulz, Stefan; Boeker, Martin

2014-08-03

Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time-consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions.This case study provides evidence that both community- and tool-enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model.

Validating archetypes for the Multiple Sclerosis Functional Composite

PubMed Central

2014-01-01

Background Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. Methods A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Results Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time-consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. Conclusions The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions. This case study provides evidence that both community- and tool-enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model. PMID:25087081

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

Treesearch

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

2006-01-01

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

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…

Assessing the Quality of Life of Persons with Developmental Disabilities: Description of a New Model, Measuring Instruments, and Initial Findings.

ERIC Educational Resources Information Center

Raphael, Dennis; And Others

1996-01-01

A conceptual model of quality of life, developed at the Centre for Health Promotion at the University of Toronto (Canada), and associated instrumentation for collecting data from persons with developmental disabilities are presented. Results from a preliminary study with 41 participants support the reliability and validity of the model's…

Modeling Writing Development: Contribution of Transcription and Self-Regulation to Portuguese Students' Text Generation Quality

ERIC Educational Resources Information Center

Limpo, Teresa; Alves, Rui A.

2013-01-01

Writing is a complex activity that requires transcription and self-regulation. We used multiple-group structural equation modeling to test the contribution of transcription (handwriting and spelling), planning, revision, and self-efficacy to writing quality at 2 developmental points (Grades 4-6 vs. 7-9). In Grades 4-6, the model explained 76% of…

Modeling, Monitoring and Fault Diagnosis of Spacecraft Air Contaminants

NASA Technical Reports Server (NTRS)

Ramirez, W. Fred; Skliar, Mikhail; Narayan, Anand; Morgenthaler, George W.; Smith, Gerald J.

1996-01-01

Progress and results in the development of an integrated air quality modeling, monitoring, fault detection, and isolation system are presented. The focus was on development of distributed models of the air contaminants transport, the study of air quality monitoring techniques based on the model of transport process and on-line contaminant concentration measurements, and sensor placement. Different approaches to the modeling of spacecraft air contamination are discussed, and a three-dimensional distributed parameter air contaminant dispersion model applicable to both laminar and turbulent transport is proposed. A two-dimensional approximation of a full scale transport model is also proposed based on the spatial averaging of the three dimensional model over the least important space coordinate. A computer implementation of the transport model is considered and a detailed development of two- and three-dimensional models illustrated by contaminant transport simulation results is presented. The use of a well established Kalman filtering approach is suggested as a method for generating on-line contaminant concentration estimates based on both real time measurements and the model of contaminant transport process. It is shown that high computational requirements of the traditional Kalman filter can render difficult its real-time implementation for high-dimensional transport model and a novel implicit Kalman filtering algorithm is proposed which is shown to lead to an order of magnitude faster computer implementation in the case of air quality monitoring.

A Mass-balance nitrate model for predicting the effects of land use on ground-water quality in municipal wellhead-protection areas

USGS Publications Warehouse

Frimpter, M.H.; Donohue, J.J.; Rapacz, M.V.; Beye, H.G.

1990-01-01

A mass-balance accounting model can be used to guide the management of septic systems and fertilizers to control the degradation of groundwater quality in zones of an aquifer that contributes water to public supply wells. The nitrate nitrogen concentration of the mixture in the well can be predicted for steady-state conditions by calculating the concentration that results from the total weight of nitrogen and total volume of water entering the zone of contribution to the well. These calculations will allow water-quality managers to predict the nitrate concentrations that would be produced by different types and levels of development, and to plan development accordingly. Computations for different development schemes provide a technical basis for planners and managers to compare water quality effects and to select alternatives that limit nitrate concentration in wells. Appendix A contains tables of nitrate loads and water volumes from common sources for use with the accounting model. Appendix B describes the preparation of a spreadsheet for the nitrate loading calculations with a software package generally available for desktop computers. (USGS)

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.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

Comprehensive approach to smart urban development based on Big Data application

NASA Astrophysics Data System (ADS)

Kurcheeva, G. I.; Klochkov, G. A.

2018-05-01

Despite a certain technological backwardness of the Russian economy, the authors believe that the transition to the «smart city» is possible if one can solve such problems: providing large-scale investment, training and retraining specialists in the field of ICT, increasing innovation managers and consumers, increasing ICT participation in the work of governments, organizations and people, creating the appropriate conditions for the development of the information society. Accordingly, when developing models, it is planned to consider the relationship between quality of life and the existing system of indicators on trends of «smart cities». Monitoring of indicators of quality of life, mutually related indicators of technological development can help us develop the process model. When selecting directions for the main components of the «smart city», let us introduce the evaluation criteria that significantly affect the quality of the values of life. The development of «smart cities» should consider the international experience of the use of breakthrough innovative technology. Research scientists of various countries show a variety of approaches to identifying the main business processes in models of the «smart city». Having the international experience, it is necessary to improve business processes in the construction of a process model «smart city», adapting the model to the characteristics of the national environment.

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 Technical Reports Server (NTRS)

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

2006-01-01

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, 80 percent of the world s population will live in cities. Directly aligned with the expansion of cities is urban sprawl. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes. A reduction in air quality over cities is a major result of these impacts. Strategies that can be directly or indirectly implemented to help remediate air quality problems in cities and that can be accepted by political decision makers and the general public are now being explored to help bring down air pollutants and improve air quality. 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 spatial growth modeling (SGM) 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, which in turn, are used to model how ozone and 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 have been found to better characterize low density/suburban development as compared with USGS 1km 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, the regional planning agency for the area. This allows the State Environmental Protection agency to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rationale decisions on urban growth and sustainability for the metropolitan area in the future.

LUMINATE: Linking agricultural land use, local water quality and Gulf of Mexico hypoxia

USDA-ARS?s Scientific Manuscript database

In this paper, we discuss the importance of developing integrated assessment models to support the design and implementation of policies to address water quality problems associated with agricultural pollution. We describe a new modelling system, LUMINATE, which links land use decisions made at the...

Integrated care: an Information Model for Patient Safety and Vigilance Reporting Systems.

PubMed

Rodrigues, Jean-Marie; Schulz, Stefan; Souvignet, Julien

2015-01-01

Quality management information systems for safety as a whole or for specific vigilances share the same information types but are not interoperable. An international initiative tries to develop an integrated information model for patient safety and vigilance reporting to support a global approach of heath care quality.

Modified HWBI Model(s) Linking Service Flows to Well-Being Endpoints: Accounting for Environmental Quality

EPA Science Inventory

This report describes an approach for modifying ORD’s Human Well-Being Index (HWBI) to increase its utility by introducing a composite index developed independently of the HWBI effort. Using ORD’s Environmental Quality Index (EQI), this research examines the potential...

AN OPERATIONAL EVALUATION OF THE ETA-CMAQ AIR QUALITY FORECAST MODEL

EPA Science Inventory

The National Oceanic and Atmospheric Administration (NOAA), in collaboration with the Environmental Protection Agency (EPA), are developing an Air Quality Forecasting Program that will eventually result in an operational Nationwide Air Quality Forecasting System. The initial pha...

Developing Quality Indicators and Auditing Protocols from Formal Guideline Models: Knowledge Representation and Transformations

PubMed Central

Advani, Aneel; Goldstein, Mary; Shahar, Yuval; Musen, Mark A.

2003-01-01

Automated quality assessment of clinician actions and patient outcomes is a central problem in guideline- or standards-based medical care. In this paper we describe a model representation and algorithm for deriving structured quality indicators and auditing protocols from formalized specifications of guidelines used in decision support systems. We apply the model and algorithm to the assessment of physician concordance with a guideline knowledge model for hypertension used in a decision-support system. The properties of our solution include the ability to derive automatically (1) context-specific and (2) case-mix-adjusted quality indicators that (3) can model global or local levels of detail about the guideline (4) parameterized by defining the reliability of each indicator or element of the guideline. PMID:14728124

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

Two approaches to improving mental health care: positivist/quantitative versus skill-based/qualitative.

PubMed

Luchins, Daniel

2012-01-01

The quality improvement model currently used in medicine and mental health was adopted from industry, where it developed out of early 20th-century efforts to apply a positivist/quantitative agenda to improving manufacturing. This article questions the application of this model to mental health care. It argues that (1) developing "operational definitions" for something as value-laden as "quality" risks conflating two realms, what we measure with what we value; (2) when measurements that are tied to individuals are aggregated to establish benchmarks and goals, unwarranted mathematical assumptions are made; (3) choosing clinical outcomes is problematic; (4) there is little relationship between process measures and clinical outcomes; and (5) since changes in quality indices do not relate to improved clinical care, management's reliance on such indices provides an illusory sense of control. An alternative model is the older, skill-based/qualitative approach to knowing, which relies on "implicit/ expert" knowledge. These two approaches offer a series of contrasts: quality versus excellence, competence versus expertise, management versus leadership, extrinsic versus intrinsic rewards. The article concludes that we need not totally dispense with the current quality improvement model, but rather should balance quantitative efforts with the older qualitative approach in a mixed methods model.

Development of Internal System of Education Quality Assessment at a University

ERIC Educational Resources Information Center

Kalimullin, Aydar M.; Khodyreva, Elena ?.; Koinova-Zoellner, Julia

2016-01-01

The urgency of the research is determined by the need to ensure the quality of higher education an essential factor of which is development of the internal assessment system for educational activities at universities. The aim of the article is validation of the model of development of the internal assessment system for educational activities at…

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.

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

PubMed

Zhang, Lei; Zou, Zhihong; Shan, Wei

2017-06-01

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

[Quality assurance and total quality management in residential home care].

PubMed

Nübling, R; Schrempp, C; Kress, G; Löschmann, C; Neubart, R; Kuhlmey, A

2004-02-01

Quality, quality assurance, and quality management have been important topics in residential care homes for several years. However, only as a result of reform processes in the German legislation (long-term care insurance, care quality assurance) is a systematic discussion taking place. Furthermore, initiatives and holistic model projects, which deal with the assessment and improvement of service quality, were developed in the field of care for the elderly. The present article gives a critical overview of essential developments. Different comprehensive approaches such as the implementation of quality management systems, nationwide expert-based initiatives, and developments towards professionalizing care are discussed. Empirically based approaches, especially those emphasizing the assessment of outcome quality, are focused on in this work. Overall, the authors conclude that in the past few years comprehensive efforts have been made to improve the quality of care. However, the current situation still requires much work to establish a nationwide launch and implementation of evidence-based quality assurance and quality management.

Curriculum Transformation through Total Quality Management.

ERIC Educational Resources Information Center

Edwards, Barbara; Algozzine, Bob

1995-01-01

Describes a massive cultural transformation project at two Charlotte, North Carolina, elementary schools that used Deming's total quality management principles to restructure curricula according to Boyer's eight commonalities of learning. Shows how the FADE (focus, analyze, develop, and execute) model was used to develop a well-coordinated,…

MODELING THE IMPACTS OF LAND USE CHANGE ON HYDROLOGY AND WATER QUALITY OF A PACIFIC NORTHWEST WATERSHED

EPA Science Inventory

In many parts of the world, aquatic ecosystems are threatened by hydrological and water quality alterations due to extraction and conversion of natural resources for agriculture, urban development, forestry, mining, transportation, and water resources development. To evaluate the...

The Future of Energy

ERIC Educational Resources Information Center

Pallant, Amy; Pryputniewicz, Sarah; Lee, Hee-Sun

2017-01-01

This article describes a five-day online energy module, developed by the Concord Consortium (an educational research and development organization) in which students compare the effects of various energy sources on air quality, water quality, and land use. The module's interactive models explore hydraulic fracturing, real-world data on energy…

Modeling and water quality assessment during realisation of the coastal projects in Sochi region (Black sea coast of Russia)

NASA Astrophysics Data System (ADS)

Prokhoda-Shumskikh, L.

2012-04-01

Sochi region is the unique subtropical resort on the Black Sea coast of Russia. Nowadays due to Sochi is the capital of the Olympic game 2014, the government of the Russian Federation accepts the special federal program of Black Sea coast development. Program foresees the existing and creation of new coastal recreational and touristic complexes along the Russian Black Sea coast, such as complex of yacht harbors, water centers (aqua-centers), network of port localities and etc. These coastal projects are different, but the main problems of the environmental impact assessment are the same. The environmental impact and the relative damage should be assessed at the stage of construction as well as at the stage of operation. The key problem for the recreation coastal zone is water quality management. The port localities network as example is considered. To increase the accuracy and informative of forecasts for the coastal zone conditions the system-dynamic model has been developed, what allows to estimate the quality of the sea water, including that in the semi-enclosed coastal water areas with the limited water exchange. The model of water quality in the coastal zone includes the equations of deposit concentration changes and chemical substances evolution in the studied areas. The model incorporates joint description of cycles of two biogenic elements - nitrogen and phosphorus. The system is completely defined by the biogeochemical reactions. The sizes of such water areas allow the applying the full mixing and zero-dimensional models of water quality. The circulation of water inside the area is taken into account additionally. Water exchange in the semi-enclosed coastal water areas is defined by the discharge through the open parts of area border. The novelty of the offered model is its adaptation to the specific conditions of semi-enclosed coastal water areas. At the same time, the model contains details of the biogeochemical processes to complete modelling of the water quality. The developed system dynamics model is realized in the «PowerSim Studio» media. The data of natural measurements of water quality are applied for the model verification, and the correlated numerical results for the Russian Black Sea coast are presented. The main objective of the present paper is to present the actual examples, and to generalise the problems and to discuss the possible approaches of their solution.

Development of An Empirical Water Quality Model for Stormwater Based on Watershed Land Use in Puget Sound

DTIC Science & Technology

2007-03-29

Development of An Empirical Water Quality Model for Stormwater Based on Watershed Land Use in Puget Sound Valerie I. Cullinan, Christopher W. May...Systems Center, Bremerton, WA) Introduction The Sinclair and Dyes Inlet watershed is located on the west side of Puget Sound in Kitsap County...Washington, U.S.A. (Figure 1). The Puget Sound Naval Shipyard (PSNS), U.S Environmental Protection Agency (USEPA), the Washington State Department of

[Research advances in secondary development of Chinese patent medicines based on quality by design concept].

PubMed

Gong, Xing-Chu; Chen, Teng; Qu, Hai-Bin

2017-03-01

Quality by design (QbD) concept is an advanced pharmaceutical quality control concept. The application of QbD concept in the research and development of pharmaceutical processes of traditional Chinese medicines (TCM) mainly contains five parts, including the definition of critical processes and their evaluation criteria, the determination of critical process parameters and critical material attributes, the establishment of quantitative models, the development of design space, as well as the application and continuous improvement of control strategy. In this work, recent research advances in QbD concept implementation methods in the secondary development of Chinese patent medicines were reviewed, and five promising fields of the implementation of QbD concept were pointed out, including the research and development of TCM new drugs and Chinese medicine granules for formulation, modeling of pharmaceutical processes, development of control strategy based on industrial big data, strengthening the research of process amplification rules, and the development of new pharmaceutical equipment.. Copyright© by the Chinese Pharmaceutical Association.

White Paper Report of the 2011 RAD-AID Conference on International Radiology for Developing Countries: Integrating Multidisciplinary Strategies for Imaging Services in the Developing World

PubMed Central

Mazal, Jonathan; Lexa, Frank; Starikovsky, Anna; Jimenez, Pablo; Jain, Sanjay; DeStigter, Kristen K.; Nathan, Robert; Krebs, Elizabeth; Noble, Vicki; Marks, William; Hirsh, Richard N.; Short, Brad; Sydnor, Ryan; Timmreck-Jackson, Emily; Lungren, Matthew P.; Maxfield, Charles; Azene, Ezana M.; Garra, Brian S.; Choi, Brian G.; Lewin, Jonathan S.; Mollura, Daniel J.

