Sample records for model quality assessment
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Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin
2015-01-01
Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. PMID:26369671
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Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin
2016-09-01
Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. Proteins 2016; 84(Suppl 1):247-259. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
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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
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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.
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A systematic literature review of open source software quality assessment models.
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.
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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…
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MQAPRank: improved global protein model quality assessment by learning-to-rank.
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.
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A manufacturing quality assessment model based-on two stages interval type-2 fuzzy logic
NASA Astrophysics Data System (ADS)
Purnomo, Muhammad Ridwan Andi; Helmi Shintya Dewi, Intan
2016-01-01
This paper presents the development of an assessment models for manufacturing quality using Interval Type-2 Fuzzy Logic (IT2-FL). The proposed model is developed based on one of building block in sustainable supply chain management (SSCM), which is benefit of SCM, and focuses more on quality. The proposed model can be used to predict the quality level of production chain in a company. The quality of production will affect to the quality of product. Practically, quality of production is unique for every type of production system. Hence, experts opinion will play major role in developing the assessment model. The model will become more complicated when the data contains ambiguity and uncertainty. In this study, IT2-FL is used to model the ambiguity and uncertainty. A case study taken from a company in Yogyakarta shows that the proposed manufacturing quality assessment model can work well in determining the quality level of production.
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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.
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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.…
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Protein single-model quality assessment by feature-based probability density functions.
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.
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DeepQA: improving the estimation of single protein model quality with deep belief networks.
Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin
2016-12-05
Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .
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A comparison of different functions for predicted protein model quality assessment.
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.
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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.
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Image quality assessment by preprocessing and full reference model combination
NASA Astrophysics Data System (ADS)
Bianco, S.; Ciocca, G.; Marini, F.; Schettini, R.
2009-01-01
This paper focuses on full-reference image quality assessment and presents different computational strategies aimed to improve the robustness and accuracy of some well known and widely used state of the art models, namely the Structural Similarity approach (SSIM) by Wang and Bovik and the S-CIELAB spatial-color model by Zhang and Wandell. We investigate the hypothesis that combining error images with a visual attention model could allow a better fit of the psycho-visual data of the LIVE Image Quality assessment Database Release 2. We show that the proposed quality assessment metric better correlates with the experimental data.
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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
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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.
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Quality assessment of protein model-structures based on structural and functional similarities.
Konopka, Bogumil M; Nebel, Jean-Christophe; Kotulska, Malgorzata
2012-09-21
Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. GOBA--Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and one of CASP9, compared to the contest participants. Consequently, GOBA offers a novel single model quality assessment program that addresses the practical needs of biologists. In conjunction with other Model Quality Assessment Programs (MQAPs), it would prove useful for the evaluation of single protein models.
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PconsD: ultra rapid, accurate model quality assessment for protein structure prediction.
Skwark, Marcin J; Elofsson, Arne
2013-07-15
Clustering methods are often needed for accurately assessing the quality of modeled protein structures. Recent blind evaluation of quality assessment methods in CASP10 showed that there is little difference between many different methods as far as ranking models and selecting best model are concerned. When comparing many models, the computational cost of the model comparison can become significant. Here, we present PconsD, a fast, stream-computing method for distance-driven model quality assessment that runs on consumer hardware. PconsD is at least one order of magnitude faster than other methods of comparable accuracy. The source code for PconsD is freely available at http://d.pcons.net/. Supplementary benchmarking data are also available there. arne@bioinfo.se Supplementary data are available at Bioinformatics online.
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Indoor Air Quality Building Education and Assessment Model Forms
The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.
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Indoor Air Quality Building Education and Assessment Model
The Indoor Air Quality Building Education and Assessment Model (I-BEAM), released in 2002, is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.
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Links Related to the Indoor Air Quality Building Education and Assessment Model
The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.
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Bibliography for the Indoor Air Quality Building Education and Assessment Model
The Indoor Air Quality Building Education and Assessment Model (I-BEAM) is a guidance tool designed for use by building professionals and others interested in indoor air quality in commercial buildings.
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Video quality assessment using a statistical model of human visual speed perception.
Wang, Zhou; Li, Qiang
2007-12-01
Motion is one of the most important types of information contained in natural video, but direct use of motion information in the design of video quality assessment algorithms has not been deeply investigated. Here we propose to incorporate a recent model of human visual speed perception [Nat. Neurosci. 9, 578 (2006)] and model visual perception in an information communication framework. This allows us to estimate both the motion information content and the perceptual uncertainty in video signals. Improved video quality assessment algorithms are obtained by incorporating the model as spatiotemporal weighting factors, where the weight increases with the information content and decreases with the perceptual uncertainty. Consistent improvement over existing video quality assessment algorithms is observed in our validation with the video quality experts group Phase I test data set.
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Doctors or technicians: assessing quality of medical education
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
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Doctors or technicians: assessing quality of medical education.
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.
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Air quality models are used to predict changes in pollutant concentrations resulting from envisioned emission control policies. Recognizing the need to assess the credibility of air quality models in a policy-relevant context, we perform a dynamic evaluation of the community Mult...
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APOLLO: a quality assessment service for single and multiple protein models.
Wang, Zheng; Eickholt, Jesse; Cheng, Jianlin
2011-06-15
We built a web server named APOLLO, which can evaluate the absolute global and local qualities of a single protein model using machine learning methods or the global and local qualities of a pool of models using a pair-wise comparison approach. Based on our evaluations on 107 CASP9 (Critical Assessment of Techniques for Protein Structure Prediction) targets, the predicted quality scores generated from our machine learning and pair-wise methods have an average per-target correlation of 0.671 and 0.917, respectively, with the true model quality scores. Based on our test on 92 CASP9 targets, our predicted absolute local qualities have an average difference of 2.60 Å with the actual distances to native structure. http://sysbio.rnet.missouri.edu/apollo/. Single and pair-wise global quality assessment software is also available at the site.
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Quality assessment of protein model-structures based on structural and functional similarities
2012-01-01
Background Experimental determination of protein 3D structures is expensive, time consuming and sometimes impossible. A gap between number of protein structures deposited in the World Wide Protein Data Bank and the number of sequenced proteins constantly broadens. Computational modeling is deemed to be one of the ways to deal with the problem. Although protein 3D structure prediction is a difficult task, many tools are available. These tools can model it from a sequence or partial structural information, e.g. contact maps. Consequently, biologists have the ability to generate automatically a putative 3D structure model of any protein. However, the main issue becomes evaluation of the model quality, which is one of the most important challenges of structural biology. Results GOBA - Gene Ontology-Based Assessment is a novel Protein Model Quality Assessment Program. It estimates the compatibility between a model-structure and its expected function. GOBA is based on the assumption that a high quality model is expected to be structurally similar to proteins functionally similar to the prediction target. Whereas DALI is used to measure structure similarity, protein functional similarity is quantified using standardized and hierarchical description of proteins provided by Gene Ontology combined with Wang's algorithm for calculating semantic similarity. Two approaches are proposed to express the quality of protein model-structures. One is a single model quality assessment method, the other is its modification, which provides a relative measure of model quality. Exhaustive evaluation is performed on data sets of model-structures submitted to the CASP8 and CASP9 contests. Conclusions The validation shows that the method is able to discriminate between good and bad model-structures. The best of tested GOBA scores achieved 0.74 and 0.8 as a mean Pearson correlation to the observed quality of models in our CASP8 and CASP9-based validation sets. GOBA also obtained the best result for two targets of CASP8, and one of CASP9, compared to the contest participants. Consequently, GOBA offers a novel single model quality assessment program that addresses the practical needs of biologists. In conjunction with other Model Quality Assessment Programs (MQAPs), it would prove useful for the evaluation of single protein models. PMID:22998498
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Modified-BRISQUE as no reference image quality assessment for structural MR images.
Chow, Li Sze; Rajagopal, Heshalini
2017-11-01
An effective and practical Image Quality Assessment (IQA) model is needed to assess the image quality produced from any new hardware or software in MRI. A highly competitive No Reference - IQA (NR - IQA) model called Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) initially designed for natural images were modified to evaluate structural MR images. The BRISQUE model measures the image quality by using the locally normalized luminance coefficients, which were used to calculate the image features. The modified-BRISQUE model trained a new regression model using MR image features and Difference Mean Opinion Score (DMOS) from 775 MR images. Two types of benchmarks: objective and subjective assessments were used as performance evaluators for both original and modified-BRISQUE models. There was a high correlation between the modified-BRISQUE with both benchmarks, and they were higher than those for the original BRISQUE. There was a significant percentage improvement in their correlation values. The modified-BRISQUE was statistically better than the original BRISQUE. The modified-BRISQUE model can accurately measure the image quality of MR images. It is a practical NR-IQA model for MR images without using reference images. Copyright © 2017 Elsevier Inc. All rights reserved.
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In this technical support document (TSD) EPA describes the air quality modeling performed to support the 2015 ozone National Ambient Air Quality Standards (NAAQS) preliminary interstate transport assessment Notice of Data Availability (NODA).
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Assessment of the Quality Management Models in Higher Education
ERIC Educational Resources Information Center
Basar, Gulsun; Altinay, Zehra; Dagli, Gokmen; Altinay, Fahriye
2016-01-01
This study involves the assessment of the quality management models in Higher Education by explaining the importance of quality in higher education and by examining the higher education quality assurance system practices in other countries. The qualitative study was carried out with the members of the Higher Education Planning, Evaluation,…
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Water quality assessment and meta model development in Melen watershed - Turkey.
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.
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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.
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AIR QUALITY MODELING AT NEIGHBORHOOD SCALES TO IMPROVE HUMAN EXPOSURE ASSESSMENT
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...
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United3D: a protein model quality assessment program that uses two consensus based methods.
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.
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Perez-Ponce, Hector; Daul, Christian; Wolf, Didier; Noel, Alain
2013-08-01
In mammography, image quality assessment has to be directly related to breast cancer indicator (e.g. microcalcifications) detectability. Recently, we proposed an X-ray source/digital detector (XRS/DD) model leading to such an assessment. This model simulates very realistic contrast-detail phantom (CDMAM) images leading to gold disc (representing microcalcifications) detectability thresholds that are very close to those of real images taken under the simulated acquisition conditions. The detection step was performed with a mathematical observer. The aim of this contribution is to include human observers into the disc detection process in real and virtual images to validate the simulation framework based on the XRS/DD model. Mathematical criteria (contrast-detail curves, image quality factor, etc.) are used to assess and to compare, from the statistical point of view, the cancer indicator detectability in real and virtual images. The quantitative results given in this paper show that the images simulated by the XRS/DD model are useful for image quality assessment in the case of all studied exposure conditions using either human or automated scoring. Also, this paper confirms that with the XRS/DD model the image quality assessment can be automated and the whole time of the procedure can be drastically reduced. Compared to standard quality assessment methods, the number of images to be acquired is divided by a factor of eight. Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.
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Dynamic Assessment of Water Quality Based on a Variable Fuzzy Pattern Recognition Model
Xu, Shiguo; Wang, Tianxiang; Hu, Suduan
2015-01-01
Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results. PMID:25689998
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Dynamic assessment of water quality based on a variable fuzzy pattern recognition model.
Xu, Shiguo; Wang, Tianxiang; Hu, Suduan
2015-02-16
Water quality assessment is an important foundation of water resource protection and is affected by many indicators. The dynamic and fuzzy changes of water quality lead to problems for proper assessment. This paper explores a method which is in accordance with the water quality changes. The proposed method is based on the variable fuzzy pattern recognition (VFPR) model and combines the analytic hierarchy process (AHP) model with the entropy weight (EW) method. The proposed method was applied to dynamically assess the water quality of Biliuhe Reservoir (Dailan, China). The results show that the water quality level is between levels 2 and 3 and worse in August or September, caused by the increasing water temperature and rainfall. Weights and methods are compared and random errors of the values of indicators are analyzed. It is concluded that the proposed method has advantages of dynamism, fuzzification and stability by considering the interval influence of multiple indicators and using the average level characteristic values of four models as results.
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Bayesian Revision of Residual Detection Power
NASA Technical Reports Server (NTRS)
DeLoach, Richard
2013-01-01
This paper addresses some issues with quality assessment and quality assurance in response surface modeling experiments executed in wind tunnels. The role of data volume on quality assurance for response surface models is reviewed. Specific wind tunnel response surface modeling experiments are considered for which apparent discrepancies exist between fit quality expectations based on implemented quality assurance tactics, and the actual fit quality achieved in those experiments. These discrepancies are resolved by using Bayesian inference to account for certain imperfections in the assessment methodology. Estimates of the fraction of out-of-tolerance model predictions based on traditional frequentist methods are revised to account for uncertainty in the residual assessment process. The number of sites in the design space for which residuals are out of tolerance is seen to exceed the number of sites where the model actually fails to fit the data. A method is presented to estimate how much of the design space in inadequately modeled by low-order polynomial approximations to the true but unknown underlying response function.
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Design guidelines for an umbilical cord blood stem cell therapy quality assessment model
NASA Astrophysics Data System (ADS)
Januszewski, Witold S.; Michałek, Krzysztof; Yagensky, Oleksandr; Wardzińska, Marta
The paper enlists the pivotal guidelines for producing an empirical umbilical cord blood stem cell therapy quality assessment model. The methodology adapted was single equation linear model with domain knowledge derived from MEDAFAR classification. The resulting model is ready for therapeutical application.
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Wu, Meiping; Cao, Juliang; Zhang, Kaidong; Cai, Shaokun; Yu, Ruihang
2018-01-01
Quality assessment is an important part in the strapdown airborne gravimetry. Root mean square error (RMSE) evaluation method is a classical way to evaluate the gravimetry quality, but classical evaluation methods are preconditioned by extra flight or reference data. Thus, a method, which is able to largely conquer the premises of classical quality assessment methods and can be used in single survey line, has been developed in this paper. According to theoretical analysis, the method chooses the stability of two horizontal attitude angles, horizontal specific force and vertical specific force as the determinants of quality assessment method. The actual data, collected by SGA-WZ02 from 13 flights 21 lines in certain survey, was used to build the model and elaborate the method. To substantiate the performance of the quality assessment model, the model is applied in extra repeat line flights from two surveys. Compared with internal RMSE, standard deviation of assessment residuals are 0.23 mGal and 0.16 mGal in two surveys, which shows that the quality assessment method is reliable and stricter. The extra flights are not necessary by specially arranging the route of flights. The method, summarized from SGA-WZ02, is a feasible approach to assess gravimetry quality using single line data and is also suitable for other strapdown gravimeters. PMID:29373535
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An Empirical Study of a Solo Performance Assessment Model
ERIC Educational Resources Information Center
Russell, Brian E.
2015-01-01
The purpose of this study was to test a hypothesized model of solo music performance assessment. Specifically, this study investigates the influence of technique and musical expression on perceptions of overall performance quality. The Aural Musical Performance Quality (AMPQ) measure was created to measure overall performance quality, technique,…
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Perceptual video quality assessment in H.264 video coding standard using objective modeling.
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.
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Mendez, Bomar Rojas
2017-01-01
Background Improving access to delivery services does not guarantee access to quality obstetric care and better survival, and therefore, concerns for quality of maternal and newborn care in low- and middle-income countries have been raised. Our study explored characteristics associated with the quality of initial assessment, intrapartum, and immediate postpartum and newborn care, and further assessed the relationships along the continuum of care. Methods The 2010 Service Provision Assessment data of Kenya for 627 routine deliveries of women aged 15–49 were used. Quality of care measures were assessed using recently validated quality of care measures during initial assessment, intrapartum, and postpartum periods. Data were analyzed with negative binomial regression and structural equation modeling technique. Results The negative binomial regression results identified a number of determinants of quality, such as the level of health facilities, managing authority, presence of delivery fee, central electricity supply and clinical guideline for maternal and neonatal care. Our structural equation modeling (SEM) further demonstrated that facility characteristics were important determinants of quality for initial assessment and postpartum care, while characteristics at the provider level became more important in shaping the quality of intrapartum care. Furthermore we also noted that quality of initial assessment had a positive association with quality of intrapartum care (β = 0.71, p < 0.001), which in turn was positively associated with the quality of newborn and immediate postpartum care (β = 1.29, p = 0.004). Conclusions A continued focus on quality of care along the continuum of maternity care is important not only to mothers but also their newborns. Policymakers should therefore ensure that required resources, as well as adequate supervision and emphasis on the quality of obstetric care, are available. PMID:28520771
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Arunasalam, Mark; Paulson, Albert; Wallace, William
2003-01-01
Preferred provider organizations (PPOs) provide healthcare services to an expanding proportion of the U.S. population. This paper presents a programmatic assessment of service quality in the workers' compensation environment using two different models: the PPO program model and the fee-for-service (FFS) payor model. The methodology used here will augment currently available research in workers' compensation, which has been lacking in measuring service quality determinants and assessing programmatic success/failure of managed care type programs. Results indicated that the SERVQUAL tool provided a reliable and valid clinical quality assessment tool that ascertained that PPO marketers should focus on promoting physician outreach (to show empathy) and accessibility (to show reliability) for injured workers.
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APPLICATION OF A WATER QUALITY ASSESSMENT MODELING SYSTEM AT A SUPERFUND SITE
Water quality modeling and related exposure assessments at a Superfund site, Silver Bow Creek-Clark Fork River in Montana, demonstrate the capability to predict the fate of mining waste pollutants in the environment. inked assessment system--consisting of hydrology and erosion, r...
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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.
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The Impact of Truth Surrogate Variance on Quality Assessment/Assurance in Wind Tunnel Testing
NASA Technical Reports Server (NTRS)
DeLoach, Richard
2016-01-01
Minimum data volume requirements for wind tunnel testing are reviewed and shown to depend on error tolerance, response model complexity, random error variance in the measurement environment, and maximum acceptable levels of inference error risk. Distinctions are made between such related concepts as quality assurance and quality assessment in response surface modeling, as well as between precision and accuracy. Earlier research on the scaling of wind tunnel tests is extended to account for variance in the truth surrogates used at confirmation sites in the design space to validate proposed response models. A model adequacy metric is presented that represents the fraction of the design space within which model predictions can be expected to satisfy prescribed quality specifications. The impact of inference error on the assessment of response model residuals is reviewed. The number of sites where reasonably well-fitted response models actually predict inadequately is shown to be considerably less than the number of sites where residuals are out of tolerance. The significance of such inference error effects on common response model assessment strategies is examined.
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A parsimonious dynamic model for river water quality assessment.
Mannina, Giorgio; Viviani, Gaspare
2010-01-01
Water quality modelling is of crucial importance for the assessment of physical, chemical, and biological changes in water bodies. Mathematical approaches to water modelling have become more prevalent over recent years. Different model types ranging from detailed physical models to simplified conceptual models are available. Actually, a possible middle ground between detailed and simplified models may be parsimonious models that represent the simplest approach that fits the application. The appropriate modelling approach depends on the research goal as well as on data available for correct model application. When there is inadequate data, it is mandatory to focus on a simple river water quality model rather than detailed ones. The study presents a parsimonious river water quality model to evaluate the propagation of pollutants in natural rivers. The model is made up of two sub-models: a quantity one and a quality one. The model employs a river schematisation that considers different stretches according to the geometric characteristics and to the gradient of the river bed. Each stretch is represented with a conceptual model of a series of linear channels and reservoirs. The channels determine the delay in the pollution wave and the reservoirs cause its dispersion. To assess the river water quality, the model employs four state variables: DO, BOD, NH(4), and NO. The model was applied to the Savena River (Italy), which is the focus of a European-financed project in which quantity and quality data were gathered. A sensitivity analysis of the model output to the model input or parameters was done based on the Generalised Likelihood Uncertainty Estimation methodology. The results demonstrate the suitability of such a model as a tool for river water quality management.
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Blind image quality assessment without training on human opinion scores
NASA Astrophysics Data System (ADS)
Mittal, Anish; Soundararajan, Rajiv; Muralidhar, Gautam S.; Bovik, Alan C.; Ghosh, Joydeep
2013-03-01
We propose a family of image quality assessment (IQA) models based on natural scene statistics (NSS), that can predict the subjective quality of a distorted image without reference to a corresponding distortionless image, and without any training results on human opinion scores of distorted images. These `completely blind' models compete well with standard non-blind image quality indices in terms of subjective predictive performance when tested on the large publicly available `LIVE' Image Quality database.
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Ozkurt, Nesimi; Sari, Deniz; Akalin, Nuray; Hilmioglu, Bilgin
2013-07-01
The characterization and assessment of air-quality in this region are essential steps for the implementation of the "Clean Air Action Plan" as this is set by the Turkish Regulation on Ambient Air-Quality Assessment and Management. This study area intends to shed a light on use of modeling tools as an alternative method for the assessment of local atmospheric pollution and the determination of the importance of local emissions. This modeling approach can be also used for the consistent geographic representation of air-quality concentration as well as for assessing the future air-quality condition after the implementation of emission reduction measures in a certain area. With this article we evaluate the impact of sulfur dioxide and nitrogen dioxide emissions on the ambient air-quality in the Çan-Bayramiç region of Turkey. The emission rates of sulfur dioxide and nitrogen dioxide were calculated by using the CALPUFF model. The concentration of these pollutants had also been monitored at ten air-quality locations during 2007-2008 in the research area. The measured data were also utilized for testing the model performance. Results showed that the air-quality in this important rural region of Turkey can be evaluated effectively by using the current numerical modeling system. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.
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Analysis of psychological factors for quality assessment of interactive multimodal service
NASA Astrophysics Data System (ADS)
Yamagishi, Kazuhisa; Hayashi, Takanori
2005-03-01
We proposed a subjective quality assessment model for interactive multimodal services. First, psychological factors of an audiovisual communication service were extracted by using the semantic differential (SD) technique and factor analysis. Forty subjects participated in subjective tests and performed point-to-point conversational tasks on a PC-based TV phone that exhibits various network qualities. The subjects assessed those qualities on the basis of 25 pairs of adjectives. Two psychological factors, i.e., an aesthetic feeling and a feeling of activity, were extracted from the results. Then, quality impairment factors affecting these two psychological factors were analyzed. We found that the aesthetic feeling is mainly affected by IP packet loss and video coding bit rate, and the feeling of activity depends on delay time and video frame rate. We then proposed an opinion model derived from the relationships among quality impairment factors, psychological factors, and overall quality. The results indicated that the estimation error of the proposed model is almost equivalent to the statistical reliability of the subjective score. Finally, using the proposed model, we discuss guidelines for quality design of interactive audiovisual communication services.
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Quality assessment of protein model-structures using evolutionary conservation.
Kalman, Matan; Ben-Tal, Nir
2010-05-15
Programs that evaluate the quality of a protein structural model are important both for validating the structure determination procedure and for guiding the model-building process. Such programs are based on properties of native structures that are generally not expected for faulty models. One such property, which is rarely used for automatic structure quality assessment, is the tendency for conserved residues to be located at the structural core and for variable residues to be located at the surface. We present ConQuass, a novel quality assessment program based on the consistency between the model structure and the protein's conservation pattern. We show that it can identify problematic structural models, and that the scores it assigns to the server models in CASP8 correlate with the similarity of the models to the native structure. We also show that when the conservation information is reliable, the method's performance is comparable and complementary to that of the other single-structure quality assessment methods that participated in CASP8 and that do not use additional structural information from homologs. A perl implementation of the method, as well as the various perl and R scripts used for the analysis are available at http://bental.tau.ac.il/ConQuass/. nirb@tauex.tau.ac.il Supplementary data are available at Bioinformatics online.
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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...
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NASA Astrophysics Data System (ADS)
Ranatunga, T.; Tong, S.; Yang, J.
2011-12-01
Hydrologic and water quality models can provide a general framework to conceptualize and investigate the relationships between climate and water resources. Under a hot and dry climate, highly urbanized watersheds are more vulnerable to changes in climate, such as excess heat and drought. In this study, a comprehensive watershed model, Hydrological Simulation Program FORTRAN (HSPF), is used to assess the impacts of future climate change on the stream discharge and water quality in Las Vegas Wash in Nevada, the only surface water body that drains from the Las Vegas Valley (an area with rapid population growth and urbanization) to Lake Mead. In this presentation, the process of model building, calibration and validation, the generation of climate change scenarios, and the assessment of future climate change effects on stream hydrology and quality are demonstrated. The hydrologic and water quality model is developed based on the data from current national databases and existing major land use categories of the watershed. The model is calibrated for stream discharge, nutrients (nitrogen and phosphorus) and sediment yield. The climate change scenarios are derived from the outputs of the Global Climate Models (GCM) and Regional Climate Models (RCM) simulations, and from the recent assessment reports from the Intergovernmental Panel on Climate Change (IPCC). The Climate Assessment Tool from US EPA's BASINS is used to assess the effects of likely future climate scenarios on the water quantity and quality in Las Vegas Wash. Also the presentation discusses the consequences of these hydrologic changes, including the deficit supplies of clean water during peak seasons of water demand, increased eutrophication potentials, wetland deterioration, and impacts on wild life habitats.
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Flight simulator fidelity assessment in a rotorcraft lateral translation maneuver
NASA Technical Reports Server (NTRS)
Hess, R. A.; Malsbury, T.; Atencio, A., Jr.
1992-01-01
A model-based methodology for assessing flight simulator fidelity in closed-loop fashion is exercised in analyzing a rotorcraft low-altitude maneuver for which flight test and simulation results were available. The addition of a handling qualities sensitivity function to a previously developed model-based assessment criteria allows an analytical comparison of both performance and handling qualities between simulation and flight test. Model predictions regarding the existence of simulator fidelity problems are corroborated by experiment. The modeling approach is used to assess analytically the effects of modifying simulator characteristics on simulator fidelity.
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[Environmental quality assessment of regional agro-ecosystem in Loess Plateau].
Wang, Limei; Meng, Fanping; Zheng, Jiyong; Wang, Zhonglin
2004-03-01
Based on the detection and analysis of the contamination status of agro-ecosystem with apple-crops intercropping as the dominant cropping model in Loess Plateau, the individual factor and comprehensive environmental quality were assessed by multilevel fuzzy synthetic evaluation model, analytical hierarchy process(AHP), and improved standard weight deciding method. The results showed that the quality of soil, water and agricultural products was grade I, the social economical environmental quality was grade II, the ecological environmental quality was grade III, and the comprehensive environmental quality was grade I. The regional agro-ecosystem dominated by apple-crops intercropping was not the best model for the ecological benefits, but had the better social economical benefits.
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Urban Air Quality Modelling with AURORA: Prague and Bratislava
NASA Astrophysics Data System (ADS)
Veldeman, N.; Viaene, P.; De Ridder, K.; Peelaerts, W.; Lauwaet, D.; Muhammad, N.; Blyth, L.
2012-04-01
The European Commission, in its strategy to protect the health of the European citizens, states that in order to assess the impact of air pollution on public health, information on long-term exposure to air pollution should be available. Currently, indicators of air quality are often being generated using measured pollutant concentrations. While air quality monitoring stations data provide accurate time series information at specific locations, air quality models have the advantage of being able to assess the spatial variability of air quality (for different resolutions) and predict air quality in the future based on different scenarios. When running such air quality models at a high spatial and temporal resolution, one can simulate the actual situation as closely as possible, allowing for a detailed assessment of the risk of exposure to citizens from different pollutants. AURORA (Air quality modelling in Urban Regions using an Optimal Resolution Approach), a prognostic 3-dimensional Eulerian chemistry-transport model, is designed to simulate urban- to regional-scale atmospheric pollutant concentration and exposure fields. The AURORA model also allows to calculate the impact of changes in land use (e.g. planting of trees) or of emission reduction scenario's on air quality. AURORA is currently being applied within the ESA atmospheric GMES service, PASODOBLE (http://www.myair-eu.org), that delivers information on air quality, greenhouse gases, stratospheric ozone, … At present there are two operational AURORA services within PASODOBLE. Within the "Air quality forecast service" VITO delivers daily air quality forecasts for Belgium at a resolution of 5 km and for the major Belgian cities: Brussels, Ghent, Antwerp, Liege and Charleroi. Furthermore forecast services are provided for Prague, Czech Republic and Bratislava, Slovakia, both at a resolution of 1 km. The "Urban/regional air quality assessment service" provides urban- and regional-scale maps (hourly resolution) for air pollution and human exposure statistics for an entire year. So far we concentrated on Brussels, Belgium and the Rotterdam harbour area, The Netherlands. In this contribution we focus on the operational forecast services. Reference Lefebvre W. et al. (2011) Validation of the MIMOSA-AURORA-IFDM model chain for policy support: Modeling concentrations of elemental carbon in Flanders, Atmospheric Environment 45, 6705-6713
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A no-reference video quality assessment metric based on ROI
NASA Astrophysics Data System (ADS)
Jia, Lixiu; Zhong, Xuefei; Tu, Yan; Niu, Wenjuan
2015-01-01
A no reference video quality assessment metric based on the region of interest (ROI) was proposed in this paper. In the metric, objective video quality was evaluated by integrating the quality of two compressed artifacts, i.e. blurring distortion and blocking distortion. The Gaussian kernel function was used to extract the human density maps of the H.264 coding videos from the subjective eye tracking data. An objective bottom-up ROI extraction model based on magnitude discrepancy of discrete wavelet transform between two consecutive frames, center weighted color opponent model, luminance contrast model and frequency saliency model based on spectral residual was built. Then only the objective saliency maps were used to compute the objective blurring and blocking quality. The results indicate that the objective ROI extraction metric has a higher the area under the curve (AUC) value. Comparing with the conventional video quality assessment metrics which measured all the video quality frames, the metric proposed in this paper not only decreased the computation complexity, but improved the correlation between subjective mean opinion score (MOS) and objective scores.
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An, Yan; Zou, Zhihong; Li, Ranran
2014-01-01
A large number of parameters are acquired during practical water quality monitoring. If all the parameters are used in water quality assessment, the computational complexity will definitely increase. In order to reduce the input space dimensions, a fuzzy rough set was introduced to perform attribute reduction. Then, an attribute recognition theoretical model and entropy method were combined to assess water quality in the Harbin reach of the Songhuajiang River in China. A dataset consisting of ten parameters was collected from January to October in 2012. Fuzzy rough set was applied to reduce the ten parameters to four parameters: BOD5, NH3-N, TP, and F. coli (Reduct A). Considering that DO is a usual parameter in water quality assessment, another reduct, including DO, BOD5, NH3-N, TP, TN, F, and F. coli (Reduct B), was obtained. The assessment results of Reduct B show a good consistency with those of Reduct A, and this means that DO is not always necessary to assess water quality. The results with attribute reduction are not exactly the same as those without attribute reduction, which can be attributed to the α value decided by subjective experience. The assessment results gained by the fuzzy rough set obviously reduce computational complexity, and are acceptable and reliable. The model proposed in this paper enhances the water quality assessment system. PMID:24675643
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Development of an Instructional Quality Assurance Model in Nursing Science
ERIC Educational Resources Information Center
Ajpru, Haruthai; Pasiphol, Shotiga; Wongwanich, Suwimon
2011-01-01
The purpose of this study was to develop an instructional quality assurance model in nursing science. The study was divided into 3 phases; (1) to study the information for instructional quality assurance model development (2) to develop an instructional quality assurance model in nursing science and (3) to audit and the assessment of the developed…
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Regional-scale air quality models are used to estimate the response of air pollutants to potential emission control strategies as part of the decision-making process. Traditionally, the model predicted pollutant concentrations are evaluated for the “base case” to assess a model’s...
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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.
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Hanna, R. Blair; Campbell, Sharon G.
2000-01-01
This report describes the water quality model developed for the Klamath River System Impact Assessment Model (SIAM). The Klamath River SIAM is a decision support system developed by the authors and other US Geological Survey (USGS), Midcontinent Ecological Science Center staff to study the effects of basin-wide water management decisions on anadromous fish in the Klamath River. The Army Corps of Engineersa?? HEC5Q water quality modeling software was used to simulate water temperature, dissolved oxygen and conductivity in 100 miles of the Klamath River Basin in Oregon and California. The water quality model simulated three reservoirs and the mainstem Klamath River influenced by the Shasta and Scott River tributaries. Model development, calibration and two validation exercises are described as well as the integration of the water quality model into the SIAM decision support system software. Within SIAM, data are exchanged between the water quantity model (MODSIM), the water quality model (HEC5Q), the salmon population model (SALMOD) and methods for evaluating ecosystem health. The overall predictive ability of the water quality model is described in the context of calibration and validation error statistics. Applications of SIAM and the water quality model are described.
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Improved model quality assessment using ProQ2.
Ray, Arjun; Lindahl, Erik; Wallner, Björn
2012-09-10
Employing methods to assess the quality of modeled protein structures is now standard practice in bioinformatics. In a broad sense, the techniques can be divided into methods relying on consensus prediction on the one hand, and single-model methods on the other. Consensus methods frequently perform very well when there is a clear consensus, but this is not always the case. In particular, they frequently fail in selecting the best possible model in the hard cases (lacking consensus) or in the easy cases where models are very similar. In contrast, single-model methods do not suffer from these drawbacks and could potentially be applied on any protein of interest to assess quality or as a scoring function for sampling-based refinement. Here, we present a new single-model method, ProQ2, based on ideas from its predecessor, ProQ. ProQ2 is a model quality assessment algorithm that uses support vector machines to predict local as well as global quality of protein models. Improved performance is obtained by combining previously used features with updated structural and predicted features. The most important contribution can be attributed to the use of profile weighting of the residue specific features and the use features averaged over the whole model even though the prediction is still local. ProQ2 is significantly better than its predecessors at detecting high quality models, improving the sum of Z-scores for the selected first-ranked models by 20% and 32% compared to the second-best single-model method in CASP8 and CASP9, respectively. The absolute quality assessment of the models at both local and global level is also improved. The Pearson's correlation between the correct and local predicted score is improved from 0.59 to 0.70 on CASP8 and from 0.62 to 0.68 on CASP9; for global score to the correct GDT_TS from 0.75 to 0.80 and from 0.77 to 0.80 again compared to the second-best single methods in CASP8 and CASP9, respectively. ProQ2 is available at http://proq2.wallnerlab.org.
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NASA Astrophysics Data System (ADS)
Faizah, Arbiati; Syafei, Wahyul Amien; Isnanto, R. Rizal
2018-02-01
This research proposed a model combining an approach of Total Quality Management (TQM) and Fuzzy method of Service Quality (SERVQUAL) to asses service quality. TQM implementation was as quality management orienting on customer's satisfaction by involving all stakeholders. SERVQUAL model was used to measure quality service based on five dimensions such as tangible, reliability, responsiveness, assurance, and empathy. Fuzzy set theory was to accommodate subjectivity and ambiguity of quality assessment. Input data consisted of indicator data and quality assessment aspect. Input data was, then, processed to be service quality assessment questionnaires of Pesantren by using Fuzzy method to get service quality score. This process consisted of some steps as follows : inputting dimension and questionnaire data to data base system, filling questionnaire through system, then, system calculated fuzzification, defuzzification, gap of quality expected and received by service receivers, and calculating each dimension rating showing quality refinement priority. Rating of each quality dimension was, then, displayed at dashboard system to enable users to see information. From system having been built, it could be known that tangible dimension had the highest gap, -0.399, thus it needs to be prioritized and gets evaluation and refinement action soon.
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Evaluating the Quality of the Child Care in Finland
ERIC Educational Resources Information Center
Hujala, Eeva; Fonsen, Elina; Elo, Janniina
2012-01-01
In this study we examine parents' and teachers' perceptions of the early childhood education and care (ECEC) quality in Finland. The study is based on the paradigm of inclusionary quality and the assessment is based on the quality evaluation model. The parents and teachers assess the quality to be good. The strength of the quality was the effect…
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COST VS. QUALITY IN DEMOGRAPHIC MODELLING: WHEN IS A VITAL RATE GOOD ENOUGH?
This presentation will focus on the assessment of quality for demographic parameters to be used in population-level risk assessment. Current population models can handle genetic, demographic, and environmental stochasticity, density dependence, and multiple stressors. However, cu...
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Hydrologic and Water Quality System (HAWQS)
The Hydrologic and Water Quality System (HAWQS) is a web-based interactive water quantity and quality modeling system that employs as its core modeling engine the Soil and Water Assessment Tool (SWAT), an internationally-recognized public domain model. HAWQS provides users with i...
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Educational Quality, Outcomes Assessment, and Policy Change: The Virginia Example
ERIC Educational Resources Information Center
Culver, Steve
2010-01-01
The higher education system in the Commonwealth of Virginia in the United States provides a case model for how discussions regarding educational quality and assessment of that quality have affected institutions' policy decisions and implementation. Using Levin's (1998) policy analysis framework, this essay explores how assessment of student…
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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.
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[Ecological environmental quality assessment of Hangzhou urban area based on RS and GIS].
Xu, Pengwei; Zhao, Duo
2006-06-01
In allusion to the shortage of traditional ecological environmental quality assessment, this paper studied the spatial distribution of assessing factors at a mid-small scale, and the conversion of integer character to girding assessing cells. The main assessing factors including natural environmental condition, environmental quality, natural landscape and urbanization pressure, which were classified into four types with about eleven assessing factors, were selected from RS images and GIS-spatial analyzing environmental quality vector graph. Based on GIS, a comprehensive assessment model for the ecological environmental quality in Hangzhou urban area was established. In comparison with observed urban heat island effects, the assessment results were in good agreement with the ecological environmental quality in the urban area of Hangzhou.
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Lu, Yan; He, Tian
2014-09-15
Much attention has been recently paid to ex-post assessments of socioeconomic and environmental benefits of payment for ecosystem services (PES) programs on poverty reduction, water quality, and forest protection. To evaluate the effects of a regional PES program on water quality, we selected chemical oxygen demand (COD) and ammonia-nitrogen (NH3-N) as indicators of water quality. Statistical methods and an intervention analysis model were employed to assess whether the PES program produced substantial changes in water quality at 10 water-quality sampling stations in the Shaying River watershed, China during 2006-2011. Statistical results from paired-sample t-tests and box plots of COD and NH3-N concentrations at the 10 stations showed that the PES program has played a positive role in improving water quality and reducing trans-boundary water pollution in the Shaying River watershed. Using the intervention analysis model, we quantitatively evaluated the effects of the intervention policy, i.e., the watershed PES program, on water quality at the 10 stations. The results suggest that this method could be used to assess the environmental benefits of watershed or water-related PES programs, such as improvements in water quality, seasonal flow regulation, erosion and sedimentation, and aquatic habitat. Copyright © 2014 Elsevier B.V. All rights reserved.
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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.
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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…
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A multi-model assessment of the co-benefits of climate mitigation for global air quality
NASA Astrophysics Data System (ADS)
Rao, Shilpa; Klimont, Zbigniew; Leitao, Joana; Riahi, Keywan; van Dingenen, Rita; Aleluia Reis, Lara; Calvin, Katherine; Dentener, Frank; Drouet, Laurent; Fujimori, Shinichiro; Harmsen, Mathijs; Luderer, Gunnar; Heyes, Chris; Strefler, Jessica; Tavoni, Massimo; van Vuuren, Detlef P.
2016-12-01
We present a model comparison study that combines multiple integrated assessment models with a reduced-form global air quality model to assess the potential co-benefits of global climate mitigation policies in relation to the World Health Organization (WHO) goals on air quality and health. We include in our assessment, a range of alternative assumptions on the implementation of current and planned pollution control policies. The resulting air pollution emission ranges significantly extend those in the Representative Concentration Pathways. Climate mitigation policies complement current efforts on air pollution control through technology and fuel transformations in the energy system. A combination of stringent policies on air pollution control and climate change mitigation results in 40% of the global population exposed to PM levels below the WHO air quality guideline; with the largest improvements estimated for India, China, and Middle East. Our results stress the importance of integrated multisector policy approaches to achieve the Sustainable Development Goals.
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Useful measures and models for analytical quality management in medical laboratories.
Westgard, James O
2016-02-01
The 2014 Milan Conference "Defining analytical performance goals 15 years after the Stockholm Conference" initiated a new discussion of issues concerning goals for precision, trueness or bias, total analytical error (TAE), and measurement uncertainty (MU). Goal-setting models are critical for analytical quality management, along with error models, quality-assessment models, quality-planning models, as well as comprehensive models for quality management systems. There are also critical underlying issues, such as an emphasis on MU to the possible exclusion of TAE and a corresponding preference for separate precision and bias goals instead of a combined total error goal. This opinion recommends careful consideration of the differences in the concepts of accuracy and traceability and the appropriateness of different measures, particularly TAE as a measure of accuracy and MU as a measure of traceability. TAE is essential to manage quality within a medical laboratory and MU and trueness are essential to achieve comparability of results across laboratories. With this perspective, laboratory scientists can better understand the many measures and models needed for analytical quality management and assess their usefulness for practical applications in medical laboratories.
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A Quality Framework for Continuous Improvement of e-Learning: The e-Learning Maturity Model
ERIC Educational Resources Information Center
Marshall, Stephen
2010-01-01
The E-Learning Maturity Model (eMM) is a quality improvement framework designed to help institutional leaders assess their institution's e-learning maturity. This paper reviews the eMM, drawing on examples of assessments conducted in New Zealand, Australia, the UK and the USA to show how it helps institutional leaders assess and compare their…
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Hoffman, Steven J; Justicz, Victoria
2016-07-01
To develop and validate a method for automatically quantifying the scientific quality and sensationalism of individual news records. After retrieving 163,433 news records mentioning the Severe Acute Respiratory Syndrome (SARS) and H1N1 pandemics, a maximum entropy model for inductive machine learning was used to identify relationships among 500 randomly sampled news records that correlated with systematic human assessments of their scientific quality and sensationalism. These relationships were then computationally applied to automatically classify 10,000 additional randomly sampled news records. The model was validated by randomly sampling 200 records and comparing human assessments of them to the computer assessments. The computer model correctly assessed the relevance of 86% of news records, the quality of 65% of records, and the sensationalism of 73% of records, as compared to human assessments. Overall, the scientific quality of SARS and H1N1 news media coverage had potentially important shortcomings, but coverage was not too sensationalizing. Coverage slightly improved between the two pandemics. Automated methods can evaluate news records faster, cheaper, and possibly better than humans. The specific procedure implemented in this study can at the very least identify subsets of news records that are far more likely to have particular scientific and discursive qualities. Copyright © 2016 Elsevier Inc. All rights reserved.
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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.
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Service Quality and Customer Satisfaction: An Assessment and Future Directions.
ERIC Educational Resources Information Center
Hernon, Peter; Nitecki, Danuta A.; Altman, Ellen
1999-01-01
Reviews the literature of library and information science to examine issues related to service quality and customer satisfaction in academic libraries. Discusses assessment, the application of a business model to higher education, a multiple constituency approach, decision areas regarding service quality, resistance to service quality, and future…
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Ranking Quality in Higher Education: Guiding or Misleading?
ERIC Educational Resources Information Center
Bergseth, Brita; Petocz, Peter; Abrandt Dahlgren, Madeleine
2014-01-01
The study examines two different models of measuring, assessing and ranking quality in higher education. Do different systems of quality assessment lead to equivalent conclusions about the quality of education? This comparative study is based on the rankings of 24 Swedish higher education institutions. Two ranking actors have independently…
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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.
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Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.
Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si
2017-07-01
Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.
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NASA Astrophysics Data System (ADS)
Azarnova, T. V.; Titova, I. A.; Barkalov, S. A.
2018-03-01
The article presents an algorithm for obtaining an integral assessment of the quality of an organization from the perspective of customers, based on the method of aggregating linguistic information on a multilevel hierarchical system of quality assessment. The algorithm is of a constructive nature, it provides not only the possibility of obtaining an integral evaluation, but also the development of a quality improvement strategy based on the method of linguistic decomposition, which forms the minimum set of areas of work with clients whose quality change will allow obtaining the required level of integrated quality assessment.
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A simple parametric model observer for quality assurance in computer tomography
NASA Astrophysics Data System (ADS)
Anton, M.; Khanin, A.; Kretz, T.; Reginatto, M.; Elster, C.
2018-04-01
Model observers are mathematical classifiers that are used for the quality assessment of imaging systems such as computer tomography. The quality of the imaging system is quantified by means of the performance of a selected model observer. For binary classification tasks, the performance of the model observer is defined by the area under its ROC curve (AUC). Typically, the AUC is estimated by applying the model observer to a large set of training and test data. However, the recording of these large data sets is not always practical for routine quality assurance. In this paper we propose as an alternative a parametric model observer that is based on a simple phantom, and we provide a Bayesian estimation of its AUC. It is shown that a limited number of repeatedly recorded images (10–15) is already sufficient to obtain results suitable for the quality assessment of an imaging system. A MATLAB® function is provided for the calculation of the results. The performance of the proposed model observer is compared to that of the established channelized Hotelling observer and the nonprewhitening matched filter for simulated images as well as for images obtained from a low-contrast phantom on an x-ray tomography scanner. The results suggest that the proposed parametric model observer, along with its Bayesian treatment, can provide an efficient, practical alternative for the quality assessment of CT imaging systems.
