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Sample records for model selection process

  1. IT vendor selection model by using structural equation model & analytical hierarchy process

    Science.gov (United States)

    Maitra, Sarit; Dominic, P. D. D.

    2012-11-01

    Selecting and evaluating the right vendors is imperative for an organization's global marketplace competitiveness. Improper selection and evaluation of potential vendors can dwarf an organization's supply chain performance. Numerous studies have demonstrated that firms consider multiple criteria when selecting key vendors. This research intends to develop a new hybrid model for vendor selection process with better decision making. The new proposed model provides a suitable tool for assisting decision makers and managers to make the right decisions and select the most suitable vendor. This paper proposes a Hybrid model based on Structural Equation Model (SEM) and Analytical Hierarchy Process (AHP) for long-term strategic vendor selection problems. The five steps framework of the model has been designed after the thorough literature study. The proposed hybrid model will be applied using a real life case study to assess its effectiveness. In addition, What-if analysis technique will be used for model validation purpose.

  2. On a Robust MaxEnt Process Regression Model with Sample-Selection

    Directory of Open Access Journals (Sweden)

    Hea-Jung Kim

    2018-04-01

    Full Text Available In a regression analysis, a sample-selection bias arises when a dependent variable is partially observed as a result of the sample selection. This study introduces a Maximum Entropy (MaxEnt process regression model that assumes a MaxEnt prior distribution for its nonparametric regression function and finds that the MaxEnt process regression model includes the well-known Gaussian process regression (GPR model as a special case. Then, this special MaxEnt process regression model, i.e., the GPR model, is generalized to obtain a robust sample-selection Gaussian process regression (RSGPR model that deals with non-normal data in the sample selection. Various properties of the RSGPR model are established, including the stochastic representation, distributional hierarchy, and magnitude of the sample-selection bias. These properties are used in the paper to develop a hierarchical Bayesian methodology to estimate the model. This involves a simple and computationally feasible Markov chain Monte Carlo algorithm that avoids analytical or numerical derivatives of the log-likelihood function of the model. The performance of the RSGPR model in terms of the sample-selection bias correction, robustness to non-normality, and prediction, is demonstrated through results in simulations that attest to its good finite-sample performance.

  3. Numerical Model based Reliability Estimation of Selective Laser Melting Process

    DEFF Research Database (Denmark)

    Mohanty, Sankhya; Hattel, Jesper Henri

    2014-01-01

    Selective laser melting is developing into a standard manufacturing technology with applications in various sectors. However, the process is still far from being at par with conventional processes such as welding and casting, the primary reason of which is the unreliability of the process. While...... of the selective laser melting process. A validated 3D finite-volume alternating-direction-implicit numerical technique is used to model the selective laser melting process, and is calibrated against results from single track formation experiments. Correlation coefficients are determined for process input...... parameters such as laser power, speed, beam profile, etc. Subsequently, uncertainties in the processing parameters are utilized to predict a range for the various outputs, using a Monte Carlo method based uncertainty analysis methodology, and the reliability of the process is established....

  4. Mental health courts and their selection processes: modeling variation for consistency.

    Science.gov (United States)

    Wolff, Nancy; Fabrikant, Nicole; Belenko, Steven

    2011-10-01

    Admission into mental health courts is based on a complicated and often variable decision-making process that involves multiple parties representing different expertise and interests. To the extent that eligibility criteria of mental health courts are more suggestive than deterministic, selection bias can be expected. Very little research has focused on the selection processes underpinning problem-solving courts even though such processes may dominate the performance of these interventions. This article describes a qualitative study designed to deconstruct the selection and admission processes of mental health courts. In this article, we describe a multi-stage, complex process for screening and admitting clients into mental health courts. The selection filtering model that is described has three eligibility screening stages: initial, assessment, and evaluation. The results of this study suggest that clients selected by mental health courts are shaped by the formal and informal selection criteria, as well as by the local treatment system.

  5. Unraveling the sub-processes of selective attention: insights from dynamic modeling and continuous behavior.

    Science.gov (United States)

    Frisch, Simon; Dshemuchadse, Maja; Görner, Max; Goschke, Thomas; Scherbaum, Stefan

    2015-11-01

    Selective attention biases information processing toward stimuli that are relevant for achieving our goals. However, the nature of this bias is under debate: Does it solely rely on the amplification of goal-relevant information or is there a need for additional inhibitory processes that selectively suppress currently distracting information? Here, we explored the processes underlying selective attention with a dynamic, modeling-based approach that focuses on the continuous evolution of behavior over time. We present two dynamic neural field models incorporating the diverging theoretical assumptions. Simulations with both models showed that they make similar predictions with regard to response times but differ markedly with regard to their continuous behavior. Human data observed via mouse tracking as a continuous measure of performance revealed evidence for the model solely based on amplification but no indication of persisting selective distracter inhibition.

  6. Modeling and Experimental Validation of the Electron Beam Selective Melting Process

    Directory of Open Access Journals (Sweden)

    Wentao Yan

    2017-10-01

    Full Text Available Electron beam selective melting (EBSM is a promising additive manufacturing (AM technology. The EBSM process consists of three major procedures: ① spreading a powder layer, ② preheating to slightly sinter the powder, and ③ selectively melting the powder bed. The highly transient multi-physics phenomena involved in these procedures pose a significant challenge for in situ experimental observation and measurement. To advance the understanding of the physical mechanisms in each procedure, we leverage high-fidelity modeling and post-process experiments. The models resemble the actual fabrication procedures, including ① a powder-spreading model using the discrete element method (DEM, ② a phase field (PF model of powder sintering (solid-state sintering, and ③ a powder-melting (liquid-state sintering model using the finite volume method (FVM. Comprehensive insights into all the major procedures are provided, which have rarely been reported. Preliminary simulation results (including powder particle packing within the powder bed, sintering neck formation between particles, and single-track defects agree qualitatively with experiments, demonstrating the ability to understand the mechanisms and to guide the design and optimization of the experimental setup and manufacturing process.

  7. An integrated model for supplier selection process

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    In today's highly competitive manufacturing environment, the supplier selection process becomes one of crucial activities in supply chain management. In order to select the best supplier(s) it is not only necessary to continuously tracking and benchmarking performance of suppliers but also to make a tradeoff between tangible and intangible factors some of which may conflict. In this paper an integration of case-based reasoning (CBR), analytical network process (ANP) and linear programming (LP) is proposed to solve the supplier selection problem.

  8. Probabilistic wind power forecasting with online model selection and warped gaussian process

    International Nuclear Information System (INIS)

    Kou, Peng; Liang, Deliang; Gao, Feng; Gao, Lin

    2014-01-01

    Highlights: • A new online ensemble model for the probabilistic wind power forecasting. • Quantifying the non-Gaussian uncertainties in wind power. • Online model selection that tracks the time-varying characteristic of wind generation. • Dynamically altering the input features. • Recursive update of base models. - Abstract: Based on the online model selection and the warped Gaussian process (WGP), this paper presents an ensemble model for the probabilistic wind power forecasting. This model provides the non-Gaussian predictive distributions, which quantify the non-Gaussian uncertainties associated with wind power. In order to follow the time-varying characteristics of wind generation, multiple time dependent base forecasting models and an online model selection strategy are established, thus adaptively selecting the most probable base model for each prediction. WGP is employed as the base model, which handles the non-Gaussian uncertainties in wind power series. Furthermore, a regime switch strategy is designed to modify the input feature set dynamically, thereby enhancing the adaptiveness of the model. In an online learning framework, the base models should also be time adaptive. To achieve this, a recursive algorithm is introduced, thus permitting the online updating of WGP base models. The proposed model has been tested on the actual data collected from both single and aggregated wind farms

  9. Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies.

    Science.gov (United States)

    Savitsky, Terrance; Vannucci, Marina; Sha, Naijun

    2011-02-01

    This paper presents a unified treatment of Gaussian process models that extends to data from the exponential dispersion family and to survival data. Our specific interest is in the analysis of data sets with predictors that have an a priori unknown form of possibly nonlinear associations to the response. The modeling approach we describe incorporates Gaussian processes in a generalized linear model framework to obtain a class of nonparametric regression models where the covariance matrix depends on the predictors. We consider, in particular, continuous, categorical and count responses. We also look into models that account for survival outcomes. We explore alternative covariance formulations for the Gaussian process prior and demonstrate the flexibility of the construction. Next, we focus on the important problem of selecting variables from the set of possible predictors and describe a general framework that employs mixture priors. We compare alternative MCMC strategies for posterior inference and achieve a computationally efficient and practical approach. We demonstrate performances on simulated and benchmark data sets.

  10. Bayesian model selection validates a biokinetic model for zirconium processing in humans

    Science.gov (United States)

    2012-01-01

    Background In radiation protection, biokinetic models for zirconium processing are of crucial importance in dose estimation and further risk analysis for humans exposed to this radioactive substance. They provide limiting values of detrimental effects and build the basis for applications in internal dosimetry, the prediction for radioactive zirconium retention in various organs as well as retrospective dosimetry. Multi-compartmental models are the tool of choice for simulating the processing of zirconium. Although easily interpretable, determining the exact compartment structure and interaction mechanisms is generally daunting. In the context of observing the dynamics of multiple compartments, Bayesian methods provide efficient tools for model inference and selection. Results We are the first to apply a Markov chain Monte Carlo approach to compute Bayes factors for the evaluation of two competing models for zirconium processing in the human body after ingestion. Based on in vivo measurements of human plasma and urine levels we were able to show that a recently published model is superior to the standard model of the International Commission on Radiological Protection. The Bayes factors were estimated by means of the numerically stable thermodynamic integration in combination with a recently developed copula-based Metropolis-Hastings sampler. Conclusions In contrast to the standard model the novel model predicts lower accretion of zirconium in bones. This results in lower levels of noxious doses for exposed individuals. Moreover, the Bayesian approach allows for retrospective dose assessment, including credible intervals for the initially ingested zirconium, in a significantly more reliable fashion than previously possible. All methods presented here are readily applicable to many modeling tasks in systems biology. PMID:22863152

  11. Model of the best-of-N nest-site selection process in honeybees

    Science.gov (United States)

    Reina, Andreagiovanni; Marshall, James A. R.; Trianni, Vito; Bose, Thomas

    2017-05-01

    The ability of a honeybee swarm to select the best nest site plays a fundamental role in determining the future colony's fitness. To date, the nest-site selection process has mostly been modeled and theoretically analyzed for the case of binary decisions. However, when the number of alternative nests is larger than two, the decision-process dynamics qualitatively change. In this work, we extend previous analyses of a value-sensitive decision-making mechanism to a decision process among N nests. First, we present the decision-making dynamics in the symmetric case of N equal-quality nests. Then, we generalize our findings to a best-of-N decision scenario with one superior nest and N -1 inferior nests, previously studied empirically in bees and ants. Whereas previous binary models highlighted the crucial role of inhibitory stop-signaling, the key parameter in our new analysis is the relative time invested by swarm members in individual discovery and in signaling behaviors. Our new analysis reveals conflicting pressures on this ratio in symmetric and best-of-N decisions, which could be solved through a time-dependent signaling strategy. Additionally, our analysis suggests how ecological factors determining the density of suitable nest sites may have led to selective pressures for an optimal stable signaling ratio.

  12. Consumer Decision Process in Restaurant Selection: An Application of the Stylized EKB Model

    Directory of Open Access Journals (Sweden)

    Eugenia Wickens

    2016-12-01

    Full Text Available Purpose – The aim of this paper is to propose a framework based on empirical work for understanding the consumer decision processes involved in the selection of a restaurant for leisure meals. Design/Methodology/Approach – An interpretive approach is taken in order to understand the intricacies of the process and the various stages in the process. Six focus group interviews with consumers of various ages and occupations in the South East of the United Kingdom were conducted. Findings and implications – The stylized EKB model of the consumer decision process (Tuan-Pham & Higgins, 2005 was used as a framework for developing different stages of the process. Two distinct parts of the process were identified. Occasion was found to be critical to the stage of problem recognition. In terms of evaluation of alternatives and, in particular, sensitivity to evaluative content, the research indicates that the regulatory focus theory of Tuan-Pham and Higgins (2005 applies to the decision of selecting a restaurant. Limitations – It is acknowledged that this exploratory study is based on a small sample in a single geographical area. Originality – The paper is the first application of the stylized EKB model, which takes into account the motivational dimensions of consumer decision making, missing in other models. It concludes that it may have broader applications to other research contexts.

  13. It Takes Three: Selection, Influence, and De-Selection Processes of Depression in Adolescent Friendship Networks

    Science.gov (United States)

    Van Zalk, Maarten Herman Walter; Kerr, Margaret; Branje, Susan J. T.; Stattin, Hakan; Meeus, Wim H. J.

    2010-01-01

    The authors of this study tested a selection-influence-de-selection model of depression. This model explains friendship influence processes (i.e., friends' depressive symptoms increase adolescents' depressive symptoms) while controlling for two processes: friendship selection (i.e., selection of friends with similar levels of depressive symptoms)…

  14. The application of feature selection to the development of Gaussian process models for percutaneous absorption.

    Science.gov (United States)

    Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P

    2010-06-01

    The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it

  15. Vibration and acoustic frequency spectra for industrial process modeling using selective fusion multi-condition samples and multi-source features

    Science.gov (United States)

    Tang, Jian; Qiao, Junfei; Wu, ZhiWei; Chai, Tianyou; Zhang, Jian; Yu, Wen

    2018-01-01

    Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble sub-models with SEN cannot guarantee the best prediction model. In this study, we use several techniques to construct mechanical vibration and acoustic frequency spectra of a data-driven industrial process parameter model based on selective fusion multi-condition samples and multi-source features. Multi-layer SEN (MLSEN) strategy is used to simulate the domain expert cognitive process. Genetic algorithm and kernel partial least squares are used to construct the inside-layer SEN sub-model based on each mechanical vibration and acoustic frequency spectral feature subset. Branch-and-bound and adaptive weighted fusion algorithms are integrated to select and combine outputs of the inside-layer SEN sub-models. Then, the outside-layer SEN is constructed. Thus, "sub-sampling training examples"-based and "manipulating input features"-based ensemble construction methods are integrated, thereby realizing the selective information fusion process based on multi-condition history samples and multi-source input features. This novel approach is applied to a laboratory-scale ball mill grinding process. A comparison with other methods indicates that the proposed MLSEN approach effectively models mechanical vibration and acoustic signals.

  16. Modeling of biopharmaceutical processes. Part 2: Process chromatography unit operation

    DEFF Research Database (Denmark)

    Kaltenbrunner, Oliver; McCue, Justin; Engel, Philip

    2008-01-01

    Process modeling can be a useful tool to aid in process development, process optimization, and process scale-up. When modeling a chromatography process, one must first select the appropriate models that describe the mass transfer and adsorption that occurs within the porous adsorbent. The theoret......Process modeling can be a useful tool to aid in process development, process optimization, and process scale-up. When modeling a chromatography process, one must first select the appropriate models that describe the mass transfer and adsorption that occurs within the porous adsorbent...

  17. ERP Software Selection Model using Analytic Network Process

    OpenAIRE

    Lesmana , Andre Surya; Astanti, Ririn Diar; Ai, The Jin

    2014-01-01

    During the implementation of Enterprise Resource Planning (ERP) in any company, one of the most important issues is the selection of ERP software that can satisfy the needs and objectives of the company. This issue is crucial since it may affect the duration of ERP implementation and the costs incurred for the ERP implementation. This research tries to construct a model of the selection of ERP software that are beneficial to the company in order to carry out the selection of the right ERP sof...

  18. A Selection Approach for Optimized Problem-Solving Process by Grey Relational Utility Model and Multicriteria Decision Analysis

    Directory of Open Access Journals (Sweden)

    Chih-Kun Ke

    2012-01-01

    Full Text Available In business enterprises, especially the manufacturing industry, various problem situations may occur during the production process. A situation denotes an evaluation point to determine the status of a production process. A problem may occur if there is a discrepancy between the actual situation and the desired one. Thus, a problem-solving process is often initiated to achieve the desired situation. In the process, how to determine an action need to be taken to resolve the situation becomes an important issue. Therefore, this work uses a selection approach for optimized problem-solving process to assist workers in taking a reasonable action. A grey relational utility model and a multicriteria decision analysis are used to determine the optimal selection order of candidate actions. The selection order is presented to the worker as an adaptive recommended solution. The worker chooses a reasonable problem-solving action based on the selection order. This work uses a high-tech company’s knowledge base log as the analysis data. Experimental results demonstrate that the proposed selection approach is effective.

  19. Solvent selection methodology for pharmaceutical processes: Solvent swap

    DEFF Research Database (Denmark)

    Papadakis, Emmanouil; Kumar Tula, Anjan; Gani, Rafiqul

    2016-01-01

    A method for the selection of appropriate solvents for the solvent swap task in pharmaceutical processes has been developed. This solvent swap method is based on the solvent selection method of Gani et al. (2006) and considers additional selection criteria such as boiling point difference...... in pharmaceutical processes as well as new solvent swap alternatives. The method takes into account process considerations such as batch distillation and crystallization to achieve the swap task. Rigorous model based simulations of the swap operation are performed to evaluate and compare the performance...

