Building Analysis for Urban Energy Planning Using Key Indicators on Virtual 3d City Models - the Energy Atlas of Berlin

Science.gov (United States)

Krüger, A.; Kolbe, T. H.

2012-07-01

In the context of increasing greenhouse gas emission and global demographic change with the simultaneous trend to urbanization, it is a big challenge for cities around the world to perform modifications in energy supply chain and building characteristics resulting in reduced energy consumption and carbon dioxide mitigation. Sound knowledge of energy resource demand and supply including its spatial distribution within urban areas is of great importance for planning strategies addressing greater energy efficiency. The understanding of the city as a complex energy system affects several areas of the urban living, e.g. energy supply, urban texture, human lifestyle, and climate protection. With the growing availability of 3D city models around the world based on the standard language and format CityGML, energy system modelling, analysis and simulation can be incorporated into these models. Both domains will profit from that interaction by bringing together official and accurate building models including building geometries, semantics and locations forming a realistic image of the urban structure with systemic energy simulation models. A holistic view on the impacts of energy planning scenarios can be modelled and analyzed including side effects on urban texture and human lifestyle. This paper focuses on the identification, classification, and integration of energy-related key indicators of buildings and neighbourhoods within 3D building models. Consequent application of 3D city models conforming to CityGML serves the purpose of deriving indicators for this topic. These will be set into the context of urban energy planning within the Energy Atlas Berlin. The generation of indicator objects covering the indicator values and related processing information will be presented on the sample scenario estimation of heating energy consumption in buildings and neighbourhoods. In their entirety the key indicators will form an adequate image of the local energy situation for

Structure model of energy efficiency indicators and applications

International Nuclear Information System (INIS)

Wu, Li-Ming; Chen, Bai-Sheng; Bor, Yun-Chang; Wu, Yin-Chin

2007-01-01

For the purposes of energy conservation and environmental protection, the government of Taiwan has instigated long-term policies to continuously encourage and assist industry in improving the efficiency of energy utilization. While multiple actions have led to practical energy saving to a limited extent, no strong evidence of improvement in energy efficiency was observed from the energy efficiency indicators (EEI) system, according to the annual national energy statistics and survey. A structural analysis of EEI is needed in order to understand the role that energy efficiency plays in the EEI system. This work uses the Taylor series expansion to develop a structure model for EEI at the level of the process sector of industry. The model is developed on the premise that the design parameters of the process are used in comparison with the operational parameters for energy differences. The utilization index of production capability and the variation index of energy utilization are formulated in the model to describe the differences between EEIs. Both qualitative and quantitative methods for the analysis of energy efficiency and energy savings are derived from the model. Through structural analysis, the model showed that, while the performance of EEI is proportional to the process utilization index of production capability, it is possible that energy may develop in a direction opposite to that of EEI. This helps to explain, at least in part, the inconsistency between EEI and energy savings. An energy-intensive steel plant in Taiwan was selected to show the application of the model. The energy utilization efficiency of the plant was evaluated and the amount of energy that had been saved or over-used in the production process was estimated. Some insights gained from the model outcomes are helpful to further enhance energy efficiency in the plant

A New Performance Improvement Model: Adding Benchmarking to the Analysis of Performance Indicator Data.

Science.gov (United States)

Al-Kuwaiti, Ahmed; Homa, Karen; Maruthamuthu, Thennarasu

2016-01-01

A performance improvement model was developed that focuses on the analysis and interpretation of performance indicator (PI) data using statistical process control and benchmarking. PIs are suitable for comparison with benchmarks only if the data fall within the statistically accepted limit-that is, show only random variation. Specifically, if there is no significant special-cause variation over a period of time, then the data are ready to be benchmarked. The proposed Define, Measure, Control, Internal Threshold, and Benchmark model is adapted from the Define, Measure, Analyze, Improve, Control (DMAIC) model. The model consists of the following five steps: Step 1. Define the process; Step 2. Monitor and measure the variation over the period of time; Step 3. Check the variation of the process; if stable (no significant variation), go to Step 4; otherwise, control variation with the help of an action plan; Step 4. Develop an internal threshold and compare the process with it; Step 5.1. Compare the process with an internal benchmark; and Step 5.2. Compare the process with an external benchmark. The steps are illustrated through the use of health care-associated infection (HAI) data collected for 2013 and 2014 from the Infection Control Unit, King Fahd Hospital, University of Dammam, Saudi Arabia. Monitoring variation is an important strategy in understanding and learning about a process. In the example, HAI was monitored for variation in 2013, and the need to have a more predictable process prompted the need to control variation by an action plan. The action plan was successful, as noted by the shift in the 2014 data, compared to the historical average, and, in addition, the variation was reduced. The model is subject to limitations: For example, it cannot be used without benchmarks, which need to be calculated the same way with similar patient populations, and it focuses only on the "Analyze" part of the DMAIC model.

Generalized indices for radiation risk analysis

International Nuclear Information System (INIS)

Bykov, A.A.; Demin, V.F.

1989-01-01

A new approach to ensuring nuclear safety has begun forming since the early eighties. The approach based on the probabilistic safety analysis, the principles of acceptable risk, the optimization of safety measures, etc. has forced a complex of adequate quantitative methods of assessment, safety analysis and risk management to be developed. The method of radiation risk assessment and analysis hold a prominent place in the complex. National and international research and regulatory organizations ICRP, IAEA, WHO, UNSCEAR, OECD/NEA have given much attention to the development of the conceptual and methodological basis of those methods. Some resolutions of the National Commission of Radiological Protection (NCRP) and the Problem Commission on Radiation Hygiene of the USSR Ministry of Health should be also noted. Both CBA (cost benefit analysis) and other methods of radiation risk analysis and safety management use a system of natural and socio-economic indices characterizing the radiation risk or damage. There exist a number of problems associated with the introduction, justification and use of these indices. For example, the price, a, of radiation damage, or collective dose unit, is a noteworthy index. The difficulties in its qualitative and quantitative determination are still an obstacle for a wide application of CBA to the radiation risk analysis and management. During recent 10-15 years these problems have been a subject of consideration for many authors. The present paper also considers the issues of the qualitative and quantitative justification of the indices of radiation risk analysis

A System of Indicators for Financial Analysis of the Municipal Real Property

Directory of Open Access Journals (Sweden)

Daniela Feschiyan

2013-08-01

Full Text Available The paper presents a system of financial indicators for the efficiency of use of municipal real property. Such a system must provide for meeting the information needs of a number of internal and external consumers and is of primary significance in the analysis of municipalities’ overall financial condition. The following may be pointed out as the major aspects of the practical analysis: i the analysis of the municipality’s provision with immoveable property; ii the analysis of the efficient use of certain categories of municipal real property. The paper aims at clarifying the major moments in the analysis of the structure, composition, and effective use of municipal real property, and the determination of definite indicators to be applied to this analysis oriented towards its implementation. The wide variety of parameters is reduced to a system of 16 indicators: reporting value, depreciation, ratio of replacement, ratio of cost efficiency, ratio of revenue efficiency, return on total assets, return on revenues, return on expenses, ratio of the fitness, ratio of the repair, ratio of real energy provision, ratio of workload, present value of a series of regular cash flows, equivalent yield model, return on investment, return on investment. The paper presents the structure and content of the indicators of the analysis of the municipal real property, as well as the input of these indicators. The estimation (values necessary to determine the indicators, the indicators themselves and their meaning make it possible to study the effectiveness of the operations (functioning of the municipal real property in terms of description of its physical condition, structure, content, purpose and functions, which generates revenues or brings expenditures to the municipality. The system of indicators provides for decision making with a view to boosting the efficiency of public sector management and more specifically – the management of municipal real property.

Modeling minimum temperature using adaptive neuro-fuzzy inference system based on spectral analysis of climate indices: A case study in Iran

Directory of Open Access Journals (Sweden)

Hojatollah Daneshmand

2015-01-01

Full Text Available Nowadays, a lot of attention is paid to the application of intelligent systems in predicting natural phenomena. Artificial neural network systems, fuzzy logic, and adaptive neuro-fuzzy inference are used in this field. Daily minimum temperature of the meteorology station of the city of Mashhad, in northeast of Iran, in a 42-year statistical period, 1966-2008, has been received from the Iranian meteorological organization. Adaptive neuro-fuzzy inference system is used for modeling and forecasting the monthly minimum temperature. To find appropriate inputs, three approaches, i.e. spectral analysis, correlation coefficient, and the knowledge of experts,are used. By applying fast Fourier transform to the parameter of monthly minimum temperature and climate indices, and by using correlation coefficient and the knowledge of experts, 3 indices, Nino 1 + 2, NP, and PNA, are selected as model inputs. A hybrid training algorithm is used to train the system. According to simulation results, a correlation coefficient of 0.987 between the observed values and the predicted values, as well as amean absolute percentage deviations of 27.6% indicate an acceptable estimation of the model.

The Use of Indicators in Modified Historical Model to Estimate the Intrinsic Value of a Stock

Directory of Open Access Journals (Sweden)

Gottwald Radim

2012-06-01

Full Text Available The article mentions several methods of a fundamental analysis used to value stocks. It primarily focuses on the historical model. This model enables undervalued, correctly valued and overvalued stocks to be identified. The model is further modified in the article, using selected accounting indicators. The modified model versions are applied to selected stocks in the SPAD segment, Prague Stock Exchange, within the 2005-2010 period. Empirical analysis is applied to a comparison of accuracy of the accounting indicator value estimates and accuracy of stock intrinsic value estimates, both separately for each stock and accounting indicator. The comparisons of accuracy of the accounting indicator value estimates and the accuracy of the stock intrinsic value estimates are also done based on the length of applied time period. With respect to the obvious fierce competition between stock issuers within the financial markets, the model enables potential investors, who are to select from an extensive offer of stocks, to make better informed investment decisions.

Variance-based sensitivity indices for stochastic models with correlated inputs

Energy Technology Data Exchange (ETDEWEB)

Kala, Zdeněk [Brno University of Technology, Faculty of Civil Engineering, Department of Structural Mechanics Veveří St. 95, ZIP 602 00, Brno (Czech Republic)

2015-03-10

The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics.

Variance-based sensitivity indices for stochastic models with correlated inputs

International Nuclear Information System (INIS)

Kala, Zdeněk

2015-01-01

The goal of this article is the formulation of the principles of one of the possible strategies in implementing correlation between input random variables so as to be usable for algorithm development and the evaluation of Sobol’s sensitivity analysis. With regard to the types of stochastic computational models, which are commonly found in structural mechanics, an algorithm was designed for effective use in conjunction with Monte Carlo methods. Sensitivity indices are evaluated for all possible permutations of the decorrelation procedures for input parameters. The evaluation of Sobol’s sensitivity coefficients is illustrated on an example in which a computational model was used for the analysis of the resistance of a steel bar in tension with statistically dependent input geometric characteristics

Analysis of economic convergence through synthetic development indicators: the chilean case study

Directory of Open Access Journals (Sweden)

Víctor Fernando Figueroa Arcila

2003-01-01

Full Text Available This paper defends the use of convergence models to study the temporary evolution of the Chilean communes’ socioeconomic development. To do so, we will use an indicator made up of using multivariate analysis techniques. By means of regression models of transversal section and models of distributional dynamics we will outline, on the basis of the historic function of communal economies, the behaviour expected for those economies in future and, therefore, the tendencial evolution of Chilean territorial economic model.

Support vector regression and artificial neural network models for stability indicating analysis of mebeverine hydrochloride and sulpiride mixtures in pharmaceutical preparation: A comparative study

Science.gov (United States)

Naguib, Ibrahim A.; Darwish, Hany W.

2012-02-01

A comparison between support vector regression (SVR) and Artificial Neural Networks (ANNs) multivariate regression methods is established showing the underlying algorithm for each and making a comparison between them to indicate the inherent advantages and limitations. In this paper we compare SVR to ANN with and without variable selection procedure (genetic algorithm (GA)). To project the comparison in a sensible way, the methods are used for the stability indicating quantitative analysis of mixtures of mebeverine hydrochloride and sulpiride in binary mixtures as a case study in presence of their reported impurities and degradation products (summing up to 6 components) in raw materials and pharmaceutical dosage form via handling the UV spectral data. For proper analysis, a 6 factor 5 level experimental design was established resulting in a training set of 25 mixtures containing different ratios of the interfering species. An independent test set consisting of 5 mixtures was used to validate the prediction ability of the suggested models. The proposed methods (linear SVR (without GA) and linear GA-ANN) were successfully applied to the analysis of pharmaceutical tablets containing mebeverine hydrochloride and sulpiride mixtures. The results manifest the problem of nonlinearity and how models like the SVR and ANN can handle it. The methods indicate the ability of the mentioned multivariate calibration models to deconvolute the highly overlapped UV spectra of the 6 components' mixtures, yet using cheap and easy to handle instruments like the UV spectrophotometer.

Regional and parametric sensitivity analysis of Sobol' indices

International Nuclear Information System (INIS)

Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

2015-01-01

Nowadays, utilizing the Monte Carlo estimators for variance-based sensitivity analysis has gained sufficient popularity in many research fields. These estimators are usually based on n+2 sample matrices well designed for computing both the main and total effect indices, where n is the input dimension. The aim of this paper is to use such n+2 sample matrices to investigate how the main and total effect indices change when the uncertainty of the model inputs are reduced. For this purpose, the regional main and total effect functions are defined for measuring the changes on the main and total effect indices when the distribution range of one input is reduced, and the parametric main and total effect functions are introduced to quantify the residual main and total effect indices due to the reduced variance of one input. Monte Carlo estimators are derived for all the developed sensitivity concepts based on the n+2 samples matrices originally used for computing the main and total effect indices, thus no extra computational cost is introduced. The Ishigami function, a nonlinear model and a planar ten-bar structure are utilized for illustrating the developed sensitivity concepts, and for demonstrating the efficiency and accuracy of the derived Monte Carlo estimators. - Highlights: • The regional main and total effect functions are developed. • The parametric main and total effect functions are introduced. • The proposed sensitivity functions are all generalizations of Sobol' indices. • The Monte Carlo estimators are derived for the four sensitivity functions. • The computational cost of the estimators is the same as that of Sobol' indices

Sociometric Indicators of Leadership: An Exploratory Analysis

Science.gov (United States)

2018-01-01

Research Report 2015 Sociometric Indicators of Leadership : An Exploratory Analysis Elizabeth R. Uhl U.S. Army...2017 4. TITLE AND SUBTITLE Sociometric Indicators of Leadership : An Exploratory Analysis 5a. CONTRACT NUMBER W5J9CQ-11-D-0001 5b...objectives and a discussion of the strengths and weaknesses of the wearable sensor technology. 15. SUBJECT TERMS Leadership ; Social Network; Sociometric

Sensitivity analysis of a radionuclide transfer model describing contaminated vegetation in Fukushima prefecture, using Morris and Sobol' - Application of sensitivity analysis on a radionuclides transfer model in the environment describing weeds contamination in Fukushima Prefecture, using Morris method and Sobol' indices indices

Energy Technology Data Exchange (ETDEWEB)

Nicoulaud-Gouin, V.; Metivier, J.M.; Gonze, M.A. [Institut de Radioprotection et de Surete Nucleaire-PRP-ENV/SERIS/LM2E (France); Garcia-Sanchez, L. [Institut de Radioprotection et de Surete Nucleaire-PRPENV/SERIS/L2BT (France)

2014-07-01

The increasing spatial and temporal complexity of models demands methods capable of ranking the influence of their large numbers of parameters. This question specifically arises in assessment studies on the consequences of the Fukushima accident. Sensitivity analysis aims at measuring the influence of input variability on the output response. Generally, two main approaches are distinguished (Saltelli, 2001, Iooss, 2011): - Screening approach, less expensive in computation time and allowing to identify non influential parameters; - Measures of importance, introducing finer quantitative indices. In this category, there are regression-based methods, assuming a linear or monotonic response (Pearson coefficient, Spearman coefficient), and variance-based methods, without assumptions on the model but requiring an increasingly prohibitive number of evaluations when the number of parameters increases. These approaches are available in various statistical programs (notably R) but are still poorly integrated in modelling platforms of radioecological risk assessment. This work aimed at illustrating the benefits of sensitivity analysis in the course of radioecological risk assessments This study used two complementary state-of-art global sensitivity analysis methods: - The screening method of Morris (Morris, 1991; Campolongo et al., 2007) based on limited model evaluations with a one-at-a-time (OAT) design; - The variance-based Sobol' sensitivity analysis (Saltelli, 2002) based a large number of model evaluations in the parameter space with a quasi-random sampling (Owen, 2003). Sensitivity analyses were applied on a dynamic Soil-Plant Deposition Model (Gonze et al., submitted to this conference) predicting foliar concentration in weeds after atmospheric radionuclide fallout. The Soil-Plant Deposition Model considers two foliage pools and a root pool, and describes foliar biomass growth with a Verhulst model. The developed semi-analytic formulation of foliar concentration

Analysis and Comparison of Overheating Indices in Energy Renovated Houses

DEFF Research Database (Denmark)

Psomas, Theofanis Ch.; Heiselberg, Per Kvols; Duer, Karsten

2015-01-01

The scientific literature offers a number of methods for assessing the likelihood of overheating in buildings. The paper calculates eight well-documented indices for four representative family houses, from moderate and temperate climates, under different renovation processes (66 variants), with t......The scientific literature offers a number of methods for assessing the likelihood of overheating in buildings. The paper calculates eight well-documented indices for four representative family houses, from moderate and temperate climates, under different renovation processes (66 variants......), with the use of multi-zone energy software. In two out of four cases, the calculation included passive cooling measures for optimization purposes (shading, ventilative cooling). The analysis shows strong correlations between different methods-indices originating from the same comfort model theory independently...

Analysis of indicators of an efficiency estimation of work of the employee and the business model of the organization

Directory of Open Access Journals (Sweden)

Yury G. Odegov

2016-01-01

Full Text Available In conditions of increasing competition, the problems of efficiency increase of activity of the company are significantly actualized, which directly depends on efficiency of labour activity of every employee and the implemented business model of the organization. On this basis the aim of the research is to analyze existing indicators of performance evaluation of the labour activities of both the employee and the business model of the organization.The theoretical basis of the study consists of principles of the economic theory, the works of native and foreign experts in the field of job evaluation. The information base of the research consists of economic and legal literature dealing with problems of this study, the data published in periodicals, materials of Russian scientific conferences, seminars, and Internet resources.In this article I have used and found the application of scientific methods of data collection, methods of research and methods of assessing their credibility: quantitative, comparative, logical analysis and synthesis.The modern business concern about the accumulation of wealth of shareholders, giving the company stability, growth and efficiency inevitably leads to necessity of creation and development of technologies aimed at improving the productivity of employees. The paper presents a comparative analysis of different approaches to assessing the labour effectiveness.The performance of the work is the ratio of the four essential parameters that determine the measure of efficiency of persons’ activity: the quantity and quality of result of work (a service, material product or technology in relation to spend time and cost on its production. The use of employees («performance» should be in the following way that they could achieve the planned results in the workplace. The authors have noted that to develop of technologies for the measurement of productivity it is very important to use the procedures and indicators that are

Quality indicators for the analysis of communication in an online course

Directory of Open Access Journals (Sweden)

Antonella Pezzotti

2012-08-01

Full Text Available This study describes the development and validation of quality indicators for analyzing forums interactions in an online course in biology teaching. The aim is to evaluate the quality of communication so as to strengthen the tutor’s role and help students learn fundamental biology concepts while enhancing their collaboration competencies. The indicators are used to analyze cognitive, metacognitive and relational aspects, drawing on a content analysis methodology. The model appears to have a wide range of possible applications in other online courses.

A Prediction Model for Community Colleges Using Graduation Rate as the Performance Indicator

Science.gov (United States)

Moosai, Susan

2010-01-01

In this thesis a prediction model using graduation rate as the performance indicator is obtained for community colleges for three cohort years, 2003, 2004, and 2005 in the states of California, Florida, and Michigan. Multiple Regression analysis, using an aggregate of seven predictor variables, was employed in determining this prediction model.…

Linear indices in nonlinear structural equation models : best fitting proper indices and other composites

NARCIS (Netherlands)

Dijkstra, T.K.; Henseler, J.

2011-01-01

The recent advent of nonlinear structural equation models with indices poses a new challenge to the measurement of scientific constructs. We discuss, exemplify and add to a family of statistical methods aimed at creating linear indices, and compare their suitability in a complex path model with

Rainfall-induced fecal indicator organisms transport from animal waste applied fields: model sensitivity analysis

Science.gov (United States)

The microbial quality of surface waters warrants attention because of associated food- and waterborne-disease outbreaks, and fecal indicator organisms (FIOs) are commonly used to evaluate levels of microbial pollution. Models that predict the fate and transport of FIOs are required for designing and...

Personalization of models with many model parameters: an efficient sensitivity analysis approach.

Science.gov (United States)

Donders, W P; Huberts, W; van de Vosse, F N; Delhaas, T

2015-10-01

Uncertainty quantification and global sensitivity analysis are indispensable for patient-specific applications of models that enhance diagnosis or aid decision-making. Variance-based sensitivity analysis methods, which apportion each fraction of the output uncertainty (variance) to the effects of individual input parameters or their interactions, are considered the gold standard. The variance portions are called the Sobol sensitivity indices and can be estimated by a Monte Carlo (MC) approach (e.g., Saltelli's method [1]) or by employing a metamodel (e.g., the (generalized) polynomial chaos expansion (gPCE) [2, 3]). All these methods require a large number of model evaluations when estimating the Sobol sensitivity indices for models with many parameters [4]. To reduce the computational cost, we introduce a two-step approach. In the first step, a subset of important parameters is identified for each output of interest using the screening method of Morris [5]. In the second step, a quantitative variance-based sensitivity analysis is performed using gPCE. Efficient sampling strategies are introduced to minimize the number of model runs required to obtain the sensitivity indices for models considering multiple outputs. The approach is tested using a model that was developed for predicting post-operative flows after creation of a vascular access for renal failure patients. We compare the sensitivity indices obtained with the novel two-step approach with those obtained from a reference analysis that applies Saltelli's MC method. The two-step approach was found to yield accurate estimates of the sensitivity indices at two orders of magnitude lower computational cost. Copyright © 2015 John Wiley & Sons, Ltd.

Traffic fatality indicators in Brazil: State diagnosis based on data envelopment analysis research.

Science.gov (United States)

Bastos, Jorge Tiago; Shen, Yongjun; Hermans, Elke; Brijs, Tom; Wets, Geert; Ferraz, Antonio Clóvis Pinto

2015-08-01

The intense economic growth experienced by Brazil in recent decades and its consequent explosive motorization process have evidenced an undesirable impact: the increasing and unbroken trend in traffic fatality numbers. In order to contribute to road safety diagnosis on a national level, this study presents a research into two main indicators available in Brazil: mortality rate (represented by fatalities per capita) and fatality rate (represented by two sub-indicators, i.e., fatalities per vehicle and fatalities per vehicle kilometer traveled). These indicators were aggregated into a composite indicator or index through a multiple layer data envelopment analysis (DEA) composite indicator model, which looks for the optimum combination of indicators' weights for each decision-making unit, in this case 27 Brazilian states. The index score represents the road safety performance, based on which a ranking of states can be made. Since such a model has never been applied for road safety evaluation in Brazil, its parameters were calibrated based on the experience of more consolidated European Union research in ranking its member countries using DEA techniques. Secondly, cluster analysis was conducted aiming to provide more realistic performance comparisons and, finally, the sensitivity of the results was measured through a bootstrapping method application. It can be concluded that by combining fatality indicators, defining clusters and applying bootstrapping procedures a trustworthy ranking can be created, which is valuable for nationwide road safety planning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Factor analysis improves the selection of prescribing indicators

DEFF Research Database (Denmark)

Rasmussen, Hanne Marie Skyggedal; Søndergaard, Jens; Sokolowski, Ineta

2006-01-01

OBJECTIVE: To test a method for improving the selection of indicators of general practitioners' prescribing. METHODS: We conducted a prescription database study including all 180 general practices in the County of Funen, Denmark, approximately 472,000 inhabitants. Principal factor analysis was us...... appropriate and inappropriate prescribing, as revealed by the correlation of the indicators in the first factor. CONCLUSION: Correlation and factor analysis is a feasible method that assists the selection of indicators and gives better insight into prescribing patterns....

Performability indicators for the traffic analysis of wide area networks

International Nuclear Information System (INIS)

Tsopelas, Panagiotis; Platis, Agapios

2003-01-01

In connecting computing networks, reliability term is strongly related to the availability of connections of Wide Area networks (WANs) or Local Area networks (LANs). In this paper we will examine the network connections activity of a Greek University in order to provide two sources of information: The Quantity of Information Not Delivered (QIND) and the Information Flow Interruption (IFI). These indicators will provide us with the inference of information from observable characteristics of data flow(s), even when the data is encrypted or otherwise not directly available (traffic), which is lost due to failures or upgrades inside this network. The reliability analysis is obtained by collecting the network failures data (duration and frequency) and traffic (total and average) for a specified period of 1 year. It is assumed that the numerical analysis is based on the fact that the lifetime follows and exponential distribution (here as we are working on discrete time the distribution must be the geometric distribution). Hence a Markov chain model seems suitable for modelling the functioning of this system. An algorithm concentrates the results in a transition probability matrix and calculates the reward functions for the QIND/IFI indicators with the use of the power method. Finally, the application part provides an example of how final results can be used to evaluate the observed network

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

Science.gov (United States)

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.

Moving Mini-Max - a new indicator for technical analysis

OpenAIRE

Z. K. Silagadze

2008-01-01

We propose a new indicator for technical analysis. The indicator emphasizes maximums and minimums in price series with inherent smoothing and has a potential to be useful in both mechanical trading rules and chart pattern analysis.

Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

Energy Technology Data Exchange (ETDEWEB)

Zhou, Ping; Song, Heda; Wang, Hong; Chai, Tianyou

2017-09-01

Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improve modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.

Use of Artificial Neural Network Models to Predict Indicator Organism Concentrations in an Urban Watershed

Science.gov (United States)

Mas, D. M.; Ahlfeld, D. P.

2004-05-01

Forecasting stream water quality is important for numerous aspects of resource protection and management. Fecal coliform and enteroccocus are primary indicator organisms used to assess potential pathogen contamination. Consequently, modeling the occurrence and concentration of fecal coliform and enterococcus is an important tool in watershed management. In addition, analyzing the relationship between model input and predicted indicator organisms is useful for elucidating possible sources of contamination and mechanisms of transport. While many process-based, statistical, and empirical models exist for water quality prediction, artificial neural network (ANN) models are increasingly being used for forecasting of water resources variables because ANNs are often capable of modeling complex systems for which behavioral rules are either unknown or difficult to simulate. The performance of ANNs compared to more established modeling approaches such as multiple linear regression (MLR) remains an importance research question. Data collected the U.S. Geological Survey in the lower Charles River in Massachusetts, USA in 1999-2000 was examined to determine correlation between various water quality constituents and indicator organisms and to explore the relationship between rainfall characteristics and indicator organism concentrations. Using the results of the statistical analysis to guide the selection of explanatory variables, MLR was performed to develop predictive equations for wet weather and dry weather conditions. The results show that the best-performing predictor variables are generally consistent for both indicator organisms considered. In addition, the regression equations show increasing indicator organism concentrations as a function of suspended sediment concentrations and length of time since last precipitation event, suggesting accumulation and wash off as a key mechanism of pathogen transport under wet weather conditions. This research also presents the

Analysis of ESG indicators for measuring enterprise performance

Directory of Open Access Journals (Sweden)

Zuzana Chvátalová

2013-01-01

Full Text Available In this article authors focus on the analysis of the whole set of environmental, social and corporate governance (ESG indicators for the elimination of double or triple effects within the next construction of methods for measuring corporate performance. They build on their previously published results (in Acta univ. agric. et silvic. Mendel. Brun., 2012. The partial actual selected results of a recently undertaken currently project entitled ‘Construction of Methods for Multifactorial Assessment of Company Complex Performance in Selected Sectors’ were used. This project was solved the research teams of the Faculty of Business and Management of Brno University Technology and Faculty of Business and Economics of Mendel University in Brno since 2011. Further theoretical resources in the environmental, social and corporate governance area, known indicator databases (namely Global Reporting Initiative, comparative analysis, resp. syntheses for identifying possible of common indicator properties were identified to classify indicator subsets to preclude double or even triple effect based on mathematical set theory (Venn diagrams. The indicator analysis in constructed multi-factorial methods contributes to precise decision making in management to improve corporate performance.

Forming Factors And Builder Indicators Of Brand Personality Models In Traditional Retail Traders

Directory of Open Access Journals (Sweden)

Yunelly Asra

2017-12-01

Full Text Available This study aims to find the factors forming and indicator builder model of brand personality of traditional retail traders through measuring the influence of retail mix and culture. The formation of brand personality uses Aaker brand personality dimension to 250 consumers in Bengkalis Regency. The type of research is causal research design. The research variables are brand personality Retail Mix and Brand Personality. Data collection is done by probability sampling with purposive method. Data analysis was done by perception analysis frequency distribution and multiple regression using SPSS version 21.0. The results of this study are The factor of retail mix partially has a positive and significant impact on the brand personality of traditional retail traders in Bengkalis Regency. Factor cultural partially does not affect the brand personality of traditional retail traders in Bengkalis Regency. Simultaneously retail mix and cultural have positive and significant influence on traditional brand traders brand personality in Bengkalis Regency. Initial forming factor of brand personality model of traditional retail traders in Bengkalis Regency is Retail Mix Factor. Indicator of the model of traditional traders brand personality builder in Bengkalis are sincerity excitement competence sophistication competence ruggedness.

Developing a Model for Assessing Public Culture Indicators at Universities

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Meisam Latifi

2015-06-01

Full Text Available The present study is aimed to develop a model for assessing public culture at universities and evaluating its indicators at public universities in Mashhad. The research follows an exploratory mixed approach. Research strategies in qualitative and quantitative sections are thematic networks analysis and descriptive- survey method, respectively. In the qualitative section, document analysis and semi-structured interviews with cultural experts are used as research tools. In this section, targeted sampling is carried out. In the quantitative section, a questionnaire which is developed based on the findings of the qualitative section is used as the research tool. Research population of the quantitative section consists of all the students who are admitted to public universities in Mashhad between 2009 and 2012. Sample size was calculated according to Cochran’s formula. Stratified sampling was used to select the sample. The results of the qualitative section led to the identification of 44 basic themes which are referred to as the micro indicators. These themes were clustered into similar groups. Then, 10 organizer themes were identified and recognized as macro indicators. In the next phase, importance factor of each indicator is determined according to the AHP method. The results of the qualitative assessment of indicators at public universities of Mashhad show that the overall cultural index declines during the years the student attends the university. Additionally, the highest correlation exists between national identity and revolutionary identity. The only negative correlations are observed between family and two indicators including social capital and cultural consumption. The results of the present study can be used to assess the state of public culture among university students and also be considered as a basis for assessing cultural planning.

Mental retardation after prenatal exposure. Re-analysis indicated

International Nuclear Information System (INIS)

Paile, W.

2000-01-01

The current risk assessment for severe mental retardation after prenatal exposure to the A-bomb radiation is based on 21 cases exposed to more than 0.005 Gy, of which 17 were exposed in the most sensitive period 8-15 weeks p.c. The latest analysis, applying the best fitting model, indicates a threshold with a lower 95% bound of 0.06-0.31 Gy, depending on whether 2 cases with Down's syndrome are included or not. The authors have interpreted this as suggesting a threshold in the low-dose region. In the dose group 0.10-0.49 Gy, except one case with Down's syndrome there is only one other case, exposed 8 weeks p.c. to 0.14 Gy. However, in a RERF report (TR 13-91) concerning brain abnormalities detected by MRI in retarded persons, the same case is described. According to this report he was actually exposed to 0.86 Gy. The distance was 1060 m, and his mother exhibited severe epilation. These details indicate that the higher dose is correct and the lower dose is erroneous. In a small material the misclassification of one case has a deep influence on the result of the data analysis. Reclassification of this case will lead to a considerable change in the estimated threshold, notably in the 95% lower bound of the threshold. There will be no indication of severe retardation after less than 0.5 Gy even in the most sensitive period. This does not preclude a milder effect on intelligence from lower doses. The fraction of severe retardation after exposure to 1 Sv in the period 8-15 weeks p.c. has been estimated at 40%. The effect on intelligence score has been estimated at 30 IQ units per Sv in the same period. These estimates have been combined in ICRP 60 to create a model, based on a presumed normal distribution of IQ scores, according to which the final outcome for an individual is determined by his expected IQ without exposure. Thus the dose required to make an otherwise normal individual retarded would be high, while a much lower dose would be enough to bring an individual

AN ANALYSIS OF ACCIDENT TRENDS AND MODELING OF SAFETY INDICES IN AN INDIAN CONSTRUCTION ORGANIZATION

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Sunku Venkata Siva Rajaprasad

2016-09-01

Full Text Available Construction industry has been recognized as a hazardous industry in many countries due to distinct nature of execution of works.The accident rate in construction sector is high all over the world due to dynamic nature of work activities. Occurrence of accidents and its severity in construction industry is several times higher than the manufacturing industries. The study was limited to a major construction organization in India to examine the trends in construction accidents for the period 2008-2014. In India, safety performance is gauged basing on safety indices; frequency, severity and incidence rates. It is not practicable to take decisions or to implement safety strategies on the basis of indices. The data used for this study was collected from a leading construction organization involved in execution of major construction activities all over India and abroad. The multiple regression method was adopted to model the pattern of safety indices wise .The pattern showed that significant relationships exist between the three safety indices and the related independent variables.

Unifying distance-based goodness-of-fit indicators for hydrologic model assessment

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Cheng, Qinbo; Reinhardt-Imjela, Christian; Chen, Xi; Schulte, Achim

2014-05-01

The goodness-of-fit indicator, i.e. efficiency criterion, is very important for model calibration. However, recently the knowledge about the goodness-of-fit indicators is all empirical and lacks a theoretical support. Based on the likelihood theory, a unified distance-based goodness-of-fit indicator termed BC-GED model is proposed, which uses the Box-Cox (BC) transformation to remove the heteroscedasticity of model errors and the generalized error distribution (GED) with zero-mean to fit the distribution of model errors after BC. The BC-GED model can unify all recent distance-based goodness-of-fit indicators, and reveals the mean square error (MSE) and the mean absolute error (MAE) that are widely used goodness-of-fit indicators imply statistic assumptions that the model errors follow the Gaussian distribution and the Laplace distribution with zero-mean, respectively. The empirical knowledge about goodness-of-fit indicators can be also easily interpreted by BC-GED model, e.g. the sensitivity to high flow of the goodness-of-fit indicators with large power of model errors results from the low probability of large model error in the assumed distribution of these indicators. In order to assess the effect of the parameters (i.e. the BC transformation parameter λ and the GED kurtosis coefficient β also termed the power of model errors) of BC-GED model on hydrologic model calibration, six cases of BC-GED model were applied in Baocun watershed (East China) with SWAT-WB-VSA model. Comparison of the inferred model parameters and model simulation results among the six indicators demonstrates these indicators can be clearly separated two classes by the GED kurtosis β: β >1 and β ≤ 1. SWAT-WB-VSA calibrated by the class β >1 of distance-based goodness-of-fit indicators captures high flow very well and mimics the baseflow very badly, but it calibrated by the class β ≤ 1 mimics the baseflow very well, because first the larger value of β, the greater emphasis is put on

Global sensitivity analysis of computer models with functional inputs

International Nuclear Information System (INIS)

Iooss, Bertrand; Ribatet, Mathieu

2009-01-01

Global sensitivity analysis is used to quantify the influence of uncertain model inputs on the response variability of a numerical model. The common quantitative methods are appropriate with computer codes having scalar model inputs. This paper aims at illustrating different variance-based sensitivity analysis techniques, based on the so-called Sobol's indices, when some model inputs are functional, such as stochastic processes or random spatial fields. In this work, we focus on large cpu time computer codes which need a preliminary metamodeling step before performing the sensitivity analysis. We propose the use of the joint modeling approach, i.e., modeling simultaneously the mean and the dispersion of the code outputs using two interlinked generalized linear models (GLMs) or generalized additive models (GAMs). The 'mean model' allows to estimate the sensitivity indices of each scalar model inputs, while the 'dispersion model' allows to derive the total sensitivity index of the functional model inputs. The proposed approach is compared to some classical sensitivity analysis methodologies on an analytical function. Lastly, the new methodology is applied to an industrial computer code that simulates the nuclear fuel irradiation.

Driver's mental workload prediction model based on physiological indices.

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Yan, Shengyuan; Tran, Cong Chi; Wei, Yingying; Habiyaremye, Jean Luc

2017-09-15

Developing an early warning model to predict the driver's mental workload (MWL) is critical and helpful, especially for new or less experienced drivers. The present study aims to investigate the correlation between new drivers' MWL and their work performance, regarding the number of errors. Additionally, the group method of data handling is used to establish the driver's MWL predictive model based on subjective rating (NASA task load index [NASA-TLX]) and six physiological indices. The results indicate that the NASA-TLX and the number of errors are positively correlated, and the predictive model shows the validity of the proposed model with an R 2 value of 0.745. The proposed model is expected to provide a reference value for the new drivers of their MWL by providing the physiological indices, and the driving lesson plans can be proposed to sustain an appropriate MWL as well as improve the driver's work performance.

Model-Based Analysis of the Potential of Macroinvertebrates as Indicators for Microbial Pathogens in Rivers

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Rubén Jerves-Cobo

2018-03-01

Full Text Available The quality of water prior to its use for drinking, farming or recreational purposes must comply with several physicochemical and microbiological standards to safeguard society and the environment. In order to satisfy these standards, expensive analyses and highly trained personnel in laboratories are required. Whereas macroinvertebrates have been used as ecological indicators to review the health of aquatic ecosystems. In this research, the relationship between microbial pathogens and macrobenthic invertebrate taxa was examined in the Machangara River located in the southern Andes of Ecuador, in which 33 sites, according to their land use, were chosen to collect physicochemical, microbiological and biological parameters. Decision tree models (DTMs were used to generate rules that link the presence and abundance of some benthic families to microbial pathogen standards. The aforementioned DTMs provide an indirect, approximate, and quick way of checking the fulfillment of Ecuadorian regulations for water use related to microbial pathogens. The models built and optimized with the WEKA package, were evaluated based on both statistical and ecological criteria to make them as clear and simple as possible. As a result, two different and reliable models were obtained, which could be used as proxy indicators in a preliminary assessment of pollution of microbial pathogens in rivers. The DTMs can be easily applied by staff with minimal training in the identification of the sensitive taxa selected by the models. The presence of selected macroinvertebrate taxa in conjunction with the decision trees can be used as a screening tool to evaluate sites that require additional follow up analyses to confirm whether microbial water quality standards are met.

Mathematical model for estimating of technical and technological indicators of railway stations operation

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D.M. Kozachenko

2013-06-01

Full Text Available Purpose. The article aims to create a mathematical model of the railway station functioning for the solving of problems of station technology development on the plan-schedule basis. Methodology. The methods of graph theory and object-oriented analysis are used as research methods. The model of the station activity plan-schedule includes a model of technical equipment of the station (plan-schedule net and a model of the station functioning , which are formalized on the basis of parametric graphs. Findings. The presented model is implemented as an application to the graphics package AutoCAD. The software is developed in Visual LISP and Visual Basic. Taking into account that the construction of the plan-schedule is mostly a traditional process of adding, deleting, and modifying of icons, the developed interface is intuitively understandable for a technologist and practically does not require additional training. Originality. A mathematical model was created on the basis of the theory of graphs and object-oriented analysis in order to evaluate the technical and process of railway stations indicators; it is focused on solving problems of technology development of their work. Practical value. The proposed mathematical model is implemented as an application to the graphics package of AutoCAD. The presence of a mathematical model allows carrying out an automatic analysis of the plan-schedule and, thereby, reducing the period of its creation more than twice.

Review and Extension of Suitability Assessment Indicators of Weather Model Output for Analyzing Decentralized Energy Systems

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Hans Schermeyer

2015-12-01

Full Text Available Electricity from renewable energy sources (RES-E is gaining more and more influence in traditional energy and electricity markets in Europe and around the world. When modeling RES-E feed-in on a high temporal and spatial resolution, energy systems analysts frequently use data generated by numerical weather models as input since there is no spatial inclusive and comprehensive measurement data available. However, the suitability of such model data depends on the research questions at hand and should be inspected individually. This paper focuses on new methodologies to carry out a performance evaluation of solar irradiation data provided by a numerical weather model when investigating photovoltaic feed-in and effects on the electricity grid. Suitable approaches of time series analysis are researched from literature and applied to both model and measurement data. The findings and limits of these approaches are illustrated and a new set of validation indicators is presented. These novel indicators complement the assessment by measuring relevant key figures in energy systems analysis: e.g., gradients in energy supply, maximum values and volatility. Thus, the results of this paper contribute to the scientific community of energy systems analysts and researchers who aim at modeling RES-E feed-in on a high temporal and spatial resolution using weather model data.

Multi-criteria decision analysis using hydrological indicators for decision support - a conceptual framework.

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Butchart-Kuhlmann, Daniel; Kralisch, Sven; Meinhardt, Markus; Fleischer, Melanie

2017-04-01

Assessing the quantity and quality of water available in water stressed environments under various potential climate and land-use changes is necessary for good water and environmental resources management and governance. Within the region covered by the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) project, such areas are common. One goal of the SASSCAL project is to develop and provide an integrated decision support system (DSS) with which decision makers (DMs) within a given catchment can obtain objective information regarding potential changes in water flow quantity and timing. The SASSCAL DSS builds upon existing data storage and distribution capability, through the SASSCAL Information System (IS), as well as the J2000 hydrological model. Using output from validated J2000 models, the SASSCAL DSS incorporates the calculation of a range of hydrological indicators based upon Indicators of Hydrological Alteration/Environmental Flow Components (IHA/EFC) calculated for a historic time series (pre-impact) and a set of model simulations based upon a selection of possible climate and land-use change scenarios (post-impact). These indicators, obtained using the IHA software package, are then used as input for a multi-criteria decision analysis (MCDA) undertaken using the open source diviz software package. The results of these analyses will provide DMs with an indication as to how various hydrological indicators within a catchment may be altered under different future scenarios, as well providing a ranking of how each scenario is preferred according to different DM preferences. Scenarios are represented through a combination of model input data and parameter settings in J2000, and preferences are represented through criteria weighting in the MCDA. Here, the methodology is presented and applied to the J2000 Luanginga model results using a set of hypothetical decision maker preference values as input for an MCDA based on

ANALYSIS OF INDICATORS FOR ASSESSING THE EFFICIENCY OF STRUCTURAL SUBDIVISIONS OF THE UNIVERSITY

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Oxana N. Romashkova

2018-03-01

Full Text Available The task of the authors was to rank the factors that are used to assess the rating of the structural units of the University. The authors define and describe the stages of ranking. The statistical analysis of data structural units, Moscow Сity University and Рeople's Friendship University of Russia in 2017. Significant factors were selected on the basis of the data of the Moscow State Pedagogical University and the PFUR separately, and then they were compared. The resulting numerical index of structural units evaluation is proposed. With the help of correlation analysis, the data were first systematized and internal connections were revealed. Next, an analysis of the multicollinearity of vectors was carried out using the correlation matrix. As a result of the study, significant factors affecting the rating of the structural unit were selected. The interpretation of the parameters of the model showed that an increase by one such parameter as "the ratio of the number of protected applicants and graduate students to the number of graduates" leads to an increase in the "rating of the relevant Department of the University" by an average of 0,696 units. Such analysis is carried out for each indicator of work of divisions which participate in the General assessment of activity of University. The average of the Hirsch index has the greatest impact on the rating of the division. Verification of the model was carried out with the help of indicators of structural divisions of PFUR. The most significant contribution to the model is given by the parameter "Number of publications in journals included in the WAC list". This factor is comparable to the significant factor of the regression model in terms of MCU ("average Hirsch index". Comparing the results of the analysis of structural divisions of different universities, it can be concluded that the factors that have the greatest and least impact are the same. Built standard was applied to split the

Modeling Chaotic Behavior of Chittagong Stock Indices

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Shipra Banik

2012-01-01

Full Text Available Stock market prediction is an important area of financial forecasting, which attracts great interest to stock buyers and sellers, stock investors, policy makers, applied researchers, and many others who are involved in the capital market. In this paper, a comparative study has been conducted to predict stock index values using soft computing models and time series model. Paying attention to the applied econometric noises because our considered series are time series, we predict Chittagong stock indices for the period from January 1, 2005 to May 5, 2011. We have used well-known models such as, the genetic algorithm (GA model and the adaptive network fuzzy integrated system (ANFIS model as soft computing forecasting models. Very widely used forecasting models in applied time series econometrics, namely, the generalized autoregressive conditional heteroscedastic (GARCH model is considered as time series model. Our findings have revealed that the use of soft computing models is more successful than the considered time series model.