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The Air Quality Model Evaluation International Initiative (AQMEII) has now reached its second phase which is dedicated to the evaluation of online coupled chemistry-meteorology models. Sixteen modeling groups from Europe and five from North America have run regional air quality m...
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NASA Astrophysics Data System (ADS)
Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim
2017-10-01
Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.
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Within the context of the Air Quality Model Evaluation International Initiative phase 2 (AQMEII2) project, this part II paper performs a multi-model assessment of major column abundances of gases, radiation, aerosol, and cloud variables for 2006 and 2010 simulations with three on...
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Barelds, Anna; van de Goor, Ien; van Heck, Guus; Schols, Jos
2010-03-01
Care and service trajectories for people with intellectual disabilities (i.e. people with mental retardations) are routes within the healthcare delivery system that consist of all the steps that people with intellectual disabilities and their families have to take in order to realise the needed care and services. This article aims to identify the quality aspects of trajectories that are considered important by people with intellectual disabilities and their parents/relatives. In addition, it examines how these aspects are related to quality determinants mentioned in the literature on integrated care and to authoritative models for quality assessment of care and service delivery. Quality aspects were collected during eight focus group discussions with people with intellectual disabilities or their parents/relatives. In addition, quality determinants of integrated care and authoritative models for quality assessment were selected by means of a thorough review of the literature. Finally, the quality aspects identified using focus groups were compared to the determinants and models found in the literature. The quality aspects presented by people with intellectual disabilities referred particularly to the immediate situation in receiving care and services, such as 'keeping appointments' and 'time and attention', whereas parents/relatives also referred to broader 'organisational issues', such as 'access to support' and 'problems with placement'. The quality aspects, however, are minimally related to the quality determinants of integrated care, probably because clients and their parents/relatives find it difficult to have an overview of the coherence between the various actions that have to be performed, when going through the trajectories. In contrast, the quality aspects seem to fit into the domains of the authoritative models for quality assessment, probably because of the minimal focus of the models on long-term aspects in care and service delivery.
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No-reference quality assessment based on visual perception
NASA Astrophysics Data System (ADS)
Li, Junshan; Yang, Yawei; Hu, Shuangyan; Zhang, Jiao
2014-11-01
The visual quality assessment of images/videos is an ongoing hot research topic, which has become more and more important for numerous image and video processing applications with the rapid development of digital imaging and communication technologies. The goal of image quality assessment (IQA) algorithms is to automatically assess the quality of images/videos in agreement with human quality judgments. Up to now, two kinds of models have been used for IQA, namely full-reference (FR) and no-reference (NR) models. For FR models, IQA algorithms interpret image quality as fidelity or similarity with a perfect image in some perceptual space. However, the reference image is not available in many practical applications, and a NR IQA approach is desired. Considering natural vision as optimized by the millions of years of evolutionary pressure, many methods attempt to achieve consistency in quality prediction by modeling salient physiological and psychological features of the human visual system (HVS). To reach this goal, researchers try to simulate HVS with image sparsity coding and supervised machine learning, which are two main features of HVS. A typical HVS captures the scenes by sparsity coding, and uses experienced knowledge to apperceive objects. In this paper, we propose a novel IQA approach based on visual perception. Firstly, a standard model of HVS is studied and analyzed, and the sparse representation of image is accomplished with the model; and then, the mapping correlation between sparse codes and subjective quality scores is trained with the regression technique of least squaresupport vector machine (LS-SVM), which gains the regressor that can predict the image quality; the visual metric of image is predicted with the trained regressor at last. We validate the performance of proposed approach on Laboratory for Image and Video Engineering (LIVE) database, the specific contents of the type of distortions present in the database are: 227 images of JPEG2000, 233 images of JPEG, 174 images of White Noise, 174 images of Gaussian Blur, 174 images of Fast Fading. The database includes subjective differential mean opinion score (DMOS) for each image. The experimental results show that the proposed approach not only can assess many kinds of distorted images quality, but also exhibits a superior accuracy and monotonicity.
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Dynamic Evaluation of Long-Term Air Quality Model Simulations Over the Northeastern U.S.
Dynamic model evaluation assesses a modeling system's ability to reproduce changes in air quality induced by changes in meteorology and/or emissions. In this paper, we illustrate various approaches to dynamic mode evaluation utilizing 18 years of air quality simulations perform...
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Yamartino, R.J.; Smith, D.G.; Bremer, S.A.
1980-07-01
This report documents the results of the Federal Aviation Administration (FAA)/Environmental Protection Agency (EPA) air quality study which has been conducted to assess the impact of aircraft emissions of carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NOx) in the vicinity of airports. This assessment includes the results of recent modeling and monitoring efforts at Washington National (DCA), Los Angeles International (LAX), Dulles International (IAD), and Lakeland, Florida airports and an updated modeling of aircraft generated pollution at LAX, John F. Kennedy (JFK) and Chicago O'Hare (ORD) airports. The Airport Vicinity Air Pollution (AVAP) model which was designed formore » use at civil airports was used in this assessment. In addition the results of the application of the military version of the AVAP model the Air Quality Assessment Model (AQAM), are summarized.« less
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Lin, Xiaotong; Liu, Mei; Chen, Xue-wen
2009-04-29
Protein-protein interactions play vital roles in nearly all cellular processes and are involved in the construction of biological pathways such as metabolic and signal transduction pathways. Although large-scale experiments have enabled the discovery of thousands of previously unknown linkages among proteins in many organisms, the high-throughput interaction data is often associated with high error rates. Since protein interaction networks have been utilized in numerous biological inferences, the inclusive experimental errors inevitably affect the quality of such prediction. Thus, it is essential to assess the quality of the protein interaction data. In this paper, a novel Bayesian network-based integrative framework is proposed to assess the reliability of protein-protein interactions. We develop a cross-species in silico model that assigns likelihood scores to individual protein pairs based on the information entirely extracted from model organisms. Our proposed approach integrates multiple microarray datasets and novel features derived from gene ontology. Furthermore, the confidence scores for cross-species protein mappings are explicitly incorporated into our model. Applying our model to predict protein interactions in the human genome, we are able to achieve 80% in sensitivity and 70% in specificity. Finally, we assess the overall quality of the experimentally determined yeast protein-protein interaction dataset. We observe that the more high-throughput experiments confirming an interaction, the higher the likelihood score, which confirms the effectiveness of our approach. This study demonstrates that model organisms certainly provide important information for protein-protein interaction inference and assessment. The proposed method is able to assess not only the overall quality of an interaction dataset, but also the quality of individual protein-protein interactions. We expect the method to continually improve as more high quality interaction data from more model organisms becomes available and is readily scalable to a genome-wide application.
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ProTSAV: A protein tertiary structure analysis and validation server.
Singh, Ankita; Kaushik, Rahul; Mishra, Avinash; Shanker, Asheesh; Jayaram, B
2016-01-01
Quality assessment of predicted model structures of proteins is as important as the protein tertiary structure prediction. A highly efficient quality assessment of predicted model structures directs further research on function. Here we present a new server ProTSAV, capable of evaluating predicted model structures based on some popular online servers and standalone tools. ProTSAV furnishes the user with a single quality score in case of individual protein structure along with a graphical representation and ranking in case of multiple protein structure assessment. The server is validated on ~64,446 protein structures including experimental structures from RCSB and predicted model structures for CASP targets and from public decoy sets. ProTSAV succeeds in predicting quality of protein structures with a specificity of 100% and a sensitivity of 98% on experimentally solved structures and achieves a specificity of 88%and a sensitivity of 91% on predicted protein structures of CASP11 targets under 2Å.The server overcomes the limitations of any single server/method and is seen to be robust in helping in quality assessment. ProTSAV is freely available at http://www.scfbio-iitd.res.in/software/proteomics/protsav.jsp. Copyright © 2015 Elsevier B.V. All rights reserved.
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DockQ: A Quality Measure for Protein-Protein Docking Models
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
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NASA Astrophysics Data System (ADS)
Banerjee, Polash; Ghose, Mrinal Kanti; Pradhan, Ratika
2018-05-01
Spatial analysis of water quality impact assessment of highway projects in mountainous areas remains largely unexplored. A methodology is presented here for Spatial Water Quality Impact Assessment (SWQIA) due to highway-broadening-induced vehicular traffic change in the East district of Sikkim. Pollution load of the highway runoff was estimated using an Average Annual Daily Traffic-Based Empirical model in combination with mass balance model to predict pollution in the rivers within the study area. Spatial interpolation and overlay analysis were used for impact mapping. Analytic Hierarchy Process-Based Water Quality Status Index was used to prepare a composite impact map. Model validation criteria, cross-validation criteria, and spatial explicit sensitivity analysis show that the SWQIA model is robust. The study shows that vehicular traffic is a significant contributor to water pollution in the study area. The model is catering specifically to impact analysis of the concerned project. It can be an aid for decision support system for the project stakeholders. The applicability of SWQIA model needs to be explored and validated in the context of a larger set of water quality parameters and project scenarios at a greater spatial scale.
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Ging, Patricia
2013-01-01
The U.S. Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Program was established by Congress in 1992 to answer the following question: What is the status of the Nation’s water quality and is it getting better or worse? Since 1992, NAWQA has been a primary source of nationally consistent data and information on the quality of the Nation’s streams and groundwater. Data and information obtained from objective and nationally consistent water-quality monitoring and modeling activities provide answers to where, when, and why the Nation’s water quality is degraded and what can be done to improve and protect it for human and ecosystem needs. For NAWQA’s third decade (2013–23), a new strategic Science Plan has been developed that describes a strategy for building upon and enhancing the USGS’s ongoing assessment of the Nation’s freshwater quality and aquatic ecosystems.
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de la Mare, William; Ellis, Nick; Pascual, Ricardo; Tickell, Sharon
2012-04-01
Simulation models have been widely adopted in fisheries for management strategy evaluation (MSE). However, in catchment management of water quality, MSE is hampered by the complexity of both decision space and the hydrological process models. Empirical models based on monitoring data provide a feasible alternative to process models; they run much faster and, by conditioning on data, they can simulate realistic responses to management actions. Using 10 years of water quality indicators from Queensland, Australia, we built an empirical model suitable for rapid MSE that reproduces the water quality variables' mean and covariance structure, adjusts the expected indicators through local management effects, and propagates effects downstream by capturing inter-site regression relationships. Empirical models enable managers to search the space of possible strategies using rapid assessment. They provide not only realistic responses in water quality indicators but also variability in those indicators, allowing managers to assess strategies in an uncertain world. Copyright © 2012 Elsevier Ltd. All rights reserved.
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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
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Perimal-Lewis, Lua; Teubner, David; Hakendorf, Paul; Horwood, Chris
2016-12-01
Effective and accurate use of routinely collected health data to produce Key Performance Indicator reporting is dependent on the underlying data quality. In this research, Process Mining methodology and tools were leveraged to assess the data quality of time-based Emergency Department data sourced from electronic health records. This research was done working closely with the domain experts to validate the process models. The hospital patient journey model was used to assess flow abnormalities which resulted from incorrect timestamp data used in time-based performance metrics. The research demonstrated process mining as a feasible methodology to assess data quality of time-based hospital performance metrics. The insight gained from this research enabled appropriate corrective actions to be put in place to address the data quality issues. © The Author(s) 2015.
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AIR QUALITY MODELING OF PM AND AIR TOXICS AT NEIGHBORHOOD SCALES
The current interest in fine particles and toxics pollutants provide an impetus for extending air quality modeling capability towards improving exposure modeling and assessments. Human exposure models require information on concentration derived from interpolation of observati...
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Objective assessment of MPEG-2 video quality
NASA Astrophysics Data System (ADS)
Gastaldo, Paolo; Zunino, Rodolfo; Rovetta, Stefano
2002-07-01
The increasing use of video compression standards in broadcasting television systems has required, in recent years, the development of video quality measurements that take into account artifacts specifically caused by digital compression techniques. In this paper we present a methodology for the objective quality assessment of MPEG video streams by using circular back-propagation feedforward neural networks. Mapping neural networks can render nonlinear relationships between objective features and subjective judgments, thus avoiding any simplifying assumption on the complexity of the model. The neural network processes an instantaneous set of input values, and yields an associated estimate of perceived quality. Therefore, the neural-network approach turns objective quality assessment into adaptive modeling of subjective perception. The objective features used for the estimate are chosen according to the assessed relevance to perceived quality and are continuously extracted in real time from compressed video streams. The overall system mimics perception but does not require any analytical model of the underlying physical phenomenon. The capability to process compressed video streams represents an important advantage over existing approaches, like avoiding the stream-decoding process greatly enhances real-time performance. Experimental results confirm that the system provides satisfactory, continuous-time approximations for actual scoring curves concerning real test videos.
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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…
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Blind prediction of natural video quality.
Saad, Michele A; Bovik, Alan C; Charrier, Christophe
2014-03-01
We propose a blind (no reference or NR) video quality evaluation model that is nondistortion specific. The approach relies on a spatio-temporal model of video scenes in the discrete cosine transform domain, and on a model that characterizes the type of motion occurring in the scenes, to predict video quality. We use the models to define video statistics and perceptual features that are the basis of a video quality assessment (VQA) algorithm that does not require the presence of a pristine video to compare against in order to predict a perceptual quality score. The contributions of this paper are threefold. 1) We propose a spatio-temporal natural scene statistics (NSS) model for videos. 2) We propose a motion model that quantifies motion coherency in video scenes. 3) We show that the proposed NSS and motion coherency models are appropriate for quality assessment of videos, and we utilize them to design a blind VQA algorithm that correlates highly with human judgments of quality. The proposed algorithm, called video BLIINDS, is tested on the LIVE VQA database and on the EPFL-PoliMi video database and shown to perform close to the level of top performing reduced and full reference VQA algorithms.
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Care zoning in a psychiatric intensive care unit: strengthening ongoing clinical risk assessment.
Mullen, Antony; Drinkwater, Vincent; Lewin, Terry J
2014-03-01
To implement and evaluate the care zoning model in an eight-bed psychiatric intensive care unit and, specifically, to examine the model's ability to improve the documentation and communication of clinical risk assessment and management. Care zoning guides nurses in assessing clinical risk and planning care within a mental health context. Concerns about the varying quality of clinical risk assessment prompted a trial of the care zoning model in a psychiatric intensive care unit within a regional mental health facility. The care zoning model assigns patients to one of 3 'zones' according to their clinical risk, encouraging nurses to document and implement targeted interventions required to manage those risks. An implementation trial framework was used for this research to refine, implement and evaluate the impact of the model on nurses' clinical practice within the psychiatric intensive care unit, predominantly as a quality improvement initiative. The model was trialled for three months using a pre- and postimplementation staff survey, a pretrial file audit and a weekly file audit. Informal staff feedback was also sought via surveys and regular staff meetings. This trial demonstrated improvement in the quality of mental state documentation, and clinical risk information was identified more accurately. There was limited improvement in the quality of care planning and the documentation of clinical interventions. Nurses' initial concerns over the introduction of the model shifted into overall acceptance and recognition of the benefits. The results of this trial demonstrate that the care zoning model was able to improve the consistency and quality of risk assessment information documented. Care planning and evaluation of associated outcomes showed less improvement. Care zoning remains a highly applicable model for the psychiatric intensive care unit environment and is a useful tool in guiding nurses to carry out routine patient risk assessments. © 2013 John Wiley & Sons Ltd.
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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.
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Quality assessment of color images based on the measure of just noticeable color difference
NASA Astrophysics Data System (ADS)
Chou, Chun-Hsien; Hsu, Yun-Hsiang
2014-01-01
Accurate assessment on the quality of color images is an important step to many image processing systems that convey visual information of the reproduced images. An accurate objective image quality assessment (IQA) method is expected to give the assessment result highly agreeing with the subjective assessment. To assess the quality of color images, many approaches simply apply the metric for assessing the quality of gray scale images to each of three color channels of the color image, neglecting the correlation among three color channels. In this paper, a metric for assessing color images' quality is proposed, in which the model of variable just-noticeable color difference (VJNCD) is employed to estimate the visibility thresholds of distortion inherent in each color pixel. With the estimated visibility thresholds of distortion, the proposed metric measures the average perceptible distortion in terms of the quantized distortion according to the perceptual error map similar to that defined by National Bureau of Standards (NBS) for converting the color difference enumerated by CIEDE2000 to the objective score of perceptual quality assessment. The perceptual error map in this case is designed for each pixel according to the visibility threshold estimated by the VJNCD model. The performance of the proposed metric is verified by assessing the test images in the LIVE database, and is compared with those of many well-know IQA metrics. Experimental results indicate that the proposed metric is an effective IQA method that can accurately predict the image quality of color images in terms of the correlation between objective scores and subjective evaluation.
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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…
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Schwartz, Carolyn E; Rapkin, Bruce D
2004-01-01
The increasing evidence for response shift phenomena in quality of life (QOL) assessment points to the necessity to reconsider both the measurement model and the application of psychometric analyses. The proposed psychometric model posits that the QOL true score is always contingent upon parameters of the appraisal process. This new model calls into question existing methods for establishing the reliability and validity of QOL assessment tools and suggests several new approaches for describing the psychometric properties of these scales. Recommendations for integrating the assessment of appraisal into QOL research and clinical practice are discussed. PMID:15038830
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Image and Video Quality Assessment Using LCD: Comparisons with CRT Conditions
NASA Astrophysics Data System (ADS)
Tourancheau, Sylvain; Callet, Patrick Le; Barba, Dominique
In this paper, the impact of display on quality assessment is addressed. Subjective quality assessment experiments have been performed on both LCD and CRT displays. Two sets of still images and two sets of moving pictures have been assessed using either an ACR or a SAMVIQ protocol. Altogether, eight experiments have been led. Results are presented and discussed, some differences are pointed out. Concerning moving pictures, these differences seem to be mainly due to LCD moving artefacts such as motion blur. LCD motion blur has been measured objectively and with psycho-physics experiments. A motion-blur metric based on the temporal characteristics of LCD can be defined. A prediction model have been then designed which predict the differences of perceived quality between CRT and LCD. This motion-blur-based model enables the estimation of perceived quality on LCD with respect to the perceived quality on CRT. Technical solutions to LCD motion blur can thus be evaluated on natural contents by this mean.
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Pouwels, Xavier Ghislain Léon Victor; Ramaekers, Bram L T; Joore, Manuela A
2017-10-01
To provide an overview of model characteristics and outcomes of model-based economic evaluations concerning chemotherapy and targeted therapy (TT) for metastatic breast cancer (MBC); to assess the quality of the studies; to analyse the association between model characteristics and study quality and outcomes. PubMED and NHS EED were systematically searched. Inclusion criteria were as follows: English or Dutch language, model-based economic evaluation, chemotherapy or TT as intervention, population diagnosed with MBC, published between 2000 and 2014, reporting life years (LY) or quality-adjusted life-year (QALY) and an incremental cost-effectiveness ratio. General characteristics, model characteristics and outcomes of the studies were extracted. Quality of the studies was assessed through a checklist. 24 studies were included, considering 50 comparisons (20 concerning chemotherapy and 30 TT). Seven comparisons were represented in multiple studies. A health state-transition model including the following health states: stable/progression-free disease, progression and death was used in 18 studies. Studies fulfilled on average 14 out of the 26 items of the quality checklist, mostly due to a lack of transparency in reporting. Thirty-one per cent of the incremental net monetary benefit was positive. TT led to higher iQALY gained, and industry-sponsored studies reported more favourable cost-effectiveness outcomes. The development of a disease-specific reference model would improve the transparency and quality of model-based cost-effectiveness assessments for MBC treatments. Incremental health benefits increased over time, but were outweighed by the increased treatment costs. Consequently, increased health benefits led to lower value for money.
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Maiti, Saumen; Erram, V C; Gupta, Gautam; Tiwari, Ram Krishna; Kulkarni, U D; Sangpal, R R
2013-04-01
Deplorable quality of groundwater arising from saltwater intrusion, natural leaching and anthropogenic activities is one of the major concerns for the society. Assessment of groundwater quality is, therefore, a primary objective of scientific research. Here, we propose an artificial neural network-based method set in a Bayesian neural network (BNN) framework and employ it to assess groundwater quality. The approach is based on analyzing 36 water samples and inverting up to 85 Schlumberger vertical electrical sounding data. We constructed a priori model by suitably parameterizing geochemical and geophysical data collected from the western part of India. The posterior model (post-inversion) was estimated using the BNN learning procedure and global hybrid Monte Carlo/Markov Chain Monte Carlo optimization scheme. By suitable parameterization of geochemical and geophysical parameters, we simulated 1,500 training samples, out of which 50 % samples were used for training and remaining 50 % were used for validation and testing. We show that the trained model is able to classify validation and test samples with 85 % and 80 % accuracy respectively. Based on cross-correlation analysis and Gibb's diagram of geochemical attributes, the groundwater qualities of the study area were classified into following three categories: "Very good", "Good", and "Unsuitable". The BNN model-based results suggest that groundwater quality falls mostly in the range of "Good" to "Very good" except for some places near the Arabian Sea. The new modeling results powered by uncertainty and statistical analyses would provide useful constrain, which could be utilized in monitoring and assessment of the groundwater quality.
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2012-01-01
Background A relationship between current socio-economic position and subjective quality of life has been demonstrated, using wellbeing, life and needs satisfaction approaches. Less is known regarding the influence of different life course socio-economic trajectories on later quality of life. Several conceptual models have been proposed to help explain potential life course effects on health, including accumulation, latent, pathway and social mobility models. This systematic review aimed to assess whether evidence supported an overall relationship between life course socio-economic position and quality of life during adulthood and if so, whether there was support for one or more life course models. Methods A review protocol was developed detailing explicit inclusion and exclusion criteria, search terms, data extraction items and quality appraisal procedures. Literature searches were performed in 12 electronic databases during January 2012 and the references and citations of included articles were checked for additional relevant articles. Narrative synthesis was used to analyze extracted data and studies were categorized based on the life course model analyzed. Results Twelve studies met the eligibility criteria and used data from 10 datasets and five countries. Study quality varied and heterogeneity between studies was high. Seven studies assessed social mobility models, five assessed the latent model, two assessed the pathway model and three tested the accumulation model. Evidence indicated an overall relationship, but mixed results were found for each life course model. Some evidence was found to support the latent model among women, but not men. Social mobility models were supported in some studies, but overall evidence suggested little to no effect. Few studies addressed accumulation and pathway effects and study heterogeneity limited synthesis. Conclusions To improve potential for synthesis in this area, future research should aim to increase study comparability. Recommendations include testing all life course models within individual studies and the use of multiple measures of socio-economic position and quality of life. Comparable cross-national data would be beneficial to enable investigation of between-country differences. PMID:22873945
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Assessing uncertain human exposure to ambient air pollution using environmental models in the Web
NASA Astrophysics Data System (ADS)
Gerharz, L. E.; Pebesma, E.; Denby, B.
2012-04-01
Ambient air quality can have significant impact on human health by causing respiratory and cardio-vascular diseases. Thereby, the pollutant concentration a person is exposed to can differ considerably between individuals depending on their daily routine and movement patterns. Using a straight forward approach this exposure can be estimated by integration of individual space-time paths and spatio-temporally resolved ambient air quality data. To allow a realistic exposure assessment, it is furthermore important to consider uncertainties due to input and model errors. In this work, we present a generic, web-based approach for estimating individual exposure by integration of uncertain position and air quality information implemented as a web service. Following the Model Web initiative envisioning an infrastructure for deploying, executing and chaining environmental models as services, existing models and data sources for e.g. air quality, can be used to assess exposure. Therefore, the service needs to deal with different formats, resolutions and uncertainty representations provided by model or data services. Potential mismatch can be accounted for by transformation of uncertainties and (dis-)aggregation of data under consideration of changes in the uncertainties using components developed in the UncertWeb project. In UncertWeb, the Model Web vision is extended to an Uncertainty-enabled Model Web, where services can process and communicate uncertainties in the data and models. The propagation of uncertainty to the exposure results is quantified using Monte Carlo simulation by combining different realisations of positions and ambient concentrations. Two case studies were used to evaluate the developed exposure assessment service. In a first study, GPS tracks with a positional uncertainty of a few meters, collected in the urban area of Münster, Germany were used to assess exposure to PM10 (particulate matter smaller 10 µm). Air quality data was provided by an uncertainty-enabled air quality model system which provided realisations of concentrations per hour on a 250 m x 250 m resolved grid over Münster. The second case study uses modelled human trajectories in Rotterdam, The Netherlands. The trajectories were provided as realisations in 15 min resolution per 4 digit postal code from an activity model. Air quality estimates were provided for different pollutants as ensembles by a coupled meteorology and air quality model system on a 1 km x 1 km grid with hourly resolution. Both case studies show the successful application of the service to different resolutions and uncertainty representations.
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NASA Astrophysics Data System (ADS)
Yang, Xinyan; Zhao, Wei; Ye, Long; Zhang, Qin
2017-07-01
This paper proposes a no-reference objective stereoscopic video quality assessment method with the motivation that making the effect of objective experiments close to that of subjective way. We believe that the image regions with different visual salient degree should not have the same weights when designing an assessment metric. Therefore, we firstly use GBVS algorithm to each frame pairs and separate both the left and right viewing images into the regions with strong, general and week saliency. Besides, local feature information like blockiness, zero-crossing and depth are extracted and combined with a mathematical model to calculate a quality assessment score. Regions with different salient degree are assigned with different weights in the mathematical model. Experiment results demonstrate the superiority of our method compared with the existed state-of-the-art no-reference objective Stereoscopic video quality assessment methods.
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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…
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Application-Driven No-Reference Quality Assessment for Dermoscopy Images With Multiple Distortions.
Xie, Fengying; Lu, Yanan; Bovik, Alan C; Jiang, Zhiguo; Meng, Rusong
2016-06-01
Dermoscopy images often suffer from blur and uneven illumination distortions that occur during acquisition, which can adversely influence consequent automatic image analysis results on potential lesion objects. The purpose of this paper is to deploy an algorithm that can automatically assess the quality of dermoscopy images. Such an algorithm could be used to direct image recapture or correction. We describe an application-driven no-reference image quality assessment (IQA) model for dermoscopy images affected by possibly multiple distortions. For this purpose, we created a multiple distortion dataset of dermoscopy images impaired by varying degrees of blur and uneven illumination. The basis of this model is two single distortion IQA metrics that are sensitive to blur and uneven illumination, respectively. The outputs of these two metrics are combined to predict the quality of multiply distorted dermoscopy images using a fuzzy neural network. Unlike traditional IQA algorithms, which use human subjective score as ground truth, here ground truth is driven by the application, and generated according to the degree of influence of the distortions on lesion analysis. The experimental results reveal that the proposed model delivers accurate and stable quality prediction results for dermoscopy images impaired by multiple distortions. The proposed model is effective for quality assessment of multiple distorted dermoscopy images. An application-driven concept for IQA is introduced, and at the same time, a solution framework for the IQA of multiple distortions is proposed.
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Quality Concerns in Technical Education in India: A Quantifiable Quality Enabled Model
ERIC Educational Resources Information Center
Gambhir, Victor; Wadhwa, N. C.; Grover, Sandeep
2016-01-01
Purpose: The paper aims to discuss current Technical Education scenarios in India. It proposes modelling the factors affecting quality in a technical institute and then applying a suitable technique for assessment, comparison and ranking. Design/methodology/approach: The paper chose graph theoretic approach for quantification of quality-enabled…
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Tomer, M D; Locke, M A
2011-01-01
The Conservation Effects Assessment Project was established to quantify water quality benefits of conservation practices supported by the U.S. Department of Agriculture (USDA). In 2004, watershed assessment studies were begun in fourteen agricultural watersheds with varying cropping systems, landscapes, climate, and water quality concerns. This paper reviews USDA Agricultural Research Service 'Benchmark' watershed studies and the challenge of identifying water quality benefits in watersheds. Study goals included modeling and field research to assess practices, and evaluation of practice placement in watersheds. Not all goals were met within five years but important lessons were learned. While practices improved water quality, problems persisted in larger watersheds. This dissociation between practice-focused and watershed-scale assessments occurred because: (1) Conservation practices were not targeted at critical sources/pathways of contaminants; (2) Sediment in streams originated more from channel and bank erosion than from soil erosion; (3) Timing lags, historical legacies, and shifting climate combined to mask effects of practice implementation; and (4) Water quality management strategies addressed single contaminants with little regard for trade-offs among contaminants. These lessons could help improve conservation strategies and set water quality goals with realistic timelines. Continued research on agricultural water quality could better integrate modeling and monitoring capabilities, and address ecosystem services.
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[Real-time detection of quality of Chinese materia medica: strategy of NIR model evaluation].
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.
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Fan, Chihhao; Ko, Chun-Han; Wang, Wei-Shen
2009-04-01
Water quality modeling has been shown to be a useful tool in strategic water quality management. The present study combines the Qual2K model with the HEC-RAS model to assess the water quality of a tidal river in northern Taiwan. The contaminant loadings of biochemical oxygen demand (BOD), ammonia nitrogen (NH(3)-N), total phosphorus (TP), and sediment oxygen demand (SOD) are utilized in the Qual2K simulation. The HEC-RAS model is used to: (i) estimate the hydraulic constants for atmospheric re-aeration constant calculation; and (ii) calculate the water level profile variation to account for concentration changes as a result of tidal effect. The results show that HEC-RAS-assisted Qual2K simulations taking tidal effect into consideration produce water quality indices that, in general, agree with the monitoring data of the river. Comparisons of simulations with different combinations of contaminant loadings demonstrate that BOD is the most import contaminant. Streeter-Phelps simulation (in combination with HEC-RAS) is also performed for comparison, and the results show excellent agreement with the observed data. This paper is the first report of the innovative use of a combination of the HEC-RAS model and the Qual2K model (or Streeter-Phelps equation) to simulate water quality in a tidal river. The combination is shown to provide an alternative for water quality simulation of a tidal river when available dynamic-monitoring data are insufficient to assess the tidal effect of the river.
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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.
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dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs.
Ma, Kede; Liu, Wentao; Liu, Tongliang; Wang, Zhou; Tao, Dacheng
2017-05-26
Objective assessment of image quality is fundamentally important in many image processing tasks. In this work, we focus on learning blind image quality assessment (BIQA) models which predict the quality of a digital image with no access to its original pristine-quality counterpart as reference. One of the biggest challenges in learning BIQA models is the conflict between the gigantic image space (which is in the dimension of the number of image pixels) and the extremely limited reliable ground truth data for training. Such data are typically collected via subjective testing, which is cumbersome, slow, and expensive. Here we first show that a vast amount of reliable training data in the form of quality-discriminable image pairs (DIP) can be obtained automatically at low cost by exploiting largescale databases with diverse image content. We then learn an opinion-unaware BIQA (OU-BIQA, meaning that no subjective opinions are used for training) model using RankNet, a pairwise learning-to-rank (L2R) algorithm, from millions of DIPs, each associated with a perceptual uncertainty level, leading to a DIP inferred quality (dipIQ) index. Extensive experiments on four benchmark IQA databases demonstrate that dipIQ outperforms state-of-the-art OU-BIQA models. The robustness of dipIQ is also significantly improved as confirmed by the group MAximum Differentiation (gMAD) competition method. Furthermore, we extend the proposed framework by learning models with ListNet (a listwise L2R algorithm) on quality-discriminable image lists (DIL). The resulting DIL Inferred Quality (dilIQ) index achieves an additional performance gain.
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Using National Coastal Assessment Data to Model Estuarine Water Quality at Large Spatial Scales.
The water quality of the Nation’s estuaries is attracting scrutiny in light of population growth and enhanced nutrient delivery. The USEPA has evaluated water quality in the National Coastal Assessment (NCA) and National Aquatic Resource Surveys (NARS) programs. Here we rep...
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Family and Community Perceptions of Quality in Juvenile Justice Programs
ERIC Educational Resources Information Center
Selber, Katherine; Streeter, Calvin
2004-01-01
The conceptualization and empirical assessment of service quality in juvenile justice remains limited. There are few reports on programmatic attempts to assess satisfaction in juvenile justice programs or attempts to include what constitutes quality of service from multiple customer perspectives. This article describes a potential model, the Gap…
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Under the Air Quality Model Evaluation International Initiative, Phase 2 (AQMEII-2), three online coupled air quality model simulations, with six different configurations, are analyzed for their performance, inter-model agreement, and responses to emission and meteorological chan...
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Hudak, R P; Jacoby, I; Meyer, G S; Potter, A L; Hooper, T I; Krakauer, H
1997-01-01
This article describes a training model that focuses on health care management by applying epidemiologic methods to assess and improve the quality of clinical practice. The model's uniqueness is its focus on integrating clinical evidence-based decision making with fundamental principles of resource management to achieve attainable, cost-effective, high-quality health outcomes. The target students are current and prospective clinical and administrative executives who must optimize decision making at the clinical and managerial levels of health care organizations.
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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
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The objective of this study is to examine changes in ambient ozone concentrations estimated by a photochemical air quality model in response to the NOx emission reductions imposed on the utility sector. To accomplish this task, CMAQ air quality model simulations were performe...
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Regional air quality models are being used in a policy-setting to estimate the response of air pollutant concentrations to changes in emissions and meteorology. Dynamic evaluation entails examination of a retrospective case(s) to assess whether an air quality model has properly p...
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Self-assessment procedure using fuzzy sets
NASA Astrophysics Data System (ADS)
Mimi, Fotini
2000-10-01
Self-Assessment processes, initiated by a company itself and carried out by its own people, are considered to be the starting point for a regular strategic or operative planning process to ensure a continuous quality improvement. Their importance has increased by the growing relevance and acceptance of international quality awards such as the Malcolm Baldrige National Quality Award, the European Quality Award and the Deming Prize. Especially award winners use the instrument of a systematic and regular Self-Assessment and not only because they have to verify their quality and business results for at least three years. The Total Quality Model of the European Foundation for Quality Management (EFQM), used for the European Quality Award, is the basis for Self-Assessment in Europe. This paper presents a self-assessment supporting method based on a methodology of fuzzy control systems providing an effective means of converting the linguistic approximation into an automatic control strategy. In particular, the elements of the Quality Model mentioned above are interpreted as linguistic variables. The LR-type of a fuzzy interval is used for their representation. The input data has a qualitative character based on empirical investigation and expert knowledge and therefore the base- variables are ordinal scaled. The aggregation process takes place on the basis of a hierarchical structure. Finally, in order to render the use of the method more practical a software system on PC basis is developed and implemented.
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An assessment model for quality management
NASA Astrophysics Data System (ADS)
Völcker, Chr.; Cass, A.; Dorling, A.; Zilioli, P.; Secchi, P.
2002-07-01
SYNSPACE together with InterSPICE and Alenia Spazio is developing an assessment method to determine the capability of an organisation in the area of quality management. The method, sponsored by the European Space Agency (ESA), is called S9kS (SPiCE- 9000 for SPACE). S9kS is based on ISO 9001:2000 with additions from the quality standards issued by the European Committee for Space Standardization (ECSS) and ISO 15504 - Process Assessments. The result is a reference model that supports the expansion of the generic process assessment framework provided by ISO 15504 to nonsoftware areas. In order to be compliant with ISO 15504, requirements from ISO 9001 and ECSS-Q-20 and Q-20-09 have been turned into process definitions in terms of Purpose and Outcomes, supported by a list of detailed indicators such as Practices, Work Products and Work Product Characteristics. In coordination with this project, the capability dimension of ISO 15504 has been revised to be consistent with ISO 9001. As contributions from ISO 9001 and the space quality assurance standards are separable, the stripped down version S9k offers organisations in all industries an assessment model based solely on ISO 9001, and is therefore interesting to all organisations, which intend to improve their quality management system based on ISO 9001.
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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.
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Prediction of global and local model quality in CASP8 using the ModFOLD server.
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.
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Chapter 4 of Assessing the Multiple Benefits of Clean Energy helps state states understand the methods, models, opportunities, and issues associated with assessing the GHG, air pollution, air quality, and human health benefits of clean energy options.
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The Feasibility of Quality Function Deployment (QFD) as an Assessment and Quality Assurance Model
ERIC Educational Resources Information Center
Matorera, D.; Fraser, W. J.
2016-01-01
Business schools are globally often seen as structured, purpose-driven, multi-sector and multi-perspective organisations. This article is based on the response of a graduate school to an innovative industrial Quality Function Deployment-based model (QFD), which was to be adopted initially in a Master's degree programme for quality assurance…
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Verification of a quality management theory: using a delphi study.
Mosadeghrad, Ali Mohammad
2013-11-01
A model of quality management called Strategic Collaborative Quality Management (SCQM) model was developed based on the quality management literature review, the findings of a survey on quality management assessment in healthcare organisations, semi-structured interviews with healthcare stakeholders, and a Delphi study on healthcare quality management experts. The purpose of this study was to verify the SCQM model. The proposed model was further developed using feedback from thirty quality management experts using a Delphi method. Further, a guidebook for its implementation was prepared including a road map and performance measurement. The research led to the development of a context-specific model of quality management for healthcare organisations and a series of guidelines for its implementation. A proper model of quality management should be developed and implemented properly in healthcare organisations to achieve business excellence.
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Verification of a Quality Management Theory: Using a Delphi Study
Mosadeghrad, Ali Mohammad
2013-01-01
Background: A model of quality management called Strategic Collaborative Quality Management (SCQM) model was developed based on the quality management literature review, the findings of a survey on quality management assessment in healthcare organisations, semi-structured interviews with healthcare stakeholders, and a Delphi study on healthcare quality management experts. The purpose of this study was to verify the SCQM model. Methods: The proposed model was further developed using feedback from thirty quality management experts using a Delphi method. Further, a guidebook for its implementation was prepared including a road map and performance measurement. Results: The research led to the development of a context-specific model of quality management for healthcare organisations and a series of guidelines for its implementation. Conclusion: A proper model of quality management should be developed and implemented properly in healthcare organisations to achieve business excellence. PMID:24596883
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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)
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Air Pollution Data for Model Evaluation and Application
One objective of designing an air pollution monitoring network is to obtain data for evaluating air quality models that are used in the air quality management process and scientific discovery.1.2 A common use is to relate emissions to air quality, including assessing ...
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Bayesian Analysis of a Reduced-Form Air Quality Model
Numerical air quality models are being used for assessing emission control strategies for improving ambient pollution levels across the globe. This paper applies probabilistic modeling to evaluate the effectiveness of emission reduction scenarios aimed at lowering ground-level oz...
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Cecchel, S; Chindamo, D; Turrini, E; Carnevale, C; Cornacchia, G; Gadola, M; Panvini, A; Volta, M; Ferrario, D; Golimbioschi, R
2018-02-01
This study presents a modelling system to evaluate the impact of weight reduction in light commercial vehicles with diesel engines on air quality and greenhouse gas emissions. The PROPS model assesses the emissions of one vehicle in the aforementioned category and its corresponding reduced-weight version. The results serve as an input to the RIAT+ tool, an air quality integrated assessment modelling system. This paper applies the tools in a case study in the Lombardy region (Italy) and discusses the input data pre-processing, the PROPS-RIAT+ modelling system runs, and the results. Copyright © 2017 Elsevier B.V. All rights reserved.
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EVALUATING AND USING AIR QUALITY MODELS
Grid-based models are being used to assess the magnitude of the pollution problem and to design emission control strategies to achieve compliance with the relevant air quality standards in the United States.
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RAPID ASSESSMENT OF URBAN WETLANDS: FUNCTIONAL ASSESSMENT MODEL DEVELOPMENT AND EVALUATION
The objective of this study was to test the ability of existing hydrogeomorphic (HGM) functional assessment models and our own proposed models to predict rates of nitrate production and removal, functions critical to water quality protection, in forested riparian wetlands in nort...
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Heuristic Model Of The Composite Quality Index Of Environmental Assessment
NASA Astrophysics Data System (ADS)
Khabarov, A. N.; Knyaginin, A. A.; Bondarenko, D. V.; Shepet, I. P.; Korolkova, L. N.
2017-01-01
The goal of the paper is to present the heuristic model of the composite environmental quality index based on the integrated application of the elements of utility theory, multidimensional scaling, expert evaluation and decision-making. The composite index is synthesized in linear-quadratic form, it provides higher adequacy of the results of the assessment preferences of experts and decision-makers.
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Gaia: automated quality assessment of protein structure models.
Kota, Pradeep; Ding, Feng; Ramachandran, Srinivas; Dokholyan, Nikolay V
2011-08-15
Increasing use of structural modeling for understanding structure-function relationships in proteins has led to the need to ensure that the protein models being used are of acceptable quality. Quality of a given protein structure can be assessed by comparing various intrinsic structural properties of the protein to those observed in high-resolution protein structures. In this study, we present tools to compare a given structure to high-resolution crystal structures. We assess packing by calculating the total void volume, the percentage of unsatisfied hydrogen bonds, the number of steric clashes and the scaling of the accessible surface area. We assess covalent geometry by determining bond lengths, angles, dihedrals and rotamers. The statistical parameters for the above measures, obtained from high-resolution crystal structures enable us to provide a quality-score that points to specific areas where a given protein structural model needs improvement. We provide these tools that appraise protein structures in the form of a web server Gaia (http://chiron.dokhlab.org). Gaia evaluates the packing and covalent geometry of a given protein structure and provides quantitative comparison of the given structure to high-resolution crystal structures. dokh@unc.edu Supplementary data are available at Bioinformatics online.
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Operation quality assessment model for video conference system
NASA Astrophysics Data System (ADS)
Du, Bangshi; Qi, Feng; Shao, Sujie; Wang, Ying; Li, Weijian
2018-01-01
Video conference system has become an important support platform for smart grid operation and management, its operation quality is gradually concerning grid enterprise. First, the evaluation indicator system covering network, business and operation maintenance aspects was established on basis of video conference system's operation statistics. Then, the operation quality assessment model combining genetic algorithm with regularized BP neural network was proposed, which outputs operation quality level of the system within a time period and provides company manager with some optimization advice. The simulation results show that the proposed evaluation model offers the advantages of fast convergence and high prediction accuracy in contrast with regularized BP neural network, and its generalization ability is superior to LM-BP neural network and Bayesian BP neural network.
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ERIC Educational Resources Information Center
Chen, Benyou
2014-01-01
Quality is the core of education and it is important to standardization construction of primary and secondary education in urban (U) and rural (R) areas. The ultimate goal of the integration of urban and rural education is to pursuit quality urban and rural education. Based on analysing the related policy basis and the existing assessment models…
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A series of lectures and exercises on how to use BASINS for water quality modeling and watershed assessment. The lectures follow sequentially. Companion exercises are provided for users to practice different BASINS water quality modeling techniques.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Yamartino, R.J.; Smith, D.G.; Bremer, S.A.
1980-07-01
This report documents the results of the Federal Aviation Administration (FAA)/Environmental Protection Agency (EPA) air quality study which has been conducted to assess the impact of aircraft emissions of carbon monoxide (CO), hydrocarbons (HC), and oxides of nitrogen (NOx) in the vicinity of airports. This assessment includes the results of recent modeling and monitoring efforts at Washington National (DCA), Los Angeles International (LAX), Dulles International (IAD), and Lakeland, Florida airports and an updated modeling of aircraft generated pollution at LAX, John F. Kennedy (JFK) and Chicago O'Hare (ORD) airports. The Airport Vicinity Air Pollution (AVAP) model which was designed formore » use at civil airports was used in this assessment. In addition the results of the application of the military version of the AVAP model the Air Quality Assessment Model (AQAM), are summarized. Both the results of the pollution monitoring analyses in Volume I and the modeling studies in Volume II suggest that: maximum hourly average CO concentrations from aircraft are unlikely to exceed 5 parts per million (ppm) in areas of public exposure and are thus small in comparison to the National Ambient Air Quality Standard of 35 ppm; maximum hourly HC concentrations from aircraft can exceed 0.25 ppm over an area several times the size of the airport; and annual average NO2 concentrations from aircraft are estimated to contribute only 10 to 20 percent of the NAAQS limit level.« less
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The UCD sectional aerosol model has been coupled to the CMAQ air quality model and used to simulate air quality in Tampa, Florida. Sea salt emissions are parameterized as a function of modeled wind speed and relative humidity. Modeled aerosol sulfate, nitrate, ammonium, sodium,...
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Directly linking air quality and watershed models could provide an effective method for estimating spatially-explicit inputs of atmospheric contaminants to watershed biogeochemical models. However, to adequately link air and watershed models for wet deposition estimates, each mod...
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The National Ambient Air Quality Standards for particulate matter (PM) and the federal regional haze regulations place some emphasis on the assessment of fine particle (PM; 5) concentrations. Current air quality models need to be improved and evaluated against observations to a...
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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...