  20. Modeling intermediate product selection under production and storage capacity limitations in food processing

    DEFF Research Database (Denmark)

    Kilic, Onur Alper; Akkerman, Renzo; Grunow, Martin

    2009-01-01

    In the food industry products are usually characterized by their recipes, which are specified by various quality attributes. For end products, this is given by customer requirements, but for intermediate products, the recipes can be chosen in such a way that raw material procurement costs and pro...... with production and inventory planning, thereby considering the production and storage capacity limitations. The resulting model can be used to solve an important practical problem typical for many food processing industries.......In the food industry products are usually characterized by their recipes, which are specified by various quality attributes. For end products, this is given by customer requirements, but for intermediate products, the recipes can be chosen in such a way that raw material procurement costs...... and processing costs are minimized. However, this product selection process is bound by production and storage capacity limitations, such as the number and size of storage tanks or silos. In this paper, we present a mathematical programming approach that combines decision making on product selection...

  1. Fusion strategies for selecting multiple tuning parameters for multivariate calibration and other penalty based processes: A model updating application for pharmaceutical analysis

    Energy Technology Data Exchange (ETDEWEB)

    Tencate, Alister J. [Department of Chemistry, Idaho State University, Pocatello, ID 83209 (United States); Kalivas, John H., E-mail: kalijohn@isu.edu [Department of Chemistry, Idaho State University, Pocatello, ID 83209 (United States); White, Alexander J. [Department of Physics and Optical Engineering, Rose-Hulman Institute of Technology, Terre Huate, IN 47803 (United States)

    2016-05-19

    New multivariate calibration methods and other processes are being developed that require selection of multiple tuning parameter (penalty) values to form the final model. With one or more tuning parameters, using only one measure of model quality to select final tuning parameter values is not sufficient. Optimization of several model quality measures is challenging. Thus, three fusion ranking methods are investigated for simultaneous assessment of multiple measures of model quality for selecting tuning parameter values. One is a supervised learning fusion rule named sum of ranking differences (SRD). The other two are non-supervised learning processes based on the sum and median operations. The effect of the number of models evaluated on the three fusion rules are also evaluated using three procedures. One procedure uses all models from all possible combinations of the tuning parameters. To reduce the number of models evaluated, an iterative process (only applicable to SRD) is applied and thresholding a model quality measure before applying the fusion rules is also used. A near infrared pharmaceutical data set requiring model updating is used to evaluate the three fusion rules. In this case, calibration of the primary conditions is for the active pharmaceutical ingredient (API) of tablets produced in a laboratory. The secondary conditions for calibration updating is for tablets produced in the full batch setting. Two model updating processes requiring selection of two unique tuning parameter values are studied. One is based on Tikhonov regularization (TR) and the other is a variation of partial least squares (PLS). The three fusion methods are shown to provide equivalent and acceptable results allowing automatic selection of the tuning parameter values. Best tuning parameter values are selected when model quality measures used with the fusion rules are for the small secondary sample set used to form the updated models. In this model updating situation, evaluation of

  2. Fusion strategies for selecting multiple tuning parameters for multivariate calibration and other penalty based processes: A model updating application for pharmaceutical analysis

    International Nuclear Information System (INIS)

    Tencate, Alister J.; Kalivas, John H.; White, Alexander J.

    2016-01-01

    New multivariate calibration methods and other processes are being developed that require selection of multiple tuning parameter (penalty) values to form the final model. With one or more tuning parameters, using only one measure of model quality to select final tuning parameter values is not sufficient. Optimization of several model quality measures is challenging. Thus, three fusion ranking methods are investigated for simultaneous assessment of multiple measures of model quality for selecting tuning parameter values. One is a supervised learning fusion rule named sum of ranking differences (SRD). The other two are non-supervised learning processes based on the sum and median operations. The effect of the number of models evaluated on the three fusion rules are also evaluated using three procedures. One procedure uses all models from all possible combinations of the tuning parameters. To reduce the number of models evaluated, an iterative process (only applicable to SRD) is applied and thresholding a model quality measure before applying the fusion rules is also used. A near infrared pharmaceutical data set requiring model updating is used to evaluate the three fusion rules. In this case, calibration of the primary conditions is for the active pharmaceutical ingredient (API) of tablets produced in a laboratory. The secondary conditions for calibration updating is for tablets produced in the full batch setting. Two model updating processes requiring selection of two unique tuning parameter values are studied. One is based on Tikhonov regularization (TR) and the other is a variation of partial least squares (PLS). The three fusion methods are shown to provide equivalent and acceptable results allowing automatic selection of the tuning parameter values. Best tuning parameter values are selected when model quality measures used with the fusion rules are for the small secondary sample set used to form the updated models. In this model updating situation, evaluation of

  3. Multiattribute Supplier Selection Using Fuzzy Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Serhat Aydin

    2010-11-01

    Full Text Available Supplier selection is a multiattribute decision making (MADM problem which contains both qualitative and quantitative factors. Supplier selection has vital importance for most companies. The aim of this paper is to provide an AHP based analytical tool for decision support enabling an effective multicriteria supplier selection process in an air conditioner seller firm under fuzziness. In this article, the Analytic Hierarchy Process (AHP under fuzziness is employed for its permissiveness to use an evaluation scale including linguistic expressions, crisp numerical values, fuzzy numbers and range numerical values. This scale provides a more flexible evaluation compared with the other fuzzy AHP methods. In this study, the modified AHP was used in supplier selection in an air conditioner firm. Three experts evaluated the suppliers according to the proposed model and the most appropriate supplier was selected. The proposed model enables decision makers select the best supplier among supplier firms effectively. We confirm that the modified fuzzy AHP is appropriate for group decision making in supplier selection problems.

  4. UML in business process modeling

    Directory of Open Access Journals (Sweden)

    Bartosz Marcinkowski

    2013-03-01

    Full Text Available Selection and proper application of business process modeling methods and techniques have a significant impact on organizational improvement capabilities as well as proper understanding of functionality of information systems that shall support activity of the organization. A number of business process modeling notations were popularized in practice in recent decades. Most significant of the notations include Business Process Modeling Notation (OMG BPMN and several Unified Modeling Language (OMG UML extensions. In this paper, the assessment whether one of the most flexible and strictly standardized contemporary business process modeling notations, i.e. Rational UML Profile for Business Modeling, enable business analysts to prepare business models that are all-embracing and understandable by all the stakeholders. After the introduction, methodology of research is discussed. Section 2 presents selected case study results. The paper is concluded with a summary.

  5. An evolutionary algorithm for model selection

    Energy Technology Data Exchange (ETDEWEB)

    Bicker, Karl [CERN, Geneva (Switzerland); Chung, Suh-Urk; Friedrich, Jan; Grube, Boris; Haas, Florian; Ketzer, Bernhard; Neubert, Sebastian; Paul, Stephan; Ryabchikov, Dimitry [Technische Univ. Muenchen (Germany)

    2013-07-01

    When performing partial-wave analyses of multi-body final states, the choice of the fit model, i.e. the set of waves to be used in the fit, can significantly alter the results of the partial wave fit. Traditionally, the models were chosen based on physical arguments and by observing the changes in log-likelihood of the fits. To reduce possible bias in the model selection process, an evolutionary algorithm was developed based on a Bayesian goodness-of-fit criterion which takes into account the model complexity. Starting from systematically constructed pools of waves which contain significantly more waves than the typical fit model, the algorithm yields a model with an optimal log-likelihood and with a number of partial waves which is appropriate for the number of events in the data. Partial waves with small contributions to the total intensity are penalized and likely to be dropped during the selection process, as are models were excessive correlations between single waves occur. Due to the automated nature of the model selection, a much larger part of the model space can be explored than would be possible in a manual selection. In addition the method allows to assess the dependence of the fit result on the fit model which is an important contribution to the systematic uncertainty.

  6. Bubble point pressures of the selected model system for CatLiq® bio-oil process

    DEFF Research Database (Denmark)

    Toor, Saqib Sohail; Rosendahl, Lasse; Baig, Muhammad Noman

    2010-01-01

    . In this work, the bubble point pressures of a selected model mixture (CO2 + H2O + Ethanol + Acetic acid + Octanoic acid) were measured to investigate the phase boundaries of the CatLiq® process. The bubble points were measured in the JEFRI-DBR high pressure PVT phase behavior system. The experimental results......The CatLiq® process is a second generation catalytic liquefaction process for the production of bio-oil from WDGS (Wet Distillers Grains with Solubles) at subcritical conditions (280-350 oC and 225-250 bar) in the presence of a homogeneous alkaline and a heterogeneous Zirconia catalyst...

  7. Predictive Active Set Selection Methods for Gaussian Processes

    DEFF Research Database (Denmark)

    Henao, Ricardo; Winther, Ole

    2012-01-01

    We propose an active set selection framework for Gaussian process classification for cases when the dataset is large enough to render its inference prohibitive. Our scheme consists of a two step alternating procedure of active set update rules and hyperparameter optimization based upon marginal...... high impact to the classifier decision process while removing those that are less relevant. We introduce two active set rules based on different criteria, the first one prefers a model with interpretable active set parameters whereas the second puts computational complexity first, thus a model...... with active set parameters that directly control its complexity. We also provide both theoretical and empirical support for our active set selection strategy being a good approximation of a full Gaussian process classifier. Our extensive experiments show that our approach can compete with state...

  8. Decision Support Model for Selection Technologies in Processing of Palm Oil Industrial Liquid Waste

    Science.gov (United States)

    Ishak, Aulia; Ali, Amir Yazid bin

    2017-12-01

    The palm oil industry continues to grow from year to year. Processing of the palm oil industry into crude palm oil (CPO) and palm kernel oil (PKO). The ratio of the amount of oil produced by both products is 30% of the raw material. This means that 70% is palm oil waste. The amount of palm oil waste will increase in line with the development of the palm oil industry. The amount of waste generated by the palm oil industry if it is not handled properly and effectively will contribute significantly to environmental damage. Industrial activities ranging from raw materials to produce products will disrupt the lives of people around the factory. There are many alternative technologies available to process other industries, but problems that often occur are difficult to implement the most appropriate technology. The purpose of this research is to develop a database of waste processing technology, looking for qualitative and quantitative criteria to select technology and develop Decision Support System (DSS) that can help make decisions. The method used to achieve the objective of this research is to develop a questionnaire to identify waste processing technology and develop the questionnaire to find appropriate database technology. Methods of data analysis performed on the system by using Analytic Hierarchy Process (AHP) and to build the model by using the MySQL Software that can be used as a tool in the evaluation and selection of palm oil mill processing technology.

  9. A SUPPLIER SELECTION MODEL FOR SOFTWARE DEVELOPMENT OUTSOURCING

    Directory of Open Access Journals (Sweden)

    Hancu Lucian-Viorel

    2010-12-01

    Full Text Available This paper presents a multi-criteria decision making model used for supplier selection for software development outsourcing on e-marketplaces. This model can be used in auctions. The supplier selection process becomes complex and difficult on last twenty years since the Internet plays an important role in business management. Companies have to concentrate their efforts on their core activities and the others activities should be realized by outsourcing. They can achieve significant cost reduction by using e-marketplaces in their purchase process and by using decision support systems on supplier selection. In the literature were proposed many approaches for supplier evaluation and selection process. The performance of potential suppliers is evaluated using multi criteria decision making methods rather than considering a single factor cost.

  10. Bayesian Model Selection under Time Constraints

    Science.gov (United States)

    Hoege, M.; Nowak, W.; Illman, W. A.

    2017-12-01

    Bayesian model selection (BMS) provides a consistent framework for rating and comparing models in multi-model inference. In cases where models of vastly different complexity compete with each other, we also face vastly different computational runtimes of such models. For instance, time series of a quantity of interest can be simulated by an autoregressive process model that takes even less than a second for one run, or by a partial differential equations-based model with runtimes up to several hours or even days. The classical BMS is based on a quantity called Bayesian model evidence (BME). It determines the model weights in the selection process and resembles a trade-off between bias of a model and its complexity. However, in practice, the runtime of models is another weight relevant factor for model selection. Hence, we believe that it should be included, leading to an overall trade-off problem between bias, variance and computing effort. We approach this triple trade-off from the viewpoint of our ability to generate realizations of the models under a given computational budget. One way to obtain BME values is through sampling-based integration techniques. We argue with the fact that more expensive models can be sampled much less under time constraints than faster models (in straight proportion to their runtime). The computed evidence in favor of a more expensive model is statistically less significant than the evidence computed in favor of a faster model, since sampling-based strategies are always subject to statistical sampling error. We present a straightforward way to include this misbalance into the model weights that are the basis for model selection. Our approach follows directly from the idea of insufficient significance. It is based on a computationally cheap bootstrapping error estimate of model evidence and is easy to implement. The approach is illustrated in a small synthetic modeling study.

  11. Modeling of the thermal physical process and study on the reliability of linear energy density for selective laser melting

    Directory of Open Access Journals (Sweden)

    Zhaowei Xiang

    2018-06-01

    Full Text Available A finite element model considering volume shrinkage with powder-to-dense process of powder layer in selective laser melting (SLM is established. Comparison between models that consider and do not consider volume shrinkage or powder-to-dense process is carried out. Further, parametric analysis of laser power and scan speed is conducted and the reliability of linear energy density as a design parameter is investigated. The results show that the established model is an effective method and has better accuracy allowing for the temperature distribution, and the length and depth of molten pool. The maximum temperature is more sensitive to laser power than scan speed. The maximum heating rate and cooling rate increase with increasing scan speed at constant laser power and increase with increasing laser power at constant scan speed as well. The simulation results and experimental result reveal that linear energy density is not always reliable using as a design parameter in the SLM. Keywords: Selective laser melting, Volume shrinkage, Powder-to-dense process, Numerical modeling, Thermal analysis, Linear energy density

  12. Quality Quandaries- Time Series Model Selection and Parsimony

    DEFF Research Database (Denmark)

    Bisgaard, Søren; Kulahci, Murat

    2009-01-01

    Some of the issues involved in selecting adequate models for time series data are discussed using an example concerning the number of users of an Internet server. The process of selecting an appropriate model is subjective and requires experience and judgment. The authors believe an important...... consideration in model selection should be parameter parsimony. They favor the use of parsimonious mixed ARMA models, noting that research has shown that a model building strategy that considers only autoregressive representations will lead to non-parsimonious models and to loss of forecasting accuracy....

  13. ASYMMETRIC PRICE TRANSMISSION MODELING: THE IMPORTANCE OF MODEL COMPLEXITY AND THE PERFORMANCE OF THE SELECTION CRITERIA

    Directory of Open Access Journals (Sweden)

    Henry de-Graft Acquah

    2013-01-01

    Full Text Available Information Criteria provides an attractive basis for selecting the best model from a set of competing asymmetric price transmission models or theories. However, little is understood about the sensitivity of the model selection methods to model complexity. This study therefore fits competing asymmetric price transmission models that differ in complexity to simulated data and evaluates the ability of the model selection methods to recover the true model. The results of Monte Carlo experimentation suggest that in general BIC, CAIC and DIC were superior to AIC when the true data generating process was the standard error correction model, whereas AIC was more successful when the true model was the complex error correction model. It is also shown that the model selection methods performed better in large samples for a complex asymmetric data generating process than with a standard asymmetric data generating process. Except for complex models, AIC's performance did not make substantial gains in recovery rates as sample size increased. The research findings demonstrate the influence of model complexity in asymmetric price transmission model comparison and selection.

  14. 45 CFR 1305.6 - Selection process.

    Science.gov (United States)

    2010-10-01

    ... 45 Public Welfare 4 2010-10-01 2010-10-01 false Selection process. 1305.6 Section 1305.6 Public... PROGRAM ELIGIBILITY, RECRUITMENT, SELECTION, ENROLLMENT AND ATTENDANCE IN HEAD START § 1305.6 Selection process. (a) Each Head Start program must have a formal process for establishing selection criteria and...

  15. Effects of binge drinking and hangover on response selection sub-processes-a study using EEG and drift diffusion modeling.

