An Integrated Approach for Quantifying Pesticide Dissipation under Diverse Conditions III: Site Specific Model Validation Using GLEAMS, EPICWQ, and EXAMS

2002 ◽  
pp. 73-87
Author(s):  
S. A. Cryer
Keyword(s):  
Model Validation ◽  
Integrated Approach ◽  
Specific Model ◽  
Site Specific

scholarly journals WATER VAPOUR WEIGHTED MEAN TEMPERATURE MODEL FOR GPS-DERIVED INTEGRATED WATER VAPOUR IN PENINSULAR MALAYSIA

2017 ◽  
Vol XLII-4/W5 ◽  
pp. 127-135 ◽  
Author(s):  
T. A. Musa ◽  
M. H. Mazlan ◽  
Y. D. Opaluwa ◽  
I. A. Musliman ◽  
Z. M. Radzi
Keyword(s):  
Water Vapour ◽  
Diurnal Cycle ◽  
Specific Model ◽  
Regional Model ◽  
Peninsular Malaysia ◽  
Site Specific ◽  
Weighted Mean Temperature ◽  
Integrated Water Vapour ◽  
Relationship Of ◽  
The Impact

This paper presents the development of T<sub>M</sub> model by using the radiosonde stations from Peninsular Malaysia. Two types of T<sub>M</sub> model were developed; site-specific and regional models. The result revealed that the estimation from site-specific model has small improvement compared to the regional model, indicating that the regional model is adequately to use in estimation of GPS-derived IWV over Peninsular Malaysia. Meanwhile, this study found that the diurnal cycle of T<sub>S</sub> has influenced the T<sub>M</sub>&amp;ndash;T<sub>S</sub> relationship. The separation between daytime and nighttime observation can improve the relationship of T<sub>M</sub>&amp;ndash;T<sub>S</sub>. However, the impact of diurnal cycle to IWV estimation is less than 1&amp;thinsp;%. The T<sub>M</sub> model from Global and Tropic also been evaluated. The Tropic T<sub>M</sub> model is superior to be utilized as compared to the Global T<sub>M</sub> model.

scholarly journals An integrated approach to design site specific distributed electrical hubs combining optimization, multi-criterion assessment and decision making

Energy ◽  
2017 ◽  
Vol 134 ◽  
pp. 103-120 ◽  
Author(s):  
A.T.D. Perera ◽  
Vahid M. Nik ◽  
Dasaraden Mauree ◽  
Jean-Louis Scartezzini
Keyword(s):  
Decision Making ◽  
Integrated Approach ◽  
Site Specific

Thoughts on Model Validation for Engineering Design

2003 ◽  
Author(s):  
George A. Hazelrigg
Keyword(s):  
Predictive Model ◽  
Engineering Design ◽  
Decision Maker ◽  
Model Validation ◽  
Predictive Models ◽  
Specific Model ◽  
System Behavior ◽  
Crucial Element ◽  
Model Validity ◽  
Subjective Input

Models are the basis for all prediction of system behavior, and hence form a crucial element of engineering design. A key concern is the validity of such models. This paper discusses the notion of model validity and the limits of what one can say about the validity of a specific model. It is shown that predictive models, such as those used in engineering design, cannot be validated objectively. That is, the validation of a predictive model can be accomplished only in the context of a specific decision, and only in the context of subjective input from the decision maker, including preferences.

scholarly journals Association of salmonella mutants with germfree rats: site specific model to detect carcinogens as mutagens.

1975 ◽  
Vol 72 (11) ◽  
pp. 4607-4611 ◽  
Author(s):  
L. A. Wheeler ◽  
J. H. Carter ◽  
F. B. Soderberg ◽  
P. Goldman
Keyword(s):  
Specific Model ◽  
Site Specific ◽  
Germfree Rats

JOHNSON COUNTY WASTEWATER'S INTEGRATED APPROACH FOR ESTABLISHING SITE–SPECIFIC AMMONIA EFFFLUENT LIMITS

2000 ◽  
Vol 2000 (14) ◽  
pp. 789-805
Author(s):  
Nicole Rowan ◽  
John Metzler ◽  
Susan Morea ◽  
Tony Gendusa
Keyword(s):  
Integrated Approach ◽  
Site Specific ◽  
Johnson County

Environmental transportation of tritium and estimation of site-specific model parameters for Kaiga site, India