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Durrieu, Gilles; Pham, Quang-Khoai; Foltête, Anne-Sophie; Maxime, Valérie; Grama, Ion; Tilly, Véronique Le; Duval, Hélène; Tricot, Jean-Marie; Naceur, Chiraz Ben; Sire, Olivier
2016-07-01
Water quality can be evaluated using biomarkers such as tissular enzymatic activities of endemic species. Measurement of molluscs bivalves activity at high frequency (e.g., valvometry) during a long time period is another way to record the animal behavior and to evaluate perturbations of the water quality in real time. As the pollution affects the activity of oysters, we consider the valves opening and closing velocities to monitor the water quality assessment. We propose to model the huge volume of velocity data collected in the framework of valvometry using a new nonparametric extreme values statistical model. The objective is to estimate the tail probabilities and the extreme quantiles of the distribution of valve closing velocity. The tail of the distribution function of valve closing velocity is modeled by a Pareto distribution with parameter t,τ , beyond a threshold τ according to the time t of the experiment. Our modeling approach reveals the dependence between the specific activity of two enzymatic biomarkers (Glutathione-S-transferase and acetylcholinesterase) and the continuous recording of oyster valve velocity, proving the suitability of this tool for water quality assessment. Thus, valvometry allows in real-time in situ analysis of the bivalves behavior and appears as an effective early warning tool in ecological risk assessment and marine environment monitoring.
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Deep supervised dictionary learning for no-reference image quality assessment
NASA Astrophysics Data System (ADS)
Huang, Yuge; Liu, Xuesong; Tian, Xiang; Zhou, Fan; Chen, Yaowu; Jiang, Rongxin
2018-03-01
We propose a deep convolutional neural network (CNN) for general no-reference image quality assessment (NR-IQA), i.e., accurate prediction of image quality without a reference image. The proposed model consists of three components such as a local feature extractor that is a fully CNN, an encoding module with an inherent dictionary that aggregates local features to output a fixed-length global quality-aware image representation, and a regression module that maps the representation to an image quality score. Our model can be trained in an end-to-end manner, and all of the parameters, including the weights of the convolutional layers, the dictionary, and the regression weights, are simultaneously learned from the loss function. In addition, the model can predict quality scores for input images of arbitrary sizes in a single step. We tested our method on commonly used image quality databases and showed that its performance is comparable with that of state-of-the-art general-purpose NR-IQA algorithms.
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Table Rock Lake Water-Clarity Assessment Using Landsat Thematic Mapper Satellite Data
Krizanich, Gary; Finn, Michael P.
2009-01-01
Water quality of Table Rock Lake in southwestern Missouri is assessed using Landsat Thematic Mapper satellite data. A pilot study uses multidate satellite image scenes in conjunction with physical measurements of secchi disk transparency collected by the Lakes of Missouri Volunteer Program to construct a regression model used to estimate water clarity. The natural log of secchi disk transparency is the dependent variable in the regression and the independent variables are Thematic Mapper band 1 (blue) reflectance and a ratio of the band 1 and band 3 (red) reflectance. The regression model can be used to reliably predict water clarity anywhere within the lake. A pixel-level lake map of predicted water clarity or computed trophic state can be produced from the model output. Information derived from this model can be used by water-resource managers to assess water quality and evaluate effects of changes in the watershed on water quality.
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A study of undue pain and surfing: using hierarchical criteria to assess website quality.
Lorence, Daniel; Abraham, Joanna
2008-09-01
In studies of web-based consumer health information, scant attention has been paid to the selective development of differential methodologies for website quality evaluation, or to selective grouping and analysis of specific ;domains of uncertainty' in healthcare. Our objective is to introduce a more refined model for website evaluation, and illustrate its application using assessment of websites within an area of ongoing medical uncertainty, back pain. In this exploratory technology assessment, we suggest a model for assessing these ;domains of uncertainty' within healthcare, using qualitative assessment of websites and hierarchical concepts. Using such a hierarchy of quality criteria, we review medical information provided by the most frequently accessed websites related to back pain. Websites are evaluated using standardized criteria, with results rated from the viewpoint of the consumer. Results show that standardization of quality rating across subjective content, and between commercial and niche search results, can provide a consumer-friendly dimension to health information.
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Effect of quality chronic disease management for alcohol and drug dependence on addiction outcomes.
Kim, Theresa W; Saitz, Richard; Cheng, Debbie M; Winter, Michael R; Witas, Julie; Samet, Jeffrey H
2012-12-01
We examined the effect of the quality of primary care-based chronic disease management (CDM) for alcohol and/or other drug (AOD) dependence on addiction outcomes. We assessed quality using (1) a visit frequency based measure and (2) a self-reported assessment measuring alignment with the chronic care model. The visit frequency based measure had no significant association with addiction outcomes. The self-reported measure of care-when care was at a CDM clinic-was associated with lower drug addiction severity. The self-reported assessment of care from any healthcare source (CDM clinic or elsewhere) was associated with lower alcohol addiction severity and abstinence. These findings suggest that high quality CDM for AOD dependence may improve addiction outcomes. Quality measures based upon alignment with the chronic care model may better capture features of effective CDM care than a visit frequency measure. Copyright © 2012 Elsevier Inc. All rights reserved.
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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.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Dolly, S; Mutic, S; Anastasio, M
Purpose: Traditionally, image quality in radiation therapy is assessed subjectively or by utilizing physically-based metrics. Some model observers exist for task-based medical image quality assessment, but almost exclusively for diagnostic imaging tasks. As opposed to disease diagnosis, the task for image observers in radiation therapy is to utilize the available images to design and deliver a radiation dose which maximizes patient disease control while minimizing normal tissue damage. The purpose of this study was to design and implement a new computer simulation model observer to enable task-based image quality assessment in radiation therapy. Methods: A modular computer simulation framework wasmore » developed to resemble the radiotherapy observer by simulating an end-to-end radiation therapy treatment. Given images and the ground-truth organ boundaries from a numerical phantom as inputs, the framework simulates an external beam radiation therapy treatment and quantifies patient treatment outcomes using the previously defined therapeutic operating characteristic (TOC) curve. As a preliminary demonstration, TOC curves were calculated for various CT acquisition and reconstruction parameters, with the goal of assessing and optimizing simulation CT image quality for radiation therapy. Sources of randomness and bias within the system were analyzed. Results: The relationship between CT imaging dose and patient treatment outcome was objectively quantified in terms of a singular value, the area under the TOC (AUTOC) curve. The AUTOC decreases more rapidly for low-dose imaging protocols. AUTOC variation introduced by the dose optimization algorithm was approximately 0.02%, at the 95% confidence interval. Conclusion: A model observer has been developed and implemented to assess image quality based on radiation therapy treatment efficacy. It enables objective determination of appropriate imaging parameter values (e.g. imaging dose). Framework flexibility allows for incorporation of additional modules to include any aspect of the treatment process, and therefore has great potential for both assessment and optimization within radiation therapy.« less
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Oliveira-Maia, Albino J; Mendonça, Carina; Pessoa, Maria J; Camacho, Marta; Gago, Joaquim
2016-01-01
Within clinical psychiatry, recovery from severe mental illness (SMI) has classically been defined according to symptoms and function (service-based recovery). However, service-users have argued that recovery should be defined as the process of overcoming mental illness, regaining self-control and establishing a meaningful life (customer-based recovery). Here, we aimed to compare customer-based and service-based recovery and clarify their differential relationship with other constructs, namely needs and quality of life. The study was conducted in 101 patients suffering from SMI, recruited from a rural community mental health setting in Portugal. Customer-based recovery and function-related service-based recovery were assessed, respectively, using a shortened version of the Mental Health Recovery Measure (MHRM-20) and the Global Assessment of Functioning score. The Camberwell Assessment of Need scale was used to objectively assess needs, while subjective quality of life was measured with the TL-30s scale. Using multiple linear regression models, we found that the Global Assessment of Functioning score was incrementally predictive of the MHRM-20 score, when added to a model including only clinical and demographic factors, and that this model was further incremented by the score for quality of life. However, in an alternate model using the Global Assessment of Functioning score as the dependent variable, while the MHRM-20 score contributed significantly to the model when added to clinical and demographic factors, the model was not incremented by the score for quality of life. These results suggest that, while a more global concept of recovery from SMI may be assessed using measures for service-based and customer-based recovery, the latter, namely the MHRM-20, also provides information about subjective well-being. Pending confirmation of these findings in other populations, this instrument could thus be useful for comprehensive assessment of recovery and subjective well-being in patients suffering from SMI.
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Oliveira-Maia, Albino J.; Mendonça, Carina; Pessoa, Maria J.; Camacho, Marta; Gago, Joaquim
2016-01-01
Within clinical psychiatry, recovery from severe mental illness (SMI) has classically been defined according to symptoms and function (service-based recovery). However, service-users have argued that recovery should be defined as the process of overcoming mental illness, regaining self-control and establishing a meaningful life (customer-based recovery). Here, we aimed to compare customer-based and service-based recovery and clarify their differential relationship with other constructs, namely needs and quality of life. The study was conducted in 101 patients suffering from SMI, recruited from a rural community mental health setting in Portugal. Customer-based recovery and function-related service-based recovery were assessed, respectively, using a shortened version of the Mental Health Recovery Measure (MHRM-20) and the Global Assessment of Functioning score. The Camberwell Assessment of Need scale was used to objectively assess needs, while subjective quality of life was measured with the TL-30s scale. Using multiple linear regression models, we found that the Global Assessment of Functioning score was incrementally predictive of the MHRM-20 score, when added to a model including only clinical and demographic factors, and that this model was further incremented by the score for quality of life. However, in an alternate model using the Global Assessment of Functioning score as the dependent variable, while the MHRM-20 score contributed significantly to the model when added to clinical and demographic factors, the model was not incremented by the score for quality of life. These results suggest that, while a more global concept of recovery from SMI may be assessed using measures for service-based and customer-based recovery, the latter, namely the MHRM-20, also provides information about subjective well-being. Pending confirmation of these findings in other populations, this instrument could thus be useful for comprehensive assessment of recovery and subjective well-being in patients suffering from SMI. PMID:27857698
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Real-time assessments of water quality: expanding nowcasting throughout the Great Lakes
,
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.
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An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression
Weiss, Brandi A.; Dardick, William
2015-01-01
This article introduces an entropy-based measure of data–model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify the quality of classification and separation of group membership. Entropy complements preexisting measures of data–model fit and provides unique information not contained in other measures. Hypothetical data scenarios, an applied example, and Monte Carlo simulation results are used to demonstrate the application of entropy in logistic regression. Entropy should be used in conjunction with other measures of data–model fit to assess how well logistic regression models classify cases into observed categories. PMID:29795897
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An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression.
Weiss, Brandi A; Dardick, William
2016-12-01
This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify the quality of classification and separation of group membership. Entropy complements preexisting measures of data-model fit and provides unique information not contained in other measures. Hypothetical data scenarios, an applied example, and Monte Carlo simulation results are used to demonstrate the application of entropy in logistic regression. Entropy should be used in conjunction with other measures of data-model fit to assess how well logistic regression models classify cases into observed categories.
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A hybrid modeling with data assimilation to evaluate human exposure level
NASA Astrophysics Data System (ADS)
Koo, Y. S.; Cheong, H. K.; Choi, D.; Kim, A. L.; Yun, H. Y.
2015-12-01
Exposure models are designed to better represent human contact with PM (Particulate Matter) and other air pollutants such as CO, SO2, O3, and NO2. The exposure concentrations of the air pollutants to human are determined by global and regional long range transport of global and regional scales from Europe and China as well as local emissions from urban and road vehicle sources. To assess the exposure level in detail, the multiple scale influence from background to local sources should be considered. A hybrid air quality modeling methodology combing a grid-based chemical transport model with a local plume dispersion model was used to provide spatially and temporally resolved air quality concentration for human exposure levels in Korea. In the hybrid modeling approach, concentrations from a grid-based chemical transport model and a local plume dispersion model are added to provide contributions from photochemical interactions, long-range (regional) transport and local-scale dispersion. The CAMx (Comprehensive Air quality Model with Extensions was used for the background concentrations from anthropogenic and natural emissions in East Asia including Korea while the road dispersion by vehicle emission was calculated by CALPUFF model. The total exposure level of the pollutants was finally assessed by summing the background and road contributions. In the hybrid modeling, the data assimilation method based on the optimal interpolation was applied to overcome the discrepancies between the model predicted concentrations and observations. The air quality data from the air quality monitoring stations in Korea. The spatial resolution of the hybrid model was 50m for the Seoul Metropolitan Ares. This example clearly demonstrates that the exposure level could be estimated to the fine scale for the exposure assessment by using the hybrid modeling approach with data assimilation.
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Mahan, Carolyn G.; Young, John A.; Miller, Bruce; Saunders, Michael C.
2014-01-01
We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)—national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks’ conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a −1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape—we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.
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Mahan, Carolyn G; Young, John A; Miller, Bruce J; Saunders, Michael C
2015-02-01
We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)-national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks' conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a -1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape-we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.
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NASA Astrophysics Data System (ADS)
Mahan, Carolyn G.; Young, John A.; Miller, Bruce J.; Saunders, Michael C.
2015-02-01
We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)—national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks' conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a -1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape—we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.
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pcr: an R package for quality assessment, analysis and testing of qPCR data
Ahmed, Mahmoud
2018-01-01
Background Real-time quantitative PCR (qPCR) is a broadly used technique in the biomedical research. Currently, few different analysis models are used to determine the quality of data and to quantify the mRNA level across the experimental conditions. Methods We developed an R package to implement methods for quality assessment, analysis and testing qPCR data for statistical significance. Double Delta CT and standard curve models were implemented to quantify the relative expression of target genes from CT in standard qPCR control-group experiments. In addition, calculation of amplification efficiency and curves from serial dilution qPCR experiments are used to assess the quality of the data. Finally, two-group testing and linear models were used to test for significance of the difference in expression control groups and conditions of interest. Results Using two datasets from qPCR experiments, we applied different quality assessment, analysis and statistical testing in the pcr package and compared the results to the original published articles. The final relative expression values from the different models, as well as the intermediary outputs, were checked against the expected results in the original papers and were found to be accurate and reliable. Conclusion The pcr package provides an intuitive and unified interface for its main functions to allow biologist to perform all necessary steps of qPCR analysis and produce graphs in a uniform way. PMID:29576953
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Development of a hydrologic connectivity dataset for SWAT assessments in the U.S.
USDA-ARS?s Scientific Manuscript database
Model based water quality assessments are as important informer of conservation and environmental policy in the US. The recently completed national scale Conservation Effects Assessment Project (CEAP) is being repeated using newer data, greater resolution, and enhanced models. National assessment...
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A flexible framework has been created for modeling multi-dimensional hydrological and water quality processes within stormwater green infrastructures (GIs). The framework models a GI system using a set of blocks (spatial features) and connectors (interfaces) representing differen...
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Code of Federal Regulations, 2011 CFR
2011-07-01
... official charged with direct responsibility for management of an area designated as Class I under the Act.... Areawide air quality modeling analysis means an assessment on a scale that includes the entire nonattainment or maintenance area using an air quality dispersion model or photochemical grid model to determine...
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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.
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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.
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NASA Astrophysics Data System (ADS)
Zhou, L.; Baker, K. R.; Napelenok, S. L.; Elleman, R. A.; Urbanski, S. P.
2016-12-01
Biomass burning, including wildfires and prescribed burns, strongly impact the global carbon cycle and are of increasing concern due to the potential impacts on ambient air quality. This modelling study focuses on the evolution of carbonaceous compounds during a prescribed burning experiment and assesses the impacts of burning on local to regional air quality. The Community Multiscale Air Quality (CMAQ) model is used to conduct 4 and 2 km grid resolution simulations of prescribed burning experiments in southeast Washington state and western Idaho state in summer 2013. The ground and airborne measurements from the field experiment are used to evaluate the model performance in capturing surface and aloft impacts from the burning events. Phase partitioning of organic compounds in the plume are studied as it is a crucial step towards understanding the fate of carbonaceous compounds. The sensitivities of ambient concentrations and deposition to emissions are conducted for organic carbon, elemental carbon and ozone to estimate the impacts of fire on air quality.
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ERIC Educational Resources Information Center
Kaliski, Pamela; Wind, Stefanie A.; Engelhard, George, Jr.; Morgan, Deanna; Plake, Barbara; Reshetar, Rosemary
2012-01-01
The Many-Facet Rasch (MFR) Model is traditionally used to evaluate the quality of ratings on constructed response assessments; however, it can also be used to evaluate the quality of judgments from panel-based standard setting procedures. The current study illustrates the use of the MFR Model by examining the quality of ratings obtained from a…
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Subjective Values of Quality of Life Dimensions in Elderly People. A SEM Preference Model Approach
ERIC Educational Resources Information Center
Elosua, Paula
2011-01-01
This article proposes a Thurstonian model in the framework of Structural Equation Modelling (SEM) to assess preferences among quality of life dimensions for the elderly. Data were gathered by a paired comparison design in a sample comprised of 323 people aged from 65 to 94 years old. Five dimensions of quality of life were evaluated: Health,…
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Reference H Cycle 3 Stability, Control, and Flying Qualities Batch Assessments
NASA Technical Reports Server (NTRS)
Henderson, Dennis K.
1999-01-01
This work is an update of the assessment completed in February of 1996, when a preliminary assessment report was issued for the Cycle 2B simulation model. The primary purpose of the final assessment was to re-evaluate each assessment against the flight control system (FCS) requirements document using the updated model. Only a limited number of final assessments were completed due to the close proximity of the release of the Langley model and the assessment deliverable date. The assessment used the nonlinear Cycle 3 simulation model because it combines nonlinear aeroelastic (quasi-static) aerodynamic with hinge moment and rate limited control surface deflections. Both Configuration Aerodynamics (Task 32) and Flight Controls (Task 36) were funded in 1996 to conduct the final stability and control assessments of the unaugmented Reference H configuration in FY96. Because the two tasks had similar output requirements, the work was divided such that Flight Controls would be responsible for the implementation and checkout of the simulation model and Configuration Aerodynamics for writing Madab "script' files, conducting the batch assessments and writing the assessment report. Additionally, Flight Controls was to investigate control surface allocations schemes different from the baseline Reference H in an effort to fulfill flying qualities criteria.
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The difficulty in assessing errors in numerical models of air quality is a major obstacle to improving their ability to predict and retrospectively map air quality. In this paper, using simulation outputs from the Community Multi-scale Air Quality Model (CMAQ), the statistic...
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ERIC Educational Resources Information Center
Chen, Chung-Yang; Chang, Huiju; Hsu, Wen-Chin; Sheen, Gwo-Ji
2017-01-01
This paper proposes a training model for raters, with the goal to improve the intra- and inter-consistency of evaluation quality for higher education curricula. The model, termed the learning, behaviour and reaction (LBR) circular training model, is an interdisciplinary application from the business and organisational training domain. The…
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USDA-ARS?s Scientific Manuscript database
Simulation models are increasingly used to assess water quality constituent losses from agricultural systems. Mis-use often gives irrelevant or erroneous answers. The Agricultural Policy Environmental Extender (APEX) model is emerging as one of the premier modeling tools for fields, farms, and agr...
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The capability of the US EPA Models-3/Community Multiscale Air Quality (CMAQ) modeling system is extended to provide gridded ambient air quality concentration fields at fine scales. These fields will drive human exposure to air toxics and fine particulate matter (PM2.5) models...
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PROJECT SUMMARY: DEVELOPMENT OF THE VIRTUAL BEACH MODEL, PHASE I: AN EMPIRICAL MODEL
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...
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VoroMQA: Assessment of protein structure quality using interatomic contact areas.
Olechnovič, Kliment; Venclovas, Česlovas
2017-06-01
In the absence of experimentally determined protein structure many biological questions can be addressed using computational structural models. However, the utility of protein structural models depends on their quality. Therefore, the estimation of the quality of predicted structures is an important problem. One of the approaches to this problem is the use of knowledge-based statistical potentials. Such methods typically rely on the statistics of distances and angles of residue-residue or atom-atom interactions collected from experimentally determined structures. Here, we present VoroMQA (Voronoi tessellation-based Model Quality Assessment), a new method for the estimation of protein structure quality. Our method combines the idea of statistical potentials with the use of interatomic contact areas instead of distances. Contact areas, derived using Voronoi tessellation of protein structure, are used to describe and seamlessly integrate both explicit interactions between protein atoms and implicit interactions of protein atoms with solvent. VoroMQA produces scores at atomic, residue, and global levels, all in the fixed range from 0 to 1. The method was tested on the CASP data and compared to several other single-model quality assessment methods. VoroMQA showed strong performance in the recognition of the native structure and in the structural model selection tests, thus demonstrating the efficacy of interatomic contact areas in estimating protein structure quality. The software implementation of VoroMQA is freely available as a standalone application and as a web server at http://bioinformatics.lt/software/voromqa. Proteins 2017; 85:1131-1145. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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Yang, Zhongshan; Wang, Jian
2017-10-01
Air pollution in many countries is worsening with industrialization and urbanization, resulting in climate change and affecting people's health, thus, making the work of policymakers more difficult. It is therefore both urgent and necessary to establish amore scientific air quality monitoring and early warning system to evaluate the degree of air pollution objectively, and predict pollutant concentrations accurately. However, the integration of air quality assessment and air pollutant concentration prediction to establish an air quality system is not common. In this paper, we propose a new air quality monitoring and early warning system, including an assessment module and forecasting module. In the air quality assessment module, fuzzy comprehensive evaluation is used to determine the main pollutants and evaluate the degree of air pollution more scientifically. In the air pollutant concentration prediction module, a novel hybridization model combining complementary ensemble empirical mode decomposition, a modified cuckoo search and differential evolution algorithm, and an Elman neural network, is proposed to improve the forecasting accuracy of six main air pollutant concentrations. To verify the effectiveness of this system, pollutant data for two cities in China are used. The result of the fuzzy comprehensive evaluation shows that the major air pollutants in Xi'an and Jinan are PM 10 and PM 2.5 respectively, and that the air quality of Xi'an is better than that of Jinan. The forecasting results indicate that the proposed hybrid model is remarkably superior to all benchmark models on account of its higher prediction accuracy and stability. Copyright © 2017 Elsevier Inc. All rights reserved.
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Sleep duration and sleep quality are associated differently with alterations of glucose homeostasis.
Byberg, S; Hansen, A-L S; Christensen, D L; Vistisen, D; Aadahl, M; Linneberg, A; Witte, D R
2012-09-01
Studies suggest that inadequate sleep duration and poor sleep quality increase the risk of impaired glucose regulation and diabetes. However, associations with specific markers of glucose homeostasis are less well explained. The objective of this study was to explore possible associations of sleep duration and sleep quality with markers of glucose homeostasis and glucose tolerance status in a healthy population-based study sample. The study comprised 771 participants from the Danish, population-based cross-sectional 'Health2008' study. Sleep duration and sleep quality were measured by self-report. Markers of glucose homeostasis were derived from a 3-point oral glucose tolerance test and included fasting plasma glucose, 2-h plasma glucose, HbA(1c), two measures of insulin sensitivity (the insulin sensitivity index(0,120) and homeostasis model assessment of insulin sensitivity), the homeostasis model assessment of β-cell function and glucose tolerance status. Associations of sleep duration and sleep quality with markers of glucose homeostasis and tolerance were analysed by multiple linear and logistic regression. A 1-h increment in sleep duration was associated with a 0.3 mmol/mol (0.3%) decrement in HbA(1c) and a 25% reduction in the risk of having impaired glucose regulation. Further, a 1-point increment in sleep quality was associated with a 2% increase in both the insulin sensitivity index(0,120) and homeostasis model assessment of insulin sensitivity, as well as a 1% decrease in homeostasis model assessment of β-cell function. In the present study, shorter sleep duration was mainly associated with later alterations in glucose homeostasis, whereas poorer sleep quality was mainly associated with earlier alterations in glucose homeostasis. Thus, adopting healthy sleep habits may benefit glucose metabolism in healthy populations. © 2012 The Authors. Diabetic Medicine © 2012 Diabetes UK.
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Modeling the Water - Quality Effects of Changes to the Klamath River Upstream of Keno Dam, Oregon
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.
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Clinical governance is "ACE"--using the EFQM excellence model to support baseline assessment.
Holland, K; Fennell, S
2000-01-01
The introduction of clinical governance in the "new NHS" means that National Health Service (NHS) organisations are now accountable for the quality of the services they provide to their local communities. As part of the implementation of clinical governance in the NHS, Trusts and health authorities had to complete a baseline assessment of their capability and capacity by September 1999. Describes one Trust's approach to developing and implementing its baseline assessment tool, based upon its existing use of the European Foundation for Quality Management (EFQM) Excellence Model. An initial review of the process suggests that the model provides an adaptable framework for the development of a comprehensive and practical assessment tool and that self-assessment ensures ownership of action plans at service level.
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NASA Astrophysics Data System (ADS)
Irby, I.; Friedrichs, M. A. M.
2017-12-01
Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea level, and changes in precipitation, have elevated the conversation surrounding the future of the Bay's water quality. As a result, in 2010, a Total Maximum Daily Load (TMDL) was established for the Chesapeake Bay that limited nutrient and sediment input in an effort to increase dissolved oxygen. This research utilizes a multiple model approach to evaluate confidence in the estuarine water quality modeling portion of the TMDL. One of the models is then used to assess the potential impact climate change may have on the success of currently mandated nutrient reduction levels in 2050. Results demonstrate that although the models examined differ structurally and in biogeochemical complexity, they project a similar attainment of regulatory water quality standards after nutrient reduction, while also establishing that meeting water quality standards is relatively independent of hydrologic conditions. By developing a Confidence Index, this research identifies the locations and causes of greatest uncertainty in modeled projections of water quality. Although there are specific locations and times where the models disagree, this research lends an increased degree of confidence in the appropriateness of the TMDL levels and in the general impact nutrient reductions will have on Chesapeake Bay water quality under current environmental conditions. However, when examining the potential impacts of climate change, this research shows that the combined impacts of increasing temperature, sea level, and river flow negatively affect dissolved oxygen throughout the Chesapeake Bay and impact progress towards meeting the water quality standards associated with the TMDL with increased temperature as the primary culprit. These results, having been continually shared with the regulatory TMDL modelers, will aid in the decision making for the 2017 TMDL Mid-Point Assessment.
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Using aircraft and satellite observations to improve regulatory air quality models
NASA Astrophysics Data System (ADS)
Canty, T. P.; Vinciguerra, T.; Anderson, D. C.; Carpenter, S. F.; Goldberg, D. L.; Hembeck, L.; Montgomery, L.; Liu, X.; Salawitch, R. J.; Dickerson, R. R.
2014-12-01
Federal and state agencies rely on EPA approved models to develop attainment strategies that will bring states into compliance with the National Ambient Air Quality Standards (NAAQS). We will describe modifications to the Community Multi-Scale Air Quality (CMAQ) model and Comprehensive Air Quality Model with Extensions (CAMx) frameworks motivated by analysis of NASA satellite and aircraft measurements. Observations of tropospheric column NO2 from OMI have already led to the identification of an important deficiency in the chemical mechanisms used by models; data collected during the DISCOVER-AQ field campaign has been instrumental in devising an improved representation of the chemistry of nitrogen species. Our recent work has focused on the use of: OMI observations of tropospheric O3 to assess and improve the representation of boundary conditions used by AQ models, OMI NO2 to derive a top down NOx emission inventory from commercial shipping vessels that affect air quality in the Eastern U.S., and OMI HCHO to assess the C5H8 emission inventories provided by bioegenic emissions models. We will describe how these OMI-driven model improvements are being incorporated into the State Implementation Plans (SIPs) being prepared for submission to EPA in summer 2015 and how future modeling efforts may be impacted by our findings.
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Objective Video Quality Assessment Based on Machine Learning for Underwater Scientific Applications
Moreno-Roldán, José-Miguel; Luque-Nieto, Miguel-Ángel; Poncela, Javier; Otero, Pablo
2017-01-01
Video services are meant to be a fundamental tool in the development of oceanic research. The current technology for underwater networks (UWNs) imposes strong constraints in the transmission capacity since only a severely limited bitrate is available. However, previous studies have shown that the quality of experience (QoE) is enough for ocean scientists to consider the service useful, although the perceived quality can change significantly for small ranges of variation of video parameters. In this context, objective video quality assessment (VQA) methods become essential in network planning and real time quality adaptation fields. This paper presents two specialized models for objective VQA, designed to match the special requirements of UWNs. The models are built upon machine learning techniques and trained with actual user data gathered from subjective tests. Our performance analysis shows how both of them can successfully estimate quality as a mean opinion score (MOS) value and, for the second model, even compute a distribution function for user scores. PMID:28333123
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EFFECT OF QUALITY CHRONIC DISEASE MANAGEMENT FOR ALCOHOL AND DRUG DEPENDENCE ON ADDICTION OUTCOMES
Kim, Theresa W.; Saitz, Richard; Cheng, Debbie M.; Winter, Michael R; Witas, Julie; Samet, Jeffrey H.
2012-01-01
We examinedthe effect ofthe quality of primary care-basedchronic disease management (CDM)for alcohol and/or other drug (AOD) dependenceonaddiction outcomes.We assessed qualityusing 1)avisit frequencybased measure and 2) a self-reported assessment measuring alignment with the chronic care model. The visit frequency based measure had no significant association with addiction outcomes. Theself-reported measure of care - when care was at a CDM clinic - was associated with lower drug addiction severity.The self-reported assessment of care from any healthcare source (CDM clinic or elsewhere)was associated with lower alcoholaddiction severity and abstinence.These findings suggest that high quality CDM for AOD dependence may improve addiction outcomes.Quality measuresbased upon alignment with the chronic care model may better capture features of effective CDM care than a visitfrequency measure. PMID:22840687
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Measuring health care process quality with software quality measures.
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.
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Melnikow, Joy; Birch, Stephen; Slee, Christina; McCarthy, Theodore J; Helms, L Jay; Kuppermann, Miriam
2008-09-01
In cost-effectiveness analysis (CEA), the effects of health-care interventions on multiple health dimensions typically require consideration of both quantity and quality of life. To explore the impact of alternative approaches to quality-of-life adjustment using patient preferences (utilities) on the outcome of a CEA on use of tamoxifen for breast cancer risk reduction. A state transition Markov model tracked hypothetical cohorts of women who did or did not take 5 years of tamoxifen for breast cancer risk reduction. Incremental quality-adjusted effectiveness and cost-effectiveness ratios (ICERs) for models including and excluding a utility adjustment for menopausal symptoms were compared with each other and to a global utility model. Two hundred fifty-five women aged 50 and over with estimated 5-year breast cancer risk >or=1.67% participated in utility assessment interviews. Standard gamble utilities were assessed for specified tamoxifen-related health outcomes, current health, and for a global assessment of possible outcomes of tamoxifen use. Inclusion of a utility for menopausal symptoms in the outcome-specific models substantially increased the ICER; at the threshold 5-year breast cancer risk of 1.67%, tamoxifen was dominated. When a global utility for tamoxifen was used in place of outcome-specific utilities, tamoxifen was dominated under all circumstances. CEAs may be profoundly affected by the types of outcomes considered for quality-of-life adjustment and how these outcomes are grouped for utility assessment. Comparisons of ICERs across analyses must consider effects of different approaches to using utilities for quality-of-life adjustment.
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Evaluating water quality ecosystem services of wetlands under historic and future climate
NASA Astrophysics Data System (ADS)
Records, R.; Arabi, M.; Fassnacht, S. R.; Duffy, W.; Ahmadi, M.; Hegewisch, K.
2013-12-01
Potential hydrologic effects of climate change have been assessed extensively; however, possible impacts of changing climate on in-stream water quality at the watershed scale have received little study. We assessed potential impacts of climate change on water quantity and quality in the mountainous Sprague River watershed, Oregon, USA, where high total phosphorus (TP) and sediment loads are associated with lake eutrophication and mortality of endangered fish species. Additionally, we analyzed water quality impacts of wetland and riparian zone loss and gain under present-day climate and future climate scenarios. We utilized the hydrologic model Soil and Water Assessment Tool (SWAT) forced with six distinct climate scenarios derived from Coupled Model Intercomparison Project 5 (CMIP5) General Circulation Models to assess magnitude and direction of trends in streamflow, sediment and TP fluxes in the mid-21st century (2030-2059). Model results showed little significant trend in average annual streamflow under most climate scenarios, but trends in annual and monthly streamflow, sediment, and TP fluxes were more pronounced and were generally increasing. Results also suggest that future loss of present-day wetlands and riparian zones under land use or climatic change could result in substantial increases in sediment and TP loads at the Sprague River outlet.
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Life Quality of Russian Immigrants to Israel: Patterns of Success and of Unsuccess
ERIC Educational Resources Information Center
Benish-Weisman, Maya; Shye, Samuel
2011-01-01
Two different perspectives on immigration outcomes are employed and interrelated: Overall assessments of the success in immigration and systemic quality of life assessments (using SQOL model, Shye in Soc Indic Res, 21:243-378, 1989). Data were collected from a sample of 337 immigrants to Israel from the former USSR. Results reveal that quality of…
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Space-Time Fusion Under Error in Computer Model Output: An Application to Modeling Air Quality
In the last two decades a considerable amount of research effort has been devoted to modeling air quality with public health objectives. These objectives include regulatory activities such as setting standards along with assessing the relationship between exposure to air pollutan...
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Characterization of spatial variability of air pollutants in an urban setting at fine scales is critical for improved air toxics exposure assessments, for model evaluation studies and also for air quality regulatory applications. For this study, we investigate an approach that su...
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Modeled source attribution information from the Community Multiscale Air Quality model was coupled with ambient data from the 2011 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality Baltimore field study. We assess ...
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Methods are needed improve the timeliness and accuracy of recreational water‐quality assessments. Traditional culture methods require 18–24 h to obtain results and may not reflect current conditions. Predictive models, based on environmental and water quality variables, have been...
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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...
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Lee, Yi-Hsuan; von Davier, Alina A
2013-07-01
Maintaining a stable score scale over time is critical for all standardized educational assessments. Traditional quality control tools and approaches for assessing scale drift either require special equating designs, or may be too time-consuming to be considered on a regular basis with an operational test that has a short time window between an administration and its score reporting. Thus, the traditional methods are not sufficient to catch unusual testing outcomes in a timely manner. This paper presents a new approach for score monitoring and assessment of scale drift. It involves quality control charts, model-based approaches, and time series techniques to accommodate the following needs of monitoring scale scores: continuous monitoring, adjustment of customary variations, identification of abrupt shifts, and assessment of autocorrelation. Performance of the methodologies is evaluated using manipulated data based on real responses from 71 administrations of a large-scale high-stakes language assessment.
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Notification: Evaluation of EPA’s Approval Process for Air Quality Dispersion Models
Project #OPE-FY17-0016, June 5, 2017. The EPA OIG plans to begin preliminary research to assess the effectiveness of EPA's process for reviewing and approving air quality dispersion models it recommends for use.
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Kramer, Andrew A; Higgins, Thomas L; Zimmerman, Jack E
2015-02-01
To compare ICU performance using standardized mortality ratios generated by the Acute Physiology and Chronic Health Evaluation IVa and a National Quality Forum-endorsed methodology and examine potential reasons for model-based standardized mortality ratio differences. Retrospective analysis of day 1 hospital mortality predictions at the ICU level using Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum models on the same patient cohort. Forty-seven ICUs at 36 U.S. hospitals from January 2008 to May 2013. Eighty-nine thousand three hundred fifty-three consecutive unselected ICU admissions. None. We assessed standardized mortality ratios for each ICU using data for patients eligible for Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum predictions in order to compare unit-level model performance, differences in ICU rankings, and how case-mix adjustment might explain standardized mortality ratio differences. Hospital mortality was 11.5%. Overall standardized mortality ratio was 0.89 using Acute Physiology and Chronic Health Evaluation IVa and 1.07 using National Quality Forum, the latter having a widely dispersed and multimodal standardized mortality ratio distribution. Model exclusion criteria eliminated mortality predictions for 10.6% of patients for Acute Physiology and Chronic Health Evaluation IVa and 27.9% for National Quality Forum. The two models agreed on the significance and direction of standardized mortality ratio only 45% of the time. Four ICUs had standardized mortality ratios significantly less than 1.0 using Acute Physiology and Chronic Health Evaluation IVa, but significantly greater than 1.0 using National Quality Forum. Two ICUs had standardized mortality ratios exceeding 1.75 using National Quality Forum, but nonsignificant performance using Acute Physiology and Chronic Health Evaluation IVa. Stratification by patient and institutional characteristics indicated that units caring for more severely ill patients and those with a higher percentage of patients on mechanical ventilation had the most discordant standardized mortality ratios between the two predictive models. Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum models yield different ICU performance assessments due to differences in case-mix adjustment. Given the growing role of outcomes in driving prospective payment patient referral and public reporting, performance should be assessed by models with fewer exclusions, superior accuracy, and better case-mix adjustment.
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ERIC Educational Resources Information Center
Kaliski, Pamela K.; Wind, Stefanie A.; Engelhard, George, Jr.; Morgan, Deanna L.; Plake, Barbara S.; Reshetar, Rosemary A.
2013-01-01
The many-faceted Rasch (MFR) model has been used to evaluate the quality of ratings on constructed response assessments; however, it can also be used to evaluate the quality of judgments from panel-based standard setting procedures. The current study illustrates the use of the MFR model for examining the quality of ratings obtained from a standard…
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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…
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ERIC Educational Resources Information Center
Crossley, Scott A.; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S.
2016-01-01
This study investigates a novel approach to automatically assessing essay quality that combines natural language processing approaches that assess text features with approaches that assess individual differences in writers such as demographic information, standardized test scores, and survey results. The results demonstrate that combining text…
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NASA Astrophysics Data System (ADS)
Kim, S.; Seo, D. J.
2017-12-01
When water temperature (TW) increases due to changes in hydrometeorological conditions, the overall ecological conditions change in the aquatic system. The changes can be harmful to human health and potentially fatal to fish habitat. Therefore, it is important to assess the impacts of thermal disturbances on in-stream processes of water quality variables and be able to predict effectiveness of possible actions that may be taken for water quality protection. For skillful prediction of in-stream water quality processes, it is necessary for the watershed water quality models to be able to reflect such changes. Most of the currently available models, however, assume static parameters for the biophysiochemical processes and hence are not able to capture nonstationaries seen in water quality observations. In this work, we assess the performance of the Hydrological Simulation Program-Fortran (HSPF) in predicting algal dynamics following TW increase. The study area is located in the Republic of Korea where waterway change due to weir construction and drought concurrently occurred around 2012. In this work we use data assimilation (DA) techniques to update model parameters as well as the initial condition of selected state variables for in-stream processes relevant to algal growth. For assessment of model performance and characterization of temporal variability, various goodness-of-fit measures and wavelet analysis are used.
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NASA Astrophysics Data System (ADS)
Goldenberg, R.; Vigouroux, G.; Chen, Y.; Bring, A.; Kalantari, Z.; Prieto, C.; Destouni, G.
2017-12-01
The Baltic Sea, located in Northern Europe, is one of the world's largest body of brackish water, enclosed and surrounded by nine different countries. The magnitude of climate change may be particularly large in northern regions, and identifying its impacts on vulnerable inland waters and their runoff and nutrient loading to the Baltic Sea is an important and complex task. Exploration of such hydro-climatic impacts is needed to understand potential future changes in physical, ecological and water quality conditions in the regional coastal and marine waters. In this study, we investigate hydro-climatic changes and impacts on the Baltic Sea by synthesizing multi-model climate projection data from the CORDEX regional downscaling initiative (EURO- and Arctic- CORDEX domains, http://www.cordex.org/). We identify key hydro-climatic variable outputs of these models and assess model performance with regard to their projected temporal and spatial change behavior and impacts on different scales and coastal-marine parts, up to the whole Baltic Sea. Model spreading, robustness and impact implications for the Baltic Sea system are investigated for and through further use in simulations of coastal-marine hydrodynamics and water quality based on these key output variables and their change projections. Climate model robustness in this context is assessed by inter-model spreading analysis and observation data comparisons, while projected change implications are assessed by forcing of linked hydrodynamic and water quality modeling of the Baltic Sea based on relevant hydro-climatic outputs for inland water runoff and waterborne nutrient loading to the Baltic sea, as well as for conditions in the sea itself. This focused synthesis and analysis of hydro-climatically relevant output data of regional climate models facilitates assessment of reliability and uncertainty in projections of driver-impact changes of key importance for Baltic Sea physical, water quality and ecological conditions and their future evolution.
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Using climate models to estimate the quality of global observational data sets.
Massonnet, François; Bellprat, Omar; Guemas, Virginie; Doblas-Reyes, Francisco J
2016-10-28
Observational estimates of the climate system are essential to monitoring and understanding ongoing climate change and to assessing the quality of climate models used to produce near- and long-term climate information. This study poses the dual and unconventional question: Can climate models be used to assess the quality of observational references? We show that this question not only rests on solid theoretical grounds but also offers insightful applications in practice. By comparing four observational products of sea surface temperature with a large multimodel climate forecast ensemble, we find compelling evidence that models systematically score better against the most recent, advanced, but also most independent product. These results call for generalized procedures of model-observation comparison and provide guidance for a more objective observational data set selection. Copyright © 2016, American Association for the Advancement of Science.
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The Predictors of Diet Quality among Australian Children Aged 3.5 Years.
Collins, Laura J; Lacy, Kathleen E; Campbell, Karen J; McNaughton, Sarah A
2016-07-01
It is critical to promote healthy eating early in life. The aim of this study was to examine diet quality and its predictors among Australian preschool-aged children. Diet was assessed at age 3.5 years using multiple 24-hour recalls. Diet quality was assessed using an adapted version of the Revised Children's Diet Quality Index (RC-DQI). Potential predictors of diet quality were from questionnaires at age 3, 9, and 18 months and informed by the ecologic model of childhood overweight. Potential predictors included child's sex, age of introduction to solid foods, breastfeeding status, food acceptance, maternal nutrition knowledge, modeling of healthy eating, self-efficacy, education, and home food availability. Data from 244 children participating in the Melbourne Infant Feeding, Activity, and Nutrition Trial in 2008-2010 and follow-up data collection in 2011-2013 were examined. Diet quality at age 3.5 years. Bivariate logistic regression was performed to assess the relationship between diet quality and each predictor. A multivariable logistic regression model accounting for influences of covariates, treatment arm, and clustering by group tested associations between diet quality and significant predictors from bivariate analyses. RC-DQI scores had a mean±standard deviation score of 62.8±8.3 points out of a maximum of 85 points. Breastfeeding status (odds ratio [OR] 2.34, 95% CI 1.33 to 4.10) and maternal modeling of healthy eating (OR 1.75, 95% CI 1.01 to 3.03) were positively associated with RC-DQI scores. Both breastfeeding status (OR 3.09, 95% CI 1.63 to 5.85) and modeling (OR 2.01, 95% CI 1.04 to 3.88) remained positively associated with diet quality after adjustment for child age, body mass index z score, energy intake, treatment arm, and clustering. Breastfeeding status and modeling of healthy eating were independently associated with children's diet quality. Early intervention could assist mothers to practice these behaviors to provide support for improving child diet quality. Copyright © 2016 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.
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ERIC Educational Resources Information Center
Nworji, Alexander O.
2013-01-01
Most organizations spend millions of dollars due to the impact of improperly implemented database application systems as evidenced by poor data quality problems. The purpose of this quantitative study was to use, and extend, the technology acceptance model (TAM) to assess the impact of information quality and technical quality factors on database…
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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…
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The Models 3 / Community Multiscale Model for Air Quality (CMAQ) has been designed for one-atmosphere assessments for multiple pollutants including ozone (O3), particulate matter (PM10, PM2.5), and acid / nutrient deposition. In this paper we report initial results of our evalu...
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Regional air quality models are frequently used for regulatory applications to predict changes in air quality due to changes in emissions or changes in meteorology. Dynamic model evaluation is thus an important step in establishing credibility in the model predicted pollutant re...
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USDA-ARS?s Scientific Manuscript database
AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic/water quality (H/WQ) simulation components under the Object Modeling System (OMS3) environmental modeling framework. AgES-W has recently been enhanced with the addition of nitrogen (N) a...
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Remote Sensing Image Quality Assessment Experiment with Post-Processing
NASA Astrophysics Data System (ADS)
Jiang, W.; Chen, S.; Wang, X.; Huang, Q.; Shi, H.; Man, Y.
2018-04-01
This paper briefly describes the post-processing influence assessment experiment, the experiment includes three steps: the physical simulation, image processing, and image quality assessment. The physical simulation models sampled imaging system in laboratory, the imaging system parameters are tested, the digital image serving as image processing input are produced by this imaging system with the same imaging system parameters. The gathered optical sampled images with the tested imaging parameters are processed by 3 digital image processes, including calibration pre-processing, lossy compression with different compression ratio and image post-processing with different core. Image quality assessment method used is just noticeable difference (JND) subject assessment based on ISO20462, through subject assessment of the gathered and processing images, the influence of different imaging parameters and post-processing to image quality can be found. The six JND subject assessment experimental data can be validated each other. Main conclusions include: image post-processing can improve image quality; image post-processing can improve image quality even with lossy compression, image quality with higher compression ratio improves less than lower ratio; with our image post-processing method, image quality is better, when camera MTF being within a small range.