    Science.gov (United States)

    Stock, Ann-Kathrin; Hoffmann, Sven; Beste, Christian

    2017-09-01

    Effects of binge drinking on cognitive control and response selection are increasingly recognized in research on alcohol (ethanol) effects. Yet, little is known about how those processes are modulated by hangover effects. Given that acute intoxication and hangover seem to be characterized by partly divergent effects and mechanisms, further research on this topic is needed. In the current study, we hence investigated this with a special focus on potentially differential effects of alcohol intoxication and subsequent hangover on sub-processes involved in the decision to select a response. We do so combining drift diffusion modeling of behavioral data with neurophysiological (EEG) data. Opposed to common sense, the results do not show an impairment of all assessed measures. Instead, they show specific effects of high dose alcohol intoxication and hangover on selective drift diffusion model and EEG parameters (as compared to a sober state). While the acute intoxication induced by binge-drinking decreased the drift rate, it was increased by the subsequent hangover, indicating more efficient information accumulation during hangover. Further, the non-decisional processes of information encoding decreased with intoxication, but not during hangover. These effects were reflected in modulations of the N2, P1 and N1 event-related potentials, which reflect conflict monitoring, perceptual gating and attentional selection processes, respectively. As regards the functional neuroanatomical architecture, the anterior cingulate cortex (ACC) as well as occipital networks seem to be modulated. Even though alcohol is known to have broad neurobiological effects, its effects on cognitive processes are rather specific. © 2016 Society for the Study of Addiction.

  16. Innovation During the Supplier Selection Process

    DEFF Research Database (Denmark)

    Pilkington, Alan; Pedraza, Isabel

    2014-01-01

    Established ideas on supplier selection have not moved much from the original premise of how to choose between bidders. Whilst we have added many different tools and refinements to choose between alternative suppliers, its nature has not evolved. We move the original selection process approach...... observed through an ethnographic embedded researcher study has refined the selection process and has two selection stages one for first supply covering tool/process developed and another later for resupply of mature parts. We report the details of the process, those involved, the criteria employed...... and identify benefits and weaknesses of this enhanced selection process....

  17. Information-Processing Models and Curriculum Design

    Science.gov (United States)

    Calfee, Robert C.

    1970-01-01

    "This paper consists of three sections--(a) the relation of theoretical analyses of learning to curriculum design, (b) the role of information-processing models in analyses of learning processes, and (c) selected examples of the application of information-processing models to curriculum design problems." (Author)

  18. Preparatory selection of sterilization regime for canned Natural Atlantic Mackerel with oil based on developed mathematical models of the process

    Directory of Open Access Journals (Sweden)

    Maslov A. A.

    2016-12-01

    Full Text Available Definition of preparatory parameters for sterilization regime of canned "Natural Atlantic Mackerel with Oil" is the aim of current study. PRSC software developed at the department of automation and computer engineering is used for preparatory selection. To determine the parameters of process model, in laboratory autoclave AVK-30M the pre-trial process of sterilization and cooling in water with backpressure of canned "Natural Atlantic Mackerel with Oil" in can N 3 has been performed. Gathering information about the temperature in the autoclave sterilization chamber and the can with product has been carried out using Ellab TrackSense PRO loggers. Due to the obtained information three transfer functions for the product model have been identified: in the least heated area of autoclave, the average heated and the most heated. In PRSC programme temporary temperature dependences in the sterilization chamber have been built using this information. The model of sterilization process of canned "Natural Atlantic Mackerel with Oil" has been received after the pre-trial process. Then in the automatic mode the sterilization regime of canned "Natural Atlantic Mackerel with Oil" has been selected using the value of actual effect close to normative sterilizing effect (5.9 conditional minutes. Furthermore, in this study step-mode sterilization of canned "Natural Atlantic Mackerel with Oil" has been selected. Utilization of step-mode sterilization with the maximum temperature equal to 125 °C in the sterilization chamber allows reduce process duration by 10 %. However, the application of this regime in practice requires additional research. Using the described approach based on the developed mathematical models of the process allows receive optimal step and variable canned food sterilization regimes with high energy efficiency and product quality.

  19. The genealogy of samples in models with selection.

    Science.gov (United States)

    Neuhauser, C; Krone, S M

    1997-02-01

    We introduce the genealogy of a random sample of genes taken from a large haploid population that evolves according to random reproduction with selection and mutation. Without selection, the genealogy is described by Kingman's well-known coalescent process. In the selective case, the genealogy of the sample is embedded in a graph with a coalescing and branching structure. We describe this graph, called the ancestral selection graph, and point out differences and similarities with Kingman's coalescent. We present simulations for a two-allele model with symmetric mutation in which one of the alleles has a selective advantage over the other. We find that when the allele frequencies in the population are already in equilibrium, then the genealogy does not differ much from the neutral case. This is supported by rigorous results. Furthermore, we describe the ancestral selection graph for other selective models with finitely many selection classes, such as the K-allele models, infinitely-many-alleles models. DNA sequence models, and infinitely-many-sites models, and briefly discuss the diploid case.

  20. Expert System Model for Educational Personnel Selection

    Directory of Open Access Journals (Sweden)

    Héctor A. Tabares-Ospina

    2013-06-01

    Full Text Available The staff selection is a difficult task due to the subjectivity that the evaluation means. This process can be complemented using a system to support decision. This paper presents the implementation of an expert system to systematize the selection process of professors. The management of software development is divided into 4 parts: requirements, design, implementation and commissioning. The proposed system models a specific knowledge through relationships between variables evidence and objective.

  1. Applying Four Different Risk Models in Local Ore Selection

    International Nuclear Information System (INIS)

    Richmond, Andrew

    2002-01-01

    Given the uncertainty in grade at a mine location, a financially risk-averse decision-maker may prefer to incorporate this uncertainty into the ore selection process. A FORTRAN program risksel is presented to calculate local risk-adjusted optimal ore selections using a negative exponential utility function and three dominance models: mean-variance, mean-downside risk, and stochastic dominance. All four methods are demonstrated in a grade control environment. In the case study, optimal selections range with the magnitude of financial risk that a decision-maker is prepared to accept. Except for the stochastic dominance method, the risk models reassign material from higher cost to lower cost processing options as the aversion to financial risk increases. The stochastic dominance model usually was unable to determine the optimal local selection

  2. A Gambler's Model of Natural Selection.

    Science.gov (United States)

    Nolan, Michael J.; Ostrovsky, David S.

    1996-01-01

    Presents an activity that highlights the mechanism and power of natural selection. Allows students to think in terms of modeling a biological process and instills an appreciation for a mathematical approach to biological problems. (JRH)

  3. Economic assessment model architecture for AGC/AVLIS selection

    International Nuclear Information System (INIS)

    Hoglund, R.L.

    1984-01-01

    The economic assessment model architecture described provides the flexibility and completeness in economic analysis that the selection between AGC and AVLIS demands. Process models which are technology-specific will provide the first-order responses of process performance and cost to variations in process parameters. The economics models can be used to test the impacts of alternative deployment scenarios for a technology. Enterprise models provide global figures of merit for evaluating the DOE perspective on the uranium enrichment enterprise, and business analysis models compute the financial parameters from the private investor's viewpoint

  4. Physics-based simulation modeling and optimization of microstructural changes induced by machining and selective laser melting processes in titanium and nickel based alloys

    Science.gov (United States)

    Arisoy, Yigit Muzaffer

    Manufacturing processes may significantly affect the quality of resultant surfaces and structural integrity of the metal end products. Controlling manufacturing process induced changes to the product's surface integrity may improve the fatigue life and overall reliability of the end product. The goal of this study is to model the phenomena that result in microstructural alterations and improve the surface integrity of the manufactured parts by utilizing physics-based process simulations and other computational methods. Two different (both conventional and advanced) manufacturing processes; i.e. machining of Titanium and Nickel-based alloys and selective laser melting of Nickel-based powder alloys are studied. 3D Finite Element (FE) process simulations are developed and experimental data that validates these process simulation models are generated to compare against predictions. Computational process modeling and optimization have been performed for machining induced microstructure that includes; i) predicting recrystallization and grain size using FE simulations and the Johnson-Mehl-Avrami-Kolmogorov (JMAK) model, ii) predicting microhardness using non-linear regression models and the Random Forests method, and iii) multi-objective machining optimization for minimizing microstructural changes. Experimental analysis and computational process modeling of selective laser melting have been also conducted including; i) microstructural analysis of grain sizes and growth directions using SEM imaging and machine learning algorithms, ii) analysis of thermal imaging for spattering, heating/cooling rates and meltpool size, iii) predicting thermal field, meltpool size, and growth directions via thermal gradients using 3D FE simulations, iv) predicting localized solidification using the Phase Field method. These computational process models and predictive models, once utilized by industry to optimize process parameters, have the ultimate potential to improve performance of

  5. Evidence accumulation as a model for lexical selection.

    Science.gov (United States)

    Anders, R; Riès, S; van Maanen, L; Alario, F X

    2015-11-01

    We propose and demonstrate evidence accumulation as a plausible theoretical and/or empirical model for the lexical selection process of lexical retrieval. A number of current psycholinguistic theories consider lexical selection as a process related to selecting a lexical target from a number of alternatives, which each have varying activations (or signal supports), that are largely resultant of an initial stimulus recognition. We thoroughly present a case for how such a process may be theoretically explained by the evidence accumulation paradigm, and we demonstrate how this paradigm can be directly related or combined with conventional psycholinguistic theory and their simulatory instantiations (generally, neural network models). Then with a demonstrative application on a large new real data set, we establish how the empirical evidence accumulation approach is able to provide parameter results that are informative to leading psycholinguistic theory, and that motivate future theoretical development. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Multi-enzyme Process Modeling

    DEFF Research Database (Denmark)

    Andrade Santacoloma, Paloma de Gracia

    are affected (in a positive or negative way) by the presence of the other enzymes and compounds in the media. In this thesis the concept of multi-enzyme in-pot term is adopted for processes that are carried out by the combination of enzymes in a single reactor and implemented at pilot or industrial scale...... features of the process and provides the information required to structure the process model by using a step-by-step procedure with the required tools and methods. In this way, this framework increases efficiency of the model development process with respect to time and resources needed (fast and effective....... In this way the model parameters that drives the main dynamic behavior can be identified and thus a better understanding of this type of processes. In order to develop, test and verify the methodology, three case studies were selected, specifically the bi-enzyme process for the production of lactobionic acid...

  7. A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

    Science.gov (United States)

    Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

    2017-07-01

    Near-infrared (NIR) spectroscopy is being widely used in various fields ranging from pharmaceutics to the food industry for analyzing chemical and physical properties of the substances concerned. Its advantages over other analytical techniques include available physical interpretation of spectral data, nondestructive nature and high speed of measurements, and little or no need for sample preparation. The successful application of NIR spectroscopy relies on three main aspects: pre-processing of spectral data to eliminate nonlinear variations due to temperature, light scattering effects and many others, selection of those wavelengths that contribute useful information, and identification of suitable calibration models using linear/nonlinear regression . Several methods have been developed for each of these three aspects and many comparative studies of different methods exist for an individual aspect or some combinations. However, there is still a lack of comparative studies for the interactions among these three aspects, which can shed light on what role each aspect plays in the calibration and how to combine various methods of each aspect together to obtain the best calibration model. This paper aims to provide such a comparative study based on four benchmark data sets using three typical pre-processing methods, namely, orthogonal signal correction (OSC), extended multiplicative signal correction (EMSC) and optical path-length estimation and correction (OPLEC); two existing wavelength selection methods, namely, stepwise forward selection (SFS) and genetic algorithm optimization combined with partial least squares regression for spectral data (GAPLSSP); four popular regression methods, namely, partial least squares (PLS), least absolute shrinkage and selection operator (LASSO), least squares support vector machine (LS-SVM), and Gaussian process regression (GPR). The comparative study indicates that, in general, pre-processing of spectral data can play a significant

  8. Selection of power market structure using the analytic hierarchy process

    International Nuclear Information System (INIS)

    Subhes Bhattacharyya; Prasanta Kumar Dey

    2003-01-01

    Selection of a power market structure from the available alternatives is an important activity within an overall power sector reform program. The evaluation criteria for selection are both subjective as well as objective in nature and the selection of alternatives is characterised by their conflicting nature. This study demonstrates a methodology for power market structure selection using the analytic hierarchy process, a multiple attribute decision- making technique, to model the selection methodology with the active participation of relevant stakeholders in a workshop environment. The methodology is applied to a hypothetical case of a State Electricity Board reform in India. (author)

  9. Fundamental Aspects of Selective Melting Additive Manufacturing Processes

    Energy Technology Data Exchange (ETDEWEB)

    van Swol, Frank B. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Miller, James E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-12-01

    Certain details of the additive manufacturing process known as selective laser melting (SLM) affect the performance of the final metal part. To unleash the full potential of SLM it is crucial that the process engineer in the field receives guidance about how to select values for a multitude of process variables employed in the building process. These include, for example, the type of powder (e.g., size distribution, shape, type of alloy), orientation of the build axis, the beam scan rate, the beam power density, the scan pattern and scan rate. The science-based selection of these settings con- stitutes an intrinsically challenging multi-physics problem involving heating and melting a metal alloy, reactive, dynamic wetting followed by re-solidification. In addition, inherent to the process is its considerable variability that stems from the powder packing. Each time a limited number of powder particles are placed, the stacking is intrinsically different from the previous, possessing a different geometry, and having a different set of contact areas with the surrounding particles. As a result, even if all other process parameters (scan rate, etc) are exactly the same, the shape and contact geometry and area of the final melt pool will be unique to that particular configuration. This report identifies the most important issues facing SLM, discusses the fundamental physics associated with it and points out how modeling can support the additive manufacturing efforts.

  10. Multiphysics modelling of manufacturing processes: A review

    DEFF Research Database (Denmark)

    Jabbari, Masoud; Baran, Ismet; Mohanty, Sankhya

    2018-01-01

    Numerical modelling is increasingly supporting the analysis and optimization of manufacturing processes in the production industry. Even if being mostly applied to multistep processes, single process steps may be so complex by nature that the needed models to describe them must include multiphysics...... the diversity in the field of modelling of manufacturing processes as regards process, materials, generic disciplines as well as length scales: (1) modelling of tape casting for thin ceramic layers, (2) modelling the flow of polymers in extrusion, (3) modelling the deformation process of flexible stamps...... for nanoimprint lithography, (4) modelling manufacturing of composite parts and (5) modelling the selective laser melting process. For all five examples, the emphasis is on modelling results as well as describing the models in brief mathematical details. Alongside with relevant references to the original work...

  11. Analysis of Using Resources in Business Process Modeling and Simulation

    Directory of Open Access Journals (Sweden)

    Vasilecas Olegas

    2014-12-01

    Full Text Available One of the key purposes of Business Process Model and Notation (BPMN is to support graphical representation of the process model. However, such models have a lack of support for the graphical representation of resources, whose processes are used during simulation or execution of process instance. The paper analyzes different methods and their extensions for resource modeling. Further, this article presents a selected set of resource properties that are relevant for resource modeling. The paper proposes an approach that explains how to use the selected set of resource properties for extension of process modeling using BPMN and simulation tools. They are based on BPMN, where business process instances use resources in a concurrency manner.

  12. Modeling HIV-1 drug resistance as episodic directional selection.

    Science.gov (United States)

    Murrell, Ben; de Oliveira, Tulio; Seebregts, Chris; Kosakovsky Pond, Sergei L; Scheffler, Konrad

    2012-01-01

    The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

  13. Modeling HIV-1 drug resistance as episodic directional selection.

    Directory of Open Access Journals (Sweden)

    Ben Murrell

    Full Text Available The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.

  14. Process chain modeling and selection in an additive manufacturing context

    DEFF Research Database (Denmark)

    Thompson, Mary Kathryn; Stolfi, Alessandro; Mischkot, Michael

    2016-01-01

    This paper introduces a new two-dimensional approach to modeling manufacturing process chains. This approach is used to consider the role of additive manufacturing technologies in process chains for a part with micro scale features and no internal geometry. It is shown that additive manufacturing...... evolving fields like additive manufacturing....

  15. 7 CFR 3570.68 - Selection process.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 15 2010-01-01 2010-01-01 false Selection process. 3570.68 Section 3570.68 Agriculture Regulations of the Department of Agriculture (Continued) RURAL HOUSING SERVICE, DEPARTMENT OF AGRICULTURE COMMUNITY PROGRAMS Community Facilities Grant Program § 3570.68 Selection process. Each request...

  16. 44 CFR 150.7 - Selection process.

    Science.gov (United States)

    2010-10-01

    ... 44 Emergency Management and Assistance 1 2010-10-01 2010-10-01 false Selection process. 150.7 Section 150.7 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF... Selection process. (a) President's Award. Nominations for the President's Award shall be reviewed, and...

  17. Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

    Science.gov (United States)

    Wichary, Szymon; Smolen, Tomasz

    2016-01-01

    In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals.