2016-01-01

The 2011 RAD-AID Conference on International Radiology for Developing Countries discussed data, experiences and models pertaining to radiology in the developing world, where widespread shortages of imaging services significantly reduce health care quality and increase health care disparity. This white paper from the 2011 RAD-AID Conference represents consensus advocacy of multidisciplinary strategies to improve planning, accessibility and quality of imaging services in the developing world. Conference presenters and participants discussed numerous solutions to imaging and healthcare disparities including: (1) economic development for radiology service planning, (2) public health mechanisms to address disease and prevention at the population and community levels, (3) comparative clinical models to implement various clinical and workflow strategies adapted to unique developing world community contexts, (4) education to improve training and optimize service quality, and (5) technology innovation to bring new technical capabilities to limited-resource regions. PMID:22748790

White paper report of the 2011 RAD-AID Conference on International Radiology for Developing Countries: integrating multidisciplinary strategies for imaging services in the developing world.

PubMed

Everton, Kathryn L; Mazal, Jonathan; Mollura, Daniel J

2012-07-01

The 2011 RAD-AID Conference on International Radiology for Developing Countries discussed data, experiences, and models pertaining to radiology in the developing world, where widespread shortages of imaging services significantly reduce health care quality and increase health care disparities. This white paper from the 2011 RAD-AID conference represents consensus advocacy of multidisciplinary strategies to improve the planning, accessibility, and quality of imaging services in the developing world. Conference presenters and participants discussed numerous solutions to imaging and health care disparities, including (1) economic development for radiologic service planning, (2) public health mechanisms to address disease and prevention at the population and community levels, (3) comparative clinical models to implement various clinical and workflow strategies adapted to unique developing world community contexts, (4) education to improve training and optimize service quality, and (5) technology innovation to bring new technical capabilities to limited-resource regions. Published by Elsevier Inc.

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.

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

PubMed

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

2013-06-01

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

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

PubMed Central

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

2013-01-01

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

“AQMEII Status Update” | Science Inventory | US EPA

EPA Pesticide Factsheets

“AQMEII Status Update”This presentation provided an overview and status update of the Air Quality Model Evaluation International Initative (AQMEII) to participants of a workshop of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP) . In addition, the presentation also outlines the objectives and potential timeline for a possible next phase of AQMEII that would involve a collaboration with the current modeling activities of TF-HTAP. The purpose of the presentation was to provide participants at the HTAP meeting with an overview of current AQMEII activities and timelines and to obtain feedback from HTAP workshop participants regarding HTAP timelines. The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air po

Moving from Control to Culture in Higher Education Quality

NASA Astrophysics Data System (ADS)

Ehlers, Ulf-Daniel

In this article, it is argued that quality development in higher education needs to go beyond the implementation of rules and processes for quality management purposes to improve the educational quality. Quality development has to rather focus on promoting a quality culture, which enables individual actors to continuously improve their profession. While this understanding of quality as part of the organizational culture gains more importance, there is still a lack of fundamental research and conceptual understanding of the phenomenon in itself. This article aims to lay the foundations for a comprehensive understanding of quality culture in organizations focusing on higher education. For this purpose, the state of the art in research on organizational culture is discussed and a model of quality culture is presented.

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 highlights the point that the resolution of models is not the only factor in determining model performance - consistency between nested models is also important.

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes

PubMed Central

Schmitt, John; Beller, Justin; Russell, Brian; Quach, Anthony; Hermann, Elizabeth; Lyon, David; Breit, Jeffrey

2017-01-01

As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption of model predictive control in biopharmaceutical cell culture processes has been hampered, however, in part due to the large amount of data and expertise required to make a predictive model of controlled CQAs, a requirement for model predictive control. Here we developed a highly automated, perfusion apparatus to systematically and efficiently generate predictive models using application of system identification approaches. We successfully created a predictive model of %galactosylation using data obtained by manipulating galactose concentration in the perfusion apparatus in serialized step change experiments. We then demonstrated the use of the model in a model predictive controller in a simulated control scenario to successfully achieve a %galactosylation set point in a simulated fed‐batch culture. The automated model identification approach demonstrated here can potentially be generalized to many CQAs, and could be a more efficient, faster, and highly automated alternative to batch experiments for developing predictive models in cell culture processes, and allow the wider adoption of model predictive control in biopharmaceutical processes. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1647–1661, 2017 PMID:28786215

Model for selecting quality standards for a salad bar through identifying elements of customer satisfaction.

PubMed

Ouellet, D; Norback, J P

1993-11-01

Continuous quality improvement is the new requirement of the Joint Commission on Accreditation of Healthcare Organizations. This means that meeting quality standards will not be enough. Dietitians will need to improve those standards and the way they are selected. Because quality is defined in terms of the customers, all quality improvement projects must start by defining what customers want. Using a salad bar as an example, this article presents and illustrates a technique developed in Japan to identify which elements in a product or service will satisfy or dissatisfy consumers. Using a model and a questionnaire format developed by Kano and coworkers, 273 students were surveyed to classify six quality elements of a salad bar. Four elements showed a dominant "must-be" characteristic: food freshness, labeling of the dressings, no spills in the food, and no spills on the salad bar. The two other elements (food easy to reach and food variety) showed a dominant one-dimensional characteristic. By better understanding consumer perceptions of quality elements, foodservice managers can select quality standards that focus on what really matters to their consumers.

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.

Development of a regional bio-optical model for water quality assessment in the US Virgin Islands

NASA Astrophysics Data System (ADS)

Kerrigan, Kristi Lisa

Previous research in the US Virgin Islands (USVI) has demonstrated that land-based sources of pollution associated with watershed development and climate change are local and global factors causing coral reef degradation. A good indicator that can be used to assess stress on these environments is the water quality. Conventional assessment methods based on in situ measurements are timely and costly. Satellite remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic nature of water quality parameters by applying bio-optical models. Chlorophyll-a, suspended sediments (TSM), and colored-dissolved organic matter are color-producing agents (CPAs) that define the water quality and can be measured remotely. However, the interference of multiple optically active constituents that characterize the water column as well as reflectance from the bottom poses a challenge in shallow coastal environments in USVI. In this study, field and laboratory based data were collected from sites on St. Thomas and St. John to characterize the CPAs and bottom reflectance of substrates. Results indicate that the optical properties of these waters are a function of multiple CPAs with chlorophyll-a values ranging from 0.10 to 2.35 microg/L and TSM values from 8.97 to 15.7 mg/L. These data were combined with in situ hyperspectral radiometric and Landsat OLI satellite data to develop a regionally tiered model that can predict CPA concentrations using traditional band ratio and multivariate approaches. Band ratio models for the hyperspectral dataset (R2 = 0.35; RMSE = 0.10 microg/L) and Landsat OLI dataset (R2 = 0.35; RMSE = 0.12 microg/L) indicated promising accuracy. However, a stronger model was developed using a multivariate, partial least squares regression to identify wavelengths that are more sensitive to chlorophyll-a (R2 = 0.62, RMSE = 0.08 microg/L) and TSM (R2 = 0.55). This approach takes advantage of the full spectrum of hyperspectral data, thus providing a more robust predictive model. Models developed in this study will significantly improve near-real time and long-term water quality monitoring in USVI and will provide insight to factors contributing to coral reef decline.

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.

A Distributed Online Curriculum and Courseware Development Model

ERIC Educational Resources Information Center

Durdu, Pinar Onay; Yalabik, Nese; Cagiltay, Kursat

2009-01-01

A distributed online curriculum and courseware development model (DONC[superscript 2]) is developed and tested in this study. Courseware development teams which may work in different institutions who need to develop high quality, reduced cost, on time products will be the users of DONC[superscript 2]. The related features from the disciplines of…

Prediction of passenger ride quality in a multifactor environment

NASA Technical Reports Server (NTRS)

Dempsey, T. K.; Leatherwood, J. D.

1976-01-01

A model being developed, permits the understanding and prediction of passenger discomfort in a multifactor environment with particular emphasis upon combined noise and vibration. The model has general applicability to diverse transportation systems and provides a means of developing ride quality design criteria as well as a diagnostic tool for identifying the vibration and/or noise stimuli causing discomfort. Presented are: (1) a review of the basic theoretical and mathematical computations associated with the model, (2) a discussion of methodological and criteria investigations for both the vertical and roll axes of vibration, (3) a description of within-axis masking of discomfort responses for the vertical axis, thereby allowing prediction of the total discomfort due to any random vertical vibration, (4) a discussion of initial data on between-axis masking, and (5) discussion of a study directed towards extension of the vibration model to the more general case of predicting ride quality in the combined noise and vibration environments.

Writing fluency and quality in kindergarten and first grade: The role of attention, reading, transcription, and oral language

PubMed Central

Kent, Shawn; Wanzek, Jeanne; Petscher, Yaacov; Al Otaiba, Stephanie; Kim, Young-Suk

2013-01-01

In the present study, we examined the influence of kindergarten component skills on writing outcomes, both concurrently and longitudinally to first grade. Using data from 265 students, we investigated a model of writing development including attention regulation along with students’ reading, spelling, handwriting fluency, and oral language component skills. Results from structural equation modeling demonstrated that a model including attention was better fitting than a model with only language and literacy factors. Attention, a higher-order literacy factor related to reading and spelling proficiency, and automaticity in letter-writing were uniquely and positively related to compositional fluency in kindergarten. Attention and higher-order literacy factor were predictive of both composition quality and fluency in first grade, while oral language showed unique relations with first grade writing quality. Implications for writing development and instruction are discussed. PMID:25132722

Environmental & Water Quality Operational Studies: Improvement of Hydropower Release Dissolved Oxygen with Turbine Venting.

DTIC Science & Technology

1987-03-01

VENTED HYDROTURBINE .. 38 Model Development .......................................... 38 Model Application...mouth intake (Figures B26-B27). 37 A F -W V .0P V *W V *. V. VW . i. ~ ~ -% PART V: MODELING OF REAERATION THROUGH A VENTED HYDROTURBINE 75. Development

The Oregon Quality Education Model Applied to Schools Characterized by Low Student Enrollment, Sparse Distribution of Students, and Remote Settings with Findings Relating to Equity of Services. White Paper.

ERIC Educational Resources Information Center

Hill, Jonathan

The Oregon Quality Education Model (QEM) was developed by the state to identify the fundamental requirements and costs for a quality education that meets Oregon's academic standards. It will determine the funding of Oregon schools. Among the assumptions upon which the QEM is built were that elementary school enrollment is 340 students, middle…

Quality Evaluation of Raw Moutan Cortex Using the AHP and Gray Correlation-TOPSIS Method

PubMed Central

Zhou, Sujuan; Liu, Bo; Meng, Jiang

2017-01-01

Background: Raw Moutan cortex (RMC) is an important Chinese herbal medicine. Comprehensive and objective quality evaluation of Chinese herbal medicine has been one of the most important issues in the modern herbs development. Objective: To evaluate and compare the quality of RMC using the weighted gray correlation- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Materials and Methods: The percentage composition of gallic acid, catechin, oxypaeoniflorin, paeoniflorin, quercetin, benzoylpaeoniflorin, paeonol in different batches of RMC was determined, and then adopting MATLAB programming to construct the gray correlation-TOPSIS assessment model for quality evaluation of RMC. Results: The quality evaluation results of model evaluation and objective evaluation were consistent, reliable, and stable. Conclusion: The model of gray correlation-TOPSIS can be well applied to the quality evaluation of traditional Chinese medicine with multiple components and has broad prospect in application. SUMMARY The experiment tries to construct a model to evaluate the quality of RMC using the weighted gray correlation- Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. Results show the model is reliable and provide a feasible way in evaluating quality of traditional Chinese medicine with multiple components. PMID:28839384

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

PubMed

Heddam, Salim

2016-09-01

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

Developing Model Assesement for Learning (AFL) to Improve Quality and Evaluation in Pragmatic Course in IAIN Surakarta

ERIC Educational Resources Information Center

Retnaningsih, Woro; Djatmiko; Sumarlam

2017-01-01

The research objective is to develop a model of Assessment for Learning (AFL) in Pragmatic course in IAIN Surakarta. The research problems are as follows: How did the lecturer develop a model of AFL? What was the form of assessment information used as the model of AFL? How was the results of the implementation of the model of assessment. The…

A user-friendly model for spray drying to aid pharmaceutical product development.

PubMed

Grasmeijer, Niels; de Waard, Hans; Hinrichs, Wouter L J; Frijlink, Henderik W

2013-01-01

The aim of this study was to develop a user-friendly model for spray drying that can aid in the development of a pharmaceutical product, by shifting from a trial-and-error towards a quality-by-design approach. To achieve this, a spray dryer model was developed in commercial and open source spreadsheet software. The output of the model was first fitted to the experimental output of a Büchi B-290 spray dryer and subsequently validated. The predicted outlet temperatures of the spray dryer model matched the experimental values very well over the entire range of spray dryer settings that were tested. Finally, the model was applied to produce glassy sugars by spray drying, an often used excipient in formulations of biopharmaceuticals. For the production of glassy sugars, the model was extended to predict the relative humidity at the outlet, which is not measured in the spray dryer by default. This extended model was then successfully used to predict whether specific settings were suitable for producing glassy trehalose and inulin by spray drying. In conclusion, a spray dryer model was developed that is able to predict the output parameters of the spray drying process. The model can aid the development of spray dried pharmaceutical products by shifting from a trial-and-error towards a quality-by-design approach.

Models to predict length of stay in the Intensive Care Unit after coronary artery bypass grafting: a systematic review.

PubMed

Atashi, Alireza; Verburg, Ilona W; Karim, Hesam; Miri, Mirmohammad; Abu-Hanna, Ameen; de Jonge, Evert; de Keizer, Nicolette F; Eslami, Saeid

2018-06-01

Intensive Care Units (ICU) length of stay (LoS) prediction models are used to compare different institutions and surgeons on their performance, and is useful as an efficiency indicator for quality control. There is little consensus about which prediction methods are most suitable to predict (ICU) length of stay. The aim of this study is to systematically review models for predicting ICU LoS after coronary artery bypass grafting and to assess the reporting and methodological quality of these models to apply them for benchmarking. A general search was conducted in Medline and Embase up to 31-12-2016. Three authors classified the papers for inclusion by reading their title, abstract and full text. All original papers describing development and/or validation of a prediction model for LoS in the ICU after CABG surgery were included. We used a checklist developed for critical appraisal and data extraction for systematic reviews of prediction modeling and extended it on handling specific patients subgroups. We also defined other items and scores to assess the methodological and reporting quality of the models. Of 5181 uniquely identified articles, fifteen studies were included of which twelve on development of new models and three on validation of existing models. All studies used linear or logistic regression as method for model development, and reported various performance measures based on the difference between predicted and observed ICU LoS. Most used a prospective (46.6%) or retrospective study design (40%). We found heterogeneity in patient inclusion/exclusion criteria; sample size; reported accuracy rates; and methods of candidate predictor selection. Most (60%) studies have not mentioned the handling of missing values and none compared the model outcome measure of survivors with non-survivors. For model development and validation studies respectively, the maximum reporting (methodological) scores were 66/78 and 62/62 (14/22 and 12/22). There are relatively few models for predicting ICU length of stay after CABG. Several aspects of methodological and reporting quality of studies in this field should be improved. There is a need for standardizing outcome and risk factor definitions in order to develop/validate a multi-institutional and international risk scoring system.