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ERIC Educational Resources Information Center
Taghdisi, M. H.; Borhani, M.; Solhi, M.; Afkari, M. E.; Hosseini, F.
2012-01-01
Background and objective: The problems caused by diabetes have direct and indirect impacts on the quality of life of diabetic patients. An increase of these problems means a decrease in a patient's quality of life. This study was conducted to assess the effect of the educational programme based on the precede model in promoting quality of life of…
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Tracking and forecasting the Nation’s water quality - Priorities and strategies for 2013-2023
Rowe, Gary L.; Gilliom, Robert J.; Woodside, Michael D.
2013-01-01
Water-quality issues facing the Nation are growing in number and complexity, and solutions are becoming more challenging and costly. Key factors that affect the quality of our drinking water supplies and ecosystem health include contaminants of human and natural origin in streams and groundwater; excess nutrients and sediment; alteration of natural streamflow; eutrophication of lakes, reservoirs, and coastal estuaries; and changes in surface and groundwater quality associated with changes in climate, land and water use, and management practices. Tracking and forecasting the Nation's water quality in the face of these and other pressing water-quality issues are important goals for 2013-2023, the third decade of the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program. In consultation with stakeholders and the National Research Council, a new strategic Science Plan has been developed that describes a strategy for building upon and enhancing assessment of the Nation's freshwater quality and aquatic ecosystems. The plan continues strategies that have been central to the NAWQA program's long-term success, but it also makes adjustments to the monitoring and modeling approaches NAWQA will use to address critical data and science information needs identified by stakeholders. This fact sheet describes surface-water and groundwater monitoring and modeling activities that will start in fiscal year 2013. It also provides examples of the types of data and information products planned for the next decade, including (1) restored monitoring for reliable and timely status and trend assessments, (2) maps and models that show the distribution of selected contaminants (such as atrazine, nitrate, and arsenic) in streams and aquifers, and (3) Web-based modeling tools that allow managers to evaluate how water quality may change in response to different scenarios of population growth, climate change, or land-use management.
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Hong, Eun-Mi; Shelton, Daniel; Pachepsky, Yakov A; Nam, Won-Ho; Coppock, Cary; Muirhead, Richard
2017-02-01
Knowledge of the microbial quality of irrigation waters is extremely limited. For this reason, the US FDA has promulgated the Produce Rule, mandating the testing of irrigation water sources for many farms. The rule requires the collection and analysis of at least 20 water samples over two to four years to adequately evaluate the quality of water intended for produce irrigation. The objective of this work was to evaluate the effect of interannual weather variability on surface water microbial quality. We used the Soil and Water Assessment Tool model to simulate E. coli concentrations in the Little Cove Creek; this is a perennial creek located in an agricultural watershed in south-eastern Pennsylvania. The model performance was evaluated using the US FDA regulatory microbial water quality metrics of geometric mean (GM) and the statistical threshold value (STV). Using the 90-year time series of weather observations, we simulated and randomly sampled the time series of E. coli concentrations. We found that weather conditions of a specific year may strongly affect the evaluation of microbial quality and that the long-term assessment of microbial water quality may be quite different from the evaluation based on short-term observations. The variations in microbial concentrations and water quality metrics were affected by location, wetness of the hydrological years, and seasonality, with 15.7-70.1% of samples exceeding the regulatory threshold. The results of this work demonstrate the value of using modeling to design and evaluate monitoring protocols to assess the microbial quality of water used for produce irrigation. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Pitfalls in statistical landslide susceptibility modelling
NASA Astrophysics Data System (ADS)
Schröder, Boris; Vorpahl, Peter; Märker, Michael; Elsenbeer, Helmut
2010-05-01
The use of statistical methods is a well-established approach to predict landslide occurrence probabilities and to assess landslide susceptibility. This is achieved by applying statistical methods relating historical landslide inventories to topographic indices as predictor variables. In our contribution, we compare several new and powerful methods developed in machine learning and well-established in landscape ecology and macroecology for predicting the distribution of shallow landslides in tropical mountain rainforests in southern Ecuador (among others: boosted regression trees, multivariate adaptive regression splines, maximum entropy). Although these methods are powerful, we think it is necessary to follow a basic set of guidelines to avoid some pitfalls regarding data sampling, predictor selection, and model quality assessment, especially if a comparison of different models is contemplated. We therefore suggest to apply a novel toolbox to evaluate approaches to the statistical modelling of landslide susceptibility. Additionally, we propose some methods to open the "black box" as an inherent part of machine learning methods in order to achieve further explanatory insights into preparatory factors that control landslides. Sampling of training data should be guided by hypotheses regarding processes that lead to slope failure taking into account their respective spatial scales. This approach leads to the selection of a set of candidate predictor variables considered on adequate spatial scales. This set should be checked for multicollinearity in order to facilitate model response curve interpretation. Model quality assesses how well a model is able to reproduce independent observations of its response variable. This includes criteria to evaluate different aspects of model performance, i.e. model discrimination, model calibration, and model refinement. In order to assess a possible violation of the assumption of independency in the training samples or a possible lack of explanatory information in the chosen set of predictor variables, the model residuals need to be checked for spatial auto¬correlation. Therefore, we calculate spline correlograms. In addition to this, we investigate partial dependency plots and bivariate interactions plots considering possible interactions between predictors to improve model interpretation. Aiming at presenting this toolbox for model quality assessment, we investigate the influence of strategies in the construction of training datasets for statistical models on model quality.
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The lack of theoretical support for using person trade-offs in QALY-type models.
Østerdal, Lars Peter
2009-10-01
Considerable support for the use of person trade-off methods to assess the quality-adjustment factor in quality-adjusted life years (QALY) models has been expressed in the literature. The WHO has occasionally used similar methods to assess the disability weights for calculation of disability-adjusted life years (DALYs). This paper discusses the theoretical support for the use of person trade-offs in QALY-type measurement of (changes in) population health. It argues that measures of this type based on such quality-adjustment factors almost always violate the Pareto principle, and so lack normative justification.
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NASA Astrophysics Data System (ADS)
Bonduel, M.; Bassier, M.; Vergauwen, M.; Pauwels, P.; Klein, R.
2017-11-01
The use of Building Information Modeling (BIM) for existing buildings based on point clouds is increasing. Standardized geometric quality assessment of the BIMs is needed to make them more reliable and thus reusable for future users. First, available literature on the subject is studied. Next, an initial proposal for a standardized geometric quality assessment is presented. Finally, this method is tested and evaluated with a case study. The number of specifications on BIM relating to existing buildings is limited. The Levels of Accuracy (LOA) specification of the USIBD provides definitions and suggestions regarding geometric model accuracy, but lacks a standardized assessment method. A deviation analysis is found to be dependent on (1) the used mathematical model, (2) the density of the point clouds and (3) the order of comparison. Results of the analysis can be graphical and numerical. An analysis on macro (building) and micro (BIM object) scale is necessary. On macro scale, the complete model is compared to the original point cloud and vice versa to get an overview of the general model quality. The graphical results show occluded zones and non-modeled objects respectively. Colored point clouds are derived from this analysis and integrated in the BIM. On micro scale, the relevant surface parts are extracted per BIM object and compared to the complete point cloud. Occluded zones are extracted based on a maximum deviation. What remains is classified according to the LOA specification. The numerical results are integrated in the BIM with the use of object parameters.
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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.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Castillo-Villar, Krystel K.; Eksioglu, Sandra; Taherkhorsandi, Milad
The production of biofuels using second-generation feedstocks has been recognized as an important alternative source of sustainable energy and its demand is expected to increase due to regulations such as the Renewable Fuel Standard. However, the pathway to biofuel industry maturity faces unique, unaddressed challenges. Here, to address this challenges, this article presents an optimization model which quantifies and controls the impact of biomass quality variability on supply chain related decisions and technology selection. We propose a two-stage stochastic programming model and associated efficient solution procedures for solving large-scale problems to (1) better represent the random nature of the biomassmore » quality (defined by moisture and ash contents) in supply chain modeling, and (2) assess the impact of these uncertainties on the supply chain design and planning. The proposed model is then applied to a case study in the state of Tennessee. Results show that high moisture and ash contents negatively impact the unit delivery cost since poor biomass quality requires the addition of quality control activities. Experimental results indicate that supply chain cost could increase as much as 27%–31% when biomass quality is poor. We assess the impact of the biomass quality on the topological supply chain. Our case study indicates that biomass quality impacts supply chain costs; thus, it is important to consider the impact of biomass quality in supply chain design and management decisions.« less
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Castillo-Villar, Krystel K.; Eksioglu, Sandra; Taherkhorsandi, Milad
2017-02-20
The production of biofuels using second-generation feedstocks has been recognized as an important alternative source of sustainable energy and its demand is expected to increase due to regulations such as the Renewable Fuel Standard. However, the pathway to biofuel industry maturity faces unique, unaddressed challenges. Here, to address this challenges, this article presents an optimization model which quantifies and controls the impact of biomass quality variability on supply chain related decisions and technology selection. We propose a two-stage stochastic programming model and associated efficient solution procedures for solving large-scale problems to (1) better represent the random nature of the biomassmore » quality (defined by moisture and ash contents) in supply chain modeling, and (2) assess the impact of these uncertainties on the supply chain design and planning. The proposed model is then applied to a case study in the state of Tennessee. Results show that high moisture and ash contents negatively impact the unit delivery cost since poor biomass quality requires the addition of quality control activities. Experimental results indicate that supply chain cost could increase as much as 27%–31% when biomass quality is poor. We assess the impact of the biomass quality on the topological supply chain. Our case study indicates that biomass quality impacts supply chain costs; thus, it is important to consider the impact of biomass quality in supply chain design and management decisions.« less
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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…
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Jeff Jenness; J. Judson Wynne
2005-01-01
In the field of spatially explicit modeling, well-developed accuracy assessment methodologies are often poorly applied. Deriving model accuracy metrics have been possible for decades, but these calculations were made by hand or with the use of a spreadsheet application. Accuracy assessments may be useful for: (1) ascertaining the quality of a model; (2) improving model...
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A simple, semi-prescriptive self-assessment model for TQM.
Warwood, Stephen; Antony, Jiju
2003-01-01
This article presents a simple, semi-prescriptive self-assessment model for use in industry as part of a continuous improvement program such as Total Quality Management (TQM). The process by which the model was constructed started with a review of the available literature in order to research TQM success factors. Next, postal surveys were conducted by sending questionnaires to the winning organisations of the Baldrige and European Quality Awards and to a preselected group of enterprising UK organisations. From the analysis of this data, the self-assessment model was constructed to help organisations in their quest for excellence. This work confirmed the findings from the literature, that there are key factors that contribute to the successful implementation of TQM and these have different levels of importance. These key factors, in order of importance, are: effective leadership, the impact of other quality-related programs, measurement systems, organisational culture, education and training, the use of teams, efficient communications, active empowerment of the workforce, and a systems infrastructure to support the business and customer-focused processes. This analysis, in turn, enabled the design of a self-assessment model that can be applied within any business setting. Further work should include the testing and review of this model to ascertain its suitability and effectiveness within industry today.
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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.
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A Review of Surface Water Quality Models
Li, Shibei; Jia, Peng; Qi, Changjun; Ding, Feng
2013-01-01
Surface water quality models can be useful tools to simulate and predict the levels, distributions, and risks of chemical pollutants in a given water body. The modeling results from these models under different pollution scenarios are very important components of environmental impact assessment and can provide a basis and technique support for environmental management agencies to make right decisions. Whether the model results are right or not can impact the reasonability and scientificity of the authorized construct projects and the availability of pollution control measures. We reviewed the development of surface water quality models at three stages and analyzed the suitability, precisions, and methods among different models. Standardization of water quality models can help environmental management agencies guarantee the consistency in application of water quality models for regulatory purposes. We concluded the status of standardization of these models in developed countries and put forward available measures for the standardization of these surface water quality models, especially in developing countries. PMID:23853533
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USDA-ARS?s Scientific Manuscript database
Water quality models address nonpoint source pollution from agricultural land at a range of scales and complexities and involve a variety of input parameters. It is often difficult for conservationists and stakeholders to understand and reconcile water quality results from different models. However,...
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Assessing the Quality of the Learning Outcome in Vocational Education: The Expero Model
ERIC Educational Resources Information Center
Cervai, Sara; Cian, Luca; Berlanga, Alicia; Borelli, Massimo; Kekale, Tauno
2013-01-01
Purpose: This paper aims to present an innovative model to evaluate the quality of the learning outcome in vocational education and training (VET) considering a wide approach that includes, in particular, stakeholders' expectations and perceptions. Design/methodology/approach: The Expero model was implemented in various kinds of vocational schools…
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NASA Astrophysics Data System (ADS)
Gan, Chuen-Meei
Air quality model forecasts from Weather Research and Forecast (WRF) and Community Multiscale Air Quality (CMAQ) are often used to support air quality applications such as regulatory issues and scientific inquiries on atmospheric science processes. In urban environments, these models become more complex due to the inherent complexity of the land surface coupling and the enhanced pollutants emissions. This makes it very difficult to diagnose the model, if the surface parameter forecasts such as PM2.5 (particulate matter with aerodynamic diameter less than 2.5 microm) are not accurate. For this reason, getting accurate boundary layer dynamic forecasts is as essential as quantifying realistic pollutants emissions. In this thesis, we explore the usefulness of vertical sounding measurements on assessing meteorological and air quality forecast models. In particular, we focus on assessing the WRF model (12km x 12km) coupled with the CMAQ model for the urban New York City (NYC) area using multiple vertical profiling and column integrated remote sensing measurements. This assessment is helpful in probing the root causes for WRF-CMAQ overestimates of surface PM2.5 occurring both predawn and post-sunset in the NYC area during the summer. In particular, we find that the significant underestimates in the WRF PBL height forecast is a key factor in explaining this anomaly. On the other hand, the model predictions of the PBL height during daytime when convective heating dominates were found to be highly correlated to lidar derived PBL height with minimal bias. Additional topics covered in this thesis include mathematical method using direct Mie scattering approach to convert aerosol microphysical properties from CMAQ into optical parameters making direct comparisons with lidar and multispectral radiometers feasible. Finally, we explore some tentative ideas on combining visible (VIS) and mid-infrared (MIR) sensors to better separate aerosols into fine and coarse modes.
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NASA Astrophysics Data System (ADS)
Toussaint, F.; Hoeck, H.; Stockhause, M.; Lautenschlager, M.
2014-12-01
The classical goals of a quality assessment system in the data life cycle are (1) to encourage data creators to improve their quality assessment procedures to reach the next quality level and (2) enable data consumers to decide, whether a dataset has a quality that is sufficient for usage in the target application, i.e. to appraise the data usability for their own purpose.As the data volumes of projects and the interdisciplinarity of data usage grow, the need for homogeneous structure and standardised notation of data and metadata increases. This third aspect is especially valid for the data repositories, as they manage data through machine agents. So checks for homogeneity and consistency in early parts of the workflow become essential to cope with today's data volumes.Selected parts of the workflow in the model intercomparison project CMIP5 and the archival of the data for the interdiscipliary user community of the IPCC-DDC AR5 and the associated quality checks are reviewed. We compare data and metadata checks and relate different types of checks to their positions in the data life cycle.The project's data citation approach is included in the discussion, with focus on temporal aspects of the time necessary to comply with the project's requirements for formal data citations and the demand for the availability of such data citations.In order to make different quality assessments of projects comparable, WDCC developed a generic Quality Assessment System. Based on the self-assessment approach of a maturity matrix, an objective and uniform quality level system for all data at WDCC is derived which consists of five maturity quality levels.
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Assessment of Reference Height Models on Quality of Tandem-X dem
NASA Astrophysics Data System (ADS)
Mirzaee, S.; Motagh, M.; Arefi, H.
2015-12-01
The aim of this study is to investigate the effect of various Global Digital Elevation Models (GDEMs) in producing high-resolution topography model using TanDEM-X (TDX) Coregistered Single Look Slant Range Complex (CoSSC) images. We selected an image acquired on Jun 12th, 2012 over Doroud region in Lorestan, west of Iran and used 4 external digital elevation models in our processing including DLR/ASI X-SAR DEM (SRTM-X, 30m resolution), ASTER GDEM Version 2 (ASTER-GDEMV2, 30m resolution), NASA SRTM Version 4 (SRTM-V4, 90m resolution), and a local photogrammetry-based DEM prepared by National Cartographic Center (NCC DEM, 10m resolution) of Iran. InSAR procedure for DEM generation was repeated four times with each of the four external height references. The quality of each external DEM was initially assessed using ICESat filtered points. Then, the quality of, each TDX-based DEM was assessed using the more precise external DEM selected in the previous step. Results showed that both local (NCC) DEM and SRTM X-band performed the best (RMSE< 9m) for TDX-DEM generation. In contrast, ASTER GDEM v2 and SRTM C-band v4 showed poorer quality.
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Wilcox, S.; Andreas, A.
2010-03-16
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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Stoffel, T.; Andreas, A.
2010-04-26
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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Wilcox, S.; Andreas, A.
2010-07-13
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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Wilcox, S.; Andreas, A.
2012-11-03
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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Solar Resource & Meteorological Assessment Project (SOLRMAP): Sun Spot Two; Swink, Colorado (Data)
Wilcox, S.; Andreas, A.
2010-11-10
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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Wilcox, S.; Andreas, A.
2010-07-14
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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Wilcox, S.; Andreas, A.
2009-07-22
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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Wilcox, S.; Andreas, A.
2010-11-03
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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What do we know about managing Dupuytren's disease cost-effectively?
Dritsaki, Melina; Rivero-Arias, Oliver; Gray, Alastair; Ball, Catherine; Nanchahal, Jagdeep
2018-01-25
Dupuytren's disease (DD) is a common and progressive, fibroproliferative disorder of the palmar and digital fascia of the hand. Various treatments have been recommended for advanced disease or to retard progression of early disease and to prevent deterioration of the finger contracture and quality of life. Recent studies have tried to evaluate the clinical and cost-effectiveness of therapies for DD, but there is currently no systematic assessment and appraisal of the economic evaluations. A systematic literature review was conducted, following PRISMA guidelines, to identify studies reporting economic evaluations of interventions for managing DD. Databases searched included the Ovid MEDLINE/Embase (without time restriction), National Health Service (NHS) Economic Evaluation Database (all years) and the National Institute for Health Research (NIHR) Journals Library) Health Technology Assessment (HTA). Cost-effectiveness analyses of treating DD were identified and their quality was assessed using the CHEERS assessment tool for quality of reporting and Phillips checklist for model evaluation. A total of 103 studies were screened, of which 4 met the study inclusion criteria. Two studies were from the US, one from the UK and one from Canada. They all assessed the same interventions for advanced DD, namely collagenase Clostridium histolyticum injection, percutaneous needle fasciotomy and partial fasciectomy. All studies conducting a cost-utility analysis, two implemented a decision analytic model and two a Markov model approach. None of them were based on a single randomised controlled trial, but rather synthesised evidence from various sources. Studies varied in their time horizon, sources of utility estimates and perspective of analysis. The overall quality of study reporting was good based on the CHEERS checklist. The quality of the model reporting in terms of model structure, data synthesis and model consistency varied across the included studies. Cost-effectiveness analyses for patients with advanced DD are limited and have applied different approaches with respect to modelling. Future studies should improve the way they are conducted and report their findings according to established guidance for conducting economic modelling of health care technologies. The protocol was registered ( CRD42016032989 ; date 08/01/2016) with the PROSPERO international prospective register of systematic reviews.
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Holcomb, David A; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R
2018-06-25
Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modeled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was ≥90%, ≤10%, or >10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Longgao; Yang, Xiaoyan; School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116
The implementation of land use planning (LUP) has a large impact on environmental quality. There lacks a widely accepted and consolidated approach to assess the LUP environmental impact using Strategic Environmental Assessment (SEA). In this paper, we developed a state-impact-state (SIS) model employed in the LUP environmental impact assessment (LUPEA). With the usage of Matter-element (ME) and Extenics method, the methodology based on the SIS model was established and applied in the LUPEA of Zoucheng County, China. The results show that: (1) this methodology provides an intuitive and easy understanding logical model for both the theoretical analysis and application ofmore » LUPEA; (2) the spatial multi-temporal assessment from base year, near-future year to planning target year suggests the positive impact on the environmental quality in the whole County despite certain environmental degradation in some towns; (3) besides the spatial assessment, other achievements including the environmental elements influenced by land use and their weights, the identification of key indicators in LUPEA, and the appropriate environmental mitigation measures were obtained; and (4) this methodology can be used to achieve multi-temporal assessment of LUP environmental impact of County or Town level in other areas. - Highlights: • A State-Impact-State model for Land Use Planning Environmental Assessment (LUPEA). • Matter-element (ME) and Extenics methods were embedded in the LUPEA. • The model was applied to the LUPEA of Zoucheng County. • The assessment shows improving environment quality since 2000 in Zoucheng County. • The method provides a useful tool for the LUPEA in the county level.« less
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NASA Astrophysics Data System (ADS)
Leitão, João P.; Moy de Vitry, Matthew; Scheidegger, Andreas; Rieckermann, Jörg
2016-04-01
Precise and detailed digital elevation models (DEMs) are essential to accurately predict overland flow in urban areas. Unfortunately, traditional sources of DEM, such as airplane light detection and ranging (lidar) DEMs and point and contour maps, remain a bottleneck for detailed and reliable overland flow models, because the resulting DEMs are too coarse to provide DEMs of sufficient detail to inform urban overland flows. Interestingly, technological developments of unmanned aerial vehicles (UAVs) suggest that they have matured enough to be a competitive alternative to satellites or airplanes. However, this has not been tested so far. In this study we therefore evaluated whether DEMs generated from UAV imagery are suitable for urban drainage overland flow modelling. Specifically, 14 UAV flights were conducted to assess the influence of four different flight parameters on the quality of generated DEMs: (i) flight altitude, (ii) image overlapping, (iii) camera pitch, and (iv) weather conditions. In addition, we compared the best-quality UAV DEM to a conventional lidar-based DEM. To evaluate both the quality of the UAV DEMs and the comparison to lidar-based DEMs, we performed regression analysis on several qualitative and quantitative metrics, such as elevation accuracy, quality of object representation (e.g. buildings, walls and trees) in the DEM, which were specifically tailored to assess overland flow modelling performance, using the flight parameters as explanatory variables. Our results suggested that, first, as expected, flight altitude influenced the DEM quality most, where lower flights produce better DEMs; in a similar fashion, overcast weather conditions are preferable, but weather conditions and other factors influence DEM quality much less. Second, we found that for urban overland flow modelling, the UAV DEMs performed competitively in comparison to a traditional lidar-based DEM. An important advantage of using UAVs to generate DEMs in urban areas is their flexibility that enables more frequent, local, and affordable elevation data updates, allowing, for example, to capture different tree foliage conditions.
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Kaale, Eliangiringa; Hope, Samuel M; Jenkins, David; Layloff, Thomas
2016-01-01
To assess the quality of cotrimoxazole tablets produced by a Tanzanian manufacturer by a newly instituted quality assurance programme. Tablets underwent a diffuse reflectance spectroscopy procedure with periodic quality assessment confirmation by assay and dissolution testing using validated HPTLC techniques (including weight variation and disintegration evaluations). Based on results from the primary test methods, the first group of product was <80% compliant, whereas subsequent groups reached >99% compliance. This approach provides a model for rapidly assuring product quality of future procurements of other products that is more cost-effective than traditional pharmaceutical testing techniques. © 2015 John Wiley & Sons Ltd.
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Assessment and Improvement of GOCE based Global Geopotential Models Using Wavelet Decomposition
NASA Astrophysics Data System (ADS)
Erol, Serdar; Erol, Bihter; Serkan Isik, Mustafa
2016-07-01
The contribution of recent Earth gravity field satellite missions, specifically GOCE mission, leads significant improvement in quality of gravity field models in both accuracy and resolution manners. However the performance and quality of each released model vary not only depending on the spatial location of the Earth but also the different bands of the spectral expansion. Therefore the assessment of the global model performances with validations using in situ-data in varying territories on the Earth is essential for clarifying their exact performances in local. Beside of this, their spectral evaluation and quality assessment of the signal in each part of the spherical harmonic expansion spectrum is essential to have a clear decision for the commission error content of the model and determining its optimal degree, revealed the best results, as well. The later analyses provide also a perspective and comparison on the global behavior of the models and opportunity to report the sequential improvement of the models depending on the mission developments and hence the contribution of the new data of missions. In this study a review on spectral assessment results of the recently released GOCE based global geopotential models DIR-R5, TIM-R5 with the enhancement using EGM2008, as reference model, in Turkey, versus the terrestrial data is provided. Beside of reporting the GOCE mission contribution to the models in Turkish territory, the possible improvement in the spectral quality of these models, via decomposition that are highly contaminated by noise, is purposed. In the analyses the motivation is on achieving an optimal amount of improvement that rely on conserving the useful component of the GOCE signal as much as possible, while fusing the filtered GOCE based models with EGM2008 in the appropriate spectral bands. The investigation also contain the assessment of the coherence and the correlation between the Earth gravity field parameters (free-air gravity anomalies and geoid undulations), derived from the validated geopotential models and terrestrial data (GPS/leveling, terrestrial gravity observations, DTM etc.), as well as the WGM2012 products. In the conclusion, with the numerical results, the performance of the assessed models are clarified in Turkish territory and the potential of the Wavelet decomposition in the improvement of the geopotential models is verified.
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Outcomes-Balanced Framework for Emergency Management: A Predictive Model for Preparedness
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
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Learning Receptive Fields and Quality Lookups for Blind Quality Assessment of Stereoscopic Images.
Shao, Feng; Lin, Weisi; Wang, Shanshan; Jiang, Gangyi; Yu, Mei; Dai, Qionghai
2016-03-01
Blind quality assessment of 3D images encounters more new challenges than its 2D counterparts. In this paper, we propose a blind quality assessment for stereoscopic images by learning the characteristics of receptive fields (RFs) from perspective of dictionary learning, and constructing quality lookups to replace human opinion scores without performance loss. The important feature of the proposed method is that we do not need a large set of samples of distorted stereoscopic images and the corresponding human opinion scores to learn a regression model. To be more specific, in the training phase, we learn local RFs (LRFs) and global RFs (GRFs) from the reference and distorted stereoscopic images, respectively, and construct their corresponding local quality lookups (LQLs) and global quality lookups (GQLs). In the testing phase, blind quality pooling can be easily achieved by searching optimal GRF and LRF indexes from the learnt LQLs and GQLs, and the quality score is obtained by combining the LRF and GRF indexes together. Experimental results on three publicly 3D image quality assessment databases demonstrate that in comparison with the existing methods, the devised algorithm achieves high consistent alignment with subjective assessment.
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Barker, S Fiona; Amoah, Philip; Drechsel, Pay
2014-07-15
With a rapidly growing urban population in Kumasi, Ghana, the consumption of street food is increasing. Raw salads, which often accompany street food dishes, are typically composed of perishable vegetables that are grown in close proximity to the city using poor quality water for irrigation. This study assessed the risk of gastroenteritis illness (caused by rotavirus, norovirus and Ascaris lumbricoides) associated with the consumption of street food salads using Quantitative Microbial Risk Assessment (QMRA). Three different risk assessment models were constructed, based on availability of microbial concentrations: 1) Water - starting from irrigation water quality, 2) Produce - starting from the quality of produce at market, and 3) Street - using microbial quality of street food salad. In the absence of viral concentrations, published ratios between faecal coliforms and viruses were used to estimate the quality of water, produce and salad, and annual disease burdens were determined. Rotavirus dominated the estimates of annual disease burden (~10(-3)Disability Adjusted Life Years per person per year (DALYs pppy)), although norovirus also exceeded the 10(-4)DALY threshold for both Produce and Street models. The Water model ignored other on-farm and post-harvest sources of contamination and consistently produced lower estimates of risk; it likely underestimates disease burden and therefore is not recommended. Required log reductions of up to 5.3 (95th percentile) for rotavirus were estimated for the Street model, demonstrating that significant interventions are required to protect the health and safety of street food consumers in Kumasi. Estimates of virus concentrations were a significant source of model uncertainty and more data on pathogen concentrations is needed to refine QMRA estimates of disease burden. Copyright © 2014 Elsevier B.V. All rights reserved.
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Hatz, Maximilian H M; Leidl, Reiner; Yates, Nichola A; Stollenwerk, Björn
2014-04-01
Thrombosis inhibitors can be used to treat acute coronary syndromes (ACS). However, there are various alternative treatment strategies, of which some have been compared using health economic decision models. To assess the quality of health economic decision models comparing thrombosis inhibitors in patients with ACS undergoing percutaneous coronary intervention, and to identify areas for quality improvement. The literature databases MEDLINE, EMBASE, EconLit, National Health Service Economic Evaluation Database (NHS EED), Database of Abstracts of Reviews of Effects (DARE) and Health Technology Assessment (HTA). A review of the quality of health economic decision models was conducted by two independent reviewers, using the Philips checklist. Twenty-one relevant studies were identified. Differences were apparent regarding the model type (six decision trees, four Markov models, eight combinations, three undefined models), the model structure (types of events, Markov states) and the incorporation of data (efficacy, cost and utility data). Critical issues were the absence of particular events (e.g. thrombocytopenia, stroke) and questionable usage of utility values within some studies. As we restricted our search to health economic decision models comparing thrombosis inhibitors, interesting aspects related to the quality of studies of adjacent medical areas that compared stents or procedures could have been missed. This review identified areas where recommendations are indicated regarding the quality of future ACS decision models. For example, all critical events and relevant treatment options should be included. Models also need to allow for changing event probabilities to correctly reflect ACS and to incorporate appropriate, age-specific utility values and decrements when conducting cost-utility analyses.
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Saengsiri, Aem-orn; Hacker, Eileen Danaher
2015-01-01
Health-related quality of life is an important clinical outcome to measure in patients with cardiovascular disease. International nurse researchers with limited English skills and novice cardiovascular nurse researchers face numerous challenges when conducting quality of life research because of the conceptual ambiguity of the construct and subsequent operationalization issues as well as difficulty identifying conceptual models to guide their quality of life research. The overall purpose of this article was to provide guidance to cardiovascular nurse researchers (using Thailand as an example) who are interested in examining quality of life in their native country but lack access to quality of life conceptual models and instruments because of language barriers. This article will examine definitions of health-related quality of life, selection of a conceptual model to guide quality of life research, use of the conceptual model to guide selection and measurement of variables, and translation of instruments when reliable and valid instruments are not available in the native language. Ferrans' definition of quality of life and the Wilson and Cleary Revised Model of Patient Outcomes were selected to guide the research. Selection of variables/instruments flowed directly from the conceptualization of constructs identified in this model. Our study, "Examining HRQOL in Thai People With Coronary Artery Disease Following Percutaneous Coronary Intervention," serves as an exemplar to illustrate the conceptual and operational challenges associated with conducting quality of life research in Thailand. The ultimate goal of cardiovascular nursing is to help patients achieve their optimal quality of life. Thai clinicians implementing quality of life assessment in clinical practice face similar conceptual and operationalization issues, especially when using instruments that are not well established or easily interpreted. Although quality of life assessment in clinical practice improves communication between patients and healthcare providers, clear guidelines for making changes to treatment strategies based on changes in quality of life must be established.
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Variability in individual assessment behaviour and its implications for collective decision-making.
O'Shea-Wheller, Thomas A; Masuda, Naoki; Sendova-Franks, Ana B; Franks, Nigel R
2017-02-08
Self-organized systems of collective behaviour have been demonstrated in a number of group-living organisms. There is, however, less research relating to how variation in individual assessments may facilitate group decision-making. Here, we investigate this using the decentralized system of collective nest choice behaviour employed by the ant Temnothorax albipennis, combining experimental results with computational modelling. In experiments, isolated workers of this species were allowed to investigate new nest sites of differing quality, and it was found that for any given nest quality, there was wide variation among individuals in the durations that they spent within each nest site. Additionally, individual workers were consistent in spending more time in nest sites of higher quality, and less time in those of lower quality. Hence, the time spent in a new nest site must have included an assessment of nest quality. As nest site visit durations (henceforth termed assessment durations) are linked to recruitment, it is possible that the variability we observed may influence the collective decision-making process of colonies. Thus, we explored this further using a computational model of nest site selection, and found that heterogeneous nest assessments conferred a number of potential benefits. Furthermore, our experiments showed that nest quality assessments were flexible, being influenced by experience of prior options. Our findings help to elucidate the potential mechanisms underlying group behaviour, and highlight the importance of heterogeneity among individuals, rather than precise calibration, in shaping collective decision-making. © 2017 The Author(s).
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Assessing Distributed Leadership for Learning and Teaching Quality: A Multi-Institutional Study
ERIC Educational Resources Information Center
Carbone, Angela; Evans, Julia; Ross, Bella; Drew, Steve; Phelan, Liam; Lindsay, Katherine; Cottman, Caroline; Stoney, Susan; Ye, Jing
2017-01-01
Distributed leadership has been explored internationally as a leadership model that will promote and advance excellence in learning and teaching in higher education. This paper presents an assessment of how effectively distributed leadership was enabled at five Australian institutions implementing a collaborative teaching quality development…
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AIR QUALITY ASSESSMENT IN USA - TECHNICAL TOOLS AND LINKAGE TO HUMAN HEALTH
This is an invited presentation to the Air4EU Final Conference to held in Prague, Czech Republic, on 10 November 2006. Air4EU is a jointly-sponsored, three-year European effort to provide recommendations on air quality assessment by monitoring and modeling for regulated pollutan...
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Quality Assurance Testing of Version 1.3 of U.S. EPA Benchmark Dose Software (Presentation)
EPA benchmark dose software (BMDS) issued to evaluate chemical dose-response data in support of Agency risk assessments, and must therefore be dependable. Quality assurance testing methods developed for BMDS were designed to assess model dependability with respect to curve-fitt...
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Rapid Training System Self-Assessment
ERIC Educational Resources Information Center
Flesher, Jeff
2007-01-01
A systematic self-assessment mirrors quality system and certification models, thus making a strong argument for high-quality design, control, and management of the training function. Accomplished for the ongoing betterment of the function, not as a summative judgment of conformance, it discovers strengths and weaknesses and results in a common…
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Using Data Mining for Wine Quality Assessment
NASA Astrophysics Data System (ADS)
Cortez, Paulo; Teixeira, Juliana; Cerdeira, António; Almeida, Fernando; Matos, Telmo; Reis, José
Certification and quality assessment are crucial issues within the wine industry. Currently, wine quality is mostly assessed by physicochemical (e.g alcohol levels) and sensory (e.g. human expert evaluation) tests. In this paper, we propose a data mining approach to predict wine preferences that is based on easily available analytical tests at the certification step. A large dataset is considered with white vinho verde samples from the Minho region of Portugal. Wine quality is modeled under a regression approach, which preserves the order of the grades. Explanatory knowledge is given in terms of a sensitivity analysis, which measures the response changes when a given input variable is varied through its domain. Three regression techniques were applied, under a computationally efficient procedure that performs simultaneous variable and model selection and that is guided by the sensitivity analysis. The support vector machine achieved promising results, outperforming the multiple regression and neural network methods. Such model is useful for understanding how physicochemical tests affect the sensory preferences. Moreover, it can support the wine expert evaluations and ultimately improve the production.
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"Total Deposition (TDEP) Maps" | Science Inventory | US EPA
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.
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Soil quality assessment using weighted fuzzy association rules
Xue, Yue-Ju; Liu, Shu-Guang; Hu, Yue-Ming; Yang, Jing-Feng
2010-01-01
Fuzzy association rules (FARs) can be powerful in assessing regional soil quality, a critical step prior to land planning and utilization; however, traditional FARs mined from soil quality database, ignoring the importance variability of the rules, can be redundant and far from optimal. In this study, we developed a method applying different weights to traditional FARs to improve accuracy of soil quality assessment. After the FARs for soil quality assessment were mined, redundant rules were eliminated according to whether the rules were significant or not in reducing the complexity of the soil quality assessment models and in improving the comprehensibility of FARs. The global weights, each representing the importance of a FAR in soil quality assessment, were then introduced and refined using a gradient descent optimization method. This method was applied to the assessment of soil resources conditions in Guangdong Province, China. The new approach had an accuracy of 87%, when 15 rules were mined, as compared with 76% from the traditional approach. The accuracy increased to 96% when 32 rules were mined, in contrast to 88% from the traditional approach. These results demonstrated an improved comprehensibility of FARs and a high accuracy of the proposed method.
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Code of Federal Regulations, 2010 CFR
2010-07-01
... manager means the Federal agency or the Federal official charged with direct responsibility for management... requirements of the Act. Areawide air quality modeling analysis means an assessment on a scale that includes the entire nonattainment or maintenance area which uses an air quality dispersion model to determine...
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QUANTIFYING SUBGRID POLLUTANT VARIABILITY IN EULERIAN AIR QUALITY MODELS
In order to properly assess human risk due to exposure to hazardous air pollutants or air toxics, detailed information is needed on the location and magnitude of ambient air toxic concentrations. Regional scale Eulerian air quality models are typically limited to relatively coar...
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Shomaker, Lauren B.; Furman, Wyndol
2010-01-01
This study examined how current parent-adolescent relationship qualities and adolescents’ representations of relationships with parents were related to friendship interactions in 200 adolescent-close friend dyads. Adolescents and friends were observed discussing problems during a series of structured tasks. Negative interactions with mothers were significantly related to adolescents’ greater conflict with friends, poorer focus on tasks, and poorer communication skills. Security of working models (as assessed by interview) was significantly associated with qualities of friendship interactions, whereas security of attachment styles (as assessed by questionnaire) was not. More dismissing (vs. secure) working models were associated with poorer focus on problem discussions and weaker communication skills with friends, even after accounting for gender differences and current parent-adolescent relationship qualities. We discuss possible mechanisms for the observed links between dimensions of parent-adolescent relationships and friendships. We also consider methodological and conceptual differences between working model and style measures of attachment representations. PMID:20174459
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Turrini, Enrico; Carnevale, Claudio; Finzi, Giovanna; Volta, Marialuisa
2018-04-15
This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO 2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy. Copyright © 2017 Elsevier B.V. All rights reserved.
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Assessment of CT image quality using a Bayesian approach
NASA Astrophysics Data System (ADS)
Reginatto, M.; Anton, M.; Elster, C.
2017-08-01
One of the most promising approaches for evaluating CT image quality is task-specific quality assessment. This involves a simplified version of a clinical task, e.g. deciding whether an image belongs to the class of images that contain the signature of a lesion or not. Task-specific quality assessment can be done by model observers, which are mathematical procedures that carry out the classification task. The most widely used figure of merit for CT image quality is the area under the ROC curve (AUC), a quantity which characterizes the performance of a given model observer. In order to estimate AUC from a finite sample of images, different approaches from classical statistics have been suggested. The goal of this paper is to introduce task-specific quality assessment of CT images to metrology and to propose a novel Bayesian estimation of AUC for the channelized Hotelling observer (CHO) applied to the task of detecting a lesion at a known image location. It is assumed that signal-present and signal-absent images follow multivariate normal distributions with the same covariance matrix. The Bayesian approach results in a posterior distribution for the AUC of the CHO which provides in addition a complete characterization of the uncertainty of this figure of merit. The approach is illustrated by its application to both simulated and experimental data.
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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.
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Juraskova, Ilona; Bonner, Carissa; Bell, Melanie L; Sharpe, Louise; Robertson, Rosalind; Butow, Phyllis
2012-11-01
Women with early stage cervical and endometrial cancer may experience complex posttreatment changes to their sexual function, but clinical practice and past research have focused more on the quantity than the perceived quality of sexual life. The aims of this prospective study were to explore the following: (i) the relative importance of quantity vs. quality of sexual life over the first year posttreatment; (ii) the psychological and sexual predictors of overall sexual function; and (iii) the relationship between sexual function and quality of life (QoL). Fifty-three cancer patients completed standardized measures at baseline, with follow-up at 6 and 12 months posttreatment. Analyses were based on prespecified linear mixed models with overall sexual function and QoL as outcomes, and quality and quantity of sexual life, anxiety, and depression as the main predictors of interest. Radiotherapy, age, and relationship satisfaction were controlled for as potential confounders. Derogatis Sexual Functioning Inventory subscales to assess quantity (Drive) and quality (Satisfaction) of sexual life, and overall sexual function (Global Sexual Satisfaction Index); Functional Assessment of Cancer Therapy--General to assess QoL; Hospital Anxiety and Depression Scale to assess psychological distress; and Relationship Satisfaction Interaction Scale to assess relationship satisfaction. The models demonstrated that: (i) overall sexual function was predicted more strongly by the perceived quality than the quantity of sexual interactions, (ii) a small change in perceived quality had a large impact on overall sexual function, and (iii) overall sexual function was a predictor of QoL. This study found that quality rather than quantity of sexual life is the best predictor of overall sexual function among women treated for early stage cervical and endometrial cancer, indicating the importance of including quality indices in posttreatment sexual assessment in clinical practice and research studies. © 2012 International Society for Sexual Medicine.
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Papageorgiou, Spyridon N; Papadopoulos, Moschos A; Athanasiou, Athanasios E
2014-02-01
Ideally meta-analyses (MAs) should consolidate the characteristics of orthodontic research in order to produce an evidence-based answer. However severe flaws are frequently observed in most of them. The aim of this study was to evaluate the statistical methods, the methodology, and the quality characteristics of orthodontic MAs and to assess their reporting quality during the last years. Electronic databases were searched for MAs (with or without a proper systematic review) in the field of orthodontics, indexed up to 2011. The AMSTAR tool was used for quality assessment of the included articles. Data were analyzed with Student's t-test, one-way ANOVA, and generalized linear modelling. Risk ratios with 95% confidence intervals were calculated to represent changes during the years in reporting of key items associated with quality. A total of 80 MAs with 1086 primary studies were included in this evaluation. Using the AMSTAR tool, 25 (27.3%) of the MAs were found to be of low quality, 37 (46.3%) of medium quality, and 18 (22.5%) of high quality. Specific characteristics like explicit protocol definition, extensive searches, and quality assessment of included trials were associated with a higher AMSTAR score. Model selection and dealing with heterogeneity or publication bias were often problematic in the identified reviews. The number of published orthodontic MAs is constantly increasing, while their overall quality is considered to range from low to medium. Although the number of MAs of medium and high level seems lately to rise, several other aspects need improvement to increase their overall quality.
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Mataria, Awad; Luchini, Stéphane; Daoud, Yousef; Moatti, Jean-Paul
2007-10-01
This paper proposes a new methodology to assess demand and price-elasticity for health care, based on patients' stated willingness to pay (WTP) values for certain aspects of health care quality improvements. A conceptual analysis of how respondents consider contingent valuation (CV) questions allowed us to specify a probability density function of stated WTP values, and consequently, to model a demand function for quality-improved health care, using a parametric survival approach. The model was empirically estimated using a CV study intended to assess patients' values for improving the quality of primary health care (PHC) services in Palestine. A random sample of 499 individuals was interviewed following medical consultation in four PHC centers. Quality was assessed using a multi-attribute approach; and respondents valued seven specific quality improvements using a decomposed valuation scenario and a payment card elicitation technique. Our results suggest an inelastic demand at low user fees levels, and when the price-increase is accompanied with substantial quality-improvements. Nevertheless, demand becomes more and more elastic if user fees continue to rise. On the other hand, patients' reactions to price-increase turn out to depend on their level of income. Our results can be used to design successful health care financing strategies that include a consideration of patients' preferences and financial capacities. John Wiley & Sons, Ltd.
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This paper examines the operational performance of the Community Multiscale Air Quality (CMAQ) model simulations for 2002 - 2006 using both 36-km and 12-km horizontal grid spacing, with a primary focus on the performance of the CMAQ model in predicting wet deposition of sulfate (...
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ERIC Educational Resources Information Center
Nur, Yusuf Ahmed; Grabner-Hagen, Melissa; Saam, Julie Reinhardt
2013-01-01
The metric for assessing the quality of a university within a traditional Western setting is well established. Evaluation of higher education institutions within developing countries, however, is not as clear-cut. In this paper the efficacy of quality assessment measures are examined through the case study of a university in the Somali Republic,…
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Arnold, Matthias
2017-12-02
The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care. A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters. Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias. This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters.
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NASA Technical Reports Server (NTRS)
Patel, Zarana S.; Kidane, Yared H.; Huff, Janice L.