Probabilistic modelling of human exposure to intense sweeteners in Italian teenagers: validation and sensitivity analysis of a probabilistic model including indicators of market share and brand loyalty.

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Arcella, D; Soggiu, M E; Leclercq, C

2003-10-01

For the assessment of exposure to food-borne chemicals, the most commonly used methods in the European Union follow a deterministic approach based on conservative assumptions. Over the past few years, to get a more realistic view of exposure to food chemicals, risk managers are getting more interested in the probabilistic approach. Within the EU-funded 'Monte Carlo' project, a stochastic model of exposure to chemical substances from the diet and a computer software program were developed. The aim of this paper was to validate the model with respect to the intake of saccharin from table-top sweeteners and cyclamate from soft drinks by Italian teenagers with the use of the software and to evaluate the impact of the inclusion/exclusion of indicators on market share and brand loyalty through a sensitivity analysis. Data on food consumption and the concentration of sweeteners were collected. A food frequency questionnaire aimed at identifying females who were high consumers of sugar-free soft drinks and/or of table top sweeteners was filled in by 3982 teenagers living in the District of Rome. Moreover, 362 subjects participated in a detailed food survey by recording, at brand level, all foods and beverages ingested over 12 days. Producers were asked to provide the intense sweeteners' concentration of sugar-free products. Results showed that consumer behaviour with respect to brands has an impact on exposure assessments. Only probabilistic models that took into account indicators of market share and brand loyalty met the validation criteria.

Global sensitivity analysis for models with spatially dependent outputs

International Nuclear Information System (INIS)

Iooss, B.; Marrel, A.; Jullien, M.; Laurent, B.

2011-01-01

The global sensitivity analysis of a complex numerical model often calls for the estimation of variance-based importance measures, named Sobol' indices. Meta-model-based techniques have been developed in order to replace the CPU time-expensive computer code with an inexpensive mathematical function, which predicts the computer code output. The common meta-model-based sensitivity analysis methods are well suited for computer codes with scalar outputs. However, in the environmental domain, as in many areas of application, the numerical model outputs are often spatial maps, which may also vary with time. In this paper, we introduce an innovative method to obtain a spatial map of Sobol' indices with a minimal number of numerical model computations. It is based upon the functional decomposition of the spatial output onto a wavelet basis and the meta-modeling of the wavelet coefficients by the Gaussian process. An analytical example is presented to clarify the various steps of our methodology. This technique is then applied to a real hydrogeological case: for each model input variable, a spatial map of Sobol' indices is thus obtained. (authors)

Asymmetric multi-fractality in the U.S. stock indices using index-based model of A-MFDFA

International Nuclear Information System (INIS)

Lee, Minhyuk; Song, Jae Wook; Park, Ji Hwan; Chang, Woojin

2017-01-01

Highlights: • ‘Index-based A-MFDFA’ model is proposed to assess the asymmetric multi-fractality. • The asymmetric multi-fractality in the U.S. stock indices are investigated using ‘Index-based’ and ‘Return-based’ A-MFDFA. • The asymmetric feature is more significantly identified by ‘Index-based’ model than ‘return-based’ model. • Source of multi-fractality and time-varying features are analyzed. - Abstract: We detect the asymmetric multi-fractality in the U.S. stock indices based on the asymmetric multi-fractal detrended fluctuation analysis (A-MFDFA). Instead using the conventional return-based approach, we propose the index-based model of A-MFDFA where the trend based on the evolution of stock index rather than stock price return plays a role for evaluating the asymmetric scaling behaviors. The results show that the multi-fractal behaviors of the U.S. stock indices are asymmetric and the index-based model detects the asymmetric multi-fractality better than return-based model. We also discuss the source of multi-fractality and its asymmetry and observe that the multi-fractal asymmetry in the U.S. stock indices has a time-varying feature where the degree of multi-fractality and asymmetry increase during the financial crisis.

A photometric analysis of ZZ Ceti stars: A parameter-free temperature indicator?

Energy Technology Data Exchange (ETDEWEB)

Bergeron, P [Departement de Physique, Universite de Montreal, C.P. 6128, Succ. Centre-Ville, Montreal, Quebec H3C 3J7 (Canada); Leggett, S K [Gemini Observatory, Northern Operations Center, 670 North A' ohoku Place, Hilo, Hawaii 96720 (United States); Harris, H C, E-mail: bergeron@astro.umontreal.c, E-mail: sleggett@gemini.ed, E-mail: hch@nofs.navy.mi [US Naval Observatory, Flagstaff Station, Flagstaff, Arizona 86001 (United States)

2009-06-01

We present a model atmosphere analysis of optical VRI and infrared JHK photometric data of about two dozen ZZ Ceti stars. We first show from a theoretical point of view that the resulting energy distributions are not particularly sensitive to surface gravity or to the assumed convective efficiency, a result which suggests a parameter-free effective temperature indicator for ZZ Ceti stars. We then fit the observed energy distributions with our grid of model atmospheres and compare the photometric effective temperatures with the spectroscopic values obtained from fits to the hydrogen line profiles. Our results are finally discussed in the context of the determination of the empirical boundaries of the ZZ Ceti instability strip.

Indicators to support the dynamic evaluation of air quality models

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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.

Sensitivity of Fit Indices to Misspecification in Growth Curve Models

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Wu, Wei; West, Stephen G.

2010-01-01

This study investigated the sensitivity of fit indices to model misspecification in within-individual covariance structure, between-individual covariance structure, and marginal mean structure in growth curve models. Five commonly used fit indices were examined, including the likelihood ratio test statistic, root mean square error of…

Multi-scale analysis of teleconnection indices: climate noise and nonlinear trend analysis

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C. Franzke

2009-02-01

Full Text Available The multi-scale nature and climate noise properties of teleconnection indices are examined by using the Empirical Mode Decomposition (EMD procedure. The EMD procedure allows for the analysis of non-stationary time series to extract physically meaningful intrinsic mode functions (IMF and nonlinear trends. The climatologically relevant monthly mean teleconnection indices of the North Atlantic Oscillation (NAO, the North Pacific index (NP and the Southern Annular Mode (SAM are analyzed.

The significance of IMFs and trends are tested against the null hypothesis of climate noise. The analysis of surrogate monthly mean time series from a red noise process shows that the EMD procedure is effectively a dyadic filter bank and the IMFs (except the first IMF are nearly Gaussian distributed. The distribution of the variance contained in IMFs of an ensemble of AR(1 simulations is nearly χ² distributed. To test the statistical significance of the IMFs of the teleconnection indices and their nonlinear trends we utilize an ensemble of corresponding monthly averaged AR(1 processes, which we refer to as climate noise. Our results indicate that most of the interannual and decadal variability of the analysed teleconnection indices cannot be distinguished from climate noise. The NP and SAM indices have significant nonlinear trends, while the NAO has no significant trend when tested against a climate noise hypothesis.

SPECTRAL COLOR INDICES BASED GEOSPATIAL MODELING OF SOIL ORGANIC MATTER IN CHITWAN DISTRICT, NEPAL

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U. K. Mandal

2016-06-01

Full Text Available Space Technology provides a resourceful-cost effective means to assess soil nutrients essential for soil management plan. Soil organic matter (SOM is one of valuable controlling productivity of crops by providing nutrient in farming systems. Geospatial modeling of soil organic matter is essential if there is unavailability of soil test laboratories and its strong spatial correlation. In the present analysis, soil organic matter is modeled from satellite image derived spectral color indices. Brightness Index (BI, Coloration Index (CI, Hue Index (HI, Redness Index (RI and Saturation Index (SI were calculated by converting DN value to radiance and radiance to reflectance from Thematic Mapper image. Geospatial model was developed by regressing SOM with color indices and producing multiple regression model using stepwise regression technique. The multiple regression equation between SOM and spectral indices was significant with R = 0. 56 at 95% confidence level. The resulting MLR equation was then used for the spatial prediction for the entire study area. Redness Index was found higher significance in estimating the SOM. It was used to predict SOM as auxiliary variables using cokringing spatial interpolation technique. It was tested in seven VDCs of Chitwan district of Nepal using Thematic Mapper remotely sensed data. SOM was found to be measured ranging from 0.15% to 4.75 %, with a mean of 2.24 %. Remotely sensed data derived spectral color indices have the potential as useful auxiliary variables for estimating SOM content to generate soil fertility management plans.

Multivariate Analysis of Profitability Indicators for Selected Companies of Croatian Market

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Ana Perisa

2017-12-01

Full Text Available In this paper, the profitability indicators are analysed for the first hundred companies of the Croatian market, which are classified according to the net profit. The profitability indicators included in the analysis are the following: EBIT margin, EBITDA margin, net profit margin, return on assets (ROA, return on invested capital (ROI and return on capital employed (ROCE. By implementing the factor analysis, six chosen profitability indicators have been reduced to two factors, thus solving the multicollinearity problem, which is one of the prerequisites for the cluster analysis. For two extracted factors, the factor scores are calculated and used in the following cluster analysis. By implementing the cluster analysis, selected companies are grouped into clusters according to their similarity in accomplished results that are measured by profitability indicators. The hierarchical and non-hierarchical cluster analyses are conducted and resulted into two clusters where ten companies were in the first cluster, while the other ninety were in the second cluster

Evaluation of natural gas supply options for south east and central Europe. Part 1: Indicator definitions and single indicator analysis

International Nuclear Information System (INIS)

Afgan, Naim H.; Carvalho, Maria G.; Pilavachi, Petros A.; Martins, Nelson

2007-01-01

The need for diversification of energy sources is an immanent goal in long term energy strategy. In particular, this is of great importance for the natural gas supply. In this respect, evaluation and assessment of potential natural gas resources and their relation to consumers is of great importance. The natural gas supply in Europe is one of the main issues of European energy strategy to be followed in the future. In particular, the natural gas supply in the southeast countries is important. This paper provides a framework for understanding how much natural gas is available for use in south east and central Europe as well as the links to the recent supply of natural gas and its transport. The analysis is focused on evaluation of the potential routes for natural gas supply to the south east and central European countries. The potential options included in this analysis are the Yamal Route; Nabucco Route; West Balkan Route; LNG NEUM Route and Gas by Wire Route. In this analysis, attention is focused on the following indicators for assessment of potential options: environmental indicator; NG cost indicator; NG transport and royalty indicator; investment indicator; and NG demand indicator. The first part of this paper is devoted to the definition of the indicators and to single indicator analysis. (author)

Statistical model of planning technological indicators for oil extraction

Energy Technology Data Exchange (ETDEWEB)

Galeyev, R G; Lavushchenko, V P; Sheshnev, A S

1979-01-01

The efficiency of the process of oil extraction is determined by the effect of a number of interrelated technological indicators. Analytical expression of the interrelationships of the indicators was represented by an econometric model consisting of a system of linear regression equations. The basic advantage of these models is the possibility of calculating in them different, significantly important interrelationships. This makes it possible to correlate all calculations into a single logically noncontradictory balanced system. The developed model of the technological process of oil extraction makes it possible to significantly facilitate calculation and planning of its basic indicators with regard for system and balance requirements, makes it possible to purposefully generate new variants. In this case because of the optimal distribution of the volumes of geological-technical measures, a decrease in the total outlays for their implementation is achieved. Thus for the Berezovskiy field, this saving was R 150,000.

Uncertainty analysis and validation of environmental models. The empirically based uncertainty analysis

International Nuclear Information System (INIS)

Monte, Luigi; Hakanson, Lars; Bergstroem, Ulla; Brittain, John; Heling, Rudie

1996-01-01

The principles of Empirically Based Uncertainty Analysis (EBUA) are described. EBUA is based on the evaluation of 'performance indices' that express the level of agreement between the model and sets of empirical independent data collected in different experimental circumstances. Some of these indices may be used to evaluate the confidence limits of the model output. The method is based on the statistical analysis of the distribution of the index values and on the quantitative relationship of these values with the ratio 'experimental data/model output'. Some performance indices are described in the present paper. Among these, the so-called 'functional distance' (d) between the logarithm of model output and the logarithm of the experimental data, defined as d 2 =Σ n 1 ( ln M i - ln O i ) 2 /n where M i is the i-th experimental value, O i the corresponding model evaluation and n the number of the couplets 'experimental value, predicted value', is an important tool for the EBUA method. From the statistical distribution of this performance index, it is possible to infer the characteristics of the distribution of the ratio 'experimental data/model output' and, consequently to evaluate the confidence limits for the model predictions. This method was applied to calculate the uncertainty level of a model developed to predict the migration of radiocaesium in lacustrine systems. Unfortunately, performance indices are affected by the uncertainty of the experimental data used in validation. Indeed, measurement results of environmental levels of contamination are generally associated with large uncertainty due to the measurement and sampling techniques and to the large variability in space and time of the measured quantities. It is demonstrated that this non-desired effect, in some circumstances, may be corrected by means of simple formulae

Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma.

Science.gov (United States)

Tadeo, Irene; Piqueras, Marta; Montaner, David; Villamón, Eva; Berbegall, Ana P; Cañete, Adela; Navarro, Samuel; Noguera, Rosa

2014-02-01

Risk classification and treatment stratification for cancer patients is restricted by our incomplete picture of the complex and unknown interactions between the patient's organism and tumor tissues (transformed cells supported by tumor stroma). Moreover, all clinical factors and laboratory studies used to indicate treatment effectiveness and outcomes are by their nature a simplification of the biological system of cancer, and cannot yet incorporate all possible prognostic indicators. A multiparametric analysis on 184 tumor cylinders was performed. To highlight the benefit of integrating digitized medical imaging into this field, we present the results of computational studies carried out on quantitative measurements, taken from stromal and cancer cells and various extracellular matrix fibers interpenetrated by glycosaminoglycans, and eight current approaches to risk stratification systems in patients with primary and nonprimary neuroblastoma. New tumor tissue indicators from both fields, the cellular and the extracellular elements, emerge as reliable prognostic markers for risk stratification and could be used as molecular targets of specific therapies. The key to dealing with personalized therapy lies in the mathematical modeling. The use of bioinformatics in patient-tumor-microenvironment data management allows a predictive model in neuroblastoma.

Analysis of the environmental and economic indicators of the industrial enterprise

Science.gov (United States)

Mikhailov, V. G.; Kiseleva, T. V.

2018-05-01

In the paper the features of the analysis of the environmental and economic indicators of the industrial enterprise are considered. The purpose of the study is to improve the system of environmental and economic analysis at the enterprise for more accurate forecasting of its main environmental and economic indicators. The study of the main approaches to the implementation of environmental and economic analysis based on the corresponding systems of indicators with identification of the most significant factors was carried out. The main result of the study is the choice of a system for analyzing the environmental and economic indicators, maximally oriented to a specific enterprise, taking into account its production specific features. The practical significance of the study consists in the selection of an adequate system of indicators at enterprises to improve the effectiveness from preparation of an environmentally safe management decision.

Major indicators of analysis of insurers’ investment activity

Directory of Open Access Journals (Sweden)

O.O. Poplavskyi

2016-12-01

Full Text Available The article is devoted to topical issues of economic nature, selection and use of economic indicators in analysis of insurers’ investment activity. The author determines the main criteria of permissible investment activity, such as different assets covering the insurance reserves and share of various types of investments in assets and capital on the base of the results of summarizing recent public requirements of key banks to insurance companies in Ukraine. The recommendations of the insurers’ analysis approved by the regulatory bodies in Ukraine (the State Commission for Regulation of Financial Services Markets, Belarus (the Ministry of Finance and Poland (the Financial Supervision Authority are not left without author’s attention. According to the results of comparing using of different indicators, like the return on equity and investment, their strength and weaknesses are identified and the improving the scales of their assessment are proposed. The article singles out the main indicators which can be adapted to national features+ and used for management decisions and regulation of investment activities of insurers.

How reliable are geometry-based building indices as thermal performance indicators?

International Nuclear Information System (INIS)

Rodrigues, Eugénio; Amaral, Ana Rita; Gaspar, Adélio Rodrigues; Gomes, Álvaro

2015-01-01

Highlights: • Geometry-based building indices are tested in different European climate regions. • Building design programs are used to randomly generate sets of simulation models. • Some indices correlate in specific climates and design programs. • Shape-based Relative Compactness presented the best correlation of all indices. • Window-to-Surface Ratio was the window-based index with best correlation. - Abstract: Architects and urban planners have been relying on geometry-based indices to design more energy efficient buildings for years. The advantage of such indices is their ease of use and capability to capture the relation of a few geometric variables with the building’s performance. However, such relation is usually found using only a few simple building models and considering only a few climate regions. This paper presents the analysis of six geometry-based building indices to determine their adequacy in eight different climate regions in Europe. For each location, three residential building design programs were used as building specifications. Two algorithms were employed to randomly generate and assess the thermal performance of three sets of 500 alternative building models. The results show that geometry-based indices only correlate with the buildings’ thermal performance according to specific climate regions and building design programs

Scenario analysis of false indication in computer-control systems

International Nuclear Information System (INIS)

Tseng, Wan-Hui; Fan, Chin-Feng

2013-01-01

Highlights: ► A new failure mode and effect for safety-critical systems is proposed. ► False indication is the most dreadful kind of partial failures. ► A model-based simulation approach to generate failure scenarios is proposed. ► Simulation results showed that multiple errors may cause undesired consequences. ► An assertion-based method to detect false indication problems is provided. -- Abstract: Computer control may cause additional failure modes and effects that are new to analogue systems. False indication is one such failure mode that may bring unknown risks to a system. False indication refers to the problem when part of a system fails while other processes still work, and the failure is not revealed to operators. This paper presents a model-based simulation approach to systematically generate potential false indication and unintended consequences. Experiments showed that once a false indication occurs, it may have drastic effects on system safety. False indication can mislead the operator to perform adverse actions or no action. Therefore, we propose an assertion-based detection method to alleviate such failures. Our assertions contain process/device dependencies, timing relations and physical conservation rules. With these assertions, the operator may be alerted at run time. The proposed technique can reduce false indication problem. Moreover, it can also be used to assist the system design.

A descriptive analysis of quantitative indices for multi-objective block layout

Directory of Open Access Journals (Sweden)

Amalia Medina Palomera

2013-01-01

Full Text Available Layout generation methods provide alternative solutions whose feasibility and quality must be evaluated. Indices must be used to distinguish the feasible solutions (involving different criteria obtained for block layout to identify s solution’s suitability, according to set objectives. This paper provides an accurate and descriptive analysis of the geometric indices used in designing facility layout (during block layout phase. The indices studied here have advantages and disadvantages which should be considered by an analyst before attempting to resolve the facility layout problem. New equations are proposed for measuring geometric indices. The analysis revealed redundant indices and that a minimum number of indices covering overall quality criteria may be used when selecting alternative solutions.

An Integrated Model Based on a Hierarchical Indices System for Monitoring and Evaluating Urban Sustainability

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Xulin Guo

2013-02-01

Full Text Available Over 50% of world’s population presently resides in cities, and this number is expected to rise to ~70% by 2050. Increasing urbanization problems including population growth, urban sprawl, land use change, unemployment, and environmental degradation, have markedly impacted urban residents’ Quality of Life (QOL. Therefore, urban sustainability and its measurement have gained increasing attention from administrators, urban planners, and scientific communities throughout the world with respect to improving urban development and human well-being. The widely accepted definition of urban sustainability emphasizes the balancing development of three primary domains (urban economy, society, and environment. This article attempts to improve the aforementioned definition of urban sustainability by incorporating a human well-being dimension. Major problems identified in existing urban sustainability indicator (USI models include a weak integration of potential indicators, poor measurement and quantification, and insufficient spatial-temporal analysis. To tackle these challenges an integrated USI model based on a hierarchical indices system was established for monitoring and evaluating urban sustainability. This model can be performed by quantifying indicators using both traditional statistical approaches and advanced geomatic techniques based on satellite imagery and census data, which aims to provide a theoretical basis for a comprehensive assessment of urban sustainability from a spatial-temporal perspective.

Model Selection in Data Analysis Competitions

DEFF Research Database (Denmark)

Wind, David Kofoed; Winther, Ole

2014-01-01

The use of data analysis competitions for selecting the most appropriate model for a problem is a recent innovation in the field of predictive machine learning. Two of the most well-known examples of this trend was the Netflix Competition and recently the competitions hosted on the online platform...... performers from Kaggle and use previous personal experiences from competing in Kaggle competitions. The stated hypotheses about feature engineering, ensembling, overfitting, model complexity and evaluation metrics give indications and guidelines on how to select a proper model for performing well...... Kaggle. In this paper, we will state and try to verify a set of qualitative hypotheses about predictive modelling, both in general and in the scope of data analysis competitions. To verify our hypotheses we will look at previous competitions and their outcomes, use qualitative interviews with top...

Environmental Indicator Principium with Case References to Agricultural Soil, Water, and Air Quality and Model-Derived Indicators.

Science.gov (United States)

Zhang, T Q; Zheng, Z M; Lal, R; Lin, Z Q; Sharpley, A N; Shober, A L; Smith, D; Tan, C S; Van Cappellen, P

2018-03-01

Environmental indicators are powerful tools for tracking environmental changes, measuring environmental performance, and informing policymakers. Many diverse environmental indicators, including agricultural environmental indicators, are currently in use or being developed. This special collection of technical papers expands on the peer-reviewed literature on environmental indicators and their application to important current issues in the following areas: (i) model-derived indicators to indicate phosphorus losses from arable land to surface runoff and subsurface drainage, (ii) glutathione-ascorbate cycle-related antioxidants as early-warning bioindicators of polybrominated diphenyl ether toxicity in mangroves, and (iii) assessing the effectiveness of using organic matrix biobeds to limit herbicide dissipation from agricultural fields, thereby controlling on-farm point-source pollution. This introductory review also provides an overview of environmental indicators, mainly for agriculture, with examples related to the quality of the agricultural soil-water-air continuum and the application of model-derived indicators. Current knowledge gaps and future lines of investigation are also discussed. It appears that environmental indicators, particularly those for agriculture, work efficiently at the field, catchment, and local scales and serve as valuable metrics of system functioning and response; however, these indicators need to be refined or further developed to comprehensively meet community expectations in terms of providing a consistent picture of relevant issues and/or allowing comparisons to be made nationally or internationally. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Global Patterns in Ecological Indicators of Marine Food Webs: A Modelling Approach

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Heymans, Johanna Jacomina; Coll, Marta; Libralato, Simone; Morissette, Lyne; Christensen, Villy

2014-01-01

Background Ecological attributes estimated from food web models have the potential to be indicators of good environmental status given their capabilities to describe redundancy, food web changes, and sensitivity to fishing. They can be used as a baseline to show how they might be modified in the future with human impacts such as climate change, acidification, eutrophication, or overfishing. Methodology In this study ecological network analysis indicators of 105 marine food web models were tested for variation with traits such as ecosystem type, latitude, ocean basin, depth, size, time period, and exploitation state, whilst also considering structural properties of the models such as number of linkages, number of living functional groups or total number of functional groups as covariate factors. Principal findings Eight indicators were robust to model construction: relative ascendency; relative overhead; redundancy; total systems throughput (TST); primary production/TST; consumption/TST; export/TST; and total biomass of the community. Large-scale differences were seen in the ecosystems of the Atlantic and Pacific Oceans, with the Western Atlantic being more complex with an increased ability to mitigate impacts, while the Eastern Atlantic showed lower internal complexity. In addition, the Eastern Pacific was less organised than the Eastern Atlantic although both of these systems had increased primary production as eastern boundary current systems. Differences by ecosystem type highlighted coral reefs as having the largest energy flow and total biomass per unit of surface, while lagoons, estuaries, and bays had lower transfer efficiencies and higher recycling. These differences prevailed over time, although some traits changed with fishing intensity. Keystone groups were mainly higher trophic level species with mostly top-down effects, while structural/dominant groups were mainly lower trophic level groups (benthic primary producers such as seagrass and macroalgae

Global patterns in ecological indicators of marine food webs: a modelling approach.

Directory of Open Access Journals (Sweden)

Johanna Jacomina Heymans

Full Text Available BACKGROUND: Ecological attributes estimated from food web models have the potential to be indicators of good environmental status given their capabilities to describe redundancy, food web changes, and sensitivity to fishing. They can be used as a baseline to show how they might be modified in the future with human impacts such as climate change, acidification, eutrophication, or overfishing. METHODOLOGY: In this study ecological network analysis indicators of 105 marine food web models were tested for variation with traits such as ecosystem type, latitude, ocean basin, depth, size, time period, and exploitation state, whilst also considering structural properties of the models such as number of linkages, number of living functional groups or total number of functional groups as covariate factors. PRINCIPAL FINDINGS: Eight indicators were robust to model construction: relative ascendency; relative overhead; redundancy; total systems throughput (TST; primary production/TST; consumption/TST; export/TST; and total biomass of the community. Large-scale differences were seen in the ecosystems of the Atlantic and Pacific Oceans, with the Western Atlantic being more complex with an increased ability to mitigate impacts, while the Eastern Atlantic showed lower internal complexity. In addition, the Eastern Pacific was less organised than the Eastern Atlantic although both of these systems had increased primary production as eastern boundary current systems. Differences by ecosystem type highlighted coral reefs as having the largest energy flow and total biomass per unit of surface, while lagoons, estuaries, and bays had lower transfer efficiencies and higher recycling. These differences prevailed over time, although some traits changed with fishing intensity. Keystone groups were mainly higher trophic level species with mostly top-down effects, while structural/dominant groups were mainly lower trophic level groups (benthic primary producers such as

Groundwater development stress: Global-scale indices compared to regional modeling

Science.gov (United States)

Alley, William; Clark, Brian R.; Ely, Matt; Faunt, Claudia

2018-01-01

The increased availability of global datasets and technologies such as global hydrologic models and the Gravity Recovery and Climate Experiment (GRACE) satellites have resulted in a growing number of global-scale assessments of water availability using simple indices of water stress. Developed initially for surface water, such indices are increasingly used to evaluate global groundwater resources. We compare indices of groundwater development stress for three major agricultural areas of the United States to information available from regional water budgets developed from detailed groundwater modeling. These comparisons illustrate the potential value of regional-scale analyses to supplement global hydrological models and GRACE analyses of groundwater depletion. Regional-scale analyses allow assessments of water stress that better account for scale effects, the dynamics of groundwater flow systems, the complexities of irrigated agricultural systems, and the laws, regulations, engineering, and socioeconomic factors that govern groundwater use. Strategic use of regional-scale models with global-scale analyses would greatly enhance knowledge of the global groundwater depletion problem.

Econometric Models for Forecasting of Macroeconomic Indices

Science.gov (United States)

Sukhanova, Elena I.; Shirnaeva, Svetlana Y.; Mokronosov, Aleksandr G.

2016-01-01

The urgency of the research topic was stipulated by the necessity to carry out an effective controlled process by the economic system which can hardly be imagined without indices forecasting characteristic of this system. An econometric model is a safe tool of forecasting which makes it possible to take into consideration the trend of indices…

The conceptualization and measurement of cognitive reserve using common proxy indicators: Testing some tenable reflective and formative models.

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Ikanga, Jean; Hill, Elizabeth M; MacDonald, Douglas A

2017-02-01

The examination of cognitive reserve (CR) literature reveals a lack of consensus regarding conceptualization and pervasive problems with its measurement. This study aimed at examining the conceptual nature of CR through the analysis of reflective and formative models using eight proxies commonly employed in the CR literature. We hypothesized that all CR proxies would significantly contribute to a one-factor reflective model and that educational and occupational attainment would produce the strongest loadings on a single CR factor. The sample consisted of 149 participants (82 male/67 female), with 18.1 average years of education and ages of 45-99 years. Participants were assessed for eight proxies of CR (parent socioeconomic status, intellectual functioning, level of education, health literacy, occupational prestige, life leisure activities, physical activities, and spiritual and religious activities). Primary statistical analyses consisted of confirmatory factor analysis (CFA) to test reflective models and structural equation modeling (SEM) to evaluate multiple indicators multiple causes (MIMIC) models. CFA did not produce compelling support for a unitary CR construct when using all eight of our CR proxy variables in a reflective model but fairly cogent evidence for a one-factor model with four variable proxies. A second three-factor reflective model based upon an exploratory principal components analysis of the eight proxies was tested using CFA. Though all eight indicators significantly loaded on their assigned factors, evidence in support of overall model fit was mixed. Based upon the results involving the three-factor reflective model, two alternative formative models were developed and evaluated. While some support was obtained for both, the model in which the formative influences were specified as latent variables appeared to best account for the contributions of all eight proxies to the CR construct. While the findings provide partial support for our

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

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Xiao-meng Song

2013-01-01

Full Text Available Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on (1 a screening method (Morris for qualitative ranking of parameters, and (2 a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model (RSMSobol. First, the Morris screening method was used to qualitatively identify the parameters' sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model (RSM were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

Review and Recommendations for Zero-inflated Count Regression Modeling of Dental Caries Indices in Epidemiological Studies

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Stamm, John W.; Long, D. Leann; Kincade, Megan E.

2012-01-01

Over the past five to ten years, zero-inflated count regression models have been increasingly applied to the analysis of dental caries indices (e.g., DMFT, dfms, etc). The main reason for that is linked to the broad decline in children’s caries experience, such that dmf and DMF indices more frequently generate low or even zero counts. This article specifically reviews the application of zero-inflated Poisson and zero-inflated negative binomial regression models to dental caries, with emphasis on the description of the models and the interpretation of fitted model results given the study goals. The review finds that interpretations provided in the published caries research are often imprecise or inadvertently misleading, particularly with respect to failing to discriminate between inference for the class of susceptible persons defined by such models and inference for the sampled population in terms of overall exposure effects. Recommendations are provided to enhance the use as well as the interpretation and reporting of results of count regression models when applied to epidemiological studies of dental caries. PMID:22710271

Modeling trends of health and health related indicators in Ethiopia (1995-2008: a time-series study

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Nigatu Tilahun H

2009-12-01

Full Text Available Abstract Background The Federal Ministry of Health of Ethiopia has been publishing Health and Health related indicators of the country annually since 1987 E.C. These indicators have been of high importance in indicating the status of health in the country in those years. However, the trends/patterns of these indicators and the factors related to the trends have not yet been investigated in a systematic manner. In addition, there were minimal efforts to develop a model for predicting future values of Health and Health related indicators based on the current trend. Objectives The overall aim of this study was to analyze trends of and develop model for prediction of Health and Health related indicators. More specifically, it described the trends of Health and Health related indicators, identified determinants of mortality and morbidity indicators and developed model for predicting future values of MDG indicators. Methods This study was conducted on Health and Health related indicators of Ethiopia from the year 1987 E.C to 2000 E.C. Key indicators of Mortality and Morbidity, Health service coverage, Health systems resources, Demographic and socio-economic, and Risk factor indicators were extracted and analyzed. The trends in these indicators were established using trend analysis techniques. The determinants of the established trends were identified using ARIMA models in STATA. The trend-line equations were then used to predict future values of the indicators. Results Among the mortality indicators considered in this study, it was only Maternal Mortality Ratio that showed statistically significant decrement within the study period. The trends of Total Fertility Rate, physician per 100,000 population, skilled birth attendance and postnatal care coverage were found to have significant association with Maternal Mortality Ratio trend. There was a reversal of malaria parasite prevalence in 1999 E.C from Plasmodium Falciparum to Plasmodium Vivax. Based on

Environmental indicators and international models for making decision

International Nuclear Information System (INIS)

Polanco, Camilo

2006-01-01

The last international features proposed by the Organization for Economic Cooperation Development (OECD) and United Nations (UN) are analyzed in the use of the environmental indicators, in typology, selection criteria, and models, for organizing the information for management, environmental performance, and decision making. The advantages and disadvantages of each model are analyzed, as well as their environmental index characteristics. The analyzed models are Pressure - State - Response (PSR) and its conceptual developments: Driving Force - State Response (DSR), Driving Force - Pressure - State - Impact - Response (DPSIR), Model- Flow-Quality (MFQ), Pressure - State - Impact - Effect - Response (PSIER), and, finally, Pressure-State - Impact - Effect - Response - Management (PSIERM). The use of one or another model will depend on the quality of the available information, as well as on the proposed objectives

Performance indicators at Embalse NPP: PSA and safety system indicators based on PSA models

International Nuclear Information System (INIS)

Fornero, D.A.

2001-01-01

Several indicators have been implemented at Embalse NPP. The objective was selecting some representative parameters to evaluate the performance of both the plant and the personnel activities, important for safety. A first set of indicators was defined in accordance with plant technical staff criteria. A complementary set of them was addressed later based on WANO guidance. This report presents the set of indicators used at Embalse NPP, centering the description to related to safety systems performance indicators (SSPI). Some considerations are done about the calculation methods, the need for aligning and updating their values following Embalse Probabilistic Safety Assessment (PSA) development, and some pros and cons of using the PSA model for getting systems indicators. Owing to the fact that PSA ownership by utilities is also a subject of the meeting, some characteristics of the organization of the PSA Project are described at the beginning of the report. At Embalse NPP a Level 1 PSA has been developed under the responsibility of its own plant and with an important contribution from the IAEA. PSA was developed at the site, conducting this to a study strongly interactive with the station staff. (author)

The modeling of response indicators of integrated water resources ...

African Journals Online (AJOL)

The results indicate that the feed forward multilayer perceptron models with back propagation are useful tools to define and prioritize the most effective response variable on water resources mobilization to intervene and solve water problems. The model evaluation shows that the correlation coefficients are more than 96% ...

Assessing plant protection practices using pressure indicator and toxicity risk indicators: analysis of therelationship between these indicators for improved risk management, application in viticulture.

Science.gov (United States)

Oussama, Mghirbi; Kamel, Ellefi; Philippe, Le Grusse; Elisabeth, Mandart; Jacques, Fabre; Habiba, Ayadi; Jean-Paul, Bord

2015-06-01

The excessive use of plant protection products (PPPs) has given rise to issues of public and environmental health because of their toxicity. Reducing the use of toxic PPPs and replacing them with products that are less toxic for human health and the environment have become socially, environmentally and economically indispensable. In this article, we assess the plant protection practices of a small group of winegrowers practicing "integrated agriculture" in the south of France, in order to measure the benefit of using toxicity risk indicators as a decision-support tool for different players in land management. An analysis of plant protection practices using indicators of the risk to operator health and the environment (IRSA, IRTE), together with a frequency-of-treatment indicator (TFI), enabled us to (i) show the variability of these indicators depending on the production system and farmers' pesticide use strategies and (ii) calculate correlations between these indicators. This analysis of plant protection practices at different scales (farm, field), carried out in collaboration with the growers, enabled us to perform an initial validation of decision-support tools for determining risk management strategies regarding the use of pesticides.

Evaluation of empowerment model on indicators of metabolic control in patients with type 2 diabetes, a randomized clinical trial study.

Science.gov (United States)

Ebrahimi, Hossein; Sadeghi, Mahdi; Amanpour, Farzaneh; Vahedi, Hamid

2016-04-01

Diabetes education is a major subject in achieving optimal glycemic control. Effective empowerment approach can be beneficial for improving patients' health. The aim of this study was to evaluate the effect of empowerment model on indicators of metabolic control in patients with type 2 diabetes. a randomized controlled trial of 103 patients with type 2 diabetes were randomly assigned to either the intervention (empowerment approach training) or the control group (conventional training) 2014. Empowerment approach training were performed for the experimental group for eight weeks. Data collection tool included demographic information form and indicators of metabolic control checklist. Analysis was performed by one-way analysis of variance, chi-square test, paired t-test, independent t-test and multiple linear regression. Before the intervention, two groups were homogeneous in terms of demographic variables, glycosylated hemoglobin (HbA1C), and other indicators of metabolic control. After the intervention, average HbA1C and other metabolic indicators except for LDL showed significant differences in the experimental group compared to the control group. study results indicated the positive effects of applying the empowerment model on the metabolic control indicators. Therefore, applying this model is recommended to nurses and the relevant authorities in order to improve clinical outcomes in diabetic patients. Copyright © 2015 Primary Care Diabetes Europe. Published by Elsevier Ltd. All rights reserved.

LBLOCA sensitivity analysis using meta models

International Nuclear Information System (INIS)

Villamizar, M.; Sanchez-Saez, F.; Villanueva, J.F.; Carlos, S.; Sanchez, A.I.; Martorell, S.

2014-01-01

This paper presents an approach to perform the sensitivity analysis of the results of simulation of thermal hydraulic codes within a BEPU approach. Sensitivity analysis is based on the computation of Sobol' indices that makes use of a meta model, It presents also an application to a Large-Break Loss of Coolant Accident, LBLOCA, in the cold leg of a pressurized water reactor, PWR, addressing the results of the BEMUSE program and using the thermal-hydraulic code TRACE. (authors)

Analysis of Behavioral Indicators as a Measure of Satiation.

Science.gov (United States)

Scalzo, Rachel; Davis, Tonya N

2017-03-01

Providing noncontingent access to a stimulus until an individual displays behavioral indicators of satiation has been used to determine when an abolishing operation is in effect, but there has been variation in its application in the literature. Four males diagnosed with autism spectrum disorder with tangibly maintained challenging behavior participated in this study. Individualized behavioral indicators were identified and verified to determine when each participant was finished playing with his/her preferred item. Three presession conditions were manipulated including restricted access to the tangible stimulus for 30 min, access to the tangible stimulus until the display of one behavioral indicator, and access to the tangible stimulus until the display of three behavioral indicators. Each presession condition was followed by a tangible condition of the functional analysis to measure challenging behavior. Results indicated that presession access to a tangible stimulus until the display of three behavioral indicators produced a greater abative effect on challenging behavior than one behavioral indicator.

Correlation and network analysis of global financial indices.

Science.gov (United States)

Kumar, Sunil; Deo, Nivedita

2012-08-01

Random matrix theory (RMT) and network methods are applied to investigate the correlation and network properties of 20 financial indices. The results are compared before and during the financial crisis of 2008. In the RMT method, the components of eigenvectors corresponding to the second largest eigenvalue form two clusters of indices in the positive and negative directions. The components of these two clusters switch in opposite directions during the crisis. The network analysis uses the Fruchterman-Reingold layout to find clusters in the network of indices at different thresholds. At a threshold of 0.6, before the crisis, financial indices corresponding to the Americas, Europe, and Asia-Pacific form separate clusters. On the other hand, during the crisis at the same threshold, the American and European indices combine together to form a strongly linked cluster while the Asia-Pacific indices form a separate weakly linked cluster. If the value of the threshold is further increased to 0.9 then the European indices (France, Germany, and the United Kingdom) are found to be the most tightly linked indices. The structure of the minimum spanning tree of financial indices is more starlike before the crisis and it changes to become more chainlike during the crisis. The average linkage hierarchical clustering algorithm is used to find a clearer cluster structure in the network of financial indices. The cophenetic correlation coefficients are calculated and found to increase significantly, which indicates that the hierarchy increases during the financial crisis. These results show that there is substantial change in the structure of the organization of financial indices during a financial crisis.

Margin of manoeuvre indicators in the workplace during the rehabilitation process: a qualitative analysis.

Science.gov (United States)

Durand, M J; Vézina, N; Baril, R; Loisel, P; Richard, M C; Ngomo, S

2009-06-01

The task of evaluating workers' capacity to return to their pre-injury employment or other jobs continues to pose a daily challenge for clinicians. In this study, a concept frequently used in the field of ergonomics, the margin of manoeuvre (MM), was applied during the rehabilitation process. The study identified the indicators of the MM taken into account during the return to work of workers with musculoskeletal disorders. This study used a multiple-case design. A case was defined as a dyad comprising a worker admitted to a work rehabilitation program and the clinician who was managing the return-to-work process. The results were then validated with investigators and expert ergonomists, through group interviews. Content analyses were performed using the conceptual framework for the work activity model adapted from Vézina and the procedures recommended by Miles and Huberman. A total of 11 workers, five clinicians, two experts and two investigators participated in this study. The interview analysis process resulted in a more detailed definition of the MM and the identification of 50 indicators. The indicators were classified according to six dimensions: (1) work context; (2) employer's requirements and expectations; (3) means and tools; (4) worker's personal parameters; (5) work activity; and (6) impacts of the work situation. The more specific indicators identified in this study will allow for more systematic observation of the MM. Subsequent studies will seek to link each indicator described in the model with a specific method of observation.

Evaluation of Cost Models and Needs & Gaps Analysis

DEFF Research Database (Denmark)

Kejser, Ulla Bøgvad

2014-01-01

they breakdown costs. This is followed by an in depth analysis of stakeholders’ needs for financial information derived from the 4C project stakeholder consultation.The stakeholders’ needs analysis indicated that models should:• support accounting, but more importantly they should enable budgeting• be able......his report ’D3.1—Evaluation of Cost Models and Needs & Gaps Analysis’ provides an analysis of existing research related to the economics of digital curation and cost & benefit modelling. It reports upon the investigation of how well current models and tools meet stakeholders’ needs for calculating...... andcomparing financial information. Based on this evaluation, it aims to point out gaps that need to be bridged in order to increase the uptake of cost & benefit modelling and good practices that will enable costing and comparison of the costs of alternative scenarios—which in turn provides a starting point...

Confirmatory factory analysis of the Neck Disability Index in a general problematic neck population indicates a one-factor model.

Science.gov (United States)

Gabel, Charles Philip; Cuesta-Vargas, Antonio I; Osborne, Jason W; Burkett, Brendan; Melloh, Markus

2014-08-01

The Neck Disability Index frequently is used to measure outcomes of the neck. The statistical rigor of the Neck Disability Index has been assessed with conflicting outcomes. To date, Confirmatory Factor Analysis of the Neck Disability Index has not been reported for a suitably large population study. Because the Neck Disability Index is not a condition-specific measure of neck function, initial Confirmatory Factor Analysis should consider problematic neck patients as a homogenous group. We sought to analyze the factor structure of the Neck Disability Index through Confirmatory Factor Analysis in a symptomatic, homogeneous, neck population, with respect to pooled populations and gender subgroups. This was a secondary analysis of pooled data. A total of 1,278 symptomatic neck patients (67.5% female, median age 41 years), 803 nonspecific and 475 with whiplash-associated disorder. The Neck Disability Index was used to measure outcomes. We analyzed pooled baseline data from six independent studies of patients with neck problems who completed Neck Disability Index questionnaires at baseline. The Confirmatory Factor Analysis was considered in three scenarios: the full sample and separate sexes. Models were compared empirically for best fit. Two-factor models have good psychometric properties across both the pooled and sex subgroups. However, according to these analyses, the one-factor solution is preferable from both a statistical perspective and parsimony. The two-factor model was close to significant for the male subgroup (pfactor structure when analyzed by Confirmatory Factor Analysis in a pooled, homogenous sample of neck problem patients. However, a two-factor model did approach significance for male subjects where questions separated into constructs of mental and physical function. Further investigations in different conditions, subgroup and sex-specific populations are warranted. Copyright © 2014 Elsevier Inc. All rights reserved.

Modelling pesticides volatilisation in greenhouses: Sensitivity analysis of a modified PEARL model.

Science.gov (United States)

Houbraken, Michael; Doan Ngoc, Kim; van den Berg, Frederik; Spanoghe, Pieter

2017-12-01

The application of the existing PEARL model was extended to include estimations of the concentration of crop protection products in greenhouse (indoor) air due to volatilisation from the plant surface. The model was modified to include the processes of ventilation of the greenhouse air to the outside atmosphere and transformation in the air. A sensitivity analysis of the model was performed by varying selected input parameters on a one-by-one basis and comparing the model outputs with the outputs of the reference scenarios. The sensitivity analysis indicates that - in addition to vapour pressure - the model had the highest ratio of variation for the rate ventilation rate and thickness of the boundary layer on the day of application. On the days after application, competing processes, degradation and uptake in the plant, becomes more important. Copyright © 2017 Elsevier B.V. All rights reserved.

Urban Sprawl Analysis and Modeling in Asmara, Eritrea

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Mussie G. Tewolde

2011-09-01

Full Text Available The extension of urban perimeter markedly cuts available productive land. Hence, studies in urban sprawl analysis and modeling play an important role to ensure sustainable urban development. The urbanization pattern of the Greater Asmara Area (GAA, the capital of Eritrea, was studied. Satellite images and geospatial tools were employed to analyze the spatiotemporal urban landuse changes. Object-Based Image Analysis (OBIA, Landuse Cover Change (LUCC analysis and urban sprawl analysis using Shannon Entropy were carried out. The Land Change Modeler (LCM was used to develop a model of urban growth. The Multi-layer Perceptron Neural Network was employed to model the transition potential maps with an accuracy of 85.9% and these were used as an input for the ‘actual’ urban modeling with Markov chains. Model validation was assessed and a scenario of urban land use change of the GAA up to year 2020 was presented. The result of the study indicated that the built-up area has tripled in size (increased by 4,441 ha between 1989 and 2009. Specially, after year 2000 urban sprawl in GAA caused large scale encroachment on high potential agricultural lands and plantation cover. The scenario for year 2020 shows an increase of the built-up areas by 1,484 ha (25% which may cause further loss. The study indicated that the land allocation system in the GAA overrode the landuse plan, which caused the loss of agricultural land and plantation cover. The recommended policy options might support decision makers to resolve further loss of agricultural land and plantation cover and to achieve sustainable urban development planning in the GAA.