  18. Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model

    Science.gov (United States)

    Wichary, Szymon; Smolen, Tomasz

    2016-01-01

    In multi-attribute choice, decision makers use decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g., affect, stress) on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models of this process. We also present the Bottom-Up Model of Strategy Selection (BUMSS). The model assumes that the use of the rational Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: (1) cue weight computation, (2) gain modulation, and (3) weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neural signals. PMID:27877103

  19. Neural underpinnings of decision strategy selection: a review and a theoretical model

    Directory of Open Access Journals (Sweden)

    Szymon Wichary

    2016-11-01

    Full Text Available In multi-attribute choice, decision makers use various decision strategies to arrive at the final choice. What are the neural mechanisms underlying decision strategy selection? The first goal of this paper is to provide a literature review on the neural underpinnings and cognitive models of decision strategy selection and thus set the stage for a unifying neurocognitive model of this process. The second goal is to outline such a unifying, mechanistic model that can explain the impact of noncognitive factors (e.g. affect, stress on strategy selection. To this end, we review the evidence for the factors influencing strategy selection, the neural basis of strategy use and the cognitive models explaining this process. We also present the neurocognitive Bottom-Up Model of Strategy Selection (BUMSS. The model assumes that the use of the rational, normative Weighted Additive strategy and the boundedly rational heuristic Take The Best can be explained by one unifying, neurophysiologically plausible mechanism, based on the interaction of the frontoparietal network, orbitofrontal cortex, anterior cingulate cortex and the brainstem nucleus locus coeruleus. According to BUMSS, there are three processes that form the bottom-up mechanism of decision strategy selection and lead to the final choice: 1 cue weight computation, 2 gain modulation, and 3 weighted additive evaluation of alternatives. We discuss how these processes might be implemented in the brain, and how this knowledge allows us to formulate novel predictions linking strategy use and neurophysiological indices.

  20. Comparative analysis of business rules and business process modeling languages

    Directory of Open Access Journals (Sweden)

    Audrius Rima

    2013-03-01

    Full Text Available During developing an information system is important to create clear models and choose suitable modeling languages. The article analyzes the SRML, SBVR, PRR, SWRL, OCL rules specifying language and UML, DFD, CPN, EPC and IDEF3 BPMN business process modeling language. The article presents business rules and business process modeling languages theoretical comparison. The article according to selected modeling aspects of the comparison between different business process modeling languages ​​and business rules representation languages sets. Also, it is selected the best fit of language set for three layer framework for business rule based software modeling.

  1. Selection Criteria in Regime Switching Conditional Volatility Models

    Directory of Open Access Journals (Sweden)

    Thomas Chuffart

    2015-05-01

    Full Text Available A large number of nonlinear conditional heteroskedastic models have been proposed in the literature. Model selection is crucial to any statistical data analysis. In this article, we investigate whether the most commonly used selection criteria lead to choice of the right specification in a regime switching framework. We focus on two types of models: the Logistic Smooth Transition GARCH and the Markov-Switching GARCH models. Simulation experiments reveal that information criteria and loss functions can lead to misspecification ; BIC sometimes indicates the wrong regime switching framework. Depending on the Data Generating Process used in the experiments, great care is needed when choosing a criterion.

  2. Selection of refractory materials for pyrochemical processing

    International Nuclear Information System (INIS)

    Axler, K.M.; DePoorter, G.L.; Bagaasen, L.M.

    1991-01-01

    Several pyrochemical processing operations require containment materials that exhibit minimal chemical interactions with the system, good thermal shock resistance, and reusability. One example is Direct Oxide Reduction (DOR). DOR involves the conversion of PuO 2 to metal by an oxidation/reduction reaction with Ca metal. The reaction proceeds within a molten salt flux at temperatures above 800C. A combination of thermodynamics, system thermodynamic modeling, and experimental investigations are in use to select and evaluate potential containment materials

  3. Parameter identification in multinomial processing tree models

    NARCIS (Netherlands)

    Schmittmann, V.D.; Dolan, C.V.; Raijmakers, M.E.J.; Batchelder, W.H.

    2010-01-01

    Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis

  4. Selection Process for New Windows | Efficient Windows Collaborative

    Science.gov (United States)

    Foundry Foundry New Construction Windows Window Selection Tool Selection Process Design Guidance Installation Replacement Windows Window Selection Tool Assessing Options Selection Process Design Guidance Installation Understanding Windows Benefits Design Considerations Measuring Performance Performance Standards

  5. Selection Process for Replacement Windows | Efficient Windows Collaborative

    Science.gov (United States)

    Foundry Foundry New Construction Windows Window Selection Tool Selection Process Design Guidance Installation Replacement Windows Window Selection Tool Assessing Options Selection Process Design Guidance Installation Understanding Windows Benefits Design Considerations Measuring Performance Performance Standards

  6. Sexual selection: Another Darwinian process.

    Science.gov (United States)

    Gayon, Jean

    2010-02-01

    the Darwin-Wallace controversy was that most Darwinian biologists avoided the subject of sexual selection until at least the 1950s, Ronald Fisher being a major exception. This controversy still deserves attention from modern evolutionary biologists, because the modern approach inherits from both Darwin and Wallace. The modern approach tends to present sexual selection as a special aspect of the theory of natural selection, although it also recognizes the big difficulties resulting from the inevitable interaction between these two natural processes of selection. And contra Wallace, it considers mate choice as a major process that deserves a proper evolutionary treatment. The paper's conclusion explains why sexual selection can be taken as a test case for a proper assessment of "Darwinism" as a scientific tradition. Darwin's and Wallace's attitudes towards sexual selection reveal two different interpretations of the principle of natural selection: Wallace's had an environmentalist conception of natural selection, whereas Darwin was primarily sensitive to the element of competition involved in the intimate mechanism of any natural process of selection. Sexual selection, which can lack adaptive significance, reveals this exemplarily. 2010 Académie des sciences. Published by Elsevier SAS. All rights reserved.

  7. Selection of Activities in Dynamic Business Process Simulation

    Directory of Open Access Journals (Sweden)

    Toma Rusinaitė

    2016-06-01

    Full Text Available Maintaining dynamicity of business processes is one of the core issues of today's business as it enables businesses to adapt to constantly changing environment. Upon changing the processes, it is vital to assess possible impact, which is achieved by using simulation of dynamic processes. In order to implement dynamicity in business processes, it is necessary to have an ability to change components of the process (a set of activities, a content of activity, a set of activity sequences, a set of rules, performers and resources or dynamically select them during execution. This problem attracted attention of researches over the past few years; however, there is no proposed solution, which ensures the business process (BP dynamicity. This paper proposes and specifies dynamic business process (DBP simulation model, which satisfies all of the formulated DBP requirements.

  8. Implementation of the Business Process Modelling Notation (BPMN) in the modelling of anatomic pathology processes.

    Science.gov (United States)

    Rojo, Marcial García; Rolón, Elvira; Calahorra, Luis; García, Felix Oscar; Sánchez, Rosario Paloma; Ruiz, Francisco; Ballester, Nieves; Armenteros, María; Rodríguez, Teresa; Espartero, Rafael Martín

    2008-07-15

    Process orientation is one of the essential elements of quality management systems, including those in use in healthcare. Business processes in hospitals are very complex and variable. BPMN (Business Process Modelling Notation) is a user-oriented language specifically designed for the modelling of business (organizational) processes. Previous experiences of the use of this notation in the processes modelling within the Pathology in Spain or another country are not known. We present our experience in the elaboration of the conceptual models of Pathology processes, as part of a global programmed surgical patient process, using BPMN. With the objective of analyzing the use of BPMN notation in real cases, a multidisciplinary work group was created, including software engineers from the Dep. of Technologies and Information Systems from the University of Castilla-La Mancha and health professionals and administrative staff from the Hospital General de Ciudad Real. The work in collaboration was carried out in six phases: informative meetings, intensive training, process selection, definition of the work method, process describing by hospital experts, and process modelling. The modelling of the processes of Anatomic Pathology is presented using BPMN. The presented subprocesses are those corresponding to the surgical pathology examination of the samples coming from operating theatre, including the planning and realization of frozen studies. The modelling of Anatomic Pathology subprocesses has allowed the creation of an understandable graphical model, where management and improvements are more easily implemented by health professionals.

  9. Automating an integrated spatial data-mining model for landfill site selection

    Science.gov (United States)

    Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Aziz, Hamidi Abdul

    2017-10-01

    An integrated programming environment represents a robust approach to building a valid model for landfill site selection. One of the main challenges in the integrated model is the complicated processing and modelling due to the programming stages and several limitations. An automation process helps avoid the limitations and improve the interoperability between integrated programming environments. This work targets the automation of a spatial data-mining model for landfill site selection by integrating between spatial programming environment (Python-ArcGIS) and non-spatial environment (MATLAB). The model was constructed using neural networks and is divided into nine stages distributed between Matlab and Python-ArcGIS. A case study was taken from the north part of Peninsular Malaysia. 22 criteria were selected to utilise as input data and to build the training and testing datasets. The outcomes show a high-performance accuracy percentage of 98.2% in the testing dataset using 10-fold cross validation. The automated spatial data mining model provides a solid platform for decision makers to performing landfill site selection and planning operations on a regional scale.

  10. Fermentation process tracking through enhanced spectral calibration modeling.

    Science.gov (United States)

    Triadaphillou, Sophia; Martin, Elaine; Montague, Gary; Norden, Alison; Jeffkins, Paul; Stimpson, Sarah

    2007-06-15

    The FDA process analytical technology (PAT) initiative will materialize in a significant increase in the number of installations of spectroscopic instrumentation. However, to attain the greatest benefit from the data generated, there is a need for calibration procedures that extract the maximum information content. For example, in fermentation processes, the interpretation of the resulting spectra is challenging as a consequence of the large number of wavelengths recorded, the underlying correlation structure that is evident between the wavelengths and the impact of the measurement environment. Approaches to the development of calibration models have been based on the application of partial least squares (PLS) either to the full spectral signature or to a subset of wavelengths. This paper presents a new approach to calibration modeling that combines a wavelength selection procedure, spectral window selection (SWS), where windows of wavelengths are automatically selected which are subsequently used as the basis of the calibration model. However, due to the non-uniqueness of the windows selected when the algorithm is executed repeatedly, multiple models are constructed and these are then combined using stacking thereby increasing the robustness of the final calibration model. The methodology is applied to data generated during the monitoring of broth concentrations in an industrial fermentation process from on-line near-infrared (NIR) and mid-infrared (MIR) spectrometers. It is shown that the proposed calibration modeling procedure outperforms traditional calibration procedures, as well as enabling the identification of the critical regions of the spectra with regard to the fermentation process.

  11. Methods for model selection in applied science and engineering.

    Energy Technology Data Exchange (ETDEWEB)

    Field, Richard V., Jr.

    2004-10-01

    Mathematical models are developed and used to study the properties of complex systems and/or modify these systems to satisfy some performance requirements in just about every area of applied science and engineering. A particular reason for developing a model, e.g., performance assessment or design, is referred to as the model use. Our objective is the development of a methodology for selecting a model that is sufficiently accurate for an intended use. Information on the system being modeled is, in general, incomplete, so that there may be two or more models consistent with the available information. The collection of these models is called the class of candidate models. Methods are developed for selecting the optimal member from a class of candidate models for the system. The optimal model depends on the available information, the selected class of candidate models, and the model use. Classical methods for model selection, including the method of maximum likelihood and Bayesian methods, as well as a method employing a decision-theoretic approach, are formulated to select the optimal model for numerous applications. There is no requirement that the candidate models be random. Classical methods for model selection ignore model use and require data to be available. Examples are used to show that these methods can be unreliable when data is limited. The decision-theoretic approach to model selection does not have these limitations, and model use is included through an appropriate utility function. This is especially important when modeling high risk systems, where the consequences of using an inappropriate model for the system can be disastrous. The decision-theoretic method for model selection is developed and applied for a series of complex and diverse applications. These include the selection of the: (1) optimal order of the polynomial chaos approximation for non-Gaussian random variables and stationary stochastic processes, (2) optimal pressure load model to be

  12. Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

    OpenAIRE

    Ma, Hui-qiang

    2014-01-01

    We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV) process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance effici...

  13. 45 CFR 2400.31 - Selection process.

    Science.gov (United States)

    2010-10-01

    ... FELLOWSHIP PROGRAM REQUIREMENTS Selection of Fellows § 2400.31 Selection process. (a) An independent Fellow... outstanding applicants from each state for James Madison Fellowships. (b) From among candidates recommended...

  14. Post-model selection inference and model averaging

    Directory of Open Access Journals (Sweden)

    Georges Nguefack-Tsague

    2011-07-01

    Full Text Available Although model selection is routinely used in practice nowadays, little is known about its precise effects on any subsequent inference that is carried out. The same goes for the effects induced by the closely related technique of model averaging. This paper is concerned with the use of the same data first to select a model and then to carry out inference, in particular point estimation and point prediction. The properties of the resulting estimator, called a post-model-selection estimator (PMSE, are hard to derive. Using selection criteria such as hypothesis testing, AIC, BIC, HQ and Cp, we illustrate that, in terms of risk function, no single PMSE dominates the others. The same conclusion holds more generally for any penalised likelihood information criterion. We also compare various model averaging schemes and show that no single one dominates the others in terms of risk function. Since PMSEs can be regarded as a special case of model averaging, with 0-1 random-weights, we propose a connection between the two theories, in the frequentist approach, by taking account of the selection procedure when performing model averaging. We illustrate the point by simulating a simple linear regression model.

  15. The Formalization of the Business Process Modeling Goals

    Directory of Open Access Journals (Sweden)

    Ligita Bušinska

    2016-10-01

    Full Text Available In business process modeling the de facto standard BPMN has emerged. However, the applications of this notation have many subsets of elements and various extensions. Also, BPMN still coincides with many other modeling languages, forming a large set of available options for business process modeling languages and dialects. While, in general, the goal of modelers is a central notion in the choice of modeling languages and notations, in most researches that propose guidelines, techniques, and methods for business process modeling language evaluation and/or selection, the business process modeling goal is not formalized and not transparently taken into account. To overcome this gap, and to explicate and help to handle business process modeling complexity, the approach to formalize the business process modeling goal, and the supporting three dimensional business process modeling framework, are proposed.

  16. The site selection process

    International Nuclear Information System (INIS)

    Kittel, J.H.

    1989-01-01

    One of the most arduous tasks associated with the management of radioactive wastes is the siting of new disposal facilities. Experience has shown that the performance of the disposal facility during and after disposal operations is critically dependent on the characteristics of the site itself. The site selection process consists of defining needs and objectives, identifying geographic regions of interest, screening and selecting candidate sites, collecting data on the candidate sites, and finally selecting the preferred site. Before the site selection procedures can be implemented, however, a formal legal system must be in place that defines broad objectives and, most importantly, clearly establishes responsibilities and accompanying authorities for the decision-making steps in the procedure. Site selection authorities should make every effort to develop trust and credibility with the public, local officials, and the news media. The responsibilities of supporting agencies must also be spelled out. Finally, a stable funding arrangement must be established so that activities such as data collection can proceed without interruption. Several examples, both international and within the US, are given

  17. Additive Manufacturing Processes: Selective Laser Melting, Electron Beam Melting and Binder Jetting-Selection Guidelines.

    Science.gov (United States)

    Gokuldoss, Prashanth Konda; Kolla, Sri; Eckert, Jürgen

    2017-06-19

    Additive manufacturing (AM), also known as 3D printing or rapid prototyping, is gaining increasing attention due to its ability to produce parts with added functionality and increased complexities in geometrical design, on top of the fact that it is theoretically possible to produce any shape without limitations. However, most of the research on additive manufacturing techniques are focused on the development of materials/process parameters/products design with different additive manufacturing processes such as selective laser melting, electron beam melting, or binder jetting. However, we do not have any guidelines that discuss the selection of the most suitable additive manufacturing process, depending on the material to be processed, the complexity of the parts to be produced, or the design considerations. Considering the very fact that no reports deal with this process selection, the present manuscript aims to discuss the different selection criteria that are to be considered, in order to select the best AM process (binder jetting/selective laser melting/electron beam melting) for fabricating a specific component with a defined set of material properties.

  18. Additive Manufacturing Processes: Selective Laser Melting, Electron Beam Melting and Binder Jetting—Selection Guidelines

    Science.gov (United States)

    Konda Gokuldoss, Prashanth; Kolla, Sri; Eckert, Jürgen

    2017-01-01

    Additive manufacturing (AM), also known as 3D printing or rapid prototyping, is gaining increasing attention due to its ability to produce parts with added functionality and increased complexities in geometrical design, on top of the fact that it is theoretically possible to produce any shape without limitations. However, most of the research on additive manufacturing techniques are focused on the development of materials/process parameters/products design with different additive manufacturing processes such as selective laser melting, electron beam melting, or binder jetting. However, we do not have any guidelines that discuss the selection of the most suitable additive manufacturing process, depending on the material to be processed, the complexity of the parts to be produced, or the design considerations. Considering the very fact that no reports deal with this process selection, the present manuscript aims to discuss the different selection criteria that are to be considered, in order to select the best AM process (binder jetting/selective laser melting/electron beam melting) for fabricating a specific component with a defined set of material properties. PMID:28773031

  19. The MCDM Model for Personnel Selection Based on SWARA and ARAS Methods

    Directory of Open Access Journals (Sweden)

    Darjan Karabasevic

    2015-05-01

    Full Text Available Competent employees are the key resource in an organization for achieving success and, therefore, competitiveness on the market. The aim of the recruitment and selection process is to acquire personnel with certain competencies required for a particular position, i.e.,a position within the company. Bearing in mind the fact that in the process of decision making decision-makers have underused the methods of making decisions, this paper aims to establish an MCDM model for the evaluation and selection of candidates in the process of the recruitment and selection of personnel based on the SWARA and the ARAS methods. Apart from providing an MCDM model, the paper will additionally provide a set of evaluation criteria for the position of a sales manager (the middle management in the telecommunication industry which will also be used in the numerical example. On the basis of a numerical example, in the process of employment, theproposed MCDMmodel can be successfully usedin selecting candidates.