2011 ◽  
Vol 149 (3) ◽  
pp. 304-308 ◽  
Author(s):  
T. K. Reji ◽  
P. M. Ravi ◽  
T. L. Ajith ◽  
B. N. Dileep ◽  
A. G. Hegde ◽  
...  
Keyword(s):  
Specific Model ◽  
Model Parameters ◽  
Site Specific

scholarly journals A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data

2017 ◽  
Author(s):  
Johanna Bertl ◽  
Qianyun Guo ◽  
Malene Juul ◽  
Søren Besenbacher ◽  
Morten Muhlig Nielsen ◽  
...  
Keyword(s):  
Mutation Rate ◽  
Null Model ◽  
Specific Model ◽  
Cancer Development ◽  
Whole Genome ◽  
Site Specific ◽  
Explanatory Variables ◽  
Different Types ◽  
Cancer Types ◽  
Mutational Process

AbstractBackgroundDetailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration.ResultsTo take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures.ConclusionWe find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.

scholarly journals A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data

2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Johanna Bertl ◽  
Qianyun Guo ◽  
Malene Juul ◽  
Søren Besenbacher ◽  
Morten Muhlig Nielsen ◽  
...  
Keyword(s):  
Somatic Mutation ◽  
Mutation Rate ◽  
Specific Model ◽  
Whole Genome ◽  
Site Specific ◽  
Cancer Data ◽  
A Site

scholarly journals Comparison of Two PARAFAC Models of Dissolved Organic Matter Fluorescence for a Mid-Atlantic Forested Watershed in the USA

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Shatrughan Singh ◽  
Shreeram Inamdar ◽  
Durelle Scott
Keyword(s):  
Organic Matter ◽  
Dissolved Organic Matter ◽  
Specific Model ◽  
Forested Watershed ◽  
Strongly Correlated ◽  
Site Specific ◽  
The Usa ◽  
Study Sites ◽  
Model Components ◽  
A Site

The composition of dissolved organic matter (DOM) in a mid-Atlantic forested watershed was evaluated using two fluorescence models—one based on previously validated model (Cory and McKnight, 2005) and the other developed specifically for our study site. DOM samples for the models were collected from multiple watershed sources over a two-year period. The previously validated parallel factor analysis (PARAFAC) model had 13 DOM components whereas our site-specific model yielded six distinct components including two terrestrial humic-like, two microbial-derived humic-like, and two protein-like components. The humic-like components were highest in surficial watershed sources and decreased from soil water to groundwater whereas the protein-like components were highest for groundwater sources. Discriminant analyses indicated that our site-specific model was more sensitive to subtle differences in DOM and the sum of the humic- and protein-like constituents yielded more pronounced differences among watershed sources as opposed to the prevalidated model. Dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) concentrations and selected DOM metrics were also more strongly correlated with the site-specific model components. These results suggest that while the pre-validated model may capture broader trends in DOM composition and allow comparisons with other study sites, a site-specific model will be more sensitive for characterizing within-site differences in DOM.

scholarly journals A State-of-the-Art Review of the Sensor Location, Flow Observability, Estimation, and Prediction Problems in Traffic Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-26 ◽  
Author(s):  
Enrique Castillo ◽  
Zacarías Grande ◽  
Aida Calviño ◽  
W. Y. Szeto ◽  
Hong K. Lo
Keyword(s):  
Relative Error ◽  
Optimization Problems ◽  
State Of The Art ◽  
Mathematical Optimization ◽  
Integrated Approach ◽  
Specific Model ◽  
Traffic Networks ◽  
Objective Functions ◽  
Estimation And Prediction ◽  
Prediction Problems

A state-of-the-art review of flow observability, estimation, and prediction problems in traffic networks is performed. Since mathematical optimization provides a general framework for all of them, an integrated approach is used to perform the analysis of these problems and consider them as different optimization problems whose data, variables, constraints, and objective functions are the main elements that characterize the problems proposed by different authors. For example, counted, scanned or “a priori” data are the most common data sources; conservation laws, flow nonnegativity, link capacity, flow definition, observation, flow propagation, and specific model requirements form the most common constraints; and least squares, likelihood, possible relative error, mean absolute relative error, and so forth constitute the bases for the objective functions or metrics. The high number of possible combinations of these elements justifies the existence of a wide collection of methods for analyzing static and dynamic situations.

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