2014-01-01
In this work, we evaluated the differential effects of low- and high-LET radiation on 3-D organotypic cultures in order to investigate radiation quality impacts on gene expression and cellular responses. Current risk models for assessment of space radiation-induced cancer have large uncertainties because the models for adverse health effects following radiation exposure are founded on epidemiological analyses of human populations exposed to low-LET radiation. Reducing these uncertainties requires new knowledge on the fundamental differences in biological responses (the so-called radiation quality effects) triggered by heavy ion particle radiation versus low-LET radiation associated with Earth-based exposures. In order to better quantify these radiation quality effects in biological systems, we are utilizing novel 3-D organotypic human tissue models for space radiation research. These models hold promise for risk assessment as they provide a format for study of human cells within a realistic tissue framework, thereby bridging the gap between 2-D monolayer culture and animal models for risk extrapolation to humans. To identify biological pathway signatures unique to heavy ion particle exposure, functional gene set enrichment analysis (GSEA) was used with whole transcriptome profiling. GSEA has been used extensively as a method to garner biological information in a variety of model systems but has not been commonly used to analyze radiation effects. It is a powerful approach for assessing the functional significance of radiation quality-dependent changes from datasets where the changes are subtle but broad, and where single gene based analysis using rankings of fold-change may not reveal important biological information.
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Large-scale model quality assessment for improving protein tertiary structure prediction.
Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin
2015-06-15
Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well. Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM's outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling. The web server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/human/. © The Author 2015. Published by Oxford University Press.
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Assessing the radar rainfall estimates in watershed-scale water quality model
USDA-ARS?s Scientific Manuscript database
Watershed-scale water quality models are effective science-based tools for interpreting change in complex environmental systems that affect hydrology cycle, soil erosion and nutrient fate and transport in watershed. Precipitation is one of the primary input data to achieve a precise rainfall-runoff ...
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MOOC Quality: The Need for New Measures
ERIC Educational Resources Information Center
Hood, Nina; Littlejohn, Allison
2016-01-01
MOOCs are re-operationalising traditional concepts in education. While they draw on elements of existing educational and learning models, they represent a new approach to instruction and learning. The challenges MOOCs present to traditional education models have important implications for approaching and assessing quality. This paper foregrounds…
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Local-scale dispersion models are increasingly being used to perform exposure assessments. These types of models, while able to characterize local-scale air quality at increasing spatial scale, however, lack the ability to include background concentration in their overall estimat...
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The Automation of Nowcast Model Assessment Processes
2016-09-01
that will automate real-time WRE-N model simulations, collect and quality control check weather observations for assimilation and verification, and...domains centered near White Sands Missile Range, New Mexico, where the Meteorological Sensor Array (MSA) will be located. The MSA will provide...observations and performing quality -control checks for the pre-forecast data assimilation period. 2. Run the WRE-N model to generate model forecast data
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Dunlop, Boadie W; Hill, Eric; Johnson, Benjamin N; Klein, Daniel N; Gelenberg, Alan J; Rothbaum, Barbara O; Thase, Michael E; Kocsis, James H
2015-03-01
Sexual dysfunction is common among depressed adults. Childhood sexual abuse (CSA) and depressive symptomology are among the risk factors for sexual dysfunction, and these factors may interact to predict adult relationship functioning. Several models have been developed postulating interactions between these variables. We tested models of the effects of CSA and elucidate the associations between CSA, sexual dysfunction, depression severity, anxiety, and relationship quality in chronically depressed adults. Baseline data from 808 chronically depressed outpatients enrolled in the Research Evaluating the Value of Augmenting Medication with Psychotherapy study were evaluated using structural equation modeling. The Inventory of Depressive Symptomology, self-report version (IDS-SR) assessed depression severity, and the Mood and Anxiety Symptom Questionnaire Anxious Arousal subscale assessed anxiety. Sexual function was assessed with the Arizona Sexual Experiences Scale (ASEX), and the Quality of Marriage Index (QMI) assessed relationship quality for patients in stable relationships. CSA scores predicted depression severity on the IDS-SR, as well as lower relationship quality and sexual satisfaction. ASEX scores were significantly associated with depression severity but were not correlated with the QMI. Two models were evaluated to elucidate these associations, revealing that (i) depression severity and anxious arousal mediated the relationship between CSA and adult sexual function, (ii) anxious arousal and sexual functioning mediated the association between CSA and depression symptoms, and (iii) when these models were combined, anxious arousal emerged as the most important mediator of CSA on depression which, in turn, mediated associations with adult sexual satisfaction and relationship quality. Although CSA predicts lower relationship and sexual satisfaction among depressed adults, the long-term effects of CSA appear to be mediated by depressive and anxious symptoms. It is important to address depression and anxiety symptoms when treating patients with CSA who present with sexual dysfunction or marital concerns. © 2014 International Society for Sexual Medicine.
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Wilcox, S.; Andreas, A.
2010-09-27
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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NASA Astrophysics Data System (ADS)
Wilcox, Steve; Myers, Daryl
2009-08-01
The U.S. Department of Energy's National Renewable Energy Laboratory has embarked on a collaborative effort with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of concentrating solar thermal power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result will be high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
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Predicting soil quality indices with near infrared analysis in a wildfire chronosequence.
Cécillon, Lauric; Cassagne, Nathalie; Czarnes, Sonia; Gros, Raphaël; Vennetier, Michel; Brun, Jean-Jacques
2009-01-15
We investigated the power of near infrared (NIR) analysis for the quantitative assessment of soil quality in a wildfire chronosequence. The effect of wildfire disturbance and soil engineering activity of earthworms on soil organic matter quality was first assessed with principal component analysis of NIR spectra. Three soil quality indices were further calculated using an adaptation of the method proposed by Velasquez et al. [Velasquez, E., Lavelle, P., Andrade, M. GISQ, a multifunctional indicator of soil quality. Soil Biol Biochem 2007; 39: 3066-3080.], each one addressing an ecosystem service provided by soils: organic matter storage, nutrient supply and biological activity. Partial least squares regression models were developed to test the predicting ability of NIR analysis for these soil quality indices. All models reached coefficients of determination above 0.90 and ratios of performance to deviation above 2.8. This finding provides new opportunities for the monitoring of soil quality, using NIR scanning of soil samples.
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Gómez-García, Francisco; Ruano, Juan; Aguilar-Luque, Macarena; Alcalde-Mellado, Patricia; Gay-Mimbrera, Jesús; Hernández-Romero, José Luis; Sanz-Cabanillas, Juan Luis; Maestre-López, Beatriz; González-Padilla, Marcelino; Carmona-Fernández, Pedro J; García-Nieto, Antonio Vélez; Isla-Tejera, Beatriz
2017-12-29
Article summaries' information and structure may influence researchers/clinicians' decisions to conduct deeper full-text analyses. Specifically, abstracts of systematic reviews (SRs) and meta-analyses (MA) should provide structured summaries for quick assessment. This study explored a method for determining the methodological quality and bias risk of full-text reviews using abstract information alone. Systematic literature searches for SRs and/or MA about psoriasis were undertaken on MEDLINE, EMBASE, and Cochrane database. For each review, quality, abstract-reporting completeness, full-text methodological quality, and bias risk were evaluated using Preferred Reporting Items for Systematic Reviews and Meta-analyses for abstracts (PRISMA-A), Assessing the Methodological Quality of Systematic Reviews (AMSTAR), and ROBIS tools, respectively. Article-, author-, and journal-derived metadata were systematically extracted from eligible studies using a piloted template, and explanatory variables concerning abstract-reporting quality were assessed using univariate and multivariate-regression models. Two classification models concerning SRs' methodological quality and bias risk were developed based on per-item and total PRISMA-A scores and decision-tree algorithms. This work was supported, in part, by project ICI1400136 (JR). No funding was received from any pharmaceutical company. This study analysed 139 SRs on psoriasis interventions. On average, they featured 56.7% of PRISMA-A items. The mean total PRISMA-A score was significantly higher for high-methodological-quality SRs than for moderate- and low-methodological-quality reviews. SRs with low-bias risk showed higher total PRISMA-A values than reviews with high-bias risk. In the final model, only 'authors per review > 6' (OR: 1.098; 95%CI: 1.012-1.194), 'academic source of funding' (OR: 3.630; 95%CI: 1.788-7.542), and 'PRISMA-endorsed journal' (OR: 4.370; 95%CI: 1.785-10.98) predicted PRISMA-A variability. Reviews with a total PRISMA-A score < 6, lacking identification as SR or MA in the title, and lacking explanation concerning bias risk assessment methods were classified as low-methodological quality. Abstracts with a total PRISMA-A score ≥ 9, including main outcomes results and explanation bias risk assessment method were classified as having low-bias risk. The methodological quality and bias risk of SRs may be determined by abstract's quality and completeness analyses. Our proposal aimed to facilitate synthesis of evidence evaluation by clinical professionals lacking methodological skills. External validation is necessary.
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Gad, Haidy A; El-Ahmady, Sherweit H; Abou-Shoer, Mohamed I; Al-Azizi, Mohamed M
2013-01-01
Recently, the fields of chemometrics and multivariate analysis have been widely implemented in the quality control of herbal drugs to produce precise results, which is crucial in the field of medicine. Thyme represents an essential medicinal herb that is constantly adulterated due to its resemblance to many other plants with similar organoleptic properties. To establish a simple model for the quality assessment of Thymus species using UV spectroscopy together with known chemometric techniques. The success of this model may also serve as a technique for the quality control of other herbal drugs. The model was constructed using 30 samples of authenticated Thymus vulgaris and challenged with 20 samples of different botanical origins. The methanolic extracts of all samples were assessed using UV spectroscopy together with chemometric techniques: principal component analysis (PCA), soft independent modeling of class analogy (SIMCA) and hierarchical cluster analysis (HCA). The model was able to discriminate T. vulgaris from other Thymus, Satureja, Origanum, Plectranthus and Eriocephalus species, all traded in the Egyptian market as different types of thyme. The model was also able to classify closely related species in clusters using PCA and HCA. The model was finally used to classify 12 commercial thyme varieties into clusters of species incorporated in the model as thyme or non-thyme. The model constructed is highly recommended as a simple and efficient method for distinguishing T. vulgaris from other related species as well as the classification of marketed herbs as thyme or non-thyme. Copyright © 2013 John Wiley & Sons, Ltd.
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Shurshakov, V A; Kartashov, D A; Kolomenskiĭ, A V; Petrov, V M; Red'ko, V I; Abramov, I P; Letkova, L I; Tikhomirov, E P
2006-01-01
Sampling irradiation of spacesuit "Orlan-M" allowed construction of a simulation model of the spacesuit shielding function for critical body organs. The critical organs self-shielding model is a Russian standard anthropomorphic phantom. Radiation protective quality of the spacesuit was assessed by calculating the dose attenuation rates for several critical body organs of an ISS crewmember implementing EVA. These calculations are intended for more accurate assessment of radiation risk to the ISS crews donning "Orlan-M" in near-Earth orbits.
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ASSESSING THE WATER QUALITY IMPACTS OF GLOBAL CLIMATE CHANGE IN SOUTHWESTERN OHIO, U.S.A
This paper uses a watershed-scale hydrologic model (Soil and Water Assessment Tool) to simulate the water quality impacts of future climate change in the Little Miami River (LMR) watershed in southwestern Ohio. The LMR watershed, the principal source of drinking water for 1.6 mi...
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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…
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Quality Management and Self Assessment Tools for Public Libraries.
ERIC Educational Resources Information Center
Evans, Margaret Kinnell
This paper describes a two-year study by the British Library Research and Innovation Centre that examined the potential of self-assessment for public library services. The approaches that formed the basis for the investigation were the Business Excellence Model, the Quality Framework, and the Democratic Approach. Core values were identified by…
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Planning and assessment in land and water resource management are evolving from simple, local-scale problems toward complex, spatially explicit regional ones. Such problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and t...
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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…
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A Conceptual Analysis of Quality in Quality Function Deployment-Based Contexts of Higher Education
ERIC Educational Resources Information Center
Matorera, Douglas
2015-01-01
The purpose of this paper is to assess and evaluate how higher education institutions (HEIs) using Quality Function Deployment draw out the relevancy and potential of the model in shaping their concept of "Quality" and how that Quality can be assured in higher education institutions' (HEIs') programmes. An intensive literature review was…
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ERIC Educational Resources Information Center
Birch, Derek W.; Johnson, F. Craig
A study was conducted using quality control and quality assurance models to examine student outcomes. The purpose was to investigate current quality control and quality assurance practices in six colleges, to evaluate the relationship between quantitative effectiveness measures and qualitative outcomes measure and to assess the readiness of each…
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Santhi, C; Kannan, N; White, M; Di Luzio, M; Arnold, J G; Wang, X; Williams, J R
2014-01-01
The USDA initiated the Conservation Effects Assessment Project (CEAP) to quantify the environmental benefits of conservation practices at regional and national scales. For this assessment, a sampling and modeling approach is used. This paper provides a technical overview of the modeling approach used in CEAP cropland assessment to estimate the off-site water quality benefits of conservation practices using the Ohio River Basin (ORB) as an example. The modeling approach uses a farm-scale model, Agricultural Policy Environmental Extender (APEX), and a watershed scale model (the Soil and Water Assessment Tool [SWAT]) and databases in the Hydrologic Unit Modeling for the United States system. Databases of land use, soils, land use management, topography, weather, point sources, and atmospheric depositions were developed to derive model inputs. APEX simulates the cultivated cropland, Conserve Reserve Program land, and the practices implemented on them, whereas SWAT simulates the noncultivated land (e.g., pasture, range, urban, and forest) and point sources. Simulation results from APEX are input into SWAT. SWAT routes all sources, including APEX's, to the basin outlet through each eight-digit watershed. Each basin is calibrated for stream flow, sediment, and nutrient loads at multiple gaging sites and turned in for simulating the effects of conservation practice scenarios on water quality. Results indicate that sediment, nitrogen, and phosphorus loads delivered to the Mississippi River from ORB could be reduced by 16, 15, and 23%, respectively, due to current conservation practices. Modeling tools are useful to provide science-based information for assessing existing conservation programs, developing future programs, and developing insights on load reductions necessary for hypoxia in the Gulf of Mexico. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
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Kirsch, Florian
2016-12-01
Disease management programs (DMPs) for chronic diseases are being increasingly implemented worldwide. To present a systematic overview of the economic effects of DMPs with Markov models. The quality of the models is assessed, the method by which the DMP intervention is incorporated into the model is examined, and the differences in the structure and data used in the models are considered. A literature search was conducted; the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement was followed to ensure systematic selection of the articles. Study characteristics e.g. results, the intensity of the DMP and usual care, model design, time horizon, discount rates, utility measures, and cost-of-illness were extracted from the reviewed studies. Model quality was assessed by two researchers with two different appraisals: one proposed by Philips et al. (Good practice guidelines for decision-analytic modelling in health technology assessment: a review and consolidation of quality asessment. Pharmacoeconomics 2006;24:355-71) and the other proposed by Caro et al. (Questionnaire to assess relevance and credibility of modeling studies for informing health care decision making: an ISPOR-AMCP-NPC Good Practice Task Force report. Value Health 2014;17:174-82). A total of 16 studies (9 on chronic heart disease, 2 on asthma, and 5 on diabetes) met the inclusion criteria. Five studies reported cost savings and 11 studies reported additional costs. In the quality, the overall score of the models ranged from 39% to 65%, it ranged from 34% to 52%. Eleven models integrated effectiveness derived from a clinical trial or a meta-analysis of complete DMPs and only five models combined intervention effects from different sources into a DMP. The main limitations of the models are bad reporting practice and the variation in the selection of input parameters. Eleven of the 14 studies reported cost-effectiveness results of less than $30,000 per quality-adjusted life-year and the remaining two studies less than $30,000 per life-year gained. Nevertheless, if the reporting and selection of data problems are addressed, then Markov models should provide more reliable information for decision makers, because understanding under what circumstances a DMP is cost-effective is an important determinant of efficient resource allocation. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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CONCENTRATIONS OF TOXIC AIR POLLUTANTS IN THE U.S. SIMULATED BY AN AIR QUALITY MODEL
As part of the US National Air Toxics Assessment, we have applied the Community Multiscale Air Quality Model, CMAQ, to study the concentrations of twenty gas-phase, toxic, hazardous air pollutants (HAPs) in the atmosphere over the continental United States. We modified the Carbo...
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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...
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77 FR 4808 - Conference on Air Quality Modeling
Federal Register 2010, 2011, 2012, 2013, 2014
2012-01-31
... update our available modeling tools with state-of-the-science techniques and for the public to offer new... C111, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711. FOR FURTHER INFORMATION CONTACT... Quality Assessment Division, Mail Code C439-01, Research Triangle Park, NC 27711; telephone: (919) 541...
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An air-quality forecasting (AQF) system based on the National Weather Service (NWS) National Centers for Environmental Prediction's (NCEP's) Eta model and the U.S. EPA's Community Multiscale Air Quality (CMAQ) Modeling System is used to simulate the distributions of tropospheric ...
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Assessing Quality in Higher Education: New Criteria for Evaluating Students' Satisfaction
ERIC Educational Resources Information Center
Zineldin, Mosad; Akdag, Hatice Camgoz; Vasicheva, Valentina
2011-01-01
The aim of this research is to present a new quality assurance model (5Qs) and to examine the major factors affecting students' perception of cumulative satisfaction. The model includes behavioural dimensions of student satisfaction. The factors included in this cumulative summation are technical, functional, infrastructure, interaction and…
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Modeling crop residue burning experiments and assessing the fire impacts on air quality
Prescribed burning is a common land management practice that results in ambient emissions of a variety of primary and secondary pollutants with negative health impacts. The community Multiscale Air Quality (CMAQ) model is used to conduct 2 km grid resolution simulations of prescr...
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An Entropy-Based Measure for Assessing Fuzziness in Logistic Regression
ERIC Educational Resources Information Center
Weiss, Brandi A.; Dardick, William
2016-01-01
This article introduces an entropy-based measure of data-model fit that can be used to assess the quality of logistic regression models. Entropy has previously been used in mixture-modeling to quantify how well individuals are classified into latent classes. The current study proposes the use of entropy for logistic regression models to quantify…
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Azouvi, Philippe; Ghout, Idir; Bayen, Eleonore; Darnoux, Emmanuelle; Azerad, Sylvie; Ruet, Alexis; Vallat-Azouvi, Claire; Pradat-Diehl, Pascale; Aegerter, Philippe; Charanton, James; Jourdan, Claire
2016-01-01
To assess predictors and indicators of disability and quality-of-life 4 years after severe traumatic brain injury (TBI), using structural equation modelling (SEM). The PariS-TBI study is a longitudinal multi-centre inception cohort study of 504 patients with severe TBI. Among 245 survivors, 147 patients were evaluated upon 4-year follow-up, and 85 completed the full assessment. Two outcome measures were analysed separately using SEM: the Glasgow Outcome Scale-extended (GOS-E), to measure disability, and the QOLIBRI, to assess quality-of-life. Four groups of variables were entered in the model: demographics; injury severity; mood and cognitive impairments; somatic impairments. The GOS-E was directly significantly related to mood and cognition, injury severity, and somatic impairments. Age and education had an indirect effect, mediated by mood/cognition or somatic deficiencies. In contrast, the only direct predictor of QOLIBRI was mood and cognition. Age and somatic impairments had an indirect influence on the QOLIBRI. Although this study should be considered as explorative, it suggests that disability and quality-of-life were directly influenced by different factors. While disability appeared to result from an interaction of a wide range of factors, quality-of-life was solely directly related to psycho-cognitive factors.
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Methodologic issues in assessing the quality of life of cancer patients.
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.
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NASA Astrophysics Data System (ADS)
Titi Purwantini, V.; Sutanto, Yusuf
2018-05-01
This research is to create a model of flood control in the city of Surakarta using Servqual method and Importance Performance Analysis. Service quality is generally defined as the overall assessment of a service by the customersor the extent to which a service meets customer’s needs or expectations. The purpose of this study is to find the first model of flood control that is appropriate to the condition of the community. Surakarta This means looking for a model that can provide satisfactory service for the people of Surakarta who are in the location of the flood. The second is to find the right model to improve service performance of Surakarta City Government in serving the people in flood location. The method used to determine the satisfaction of the public on the quality of service is to see the difference in the quality of service expected by the community with the reality. This method is Servqual Method While to assess the performance of city government officials is by comparing the actual performance with the quality of services provided, this method is This means looking for a model that can provide satisfactory service for the people of Surakarta who are in the location of the flood.The second is to find the right model to improve service performance of Surakarta City Government in serving the people in flood location. The method used to determine the satisfaction of the public on the quality of service is to see the difference in the quality of service expected by the community with the reality. This method is Servqual Method While to assess the performance of city government officials is by comparing the actual performance with the quality of services provided, this method is Importance Performance Analysis. Samples were people living in flooded areas in the city of Surakarta. Result this research is Satisfaction = Responsiveness+ Realibility + Assurance + Empathy+ Tangible (Servqual Model) and Importance Performance Analysis is From Cartesian diagram can be made Flood Control Formula as follow: Food Control = High performance
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Effect of soil in nutrient cycle assessment at dairy farms
NASA Astrophysics Data System (ADS)
van Leeuwen, Maricke; de Boer, Imke; van Dam, Jos; van Middelaar, Corina; Stoof, Cathelijne
2016-04-01
Annual farm nutrient cycle assessments give valuable insight in the nutrient cycles and nutrient losses at dairy farms. It describes nutrient use efficiencies for the entire farm and for the underlying components cattle, manure, crops and soil. In many modelling studies, soil is kept as a constant factor, while soil quality is vital for soil functioning of the ecosystem. Improving soil quality will improve the nutrient cycle, and will also have positive effect on the soil functions crop production, water cycling and greenhouse gas mitigation. Spatial variation of soil properties within a farm, however, are not included in annual nutrient cycle assessments. Therefore it is impossible to identify fields where most profit can be gained by improving farm management at field level, and it is not possible to identify and to quantify nutrient flow path ways. The aim of this study is to develop a framework to improve the annual nutrient cycle assessment at Dutch dairy farms, by including soil properties and their spatial variation within farms. Soil type and soil quality will be described by visual soil assessment of soil quality characteristics. The visual observations will be linked to the nutrient cycle assessment, using soil-hydrological model SWAP. We will demonstrate how soil quality at field level can impact on crop production, eutrophication potential and greenhouse gas potential at farm level. Also, we will show how this framework can be used by farmers to improve their farm management. This new approach is focusing on annual nutrient cycle assessment, but could also be used in life cycle assessment. It will improve understanding of soil functioning and dairy farm management.
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Quantifying Co-benefits of Renewable Energy through Integrated Electricity and Air Quality Modeling
NASA Astrophysics Data System (ADS)
Abel, D.
2016-12-01
This work focuses on the coordination of electricity sector changes with air quality and health improvement strategies through the integration of electricity and air quality models. Two energy models are used to calculate emission perturbations associated with changes in generation technology (20% generation from solar photovoltaics) and demand (future electricity use under a warmer climate). Impacts from increased solar PV penetration are simulated with the electricity model GridView, in collaboration with the National Renewable Energy Laboratory (NREL). Generation results are used to scale power plant emissions from an inventory developed by the Lake Michigan Air Directors Consortium (LADCO). Perturbed emissions and are used to calculate secondary particulate matter with the Community Multiscale Air Quality (CMAQ) model. We find that electricity NOx and SO2 emissions decrease at a rate similar to the total fraction of electricity supplied by solar. Across the Eastern U.S. region, average PM2.5 is reduced 5% over the summer, with highest reduction in regions and on days of greater PM2.5. A similar approach evaluates the air quality impacts of elevated electricity demand under a warmer climate. Meteorology is selected from the North American Regional Climate Change Assessment Program (NARCCAP) and input to a building energy model, eQUEST, to assess electricity demand as a function of ambient temperature. The associated generation and emissions are calculated on a plant-by-plant basis by the MyPower power sector model. These emissions are referenced to the 2011 National Emissions Inventory to be modeled in CMAQ for the Eastern U.S. and extended to health impact evaluation with the Environmental Benefits Mapping and Analysis Program (BenMAP). All results focus on the air quality and health consequences of energy system changes, considering grid-level changes to meet climate and air quality goals.
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LOUISIANA ENVIRONMENTAL MODELING SYSTEM FOR HYPOXIA RELATED ISSUES
An environmental assessment tool to evaluate the impacts of nonpoint source (NPS) pollutants discharged from Mississippi River basins into the Gulf of Mexico and to assess their effects on receiving water quality will be described. This system (Louisiana Environmental Modeling S...
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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.
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No-Reference Image Quality Assessment by Wide-Perceptual-Domain Scorer Ensemble Method.
Liu, Tsung-Jung; Liu, Kuan-Hsien
2018-03-01
A no-reference (NR) learning-based approach to assess image quality is presented in this paper. The devised features are extracted from wide perceptual domains, including brightness, contrast, color, distortion, and texture. These features are used to train a model (scorer) which can predict scores. The scorer selection algorithms are utilized to help simplify the proposed system. In the final stage, the ensemble method is used to combine the prediction results from selected scorers. Two multiple-scale versions of the proposed approach are also presented along with the single-scale one. They turn out to have better performances than the original single-scale method. Because of having features from five different domains at multiple image scales and using the outputs (scores) from selected score prediction models as features for multi-scale or cross-scale fusion (i.e., ensemble), the proposed NR image quality assessment models are robust with respect to more than 24 image distortion types. They also can be used on the evaluation of images with authentic distortions. The extensive experiments on three well-known and representative databases confirm the performance robustness of our proposed model.
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Curtis, J. Randall; Tulsky, James A.
2018-01-01
Abstract Background: High-quality care for seriously ill patients aligns treatment with their goals and values. Failure to achieve “goal-concordant” care is a medical error that can harm patients and families. Because communication between clinicians and patients enables goal concordance and also affects the illness experience in its own right, healthcare systems should endeavor to measure communication and its outcomes as a quality assessment. Yet, little consensus exists on what should be measured and by which methods. Objectives: To propose measurement priorities for serious illness communication and its anticipated outcomes, including goal-concordant care. Methods: We completed a narrative review of the literature to identify links between serious illness communication, goal-concordant care, and other outcomes. We used this review to identify gaps and opportunities for quality measurement in serious illness communication. Results: Our conceptual model describes the relationship between communication, goal-concordant care, and other relevant outcomes. Implementation-ready measures to assess the quality of serious illness communication and care include (1) the timing and setting of serious illness communication, (2) patient experience of communication and care, and (3) caregiver bereavement surveys that include assessment of perceived goal concordance of care. Future measurement priorities include direct assessment of communication quality, prospective patient or family assessment of care concordance with goals, and assessment of the bereaved caregiver experience. Conclusion: Improving serious illness care necessitates ensuring that high-quality communication has occurred and measuring its impact. Measuring patient experience and receipt of goal-concordant care should be our highest priority. We have the tools to measure both. PMID:29091522
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Segurado, P; Caiola, N; Pont, D; Oliveira, J M; Delaigue, O; Ferreira, M T
2014-04-01
In this work we compare two Iberian and a pan-European fish-based methods to assess ecological quality in rivers: the Fish-based Index of Biotic Integrity for Portuguese Wadeable Streams (F-IBIP), the Mediterranean Index of Biotic Integrity (IBIMED) and the pan-European Fish Index (EFI+). The results presented herein were developed in the context of the 2nd phase of the Intercalibration Exercise (IC), as required by the Water Frame Directive (WFD). The IC is aimed at ensuring comparability of the quality boundaries among the different WFD assessment methods developed by the Member States for each biological quality element. Although the two national assessment methods were developed for very distinct regions of Iberia (Western and Eastern Iberian Peninsula) they share the same methodological background: both are type-specific and guild-based multimetric indices. EFI+ is a multimetric guild-based model, but it is site-specific and uses a predictive modelling approach. The three indices were computed for all sites included in the Iberian Intercalibration database to allow the direct comparison, by means of linear regressions, of the resulting three quality values per site. The quality boundary harmonization between the two Iberian methods was only possible through an indirect comparison between the two indices, using EFI+ as a common metric. The three indices were also shown to be responsive to a common set of human induced pressures. This study highlights the need to develop general assessment methods adapted to wide geographical ranges with high species turnover to help intercalibrating assessment methods tailored for geographically more restricted regions. © 2013.
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Sanders, Justin J; Curtis, J Randall; Tulsky, James A
2018-03-01
High-quality care for seriously ill patients aligns treatment with their goals and values. Failure to achieve "goal-concordant" care is a medical error that can harm patients and families. Because communication between clinicians and patients enables goal concordance and also affects the illness experience in its own right, healthcare systems should endeavor to measure communication and its outcomes as a quality assessment. Yet, little consensus exists on what should be measured and by which methods. To propose measurement priorities for serious illness communication and its anticipated outcomes, including goal-concordant care. We completed a narrative review of the literature to identify links between serious illness communication, goal-concordant care, and other outcomes. We used this review to identify gaps and opportunities for quality measurement in serious illness communication. Our conceptual model describes the relationship between communication, goal-concordant care, and other relevant outcomes. Implementation-ready measures to assess the quality of serious illness communication and care include (1) the timing and setting of serious illness communication, (2) patient experience of communication and care, and (3) caregiver bereavement surveys that include assessment of perceived goal concordance of care. Future measurement priorities include direct assessment of communication quality, prospective patient or family assessment of care concordance with goals, and assessment of the bereaved caregiver experience. Improving serious illness care necessitates ensuring that high-quality communication has occurred and measuring its impact. Measuring patient experience and receipt of goal-concordant care should be our highest priority. We have the tools to measure both.
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NASA Technical Reports Server (NTRS)
Yu, Hongbin
2011-01-01
Mounting evidence for intercontinental transport of aerosols suggests that aerosols from a region could significantly affect climate and air quality in downwind regions and continents. Current assessment of these impacts for the most part has been based on global model simulations that show large variability. The aerosol intercontinental transport and its influence on air quality and climate involve many processes at local, regional, and intercontinental scales. There is a pressing need to establish modeling systems that bridge the wide range of scales. The modeling systems need to be evaluated and constrained by observations, including satellite measurements. Columnar loadings of dust and combustion aerosols can be derived from the MODIS and MISR measurements of total aerosol optical depth and particle size and shape information. Characteristic transport heights of dust and combustion aerosols can be determined from the CALIPSO lidar and AIRS measurements. CALIPSO liar and OMI UV technique also have a unique capability of detecting aerosols above clouds, which could offer some insights into aerosol lofting processes and the importance of above-cloud transport pathway. In this presentation, I will discuss our efforts of integrating these satellite measurements and models to assess the significance of intercontinental transport of dust and combustion aerosols on regional air quality and climate.
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NASA Astrophysics Data System (ADS)
van Ginneken, Meike; Oron, Gideon
2000-09-01
This study assesses health risks to consumers due to the use of agricultural products irrigated with reclaimed wastewater. The analysis is based on a definition of an exposure model which takes into account several parameters: (1) the quality of the applied wastewater, (2) the irrigation method, (3) the elapsed times between irrigation, harvest, and product consumption, and (4) the consumers' habits. The exposure model is used for numerical simulation of human consumers' risks using the Monte Carlo simulation method. The results of the numerical simulation show large deviations, probably caused by uncertainty (impreciseness in quality of input data) and variability due to diversity among populations. There is a 10-orders of magnitude difference in the risk of infection between the different exposure scenarios with the same water quality. This variation indicates the need for setting risk-based criteria for wastewater reclamation rather than single water quality guidelines. Extra data are required to decrease uncertainty in the risk assessment. Future research needs to include definition of acceptable risk criteria, more accurate dose-response modeling, information regarding pathogen survival in treated wastewater, additional data related to the passage of pathogens into and in the plants during irrigation, and information regarding the behavior patterns of the community of human consumers.
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Advanced capability of air quality simulation models towards accurate performance at finer scales will be needed for such models to serve as tools for performing exposure and risk assessments in urban areas. It is recognized that the impact of urban features such as street and t...
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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…
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A residency clinic chronic condition management quality improvement project.
Halverson, Larry W; Sontheimer, Dan; Duvall, Sharon
2007-02-01
Quality improvement in chronic disease management is a major agenda for improving health and reducing health care costs. A six-component chronic disease management model can help guide this effort. Several characteristics of the "new model" of family medicine described by the Future of Family Medicine (FFM) Project Leadership Committee are promulgated to foster practice changes that improve quality. Our objective was to implement and assess a quality improvement project guided by the components of a chronic disease management model and FFM new model characteristics. Diabetes was selected as a model chronic disease focus. Multiple practice changes were implemented. A mature electronic medical record facilitated data collection and measurement of quality improvement progress. Data from the diabetes registry demonstrates that our efforts have been effective. Significant improvement occurred in five out of six quality indicators. Multidisciplinary teamwork in a model residency practice guided by chronic disease management principles and the FFM new model characteristics can produce significant management improvements in one important chronic disease.
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Langhammer, Birgitta; Stanghelle, Johan K
2011-06-01
The primary aim of the present study was to investigate, based on data from our study in 2000, whether the Bobath approach enhanced quality of movement better than the Motor Relearning Programme (MRP) during rehabilitation of stroke patients. A randomized controlled stratified trial of acute stroke patients. The patients were treated according to Motor Relearning Programme and Bobath approach and assessed with Motor Assessment Scale, Sødring Motor Evaluation Scale, Nottingham Health Profile and the Barthel Index. A triangulation of the test scores was made in reference to the Movement Quality Model and biomechanical, physiological, psycho-socio-cultural, and existential themes. The items arm (p = 0.02-0.04) sitting (p = 0.04) and hand (p = 0.01-0.03) were significantly better in the Motor Relearning Programme group than in the Bobath group, in both Sødring Motor Evaluation Scale and Motor Assessment Scale. Leg function, balance, transfer, walking and stair climbing did not differ between the groups. The Movement Quality Model and the movement qualities biomechanical, physiological and psycho-socio-cultural showed higher scoring in the Motor Relearning Programme group, indicating better quality of movement in all items. Regression models established the relationship with significant models of motor performance and self reported physical mobility (adjusted R(2) 0.30-0.68, p < 0.0001), energy (adjusted R(2) 0.13-0.14, p = 0.03-0.04, emotion (adjusted R(2) 0.30-0.38, p < 0.0001) and social interaction (arm function, adjusted R(2) 0.25, p = 0.0001). These analyses confirm that task oriented exercises of the Motor Relearning Programme type are preferable regarding quality of movement in the acute rehabilitation of patients with stroke. Copyright © 2010 John Wiley & Sons, Ltd.
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ProQ3: Improved model quality assessments using Rosetta energy terms
Uziela, Karolis; Shu, Nanjiang; Wallner, Björn; Elofsson, Arne
2016-01-01
Quality assessment of protein models using no other information than the structure of the model itself has been shown to be useful for structure prediction. Here, we introduce two novel methods, ProQRosFA and ProQRosCen, inspired by the state-of-art method ProQ2, but using a completely different description of a protein model. ProQ2 uses contacts and other features calculated from a model, while the new predictors are based on Rosetta energies: ProQRosFA uses the full-atom energy function that takes into account all atoms, while ProQRosCen uses the coarse-grained centroid energy function. The two new predictors also include residue conservation and terms corresponding to the agreement of a model with predicted secondary structure and surface area, as in ProQ2. We show that the performance of these predictors is on par with ProQ2 and significantly better than all other model quality assessment programs. Furthermore, we show that combining the input features from all three predictors, the resulting predictor ProQ3 performs better than any of the individual methods. ProQ3, ProQRosFA and ProQRosCen are freely available both as a webserver and stand-alone programs at http://proq3.bioinfo.se/. PMID:27698390
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The quality of mental disorder information websites: a review.
Reavley, Nicola J; Jorm, Anthony F
2011-11-01
This paper reviews studies assessing the quality of websites providing information about mental disorders. The review included 31 articles identified by searching research databases in March 2010. Topics covered included affective disorders, anxiety disorders, eating disorders, substance use disorders and schizophrenia/psychosis. The largest number of articles (13) reported studies assessing affective disorder information quality. Methodologies varied in site selection and rating methods, with some of limited validity. Most concluded that quality was poor, although quality of affective disorder sites may be improving. There is currently very little understanding of the influence of website quality on user behaviour. Future quality assessments might use the criteria informed by key behaviour change theories. A possible approach to research on websites and user behaviour might be to develop an evaluation framework incorporating strategies from behaviour change models, key mental health literacy elements and health outcomes relevant to mental health promotion. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
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Stewart, C; Bench, S
2018-05-15
Quality improvement (QI) is a way through which health care delivery can be made safer and more effective. Various models of quality improvement methods exist in health care today. These models can help guide and manage the process of introducing changes into clinical practice. The aim of this project was to implement the use of a delirium assessment tool into three adult critical care units within the same hospital using a QI approach. The objective was to improve the identification and management of delirium. Using the Model for Improvement framework, a multidisciplinary working group was established. A delirium assessment tool was introduced via a series of educational initiatives. New local guidelines regarding the use of delirium assessment and management for the multidisciplinary team were also produced. Audit data were collected at 6 weeks and 5 months post-implementation to evaluate compliance with the use of the tool across three critical care units within a single hospital in London. At 6 weeks, in 134 assessment points out of a possible 202, the tool was deemed to be used appropriately, meaning that 60% of patients received timely assessment; 18% of patients were identified as delirious in audit one. Five months later, only 95 assessment points out of a possible 199 were being appropriately assessed (47%); however, a greater number (32%) were identified as delirious. This project emphasizes the complexity of changing practice in a large busy critical care centre. Despite an initial increase in delirium assessment, this was not sustained over time. The use of a QI model highlights the continuous process of embedding changes into clinical practice and the need to use a QI method that can address the challenging nature of modern health care. QI models guide changes in practice. Consideration should be given to the type of QI model used. © 2018 British Association of Critical Care Nurses.
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NASA Astrophysics Data System (ADS)
Zhang, Yan-yu; Wang, Jing; Shi, Yan-xi; Li, Yu-huan; Lv, Chun-yan
2005-10-01
The Crisscross Region of Wind-drift Sand Regions along the Great Wall and Loess Plateau locates in southern Ordos Plateau and northern Chinese Loess Plateau, where wind erosion and water erosion coexist and specified environmental and socio-economic factors, especially human activities induce serious land degradation. However, there are only a few studies provide an overall assessment consequences. Integrated land quality assessment considering impacts of soil, topography, vegetation, environmental hazards, social-economic factors and land managements are imperative to the regional sustainable land managements. A pilot study was made in Hengshan County (Shanxi Province) with the objective of developing comprehensive land quality evaluation model integrating data from farmers' survey and Remote Sensing. Surveys were carried out in 107 households of study area in 2003 and 2004 to get farmers' perceptions of land quality and to collect correlative information. It was found out that farmers evaluated land quality by slope, water availability, soil texture, yields, amount of fertilizer, crop performance, sandy erosion degree and water erosion degree. Scientists' indicators which emphasize on getting information by RS technology were introduced to reflecting above indicators information for the sake of developing a rapid, efficient and local-fitted land quality assessment model including social-economic, environmental and anthropogenic factors. Data from satellite and surveys were integrated with socio-economic statistic data using geographical information system (GIS) and three indexes, namely Production Press Index (PPI), Land State Index (LSI) and Farmer Behavior Index (FBI) were proposed to measure different aspects of land quality. A model was further derived from the three indexes to explore the overall land quality of the study area. Results suggest that local land prevalently had a poor quality. This paper shows that whilst the model was competent for its work in the study area and evaluation results would supply beneficial information for management decisions.
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Research on Holographic Evaluation of Service Quality in Power Data Network
NASA Astrophysics Data System (ADS)
Wei, Chen; Jing, Tao; Ji, Yutong
2018-01-01
With the rapid development of power data network, the continuous development of the Power data application service system, more and more service systems are being put into operation. Following this, the higher requirements for network quality and service quality are raised, in the actual process for the network operation and maintenance. This paper describes the electricity network and data network services status. A holographic assessment model was presented to achieve a comprehensive intelligence assessment on the power data network and quality of service in the operation and maintenance on the power data network. This evaluation method avoids the problems caused by traditional means which performs a single assessment of network performance quality. This intelligent Evaluation method can improve the efficiency of network operation and maintenance guarantee the quality of real-time service in the power data network..
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Lesjes van de Nederlanders: Little Lessons from the Dutch to Promote Educational Quality.
ERIC Educational Resources Information Center
Palmer, Barbara H.
1996-01-01
A study explored quality assessment and accountability in Dutch university education. The national system of quality assurance and various models used successfully to implement it are described, and the range of apparent effects and influences of quality assurance on Dutch higher education are examined. Comparison is made with American higher…
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Stimpfel, Amy Witkoski; Rosen, Jennifer E.; McHugh, Matthew D.
2017-01-01
OBJECTIVE The aim of this study was to explore the relationship between Magnet Recognition® and nurse-reported quality of care. BACKGROUND Magnet® hospitals are recognized for nursing excellence and quality patient outcomes; however, few studies have explored contributing factors for these superior outcomes. METHODS This was a secondary analysis of linked nurse survey data, hospital administrative data, and a listing of American Nurses Credentialing Center Magnet hospitals. Multivariate regressions were modeled before and after propensity score matching to assess the relationship between Magnet status and quality of care. A mediation model assessed the indirect effect of the professional practice environment on quality of care. RESULTS Nurse-reported quality of care was significantly associated with Magnet Recognition after matching. The professional practice environment mediates the relationship between Magnet status and quality of care. CONCLUSION A prominent feature of Magnet hospitals, a professional practice environment that is supportive of nursing, plays a role in explaining why Magnet hospitals have better nurse-reported quality of care. PMID:26426138
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Stimpfel, Amy Witkoski; Rosen, Jennifer E.; McHugh, Matthew D.
2014-01-01
OBJECTIVE The aim of this study was to explore the relationship between Magnet Recognition® and nurse-reported quality of care. BACKGROUND Magnet® hospitals are recognized for nursing excellence and quality patient outcomes; however, few studies have explored contributing factors for these superior outcomes. METHODS This was a secondary analysis of linked nurse survey data, hospital administrative data, and a listing of American Nurses Credentialing Center Magnet hospitals. Multivariate regressions were modeled before and after propensity score matching to assess the relationship between Magnet status and quality of care. A mediation model assessed the indirect effect of the professional practice environment on quality of care. RESULTS Nurse-reported quality of care was significantly associated with Magnet Recognition after matching. The professional practice environment mediates the relationship between Magnet status and quality of care. CONCLUSION A prominent feature of Magnet hospitals, a professional practice environment that is supportive of nursing, plays a role in explaining why Magnet hospitals have better nurse-reported quality of care. PMID:24316613
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Booth, N.L.; Everman, E.J.; Kuo, I.-L.; Sprague, L.; Murphy, L.
2011-01-01
The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water-quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water-quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow-weighted concentration, or load of constituents in water under various land-use condition, change, or resource management scenarios. A web-based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.
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USDA-ARS?s Scientific Manuscript database
The USDA initiated the Conservation Effects Assessment Project (CEAP) to quantify the environmental benefits of conservation practices at regional and national scales. For this assessment, a sampling and modeling approach is used. This paper provides a technical overview of the modeling approach use...
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An investigation of the concentrations of nitrogen oxides (NOx) from an air quality model and observations at monitoring sites was performed to assess the changes in NOx levels attributable to changes in mobile emissions. This evaluation effort focused on weekday morning rush hou...
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USDA-ARS?s Scientific Manuscript database
The resolution of General Circulation Models (GCMs) is too coarse to assess the fine scale or site-specific impacts of climate change. Downscaling approaches including dynamical and statistical downscaling have been developed to meet this requirement. As the resolution of climate model increases, it...
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Groundwater studies: principal aquifer surveys
Burow, Karen R.; Belitz, Kenneth
2014-01-01
In 1991, the U.S. Congress established the National Water-Quality Assessment (NAWQA) program within the U.S. Geological Survey (USGS) to develop nationally consistent long-term datasets and provide information about the quality of the Nation’s streams and groundwater. The USGS uses objective and reliable data, water-quality models, and systematic scientific studies to assess current water-quality conditions, to identify changes in water quality over time, and to determine how natural factors and human activities affect the quality of streams and groundwater. NAWQA is the only non-regulatory Federal program to perform these types of studies; participation is voluntary. In the third decade (Cycle 3) of the NAWQA program (2013–2023), the USGS will evaluate the quality and availability of groundwater for drinking supply, improve our understanding of where and why water quality is degraded, and assess how groundwater quality could respond to changes in climate and land use. These goals will be addressed through the implementation of a new monitoring component in Cycle 3: Principal Aquifer Surveys.