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

EPA Pesticide Factsheets

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

Application of the Rasch Rating Scale Model to the Assessment of Quality of Life of Persons with Intellectual Disability

ERIC Educational Resources Information Center

Gomez, Laura E.; Arias, Benito; Verdugo, Miguel Angel; Navas, Patricia

2012-01-01

Background: Most instruments that assess quality of life have been validated by means of the classical test theory (CTT). However, CTT limitations have resulted in the development of alternative models, such as the Rasch rating scale model (RSM). The main goal of this paper is testing and improving the psychometric properties of the INTEGRAL…

Longitudinal analysis on the development of hospital quality management systems in the Netherlands.

PubMed

Dückers, Michel; Makai, Peter; Vos, Leti; Groenewegen, Peter; Wagner, Cordula

2009-10-01

Many changes have been initiated in the Dutch hospital sector to optimize health-care delivery: national agenda-setting, increased competition and transparency, a new system of hospital reimbursement based on diagnosis-treatment combinations, intensified monitoring of quality and a multi-layered organizational development programme based on quality improvement collaboratives. The objective is to answer the question as to whether these changes were accompanied by a further development of hospital quality management systems and to what extent did the development within the multi-layered programme hospitals differ from that in other hospitals. Longitudinal data were collected in 1995, 2000, 2005 and 2007 using a validated questionnaire. Descriptive analyses and multi-level modelling were applied to test whether: (1) quality management system development stages in hospitals differ over time, (2) development stages and trends differ between hospitals participating or not participating in the multi-layered programme and (3) hospital size has an effect on development stage. Dutch hospital sector between 1995 and 2007. Hospital organizations. Changes through time. Quality management system development stage. Since 1995, hospital quality management systems have reached higher development levels. Programme participants have developed their quality management system more rapidly than have non-participants. However, this effect is confounded by hospital size. Study results suggest that the combination of policy measures at macro level was accompanied by an increase in hospital size and the further development of quality management systems. Hospitals are entering the stage of systematic quality improvement.

DEVELOPMENT OF NEAR-SHORE HYDRODYNAMIC MODELS FOR BEACH CLOSURE FORECASTING IN THE GREAT LAKES

EPA Science Inventory

Water quality managers and other planning and decision entities are increasingly calling for up-to-the-minute data on present water quality conditions or forecasts of these data that can be used to adjust or respond to quickly developing activities with environmental implications...

DEVELOPMENT AND APPLICATIONS OF CFD SIMULATIONS SUPPORTING URBAN AIR QUALITY AND HOMELAND SECURITY

EPA Science Inventory

Prior to September 11, 2001 developments of Computational Fluid Dynamics (CFD) were begun to support air quality applications. CFD models are emerging as a promising technology for such assessments, in part due to the advancing power of computational hardware and software. CFD si...

DEVELOPMENT AND APPLICATIONS OF CFD SIMULATIONS IN SUPPORT OF AIR QUALITY STUDIES INVOLVING BUILDINGS

EPA Science Inventory

There is a need to properly develop the application of Computational Fluid Dynamics (CFD) methods in support of air quality studies involving pollution sources near buildings at industrial sites. CFD models are emerging as a promising technology for such assessments, in part due ...

Software quality and process improvement in scientific simulation codes

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

Ambrosiano, J.; Webster, R.

1997-11-01

This report contains viewgraphs on the quest to develope better simulation code quality through process modeling and improvement. This study is based on the experience of the authors and interviews with ten subjects chosen from simulation code development teams at LANL. This study is descriptive rather than scientific.

Constraint-Driven Software Design: An Escape from the Waterfall Model.

ERIC Educational Resources Information Center

de Hoog, Robert; And Others

1994-01-01

Presents the principles of a development methodology for software design based on a nonlinear, product-driven approach that integrates quality aspects. Two examples are given to show that the flexibility needed for building high quality systems leads to integrated development environments in which methodology, product, and tools are closely…

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

Software development infrastructure for the HYBRID modeling and simulation project

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

Epiney, Aaron S.; Kinoshita, Robert A.; Kim, Jong Suk

One of the goals of the HYBRID modeling and simulation project is to assess the economic viability of hybrid systems in a market that contains renewable energy sources like wind. The idea is that it is possible for the nuclear plant to sell non-electric energy cushions, which absorb (at least partially) the volatility introduced by the renewable energy sources. This system is currently modeled in the Modelica programming language. To assess the economics of the system, an optimization procedure is trying to find the minimal cost of electricity production. The RAVEN code is used as a driver for the wholemore » problem. It is assumed that at this stage, the HYBRID modeling and simulation framework can be classified as non-safety “research and development” software. The associated quality level is Quality Level 3 software. This imposes low requirements on quality control, testing and documentation. The quality level could change as the application development continues.Despite the low quality requirement level, a workflow for the HYBRID developers has been defined that include a coding standard and some documentation and testing requirements. The repository performs automated unit testing of contributed models. The automated testing is achieved via an open-source python script called BuildingsP from Lawrence Berkeley National Lab. BuildingsPy runs Modelica simulation tests using Dymola in an automated manner and generates and runs unit tests from Modelica scripts written by developers. In order to assure effective communication between the different national laboratories a biweekly videoconference has been set-up, where developers can report their progress and issues. In addition, periodic face-face meetings are organized intended to discuss high-level strategy decisions with management. A second means of communication is the developer email list. This is a list to which everybody can send emails that will be received by the collective of the developers and managers involved in the project. Thirdly, to exchange documents quickly, a SharePoint directory has been set-up. SharePoint allows teams and organizations to intelligently share, and collaborate on content from anywhere.« less

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.

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

EPA Science Inventory

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used t...

Quality Assurance in E-Learning: PDPP Evaluation Model and Its Application

ERIC Educational Resources Information Center

Zhang, Weiyuan; Cheng, Y. L.

2012-01-01

E-learning has become an increasingly important teaching and learning mode in educational institutions and corporate training. The evaluation of e-learning, however, is essential for the quality assurance of e-learning courses. This paper constructs a four-phase evaluation model for e-learning courses, which includes planning, development,…

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

ERIC Educational Resources Information Center

Bremer, C.

2012-01-01

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

Guide to Selected Algorithms, Distributions, and Databases Used in Exposure Models Developed By the Office of Air Quality Planning and Standards

EPA Pesticide Factsheets

In the evaluation of emissions standards, OAQPS frequently uses one or more computer-based models to estimate the number of people who will be exposed to the air pollution levels that are expected to occur under various air quality scenarios.

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

EPA Science Inventory

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

Teachers as Managers of the Modelling Process

ERIC Educational Resources Information Center

Lingefjard, Thomas; Meier, Stephanie

2010-01-01

The work in the Comenius Network project Developing Quality in Mathematics Education II (DQME II) has a main focus on development and evaluation of modelling tasks. One reason is the gap between what mathematical modelling is and what is taught in mathematical classrooms. This article deals with one modelling task and focuses on how two teachers…

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.

Ground-water models for water resource planning

USGS Publications Warehouse

Moore, J.E.

1983-01-01

In the past decade hydrogeologists have emphasized the development of computer-based mathematical models to aid in the understanding of flow, the transport of solutes, transport of heat, and deformation in the ground-water system. These models have been used to provide information and predictions for water managers. Too frequently, ground-water was neglected in water resource planning because managers believed that it could not be adequately evaluated in terms of availability, quality, and effect of development on surface-water supplies. Now, however, with newly developed digital ground-water models, effects of development can be predicted. Such models have been used to predict hydrologic and quality changes under different stresses. These models have grown in complexity over the last ten years from simple one-layer models to three-dimensional simulations of ground-water flow, which may include solute transport, heat transport, effects of land subsidence, and encroachment of saltwater. Case histories illustrate how predictive ground-water models have provided the information needed for the sound planning and management of water resources in the USA. ?? 1983 D. Reidel Publishing Company.

A Data Model for Teleconsultation in Managing High-Risk Pregnancies: Design and Preliminary Evaluation

PubMed Central

Deldar, Kolsoum

2017-01-01

Background Teleconsultation is a guarantor for virtual supervision of clinical professors on clinical decisions made by medical residents in teaching hospitals. Type, format, volume, and quality of exchanged information have a great influence on the quality of remote clinical decisions or tele-decisions. Thus, it is necessary to develop a reliable and standard model for these clinical relationships. Objective The goal of this study was to design and evaluate a data model for teleconsultation in the management of high-risk pregnancies. Methods This study was implemented in three phases. In the first phase, a systematic review, a qualitative study, and a Delphi approach were done in selected teaching hospitals. Systematic extraction and localization of diagnostic items to develop the tele-decision clinical archetypes were performed as the second phase. Finally, the developed model was evaluated using predefined consultation scenarios. Results Our review study has shown that present medical consultations have no specific structure or template for patient information exchange. Furthermore, there are many challenges in the remote medical decision-making process, and some of them are related to the lack of the mentioned structure. The evaluation phase of our research has shown that data quality (P<.001), adequacy (P<.001), organization (P<.001), confidence (P<.001), and convenience (P<.001) had more scores in archetype-based consultation scenarios compared with routine-based ones. Conclusions Our archetype-based model could acquire better and higher scores in the data quality, adequacy, organization, confidence, and convenience dimensions than ones with routine scenarios. It is probable that the suggested archetype-based teleconsultation model may improve the quality of physician-physician remote medical consultations. PMID:29242181

Development of techniques and data for evaluating ride quality. Volume 2 : ride-quality research

DOT National Transportation Integrated Search

1978-03-01

Ride-quality models for city buses and intercity trains are presented : and discussed in terms of their ability to predict passenger : comfort and ride acceptability. : This, the second of three volumes, contains a technical discussion, : of the ride...

OVERVIEW OF THE CLIMATE IMPACT ON REGIONAL AIR QUALITY (CIRAQ) PROJECT

EPA Science Inventory

The Climate Impacts on Regional Air Quality (CIRAQ) project will develop model-estimated impacts of global climate changes on ozone and particulate matter (PM) in direct support of the USEPA Global Change Research Program's (GCRP) national air quality assessment. EPA's urban/reg...

Health care competition, strategic mission, and patient satisfaction: research model and propositions.

PubMed

Rivers, Patrick A; Glover, Saundra H

2008-01-01

In all industries, competition among businesses has long been encouraged as a mechanism to increase value for patients. In other words, competition ensures the provision of better products and services to satisfy the needs of customers This paper aims to develop a model that can be used to empirically investigate a number of complex issues and relationships associated with competition in the health care industry. A literature review was conducted. A total of 50 items of literature related to the subject were reviewed. Various perspectives of competition, the nature of service quality, health system costs, and patient satisfaction in health care are examined. A model of the relationship among these variables is developed. The model depicts patient satisfaction as an outcome measure directly dependent on competition. Quality of care and health care systems costs, while also directly dependent on the strategic mission and goals, are considered as determinants of customer satisfaction as well. The model is discussed in the light of propositions for empirical research. Empirical studies based on the model proposed in this paper should help identify areas with significant impact on patient satisfaction while maintaining high quality of service at lower costs in a competitive environment. The authors develop a research model which included propositions to examine the complex issues of competition in the health care industry.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Development of a multihospital pharmacy quality assurance program.

PubMed

Hoffmann, R P; Ravin, R; Colaluca, D M; Gifford, R; Grimes, D; Grzegorczyk, R; Keown, F; Kuhr, F; McKay, R; Peyser, J; Ryan, R; Zalewski, C

1980-07-01

Seven community hospitals have worked cooperatively for 18 months to develop an initial hospital pharmacy quality assurance program. Auditing criteria were developed for nine service areas corresponding to the model program developed by the American Society of Hospital Pharmacists. Current plans are to implement and modify this program as required at each participating hospital. Follow-up programs will also be essential to a functional, ongoing program, and these will be developed in the future.

Storm Water Management Model Reference Manual Volume II ...

EPA Pesticide Factsheets

SWMM is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and generate runoff and pollutant loads. The routing portion of SWMM transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps. The reference manual for this edition of SWMM is comprised of three volumes. Volume I describes SWMM’s hydrologic models, Volume II its hydraulic models, and Volume III its water quality and low impact development models. This document provides the underlying mathematics for the hydraulic calculations of the Storm Water Management Model (SWMM)

Quality assessment and artificial neural networks modeling for characterization of chemical and physical parameters of potable water.

PubMed

Salari, Marjan; Salami Shahid, Esmaeel; Afzali, Seied Hosein; Ehteshami, Majid; Conti, Gea Oliveri; Derakhshan, Zahra; Sheibani, Solmaz Nikbakht

2018-04-22

Today, due to the increase in the population, the growth of industry and the variety of chemical compounds, the quality of drinking water has decreased. Five important river water quality properties such as: dissolved oxygen (DO), total dissolved solids (TDS), total hardness (TH), alkalinity (ALK) and turbidity (TU) were estimated by parameters such as: electric conductivity (EC), temperature (T), and pH that could be measured easily with almost no costs. Simulate water quality parameters were examined with two methods of modeling include mathematical and Artificial Neural Networks (ANN). Mathematical methods are based on polynomial fitting with least square method and ANN modeling algorithms are feed-forward networks. All conditions/circumstances covered by neural network modeling were tested for all parameters in this study, except for Alkalinity. All optimum ANN models developed to simulate water quality parameters had precision value as R-value close to 0.99. The ANN model extended to simulate alkalinity with R-value equals to 0.82. Moreover, Surface fitting techniques were used to refine data sets. Presented models and equations are reliable/useable tools for studying water quality parameters at similar rivers, as a proper replacement for traditional water quality measuring equipment's. Copyright © 2018 Elsevier Ltd. All rights reserved.

Integrating Hydrologic and Water Quality Models as a Decision Support Tool for Implementation of Low Impact Development in a Coastal Urban Watershed under Climate Variability and Sea Level Rise

NASA Astrophysics Data System (ADS)

Chang, N. B.

2016-12-01

Many countries concern about development and redevelopment efforts in urban regions to reduce the flood risk by considering hazards such as high-tide events, storm surge, flash floods, stormwater runoff, and impacts of sea level rise. Combining these present and future hazards with vulnerable characteristics found throughout coastal communities such as majority low-lying areas and increasing urban development, create scenarios for increasing exposure of flood hazard. As such, the most vulnerable areas require adaptation strategies and mitigation actions for flood hazard management. In addition, in the U.S., Numeric Nutrient Criteria (NNC) are a critical tool for protecting and restoring the designated uses of a waterbody with regard to nitrogen and phosphorus pollution. Strategies such as low impact development (LID) have been promoted in recent years as an alternative to traditional stormwater management and drainage to control both flooding and water quality impact. LID utilizes decentralized multifunctional site designs and incorporates on-site storm water management practices rather than conventional storm water management approaches that divert flow toward centralized facilities. How to integrate hydrologic and water quality models to achieve the decision support becomes a challenge. The Cross Bayou Watershed of Pinellas County in Tampa Bay, a highly urbanized coastal watershed, is utilized as a case study due to its sensitivity to flood hazards and water quality management within the watershed. This study will aid the County, as a decision maker, to implement its stormwater management policy and honor recent NNC state policy via demonstration of an integrated hydrologic and water quality model, including the Interconnected Channel and Pond Routing Model v.4 (ICPR4) and the BMPTRAIN model as a decision support tool. The ICPR4 can be further coupled with the ADCIRC/SWAN model to reflect the storm surge and seal level rise in coastal regions.