Evaluation Indicators for Analysis of Nuclear Fuel Cycle Sustainability

Energy Technology Data Exchange (ETDEWEB)

Jeong, Chang Joon; Ko, Won Il; Chang, Hong Lae

2008-01-15

In this report, an attempt was made to derive indicators for the evaluation of the sustainability of the nuclear fuel cycle, using the methodologies developed by the INPRO, OECD/NEA and Gen-IV. In deriving the indicators, the three main elements of the sustainability, i.e., economics, environmental impact, and social aspect, as well as the technological aspect of the nuclear fuel cycle, considering the importance of the safety, were selected as the main criteria. An evaluation indicator for each criterion was determined, and the contents and evaluation method of each indicator were proposed. In addition, a questionnaire survey was carried out for the objectivity of the selection of the indicators in which participated some experts of the Korea Energy Technology and Emergency Management Institute (KETEMI) . Although the proposed indicators do not satisfy the characteristics and requirements of general indicators, it is presumed that they can be used in the analysis of the sustainability of the nuclear fuel cycle because those indicators incorporate various expert judgment and public opinions. On the other hand, the weighting factor of each indicator should be complemented in the future, using the AHP method and expert advice/consultations.

Modelling Dynamics of Main Economic Indicators of an Enterprise

Directory of Open Access Journals (Sweden)

Sherstennykov Yurii V.

2014-03-01

Full Text Available The article develops an economic and mathematical model of dynamics of main economic indicators of an enterprise, reflected in six book-keeping accounts with consideration of logistics and interrelation with current market characteristics and needs of products consumers. It applies this model for a quantitative study of influence of an advertising campaign and seasonality upon quantitative indicators of economic activity of the enterprise. The enterprise operation programme includes internal financial and economic procedures, which ensure the production process, and also connection with suppliers and buyers (customers. When setting different initial conditions, it is possible to trace transitional processes and enterprise entering (under favourable conditions the stationary mode of operation or its laying-off (in case of insufficiency of circulating funds. The developed model contains many parameters, which allow not only study of dependence of enterprise operation on alteration of one of them but also optimisation of economic conditions of functioning.

Trace analysis of cyanide by ion-selective electrode indicator technique

International Nuclear Information System (INIS)

Tom, R.L.; Kapauan, P.A.

1977-01-01

Due to the toxicity of cyanide, its analysis in water is important. The use of ion-selective electrodes for its determination was studied. The known addition method using a silver sulfide membrane electrode was studied. This involved using a silver indicator solution to determine the cyanide content of a sample. Known amounts of a standard cyanide solution were added and the potentials noted. The results were plotted and the original concentration of cyanide extrapolated. The results of the experiment indicated the method to be practical for analysis of industrial waste waters, even in the presence of metal ions. The metal ions were masked using an EDTA solution while possible sulfides were precipitated out using a Pb (N0 3 ) 2 solution. The method was tested on four actual samples and the results indicated the applicability of the method

Hydrochemical analysis of groundwater using a tree-based model

Science.gov (United States)

Litaor, M. Iggy; Brielmann, H.; Reichmann, O.; Shenker, M.

2010-06-01

SummaryHydrochemical indices are commonly used to ascertain aquifer characteristics, salinity problems, anthropogenic inputs and resource management, among others. This study was conducted to test the applicability of a binary decision tree model to aquifer evaluation using hydrochemical indices as input. The main advantage of the tree-based model compared to other commonly used statistical procedures such as cluster and factor analyses is the ability to classify groundwater samples with assigned probability and the reduction of a large data set into a few significant variables without creating new factors. We tested the model using data sets collected from headwater springs of the Jordan River, Israel. The model evaluation consisted of several levels of complexity, from simple separation between the calcium-magnesium-bicarbonate water type of karstic aquifers to the more challenging separation of calcium-sodium-bicarbonate water type flowing through perched and regional basaltic aquifers. In all cases, the model assigned measures for goodness of fit in the form of misclassification errors and singled out the most significant variable in the analysis. The model proceeded through a sequence of partitions providing insight into different possible pathways and changing lithology. The model results were extremely useful in constraining the interpretation of geological heterogeneity and constructing a conceptual flow model for a given aquifer. The tree model clearly identified the hydrochemical indices that were excluded from the analysis, thus providing information that can lead to a decrease in the number of routinely analyzed variables and a significant reduction in laboratory cost.

Profile agreement indices in Rietveld and pattern-fitting analysis

International Nuclear Information System (INIS)

Hill, R.J.; Fischer, R.X.

1990-01-01

Two definitions of profile agreement indices are now in common use for estimating the degree of fit in Rietveld refinement and in structure-independent pattern-fitting methods of powder diffraction analysis. In the original program written by Rietveld, the background was subtracted and the 'non-peak' regions of the pattern were removed from further consideration in a preliminary data-reduction stage prior to structure refinement. However, the agreement indices used in many of the more recent programs retain the background counts in the observed step intensities and include all portions of the pattern in the sums. These latter definitions are strongly dependent on the signal-to-noise ratio and on the relative amount of 'background-only' regions and do not, therefore, provide a sound basis for comparing the degree of fit of peak profile and crystal structure model refinements in the general case. The extent of this dependence is illustrated quantitatively using conventional and synchrotron X-ray and constant-wavelength and time-of-flight neutron data sets with different inherent background levels and peak densities. The unweighted background-corrected peak-only profile agreement index R' p =Σ i vertical strokeY io -Y ic vertical stroke/Σ i vertical strokeY io -Y ib vertical stroke (and, to a lesser extent, its weighted equivalent) is recommended as the most appropriate criterion of fit for comparative work between diffraction patterns of all kinds. (orig.)

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

Science.gov (United States)

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

2017-11-01

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

Indicators Used in the Dynamic Analysis of Turnover

Directory of Open Access Journals (Sweden)

Mihaela Loredana Ecobici

2016-01-01

Full Text Available The dynamic evolution of an indicator is an important aspect to be taken into consideration when analyzing the evolution in a company. Dynamic evolution uses a number of indicators that reveal aspects that the management of a company must introduce in the development strategy or in the rehabilitation process of a company. The purpose of this article is to analyse the dynamic evolution of the turnover at a company that operates in the field of industry. The finality of this article will result in a number of conclusions concerning the evolution of turnover analysed in the light of absolute modification, indices, growth rates and annual average rate of growth. The importance of the analysis of its evolution, stemming from the fact that it is in a relationship of perpetuous interdependence with the main economic factors that participate in the activity of production and marketing.

On the usage of geomagnetic indices for data selection in internal field modelling

DEFF Research Database (Denmark)

Kauristie, K.; Morschhauser, A.; Olsen, Nils

2017-01-01

are primarily used in data selection criteria for weak magnetic activity.The publicly available extensive data bases of index values are used to derive joint conditional Probability Distribution Functions (PDFs) for different pairs of indices in order to investigate their mutual consistency in describing quiet......) as derived from solar wind observations. We use in our PDF analysis the PC-index as a proxy for MEF and estimate the magnetic activity level at auroral latitudes with the AL-index. With these boundary conditions we conclude that the quiet time conditions that are typically used in main field modelling (PC...

Dynamic sensitivity analysis of long running landslide models through basis set expansion and meta-modelling

Science.gov (United States)

Rohmer, Jeremy

2016-04-01

Predicting the temporal evolution of landslides is typically supported by numerical modelling. Dynamic sensitivity analysis aims at assessing the influence of the landslide properties on the time-dependent predictions (e.g., time series of landslide displacements). Yet two major difficulties arise: 1. Global sensitivity analysis require running the landslide model a high number of times (> 1000), which may become impracticable when the landslide model has a high computation time cost (> several hours); 2. Landslide model outputs are not scalar, but function of time, i.e. they are n-dimensional vectors with n usually ranging from 100 to 1000. In this article, I explore the use of a basis set expansion, such as principal component analysis, to reduce the output dimensionality to a few components, each of them being interpreted as a dominant mode of variation in the overall structure of the temporal evolution. The computationally intensive calculation of the Sobol' indices for each of these components are then achieved through meta-modelling, i.e. by replacing the landslide model by a "costless-to-evaluate" approximation (e.g., a projection pursuit regression model). The methodology combining "basis set expansion - meta-model - Sobol' indices" is then applied to the La Frasse landslide to investigate the dynamic sensitivity analysis of the surface horizontal displacements to the slip surface properties during the pore pressure changes. I show how to extract information on the sensitivity of each main modes of temporal behaviour using a limited number (a few tens) of long running simulations. In particular, I identify the parameters, which trigger the occurrence of a turning point marking a shift between a regime of low values of landslide displacements and one of high values.

Use of Quality Models and Indicators for Evaluating Test Quality in an ESP Course

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IEVA RUDZINSKA

2013-12-01

Full Text Available Qualitative methods of assessment play a decisive role in education in general and in language learning in particular. The necessity to perform a qualitative assessment comes from both increased student competition in higher education institutions (HEIs, and hence higher demands for fair assessment, and a growing public awareness on higher education issues, and therefore the need to account for a wider circle of stakeholders, including society as a whole. The aim of the present paper is to study the regulations and laws pertaining to the issue of assessment in Latvian HEIs, as well as to carry out literature sources analysis about assessment in language testing, seeking to select criteria characterizing the quality of English for Specific Purposes (ESP tests and to apply the model of evaluating the quality of a language test on an example of a test in sport English, developed in a Latvian higher education institution. An analysis of the regulations and laws about assessment in higher education and literature sources about tests in language courses has enabled the development of a test quality model, consisting of seven intrinsic quality criteria: clarity, adequacy, deep approach, attractiveness, originality/similarity, orientation towards student learning result/process, test scoring objectivity/subjectivity. Quality criteria comprise eleven indicators. The reliability of the given model is evaluated by means of the whole model, its criteria and indicator Cronbach’s alphas and point-biserial (item-total correlations or discrimination indexes DI. The test was taken by 63 participants, all of them 2nd year full time students attending a Latvian higher education institution. A statistical data analysis was performed with SPSS 17.0. The results show that, although test adequacy and clarity is sufficiently high, attractiveness and deep approach should be improved. Also the reliability of one version of the test is higher than that of the other one

Bioclimatic indices based on the menex model example on Banja Luka

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Pecelj Milica

2013-01-01

Full Text Available It has long been known that weather and climate have influence on human health and well-being. The human organism is in constant interaction with the environmental conditions. To access the atmospheric impact on humans, different methods in human bioclimatology are created. Most of them are based on human heat balance. In this paper it has been tried to present several bioclimatic indices based on the human heat balance according to the bioclimatic model menex (man-environment exchange. The aim of this paper is to present bioclimatic conditions in Banja Luka vicinage (Bosnia and Herzegovina and to explore climate-recreation relationship. In the near vicinity of Banja Luka there are three spa centers that are favorable for recreation. For this analysis average available daily weather data for two extreme months (January and July, 1990 were used as well as the average monthly weather values for the period 1961-1990. The data were taken from Banja Luka weather station. As a result, several thermophisiological bioclimatic indices have been obtained. These are heat load in man, physiological strain, subjective temperature, subjective physiological temperature.

Testing for Nonuniform Differential Item Functioning with Multiple Indicator Multiple Cause Models

Science.gov (United States)

Woods, Carol M.; Grimm, Kevin J.

2011-01-01

In extant literature, multiple indicator multiple cause (MIMIC) models have been presented for identifying items that display uniform differential item functioning (DIF) only, not nonuniform DIF. This article addresses, for apparently the first time, the use of MIMIC models for testing both uniform and nonuniform DIF with categorical indicators. A…

Dynamic energy conservation model REDUCE. Extension with experience curves, energy efficiency indicators and user's guide

International Nuclear Information System (INIS)

Uyterlinde, M.A.; Rijkers, F.A.M.

1999-12-01

The main objective of the energy conservation model REDUCE (Reduction of Energy Demand by Utilization of Conservation of Energy) is the evaluation of the effectiveness of economical, financial, institutional, and regulatory measures for improving the rational use of energy in end-use sectors. This report presents the results of additional model development activities, partly based on the first experiences in a previous project. Energy efficiency indicators have been added as an extra tool for output analysis in REDUCE. The methodology is described and some examples are given. The model has been extended with a method for modelling the effects of technical development on production costs, by means of an experience curve. Finally, the report provides a 'users guide', by describing in more detail the input data specification as well as all menus and buttons. 19 refs

Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation

Science.gov (United States)

Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten

2015-04-01

Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.

PERFORMANCE INDICATORS: A COMPARATIVE ANALYSIS BETWEEN PUBLIC AND PRIVATE COLLEGES IN BRAZIL

Directory of Open Access Journals (Sweden)

Átila de Melo Lira

2015-06-01

Full Text Available A comparative analysis between the use of performance indicators to public and private organizations have always been required to examine the scenario related to both. This study seeks to analyze the use of Balanced Scorecard (BSC to identify and understand the main differences and similarities in public and private higher education institutions (HEIs in Brazil in relation to the use of other organizations performance indicators. A quantitative and exploratory approach was adopted using institutional documents analysis. Data was searched on the websites of Brazilian higher education public and private organizations in order to accomplish this analysis comparative. The results showed that even reviewing few public institutions the use of performance indicators appears to be more efficient than those applied to the private ones. Private universities should observe and improve their processes and performance indicators based on those used in Brazilian public universities. This initial research still opens a horizon so that other studies be developed within this thought stream.

Mathematical supply-chain modelling: Product analysis of cost and time

International Nuclear Information System (INIS)

Easters, D J

2014-01-01

Establishing a mathematical supply-chain model is a proposition that has received attention due to its inherent benefits of evolving global supply-chain efficiencies. This paper discusses the prevailing relationships found within apparel supply-chain environments, and contemplates the complex issues indicated for constituting a mathematical model. Principal results identified within the data suggest, that the multifarious nature of global supply-chain activities require a degree of simplification in order to fully dilate the necessary factors which affect, each sub-section of the chain. Subsequently, the research findings allowed the division of supply-chain components into sub-sections, which amassed a coherent method of product development activity. Concurrently, the supply-chain model was found to allow systematic mathematical formulae analysis, of cost and time, within the multiple contexts of each subsection encountered. The paper indicates the supply-chain model structure, the mathematics, and considers how product analysis of cost and time can improve the comprehension of product lifecycle management

Mathematical supply-chain modelling: Product analysis of cost and time

Science.gov (United States)

Easters, D. J.

2014-03-01

Establishing a mathematical supply-chain model is a proposition that has received attention due to its inherent benefits of evolving global supply-chain efficiencies. This paper discusses the prevailing relationships found within apparel supply-chain environments, and contemplates the complex issues indicated for constituting a mathematical model. Principal results identified within the data suggest, that the multifarious nature of global supply-chain activities require a degree of simplification in order to fully dilate the necessary factors which affect, each sub-section of the chain. Subsequently, the research findings allowed the division of supply-chain components into sub-sections, which amassed a coherent method of product development activity. Concurrently, the supply-chain model was found to allow systematic mathematical formulae analysis, of cost and time, within the multiple contexts of each subsection encountered. The paper indicates the supply-chain model structure, the mathematics, and considers how product analysis of cost and time can improve the comprehension of product lifecycle management.

Using species abundance distribution models and diversity indices for biogeographical analyses

Science.gov (United States)

Fattorini, Simone; Rigal, François; Cardoso, Pedro; Borges, Paulo A. V.

2016-01-01

We examine whether Species Abundance Distribution models (SADs) and diversity indices can describe how species colonization status influences species community assembly on oceanic islands. Our hypothesis is that, because of the lack of source-sink dynamics at the archipelago scale, Single Island Endemics (SIEs), i.e. endemic species restricted to only one island, should be represented by few rare species and consequently have abundance patterns that differ from those of more widespread species. To test our hypothesis, we used arthropod data from the Azorean archipelago (North Atlantic). We divided the species into three colonization categories: SIEs, archipelagic endemics (AZEs, present in at least two islands) and native non-endemics (NATs). For each category, we modelled rank-abundance plots using both the geometric series and the Gambin model, a measure of distributional amplitude. We also calculated Shannon entropy and Buzas and Gibson's evenness. We show that the slopes of the regression lines modelling SADs were significantly higher for SIEs, which indicates a relative predominance of a few highly abundant species and a lack of rare species, which also depresses diversity indices. This may be a consequence of two factors: (i) some forest specialist SIEs may be at advantage over other, less adapted species; (ii) the entire populations of SIEs are by definition concentrated on a single island, without possibility for inter-island source-sink dynamics; hence all populations must have a minimum number of individuals to survive natural, often unpredictable, fluctuations. These findings are supported by higher values of the α parameter of the Gambin mode for SIEs. In contrast, AZEs and NATs had lower regression slopes, lower α but higher diversity indices, resulting from their widespread distribution over several islands. We conclude that these differences in the SAD models and diversity indices demonstrate that the study of these metrics is useful for

The impact of removing financial incentives from clinical quality indicators: longitudinal analysis of four Kaiser Permanente indicators.

NARCIS (Netherlands)

Lester, H.; Schmittdiel, J.; Selby, J.; Fireman, B.; Campbell, S.M.; Lee, J.; Whippy, A.; Madvig, P.

2010-01-01

OBJECTIVE: To evaluate the effect of financial incentives on four clinical quality indicators common to pay for performance plans in the United Kingdom and at Kaiser Permanente in California. DESIGN: Longitudinal analysis. SETTING: 35 medical facilities of Kaiser Permanente Northern California,

An investigation into the inputs controlling predictions from a diffuse phosphorus loss model for the UK; the Phosphorus Indicators Tool (PIT).

Science.gov (United States)

Liu, Shuming; Brazier, Richard; Heathwaite, Louise

2005-05-15

A simple catchment scale model simulating diffuse phosphorus (P) loss from agricultural land to water, the Phosphorus Indicators Tool (PIT), has been developed. Previous research has shown that this model worked well in simulating the average annual P lost from two catchments: Windermere and Windrush, but it was not known which drivers in the model had the greatest control on predicted P delivery to water from agricultural land. In order to simulate the P export from each catchment source via each hydrological pathway specified individually, 108 coefficients are used in the model code. A univariate sensitivity analysis was conducted to evaluate which coefficient exerted the greatest control on the model output. Results from the univariate analysis suggest that the model is sensitive to a number of coefficients, but importantly, not all of the coefficients that were varied in the sensitivity analysis, altered the model output. The PIT model has been calibrated by optimizing results from the univariate analysis against observed data in the Windermere catchment. The simulated results from model calibration fit the observed data well, at the 95% level. This paper describes the methodology developed for the univariate analysis and evaluates the model calibration procedure against observed data from the Windermere catchment.

A global sensitivity analysis approach for morphogenesis models

KAUST Repository

Boas, Sonja E. M.

2015-11-21

Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

A global sensitivity analysis approach for morphogenesis models.

Science.gov (United States)

Boas, Sonja E M; Navarro Jimenez, Maria I; Merks, Roeland M H; Blom, Joke G

2015-11-21

Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such 'black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all 'black-box' models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

Using a phosphorus loss model to evaluate and improve phosphorus indices.

Science.gov (United States)

Bolster, Carl H; Vadas, Peter A; Sharpley, Andrew N; Lory, John A

2012-01-01

In most states, the phosphorus (P) index (PI) is the adopted strategy for assessing a field's vulnerability to P loss; however, many state PIs have not been rigorously evaluated against measured P loss data to determine how well the PI assigns P loss risk-a major reason being the lack of field data available for such an analysis. Given the lack of P loss data available for PI evaluation, our goal was to demonstrate how a P loss model can be used to evaluate and revise a PI using the Pennsylvania (PA) PI as an example. Our first objective was to compare two different formulations-multiplicative and component-for calculating a PI. Our second objective was to evaluate whether output from a P loss model can be used to improve PI weighting by calculating weights for modified versions of the PA PI from model-generated P loss data. Our results indicate that several potential limitations exist with the original multiplicative index formulation and that a component formulation is more consistent with how P loss is calculated with P loss models and generally provides more accurate estimates of P loss. Moreover, using the PI weights calculated from the model-generated data noticeably improved the correlation between PI values and a large and diverse measured P loss data set. The approach we use here can be used with any P loss model and PI and thus can serve as a guide to assist states in evaluating and modifying their PI. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Key performance indicators in hospital based on balanced scorecard model

Directory of Open Access Journals (Sweden)

Hamed Rahimi

2017-01-01

Full Text Available Introduction: Performance measurement is receiving increasing verification all over the world. Nowadays in a lot of organizations, irrespective of their type or size, performance evaluation is the main concern and a key issue for top administrators. The purpose of this study is to organize suitable key performance indicators (KPIs for hospitals’ performance evaluation based on the balanced scorecard (BSC. Method: This is a mixed method study. In order to identify the hospital’s performance indicators (HPI, first related literature was reviewed and then the experts’ panel and Delphi method were used. In this study, two rounds were needed for the desired level of consensus. The experts rated the importance of the indicators, on a five-point Likert scale. In the consensus calculation, the consensus percentage was calculated by classifying the values 1-3 as not important (0 and 4-5 to (1 as important. Simple additive weighting technique was used to rank the indicators and select hospital’s KPIs. The data were analyzed by Excel 2010 software. Results: About 218 indicators were obtained from a review of selected literature. Through internal expert panel, 77 indicators were selected. Finally, 22 were selected for KPIs of hospitals. Ten indicators were selected in internal process perspective and 5, 4, and 3 indicators in finance, learning and growth, and customer, respectively. Conclusion: This model can be a useful tool for evaluating and comparing the performance of hospitals. However, this model is flexible and can be adjusted according to differences in the target hospitals. This study can be beneficial for hospital administrators and it can help them to change their perspective about performance evaluation.

Univariate and Multivariate Specification Search Indices in Covariance Structure Modeling.

Science.gov (United States)

Hutchinson, Susan R.

1993-01-01

Simulated population data were used to compare relative performances of the modification index and C. Chou and P. M. Bentler's Lagrange multiplier test (a multivariate generalization of a modification index) for four levels of model misspecification. Both indices failed to recover the true model except at the lowest level of misspecification. (SLD)

Large-scale determinants of diversity across Spanish forest habitats: accounting for model uncertainty in compositional and structural indicators

Energy Technology Data Exchange (ETDEWEB)

Martin-Quller, E.; Torras, O.; Alberdi, I.; Solana, J.; Saura, S.

2011-07-01

An integral understanding of forest biodiversity requires the exploration of the many aspects it comprises and of the numerous potential determinants of their distribution. The landscape ecological approach provides a necessary complement to conventional local studies that focus on individual plots or forest ownerships. However, most previous landscape studies used equally-sized cells as units of analysis to identify the factors affecting forest biodiversity distribution. Stratification of the analysis by habitats with a relatively homogeneous forest composition might be more adequate to capture the underlying patterns associated to the formation and development of a particular ensemble of interacting forest species. Here we used a landscape perspective in order to improve our understanding on the influence of large-scale explanatory factors on forest biodiversity indicators in Spanish habitats, covering a wide latitudinal and attitudinal range. We considered six forest biodiversity indicators estimated from more than 30,000 field plots in the Spanish national forest inventory, distributed in 213 forest habitats over 16 Spanish provinces. We explored biodiversity response to various environmental (climate and topography) and landscape configuration (fragmentation and shape complexity) variables through multiple linear regression models (built and assessed through the Akaike Information Criterion). In particular, we took into account the inherent model uncertainty when dealing with a complex and large set of variables, and considered different plausible models and their probability of being the best candidate for the observed data. Our results showed that compositional indicators (species richness and diversity) were mostly explained by environmental factors. Models for structural indicators (standing deadwood and stand complexity) had the worst fits and selection uncertainties, but did show significant associations with some configuration metrics. In general

New Indicated Mean Effective Pressure (IMEP) model for predicting crankshaft movement

International Nuclear Information System (INIS)

Omran, Rabih; Younes, Rafic; Champoussin, Jean-Claude; Outbib, Rachid

2011-01-01

Highlights: → IMEP is essential to estimate the indicated torque in internal combustion engine. → We proposed model which describes the IMEP-Low pressure and the IMEP-High pressure. → We studied the evolution of the IMEP with respect to the engine's variables. → We deduced the variables of influence that can be used to develop the models. → The IMEP model is compared to transient experimental New European Driving Cycle. - Abstract: Indicated Mean Effective Pressure models (IMEP) are essential to estimate the indicated torque in internal combustion engine; they also provide important information about the mechanical efficiency of the engine thermodynamic cycle which describes the conversion of the fuel combustion energy into mechanical work. In the past, many researches were made to improve the IMEP prediction and measurement techniques at different engine operating conditions. In this paper, we proposed a detailed IMEP model which separately describes the IMEP-Low pressure and the IMEP-High pressure of a modern diesel engine; the IMEP is the direct subtraction result between these two variables. We firstly studied the evolution of the IMEP HP and IMEP LP with respect to the engine's variables and then we deduced the variables of influence and the form of the equations that can be used to develop the models. Finally, the models' coefficients were determined based on experimental data collected on a steady state test bench and using the least square regression method. In addition, the IMEP HP model results were compared to transient experimental data collected on a chassis dynamometer test bench; the model results are in excellent agreement with the experimental data.

A critical cluster analysis of 44 indicators of author-level performance

DEFF Research Database (Denmark)

Wildgaard, Lorna Elizabeth

2016-01-01

-four indicators of individual researcher performance were computed using the data. The clustering solution was supported by continued reference to the researcher’s curriculum vitae, an effect analysis and a risk analysis. Disciplinary appropriate indicators were identified and used to divide the researchers......This paper explores a 7-stage cluster methodology as a process to identify appropriate indicators for evaluation of individual researchers at a disciplinary and seniority level. Publication and citation data for 741 researchers from 4 disciplines was collected in Web of Science. Forty...... of statistics in research evaluation. The strength of the 7-stage cluster methodology is that it makes clear that in the evaluation of individual researchers, statistics cannot stand alone. The methodology is reliant on contextual information to verify the bibliometric values and cluster solution...

Three Cs in Measurement Models: Causal Indicators, Composite Indicators, and Covariates

OpenAIRE

Bollen, Kenneth A.; Bauldry, Shawn

2011-01-01

In the last two decades attention to causal (and formative) indicators has grown. Accompanying this growth has been the belief that we can classify indicators into two categories, effect (reflective) indicators and causal (formative) indicators. This paper argues that the dichotomous view is too simple. Instead, there are effect indicators and three types of variables on which a latent variable depends: causal indicators, composite (formative) indicators, and covariates (the “three Cs”). Caus...

The ATLAS Analysis Model

CERN Multimedia

Amir Farbin

The ATLAS Analysis Model is a continually developing vision of how to reconcile physics analysis requirements with the ATLAS offline software and computing model constraints. In the past year this vision has influenced the evolution of the ATLAS Event Data Model, the Athena software framework, and physics analysis tools. These developments, along with the October Analysis Model Workshop and the planning for CSC analyses have led to a rapid refinement of the ATLAS Analysis Model in the past few months. This article introduces some of the relevant issues and presents the current vision of the future ATLAS Analysis Model. Event Data Model The ATLAS Event Data Model (EDM) consists of several levels of details, each targeted for a specific set of tasks. For example the Event Summary Data (ESD) stores calorimeter cells and tracking system hits thereby permitting many calibration and alignment tasks, but will be only accessible at particular computing sites with potentially large latency. In contrast, the Analysis...

Longitudinal Trend Analysis of Performance Indicators for South Carolina's Technical Colleges

Science.gov (United States)

Hossain, Mohammad Nurul

2010-01-01

This study included an analysis of the trend of performance indicators for the technical college sector of higher education in South Carolina. In response to demands for accountability and transparency in higher education, the state of South Carolina developed sector specific performance indicators to measure various educational outcomes for each…

Interpretive Structural Model of Key Performance Indicators for Sustainable Maintenance Evaluatian in Rubber Industry

Science.gov (United States)

Amrina, E.; Yulianto, A.

2018-03-01

Sustainable maintenance is a new challenge for manufacturing companies to realize sustainable development. In this paper, an interpretive structural model is developed to evaluate sustainable maintenance in the rubber industry. The initial key performance indicators (KPIs) is identified and derived from literature and then validated by academic and industry experts. As a result, three factors of economic, social, and environmental dividing into a total of thirteen indicators are proposed as the KPIs for sustainable maintenance evaluation in rubber industry. Interpretive structural modeling (ISM) methodology is applied to develop a network structure model of the KPIs consisting of three levels. The results show the economic factor is regarded as the basic factor, the social factor as the intermediate factor, while the environmental factor indicated to be the leading factor. Two indicators of social factor i.e. labor relationship, and training and education have both high driver and dependence power, thus categorized as the unstable indicators which need further attention. All the indicators of environmental factor and one indicator of social factor are indicated as the most influencing indicator. The interpretive structural model hoped can aid the rubber companies in evaluating sustainable maintenance performance.

Labor satisfaction as an indicator of public administration efficiency (sociological analysis

Directory of Open Access Journals (Sweden)

Galina Valentinovna Leonidova

2014-07-01

Full Text Available Labor satisfaction is an indicator of social wellbeing of the working population. The study of subjective perceptions of labor is an important indicator of public administration efficiency. The article contains the analysis of the population’s satisfaction with labor, particularly, with one of its structural components – labor conditions. It reveals the high correlation of these indicators with the satisfaction with everyday life and labor productivity. It determines the degree of employees’ satisfaction with working conditions in such areas as health and psychological atmosphere at the workplace, equipment capability and security. The study discloses employees’ estimates in socio-demographic and territorialdimensional aspects. The research demonstrates the interrelation between satisfaction with working environment and implementation of labor potential. The analysis indicates the importance of regular sociological research into the issues of satisfaction with various aspects of labor activity. The article indicates that for the country’s development it is necessary to take into account the labor satisfaction factor (in the narrow sense – working conditions while developing strategies and approaches for social-economic policy and defining the standards of social responsibility, primarily, of the state and employers

Modeling change in learning strategies throughout higher education: a multi-indicator latent growth perspective.

Science.gov (United States)

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2013-01-01

The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.

Modeling change in learning strategies throughout higher education: a multi-indicator latent growth perspective.

Directory of Open Access Journals (Sweden)

Liesje Coertjens

Full Text Available The change in learning strategies during higher education is an important topic of research in the Student Approaches to Learning field. Although the studies on this topic are increasingly longitudinal, analyses have continued to rely primarily on traditional statistical methods. The present research is innovative in the way it uses a multi-indicator latent growth analysis in order to more accurately estimate the general and differential development in learning strategy scales. Moreover, the predictive strength of the latent growth models are estimated. The sample consists of one cohort of Flemish University College students, 245 of whom participated in the three measurement waves by filling out the processing and regulation strategies scales of the Inventory of Learning Styles--Short Versions. Independent-samples t-tests revealed that the longitudinal group is a non-random subset of students starting University College. For each scale, a multi-indicator latent growth model is estimated using Mplus 6.1. Results suggest that, on average, during higher education, students persisting in their studies in a non-delayed manner seem to shift towards high-quality learning and away from undirected and surface-oriented learning. Moreover, students from the longitudinal group are found to vary in their initial levels, while, unexpectedly, not in their change over time. Although the growth models fit the data well, significant residual variances in the latent factors remain.

Analysis of Pitch Gear Deterioration using Indicators

DEFF Research Database (Denmark)

Nielsen, Jannie Jessen; Sørensen, John Dalsgaard

2011-01-01

This work concerns a case study in the context of risk-based operation and maintenance of offshore wind turbines. For wind turbines with electrical pitch systems, deterioration can generally be observed at the pitch gear teeth; especially at the point where the blades are located during normal...... of the damage, and can be used for Bayesian updating of a damage model used for risk-based decision making. For this decision problem, the risk of failure should be compared to the cost of preventive maintenance. The hypothesis that the maximum pitch motor torque is an indicator of the damage size is supported...... changes in the temperature are the primary cause of the decrease. A model is established to remove the effect of the explained variation, and it is investigated if deterioration can be detected as changes in the peak torque. A small increase could be detected after the maintenance, but before...

Relative Release-to-Birth Indicators for Investigating TRISO Fuel Fission Gas Release Models

International Nuclear Information System (INIS)

Harp, Jason M.; Hawari, Ayman I.

2008-01-01

TRISO microsphere fuel is the fundamental fuel unit for Very High Temperature Reactors (VHTR). A single TRISO particle consists of an inner kernel of uranium dioxide or uranium oxycarbide surrounded by layers of pyrolytic carbon and silicon carbide. If the silicon carbide layer fails, fission products, especially the noble fission gases Kr and Xe, will begin to escape the failed particle. The release of fission gas is usually quantified by measuring the ratio of the released activity (R) to the original birth activity (B), which is designated as the R/B ratio. In this work, relative Release-to-Birth indicators (I) are proposed as a technique for interpreting the results of TRISO irradiation experiments. By implementing a relative metric, it is possible to reduce the sensitivity of the indicators to instrumental uncertainties and variations in experimental conditions. As an example, relative R/B indicators are applied to the interpretation of representative data from the Advanced Gas Reactor-1 TRISO fuel experiment that is currently taking place at the Advanced Test Reactor of Idaho National Laboratory. It is shown that the comparison of measured to predicted relative R/B indicators (I) gives insight into the physics of release and helps validate release models. Different trends displayed by the indicators are related to the mechanisms of fission gas release such as diffusion and recoil. The current analysis shows evidence for separate diffusion coefficients for Kr and Xe and supports the need to account for recoil release. (authors)

Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models

International Nuclear Information System (INIS)

Lamboni, Matieyendou; Monod, Herve; Makowski, David

2011-01-01

Many dynamic models are used for risk assessment and decision support in ecology and crop science. Such models generate time-dependent model predictions, with time either discretised or continuous. Their global sensitivity analysis is usually applied separately on each time output, but Campbell et al. (2006 ) advocated global sensitivity analyses on the expansion of the dynamics in a well-chosen functional basis. This paper focuses on the particular case when principal components analysis is combined with analysis of variance. In addition to the indices associated with the principal components, generalised sensitivity indices are proposed to synthesize the influence of each parameter on the whole time series output. Index definitions are given when the uncertainty on the input factors is either discrete or continuous and when the dynamic model is either discrete or functional. A general estimation algorithm is proposed, based on classical methods of global sensitivity analysis. The method is applied to a dynamic wheat crop model with 13 uncertain parameters. Three methods of global sensitivity analysis are compared: the Sobol'-Saltelli method, the extended FAST method, and the fractional factorial design of resolution 6.

Multivariate sensitivity analysis to measure global contribution of input factors in dynamic models

Energy Technology Data Exchange (ETDEWEB)

Lamboni, Matieyendou [INRA, Unite MIA (UR341), F78352 Jouy en Josas Cedex (France); Monod, Herve, E-mail: herve.monod@jouy.inra.f [INRA, Unite MIA (UR341), F78352 Jouy en Josas Cedex (France); Makowski, David [INRA, UMR Agronomie INRA/AgroParisTech (UMR 211), BP 01, F78850 Thiverval-Grignon (France)

2011-04-15

Many dynamic models are used for risk assessment and decision support in ecology and crop science. Such models generate time-dependent model predictions, with time either discretised or continuous. Their global sensitivity analysis is usually applied separately on each time output, but Campbell et al. (2006) advocated global sensitivity analyses on the expansion of the dynamics in a well-chosen functional basis. This paper focuses on the particular case when principal components analysis is combined with analysis of variance. In addition to the indices associated with the principal components, generalised sensitivity indices are proposed to synthesize the influence of each parameter on the whole time series output. Index definitions are given when the uncertainty on the input factors is either discrete or continuous and when the dynamic model is either discrete or functional. A general estimation algorithm is proposed, based on classical methods of global sensitivity analysis. The method is applied to a dynamic wheat crop model with 13 uncertain parameters. Three methods of global sensitivity analysis are compared: the Sobol'-Saltelli method, the extended FAST method, and the fractional factorial design of resolution 6.

Bivariate Drought Analysis Using Streamflow Reconstruction with Tree Ring Indices in the Sacramento Basin, California, USA

Directory of Open Access Journals (Sweden)

Jaewon Kwak

2016-03-01

Full Text Available Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return period plot for the Sacramento River basin. Results showed strong correlation among drought characteristics, and the drought with a 20-year return period (17.2 million acre-feet (MAF per year in the Sacramento River basin could be considered a critical level of drought for water shortages.

Energy-Water Modeling and Analysis | Energy Analysis | NREL

Science.gov (United States)

Generation (ReEDS Model Analysis) U.S. Energy Sector Vulnerabilities to Climate Change and Extreme Weather Modeling and Analysis Energy-Water Modeling and Analysis NREL's energy-water modeling and analysis vulnerabilities from various factors, including water. Example Projects Renewable Electricity Futures Study

Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness.

Science.gov (United States)

Tang, Niansheng; Chow, Sy-Miin; Ibrahim, Joseph G; Zhu, Hongtu

2017-12-01

Many psychological concepts are unobserved and usually represented as latent factors apprehended through multiple observed indicators. When multiple-subject multivariate time series data are available, dynamic factor analysis models with random effects offer one way of modeling patterns of within- and between-person variations by combining factor analysis and time series analysis at the factor level. Using the Dirichlet process (DP) as a nonparametric prior for individual-specific time series parameters further allows the distributional forms of these parameters to deviate from commonly imposed (e.g., normal or other symmetric) functional forms, arising as a result of these parameters' restricted ranges. Given the complexity of such models, a thorough sensitivity analysis is critical but computationally prohibitive. We propose a Bayesian local influence method that allows for simultaneous sensitivity analysis of multiple modeling components within a single fitting of the model of choice. Five illustrations and an empirical example are provided to demonstrate the utility of the proposed approach in facilitating the detection of outlying cases and common sources of misspecification in dynamic factor analysis models, as well as identification of modeling components that are sensitive to changes in the DP prior specification.

Moderation analysis using a two-level regression model.

Science.gov (United States)

Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott

2014-10-01

Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.

Analysis of the Main Indicators of the Bucharest Stock Exchange

OpenAIRE

Madalina Gabriela ANGHEL

2014-01-01

The goal of this article is to achieve an analysis of the evolution and significance of the main indicators of the Bucharest Stock Exchange (stock exchange capitalization, BET index, value of the concluded transactions) over the last fifteen years. One of the significant elements in analyzing the performances of the capital market consist of the stock exchange capitalization which an essential indicator for characterizing of this domain of activity, mainly if considering the fact that it is u...

The approach of Bayesian model indicates media awareness of medical errors

Science.gov (United States)

Ravichandran, K.; Arulchelvan, S.

2016-06-01

This research study brings out the factors behind the increase in medical malpractices in the Indian subcontinent in the present day environment and impacts of television media awareness towards it. Increased media reporting of medical malpractices and errors lead to hospitals taking corrective action and improve the quality of medical services that they provide. The model of Cultivation Theory can be used to measure the influence of media in creating awareness of medical errors. The patient's perceptions of various errors rendered by the medical industry from different parts of India were taken up for this study. Bayesian method was used for data analysis and it gives absolute values to indicate satisfaction of the recommended values. To find out the impact of maintaining medical records of a family online by the family doctor in reducing medical malpractices which creates the importance of service quality in medical industry through the ICT.

Development of a Predictive Corrosion Model Using Locality-Specific Corrosion Indices

Science.gov (United States)

2017-09-12

components, and method) were compiled into an executable program that uses mathematical models of materials degradation, and statistical calcula- tions...The primary metric used to validate the model was statistical analysis of its application to specific geospatial locations, comparing the severity...6 3.2.1 Statistical data analysis methods

Analysis of architect’s performance indicators in project delivery process

Science.gov (United States)

Marisa, A.

2018-03-01

Architect as a professional in the construction industry should possess a good performance in project delivery process. As a design professional, architect has an important role to ensure that the process is well-conducted by delivering a high-quality product for the clients. Thus, analyzing architect’s performance indicators is crucial in the project delivery process. This study aims to analyze the relative importance of architect performance indicators in project delivery process among registered architects in North Sumatera, Indonesia. A total of five indicators that measure architect performance in project delivery process were identified and 110 completed questionnaires were obtained and used for data analysis. A relative importance index is used to rank the relative importance of architect performance indicators. Results indicate that focus on the clients is the most important indicator of architect performance in project delivery process. This study demonstrates project communication as one of crucial indicators perceived by the architects for measuring their performance, and fills a knowledge gap on the importance of identifying the most important indicator for measuring architect performance from their own perspectives which previous studies have overlooked to improve performance assessment in project delivery process.

Advanced Model of Squirrel Cage Induction Machine for Broken Rotor Bars Fault Using Multi Indicators

Directory of Open Access Journals (Sweden)

Ilias Ouachtouk

2016-01-01

Full Text Available Squirrel cage induction machine are the most commonly used electrical drives, but like any other machine, they are vulnerable to faults. Among the widespread failures of the induction machine there are rotor faults. This paper focuses on the detection of broken rotor bars fault using multi-indicator. However, diagnostics of asynchronous machine rotor faults can be accomplished by analysing the anomalies of machine local variable such as torque, magnetic flux, stator current and neutral voltage signature analysis. The aim of this research is to summarize the existing models and to develop new models of squirrel cage induction motors with consideration of the neutral voltage and to study the effect of broken rotor bars on the different electrical quantities such as the park currents, torque, stator currents and neutral voltage. The performance of the model was assessed by comparing the simulation and experimental results. The obtained results show the effectiveness of the model, and allow detection and diagnosis of these defects.

Prioritizing public- private partnership models for public hospitals of iran based on performance indicators.

Science.gov (United States)

Gholamzadeh Nikjoo, Raana; Jabbari Beyrami, Hossein; Jannati, Ali; Asghari Jaafarabadi, Mohammad

2012-01-01

The present study was conducted to scrutinize Public- Private Partnership (PPP) models in public hospitals of different countries based on performance indicators in order to se-lect appropriated models for Iran hospitals. In this mixed (quantitative-qualitative) study, systematic review and expert panel has been done to identify varied models of PPP as well as performance indicators. In the second step we prioritized performance indicator and PPP models based on selected performance indicators by Analytical Hierarchy process (AHP) technique. The data were analyzed by Excel 2007 and Expert Choice11 software's. In quality - effectiveness area, indicators like the rate of hospital infections (100%), hospital accidents prevalence rate (73%), pure rate of hospital mortality (63%), patient satisfaction percentage (53%), in accessibility equity area indicators such as average inpatient waiting time (100%) and average outpatient waiting time (74%), and in financial - efficiency area, indicators including average length of stay (100%), bed occupation ratio (99%), specific income to total cost ratio (97%) have been chosen to be the most key performance indicators. In the pri¬oritization of the PPP models clinical outsourcing, management, privatization, BOO (build, own, operate) and non-clinical outsourcing models, achieved high priority for various performance in¬dicator areas. This study had been provided the most common PPP options in the field of public hospitals and had gathered suitable evidences from experts for choosing appropriate PPP option for public hospitals. Effect of private sector presence in public hospital performance, based on which PPP options undertaken, will be different.

National socioeconomic indicators are associated with outcomes after aneurysmal subarachnoid hemorrhage: a hierarchical mixed-effects analysis.

Science.gov (United States)

Guha, Daipayan; Ibrahim, George M; Kertzer, Joshua D; Macdonald, R Loch

2014-11-01

Although heterogeneity exists in patient outcomes following subarachnoid hemorrhage (SAH) across different centers and countries, it is unclear which factors contribute to such disparities. In this study, the authors performed a post hoc analysis of a large international database to evaluate the association between a country's socioeconomic indicators and patient outcome following aneurysmal SAH. An analysis was performed on a database of 3552 patients enrolled in studies of tirilazad mesylate for aneurysmal SAH from 1991 to 1997, which included 162 neurosurgical centers in North and Central America, Australia, Europe, and Africa. Two primary outcomes were assessed at 3 months after SAH: mortality and Glasgow Outcome Scale (GOS) score. The association between these outcomes, nation-level socioeconomic indicators (percapita gross domestic product [GDP], population-to-neurosurgeon ratio, and health care funding model), and patientlevel covariates were assessed using a hierarchical mixed-effects logistic regression analysis. Multiple previously identified patient-level covariates were significantly associated with increased mortality and worse neurological outcome, including age, intraventricular hemorrhage, and initial neurological grade. Among national-level covariates, higher per-capita GDP (p funding model was not a significant predictor of either primary outcome. Higher per-capita gross GDP and population-to-neurosurgeon ratio were associated with improved outcome after aneurysmal SAH. The former result may speak to the availability of resources, while the latter may be a reflection of better outcomes with centralized care. Although patient clinical and radiographic phenotypes remain the primary predictors of outcome, this study shows that national socioeconomic disparities also explain heterogeneity in outcomes following SAH.