  20. Modeling of the thermal physical process and study on the reliability of linear energy density for selective laser melting

    Science.gov (United States)

    Xiang, Zhaowei; Yin, Ming; Dong, Guanhua; Mei, Xiaoqin; Yin, Guofu

    2018-06-01

    A finite element model considering volume shrinkage with powder-to-dense process of powder layer in selective laser melting (SLM) is established. Comparison between models that consider and do not consider volume shrinkage or powder-to-dense process is carried out. Further, parametric analysis of laser power and scan speed is conducted and the reliability of linear energy density as a design parameter is investigated. The results show that the established model is an effective method and has better accuracy allowing for the temperature distribution, and the length and depth of molten pool. The maximum temperature is more sensitive to laser power than scan speed. The maximum heating rate and cooling rate increase with increasing scan speed at constant laser power and increase with increasing laser power at constant scan speed as well. The simulation results and experimental result reveal that linear energy density is not always reliable using as a design parameter in the SLM.

  1. Selective hydrogenation processes in steam cracking

    Energy Technology Data Exchange (ETDEWEB)

    Bender, M.; Schroeter, M.K.; Hinrichs, M.; Makarczyk, P. [BASF SE, Ludwigshafen (Germany)

    2010-12-30

    Hydrogen is the key elixir used to trim the quality of olefinic and aromatic product slates from steam crackers. Being co-produced in excess amounts in the thermal cracking process a small part of the hydrogen is consumed in the ''cold part'' of a steam cracker to selectively hydrogenate unwanted, unsaturated hydrocarbons. The compositions of the various steam cracker product streams are adjusted by these processes to the outlet specifications. This presentation gives an overview over state-of-art selective hydrogenation technologies available from BASF for these processes. (Published in summary form only) (orig.)

  2. Verification Techniques for Parameter Selection and Bayesian Model Calibration Presented for an HIV Model

    Science.gov (United States)

    Wentworth, Mami Tonoe

    Uncertainty quantification plays an important role when making predictive estimates of model responses. In this context, uncertainty quantification is defined as quantifying and reducing uncertainties, and the objective is to quantify uncertainties in parameter, model and measurements, and propagate the uncertainties through the model, so that one can make a predictive estimate with quantified uncertainties. Two of the aspects of uncertainty quantification that must be performed prior to propagating uncertainties are model calibration and parameter selection. There are several efficient techniques for these processes; however, the accuracy of these methods are often not verified. This is the motivation for our work, and in this dissertation, we present and illustrate verification frameworks for model calibration and parameter selection in the context of biological and physical models. First, HIV models, developed and improved by [2, 3, 8], describe the viral infection dynamics of an HIV disease. These are also used to make predictive estimates of viral loads and T-cell counts and to construct an optimal control for drug therapy. Estimating input parameters is an essential step prior to uncertainty quantification. However, not all the parameters are identifiable, implying that they cannot be uniquely determined by the observations. These unidentifiable parameters can be partially removed by performing parameter selection, a process in which parameters that have minimal impacts on the model response are determined. We provide verification techniques for Bayesian model calibration and parameter selection for an HIV model. As an example of a physical model, we employ a heat model with experimental measurements presented in [10]. A steady-state heat model represents a prototypical behavior for heat conduction and diffusion process involved in a thermal-hydraulic model, which is a part of nuclear reactor models. We employ this simple heat model to illustrate verification

  3. Review and selection of unsaturated flow models

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1993-09-10

    Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M&O) has the responsibility to review, evaluate, and document existing computer ground-water flow models; to conduct performance assessments; and to develop performance assessment models, where necessary. In the area of scientific modeling, the M&O CRWMS has the following responsibilities: To provide overall management and integration of modeling activities. To provide a framework for focusing modeling and model development. To identify areas that require increased or decreased emphasis. To ensure that the tools necessary to conduct performance assessment are available. These responsibilities are being initiated through a three-step process. It consists of a thorough review of existing models, testing of models which best fit the established requirements, and making recommendations for future development that should be conducted. Future model enhancement will then focus on the models selected during this activity. Furthermore, in order to manage future model development, particularly in those areas requiring substantial enhancement, the three-step process will be updated and reported periodically in the future.

  4. Analytical network process based optimum cluster head selection in wireless sensor network.

    Science.gov (United States)

    Farman, Haleem; Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

    2017-01-01

    Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of

  5. Process cost and facility considerations in the selection of primary cell culture clarification technology.

    Science.gov (United States)

    Felo, Michael; Christensen, Brandon; Higgins, John

    2013-01-01

    The bioreactor volume delineating the selection of primary clarification technology is not always easily defined. Development of a commercial scale process for the manufacture of therapeutic proteins requires scale-up from a few liters to thousands of liters. While the separation techniques used for protein purification are largely conserved across scales, the separation techniques for primary cell culture clarification vary with scale. Process models were developed to compare monoclonal antibody production costs using two cell culture clarification technologies. One process model was created for cell culture clarification by disc stack centrifugation with depth filtration. A second process model was created for clarification by multi-stage depth filtration. Analyses were performed to examine the influence of bioreactor volume, product titer, depth filter capacity, and facility utilization on overall operating costs. At bioreactor volumes 5,000 L, clarification using centrifugation followed by depth filtration offers significant cost savings. For bioreactor volumes of ∼ 2,000 L, clarification costs are similar between depth filtration and centrifugation. At this scale, factors including facility utilization, available capital, ease of process development, implementation timelines, and process performance characterization play an important role in clarification technology selection. In the case study presented, a multi-product facility selected multi-stage depth filtration for cell culture clarification at the 500 and 2,000 L scales of operation. Facility implementation timelines, process development activities, equipment commissioning and validation, scale-up effects, and process robustness are examined. © 2013 American Institute of Chemical Engineers.

  6. Development of Physics-Based Numerical Models for Uncertainty Quantification of Selective Laser Melting Processes

    Data.gov (United States)

    National Aeronautics and Space Administration — The goal of the proposed research is to characterize the influence of process parameter variability inherent to Selective Laser Melting (SLM) and performance effect...

  7. A Heckman Selection- t Model

    KAUST Repository

    Marchenko, Yulia V.

    2012-03-01

    Sample selection arises often in practice as a result of the partial observability of the outcome of interest in a study. In the presence of sample selection, the observed data do not represent a random sample from the population, even after controlling for explanatory variables. That is, data are missing not at random. Thus, standard analysis using only complete cases will lead to biased results. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. The method was criticized in the literature because of its sensitivity to the normality assumption. In practice, data, such as income or expenditure data, often violate the normality assumption because of heavier tails. We first establish a new link between sample selection models and recently studied families of extended skew-elliptical distributions. Then, this allows us to introduce a selection-t (SLt) model, which models the error distribution using a Student\\'s t distribution. We study its properties and investigate the finite-sample performance of the maximum likelihood estimators for this model. We compare the performance of the SLt model to the conventional Heckman selection-normal (SLN) model and apply it to analyze ambulatory expenditures. Unlike the SLNmodel, our analysis using the SLt model provides statistical evidence for the existence of sample selection bias in these data. We also investigate the performance of the test for sample selection bias based on the SLt model and compare it with the performances of several tests used with the SLN model. Our findings indicate that the latter tests can be misleading in the presence of heavy-tailed data. © 2012 American Statistical Association.

  8. Modeling selective attention using a neuromorphic analog VLSI device.

    Science.gov (United States)

    Indiveri, G

    2000-12-01

    Attentional mechanisms are required to overcome the problem of flooding a limited processing capacity system with information. They are present in biological sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) chip, using analog neuromorphic circuits. The chip exploits a spike-based representation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the selective attention mechanism and provide experimental data for each circuit. We demonstrate the expected behavior of the model at the system level by stimulating the chip with both artificially generated control signals and signals obtained from a saliency map, computed from an image containing several salient features.

  9. Behavioral optimization models for multicriteria portfolio selection

    Directory of Open Access Journals (Sweden)

    Mehlawat Mukesh Kumar

    2013-01-01

    Full Text Available In this paper, behavioral construct of suitability is used to develop a multicriteria decision making framework for portfolio selection. To achieve this purpose, we rely on multiple methodologies. Analytical hierarchy process technique is used to model the suitability considerations with a view to obtaining the suitability performance score in respect of each asset. A fuzzy multiple criteria decision making method is used to obtain the financial quality score of each asset based upon investor's rating on the financial criteria. Two optimization models are developed for optimal asset allocation considering simultaneously financial and suitability criteria. An empirical study is conducted on randomly selected assets from National Stock Exchange, Mumbai, India to demonstrate the effectiveness of the proposed methodology.

  10. HOW DO STUDENTS SELECT SOCIAL NETWORKING SITES? AN ANALYTIC HIERARCHY PROCESS (AHP MODEL

    Directory of Open Access Journals (Sweden)

    Chun Meng Tang

    2015-12-01

    Full Text Available Social networking sites are popular among university students, and students today are indeed spoiled for choice. New emerging social networking sites sprout up amid popular sites, while some existing ones die out. Given the choice of so many social networking sites, how do students decide which one they will sign up for and stay on as an active user? The answer to this question is of interest to social networking site designers and marketers. The market of social networking sites is highly competitive. To maintain the current user base and continue to attract new users, how should social networking sites design their sites? Marketers spend a fairly large percent of their marketing budget on social media marketing. To formulate an effective social media strategy, how much do marketers understand the users of social networking sites? Learning from website evaluation studies, this study intends to provide some answers to these questions by examining how university students decide between two popular social networking sites, Facebook and Twitter. We first developed an analytic hierarchy process (AHP model of four main selection criteria and 12 sub-criteria, and then administered a questionnaire to a group of university students attending a course at a Malaysian university. AHP analyses of the responses from 12 respondents provided an insight into the decision-making process involved in students’ selection of social networking sites. It seemed that of the four main criteria, privacy was the top concern, followed by functionality, usability, and content. The sub-criteria that were of key concern to the students were apps, revenue-generating opportunities, ease of use, and information security. Between Facebook and Twitter, the students thought that Facebook was the better choice. This information is useful for social networking site designers to design sites that are more relevant to their users’ needs, and for marketers to craft more effective

  11. Waste package materials selection process

    International Nuclear Information System (INIS)

    Roy, A.K.; Fish, R.L.; McCright, R.D.

    1994-01-01

    The office of Civilian Radioactive Waste Management (OCRWM) of the United States Department of Energy (USDOE) is evaluating a site at Yucca Mountain in Southern Nevada to determine its suitability as a mined geologic disposal system (MGDS) for the disposal of high-level nuclear waste (HLW). The B ampersand W Fuel Company (BWFC), as a part of the Management and Operating (M ampersand O) team in support of the Yucca Mountain Site Characterization Project (YMP), is responsible for designing and developing the waste package for this potential repository. As part of this effort, Lawrence Livermore National Laboratory (LLNL) is responsible for testing materials and developing models for the materials to be used in the waste package. This paper is aimed at presenting the selection process for materials needed in fabricating the different components of the waste package

  12. Selection, calibration, and validation of models of tumor growth.

    Science.gov (United States)

    Lima, E A B F; Oden, J T; Hormuth, D A; Yankeelov, T E; Almeida, R C

    2016-11-01

    This paper presents general approaches for addressing some of the most important issues in predictive computational oncology concerned with developing classes of predictive models of tumor growth. First, the process of developing mathematical models of vascular tumors evolving in the complex, heterogeneous, macroenvironment of living tissue; second, the selection of the most plausible models among these classes, given relevant observational data; third, the statistical calibration and validation of models in these classes, and finally, the prediction of key Quantities of Interest (QOIs) relevant to patient survival and the effect of various therapies. The most challenging aspects of this endeavor is that all of these issues often involve confounding uncertainties: in observational data, in model parameters, in model selection, and in the features targeted in the prediction. Our approach can be referred to as "model agnostic" in that no single model is advocated; rather, a general approach that explores powerful mixture-theory representations of tissue behavior while accounting for a range of relevant biological factors is presented, which leads to many potentially predictive models. Then representative classes are identified which provide a starting point for the implementation of OPAL, the Occam Plausibility Algorithm (OPAL) which enables the modeler to select the most plausible models (for given data) and to determine if the model is a valid tool for predicting tumor growth and morphology ( in vivo ). All of these approaches account for uncertainties in the model, the observational data, the model parameters, and the target QOI. We demonstrate these processes by comparing a list of models for tumor growth, including reaction-diffusion models, phase-fields models, and models with and without mechanical deformation effects, for glioma growth measured in murine experiments. Examples are provided that exhibit quite acceptable predictions of tumor growth in laboratory

  13. Selecting an optimal mixed products using grey relationship model

    Directory of Open Access Journals (Sweden)

    Farshad Faezy Razi

    2013-06-01

    Full Text Available This paper presents an integrated supplier selection and inventory management using grey relationship model (GRM as well as multi-objective decision making process. The proposed model of this paper first ranks different suppliers based on GRM technique and then determines the optimum level of inventory by considering different objectives. To show the implementation of the proposed model, we use some benchmark data presented by Talluri and Baker [Talluri, S., & Baker, R. C. (2002. A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research, 141(3, 544-558.]. The preliminary results indicate that the proposed model of this paper is capable of handling different criteria for supplier selection.

  14. A finite volume alternate direction implicit approach to modeling selective laser melting

    DEFF Research Database (Denmark)

    Hattel, Jesper Henri; Mohanty, Sankhya

    2013-01-01

    Over the last decade, several studies have attempted to develop thermal models for analyzing the selective laser melting process with a vision to predict thermal stresses, microstructures and resulting mechanical properties of manufactured products. While a holistic model addressing all involved...... to accurately simulate the process, are constrained by either the size or scale of the model domain. A second challenging aspect involves the inclusion of non-linear material behavior into the 3D implicit FE models. An alternating direction implicit (ADI) method based on a finite volume (FV) formulation...... is proposed for modeling single-layer and few-layers selective laser melting processes. The ADI technique is implemented and applied for two cases involving constant material properties and non-linear material behavior. The ADI FV method consume less time while having comparable accuracy with respect to 3D...

  15. Multi-Criteria Decision Making For Determining A Simple Model of Supplier Selection

    Science.gov (United States)

    Harwati

    2017-06-01

    Supplier selection is a decision with many criteria. Supplier selection model usually involves more than five main criteria and more than 10 sub-criteria. In fact many model includes more than 20 criteria. Too many criteria involved in supplier selection models sometimes make it difficult to apply in many companies. This research focuses on designing supplier selection that easy and simple to be applied in the company. Analytical Hierarchy Process (AHP) is used to weighting criteria. The analysis results there are four criteria that are easy and simple can be used to select suppliers: Price (weight 0.4) shipment (weight 0.3), quality (weight 0.2) and services (weight 0.1). A real case simulation shows that simple model provides the same decision with a more complex model.