Relations between continuous real-time physical properties and discrete water-quality constituents in the Little Arkansas River, south-central Kansas, 1998-2014

USGS Publications Warehouse

Rasmussen, Patrick P.; Eslick, Patrick J.; Ziegler, Andrew C.

2016-08-11

Water from the Little Arkansas River is used as source water for artificial recharge of the Equus Beds aquifer, one of the primary water-supply sources for the city of Wichita, Kansas. The U.S. Geological Survey has operated two continuous real-time water-quality monitoring stations since 1995 on the Little Arkansas River in Kansas. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to compute concentrations of those constituents of interest. Site-specific regression models were originally published in 2000 for the near Halstead and near Sedgwick U.S. Geological Survey streamgaging stations and the site-specific regression models were then updated in 2003. This report updates those regression models using discrete and continuous data collected during May 1998 through August 2014. In addition to the constituents listed in the 2003 update, new regression models were developed for total organic carbon. The real-time computations of water-quality concentrations and loads are available at http://nrtwq.usgs.gov. The water-quality information in this report is important to the city of Wichita because water-quality information allows for real-time quantification and characterization of chemicals of concern (including chloride), in addition to nutrients, sediment, bacteria, and atrazine transported in the Little Arkansas River. The water-quality information in this report aids in the decision making for water treatment before artificial recharge.

Model documentation for relations between continuous real-time and discrete water-quality constituents in the North Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999--2009

USGS Publications Warehouse

Stone, Mandy L.; Graham, Jennifer L.; Gatotho, Jackline W.

2013-01-01

Cheney Reservoir in south-central Kansas is one of the primary sources of water for the city of Wichita. The North Fork Ninnescah River is the largest contributing tributary to Cheney Reservoir. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station since 1998 on the North Fork Ninnescah River. Continuously measured water-quality physical properties include streamflow, specific conductance, pH, water temperature, dissolved oxygen, and turbidity. Discrete water-quality samples were collected during 1999 through 2009 and analyzed for sediment, nutrients, bacteria, and other water-quality constituents. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to estimate concentrations of those constituents of interest that are not easily measured in real time because of limitations in sensor technology and fiscal constraints. Regression models were published in 2006 that were based on a different dataset collected during 1997 through 2003. This report updates those models using discrete and continuous data collected during January 1999 through December 2009. Models also were developed for five new constituents, including additional nutrient species and indicator bacteria. The water-quality information in this report is important to the city of Wichita because it allows the concentrations of many potential pollutants of interest, including nutrients and sediment, to be estimated in real time and characterized over conditions and time scales that would not be possible otherwise.

Underground Test Area Quality Assurance Project Plan Nevada National Security Site, Nevada, Revision 0

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

Irene Farnham

This Quality Assurance Project Plan (QAPP) provides the overall quality assurance (QA) program requirements and general quality practices to be applied to the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Site Office (NNSA/NSO) Underground Test Area (UGTA) Sub-Project (hereafter the Sub-Project) activities. The requirements in this QAPP are consistent with DOE Order 414.1C, Quality Assurance (DOE, 2005); U.S. Environmental Protection Agency (EPA) Guidance for Quality Assurance Project Plans for Modeling (EPA, 2002); and EPA Guidance on the Development, Evaluation, and Application of Environmental Models (EPA, 2009). The QAPP Revision 0 supersedes DOE--341, Underground Test Area Quality Assurancemore » Project Plan, Nevada Test Site, Nevada, Revision 4.« less

Innovative Stormwater Quality Tools by SARA for Holistic Watershed Master Planning

NASA Astrophysics Data System (ADS)

Thomas, S. M.; Su, Y. C.; Hummel, P. R.

2016-12-01

Stormwater management strategies such as Best Management Practices (BMP) and Low-Impact Development (LID) have increasingly gained attention in urban runoff control, becoming vital to holistic watershed master plans. These strategies can help address existing water quality impairments and support regulatory compliance, as well as guide planning and management of future development when substantial population growth and urbanization is projected to occur. However, past efforts have been limited to qualitative planning due to the lack of suitable tools to conduct quantitative assessment. The San Antonio River Authority (SARA), with the assistance of Lockwood, Andrews & Newnam, Inc. (LAN) and AQUA TERRA Consultants (a division of RESPEC), developed comprehensive hydrodynamic and water quality models using the Hydrological Simulation Program-FORTRAN (HSPF) for several urban watersheds in the San Antonio River Basin. These models enabled watershed management to look at water quality issues on a more refined temporal and spatial scale than the limited monitoring data. They also provided a means to locate and quantify potential water quality impairments and evaluate the effects of mitigation measures. To support the models, a suite of software tools were developed. including: 1) SARA Timeseries Utility Tool for managing and processing of large model timeseries files, 2) SARA Load Reduction Tool to determine load reductions needed to achieve screening levels for each modeled constituent on a sub-basin basis, and 3) SARA Enhanced BMP Tool to determine the optimal combination of BMP types and units needed to achieve the required load reductions. Using these SARA models and tools, water quality agencies and stormwater professionals can determine the optimal combinations of BMP/LID to accomplish their goals and save substantial stormwater infrastructure and management costs. The tools can also help regulators and permittees evaluate the feasibility of achieving compliance using BMP/LID. The project has gained national attention, being showcased in multiple newsletters, professional magazines, and conference presentations. The project also won the Texas American Council of Engineering Companies (ACEC) Gold Medal Award and the ACEC National Recognition Award in 2016.

Methodologic issues in assessing the quality of life of cancer patients.

PubMed

Aaronson, N K

1991-02-01

Although quality of life assessments have been employed successfully in descriptive and evaluative studies in oncology, their use in cancer clinical trials has, to date, been limited. A range of issues have impeded the conduct of clinical trial-based quality of life investigations. These include: the absence of theoretical models to guide the development of quality of life measures; over-reliance on ad hoc approaches to quality of life assessment; and insufficient attention to the practical constraints operating in clinical research settings. Of primary importance is the need to develop multidimensional quality of life instruments that are brief and psychometrically robust. It is suggested that future work on instrument development focus on refining currently available generic or cancer-specific measures, and on developing new diagnostic-specific questionnaire modules. This psychometric work should be guided by appropriate theoretical models of the relationship among health-related quality of life domains. Although it is widely accepted that the patient represents the most appropriate source of quality of life data, it is suggested that efforts also be directed toward improving the validity and reliability of physician-generated assessments of patients' performance status and of treatment toxicities, and toward determining the feasibility of employing family members as proxy raters of the psychologic and social health status of patients who are unwilling or unable to provide such information. Additional attention should be paid to the many logistical problems that arise in clinical trial-based quality of life investigations. In particular, research designs and data collection procedures should be selected that minimize patient, medical staff, and institutional burden.

The trust-commitment challenge in service quality-loyalty relationships.

PubMed

Moreira, Antonio Carrizo; Silva, Pedro Miguel

2015-01-01

The purpose of this paper is to develop and empirically test a model to examine service quality, satisfaction, trust and commitment as loyalty antecedents in a private healthcare service. The approach was tested using structural equation modelling, involving 175 patients from a private Portuguese healthcare unit, using a revised Service Quality Assessment Scale (SQAS) scale for service quality evaluation. The scale used to evaluate service quality is valid and meaningful. Service quality proved to be a multidimensional construct and relevant to build satisfaction. The path satisfaction→trust→loyalty was validated, whereas the path satisfaction→commitment→loyalty was not statistically supported. The revised SQAS scale showed good internal consistency in healthcare context. Further trust-commitment antecedents must be examined in a private healthcare landscape to generalise the findings. Healthcare quality managers must explore the service quality dimensions to generate satisfaction among their patients. Developing trust generates positive patient attitudes and loyalty. This study explores using the SQAS scale in a private healthcare context. The authors provide further evidence that service quality is an antecedent and different from satisfaction. All the measures used proved to be valid and reliable. Trust and commitment play different roles in their relationship with loyalty.

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

PubMed

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

2015-02-01

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

Industrial pollution and the management of river water quality: a model of Kelani River, Sri Lanka.

PubMed

Gunawardena, Asha; Wijeratne, E M S; White, Ben; Hailu, Atakelty; Pandit, Ram

2017-08-19

Water quality of the Kelani River has become a critical issue in Sri Lanka due to the high cost of maintaining drinking water standards and the market and non-market costs of deteriorating river ecosystem services. By integrating a catchment model with a river model of water quality, we developed a method to estimate the effect of pollution sources on ambient water quality. Using integrated model simulations, we estimate (1) the relative contribution from point (industrial and domestic) and non-point sources (river catchment) to river water quality and (2) pollutant transfer coefficients for zones along the lower section of the river. Transfer coefficients provide the basis for policy analyses in relation to the location of new industries and the setting of priorities for industrial pollution control. They also offer valuable information to design socially optimal economic policy to manage industrialized river catchments.

The Quality Adaptation Model: Adaptation and Adoption of the Quality Standard ISO/IEC 19796-1 for Learning, Education, and Training

ERIC Educational Resources Information Center

Pawlowski, Jan M.

2007-01-01

In 2005, the new quality standard for learning, education, and training, ISO/IEC 19796-1, was published. Its purpose is to help educational organizations to develop quality systems and to improve the quality of their processes, products, and services. In this article, the standard is presented and compared to existing approaches, showing the…

Development of Load Duration Curve System in Data Scarce Watersheds Based on a Distributed Hydrological Model

NASA Astrophysics Data System (ADS)

WANG, J.

2017-12-01

In stream water quality control, the total maximum daily load (TMDL) program is very effective. However, the load duration curves (LDC) of TMDL are difficult to be established because no sufficient observed flow and pollutant data can be provided in data-scarce watersheds in which no hydrological stations or consecutively long-term hydrological data are available. Although the point sources or a non-point sources of pollutants can be clarified easily with the aid of LDC, where does the pollutant come from and to where it will be transported in the watershed cannot be traced by LDC. To seek out the best management practices (BMPs) of pollutants in a watershed, and to overcome the limitation of LDC, we proposed to develop LDC based on a distributed hydrological model of SWAT for the water quality management in data scarce river basins. In this study, firstly, the distributed hydrological model of SWAT was established with the scarce-hydrological data. Then, the long-term daily flows were generated with the established SWAT model and rainfall data from the adjacent weather station. Flow duration curves (FDC) was then developed with the aid of generated daily flows by SWAT model. Considering the goal of water quality management, LDC curves of different pollutants can be obtained based on the FDC. With the monitored water quality data and the LDC curves, the water quality problems caused by the point or non-point source pollutants in different seasons can be ascertained. Finally, the distributed hydrological model of SWAT was employed again to tracing the spatial distribution and the origination of the pollutants of coming from what kind of agricultural practices and/or other human activities. A case study was conducted in the Jian-jiang river, a tributary of Yangtze river, of Duyun city, Guizhou province. Results indicate that this kind of method can realize the water quality management based on TMDL and find out the suitable BMPs for reducing pollutant in a watershed.

Development and application of the microbial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

NASA Astrophysics Data System (ADS)

Hong, E.; Park, Y.; Muirhead, R.; Jeong, J.; Pachepsky, Y. A.

2017-12-01

Pathogenic microorganisms in recreational and irrigation waters remain the subject of concern. Water quality models are used to estimate microbial quality of water sources, to evaluate microbial contamination-related risks, to guide the microbial water quality monitoring, and to evaluate the effect of agricultural management on the microbial water quality. The Agricultural Policy/Environmental eXtender (APEX) is the watershed-scale water quality model that includes highly detailed representation of agricultural management. The APEX currently does not have microbial fate and transport simulation capabilities. The objective of this work was to develop the first APEX microbial fate and transport module that could use the APEX conceptual model of manure removal together with recently introduced conceptualizations of the in-stream microbial fate and transport. The module utilizes manure erosion rates found in the APEX. Bacteria survival in soil-manure mixing layer was simulated with the two-stage survival model. Individual survival patterns were simulated for each manure application date. Simulated in-stream microbial fate and transport processes included the reach-scale passive release of bacteria with resuspended bottom sediment during high flow events, the transport of bacteria from bottom sediment due to the hyporheic exchange during low flow periods, the deposition with settling sediment, and the two-stage survival. Default parameter values were available from recently published databases. The APEX model with the newly developed microbial fate and transport module was applied to simulate seven years of monitoring data for the Toenepi watershed in New Zealand. Based on calibration and testing results, the APEX with the microbe module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water under various agricultural practices, evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations.

Assessing the Culture and Climate for Quality Improvement in the Work Environment. AIR 1994 Annual Forum Paper.

ERIC Educational Resources Information Center

Cameron, Kim; And Others

This study attempted to develop a reliable and valid instrument for assessing work environment and continuous quality improvement efforts in the non-academic sectors of colleges and universities particularly those institutions who have adopted Total Quality Management programs. A model of a work environment for continuous quality improvement was…

Software cost/resource modeling: Software quality tradeoff measurement

NASA Technical Reports Server (NTRS)

Lawler, R. W.

1980-01-01

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

Studies on kinetics of water quality factors to establish water transparency model in Neijiang River, China.

PubMed

Li, Ronghui; Pan, Wei; Guo, Jinchuan; Pang, Yong; Wu, Jianqiang; Li, Yiping; Pan, Baozhu; Ji, Yong; Ding, Ling

2014-05-01

The basis for submerged plant restoration in surface water is to research the complicated dynamic mechanism of water transparency. In this paper, through the impact factor analysis of water transparency, the suspended sediment, dissolved organic matter, algae were determined as three main impactfactors for water transparency of Neijiang River in Eastern China. And the multiple regression equation of water transparency and sediment concentration, permanganate index, chlorophyll-a concentration was developed. Considering the complicated transport and transformation of suspended sediment, dissolved organic matter and algae, numerical model of them were developed respectively for simulating the dynamic process. Water transparency numerical model was finally developed by coupling the sediment, water quality, and algae model. These results showed that suspended sediment was a key factor influencing water transparency of Neijiang River, the influence of water quality indicated by chemical oxygen demand and algal concentration indicated by chlorophyll a were indeterminate when their concentrations were lower, the influence was more obvious when high concentrations are available, such three factors showed direct influence on water transparency.

The development of a model for predicting passenger acceptance of short-haul air transportation systems

NASA Technical Reports Server (NTRS)

Kuhlthau, A. R.; Jacobson, I. D.

1977-01-01

Meaningful criteria and methodology for assessing, particularly in the area of ride quality, the potential acceptability to the traveling public of present and future transportation systems were investigated. Ride quality was found to be one of the important variables affecting the decision of users of air transportation, and to be influenced by several environmental factors, especially motion, noise, pressure, temperature, and seating. Models were developed to quantify the relationship of subjective comfort to all of these parameters and then were exercised for a variety of situations. Passenger satisfaction was found to be strongly related to ride quality and was so modeled. A computer program was developed to assess the comfort and satisfaction levels of passengers on aircraft subjected to arbitrary flight profiles over arbitrary terrain. A model was deduced of the manner in which passengers integrate isolated segments of a flight to obtain an overall trip comfort rating. A method was established for assessing the influence of other links (e.g., access, terminal conditions) in the overall passenger trip.