Identification of novel indicators of cyclosporine A nephrotoxicity in a CD-1 mouse model

International Nuclear Information System (INIS)

O'Connell, Sein; Slattery, Craig; Ryan, Michael P.; McMorrow, Tara

2011-01-01

The calcineurin inhibitor cyclosporine A (CsA) is a widely used immunosuppressive agent. However, nephrotoxicity is a serious side effect observed in patients which limits clinical use of CsA. CsA nephrotoxicity is associated with tubulointerstitial injury progressing to nephropathy. This is typically diagnosed by invasive renal biopsy and is often only detected when the disease process is well advanced. Therefore identification of novel, early indicators of CsA nephrotoxicity could be clinically advantageous. This study aimed to establish a murine model of CsA nephrotoxicity and to identify urinary proteins that may indicate the onset of CsA-induced nephropathy using 2-D gel electrophoresis. CsA nephrotoxicity was induced in CD-1 mice by daily CsA administration for 4 weeks. By week 4, elevated serum creatinine and proteinuria were observed after CsA treatment indicating significant renal dysfunction. Decreased cadherin-1, increased α-smooth muscle actin and fibroblast specific protein 1 in kidney tissue indicated disruption of normal tubular architecture. Alterations in podocin and uromodulin were also observed which may indicate damage to other segments of the nephron. Proteomic analysis of urine identified a number of differentially regulated proteins that may be involved in early CsA nephropathy including cadherin 1, superoxide dismutase and vinculin. These findings suggest novel mechanisms of CsA nephrotoxicity and identify novel potential markers of the disease.

Socio-economic vulnerability to natural hazards - proposal for an indicator-based model

Science.gov (United States)

Eidsvig, U.; McLean, A.; Vangelsten, B. V.; Kalsnes, B.; Ciurean, R. L.; Argyroudis, S.; Winter, M.; Corominas, J.; Mavrouli, O. C.; Fotopoulou, S.; Pitilakis, K.; Baills, A.; Malet, J. P.

2012-04-01

Vulnerability assessment, with respect to natural hazards, is a complex process that must consider multiple dimensions of vulnerability, including both physical and social factors. Physical vulnerability refers to conditions of physical assets, and may be modeled by the intensity and magnitude of the hazard, the degree of physical protection provided by the natural and built environment, and the physical robustness of the exposed elements. Social vulnerability refers to the underlying factors leading to the inability of people, organizations, and societies to withstand impacts from the natural hazards. Social vulnerability models can be used in combination with physical vulnerability models to estimate both direct losses, i.e. losses that occur during and immediately after the impact, as well as indirect losses, i.e. long-term effects of the event. Direct impact of a landslide typically includes casualties and damages to buildings and infrastructure while indirect losses may e.g. include business closures or limitations in public services. The direct losses are often assessed using physical vulnerability indicators (e.g. construction material, height of buildings), while indirect losses are mainly assessed using social indicators (e.g. economical resources, demographic conditions). Within the EC-FP7 SafeLand research project, an indicator-based method was proposed to assess relative socio-economic vulnerability to landslides. The indicators represent the underlying factors which influence a community's ability to prepare for, deal with, and recover from the damage associated with landslides. The proposed model includes indicators representing demographic, economic and social characteristics as well as indicators representing the degree of preparedness and recovery capacity. Although the model focuses primarily on the indirect losses, it could easily be extended to include more physical indicators which account for the direct losses. Each indicator is individually

A harmonized calculation model for transforming EU bottom-up energy efficiency indicators into empirical estimates of policy impacts

International Nuclear Information System (INIS)

Horowitz, Marvin J.; Bertoldi, Paolo

2015-01-01

This study is an impact analysis of European Union (EU) energy efficiency policy that employs both top-down energy consumption data and bottom-up energy efficiency statistics or indicators. As such, it may be considered a contribution to the effort called for in the EU's 2006 Energy Services Directive (ESD) to develop a harmonized calculation model. Although this study does not estimate the realized savings from individual policy measures, it does provide estimates of realized energy savings for energy efficiency policy measures in aggregate. Using fixed effects panel models, the annual cumulative savings in 2011 of combined household and manufacturing sector electricity and natural gas usage attributed to EU energy efficiency policies since 2000 is estimated to be 1136 PJ; the savings attributed to energy efficiency policies since 2006 is estimated to be 807 PJ, or the equivalent of 5.6% of 2011 EU energy consumption. As well as its contribution to energy efficiency policy analysis, this study adds to the development of methods that can improve the quality of information provided by standardized energy efficiency and sustainable resource indexes. - Highlights: • Impact analysis of European Union energy efficiency policy. • Harmonization of top-down energy consumption and bottom-up energy efficiency indicators. • Fixed effects models for Member States for household and manufacturing sectors and combined electricity and natural gas usage. • EU energy efficiency policies since 2000 are estimated to have saved 1136 Petajoules. • Energy savings attributed to energy efficiency policies since 2006 are 5.6 percent of 2011 combined electricity and natural gas usage.

Prioritizing Public- Private Partnership Models for Public Hospitals of Iran Based on Performance Indicators

Directory of Open Access Journals (Sweden)

Mohammad Asghari Jaafarabadi

2012-12-01

Full Text Available Background: The present study was conducted to scrutinize Public- Private Partnership (PPP models in public hospitals of different countries based on performance indicators in order to se-lect appropriated models for Iran hospitals.Methods: In this mixed (quantitative-qualitative study, systematic review and expert panel hasbeen done to identify varied models of PPP as well as performance indicators. In the second stepwe prioritized performance indicator and PPP models based on selected performance indicatorsby Analytical Hierarchy process (AHP technique. The data were analyzed by Excel 2007 andExpert Choice11 software’s.Results: In quality – effectiveness area, indicators like the rate of hospital infections(100%, hospital accidents prevalence rate (73%, pure rate of hospital mortality (63%, patientsatisfaction percentage (53%, in accessibility equity area indicators such as average inpatientwaiting time (100% and average outpatient waiting time (74%, and in financial – efficiency area,indicators including average length of stay (100%, bed occupation ratio (99%, specific incometo total cost ratio (97% have been chosen to be the most key performance indicators. In the prioritizationof the PPP models clinical outsourcing, management, privatization, BOO (build, own,operate and non-clinical outsourcing models, achieved high priority for various performance indicatorareas.Conclusion: This study had been provided the most common PPP options in the field of public hospitals and had gathered suitable evidences from experts for choosing appropriate PPP option for public hospitals. Effect of private sector presence in public hospital performance, based on which PPP options undertaken, will be different.

Calculations of Sobol indices for the Gaussian process metamodel

Energy Technology Data Exchange (ETDEWEB)

Marrel, Amandine [CEA, DEN, DTN/SMTM/LMTE, F-13108 Saint Paul lez Durance (France)], E-mail: amandine.marrel@cea.fr; Iooss, Bertrand [CEA, DEN, DER/SESI/LCFR, F-13108 Saint Paul lez Durance (France); Laurent, Beatrice [Institut de Mathematiques, Universite de Toulouse (UMR 5219) (France); Roustant, Olivier [Ecole des Mines de Saint-Etienne (France)

2009-03-15

Global sensitivity analysis of complex numerical models can be performed by calculating variance-based importance measures of the input variables, such as the Sobol indices. However, these techniques, requiring a large number of model evaluations, are often unacceptable for time expensive computer codes. A well-known and widely used decision consists in replacing the computer code by a metamodel, predicting the model responses with a negligible computation time and rending straightforward the estimation of Sobol indices. In this paper, we discuss about the Gaussian process model which gives analytical expressions of Sobol indices. Two approaches are studied to compute the Sobol indices: the first based on the predictor of the Gaussian process model and the second based on the global stochastic process model. Comparisons between the two estimates, made on analytical examples, show the superiority of the second approach in terms of convergence and robustness. Moreover, the second approach allows to integrate the modeling error of the Gaussian process model by directly giving some confidence intervals on the Sobol indices. These techniques are finally applied to a real case of hydrogeological modeling.

Calculations of Sobol indices for the Gaussian process metamodel

International Nuclear Information System (INIS)

Marrel, Amandine; Iooss, Bertrand; Laurent, Beatrice; Roustant, Olivier

2009-01-01

Global sensitivity analysis of complex numerical models can be performed by calculating variance-based importance measures of the input variables, such as the Sobol indices. However, these techniques, requiring a large number of model evaluations, are often unacceptable for time expensive computer codes. A well-known and widely used decision consists in replacing the computer code by a metamodel, predicting the model responses with a negligible computation time and rending straightforward the estimation of Sobol indices. In this paper, we discuss about the Gaussian process model which gives analytical expressions of Sobol indices. Two approaches are studied to compute the Sobol indices: the first based on the predictor of the Gaussian process model and the second based on the global stochastic process model. Comparisons between the two estimates, made on analytical examples, show the superiority of the second approach in terms of convergence and robustness. Moreover, the second approach allows to integrate the modeling error of the Gaussian process model by directly giving some confidence intervals on the Sobol indices. These techniques are finally applied to a real case of hydrogeological modeling

Simulated trends of extreme climate indices for the Carpathian basin using outputs of different regional climate models

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Pongracz, R.; Bartholy, J.; Szabo, P.; Pieczka, I.; Torma, C. S.

2009-04-01

Regional climatological effects of global warming may be recognized not only in shifts of mean temperature and precipitation, but in the frequency or intensity changes of different climate extremes. Several climate extreme indices are analyzed and compared for the Carpathian basin (located in Central/Eastern Europe) following the guidelines suggested by the joint WMO-CCl/CLIVAR Working Group on climate change detection. Our statistical trend analysis includes the evaluation of several extreme temperature and precipitation indices, e.g., the numbers of severe cold days, winter days, frost days, cold days, warm days, summer days, hot days, extremely hot days, cold nights, warm nights, the intra-annual extreme temperature range, the heat wave duration, the growing season length, the number of wet days (using several threshold values defining extremes), the maximum number of consecutive dry days, the highest 1-day precipitation amount, the greatest 5-day rainfall total, the annual fraction due to extreme precipitation events, etc. In order to evaluate the future trends (2071-2100) in the Carpathian basin, daily values of meteorological variables are obtained from the outputs of various regional climate model (RCM) experiments accomplished in the frame of the completed EU-project PRUDENCE (Prediction of Regional scenarios and Uncertainties for Defining EuropeaN Climate change risks and Effects). Horizontal resolution of the applied RCMs is 50 km. Both scenarios A2 and B2 are used to compare past and future trends of the extreme climate indices for the Carpathian basin. Furthermore, fine-resolution climate experiments of two additional RCMs adapted and run at the Department of Meteorology, Eotvos Lorand University are used to extend the trend analysis of climate extremes for the Carpathian basin. (1) Model PRECIS (run at 25 km horizontal resolution) was developed at the UK Met Office, Hadley Centre, and it uses the boundary conditions from the HadCM3 GCM. (2) Model Reg

A comparison of emission calculations using different modeled indicators with 1-year online measurements.

Science.gov (United States)

Lengers, Bernd; Schiefler, Inga; Büscher, Wolfgang

2013-12-01

The overall measurement of farm level greenhouse gas (GHG) emissions in dairy production is not feasible, from either an engineering or administrative point of view. Instead, computational model systems are used to generate emission inventories, demanding a validation by measurement data. This paper tests the GHG calculation of the dairy farm-level optimization model DAIRYDYN, including methane (CH₄) from enteric fermentation and managed manure. The model involves four emission calculation procedures (indicators), differing in the aggregation level of relevant input variables. The corresponding emission factors used by the indicators range from default per cow (activity level) emissions up to emission factors based on feed intake, manure amount, and milk production intensity. For validation of the CH₄ accounting of the model, 1-year CH₄ measurements of an experimental free-stall dairy farm in Germany are compared to model simulation results. An advantage of this interdisciplinary study is given by the correspondence of the model parameterization and simulation horizon with the experimental farm's characteristics and measurement period. The results clarify that modeled emission inventories (2,898, 4,637, 4,247, and 3,600 kg CO₂-eq. cow(-1) year(-1)) lead to more or less good approximations of online measurements (average 3,845 kg CO₂-eq. cow(-1) year(-1) (±275 owing to manure management)) depending on the indicator utilized. The more farm-specific characteristics are used by the GHG indicator; the lower is the bias of the modeled emissions. Results underline that an accurate emission calculation procedure should capture differences in energy intake, owing to milk production intensity as well as manure storage time. Despite the differences between indicator estimates, the deviation of modeled GHGs using detailed indicators in DAIRYDYN from on-farm measurements is relatively low (between -6.4% and 10.5%), compared with findings from the literature.

Analysis of Kerch by Local Indicators of Sustainable Development

Science.gov (United States)

Mazygula, E.; Kharlamova, M.; Kozlova, E.

2017-11-01

This article presents an analysis of the city of Kerch (Crimea Republic, Kerch Peninsula) in accordance with the local sustainable development indicators. The authors carried out the assessment of the existing environmental problems in the city which was necessary for the further development of the environmentally oriented infrastructure under various development scenarios. Due to the natural and economic factors, Kerch can develop both as an industrial and recreational centre of the peninsula. The analysis of the atmospheric air condition, use of water and energy resources and the waste management system was conducted. The presented results showed the presence of major environmental problems in almost all spheres.

Factor Analysis of Drawings: Application to college student models of the greenhouse effect

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Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-09-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance, suggesting that 4 archetype models of the greenhouse effect dominate thinking within this population. Factor scores, indicating the extent to which each student's drawing aligned with representative models, were compared to performance on conceptual understanding and attitudes measures, demographics, and non-cognitive features of drawings. Student drawings were also compared to drawings made by scientists to ascertain the extent to which models reflect more sophisticated and accurate models. Results indicate that student and scientist drawings share some similarities, most notably the presence of some features of the most sophisticated non-scientific model held among the study population. Prior knowledge, prior attitudes, gender, and non-cognitive components are also predictive of an individual student's model. This work presents a new technique for analyzing drawings, with general implications for the use of drawings in investigating student conceptions.

An efficient computational method for global sensitivity analysis and its application to tree growth modelling

International Nuclear Information System (INIS)

Wu, Qiong-Li; Cournède, Paul-Henry; Mathieu, Amélie

2012-01-01

Global sensitivity analysis has a key role to play in the design and parameterisation of functional–structural plant growth models which combine the description of plant structural development (organogenesis and geometry) and functional growth (biomass accumulation and allocation). We are particularly interested in this study in Sobol's method which decomposes the variance of the output of interest into terms due to individual parameters but also to interactions between parameters. Such information is crucial for systems with potentially high levels of non-linearity and interactions between processes, like plant growth. However, the computation of Sobol's indices relies on Monte Carlo sampling and re-sampling, whose costs can be very high, especially when model evaluation is also expensive, as for tree models. In this paper, we thus propose a new method to compute Sobol's indices inspired by Homma–Saltelli, which improves slightly their use of model evaluations, and then derive for this generic type of computational methods an estimator of the error estimation of sensitivity indices with respect to the sampling size. It allows the detailed control of the balance between accuracy and computing time. Numerical tests on a simple non-linear model are convincing and the method is finally applied to a functional–structural model of tree growth, GreenLab, whose particularity is the strong level of interaction between plant functioning and organogenesis. - Highlights: ► We study global sensitivity analysis in the context of functional–structural plant modelling. ► A new estimator based on Homma–Saltelli method is proposed to compute Sobol indices, based on a more balanced re-sampling strategy. ► The estimation accuracy of sensitivity indices for a class of Sobol's estimators can be controlled by error analysis. ► The proposed algorithm is implemented efficiently to compute Sobol indices for a complex tree growth model.

Odor composition analysis and odor indicator selection during sewage sludge composting

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Zhu, Yan-li; Zheng, Guo-di; Gao, Ding; Chen, Tong-bin; Wu, Fang-kun; Niu, Ming-jie; Zou, Ke-hua

2016-01-01

ABSTRACT On the basis of total temperature increase, normal dehydration, and maturity, the odor compositions of surface and internal piles in a well-run sewage sludge compost plant were analyzed using gas chromatography–mass spectrometry with a liquid nitrogen cooling system and a portable odor detector. Approximately 80 types of substances were detected, including 2 volatile inorganic compounds, 4 sulfur organic compounds, 16 benzenes, 27 alkanes, 15 alkenes, and 19 halogenated compounds. Most pollutants were mainly produced in the mesophilic and pre-thermophilic periods. The sulfur volatile organic compounds contributed significantly to odor and should be controlled primarily. Treatment strategies should be based on the properties of sulfur organic compounds. Hydrogen sulfide, methyl mercaptan, dimethyl disulfide, dimethyl sulfide, ammonia, and carbon disulfide were selected as core indicators. Ammonia, hydrogen sulfide, carbon disulfide, dimethyl disulfide, methyl mercaptan, dimethylbenzene, phenylpropane, and isopentane were designated as concentration indicators. Benzene, m-xylene, p-xylene, dimethylbenzene, dichloromethane, toluene, chlorobenzene, trichloromethane, carbon tetrachloride, and ethylbenzene were selected as health indicators. According to the principle of odor pollution indicator selection, dimethyl disulfide was selected as an odor pollution indicator of sewage sludge composting. Monitoring dimethyl disulfide provides a highly scientific method for modeling and evaluating odor pollution from sewage sludge composting facilities. Implications: Composting is one of the most important methods for sewage sludge treatment and improving the low organic matter content of many agricultural soils. However, odors are inevitably produced during the composting process. Understanding the production and emission patterns of odors is important for odor control and treatment. Core indicators, concentration indicators, and health indicators provide an index

Odor composition analysis and odor indicator selection during sewage sludge composting.

Science.gov (United States)

Zhu, Yan-Li; Zheng, Guo-di; Gao, Ding; Chen, Tong-Bin; Wu, Fang-Kun; Niu, Ming-Jie; Zou, Ke-Hua

2016-09-01

On the basis of total temperature increase, normal dehydration, and maturity, the odor compositions of surface and internal piles in a well-run sewage sludge compost plant were analyzed using gas chromatography-mass spectrometry with a liquid nitrogen cooling system and a portable odor detector. Approximately 80 types of substances were detected, including 2 volatile inorganic compounds, 4 sulfur organic compounds, 16 benzenes, 27 alkanes, 15 alkenes, and 19 halogenated compounds. Most pollutants were mainly produced in the mesophilic and pre-thermophilic periods. The sulfur volatile organic compounds contributed significantly to odor and should be controlled primarily. Treatment strategies should be based on the properties of sulfur organic compounds. Hydrogen sulfide, methyl mercaptan, dimethyl disulfide, dimethyl sulfide, ammonia, and carbon disulfide were selected as core indicators. Ammonia, hydrogen sulfide, carbon disulfide, dimethyl disulfide, methyl mercaptan, dimethylbenzene, phenylpropane, and isopentane were designated as concentration indicators. Benzene, m-xylene, p-xylene, dimethylbenzene, dichloromethane, toluene, chlorobenzene, trichloromethane, carbon tetrachloride, and ethylbenzene were selected as health indicators. According to the principle of odor pollution indicator selection, dimethyl disulfide was selected as an odor pollution indicator of sewage sludge composting. Monitoring dimethyl disulfide provides a highly scientific method for modeling and evaluating odor pollution from sewage sludge composting facilities. Composting is one of the most important methods for sewage sludge treatment and improving the low organic matter content of many agricultural soils. However, odors are inevitably produced during the composting process. Understanding the production and emission patterns of odors is important for odor control and treatment. Core indicators, concentration indicators, and health indicators provide an index system to odor evaluation

Container Throughput Forecasting Using Dynamic Factor Analysis and ARIMAX Model

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Marko Intihar

2017-11-01

Full Text Available The paper examines the impact of integration of macroeconomic indicators on the accuracy of container throughput time series forecasting model. For this purpose, a Dynamic factor analysis and AutoRegressive Integrated Moving-Average model with eXogenous inputs (ARIMAX are used. Both methodologies are integrated into a novel four-stage heuristic procedure. Firstly, dynamic factors are extracted from external macroeconomic indicators influencing the observed throughput. Secondly, the family of ARIMAX models of different orders is generated based on the derived factors. In the third stage, the diagnostic and goodness-of-fit testing is applied, which includes statistical criteria such as fit performance, information criteria, and parsimony. Finally, the best model is heuristically selected and tested on the real data of the Port of Koper. The results show that by applying macroeconomic indicators into the forecasting model, more accurate future throughput forecasts can be achieved. The model is also used to produce future forecasts for the next four years indicating a more oscillatory behaviour in (2018-2020. Hence, care must be taken concerning any bigger investment decisions initiated from the management side. It is believed that the proposed model might be a useful reinforcement of the existing forecasting module in the observed port.

Daily House Price Indices: Construction, Modeling, and Longer-Run Predictions

DEFF Research Database (Denmark)

Bollerslev, Tim; Patton, Andrew J.; Wang, Wenjing

We construct daily house price indices for ten major U.S. metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat-sales method that closely mimics the methodology of the popular monthly Case-Shiller house...... price indices. Our new daily house price indices exhibit dynamic features similar to those of other daily asset prices, with mild autocorrelation and strong conditional heteroskedasticity of the corresponding daily returns. A relatively simple multivariate time series model for the daily house price...... index returns, explicitly allowing for commonalities across cities and GARCH effects, produces forecasts of monthly house price changes that are superior to various alternative forecast procedures based on lower frequency data....

Model Proposition for the Fiscal Policies Analysis Applied in Economic Field

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Larisa Preda

2007-05-01

Full Text Available This paper presents a study about fiscal policy applied in economic development. Correlations between macroeconomics and fiscal indicators signify the first steep in our analysis. Next step is a new model proposal for the fiscal and budgetary choices. This model is applied on the date of the Romanian case.

Global plastic models for computerized structural analysis

International Nuclear Information System (INIS)

Roche, R.L.; Hoffmann, A.

1977-01-01

In many types of structures, it is possible to use generalized stresses (like membrane forces, bending moment, torsion moment...) to define a yield surface for a part of the structure. Analysis can be achieved by using the HILL's principle and a hardening rule. The whole formulation is said 'Global Plastic Model'. Two different global models are used in the CEASEMT system for structural analysis, one for shell analysis and the other for piping analysis (in plastic or creep field). In shell analysis the generalized stresses chosen are the membrane forces and bending (including torsion) moments. There is only one yield condition for a normal to the middle surface and no integration along the thickness is required. In piping analysis, the choice of generalized stresses is bending moments, torsional moment, hoop stress and tension stress. There is only a set of stresses for a cross section and no integration over the cross section area is needed. Connected strains are axis curvature, torsion, uniform strains. The definition of the yield surface is the most important item. A practical way is to use a diagonal quadratic function of the stress components. But the coefficients are depending of the shape of the pipe element, especially for curved segments. Indications will be given on the yield functions used. Some examples of applications in structural analysis are added to the text

[Indicators of statin use as a model for qualitative evaluation of chronic disease management in the Local Health Unit Roma B].

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Ciaralli, Fabrizio; Summaria, Francesco; Mustilli, Marina; Vasselli, Loredana; D'Urso, Antonio; Degrassi, Flori

2010-01-01

In chronic diseases the adherence and persistence to therapeutic treatments are often lower than guidelines said. This leads to a worse therapeutic effect of the treatments and to a misuse in healthcare costs. Our study evaluates the impact of a pharmacoutilization analysis model, derived from the administrative database of the Local Health Unit Roma B. In particularly we calculate some indicators of adherence, persistence, occasional treatment and switch in patients on statins secondary prevention treatment (patients discharged from Hospital with Acute Myocardial Infarction diagnosis). The model that we developed would be successfully used in the cost-effective analysis of other drugs.

A neighborhood statistics model for predicting stream pathogen indicator levels.

Science.gov (United States)

Pandey, Pramod K; Pasternack, Gregory B; Majumder, Mahbubul; Soupir, Michelle L; Kaiser, Mark S

2015-03-01

Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale.

Standards of care and quality indicators for multidisciplinary care models for psoriatic arthritis in Spain.

Science.gov (United States)

Gratacós, Jordi; Luelmo, Jesús; Rodríguez, Jesús; Notario, Jaume; Marco, Teresa Navío; de la Cueva, Pablo; Busquets, Manel Pujol; Font, Mercè García; Joven, Beatriz; Rivera, Raquel; Vega, Jose Luis Alvarez; Álvarez, Antonio Javier Chaves; Parera, Ricardo Sánchez; Carrascosa, Jose Carlos Ruiz; Martínez, Fernando José Rodríguez; Sánchez, José Pardo; Olmos, Carlos Feced; Pujol, Conrad; Galindez, Eva; Barrio, Silvia Pérez; Arana, Ana Urruticoechea; Hergueta, Mercedes; Coto, Pablo; Queiro, Rubén

2018-06-01

To define and give priority to standards of care and quality indicators of multidisciplinary care for patients with psoriatic arthritis (PsA). A systematic literature review on PsA standards of care and quality indicators was performed. An expert panel of rheumatologists and dermatologists who provide multidisciplinary care was established. In a consensus meeting group, the experts discussed and developed the standards of care and quality indicators and graded their priority, agreement and also the feasibility (only for quality indicators) following qualitative methodology and a Delphi process. Afterwards, these results were discussed with 2 focus groups, 1 with patients, another with health managers. A descriptive analysis is presented. We obtained 25 standards of care (9 of structure, 9 of process, 7 of results) and 24 quality indicators (2 of structure, 5 of process, 17 of results). Standards of care include relevant aspects in the multidisciplinary care of PsA patients like an appropriate physical infrastructure and technical equipment, the access to nursing care, labs and imaging techniques, other health professionals and treatments, or the development of care plans. Regarding quality indicators, the definition of multidisciplinary care model objectives and referral criteria, the establishment of responsibilities and coordination among professionals and the active evaluation of patients and data collection were given a high priority. Patients considered all of them as important. This set of standards of care and quality indicators for the multidisciplinary care of patients with PsA should help improve quality of care in these patients.

Trophic flow structure of a neotropical estuary in northeastern Brazil and the comparison of ecosystem model indicators of estuaries

Science.gov (United States)

Lira, Alex; Angelini, Ronaldo; Le Loc'h, François; Ménard, Frédéric; Lacerda, Carlos; Frédou, Thierry; Lucena Frédou, Flávia

2018-06-01

We developed an Ecopath model for the Estuary of Sirinhaém River (SIR), a small-sized system surrounded by mangroves, subject to high impact, mainly by the sugar cane and other farming industries in order to describe the food web structure and trophic interactions. In addition, we compared our findings with those of 20 available Ecopath estuarine models for tropical, subtropical and temperate regions, aiming to synthesize the knowledge on trophic dynamics and provide a comprehensive analysis of the structures and functioning of estuaries. Our model consisted of 25 compartments and its indicators were within the expected range for estuarine areas around the world. The average trophic transfer efficiency for the entire system was 11.8%, similar to the theoretical value of 10%. The Keystone Index and MTI (Mixed Trophic Impact) analysis indicated that the snook (Centropomus undecimalis and Centropomus parallelus) and jack (Caranx latus and Caranx hippos) are considered as key resources in the system, revealing their high impact in the food web. Both groups have a high ecological and commercial relevance, despite the unregulated fisheries. As result of the comparison of ecosystem model indicators in estuaries, differences in the ecosystem structure from the low latitude zones (tropical estuaries) to the high latitude zones (temperate system) were noticed. The structure of temperate and sub-tropical estuaries is based on high flows of detritus and export, while tropical systems have high biomass, respiration and consumption rates. Higher values of System Omnivory Index (SOI) and Overhead (SO) were observed in the tropical and subtropical estuaries, denoting a more complex food chain. Globally, none of the estuarine models were classified as fully mature ecosystems, although the tropical ecosystems were considered more mature than the subtropical and temperate ecosystems. This study is an important contribution to the trophic modeling of estuaries, which may also help

Structural Modeling for the Comparison Indicators in Various Electricity Generating Systems

International Nuclear Information System (INIS)

Kim, Seong Ho; Kim, Tae Woon

2006-01-01

Comparison indicators of various power systems can be yielded by solving a multicriteria decision-making (MCDM) problem. In reality, there are different grades of interdependence among the decision elements (e.g., decision goal, decision criteria, and decision alternatives). In our previous work, based on an analytic hierarchy process (AHP) technique, an independence model was developed for the comparison indicators under the assumption that there is no interdependence among the decision elements. For handling different interdependence phenomena (e.g., independence, inner dependence, outer dependence, feedback effect, a combination thereof) among the decision elements, one of the simplest graph structures was investigated on the basis of an analytic network process (ANP) technique. In the present work, the main objective is to study an assessment model with a high grade of interactions among the decision elements. Comparison indicators (e.g., weighting factors, overall priority scores, and risk attitudes towards a nuclear power plant) for seven power generation systems are obtained

Certified metamodels for sensitivity indices estimation

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Prieur Clémentine

2012-04-01

Full Text Available Global sensitivity analysis of a numerical code, more specifically estimation of Sobol indices associated with input variables, generally requires a large number of model runs. When those demand too much computation time, it is necessary to use a reduced model (metamodel to perform sensitivity analysis, whose outputs are numerically close to the ones of the original model, while being much faster to run. In this case, estimated indices are subject to two kinds of errors: sampling error, caused by the computation of the integrals appearing in the definition of the Sobol indices by a Monte-Carlo method, and metamodel error, caused by the replacement of the original model by the metamodel. In cases where we have certified bounds for the metamodel error, we propose a method to quantify both types of error, and we compute confidence intervals for first-order Sobol indices. L’analyse de sensibilité globale d’un modèle numérique, plus précisément l’estimation des indices de Sobol associés aux variables d’entrée, nécessite généralement un nombre important d’exécutions du modèle à analyser. Lorsque celles-ci requièrent un temps de calcul important, il est judicieux d’effectuer l’analyse de sensibilité sur un modèle réduit (ou métamodèle, fournissant des sorties numériquement proches du modèle original mais pour un coût nettement inférieur. Les indices estimés sont alors entâchés de deux sortes d’erreur : l’erreur d’échantillonnage, causée par l’estimation des intégrales définissant les indices de Sobol par une méthode de Monte-Carlo, et l’erreur de métamodèle, liée au remplacement du modèle original par le métamodèle. Lorsque nous disposons de bornes d’erreurs certifiées pour le métamodèle, nous proposons une méthode pour quantifier les deux types d’erreurs et fournir des intervalles de confiance pour les indices de Sobol du premier ordre.

Structural Equation Models in a Redundancy Analysis Framework With Covariates.

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Lovaglio, Pietro Giorgio; Vittadini, Giorgio

2014-01-01

A recent method to specify and fit structural equation modeling in the Redundancy Analysis framework based on so-called Extended Redundancy Analysis (ERA) has been proposed in the literature. In this approach, the relationships between the observed exogenous variables and the observed endogenous variables are moderated by the presence of unobservable composites, estimated as linear combinations of exogenous variables. However, in the presence of direct effects linking exogenous and endogenous variables, or concomitant indicators, the composite scores are estimated by ignoring the presence of the specified direct effects. To fit structural equation models, we propose a new specification and estimation method, called Generalized Redundancy Analysis (GRA), allowing us to specify and fit a variety of relationships among composites, endogenous variables, and external covariates. The proposed methodology extends the ERA method, using a more suitable specification and estimation algorithm, by allowing for covariates that affect endogenous indicators indirectly through the composites and/or directly. To illustrate the advantages of GRA over ERA we propose a simulation study of small samples. Moreover, we propose an application aimed at estimating the impact of formal human capital on the initial earnings of graduates of an Italian university, utilizing a structural model consistent with well-established economic theory.

Invariant density analysis: modeling and analysis of the postural control system using Markov chains.

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Hur, Pilwon; Shorter, K Alex; Mehta, Prashant G; Hsiao-Wecksler, Elizabeth T

2012-04-01

In this paper, a novel analysis technique, invariant density analysis (IDA), is introduced. IDA quantifies steady-state behavior of the postural control system using center of pressure (COP) data collected during quiet standing. IDA relies on the analysis of a reduced-order finite Markov model to characterize stochastic behavior observed during postural sway. Five IDA parameters characterize the model and offer physiological insight into the long-term dynamical behavior of the postural control system. Two studies were performed to demonstrate the efficacy of IDA. Study 1 showed that multiple short trials can be concatenated to create a dataset suitable for IDA. Study 2 demonstrated that IDA was effective at distinguishing age-related differences in postural control behavior between young, middle-aged, and older adults. These results suggest that the postural control system of young adults converges more quickly to their steady-state behavior while maintaining COP nearer an overall centroid than either the middle-aged or older adults. Additionally, larger entropy values for older adults indicate that their COP follows a more stochastic path, while smaller entropy values for young adults indicate a more deterministic path. These results illustrate the potential of IDA as a quantitative tool for the assessment of the quiet-standing postural control system.

Physical Examination-Indicated Cerclage: A Systematic Review and Meta-analysis.

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Ehsanipoor, Robert M; Seligman, Neil S; Saccone, Gabriele; Szymanski, Linda M; Wissinger, Christina; Werner, Erika F; Berghella, Vincenzo

2015-07-01

To estimate the effectiveness of physical examination-indicated cerclage in the setting of second-trimester cervical dilatation by systematic review and meta-analysis of published studies. We searched MEDLINE, EMBASE, Scopus, ClinicalTrials.gov, Web of Science, and the Cochrane Library for studies published between 1966 and 2014 that evaluated cervical cerclage for the treatment of cervical insufficiency. The search yielded 6,314 citations. We included cohort studies and randomized controlled trials comparing cerclage placement with expectant management of women with cervical dilatation between 14 and 27 weeks of gestation. Two investigators independently reviewed each citation for inclusion or exclusion and discordant decisions were arbitrated by a third reviewer. Summary estimates were reported as the mean difference and 95% confidence interval (CI) for continuous variables or relative risk and with 95% CI for dichotomous outcomes. Fixed- and random-effects meta-analysis was used, depending on heterogeneity. Ten studies met inclusion criteria and were included in the final analysis. One was a randomized controlled trial, two were prospective cohort studies, and the remaining seven were retrospective cohort studies. Of the 757 women, 485 (64%) underwent physical examination-indicated cerclage placement and 272 (36%) were expectantly managed. Cerclage was associated with increased neonatal survival (71% compared with 43%; relative risk 1.65, 95% CI 1.19-2.28) and prolongation of pregnancy (mean difference 33.98 days, 95% CI 17.88-50.08). Physical examination-indicated cerclage is associated with a significant increase in neonatal survival and prolongation of pregnancy of approximately 1 month when compared with no such cerclage. The strength of this conclusion is limited by the potential for bias in the included studies.

Identification, Analysis, Modeling and Prediction of Time Series Characterizing the Indicators of Asset Structure in the Credit Institutions Operating in Romania

Directory of Open Access Journals (Sweden)

Daniel CALINICA

2012-08-01

Full Text Available This paper aims to accurately characterize the dynamics of the structural indicators of the assets in the credit institutions operating in Romania through an empirical mathematical model of dual function: regulation and control. The model can be used to predict the future evolution of the economic processes involved, or to study how to act upon them (management in case of changes in the environment around them (e.g. the impact of reducing the minimum compulsory reserve requirements on credit etc.

Constructing core competency indicators for clinical teachers in Taiwan: a qualitative analysis and an analytic hierarchy process.

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Li, Ai-Tzu; Lin, Jou-Wei

2014-04-11

The objective of this study was to construct a framework of core competency indicators of medical doctors who teach in the clinical setting in Taiwan and to evaluate the relative importance of the indicators among these clinical teachers. The preliminary framework of the indicators was developed from an in-depth interview conducted with 12 clinical teachers who had previously been recognized and awarded for their teaching excellence in university hospitals. The framework was categorized into 4 dimensions: 1) Expertise (i.e., professional knowledge and skill); 2) Teaching Ability; 3) Attitudes and Traits; and 4) Beliefs and Values. These areas were further divided into 11 sub-dimensions and 40 indicators. Subsequently, a questionnaire built upon this qualitative analysis was distributed to another group of 17 clinical teachers. Saaty's eigenvector approach, or the so-called analytic hierarchy process (AHP), was applied to perform the pairwise comparisons between indicators and to determine the ranking and relative importance of the indicators. Fourteen questionnaires were deemed valid for AHP assessment due to completeness of data input. The relative contribution of the four main dimensions was 31% for Attitudes and Traits, 30% for Beliefs and Values, 22% for Expertise, and 17% for Teaching Ability. Specifically, 9 out of the 10 top-ranked indicators belonged to the "Attitudes and Traits" or "Beliefs and Values" dimensions, indicating that inner characteristics (i.e., attitudes, traits, beliefs, and values) were perceived as more important than surface ones (i.e., professional knowledge, skills, and teaching competency). We performed a qualitative analysis and developed a questionnaire based upon an interview with experienced clinical teachers in Taiwan, and used this tool to construct the key features for the role model. The application has also demonstrated the relative importance in the dimensions of the core competencies for clinical teachers in Taiwan.

Estimating indices of range shifts in birds using dynamic models when detection is imperfect

Science.gov (United States)

Clement, Matthew J.; Hines, James E.; Nichols, James D.; Pardieck, Keith L.; Ziolkowski, David J.

2016-01-01

There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near-term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology.

Evaluating the ClimEx Single Model large ensemble in comparison with EURO-CORDEX results of heatwave and drought indicators

Science.gov (United States)

von Trentini, F.; Schmid, F. J.; Braun, M.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several indicators concerning heatwave frequency, duration and mean temperature a well as number and maximum length of dry periods (cons. days <1mm) are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

Use of tamper-indicating seals at model facility. Part 1

International Nuclear Information System (INIS)

Logsdon, R.B.

1984-01-01

Tamper-indicating seals, when applied to containers of nuclear material, serve a vital safeguards function. Because of the importance of the seal in safeguards, it is essential that their acquisition, storage, and distribution be controlled effectively. These functions are described for the model facility

Time-Dependent Global Sensitivity Analysis for Long-Term Degeneracy Model Using Polynomial Chaos

Directory of Open Access Journals (Sweden)

Jianbin Guo

2014-07-01

Full Text Available Global sensitivity is used to quantify the influence of uncertain model inputs on the output variability of static models in general. However, very few approaches can be applied for the sensitivity analysis of long-term degeneracy models, as far as time-dependent reliability is concerned. The reason is that the static sensitivity may not reflect the completed sensitivity during the entire life circle. This paper presents time-dependent global sensitivity analysis for long-term degeneracy models based on polynomial chaos expansion (PCE. Sobol’ indices are employed as the time-dependent global sensitivity since they provide accurate information on the selected uncertain inputs. In order to compute Sobol’ indices more efficiently, this paper proposes a moving least squares (MLS method to obtain the time-dependent PCE coefficients with acceptable simulation effort. Then Sobol’ indices can be calculated analytically as a postprocessing of the time-dependent PCE coefficients with almost no additional cost. A test case is used to show how to conduct the proposed method, then this approach is applied to an engineering case, and the time-dependent global sensitivity is obtained for the long-term degeneracy mechanism model.

Percentile-Based ETCCDI Temperature Extremes Indices for CMIP5 Model Output: New Results through Semiparametric Quantile Regression Approach

Science.gov (United States)

Li, L.; Yang, C.

2017-12-01

Climate extremes often manifest as rare events in terms of surface air temperature and precipitation with an annual reoccurrence period. In order to represent the manifold characteristics of climate extremes for monitoring and analysis, the Expert Team on Climate Change Detection and Indices (ETCCDI) had worked out a set of 27 core indices based on daily temperature and precipitation data, describing extreme weather and climate events on an annual basis. The CLIMDEX project (http://www.climdex.org) had produced public domain datasets of such indices for data from a variety of sources, including output from global climate models (GCM) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Among the 27 ETCCDI indices, there are six percentile-based temperature extremes indices that may fall into two groups: exceedance rates (ER) (TN10p, TN90p, TX10p and TX90p) and durations (CSDI and WSDI). Percentiles must be estimated prior to the calculation of the indices, and could more or less be biased by the adopted algorithm. Such biases will in turn be propagated to the final results of indices. The CLIMDEX used an empirical quantile estimator combined with a bootstrap resampling procedure to reduce the inhomogeneity in the annual series of the ER indices. However, there are still some problems remained in the CLIMDEX datasets, namely the overestimated climate variability due to unaccounted autocorrelation in the daily temperature data, seasonally varying biases and inconsistency between algorithms applied to the ER indices and to the duration indices. We now present new results of the six indices through a semiparametric quantile regression approach for the CMIP5 model output. By using the base-period data as a whole and taking seasonality and autocorrelation into account, this approach successfully addressed the aforementioned issues and came out with consistent results. The new datasets cover the historical and three projected (RCP2.6, RCP4.5 and RCP

Exploratory regression analysis: a tool for selecting models and determining predictor importance.

Science.gov (United States)

Braun, Michael T; Oswald, Frederick L

2011-06-01

Linear regression analysis is one of the most important tools in a researcher's toolbox for creating and testing predictive models. Although linear regression analysis indicates how strongly a set of predictor variables, taken together, will predict a relevant criterion (i.e., the multiple R), the analysis cannot indicate which predictors are the most important. Although there is no definitive or unambiguous method for establishing predictor variable importance, there are several accepted methods. This article reviews those methods for establishing predictor importance and provides a program (in Excel) for implementing them (available for direct download at http://dl.dropbox.com/u/2480715/ERA.xlsm?dl=1) . The program investigates all 2(p) - 1 submodels and produces several indices of predictor importance. This exploratory approach to linear regression, similar to other exploratory data analysis techniques, has the potential to yield both theoretical and practical benefits.

Multi-indication Pharmacotherapeutic Multicriteria Decision Analytic Model for the Comparative Formulary Inclusion of Proton Pump Inhibitors in Qatar.

Science.gov (United States)

Al-Badriyeh, Daoud; Alabbadi, Ibrahim; Fahey, Michael; Al-Khal, Abdullatif; Zaidan, Manal

2016-05-01

The formulary inclusion of proton pump inhibitors (PPIs) in the government hospital health services in Qatar is not comparative or restricted. Requests to include a PPI in the formulary are typically accepted if evidence of efficacy and tolerability is presented. There are no literature reports of a PPI scoring model that is based on comparatively weighted multiple indications and no reports of PPI selection in Qatar or the Middle East. This study aims to compare first-line use of the PPIs that exist in Qatar. The economic effect of the study recommendations was also quantified. A comparative, evidence-based multicriteria decision analysis (MCDA) model was constructed to follow the multiple indications and pharmacotherapeutic criteria of PPIs. Literature and an expert panel informed the selection criteria of PPIs. Input from the relevant local clinician population steered the relative weighting of selection criteria. Comparatively scored PPIs, exceeding a defined score threshold, were recommended for selection. Weighted model scores were successfully developed, with 95% CI and 5% margin of error. The model comprised 7 main criteria and 38 subcriteria. Main criteria are indication, dosage frequency, treatment duration, best published evidence, available formulations, drug interactions, and pharmacokinetic and pharmacodynamic properties. Most weight was achieved for the indications selection criteria. Esomeprazole and rabeprazole were suggested as formulary options, followed by lansoprazole for nonformulary use. The estimated effect of the study recommendations was up to a 15.3% reduction in the annual PPI expenditure. Robustness of study conclusions against variabilities in study inputs was confirmed via sensitivity analyses. The implementation of a locally developed PPI-specific comparative MCDA scoring model, which is multiweighted indication and criteria based, into the Qatari formulary selection practices is a successful evidence-based cost-cutting exercise

Consistent robustness analysis (CRA) identifies biologically relevant properties of regulatory network models.

Science.gov (United States)

Saithong, Treenut; Painter, Kevin J; Millar, Andrew J

2010-12-16

A number of studies have previously demonstrated that "goodness of fit" is insufficient in reliably classifying the credibility of a biological model. Robustness and/or sensitivity analysis is commonly employed as a secondary method for evaluating the suitability of a particular model. The results of such analyses invariably depend on the particular parameter set tested, yet many parameter values for biological models are uncertain. Here, we propose a novel robustness analysis that aims to determine the "common robustness" of the model with multiple, biologically plausible parameter sets, rather than the local robustness for a particular parameter set. Our method is applied to two published models of the Arabidopsis circadian clock (the one-loop [1] and two-loop [2] models). The results reinforce current findings suggesting the greater reliability of the two-loop model and pinpoint the crucial role of TOC1 in the circadian network. Consistent Robustness Analysis can indicate both the relative plausibility of different models and also the critical components and processes controlling each model.