  16. Modeling selective pressures on phytoplankton in the global ocean.

    Directory of Open Access Journals (Sweden)

    Jason G Bragg

    Full Text Available Our view of marine microbes is transforming, as culture-independent methods facilitate rapid characterization of microbial diversity. It is difficult to assimilate this information into our understanding of marine microbe ecology and evolution, because their distributions, traits, and genomes are shaped by forces that are complex and dynamic. Here we incorporate diverse forces--physical, biogeochemical, ecological, and mutational--into a global ocean model to study selective pressures on a simple trait in a widely distributed lineage of picophytoplankton: the nitrogen use abilities of Synechococcus and Prochlorococcus cyanobacteria. Some Prochlorococcus ecotypes have lost the ability to use nitrate, whereas their close relatives, marine Synechococcus, typically retain it. We impose mutations for the loss of nitrogen use abilities in modeled picophytoplankton, and ask: in which parts of the ocean are mutants most disadvantaged by losing the ability to use nitrate, and in which parts are they least disadvantaged? Our model predicts that this selective disadvantage is smallest for picophytoplankton that live in tropical regions where Prochlorococcus are abundant in the real ocean. Conversely, the selective disadvantage of losing the ability to use nitrate is larger for modeled picophytoplankton that live at higher latitudes, where Synechococcus are abundant. In regions where we expect Prochlorococcus and Synechococcus populations to cycle seasonally in the real ocean, we find that model ecotypes with seasonal population dynamics similar to Prochlorococcus are less disadvantaged by losing the ability to use nitrate than model ecotypes with seasonal population dynamics similar to Synechococcus. The model predictions for the selective advantage associated with nitrate use are broadly consistent with the distribution of this ability among marine picocyanobacteria, and at finer scales, can provide insights into interactions between temporally varying

  17. Modeling selective pressures on phytoplankton in the global ocean.

    Science.gov (United States)

    Bragg, Jason G; Dutkiewicz, Stephanie; Jahn, Oliver; Follows, Michael J; Chisholm, Sallie W

    2010-03-10

    Our view of marine microbes is transforming, as culture-independent methods facilitate rapid characterization of microbial diversity. It is difficult to assimilate this information into our understanding of marine microbe ecology and evolution, because their distributions, traits, and genomes are shaped by forces that are complex and dynamic. Here we incorporate diverse forces--physical, biogeochemical, ecological, and mutational--into a global ocean model to study selective pressures on a simple trait in a widely distributed lineage of picophytoplankton: the nitrogen use abilities of Synechococcus and Prochlorococcus cyanobacteria. Some Prochlorococcus ecotypes have lost the ability to use nitrate, whereas their close relatives, marine Synechococcus, typically retain it. We impose mutations for the loss of nitrogen use abilities in modeled picophytoplankton, and ask: in which parts of the ocean are mutants most disadvantaged by losing the ability to use nitrate, and in which parts are they least disadvantaged? Our model predicts that this selective disadvantage is smallest for picophytoplankton that live in tropical regions where Prochlorococcus are abundant in the real ocean. Conversely, the selective disadvantage of losing the ability to use nitrate is larger for modeled picophytoplankton that live at higher latitudes, where Synechococcus are abundant. In regions where we expect Prochlorococcus and Synechococcus populations to cycle seasonally in the real ocean, we find that model ecotypes with seasonal population dynamics similar to Prochlorococcus are less disadvantaged by losing the ability to use nitrate than model ecotypes with seasonal population dynamics similar to Synechococcus. The model predictions for the selective advantage associated with nitrate use are broadly consistent with the distribution of this ability among marine picocyanobacteria, and at finer scales, can provide insights into interactions between temporally varying ocean processes and

  18. Characteristics of products generated by selective sintering and stereolithography rapid prototyping processes

    Science.gov (United States)

    Cariapa, Vikram

    1993-01-01

    The trend in the modern global economy towards free market policies has motivated companies to use rapid prototyping technologies to not only reduce product development cycle time but also to maintain their competitive edge. A rapid prototyping technology is one which combines computer aided design with computer controlled tracking of focussed high energy source (eg. lasers, heat) on modern ceramic powders, metallic powders, plastics or photosensitive liquid resins in order to produce prototypes or models. At present, except for the process of shape melting, most rapid prototyping processes generate products that are only dimensionally similar to those of the desired end product. There is an urgent need, therefore, to enhance the understanding of the characteristics of these processes in order to realize their potential for production. Currently, the commercial market is dominated by four rapid prototyping processes, namely selective laser sintering, stereolithography, fused deposition modelling and laminated object manufacturing. This phase of the research has focussed on the selective laser sintering and stereolithography rapid prototyping processes. A theoretical model for these processes is under development. Different rapid prototyping sites supplied test specimens (based on ASTM 638-84, Type I) that have been measured and tested to provide a data base on surface finish, dimensional variation and ultimate tensile strength. Further plans call for developing and verifying the theoretical models by carefully designed experiments. This will be a joint effort between NASA and other prototyping centers to generate a larger database, thus encouraging more widespread usage by product designers.

  19. The Added Value of the Project Selection Process

    Directory of Open Access Journals (Sweden)

    Adel Oueslati

    2016-06-01

    Full Text Available The project selection process comes in the first stage of the overall project management life cycle. It does have a very important impact on organization success. The present paper provides defi nitions of the basic concepts and tools related to the project selection process. It aims to stress the added value of this process for the entire organization success. The mastery of the project selection process is the right way for any organization to ensure that it will do the right project with the right resources at the right time and within the right priorities

  20. Fermentation process diagnosis using a mathematical model

    Energy Technology Data Exchange (ETDEWEB)

    Yerushalmi, L; Volesky, B; Votruba, J

    1988-09-01

    Intriguing physiology of a solvent-producing strain of Clostridium acetobutylicum led to the synthesis of a mathematical model of the acetone-butanol fermentation process. The model presented is capable of describing the process dynamics and the culture behavior during a standard and a substandard acetone-butanol fermentation. In addition to the process kinetic parameters, the model includes the culture physiological parameters, such as the cellular membrane permeability and the number of membrane sites for active transport of sugar. Computer process simulation studies for different culture conditions used the model, and quantitatively pointed out the importance of selected culture parameters that characterize the cell membrane behaviour and play an important role in the control of solvent synthesis by the cell. The theoretical predictions by the new model were confirmed by experimental determination of the cellular membrane permeability.

  1. A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

    Directory of Open Access Journals (Sweden)

    Chung-Min Wu

    2013-01-01

    Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.

  2. Large deviations for the Fleming-Viot process with neutral mutation and selection

    OpenAIRE

    Dawson, Donald; Feng, Shui

    1998-01-01

    Large deviation principles are established for the Fleming-Viot processes with neutral mutation and selection, and the corresponding equilibrium measures as the sampling rate goes to 0. All results are first proved for the finite allele model, and then generalized, through the projective limit technique, to the infinite allele model. Explicit expressions are obtained for the rate functions.

  3. Laser dimpling process parameters selection and optimization using surrogate-driven process capability space

    Science.gov (United States)

    Ozkat, Erkan Caner; Franciosa, Pasquale; Ceglarek, Dariusz

    2017-08-01

    Remote laser welding technology offers opportunities for high production throughput at a competitive cost. However, the remote laser welding process of zinc-coated sheet metal parts in lap joint configuration poses a challenge due to the difference between the melting temperature of the steel (∼1500 °C) and the vapourizing temperature of the zinc (∼907 °C). In fact, the zinc layer at the faying surface is vapourized and the vapour might be trapped within the melting pool leading to weld defects. Various solutions have been proposed to overcome this problem over the years. Among them, laser dimpling has been adopted by manufacturers because of its flexibility and effectiveness along with its cost advantages. In essence, the dimple works as a spacer between the two sheets in lap joint and allows the zinc vapour escape during welding process, thereby preventing weld defects. However, there is a lack of comprehensive characterization of dimpling process for effective implementation in real manufacturing system taking into consideration inherent changes in variability of process parameters. This paper introduces a methodology to develop (i) surrogate model for dimpling process characterization considering multiple-inputs (i.e. key control characteristics) and multiple-outputs (i.e. key performance indicators) system by conducting physical experimentation and using multivariate adaptive regression splines; (ii) process capability space (Cp-Space) based on the developed surrogate model that allows the estimation of a desired process fallout rate in the case of violation of process requirements in the presence of stochastic variation; and, (iii) selection and optimization of the process parameters based on the process capability space. The proposed methodology provides a unique capability to: (i) simulate the effect of process variation as generated by manufacturing process; (ii) model quality requirements with multiple and coupled quality requirements; and (iii

  4. Evaluation and selection of in-situ leaching mining method using analytic hierarchy process

    International Nuclear Information System (INIS)

    Zhao Heyong; Tan Kaixuan; Liu Huizhen

    2007-01-01

    According to the complicated conditions and main influence factors of in-situ leaching min- ing, a model and processes of analytic hierarchy are established for evaluation and selection of in-situ leaching mining methods based on analytic hierarchy process. Taking a uranium mine in Xinjiang of China for example, the application of this model is presented. The results of analyses and calculation indicate that the acid leaching is the optimum project. (authors)

  5. Variable selection in Logistic regression model with genetic algorithm.

    Science.gov (United States)

    Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

    2018-02-01

    Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

  6. Evaluation and comparison of alternative fleet-level selective maintenance models

    International Nuclear Information System (INIS)

    Schneider, Kellie; Richard Cassady, C.

    2015-01-01

    Fleet-level selective maintenance refers to the process of identifying the subset of maintenance actions to perform on a fleet of repairable systems when the maintenance resources allocated to the fleet are insufficient for performing all desirable maintenance actions. The original fleet-level selective maintenance model is designed to maximize the probability that all missions in a future set are completed successfully. We extend this model in several ways. First, we consider a cost-based optimization model and show that a special case of this model maximizes the expected value of the number of successful missions in the future set. We also consider the situation in which one or more of the future missions may be canceled. These models and the original fleet-level selective maintenance optimization models are nonlinear. Therefore, we also consider an alternative model in which the objective function can be linearized. We show that the alternative model is a good approximation to the other models. - Highlights: • Investigate nonlinear fleet-level selective maintenance optimization models. • A cost based model is used to maximize the expected number of successful missions. • Another model is allowed to cancel missions if reliability is sufficiently low. • An alternative model has an objective function that can be linearized. • We show that the alternative model is a good approximation to the other models

  7. Process-based models of feeding and prey selection in larval fish

    DEFF Research Database (Denmark)

    Fiksen, O.; MacKenzie, Brian

    2002-01-01

    believed to be important to prey selectivity and environmental regulation of feeding in fish. We include the sensitivity of prey to the hydrodynamic signal generated by approaching larval fish and a simple model of the potential loss of prey due to turbulence whereby prey is lost if it leaves...... jig dry wt l(-1). The spatio-temporal fluctuation of turbulence (tidal cycle) and light (sun height) over the bank generates complex structure in the patterns of food intake of larval fish, with different patterns emerging for small and large larvae....

  8. Algorithms of control parameters selection for automation of FDM 3D printing process

    Directory of Open Access Journals (Sweden)

    Kogut Paweł

    2017-01-01

    Full Text Available The paper presents algorithms of control parameters selection of the Fused Deposition Modelling (FDM technology in case of an open printing solutions environment and 3DGence ONE printer. The following parameters were distinguished: model mesh density, material flow speed, cooling performance, retraction and printing speeds. These parameters are independent in principle printing system, but in fact to a certain degree that results from the selected printing equipment features. This is the first step for automation of the 3D printing process in FDM technology.

  9. Multiphysics modeling of selective laser sintering/melting

    Science.gov (United States)

    Ganeriwala, Rishi Kumar

    A significant percentage of total global employment is due to the manufacturing industry. However, manufacturing also accounts for nearly 20% of total energy usage in the United States according to the EIA. In fact, manufacturing accounted for 90% of industrial energy consumption and 84% of industry carbon dioxide emissions in 2002. Clearly, advances in manufacturing technology and efficiency are necessary to curb emissions and help society as a whole. Additive manufacturing (AM) refers to a relatively recent group of manufacturing technologies whereby one can 3D print parts, which has the potential to significantly reduce waste, reconfigure the supply chain, and generally disrupt the whole manufacturing industry. Selective laser sintering/melting (SLS/SLM) is one type of AM technology with the distinct advantage of being able to 3D print metals and rapidly produce net shape parts with complicated geometries. In SLS/SLM parts are built up layer-by-layer out of powder particles, which are selectively sintered/melted via a laser. However, in order to produce defect-free parts of sufficient strength, the process parameters (laser power, scan speed, layer thickness, powder size, etc.) must be carefully optimized. Obviously, these process parameters will vary depending on material, part geometry, and desired final part characteristics. Running experiments to optimize these parameters is costly, energy intensive, and extremely material specific. Thus a computational model of this process would be highly valuable. In this work a three dimensional, reduced order, coupled discrete element - finite difference model is presented for simulating the deposition and subsequent laser heating of a layer of powder particles sitting on top of a substrate. Validation is provided and parameter studies are conducted showing the ability of this model to help determine appropriate process parameters and an optimal powder size distribution for a given material. Next, thermal stresses upon

  10. Model Identification of Integrated ARMA Processes

    Science.gov (United States)

    Stadnytska, Tetiana; Braun, Simone; Werner, Joachim

    2008-01-01

    This article evaluates the Smallest Canonical Correlation Method (SCAN) and the Extended Sample Autocorrelation Function (ESACF), automated methods for the Autoregressive Integrated Moving-Average (ARIMA) model selection commonly available in current versions of SAS for Windows, as identification tools for integrated processes. SCAN and ESACF can…

  11. Computer modeling of lung cancer diagnosis-to-treatment process.

    Science.gov (United States)

    Ju, Feng; Lee, Hyo Kyung; Osarogiagbon, Raymond U; Yu, Xinhua; Faris, Nick; Li, Jingshan

    2015-08-01

    We introduce an example of a rigorous, quantitative method for quality improvement in lung cancer care-delivery. Computer process modeling methods are introduced for lung cancer diagnosis, staging and treatment selection process. Two types of process modeling techniques, discrete event simulation (DES) and analytical models, are briefly reviewed. Recent developments in DES are outlined and the necessary data and procedures to develop a DES model for lung cancer diagnosis, leading up to surgical treatment process are summarized. The analytical models include both Markov chain model and closed formulas. The Markov chain models with its application in healthcare are introduced and the approach to derive a lung cancer diagnosis process model is presented. Similarly, the procedure to derive closed formulas evaluating the diagnosis process performance is outlined. Finally, the pros and cons of these methods are discussed.

  12. Risk calculations in the manufacturing technology selection process

    DEFF Research Database (Denmark)

    Farooq, S.; O'Brien, C.

    2010-01-01

    Purpose - The purpose of this paper is to present result obtained from a developed technology selection framework and provide a detailed insight into the risk calculations and their implications in manufacturing technology selection process. Design/methodology/approach - The results illustrated...... in the paper are the outcome of an action research study that was conducted in an aerospace company. Findings - The paper highlights the role of risk calculations in manufacturing technology selection process by elaborating the contribution of risk associated with manufacturing technology alternatives...... in the shape of opportunities and threats in different decision-making environments. Practical implications - The research quantifies the risk associated with different available manufacturing technology alternatives. This quantification of risk crystallises the process of technology selection decision making...

  13. A concurrent optimization model for supplier selection with fuzzy quality loss

    International Nuclear Information System (INIS)

    Rosyidi, C.; Murtisari, R.; Jauhari, W.

    2017-01-01

    The purpose of this research is to develop a concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification. Design/methodology/approach: This research integrates fuzzy quality loss in the model to concurrently solve the decision making in detailed design stage and manufacturing stage. Findings: The resulted model can be used to concurrently select the optimal supplier and determine the tolerance of the components. The model balances the purchasing cost and fuzzy quality loss. Originality/value: An assembled product consists of many components which must be purchased from the suppliers. Fuzzy quality loss is integrated in the supplier selection model to allow the vagueness in final assembly by grouping the assembly into several grades according to the resulted assembly tolerance.

  14. A concurrent optimization model for supplier selection with fuzzy quality loss

    Energy Technology Data Exchange (ETDEWEB)

    Rosyidi, C.; Murtisari, R.; Jauhari, W.

    2017-07-01

    The purpose of this research is to develop a concurrent supplier selection model to minimize the purchasing cost and fuzzy quality loss considering process capability and assembled product specification. Design/methodology/approach: This research integrates fuzzy quality loss in the model to concurrently solve the decision making in detailed design stage and manufacturing stage. Findings: The resulted model can be used to concurrently select the optimal supplier and determine the tolerance of the components. The model balances the purchasing cost and fuzzy quality loss. Originality/value: An assembled product consists of many components which must be purchased from the suppliers. Fuzzy quality loss is integrated in the supplier selection model to allow the vagueness in final assembly by grouping the assembly into several grades according to the resulted assembly tolerance.

  15. Model selection in periodic autoregressions

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)

    1994-01-01

    textabstractThis paper focuses on the issue of period autoagressive time series models (PAR) selection in practice. One aspect of model selection is the choice for the appropriate PAR order. This can be of interest for the valuation of economic models. Further, the appropriate PAR order is important

  16. Exploring selection and recruitment processes for newly qualified nurses: a sequential-explanatory mixed-method study.

    Science.gov (United States)

    Newton, Paul; Chandler, Val; Morris-Thomson, Trish; Sayer, Jane; Burke, Linda

    2015-01-01

    To map current selection and recruitment processes for newly qualified nurses and to explore the advantages and limitations of current selection and recruitment processes. The need to improve current selection and recruitment practices for newly qualified nurses is highlighted in health policy internationally. A cross-sectional, sequential-explanatory mixed-method design with 4 components: (1) Literature review of selection and recruitment of newly qualified nurses; and (2) Literature review of a public sector professions' selection and recruitment processes; (3) Survey mapping existing selection and recruitment processes for newly qualified nurses; and (4) Qualitative study about recruiters' selection and recruitment processes. Literature searches on the selection and recruitment of newly qualified candidates in teaching and nursing (2005-2013) were conducted. Cross-sectional, mixed-method data were collected from thirty-one (n = 31) individuals in health providers in London who had responsibility for the selection and recruitment of newly qualified nurses using a survey instrument. Of these providers who took part, six (n = 6) purposively selected to be interviewed qualitatively. Issues of supply and demand in the workforce, rather than selection and recruitment tools, predominated in the literature reviews. Examples of tools to measure values, attitudes and skills were found in the nursing literature. The mapping exercise found that providers used many selection and recruitment tools, some providers combined tools to streamline process and assure quality of candidates. Most providers had processes which addressed the issue of quality in the selection and recruitment of newly qualified nurses. The 'assessment centre model', which providers were adopting, allowed for multiple levels of assessment and streamlined recruitment. There is a need to validate the efficacy of the selection tools. © 2014 John Wiley & Sons Ltd.