Development and field validation of a regional, management-scale habitat model: A koala Phascolarctos cinereus case study.

PubMed

Law, Bradley; Caccamo, Gabriele; Roe, Paul; Truskinger, Anthony; Brassil, Traecey; Gonsalves, Leroy; McConville, Anna; Stanton, Matthew

2017-09-01

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional-scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently-collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2-km spatial filter and by modeling separately two subregions separated by the 500-m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground-truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows ( n  = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground-truth sites. Similarly, a site habitat quality index at ground-truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site-based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field-validated models of similar resolution would assist in guiding management of conservation-dependent species.

A Quality Model to Select Patients in Cupping Therapy Clinics: A New Tool for Ensuring Safety in Clinical Practice.

PubMed

Aboushanab, Tamer; AlSanad, Saud

2018-06-08

Cupping therapy is a popular treatment in various countries and regions, including Saudi Arabia. Cupping therapy is regulated in Saudi Arabia by the National Center for Complementary and Alternative Medicine (NCCAM), Ministry of Health. The authors recommend that this quality model for selecting patients in cupping clinics - first version (QMSPCC-1) - be used routinely as part of clinical practice and quality management in cupping clinics. The aim of the quality model is to ensure the safety of patients and to introduce and facilitate quality and auditing processes in cupping therapy clinics. Clinical evaluation of this tool is recommended. Continued development, re-evaluation and reassessment of this tool are important. Copyright © 2018. Published by Elsevier B.V.

A three-dimensional conceptual model of the water quality distribution in the Albuquerque Basin

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

Romero, D.

1995-12-31

It is possible to construct a conceptual model of the Albuquerque Basin`s geochemical characteristics and water quality distribution based on (1) the Hawley and Haase hydrogeological model, (2) water analyses from City of Albuquerque water wells, and (3) sound geological and chemical principles. Previous studies have characterized the water quality and geochemistry of the Albuquerque Basin from a two-dimensional perspective; however, to date, there has been no examination of the variation of water quality with depth within the Albuquerque Basin. The primary focus of this paper is to describe a first attempt at developing a conceptual understanding of the three-dimensionalmore » water quality distribution of the Albuquerque Basin based on the above three building blocks.« less

The Indirect Effects of Maternal Emotion Socialization on Friendship Quality in Middle Childhood

PubMed Central

Blair, Bethany L.; Perry, Nicole B.; O’Brien, Marion; Calkins, Susan D.; Keane, Susan P.; Shanahan, Lilly

2014-01-01

Emotion development processes have long been linked to social competence in early childhood but rarely have these associations been examined in middle childhood or with relational outcomes. Guided by theories of interpersonal relationships and emotion socialization, the current study was designed to fill these gaps by examining a longitudinal process model indirectly linking emotion development to friendship quality. Data were drawn from 336 children (179 girls, 65% White), their mothers, and their teachers across 3 time points spanning the ages of 5–10 years. A path analysis model was utilized to examine the way in which maternal emotion socialization indirectly affects children’s friendship quality. Results supported the hypothesized model in which maternal emotion socialization strategies used when children were age 5 were associated with changes in friendship quality from ages 7 to 10 via changes in children’s emotion regulation. Findings highlight the importance of emotional processes for relational outcomes in middle childhood. PMID:23795555

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.

Development of a regional ocean color algorithm using field- and satellite-derived datasets: Long Bay, South Carolina

NASA Astrophysics Data System (ADS)

Ryan, Kimberly Susan

Coastal and inland waters represent a diverse set of resources that support natural habitat and provide numerous ecosystem services to the human population. Conventional techniques to monitor water quality using in situ sensors and laboratory analysis of water samples can be very time- and cost-intensive. Alternatively, remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic and unique water quality parameters. However, bio and geo-optical models are required that relate the remotely sensed spectral data with color producing agents (CPAs) that define the water quality. These CPAs include chlorophyll-a, suspended sediments, and colored-dissolved organic matter. Developing these models may be challenging for coastal environments such as Long Bay, South Carolina, due to the presence of multiple optically interfering CPAs. In this work, a regionally tiered ocean color model was developed using band ratio techniques to specifically predict the variability of chlorophyll-a concentrations in the turbid Long Bay waters. This model produced higher accuracy results (r-squared = 0.62; RMSE = 0.87 micrograms per liter) compared to the existing models, which gave a highest r-squared value of 0.58 and RMSE = 0.99 micrograms per liter. To further enhance the retrievals of chlorophyll-a in these optically complex waters, a novel multivariate-based approach was developed using current generation hyperspectral data. This approach uses a partial least-squares regression model to identify wavelengths that are more sensitive to chlorophyll-a relative to other associated CPAs. This model was able to explain 80% of the observed chlorophyll-a variability in Long Bay with RMSE = 2.03 micrograms per liter. This approach capitalizes on the spectral advantage gained from hyperspectral sensors, thus providing a more robust predicting model. This enhanced mode of water quality monitoring in marine environments will provide insight to point-sources and problem areas that may contribute to a decline in water quality. Moreover, remote sensing applications such as this can be used as a tool for coastal and fisheries managers with regard to recreation, regulation, economic and public health purposes.

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

PubMed Central

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

2013-01-01

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

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.

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

PubMed

Liu, Mei; Lu, Jun

2014-09-01

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

Data collection and development of a hydrodynamic and temperature model to evaluate causeway modifications at the mouth of the Yakima River

NASA Astrophysics Data System (ADS)

Martinez Baquero, G. F.; Furnans, J.; Hudson, C.; Magan, C.

2012-12-01

Management decisions on rivers and associated habitats require sound tools to identify major drivers for spatial and temporal variations of temperature and related water quality variables. 3D hydrodynamic and water quality models are key components to abstract flow dynamics in complex river systems as they allow extrapolating available observations to ungaged locations and alternative scenarios. The data collection and model development are intended to support the Mid-Columbia Fisheries Enhancement Group in conjunction with the Benton Conservation District in efforts to understand how seasonal flow patterns in the Yakima and Columbia rivers interact with the Yakima delta geometry to cause the relatively high water temperatures previously observed west of Bateman Island. These high temperatures are suspected of limiting salmonid success in the area, possibly contributing to adjustments in migration patterns and increased predation. The Environmental Fluid Dynamics Code (EFDC) and Water Quality Analysis Simulation Program (WASP) are used to model flow patterns and enable simulations of temperature distributions and water quality parameters at the confluence. Model development is supported by a bathymetric campaign in 2011 to evaluate delta geometry and to construct the EFDC domain, a sonar river survey in 2012 to measure velocity profiles and to enable model calibration, and a continuous collection of temperature and dissolved oxygen records from Level Scout probes at key locations during last year to drive water quality simulations. The current model is able to reproduce main flow features observed at the confluence and is being prepared to integrate previous and current temperature observations. The final model is expected to evaluate scenarios for the removal or alteration of the Bateman Island Causeway. Alterations to the causeway that permit water passage to the south of Bateman Island are likely to dramatically alter the water flow patterns through the Yakima and Columbia River confluence, which in turn will alter water temperature distributions, sediment transport pathways, and salmonid migration routes.

Anxiety after completion of treatment for early-stage breast cancer: a systematic review to identify candidate predictors and evaluate multivariable model development.

PubMed

Harris, Jenny; Cornelius, Victoria; Ream, Emma; Cheevers, Katy; Armes, Jo

2017-07-01

The purpose of this review was to identify potential candidate predictors of anxiety in women with early-stage breast cancer (BC) after adjuvant treatments and evaluate methodological development of existing multivariable models to inform the future development of a predictive risk stratification model (PRSM). Databases (MEDLINE, Web of Science, CINAHL, CENTRAL and PsycINFO) were searched from inception to November 2015. Eligible studies were prospective, recruited women with stage 0-3 BC, used a validated anxiety outcome ≥3 months post-treatment completion and used multivariable prediction models. Internationally accepted quality standards were used to assess predictive risk of bias and strength of evidence. Seven studies were identified: five were observational cohorts and two secondary analyses of RCTs. Variability of measurement and selective reporting precluded meta-analysis. Twenty-one candidate predictors were identified in total. Younger age and previous mental health problems were identified as risk factors in ≥3 studies. Clinical variables (e.g. treatment, tumour grade) were not identified as predictors in any studies. No studies adhered to all quality standards. Pre-existing vulnerability to mental health problems and younger age increased the risk of anxiety after completion of treatment for BC survivors, but there was no evidence that chemotherapy was a predictor. Multiple predictors were identified but many lacked reproducibility or were not measured across studies, and inadequate reporting did not allow full evaluation of the multivariable models. The use of quality standards in the development of PRSM within supportive cancer care would improve model quality and performance, thereby allowing professionals to better target support for patients.

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

PubMed

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

2009-10-01

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

Integrated planning for regional development planning and water resources management under uncertainty: A case study of Xining, China

NASA Astrophysics Data System (ADS)

Fu, Z. H.; Zhao, H. J.; Wang, H.; Lu, W. T.; Wang, J.; Guo, H. C.

2017-11-01

Economic restructuring, water resources management, population planning and environmental protection are subjects to inner uncertainties of a compound system with objectives which are competitive alternatives. Optimization model and water quality model are usually used to solve problems in a certain aspect. To overcome the uncertainty and coupling in reginal planning management, an interval fuzzy program combined with water quality model for regional planning and management has been developed to obtain the absolutely ;optimal; solution in this study. The model is a hybrid methodology of interval parameter programming (IPP), fuzzy programing (FP), and a general one-dimensional water quality model. The method extends on the traditional interval parameter fuzzy programming method by integrating water quality model into the optimization framework. Meanwhile, as an abstract concept, water resources carrying capacity has been transformed into specific and calculable index. Besides, unlike many of the past studies about water resource management, population as a significant factor has been considered. The results suggested that the methodology was applicable for reflecting the complexities of the regional planning and management systems within the planning period. The government policy makers could establish effective industrial structure, water resources utilization patterns and population planning, and to better understand the tradeoffs among economic, water resources, population and environmental objectives.

A Hemispheric Version of the Community Multiscale Air Quality (CMAQ) Modeling System

EPA Science Inventory

This invited presentation will be given at the 4th Biannual Western Modeling Workshop in the Plenary session on Global model development, evaluation, and new source attribution tools. We describe the development and application of the hemispheric version of the CMAQ to examine th...

Development and evaluation of a physics-based windblown dust emission scheme implemented in the CMAQ modeling system

EPA Science Inventory

A new windblown dust emission treatment was incorporated in the Community Multiscale Air Quality (CMAQ) modeling system. This new model treatment has been built upon previously developed physics-based parameterization schemes from the literature. A distinct and novel feature of t...

A probabilistic assessment of health risks associated with short-term exposure to tropospheric ozone

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

Whitfield, R.G; Biller, W.F.; Jusko, M.J.

1996-06-01

The work described in this report is part of a larger risk assessment sponsored by the U.S. Environmental Protection Agency. Earlier efforts developed exposure-response relationships for acute health effects among populations engaged in heavy exertion. Those efforts also developed a probabilistic national ambient air quality standards exposure model and a general methodology for integrating probabilistic exposure-response relation- ships and exposure estimates to calculate overall risk results. Recently published data make it possible to model additional health endpoints (for exposure at moderate exertion), including hospital admissions. New air quality and exposure estimates for alternative national ambient air quality standards for ozonemore » are combined with exposure-response models to produce the risk results for hospital admissions and acute health effects. Sample results explain the methodology and introduce risk output formats.« less

Exploring the Quality of Teacher-Child Interactions: The Soka Discourse in Practice

ERIC Educational Resources Information Center

Ikegami, Kiiko; Rivalland, Corine

2016-01-01

Numerous research has shown that quality of interactions between early childhood teachers and children contribute significantly to children's holistic development. Most literature on this topic comes from developed/Western countries and little is known about the kind of interactions occurring within the Soka kindergarten model. This article, based…

Quantitative Procedures for the Assessment of Quality in Higher Education Institutions.

ERIC Educational Resources Information Center

Moran, Tom; Rowse, Glenwood

The development of procedures designed to provide quantitative assessments of quality in higher education institutions are reviewed. These procedures employ a systems framework and utilize quantitative data to compare institutions or programs of similar types with one another. Three major elements essential in the development of models focusing on…

Professional Learning: A Collaborative Model for Online Teaching and Development

ERIC Educational Resources Information Center

Bowser, Audrey; Davis, Kimberley; Singleton, Jacques; Small, Topeka

2017-01-01

This article examined a unique collaborative initiative between a team of graduate level faculty to improve the quality of course development and delivery using a collaborative review process. The collaborative review of teaching has become a widely accepted means for assuring quality distance learning coursework and for the purpose of evaluating…

Social Work, Pastoral Care and Resilience

ERIC Educational Resources Information Center

Considine, Tom; Hollingdale, Paul; Neville, Ruth

2015-01-01

This paper briefly examines the growing interest in developing resilience in the social work curricula as it is seen as a crucial quality necessary to cope with the increasing demands of the profession. The recent research into developing resilience is dominated by a psychological model which emphasises personal qualities. It runs the risk of…

Assessing U.S. Public School Quality: The Advantages of Combining Internal "Consumer Ratings" with External NCLB Ratings

ERIC Educational Resources Information Center

Price, Heather E.

2016-01-01

The school quality assessment process under No Child Left Behind (NCLB) is criticized for oversimplifying and overemphasizing standardized test results and unfairly targeting diverse, urban schools. There has been much development in alternative test score evaluations, especially value-added models. These developments have tilted the public…

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

PubMed

Downey, Brandon; Schmitt, John; Beller, Justin; Russell, Brian; Quach, Anthony; Hermann, Elizabeth; Lyon, David; Breit, Jeffrey

2017-11-01

As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption of model predictive control in biopharmaceutical cell culture processes has been hampered, however, in part due to the large amount of data and expertise required to make a predictive model of controlled CQAs, a requirement for model predictive control. Here we developed a highly automated, perfusion apparatus to systematically and efficiently generate predictive models using application of system identification approaches. We successfully created a predictive model of %galactosylation using data obtained by manipulating galactose concentration in the perfusion apparatus in serialized step change experiments. We then demonstrated the use of the model in a model predictive controller in a simulated control scenario to successfully achieve a %galactosylation set point in a simulated fed-batch culture. The automated model identification approach demonstrated here can potentially be generalized to many CQAs, and could be a more efficient, faster, and highly automated alternative to batch experiments for developing predictive models in cell culture processes, and allow the wider adoption of model predictive control in biopharmaceutical processes. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1647-1661, 2017. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers.

Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality.

PubMed

Islam, M M Majedul; Iqbal, Muhammad Shahid; Leemans, Rik; Hofstra, Nynke

2018-03-01

Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.

Candidate Predictors of Health-Related Quality of Life of Colorectal Cancer Survivors: A Systematic Review

PubMed Central

van der Linden, Bernadette W.A.; Winkels, Renate M.; van Duijnhoven, Fränzel J.; Mols, Floortje; van Roekel, Eline H.; Kampman, Ellen; Beijer, Sandra; Weijenberg, Matty P.