Comparative Analysis of Red-Edge Hyperspectral Indices

Science.gov (United States)

Gupta, R.; Vijayan, D.; Prasad, T.

The spectrally continuous observations of 3 nm bandwidth in 680 to 800 nm range over the growth cycle of wheat were subjected to first order differentiation to identify the point of inflection in red to near-IR transition zone. During 40 to 84 days after sowing (DAS), the point of inflection was observed in 723 to 735 nm region with peak response at 729 nm for 64 DAS . For differentiated curve pertaining to 25 DAS (initial vegetative) and 90 DAS (initial senescence) phenological stages, the point of inflection was in 690-693 and 744-747 nm spectral region, respectively. The ratios corresponding to 1dB (RI1dB = R 735 /R720), 2dB (RI 2dB = R738/R 720), 3dB (RI3dB = R741 /R 717) down signal levels and half signal level (RIhalf = R747/R 708 ) were computed. For nomenclature point of view, R41 refers to reflectance for 3 nm7 bandwidth centered at 741 nm. Correlations for these developed RIs were studied with reference to indices given by Vogelmann i.e., VOG a = R 740 /R720 , VOG b = [(R 734-R747)/(R715+R720)] and red edge spectral parameter (RESP) = R750 /R 710. VOG a and RESP conceptually resemble with developed RI 2dB and RIhalf , respectively. All RIs were found correlated with VOGa , VOG b and RESP with r2 in the range of 0.96 to 0.99; r2 was 0.998 for RI2dB and VOG a pair and 0.996 for RI half and RESP pair; the slope factor of regression relationship improved by about 50% from RI dB to2 RI3dB and by about 125% from RI3dB to RIhalf with r2 in 0.97-0.99 range. Thus, theoretical basis for VOG a and RESP in terms of dB based indices has been provided. The wavelengths used in VOGb are noticed in dB based indices ; to provide stability to small magnitude R720, the sum of R720 and R715 has been used in VOGb. Based on regression analysis of these indices with LAI in its growth and decline phases separately, the slope value for VOG b, RI 2dB, VOG a, RIhalf, RESP and area under 680 to 760 nm for first order derivative curve (area) were in 0.08-0.11, 0.24 - 0.34, 0

Developing of Indicators of an E-Learning Benchmarking Model for Higher Education Institutions

Science.gov (United States)

Sae-Khow, Jirasak

2014-01-01

This study was the development of e-learning indicators used as an e-learning benchmarking model for higher education institutes. Specifically, it aimed to: 1) synthesize the e-learning indicators; 2) examine content validity by specialists; and 3) explore appropriateness of the e-learning indicators. Review of related literature included…

Hamiltonian model analysis of ππ scattering and production

International Nuclear Information System (INIS)

Obu, Mitsuaki

2000-01-01

A simple Hamiltonian model for ππ scattering and production is presented which incorporates resonant and background interactions. Analysis of isoscalar S wave ππ phase shift indicates that the background interaction plays only a minor role and the σ may be a dynamical resonance which is not originated from a corresponding bare state. (author)

Serial Analysis of Ten Precipitation-Based Indices by Land Use in Semiarid Regions

Directory of Open Access Journals (Sweden)

Victor M. Rodríguez-Moreno

2015-01-01

Full Text Available Open ecosystems in Mexico are under increasing pressure, due particularly to the expansion of cities and agricultural activities. These developments occur without integrating biodiversity concerns in land use planning and result in extensive fragmentation and transformation of the landscapes. The semiarid region of Mesa Central was characterized using ten precipitation-based indices. Using multivariate statistical and geostatistical spatial analysis techniques, the influence of those indices on five land use strata was explored. Land use analysis indicated that the maximum values of the five significant precipitation-based indices were found in Grasslands, Agricultural Use, and Shrubs; minimum values were characteristic of substrates Secondary Desert Vegetation and Other Use. Our results suggest that the greatest number of extreme precipitation events is likely to occur in open ecosystems and consequently will have a strong influence on landscaping and land use. The semivariogram analysis and geostatistical layers demand attention from research institutions, policy makers, researchers, and food producers to take the appropriate and coordinated actions to propose scenarios to deal with climate change. Perhaps this study can stimulate thought concerning research endeavours aimed at promoting initiatives for biodiversity conservation and planning programs for climate change mitigation.

Historical analysis indicates seepage control on initiation of meandering

NARCIS (Netherlands)

Eekhout, J.P.C.; Hoitink, A.J.F.; Makaske, B.

2013-01-01

In analytical and numerical models of river meandering, initiation of meandering typically occurs uniformly along the streamwise coordinate in the channel. Based on a historical analysis of the Nierskanaal, here we show how and under which circumstances meandering has initiated in isolated sections

Knowledge-based competitiveness indices and its connection with energy indices

Directory of Open Access Journals (Sweden)

Katić Andrea V.

2016-01-01

Full Text Available Knowledge-based economy has become a major trend in international society in the 21st century. However, today’s strategies place a greater emphasis on sustainability than in the past, while continuing to emphasize the importance of education and its connection with labour market. There has been a re-orientation, where resource, eco-efficiency and innovation have become major elements for achieving national objectives and a relevant level of competitiveness. This article deals with 30 indices, which define the competitiveness of a specific economy, and involve knowledge parameters. They are classified into four main categories and one special category. They are then analysed regarding the participation of Serbia and their availability. The main focus of this paper is to give detailed analyses of energy indices, as a special category of knowledge indexes. It has been shown that Serbia, in many cases, was not included in the study analysis or that there was insufficient information about Serbia’s position. This article shows that only a part of the presented indices includes Serbia. It is concluded that a new, revised model is needed that will include more exact indicators.

Midterm Periodicity Analysis of the Mount Wilson Magnetic Indices Using the Synchrosqueezing Transform

Energy Technology Data Exchange (ETDEWEB)

Feng, Song; Wang, Feng; Deng, Hui; Yang, Yunfei [Yunnan Key Laboratory of Computer Technology Application/Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500 (China); Yu, Lan, E-mail: ynkmfs@escience.cn [Department of Mechanical and Electrical Engineering, Yunnan Land and Resources Vocational College, Kunming 650217 (China)

2017-08-10

A novel time–frequency technique, called the synchrosqueezing transform (SST), is used to investigate the midterm periodic variations of magnetic fields on the solar surface. The Magnetic Plage Strength Index (MPSI) and the Mount Wilson Sunspot Index (MWSI), measured daily by the Mount Wilson Observatory between 1970 January 19 and 2012 January 22, are selected. Short-, mid, and longer-term periodicities are represented and decomposed by the SST with hardly any mode mixing. This demonstrates that the SST is a useful time–frequency analysis technique to characterize the periodic modes of helioseismic data. Apart from the fundamental modes of the annual periodicity, ∼27 day rotational cycle and ∼11 year solar cycle, the SST reveals several midterm periodicities in the two magnetic activity indices, specifically, ∼157 days (i.e., Rieger-type periodicity), and ∼1.3 and 1.7 years. The periodic modes, with 116.4 and 276.2 day periodicity in the MPSI, 108.5 and 251.6 day periodicity in the MWSI, and 157.7 day periodicity in the two indices, are in better accord with those significant periodicities derived from the Rossby waves theoretical model. This study suggests that the modes are caused by Rossby waves. For the 1.30 and 1.71 year periodicity of the MPSI, and the 1.33 and 1.67 year periodicity of the MWSI, our analysis infers that they are related to those periodicities with the same timescale in the interior of the Sun and in the high atmospheric layers.

Strategic analysis of the performance of companies trading pharmaceutical products in the Republic of Serbia: As a integrated system of indicators

Directory of Open Access Journals (Sweden)

Čavlin Miroslav S.

2015-01-01

Full Text Available Modern approach to strategic analysis is based on the usage of appropriate systems of indicators, economic and financial, that especially stand out, recommending certain models that are discussed in this paper. In addition to the limitations of the availability of data for a specific analysis which is the subject of this paper, attention is focused on the presentation of the method of 'Force Five' pESTLE. This method has been applied for external analysis of the strategic plan as well as a comparative method of analysis of the financial performance of the related activities of the company, as a core internal resource analysis and management of the companies in the business of trading pharmaceutical products in the Republic of Serbia. In the presented analysis we have indicated the possibility of using an integrative internal and external analysis that produced the financial and non-financial information in order to understand the strategic position of the company. Such an integral concept analysis (strategic and operational creates a unique information and objective basis for the relevant assessment of growth and development and competitive capacity of enterprises.

Panel Analysis of Internet Booking of Travel and Holiday Accommodation Indicators

Directory of Open Access Journals (Sweden)

Ksenija Dumičić

2016-01-01

Full Text Available In the article four development indicators have been carefully selected and their impact on the level of acceptance of the Internet booking of travel and holiday accommodation in selected European countries has been observed. The statistical panel analysis approach was used to determine the individual and the common impact of the development indicators. The analysis has shown that an individual’s wealth, the public expenditure on education, and the Internet penetration rate have a positive statistically significant impact on the level of acceptance of the Internet booking of travel and holiday accommodation whereas the share of individuals with low level Internet skills has a negative statistically significant impact. These results carry significant importance for economists, politicians and all other stakeholders responsible for tourism development in a country. The use of the unbalanced panel is the main limitation of the article.

Using path analysis to examine causal relationships among balanced scorecard performance indicators for general hospitals: the case of a public hospital system in Taiwan.

Science.gov (United States)

Yang, Ming-Chin; Tung, Yu-Chi

2006-01-01

Examining whether the causal relationships among the performance indicators of the balanced scorecard (BSC) framework exist in hospitals is the aim of this article. Data were collected from all twenty-one general hospitals in a public hospital system and their supervising agency for the 3-year period, 2000-2002. The results of the path analyses identified significant causal relationships among four perspectives in the BSC model. We also verified the relationships among indicators within each perspective, some of which varied as time changed. We conclude that hospital administrators can use path analysis to help them identify and manage leading indicators when adopting the BSC model. However, they should also validate causal relationships between leading and lagging indicators periodically because the management environment changes constantly.

A Spatial Analysis of Poverty in Kigali, Rwanda using indicators of ...

African Journals Online (AJOL)

A Spatial Analysis of Poverty in Kigali, Rwanda using indicators of household ... conducted by the National Institute of Statistics of Rwanda in 2000-2001. ... The third region of low poverty incident has between 4-12% of its population poor.

The performance indicators of model projects. A special evaluation

International Nuclear Information System (INIS)

1995-11-01

As a result of the acknowledgment of the key role of the Model Project concept in the Agency's Technical Co-operation Programme, the present review of the objectives of the model projects which are now in operation, was undertaken, as recommended by the Board of Governors, to determine at an early stage: the extent to which the present objectives have been defined in a measurable way; whether objectively verifiable performance indicators and success criteria had been identified for each project; whether mechanisms to obtain feedback on the achievements had been foreseen. The overall budget for the 23 model projects, as approved from 1994 to 1998, amounts to $32,557,560, of which 45% is funded by Technical Co-operation Fund. This represents an average investment of about $8 million per year, that is over 15% of the annual TC budget. The conceptual importance of the Model Project initiative, as well as the significant funds allocated to them, led the Secretariat to plan the methods to be used to determine their socio-economic impact. 1 tab

Data analysis and approximate models model choice, location-scale, analysis of variance, nonparametric regression and image analysis

CERN Document Server

Davies, Patrick Laurie

2014-01-01

Introduction IntroductionApproximate Models Notation Two Modes of Statistical AnalysisTowards One Mode of Analysis Approximation, Randomness, Chaos, Determinism ApproximationA Concept of Approximation Approximation Approximating a Data Set by a Model Approximation Regions Functionals and EquivarianceRegularization and Optimality Metrics and DiscrepanciesStrong and Weak Topologies On Being (almost) Honest Simulations and Tables Degree of Approximation and p-values ScalesStability of Analysis The Choice of En(α, P) Independence Procedures, Approximation and VaguenessDiscrete Models The Empirical Density Metrics and Discrepancies The Total Variation Metric The Kullback-Leibler and Chi-Squared Discrepancies The Po(λ) ModelThe b(k, p) and nb(k, p) Models The Flying Bomb Data The Student Study Times Data OutliersOutliers, Data Analysis and Models Breakdown Points and Equivariance Identifying Outliers and Breakdown Outliers in Multivariate Data Outliers in Linear Regression Outliers in Structured Data The Location...

Proposal of performance indicators/model for Operational Readiness Verification (ORV) at restart after a planned shutdown

International Nuclear Information System (INIS)

Hollnagel, Erik; Nygren, Magnus

2005-12-01

The objectives of the study reported here were to propose a model that can be used in the analysis of possible future ORV-related events and to outline a set of performance indicators that can be used by the inspectorate to assess a utility's level of readiness if an ORV-event should take place. Together the two objectives serve to improve the inspectorate's ability to ensure that the utilities maintain an adequate capability to respond. The background for the current study is the nine ORV events that occurred in Sweden between 1995- 1998, as well as the findings of a previous study of safety during outage and restart of nuclear power plants project. This study found that the three levels or types of tests that occur in ORV were used according to need rather than according to a predefined arrangement or procedure, and that tasks were adapted relative to the different types of embedding and the degree of correspondence between nominal and actual ORV. The organisation's coping with the complexity of ORV was discussed by the relation between expectations and surprises, how planning was used as control, attention to details, and the practices of shift changes. It is a truism that accidents are analysed and interpreted relative to a commonly accepted understanding of their nature. This understanding is, however, relative rather than absolute, and has changed significantly during the last decade. In the 1990s, accidents were analysed step by step, and explanations and recommendations therefore emphasised specific rather than generic solutions. The present study illustrates this by going through the responses to the nine ORV events. Following that, the nine events are analysed anew using a contemporary understanding of accidents (a systemic model), which emphasises that incidents more often arise from context induced performance variability than from failures of people. The alternative interpretation provided by a systemic model is illustrated by a detailed analysis of

Model-based security analysis of the German health card architecture.

Science.gov (United States)

Jürjens, J; Rumm, R

2008-01-01

Health-care information systems are particularly security-critical. In order to make these applications secure, the security analysis has to be an integral part of the system design and IT management process for such systems. This work presents the experiences and results from the security analysis of the system architecture of the German Health Card, by making use of an approach to model-based security engineering that is based on the UML extension UMLsec. The focus lies on the security mechanisms and security policies of the smart-card-based architecture which were analyzed using the UMLsec method and tools. Main results of the paper include a report on the employment of the UMLsec method in an industrial health information systems context as well as indications of its benefits and limitations. In particular, two potential security weaknesses were detected and countermeasures discussed. The results indicate that it can be feasible to apply a model-based security analysis using UMLsec to an industrial health information system like the German Health Card architecture, and that doing so can have concrete benefits (such as discovering potential weaknesses, and an increased confidence that no further vulnerabilities of the kind that were considered are present).

TU-EF-BRD-02: Indicators and Technique Analysis

Energy Technology Data Exchange (ETDEWEB)

Carlone, M. [Princess Margaret Hospital (Canada)

2015-06-15

Research related to quality and safety has been a staple of medical physics academic activities for a long time. From very early on, medical physicists have developed new radiation measurement equipment and analysis techniques, created ever increasingly accurate dose calculation models, and have vastly improved imaging, planning, and delivery techniques. These and other areas of interest have improved the quality and safety of radiotherapy for our patients. With the advent of TG-100, quality and safety is an area that will garner even more research interest in the future. As medical physicists pursue quality and safety research in greater numbers, it is worthwhile to consider what actually constitutes research on quality and safety. For example, should the development of algorithms for real-time EPID-based in-vivo dosimetry be defined as “quality and safety” research? How about the clinical implementation of such as system? Surely the application of failure modes and effects analysis to a clinical process would be considered quality and safety research, but is this type of research that should be included in the medical physics peer-reviewed literature? The answers to such questions are of critical importance to set researchers in a direction that will provide the greatest benefit to our field and the patients we serve. The purpose of this symposium is to consider what constitutes research in the arena of quality and safety and differentiate it from other research directions. The key distinction here is developing the tool itself (e.g. algorithms for EPID dosimetry) vs. studying the impact of the tool with some quantitative metric. Only the latter would I call quality and safety research. Issues of ‘basic’ versus ‘applied’ quality and safety research will be covered as well as how the research results should be structured to provide increasing levels of support that a quality and safety intervention is effective and sustainable. Examples from existing

TU-EF-BRD-02: Indicators and Technique Analysis

International Nuclear Information System (INIS)

Carlone, M.

2015-01-01

Research related to quality and safety has been a staple of medical physics academic activities for a long time. From very early on, medical physicists have developed new radiation measurement equipment and analysis techniques, created ever increasingly accurate dose calculation models, and have vastly improved imaging, planning, and delivery techniques. These and other areas of interest have improved the quality and safety of radiotherapy for our patients. With the advent of TG-100, quality and safety is an area that will garner even more research interest in the future. As medical physicists pursue quality and safety research in greater numbers, it is worthwhile to consider what actually constitutes research on quality and safety. For example, should the development of algorithms for real-time EPID-based in-vivo dosimetry be defined as “quality and safety” research? How about the clinical implementation of such as system? Surely the application of failure modes and effects analysis to a clinical process would be considered quality and safety research, but is this type of research that should be included in the medical physics peer-reviewed literature? The answers to such questions are of critical importance to set researchers in a direction that will provide the greatest benefit to our field and the patients we serve. The purpose of this symposium is to consider what constitutes research in the arena of quality and safety and differentiate it from other research directions. The key distinction here is developing the tool itself (e.g. algorithms for EPID dosimetry) vs. studying the impact of the tool with some quantitative metric. Only the latter would I call quality and safety research. Issues of ‘basic’ versus ‘applied’ quality and safety research will be covered as well as how the research results should be structured to provide increasing levels of support that a quality and safety intervention is effective and sustainable. Examples from existing

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

Energy Technology Data Exchange (ETDEWEB)

Thornton, Peter E [ORNL; Wang, Weile [ORNL; Law, Beverly E. [Oregon State University; Nemani, Ramakrishna R [NASA Ames Research Center

2009-01-01

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.

Global plastic models for computerized structural analysis

International Nuclear Information System (INIS)

Roche, R.; Hoffmann, A.

1977-01-01

Two different global models are used in the CEASEMT system for structural analysis, one for the shells analysis and the other for piping analysis (in plastic or creep field). In shell analysis the generalized stresses choosed are the membrane forces Nsub(ij) and bending (including torsion) moments Msub(ij). There is only one yield condition for a normal (to the middle surface) and no integration along the thickness is required. In piping analysis, the choice of generalized stresses is: bending moments, torsional moments, Hoop stress and tension stress. There is only a set of stresses for a cross section and non integration over the cross section area is needed. Connected strains are axis curvature, torsion, uniform strains. The definition of the yield surface is the most important item. A practical way is to use a diagonal quadratic fonction of the stress components. But the coefficients are depending of the shape of the pipe element, especially for curved segments. Indications will be given on the yield fonctions used. Some examples of applications in structural analysis are added to the text [fr

Stability Analysis of the Embankment Model

Directory of Open Access Journals (Sweden)

G.S. Gopalakrishna

2009-01-01

Full Text Available In analysis of embankment model affected by dynamic force, employment of shaking table is a scientific way in assessment of earthquake behavior. This work focused on saturated loose sandy foundation and enbankment. The results generated through the pore pressure sensors indicated pore water pressure playing main role in creation of liquefaction and stability of the system, and also revealed deformation, settlement, liquefaction intensity and time stability of system in direct correlation with the strength and characteristics of soil. One of the economical methods in stabilization of soil foundation is improvement of some part soil foundation.

Economic performance indicators of wind energy based on wind speed stochastic modeling

International Nuclear Information System (INIS)

D’Amico, Guglielmo; Petroni, Filippo; Prattico, Flavio

2015-01-01

Highlights: • We propose a new and different wind energy production indicator. • We compute financial profitability of potential wind power sites. • The wind speed process is modeled as an indexed semi-Markov chain. • We check if the wind energy is a good investment with and without incentives. - Abstract: We propose the computation of different wind energy production indicators and financial profitability of potential wind power sites. The computation is performed by modeling the wind speed process as an indexed semi-Markov chain to predict and simulate the wind speed dynamics. We demonstrate that the indexed semi-Markov chain approach enables reproducing the indicators calculated on real data. Two different time horizons of 15 and 30 years are analyzed. In the first case we consider the government incentives on the energy price now present in Italy, while in the second case the incentives have not been taken into account

Biometeorological and autoregressive indices for predicting olive pollen intensity.

Science.gov (United States)

Oteros, J; García-Mozo, H; Hervás, C; Galán, C

2013-03-01

This paper reports on modelling to predict airborne olive pollen season severity, expressed as a pollen index (PI), in Córdoba province (southern Spain) several weeks prior to the pollen season start. Using a 29-year database (1982-2010), a multivariate regression model based on five indices-the index-based model-was built to enhance the efficacy of prediction models. Four of the indices used were biometeorological indices: thermal index, pre-flowering hydric index, dormancy hydric index and summer index; the fifth was an autoregressive cyclicity index based on pollen data from previous years. The extreme weather events characteristic of the Mediterranean climate were also taken into account by applying different adjustment criteria. The results obtained with this model were compared with those yielded by a traditional meteorological-based model built using multivariate regression analysis of simple meteorological-related variables. The performance of the models (confidence intervals, significance levels and standard errors) was compared, and they were also validated using the bootstrap method. The index-based model built on biometeorological and cyclicity indices was found to perform better for olive pollen forecasting purposes than the traditional meteorological-based model.

Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates

Science.gov (United States)

López, J.; Francés, F.

2013-08-01

Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS). Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation) and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.

Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates

Directory of Open Access Journals (Sweden)

J. López

2013-08-01

Full Text Available Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS. Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.

A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research.

OpenAIRE

Jarvis, Cheryl Burke; MacKenzie, Scott B; Podsakoff, Philip M

2003-01-01

A review of the literature suggests that few studies use formative indicator measurement models, even though they should. Therefore, the purpose of this research is to (a) discuss the distinction between formative and reflective measurement models, (b) develop a set of conceptual criteria that can be used to determine whether a construct should be modeled as having formative or reflective indicators, (c) review the marketing literature to obtain an estimate of the extent of measurement model ...

Analysis of Malaysian Nuclear Agency Key Performance Indicator (KPI) 2005-2013

International Nuclear Information System (INIS)

Aisya Raihan Abdul Kadir; Hazmimi Kasim; Azlinda Aziz; Noriah Jamal

2014-01-01

Malaysia Nuclear Agency (Nuclear Malaysia) was established on 19 September 1972. Since its inception, Nuclear Malaysia has been entrusted with the responsibility to introduce and promote nuclear science and technology for national development. After more than 40 years of operation, Nuclear Malaysia remains significant as an excellent organization of science, technology and innovation. An analysis of the key performance indicator (KPI) achievements in 2005-2013 as indicator to the role of Nuclear Malaysia as a national research institution. It was established to promote, develop and encourage the application of nuclear technology. (author)

PCA as a practical indicator of OPLS-DA model reliability.

Science.gov (United States)

Worley, Bradley; Powers, Robert

Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) are powerful statistical modeling tools that provide insights into separations between experimental groups based on high-dimensional spectral measurements from NMR, MS or other analytical instrumentation. However, when used without validation, these tools may lead investigators to statistically unreliable conclusions. This danger is especially real for Partial Least Squares (PLS) and OPLS, which aggressively force separations between experimental groups. As a result, OPLS-DA is often used as an alternative method when PCA fails to expose group separation, but this practice is highly dangerous. Without rigorous validation, OPLS-DA can easily yield statistically unreliable group separation. A Monte Carlo analysis of PCA group separations and OPLS-DA cross-validation metrics was performed on NMR datasets with statistically significant separations in scores-space. A linearly increasing amount of Gaussian noise was added to each data matrix followed by the construction and validation of PCA and OPLS-DA models. With increasing added noise, the PCA scores-space distance between groups rapidly decreased and the OPLS-DA cross-validation statistics simultaneously deteriorated. A decrease in correlation between the estimated loadings (added noise) and the true (original) loadings was also observed. While the validity of the OPLS-DA model diminished with increasing added noise, the group separation in scores-space remained basically unaffected. Supported by the results of Monte Carlo analyses of PCA group separations and OPLS-DA cross-validation metrics, we provide practical guidelines and cross-validatory recommendations for reliable inference from PCA and OPLS-DA models.

A low free-parameter stochastic model of daily Forbush decrease indices

Science.gov (United States)

Patra, Sankar Narayan; Bhattacharya, Gautam; Panja, Subhash Chandra; Ghosh, Koushik

2014-01-01

Forbush decrease is a rapid decrease in the observed galactic cosmic ray intensity pattern occurring after a coronal mass ejection. In the present paper we have analyzed the daily Forbush decrease indices from January, 1967 to December, 2003 generated in IZMIRAN, Russia. First the entire indices have been smoothened and next we have made an attempt to fit a suitable stochastic model for the present time series by means of a necessary number of process parameters. The study reveals that the present time series is governed by a stationary autoregressive process of order 2 with a trace of white noise. Under the consideration of the present model we have shown that chaos is not expected in the present time series which opens up the possibility of validation of its forecasting (both short-term and long-term) as well as its multi-periodic behavior.

Development and Application of Econometric Models for Forecasting and Analysis of Monetary Policy Scenarios

OpenAIRE

Malugin, Vladimir; Demidenko , Mikhail; Kalechits, Dmitry; Miksjuk , Alexei; Tsukarev , Taras

2009-01-01

A system of econometric models designed for forecasting target monetary indicators as well as conducting monetary policy scenarios analysis is presented. The econometric models integrated in the system are represented in the error correction form and are interlinked by means of monetary policy instruments variables, common exogenous variables characterizing external shocks, and monetary policy target endogenous variables. Forecast accuracy estimates and monetary policy analysis results are pr...

Application of Statistical Method of Path Analysis to Describe Soil Biological Indices

Directory of Open Access Journals (Sweden)

Y. Kooch

2016-09-01

Full Text Available Introduction: Among the collection of natural resources in the world, soil is considered as one of the most important components of the environment. Protect and improve the properties of this precious resource, requires a comprehensive and coordinated action that only through a deep understanding of quantitative (not only recognition of the quality the origin, distribution and functionality in a natural ecosystem is possible. Many researchers believe that due to the quick reactions of soil organisms to environmental changes, soil biological survey to estimate soil quality is more important than the chemical and physical properties. For this reason, in many studies the nitrogen mineralization and microbial respiration indices are regarded. The aim of the present study were to study the direct and indirect effects of soil physicochemical characteristics on the most important biological indicators (nitrogen mineralization and microbial respiration, which has not been carefully considered up to now. This research is the first study to provide evidence to the future planning and management of soil sciences. Materials and Methods: For this, a limitation of 20 ha area of Experimental Forest Station of Tarbiat Modares University was considered. Fifty five soil samples, from the top 15 cm of soil, were taken, from which bulk density, texture, organic C, total N, cation exchange capacity (CEC, nitrogen mineralization and microbial respiration were determined at the laboratory. The data stored in Excel as a database. To determine the relationship between biological indices and soil physicochemical characteristics, correlation analysis and factor analysis using principal component analysis (PCA were employed. To investigate all direct and indirect relationships between biological indices and different soil characteristics, path analysis (path analysis was used. Results and Discussion: Results showed significant positive relations between biological indices

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

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

Modelling effective soil depth at field scale from soil sensors and geomorphometric indices

Directory of Open Access Journals (Sweden)

Mauricio Castro Franco

2017-04-01

Full Text Available The effective soil depth (ESD affects both dynamic of hydrology and plant growth. In the southeast of Buenos Aires province, the presence of petrocalcic horizon constitutes a limitation to ESD. The aim of this study was to develop a statistic model to predict spatial patterns of ESD using apparent electrical conductivity at two depths: 0-30 (ECa_30 and 0-90 (ECa_90 and geomorphometric indices. To do this, a Random Forest (RF analysis was applied. RF was able to select those variables according to their predictive potential for ESD. In that order, ECa_90, catchment slope, elevation and ECa_30 had main prediction importance. For validating purposes, 3035 ESD measurements were carried out, in five fields. ECa and ESD values showed complex spatial pattern at short distances. RF parameters with lowest error (OOBerror were calibrated. RF model simplified which uses main predictors had a similar predictive development to it uses all predictors. Furthermore, RF model simplified had the ability to delineate similar pattern to those obtained from in situ measure of ESD in all fields. In general, RF was an effective method and easy to work. However, further studies are needed which add other types of variables importance calculation, greater number of fields and test other predictors in order to improve these results.

COMPARATIVE ANALYSIS OF INDICATORS OBTAINED BY CORINELAND COVER METHODOLOGY FOR SUSTAINABLE USE OF FOREST ECOSYSTEMS

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Slaviša Popović

2015-07-01

Full Text Available Serbian Environmental Protection Agency followed international and national indicators to do monitoring of forested landscape area for the period 1990-2000. Based on the data obtained by Corine Land Cover methodology following the indicators like Forest area, Forested landscape, Forest land and Forest and semi natural area, analysis was done. The forested landscape indicators analysis helped trends monitoring during the period from 1990 - 2000 year. Dynamic of forested area changes could have direct impact on the practical implementation of indicators. Indicator Forest area can be used in planning sustainable use of forests. Recorded growth rates value in 2000year, compared to the 1990th is 0.296%. Indicator Forested landscape increase for 0.186% till 2000 year, while the indicator Forested Land recorded value growth rate of 0.193%. Changes in rates of those indicators can be used in the future for “emission trading”. The smallest increment of rate change of 0.1% was recorded in indicator Forests and semi natural area. Information given by this indicator can be used for monitoring habitats in high mountain areas.

A critical cluster analysis of 44 indicators of author-level performance

DEFF Research Database (Denmark)

Wildgaard, Lorna Elizabeth

2015-01-01

. Publication and citation data for 741 researchers across Astronomy, Environmental Science, Philosophy and Public Health was collected in Web of Science (WoS). Forty-four indicators of individual performance were computed using the data. A two-step cluster analysis using IBM SPSS version 22 was performed...

Integral Indicator of Ecological Footprint for Croatian Power Plants

International Nuclear Information System (INIS)

Strijov, V.; Granic, G.; Juric, Z.; Jelavic, B.; Antesevic Maricic, S.

2009-01-01

The main goal of this paper is to present the methodology of construction of the Integral Indicator for Croatian Thermal Power Plants and Combined Heat and Power Plants. The Integral Indicator is necessary to compare Power Plants selected according to a certain criterion. The criterion of the Ecological Footprint is chosen. The following features of the Power Plants are used: generated electricity and heat; consumed coal and liquid fuel; sulphur content in fuel; emitted CO 2 , SO 2 , NO x and particles. To construct the Integral Indicator the linear model is used. The model parameters are tuned by the Principal Component Analysis algorithm. The constructed Integral Indicator is compared with several others, such as Pareto-Optimal Slicing Indicator and Metric Indicator. The Integral Indicator keeps as much information about features of the Power Plants as possible; it is simple and robust.(author).

The long-term memory analysis of industrial indices of the Chinese stock market

International Nuclear Information System (INIS)

Yong, L

2008-01-01

The main work of this paper is to apply the fractional market theory and time series analysis for analyzing various industrial indices of the Chinese stock market by rescaling range analysis. Hurst index and the long-term memory of price change in Chinese stock market are studied

Effect of Epistemic Uncertainty Modeling Approach on Decision-Making: Example using Equipment Performance Indicator

Energy Technology Data Exchange (ETDEWEB)

Dana Kelly; Robert Youngblood

2012-06-01

Quantitative risk assessments are an integral part of risk-informed regulation of current and future nuclear plants in the U.S. The Bayesian approach to uncertainty, in which both stochastic and epistemic uncertainties are represented with precise probability distributions, is the standard approach to modeling uncertainties in such quantitative risk assessments. However, there are long-standing criticisms of the Bayesian approach to epistemic uncertainty from many perspectives, and a number of alternative approaches have been proposed. Among these alternatives, the most promising (and most rapidly developing) would appear to be the concept of imprecise probability. In this paper, we employ a performance indicator example to focus the discussion. We first give a short overview of the traditional Bayesian paradigm and review some its controversial aspects, for example, issues with so-called noninformative prior distributions. We then discuss how the imprecise probability approach treats these issues and compare it with two other approaches: sensitivity analysis and hierarchical Bayes modeling. We conclude with some practical implications for risk-informed decision making.

PUBLIC DEBT ANALYSIS BASED ON SUSTAINABILITY INDICATORS

Directory of Open Access Journals (Sweden)

Elena DASCALU

2016-09-01

Full Text Available This article is an analysis of public debt, in terms of sustainability and vulnerability indicators, under a functioning market economy. The problems encountered regarding the high level of public debt or the potential risks of budgetary pressure converge to the idea that sustainability of public finances should be a major challenge for public policy. Thus, the policy adequate to address public finance sustainability must have as its starting point the overall strategy of the European Union, as well as the economic development of Member States, focusing on the most important performance components, namely, reducing public debt levels, increasing productivity and employment and, last but not the least, reforming social security systems. In order to achieve sustainable levels of public debt, the European Union Member States are required to establish and accomplish medium term strategic budgetary goals to ensure a downward trend in public debt.

Background effects of emergencies on indicators of economic analysis of enterprise economic activity

Directory of Open Access Journals (Sweden)

K.Yu. Polyak

2017-03-01

Full Text Available The paper deals with the study of scientific works on the issue of formation and development of organizational and methodological regulations of accounting and analytical support of the economic activity of an enterprise in emergencies, which led to the conclusion about the complex character of the study of theory, methodology and economic analysis of enterprises in various sectors of national economy. The author studies the approaches to the nature and methods of economic analysis that resulted in the presentation of instructional techniques to the economic structure. In assessing the consequences of emergencies, it is necessary to determine their impact on the indices of economic analysis; so, there was the need to define areas resulting index changes as a result of emergency situations by identifying its components which may affect emergencies. After analyzing the data, it was found that the consequences of emergency situations affecting the indices of business analysis and can lead to changes in management decisions of internal and external users.

Indicators for knowledge transfer analysis

International Nuclear Information System (INIS)

Plaza, L. M.

2007-01-01

Understanding by knowledge transfer, the process by which the scientific knowledge generated by the R+Ds Spanish public system investigators is finally harnessed and officially used by the agents that make up the productive system, or by the administration; this project aims to offer a global view of the main scientific indicators by which said process can be analysed and in particular, of the way that some of these indicators allow us to evaluate this transfer in the case of the Spanish I+D system and in that concerning the Biotechnology sector. (Author) 12 refs

Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

Science.gov (United States)

Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

2014-01-01

Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915

The soil indicator of forest health in the Forest Inventory and Analysis Program

Science.gov (United States)

Michael C. Amacher; Charles H. Perry

2010-01-01

Montreal Process Criteria and Indicators (MPCI) were established to monitor forest conditions and trends to promote sustainable forest management. The Soil Indicator of forest health was developed and implemented within the USFS Forest Inventory and Analysis (FIA) program to assess condition and trends in forest soil quality in U.S. forests regardless of ownership. The...

Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease.

Science.gov (United States)

Christensen, Julie A E; Zoetmulder, Marielle; Koch, Henriette; Frandsen, Rune; Arvastson, Lars; Christensen, Søren R; Jennum, Poul; Sorensen, Helge B D

2014-09-30

Manual scoring of sleep relies on identifying certain characteristics in polysomnograph (PSG) signals. However, these characteristics are disrupted in patients with neurodegenerative diseases. This study evaluates sleep using a topic modeling and unsupervised learning approach to identify sleep topics directly from electroencephalography (EEG) and electrooculography (EOG). PSG data from control subjects were used to develop an EOG and an EEG topic model. The models were applied to PSG data from 23 control subjects, 25 patients with periodic leg movements (PLMs), 31 patients with idiopathic REM sleep behavior disorder (iRBD) and 36 patients with Parkinson's disease (PD). The data were divided into training and validation datasets and features reflecting EEG and EOG characteristics based on topics were computed. The most discriminative feature subset for separating iRBD/PD and PLM/controls was estimated using a Lasso-regularized regression model. The features with highest discriminability were the number and stability of EEG topics linked to REM and N3, respectively. Validation of the model indicated a sensitivity of 91.4% and a specificity of 68.8% when classifying iRBD/PD patients. The topics showed visual accordance with the manually scored sleep stages, and the features revealed sleep characteristics containing information indicative of neurodegeneration. This study suggests that the amount of N3 and the ability to maintain NREM and REM sleep have potential as early PD biomarkers. Data-driven analysis of sleep may contribute to the evaluation of neurodegenerative patients. Copyright © 2014 Elsevier B.V. All rights reserved.

Monte Carlo sensitivity analysis of an Eulerian large-scale air pollution model

International Nuclear Information System (INIS)

Dimov, I.; Georgieva, R.; Ostromsky, Tz.

2012-01-01

Variance-based approaches for global sensitivity analysis have been applied and analyzed to study the sensitivity of air pollutant concentrations according to variations of rates of chemical reactions. The Unified Danish Eulerian Model has been used as a mathematical model simulating a remote transport of air pollutants. Various Monte Carlo algorithms for numerical integration have been applied to compute Sobol's global sensitivity indices. A newly developed Monte Carlo algorithm based on Sobol's quasi-random points MCA-MSS has been applied for numerical integration. It has been compared with some existing approaches, namely Sobol's ΛΠ τ sequences, an adaptive Monte Carlo algorithm, the plain Monte Carlo algorithm, as well as, eFAST and Sobol's sensitivity approaches both implemented in SIMLAB software. The analysis and numerical results show advantages of MCA-MSS for relatively small sensitivity indices in terms of accuracy and efficiency. Practical guidelines on the estimation of Sobol's global sensitivity indices in the presence of computational difficulties have been provided. - Highlights: ► Variance-based global sensitivity analysis is performed for the air pollution model UNI-DEM. ► The main effect of input parameters dominates over higher-order interactions. ► Ozone concentrations are influenced mostly by variability of three chemical reactions rates. ► The newly developed MCA-MSS for multidimensional integration is compared with other approaches. ► More precise approaches like MCA-MSS should be applied when the needed accuracy has not been achieved.

ModelMate - A graphical user interface for model analysis

Science.gov (United States)

Banta, Edward R.

2011-01-01

ModelMate is a graphical user interface designed to facilitate use of model-analysis programs with models. This initial version of ModelMate supports one model-analysis program, UCODE_2005, and one model software program, MODFLOW-2005. ModelMate can be used to prepare input files for UCODE_2005, run UCODE_2005, and display analysis results. A link to the GW_Chart graphing program facilitates visual interpretation of results. ModelMate includes capabilities for organizing directories used with the parallel-processing capabilities of UCODE_2005 and for maintaining files in those directories to be identical to a set of files in a master directory. ModelMate can be used on its own or in conjunction with ModelMuse, a graphical user interface for MODFLOW-2005 and PHAST.

Bitmap indices for fast end-user physics analysis in ROOT

International Nuclear Information System (INIS)

Stockinger, Kurt; Wu Kesheng; Brun, Rene; Canal, Philippe

2006-01-01

Most physics analysis jobs involve multiple selection steps on the input data. These selection steps are called cuts or queries. A common strategy to implement these queries is to read all input data from files and then process the queries in memory. In many applications the number of variables used to define these queries is a relative small portion of the overall data set therefore reading all variables into memory takes unnecessarily long time. In this paper we describe an integration effort that can significantly reduce this unnecessary reading by using an efficient compressed bitmap index technology. The primary advantage of this index is that it can process arbitrary combinations of queries very efficiently, while most other indexing technologies suffer from the 'curse of dimensionality' as the number of queries increases. By integrating this index technology with the ROOT analysis framework, the end-users can benefit from the added efficiency without having to modify their analysis programs. Our performance results show that for multi-dimensional queries, bitmap indices outperform the traditional analysis method up to a factor of 10

Supplementary Material for: A global sensitivity analysis approach for morphogenesis models

KAUST Repository

Boas, Sonja

2015-01-01

Abstract Background Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such ‘black-box’ models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. Results To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. Conclusions We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all ‘black-box’ models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

Estimating daily climatologies for climate indices derived from climate model data and observations

Science.gov (United States)

Mahlstein, Irina; Spirig, Christoph; Liniger, Mark A; Appenzeller, Christof

2015-01-01

Climate indices help to describe the past, present, and the future climate. They are usually closer related to possible impacts and are therefore more illustrative to users than simple climate means. Indices are often based on daily data series and thresholds. It is shown that the percentile-based thresholds are sensitive to the method of computation, and so are the climatological daily mean and the daily standard deviation, which are used for bias corrections of daily climate model data. Sample size issues of either the observed reference period or the model data lead to uncertainties in these estimations. A large number of past ensemble seasonal forecasts, called hindcasts, is used to explore these sampling uncertainties and to compare two different approaches. Based on a perfect model approach it is shown that a fitting approach can improve substantially the estimates of daily climatologies of percentile-based thresholds over land areas, as well as the mean and the variability. These improvements are relevant for bias removal in long-range forecasts or predictions of climate indices based on percentile thresholds. But also for climate change studies, the method shows potential for use. Key Points More robust estimates of daily climate characteristics Statistical fitting approach Based on a perfect model approach PMID:26042192

Hybrid analysis for indicating patients with breast cancer using temperature time series.

Science.gov (United States)

Silva, Lincoln F; Santos, Alair Augusto S M D; Bravo, Renato S; Silva, Aristófanes C; Muchaluat-Saade, Débora C; Conci, Aura

2016-07-01

Breast cancer is the most common cancer among women worldwide. Diagnosis and treatment in early stages increase cure chances. The temperature of cancerous tissue is generally higher than that of healthy surrounding tissues, making thermography an option to be considered in screening strategies of this cancer type. This paper proposes a hybrid methodology for analyzing dynamic infrared thermography in order to indicate patients with risk of breast cancer, using unsupervised and supervised machine learning techniques, which characterizes the methodology as hybrid. The dynamic infrared thermography monitors or quantitatively measures temperature changes on the examined surface, after a thermal stress. In the dynamic infrared thermography execution, a sequence of breast thermograms is generated. In the proposed methodology, this sequence is processed and analyzed by several techniques. First, the region of the breasts is segmented and the thermograms of the sequence are registered. Then, temperature time series are built and the k-means algorithm is applied on these series using various values of k. Clustering formed by k-means algorithm, for each k value, is evaluated using clustering validation indices, generating values treated as features in the classification model construction step. A data mining tool was used to solve the combined algorithm selection and hyperparameter optimization (CASH) problem in classification tasks. Besides the classification algorithm recommended by the data mining tool, classifiers based on Bayesian networks, neural networks, decision rules and decision tree were executed on the data set used for evaluation. Test results support that the proposed analysis methodology is able to indicate patients with breast cancer. Among 39 tested classification algorithms, K-Star and Bayes Net presented 100% classification accuracy. Furthermore, among the Bayes Net, multi-layer perceptron, decision table and random forest classification algorithms, an

Statistical analysis of morphometric indicators and physical readiness variability of students

Directory of Open Access Journals (Sweden)

R.A. Gainullin

2017-10-01

Full Text Available Aim: To evaluate the interaction of morphometric characteristics with the reactions of the cardiorespiratory system and the indices of physical training during the process of physical exercise training at the university. Material: The students of the first course (n = 91, aged 17-18 took part in the survey. The students were divided into 6 groups. All students were engaged in physical training. All the studied indicators were conditionally divided into two groups. The first group of studies included indicators of physical fitness. The second group was formed by morphofunctional indices. Results: The indicators of the physical preparedness of students demonstrate a wide range and heterogeneity. This should be taken into account when staffing training groups. When using the technique of development of local regional muscular endurance, the values of orthostatic test and the Skibinski index show significant variability. Also high and significant correlation interactions are shown by indicators: manual dynamometry; strength endurance; the values of the Skibinski index. Also, in the orthotropic test, the same effect was observed: age, body length, heart rate. A similar analysis of morphofunctional indices shows significant correlation links: the Skibinski index and orthotropic tests; age and the Skibinski index; weight and body length. Conclusions: from the point of view of physical fitness, groups of sports training (the second group and hypertensive groups (group 5 proved to be the most stable. A group of volunteers turned out to be the most stable relative to the morphofunctional indicators.

Development of stochastic indicator models of lithology, Yucca Mountain, Nevada

International Nuclear Information System (INIS)

Rautman, C.A.; Robey, T.H.