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MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, G; Pan, X; Stayman, J
2014-06-15
Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within themore » reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical applications. Learning Objectives: Learn the general methodologies associated with model-based 3D image reconstruction. Learn the potential advantages in image quality and dose associated with model-based image reconstruction. Learn the challenges associated with computational load and image quality assessment for such reconstruction methods. Learn how imaging task can be incorporated as a means to drive optimal image acquisition and reconstruction techniques. Learn how model-based reconstruction methods can incorporate prior information to improve image quality, ease sampling requirements, and reduce dose.« less
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Colonoscopy video quality assessment using hidden Markov random fields
NASA Astrophysics Data System (ADS)
Park, Sun Young; Sargent, Dusty; Spofford, Inbar; Vosburgh, Kirby
2011-03-01
With colonoscopy becoming a common procedure for individuals aged 50 or more who are at risk of developing colorectal cancer (CRC), colon video data is being accumulated at an ever increasing rate. However, the clinically valuable information contained in these videos is not being maximally exploited to improve patient care and accelerate the development of new screening methods. One of the well-known difficulties in colonoscopy video analysis is the abundance of frames with no diagnostic information. Approximately 40% - 50% of the frames in a colonoscopy video are contaminated by noise, acquisition errors, glare, blur, and uneven illumination. Therefore, filtering out low quality frames containing no diagnostic information can significantly improve the efficiency of colonoscopy video analysis. To address this challenge, we present a quality assessment algorithm to detect and remove low quality, uninformative frames. The goal of our algorithm is to discard low quality frames while retaining all diagnostically relevant information. Our algorithm is based on a hidden Markov model (HMM) in combination with two measures of data quality to filter out uninformative frames. Furthermore, we present a two-level framework based on an embedded hidden Markov model (EHHM) to incorporate the proposed quality assessment algorithm into a complete, automated diagnostic image analysis system for colonoscopy video.
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Reduced order models for prediction of groundwater quality impacts from CO₂ and brine leakage
Zheng, Liange; Carroll, Susan; Bianchi, Marco; ...
2014-12-31
A careful assessment of the risk associated with geologic CO₂ storage is critical to the deployment of large-scale storage projects. A potential risk is the deterioration of groundwater quality caused by the leakage of CO₂ and brine leakage from deep subsurface reservoirs. In probabilistic risk assessment studies, numerical modeling is the primary tool employed to assess risk. However, the application of traditional numerical models to fully evaluate the impact of CO₂ leakage on groundwater can be computationally complex, demanding large processing times and resources, and involving large uncertainties. As an alternative, reduced order models (ROMs) can be used as highlymore » efficient surrogates for the complex process-based numerical models. In this study, we represent the complex hydrogeological and geochemical conditions in a heterogeneous aquifer and subsequent risk by developing and using two separate ROMs. The first ROM is derived from a model that accounts for the heterogeneous flow and transport conditions in the presence of complex leakage functions for CO₂ and brine. The second ROM is obtained from models that feature similar, but simplified flow and transport conditions, and allow for a more complex representation of all relevant geochemical reactions. To quantify possible impacts to groundwater aquifers, the basic risk metric is taken as the aquifer volume in which the water quality of the aquifer may be affected by an underlying CO₂ storage project. The integration of the two ROMs provides an estimate of the impacted aquifer volume taking into account uncertainties in flow, transport and chemical conditions. These two ROMs can be linked in a comprehensive system level model for quantitative risk assessment of the deep storage reservoir, wellbore leakage, and shallow aquifer impacts to assess the collective risk of CO₂ storage projects.« less
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Improvement of the edge method for on-orbit MTF measurement.
Viallefont-Robinet, Françoise; Léger, Dominique
2010-02-15
The edge method is a widely used way to assess the on-orbit Modulation Transfer Function (MTF). Since good quality is required for the edge, the higher the spatial resolution, the better the results are. In this case, an artificial target can be built and used to ensure a good edge quality. For moderate spatial resolutions, only natural targets are available. Hence the edge quality is unknown and generally rather poor. Improvements of the method have been researched in order to compensate for the poor quality of natural edges. This has been done through the use of symmetry and/or a transfer function model, which enables the elimination of noise. This has also been used for artificial target. In this case, the use of the model overcomes the incomplete sampling when the target is too small or gives the opportunity to assess the defocus of the sensor. This paper begins with a recall of the method followed by a presentation of the changes relying on transfer function parametric model. The transfer function model and the process corresponding to the changes are described. Applications of these changes for several satellites of the French spatial agency are presented: for SPOT 1, it enables to assess XS MTF with natural edges, for SPOT 5, it enables to use the Salon-de-Provence artificial target for MTF assessment in the HM mode, and for the foreseen Pleiades, it enables to estimate the defocus.
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Using Data From Ontario's Episode-Based Funding Model to Assess Quality of Chemotherapy.
Kaizer, Leonard; Simanovski, Vicky; Lalonde, Carlin; Tariq, Huma; Blais, Irene; Evans, William K
2016-10-01
A new episode-based funding model for ambulatory systemic therapy was implemented in Ontario, Canada on April 1, 2014, after a comprehensive knowledge transfer and exchange strategy with providers and administrators. An analysis of the data from the first year of the new funding model provided an opportunity to assess the quality of chemotherapy, which was not possible under the old funding model. Options for chemotherapy regimens given with adjuvant/curative intent or palliative intent were informed by input from disease site groups. Bundles were developed and priced to enable evidence-informed best practice. Analysis of systemic therapy utilization after model implementation was performed to assess the concordance rate of the treatments chosen with recommended practice. The actual number of cycles of treatment delivered was also compared with expert recommendations. Significant improvement compared with baseline was seen in the proportion of adjuvant/curative regimens that aligned with disease site group-recommended options (98% v 90%). Similar improvement was seen for palliative regimens (94% v 89%). However, overall, the number of cycles of adjuvant/curative therapy delivered was lower than recommended best practice in 57.5% of patients. There was significant variation by disease site and between facilities. Linking funding to quality, supported by knowledge transfer and exchange, resulted in a rapid improvement in the quality of systemic treatment in Ontario. This analysis has also identified further opportunities for improvement and the need for model refinement.
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The data quality analyzer: a quality control program for seismic data
Ringler, Adam; Hagerty, M.T.; Holland, James F.; Gonzales, A.; Gee, Lind S.; Edwards, J.D.; Wilson, David; Baker, Adam
2015-01-01
The quantification of data quality is based on the evaluation of various metrics (e.g., timing quality, daily noise levels relative to long-term noise models, and comparisons between broadband data and event synthetics). Users may select which metrics contribute to the assessment and those metrics are aggregated into a “grade” for each station. The DQA is being actively used for station diagnostics and evaluation based on the completed metrics (availability, gap count, timing quality, deviation from a global noise model, deviation from a station noise model, coherence between co-located sensors, and comparison between broadband data and synthetics for earthquakes) on stations in the Global Seismographic Network and Advanced National Seismic System.
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A condition metric for Eucalyptus woodland derived from expert evaluations.
Sinclair, Steve J; Bruce, Matthew J; Griffioen, Peter; Dodd, Amanda; White, Matthew D
2018-02-01
The evaluation of ecosystem quality is important for land-management and land-use planning. Evaluation is unavoidably subjective, and robust metrics must be based on consensus and the structured use of observations. We devised a transparent and repeatable process for building and testing ecosystem metrics based on expert data. We gathered quantitative evaluation data on the quality of hypothetical grassy woodland sites from experts. We used these data to train a model (an ensemble of 30 bagged regression trees) capable of predicting the perceived quality of similar hypothetical woodlands based on a set of 13 site variables as inputs (e.g., cover of shrubs, richness of native forbs). These variables can be measured at any site and the model implemented in a spreadsheet as a metric of woodland quality. We also investigated the number of experts required to produce an opinion data set sufficient for the construction of a metric. The model produced evaluations similar to those provided by experts, as shown by assessing the model's quality scores of expert-evaluated test sites not used to train the model. We applied the metric to 13 woodland conservation reserves and asked managers of these sites to independently evaluate their quality. To assess metric performance, we compared the model's evaluation of site quality with the managers' evaluations through multidimensional scaling. The metric performed relatively well, plotting close to the center of the space defined by the evaluators. Given the method provides data-driven consensus and repeatability, which no single human evaluator can provide, we suggest it is a valuable tool for evaluating ecosystem quality in real-world contexts. We believe our approach is applicable to any ecosystem. © 2017 State of Victoria.
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NASA Astrophysics Data System (ADS)
Li, D.
2016-12-01
Sudden water pollution accidents are unavoidable risk events that we must learn to co-exist with. In China's Taihu River Basin, the river flow conditions are complicated with frequently artificial interference. Sudden water pollution accident occurs mainly in the form of a large number of abnormal discharge of wastewater, and has the characteristics with the sudden occurrence, the uncontrollable scope, the uncertainty object and the concentrated distribution of many risk sources. Effective prevention of pollution accidents that may occur is of great significance for the water quality safety management. Bayesian networks can be applied to represent the relationship between pollution sources and river water quality intuitively. Using the time sequential Monte Carlo algorithm, the pollution sources state switching model, water quality model for river network and Bayesian reasoning is integrated together, and the sudden water pollution risk assessment model for river network is developed to quantify the water quality risk under the collective influence of multiple pollution sources. Based on the isotope water transport mechanism, a dynamic tracing model of multiple pollution sources is established, which can describe the relationship between the excessive risk of the system and the multiple risk sources. Finally, the diagnostic reasoning algorithm based on Bayesian network is coupled with the multi-source tracing model, which can identify the contribution of each risk source to the system risk under the complex flow conditions. Taking Taihu Lake water system as the research object, the model is applied to obtain the reasonable results under the three typical years. Studies have shown that the water quality risk at critical sections are influenced by the pollution risk source, the boundary water quality, the hydrological conditions and self -purification capacity, and the multiple pollution sources have obvious effect on water quality risk of the receiving water body. The water quality risk assessment approach developed in this study offers a effective tool for systematically quantifying the random uncertainty in plain river network system, and it also provides the technical support for the decision-making of controlling the sudden water pollution through identification of critical pollution sources.
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Evaluation of Model Recognition for Grammar-Based Automatic 3d Building Model Reconstruction
NASA Astrophysics Data System (ADS)
Yu, Qian; Helmholz, Petra; Belton, David
2016-06-01
In recent years, 3D city models are in high demand by many public and private organisations, and the steadily growing capacity in both quality and quantity are increasing demand. The quality evaluation of these 3D models is a relevant issue both from the scientific and practical points of view. In this paper, we present a method for the quality evaluation of 3D building models which are reconstructed automatically from terrestrial laser scanning (TLS) data based on an attributed building grammar. The entire evaluation process has been performed in all the three dimensions in terms of completeness and correctness of the reconstruction. Six quality measures are introduced to apply on four datasets of reconstructed building models in order to describe the quality of the automatic reconstruction, and also are assessed on their validity from the evaluation point of view.
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Schuwirth, Lambert; Ash, Julie
2013-07-01
In this paper we are challenging six traditional notions about assessment that are unhelpful when designing 'assessment for learning'-programmes for competency-based education. We are arguing for the following: Reductionism is not the only way to assure rigour in high-stakes assessment; holistic judgements can be equally rigorous. Combining results of assessment parts only because they are of the same format (like different stations in an OSCE) is often not defensible; instead there must be a logically justifiable combination. Numbers describe the quality of the assessment. Therefore, manipulating the numbers is usually not the best way to improve its quality. Not every assessment moment needs to be a decision moment, disconnecting both makes combining summative and formative functions of assessment easier. Standardisation is not the only route to equity. Especially with diverse student groups tailoring is more equitable than standardisation. The most important element to standardise is the quality of the process and not the process itself. Finally, most assessment is too much focussed on detecting deficiencies and not on valuing individual student differences. In competency-based education--especially with a focus on learner orientation--this 'deficiency-model' is not as well aligned as a 'differences-model'.
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An assessment technique for computer-socket manufacturing
Sanders, Joan; Severance, Michael
2015-01-01
An assessment strategy is presented for testing the quality of carving and forming of individual computer aided manufacturing facilities. The strategy is potentially useful to facilities making sockets and companies marketing manufacturing equipment. To execute the strategy, an evaluator fabricates a collection of test models and sockets using the manufacturing suite under evaluation, and then measures their shapes using scanning equipment. Overall socket quality is assessed by comparing socket shapes with electronic file shapes. Then model shapes are compared with electronic file shapes to characterize carving performance. Socket shapes are compared with model shapes to characterize forming performance. The mean radial error (MRE), which is the average difference in radii between the two shapes being compared, provides insight into sizing quality. Inter-quartile range (IQR), the range of radial error for the best matched half of the points on the surfaces being compared, provides insight into shape quality. By determining MRE and IQR for carving and forming separately, the source(s) of socket shape error may be pinpointed. The developed strategy may provide a useful tool to the prosthetics community and industry to help identify problems and limitations in computer aided manufacturing and insight into appropriate modifications to overcome them. PMID:21938663
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ERIC Educational Resources Information Center
Takao, Allison Y.; Prothero, William A.; Kelly, Gregory J.
2002-01-01
Presents the methods and results of an assessment of students' scientific writing. Studies an introductory oceanography course in a large public university that used an interactive CD-ROM, "Our Dynamic Planet". Analyzes the quality of students' written arguments by using a grading rubric and an argumentation analysis model. Includes 18…
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ERIC Educational Resources Information Center
Murphy, Francis S.
2005-01-01
Education of potential professional engineers should take account of the type of employment that they will eventually obtain. The quality of an engineering degree course can be judged by assessing whether the correct balance of "essential attributes" has been effectively obtained. This case study is concerned with assessing the balance…
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OVERVIEW OF THE CLIMATE IMPACT ON REGIONAL AIR QUALITY (CIRAQ) PROJECT
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...
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An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers
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.
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NASA Technical Reports Server (NTRS)
1978-01-01
Papers are presented on such topics as environmental chemistry, the effects of sulfur compounds on air quality, the prediction and monitoring of biological effects caused by environmental pollutants, environmental indicators, the satellite remote sensing of air pollution, weather and climate modification by pollution, and the monitoring and assessment of radioactive pollutants. Consideration is also given to empirical and quantitative modeling of air quality, disposal of hazardous and nontoxic materials, sensing and assessment of water quality, pollution source monitoring, and assessment of some environmental impacts of fossil and nuclear fuels.
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Automated antibody structure prediction using Accelrys tools: Results and best practices
Fasnacht, Marc; Butenhof, Ken; Goupil-Lamy, Anne; Hernandez-Guzman, Francisco; Huang, Hongwei; Yan, Lisa
2014-01-01
We describe the methodology and results from our participation in the second Antibody Modeling Assessment experiment. During the experiment we predicted the structure of eleven unpublished antibody Fv fragments. Our prediction methods centered on template-based modeling; potential templates were selected from an antibody database based on their sequence similarity to the target in the framework regions. Depending on the quality of the templates, we constructed models of the antibody framework regions either using a single, chimeric or multiple template approach. The hypervariable loop regions in the initial models were rebuilt by grafting the corresponding regions from suitable templates onto the model. For the H3 loop region, we further refined models using ab initio methods. The final models were subjected to constrained energy minimization to resolve severe local structural problems. The analysis of the models submitted show that Accelrys tools allow for the construction of quite accurate models for the framework and the canonical CDR regions, with RMSDs to the X-ray structure on average below 1 Å for most of these regions. The results show that accurate prediction of the H3 hypervariable loops remains a challenge. Furthermore, model quality assessment of the submitted models show that the models are of quite high quality, with local geometry assessment scores similar to that of the target X-ray structures. Proteins 2014; 82:1583–1598. © 2014 The Authors. Proteins published by Wiley Periodicals, Inc. PMID:24833271
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Shim, Eun-Jung; Hahm, Bong-Jin; Go, Dong Jin; Lee, Kwang-Min; Noh, Hae Lim; Park, Seung-Hee; Song, Yeong Wook
2018-06-01
To examine factors in the fear-avoidance model, such as pain, pain catastrophizing, fear-avoidance beliefs, physical disability, and depression and their relationships with physical and psychological quality of life in patients with rheumatic diseases. The data were obtained from 360 patients with rheumatic diseases who completed self-report measures assessing study variables. Structural equation modeling was used to examine the hypothesized relationships among factors specified in the fear-avoidance model predicting physical and psychological quality of life. Final models fit the data well, explaining 96% and 82% of the variance in physical and psychological quality of life, respectively. Higher pain catastrophizing was related to stronger fear-avoidance beliefs that had a direct negative association with physical disability and depression, which, in turn, negatively affected physical quality of life. Pain severity was also directly related to physical disability. Physical disability also affected physical quality of life indirectly through depression. The hypothesized relationships specified in the model were also confirmed for psychological quality of life. However, physical disability had an indirect association with psychological quality of life via depression. The current results underscore the significant role of cognitive, affective, and behavioral factors in perceived physical disability and their mediated detrimental effect on physical and psychological quality of life in patients with rheumatic diseases. Implications for rehabilitation The fear-avoidance model is applicable to the prediction of quality of life in patients with rheumatic diseases. As pain-catastrophizing and fear-avoidance beliefs are important factors linked to physical disability and depression, intervening these cognitive factors is necessary to improve physical function and depression in patients with rheumatic diseases. Considering the strong association between depression and physical and psychological quality of life, the assessment and treatment of the former should be included in the rehabilitation of patients with rheumatic diseases. Interventions targeting physical function and depression are likely to be effective in terms of improving physical and psychological quality of life in patients with rheumatic diseases.
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2011-09-01
a quality evaluation with limited data, a model -based assessment must be...that affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a ...affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a wide range
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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.
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Assessing product image quality for online shopping
NASA Astrophysics Data System (ADS)
Goswami, Anjan; Chung, Sung H.; Chittar, Naren; Islam, Atiq
2012-01-01
Assessing product-image quality is important in the context of online shopping. A high quality image that conveys more information about a product can boost the buyer's confidence and can get more attention. However, the notion of image quality for product-images is not the same as that in other domains. The perception of quality of product-images depends not only on various photographic quality features but also on various high level features such as clarity of the foreground or goodness of the background etc. In this paper, we define a notion of product-image quality based on various such features. We conduct a crowd-sourced experiment to collect user judgments on thousands of eBay's images. We formulate a multi-class classification problem for modeling image quality by classifying images into good, fair and poor quality based on the guided perceptual notions from the judges. We also conduct experiments with regression using average crowd-sourced human judgments as target. We compute a pseudo-regression score with expected average of predicted classes and also compute a score from the regression technique. We design many experiments with various sampling and voting schemes with crowd-sourced data and construct various experimental image quality models. Most of our models have reasonable accuracies (greater or equal to 70%) on test data set. We observe that our computed image quality score has a high (0.66) rank correlation with average votes from the crowd sourced human judgments.
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Comans, Tracy A; Currin, Michelle L; Brauer, Sandra G; Haines, Terry P
2011-01-01
To identify factors contributing to reduced quality of life and increased caregiver strain in an older population referred to a community rehabilitation team and to recommend service delivery models. Analytical cross-sectional study arising from baseline assessments from 107 subjects drawn from a randomised controlled trial of community rehabilitation service delivery models. A community rehabilitation team based in Brisbane, Queensland, Australia. Primary outcome variables include quality of life (EQ-5D & VAS) and Carer Strain Index. Predictor variables include participation in functional activities, history of falls, number of medications, number of co-morbidities, depression, environmental hazards, physical function and nutrition. Association between variables assessed using linear regression. Major factors contributing to reduced quality of life were having reduced participation in daily activities, depression, and having poor vision. Having poor nutrition and no longer driving also contributed to poor quality of life. The major factor contributing to increased caregiver strain was reduced participation in daily activities by the older person. Community rehabilitation services working with older populations must adopt models of care that screen for and address a wide range of factors that contribute to poor quality of life and caregiver strain.
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ERIC Educational Resources Information Center
Hosan, Naheed E.; Hoglund, Wendy
2017-01-01
This study examined three competing models assessing the directional associations between the quality of children's relationships with teachers and friends (i.e., closeness and conflict) and their emotional and behavioral school engagement (i.e., the relationship-driven, engagement-driven, and transactional models). The additive contributions of…
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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...
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Weather Research and Forecasting (WRF)–Community Multi-scale Air Quality (CMAQ) model over the contiguous United States is conducted to assess how well the changes in observed ozone air quality are simulated by the model. The changes induced by variations in meteorology and...
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Assessment of the Quality of Digital Terrain Model Produced from Unmanned Aerial System Imagery
NASA Astrophysics Data System (ADS)
Kosmatin Fras, M.; Kerin, A.; Mesarič, M.; Peterman, V.; Grigillo, D.
2016-06-01
Production of digital terrain model (DTM) is one of the most usual tasks when processing photogrammetric point cloud generated from Unmanned Aerial System (UAS) imagery. The quality of the DTM produced in this way depends on different factors: the quality of imagery, image orientation and camera calibration, point cloud filtering, interpolation methods etc. However, the assessment of the real quality of DTM is very important for its further use and applications. In this paper we first describe the main steps of UAS imagery acquisition and processing based on practical test field survey and data. The main focus of this paper is to present the approach to DTM quality assessment and to give a practical example on the test field data. For data processing and DTM quality assessment presented in this paper mainly the in-house developed computer programs have been used. The quality of DTM comprises its accuracy, density, and completeness. Different accuracy measures like RMSE, median, normalized median absolute deviation and their confidence interval, quantiles are computed. The completeness of the DTM is very often overlooked quality parameter, but when DTM is produced from the point cloud this should not be neglected as some areas might be very sparsely covered by points. The original density is presented with density plot or map. The completeness is presented by the map of point density and the map of distances between grid points and terrain points. The results in the test area show great potential of the DTM produced from UAS imagery, in the sense of detailed representation of the terrain as well as good height accuracy.
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ERIC Educational Resources Information Center
La Grow, Steven; Yeung, Polly; Towers, Andrew; Alpass, Fiona; Stephens, Christine
2011-01-01
A model of vision rehabilitation that assumes that functional ability will affect the emotional and psychosocial adjustment of older persons with visual impairments, and ultimately their quality of life, was assessed using structured equation modeling. The proposed model was upheld. In addition, the ability to get around was found to contribute to…
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The impact of competition on quality and prices in the English care homes market
Forder, Julien; Allan, Stephen
2014-01-01
This study assesses the impact of competition on quality and price in the English care/nursing homes market. Considering the key institutional features, we use a theoretical model to assess the conditions under which further competition could increase or reduce quality. A dataset comprising the population of 10,000 care homes was used. We constructed distance/travel-time weighted competition measures. Instrumental variable estimations, used to account for the endogeneity of competition, showed quality and price were reduced by greater competition. Further analyses suggested that the negative quality effect worked through the effect on price – higher competition reduces revenue which pushes down quality. PMID:24487075
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The impact of competition on quality and prices in the English care homes market.
Forder, Julien; Allan, Stephen
2014-03-01
This study assesses the impact of competition on quality and price in the English care/nursing homes market. Considering the key institutional features, we use a theoretical model to assess the conditions under which further competition could increase or reduce quality. A dataset comprising the population of 10,000 care homes was used. We constructed distance/travel-time weighted competition measures. Instrumental variable estimations, used to account for the endogeneity of competition, showed quality and price were reduced by greater competition. Further analyses suggested that the negative quality effect worked through the effect on price - higher competition reduces revenue which pushes down quality. Copyright © 2013 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Johnston, J. M.
2013-12-01
Freshwater habitats provide fishable, swimmable and drinkable resources and are a nexus of geophysical and biological processes. These processes in turn influence the persistence and sustainability of populations, communities and ecosystems. Climate change and landuse change encompass numerous stressors of potential exposure, including the introduction of toxic contaminants, invasive species, and disease in addition to physical drivers such as temperature and hydrologic regime. A systems approach that includes the scientific and technologic basis of assessing the health of ecosystems is needed to effectively protect human health and the environment. The Integrated Environmental Modeling Framework 'iemWatersheds' has been developed as a consistent and coherent means of forecasting the cumulative impact of co-occurring stressors. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standardization of input data; the Framework for Risk Assessment of Multimedia Environmental Systems (FRAMES) that manages the flow of information between linked models; and the Supercomputer for Model Uncertainty and Sensitivity Evaluation (SuperMUSE) that provides post-processing and analysis of model outputs, including uncertainty and sensitivity analysis. Five models are linked within the Framework to provide multimedia simulation capabilities for hydrology and water quality processes: the Soil Water Assessment Tool (SWAT) predicts surface water and sediment runoff and associated contaminants; the Watershed Mercury Model (WMM) predicts mercury runoff and loading to streams; the Water quality Analysis and Simulation Program (WASP) predicts water quality within the stream channel; the Habitat Suitability Index (HSI) model scores physicochemical habitat quality for individual fish species; and the Bioaccumulation and Aquatic System Simulator (BASS) predicts fish growth, population dynamics and bioaccumulation of toxic substances. The capability of the Framework to address cumulative impacts will be demonstrated for freshwater ecosystem services and mountaintop mining.
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Modeled Oil and Gas Atmospheric Impacts in National Parks and Wilderness Areas in the Western US
NASA Astrophysics Data System (ADS)
Thompson, T. M.; Barna, M. G.; Schichtel, B. A.; Vimont, J.; Moore, C. T.
2014-12-01
Oil and gas production in the Western United States has increased considerably over the past 10 years. While many of the still limited oil and gas impact assessments have focused on potential human health impacts, the typically remote locations of production in the Intermountain West suggests that the impacts of oil and gas production on national parks and wilderness areas (class 1&2 areas) could also be important. To evaluate this, we utilize the Comprehensive Air quality Model with Extensions (CAMx) with two year-long modeling episodes representing 2008 and 2011, meteorology and emissions. The model inputs for the 2008 and 2011 episodes were generated as part of the West-wide Jump-start Air Quality Modeling Study (WestJumpAQMS) and Three State Air Quality Study (3SAQS) respectively. Both studies included a detailed assessment of oil and gas (O&G) emissions in Western States for the respective years. Each year-long modeling episode was run both with and without emissions from O&G production. The difference between these two runs provides an estimate of the contribution of the O&G production to air quality. These data were used to assess the contribution of O&G to the 8 hour average ozone concentrations, daily and annual fine particulate concentrations, annual nitrogen deposition totals and visibility in the modeling domain. We present the results for the class 1&2 areas in the Western US. We also present temporal trends of O&G impacts, differentiating between trends in urban and rural areas.
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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
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Sound quality indicators for urban places in Paris cross-validated by Milan data.
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.
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Benedict, Stephen T.; Conrads, Paul; Feaster, Toby D.; Journey, Celeste A.; Golden, Heather E.; Knightes, Christopher D.; Davis, Gary M.; Bradley, Paul M.
2012-01-01
The McTier Creek watershed is located in the headwaters of the Edisto River Basin, which is in the Coastal Plain region of South Carolina. The Edisto ecosystem has some of the highest recorded fish-tissue mercury concentrations in the United States. In an effort to advance the understanding of the fate and transport of mercury in stream ecosystems, the U.S. Geological Survey, as part of its National Water-Quality Assessment Program, initiated a field investigation of mercury in the McTier Creek watershed in 2006. The initial efforts of the investigation included the collection of extensive hydrologic and water-quality field data, along with the development of several hydrologic and water-quality models. This series of measured and modeled data forms the primary source of information for this investigation to assess the fate and transport of mercury within the McTier Creek watershed.
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Villiers-Tuthill, Amanda; Doulougeri, Karolina; McGee, Hannah; Montgomery, Anthony; Panagopoulou, Efharis; Morgan, Karen
2017-12-01
Patient perceptions of quality of care (QoC) are directly linked with patient safety and clinical effectiveness. We need patient-designed QoC instruments that work across languages and countries to optimise studies across systems in this area. Few QoC measurement tools exist that assess all aspects of QoC from the patient perspective. This paper describes the development and validation of a comprehensive measure to assess patient perceptions of QoC that incorporates technical and interpersonal aspects of care and is grounded in the established Institute of Medicine (IOM) QoC framework. We conducted a multi-country cross-sectional study. Following a literature review and patient focus groups, an expert panel generated questionnaire items. Following a pilot study, item numbers were reduced. The final questionnaire consisted of three sections: demographics, perceived QoC and one open-ended question. Data was collected from patients (n = 531) discharged from hospitals across seven countries in South East Europe (languages: Turkish, Greek, Portuguese, Romanian, Croatian, Macedonian and Bulgarian). Reliability and validity of the measure were assessed. Confirmatory factor analysis was used to compare various factor models of patient-perceived QoC. Good model fit was demonstrated for a two-factor model: communication and interpersonal care, and hospital facilities. The ORCAB (Improving quality and safety in the hospital: The link between organisational culture, burnout and quality of care) Patient QoC questionnaire has been collaboratively and exhaustively developed between healthcare professionals and patients. It enables patient QoC data to be assessed in the context of the IOM pillars of quality, considering both technical and interpersonal dimensions of care. It represents an important first step in including the patient perspective.
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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.
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Giri, Subhasis; Qiu, Zeyuan; Zhang, Zhen
2018-05-01
Understanding the relationship between land use and water quality is essential to improve water quality through carefully managing landscape change. This study applies a linear mixed model at both watershed and hydrologically sensitive areas (HSAs) scales to assess such a relationship in 28 northcentral New Jersey watersheds located in a rapidly urbanizing region in the United States. Two models differ in terms of the geographic scope used to derive land use matrices that quantify land use conditions. The land use matrices at the watershed and HSAs scales represent the land use conditions in these watersheds and their HSAs, respectively. HSAs are the hydrological "hotspots" in a watershed that are prone to runoff generation during storm events. HSAs are derived using a soil topographic index (STI) that predicts hydrological sensitivity of a landscape based on a variable source area hydrology concept. The water quality indicators in these models are total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) concentrations in streams observed at the watershed outlets. The modeling results suggest that presence of low density urban land, agricultural land and wetlands elevate while forest decreases TN, TP and/or TSS concentrations in streams. The watershed scale model tends to emphasize the role of agricultural lands in water quality degradation while the HSA scale model highlights the role of forest in water quality improvement. This study supports the hypothesis that even though HSAs are relatively smaller area compared to watershed, still the land uses within HSAs have similar impacts on downstream water quality as the land uses in entire watersheds, since both models have negligible differences in model evaluation parameters. Inclusion of HSAs brings an interesting perspective to understand the dynamic relationships between land use and water quality. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Evaluating water management strategies with the Systems Impact Assessment Model: SIAM version 4
Bartholow, John M.; Heasley, John; Hanna, Blair; Sandelin, Jeff; Flug, Marshall; Campbell, Sharon; Henriksen, Jim; Douglas, Aaron
2005-01-01
The apparent disparity between restoration benefits and costs for the Klamath River may suggest to some that water resources on the Klamath be reallocated to environmentally friendly nonmarket uses. The economic analysis rests in part on the information made available to the survey designers by the biological, hydrologic, and water quality data incorporated in The System Impact Assessment Model (SIAM). It is our hope that SIAM can be used to improve the river's water quality and fishery, and strengthen the important regional economy.
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Indoor Air Quality and Energy Efficiency
EPA completed an extensive modeling study to assess the compatibilities and trade-offs between energy, indoor air quality, and thermal comfort objectives for HVAC systems and to formulate strategies for superior performance across all areas.
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Ebrahimi, Milad; Gerber, Erin L; Rockaway, Thomas D
2017-05-15
For most water treatment plants, a significant number of performance data variables are attained on a time series basis. Due to the interconnectedness of the variables, it is often difficult to assess over-arching trends and quantify operational performance. The objective of this study was to establish simple and reliable predictive models to correlate target variables with specific measured parameters. This study presents a multivariate analysis of the physicochemical parameters of municipal wastewater. Fifteen quality and quantity parameters were analyzed using data recorded from 2010 to 2016. To determine the overall quality condition of raw and treated wastewater, a Wastewater Quality Index (WWQI) was developed. The index summarizes a large amount of measured quality parameters into a single water quality term by considering pre-established quality limitation standards. To identify treatment process performance, the interdependencies between the variables were determined by using Principal Component Analysis (PCA). The five extracted components from the 15 variables accounted for 75.25% of total dataset information and adequately represented the organic, nutrient, oxygen demanding, and ion activity loadings of influent and effluent streams. The study also utilized the model to predict quality parameters such as Biological Oxygen Demand (BOD), Total Phosphorus (TP), and WWQI. High accuracies ranging from 71% to 97% were achieved for fitting the models with the training dataset and relative prediction percentage errors less than 9% were achieved for the testing dataset. The presented techniques and procedures in this paper provide an assessment framework for the wastewater treatment monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Modeling the ecological trap hypothesis: a habitat and demographic analysis for migrant songbirds
Therese M. Donovan; Frank R, III Thompson
2001-01-01
Most species occupy both high- and low-quality habitats throughout their ranges. As habitats become modified through anthropogenic change, low-quality habitat may become a more dominant component of the landscape for some species. To conserve species, information on how to assess habitat quality and guidelines for maintaining or eliminating low-quality habitats are...
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Mannina, Giorgio; Viviani, Gaspare
2010-01-01
Urban water quality management often requires use of numerical models allowing the evaluation of the cause-effect relationship between the input(s) (i.e. rainfall, pollutant concentrations on catchment surface and in sewer system) and the resulting water quality response. The conventional approach to the system (i.e. sewer system, wastewater treatment plant and receiving water body), considering each component separately, does not enable optimisation of the whole system. However, recent gains in understanding and modelling make it possible to represent the system as a whole and optimise its overall performance. Indeed, integrated urban drainage modelling is of growing interest for tools to cope with Water Framework Directive requirements. Two different approaches can be employed for modelling the whole urban drainage system: detailed and simplified. Each has its advantages and disadvantages. Specifically, detailed approaches can offer a higher level of reliability in the model results, but can be very time consuming from the computational point of view. Simplified approaches are faster but may lead to greater model uncertainty due to an over-simplification. To gain insight into the above problem, two different modelling approaches have been compared with respect to their uncertainty. The first urban drainage integrated model approach uses the Saint-Venant equations and the 1D advection-dispersion equations, for the quantity and for the quality aspects, respectively. The second model approach consists of the simplified reservoir model. The analysis used a parsimonious bespoke model developed in previous studies. For the uncertainty analysis, the Generalised Likelihood Uncertainty Estimation (GLUE) procedure was used. Model reliability was evaluated on the basis of capacity of globally limiting the uncertainty. Both models have a good capability to fit the experimental data, suggesting that all adopted approaches are equivalent both for quantity and quality. The detailed model approach is more robust and presents less uncertainty in terms of uncertainty bands. On the other hand, the simplified river water quality model approach shows higher uncertainty and may be unsuitable for receiving water body quality assessment.
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A comprehensive framework for data quality assessment in CER.
Holve, Erin; Kahn, Michael; Nahm, Meredith; Ryan, Patrick; Weiskopf, Nicole
2013-01-01
The panel addresses the urgent need to ensure that comparative effectiveness research (CER) findings derived from diverse and distributed data sources are based on credible, high-quality data; and that the methods used to assess and report data quality are consistent, comprehensive, and available to data consumers. The panel consists of representatives from four teams leveraging electronic clinical data for CER, patient centered outcomes research (PCOR), and quality improvement (QI) and seeks to change the current paradigm where data quality assessment (DQA) is performed "behind the scenes" using one-off project specific methods. The panelists will present their process of harmonizing existing models for describing and measuring clinical data quality and will describe a comprehensive integrated framework for assessing and reporting DQA findings. The collaborative project is supported by the Electronic Data Methods (EDM) Forum, a three-year grant from the Agency for Healthcare Research and Quality (AHRQ) to facilitate learning and foster collaboration across a set of CER, PCOR, and QI projects designed to build infrastructure and methods for collecting and analyzing prospective data from electronic clinical data .
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ERIC Educational Resources Information Center
Battisti, Bryce Thomas; Hanegan, Nikki; Sudweeks, Richard; Cates, Rex
2010-01-01
Concept inventories are often used to assess current student understanding although conceptual change models are problematic. Due to controversies with conceptual change models and the realities of student assessment, it is important that concept inventories are evaluated using a variety of theoretical models to improve quality. This study used a…
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[Assessing user satisfaction, an objective for quality of care].
Séné-Bourgeois, Martine; Mathieu-Chakroun, Isabelle; Margat, Aurore
The assessment of user satisfaction constitutes a key indicator of the quality of care. It can be envisaged either as part of an internal strategy which favours the improvement of practices, an external strategy whose focus is more commercial and/or an exploratory strategy to develop care models. User satisfaction is expressed in particular through complaint letters and discharge questionnaires. These regulated schemes enable quality to be approached on an individual and collective level. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
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Quality assessment of a new surgical simulator for neuroendoscopic training.
Filho, Francisco Vaz Guimarães; Coelho, Giselle; Cavalheiro, Sergio; Lyra, Marcos; Zymberg, Samuel T
2011-04-01
Ideal surgical training models should be entirely reliable, atoxic, easy to handle, and, if possible, low cost. All available models have their advantages and disadvantages. The choice of one or another will depend on the type of surgery to be performed. The authors created an anatomical model called the S.I.M.O.N.T. (Sinus Model Oto-Rhino Neuro Trainer) Neurosurgical Endotrainer, which can provide reliable neuroendoscopic training. The aim in the present study was to assess both the quality of the model and the development of surgical skills by trainees. The S.I.M.O.N.T. is built of a synthetic thermoretractable, thermosensible rubber called Neoderma, which, combined with different polymers, produces more than 30 different formulas. Quality assessment of the model was based on qualitative and quantitative data obtained from training sessions with 9 experienced and 13 inexperienced neurosurgeons. The techniques used for evaluation were face validation, retest and interrater reliability, and construct validation. The experts considered the S.I.M.O.N.T. capable of reproducing surgical situations as if they were real and presenting great similarity with the human brain. Surgical results of serial training showed that the model could be considered precise. Finally, development and improvement in surgical skills by the trainees were observed and considered relevant to further training. It was also observed that the probability of any single error was dramatically decreased after each training session, with a mean reduction of 41.65% (range 38.7%-45.6%). Neuroendoscopic training has some specific requirements. A unique set of instruments is required, as is a model that can resemble real-life situations. The S.I.M.O.N.T. is a new alternative model specially designed for this purpose. Validation techniques followed by precision assessments attested to the model's feasibility.
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This dataset supports the modeling study of Seltzer et al. (2016) published in Atmospheric Environment. In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000-2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method??s use for future air quality projections.This dataset is associated with the following publication:Seltzer, K., C
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Stiletto, R; Röthke, M; Schäfer, E; Lefering, R; Waydhas, Ch
2006-10-01
Patient security has become one of the major aspects of clinical management in recent years. The crucial point in research was focused on malpractice. In contradiction to the economic process in non medical fields, the analysis of errors during the in-patient treatment time was neglected. Patient risk management can be defined as a structured procedure in a clinical unit with the aim to reduce harmful events. A risk point model was created based on a Delphi process and founded on the DIVI data register. The risk point model was evaluated in clinically working ICU departments participating in the register data base. The results of the risk point evaluation will be integrated in the next data base update. This might be a step to improve the reliability of the register to measure quality assessment in the ICU.
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Gu, Qing; Deng, Jinsong; Wang, Ke; Lin, Yi; Li, Jun; Gan, Muye; Ma, Ligang; Hong, Yang
2014-01-01
Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources. PMID:24919129
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Gu, Qing; Deng, Jinsong; Wang, Ke; Lin, Yi; Li, Jun; Gan, Muye; Ma, Ligang; Hong, Yang
2014-06-10
Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources.
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High-quality, daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decision making. This paper describes the development, application, and assessment of ...
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An assessment model for atmospheric composition
NASA Technical Reports Server (NTRS)
Prather, Michael J. (Editor)
1988-01-01
Predicting future perturbations to global air quality and climate requires, as a prerequisite, prognostic models for the composition of the Earth's atmosphere. Such assessment models are needed to evaluate the impact on our environment of different social choices that affect emissions of the photochemically and radiatively important trace gases. Our presentation here of a prototype assessment model is intended to encourage public scientific discussions of the necessary components of the model and their interactions, with the recognition that models similar to this will likely be used by the Environmental Protection Agency and other regulatory agencies in order to assess the effect of changes in atmospheric composition on climate over the next century.
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Predicting perceptual quality of images in realistic scenario using deep filter banks
NASA Astrophysics Data System (ADS)
Zhang, Weixia; Yan, Jia; Hu, Shiyong; Ma, Yang; Deng, Dexiang
2018-03-01
Classical image perceptual quality assessment models usually resort to natural scene statistic methods, which are based on an assumption that certain reliable statistical regularities hold on undistorted images and will be corrupted by introduced distortions. However, these models usually fail to accurately predict degradation severity of images in realistic scenarios since complex, multiple, and interactive authentic distortions usually appear on them. We propose a quality prediction model based on convolutional neural network. Quality-aware features extracted from filter banks of multiple convolutional layers are aggregated into the image representation. Furthermore, an easy-to-implement and effective feature selection strategy is used to further refine the image representation and finally a linear support vector regression model is trained to map image representation into images' subjective perceptual quality scores. The experimental results on benchmark databases present the effectiveness and generalizability of the proposed model.
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Harris, Katherine M
2002-06-01
To investigate the impact of quality information on the willingness of consumers to enroll in health plans that restrict provider access. A survey administered to respondents between the ages of 25 and 64 in the West Los Angeles area with private health insurance. An experimental approach is used to measure the effect of variation in provider network features and information about the quality of network physicians on hypothetical plan choices. Conditional logit models are used to analyze the experimental choice data. Next, choice model parameter estimates are used to simulate the impact of changes in plan features on the market shares of competing health plans and to calculate the quality level required to make consumers indifferent to changes in provider access. The presence of quality information reduced the importance of provider network features in plan choices as hypothesized. However, there were not statistically meaningful differences by type of quality measure (i.e., consumer assessed versus expert assessed). The results imply that large quality differences are required to make consumers indifferent to changes in provider access. The impact of quality on plan choices depended more on the particular measure and less on the type of measure. Quality ratings based on the proportion of survey respondents "extremely satisfied with results of care" had the greatest impact on plan choice while the proportion of network doctors "affiliated with university medical centers" had the least. Other consumer and expert assessed measures had more comparable effects. Overall the results provide empirical evidence that consumers are willing to trade high quality for restrictions on provider access. This willingness to trade implies that relatively small plans that place restrictions on provider access can successfully compete against less restrictive plans when they can demonstrate high quality. However, the results of this study suggest that in many cases, the level of quality required for consumers to accept access restrictions may be so high as to be unattainable. The results provide empirical support for the current focus of decision support efforts on consumer assessed quality measures. At the same time, however, the results suggest that consumers would also value quality measures based on expert assessments. This finding is relevant given the lack of comparative quality information based on expert judgment and research suggesting that consumers have apprehensions about their ability to meaningfully interpret performance-based quality measures.
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Johnson, Blair T; Low, Robert E; MacDonald, Hayley V
2015-01-01
Systematic reviews now routinely assess methodological quality to gauge the validity of the included studies and of the synthesis as a whole. Although trends from higher quality studies should be clearer, it is uncertain how often meta-analyses incorporate methodological quality in models of study results either as predictors, or, more interestingly, in interactions with theoretical moderators. We survey 200 meta-analyses in three health promotion domains to examine when and how meta-analyses incorporate methodological quality. Although methodological quality assessments commonly appear in contemporary meta-analyses (usually as scales), they are rarely incorporated in analyses, and still more rarely analysed in interaction with theoretical determinants of the success of health promotions. The few meta-analyses (2.5%) that did include such an interaction analysis showed that moderator results remained significant in higher quality studies or were present only among higher quality studies. We describe how to model quality interactively with theoretically derived moderators and discuss strengths and weaknesses of this approach and in relation to current meta-analytic practice. In large literatures exhibiting heterogeneous effects, meta-analyses can incorporate methodological quality and generate conclusions that enable greater confidence not only about the substantive phenomenon but also about the role that methodological quality itself plays.
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ERIC Educational Resources Information Center
Dogan, Sebnem Koldas; Ay, Saime; Oztuna, Derya; Aytur, Yesim Kurtais; Evcik, Deniz
2010-01-01
This study was planned to investigate the utility of the vertical Faces Pain Scale (FPS) in the assessment of pain in stroke patients using the shoulder pain model and to assess its utility in the Turkish patient population. The secondary aim was to analyze the association of FPS with the quality of life and depression in the study population.…
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Physician Peer Assessments for Compliance with Methadone Maintenance Treatment Guidelines
ERIC Educational Resources Information Center
Strike, Carol; Wenghofer, Elizabeth; Gnam, William; Hillier, Wade; Veldhuizen, Scott; Millson, Margaret
2007-01-01
Introduction: Medical associations and licensing bodies face pressure to implement quality assurance programs, but evidence-based models are lacking. To improve the quality of methadone maintenance treatment (MMT), the College of Physicians and Surgeons of Ontario, Canada, conducts an innovative quality assurance program on the basis of peer…
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Using National Coastal Assessment Data to Model Estuarine Water Quality at Large Spatial Scales
Background/Question/MethodThe water quality of the Nation’s estuaries is attracting increasing scrutiny in light of burgeoning coastal population growth and enhanced delivery of nutrients via riverine flux. The USEPA has evaluated water quality in US estuaries in the Nation...
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Vergara, Pablo M.; Soto, Gerardo E.; Rodewald, Amanda D.; Meneses, Luis O.; Pérez-Hernández, Christian G.