2016-01-01

The population of colorectal cancer (CRC) survivors is growing and many survivors experience deteriorated health-related quality of life (HRQoL) in both early and late post-treatment phases. Identification of CRC survivors at risk for HRQoL deterioration can be improved by using prediction models. However, such models are currently not available for oncology practice. As a starting point for developing prediction models of HRQoL for CRC survivors, a comprehensive overview of potential candidate HRQoL predictors is necessary. Therefore, a systematic literature review was conducted to identify candidate predictors of HRQoL of CRC survivors. Original research articles on associations of biopsychosocial factors with HRQoL of CRC survivors were searched in PubMed, Embase, and Google Scholar. Two independent reviewers assessed eligibility and selected articles for inclusion (N = 53). Strength of evidence for candidate HRQoL predictors was graded according to predefined methodological criteria. The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) was used to develop a biopsychosocial framework in which identified candidate HRQoL predictors were mapped across the main domains of the ICF: health condition, body structures and functions, activities, participation, and personal and environmental factors. The developed biopsychosocial ICF framework serves as a basis for selecting candidate HRQoL predictors, thereby providing conceptual guidance for developing comprehensive, evidence-based prediction models of HRQoL for CRC survivors. Such models are useful in clinical oncology practice to aid in identifying individual CRC survivors at risk for HRQoL deterioration and could also provide potential targets for a biopsychosocial intervention aimed at safeguarding the HRQoL of at-risk individuals. Implications for Practice: More and more people now survive a diagnosis of colorectal cancer. The quality of life of these cancer survivors is threatened by health problems persisting for years after diagnosis and treatment. Early identification of survivors at risk of experiencing low quality of life in the future is thus important for taking preventive measures. Clinical prediction models are tools that can help oncologists identify at-risk individuals. However, such models are currently not available for clinical oncology practice. This systematic review outlines candidate predictors of low quality of life of colorectal cancer survivors, providing a firm conceptual basis for developing prediction models. PMID:26911406

Methods for estimating monthly mean concentrations of selected water-quality constituents for stream sites in the Red River of the North basin, North Dakota and Minnesota

USGS Publications Warehouse

Guenthner, R.S.

1991-01-01

Future development of the Garrison Diversion Unit may divert water from the Missouri River into the Sheyenne River and the Red River of the North for municipal and industrial use. The U.S. Bureau of Reclamation's Canals, Rivers, and Reservoirs Salinity Accounting Procedures model can be used to predict the effect various operating plans could have on water quality in the Sheyenne River and the Red River of the North. The model uses, as Input, monthly means of streamflow and selected water-quality constituents for a 54-year period at 28 nodes on the Sheyenne River and the Red River of the North. This report provides methods for estimating monthly mean concentrations of selected water-quality constituents that can be used for input to and calibration of the salinity model.Mater-quality data for 32 gaging stations can be used to define selected water-quality characteristics at the 28 model nodes. Materquality data were retrieved from the U.S. Geological Survey's National Mater Data Storage and Retrieval System data base and statistical summaries were prepared. The frequency of water-quality data collection at the gaging stations is inadequate to define monthly mean concentrations of the individual water-quality constituents for all months for the 54-year period; therefore, methods for estimating monthly mean concentrations were developed. Relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and streamflow were developed as the primary method to estimate monthly mean concentrations. Relations between specific conductance and streamflow and relations between selected water-quality constituents [dissolved solids, hardness (as CaCO3), sodium, sulfate, and chloride] and specific conductance were developed so that a cascaded-regression relation could be developed as a second method of estimating monthly mean concentrations and, thus, utilize a large specific-conductance data base. Information about the quantity and the quality of ground water discharging to the Sheyenne River is needed for model input for reaches of the river where ground water accounts for a substantial part of streamflow during periods of low flow. Ground-water discharge was identified for two reaches of the Sheyenne River. Ground-water discharge to the Sheyenne River in the vicinity of Warwick, N.Dak., was about 14.8 cubic feet per second and the estimated dissolved-solids concentration was about 441 milligrams per liter during October 15 and 16, 1986. Ground-water discharge to the Sheyenne River in a reach between Lisbon and Kindred, N.Dak., ranged from an average of 25.3 cubic feet per second during September 13 to November 19, 1963, to about 45.0 cubic feet per second during October 21 and 22, 1986. Dissolved-solids concentration was estimated at about 442 milligrams per liter during October 21 and 22, 1986.

Impacts of crop growth dynamics on soil quality at the regional scale

NASA Astrophysics Data System (ADS)

Gobin, Anne

2014-05-01

Agricultural land use and in particular crop growth dynamics can greatly affect soil quality. Both the amount of soil lost from erosion by water and soil organic matter are key indicators for soil quality. The aim was to develop a modelling framework for quantifying the impacts of crop growth dynamics on soil quality at the regional scale with test case Flanders. A framework for modelling the impacts of crop growth on soil erosion and soil organic matter was developed by coupling the dynamic crop cover model REGCROP (Gobin, 2010) to the PESERA soil erosion model (Kirkby et al., 2009) and to the RothC carbon model (Coleman and Jenkinson, 1999). All three models are process-based, spatially distributed and intended as a regional diagnostic tool. A geo-database was constructed covering 10 years of crop rotation in Flanders using the IACS parcel registration (Integrated Administration and Control System). Crop allometric models were developed from variety trials to calculate crop residues for common crops in Flanders and subsequently derive stable organic matter fluxes to the soil. Results indicate that crop growth dynamics and crop rotations influence soil quality for a very large percentage. soil erosion mainly occurs in the southern part of Flanders, where silty to loamy soils and a hilly topography are responsible for soil loss rates of up to 40 t/ha. Parcels under maize, sugar beet and potatoes are most vulnerable to soil erosion. Crop residues of grain maize and winter wheat followed by catch crops contribute most to the total carbon sequestered in agricultural soils. For the same rotations carbon sequestration is highest on clay soils and lowest on sandy soils. This implies that agricultural policies that impact on agricultural land management influence soil quality for a large percentage. The coupled REGCROP-PESERA-ROTHC model allows for quantifying the impact of seasonal and year-to-year crop growth dynamics on soil quality. When coupled to a multi-annual crop rotation database both spatial and temporal analysis becomes possible and allows for decision support at both farm and regional level. The framework is therefore suited for further scenario analysis and impact assessment. The research is funded by the Belgian Science Policy Organisation (Belspo) under contract nr SD/RI/03A.

[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 that the first derivatives or the wavelet coefficients of hyperspectral reflectance in visible and near-infrared regions can be used for pasture quality estimation, and that it will provide a basis for real-time prediction of pasture quality using remote sensing techniques.

Use of ocean color scanner data in water quality mapping

NASA Technical Reports Server (NTRS)

Khorram, S.

1981-01-01

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

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.

Modeling of Micro Deval abrasion loss based on some rock properties

NASA Astrophysics Data System (ADS)

Capik, Mehmet; Yilmaz, Ali Osman

2017-10-01

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

Mentoring Professors: A Model for Developing Quality Online Instructors and Courses in Higher Education

ERIC Educational Resources Information Center

Barczyk, Casimir; Buckenmeyer, Janet; Feldman, Lori

2010-01-01

This article presents a four-stage model for mentoring faculty in higher education to deliver high quality online instruction. It provides a timeline that shows the stages of program implementation. Known as the Distance Education Mentoring Program, its major outcomes include certified instructors, student achievement, and the attainment of a…

Growing high quality hardwoods: Plantation trials of mixed hardwood species in Tennessee

Treesearch

Christopher M. Oswalt; Wayne K. Clatterbuck

2011-01-01

Hardwood plantations are becoming increasingly important in the United States. To date, many foresters have relied on a conifer plantation model as the basis of establishing and managing hardwood plantations. The monospecific approach suggested by the conifer plantation model does not appear to provide for the development of quality hardwood logs similar to those found...

A Theory of Information Genetics: How Four Subforces Generate Information and the Implications for Total Quality Knowledge Management.

ERIC Educational Resources Information Center

Tsai, Bor-sheng

2002-01-01

Proposes a model called information genetics to elaborate on the origin of information generating. Explains conceptual and data models; and describes a software program that was developed for citation data mining, infomapping, and information repackaging for total quality knowledge management in Web representation. (Contains 112 references.)…

Forest growth and timber quality: crown models and simulation methods for sustainable forest management

Treesearch

Dennis P. Dykstra; Robert A. Monserud

2009-01-01

The purpose of the international conference from which these proceedings are drawn was to explore relationships between forest management activities and timber quality. Sessions were organized to explore models and simulation methodologies that contribute to an understanding of tree development over time and the ways that management and harvesting activities can...

National Models for Continuing Professional Development: The Challenges of Twenty-First-Century Knowledge Management

ERIC Educational Resources Information Center

Leask, Marilyn; Younie, Sarah

2013-01-01

If teacher quality is the most critical factor in improving educational outcomes, then why is so little attention drawn to the knowledge and evidence base available to support teachers in improving the quality of their professional knowledge? This paper draws together findings from a range of sources to propose national models for continuing…

Modeling Reader and Text Interactions during Narrative Comprehension: A Test of the Lexical Quality Hypothesis

ERIC Educational Resources Information Center

Hamilton, Stephen T.; Freed, Erin M.; Long, Debra L.

2013-01-01

The goal of this study was to examine predictions derived from the Lexical Quality Hypothesis regarding relations among word decoding, working-memory capacity, and the ability to integrate new concepts into a developing discourse representation. Hierarchical Linear Modeling was used to quantify the effects of three text properties (length,…

A framework for expanding aqueous chemistry in the Community Multiscale Air Quality (CMAQ) model version 5.1

EPA Science Inventory

This paper describes the development and implementation of an extendable aqueous-phase chemistry option (AQCHEM − KMT(I)) for the Community Multiscale Air Quality (CMAQ) modeling system, version 5.1. Here, the Kinetic PreProcessor (KPP), version 2.2.3, is used to generate a Rosen...

A Model of Quality of College Life (QCL) of Students in Korea

ERIC Educational Resources Information Center

Yu, Grace (Byung-Hee); Lee, Dong-Jin

2008-01-01

This study develops and tests a model of quality of college life (QCL) of students in Korea. In this study, QCL of students is conceptualized in terms of needs satisfaction and affect balance. It has been hypothesized that satisfaction with education services, administrative services, and facilities have a significant impact on QCL, which in turn…

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

EPA Science Inventory

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

Homework Works If Homework Quality Is High: Using Multilevel Modeling to Predict the Development of Achievement in Mathematics

ERIC Educational Resources Information Center

Dettmers, Swantje; Trautwein, Ulrich; Ludtke, Oliver; Kunter, Mareike; Baumert, Jurgen

2010-01-01

The present study examined the associations of 2 indicators of homework quality (homework selection and homework challenge) with homework motivation, homework behavior, and mathematics achievement. Multilevel modeling was used to analyze longitudinal data from a representative national sample of 3,483 students in Grades 9 and 10; homework effects…

Who will have Sustainable Employment After a Back Injury? The Development of a Clinical Prediction Model in a Cohort of Injured Workers.

PubMed

Shearer, Heather M; Côté, Pierre; Boyle, Eleanor; Hayden, Jill A; Frank, John; Johnson, William G

2017-09-01

Purpose Our objective was to develop a clinical prediction model to identify workers with sustainable employment following an episode of work-related low back pain (LBP). Methods We used data from a cohort study of injured workers with incident LBP claims in the USA to predict employment patterns 1 and 6 months following a workers' compensation claim. We developed three sequential models to determine the contribution of three domains of variables: (1) basic demographic/clinical variables; (2) health-related variables; and (3) work-related factors. Multivariable logistic regression was used to develop the predictive models. We constructed receiver operator curves and used the c-index to measure predictive accuracy. Results Seventy-nine percent and 77 % of workers had sustainable employment at 1 and 6 months, respectively. Sustainable employment at 1 month was predicted by initial back pain intensity, mental health-related quality of life, claim litigation and employer type (c-index = 0.77). At 6 months, sustainable employment was predicted by physical and mental health-related quality of life, claim litigation and employer type (c-index = 0.77). Adding health-related and work-related variables to models improved predictive accuracy by 8.5 and 10 % at 1 and 6 months respectively. Conclusion We developed clinically-relevant models to predict sustainable employment in injured workers who made a workers' compensation claim for LBP. Inquiring about back pain intensity, physical and mental health-related quality of life, claim litigation and employer type may be beneficial in developing programs of care. Our models need to be validated in other populations.

Development of Source-Receptor matrix over South Korea in support of GAINS-Korea model

NASA Astrophysics Data System (ADS)

Choi, K. C.; Woo, J. H.; Kim, H. K.; Lee, Y. M.; Kim, Y.; Heyes, C.; Lee, J. B.; Song, C. K.; Han, J.

2014-12-01

A comprehensive and combined analysis of air pollution and climate change could reveal important synergies of emission control measures, which could be of high policy relevance. IIASA's GAINS model (The Greenhouse gas - Air pollution Interactions and Synergies) has been developed as a tool to identify emission control strategies that achieve given targets on air quality and greenhouse gas emissions at least costs. The GAINS-Korea Model, which is being jointly developed by Konkuk University and IIASA, should play an important role in understanding the impact of air quality improvements across the regions in Korea. Source-Receptor relationships (S-R) is an useful methodology in air pollution studies to determine the areas of origin of chemical compounds at receptor point, and thus be able to target actions to reduce pollutions. The GAINS model can assess the impact of emission reductions of sources on air quality in receptor regions based on S-R matrix, derived from chemical transport model. In order to develop S-R matrix for GAINS-Korea, the CAMx model with PSAT/OSAT tools was applied in this study. The coarse domain covers East Asia, and a nesting domain as main research area was used for Korea peninsula. To evaluate of S-R relationships, a modeling domain is divided into sixteen regions over South Korea with three outside of S. Korea countries (China, N. Korea and Japan) for estimating transboundary contributions. The results of our analysis will be presented at the conference.

Designing and implementing a trust-wide quality assurance programme.

PubMed

Coope, Sally-Ann

2018-04-02

Derbyshire Community Health Services (DCHS) NHS Foundation Trust provides a wide range of community-based health services. After the Care Quality Commission (CQC) found gaps in the trust's assurance process, its board decided to develop a method of continuous quality improvements that could be used as a basis for the trust's quality assurance system. The trust adapted and built on an acute model so it was suitable for community services. The final assurance system, Quality Always, has four elements: the clinical assessment and accreditation scheme; leadership development; 'champions' within clinical teams to support and promote the scheme; and dashboards to record and monitor progress. A system to recognise and reward achievement was essential for success. Quality Always has resulted in better care quality, an improved CQC rating, a sense of achievement among staff, the development of support networks, learning (especially among support staff) and good practice being shared.

Spirituality in Counseling: A Faith Development Perspective

ERIC Educational Resources Information Center

Parker, Stephen

2011-01-01

This article describes the use of Fowler's (1981) faith development theory (FDT) in counseling. FDT is a stage model of spiritual and religious development that allows counselors to identify both adaptive qualities and potential encumbrances in spiritual or religious expression. FDT offers a nonsectarian model of spiritual growth that permits…

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

Bell, L.; Castaldi, A.; Jones, C.