1994-01-01

Indicator geostatistical techniques have been used to produce a number of fully three-dimensional stochastic simulations of large-scale lithologic categories at the Yucca Mountain site. Each realization reproduces the available drill hole data used to condition the simulation. Information is propagated away from each point of observation in accordance with a mathematical model of spatial continuity inferred through soft data taken from published geologic cross sections. Variations among the simulated models collectively represent uncertainty in the lithology at unsampled locations. These stochastic models succeed in capturing many major features of welded-nonwelded lithologic framework of Yucca Mountain. However, contacts between welded and nonwelded rock types for individual simulations appear more complex than suggested by field observation, and a number of probable numerical artifacts exist in these models. Many of the apparent discrepancies between the simulated models and the general geology of Yucca Mountain represent characterization uncertainty, and can be traced to the sparse site data used to condition the simulations. Several vertical stratigraphic columns have been extracted from the three-dimensional stochastic models for use in simplified total-system performance assessment exercises. Simple, manual adjustments are required to eliminate the more obvious simulation artifacts and to impose a secondary set of deterministic geologic features on the overall stratigraphic framework provided by the indictor models

Coliform bacteria as indicators of diarrheal risk in household drinking water: systematic review and meta-analysis.

Science.gov (United States)

Gruber, Joshua S; Ercumen, Ayse; Colford, John M

2014-01-01

Current guidelines recommend the use of Escherichia coli (EC) or thermotolerant ("fecal") coliforms (FC) as indicators of fecal contamination in drinking water. Despite their broad use as measures of water quality, there remains limited evidence for an association between EC or FC and diarrheal illness: a previous review found no evidence for a link between diarrhea and these indicators in household drinking water. We conducted a systematic review and meta-analysis to update the results of the previous review with newly available evidence, to explore differences between EC and FC indicators, and to assess the quality of available evidence. We searched major databases using broad terms for household water quality and diarrhea. We extracted study characteristics and relative risks (RR) from relevant studies. We pooled RRs using random effects models with inverse variance weighting, and used standard methods to evaluate heterogeneity and publication bias. We identified 20 relevant studies; 14 studies provided extractable results for meta-analysis. When combining all studies, we found no association between EC or FC and diarrhea (RR 1.26 [95% CI: 0.98, 1.63]). When analyzing EC and FC separately, we found evidence for an association between diarrhea and EC (RR: 1.54 [95% CI: 1.37, 1.74]) but not FC (RR: 1.07 [95% CI: 0.79, 1.45]). Across all studies, we identified several elements of study design and reporting (e.g., timing of outcome and exposure measurement, accounting for correlated outcomes) that could be improved upon in future studies that evaluate the association between drinking water contamination and health. Our findings, based on a review of the published literature, suggest that these two coliform groups have different associations with diarrhea in household drinking water. Our results support the use of EC as a fecal indicator in household drinking water.

Comparative analysis of used car price evaluation models

Science.gov (United States)

Chen, Chuancan; Hao, Lulu; Xu, Cong

2017-05-01

An accurate used car price evaluation is a catalyst for the healthy development of used car market. Data mining has been applied to predict used car price in several articles. However, little is studied on the comparison of using different algorithms in used car price estimation. This paper collects more than 100,000 used car dealing records throughout China to do empirical analysis on a thorough comparison of two algorithms: linear regression and random forest. These two algorithms are used to predict used car price in three different models: model for a certain car make, model for a certain car series and universal model. Results show that random forest has a stable but not ideal effect in price evaluation model for a certain car make, but it shows great advantage in the universal model compared with linear regression. This indicates that random forest is an optimal algorithm when handling complex models with a large number of variables and samples, yet it shows no obvious advantage when coping with simple models with less variables.

Indicating the Attitudes of High School Students to Environment

Science.gov (United States)

Ozkan, Recep

2013-01-01

Within this work in which it has been aimed to indicate the attitudes of High School Students to environment, indication of the attitudes of high school students in Nigde has been regarded as the problem matter. This analysis has the qualification of survey model and techniques of questionnaire and observation have been used. The investigation has…

Indicators for energy security

International Nuclear Information System (INIS)

Kruyt, Bert; Van Vuuren, D.P.; De Vries, H.J.M.; Groenenberg, H.

2009-01-01

The concept of energy security is widely used, yet there is no consensus on its precise interpretation. In this research, we have provided an overview of available indicators for long-term security of supply (SOS). We distinguished four dimensions of energy security that relate to the availability, accessibility, affordability and acceptability of energy and classified indicators for energy security according to this taxonomy. There is no one ideal indicator, as the notion of energy security is highly context dependent. Rather, applying multiple indicators leads to a broader understanding. Incorporating these indicators in model-based scenario analysis showed accelerated depletion of currently known fossil resources due to increasing global demand. Coupled with increasing spatial discrepancy between consumption and production, international trade in energy carriers is projected to have increased by 142% in 2050 compared to 2008. Oil production is projected to become increasingly concentrated in a few countries up to 2030, after which production from other regions diversifies the market. Under stringent climate policies, this diversification may not occur due to reduced demand for oil. Possible benefits of climate policy include increased fuel diversity and slower depletion of fossil resources. (author)

A sensitivity analysis of regional and small watershed hydrologic models

Science.gov (United States)

Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.

1975-01-01

Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.

Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

Science.gov (United States)

Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

2010-10-24

Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary

Regime Switching Vine Copula Models for Global Equity and Volatility Indices

Directory of Open Access Journals (Sweden)

Holger Fink

2017-01-01

Full Text Available For nearly every major stock market there exist equity and implied volatility indices. These play important roles within finance: be it as a benchmark, a measure of general uncertainty or a way of investing or hedging. It is well known in the academic literature that correlations and higher moments between different indices tend to vary in time. However, to the best of our knowledge, no one has yet considered a global setup including both equity and implied volatility indices of various continents, and allowing for a changing dependence structure. We aim to close this gap by applying Markov-switching R-vine models to investigate the existence of different, global dependence regimes. In particular, we identify times of “normal” and “abnormal” states within a data set consisting of North-American, European and Asian indices. Our results confirm the existence of joint points in a time at which global regime switching between two different R-vine structures takes place.

Artificial neural network model for prediction of safety performance indicators goals in nuclear plants

Energy Technology Data Exchange (ETDEWEB)

Souto, Kelling C.; Nunes, Wallace W. [Instituto Federal de Educacao, Ciencia e Tecnologia do Rio de Janeiro, Nilopolis, RJ (Brazil). Lab. de Aplicacoes Computacionais; Machado, Marcelo D., E-mail: dornemd@eletronuclear.gov.b [ELETROBRAS Termonuclear S.A. (ELETRONUCLEAR), Rio de Janeiro, RJ (Brazil). Gerencia de Combustivel Nuclear - GCN.T

2011-07-01

Safety performance indicators have been developed to provide a quantitative indication of the performance and safety in various industry sectors. These indexes can provide assess to aspects ranging from production, design, and human performance up to management issues in accordance with policy, objectives and goals of the company. The use of safety performance indicators in nuclear power plants around the world is a reality. However, it is necessary to periodically set goal values. Such goals are targets relating to each of the indicators to be achieved by the plant over a predetermined period of operation. The current process of defining these goals is carried out by experts in a subjective way, based on actual data from the plant, and comparison with global indices. Artificial neural networks are computational techniques that present a mathematical model inspired by the neural structure of intelligent organisms that acquire knowledge through experience. This paper proposes an artificial neural network model aimed at predicting values of goals to be used in the evaluation of safety performance indicators for nuclear power plants. (author)

Artificial neural network model for prediction of safety performance indicators goals in nuclear plants

International Nuclear Information System (INIS)

Souto, Kelling C.; Nunes, Wallace W.; Machado, Marcelo D.

2011-01-01

Safety performance indicators have been developed to provide a quantitative indication of the performance and safety in various industry sectors. These indexes can provide assess to aspects ranging from production, design, and human performance up to management issues in accordance with policy, objectives and goals of the company. The use of safety performance indicators in nuclear power plants around the world is a reality. However, it is necessary to periodically set goal values. Such goals are targets relating to each of the indicators to be achieved by the plant over a predetermined period of operation. The current process of defining these goals is carried out by experts in a subjective way, based on actual data from the plant, and comparison with global indices. Artificial neural networks are computational techniques that present a mathematical model inspired by the neural structure of intelligent organisms that acquire knowledge through experience. This paper proposes an artificial neural network model aimed at predicting values of goals to be used in the evaluation of safety performance indicators for nuclear power plants. (author)

A systems approach to risk management through leading safety indicators

International Nuclear Information System (INIS)

Leveson, Nancy

2015-01-01

The goal of leading indicators for safety is to identify the potential for an accident before it occurs. Past efforts have focused on identifying general leading indicators, such as maintenance backlog, that apply widely in an industry or even across industries. Other recommendations produce more system-specific leading indicators, but start from system hazard analysis and thus are limited by the causes considered by the traditional hazard analysis techniques. Most rely on quantitative metrics, often based on probabilistic risk assessments. This paper describes a new and different approach to identifying system-specific leading indicators and provides guidance in designing a risk management structure to generate, monitor and use the results. The approach is based on the STAMP (System-Theoretic Accident Model and Processes) model of accident causation and tools that have been designed to build on that model. STAMP extends current accident causality to include more complex causes than simply component failures and chains of failure events or deviations from operational expectations. It incorporates basic principles of systems thinking and is based on systems theory rather than traditional reliability theory. - Highlights: • Much effort has gone into developing leading indicators with only limited success. • A systems-theoretic, assumption-based approach may be more successful. • Leading indicators are warning signals of an assumption’s changing vulnerability. • Heuristic biases can be controlled by using plausibility rather than likelihood

Evaluating the ClimEx Single Model Large Ensemble in Comparison with EURO-CORDEX Results of Seasonal Means and Extreme Precipitation Indicators

Science.gov (United States)

von Trentini, F.; Schmid, F. J.; Braun, M.; Brisette, F.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several extreme indicators like R95pTOT, RX5day and others are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

Models of Economic Analysis

OpenAIRE

Adrian Ioana; Tiberiu Socaciu

2013-01-01

The article presents specific aspects of management and models for economic analysis. Thus, we present the main types of economic analysis: statistical analysis, dynamic analysis, static analysis, mathematical analysis, psychological analysis. Also we present the main object of the analysis: the technological activity analysis of a company, the analysis of the production costs, the economic activity analysis of a company, the analysis of equipment, the analysis of labor productivity, the anal...

Detection of bias in animal model pedigree indices of heifers

Directory of Open Access Journals (Sweden)

M. LIDAUER

2008-12-01

Full Text Available The objective of the study was to test whether the pedigree indices (PI of heifers are biased, and if so, whether the magnitude of the bias varies in different groups of heifers. Therefore, two animal model evaluations with two different data sets were computed. Data with all the records from the national evaluation in December 1994 was used to obtain estimated breeding values (EBV for 305-days' milk yield and protein yield. In the second evaluation, the PIs were estimated for cows calving the first time in 1993 by excluding all their production records from the data. Three different statistics, a simple t-test, the linear regression of EBV on PI, and the polynomial regression of the difference in the predictions (EBV-PI on PI, were computed for three groups of first parity Ayrshire cows: daughters of proven sires, daughters of young sires, and daughters of bull dam candidates. A practically relevant bias was found only in the PIs for the daughters of young sires. On average their PIs were biased upwards by 0.20 standard deviations (78.8 kg for the milk yield and by 0.21 standard deviations (2.2 kg for the protein yield. The polynomial regression analysis showed that the magnitude of the bias in the PIs changed somewhat with the size of the PIs.;

Latent degradation indicators estimation and prediction: A Monte Carlo approach

Science.gov (United States)

Zhou, Yifan; Sun, Yong; Mathew, Joseph; Wolff, Rodney; Ma, Lin

2011-01-01

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.

Global sensitivity analysis applied to drying models for one or a population of granules

DEFF Research Database (Denmark)

Mortier, Severine Therese F. C.; Gernaey, Krist; Thomas, De Beer

2014-01-01

The development of mechanistic models for pharmaceutical processes is of increasing importance due to a noticeable shift toward continuous production in the industry. Sensitivity analysis is a powerful tool during the model building process. A global sensitivity analysis (GSA), exploring sensitiv......The development of mechanistic models for pharmaceutical processes is of increasing importance due to a noticeable shift toward continuous production in the industry. Sensitivity analysis is a powerful tool during the model building process. A global sensitivity analysis (GSA), exploring...... sensitivity in a broad parameter space, is performed to detect the most sensitive factors in two models, that is, one for drying of a single granule and one for the drying of a population of granules [using population balance model (PBM)], which was extended by including the gas velocity as extra input...... compared to our earlier work. beta(2) was found to be the most important factor for the single particle model which is useful information when performing model calibration. For the PBM-model, the granule radius and gas temperature were found to be most sensitive. The former indicates that granulator...

Risk-based safety indicators

International Nuclear Information System (INIS)

Sedlak, J.

2001-12-01

The report is structured as follows: 1. Risk-based safety indicators: Typology of risk-based indicators (RBIs); Tools for defining RBIs; Requirements for the PSA model; Data sources for RBIs; Types of risks monitored; RBIs and operational safety indicators; Feedback from operating experience; PSO model modification for RBIs; RBI categorization; RBI assessment; RBI applications; Suitable RBI applications. 2. Proposal for risk-based indicators: Acquiring information from operational experience; Method of acquiring safety relevance coefficients for the systems from a PSA model; Indicator definitions; On-line indicators. 3. Annex: Application of RBIs worldwide. (P.A.)

The knowledge conversion SECI process as innovation indicator analysis factor

OpenAIRE

Silva, Elaine da [UNESP; Valentim, Marta Lígia Pomim [UNESP

2013-01-01

It highlights the innovation importance in the current society and presents innovation indicators applied in 125 countries. We made an analysis in the 80 variables distributed through seven GII pillars, trying to identify the direct, indirect or null incidences of the knowledge conversion way described by the SECI Process. The researched revealed the fact that knowledge management, in this case specifically the knowledge conversion SECI Process, is present in the variables that, according to ...

Random effects coefficient of determination for mixed and meta-analysis models.

Science.gov (United States)

Demidenko, Eugene; Sargent, James; Onega, Tracy

2012-01-01

The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, [Formula: see text], that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If [Formula: see text] is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of [Formula: see text] apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects-the model can be estimated using the dummy variable approach. We derive explicit formulas for [Formula: see text] in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine.

Application of two way indicator species analysis in lowland plant types classification.

Science.gov (United States)

Kooch, Yahya; Jalilvand, Hamid; Bahmanyar, Mohammad Ali; Pormajidian, Mohammad Reza

2008-03-01

A TWINSPAN classification of 60 sample plots from the Khanikan forest (North of Iran) is presented. Plant types were determined from field observations and sample plot data arranged and analyzed in association tables. The types were defined on the basis of species patterns of presence, absence and coverage values. Vegetation was sampled with randomized-systematic method. Vegetation data including density and cover percentage were estimated quantitatively within each quadrate and using the two-way indicator species analysis. The objectives of the study were to plant type's classification for Khanikan lowland forest in North of Iran, Identification of indicator species in plant types and increase our understanding in regarding to one of Multivariate analysis methods (TWINSPAN). Five plant types were produced for the study area by TWINSPAN, i.e., Menta aquatica, Oplismenus undulatifolius, Carex grioletia, Viola odarata and Rubus caesius. Therefore, at each step of the process, the program identifies indicator species that show strongly differential distributions between groups and so can severe to distinguish the groups. The final result, incorporating elements of classification can provide a compact and powerful summary of pattern in the data set.

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

Science.gov (United States)

2016-07-31

distribution unlimited Hydrocarbon Fuel Thermal Performance Modeling based on Systematic Measurement and Comprehensive Chromatographic Analysis Matthew...vital importance for hydrocarbon -fueled propulsion systems: fuel thermal performance as indicated by physical and chemical effects of cooling passage... analysis . The selection and acquisition of a set of chemically diverse fuels is pivotal for a successful outcome since test method validation and

Process-oriented performance indicators for measuring ecodesign management practices

DEFF Research Database (Denmark)

Rodrigues, Vinicius Picanco; Pigosso, Daniela Cristina Antelmi; McAloone, Tim C.

2016-01-01

In order to support ecodesign performance measurement from a business perspective, this paper performs an exploration of available process-oriented indicators to be applied to ecodesign management practices. With the Ecodesign Maturity Model as a background framework, a systematic literature review...... coupled with a cross-content analysis was carried out to assign proper indicators to the practices. Results show that the currently available indicators do not fully reflect the characteristics of ecodesign and there is significant room for improving the development of tailor-made indicators....

Comparison of several climate indices as inputs in modelling of the Baltic Sea runoff

Energy Technology Data Exchange (ETDEWEB)

Hanninen, J.; Vuorinen, I. [Turku Univ. (Finland). Archipelaco Research Inst.], e-mail: jari.hanninen@utu.fi

2012-11-01

Using Transfer function (TF) models, we have earlier presented a chain of events between changes in the North Atlantic Oscillation (NAO) and their oceanographical and ecological consequences in the Baltic Sea. Here we tested whether other climate indices as inputs would improve TF models, and our understanding of the Baltic Sea ecosystem. Besides NAO, the predictors were the Arctic Oscillation (AO), sea-level air pressures at Iceland (SLP), and wind speeds at Hoburg (Gotland). All indices produced good TF models when the total riverine runoff to the Baltic Sea was used as a modelling basis. AO was not applicable in all study areas, showing a delay of about half a year between climate and runoff events, connected with freezing and melting time of ice and snow in the northern catchment area of the Baltic Sea. NAO appeared to be most useful modelling tool as its area of applicability was the widest of the tested indices, and the time lag between climate and runoff events was the shortest. SLP and Hoburg wind speeds showed largely same results as NAO, but with smaller areal applicability. Thus AO and NAO were both mostly contributing to the general understanding of climate control of runoff events in the Baltic Sea ecosystem. (orig.)

Above-ground biomass of mangrove species. I. Analysis of models

Science.gov (United States)

Soares, Mário Luiz Gomes; Schaeffer-Novelli, Yara

2005-10-01

This study analyzes the above-ground biomass of Rhizophora mangle and Laguncularia racemosa located in the mangroves of Bertioga (SP) and Guaratiba (RJ), Southeast Brazil. Its purpose is to determine the best regression model to estimate the total above-ground biomass and compartment (leaves, reproductive parts, twigs, branches, trunk and prop roots) biomass, indirectly. To do this, we used structural measurements such as height, diameter at breast-height (DBH), and crown area. A combination of regression types with several compositions of independent variables generated 2.272 models that were later tested. Subsequent analysis of the models indicated that the biomass of reproductive parts, branches, and prop roots yielded great variability, probably because of environmental factors and seasonality (in the case of reproductive parts). It also indicated the superiority of multiple regression to estimate above-ground biomass as it allows researchers to consider several aspects that affect above-ground biomass, specially the influence of environmental factors. This fact has been attested to the models that estimated the biomass of crown compartments.

Impact of Climate Variability and Landscape Patterns on Water Budget and Nutrient Loads in a Peri-urban Watershed: A Coupled Analysis Using Process-based Hydrological Model and Landscape Indices

Science.gov (United States)

Li, Chongwei; Zhang, Yajuan; Kharel, Gehendra; Zou, Chris B.

2018-06-01

Nutrient discharge into peri-urban streams and reservoirs constitutes a significant pressure on environmental management, but quantitative assessment of non-point source pollution under climate variability in fast changing peri-urban watersheds is challenging. Soil and Water Assessment Tool (SWAT) was used to simulate water budget and nutrient loads for landscape patterns representing a 30-year progression of urbanization in a peri-urban watershed near Tianjin metropolis, China. A suite of landscape pattern indices was related to nitrogen (N) and phosphorous (P) loads under dry and wet climate using CANOCO redundancy analysis. The calibrated SWAT model was adequate to simulate runoff and nutrient loads for this peri-urban watershed, with Nash-Sutcliffe coefficient (NSE) and coefficient of determination ( R 2) > 0.70 and percentage bias (PBIAS) between -7 and +18 for calibration and validation periods. With the progression of urbanization, forest remained the main "sink" landscape while cultivated and urban lands remained the main "source" landscapes with the role of orchard and grassland being uncertain and changing with time. Compared to 1984, the landscape use pattern in 2013 increased nutrient discharge by 10%. Nutrient loads modelled under wet climate were 3-4 times higher than that under dry climate for the same landscape pattern. Results indicate that climate change could impose a far greater impact on runoff and nutrient discharge in a peri-urban watershed than landscape pattern change.

Impact of Climate Variability and Landscape Patterns on Water Budget and Nutrient Loads in a Peri-urban Watershed: A Coupled Analysis Using Process-based Hydrological Model and Landscape Indices.

Science.gov (United States)

Li, Chongwei; Zhang, Yajuan; Kharel, Gehendra; Zou, Chris B

2018-06-01

Nutrient discharge into peri-urban streams and reservoirs constitutes a significant pressure on environmental management, but quantitative assessment of non-point source pollution under climate variability in fast changing peri-urban watersheds is challenging. Soil and Water Assessment Tool (SWAT) was used to simulate water budget and nutrient loads for landscape patterns representing a 30-year progression of urbanization in a peri-urban watershed near Tianjin metropolis, China. A suite of landscape pattern indices was related to nitrogen (N) and phosphorous (P) loads under dry and wet climate using CANOCO redundancy analysis. The calibrated SWAT model was adequate to simulate runoff and nutrient loads for this peri-urban watershed, with Nash-Sutcliffe coefficient (NSE) and coefficient of determination (R 2 ) > 0.70 and percentage bias (PBIAS) between -7 and +18 for calibration and validation periods. With the progression of urbanization, forest remained the main "sink" landscape while cultivated and urban lands remained the main "source" landscapes with the role of orchard and grassland being uncertain and changing with time. Compared to 1984, the landscape use pattern in 2013 increased nutrient discharge by 10%. Nutrient loads modelled under wet climate were 3-4 times higher than that under dry climate for the same landscape pattern. Results indicate that climate change could impose a far greater impact on runoff and nutrient discharge in a peri-urban watershed than landscape pattern change.

Early indication of noise-induced hearing loss from PMP use in adolescents: A cross-sectional analysis

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Diana C Colon

2016-01-01

Full Text Available Context: Distortion product otoacoustic emissions (DPOAEs may indicate preclinical noise-induced hearing loss (NIHL in adolescents from unsafe personal music player (PMP use. Aims: The objective, therefore, was to observe preclinical signs of NIHL in 9th grade adolescents with clinically normal hearing by comparing DPOAE signals between different levels of A-weighted equivalent PMP exposure. Settings and Design: Subjects were recruited from all secondary-level schools located in the city of Regensburg, Germany during two academic years 2009/2010 and 2010/2011. Subjects and Methods: A-weighted equivalent sound pressure levels (SPLs for a 40-hour work week (LAeq,40h were estimated from questionnaire responses on output and duration of PMP use of the previous week. Subjects were then categorized into four levels of exposure: 85 to <90, and ≥90 A-weighted Decibel [dB(A]. DPOAE signals were collected by trained audiological staff, applying a standard optimized protocol, at the Department of Otorhinolaryngology of the University Hospital Regensburg. Statistical Analysis Used: Mean DPOAE signals were compared between levels by unpaired t test. Novel linear regression models adjusting for other leisure noise exposures and with outcome variables DPoutcome and 4 kilo Hertz (kHz DPOAEs estimated effects between levels. Results: A total of 1468 subjects (56% female, mostly aged 15 or 16 years were available for analysis. Comparison of DPOAE means by PMP exposure typically showed no greater than 1 dB difference between groups. In fact, comparisons between ≥90 dB(A and <80 dB(A presented the least differences in magnitude. Both DPoutcome and 4 kHz linear regression models presented a weak association with the 4-level PMP exposure variable. An expected dose-response to PMP exposure was not observed in any analyses. Conclusions: DPOAE signal strength alone cannot indicate preclinical NIHL in adolescents.

Radiological impacts analysis with use of new endpoint as complementary safety indicators

International Nuclear Information System (INIS)

Peralta Vital, J.L.; Gil Castillo, R.; Fleitas Estevez, G.G.; Olivera Acosta, J.

2015-01-01

The paper shows the new safety indicators on risk assessment (safety assessment) to radioactive waste environmental management implementation (concentrations and fluxes of naturally occurring radioactive materials (NORM)). The endpoint obtained, allow the best analysis of the radiological impact associated to radioactive waste isolation system. The common safety indicators for safety assessment purpose, dose and risk, are very time dependent, increasing the uncertainties in the results for long term assessment. The complementary and new proposed endpoints are more stable and they are not affected by changes in the critical group, pathways, etc. The NORM values on facility site were obtained as result of national surveys, the natural concentrations of U, Ra, Th, K has been associated with the variation of the lithologies in 3 geographical areas of the Country (Occidental, Central and Oriental). The results obtained are related with the safety assessment topics and allowed to apply the new complementary safety indicators, by comparisons between the natural concentrations and fluxes on site and its calculated values for the conceptual repository design. In order to normalize the concentration results, the analysis was realized adopting the criteria of the Repository Equivalent Rock Volume (RERV). The preliminary comparison showed that the calculated concentrations and fluxes in the Cuban conceptual radioactive waste repository are not higher than the natural values in the host rock. According to the application of new safety indicators, the reference disposal facility does not increase the natural activity concentration and fluxes in the environment. In order to implement these new safety indicator it has been used the current 226 Ra inventory of the Repository and the 226 Ra as natural concentration on the site. (authors)

Correlation analysis of energy indicators for sustainable development using multivariate statistical techniques

International Nuclear Information System (INIS)

Carneiro, Alvaro Luiz Guimaraes; Santos, Francisco Carlos Barbosa dos

2007-01-01

Energy is an essential input for social development and economic growth. The production and use of energy cause environmental degradation at all levels, being local, regional and global such as, combustion of fossil fuels causing air pollution; hydropower often causes environmental damage due to the submergence of large areas of land; and global climate change associated with the increasing concentration of greenhouse gases in the atmosphere. As mentioned in chapter 9 of Agenda 21, the Energy is essential to economic and social development and improved quality of life. Much of the world's energy, however, is currently produced and consumed in ways that could not be sustained if technologies were remain constant and if overall quantities were to increase substantially. All energy sources will need to be used in ways that respect the atmosphere, human health, and the environment as a whole. The energy in the context of sustainable development needs a set of quantifiable parameters, called indicators, to measure and monitor important changes and significant progress towards the achievement of the objectives of sustainable development policies. The indicators are divided into four dimensions: social, economic, environmental and institutional. This paper shows a methodology of analysis using Multivariate Statistical Technique that provide the ability to analyse complex sets of data. The main goal of this study is to explore the correlation analysis among the indicators. The data used on this research work, is an excerpt of IBGE (Instituto Brasileiro de Geografia e Estatistica) data census. The core indicators used in this study follows The IAEA (International Atomic Energy Agency) framework: Energy Indicators for Sustainable Development. (author)

Comparative assessment of safety indicators for vehicle trajectories on the highway

NARCIS (Netherlands)

Mullakkal Babu, F.A.; Wang, M.; Farah, H.; van Arem, B.; Happee, R.

2017-01-01

Safety measurement and analysis have been a challenging and well-researched topic in transportation. Conventionally, surrogate safety measures have been used as safety indicators in simulation models for safety assessment, in control formulations for driver assistance systems, and in data analysis

A Comparative Analysis of Disaster Risk, Vulnerability and Resilience Composite Indicators.

Science.gov (United States)

Beccari, Benjamin

2016-03-14

% to the disaster environment, 20% to the economic environment, 13% to the built environment, 6% to the natural environment and 3% were other indices. However variables specifically measuring action to mitigate or prepare for disasters only comprised 12%, on average, of the total number of variables in each index. Only 19% of methodologies employed any sensitivity or uncertainty analysis and in only a single case was this comprehensive. A number of potential limitations of the present state of practice and how these might impact on decision makers are discussed. In particular the limited deployment of sensitivity and uncertainty analysis and the low use of direct measures of disaster risk, vulnerability and resilience could significantly limit the quality and reliability of existing methodologies. Recommendations for improvements to indicator development and use are made, as well as suggested future research directions to enhance the theoretical and empirical knowledge base for composite indicator development.

Genetic analysis of processed in-line mastitis indicator data

DEFF Research Database (Denmark)

Sørensen, Lars Peter; Løvendahl, Peter

2013-01-01

indicates high risk of mastitis. The EMR values were summarized for each cow using the log-transformed median EMR. A second trait was defined as the median of the log-transformed SCC values from 5 to 305 d in milk. A bivariate animal model was used for estimation of co-variance components for the 2 traits......The aim of this study was to estimate heritability of elevated mastitis risk (EMR), a trait derived from in-line measurements of cell counts expressing risk of mastitis on a continuous scale, and its genetic correlation with in-line somatic cell counts. Log-transformed somatic cell counts (SCC; n...... = 855,181) based on in-line measurements (OCC, DeLaval, Sweden) in automatic milking systems were collected from 2007 to2013 in 7 herds from a total of 1986 first and second parity cows (5 to 305 d in milk). Only data from the lactation with most measurements was used from each cow. A bio-model based...

Rich analysis and rational models: Inferring individual behavior from infant looking data

Science.gov (United States)

Piantadosi, Steven T.; Kidd, Celeste; Aslin, Richard

2013-01-01

Studies of infant looking times over the past 50 years have provided profound insights about cognitive development, but their dependent measures and analytic techniques are quite limited. In the context of infants' attention to discrete sequential events, we show how a Bayesian data analysis approach can be combined with a rational cognitive model to create a rich data analysis framework for infant looking times. We formalize (i) a statistical learning model (ii) a parametric linking between the learning model's beliefs and infants' looking behavior, and (iii) a data analysis model that infers parameters of the cognitive model and linking function for groups and individuals. Using this approach, we show that recent findings from Kidd, Piantadosi, and Aslin (2012) of a U-shaped relationship between look-away probability and stimulus complexity even holds within infants and is not due to averaging subjects with different types of behavior. Our results indicate that individual infants prefer stimuli of intermediate complexity, reserving attention for events that are moderately predictable given their probabilistic expectations about the world. PMID:24750256

Using GIS-based methods of multicriteria analysis to construct socio-economic deprivation indices

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Hayes Michael V

2007-05-01

Full Text Available Abstract Background Over the past several decades researchers have produced substantial evidence of a social gradient in a variety of health outcomes, rising from systematic differences in income, education, employment conditions, and family dynamics within the population. Social gradients in health are measured using deprivation indices, which are typically constructed from aggregated socio-economic data taken from the national census – a technique which dates back at least until the early 1970's. The primary method of index construction over the last decade has been a Principal Component Analysis. Seldom are the indices constructed from survey-based data sources due to the inherent difficulty in validating the subjectivity of the response scores. We argue that this very subjectivity can uncover spatial distributions of local health outcomes. Moreover, indication of neighbourhood socio-economic status may go underrepresented when weighted without expert opinion. In this paper we propose the use of geographic information science (GIS for constructing the index. We employ a GIS-based Order Weighted Average (OWA Multicriteria Analysis (MCA as a technique to validate deprivation indices that are constructed using more qualitative data sources. Both OWA and traditional MCA are well known and used methodologies in spatial analysis but have had little application in social epidemiology. Results A survey of British Columbia's Medical Health Officers (MHOs was used to populate the MCA-based index. Seven variables were selected and weighted based on the survey results. OWA variable weights assign both local and global weights to the index variables using a sliding scale, producing a range of variable scenarios. The local weights also provide leverage for controlling the level of uncertainty in the MHO response scores. This is distinct from traditional deprivation indices in that the weighting is simultaneously dictated by the original respondent scores

EFFECT OF DIGITAL ELEVATION MODEL MESH SIZE ON GEOMORPHIC INDICES: A CASE STUDY OF THE IVAÍ RIVER WATERSHED - STATE OF PARANÁ, BRAZIL

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Vanessa Cristina Dos Santos

Full Text Available Abstract: Geomorphometry is the science of quantitative description of land surface morphology by the mean of geomorphic indices extracted from Digital Elevation Models (DEMs. The analysis of these indices is the first and most common procedure performed in several geoscience-related subjects. This study aims to assess the impact of mesh size degradation on different local and regional geomorphic indices extracted for GDEM and TOPODATA DEMs. Thus, these DEMs, having a mesh size of 30 m, were subsampled to 60, 120 and 240 m and then geomorphic indices were calculated using the full resolution DEM and the subsampled ones. Depending on their behavior, these indices are then classified into stable and unstable. The results show that the most affected indices are slope and hydrographic indices such as Strahler order, stream sinuosity and fractal dimension and watershed perimeter, whereas elevation remains stable. It also shows that the effect depends on the presence of the canopy and geological structures in the studied area.

Reference indices of hip structural analysis in Ukrainian women

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N.V. Grygorieva

2017-10-01

Full Text Available Background. Nowadays, a comprehensive assessment of osteoporosis and the risk of osteoporotic fractures involves the combine use of bone mineral density (BMD, 10-year probability of major osteoporotic fractures (Fracture Risk Assessment Tool, Trabecular Bone Score, and parameters of hip structural ana­lysis. In recent years, reference data on the three above-mentioned methods have been developed for the Ukrainian population, but there are no data on the latest methodology. The objective of the study was to assess the age characteristics of hip structural analysis parameters in Ukrainian women and to offer their reference values for use in clinical practice. Materials and methods. Using the dual energy X-ray absorptiometry method, we examined 690 healthy women aged 20–89 years wi­thout osteoporosis and other clinically significant diseases and conditions affecting the bone metabolism, without other accompanying pathology of hip joint. Results. The results of the study showed a significant effect of age on femoral strength index (FSI, cross-sectional moment of inertia (CSMI, cross-sectional area (CSA, distance from center of femoral head to center of femoral neck (d1, distance from center of femoral head to inter-trochanteric line (d2, mean femoral neck dia­meter (d3, distance from center of mass of femoral neck to superior neck margin (y, shaft angle (a and hip axis length (HAL indices, but not on parameters of neck/shaft angle (q. A significant decrease of FSI with age was established on the background on increase of CSMI, CSA and HAL parameters. Indices of height and body weight were reliably related with parameters of CSMI, CSA and HAL. FSI was significantly related to the body weight, but not to the height. In addition, it reliably correlated with BMD measured at femoral neck and lesser at total hip and lumbar spine. The HAL did not significant correlate with any of the measured BMD, which confirms its independent role in prediction of

Correlation analysis between forest carbon stock and spectral vegetation indices in Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam

Science.gov (United States)

Dung Nguyen, The; Kappas, Martin

2017-04-01

In the last several years, the interest in forest biomass and carbon stock estimation has increased due to its importance for forest management, modelling carbon cycle, and other ecosystem services. However, no estimates of biomass and carbon stocks of deferent forest cover types exist throughout in the Xuan Lien Nature Reserve, Thanh Hoa, Viet Nam. This study investigates the relationship between above ground carbon stock and different vegetation indices and to identify the most likely vegetation index that best correlate with forest carbon stock. The terrestrial inventory data come from 380 sample plots that were randomly sampled. Individual tree parameters such as DBH and tree height were collected to calculate the above ground volume, biomass and carbon for different forest types. The SPOT6 2013 satellite data was used in the study to obtain five vegetation indices NDVI, RDVI, MSR, RVI, and EVI. The relationships between the forest carbon stock and vegetation indices were investigated using a multiple linear regression analysis. R-square, RMSE values and cross-validation were used to measure the strength and validate the performance of the models. The methodology presented here demonstrates the possibility of estimating forest volume, biomass and carbon stock. It can also be further improved by addressing more spectral bands data and/or elevation.

Comparison of composite rotor blade models: A coupled-beam analysis and an MSC/NASTRAN finite-element model

Science.gov (United States)

Hodges, Robert V.; Nixon, Mark W.; Rehfield, Lawrence W.

1987-01-01

A methodology was developed for the structural analysis of composite rotor blades. This coupled-beam analysis is relatively simple to use compared with alternative analysis techniques. The beam analysis was developed for thin-wall single-cell rotor structures and includes the effects of elastic coupling. This paper demonstrates the effectiveness of the new composite-beam analysis method through comparison of its results with those of an established baseline analysis technique. The baseline analysis is an MSC/NASTRAN finite-element model built up from anisotropic shell elements. Deformations are compared for three linear static load cases of centrifugal force at design rotor speed, applied torque, and lift for an ideal rotor in hover. A D-spar designed to twist under axial loading is the subject of the analysis. Results indicate the coupled-beam analysis is well within engineering accuracy.

Modelization of cognition, activity and motivation as indicators for Interactive Learning Environment

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Asmaa Darouich

2017-06-01

Full Text Available In Interactive Learning Environment (ILE, the cognitive activity and behavior of learners are the center of the researchers’ concerns. The improvement of learning through combining these axes as a structure of indicators for well-designed learning environment, encloses the measurement of the educational activity as a part of the learning process. In this paper, we propose a mathematical modeling approach based on learners actions to estimate the cognitive activity, learning behavior and motivation, in accordance with a proposed course content structure. This Cognitive indicator includes the study of knowledge, memory and reasoning. While, activity indicator aims to study effort, resistance and intensity. The results recovered on a sample of students with different levels of education, assume that the proposed approach presents a relation among all these indicators which is relatively reliable in the term of cognitive system.

Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

Science.gov (United States)

Clark, D Angus; Bowles, Ryan P

2018-04-23

In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

Improving the performance of high-energy physics analysis through bitmap indices

CERN Document Server

Stockinger, K; Hoschek, W; Schikuta, E

2000-01-01

Bitmap indices are popular multi-dimensional data structures for accessing read-mostly data such as data warehouse (DW) applications, decision support systems (DSS) and online analytical processing (OLAP). One of their main strengths is that they provide good performance characteristics for complex adhoc queries and an efficient combination of multiple index dimensions in one query. Considerable research work has been done in the area of finite (and low) attribute cardinalities. However, additional complexity is imposed on the design of bitmap indices for high cardinality or even non-discrete attributes, where different optimisation techniques than the ones proposed so far have to be applied. We discuss the design and implementation of bitmap indices for high-energy physics (HEP) analysis, where the potential search space consists of hundreds of independent dimensions. A single HEP query typically covers 10 to 100 dimensions out of the whole search space. In this context we evaluated two different bitmap enco...

Gentrification and models for real estate analysis

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Gianfranco Brusa

2013-08-01

Full Text Available This research propose a deep analysis of Milanese real estate market, based on data supplied by three real estate organizations; gentrification appears in some neighborhoods, such as Tortona, Porta Genova, Bovisa, Isola Garibaldi: the latest is the subject of the final analysis, by surveying of physical and social state of the area. The survey takes place in two periods (2003 and 2009 to compare the evolution of gentrification. The results of surveys has been employed in a simulation by multi-agent system model, to foresee long term evolution of the phenomenon. These neighborhood micro-indicators allow to put in evidence actual trends, conditioning a local real estate market, which can translate themselves in phenomena such as gentrification. In present analysis, the employ of cellular automata models applied to a neighborhood in Milan (Isola Garibaldi produced the dynamic simulation of gentrification trend during a very long time: the cyclical phenomenon (one loop holds a period of twenty – thirty years appears sometimes during a theoretical time of 100 – 120 – 150 years. Simulation of long period scenarios by multi-agent systems and cellular automata provides estimator with powerful tool, without limits in implementing it, able to support him in appraisal judge. It stands also to reason that such a tool can sustain urban planning and related evaluation processes.

Importance measures in global sensitivity analysis of nonlinear models

International Nuclear Information System (INIS)

Homma, Toshimitsu; Saltelli, Andrea

1996-01-01

The present paper deals with a new method of global sensitivity analysis of nonlinear models. This is based on a measure of importance to calculate the fractional contribution of the input parameters to the variance of the model prediction. Measures of importance in sensitivity analysis have been suggested by several authors, whose work is reviewed in this article. More emphasis is given to the developments of sensitivity indices by the Russian mathematician I.M. Sobol'. Given that Sobol' treatment of the measure of importance is the most general, his formalism is employed throughout this paper where conceptual and computational improvements of the method are presented. The computational novelty of this study is the introduction of the 'total effect' parameter index. This index provides a measure of the total effect of a given parameter, including all the possible synergetic terms between that parameter and all the others. Rank transformation of the data is also introduced in order to increase the reproducibility of the method. These methods are tested on a few analytical and computer models. The main conclusion of this work is the identification of a sensitivity analysis methodology which is both flexible, accurate and informative, and which can be achieved at reasonable computational cost

Screening for gestational diabetes mellitus by a model based on risk indicators

DEFF Research Database (Denmark)

Jensen, Dorte Møller; Mølsted-Pedersen, Lars; Beck-Nielsen, Henning

2003-01-01

OBJECTIVE: This study was performed to prospectively evaluate a screening model for gestational diabetes mellitus on the basis of clinical risk indicators. STUDY DESIGN: In a prospective multicenter study with 5235 consecutive pregnant women, diagnostic testing with a 2-hour 75-g oral glucose...... of the results from tested women to the whole group in question, a 2.4% prevalence of gestational diabetes mellitus was calculated. Sensitivity and specificity of the model was 80.6 (73.7-87.6) and 64.8 (63.5-66.1), respectively (95% CIs). CONCLUSION: Under ideal conditions, sensitivity of the model...

Comparison between model-predicted tumor oxygenation dynamics and vascular-/flow-related Doppler indices.

Science.gov (United States)

Belfatto, Antonella; Vidal Urbinati, Ailyn M; Ciardo, Delia; Franchi, Dorella; Cattani, Federica; Lazzari, Roberta; Jereczek-Fossa, Barbara A; Orecchia, Roberto; Baroni, Guido; Cerveri, Pietro

2017-05-01

Mathematical modeling is a powerful and flexible method to investigate complex phenomena. It discloses the possibility of reproducing expensive as well as invasive experiments in a safe environment with limited costs. This makes it suitable to mimic tumor evolution and response to radiotherapy although the reliability of the results remains an issue. Complexity reduction is therefore a critical aspect in order to be able to compare model outcomes to clinical data. Among the factors affecting treatment efficacy, tumor oxygenation is known to play a key role in radiotherapy response. In this work, we aim at relating the oxygenation dynamics, predicted by a macroscale model trained on tumor volumetric data of uterine cervical cancer patients, to vascularization and blood flux indices assessed on Ultrasound Doppler images. We propose a macroscale model of tumor evolution based on three dynamics, namely active portion, necrotic portion, and oxygenation. The model parameters were assessed on the volume size of seven cervical cancer patients administered with 28 fractions of intensity modulated radiation therapy (IMRT) (1.8 Gy/fraction). For each patient, five Doppler ultrasound tests were acquired before, during, and after the treatment. The lesion was manually contoured by an expert physician using 4D View ® (General Electric Company - Fairfield, Connecticut, United States), which automatically provided the overall tumor volume size along with three vascularization and/or blood flow indices. Volume data only were fed to the model for training purpose, while the predicted oxygenation was compared a posteriori to the measured Doppler indices. The model was able to fit the tumor volume evolution within 8% error (range: 3-8%). A strong correlation between the intrapatient longitudinal indices from Doppler measurements and oxygen predicted by the model (about 90% or above) was found in three cases. Two patients showed an average correlation value (50-70%) and the remaining

Generic Modelling of Faecal Indicator Organism Concentrations in the UK

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Carl M. Stapleton

2011-06-01

Full Text Available To meet European Water Framework Directive requirements, data are needed on faecal indicator organism (FIO concentrations in rivers to enable the more heavily polluted to be targeted for remedial action. Due to the paucity of FIO data for the UK, especially under high-flow hydrograph event conditions, there is an urgent need by the policy community for generic models that can accurately predict FIO concentrations, thus informing integrated catchment management programmes. This paper reports the development of regression models to predict base- and high-flow faecal coliform (FC and enterococci (EN concentrations for 153 monitoring points across 14 UK catchments, using land cover, population (human and livestock density and other variables that may affect FIO source strength, transport and die-off. Statistically significant models were developed for both FC and EN, with greater explained variance achieved in the high-flow models. Both land cover and, in particular, population variables are significant predictors of FIO concentrations, with r2 maxima for EN of 0.571 and 0.624, respectively. It is argued that the resulting models can be applied, with confidence, to other UK catchments, both to predict FIO concentrations in unmonitored watercourses and evaluate the likely impact of different land use/stocking level and human population change scenarios.

A Novel Clustering Model Based on Set Pair Analysis for the Energy Consumption Forecast in China

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Mingwu Wang

2014-01-01

Full Text Available The energy consumption forecast is important for the decision-making of national economic and energy policies. But it is a complex and uncertainty system problem affected by the outer environment and various uncertainty factors. Herein, a novel clustering model based on set pair analysis (SPA was introduced to analyze and predict energy consumption. The annual dynamic relative indicator (DRI of historical energy consumption was adopted to conduct a cluster analysis with Fisher’s optimal partition method. Combined with indicator weights, group centroids of DRIs for influence factors were transferred into aggregating connection numbers in order to interpret uncertainty by identity-discrepancy-contrary (IDC analysis. Moreover, a forecasting model based on similarity to group centroid was discussed to forecast energy consumption of a certain year on the basis of measured values of influence factors. Finally, a case study predicting China’s future energy consumption as well as comparison with the grey method was conducted to confirm the reliability and validity of the model. The results indicate that the method presented here is more feasible and easier to use and can interpret certainty and uncertainty of development speed of energy consumption and influence factors as a whole.