  17. 7 CFR 1469.6 - Enrollment criteria and selection process.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 10 2010-01-01 2010-01-01 false Enrollment criteria and selection process. 1469.6... General Provisions § 1469.6 Enrollment criteria and selection process. (a) Selection and funding of... existing natural resource, environmental quality, and agricultural activity data along with other...

  18. Computationally efficient thermal-mechanical modelling of selective laser melting

    NARCIS (Netherlands)

    Yang, Y.; Ayas, C.; Brabazon, Dermot; Naher, Sumsun; Ul Ahad, Inam

    2017-01-01

    The Selective laser melting (SLM) is a powder based additive manufacturing (AM) method to produce high density metal parts with complex topology. However, part distortions and accompanying residual stresses deteriorates the mechanical reliability of SLM products. Modelling of the SLM process is

  19. A Primer for Model Selection: The Decisive Role of Model Complexity

    Science.gov (United States)

    Höge, Marvin; Wöhling, Thomas; Nowak, Wolfgang

    2018-03-01

    Selecting a "best" model among several competing candidate models poses an often encountered problem in water resources modeling (and other disciplines which employ models). For a modeler, the best model fulfills a certain purpose best (e.g., flood prediction), which is typically assessed by comparing model simulations to data (e.g., stream flow). Model selection methods find the "best" trade-off between good fit with data and model complexity. In this context, the interpretations of model complexity implied by different model selection methods are crucial, because they represent different underlying goals of modeling. Over the last decades, numerous model selection criteria have been proposed, but modelers who primarily want to apply a model selection criterion often face a lack of guidance for choosing the right criterion that matches their goal. We propose a classification scheme for model selection criteria that helps to find the right criterion for a specific goal, i.e., which employs the correct complexity interpretation. We identify four model selection classes which seek to achieve high predictive density, low predictive error, high model probability, or shortest compression of data. These goals can be achieved by following either nonconsistent or consistent model selection and by either incorporating a Bayesian parameter prior or not. We allocate commonly used criteria to these four classes, analyze how they represent model complexity and what this means for the model selection task. Finally, we provide guidance on choosing the right type of criteria for specific model selection tasks. (A quick guide through all key points is given at the end of the introduction.)

  20. Data-driven process decomposition and robust online distributed modelling for large-scale processes

    Science.gov (United States)

    Shu, Zhang; Lijuan, Li; Lijuan, Yao; Shipin, Yang; Tao, Zou

    2018-02-01

    With the increasing attention of networked control, system decomposition and distributed models show significant importance in the implementation of model-based control strategy. In this paper, a data-driven system decomposition and online distributed subsystem modelling algorithm was proposed for large-scale chemical processes. The key controlled variables are first partitioned by affinity propagation clustering algorithm into several clusters. Each cluster can be regarded as a subsystem. Then the inputs of each subsystem are selected by offline canonical correlation analysis between all process variables and its controlled variables. Process decomposition is then realised after the screening of input and output variables. When the system decomposition is finished, the online subsystem modelling can be carried out by recursively block-wise renewing the samples. The proposed algorithm was applied in the Tennessee Eastman process and the validity was verified.

  1. Modeling Dynamic Food Choice Processes to Understand Dietary Intervention Effects.

    Science.gov (United States)

    Marcum, Christopher Steven; Goldring, Megan R; McBride, Colleen M; Persky, Susan

    2018-02-17

    Meal construction is largely governed by nonconscious and habit-based processes that can be represented as a collection of in dividual, micro-level food choices that eventually give rise to a final plate. Despite this, dietary behavior intervention research rarely captures these micro-level food choice processes, instead measuring outcomes at aggregated levels. This is due in part to a dearth of analytic techniques to model these dynamic time-series events. The current article addresses this limitation by applying a generalization of the relational event framework to model micro-level food choice behavior following an educational intervention. Relational event modeling was used to model the food choices that 221 mothers made for their child following receipt of an information-based intervention. Participants were randomized to receive either (a) control information; (b) childhood obesity risk information; (c) childhood obesity risk information plus a personalized family history-based risk estimate for their child. Participants then made food choices for their child in a virtual reality-based food buffet simulation. Micro-level aspects of the built environment, such as the ordering of each food in the buffet, were influential. Other dynamic processes such as choice inertia also influenced food selection. Among participants receiving the strongest intervention condition, choice inertia decreased and the overall rate of food selection increased. Modeling food selection processes can elucidate the points at which interventions exert their influence. Researchers can leverage these findings to gain insight into nonconscious and uncontrollable aspects of food selection that influence dietary outcomes, which can ultimately improve the design of dietary interventions.

  2. The Automation of Nowcast Model Assessment Processes

    Science.gov (United States)

    2016-09-01

    secondly, provide modelers with the information needed to understand the model errors and how their algorithm changes might mitigate these errors. In...by ARL modelers. 2. Development Environment The automation of Point-Stat processes (i.e., PSA) was developed using Python 3.5.* Python was selected...because it is easy to use, widely used for scripting, and satisfies all the requirements to automate the implementation of the Point-Stat tool. In

  3. A Heckman selection model for the safety analysis of signalized intersections.

    Directory of Open Access Journals (Sweden)

    Xuecai Xu

    Full Text Available The objective of this paper is to provide a new method for estimating crash rate and severity simultaneously.This study explores a Heckman selection model of the crash rate and severity simultaneously at different levels and a two-step procedure is used to investigate the crash rate and severity levels. The first step uses a probit regression model to determine the sample selection process, and the second step develops a multiple regression model to simultaneously evaluate the crash rate and severity for slight injury/kill or serious injury (KSI, respectively. The model uses 555 observations from 262 signalized intersections in the Hong Kong metropolitan area, integrated with information on the traffic flow, geometric road design, road environment, traffic control and any crashes that occurred during two years.The results of the proposed two-step Heckman selection model illustrate the necessity of different crash rates for different crash severity levels.A comparison with the existing approaches suggests that the Heckman selection model offers an efficient and convenient alternative method for evaluating the safety performance at signalized intersections.

  4. Selective detachment process in column flotation froth

    Energy Technology Data Exchange (ETDEWEB)

    Honaker, R.Q.; Ozsever, A.V.; Parekh, B.K. [University of Kentucky, Lexington, KY (United States). Dept. of Mining Engineering

    2006-05-15

    The selectivity in flotation columns involving the separation of particles of varying degrees of floatability is based on differential flotation rates in the collection zone, reflux action between the froth and collection zones, and differential detachment rates in the froth zone. Using well-known theoretical models describing the separation process and experimental data, froth zone and overall flotation recovery values were quantified for particles in an anthracite coal that have a wide range of floatability potential. For highly floatable particles, froth recovery had a very minimal impact on overall recovery while the recovery of weakly floatable material was decreased substantially by reductions in froth recovery values. In addition, under carrying-capacity limiting conditions, selectivity was enhanced by the preferential detachment of the weakly floatable material. Based on this concept, highly floatable material was added directly into the froth zone when treating the anthracite coal. The enriched froth phase reduced the product ash content of the anthracite product by five absolute percentage points while maintaining a constant recovery value.

  5. The partner selection process : Steps, effectiveness, governance

    NARCIS (Netherlands)

    Duisters, D.; Duijsters, G.M.; de Man, A.P.

    2011-01-01

    Selecting the right partner is important for creating value in alliances. Even though prior research suggests that a structured partner selection process increases alliance success, empirical research remains scarce. This paper presents an explorative empirical study that shows that some steps in

  6. The partner selection process : steps, effectiveness, governance

    NARCIS (Netherlands)

    Duisters, D.; Duysters, G.M.; Man, de A.P.

    2011-01-01

    Selecting the right partner is important for creating value in alliances. Even though prior research suggests that a structured partner selection process increases alliance success, empirical research remains scarce. This paper presents an explorative empirical study that shows that some steps in

  7. PopGen Fishbowl: A Free Online Simulation Model of Microevolutionary Processes

    Science.gov (United States)

    Jones, Thomas C.; Laughlin, Thomas F.

    2010-01-01

    Natural selection and other components of evolutionary theory are known to be particularly challenging concepts for students to understand. To help illustrate these concepts, we developed a simulation model of microevolutionary processes. The model features all the components of Hardy-Weinberg theory, with population size, selection, gene flow,…

  8. Optimal processing pathway selection for microalgae-based biorefinery under uncertainty

    DEFF Research Database (Denmark)

    Rizwan, Muhammad; Zaman, Muhammad; Lee, Jay H.

    2015-01-01

    We propose a systematic framework for the selection of optimal processing pathways for a microalgaebased biorefinery under techno-economic uncertainty. The proposed framework promotes robust decision making by taking into account the uncertainties that arise due to inconsistencies among...... and shortage in the available technical information. A stochastic mixed integer nonlinear programming (sMINLP) problem is formulated for determining the optimal biorefinery configurations based on a superstructure model where parameter uncertainties are modeled and included as sampled scenarios. The solution...... the accounting of uncertainty are compared with respect to different objectives. (C) 2015 Elsevier Ltd. All rights reserved....

  9. Pedagogic process modeling: Humanistic-integrative approach

    Directory of Open Access Journals (Sweden)

    Boritko Nikolaj M.

    2007-01-01

    Full Text Available The paper deals with some current problems of modeling the dynamics of the subject-features development of the individual. The term "process" is considered in the context of the humanistic-integrative approach, in which the principles of self education are regarded as criteria for efficient pedagogic activity. Four basic characteristics of the pedagogic process are pointed out: intentionality reflects logicality and regularity of the development of the process; discreteness (stageability in dicates qualitative stages through which the pedagogic phenomenon passes; nonlinearity explains the crisis character of pedagogic processes and reveals inner factors of self-development; situationality requires a selection of pedagogic conditions in accordance with the inner factors, which would enable steering the pedagogic process. Offered are two steps for singling out a particular stage and the algorithm for developing an integrative model for it. The suggested conclusions might be of use for further theoretic research, analyses of educational practices and for realistic predicting of pedagogical phenomena. .

  10. Models of microbiome evolution incorporating host and microbial selection.

    Science.gov (United States)

    Zeng, Qinglong; Wu, Steven; Sukumaran, Jeet; Rodrigo, Allen

    2017-09-25

    Numerous empirical studies suggest that hosts and microbes exert reciprocal selective effects on their ecological partners. Nonetheless, we still lack an explicit framework to model the dynamics of both hosts and microbes under selection. In a previous study, we developed an agent-based forward-time computational framework to simulate the neutral evolution of host-associated microbial communities in a constant-sized, unstructured population of hosts. These neutral models allowed offspring to sample microbes randomly from parents and/or from the environment. Additionally, the environmental pool of available microbes was constituted by fixed and persistent microbial OTUs and by contributions from host individuals in the preceding generation. In this paper, we extend our neutral models to allow selection to operate on both hosts and microbes. We do this by constructing a phenome for each microbial OTU consisting of a sample of traits that influence host and microbial fitnesses independently. Microbial traits can influence the fitness of hosts ("host selection") and the fitness of microbes ("trait-mediated microbial selection"). Additionally, the fitness effects of traits on microbes can be modified by their hosts ("host-mediated microbial selection"). We simulate the effects of these three types of selection, individually or in combination, on microbiome diversities and the fitnesses of hosts and microbes over several thousand generations of hosts. We show that microbiome diversity is strongly influenced by selection acting on microbes. Selection acting on hosts only influences microbiome diversity when there is near-complete direct or indirect parental contribution to the microbiomes of offspring. Unsurprisingly, microbial fitness increases under microbial selection. Interestingly, when host selection operates, host fitness only increases under two conditions: (1) when there is a strong parental contribution to microbial communities or (2) in the absence of a strong

  11. Numerical simulation of complex part manufactured by selective laser melting process

    Science.gov (United States)

    Van Belle, Laurent

    2017-10-01

    Selective Laser Melting (SLM) process belonging to the family of the Additive Manufacturing (AM) technologies, enable to build parts layer by layer, from metallic powder and a CAD model. Physical phenomena that occur in the process have the same issues as conventional welding. Thermal gradients generate significant residual stresses and distortions in the parts. Moreover, the large and complex parts to manufacturing, accentuate the undesirable effects. Therefore, it is essential for manufacturers to offer a better understanding of the process and to ensure production reliability of parts with high added value. This paper focuses on the simulation of manufacturing turbine by SLM process in order to calculate residual stresses and distortions. Numerical results will be presented.

  12. Category-selective attention modulates unconscious processes in the middle occipital gyrus.

    Science.gov (United States)

    Tu, Shen; Qiu, Jiang; Martens, Ulla; Zhang, Qinglin

    2013-06-01

    Many studies have revealed the top-down modulation (spatial attention, attentional load, etc.) on unconscious processing. However, there is little research about how category-selective attention could modulate the unconscious processing. In the present study, using functional magnetic resonance imaging (fMRI), the results showed that category-selective attention modulated unconscious face/tool processing in the middle occipital gyrus (MOG). Interestingly, MOG effects were of opposed direction for face and tool processes. During unconscious face processing, activation in MOG decreased under the face-selective attention compared with tool-selective attention. This result was in line with the predictive coding theory. During unconscious tool processing, however, activation in MOG increased under the tool-selective attention compared with face-selective attention. The different effects might be ascribed to an interaction between top-down category-selective processes and bottom-up processes in the partial awareness level as proposed by Kouider, De Gardelle, Sackur, and Dupoux (2010). Specifically, we suppose an "excessive activation" hypothesis. Copyright © 2013 Elsevier Inc. All rights reserved.

  13. Bayesian site selection for fast Gaussian process regression

    KAUST Repository

    Pourhabib, Arash; Liang, Faming; Ding, Yu

    2014-01-01

    Gaussian Process (GP) regression is a popular method in the field of machine learning and computer experiment designs; however, its ability to handle large data sets is hindered by the computational difficulty in inverting a large covariance matrix. Likelihood approximation methods were developed as a fast GP approximation, thereby reducing the computation cost of GP regression by utilizing a much smaller set of unobserved latent variables called pseudo points. This article reports a further improvement to the likelihood approximation methods by simultaneously deciding both the number and locations of the pseudo points. The proposed approach is a Bayesian site selection method where both the number and locations of the pseudo inputs are parameters in the model, and the Bayesian model is solved using a reversible jump Markov chain Monte Carlo technique. Through a number of simulated and real data sets, it is demonstrated that with appropriate priors chosen, the Bayesian site selection method can produce a good balance between computation time and prediction accuracy: it is fast enough to handle large data sets that a full GP is unable to handle, and it improves, quite often remarkably, the prediction accuracy, compared with the existing likelihood approximations. © 2014 Taylor and Francis Group, LLC.

  14. Bayesian site selection for fast Gaussian process regression

    KAUST Repository

    Pourhabib, Arash

    2014-02-05

    Gaussian Process (GP) regression is a popular method in the field of machine learning and computer experiment designs; however, its ability to handle large data sets is hindered by the computational difficulty in inverting a large covariance matrix. Likelihood approximation methods were developed as a fast GP approximation, thereby reducing the computation cost of GP regression by utilizing a much smaller set of unobserved latent variables called pseudo points. This article reports a further improvement to the likelihood approximation methods by simultaneously deciding both the number and locations of the pseudo points. The proposed approach is a Bayesian site selection method where both the number and locations of the pseudo inputs are parameters in the model, and the Bayesian model is solved using a reversible jump Markov chain Monte Carlo technique. Through a number of simulated and real data sets, it is demonstrated that with appropriate priors chosen, the Bayesian site selection method can produce a good balance between computation time and prediction accuracy: it is fast enough to handle large data sets that a full GP is unable to handle, and it improves, quite often remarkably, the prediction accuracy, compared with the existing likelihood approximations. © 2014 Taylor and Francis Group, LLC.

  15. Pareto genealogies arising from a Poisson branching evolution model with selection.

    Science.gov (United States)

    Huillet, Thierry E

    2014-02-01

    We study a class of coalescents derived from a sampling procedure out of N i.i.d. Pareto(α) random variables, normalized by their sum, including β-size-biasing on total length effects (β Poisson-Dirichlet (α, -β) Ξ-coalescent (α ε[0, 1)), or to a family of continuous-time Beta (2 - α, α - β)Λ-coalescents (α ε[1, 2)), or to the Kingman coalescent (α ≥ 2). We indicate that this class of coalescent processes (and their scaling limits) may be viewed as the genealogical processes of some forward in time evolving branching population models including selection effects. In such constant-size population models, the reproduction step, which is based on a fitness-dependent Poisson Point Process with scaling power-law(α) intensity, is coupled to a selection step consisting of sorting out the N fittest individuals issued from the reproduction step.