The ultimate goal of the project is to develop procedures, techniques, data and other information that will aid in the design of cost effective and energy efficient drying processes that produce high quality foods. This objective has been sought by performing studies to determine the pertinent properties of food products, by developing models to describe the fundamental phenomena of food drying and by testing the models at laboratory scale. Finally, this information is used to develop recommendations and strategies for improved dryer design and control. This volume emphasizes a detailed literature review and several extensive experimental studies. Since the basicmore » principle of food dehydration is the removal of water from food, the process of removing water causes quality changes which can be categorized as physical, chemical, and nutritional. These changes often have adverse effects on the quality of the resulting dehydrated food. In this work, the types of physical and chemical changes common in food drying and the important factors for them were reviewed. Pertinent kinetic models and kinetic data reported in literature were also collected and compiled as the results of review study. The overall objectives of this study were to identify major quality change in foods caused by drying process and to get the knowledge of the relationship between the quality change and factors known to affect them. The quality parameters reviewed included: browning, lipid oxidation, color loss, shrinkage, solubility, texture, aroma and flavor, vitamin and protein loss and microbiological concerns. 54 refs., 74 figs., 49 tabs.« less

Officer Career Development: A Review of the Civilian and Military Research Literature on Turnover and Retention

DTIC Science & Technology

1991-09-01

balance of costs associated with turnover and the costs associated with retaining employees. Under this approach, the optimal level of aggregate turnover...behavior psychiatric technicians psychological attachment push/pull models quality of life quality of service quality of worklife questionnaires race

ISO 9000 Quality Systems: Application to Higher Education.

ERIC Educational Resources Information Center

Clery, Roger G.

This paper describes and explains the 20 elements of the International Organization for Standards 9000 (ISO 9000) series, a model for quality assurance in the business processes of design/development, production, installation and servicing. The standards were designed in 1987 to provide a common denominator for business quality particularly to…

Helicopter mathematical models and control law development for handling qualities research

NASA Technical Reports Server (NTRS)

Chen, Robert T. N.; Lebacqz, J. Victor; Aiken, Edwin W.; Tischler, Mark B.

1988-01-01

Progress made in joint NASA/Army research concerning rotorcraft flight-dynamics modeling, design methodologies for rotorcraft flight-control laws, and rotorcraft parameter identification is reviewed. Research into these interactive disciplines is needed to develop the analytical tools necessary to conduct flying qualities investigations using both the ground-based and in-flight simulators, and to permit an efficient means of performing flight test evaluation of rotorcraft flying qualities for specification compliance. The need for the research is particularly acute for rotorcraft because of their mathematical complexity, high order dynamic characteristics, and demanding mission requirements. The research in rotorcraft flight-dynamics modeling is pursued along two general directions: generic nonlinear models and nonlinear models for specific rotorcraft. In addition, linear models are generated that extend their utilization from 1-g flight to high-g maneuvers and expand their frequency range of validity for the design analysis of high-gain flight control systems. A variety of methods ranging from classical frequency-domain approaches to modern time-domain control methodology that are used in the design of rotorcraft flight control laws is reviewed. Also reviewed is a study conducted to investigate the design details associated with high-gain, digital flight control systems for combat rotorcraft. Parameter identification techniques developed for rotorcraft applications are reviewed.

Client satisfaction with reproductive health-care quality: integrating business approaches to modeling and measurement.

PubMed

Alden, Dana L; Do, Mai Hoa; Bhawuk, Dharm

2004-12-01

Health-care managers are increasingly interested in client perceptions of clinic service quality and satisfaction. While tremendous progress has occurred, additional perspectives on the conceptualization, modeling and measurement of these constructs may further assist health-care managers seeking to provide high-quality care. To that end, this study draws on theories from business and health to develop an integrated model featuring antecedents to and consequences of reproductive health-care client satisfaction. In addition to developing a new model, this study contributes by testing how well Western-based theories of client satisfaction hold in a developing, Asian country. Applied to urban, reproductive health clinic users in Hanoi, Vietnam, test results suggest that hypothesized antecedents such as pre-visit expectations, perceived clinic performance and how much performance exceeds expectations impact client satisfaction. However, the relative importance of these predictors appears to vary depending on a client's level of service-related experience. Finally, higher levels of client satisfaction are positively related to future clinic use intentions. This study demonstrates the value of: (1) incorporating theoretical perspectives from multiple disciplines to model processes underlying health-care satisfaction and (2) field testing those models before implementation. It also furthers research designed to provide health-care managers with actionable measures of the complex processes related to their clients' satisfaction.

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 of appropriately upscaling advection-dispersion and reactions at the basin scale (10^2 km). A road map for research and development in groundwater quality management modeling and its application toward securing future groundwater resources will be discussed.

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 microbial physiology and enzyme traits can be incorporated in a model based on a continuous representation of the organic matter and evaluate how it can improve our ability to predict soil C cycling. To do so, we analyse the properties of the model by implementing different scenarii and test the sensitivity of its parameters. Agren, G. I., & Bosatta, E. (1998). Theoretical ecosystem ecology: understanding element cycles. Cambridge University Press.

Key Issues for Seamless Integrated Chemistry–Meteorology Modeling

EPA Science Inventory

Online coupled meteorology–atmospheric chemistry models have greatly evolved in recent years. Although mainly developed by the air quality modeling community, these integrated models are also of interest for numerical weather prediction and climate modeling, as they can con...

The Impact of a Potential Shale Gas Development in Germany and the United Kingdom on Local and Regional Air Quality

NASA Astrophysics Data System (ADS)

Weger, L.; Lupascu, A.; Cremonese, L.; Butler, T. M.

2017-12-01

Numerous countries in Europe that possess domestic shale gas reserves are considering exploiting this unconventional gas resource as part of their energy transition agenda. While natural gas generates less CO2 emissions upon combustion compared to coal or oil, making it attractive as a bridge in the transition from fossil fuels to renewables, production of shale gas leads to emissions of CH4 and air pollutants such as NOx, VOCs and PM. These gases in turn influence the climate as well as air quality. In this study, we investigate the impact of a potential shale gas development in Germany and the United Kingdom on local and regional air quality. This work builds on our previous study in which we constructed emissions scenarios based on shale gas utilization in these counties. In order to explore the influence of shale gas production on air quality, we investigate emissions predicted from our shale gas scenarios with the Weather Research and Forecasting model with chemistry (WRF-Chem) model. In order to do this, we first design a model set-up over Europe and evaluate its performance for the meteorological and chemical parameters. Subsequently we add shale gas emissions fluxes based on the scenarios over the area of the grid in which the shale gas activities are predicted to occur. Finally, we model these emissions and analyze the impact on air quality on both a local and regional scale. The aims of this work are to predict the range of adverse effects on air quality, highlight the importance of emissions control strategies in reducing air pollution, to promote further discussion, and to provide policy makers with information for decision making on a potential shale gas development in the two study countries.

Urbanization and watershed sustainability: Collaborative simulation modeling of future development states

NASA Astrophysics Data System (ADS)

Randhir, Timothy O.; Raposa, Sarah

2014-11-01

Urbanization has a significant impact on water resources and requires a watershed-based approach to evaluate impacts of land use and urban development on watershed processes. This study uses a simulation with urban policy scenarios to model and strategize transferable recommendations for municipalities and cities to guide urban decisions using watershed ecohydrologic principles. The watershed simulation model is used to evaluation intensive (policy in existing built regions) and extensive (policy outside existing build regions) urban development scenarios with and without implementation of Best Management practices (BMPs). Water quantity and quality changes are simulated to assess effectiveness of five urban development scenarios. It is observed that optimal combination of intensive and extensive strategies can be used to sustain urban ecosystems. BMPs are found critical to reduce storm water and water quality impacts on urban development. Conservation zoning and incentives for voluntary adoption of BMPs can be used in sustaining urbanizing watersheds.

Lesjes van de Nederlanders: Little Lessons from the Dutch to Promote Educational Quality. AIR 1995 Annual Forum Paper.

ERIC Educational Resources Information Center

Palmer, Barbara H.

This study explored quality assessment and accountability in Dutch university education using a case study approach. The Dutch national system of quality assurance is described, and developments since the mid-1980s are traced. The university case studies illustrate models which are being employed to implement the quality assurance system including…

Development and evaluation of the microbial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model

NASA Astrophysics Data System (ADS)

Hong, Eun-Mi; Park, Yongeun; Muirhead, Richard; Pachepsky, Yakov

2017-04-01

Pathogenic microorganisms in recreational and irrigation waters remain the subject of concern. Water quality models are used to estimate microbial quality of water sources, to evaluate microbial contamination-related risks, to guide the microbial water quality monitoring, and to evaluate the effect of agricultural management on the microbial water quality. The Agricultural Policy/Environmental eXtender (APEX) is the watershed-scale water quality model that includes highly detailed representation of agricultural management. The APEX currently does not have microbial fate and transport simulation capabilities. The objective of this work was to develop the first APEX microbial fate and transport module that could use the APEX conceptual model of manure removal together with recently introduced conceptualizations of the in-stream microbial fate and transport. The module utilizes manure erosion rates found in the APEX. The total number of removed bacteria was set to the concentrations of bacteria in soil-manure mixing layer and eroded manure amount. Bacteria survival in soil-manure mixing layer was simulated with the two-stage survival model. Individual survival patterns were simulated for each manure application date. Simulated in-stream microbial fate and transport processes included the reach-scale passive release of bacteria with resuspended bottom sediment during high flow events, the transport of bacteria from bottom sediment due to the hyporheic exchange during low flow periods, the deposition with settling sediment, and the two-stage survival. Default parameter values were available from recently published databases. The APEX model with the newly developed microbial fate and transport module was applied to simulate seven years of monitoring data for the Toenepi watershed in New Zealand. The stream network of the watershed ran through grazing lands with the daily bovine waste deposition. Based on calibration and testing results, the APEX with the microbe module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water under various agricultural practices (grazing, cropping, and manure application), evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations. Future development should include modeling contributions of wildlife, manure weathering, and weather effects on manure-borne microorganism survival and release.

Understanding organisational development, sustainability, and diffusion of innovations within hospitals participating in a multilevel quality collaborative.

PubMed

Dückers, Michel La; Wagner, Cordula; Vos, Leti; Groenewegen, Peter P

2011-03-09

Between 2004 and 2008, 24 Dutch hospitals participated in a two-year multilevel quality collaborative (MQC) comprised of (a) a leadership programme for hospital executives, (b) six quality-improvement collaboratives (QICs) for healthcare professionals and other staff, and (c) an internal programme organisation to help senior management monitor and coordinate team progress. The MQC aimed to stimulate the development of quality-management systems and the spread of methods to improve patient safety and logistics. The objective of this study is to describe how the first group of eight MQC hospitals sustained and disseminated improvements made and the quality methods used. The approach followed by the hospitals was described using interview and questionnaire data gathered from eight programme coordinators. MQC hospitals followed a systematic strategy of diffusion and sustainability. Hospital quality-management systems are further developed according to a model linking plan-do-study-act cycles at the unit and hospital level. The model involves quality norms based on realised successes, performance agreements with unit heads, organisational support, monitoring, and quarterly accountability reports. It is concluded from this study that the MQC contributed to organisational development and dissemination within participating hospitals. Organisational learning effects were demonstrated. System changes affect the context factors in the theory of organisational readiness: organisational culture, policies and procedures, past experience, organisational resources, and organisational structure. Programme coordinator responses indicate that these factors are utilised to manage spread and sustainability. Further research is needed to assess long-term effects.

A web tool for STORET/WQX water quality data retrieval and Best Management Practice scenario suggestion.

PubMed

Park, Youn Shik; Engel, Bernie A; Kim, Jonggun; Theller, Larry; Chaubey, Indrajeet; Merwade, Venkatesh; Lim, Kyoung Jae

2015-03-01

Total Maximum Daily Load is a water quality standard to regulate water quality of streams, rivers and lakes. A wide range of approaches are used currently to develop TMDLs for impaired streams and rivers. Flow and load duration curves (FDC and LDC) have been used in many states to evaluate the relationship between flow and pollutant loading along with other models and approaches. A web-based LDC Tool was developed to facilitate development of FDC and LDC as well as to support other hydrologic analyses. In this study, the FDC and LDC tool was enhanced to allow collection of water quality data via the web and to assist in establishing cost-effective Best Management Practice (BMP) implementations. The enhanced web-based tool provides use of water quality data not only from the US Geological Survey but also from the Water Quality Portal for the U.S. via web access. Moreover, the web-based tool identifies required pollutant reductions to meet standard loads and suggests a BMP scenario based on ability of BMPs to reduce pollutant loads, BMP establishment and maintenance costs. In the study, flow and water quality data were collected via web access to develop LDC and to identify the required reduction. The suggested BMP scenario from the web-based tool was evaluated using the EPA Spreadsheet Tool for the Estimation of Pollutant Load model to attain the required pollutant reduction at least cost. Copyright © 2014 Elsevier Ltd. All rights reserved.

A changing climate: impacts on human exposures to O3 using ...

EPA Pesticide Factsheets

Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposures due to these impacts was developed by linking climate, air quality, land-use, and human exposure models. This methodology was then applied to characterize changes in predicted human exposures to O3 under multiple future scenarios. Regional climate projections for the U.S. were developed by downscaling global circulation model (GCM) scenarios for three of the Intergovernmental Panel on Climate Change’s (IPCC’s) Representative Concentration Pathways (RCPs) using the Weather Research and Forecasting (WRF) model. The regional climate results were in turn used to generate air quality (concentration) projections using the Community Multiscale Air Quality (CMAQ) model. For each of the climate change scenarios, future U.S. census-tract level population distributions from the Integrated Climate and Land Use Scenarios (ICLUS) model for four future scenarios based on the IPCC’s Special Report on Emissions Scenarios (SRES) storylines were used. These climate, air quality, and population projections were used as inputs to EPA’s Air Pollutants Exposure (APEX) model for 12 U.S. cities. Probability density functions show changes in the population distribution of 8 h maximum daily O3 exposur

A User-Friendly Model for Spray Drying to Aid Pharmaceutical Product Development

PubMed Central

Grasmeijer, Niels; de Waard, Hans; Hinrichs, Wouter L. J.; Frijlink, Henderik W.

2013-01-01

The aim of this study was to develop a user-friendly model for spray drying that can aid in the development of a pharmaceutical product, by shifting from a trial-and-error towards a quality-by-design approach. To achieve this, a spray dryer model was developed in commercial and open source spreadsheet software. The output of the model was first fitted to the experimental output of a Büchi B-290 spray dryer and subsequently validated. The predicted outlet temperatures of the spray dryer model matched the experimental values very well over the entire range of spray dryer settings that were tested. Finally, the model was applied to produce glassy sugars by spray drying, an often used excipient in formulations of biopharmaceuticals. For the production of glassy sugars, the model was extended to predict the relative humidity at the outlet, which is not measured in the spray dryer by default. This extended model was then successfully used to predict whether specific settings were suitable for producing glassy trehalose and inulin by spray drying. In conclusion, a spray dryer model was developed that is able to predict the output parameters of the spray drying process. The model can aid the development of spray dried pharmaceutical products by shifting from a trial-and-error towards a quality-by-design approach. PMID:24040240

Quality assessment concept of the World Data Center for Climate and its application to CMIP5 data

NASA Astrophysics Data System (ADS)

Stockhause, M.; Höck, H.; Toussaint, F.; Lautenschlager, M.