Analysis of Statistical Distributions Used for Modeling Reliability and Failure Rate of Temperature Alarm Circuit

International Nuclear Information System (INIS)

EI-Shanshoury, G.I.

2011-01-01

Several statistical distributions are used to model various reliability and maintainability parameters. The applied distribution depends on the' nature of the data being analyzed. The presented paper deals with analysis of some statistical distributions used in reliability to reach the best fit of distribution analysis. The calculations rely on circuit quantity parameters obtained by using Relex 2009 computer program. The statistical analysis of ten different distributions indicated that Weibull distribution gives the best fit distribution for modeling the reliability of the data set of Temperature Alarm Circuit (TAC). However, the Exponential distribution is found to be the best fit distribution for modeling the failure rate

MEMBANGUN EARLY WARNING INDICATORS PERGERAKAN KURS DI INDONESIA: PENGEMBANGAN BUSINESS CYCLE ANALYSIS

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Andra Devi Benazir

2011-08-01

Full Text Available The economic crisis in 1997/1998 that was signed by depreciation rupiah almost destroyed the pillars of the economy. This exchange rate shock possibly will happen in the future like that happened in August 2007. At the same time, rupiah falled to the lowest level Rp. 9.410 per dollar (the exchange rate use the last month in August 2007. The exchange rate of its daily until above Rp 9.500 per dollar (Sadewa, 2007. Therefore, it was needed indicator of theearly detection with build leading indicators the movement of the exchange rate in Indonesia. The purpose of this research is building leading indicators the movement of the exchangerate in Indonesia. It could give the capacity forecasting of the Indonesian economy of the movement direction in a manner the aggregate with the Business Cycle Analysis method andIts development. Empirical results showed that is received by four leading indicators and four coincident indicators. The real export, the real import, foreign currency deposit, and forexbanks demand deposits in foreign currency became the moving indicator preceded the exchange rate. Whereas, there are four indicators to coincident was foreign assets, interbank call money rate 1 day, the German share index (DAX, and the USA share index (Nasdaq. This condition indicated that the exchange rate rupiah really was affected by the external factor.

Stable isotope analysis indicates a lack of inter- and intra-specific dietary redundancy among ecologically important coral reef fishes

Science.gov (United States)

Plass-Johnson, J. G.; McQuaid, C. D.; Hill, J. M.

2013-06-01

Parrotfish are critical consumers on coral reefs, mediating the balance between algae and corals, and are often categorised into three functional groups based on adult morphology and feeding behaviour. We used stable isotope analysis (δ13C, δ15N) to investigate size-related ontogenetic dietary changes in multiple species of parrotfish on coral reefs around Zanzibar. We compared signatures among species and functional groups (scrapers, excavators and browsers) as well as ontogenetic stages (immature, initial and terminal phase) within species. Stable isotope analysis suggests that ontogenetic dietary shifts occurred in seven of the nine species examined; larger individuals had enriched δ13C values, with no relationship between size and δ15N. The relationship between fish length and δ13C signature was maintained when species were categorised as scrapers and excavators, but was more pronounced for scrapers than excavators, indicating stronger ontogenetic changes. Isotopic mixing models classified the initial phase of both the most abundant excavator ( Chlorurus sordidus) as a scraper and the immature stage of the scraper Scarus ghobban (the largest species) as an excavator, indicating that diet relates to size rather than taxonomy. The results indicate that parrotfish may show similar intra-group changes in diet with length, but that their trophic ecology is more complex than suggested by morphology alone. Stable isotope analyses indicate that feeding ecology may differ among species within functional groups, and according to ontogenetic stage within a species.

Regression analysis of informative current status data with the additive hazards model.

Science.gov (United States)

Zhao, Shishun; Hu, Tao; Ma, Ling; Wang, Peijie; Sun, Jianguo

2015-04-01

This paper discusses regression analysis of current status failure time data arising from the additive hazards model in the presence of informative censoring. Many methods have been developed for regression analysis of current status data under various regression models if the censoring is noninformative, and also there exists a large literature on parametric analysis of informative current status data in the context of tumorgenicity experiments. In this paper, a semiparametric maximum likelihood estimation procedure is presented and in the method, the copula model is employed to describe the relationship between the failure time of interest and the censoring time. Furthermore, I-splines are used to approximate the nonparametric functions involved and the asymptotic consistency and normality of the proposed estimators are established. A simulation study is conducted and indicates that the proposed approach works well for practical situations. An illustrative example is also provided.

Mechanistic approach to generalized technical analysis of share prices and stock market indices

Science.gov (United States)

Ausloos, M.; Ivanova, K.

2002-05-01

Classical technical analysis methods of stock evolution are recalled, i.e. the notion of moving averages and momentum indicators. The moving averages lead to define death and gold crosses, resistance and support lines. Momentum indicators lead the price trend, thus give signals before the price trend turns over. The classical technical analysis investment strategy is thereby sketched. Next, we present a generalization of these tricks drawing on physical principles, i.e. taking into account not only the price of a stock but also the volume of transactions. The latter becomes a time dependent generalized mass. The notion of pressure, acceleration and force are deduced. A generalized (kinetic) energy is easily defined. It is understood that the momentum indicators take into account the sign of the fluctuations, while the energy is geared toward the absolute value of the fluctuations. They have different patterns which are checked by searching for the crossing points of their respective moving averages. The case of IBM evolution over 1990-2000 is used for illustrations.

Survival analysis models and applications

CERN Document Server

Liu, Xian

2012-01-01

Survival analysis concerns sequential occurrences of events governed by probabilistic laws.  Recent decades have witnessed many applications of survival analysis in various disciplines. This book introduces both classic survival models and theories along with newly developed techniques. Readers will learn how to perform analysis of survival data by following numerous empirical illustrations in SAS. Survival Analysis: Models and Applications: Presents basic techniques before leading onto some of the most advanced topics in survival analysis.Assumes only a minimal knowledge of SAS whilst enablin

An analysis of extrusion of buffer material into fracture behavior by diffusion model

International Nuclear Information System (INIS)

Matsumoto, Kazuhiro; Tanai, Kenji; Kanno, Takeshi; Iwata, Yumiko

2005-06-01

The buffer that will be used as a component of the engineered barriers system swells when saturated by groundwater. As a result of this swelling, buffer may penetrate into the surrounding rock zone through open fractures. It sustained for extremely long periods of time, the buffer extrusion could lead to reduction of buffer density, which may in turn degrade the assumed performance. In this report, the viscosity of bentonite was measured as one of the parameter of diffusion model. In addition, the simulation analysis was carried out to confirm the applicability of diffusion model. Moreover, an analytical evaluation on extrusion behavior of buffer into rock fractures was performed to estimate the long-term stability of buffer as reduction of density. (1) Measurement of the viscosity of bentonite. The viscosity of bentonite is measured by the Rheometer. The viscosity of bentonite indicated tendency to non-Newton flow. The viscosity of bentonite at water contents of 400-1000% was estimated. The evaluated value of the viscosity was modified based on this measurement. (2) Simulation analysis of an experiment results. The simulation analysis of the experimental result using diffusion model was performed to confirm applicability of this model. The results of the simulation reasonably agreed with obtained experimental result. (3) Example analysis of a long-term stability of buffer. The analysis of a long-term stability of buffer as reduction of density was performed to compare with the results in H12 report. In this analysis, the density of the buffer material decreased earlier than the results in H12 report. In addition, a long-term change in the density of the buffer material under seawater condition was preliminary calculated. As a result, it is indicated that extrusion behavior is not significant under seawater condition. (author)

Using sparse polynomial chaos expansions for the global sensitivity analysis of groundwater lifetime expectancy in a multi-layered hydrogeological model

International Nuclear Information System (INIS)

Deman, G.; Konakli, K.; Sudret, B.; Kerrou, J.; Perrochet, P.; Benabderrahmane, H.

2016-01-01

The study makes use of polynomial chaos expansions to compute Sobol' indices within the frame of a global sensitivity analysis of hydro-dispersive parameters in a simplified vertical cross-section of a segment of the subsurface of the Paris Basin. Applying conservative ranges, the uncertainty in 78 input variables is propagated upon the mean lifetime expectancy of water molecules departing from a specific location within a highly confining layer situated in the middle of the model domain. Lifetime expectancy is a hydrogeological performance measure pertinent to safety analysis with respect to subsurface contaminants, such as radionuclides. The sensitivity analysis indicates that the variability in the mean lifetime expectancy can be sufficiently explained by the uncertainty in the petrofacies, i.e. the sets of porosity and hydraulic conductivity, of only a few layers of the model. The obtained results provide guidance regarding the uncertainty modeling in future investigations employing detailed numerical models of the subsurface of the Paris Basin. Moreover, the study demonstrates the high efficiency of sparse polynomial chaos expansions in computing Sobol' indices for high-dimensional models. - Highlights: • Global sensitivity analysis of a 2D 15-layer groundwater flow model is conducted. • A high-dimensional random input comprising 78 parameters is considered. • The variability in the mean lifetime expectancy for the central layer is examined. • Sparse polynomial chaos expansions are used to compute Sobol' sensitivity indices. • The petrofacies of a few layers can sufficiently explain the response variance.

Escherichia coli at Ohio Bathing Beaches--Distribution, Sources, Wastewater Indicators, and Predictive Modeling

Science.gov (United States)

Francy, Donna S.; Gifford, Amie M.; Darner, Robert A.

2003-01-01

. None of the concentrations of wastewater indicators of fecal contamination, including 3b-coprostanol and cholesterol, were significantly correlated (a=0.05) to concentrations of E. coli. Concentrations of the two compounds that were significantly correlated to E. coli were components of coal tar and asphalt, which are not necessarily indicative of fecal contamination. Data were collected to build on an earlier 1997 study to develop and test multiple-linear-regression models to predict E. coli concentrations using water-quality and environmental variables as explanatory variables. The probability of exceeding the single-sample bathing-water standard for E. coli (235 colonies per 100 milliliters) was used as the model output variable. Threshold probabilities for each model were established. Computed probabilities that are less than a threshold probability indicate that bacterial water quality is most likely acceptable. Computed probabilities equal to or above the threshold probability indicate that the water quality is most likely not acceptable and that a water-quality advisory may be needed. Models were developed at each beach, whenever possible, using combinations of 1997, 2000, and (or) 2001 data. The models developed and tested in this study were shown to be beach specific; that is, different explanatory variables were used to predict the probability of exceeding the standard at each beach. At Mentor Headlands and Fairport Harbor, models were not developed because water quality was generally good. At the three Lake Erie urban beaches, models were developed with variable lists that included the number of birds on the beach at the time of sampling, lake-current direction, wave height, turbidity, streamflow of a nearby river, and rainfall. The models for Huntington explained a larger percentage of the variability in E. coli concentrations than the models for Edgewater and Villa Angela. At Mosquito Lake, a model based on 2000 and 2001 data contained the

Assessment of the greenhouse gas emissions from cogeneration and trigeneration systems. Part I: Models and indicators

International Nuclear Information System (INIS)

Chicco, Gianfranco; Mancarella, Pierluigi

2008-01-01

The diffusion of cogeneration and trigeneration plants as local generation sources could bring significant energy saving and emission reduction of various types of pollutants with respect to the separate production of electricity, heat and cooling power. The advantages in terms of primary energy saving are well established. However, the potential of combined heat and power (CHP) and combined cooling heat and power (CCHP) systems for reducing the emission of hazardous greenhouse gases (GHG) needs to be further investigated. This paper presents and discusses a novel approach, based upon an original indicator called trigeneration CO 2 emission reduction (TCO 2 ER), to assess the emission reduction of CO 2 and other GHGs from CHP and CCHP systems with respect to the separate production. The indicator is defined in function of the performance characteristics of the CHP and CCHP systems, represented with black-box models, and of the GHG emission characteristics from conventional sources. The effectiveness of the proposed approach is shown in the companion paper (Part II: Analysis techniques and application cases) with application to various cogeneration and trigeneration solutions

Predicting hydrological response to forest changes by simple statistical models: the selection of the best indicator of forest changes with a hydrological perspective

Science.gov (United States)

Ning, D.; Zhang, M.; Ren, S.; Hou, Y.; Yu, L.; Meng, Z.

2017-01-01

Forest plays an important role in hydrological cycle, and forest changes will inevitably affect runoff across multiple spatial scales. The selection of a suitable indicator for forest changes is essential for predicting forest-related hydrological response. This study used the Meijiang River, one of the headwaters of the Poyang Lake as an example to identify the best indicator of forest changes for predicting forest change-induced hydrological responses. Correlation analysis was conducted first to detect the relationships between monthly runoff and its predictive variables including antecedent monthly precipitation and indicators for forest changes (forest coverage, vegetation indices including EVI, NDVI, and NDWI), and by use of the identified predictive variables that were most correlated with monthly runoff, multiple linear regression models were then developed. The model with best performance identified in this study included two independent variables -antecedent monthly precipitation and NDWI. It indicates that NDWI is the best indicator of forest change in hydrological prediction while forest coverage, the most commonly used indicator of forest change is insignificantly related to monthly runoff. This highlights the use of vegetation index such as NDWI to indicate forest changes in hydrological studies. This study will provide us with an efficient way to quantify the hydrological impact of large-scale forest changes in the Meijiang River watershed, which is crucial for downstream water resource management and ecological protection in the Poyang Lake basin.

Toward a more robust variance-based global sensitivity analysis of model outputs

Energy Technology Data Exchange (ETDEWEB)

Tong, C

2007-10-15

Global sensitivity analysis (GSA) measures the variation of a model output as a function of the variations of the model inputs given their ranges. In this paper we consider variance-based GSA methods that do not rely on certain assumptions about the model structure such as linearity or monotonicity. These variance-based methods decompose the output variance into terms of increasing dimensionality called 'sensitivity indices', first introduced by Sobol' [25]. Sobol' developed a method of estimating these sensitivity indices using Monte Carlo simulations. McKay [13] proposed an efficient method using replicated Latin hypercube sampling to compute the 'correlation ratios' or 'main effects', which have been shown to be equivalent to Sobol's first-order sensitivity indices. Practical issues with using these variance estimators are how to choose adequate sample sizes and how to assess the accuracy of the results. This paper proposes a modified McKay main effect method featuring an adaptive procedure for accuracy assessment and improvement. We also extend our adaptive technique to the computation of second-order sensitivity indices. Details of the proposed adaptive procedure as wells as numerical results are included in this paper.

Multiscale Signal Analysis and Modeling

CERN Document Server

Zayed, Ahmed

2013-01-01

Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...

Cluster analysis of indicators of liver functional and preoperative low branched-chain amino acid tyrosine ration indicate a high risk of early recurrence in analysis of 165 hepatocellular carcinoma patients after initial hepatectomy.

Science.gov (United States)

Nakamura, Yukio; Mizuguchi, Toru; Kawamoto, Masaki; Meguro, Makoto; Harada, Kohei; Ota, Shigenori; Hirata, Koichi

2011-08-01

Cluster analysis is used for dividing many prognostic indicators, including liver function, tumor progression, and operative variables, into specific clusters. The albumin (ALB), hepatocyte growth factor (HGF), and branched chain amino-acid to tyrosine ratio (BTR) may represent the severity of liver disease and function of the hepatic reserve. We developed the ALB-BTR and HGF-BTR classifications depending on each level to find specific unique subgroups. Our aim was to identify specific subgroups destined for favorable and poor prognoses after initial hepatectomy. Between 2002 and 2008, 165 patients were analyzed retrospectively. Liver function indicators, including BTR, tumor-related factors, and operative variables, were evaluated by cluster analysis with Ward's criterion. The ALB-BTR classification was divided into 4 groups depending on ALB (cutoff value, 4.0 g/dL) and BTR (cutoff value, 6.0). The HGF-BTR classification was also divided into 4 groups depending on HGF (cutoff value, 0.35 ng/mL) and BTR (cutoff value, 6.0). The prognoses of the subgroups were compared by the log-rank test. Cluster analysis divided multiple indicators into 5 different clusters. In each cluster, we further analyzed subgroups using the ALB-BTR and HGF-BTR classification. Mean recurrence-free survival times in ALB-GI (19.1 ± 2.4 months) and HGF-GIII (29.4 ± 3.8 months) were less than their mean overall survival times. Cluster analysis is useful to find similar and different indicators. Even though liver function was well preserved, low BTR could identify early recurrence in hepatocellular carcinoma patients after resection. Copyright © 2011 Mosby, Inc. All rights reserved.

Comparison of UTCI to selected thermal indices.

Science.gov (United States)

Blazejczyk, Krzysztof; Epstein, Yoram; Jendritzky, Gerd; Staiger, Henning; Tinz, Birger

2012-05-01

Over the past century more than 100 indices have been developed and used to assess bioclimatic conditions for human beings. The majority of these indices are used sporadically or for specific purposes. Some are based on generalized results of measurements (wind chill, cooling power, wet bulb temperature) and some on the empirically observed reactions of the human body to thermal stress (physiological strain, effective temperature). Those indices that are based on human heat balance considerations are referred to as "rational indices". Several simple human heat balance models are known and are used in research and practice. This paper presents a comparative analysis of the newly developed Universal Thermal Climate Index (UTCI), and some of the more prevalent thermal indices. The analysis is based on three groups of data: global data-set, synoptic datasets from Europe, and local scale data from special measurement campaigns of COST Action 730. We found the present indices to express bioclimatic conditions reasonably only under specific meteorological situations, while the UTCI represents specific climates, weather, and locations much better. Furthermore, similar to the human body, the UTCI is very sensitive to changes in ambient stimuli: temperature, solar radiation, wind and humidity. UTCI depicts temporal variability of thermal conditions better than other indices. The UTCI scale is able to express even slight differences in the intensity of meteorological stimuli.

Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices.

Science.gov (United States)

Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H Eugene

2011-04-01

We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes "bad news" for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.

Quantifying and modeling long-range cross correlations in multiple time series with applications to world stock indices

Science.gov (United States)

Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H. Eugene

2011-04-01

We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes “bad news” for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.

Sensitivity analysis for thermo-hydraulics model of a Westinghouse type PWR. Verification of the simulation results

Energy Technology Data Exchange (ETDEWEB)

Farahani, Aref Zarnooshe [Islamic Azad Univ., Tehran (Iran, Islamic Republic of). Dept. of Nuclear Engineering, Science and Research Branch; Yousefpour, Faramarz [Nuclear Science and Technology Research Institute, Tehran (Iran, Islamic Republic of); Hoseyni, Seyed Mohsen [Islamic Azad Univ., Tehran (Iran, Islamic Republic of). Dept. of Basic Sciences; Islamic Azad Univ., Tehran (Iran, Islamic Republic of). Young Researchers and Elite Club

2017-07-15

Development of a steady-state model is the first step in nuclear safety analysis. The developed model should be qualitatively analyzed first, then a sensitivity analysis is required on the number of nodes for models of different systems to ensure the reliability of the obtained results. This contribution aims to show through sensitivity analysis, the independence of modeling results to the number of nodes in a qualified MELCOR model for a Westinghouse type pressurized power plant. For this purpose, and to minimize user error, the nuclear analysis software, SNAP, is employed. Different sensitivity cases were developed by modification of the existing model and refinement of the nodes for the simulated systems including steam generators, reactor coolant system and also reactor core and its connecting flow paths. By comparing the obtained results to those of the original model no significant difference is observed which is indicative of the model independence to the finer nodes.

Deriving Multidimensional Poverty Indicators: Methodological Issues and an Empirical Analysis for Italy

Science.gov (United States)

Coromaldi, Manuela; Zoli, Mariangela

2012-01-01

Theoretical and empirical studies have recently adopted a multidimensional concept of poverty. There is considerable debate about the most appropriate degree of multidimensionality to retain in the analysis. In this work we add to the received literature in two ways. First, we derive indicators of multiple deprivation by applying a particular…

Activation analysis of several species of marine invertebrates as indicators of environmental conditions

International Nuclear Information System (INIS)

Fukushima, M.; Tamate, H.; Nakano, Y.

2000-01-01

Marine invertebrates are well known to accumulate trace metals from seawater, plankton, sea plants, and sediments. To test the usefulness of such organisms as a bio-indicator of environmental conditions, we have determined levels of trace elements in tissue of twelve species of marine invertebrates by photon and neutron activation analysis. Relatively higher concentration of elements were observed for Ni and Sn in mid-gut gland, for Cu and Zn in oyster tissues, for Se in swimming crabs, for Cu, Fe, and Se in gills of swimming crabs. Our results indicate that mid-gut gland of ear-shell will be useful as the indicator of environmental conditions. (author)

Bayesian analysis for uncertainty estimation of a canopy transpiration model

Science.gov (United States)

Samanta, S.; Mackay, D. S.; Clayton, M. K.; Kruger, E. L.; Ewers, B. E.

2007-04-01

A Bayesian approach was used to fit a conceptual transpiration model to half-hourly transpiration rates for a sugar maple (Acer saccharum) stand collected over a 5-month period and probabilistically estimate its parameter and prediction uncertainties. The model used the Penman-Monteith equation with the Jarvis model for canopy conductance. This deterministic model was extended by adding a normally distributed error term. This extension enabled using Markov chain Monte Carlo simulations to sample the posterior parameter distributions. The residuals revealed approximate conformance to the assumption of normally distributed errors. However, minor systematic structures in the residuals at fine timescales suggested model changes that would potentially improve the modeling of transpiration. Results also indicated considerable uncertainties in the parameter and transpiration estimates. This simple methodology of uncertainty analysis would facilitate the deductive step during the development cycle of deterministic conceptual models by accounting for these uncertainties while drawing inferences from data.

A sensitivity analysis for a thermomechanical model of the Antarctic ice sheet and ice shelves

Science.gov (United States)

Baratelli, F.; Castellani, G.; Vassena, C.; Giudici, M.

2012-04-01

The outcomes of an ice sheet model depend on a number of parameters and physical quantities which are often estimated with large uncertainty, because of lack of sufficient experimental measurements in such remote environments. Therefore, the efforts to improve the accuracy of the predictions of ice sheet models by including more physical processes and interactions with atmosphere, hydrosphere and lithosphere can be affected by the inaccuracy of the fundamental input data. A sensitivity analysis can help to understand which are the input data that most affect the different predictions of the model. In this context, a finite difference thermomechanical ice sheet model based on the Shallow-Ice Approximation (SIA) and on the Shallow-Shelf Approximation (SSA) has been developed and applied for the simulation of the evolution of the Antarctic ice sheet and ice shelves for the last 200 000 years. The sensitivity analysis of the model outcomes (e.g., the volume of the ice sheet and of the ice shelves, the basal melt rate of the ice sheet, the mean velocity of the Ross and Ronne-Filchner ice shelves, the wet area at the base of the ice sheet) with respect to the model parameters (e.g., the basal sliding coefficient, the geothermal heat flux, the present-day surface accumulation and temperature, the mean ice shelves viscosity, the melt rate at the base of the ice shelves) has been performed by computing three synthetic numerical indices: two local sensitivity indices and a global sensitivity index. Local sensitivity indices imply a linearization of the model and neglect both non-linear and joint effects of the parameters. The global variance-based sensitivity index, instead, takes into account the complete variability of the input parameters but is usually conducted with a Monte Carlo approach which is computationally very demanding for non-linear complex models. Therefore, the global sensitivity index has been computed using a development of the model outputs in a

Linear mixed-effects modeling approach to FMRI group analysis.

Science.gov (United States)

Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W

2013-06-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity

Can confidence indicators forecast the probability of expansion in Croatia?

Directory of Open Access Journals (Sweden)

Mirjana Čižmešija

2016-04-01

Full Text Available The aim of this paper is to investigate how reliable are confidence indicators in forecasting the probability of expansion. We consider three Croatian Business Survey indicators: the Industrial Confidence Indicator (ICI, the Construction Confidence Indicator (BCI and the Retail Trade Confidence Indicator (RTCI. The quarterly data, used in the research, covered the periods from 1999/Q1 to 2014/Q1. Empirical analysis consists of two parts. The non-parametric Bry-Boschan algorithm is used for distinguishing periods of expansion from the period of recession in the Croatian economy. Then, various nonlinear probit models were estimated. The models differ with respect to the regressors (confidence indicators and the time lags. The positive signs of estimated parameters suggest that the probability of expansion increases with an increase in Confidence Indicators. Based on the obtained results, the conclusion is that ICI is the most powerful predictor of the probability of expansion in Croatia.

Analysis and modeling of ensemble recordings from respiratory pre-motor neurons indicate changes in functional network architecture after acute hypoxia

Directory of Open Access Journals (Sweden)

Roberto F Galán

2010-09-01

Full Text Available We have combined neurophysiologic recording, statistical analysis, and computational modeling to investigate the dynamics of the respiratory network in the brainstem. Using a multielectrode array, we recorded ensembles of respiratory neurons in perfused in situ rat preparations that produce spontaneous breathing patterns, focusing on inspiratory pre-motor neurons. We compared firing rates and neuronal synchronization among these neurons before and after a brief hypoxic stimulus. We observed a significant decrease in the number of spikes after stimulation, in part due to a transient slowing of the respiratory pattern. However, the median interspike interval did not change, suggesting that the firing threshold of the neurons was not affected but rather the synaptic input was. A bootstrap analysis of synchrony between spike trains revealed that, both before and after brief hypoxia, up to 45 % (but typically less than 5 % of coincident spikes across neuronal pairs was not explained by chance. Most likely, this synchrony resulted from common synaptic input to the pre-motor population, an example of stochastic synchronization. After brief hypoxia most pairs were less synchronized, although some were more, suggesting that the respiratory network was “rewired” transiently after the stimulus. To investigate this hypothesis, we created a simple computational model with feed-forward divergent connections along the inspiratory pathway. Assuming that 1 the number of divergent projections was not the same for all presynaptic cells, but rather spanned a wide range and 2 that the stimulus increased inhibition at the top of the network; this model reproduced the reduction in firing rate and bootstrap-corrected synchrony subsequent to hypoxic stimulation observed in our experimental data.

An integrated 3D design, modeling and analysis resource for SSC detector systems

International Nuclear Information System (INIS)

DiGiacomo, N.J.; Adams, T.; Anderson, M.K.; Davis, M.; Easom, B.; Gliozzi, J.; Hale, W.M.; Hupp, J.; Killian, K.; Krohn, M.; Leitch, R.; Lajczok, M.; Mason, L.; Mitchell, J.; Pohlen, J.; Wright, T.

1989-01-01

Integrated computer aided engineering and design (CAE/CAD) is having a significant impact on the way design, modeling and analysis is performed, from system concept exploration and definition through final design and integration. Experience with integrated CAE/CAD in high technology projects of scale and scope similar to SSC detectors leads them to propose an integrated computer-based design, modeling and analysis resource aimed specifically at SSC detector system development. The resource architecture emphasizes value-added contact with data and efficient design, modeling and analysis of components, sub-systems or systems with fidelity appropriate to the task. They begin with a general examination of the design, modeling and analysis cycle in high technology projects, emphasizing the transition from the classical islands of automation to the integrated CAE/CAD-based approach. They follow this with a discussion of lessons learned from various attempts to design and implement integrated CAE/CAD systems in scientific and engineering organizations. They then consider the requirements for design, modeling and analysis during SSC detector development, and describe an appropriate resource architecture. They close with a report on the status of the resource and present some results that are indicative of its performance. 10 refs., 7 figs

Modeling of asphalt-rubber rotational viscosity by statistical analysis and neural networks

Directory of Open Access Journals (Sweden)

Luciano Pivoto Specht

2007-03-01

Full Text Available It is of a great importance to know binders' viscosity in order to perform handling, mixing, application processes and asphalt mixes compaction in highway surfacing. This paper presents the results of viscosity measurement in asphalt-rubber binders prepared in laboratory. The binders were prepared varying the rubber content, rubber particle size, duration and temperature of mixture, all following a statistical design plan. The statistical analysis and artificial neural networks were used to create mathematical models for prediction of the binders viscosity. The comparison between experimental data and simulated results with the generated models showed best performance of the neural networks analysis in contrast to the statistic models. The results indicated that the rubber content and duration of mixture have major influence on the observed viscosity for the considered interval of parameters variation.

INVESTOR’S PREFERENCE MODEL FOR DATA ENVELOPMENT ANALYSIS MID (DEA IN BRAZILIAN

Directory of Open Access Journals (Sweden)

Mara Vogt

2018-01-01

Full Text Available This study had aimed to analyze the preferred model investor through data envelopment analysis (DEA in Brazilian companies. We conducted a descriptive research with quantitative approach and through document analysis with secondary data. The study population comprised 50 companies listed on the BM&Bovespa IBrX50 and the sample had been composed of 46 companies that presented all the necessary data for analysis of data from 2013 to 2015. To analyze the results we used the method DEA to identify companies that are efficient to in connection to risk and expected return on the stock market, these serving as the preferred model. The results have indicated that the best option for investor would be Ambev companies, BRF, Cetip, Cosan, Itausa, Klabin, Multiplan, Telefonica Brazil and Ultrapar Participações, as these companies had maximum efficiency scores, that is, the score value 1.0.Each company who has that score have expected return that none in the sample managed to overcome with less risk and even equal. The results also indicate that several companies have been above average efficiency score and below average, indicating that there are significant differences in efficiency between the companies analyzed. It is concluded that the efficiency of the sample front companies the capital market is considered satisfactory, since the existence of inefficiencies in many companies prevents IBrX50 index reaches its maximum potential over the actions and the risk and return expected by investors.

Vibration Spectrum Analysis for Indicating Damage on Turbine and Steam Generator Amurang Unit 1

Directory of Open Access Journals (Sweden)

Beny Cahyono

2017-12-01

Full Text Available Maintenance on machines is a mandatory asset management activity to maintain asset reliability in order to reduce losses due to failure. 89% of defects have random failure mode, the proper maintenance method is predictive maintenance. Predictive maintenance object in this research is Steam Generator Amurang Unit 1, which is predictive maintenance is done through condition monitoring in the form of vibration analysis. The conducting vibration analysis on Amurang Unit 1 Steam Generator is because vibration analysis is very effective on rotating objects. Vibration analysis is predicting the damage based on the vibration spectrum, where the vibration spectrum is the result of separating time-based vibrations and simplifying them into vibrations based on their frequency domain. The transformation of time-domain-wave into frequency-domain-wave is using the application of FFT, namely AMS Machinery. The measurement of vibration value is done on turbine bearings and steam generator of Unit 1 Amurang using Turbine Supervisory Instrument and CSI 2600 instrument. The result of this research indicates that vibration spectrum from Unit 1 Amurang Power Plant indicating that there is rotating looseness, even though the vibration value does not require the Unit 1 Amurang Power Plant to stop operating (shut down. This rotating looseness, at some point, can produce some indications that similar with the unbalance. In order to avoid more severe vibrations, it is necessary to do inspection on the bearings in the Amurang Unit 1 Power Plant.

A Price Index Model for Road Freight Transportation and Its Empirical analysis in China

Directory of Open Access Journals (Sweden)

Liu Zhishuo

2017-01-01

Full Text Available The aim of price index for road freight transportation (RFT is to reflect the changes of price in the road transport market. Firstly, a price index model for RFT based on the sample data from Alibaba logistics platform is built. This model is a three levels index system including total index, classification index and individual index and the Laspeyres method is applied to calculate these indices. Finally, an empirical analysis of the price index for RFT market in Zhejiang Province is performed. In order to demonstrate the correctness and validity of the exponential model, a comparative analysis with port throughput and PMI index is carried out.

Testing of technology readiness index model based on exploratory factor analysis approach

Science.gov (United States)

Ariani, AF; Napitupulu, D.; Jati, RK; Kadar, JA; Syafrullah, M.

2018-04-01

SMEs readiness in using ICT will determine the adoption of ICT in the future. This study aims to evaluate the model of technology readiness in order to apply the technology on SMEs. The model is tested to find if TRI model is relevant to measure ICT adoption, especially for SMEs in Indonesia. The research method used in this paper is survey to a group of SMEs in South Tangerang. The survey measures the readiness to adopt ICT based on four variables which is Optimism, Innovativeness, Discomfort, and Insecurity. Each variable contains several indicators to make sure the variable is measured thoroughly. The data collected through survey is analysed using factor analysis methodwith the help of SPSS software. The result of this study shows that TRI model gives more descendants on some indicators and variables. This result can be caused by SMEs owners’ knowledge is not homogeneous about either the technology that they are used, knowledge or the type of their business.

Failure analysis and modeling of a multicomputer system. M.S. Thesis

Science.gov (United States)

Subramani, Sujatha Srinivasan

1990-01-01

This thesis describes the results of an extensive measurement-based analysis of real error data collected from a 7-machine DEC VaxCluster multicomputer system. In addition to evaluating basic system error and failure characteristics, we develop reward models to analyze the impact of failures and errors on the system. The results show that, although 98 percent of errors in the shared resources recover, they result in 48 percent of all system failures. The analysis of rewards shows that the expected reward rate for the VaxCluster decreases to 0.5 in 100 days for a 3 out of 7 model, which is well over a 100 times that for a 7-out-of-7 model. A comparison of the reward rates for a range of k-out-of-n models indicates that the maximum increase in reward rate (0.25) occurs in going from the 6-out-of-7 model to the 5-out-of-7 model. The analysis also shows that software errors have the lowest reward (0.2 vs. 0.91 for network errors). The large loss in reward rate for software errors is due to the fact that a large proportion (94 percent) of software errors lead to failure. In comparison, the high reward rate for network errors is due to fast recovery from a majority of these errors (median recovery duration is 0 seconds).

A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

Science.gov (United States)

Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

2018-06-01

Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.

TECHNICAL EFFICIENCY AND TECHNICAL LEVEL INDICATORS APPLICATION FOR CIVIL AIRCRAFT FUNCTIONAL PROPERTIES ANALYSIS

Directory of Open Access Journals (Sweden)

Vadim V. Efimov

2018-01-01

Full Text Available Functional properties characterize the purpose of the aircraft and are described by its flight performance characteristics such as range and cruising speed, payload, runway characteristics, etc. Functional properties also characterize the aircraft efficiency that determines the objective need for their analysis by both aircraft designers and operators in conditions of permanent and systematic efficiency increase necessity. When choosing the aircraft, it is important for the operator to make sure that a selected aircraft type has a high level of functional properties, which will allow it to provide high operational efficiency without obsolescence in the long term. However, when choosing from several aircraft types the operator has to face the fact that some characteristics of considered aircraft variants are better and the others are worse that does not allow to definitely determine what aircraft type has a higher level of functional properties.The possibility of applying technical efficiency indicators and a generalized technical level indicator for analyzing the functional properties of civil aviation aircraft is explored in this article. Fuel, weight and target efficiency values as well as the previously improved technical level indicator value were calculated for the different generations and modifications of Boeing 737 and Airbus A320 families of medium-range airplanes, which was followed by the results interpretation within one airplane generation and when moving historically from one airplane generation to another. According to analysis results it is concluded that it is impossible to define the change of the aircraft functional properties level by the change in the values of separate technical efficiency indicators. Thus, it is proposed to use a generalized technical level indicator that determines the level of aircraft technical perfection for purpose and to use efficiency indicators to analyze the cost of providing this level of

On the Paleostress Analysis Using Kinematic Indicators Found on an Oriented Core

Czech Academy of Sciences Publication Activity Database

Nováková, Lucie; Brož, Milan

2014-01-01

Roč. 2, č. 2 (2014), s. 76-83 ISSN 2331-9593 R&D Projects: GA MPO(CZ) FR-TI1/367 Institutional support: RVO:67985891 Keywords : paleostress analysis * borehole core * kinematic indicators * bias sampling * recent stress Subject RIV: DC - Siesmology, Volcanology, Earth Structure http://www.hrpub.org/download/20140105/UJG6-13901884.pdf

COMPARABLE ANALYSIS REGARDING KEY MACROECONOMIC INDICATORS ON MOLDOVA’S WAY TOWARDS EUROPEAN INTEGRATION

Directory of Open Access Journals (Sweden)

Valentina GANCIUCOV

2015-07-01

Full Text Available As Moldova has the purpose to enter the European Union the actual situation in the country is analyzed in this article. The article gives the comparative analysis of the basic parameters of Moldova with the other European Union country-members to define the ways of development of the country in the given direction. Since 1994 relations between Moldova and the European Union have developed on an upward trajectory. The dialogue between the two sides officially started that year with the signing of the Partnership and Cooperation Agreement (PCA, which entered into force in 1998 and provided the basis for cooperation with the EU in political, commercial, economic, legal, cultural fields. EU-Moldova relations have advanced to a higher level in 2009 when the country participated in the Eastern Partnership – an instrument of European policy that favored the signing on 29 May 2013 of the Association Agreement, the document which came to replace previous PCA and that is currently the most important element of the legal framework of Moldova-EU dialogue. But beyond the respective treaties signed, individually, between EU and states that intend to join the European community, there are a number of fundamental requirements3 (criteria, which condition the process of European integration of the state with declared intentions of accession. The aim of the research is to analyze to what extent Moldovan economy meet the requirements of economic alignment with EU standards, achieving a comparative analysis of the main relevant macroeconomic indicators. Research methodology. For analysis were used analysis-synthesis method, comparison method and others. Results of the analysis. Part of the criteria analyzed converge with EU requirements, while the most relevant indicators regarding standards of living show reserves show reserves for future improvement, such as the average wage, the lending rate, the exchange rate of the Moldovan Leu against the major international

Quantitative risk analysis using vulnerability indicators to assess food insecurity in the Niayes agricultural region of West Senegal

Directory of Open Access Journals (Sweden)

Mateugue Diack

2017-11-01

Full Text Available There is an increasing need to develop indicators of vulnerability and adaptive capacity to determine the robustness of response strategies over time and better understand the underlying processes. This study aimed to determine levels of risk of food insecurity using defined vulnerability indicators. For the purpose of this study, factors influencing food insecurity and different vulnerable indicators were examined using quantitative and qualitative research methods. Observations made on the physical environment (using tools for spatial analysis and socio-economic surveys conducted with local populations have quantified vulnerability indicators in the Niayes agricultural region. Application of the Classification and Regression Tree (CART model has enabled us to quantify the level of vulnerability of the zone. The results show that the decrease in agricultural surface areas is the most discriminant one in this study. The speed of reduction of the agricultural areas has specially increased between 2009 and 2014, with a loss of 65% of these areas. Therefore, a decision-making system, centred on the need for reinforcing the resilience of local populations, by preserving the agricultural vocation of the Niayes region and even in the Sahelian regions requires support and extension services for the farmers in order to promote sustainable agricultural practices.

A Real-Time Recording Model of Key Indicators for Energy Consumption and Carbon Emissions of Sustainable Buildings

Directory of Open Access Journals (Sweden)

Weiwei Wu

2014-05-01

Full Text Available Buildings’ sustainability is one of the crucial parts for achieving urban sustainability. Applied to buildings, life-cycle assessment encompasses the analysis and assessment of the environmental effects of building materials, components and assemblies throughout the entire life of the building construction, use and demolition. Estimate of carbon emissions is essential and crucial for an accurate and reasonable life-cycle assessment. Addressing the need for more research into integrating analysis of real-time and automatic recording of key indicators for a more accurate calculation and comparison, this paper aims to design a real-time recording model of these crucial indicators concerning the calculation and estimation of energy use and carbon emissions of buildings based on a Radio Frequency Identification (RFID-based system. The architecture of the RFID-based carbon emission recording/tracking system, which contains four functional layers including data record layer, data collection/update layer, data aggregation layer and data sharing/backup layer, is presented. Each of these layers is formed by RFID or network devices and sub-systems that operate at a specific level. In the end, a proof-of-concept system is developed to illustrate the implementation of the proposed architecture and demonstrate the feasibility of the design. This study would provide the technical solution for real-time recording system of building carbon emissions and thus is of great significance and importance to improve urban sustainability.

A Real-Time Recording Model of Key Indicators for Energy Consumption and Carbon Emissions of Sustainable Buildings

Science.gov (United States)

Wu, Weiwei; Yang, Huanjia; Chew, David; Hou, Yanhong; Li, Qiming

2014-01-01

Buildings' sustainability is one of the crucial parts for achieving urban sustainability. Applied to buildings, life-cycle assessment encompasses the analysis and assessment of the environmental effects of building materials, components and assemblies throughout the entire life of the building construction, use and demolition. Estimate of carbon emissions is essential and crucial for an accurate and reasonable life-cycle assessment. Addressing the need for more research into integrating analysis of real-time and automatic recording of key indicators for a more accurate calculation and comparison, this paper aims to design a real-time recording model of these crucial indicators concerning the calculation and estimation of energy use and carbon emissions of buildings based on a Radio Frequency Identification (RFID)-based system. The architecture of the RFID-based carbon emission recording/tracking system, which contains four functional layers including data record layer, data collection/update layer, data aggregation layer and data sharing/backup layer, is presented. Each of these layers is formed by RFID or network devices and sub-systems that operate at a specific level. In the end, a proof-of-concept system is developed to illustrate the implementation of the proposed architecture and demonstrate the feasibility of the design. This study would provide the technical solution for real-time recording system of building carbon emissions and thus is of great significance and importance to improve urban sustainability. PMID:24831109

Comparative study on DuPont analysis and DEA models for measuring stock performance using financial ratio

Science.gov (United States)

Arsad, Roslah; Shaari, Siti Nabilah Mohd; Isa, Zaidi

2017-11-01

Determining stock performance using financial ratio is challenging for many investors and researchers. Financial ratio can indicate the strengths and weaknesses of a company's stock performance. There are five categories of financial ratios namely liquidity, efficiency, leverage, profitability and market ratios. It is important to interpret the ratio correctly for proper financial decision making. The purpose of this study is to compare the performance of listed companies in Bursa Malaysia using Data Envelopment Analysis (DEA) and DuPont analysis Models. The study is conducted in 2015 involving 116 consumer products companies listed in Bursa Malaysia. The estimation method of Data Envelopment Analysis computes the efficiency scores and ranks the companies accordingly. The Alirezaee and Afsharian's method of analysis based Charnes, Cooper and Rhodes (CCR) where Constant Return to Scale (CRS) is employed. The DuPont analysis is a traditional tool for measuring the operating performance of companies. In this study, DuPont analysis is used to evaluate three different aspects such as profitability, efficiency of assets utilization and financial leverage. Return on Equity (ROE) is also calculated in DuPont analysis. This study finds that both analysis models provide different rankings of the selected samples. Hypothesis testing based on Pearson's correlation, indicates that there is no correlation between rankings produced by DEA and DuPont analysis. The DEA ranking model proposed by Alirezaee and Asharian is unstable. The method cannot provide complete ranking because the values of Balance Index is equal and zero.

Analysis of Social Variables when an Initial Functional Analysis Indicates Automatic Reinforcement as the Maintaining Variable for Self-Injurious Behavior

Science.gov (United States)

Kuhn, Stephanie A. Contrucci; Triggs, Mandy

2009-01-01

Self-injurious behavior (SIB) that occurs at high rates across all conditions of a functional analysis can suggest automatic or multiple functions. In the current study, we conducted a functional analysis for 1 individual with SIB. Results indicated that SIB was, at least in part, maintained by automatic reinforcement. Further analyses using…

Analysis of Urine as Indicators of Specific Body Conditions

Science.gov (United States)

Dey, Souradeep; Saha, Triya; Narendrakumar, Uttamchand

2017-11-01

Urinalysis can be defined as a procedure for examining various factors of urine, which include physical properties, particulate matter, cells, casts, crystals, organisms and solutes. Urinalysis is recommended to be a part of the initial examination of all patients as its cheap, feasible and gives productive results. This paper focuses on the analysis of urine collected at specific body conditions. Here we illustrate the urine profile of different persons having various body conditions, which include, having urinary tract infection, undergoing strenuous exercise, having back pain regularly, having very low urine output and a person who is on 24 hours of diet. Examination of urine collected from different persons having specific body conditions usually helps us in the diagnosis of various diseases, which it indicates.

Value Added Productivity Indicators: A Statistical Comparison of the Pre-Test/Post-Test Model and Gain Model.

Science.gov (United States)

Weerasinghe, Dash; Orsak, Timothy; Mendro, Robert

In an age of student accountability, public school systems must find procedures for identifying effective schools, classrooms, and teachers that help students continue to learn academically. As a result, researchers have been modeling schools and classrooms to calculate productivity indicators that will withstand not only statistical review but…

Sensitivity analysis of a modified energy model

International Nuclear Information System (INIS)

Suganthi, L.; Jagadeesan, T.R.