2016-01-01
Theoretical models predict that animals should make foraging decisions after assessing the quality of available habitat, but most models fail to consider the spatio-temporal scales at which animals perceive habitat availability. We tested three foraging strategies that explain how Magellanic woodpeckers (Campephilus magellanicus) assess the relative quality of trees: 1) Woodpeckers with local knowledge select trees based on the available trees in the immediate vicinity. 2) Woodpeckers lacking local knowledge select trees based on their availability at previously visited locations. 3) Woodpeckers using information from long-term memory select trees based on knowledge about trees available within the entire landscape. We observed foraging woodpeckers and used a Brownian Bridge Movement Model to identify trees available to woodpeckers along foraging routes. Woodpeckers selected trees with a later decay stage than available trees. Selection models indicated that preferences of Magellanic woodpeckers were based on clusters of trees near the most recently visited trees, thus suggesting that woodpeckers use visual cues from neighboring trees. In a second analysis, Cox’s proportional hazards models showed that woodpeckers used information consolidated across broader spatial scales to adjust tree residence times. Specifically, woodpeckers spent more time at trees with larger diameters and in a more advanced stage of decay than trees available along their routes. These results suggest that Magellanic woodpeckers make foraging decisions based on the relative quality of trees that they perceive and memorize information at different spatio-temporal scales. PMID:27416115
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Vergara, Pablo M; Soto, Gerardo E; Moreira-Arce, Darío; Rodewald, Amanda D; Meneses, Luis O; Pérez-Hernández, Christian G
2016-01-01
Theoretical models predict that animals should make foraging decisions after assessing the quality of available habitat, but most models fail to consider the spatio-temporal scales at which animals perceive habitat availability. We tested three foraging strategies that explain how Magellanic woodpeckers (Campephilus magellanicus) assess the relative quality of trees: 1) Woodpeckers with local knowledge select trees based on the available trees in the immediate vicinity. 2) Woodpeckers lacking local knowledge select trees based on their availability at previously visited locations. 3) Woodpeckers using information from long-term memory select trees based on knowledge about trees available within the entire landscape. We observed foraging woodpeckers and used a Brownian Bridge Movement Model to identify trees available to woodpeckers along foraging routes. Woodpeckers selected trees with a later decay stage than available trees. Selection models indicated that preferences of Magellanic woodpeckers were based on clusters of trees near the most recently visited trees, thus suggesting that woodpeckers use visual cues from neighboring trees. In a second analysis, Cox's proportional hazards models showed that woodpeckers used information consolidated across broader spatial scales to adjust tree residence times. Specifically, woodpeckers spent more time at trees with larger diameters and in a more advanced stage of decay than trees available along their routes. These results suggest that Magellanic woodpeckers make foraging decisions based on the relative quality of trees that they perceive and memorize information at different spatio-temporal scales.
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Support Center for Regulatory Atmospheric Modeling (SCRAM)
This technical site provides access to air quality models (including computer code, input data, and model processors) and other mathematical simulation techniques used in assessing air emissions control strategies and source impacts.
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Robert J. Luxmoore; William W. Hargrove; M. Lynn Tharp; Wilfred M. Post; Michael W. Berry; Karen S. Minser; Wendell P. Cropper; Dale W. Johnson; Boris Zeide; Ralph L. Amateis; Harold E. Burkhart; V. Clark Baldwin; Kelly D. Peterson
2000-01-01
Stochastic transfer of information in a hierarchy of simulators is offered as a conceptual approach for assessing forest responses to changing climate and air quality across 13 southeastern states of the USA. This assessment approach combines geographic information system and Monte Carlo capabilities with several scales of computer modeling for southern pine species...
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Global ozone and air quality: a multi-model assessment of risks to human health and crops
NASA Astrophysics Data System (ADS)
Ellingsen, K.; Gauss, M.; van Dingenen, R.; Dentener, F. J.; Emberson, L.; Fiore, A. M.; Schultz, M. G.; Stevenson, D. S.; Ashmore, M. R.; Atherton, C. S.; Bergmann, D. J.; Bey, I.; Butler, T.; Drevet, J.; Eskes, H.; Hauglustaine, D. A.; Isaksen, I. S. A.; Horowitz, L. W.; Krol, M.; Lamarque, J. F.; Lawrence, M. G.; van Noije, T.; Pyle, J.; Rast, S.; Rodriguez, J.; Savage, N.; Strahan, S.; Sudo, K.; Szopa, S.; Wild, O.
2008-02-01
Within ACCENT, a European Network of Excellence, eighteen atmospheric models from the U.S., Europe, and Japan calculated present (2000) and future (2030) concentrations of ozone at the Earth's surface with hourly temporal resolution. Comparison of model results with surface ozone measurements in 14 world regions indicates that levels and seasonality of surface ozone in North America and Europe are characterized well by global models, with annual average biases typically within 5-10 nmol/mol. However, comparison with rather sparse observations over some regions suggest that most models overestimate annual ozone by 15-20 nmol/mol in some locations. Two scenarios from the International Institute for Applied Systems Analysis (IIASA) and one from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (IPCC SRES) have been implemented in the models. This study focuses on changes in near-surface ozone and their effects on human health and vegetation. Different indices and air quality standards are used to characterise air quality. We show that often the calculated changes in the different indices are closely inter-related. Indices using lower thresholds are more consistent between the models, and are recommended for global model analysis. Our analysis indicates that currently about two-thirds of the regions considered do not meet health air quality standards, whereas only 2-4 regions remain below the threshold. Calculated air quality exceedances show moderate deterioration by 2030 if current emissions legislation is followed and slight improvements if current emissions reduction technology is used optimally. For the "business as usual" scenario severe air quality problems are predicted. We show that model simulations of air quality indices are particularly sensitive to how well ozone is represented, and improved accuracy is needed for future projections. Additional measurements are needed to allow a more quantitative assessment of the risks to human health and vegetation from changing levels of surface ozone.
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Recent assessments have analyzed the health impacts of PM2.5 from emissions from different locations and sectors using simplified or reduced-form air quality models. Here we present an alternative approach using the adjoint of the Community Multiscale Air Quality (CMAQ) model, wh...
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Are Model PISA Pupils Happy at School? Quality of School Life of Adolescents in Finland and Korea
ERIC Educational Resources Information Center
Yoon, Junghyun; Järvinen, Tero
2016-01-01
This paper explores the quality of school life (QSL) of two 'model pupils' in Programme for International Student Assessment (PISA) tests, Finland and Korea, and investigates students' views on the central aspects of QSL ("general satisfaction," "peer relations" and "teacher-student relations") using PISA 2012 data.…
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NASA Technical Reports Server (NTRS)
Stringer, Mary T.; Cowen, Brandon; Hoffler, Keith D.; Couch, Jesse C.; Ogburn, Marilyn E.; Diebler, Corey G.
2013-01-01
The NASA Langley Research Center Cockpit Motion Facility (CMF) was used to conduct a piloted simulation assessment of the impact of flexible structures on flying qualities. The CMF was used because of its relatively high bandwidth, six degree-of-freedom motion capability. Previous studies assessed and attempted to mitigate the effects of multiple dynamic aeroservoelastic modes (DASE). Those results indicated problems existed, but the specific cause and effect was difficult to ascertain. The goal of this study was to identify specific DASE frequencies, damping ratios, and gains that cause degradation in handling qualities. A generic aircraft simulation was developed and designed to have Cooper-Harper Level 1 handling qualities when flown without DASE models. A test matrix of thirty-six DASE modes was implemented. The modes had frequencies ranging from 1 to 3.5 Hz and were applied to each axis independently. Each mode consisted of a single axis, frequency, damping, and gain, and was evaluated individually by six subject pilots with test pilot backgrounds. Analysis completed to date suggests that a number of the DASE models evaluated degrade the handling qualities of this class of aircraft to an uncontrollable condition.
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De Leeuw, R A; Westerman, Michiel; Nelson, E; Ket, J C F; Scheele, F
2016-07-08
E-learning is driving major shifts in medical education. Prioritizing learning theories and quality models improves the success of e-learning programs. Although many e-learning quality standards are available, few are focused on postgraduate medical education. We conducted an integrative review of the current postgraduate medical e-learning literature to identify quality specifications. The literature was thematically organized into a working model. Unique quality specifications (n = 72) were consolidated and re-organized into a six-domain model that we called the Postgraduate Medical E-learning Model (Postgraduate ME Model). This model was partially based on the ISO-19796 standard, and drew on cognitive load multimedia principles. The domains of the model are preparation, software design and system specifications, communication, content, assessment, and maintenance. This review clarified the current state of postgraduate medical e-learning standards and specifications. It also synthesized these specifications into a single working model. To validate our findings, the next-steps include testing the Postgraduate ME Model in controlled e-learning settings.
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Long, Shicheng; Zhu, Yun; Jang, Carey; Lin, Che-Jen; Wang, Shuxiao; Zhao, Bin; Gao, Jian; Deng, Shuang; Xie, Junping; Qiu, Xuezhen
2016-03-01
This article describes the development and application of a streamlined air control and response modeling system with a novel response surface modeling-linear coupled fitting method and a new module to provide streamlined model data for PM2.5 attainment assessment in China. This method is capable of significantly reducing the dimensions required to establish a response surface model, as well as capturing more realistic response of PM2.5 to emission changes with a limited number of model simulations. The newly developed module establishes a data link between the system and the Software for Model Attainment Test-Community Edition (SMAT-CE), and has the ability to rapidly provide model responses to emission control scenarios for SMAT-CE using a simple interface. The performance of this streamlined system is demonstrated through a case study of the Yangtze River Delta (YRD) in China. Our results show that this system is capable of reproducing the Community Multi-Scale Air Quality (CMAQ) model simulation results with maximum mean normalized error<3.5%. It is also demonstrated that primary emissions make a major contribution to ambient levels of PM2.5 in January and August (e.g., more than 50% contributed by primary emissions in Shanghai), and Shanghai needs to have regional emission control both locally and in its neighboring provinces to meet China's annual PM2.5 National Ambient Air Quality Standard. The streamlined system provides a real-time control/response assessment to identify the contributions of major emission sources to ambient PM2.5 (and potentially O3 as well) and streamline air quality data for SMAT-CE to perform attainment assessments. Copyright © 2015. Published by Elsevier B.V.
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Managing Chronic Disease in Ontario Primary Care: The Impact of Organizational Factors
Russell, Grant M.; Dahrouge, Simone; Hogg, William; Geneau, Robert; Muldoon, Laura; Tuna, Meltem
2009-01-01
PURPOSE New approaches to chronic disease management emphasize the need to improve the delivery of primary care services to meet the needs of chronically ill patients. This study (1) assessed whether chronic disease management differed among 4 models of primary health care delivery and (2) identified which practice organizational factors were independently associated with high-quality care. METHODS We undertook a cross-sectional survey with nested qualitative case studies (2 practices per model) in 137 randomly selected primary care practices from 4 delivery models in Ontario Canada: fee for service, capitation, blended payment, and community health centers (CHCs). Practice and clinician surveys were based on the Primary Care Assessment Tool. A chart audit assessed evidence-based care delivery for patients with diabetes, congestive heart failure, and coronary artery disease. Intermediate outcomes were calculated for patients with diabetes and hypertension. Multiple linear regression identified those organizational factors independently associated with chronic disease management. RESULTS Chronic disease management was superior in CHCs. Clinicians in CHCs found it easier than those in the other models to promote high-quality care through longer consultations and interprofessional collaboration. Across the whole sample and independent of model, high-quality chronic disease management was associated with the presence of a nurse-practitioner. It was also associated with lower patient-family physician ratios and when practices had 4 or fewer full-time-equivalent family physicians. CONCLUSIONS The study adds to the literature supporting the value of nurse-practitioners within primary care teams and validates the contributions of Ontario’s CHCs. Our observation that quality of care decreased in larger, busier practices suggests that moves toward larger practices and greater patient-physician ratios may have unanticipated negative effects on processes of care quality. PMID:19597168
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Post, Ellen S.; Grambsch, Anne; Weaver, Chris; Morefield, Philip; Leung, Lai-Yung; Nolte, Christopher G.; Adams, Peter; Liang, Xin-Zhong; Zhu, Jin-Hong; Mahoney, Hardee
2012-01-01
Background: Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices. Objectives: Our goal was to assess the sensitivity of estimated ozone-related human health impacts of climate change to key modeling choices. Methods: Our analysis included seven modeling systems in which a climate change model is linked to an air quality model, five population projections, and multiple concentration–response functions. Using the U.S. Environmental Protection Agency’s (EPA’s) Environmental Benefits Mapping and Analysis Program (BenMAP), we estimated future ozone (O3)-related health effects in the United States attributable to simulated climate change between the years 2000 and approximately 2050, given each combination of modeling choices. Health effects and concentration–response functions were chosen to match those used in the U.S. EPA’s 2008 Regulatory Impact Analysis of the National Ambient Air Quality Standards for O3. Results: Different combinations of methodological choices produced a range of estimates of national O3-related mortality from roughly 600 deaths avoided as a result of climate change to 2,500 deaths attributable to climate change (although the large majority produced increases in mortality). The choice of the climate change and the air quality model reflected the greatest source of uncertainty, with the other modeling choices having lesser but still substantial effects. Conclusions: Our results highlight the need to use an ensemble approach, instead of relying on any one set of modeling choices, to assess the potential risks associated with O3-related human health effects resulting from climate change. PMID:22796531
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The Quality Imperative for Palliative Care
Kamal, Arif H.; Hanson, Laura C.; Casarett, David J.; Dy, Sydney M.; Pantilat, Steven Z.; Lupu, Dale; Abernethy, Amy P.
2015-01-01
Palliative medicine must prioritize the routine assessment of the quality of clinical care we provide. This includes regular assessment, analysis, and reporting of data on quality. Assessment of quality informs opportunities for improvement and demonstrates to our peers and ourselves the value of our efforts. In fact, continuous messaging of the value of palliative care services is needed to sustain our discipline; this requires regularly evaluating the quality of our care. As the reimbursement mechanisms for health care in the United States shift from fee-for-service to fee-for-value models, palliative care will be expected to report robust data on quality of care. We must move beyond demonstrating to our constituents (including patients and referrers), “here is what we do,” and increase the focus on “this is how well we do it” and “let’s see how we can do it better.” It is incumbent on palliative care professionals to lead these efforts. This involves developing standardized methods to collect data without adding additional burden, comparing and sharing our experiences to promote discipline-wide quality assessment and improvement initiatives, and demonstrating our intentions for quality improvement on the clinical frontline. PMID:25057987
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Water quality modelling of an impacted semi-arid catchment using flow data from the WEAP model
NASA Astrophysics Data System (ADS)
Slaughter, Andrew R.; Mantel, Sukhmani K.
2018-04-01
The continuous decline in water quality in many regions is forcing a shift from quantity-based water resources management to a greater emphasis on water quality management. Water quality models can act as invaluable tools as they facilitate a conceptual understanding of processes affecting water quality and can be used to investigate the water quality consequences of management scenarios. In South Africa, the Water Quality Systems Assessment Model (WQSAM) was developed as a management-focussed water quality model that is relatively simple to be able to utilise the small amount of available observed data. Importantly, WQSAM explicitly links to systems (yield) models routinely used in water resources management in South Africa by using their flow output to drive water quality simulations. Although WQSAM has been shown to be able to represent the variability of water quality in South African rivers, its focus on management from a South African perspective limits its use to within southern African regions for which specific systems model setups exist. Facilitating the use of WQSAM within catchments outside of southern Africa and within catchments for which these systems model setups to not exist would require WQSAM to be able to link to a simple-to-use and internationally-applied systems model. One such systems model is the Water Evaluation and Planning (WEAP) model, which incorporates a rainfall-runoff component (natural hydrology), and reservoir storage, return flows and abstractions (systems modelling), but within which water quality modelling facilities are rudimentary. The aims of the current study were therefore to: (1) adapt the WQSAM model to be able to use as input the flow outputs of the WEAP model and; (2) provide an initial assessment of how successful this linkage was by application of the WEAP and WQSAM models to the Buffalo River for historical conditions; a small, semi-arid and impacted catchment in the Eastern Cape of South Africa. The simulations of the two models were compared to the available observed data, with the initial focus within WQSAM on a simulation of instream total dissolved solids (TDS) and nutrient concentrations. The WEAP model was able to adequately simulate flow in the Buffalo River catchment, with consideration of human inputs and outputs. WQSAM was adapted to successfully take as input the flow output of the WEAP model, and the simulations of nutrients by WQSAM provided a good representation of the variability of observed nutrient concentrations in the catchment. This study showed that the WQSAM model is able to accept flow inputs from the WEAP model, and that this approach is able to provide satisfactory estimates of both flow and water quality for a small, semi-arid and impacted catchment. It is hoped that this research will encourage the application of WQSAM to an increased number of catchments within southern Africa and beyond.
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Natural language processing in an intelligent writing strategy tutoring system.
McNamara, Danielle S; Crossley, Scott A; Roscoe, Rod
2013-06-01
The Writing Pal is an intelligent tutoring system that provides writing strategy training. A large part of its artificial intelligence resides in the natural language processing algorithms to assess essay quality and guide feedback to students. Because writing is often highly nuanced and subjective, the development of these algorithms must consider a broad array of linguistic, rhetorical, and contextual features. This study assesses the potential for computational indices to predict human ratings of essay quality. Past studies have demonstrated that linguistic indices related to lexical diversity, word frequency, and syntactic complexity are significant predictors of human judgments of essay quality but that indices of cohesion are not. The present study extends prior work by including a larger data sample and an expanded set of indices to assess new lexical, syntactic, cohesion, rhetorical, and reading ease indices. Three models were assessed. The model reported by McNamara, Crossley, and McCarthy (Written Communication 27:57-86, 2010) including three indices of lexical diversity, word frequency, and syntactic complexity accounted for only 6% of the variance in the larger data set. A regression model including the full set of indices examined in prior studies of writing predicted 38% of the variance in human scores of essay quality with 91% adjacent accuracy (i.e., within 1 point). A regression model that also included new indices related to rhetoric and cohesion predicted 44% of the variance with 94% adjacent accuracy. The new indices increased accuracy but, more importantly, afford the means to provide more meaningful feedback in the context of a writing tutoring system.
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BASINS Climate Assessment Tool Tutorials
The BASINS Climate Assessment Tool (CAT) provides a flexible set of capabilities for exploring the potential effects of climate change on streamflow and water quality using different watershed models in BASINS.
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Comparison of SWAT Model Water Balance Calibration Using NEXRAD and Surface Rain Gauge Data
USDA-ARS?s Scientific Manuscript database
The value of watershed-scale, water quality models to ecosystem management is increasingly evident as more programs adopt these tools to help assess the effectiveness of different management scenarios on the environment. The USDA-Conservation Effects Assessment Project (CEAP) is one such program whi...
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We demonstrate a novel, spatially explicit assessment of the current condition of aquatic ecosystem services, with limited sensitivity analysis for the atmospheric contaminant mercury. The Integrated Ecological Modeling System (IEMS) forecasts water quality and quantity, habitat ...
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Various technological pathways can lead to reduced CO2 emissions. However, different pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. The Global Change Assessment Model (GCAM) is a high resolu...
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Development of cropland management dataset to support U.S. SWAT assessments
USDA-ARS?s Scientific Manuscript database
The Soil and Water Assessment Tool (SWAT) is a widely used hydrologic/water quality simulation model in the U.S. Process-based models like SWAT require a great deal of data to accurately represent the natural world, including topography, landuse, soils, weather, and management. With the exception ...
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Lehotsky, Á; Szilágyi, L; Bánsághi, S; Szerémy, P; Wéber, G; Haidegger, T
2017-09-01
Ultraviolet spectrum markers are widely used for hand hygiene quality assessment, although their microbiological validation has not been established. A microbiology-based assessment of the procedure was conducted. Twenty-five artificial hand models underwent initial full contamination, then disinfection with UV-dyed hand-rub solution, digital imaging under UV-light, microbiological sampling and cultivation, and digital imaging of the cultivated flora were performed. Paired images of each hand model were registered by a software tool, then the UV-marked regions were compared with the pathogen-free sites pixel by pixel. Statistical evaluation revealed that the method indicates correctly disinfected areas with 95.05% sensitivity and 98.01% specificity. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.
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Rezaei, Satar; Matin, Behzad Karami; Moradi, Khalil; Bijan, Behroz; Fallahi, Masoud; Shokati, Behnam; Saeidi, Hamid
2016-03-01
The main mission of hospitals in any health system is to deliver high quality healthcare for patients and meet their needs and expectations. The aim of the current study was to assess the quality of the service of educational hospitals affiliated with Kermanshah University of Medical Sciences in 2015, from the perspective of patients. In this cross-sectional study, the perspectives of 400 patients were assessed about the quality of the services provided by educational hospitals in Kermanshah (western Iran) in 2015. The quality was assessed by the SERVQUAL questionnaire with five dimensions, i.e., tangibility, reliability, responsiveness, assurance, and empathy. In addition, the Wilcoxon test and the Kruskal-Wallis test were used to explore any association between the dependent variable and explanatory variables. The data were analyzed using Stata V.12 software. There were negative gaps in all five dimensions. The highest and lowest gaps in the mean score were found in the assurance (-0.88) and responsiveness (-0.56) dimensions. The patients ranked responsiveness as the most important dimension of the quality of healthcare. There were gaps between the patients' perceptions and their expectation about the five dimensions that were studied based on the SERVQUAL model. Also, it is recommended that improving the quality of healthcare is possible by various policies, such as good responsiveness, access to health workers, and delivering healthcare in less time.
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Data envelopment analysis in service quality evaluation: an empirical study
NASA Astrophysics Data System (ADS)
Najafi, Seyedvahid; Saati, Saber; Tavana, Madjid
2015-09-01
Service quality is often conceptualized as the comparison between service expectations and the actual performance perceptions. It enhances customer satisfaction, decreases customer defection, and promotes customer loyalty. Substantial literature has examined the concept of service quality, its dimensions, and measurement methods. We introduce the perceived service quality index (PSQI) as a single measure for evaluating the multiple-item service quality construct based on the SERVQUAL model. A slack-based measure (SBM) of efficiency with constant inputs is used to calculate the PSQI. In addition, a non-linear programming model based on the SBM is proposed to delineate an improvement guideline and improve service quality. An empirical study is conducted to assess the applicability of the method proposed in this study. A large number of studies have used DEA as a benchmarking tool to measure service quality. These models do not propose a coherent performance evaluation construct and consequently fail to deliver improvement guidelines for improving service quality. The DEA models proposed in this study are designed to evaluate and improve service quality within a comprehensive framework and without any dependency on external data.
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NASA Astrophysics Data System (ADS)
Booth, N. L.; Everman, E.; Kuo, I.; Sprague, L.; Murphy, L.
2011-12-01
A new web-based decision support system has been developed as part of the U.S. Geological Survey (USGS) National Water Quality Assessment Program's (NAWQA) effort to provide ready access to Spatially Referenced Regressions On Watershed attributes (SPARROW) results of stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via an intuitive graphical user interface with a map-based display. The SPARROW Decision Support System (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions, distribution of nutrient sources, nutrient delivery to downstream waterbodies, and simulations of altered nutrient inputs including atmospheric and agricultural sources. The DSS offers other features for analysis including various background map layers, model output exports, and the ability to save and share prediction scenarios. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. The underlying modeling framework and server infrastructure illustrate innovations in the information technology and geosciences fields for delivering SPARROW model predictions over the web by performing intensive model computations and map visualizations of the predicted conditions within the stream network.
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NASA Astrophysics Data System (ADS)
Hancock, G. R.; Willgoose, G. R.; Cohen, S.
2009-12-01
Recently there has been recognition that changing climate will affect rainfall and storm patterns with research directed to examine how the global hydrological cycle will respond to climate change. This study investigates the effect of different rainfall patterns on erosion and resultant water quality for a well studied tropical monsoonal catchment that is undisturbed by Europeans in the Northern Territory, Australia. Water quality has a large affect on a range of aquatic flora and fauna and a significant change in sediment could have impacts on the aquatic ecosystems. There have been several studies of the effect of climate change on rainfall patterns in the study area with projections indicating a significant increase in storm activity. Therefore it is important that the impact of this variability be assessed in terms of catchment hydrology, sediment transport and water quality. Here a numerical model of erosion and hydrology (CAESAR) is used to assess several different rainfall scenarios over a 1000 year modelled period. The results show that that increased rainfall amount and intensity increases sediment transport rates but predicted water quality was variable and non-linear but within the range of measured field data for the catchment and region. Therefore an assessment of sediment transport and water quality is a significant and complex issue that requires further understandings of the role of biophysical feedbacks such as vegetation as well as the role of humans in managing landscapes (i.e. controlled and uncontrolled fire). The study provides a robust methodology for assessing the impact of enhanced climate variability on sediment transport and water quality.
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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…
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ERIC Educational Resources Information Center
Mark, Katharine M.; Pike, Alison
2017-01-01
We investigated the association between marital quality and child behavior, assessing mother-child relationship quality as a potential mediator. The sample included 78 mothers with two target children (mean ages = 9.82 and 12.05 years, respectively). Mothers reported on their children's behavior as well as their marital quality, while each child…
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Regional photochemical air quality modeling in the Mexico-US border area
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mendoza, A.; Russell, A.G.; Mejia, G.M.
1998-12-31
The Mexico-United States border area has become an increasingly important region due to its commercial, industrial and urban growth. As a result, environmental concerns have risen. Treaties like the North American Free Trade Agreement (NAFTA) have further motivated the development of environmental impact assessment in the area. Of particular concern are air quality, and how the activities on both sides of the border contribute to its degradation. This paper presents results of applying a three-dimensional photochemical airshed model to study air pollution dynamics along the Mexico-United States border. In addition, studies were conducted to assess how size resolution impacts themore » model performance. The model performed within acceptable statistic limits using 12.5 x 12.5 km{sup 2} grid cells, and the benefits using finer grids were limited. Results were further used to assess the influence of grid-cell size on the modeling of control strategies, where coarser grids lead to significant loss of information.« less
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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.
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Assessment of Soil Environmental Quality in Huangguoshu Waterfalls Scenic Area
NASA Astrophysics Data System (ADS)
Luo, Rongbin; Feng, Kaiyu; Gu, Bo; Xu, Chengcheng
2018-03-01
This paper concentrates on five major heavy metal pollutants as soil environmental quality evaluation factors, respectively Lead (Pb), Cadmium (Cd), Mercury (Hg), Arsenic (As), Chromium (Cr), based on the National Soil Environmental Quality Standards (GB15618 - 1995), we used single factor index evaluation model of soil environmental quality and comprehensive index evaluation model to analyze surface soil environmental quality in the Huangguoshu Waterfalls scenic area. Based on surface soil analysis, our results showed that the individual contamination index, Pb, Hg, As and Cr in the Huangguoshu Waterfalls scenic area met class I according to requirements of National Soil Environmental Quality Standards, which indicated that Pb, Hg, As and Cr were not main heavy metal pollutants in this area, but the individual contamination index of Cd in soil was seriously exceeded National Soil Environmental Quality Standards’ requirement. Soil environmental quality in Shitouzhai, Luoshitan, Langgong Hongyan Power Plant have exceeded the requirement of National Soil Environmental Quality Standards “0.7< Pc≤ 1.0” (Alert Level), these soils had been slightly polluted; the classification of soil environmental quality assessment in Longgong downstream area was above “Alert Level”, it indicated that soil in this area was not polluted. Above all, relevant measures for soil remediation are put forward.
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Clavijo, Araceli; Kronberg, María Florencia; Rossen, Ariana; Moya, Aldana; Calvo, Daniel; Salatino, Santa Esmeralda; Pagano, Eduardo Antonio; Morábito, José Antonio; Munarriz, Eliana Rosa
2016-11-01
Determination of water quality status in rivers is critical to establish a sustainable water management policy. For this reason, over the last decades it has been recommended to perform integrated water assessments that include water quantities and physicochemical, ecological and toxicological tests. However, sometimes resources are limited and it is not possible to perform large-scale chemical determinations of pollutants or conduct numerous ecotoxicological tests. To overcome this problem we use and measure the growth, as a response parameter, of the soil nematode Caenorhabditis elegans to assess water quality in rivers. The C. elegans is a ubiquitous organism that has emerged as an important model organism in aquatic and soil toxicology research. The Tunuyán River Basin (Province of Mendoza, Argentina) has been selected as a representative traditional water monitoring system to test the applicability of the C. elegans toxicological bioassay to generate an integrated water quality evaluation. Jointly with the C. elegans toxic assays, physicochemical and bacteriological parameters were determined for each monitoring site. C. elegans bioassays help to identify different water qualities in the river basin. Multivariate statistical analysis (PCA and linear regression models) has allowed us to confirm that traditional water quality studies do not predict potential toxic effects on living organisms. On the contrary, physicochemical and bacteriological analyzes explain <62% of the C. elegans growth response variability, showing that ecotoxicological bioassays are important to obtain a realistic scenario of water quality threats. Our results confirm that the C. elegans bioassay is a sensible and suitable tool to assess toxicity and should be implemented in routine water quality monitoring. Copyright © 2016 Elsevier B.V. All rights reserved.
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Zessner, Matthias; Schönhart, Martin; Parajka, Juraj; Trautvetter, Helene; Mitter, Hermine; Kirchner, Mathias; Hepp, Gerold; Blaschke, Alfred Paul; Strenn, Birgit; Schmid, Erwin
2017-02-01
Changes in climatic conditions will directly affect the quality and quantity of water resources. Further on, they will affect them indirectly through adaptation in land use which ultimately influences diffuse nutrient emissions to rivers and therefore potentially the compliance with good ecological status according to the EU Water Framework Directive (WFD). We present an integrated impact modelling framework (IIMF) to track and quantify direct and indirect pollution impacts along policy-economy-climate-agriculture-water interfaces. The IIMF is applied to assess impacts of climatic and socio-economic drivers on agricultural land use (crop choices, farming practices and fertilization levels), river flows and the risk for exceedance of environmental quality standards for determination of the ecological water quality status in Austria. This article also presents model interfaces as well as validation procedures and results of single models and the IIMF with respect to observed state variables such as land use, river flow and nutrient river loads. The performance of the IIMF for calculations of river nutrient loads (120 monitoring stations) shows a Nash-Sutcliffe Efficiency of 0.73 for nitrogen and 0.51 for phosphorus. Most problematic is the modelling of phosphorus loads in the alpine catchments dominated by forests and mountainous landscape. About 63% of these catchments show a deviation between modelled and observed loads of 30% and more. In catchments dominated by agricultural production, the performance of the IIMF is much better as only 30% of cropland and 23% of permanent grassland dominated areas have a deviation of >30% between modelled and observed loads. As risk of exceedance of environmental quality standards is mainly recognized in catchments dominated by cropland, the IIMF is well suited for assessing the nutrient component of the WFD ecological status. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.
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Diagnosing Alzheimer's disease: a systematic review of economic evaluations.
Handels, Ron L H; Wolfs, Claire A G; Aalten, Pauline; Joore, Manuela A; Verhey, Frans R J; Severens, Johan L
2014-03-01
The objective of this study is to systematically review the literature on economic evaluations of interventions for the early diagnosis of Alzheimer's disease (AD) and related disorders and to describe their general and methodological characteristics. We focused on the diagnostic aspects of the decision models to assess the applicability of existing decision models for the evaluation of the recently revised diagnostic research criteria for AD. PubMed and the National Institute for Health Research Economic Evaluation database were searched for English-language publications related to economic evaluations on diagnostic technologies. Trial-based economic evaluations were assessed using the Consensus on Health Economic Criteria list. Modeling studies were assessed using the framework for quality assessment of decision-analytic models. The search retrieved 2109 items, from which eight decision-analytic modeling studies and one trial-based economic evaluation met all eligibility criteria. Diversity among the study objective and characteristics was considerable and, despite considerable methodological quality, several flaws were indicated. Recommendations were focused on diagnostic aspects and the applicability of existing models for the evaluation of recently revised diagnostic research criteria for AD. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.
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Booker, Kathy; Hilgenberg, Cheryl
2010-01-01
Nursing is often considered expensive in the cost analysis of academic programs. Yet nursing programs have the power to attract many students, and the national nursing shortage has resulted in a high demand for nurses. Methods to systematically assess programs across an entire university academic division are often dissimilar in technique and outcome. At a small, private, Midwestern university, a model for comprehensive program assessment, titled the Quality, Potential and Cost (QPC) model, was developed and applied to each major offered at the university through the collaborative effort of directors, chairs, deans, and the vice president for academic affairs. The QPC model provides a means of equalizing data so that single measures (such as cost) are not viewed in isolation. It also provides a common language to ensure that all academic leaders at an institution apply consistent methods for assessment of individual programs. The application of the QPC model allowed for consistent, fair assessments and the ability to allocate resources to programs according to strategic direction. In this article, the application of the QPC model to School of Nursing majors and other selected university majors will be illustrated. Copyright 2010 Elsevier Inc. All rights reserved.
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Zhou, Hongyi; Skolnick, Jeffrey
2010-01-01
In this work, we develop a method called FTCOM for assessing the global quality of protein structural models for targets of medium and hard difficulty (remote homology) produced by structure prediction approaches such as threading or ab initio structure prediction. FTCOM requires the Cα coordinates of full length models and assesses model quality based on fragment comparison and a score derived from comparison of the model to top threading templates. On a set of 361 medium/hard targets, FTCOM was applied to and assessed for its ability to improve upon the results from the SP3, SPARKS, PROSPECTOR_3, and PRO-SP3-TASSER threading algorithms. The average TM-score improves by 5%–10% for the first selected model by the new method over models obtained by the original selection procedure in the respective threading methods. Moreover the number of foldable targets (TM-score ≥0.4) increases from least 7.6% for SP3 to 54% for SPARKS. Thus, FTCOM is a promising approach to template selection. PMID:20455261
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Rehm, Colin D; Drewnowski, Adam
2017-09-13
Replacing the typical American breakfast with ready-to-eat cereals (RTECs) may improve diet quality. Our goal was to assess the impact of RTECs on diet quality measures for different age groups, using substitution modeling. Dietary intakes came from the 2007-2010 National Health and Examination Surveys (NHANES; n = 18,112). All breakfast foods, excluding beverages, were replaced on a per calorie basis, with frequency-weighted and age/race specific RTECs. Model 1 replaced foods with RTECs alone; Model 2 replaced foods with RTECs and milk. Diet quality measures were based on desirable food groups and nutrients, Healthy Eating Index (HEI)-2010 scores, and estimated diet costs. Model 1 diets were significantly higher in whole grains (+84.6%), fiber (+14.3%), vitamin D (+14.0%), iron (+54.5%) and folic acid (+104.6%), as compared to observed diets. Model 2 diets were additionally higher in dairy (+15.8%), calcium (+11.3%) and potassium (+3.95%). In Model 1, added sugar increased (+5.0%), but solid fats declined (-10.9%). Energy from solid fats and added sugars declined (-3.2%) in both models. Model 2 offered higher diet quality (57.1 vs. 54.6, p -value < 0.01) at a lower cost ($6.70 vs. $6.92; p < 0.01), compared to observed diets. Substitution modeling of NHANES data can assess the nutritional and economic impact of dietary guidance.
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Rehm, Colin D.; Drewnowski, Adam
2017-01-01
Replacing the typical American breakfast with ready-to-eat cereals (RTECs) may improve diet quality. Our goal was to assess the impact of RTECs on diet quality measures for different age groups, using substitution modeling. Dietary intakes came from the 2007–2010 National Health and Examination Surveys (NHANES; n = 18,112). All breakfast foods, excluding beverages, were replaced on a per calorie basis, with frequency-weighted and age/race specific RTECs. Model 1 replaced foods with RTECs alone; Model 2 replaced foods with RTECs and milk. Diet quality measures were based on desirable food groups and nutrients, Healthy Eating Index (HEI)-2010 scores, and estimated diet costs. Model 1 diets were significantly higher in whole grains (+84.6%), fiber (+14.3%), vitamin D (+14.0%), iron (+54.5%) and folic acid (+104.6%), as compared to observed diets. Model 2 diets were additionally higher in dairy (+15.8%), calcium (+11.3%) and potassium (+3.95%). In Model 1, added sugar increased (+5.0%), but solid fats declined (−10.9%). Energy from solid fats and added sugars declined (−3.2%) in both models. Model 2 offered higher diet quality (57.1 vs. 54.6, p-value < 0.01) at a lower cost ($6.70 vs. $6.92; p < 0.01), compared to observed diets. Substitution modeling of NHANES data can assess the nutritional and economic impact of dietary guidance. PMID:28902145
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Assessing the condition of bayous and estuaries: Bayou Chico Gulf of Mexico demonstration study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dickson, K.; Acevedo, M.; Waller, T.
1995-12-31
A demonstration study was conducted in May 1994 on Bayou Chico to assess the utility of various assessment and measurement endpoints in determining the condition of bayous and estuaries. Bayou Chico has water quality problems attributed to its low flushing rate and urban/industrial land use in its watershed. The sampling scheme assessed the within-sampling station and spatial variability of measurement endpoints. Fourteen sampling stations in Bayou Chico and 3 stations in Pensacola Bay were selected based on an intensified EMAP sampling grid. Time and space coordinated sampling was conducted for: sediment contaminants and properties, sediment toxicity, water quality, benthic infauna,more » zooplankton and phytoplankton populations. Fish and crabs were also collected and analyzed for a suite of biomarkers and organic chemical residues. Primary productivity was measured via the light bottle dark bottle oxygen method and via diurnal oxygen measurements made with continuous recording data sondes. Stream sites were evaluated for water and sediment quality, water and sediment toxicity, benthic invertebrates and fish. Watershed analyses included assessment of land use/landcover (via SPOT and TM images), soils, pollution sources (point and non-point) and hydrography. These data were coordinated via an Arc/Info GIS system for display and spatial analysis. 1994 survey data were used to parameterize environmental fate models such as SWMM (Storm Water Management Model), DYNHYD5 (WASP5 hydrodynamics model) and WASP5 (Water Quality Analysis Simulation Program) to make predictions about the dynamics and fate of chemical contaminants in Bayou Chico. This paper will present an overview, and report on the results in regards to within-site and spatial variability in Bayou Chico. Conclusions on the efficacy of the assessment and measurement endpoints in evaluating the condition (health) of Bayou Chico will be presented.« less
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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.
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Graffigna, Guendalina; Bonanomi, Andrea
2017-01-01
Background Increasing bodies of scientific research today examines the factors and interventions affecting patients’ ability to self-manage and adhere to treatment. Patient activation is considered the most reliable indicator of patients’ ability to manage health autonomously. Only a few studies have tried to assess the role of psychosocial factors in promoting patient activation. A more systematic modeling of the psychosocial factors explaining the variance of patient activation is needed. Objective To test the hypothesized effect of patient activation on medication adherence; to test the the hypothesized effects of positive emotions and of the quality of the patient/doctor relationship on patient activation; and to test the hypothesized mediating effect of Patient Health Engagement (PHE-model) in this pathway. Material and methods This cross-sectional study involved 352 Italian-speaking adult chronic patients. The survey included measures of i) patient activation (Patient Activation Measure 13 –short form); ii) Patient Health Engagement model (Patient Health Engagement Scale); iii) patient adherence (4 item-Morinsky Medication Adherence Scale); iv) the quality of the patients’ emotional feelings (Manikin Self Assessment Scale); v) the quality of the patient/doctor relationship (Health Care Climate Questionnaire). Structural equation modeling was used to test the hypotheses proposed. Results According to the theoretical model we hypothesized, research results confirmed that patients’ activation significantly affects their reported medication adherence. Moreover, psychosocial factors, such as the patients’ quality of the emotional feelings and the quality of the patient/doctor relationship were demonstrated to be factors affecting the level of patient activation. Finally, the mediation effect of the Patient Health Engagement model was confirmed by the analysis. Conclusions Consistently with the results of previous studies, these findings demonstrate that the Patient Health Engagement Model is a critical factor in enhancing the quality of care. The Patient Health Engagement Model might acts as a mechanism to increase patient activation and adherence. PMID:28654686
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Graffigna, Guendalina; Barello, Serena; Bonanomi, Andrea
2017-01-01
Increasing bodies of scientific research today examines the factors and interventions affecting patients' ability to self-manage and adhere to treatment. Patient activation is considered the most reliable indicator of patients' ability to manage health autonomously. Only a few studies have tried to assess the role of psychosocial factors in promoting patient activation. A more systematic modeling of the psychosocial factors explaining the variance of patient activation is needed. To test the hypothesized effect of patient activation on medication adherence; to test the the hypothesized effects of positive emotions and of the quality of the patient/doctor relationship on patient activation; and to test the hypothesized mediating effect of Patient Health Engagement (PHE-model) in this pathway. This cross-sectional study involved 352 Italian-speaking adult chronic patients. The survey included measures of i) patient activation (Patient Activation Measure 13 -short form); ii) Patient Health Engagement model (Patient Health Engagement Scale); iii) patient adherence (4 item-Morinsky Medication Adherence Scale); iv) the quality of the patients' emotional feelings (Manikin Self Assessment Scale); v) the quality of the patient/doctor relationship (Health Care Climate Questionnaire). Structural equation modeling was used to test the hypotheses proposed. According to the theoretical model we hypothesized, research results confirmed that patients' activation significantly affects their reported medication adherence. Moreover, psychosocial factors, such as the patients' quality of the emotional feelings and the quality of the patient/doctor relationship were demonstrated to be factors affecting the level of patient activation. Finally, the mediation effect of the Patient Health Engagement model was confirmed by the analysis. Consistently with the results of previous studies, these findings demonstrate that the Patient Health Engagement Model is a critical factor in enhancing the quality of care. The Patient Health Engagement Model might acts as a mechanism to increase patient activation and adherence.
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NASA Astrophysics Data System (ADS)
Osterman, G. B.; Neu, J. L.; Eldering, A.; Pinder, R. W.; Tang, Y.; McQueen, J.
2014-12-01
Most regional scale models that are used for air quality forecasts and ozone source attribution do not adequately capture the distribution of ozone in the mid- and upper troposphere, but it is unclear how this shortcoming relates to their ability to simulate surface ozone. We combine ozone profile data from the NASA Earth Observing System (EOS) Tropospheric Emission Spectrometer (TES) and a new joint product from TES and the Ozone Monitoring Instrument along with ozonesonde measurements and EPA AirNow ground station ozone data to examine air quality events during August 2006 in the Community Multi-Scale Air Quality (CMAQ) and National Air Quality Forecast Capability (NAQFC) models. We present both aggregated statistics and case-study analyses with the goal of assessing the relationship between the models' ability to reproduce surface air quality events and their ability to capture the vertical distribution of ozone. We find that the models lack the mid-tropospheric ozone variability seen in TES and the ozonesonde data, and discuss the conditions under which this variability appears to be important for surface air quality.
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Measurements of Protein Crystal Face Growth Rates
NASA Technical Reports Server (NTRS)
Gorti, S.
2014-01-01
Protein crystal growth rates will be determined for several hyperthermophile proteins.; The growth rates will be assessed using available theoretical models, including kinetic roughening.; If/when kinetic roughening supersaturations are established, determinations of protein crystal quality over a range of supersaturations will also be assessed.; The results of our ground based effort may well address the existence of a correlation between fundamental growth mechanisms and protein crystal quality.
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Since aviation gasoline is now the largest remaining source of lead (Pb) emissions to the air in the United States, there is increased interest by regulatory agencies and the public in assessing the impacts on residents living in close proximity to these sources. An air quality m...
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Temporal evolution modeling of hydraulic and water quality performance of permeable pavements
NASA Astrophysics Data System (ADS)
Huang, Jian; He, Jianxun; Valeo, Caterina; Chu, Angus
2016-02-01
A mathematical model for predicting hydraulic and water quality performance in both the short- and long-term is proposed based on field measurements for three types of permeable pavements: porous asphalt (PA), porous concrete (PC), and permeable inter-locking concrete pavers (PICP). The model was applied to three field-scale test sites in Calgary, Alberta, Canada. The model performance was assessed in terms of hydraulic parameters including time to peak, peak flow and water balance and a water quality variable (the removal rate of total suspended solids). A total of 20 simulated storm events were used for model calibration and verification processes. The proposed model can simulate the outflow hydrographs with a coefficient of determination (R2) ranging from 0.762 to 0.907, and normalized root-mean-square deviation (NRMSD) ranging from 13.78% to 17.83%. Comparison of the time to peak flow, peak flow, runoff volume and TSS removal rates between the measured and modeled values in model verification phase had a maximum difference of 11%. The results demonstrate that the proposed model is capable of capturing the temporal dynamics of the pavement performance. Therefore, the model has great potential as a practical modeling tool for permeable pavement design and performance assessment.
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Evaluation of near surface ozone and particulate matter in air ...