2012-08-01

The preservation of data in a high state of quality which is suitable for interdisciplinary use is one of the most pressing and challenging current issues in long-term archiving. For high volume data such as climate model data, the data and data replica are no longer stored centrally but distributed over several local data repositories, e.g. the data of the Climate Model Intercomparison Project Phase 5 (CMIP5). The most important part of the data is to be archived, assigned a DOI, and published according to the World Data Center for Climate's (WDCC) application of the DataCite regulations. The integrated part of WDCC's data publication process, the data quality assessment, was adapted to the requirements of a federated data infrastructure. A concept of a distributed and federated quality assessment procedure was developed, in which the workload and responsibility for quality control is shared between the three primary CMIP5 data centers: Program for Climate Model Diagnosis and Intercomparison (PCMDI), British Atmospheric Data Centre (BADC), and WDCC. This distributed quality control concept, its pilot implementation for CMIP5, and first experiences are presented. The distributed quality control approach is capable of identifying data inconsistencies and to make quality results immediately available for data creators, data users and data infrastructure managers. Continuous publication of new data versions and slow data replication prevents the quality control from check completion. This together with ongoing developments of the data and metadata infrastructure requires adaptations in code and concept of the distributed quality control approach.

Geophysical insights on the GIA process provided by high-quality constraints from peripheral regions: An outlook on perspectives from North America and from the Mediterranean basin

NASA Astrophysics Data System (ADS)

Roy, K.; Peltier, W. R.

2017-12-01

Our understanding of the Earth-Ice-Ocean interactions that have accompanied the large glaciation-deglaciation process characteristic of the last half of the Pleistocene has benefited significantly from the development of high-quality models of the Glacial Isostatic Adjustment (GIA) process. These models provide fundamental insight on the large changes in sea level and land ice cover over this time period, as well as key constraints on the viscosity structure of the Earth's interior. Their development has benefited from the recent availability of high-quality constraints from regions of forebulge collapse. In particular, over North America, the joint use of high-quality sea level data from the U.S. East coast, together with the vast network of precise space-geodetic observations of crustal motion existing over most of the interior of the continent, has led to the latest ICE-7G_NA (VM7) model (Roy & Peltier, GJI, 2017). In this paper, exciting opportunities provided by such high-quality observations related to the GIA process will be discussed, not only in the context of the continuing effort to refine global models of this phenomenon, but also in terms of the fundamental insight they may provide on outstanding issues in high-pressure geophysics, paleoclimatology or hydrogeology. Specific examples where such high-quality observations can be used (either separately, or using a combination of independent sources) will be presented, focusing particularly on constraints from the North American continent and from the Mediterranean basin. This work will demonstrate that, given the high-quality of currently available constraints on the GIA process, considerable further geophysical insight can be obtained based upon the use of spherically-symmetric models of the viscosity structure of the planet.

Nondestructive detection of pork comprehensive quality based on spectroscopy and support vector machine

NASA Astrophysics Data System (ADS)

Liu, Yuanyuan; Peng, Yankun; Zhang, Leilei; Dhakal, Sagar; Wang, Caiping

2014-05-01

Pork is one of the highly consumed meat item in the world. With growing improvement of living standard, concerned stakeholders including consumers and regulatory body pay more attention to comprehensive quality of fresh pork. Different analytical-laboratory based technologies exist to determine quality attributes of pork. However, none of the technologies are able to meet industrial desire of rapid and non-destructive technological development. Current study used optical instrument as a rapid and non-destructive tool to classify 24 h-aged pork longissimus dorsi samples into three kinds of meat (PSE, Normal and DFD), on the basis of color L* and pH24. Total of 66 samples were used in the experiment. Optical system based on Vis/NIR spectral acquisition system (300-1100 nm) was self- developed in laboratory to acquire spectral signal of pork samples. Median smoothing filter (M-filter) and multiplication scatter correction (MSC) was used to remove spectral noise and signal drift. Support vector machine (SVM) prediction model was developed to classify the samples based on their comprehensive qualities. The results showed that the classification model is highly correlated with the actual quality parameters with classification accuracy more than 85%. The system developed in this study being simple and easy to use, results being promising, the system can be used in meat processing industry for real time, non-destructive and rapid detection of pork qualities in future.

A Multiple-Item Scale for Assessing E-Government Service Quality

NASA Astrophysics Data System (ADS)

Papadomichelaki, Xenia; Mentzas, Gregoris

A critical element in the evolution of e-governmental services is the development of sites that better serve the citizens’ needs. To deliver superior service quality, we must first understand how citizens perceive and evaluate online citizen service. This involves defining what e-government service quality is, identifying its underlying dimensions, and determining how it can be conceptualized and measured. In this article we conceptualise an e-government service quality model (e-GovQual) and then we develop, refine, validate, confirm and test a multiple-item scale for measuring e-government service quality for public administration sites where citizens seek either information or services.

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.

Improving access to psychosocial interventions for common mental health problems in the United Kingdom: narrative review and development of a conceptual model for complex interventions

PubMed Central

2012-01-01

Background In the United Kingdom and worldwide, there is significant policy interest in improving the quality of care for patients with mental health disorders and distress. Improving quality of care means addressing not only the effectiveness of interventions but also the issue of limited access to care. Research to date into improving access to mental health care has not been strongly rooted within a conceptual model, nor has it systematically identified the different elements of the patient journey from identification of illness to receipt of care. This paper set out to review core concepts underlying patient access to mental health care, synthesise these to develop a conceptual model of access, and consider the implications of the model for the development and evaluation of interventions for groups with poor access to mental health care such as older people and ethnic minorities. Methods Narrative review of the literature to identify concepts underlying patient access to mental health care, and synthesis into a conceptual model to support the delivery and evaluation of complex interventions to improve access to mental health care. Results The narrative review adopted a process model of access to care, incorporating interventions at three levels. The levels comprise (a) community engagement (b) addressing the quality of interactions in primary care and (c) the development and delivery of tailored psychosocial interventions. Conclusions The model we propose can form the basis for the development and evaluation of complex interventions in access to mental health care. We highlight the key methodological challenges in evaluating the overall impact of access interventions, and assessing the relative contribution of the different elements of the model. PMID:22889290

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Effect of the spatiotemporal variability of rainfall inputs in water quality integrated catchment modelling for dissolved oxygen concentrations

NASA Astrophysics Data System (ADS)

Moreno Ródenas, Antonio Manuel; Cecinati, Francesca; ten Veldhuis, Marie-Claire; Langeveld, Jeroen; Clemens, Francois

2016-04-01

Maintaining water quality standards in highly urbanised hydrological catchments is a worldwide challenge. Water management authorities struggle to cope with changing climate and an increase in pollution pressures. Water quality modelling has been used as a decision support tool for investment and regulatory developments. This approach led to the development of integrated catchment models (ICM), which account for the link between the urban/rural hydrology and the in-river pollutant dynamics. In the modelled system, rainfall triggers the drainage systems of urban areas scattered along a river. When flow exceeds the sewer infrastructure capacity, untreated wastewater enters the natural system by combined sewer overflows. This results in a degradation of the river water quality, depending on the magnitude of the emission and river conditions. Thus, being capable of representing these dynamics in the modelling process is key for a correct assessment of the water quality. In many urbanised hydrological systems the distances between draining sewer infrastructures go beyond the de-correlation length of rainfall processes, especially, for convective summer storms. Hence, spatial and temporal scales of selected rainfall inputs are expected to affect water quality dynamics. The objective of this work is to evaluate how the use of rainfall data from different sources and with different space-time characteristics affects modelled output concentrations of dissolved oxygen in a simplified ICM. The study area is located at the Dommel, a relatively small and sensitive river flowing through the city of Eindhoven (The Netherlands). This river stretch receives the discharge of the 750,000 p.e. WWTP of Eindhoven and from over 200 combined sewer overflows scattered along its length. A pseudo-distributed water quality model has been developed in WEST (mikedhi.com); this is a lumped-physically based model that accounts for urban drainage processes, WWTP and river dynamics for several pollutant typologies. Different rainfall products are tested: 1) Block kriging of a single reliable rain gauge, 2) Block kriging product from a network of 13 rain gauges and, 3) Universal block kriging with 13 rain gauges and KNMI weather radar estimates as a covariate. Different temporal accumulation levels are compared ranging from 10min to 1h. A geostatistical approach is used to allocate the prediction of the rainfall input in each of the urban hydrological units composing the model. The change in model performance is then assessed by contrasting it with dissolved oxygen monitoring data in a series of events.

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

USGS Publications Warehouse

,

2013-01-01

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

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.

Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14

USGS Publications Warehouse

Francy, Donna S.; Graham, Jennifer L.; Stelzer, Erin A.; Ecker, Christopher D.; Brady, Amie M. G.; Pam Struffolino,; Loftin, Keith A.

2015-11-06

The results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.

Puget Sound Dissolved Oxygen Modeling Study: Development of an Intermediate Scale Water Quality Model

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

Khangaonkar, Tarang; Sackmann, Brandon S.; Long, Wen

2012-10-01

The Salish Sea, including Puget Sound, is a large estuarine system bounded by over seven thousand miles of complex shorelines, consists of several subbasins and many large inlets with distinct properties of their own. Pacific Ocean water enters Puget Sound through the Strait of Juan de Fuca at depth over the Admiralty Inlet sill. Ocean water mixed with freshwater discharges from runoff, rivers, and wastewater outfalls exits Puget Sound through the brackish surface outflow layer. Nutrient pollution is considered one of the largest threats to Puget Sound. There is considerable interest in understanding the effect of nutrient loads on themore » water quality and ecological health of Puget Sound in particular and the Salish Sea as a whole. The Washington State Department of Ecology (Ecology) contracted with Pacific Northwest National Laboratory (PNNL) to develop a coupled hydrodynamic and water quality model. The water quality model simulates algae growth, dissolved oxygen, (DO) and nutrient dynamics in Puget Sound to inform potential Puget Sound-wide nutrient management strategies. Specifically, the project is expected to help determine 1) if current and potential future nitrogen loadings from point and non-point sources are significantly impairing water quality at a large scale and 2) what level of nutrient reductions are necessary to reduce or control human impacts to DO levels in the sensitive areas. The project did not include any additional data collection but instead relied on currently available information. This report describes model development effort conducted during the period 2009 to 2012 under a U.S. Environmental Protection Agency (EPA) cooperative agreement with PNNL, Ecology, and the University of Washington awarded under the National Estuary Program« less

Development and Examination of a Family Triadic Measure to Examine Quality of Life Family Congruence in Nursing Home Residents and Two Family Members.

PubMed

Aalgaard Kelly, Gina

2015-01-01

Objective: The overall purpose of this study was to propose and test a conceptual model and apply family analyses methods to understand quality of life family congruence in the nursing home setting. Method: Secondary data for this study were from a larger study, titled Measurement, Indicators and Improvement of the Quality of Life (QOL) in Nursing Homes . Research literature, family systems theory and human ecological assumptions, fostered the conceptual model empirically testing quality of life family congruence. Results: The study results supported a model examining nursing home residents and two family members on quality of life family congruence. Specifically, family intergenerational dynamic factors, resident personal and social-psychological factors, and nursing home family input factors were examined to identify differences in quality of life family congruence among triad families. Discussion: Formal family involvement and resident cognitive functioning were found as the two most influential factors to quality of life family congruence (QOLFC).

Development and Examination of a Family Triadic Measure to Examine Quality of Life Family Congruence in Nursing Home Residents and Two Family Members

PubMed Central

Aalgaard Kelly, Gina

2015-01-01

Objective: The overall purpose of this study was to propose and test a conceptual model and apply family analyses methods to understand quality of life family congruence in the nursing home setting. Method: Secondary data for this study were from a larger study, titled Measurement, Indicators and Improvement of the Quality of Life (QOL) in Nursing Homes. Research literature, family systems theory and human ecological assumptions, fostered the conceptual model empirically testing quality of life family congruence. Results: The study results supported a model examining nursing home residents and two family members on quality of life family congruence. Specifically, family intergenerational dynamic factors, resident personal and social-psychological factors, and nursing home family input factors were examined to identify differences in quality of life family congruence among triad families. Discussion: Formal family involvement and resident cognitive functioning were found as the two most influential factors to quality of life family congruence (QOLFC). PMID:28138474

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.

Improvements on NYMTC Data Products

DOT National Transportation Integrated Search

2009-11-11

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

THE SCIENTIFIC BASIS OF NOAA'S AIR QUALITY FORECASTING PROGRAM

EPA Science Inventory

For many years, the National Oceanic and Atmospheric Administration (NOAA) has conducted atmospheric research, including chemical and physical measurements, process studies, and the development and evaluation of experimental meteorological and photochemical air quality models. ...

Visions, Strategic Planning, and Quality--More than Hype.

ERIC Educational Resources Information Center

Kaufman, Roger

1996-01-01

Discusses the need to shift from the old models for organizational development to the new methods of quality management and continuous improvement, visions and visioning, and strategic planning, despite inappropriate criticisms they receive. (AEF)

Quality Assessment of TPB-Based Questionnaires: A Systematic Review

PubMed Central

Oluka, Obiageli Crystal; Nie, Shaofa; Sun, Yi

2014-01-01

Objective This review is aimed at assessing the quality of questionnaires and their development process based on the theory of planned behavior (TPB) change model. Methods A systematic literature search for studies with the primary aim of TPB-based questionnaire development was conducted in relevant databases between 2002 and 2012 using selected search terms. Ten of 1,034 screened abstracts met the inclusion criteria and were assessed for methodological quality using two different appraisal tools: one for the overall methodological quality of each study and the other developed for the appraisal of the questionnaire content and development process. Both appraisal tools consisted of items regarding the likelihood of bias in each study and were eventually combined to give the overall quality score for each included study. Results 8 of the 10 included studies showed low risk of bias in the overall quality assessment of each study, while 9 of the studies were of high quality based on the quality appraisal of questionnaire content and development process. Conclusion Quality appraisal of the questionnaires in the 10 reviewed studies was successfully conducted, highlighting the top problem areas (including: sample size estimation; inclusion of direct and indirect measures; and inclusion of questions on demographics) in the development of TPB-based questionnaires and the need for researchers to provide a more detailed account of their development process. PMID:24722323

Habitat Suitability Index Models: Black-shouldered kite

USGS Publications Warehouse

Faanes, Craig A.; Howard, Rebecca J.

1987-01-01

A review and synthesis of existing information were used to develop a model for evaluating black-shouldered kite habitat quality. The model is scaled to produce an index between 0 (unsuitable habitat) to 1.0 (optimal habitat). Habitat suitability index models are designed for use with the Habitat Evaluation Procedures previously developed by the U.S. Fish and Wildlife Service. Guidelines for model application are provided.

Sharpening a District's Leadership Model

ERIC Educational Resources Information Center

Namit, Chuck

2008-01-01

To create an integrated board self-assessment and superintendent evaluation process, district leaders must develop a school leadership model by adopting a coherent governance model. At the same time, they must also develop goals at the appropriate level that ensure quality governance of a school system. In the second of a two-part series, the…

A Product Development Decision Model for Cockpit Weather Information System

NASA Technical Reports Server (NTRS)

Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin; Johnson, Edward J., Jr. (Technical Monitor)

2003-01-01

There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.

A Product Development Decision Model for Cockpit Weather Information Systems

NASA Technical Reports Server (NTRS)

Sireli, Yesim; Kauffmann, Paul; Gupta, Surabhi; Kachroo, Pushkin

2003-01-01

There is a significant market demand for advanced cockpit weather information products. However, it is unclear how to identify the most promising technological options that provide the desired mix of consumer requirements by employing feasible technical systems at a price that achieves market success. This study develops a unique product development decision model that employs Quality Function Deployment (QFD) and Kano's model of consumer choice. This model is specifically designed for exploration and resolution of this and similar information technology related product development problems.

Guiding Principles and Checklist for Population-Based Quality Metrics

PubMed Central

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

2014-01-01

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