1997-01-01

Sensitivity analysis is carried out to validate model formulation. A modified model has been developed to predict the future energy requirement of coal, oil and electricity, considering price, income, technological and environmental factors. The impact and sensitivity of the independent variables on the dependent variable are analysed. The error distribution pattern in the modified model as compared to a conventional time series model indicated the absence of clusters. The residual plot of the modified model showed no distinct pattern of variation. The percentage variation of error in the conventional time series model for coal and oil ranges from -20% to +20%, while for electricity it ranges from -80% to +20%. However, in the case of the modified model the percentage variation in error is greatly reduced - for coal it ranges from -0.25% to +0.15%, for oil -0.6% to +0.6% and for electricity it ranges from -10% to +10%. The upper and lower limit consumption levels at 95% confidence is determined. The consumption at varying percentage changes in price and population are analysed. The gap between the modified model predictions at varying percentage changes in price and population over the years from 1990 to 2001 is found to be increasing. This is because of the increasing rate of energy consumption over the years and also the confidence level decreases as the projection is made far into the future. (author)

The Use Of Computational Human Performance Modeling As Task Analysis Tool

Energy Technology Data Exchange (ETDEWEB)

Jacuqes Hugo; David Gertman

2012-07-01

During a review of the Advanced Test Reactor safety basis at the Idaho National Laboratory, human factors engineers identified ergonomic and human reliability risks involving the inadvertent exposure of a fuel element to the air during manual fuel movement and inspection in the canal. There were clear indications that these risks increased the probability of human error and possible severe physical outcomes to the operator. In response to this concern, a detailed study was conducted to determine the probability of the inadvertent exposure of a fuel element. Due to practical and safety constraints, the task network analysis technique was employed to study the work procedures at the canal. Discrete-event simulation software was used to model the entire procedure as well as the salient physical attributes of the task environment, such as distances walked, the effect of dropped tools, the effect of hazardous body postures, and physical exertion due to strenuous tool handling. The model also allowed analysis of the effect of cognitive processes such as visual perception demands, auditory information and verbal communication. The model made it possible to obtain reliable predictions of operator performance and workload estimates. It was also found that operator workload as well as the probability of human error in the fuel inspection and transfer task were influenced by the concurrent nature of certain phases of the task and the associated demand on cognitive and physical resources. More importantly, it was possible to determine with reasonable accuracy the stages as well as physical locations in the fuel handling task where operators would be most at risk of losing their balance and falling into the canal. The model also provided sufficient information for a human reliability analysis that indicated that the postulated fuel exposure accident was less than credible.

Novel indexes based on network structure to indicate financial market

Science.gov (United States)

Zhong, Tao; Peng, Qinke; Wang, Xiao; Zhang, Jing

2016-02-01

There have been various achievements to understand and to analyze the financial market by complex network model. However, current studies analyze the financial network model but seldom present quantified indexes to indicate or forecast the price action of market. In this paper, the stock market is modeled as a dynamic network, in which the vertices refer to listed companies and edges refer to their rank-based correlation based on price series. Characteristics of the network are analyzed and then novel indexes are introduced into market analysis, which are calculated from maximum and fully-connected subnets. The indexes are compared with existing ones and the results confirm that our indexes perform better to indicate the daily trend of market composite index in advance. Via investment simulation, the performance of our indexes is analyzed in detail. The results indicate that the dynamic complex network model could not only serve as a structural description of the financial market, but also work to predict the market and guide investment by indexes.

Development of multiple performance indices and system parameter study for the design of a MEMS accelerometer

International Nuclear Information System (INIS)

Kim, Yong Il; Choi, Chan Kyu; Yoo, Hong Hee

2012-01-01

For the design of a MEMS accelerometer, proper performance indices should be defined and employed. Performance indices are obtained using either an experimental method or a numerical method. In the present study, a vibration analysis model of a MEMS accelerometer is introduced to calculate three performance indices: sensitivity, measurable acceleration range, and measurable frequency range. The accuracy of the vibration analysis model is first validated by comparing its modal and transient results with those of a commercial finite element code. Measurable acceleration and frequency ranges versus allowable errors for electrical and mechanical sensitivities are obtained and the effects of system parameter variations on the three performance indices are investigated

A critical examination of the validity of simplified models for radiant heat transfer analysis.

Science.gov (United States)

Toor, J. S.; Viskanta, R.

1972-01-01

Examination of the directional effects of the simplified models by comparing the experimental data with the predictions based on simple and more detailed models for the radiation characteristics of surfaces. Analytical results indicate that the constant property diffuse and specular models do not yield the upper and lower bounds on local radiant heat flux. In general, the constant property specular analysis yields higher values of irradiation than the constant property diffuse analysis. A diffuse surface in the enclosure appears to destroy the effect of specularity of the other surfaces. Semigray and gray analyses predict the irradiation reasonably well provided that the directional properties and the specularity of the surfaces are taken into account. The uniform and nonuniform radiosity diffuse models are in satisfactory agreement with each other.

Hypersonic - Model Analysis as a Service

DEFF Research Database (Denmark)

Acretoaie, Vlad; Störrle, Harald

2014-01-01

Hypersonic is a Cloud-based tool that proposes a new approach to the deployment of model analysis facilities. It is implemented as a RESTful Web service API o_ering analysis features such as model clone detection. This approach allows the migration of resource intensive analysis algorithms from...

The development and evaluation of programmatic performance indicators associated with maintenance at nuclear power plants

International Nuclear Information System (INIS)

Wreathall, J.; Fragola, J.; Appignani, P.; Burlile, G.; Shen, Y.

1990-05-01

This report summarizes the development and evaluation of programmatic performance indicators of maintenance. These indicators were selected by: (1) creating a formal framework of plant processes; (2) identifying features of plant behavior considered important to safety; (3) evaluating existing indicators against these features; and (4) performing statistical analyses for the selected indicators. The report recommends additional testing. This document provides the appendices to the report. These appendices are: synopsis of process model; detailed results of statistical analysis; and signal processing analysis of daily power loss indicator

Indications for colonoscopy An analysis based on indications and ...

African Journals Online (AJOL)

Four hundred and forty-eight procedures were included in the analysis, with rectal bleeding, polyp follow-up and iron deficiency anaemia producing the highest diagnostic yields of 69,1%, 53,3% and 47,7% respectively. Lower yields were obtained for cancer follow-up (21%), abdominal pain (38,2%) and abnormal bowel ...

Sensitivity analysis approaches applied to systems biology models.

Science.gov (United States)

Zi, Z

2011-11-01

With the rising application of systems biology, sensitivity analysis methods have been widely applied to study the biological systems, including metabolic networks, signalling pathways and genetic circuits. Sensitivity analysis can provide valuable insights about how robust the biological responses are with respect to the changes of biological parameters and which model inputs are the key factors that affect the model outputs. In addition, sensitivity analysis is valuable for guiding experimental analysis, model reduction and parameter estimation. Local and global sensitivity analysis approaches are the two types of sensitivity analysis that are commonly applied in systems biology. Local sensitivity analysis is a classic method that studies the impact of small perturbations on the model outputs. On the other hand, global sensitivity analysis approaches have been applied to understand how the model outputs are affected by large variations of the model input parameters. In this review, the author introduces the basic concepts of sensitivity analysis approaches applied to systems biology models. Moreover, the author discusses the advantages and disadvantages of different sensitivity analysis methods, how to choose a proper sensitivity analysis approach, the available sensitivity analysis tools for systems biology models and the caveats in the interpretation of sensitivity analysis results.

Bayesian sensitivity analysis of a 1D vascular model with Gaussian process emulators.

Science.gov (United States)

Melis, Alessandro; Clayton, Richard H; Marzo, Alberto

2017-12-01

One-dimensional models of the cardiovascular system can capture the physics of pulse waves but involve many parameters. Since these may vary among individuals, patient-specific models are difficult to construct. Sensitivity analysis can be used to rank model parameters by their effect on outputs and to quantify how uncertainty in parameters influences output uncertainty. This type of analysis is often conducted with a Monte Carlo method, where large numbers of model runs are used to assess input-output relations. The aim of this study was to demonstrate the computational efficiency of variance-based sensitivity analysis of 1D vascular models using Gaussian process emulators, compared to a standard Monte Carlo approach. The methodology was tested on four vascular networks of increasing complexity to analyse its scalability. The computational time needed to perform the sensitivity analysis with an emulator was reduced by the 99.96% compared to a Monte Carlo approach. Despite the reduced computational time, sensitivity indices obtained using the two approaches were comparable. The scalability study showed that the number of mechanistic simulations needed to train a Gaussian process for sensitivity analysis was of the order O(d), rather than O(d×103) needed for Monte Carlo analysis (where d is the number of parameters in the model). The efficiency of this approach, combined with capacity to estimate the impact of uncertain parameters on model outputs, will enable development of patient-specific models of the vascular system, and has the potential to produce results with clinical relevance. © 2017 The Authors International Journal for Numerical Methods in Biomedical Engineering Published by John Wiley & Sons Ltd.

A decision support model for identification and prioritization of key performance indicators in the logistics industry

OpenAIRE

Kucukaltan, Berk; Irani, Zahir; Aktas, Emel

2016-01-01

Performance measurement of logistics companies is based upon various performance indicators. Yet, in the logistics industry, there are several vaguenesses, such as deciding on key indicators and determining interrelationships between performance indicators. In order to resolve these vaguenesses, this paper first presents the stakeholder-informed Balanced Scorecard (BSC) model, by incorporating financial (e.g. cost) and non-financial (e.g. social media) performance indicators, with a comprehen...

Joint analysis of time-to-event and multiple binary indicators of latent classes

DEFF Research Database (Denmark)

Larsen, Klaus

2004-01-01

Multiple categorical variables are commonly used in medical and epidemiological research to measure specific aspects of human health and functioning. To analyze such data, models have been developed considering these categorical variables as imperfect indicators of an individual's "true" status o...

Indicators of safety culture - selection and utilization of leading safety performance indicators

Energy Technology Data Exchange (ETDEWEB)

Reiman, Teemu; Pietikaeinen, Elina (VTT, Technical Research Centre of Finland (Finland))

2010-03-15

Safety indicators play a role in providing information on organizational performance, motivating people to work on safety and increasing organizational potential for safety. The aim of this report is to provide an overview on leading safety indicators in the domain of nuclear safety. The report explains the distinction between lead and lag indicators and proposes a framework of three types of safety performance indicators - feedback, monitor and drive indicators. Finally the report provides guidance for nuclear energy organizations for selecting and interpreting safety indicators. It proposes the use of safety culture as a leading safety performance indicator and offers an example list of potential indicators in all three categories. The report concludes that monitor and drive indicators are so called lead indicators. Drive indicators are chosen priority areas of organizational safety activity. They are based on the underlying safety model and potential safety activities and safety policy derived from it. Drive indicators influence control measures that manage the socio technical system; change, maintain, reinforce, or reduce something. Monitor indicators provide a view on the dynamics of the system in question; the activities taking place, abilities, skills and motivation of the personnel, routines and practices - the organizational potential for safety. They also monitor the efficacy of the control measures that are used to manage the socio technical system. Typically the safety performance indicators that are used are lagging (feedback) indicators that measure the outcomes of the socio technical system. Besides feedback indicators, organizations should also acknowledge the important role of monitor and drive indicators in managing safety. The selection and use of safety performance indicators is always based on an understanding (a model) of the socio technical system and safety. The safety model defines what risks are perceived. It is important that the safety

Indicators of safety culture - selection and utilization of leading safety performance indicators

International Nuclear Information System (INIS)

Reiman, Teemu; Pietikaeinen, Elina

2010-03-01

Safety indicators play a role in providing information on organizational performance, motivating people to work on safety and increasing organizational potential for safety. The aim of this report is to provide an overview on leading safety indicators in the domain of nuclear safety. The report explains the distinction between lead and lag indicators and proposes a framework of three types of safety performance indicators - feedback, monitor and drive indicators. Finally the report provides guidance for nuclear energy organizations for selecting and interpreting safety indicators. It proposes the use of safety culture as a leading safety performance indicator and offers an example list of potential indicators in all three categories. The report concludes that monitor and drive indicators are so called lead indicators. Drive indicators are chosen priority areas of organizational safety activity. They are based on the underlying safety model and potential safety activities and safety policy derived from it. Drive indicators influence control measures that manage the socio technical system; change, maintain, reinforce, or reduce something. Monitor indicators provide a view on the dynamics of the system in question; the activities taking place, abilities, skills and motivation of the personnel, routines and practices - the organizational potential for safety. They also monitor the efficacy of the control measures that are used to manage the socio technical system. Typically the safety performance indicators that are used are lagging (feedback) indicators that measure the outcomes of the socio technical system. Besides feedback indicators, organizations should also acknowledge the important role of monitor and drive indicators in managing safety. The selection and use of safety performance indicators is always based on an understanding (a model) of the socio technical system and safety. The safety model defines what risks are perceived. It is important that the safety

Sources of energy productivity change in China during 1997–2012: A decomposition analysis based on the Luenberger productivity indicator

International Nuclear Information System (INIS)

Wang, Ke; Wei, Yi-Ming

2016-01-01

Given that different energy inputs play different roles in production and that energy policy decision making requires an evaluation of productivity change in individual energy input to provide insight into the scope for improvement of the utilization of specific energy input, this study develops, based on the Luenberger productivity indicator and data envelopment analysis models, an aggregated specific energy productivity indicator combining the individual energy input productivity indicators that account for the contributions of each specific energy input toward energy productivity change. In addition, these indicators can be further decomposed into four factors: pure efficiency change, scale efficiency change, pure technology change, and scale of technology change. These decompositions enable a determination of which specific energy input is the driving force of energy productivity change and which of the four factors is the primary contributor of energy productivity change. An empirical analysis of China's energy productivity change over the period 1997–2012 indicates that (i) China's energy productivity growth may be overestimated if energy consumption structure is omitted; (ii) in regard to the contribution of specific energy input toward energy productivity growth, oil and electricity show positive contributions, but coal and natural gas show negative contributions; (iii) energy-specific productivity changes are mainly caused by technical changes rather than efficiency changes; and (iv) the Porter Hypothesis is partially supported in China that carbon emissions control regulations may lead to energy productivity growth. - Highlights: • An energy input specific Luenberger productivity indicator is proposed. • It enables to examine the contribution of specific energy input productivity change. • It can be decomposed for identifying pure and scale efficiency changes, as well as pure and scale technical changes. • China's energy productivity growth may

Performance of technical indicators in forecasting high-frequency foreign exchange rates

Directory of Open Access Journals (Sweden)

Václav Mastný

2004-01-01

Full Text Available This paper deals with technical analysis and its forecasting ability in the intradaily foreign exchange market. The objective of this study is to investigate whether technical indicators are able to provide prediction superior to „buy and hold“ strategy. Each indicator is tested with series of parameters in time series of different frequency (5, 15, 30, 60 min. The profitability of each indicator is examined in simple trading modell.

The effect of measurement quality on targeted structural model fit indices: A comment on Lance, Beck, Fan, and Carter (2016).

Science.gov (United States)

McNeish, Daniel; Hancock, Gregory R

2018-03-01

Lance, Beck, Fan, and Carter (2016) recently advanced 6 new fit indices and associated cutoff values for assessing data-model fit in the structural portion of traditional latent variable path models. The authors appropriately argued that, although most researchers' theoretical interest rests with the latent structure, they still rely on indices of global model fit that simultaneously assess both the measurement and structural portions of the model. As such, Lance et al. proposed indices intended to assess the structural portion of the model in isolation of the measurement model. Unfortunately, although these strategies separate the assessment of the structure from the fit of the measurement model, they do not isolate the structure's assessment from the quality of the measurement model. That is, even with a perfectly fitting measurement model, poorer quality (i.e., less reliable) measurements will yield a more favorable verdict regarding structural fit, whereas better quality (i.e., more reliable) measurements will yield a less favorable structural assessment. This phenomenon, referred to by Hancock and Mueller (2011) as the reliability paradox, affects not only traditional global fit indices but also those structural indices proposed by Lance et al. as well. Fortunately, as this comment will clarify, indices proposed by Hancock and Mueller help to mitigate this problem and allow the structural portion of the model to be assessed independently of both the fit of the measurement model as well as the quality of indicator variables contained therein. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Evidence-based practice: a quality indicator analysis of peer-tutoring in adapted physical education.

Science.gov (United States)

Kalef, Laura; Reid, Greg; Macdonald, Cathy

2013-09-01

The purpose of the research was to conduct a quality indicator analysis of studies investigating peer-tutoring for students with a disability in adapted physical education. An electronic search was conducted among English journals published from 1960 to November 2012. Databases included ERIC, PsycINFO, and SPORTDiscus. Fifteen research studies employing group-experimental (Gersten et al., 2005) or single-subject designs (Horner et al., 2005) met inclusion criteria. Each study was assessed for the presence and clarity of quality indicators. Group designs met an average of 62.5% essential and 69% desirable indicators. An average of 80% of indicators was present for single-subject designs. Results suggest claims of peer-tutoring being an evidence-based practice are premature. Recommendations for clarifying and applying the quality indicators are offered. Copyright © 2013 Elsevier Ltd. All rights reserved.

Statistical Modelling of Wind Proles - Data Analysis and Modelling

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre

The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles.......The aim of the analysis presented in this document is to investigate whether statistical models can be used to make very short-term predictions of wind profiles....

Effective Solar Indices for Ionospheric Modeling: A Review and a Proposal for a Real-Time Regional IRI

Science.gov (United States)

Pignalberi, A.; Pezzopane, M.; Rizzi, R.; Galkin, I.

2018-01-01

The first part of this paper reviews methods using effective solar indices to update a background ionospheric model focusing on those employing the Kriging method to perform the spatial interpolation. Then, it proposes a method to update the International Reference Ionosphere (IRI) model through the assimilation of data collected by a European ionosonde network. The method, called International Reference Ionosphere UPdate (IRI UP), that can potentially operate in real time, is mathematically described and validated for the period 9-25 March 2015 (a time window including the well-known St. Patrick storm occurred on 17 March), using IRI and IRI Real Time Assimilative Model (IRTAM) models as the reference. It relies on foF2 and M(3000)F2 ionospheric characteristics, recorded routinely by a network of 12 European ionosonde stations, which are used to calculate for each station effective values of IRI indices IG_{12} and R_{12} (identified as IG_{{12{eff}}} and R_{{12{eff}}}); then, starting from this discrete dataset of values, two-dimensional (2D) maps of IG_{{12{eff}}} and R_{{12{eff}}} are generated through the universal Kriging method. Five variogram models are proposed and tested statistically to select the best performer for each effective index. Then, computed maps of IG_{{12{eff}}} and R_{{12{eff}}} are used in the IRI model to synthesize updated values of foF2 and hmF2. To evaluate the ability of the proposed method to reproduce rapid local changes that are common under disturbed conditions, quality metrics are calculated for two test stations whose measurements were not assimilated in IRI UP, Fairford (51.7°N, 1.5°W) and San Vito (40.6°N, 17.8°E), for IRI, IRI UP, and IRTAM models. The proposed method turns out to be very effective under highly disturbed conditions, with significant improvements of the foF2 representation and noticeable improvements of the hmF2 one. Important improvements have been verified also for quiet and moderately disturbed

Cause-effect analysis: improvement of a first year engineering students' calculus teaching model

Science.gov (United States)

van der Hoff, Quay; Harding, Ansie

2017-01-01

This study focuses on the mathematics department at a South African university and in particular on teaching of calculus to first year engineering students. The paper reports on a cause-effect analysis, often used for business improvement. The cause-effect analysis indicates that there are many factors that impact on secondary school teaching of mathematics, factors that the tertiary sector has no control over. The analysis also indicates the undesirable issues that are at the root of impeding success in the calculus module. Most important is that students are not encouraged to become independent thinkers from an early age. This triggers problems in follow-up courses where students are expected to have learned to deal with the work load and understanding of certain concepts. A new model was designed to lessen the impact of these undesirable issues.

Analytic network process model for sustainable lean and green manufacturing performance indicator

Science.gov (United States)

Aminuddin, Adam Shariff Adli; Nawawi, Mohd Kamal Mohd; Mohamed, Nik Mohd Zuki Nik

2014-09-01

Sustainable manufacturing is regarded as the most complex manufacturing paradigm to date as it holds the widest scope of requirements. In addition, its three major pillars of economic, environment and society though distinct, have some overlapping among each of its elements. Even though the concept of sustainability is not new, the development of the performance indicator still needs a lot of improvement due to its multifaceted nature, which requires integrated approach to solve the problem. This paper proposed the best combination of criteria en route a robust sustainable manufacturing performance indicator formation via Analytic Network Process (ANP). The integrated lean, green and sustainable ANP model can be used to comprehend the complex decision system of the sustainability assessment. The finding shows that green manufacturing is more sustainable than lean manufacturing. It also illustrates that procurement practice is the most important criteria in the sustainable manufacturing performance indicator.

Stochastic modeling analysis and simulation

CERN Document Server

Nelson, Barry L

1995-01-01

A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Suitable for advanced undergraduates and graduate-level industrial engineers and management science majors, it proposes modeling systems in terms of their simulation, regardless of whether simulation is employed for analysis. Beginning with a view of the conditions that permit a mathematical-numerical analysis, the text explores Poisson and renewal processes, Markov chains in discrete and continuous time, se

The integrated indicator of sustainable urban development based on standardization

Directory of Open Access Journals (Sweden)

Leonova Tatiana

2018-01-01

Full Text Available The paper justifies the necessity for the system of planned indicators for sustainable urban development design in accordance with the requirements of international standards and the Russian standard GOST R ISO 37120-2015, and the estimation of their actual achievement based on complex qualimetric models. An analysis of opinions on this issue and an overview of Russian normative documents for assessing the effectiveness of the municipalities, including urban development are presented. General methodological principles and sequence for the construction of qualimetric models, as well as formulas for the calculation of complex indicators, taking into account the specific weights obtained on the basis of expert assessment, are presented, the need for careful selection of experts and determination of the consistency of expert opinions is indicated. The advantages and disadvantages of this approach are shown. Conclusions are drawn on the use of qualimetric models for sustainable urban development.

Toward a Progress Indicator for Machine Learning Model Building and Data Mining Algorithm Execution: A Position Paper

Science.gov (United States)

Luo, Gang

2017-01-01

For user-friendliness, many software systems offer progress indicators for long-duration tasks. A typical progress indicator continuously estimates the remaining task execution time as well as the portion of the task that has been finished. Building a machine learning model often takes a long time, but no existing machine learning software supplies a non-trivial progress indicator. Similarly, running a data mining algorithm often takes a long time, but no existing data mining software provides a nontrivial progress indicator. In this article, we consider the problem of offering progress indicators for machine learning model building and data mining algorithm execution. We discuss the goals and challenges intrinsic to this problem. Then we describe an initial framework for implementing such progress indicators and two advanced, potential uses of them, with the goal of inspiring future research on this topic. PMID:29177022

Sensitivity analysis of complex models: Coping with dynamic and static inputs

International Nuclear Information System (INIS)

Anstett-Collin, F.; Goffart, J.; Mara, T.; Denis-Vidal, L.

2015-01-01

In this paper, we address the issue of conducting a sensitivity analysis of complex models with both static and dynamic uncertain inputs. While several approaches have been proposed to compute the sensitivity indices of the static inputs (i.e. parameters), the one of the dynamic inputs (i.e. stochastic fields) have been rarely addressed. For this purpose, we first treat each dynamic as a Gaussian process. Then, the truncated Karhunen–Loève expansion of each dynamic input is performed. Such an expansion allows to generate independent Gaussian processes from a finite number of independent random variables. Given that a dynamic input is represented by a finite number of random variables, its variance-based sensitivity index is defined by the sensitivity index of this group of variables. Besides, an efficient sampling-based strategy is described to estimate the first-order indices of all the input factors by only using two input samples. The approach is applied to a building energy model, in order to assess the impact of the uncertainties of the material properties (static inputs) and the weather data (dynamic inputs) on the energy performance of a real low energy consumption house. - Highlights: • Sensitivity analysis of models with uncertain static and dynamic inputs is performed. • Karhunen–Loève (KL) decomposition of the spatio/temporal inputs is performed. • The influence of the dynamic inputs is studied through the modes of the KL expansion. • The proposed approach is applied to a building energy model. • Impact of weather data and material properties on performance of real house is given

Network based early warning indicators of vegetation changes in a land–atmosphere model

NARCIS (Netherlands)

Yin, Z.; Dekker, S.C.; Rietkerk, M.; Hurk, B.J.J.M. van den; Dijkstra, H.A.

2016-01-01

Abstract Numerous model studies demonstrate that ecosystems might not shift smoothly with a gradual change in resource concentration. At specific points, vegetation can suddenly shift from one stable state to another. To predict such undesirable shifts, statistical indicators are proposed for early

Validation Analysis of the Shoal Groundwater Flow and Transport Model

Energy Technology Data Exchange (ETDEWEB)

A. Hassan; J. Chapman

2008-11-01

groundwater withdrawal activities in the area. The conceptual and numerical models were developed based upon regional hydrogeologic investigations conducted in the 1960s, site characterization investigations (including ten wells and various geophysical and geologic studies) at Shoal itself prior to and immediately after the test, and two site characterization campaigns in the 1990s for environmental restoration purposes (including eight wells and a year-long tracer test). The new wells are denoted MV-1, MV-2, and MV-3, and are located to the northnortheast of the nuclear test. The groundwater model was generally lacking data in the north-northeastern area; only HC-1 and the abandoned PM-2 wells existed in this area. The wells provide data on fracture orientation and frequency, water levels, hydraulic conductivity, and water chemistry for comparison with the groundwater model. A total of 12 real-number validation targets were available for the validation analysis, including five values of hydraulic head, three hydraulic conductivity measurements, three hydraulic gradient values, and one angle value for the lateral gradient in radians. In addition, the fracture dip and orientation data provide comparisons to the distributions used in the model and radiochemistry is available for comparison to model output. Goodness-of-fit analysis indicates that some of the model realizations correspond well with the newly acquired conductivity, head, and gradient data, while others do not. Other tests indicated that additional model realizations may be needed to test if the model input distributions need refinement to improve model performance. This approach (generating additional realizations) was not followed because it was realized that there was a temporal component to the data disconnect: the new head measurements are on the high side of the model distributions, but the heads at the original calibration locations themselves have also increased over time. This indicates that the steady

Bayesian Geostatistical Modeling of Malaria Indicator Survey Data in Angola

Science.gov (United States)

Gosoniu, Laura; Veta, Andre Mia; Vounatsou, Penelope

2010-01-01

The 2006–2007 Angola Malaria Indicator Survey (AMIS) is the first nationally representative household survey in the country assessing coverage of the key malaria control interventions and measuring malaria-related burden among children under 5 years of age. In this paper, the Angolan MIS data were analyzed to produce the first smooth map of parasitaemia prevalence based on contemporary nationwide empirical data in the country. Bayesian geostatistical models were fitted to assess the effect of interventions after adjusting for environmental, climatic and socio-economic factors. Non-linear relationships between parasitaemia risk and environmental predictors were modeled by categorizing the covariates and by employing two non-parametric approaches, the B-splines and the P-splines. The results of the model validation showed that the categorical model was able to better capture the relationship between parasitaemia prevalence and the environmental factors. Model fit and prediction were handled within a Bayesian framework using Markov chain Monte Carlo (MCMC) simulations. Combining estimates of parasitaemia prevalence with the number of children under we obtained estimates of the number of infected children in the country. The population-adjusted prevalence ranges from in Namibe province to in Malanje province. The odds of parasitaemia in children living in a household with at least ITNs per person was by 41% lower (CI: 14%, 60%) than in those with fewer ITNs. The estimates of the number of parasitaemic children produced in this paper are important for planning and implementing malaria control interventions and for monitoring the impact of prevention and control activities. PMID:20351775

Shelf-life modeling of bakery products by using oxidation indices.

Science.gov (United States)

Calligaris, Sonia; Manzocco, Lara; Kravina, Giuditta; Nicoli, Maria Cristina

2007-03-07

The aim of this work was to develop a shelf-life prediction model of lipid-containing bakery products. To this purpose (i) the temperature dependence of the oxidation rate of bakery products was modeled, taking into account the changes in lipid physical state; (ii) the acceptance limits were assessed by sensory analysis; and (iii) the relationship between chemical oxidation index and acceptance limit was evaluated. Results highlight that the peroxide number, the changes of which are linearly related to consumer acceptability, is a representative index of the quality depletion of biscuits during their shelf life. In addition, the evolution of peroxides can be predicted by a modified Arrhenius equation accounting for the changes in the physical state of biscuit fat. Knowledge of the relationship between peroxides and sensory acceptability together with the temperature dependence of peroxide formation allows a mathematical model to be set up to simply and quickly calculate the shelf life of biscuits.

Geological-structural models used in SR 97. Uncertainty analysis

Energy Technology Data Exchange (ETDEWEB)

Saksa, P.; Nummela, J. [FINTACT Oy (Finland)

1998-10-01

The uncertainty of geological-structural models was studied for the three sites in SR 97, called Aberg, Beberg and Ceberg. The evaluation covered both regional and site scale models, the emphasis being placed on fracture zones in the site scale. Uncertainty is a natural feature of all geoscientific investigations. It originates from measurements (errors in data, sampling limitations, scale variation) and conceptualisation (structural geometries and properties, ambiguous geometric or parametric solutions) to name the major ones. The structures of A-, B- and Ceberg are fracture zones of varying types. No major differences in the conceptualisation between the sites were noted. One source of uncertainty in the site models is the non-existence of fracture and zone information in the scale from 10 to 300 - 1000 m. At Aberg the development of the regional model has been performed very thoroughly. At the site scale one major source of uncertainty is that a clear definition of the target area is missing. Structures encountered in the boreholes are well explained and an interdisciplinary approach in interpretation have taken place. Beberg and Ceberg regional models contain relatively large uncertainties due to the investigation methodology and experience available at that time. In site scale six additional structures were proposed both to Beberg and Ceberg to variant analysis of these sites. Both sites include uncertainty in the form of many non-interpreted fractured sections along the boreholes. Statistical analysis gives high occurrences of structures for all three sites: typically 20 - 30 structures/km{sup 3}. Aberg has highest structural frequency, Beberg comes next and Ceberg has the lowest. The borehole configuration, orientations and surveying goals were inspected to find whether preferences or factors causing bias were present. Data from Aberg supports the conclusion that Aespoe sub volume would be an anomalously fractured, tectonised unit of its own. This means that

Geological-structural models used in SR 97. Uncertainty analysis

International Nuclear Information System (INIS)

Saksa, P.; Nummela, J.

1998-10-01

The uncertainty of geological-structural models was studied for the three sites in SR 97, called Aberg, Beberg and Ceberg. The evaluation covered both regional and site scale models, the emphasis being placed on fracture zones in the site scale. Uncertainty is a natural feature of all geoscientific investigations. It originates from measurements (errors in data, sampling limitations, scale variation) and conceptualisation (structural geometries and properties, ambiguous geometric or parametric solutions) to name the major ones. The structures of A-, B- and Ceberg are fracture zones of varying types. No major differences in the conceptualisation between the sites were noted. One source of uncertainty in the site models is the non-existence of fracture and zone information in the scale from 10 to 300 - 1000 m. At Aberg the development of the regional model has been performed very thoroughly. At the site scale one major source of uncertainty is that a clear definition of the target area is missing. Structures encountered in the boreholes are well explained and an interdisciplinary approach in interpretation have taken place. Beberg and Ceberg regional models contain relatively large uncertainties due to the investigation methodology and experience available at that time. In site scale six additional structures were proposed both to Beberg and Ceberg to variant analysis of these sites. Both sites include uncertainty in the form of many non-interpreted fractured sections along the boreholes. Statistical analysis gives high occurrences of structures for all three sites: typically 20 - 30 structures/km 3 . Aberg has highest structural frequency, Beberg comes next and Ceberg has the lowest. The borehole configuration, orientations and surveying goals were inspected to find whether preferences or factors causing bias were present. Data from Aberg supports the conclusion that Aespoe sub volume would be an anomalously fractured, tectonised unit of its own. This means that the

Waste indicators

Energy Technology Data Exchange (ETDEWEB)

Dall, O.; Lassen, C.; Hansen, E. [Cowi A/S, Lyngby (Denmark)

2003-07-01

The Waste Indicator Project focuses on methods to evaluate the efficiency of waste management. The project proposes the use of three indicators for resource consumption, primary energy and landfill requirements, based on the life-cycle principles applied in the EDIP Project. Trial runs are made With the indicators on paper, glass packaging and aluminium, and two models are identified for mapping the Danish waste management, of which the least extensive focuses on real and potential savings. (au)

Waste indicators

International Nuclear Information System (INIS)

Dall, O.; Lassen, C.; Hansen, E.

2003-01-01

The Waste Indicator Project focuses on methods to evaluate the efficiency of waste management. The project proposes the use of three indicators for resource consumption, primary energy and landfill requirements, based on the life-cycle principles applied in the EDIP Project. Trial runs are made With the indicators on paper, glass packaging and aluminium, and two models are identified for mapping the Danish waste management, of which the least extensive focuses on real and potential savings. (au)

Bioclimatic indices based on the menex model example on Banja Luka

OpenAIRE

Pecelj Milica

2013-01-01

It has long been known that weather and climate have influence on human health and well-being. The human organism is in constant interaction with the environmental conditions. To access the atmospheric impact on humans, different methods in human bioclimatology are created. Most of them are based on human heat balance. In this paper it has been tried to present several bioclimatic indices based on the human heat balance according to the bioclimatic model menex (man-environment exchange)...

An indicator for ecosystem externalities in fishing

DEFF Research Database (Denmark)

Ravn-Jonsen, Lars; Andersen, Ken Haste; Vestergaard, Niels

2016-01-01

Ecosystem externalities arise when one use of an ecosystem affects its other uses through the production functions of the ecosystem. We use simulations with a size-spectrum ecosystem model to investigate the ecosystem externality created by fishing of multiple species. The model is based upon...... general ecological principles and is calibrated to the North Sea. Two fleets are considered: a "forage fish" fleet targeting species that mature at small sizes and a "large fish" fleet targeting large piscivorous species. Based on the marginal analysis of the present value of the rent, we develop...... a benefit indicator that explicitly divides the consequences of fishing into internal and external benefits. This analysis demonstrates that the forage fish fleet has a notable economic impact on the large fish fleet, but the reverse is not true. The impact can be either negative or positive, which entails...

The use of physical indicators for industrial energy demand scenarios

International Nuclear Information System (INIS)

Schenk, Niels J.; Moll, Henri C.

2007-01-01

Scientific information on the size and nature of the threat of climate change is needed by politicians in order to weight their decisions. Computerised models are extremely useful tools to quantify the long-term effects of current policies. This paper describes a new modelling approach that allows formulation of industrial energy demand projections consistent with the assumptions for scenario drivers such as GDP and population. In the model, a level of industrial production is used as a key variable, and we define it in physical units, rather than in monetary units. The aim of this research is to increase insights that come with long-term energy demand scenarios. This research clearly shows that physical indicators provide additional insights in scenario analysis. The use of physical indicators instead of monetary indicators seems to affect the energy scenarios significantly. The differences with monetary indicators are larger in developing regions than in OECD regions. We conclude that an integrated energy and materials approach reveals developments that are hardly visible using a monetary approach. Moreover, this research shows the potential and benefits of the use of physical indicators for scenario development. (author)

A thermodynamic analysis of the environmental indicators of natural gas combustion processes

Science.gov (United States)

Elsukov, V. K.

2010-07-01

Environmental indicators of the natural gas combustion process are studied using the model of extreme intermediate states developed at the Melent’ev Institute of Power Engineering Systems. Technological factors responsible for generation of polycyclic aromatic hydrocarbons and hydrogen cyanide are revealed. Measures for reducing the amounts of polycyclic aromatic hydrocarbons, hydrogen cyanide, nitrogen oxide, and other pollutants emitted from boilers are developed.

Preliminary analysis on hybrid Box-Jenkins - GARCH modeling in forecasting gold price

Science.gov (United States)

Yaziz, Siti Roslindar; Azizan, Noor Azlinna; Ahmad, Maizah Hura; Zakaria, Roslinazairimah; Agrawal, Manju; Boland, John

2015-02-01

Gold has been regarded as a valuable precious metal and the most popular commodity as a healthy return investment. Hence, the analysis and prediction of gold price become very significant to investors. This study is a preliminary analysis on gold price and its volatility that focuses on the performance of hybrid Box-Jenkins models together with GARCH in analyzing and forecasting gold price. The Box-Cox formula is used as the data transformation method due to its potential best practice in normalizing data, stabilizing variance and reduces heteroscedasticity using 41-year daily gold price data series starting 2nd January 1973. Our study indicates that the proposed hybrid model ARIMA-GARCH with t-innovation can be a new potential approach in forecasting gold price. This finding proves the strength of GARCH in handling volatility in the gold price as well as overcomes the non-linear limitation in the Box-Jenkins modeling.

A new estimator for sensitivity analysis of model output: An application to the e-business readiness composite indicator

International Nuclear Information System (INIS)

Tarantola, Stefano; Nardo, Michela; Saisana, Michaela; Gatelli, Debora

2006-01-01

In this paper we propose and test a generalisation of the method originally proposed by Sobol', and recently extended by Saltelli, to estimate the first-order and total effect sensitivity indices. Exploiting the symmetries and the dualities of the formulas, we obtain additional estimates of first-order and total indices at no extra computational cost. We test the technique on a case study involving the construction of a composite indicator of e-business readiness, which is part of the initiative 'e-Readiness of European enterprises' of the European Commission 'e-Europe 2005' action plan. The method is used to assess the contribution of uncertainties in (a) the weights of the component indicators and (b) the imputation of missing data on the composite indicator values for several European countries

A new estimator for sensitivity analysis of model output: An application to the e-business readiness composite indicator

Energy Technology Data Exchange (ETDEWEB)

Tarantola, Stefano [European Commission , Joint Research Centre, Institute for the Protection and Security of the Citizen, Applied Statistics Group, TP 361, Via E. Fermi, 1, Ispra (Vatican City State, Holy See,), 21020 (Italy)]. E-mail: stefano.tarantola@jrc.it; Nardo, Michela [European Commission, Joint Research Centre, Institute for the Protection and Security of the Citizen, Applied Statistics Group, TP 361, Via E. Fermi, 1, Ispra (VA), 21020 (Italy); Saisana, Michaela [European Commission , Joint Research Centre, Institute for the Protection and Security of the Citizen, Applied Statistics Group, TP 361, Via E. Fermi, 1, Ispra (VA), 21020 (Italy); Gatelli, Debora [European Commission , Joint Research Centre, Institute for the Protection and Security of the Citizen, Applied Statistics Group, TP 361, Via E. Fermi, 1, Ispra (VA), 21020 (Italy)

2006-10-15

In this paper we propose and test a generalisation of the method originally proposed by Sobol', and recently extended by Saltelli, to estimate the first-order and total effect sensitivity indices. Exploiting the symmetries and the dualities of the formulas, we obtain additional estimates of first-order and total indices at no extra computational cost. We test the technique on a case study involving the construction of a composite indicator of e-business readiness, which is part of the initiative 'e-Readiness of European enterprises' of the European Commission 'e-Europe 2005' action plan. The method is used to assess the contribution of uncertainties in (a) the weights of the component indicators and (b) the imputation of missing data on the composite indicator values for several European countries.

THE STUDY OF THE CHARACTERIZATION INDICES OF FABRICS BY PRINCIPAL COMPONENT ANALYSIS METHOD

Directory of Open Access Journals (Sweden)

HRISTIAN Liliana

2017-05-01

Full Text Available The paper was pursued to prioritize the worsted fabrics type, for the manufacture of outerwear products by characterization indeces of fabrics, using the mathematical model of Principal Component Analysis (PCA. There are a number of variables with a certain influence on the quality of fabrics, but some of these variables are more important than others, so it is useful to identify those variables to a better understanding the factors which can lead the improving of the fabrics quality. A solution to this problem can be the application of a method of factorial analysis, the so-called Principal Component Analysis, with the final goal of establishing and analyzing those variables which influence in a significant manner the internal structure of combed wool fabrics according to armire type. By applying PCA it is obtained a small number of the linear combinations (principal components from a set of variables, describing the internal structure of the fabrics, which can hold as much information as possible from the original variables. Data analysis is an important initial step in decision making, allowing identification of the causes that lead to a decision- making situations. Thus it is the action of transforming the initial data in order to extract useful information and to facilitate reaching the conclusions. The process of data analysis can be defined as a sequence of steps aimed at formulating hypotheses, collecting primary information and validation, the construction of the mathematical model describing this phenomenon and reaching these conclusions about the behavior of this model.

Modeling technical change in energy system analysis: analyzing the introduction of learning-by-doing in bottom-up energy models

International Nuclear Information System (INIS)

Berglund, Christer; Soederholm, Patrik

2006-01-01

The main objective of this paper is to provide an overview and a critical analysis of the recent literature on incorporating induced technical change in energy systems models. Special emphasis is put on surveying recent studies aimed at integrating learning-by-doing into bottom-up energy systems models through so-called learning curves, and on analyzing the relevance of learning curve analysis for understanding the process of innovation and technology diffusion in the energy sector. The survey indicates that this model work represents a major advance in energy research, and embeds important policy implications, not the least concerning the cost and the timing of environmental policies (including carbon emission constraints). However, bottom-up energy models with endogenous learning are also limited in their characterization of technology diffusion and innovation. While they provide a detailed account of technical options-which is absent in many top-down models-they also lack important aspects of diffusion behavior that are captured in top-down representations. For instance, they often fail in capturing strategic technology diffusion behavior in the energy sector as well as the energy sector's endogenous responses to policy, and they neglect important general equilibrium impacts (such as the opportunity cost of redirecting R and D support to the energy sector). Some suggestions on how innovation and diffusion modeling in bottom-up analysis can be improved are put forward

Prediction of Agriculture Drought Using Support Vector Regression Incorporating with Climatology Indices

Science.gov (United States)

Tian, Y.; Xu, Y. P.

2017-12-01

In this paper, the Support Vector Regression (SVR) model incorporating climate indices and drought indices are developed to predict agriculture drought in Xiangjiang River basin, Central China. The agriculture droughts are presented with the Precipitation-Evapotranspiration Index (SPEI). According to the analysis of the relationship between SPEI with different time scales and soil moisture, it is found that SPEI of six months time scales (SPEI-6) could reflect the soil moisture better than that of three and one month time scale from the drought features including drought duration, severity and peak. Climate forcing like El Niño Southern Oscillation and western Pacific subtropical high (WPSH) are represented by climate indices such as MEI and series indices of WPSH. Ridge Point of WPSH is found to be the key factor that influences the agriculture drought mainly through the control of temperature. Based on the climate indices analysis, the predictions of SPEI-6 are conducted using the SVR model. The results show that the SVR model incorperating climate indices, especially ridge point of WPSH, could improve the prediction accuracy compared to that using drought index only. The improvement was more significant for the prediction of one month lead time than that of three months lead time. However, it needs to be cautious in selection of the input parameters, since adding more useless information could have a counter effect in attaining a better prediction.

Scaling Analysis of Author-Level Bibliometric Indicators

DEFF Research Database (Denmark)

Wildgaard, Lorna Elizabeth; Larsen, Birger

2014-01-01

Despite of the concerns from the bibliometric community, evaluation of the individual through bibliometric indices is already performed as a form of ‘pseudo peer review’ in selection of candidates for tenure, in background checks of potential employees’ publicationand citation impact, and in appr......Despite of the concerns from the bibliometric community, evaluation of the individual through bibliometric indices is already performed as a form of ‘pseudo peer review’ in selection of candidates for tenure, in background checks of potential employees’ publicationand citation impact......, and in appraisal of funding applications. We investigate the role of central and isolated indicators in the fields of Astronomy, Environmental Science, Philosophy and Public Health and the effect these have on author-rankings....

[Model-based biofuels system analysis: a review].

Science.gov (United States)

Chang, Shiyan; Zhang, Xiliang; Zhao, Lili; Ou, Xunmin

2011-03-01

Model-based system analysis is an important tool for evaluating the potential and impacts of biofuels, and for drafting biofuels technology roadmaps and targets. The broad reach of the biofuels supply chain requires that biofuels system analyses span a range of disciplines, including agriculture/forestry, energy, economics, and the environment. Here we reviewed various models developed for or applied to modeling biofuels, and presented a critical analysis of Agriculture/Forestry System Models, Energy System Models, Integrated Assessment Models, Micro-level Cost, Energy and Emission Calculation Models, and Specific Macro-level Biofuel Models. We focused on the models' strengths, weaknesses, and applicability, facilitating the selection of a suitable type of model for specific issues. Such an analysis was a prerequisite for future biofuels system modeling, and represented a valuable resource for researchers and policy makers.