In this study, techniques typically used for future air quality projections are applied to a historical 11-year period to assess the performance of the modeling system when the driving meteorological conditions are obtained using dynamical downscaling of coarse-scale fields without correcting toward higher-resolution observations. The Weather Research and Forecasting model and the Community Multiscale Air Quality model are used to simulate regional climate and air quality over the contiguous United States for 2000–2010. The air quality simulations for that historical period are then compared to observations from four national networks. Comparisons are drawn between defined performance metrics and other published modeling results for predicted ozone, fine particulate matter, and speciated fine particulate matter. The results indicate that the historical air quality simulations driven by dynamically downscaled meteorology are typically within defined modeling performance benchmarks and are consistent with results from other published modeling studies using finer-resolution meteorology. This indicates that the regional climate and air quality modeling framework utilized here does not introduce substantial bias, which provides confidence in the method’s use for future air quality projections. This paper shows that if emissions inputs and coarse-scale meteorological inputs are reasonably accurate, then air quality can be simulated with acceptable accuracy even wi
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Kirsch, Florian
2015-04-01
Smoking cessation is the only strategy that has shown a lasting reduction in the decline of lung function in patients with chronic obstructive pulmonary disease. This study aims to evaluate the cost-effectiveness of smoking cessation interventions in patients with chronic obstructive pulmonary disease, to assess the quality of the Markov models and to estimate the consequences of model structure and input data on cost-effectiveness. A systematic literature search was conducted in PubMed, Embase, BusinessSourceComplete and Econlit on June 11, 2014. Data were extracted, and costs were inflated. Model quality was evaluated by a quality appraisal, and results were interpreted. Ten studies met the inclusion criteria. The results varied widely from cost savings to additional costs of €17,004 per quality adjusted life year. The models scored best in the category structure, followed by data and consistency. The quality of the models seems to rise over time, and regarding the results there is no economic reason to refuse the reimbursement of any smoking cessation intervention.
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NASA Astrophysics Data System (ADS)
Jia, Huizhen; Sun, Quansen; Ji, Zexuan; Wang, Tonghan; Chen, Qiang
2014-11-01
The goal of no-reference/blind image quality assessment (NR-IQA) is to devise a perceptual model that can accurately predict the quality of a distorted image as human opinions, in which feature extraction is an important issue. However, the features used in the state-of-the-art "general purpose" NR-IQA algorithms are usually natural scene statistics (NSS) based or are perceptually relevant; therefore, the performance of these models is limited. To further improve the performance of NR-IQA, we propose a general purpose NR-IQA algorithm which combines NSS-based features with perceptually relevant features. The new method extracts features in both the spatial and gradient domains. In the spatial domain, we extract the point-wise statistics for single pixel values which are characterized by a generalized Gaussian distribution model to form the underlying features. In the gradient domain, statistical features based on neighboring gradient magnitude similarity are extracted. Then a mapping is learned to predict quality scores using a support vector regression. The experimental results on the benchmark image databases demonstrate that the proposed algorithm correlates highly with human judgments of quality and leads to significant performance improvements over state-of-the-art methods.
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Ma, Deqiang; Zhang, Liyu; Fang, Qinhua; Jiang, Yuwu; Elliott, Michael
2017-05-15
Large scale coastal land-claim and sea-enclosing (CLASE) activities have caused habitat destruction, biodiversity losses and water deterioration, thus the local governments in China have recently undertaken seabed dredging and dyke opening (SDADO) as typical ecological restoration projects. However, some projects focus on a single impact on hydrodynamic conditions, water quality or marine organisms. In a case study in Xiamen, China, an integrated effects assessment framework centres on ecohydrology, using modeling of hydrodynamic conditions and statistical analysis of water quality, was developed to assess the effects of ecological restoration projects. The benefits of SDADO projects include improving hydrodynamic conditions and water quality, as a precursor to further marine biological improvements. This study highlights the need to comprehensively consider ecological effects of SDADO projects in the planning stage, and an integrative assessment method combining cumulative effects of hydrodynamic conditions, water quality and biological factors. Copyright © 2017 Elsevier Ltd. All rights reserved.
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2011-11-01
assessment to quality of localization/characterization estimates. This protocol includes four critical components: (1) a procedure to identify the...critical factors impacting SHM system performance; (2) a multistage or hierarchical approach to SHM system validation; (3) a model -assisted evaluation...Lindgren, E. A ., Buynak, C. F., Steffes, G., Derriso, M., “ Model -assisted Probabilistic Reliability Assessment for Structural Health Monitoring
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Merit Scholarships Are No Quick Fix for College Quality.
ERIC Educational Resources Information Center
Kealy, Mary Jo; Rockel, Mark L.
1988-01-01
Presents a method allowing college leaders to assess the potential success of an academic merit scholarship program. Specifies a college choice model accounting for the price/quality trade-off, using Colgate University as an example. Quality differences between schools in an individual's choice set are the most important determinants of college…
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Managing Change to a Quality Philosophy: A Partnership Perspective.
ERIC Educational Resources Information Center
Snyder, Karolyn J.; Acker-Hocevar, Michele
Within the past 5 years there has been an international movement to adapt the principles and practices of Total Quality Management work environments to school-restructuring agendas. This paper reports on the development of a model called the Educational Quality System, a benchmark assessment tool for identifying the essential elements of quality…
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USDA-ARS?s Scientific Manuscript database
Pasta is a simple food made from water and durum wheat (Triticum turgidum subsp. durum) semolina. As pasta increases in popularity, studies have endeavored to analyze the attributes that contribute to high quality pasta. Despite being a simple food, the laboratory scale analysis of pasta quality is ...
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ERIC Educational Resources Information Center
Azkiyah, Siti Nurul; Mukminin, Amirul
2017-01-01
This study was intended to investigate the teaching quality of student teachers when they conducted their teaching practicum. Teaching quality is conceptualised based on eight classroom factors (orientation, structuring, modelling, application, questioning, building classroom as a learning environment, assessment, and time management) of the…
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Minnesota 4-H Youth Program Quality Improvement Model
ERIC Educational Resources Information Center
Herman, Margo; Grant, Samantha
2015-01-01
The University of Minnesota Extension Center for Youth Development made an organizational decision in 2011 to invest in a system-wide approach to implement youth program quality into the 4-H program using the Youth Program Quality Assessment (YPQA) tool. This article describes the four key components to the Minnesota Youth Program Quality…
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Statistical Analysis of Regional Surface Water Quality in Southeastern Ontario.
ERIC Educational Resources Information Center
Bodo, Byron A.
1992-01-01
Historical records from Ontario's Provincial Water Quality Monitoring Network for rivers and streams were analyzed to assess the feasibility of mapping regional water quality patterns in southeastern Ontario, spanning the Precambrian Shield and the St. Lawrence Lowlands. The study served as a model for much of Ontario. (54 references) (Author/MDH)
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A Strategic Quality Assurance Framework in an African Higher Education Context
ERIC Educational Resources Information Center
Ansah, Francis
2015-01-01
This study is based on a pragmatist analysis of selected international accounts on quality assurance in higher education. A pragmatist perspective was used to conceptualise a logical internal quality assurance model to embed and support the alignment of graduate competencies in curriculum and assessment of Ghanaian polytechnics. Through focus…
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Environmetric data interpretation to assess the water quality of Maritsa River catchment.
Papazova, Petia; Simeonova, Pavlina
2013-01-01
Maritsa River is one of the largest rivers flowing on Bulgarian territory. The quality of its waters is of substantial importance for irrigation, industrial, recreation and domestic use. Besides, part of the river is flowing on Turkish territory and the control and management of the Maritsa catchment is of mutual interst for the neighboring countires. Thus, performing interpretation and modeling of the river water quality is a major environmetric problem. Two multivariate statstical methods (Cluster analysis/CA/and Principal components analysis/PCA/) were applied for model assessment of the water quality of Maritsa River on Bulgarian territory. The study used long-term monitoring data from 21 sampling sites characterized by 8 surface water quality indicators. The application of CA to the indicators results in 3 significant clusters showing the impact of biological, anthropogenic and eutrophication sources. For further assessment of the monitoring data, PCA was implemented, which identified, again,three latent factors confirming, in principle, the clustering output. The latent factors were conditionally named "biologic", "anthropogenic" and "eutrophication" source. Their identification coinside correctly to the location of real pollution sources along the Maritsa River catchment. The linkage of the sampling sites along the river flow by CA identified four special patterns separated by specific tracers levels: biological and anthropogenic major impact for pattern 1, euthrophication major impact for pattern 2, background levels for pattern 3 and eutrophication and agricultural major impact for pattern 4. The apportionment models of the pollution determined the contribution of each one of identified pollution factors to the total concentration of each one of the water quality parameters. Thus, a better risk management of the surface water quality is achieved both on local and national level.
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Xu, Jin-Hai; Yao, Min; Ye, Jie; Wang, Guo-Dong; Wang, Jing; Cui, Xue-Jun; Mo, Wen
2016-10-01
Ovariectomy (OVX)-induced rats are the most frequently used animal model to research postmenopausal osteoporosis. Our objective was to summarize and critically assess the bone mass improved effect of icariin (ICA) for treatment of postmenopausal osteoporosis in an OVX-induced rat model. The PUBMED, EMBASE, and Chinese databases were searched from their inception date to February 2015. Two reviewers independently selected animal studies that evaluated the bone mass improved effect of ICA compared with control in OVX-induced rats. Extracted data were analyzed by RevMan statistical software, and the methodological quality of each study was assessed. Seven studies with adequate randomization were included in the systematic review. Overall, ICA seemed to significantly improve bone mass as assessed using the bone mineral density (seven studies, n = 169; weighted mean difference, 0.02; 95% CI, 0.01-0.02, I = 77%, P < 0.00001) using a random-effects model. There is no significant difference between ICA and estrogen (E) (six studies, n = 128; weighted mean difference, 0.00; 95% CI, -0.00 to 0.01, I = 54%, P = 0.01). Bone mass improved effect of ICA for postmenopausal osteoporosis was observed in OVX-induced rats. Assessment of the methodological quality of studies involving OVX-induced animal models is required, and good methodological quality should be valued in systematic reviews of animal studies.
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Rocket exhaust effluent modeling for tropospheric air quality and environmental assessments
NASA Technical Reports Server (NTRS)
Stephens, J. B.; Stewart, R. B.
1977-01-01
The various techniques for diffusion predictions to support air quality predictions and environmental assessments for aerospace applications are discussed in terms of limitations imposed by atmospheric data. This affords an introduction to the rationale behind the selection of the National Aeronautics and Space Administration (NASA)/Marshall Space Flight Center (MSFC) Rocket Exhaust Effluent Diffusion (REED) program. The models utilized in the NASA/MSFC REED program are explained. This program is then evaluated in terms of some results from a joint MSFC/Langley Research Center/Kennedy Space Center Titan Exhaust Effluent Prediction and Monitoring Program.
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This study presents the first evaluation of the performance of the Eta-CMAQ air quality forecast model to predict a variety of widely used seasonal mean and cumulative O3 exposure indices associated with vegetation using the U.S. AIRNow O3 observations.
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Adapting water treatment design and operations to the impacts of global climate change
NASA Astrophysics Data System (ADS)
Clark, Robert M.; Li, Zhiwei; Buchberger, Steven G.
2011-12-01
It is anticipated that global climate change will adversely impact source water quality in many areas of the United States and will therefore, potentially, impact the design and operation of current and future water treatment systems. The USEPA has initiated an effort called the Water Resources Adaptation Program (WRAP) which is intended to develop tools and techniques that can assess the impact of global climate change on urban drinking water and wastewater infrastructure. A three step approach for assessing climate change impacts on water treatment operation and design is being persude in this effort. The first step is the stochastic characterization of source water quality, the second step is the application of the USEPA Water Treatment Plant model and the third step is the application of cost algorithms to provide a metric that can be used to assess the coat impact of climate change. A model has been validated using data collected from Cincinnati's Richard Miller Water Treatment Plant for the USEPA Information Collection Rule (ICR) database. An analysis of the water treatment processes in response to assumed perturbations in raw water quality identified TOC, pH, and bromide as the three most important parameters affecting performance of the Miller WTP. The Miller Plant was simulated using the EPA WTP model to examine the impact of these parameters on selected regulated water quality parameters. Uncertainty in influent water quality was analyzed to estimate the risk of violating drinking water maximum contaminant levels (MCLs).Water quality changes in the Ohio River were projected for 2050 using Monte Carlo simulation and the WTP model was used to evaluate the effects of water quality changes on design and operation. Results indicate that the existing Miller WTP might not meet Safe Drinking Water Act MCL requirements for certain extreme future conditions. However, it was found that the risk of MCL violations under future conditions could be controlled by enhancing existing WTP design and operation or by process retrofitting and modification.
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Rowe, Gary L.; Belitz, Kenneth; Demas, Charlie R.; Essaid, Hedeff I.; Gilliom, Robert J.; Hamilton, Pixie A.; Hoos, Anne B.; Lee, Casey J.; Munn, Mark D.; Wolock, David W.
2013-01-01
This report presents a science strategy for the third decade of the National Water-Quality Assessment (NAWQA) Program, which since 1991, has been responsible for providing nationally consistent information on the quality of the Nation's streams and groundwater; how water quality is changing over time; and the major natural and human factors that affect current water quality conditions and trends. The strategy is based on an extensive evaluation of the accomplishments of NAWQA over its first two decades, the current status of water-quality monitoring activities by USGS and its partners, and an updated analysis of stakeholder priorities. The plan is designed to address priority issues and national needs identified by NAWQA stakeholders and the National Research Council (2012) irrespective of budget constraints. This plan describes four major goals for the third decade (Cycle 3), the approaches for monitoring, modeling, and scientific studies, key partnerships required to achieve these goals, and products and outcomes that will result from planned assessment activities. The science plan for 2013–2023 is a comprehensive approach to meet stakeholder priorities for: (1) rebuilding NAWQA monitoring networks for streams, rivers, and groundwater, and (2) upgrading models used to extrapolate and forecast changes in water-quality and stream ecosystem condition in response to changing climate and land use. The Cycle 3 plan continues approaches that have been central to the Program’s long-term success, but adjusts monitoring intensities and study designs to address critical information needs and identified data gaps. Restoration of diminished monitoring networks and new directions in modeling and interpretative studies address growing and evolving public and stakeholder needs for water-quality information and improved management, particularly in the face of increasing challenges related to population growth, increasing demands for water, and changing land use and climate. However, a combination of funding growth and extensive collaboration with other USGS programs and other Federal, State, and local agencies, public interest groups, professional and trade associations, academia, and private industry will be needed to fully realize the monitoring and modeling goals laid out in this plan (USGS Fact Sheet 2013-3008).
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Green House Adoption and Nursing Home Quality.
Afendulis, Christopher C; Caudry, Daryl J; O'Malley, A James; Kemper, Peter; Grabowski, David C
2016-02-01
To evaluate the impact of the Green House (GH) model on nursing home resident-level quality of care measures. Resident-level minimum data set (MDS) assessments merged with Medicare inpatient claims for the period 2005 through 2010. Using a difference-in-differences framework, we compared changes in care quality and outcomes in 15 nursing homes that adopted the GH model relative to changes over the same time period in 223 matched nursing homes that had not adopted the GH model. For individuals residing in GH homes, adoption of the model lowered readmissions and several MDS measures of poor quality, including bedfast residents, catheter use, and pressure ulcers, but these results were not present across the entire GH organization, suggesting possible offsetting effects for residents of non-GH "legacy" units within the GH organization. GH adoption led to improvement in rehospitalizations and certain nursing home quality measures for individuals residing in a GH home. The absence of evidence of a decline in other clinical quality measures in GH nursing homes should reassure anyone concerned that GH might have sacrificed clinical quality for improved quality of life. © Health Research and Educational Trust.
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Assessing air quality in Aksaray with time series analysis
NASA Astrophysics Data System (ADS)
Kadilar, Gamze Özel; Kadilar, Cem
2017-04-01
Sulphur dioxide (SO2) is a major air pollutant caused by the dominant usage of diesel, petrol and fuels by vehicles and industries. One of the most air-polluted city in Turkey is Aksaray. Hence, in this study, the level of SO2 is analyzed in Aksaray based on the database monitored at air quality monitoring station of Turkey. Seasonal Autoregressive Integrated Moving Average (SARIMA) approach is used to forecast the level of SO2 air quality parameter. The results indicate that the seasonal ARIMA model provides reliable and satisfactory predictions for the air quality parameters and expected to be an alternative tool for practical assessment and justification.
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Positional Quality Assessment of Orthophotos Obtained from Sensors Onboard Multi-Rotor UAV Platforms
Mesas-Carrascosa, Francisco Javier; Rumbao, Inmaculada Clavero; Berrocal, Juan Alberto Barrera; Porras, Alfonso García-Ferrer
2014-01-01
In this study we explored the positional quality of orthophotos obtained by an unmanned aerial vehicle (UAV). A multi-rotor UAV was used to obtain images using a vertically mounted digital camera. The flight was processed taking into account the photogrammetry workflow: perform the aerial triangulation, generate a digital surface model, orthorectify individual images and finally obtain a mosaic image or final orthophoto. The UAV orthophotos were assessed with various spatial quality tests used by national mapping agencies (NMAs). Results showed that the orthophotos satisfactorily passed the spatial quality tests and are therefore a useful tool for NMAs in their production flowchart. PMID:25587877
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Mesas-Carrascosa, Francisco Javier; Rumbao, Inmaculada Clavero; Berrocal, Juan Alberto Barrera; Porras, Alfonso García-Ferrer
2014-11-26
In this study we explored the positional quality of orthophotos obtained by an unmanned aerial vehicle (UAV). A multi-rotor UAV was used to obtain images using a vertically mounted digital camera. The flight was processed taking into account the photogrammetry workflow: perform the aerial triangulation, generate a digital surface model, orthorectify individual images and finally obtain a mosaic image or final orthophoto. The UAV orthophotos were assessed with various spatial quality tests used by national mapping agencies (NMAs). Results showed that the orthophotos satisfactorily passed the spatial quality tests and are therefore a useful tool for NMAs in their production flowchart.
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Evidence-based dentistry: a model for clinical practice.
Faggion, Clóvis M; Tu, Yu-Kang
2007-06-01
Making decisions in dentistry should be based on the best evidence available. The objective of this study was to demonstrate a practical procedure and model that clinicians can use to apply the results of well-conducted studies to patient care by critically appraising the evidence with checklists and letter grade scales. To demonstrate application of this model for critically appraising the quality of research evidence, a hypothetical case involving an adult male with chronic periodontitis is used as an example. To determine the best clinical approach for this patient, a four-step, evidence-based model is demonstrated, consisting of the following: definition of a research question using the PICO format, search and selection of relevant literature, critical appraisal of identified research reports using checklists, and the application of evidence. In this model, the quality of research evidence was assessed quantitatively based on different levels of quality that are assigned letter grades of A, B, and C by evaluating the studies against the QUOROM (Quality of Reporting Meta-Analyses) and CONSORT (Consolidated Standards of Reporting Trials) checklists in a tabular format. For this hypothetical periodontics case, application of the model identified the best available evidence for clinical decision making, i.e., one randomized controlled trial and one systematic review of randomized controlled trials. Both studies showed similar answers for the research question. The use of a letter grade scale allowed an objective analysis of the quality of evidence. A checklist-driven model that assesses and applies evidence to dental practice may substantially improve dentists' decision making skill.
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Indicators to support the dynamic evaluation of air quality models
NASA Astrophysics Data System (ADS)
Thunis, P.; Clappier, A.
2014-12-01
Air quality models are useful tools for the assessment and forecast of pollutant concentrations in the atmosphere. Most of the evaluation process relies on the “operational phase” or in other words the comparison of model results with available measurements which provides insight on the model capability to reproduce measured concentrations for a given application. But one of the key advantages of air quality models lies in their ability to assess the impact of precursor emission reductions on air quality levels. Models are then used in a dynamic mode (i.e. response to a change in a given model input data) for which evaluation of the model performances becomes a challenge. The objective of this work is to propose common indicators and diagrams to facilitate the understanding of model responses to emission changes when models are to be used for policy support. These indicators are shown to be useful to retrieve information on the magnitude of the locally produced impacts of emission reductions on concentrations with respect to the “external to the domain” contribution but also to identify, distinguish and quantify impacts arising from different factors (different precursors). In addition information about the robustness of the model results is provided. As such these indicators might reveal useful as first screening methodology to identify the feasibility of a given action as well as to prioritize the factors on which to act for an increased efficiency. Finally all indicators are made dimensionless to facilitate the comparison of results obtained with different models, different resolutions, or on different geographical areas.
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Assessment and management of the performance risk of a pilot reclaimed water disinfection process.
Zhou, Guangyu; Zhao, Xinhua; Zhang, Lei; Wu, Qing
2013-10-01
Chlorination disinfection has been widely used in reclaimed water treatment plants to ensure water quality. In order to assess the downstream quality risk of a running reclaimed water disinfection process, a set of dynamic equations was developed to simulate reactions in the disinfection process concerning variables of bacteria, chemical oxygen demand (COD), ammonia and monochloramine. The model was calibrated by the observations obtained from a pilot disinfection process which was designed to simulate the actual process in a reclaimed water treatment plant. A Monte Carlo algorithm was applied to calculate the predictive effluent quality distributions that were used in the established hierarchical assessment system for the downstream quality risk, and the key factors affecting the downstream quality risk were defined using the Regional Sensitivity Analysis method. The results showed that the seasonal upstream quality variation caused considerable downstream quality risk; the effluent ammonia was significantly influenced by its upstream concentration; the upstream COD was a key factor determining the process effluent risk of bacterial, COD and residual disinfectant indexes; and lower COD and ammonia concentrations in the influent would mean better downstream quality.
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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.
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ERIC Educational Resources Information Center
Mail, Abdul; Pratikto; Suparman, Sudjito; Purnomo; Santoso, Budi
2014-01-01
The study aims to find out the influence of internal quality process on the growth of quality culture in private college. This study is treated toward 178 lecturers of 25 private colleges in Sulawesi, Indonesia by means of questionnaire. Confirmatory factor analysis applied to assess the reliability of validity and measurement model. Relationship…
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Federal Workforce Quality: Measurement and Improvement
1992-08-01
explicit standards of production and service quality . Assessment Tools 4 OPM should institutionalize its data collection program of longitudinal research...include data about quirements, should set explicit standards of various aspects of the model. That is, the production and service quality . effort...are the immediate consumers service quality are possible. of the products and services delivered, and still others in the larger society who have no
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Vaidya, Anil; Joore, Manuela A; ten Cate-Hoek, Arina J; Kleinegris, Marie-Claire; ten Cate, Hugo; Severens, Johan L
2014-01-01
Lower extremity artery disease (LEAD) is a sign of wide spread atherosclerosis also affecting coronary, cerebral and renal arteries and is associated with increased risk of cardiovascular events. Many economic evaluations have been published for LEAD due to its clinical, social and economic importance. The aim of this systematic review was to assess modelling methods used in published economic evaluations in the field of LEAD. Our review appraised and compared the general characteristics, model structure and methodological quality of published models. Electronic databases MEDLINE and EMBASE were searched until February 2013 via OVID interface. Cochrane database of systematic reviews, Health Technology Assessment database hosted by National Institute for Health research and National Health Services Economic Evaluation Database (NHSEED) were also searched. The methodological quality of the included studies was assessed by using the Philips' checklist. Sixteen model-based economic evaluations were identified and included. Eleven models compared therapeutic health technologies; three models compared diagnostic tests and two models compared a combination of diagnostic and therapeutic options for LEAD. Results of this systematic review revealed an acceptable to low methodological quality of the included studies. Methodological diversity and insufficient information posed a challenge for valid comparison of the included studies. In conclusion, there is a need for transparent, methodologically comparable and scientifically credible model-based economic evaluations in the field of LEAD. Future modelling studies should include clinically and economically important cardiovascular outcomes to reflect the wider impact of LEAD on individual patients and on the society.
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Evaluating Rater Accuracy in Rater-Mediated Assessments Using an Unfolding Model
ERIC Educational Resources Information Center
Wang, Jue; Engelhard, George, Jr.; Wolfe, Edward W.
2016-01-01
The number of performance assessments continues to increase around the world, and it is important to explore new methods for evaluating the quality of ratings obtained from raters. This study describes an unfolding model for examining rater accuracy. Accuracy is defined as the difference between observed and expert ratings. Dichotomous accuracy…
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USDA-ARS?s Scientific Manuscript database
We coupled the Soil and Water Assessment Tool (SWAT) with a hydrodynamic model in the Daoulas’ catchment and estuary to estimate daily variations in Escherichia coli fluxes due to catchment activities (manure spreading and wastewater treatment plants discharge) and to assess their impact on coastal ...
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DOT National Transportation Integrated Search
2012-03-01
The Alaska adapted version of the Weather Research and Forecasting and the Community Modeling and Analysis Quality (WRF-CMAQ) modeling : systems was used to assess the contribution of traffic to the PM2.5-concentration in the Fairbanks nonattainment ...
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Overview and insights regarding the JEQ soil and water assessment tool (SWAT) special issue
USDA-ARS?s Scientific Manuscript database
The Soil and Water Assessment Tool (SWAT) model has emerged as one of the most widely used water quality watershed- and river basin-scale models worldwide, and has been extensively applied for a broad range of hydrologic and/or environmental problems. Factors driving the international use of SWAT i...
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We present an integrated assessment model to predict potential unintended consequences of urban development on the sustainability of seagrasses and preservation of ecosystem services, such as catchable fish, in Tampa Bay. Ecosystem services are those ecological functions and pro...
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Quality Evaluation of Raw Moutan Cortex Using the AHP and Gray Correlation-TOPSIS Method
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
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NASA Astrophysics Data System (ADS)
Lallahem, S.; Hani, A.
2017-02-01
Water sustainability in the lower Seybouse River basin, eastern Algeria, must take into account the importance of water quantity and quality integration. So, there is a need for a better knowledge and understanding of the water quality determinants of groundwater abstraction to meet the municipal and agricultural uses. In this paper, the artificial neural network (ANN) models were used to model and predict the relationship between groundwater abstraction and water quality determinants in the lower Seybouse River basin. The study area chosen is the lower Seybouse River basin and real data were collected from forty five wells for reference year 2006. Results indicate that the feed-forward multilayer perceptron models with back-propagation are useful tools to define and prioritize the important water quality parameters of groundwater abstraction and use. The model evaluation shows that the correlation coefficients are more than 95% for training, verification and testing data. The model aims to link the water quantity and quality with the objective to strengthen the Integrated Water Resources Management approach. It assists water planners and managers to better assess the water quality parameters and progress towards the provision of appropriate quantities of water of suitable quality.
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Validation of an organizational communication climate assessment toolkit.
Wynia, Matthew K; Johnson, Megan; McCoy, Thomas P; Griffin, Leah Passmore; Osborn, Chandra Y
2010-01-01
Effective communication is critical to providing quality health care and can be affected by a number of modifiable organizational factors. The authors performed a prospective multisite validation study of an organizational communication climate assessment tool in 13 geographically and ethnically diverse health care organizations. Communication climate was measured across 9 discrete domains. Patient and staff surveys with matched items in each domain were developed using a national consensus process, which then underwent psychometric field testing and assessment of domain coherence. The authors found meaningful within-site and between-site performance score variability in all domains. In multivariable models, most communication domains were significant predictors of patient-reported quality of care and trust. The authors conclude that these assessment tools provide a valid empirical assessment of organizational communication climate in 9 domains. Assessment results may be useful to track organizational performance, to benchmark, and to inform tailored quality improvement interventions.
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[The organization of system of quality management in large multitype hospital].
Taĭts, B M; Krichmar, G N; Stvolinskiĭ, I Iu; Grandilevskaia, O L
2013-01-01
The article presents the characteristics and assessment of functioning of model of quality management in large multitype hospital. The results of work of the municipal hospital of Saint Venerable martyr Elizabeth of St Petersburg concerning the implementation of system of quality management in 2001-2011 of the foundation of principles of total quality management of medical service and principles of quality management according international standards ISO and their Russian analogues.
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GLIMPSE: An integrated assessment model-based tool for ...
Dan Loughlin will describe the GCAM-USA integrated assessment model and how that model is being improved and integrated into the GLIMPSE decision support system. He will also demonstrate the application of the model to evaluate the emissions and health implications of hypothetical state-level renewable electricity standards. Introduce the GLIMPSE project to state and regional environmental modelers and analysts. Presented as part of the State Energy and Air Quality Group Webinar Series, which is organized by NESCAUM.
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[Quality assurance and total quality management in residential home care].
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.
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Uncertainty in BMP evaluation and optimization for watershed management
NASA Astrophysics Data System (ADS)
Chaubey, I.; Cibin, R.; Sudheer, K.; Her, Y.
2012-12-01
Use of computer simulation models have increased substantially to make watershed management decisions and to develop strategies for water quality improvements. These models are often used to evaluate potential benefits of various best management practices (BMPs) for reducing losses of pollutants from sources areas into receiving waterbodies. Similarly, use of simulation models in optimizing selection and placement of best management practices under single (maximization of crop production or minimization of pollutant transport) and multiple objective functions has increased recently. One of the limitations of the currently available assessment and optimization approaches is that the BMP strategies are considered deterministic. Uncertainties in input data (e.g. precipitation, streamflow, sediment, nutrient and pesticide losses measured, land use) and model parameters may result in considerable uncertainty in watershed response under various BMP options. We have developed and evaluated options to include uncertainty in BMP evaluation and optimization for watershed management. We have also applied these methods to evaluate uncertainty in ecosystem services from mixed land use watersheds. In this presentation, we will discuss methods to to quantify uncertainties in BMP assessment and optimization solutions due to uncertainties in model inputs and parameters. We have used a watershed model (Soil and Water Assessment Tool or SWAT) to simulate the hydrology and water quality in mixed land use watershed located in Midwest USA. The SWAT model was also used to represent various BMPs in the watershed needed to improve water quality. SWAT model parameters, land use change parameters, and climate change parameters were considered uncertain. It was observed that model parameters, land use and climate changes resulted in considerable uncertainties in BMP performance in reducing P, N, and sediment loads. In addition, climate change scenarios also affected uncertainties in SWAT simulated crop yields. Considerable uncertainties in the net cost and the water quality improvements resulted due to uncertainties in land use, climate change, and model parameter values.
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Aerothermal modeling program, phase 2
NASA Technical Reports Server (NTRS)
Mongia, H. C.; Patankar, S. V.; Murthy, S. N. B.; Sullivan, J. P.; Samuelsen, G. S.
1985-01-01
The main objectives of the Aerothermal Modeling Program, Phase 2 are: to develop an improved numerical scheme for incorporation in a 3-D combustor flow model; to conduct a benchmark quality experiment to study the interaction of a primary jet with a confined swirling crossflow and to assess current and advanced turbulence and scalar transport models; and to conduct experimental evaluation of the air swirler interaction with fuel injectors, assessments of current two-phase models, and verification the improved spray evaporation/dispersion models.
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THE CHALLENGE OF ASSESSING CHILDREN'S EXPOSURE TO PESTICIDES
In implementing the Food Quality Protection Act (FQPA) the U.S. Environmental Protection Agency (USEPA) has adopted a policy that the exposure factors and models used to assess and predict exposure to pesticides should generally be conservative. Some elements of exposure assess...
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E-Services quality assessment framework for collaborative networks
NASA Astrophysics Data System (ADS)
Stegaru, Georgiana; Danila, Cristian; Sacala, Ioan Stefan; Moisescu, Mihnea; Mihai Stanescu, Aurelian
2015-08-01
In a globalised networked economy, collaborative networks (CNs) are formed to take advantage of new business opportunities. Collaboration involves shared resources and capabilities, such as e-Services that can be dynamically composed to automate CN participants' business processes. Quality is essential for the success of business process automation. Current approaches mostly focus on quality of service (QoS)-based service selection and ranking algorithms, overlooking the process of service composition which requires interoperable, adaptable and secure e-Services to ensure seamless collaboration, data confidentiality and integrity. Lack of assessment of these quality attributes can result in e-Service composition failure. The quality of e-Service composition relies on the quality of each e-Service and on the quality of the composition process. Therefore, there is the need for a framework that addresses quality from both views: product and process. We propose a quality of e-Service composition (QoESC) framework for quality assessment of e-Service composition for CNs which comprises of a quality model for e-Service evaluation and guidelines for quality of e-Service composition process. We implemented a prototype considering a simplified telemedicine use case which involves a CN in e-Healthcare domain. To validate the proposed quality-driven framework, we analysed service composition reliability with and without using the proposed framework.
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Note on Professor Sizer's Paper.
ERIC Educational Resources Information Center
Balderston, Frederick E.
1979-01-01
Issues suggested by John Sizer's paper, an overview of the assessment of institutional performance, include: the efficient-frontier approach, multiple-criterion decision-making models, performance analysis approached as path analysis, and assessment of academic quality. (JMD)
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Modeling to Evaluate Contribution of Oil and Gas Emissions to Air Pollution.
Thompson, Tammy M; Shepherd, Donald; Stacy, Andrea; Barna, Michael G; Schichtel, Bret A
2017-04-01
Oil and gas production in the Western United States has increased considerably over the past 10 years. While many of the still limited oil and gas impact assessments have focused on potential human health impacts, the typically remote locations of production in the Intermountain West suggests that the impacts of oil and gas production on national parks and wilderness areas (Class I and II areas) could also be important. To evaluate this, we utilize the Comprehensive Air quality Model with Extensions (CAMx) with a year-long modeling episode representing the best available representation of 2011 meteorology and emissions for the Western United States. The model inputs for the 2011 episodes were generated as part of the Three State Air Quality Study (3SAQS). The study includes a detailed assessment of oil and gas (O&G) emissions in Western States. The year-long modeling episode was run both with and without emissions from O&G production. The difference between these two runs provides an estimate of the contribution of the O&G production to air quality. These data were used to assess the contribution of O&G to the 8 hour average ozone concentrations, daily and annual fine particulate concentrations, annual nitrogen deposition totals and visibility in the modeling domain. We present the results for the Class I and II areas in the Western United States. Modeling results suggest that emissions from O&G activity are having a negative impact on air quality and ecosystem health in our National Parks and Class I areas. In this research, we use a modeling framework developed for oil and gas evaluation in the western United States to determine the modeled impacts of emissions associated with oil and gas production on air pollution metrics. We show that oil and gas production may have a significant negative impact on air quality and ecosystem health in some national parks and other Class I areas in the western United States. Our findings are of particular interest to federal land managers as well as regulators in states heavy in oil and gas production as they consider control strategies to reduce the impact of development.
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Dinkel, Andreas; Schneider, Antonius; Schmutzer, Gabriele; Brähler, Elmar; Henningsen, Peter; Häuser, Winfried
2016-03-01
Patient-centeredness and a strong working alliance are core elements of family medicine. Surveys in Germany showed that most people are satisfied with the quality of the family physician-patient relationship. However, factors that are responsible for the quality of the family physician-patient relationship remain unclear. This study aimed at identifying patient-related predictors of the quality of this relationship. Participants of a cross-sectional survey representative for the general German population were assessed using standardized questionnaires. The perceived quality of the family physician-patient relationship was measured with the German version of the Patient-Doctor Relationship Questionnaire (PDRQ-9). Associations of demographic and clinical variables (comorbidity, somatic symptom burden, psychological distress) with the quality of the family physician-patient relationship were assessed by applying hierarchical linear regression. 2278 participants (91,9%) reported having a family physician. The mean total score of the PDRQ-9 was high (M=4,12, SD=0,70). The final regression model showed that higher age, being female, and most notably less somatic and less depressive symptoms predicted a higher quality of the family physician-patient relationship. Comorbidity lost significance when somatic symptom burden was added to the regression model. The final model explained 11% of the variance, indicating a small effect. Experiencing somatic and depressive symptoms emerged as most relevant patient-related predictors of the quality of the family physician-patient relationship. © Georg Thieme Verlag KG Stuttgart · New York.
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Garcia-Hernandez, Alberto
2014-03-01
Although the quality-adjusted life-years (QALY) model is standard in health technology assessment, quantitative methods are less frequent but increasingly used for benefit-risk assessment (BRA) at earlier stages of drug development. A frequent challenge when implementing metrics for BRA is to weigh the importance of effects on a chronic condition against the risk of severe events during the trial. The lifetime component of the QALY model has a counterpart in the BRA context, namely, the risk of dying during the study. A new concept is presented, the hazard of death function that a subject is willing to accept instead of the baseline hazard to improve his or her chronic health status, which we have called the quality-of-life-adjusted hazard of death. It has been proven that if assumptions of the linear QALY model hold, the excess mortality rate tolerated by a subject for a chronic health improvement is inversely proportional to the mean residual life. This result leads to a new representation of the linear QALY model in terms of hazard rate functions and allows utilities obtained by using standard methods involving trade-offs of life duration to be translated into thresholds of tolerated mortality risk during a short period of time, thereby avoiding direct trade-offs using small probabilities of events during the study, which is known to lead to bias and variability. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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NASA Astrophysics Data System (ADS)
Julianto, E. A.; Suntoro, W. A.; Dewi, W. S.; Partoyo
2018-03-01
Climate change has been reported to exacerbate land resources degradation including soil fertility decline. The appropriate validity use on soil fertility evaluation could reduce the risk of climate change effect on plant cultivation. This study aims to assess the validity of a Soil Fertility Evaluation Model using a graphical approach. The models evaluated were the Indonesian Soil Research Center (PPT) version model, the FAO Unesco version model, and the Kyuma version model. Each model was then correlated with rice production (dry grain weight/GKP). The goodness of fit of each model can be tested to evaluate the quality and validity of a model, as well as the regression coefficient (R2). This research used the Eviews 9 programme by a graphical approach. The results obtained three curves, namely actual, fitted, and residual curves. If the actual and fitted curves are widely apart or irregular, this means that the quality of the model is not good, or there are many other factors that are still not included in the model (large residual) and conversely. Indeed, if the actual and fitted curves show exactly the same shape, it means that all factors have already been included in the model. Modification of the standard soil fertility evaluation models can improve the quality and validity of a model.
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Air Quality Response Modeling for Decision Support | Science ...
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
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Christianson, O; Winslow, J; Samei, E
2014-06-15
Purpose: One of the principal challenges of clinical imaging is to achieve an ideal balance between image quality and radiation dose across multiple CT models. The number of scanners and protocols at large medical centers necessitates an automated quality assurance program to facilitate this objective. Therefore, the goal of this work was to implement an automated CT image quality and radiation dose monitoring program based on actual patient data and to use this program to assess consistency of protocols across CT scanner models. Methods: Patient CT scans are routed to a HIPPA compliant quality assurance server. CTDI, extracted using opticalmore » character recognition, and patient size, measured from the localizers, are used to calculate SSDE. A previously validated noise measurement algorithm determines the noise in uniform areas of the image across the scanned anatomy to generate a global noise level (GNL). Using this program, 2358 abdominopelvic scans acquired on three commercial CT scanners were analyzed. Median SSDE and GNL were compared across scanner models and trends in SSDE and GNL with patient size were used to determine the impact of differing automatic exposure control (AEC) algorithms. Results: There was a significant difference in both SSDE and GNL across scanner models (9–33% and 15–35% for SSDE and GNL, respectively). Adjusting all protocols to achieve the same image noise would reduce patient dose by 27–45% depending on scanner model. Additionally, differences in AEC methodologies across vendors resulted in disparate relationships of SSDE and GNL with patient size. Conclusion: The difference in noise across scanner models indicates that protocols are not optimally matched to achieve consistent image quality. Our results indicated substantial possibility for dose reduction while achieving more consistent image appearance. Finally, the difference in AEC methodologies suggests the need for size-specific CT protocols to minimize variability in image quality across CT vendors.« less
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A comparison of major petroleum life cycle models | Science ...
Many organizations have attempted to develop an accurate well-to-pump life cycle model of petroleum products in order to inform decision makers of the consequences of its use. Our paper studies five of these models, demonstrating the differences in their predictions and attempting to evaluate their data quality. Carbon dioxide well-to-pump emissions for gasoline showed a variation of 35 %, and other pollutants such as ammonia and particulate matter varied up to 100 %. Differences in allocation do not appear to explain differences in predictions. Effects of these deviations on well-to-wheels passenger vehicle and truck transportation life cycle models may be minimal for effects such as global warming potential (6 % spread), but for respiratory effects of criteria pollutants (41 % spread) and other impact categories, they can be significant. A data quality assessment of the models’ documentation revealed real differences between models in temporal and geographic representativeness, completeness, as well as transparency. Stakeholders may need to consider carefully the tradeoffs inherent when selecting a model to conduct life cycle assessments for systems that make heavy use of petroleum products. This is a qualitative and quantitative comparison of petroleum LCA models intended for an expert audience interested in better understanding the data quality of existing petroleum life cycle models and the quantitative differences between these models.
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Nigro, Joseph; Toll, David; Partington, Ed; Ni-Meister, Wenge; Lee, Shihyan; Gutierrez-Magness, Angelica; Engman, Ted; Arsenault, Kristi
2010-01-01
The USEPA has estimated that over 20,000 water bodies within the United States do not meet water quality standards. One of the regulations in the Clean Water Act of 1972 requires states to monitor the total maximum daily load, or the amount of pollution that can be carried by a water body before it is determined to be "polluted," for any watershed in the United States (Copeland, 2005). In response to this mandate, the USEPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a decision support tool for assessing pollution and to guide the decision-making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program-Fortran (HSPF), computes continuous streamflow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events, especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA-modified/NOAA precipitation data. Using these data within HSPF, streamflow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better streamflow statistics and, potentially, in improved water quality assessment.
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Development of risk-based air quality management strategies under impacts of climate change.
Liao, Kuo-Jen; Amar, Praveen; Tagaris, Efthimios; Russell, Armistead G
2012-05-01
Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of climate change includes determination of air quality targets, selections of potential management options, and identification of effective air quality management strategies through decision-making models. The risk-based decision-making framework can also be applied to develop climate-responsive management strategies for the other environmental dimensions and assess costs and benefits of future environmental management policies.
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Spreadsheet WATERSHED modeling for nonpoint-source pollution management in a Wisconsin basin
Walker, J.F.; Pickard, S.A.; Sonzogni, W.C.
1989-01-01
Although several sophisticated nonpoint pollution models exist, few are available that are easy to use, cover a variety of conditions, and integrate a wide range of information to allow managers and planners to assess different control strategies. Here, a straightforward pollutant input accounting approach is presented in the form of an existing model (WATERSHED) that has been adapted to run on modern electronic spreadsheets. As an application, WATERSHED is used to assess options to improve the quality of highly eutrophic Delavan Lake in Wisconsin. WATERSHED is flexible in that several techniques, such as the Universal Soil Loss Equation or unit-area loadings, can be used to estimate nonpoint-source inputs. Once the model parameters are determined (and calibrated, if possible), the spreadsheet features can be used to conduct a sensitivity analysis of management options. In the case of Delavan Lake, it was concluded that, although some nonpoint controls were cost-effective, the overall reduction in phosphorus would be insufficient to measurably improve water quality.A straightforward pollutant input accounting approach is presented in the form of an existing model (WATERSHED) that has been adapted to run on modern electronic spreadsheets. As an application, WATERSHED is used to assess options to improve the quality of highly eutrophic Delavan Lake in Wisconsin. WATERSHED is flexible in that several techniques, such as the Universal Soil Loss Equation or unit-area loadings, can be used to estimate nonpoint-source inputs. Once the model parameters are determined (and calibrated, if possible), the spreadsheet features can be used to conduct a sensitivity analysis of management options. In the case of Delavan Lake, it was concluded that, although some nonpoint controls were cost-effective, the overall reduction in phosphorus would be insufficient to measurably improve water quality.
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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.
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2018-01-01
In this study, we leverage human evaluations, content analysis, and computational modeling to generate a comprehensive analysis of readers’ evaluations of authors’ communication quality in social media with respect to four factors: author credibility, interpersonal attraction, communication competence, and intent to interact. We review previous research on the human evaluation process and highlight its limitations in providing sufficient information for readers to assess authors’ communication quality. From our analysis of the evaluations of 1,000 Twitter authors’ communication quality from 300 human evaluators, we provide empirical evidence of the impact of the characteristics of the reader (demographic, social media experience, and personality), author (profile and social media engagement), and content (linguistic, syntactic, similarity, and sentiment) on the evaluation of an author’s communication quality. In addition, based on the author and message characteristics, we demonstrate the potential for building accurate models that can indicate an author’s communication quality. PMID:29389979
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Han, Kyungsik
2018-01-01
In this study, we leverage human evaluations, content analysis, and computational modeling to generate a comprehensive analysis of readers' evaluations of authors' communication quality in social media with respect to four factors: author credibility, interpersonal attraction, communication competence, and intent to interact. We review previous research on the human evaluation process and highlight its limitations in providing sufficient information for readers to assess authors' communication quality. From our analysis of the evaluations of 1,000 Twitter authors' communication quality from 300 human evaluators, we provide empirical evidence of the impact of the characteristics of the reader (demographic, social media experience, and personality), author (profile and social media engagement), and content (linguistic, syntactic, similarity, and sentiment) on the evaluation of an author's communication quality. In addition, based on the author and message characteristics, we demonstrate the potential for building accurate models that can indicate an author's communication quality.
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Transported air pollutants receive increasing attention as regulations tighten and global concentrations increase. The need to represent international transport in regional air quality assessments requires improved representation of boundary concentrations. Currently available ob...