  16. A proposed selection process in Over-The-Top project portfolio management

    Directory of Open Access Journals (Sweden)

    Jemy Vestius Confido

    2018-05-01

    Full Text Available Purpose: The purpose of this paper is to propose an Over-The-Top (OTT initiative selection process for communication service providers (CSPs entering an OTT business. Design/methodology/approach: To achieve this objective, a literature review was conducted to comprehend the past and current practices of the project (or initiative selection process as mainly suggested in project portfolio management (PPM. This literature was compared with specific situations and the needs of CSPs when constructing an OTT portfolio. Based on the contrast between the conventional project selection process and specific OTT characteristics, a different selection process is developed and tested using group model-building (GMB, which involved an in-depth interview, a questionnaire and a focus group discussion (FGD. Findings: The paper recommends five distinct steps for CSPs to construct an OTT initiative portfolio: candidate list of OTT initiatives, interdependency diagram, evaluation of all interdependent OTT initiatives, evaluation of all non-interdependent OTT initiatives and optimal portfolio of OTT initiatives. Research limitations/implications: The research is empirical, and various OTT services are implemented; the conclusion is derived only from one CSP, which operates as a group. Generalization of this approach will require further empirical tests on different CSPs, OTT players or any firms performing portfolio selection with a degree of interdependency among the projects. Practical implications: Having considered interdependency, the proposed OTT initiative selection steps can be further implemented by portfolio managers for more effective OTT initiative portfolio construction. Originality/value: While the previous literature and common practices suggest ensuring the benefits (mainly financial of individual projects, this research accords higher priority to the success of the overall OTT initiative portfolio and recommends that an evaluation of the overall

  17. Decision support model for selecting and evaluating suppliers in the construction industry

    Directory of Open Access Journals (Sweden)

    Fernando Schramm

    2012-12-01

    Full Text Available A structured evaluation of the construction industry's suppliers, considering aspects which make their quality and credibility evident, can be a strategic tool to manage this specific supply chain. This study proposes a multi-criteria decision model for suppliers' selection from the construction industry, as well as an efficient evaluation procedure for the selected suppliers. The model is based on SMARTER (Simple Multi-Attribute Rating Technique Exploiting Ranking method and its main contribution is a new approach to structure the process of suppliers' selection, establishing explicit strategic policies on which the company management system relied to make the suppliers selection. This model was applied to a Civil Construction Company in Brazil and the main results demonstrate the efficiency of the proposed model. This study allowed the development of an approach to Construction Industry which was able to provide a better relationship among its managers, suppliers and partners.

  18. Traditional and robust vector selection methods for use with similarity based models

    International Nuclear Information System (INIS)

    Hines, J. W.; Garvey, D. R.

    2006-01-01

    Vector selection, or instance selection as it is often called in the data mining literature, performs a critical task in the development of nonparametric, similarity based models. Nonparametric, similarity based modeling (SBM) is a form of 'lazy learning' which constructs a local model 'on the fly' by comparing a query vector to historical, training vectors. For large training sets the creation of local models may become cumbersome, since each training vector must be compared to the query vector. To alleviate this computational burden, varying forms of training vector sampling may be employed with the goal of selecting a subset of the training data such that the samples are representative of the underlying process. This paper describes one such SBM, namely auto-associative kernel regression (AAKR), and presents five traditional vector selection methods and one robust vector selection method that may be used to select prototype vectors from a larger data set in model training. The five traditional vector selection methods considered are min-max, vector ordering, combination min-max and vector ordering, fuzzy c-means clustering, and Adeli-Hung clustering. Each method is described in detail and compared using artificially generated data and data collected from the steam system of an operating nuclear power plant. (authors)

  19. Three Tier Unified Process Model for Requirement Negotiations and Stakeholder Collaborations

    Science.gov (United States)

    Niazi, Muhammad Ashraf Khan; Abbas, Muhammad; Shahzad, Muhammad

    2012-11-01

    This research paper is focused towards carrying out a pragmatic qualitative analysis of various models and approaches of requirements negotiations (a sub process of requirements management plan which is an output of scope managementís collect requirements process) and studies stakeholder collaborations methodologies (i.e. from within communication management knowledge area). Experiential analysis encompass two tiers; first tier refers to the weighted scoring model while second tier focuses on development of SWOT matrices on the basis of findings of weighted scoring model for selecting an appropriate requirements negotiation model. Finally the results are simulated with the help of statistical pie charts. On the basis of simulated results of prevalent models and approaches of negotiations, a unified approach for requirements negotiations and stakeholder collaborations is proposed where the collaboration methodologies are embeded into selected requirements negotiation model as internal parameters of the proposed process alongside some external required parameters like MBTI, opportunity analysis etc.

  20. Spatial Fleming-Viot models with selection and mutation

    CERN Document Server

    Dawson, Donald A

    2014-01-01

    This book constructs a rigorous framework for analysing selected phenomena in evolutionary theory of populations arising due to the combined effects of migration, selection and mutation in a spatial stochastic population model, namely the evolution towards fitter and fitter types through punctuated equilibria. The discussion is based on a number of new methods, in particular multiple scale analysis, nonlinear Markov processes and their entrance laws, atomic measure-valued evolutions and new forms of duality (for state-dependent mutation and multitype selection) which are used to prove ergodic theorems in this context and are applicable for many other questions and renormalization analysis for a variety of phenomena (stasis, punctuated equilibrium, failure of naive branching approximations, biodiversity) which occur due to the combination of rare mutation, mutation, resampling, migration and selection and make it necessary to mathematically bridge the gap (in the limit) between time and space scales.

  1. Variable selection and model choice in geoadditive regression models.

    Science.gov (United States)

    Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

    2009-06-01

    Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

  2. Fit Gap Analysis – The Role of Business Process Reference Models

    Directory of Open Access Journals (Sweden)

    Dejan Pajk

    2013-12-01

    Full Text Available Enterprise resource planning (ERP systems support solutions for standard business processes such as financial, sales, procurement and warehouse. In order to improve the understandability and efficiency of their implementation, ERP vendors have introduced reference models that describe the processes and underlying structure of an ERP system. To select and successfully implement an ERP system, the capabilities of that system have to be compared with a company’s business needs. Based on a comparison, all of the fits and gaps must be identified and further analysed. This step usually forms part of ERP implementation methodologies and is called fit gap analysis. The paper theoretically overviews methods for applying reference models and describes fit gap analysis processes in detail. The paper’s first contribution is its presentation of a fit gap analysis using standard business process modelling notation. The second contribution is the demonstration of a process-based comparison approach between a supply chain process and an ERP system process reference model. In addition to its theoretical contributions, the results can also be practically applied to projects involving the selection and implementation of ERP systems.

  3. A decision model for the risk management of hazardous processes

    International Nuclear Information System (INIS)

    Holmberg, J.E.

    1997-03-01

    A decision model for risk management of hazardous processes as an optimisation problem of a point process is formulated in the study. In the approach, the decisions made by the management are divided into three categories: (1) planned process lifetime, (2) selection of the design and, (3) operational decisions. These three controlling methods play quite different roles in the practical risk management, which is also reflected in our approach. The optimisation of the process lifetime is related to the licensing problem of the process. It provides a boundary condition for a feasible utility function that is used as the actual objective function, i.e., maximizing the process lifetime utility. By design modifications, the management can affect the inherent accident hazard rate of the process. This is usually a discrete optimisation task. The study particularly concentrates upon the optimisation of the operational strategies given a certain design and licensing time. This is done by a dynamic risk model (marked point process model) representing the stochastic process of events observable or unobservable to the decision maker. An optimal long term control variable guiding the selection of operational alternatives in short term problems is studied. The optimisation problem is solved by the stochastic quasi-gradient procedure. The approach is illustrated by a case study. (23 refs.)

  4. Impact of selected troposphere models on Precise Point Positioning convergence

    Science.gov (United States)

    Kalita, Jakub; Rzepecka, Zofia

    2016-04-01

    The Precise Point Positioning (PPP) absolute method is currently intensively investigated in order to reach fast convergence time. Among various sources that influence the convergence of the PPP, the tropospheric delay is one of the most important. Numerous models of tropospheric delay are developed and applied to PPP processing. However, with rare exceptions, the quality of those models does not allow fixing the zenith path delay tropospheric parameter, leaving difference between nominal and final value to the estimation process. Here we present comparison of several PPP result sets, each of which based on different troposphere model. The respective nominal values are adopted from models: VMF1, GPT2w, MOPS and ZERO-WET. The PPP solution admitted as reference is based on the final troposphere product from the International GNSS Service (IGS). The VMF1 mapping function was used for all processing variants in order to provide capability to compare impact of applied nominal values. The worst case initiates zenith wet delay with zero value (ZERO-WET). Impact from all possible models for tropospheric nominal values should fit inside both IGS and ZERO-WET border variants. The analysis is based on data from seven IGS stations located in mid-latitude European region from year 2014. For the purpose of this study several days with the most active troposphere were selected for each of the station. All the PPP solutions were determined using gLAB open-source software, with the Kalman filter implemented independently by the authors of this work. The processing was performed on 1 hour slices of observation data. In addition to the analysis of the output processing files, the presented study contains detailed analysis of the tropospheric conditions for the selected data. The overall results show that for the height component the VMF1 model outperforms GPT2w and MOPS by 35-40% and ZERO-WET variant by 150%. In most of the cases all solutions converge to the same values during first

  5. Predictive and Descriptive CoMFA Models: The Effect of Variable Selection.

    Science.gov (United States)

    Sepehri, Bakhtyar; Omidikia, Nematollah; Kompany-Zareh, Mohsen; Ghavami, Raouf

    2018-01-01

    Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  6. Expatriates Selection: An Essay of Model Analysis

    Directory of Open Access Journals (Sweden)

    Rui Bártolo-Ribeiro

    2015-03-01

    Full Text Available The business expansion to other geographical areas with different cultures from which organizations were created and developed leads to the expatriation of employees to these destinations. Recruitment and selection procedures of expatriates do not always have the intended success leading to an early return of these professionals with the consequent organizational disorders. In this study, several articles published in the last five years were analyzed in order to identify the most frequently mentioned dimensions in the selection of expatriates in terms of success and failure. The characteristics in the selection process that may increase prediction of adaptation of expatriates to new cultural contexts of the some organization were studied according to the KSAOs model. Few references were found concerning Knowledge, Skills and Abilities dimensions in the analyzed papers. There was a strong predominance on the evaluation of Other Characteristics, and was given more importance to dispositional factors than situational factors for promoting the integration of the expatriates.

  7. A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

    Science.gov (United States)

    Thomas, D.L.; Johnson, D.; Griffith, B.

    2006-01-01

    Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a

  8. Generation unit selection via capital asset pricing model for generation planning

    Energy Technology Data Exchange (ETDEWEB)

    Romy Cahyadi; K. Jo Min; Chung-Hsiao Wang; Nick Abi-Samra [College of Engineering, Ames, IA (USA)

    2003-11-01

    The USA's electric power industry is undergoing substantial regulatory and organizational changes. Such changes introduce substantial financial risk in generation planning. In order to incorporate the financial risk into the capital investment decision process of generation planning, this paper develops and analyses a generation unit selection process via the capital asset pricing model (CAPM). In particular, utilizing realistic data on gas-fired, coal-fired, and wind power generation units, the authors show which and how concrete steps can be taken for generation planning purposes. It is hoped that the generation unit selection process will help utilities in the area of effective and efficient generation planning when financial risks are considered. 20 refs., 14 tabs.

  9. Forest Fragmentation and Selective Logging Have Inconsistent Effects on Multiple Animal-Mediated Ecosystem Processes in a Tropical Forest

    Science.gov (United States)

    Schleuning, Matthias; Farwig, Nina; Peters, Marcell K.; Bergsdorf, Thomas; Bleher, Bärbel; Brandl, Roland; Dalitz, Helmut; Fischer, Georg; Freund, Wolfram; Gikungu, Mary W.; Hagen, Melanie; Garcia, Francisco Hita; Kagezi, Godfrey H.; Kaib, Manfred; Kraemer, Manfred; Lung, Tobias; Schaab, Gertrud; Templin, Mathias; Uster, Dana; Wägele, J. Wolfgang; Böhning-Gaese, Katrin

    2011-01-01

    Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the

  10. Decision making model design for antivirus software selection using Factor Analysis and Analytical Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Nurhayati Ai

    2018-01-01

    Full Text Available Virus spread increase significantly through the internet in 2017. One of the protection method is using antivirus software. The wide variety of antivirus software in the market tends to creating confusion among consumer. Selecting the right antivirus according to their needs has become difficult. This is the reason we conduct our research. We formulate a decision making model for antivirus software consumer. The model is constructed by using factor analysis and AHP method. First we spread questionnaires to consumer, then from those questionnaires we identified 16 variables that needs to be considered on selecting antivirus software. This 16 variables then divided into 5 factors by using factor analysis method in SPSS software. These five factors are security, performance, internal, time and capacity. To rank those factors we spread questionnaires to 6 IT expert then the data is analyzed using AHP method. The result is that performance factors gained the highest rank from all of the other factors. Thus, consumer can select antivirus software by judging the variables in the performance factors. Those variables are software loading speed, user friendly, no excessive memory use, thorough scanning, and scanning virus fast and accurately.

  11. Process modelling on a canonical basis[Process modelling; Canonical modelling

    Energy Technology Data Exchange (ETDEWEB)

    Siepmann, Volker

    2006-12-20

    Based on an equation oriented solving strategy, this thesis investigates a new approach to process modelling. Homogeneous thermodynamic state functions represent consistent mathematical models of thermodynamic properties. Such state functions of solely extensive canonical state variables are the basis of this work, as they are natural objective functions in optimisation nodes to calculate thermodynamic equilibrium regarding phase-interaction and chemical reactions. Analytical state function derivatives are utilised within the solution process as well as interpreted as physical properties. By this approach, only a limited range of imaginable process constraints are considered, namely linear balance equations of state variables. A second-order update of source contributions to these balance equations is obtained by an additional constitutive equation system. These equations are general dependent on state variables and first-order sensitivities, and cover therefore practically all potential process constraints. Symbolic computation technology efficiently provides sparsity and derivative information of active equations to avoid performance problems regarding robustness and computational effort. A benefit of detaching the constitutive equation system is that the structure of the main equation system remains unaffected by these constraints, and a priori information allows to implement an efficient solving strategy and a concise error diagnosis. A tailor-made linear algebra library handles the sparse recursive block structures efficiently. The optimisation principle for single modules of thermodynamic equilibrium is extended to host entire process models. State variables of different modules interact through balance equations, representing material flows from one module to the other. To account for reusability and encapsulation of process module details, modular process modelling is supported by a recursive module structure. The second-order solving algorithm makes it

  12. The Ideal Criteria of Supplier Selection for SMEs Food Processing Industry

    Directory of Open Access Journals (Sweden)

    Ramlan Rohaizan

    2016-01-01

    Full Text Available Selection of good supplier is important to determine the performance and profitability of SMEs food processing industry. The lack of managerial capability on supplier selection in SMEs food processing industry affects the competitiveness of SMEs food processing industry. This research aims to determine the ideal criteria of supplier for food processing industry using Analytical Hierarchy Process (AHP. The research was carried out in a quantitative method by distributing questionnaires to 50 SMEs food processing industries. The collected data analysed using Expert Choice software to rank the supplier selection criteria. The result shows that criteria for supplier selection are ranked by cost, quality, service, delivery and management and organisation while purchase cost, audit result, defect analysis, transportation cost and fast responsiveness are the first five sub-criteria. The result of this research intends to improve managerial capabilities of SMEs food processing industry in supplier selection.

  13. Efficient spiking neural network model of pattern motion selectivity in visual cortex.

    Science.gov (United States)

    Beyeler, Michael; Richert, Micah; Dutt, Nikil D; Krichmar, Jeffrey L

    2014-07-01

    Simulating large-scale models of biological motion perception is challenging, due to the required memory to store the network structure and the computational power needed to quickly solve the neuronal dynamics. A low-cost yet high-performance approach to simulating large-scale neural network models in real-time is to leverage the parallel processing capability of graphics processing units (GPUs). Based on this approach, we present a two-stage model of visual area MT that we believe to be the first large-scale spiking network to demonstrate pattern direction selectivity. In this model, component-direction-selective (CDS) cells in MT linearly combine inputs from V1 cells that have spatiotemporal receptive fields according to the motion energy model of Simoncelli and Heeger. Pattern-direction-selective (PDS) cells in MT are constructed by pooling over MT CDS cells with a wide range of preferred directions. Responses of our model neurons are comparable to electrophysiological results for grating and plaid stimuli as well as speed tuning. The behavioral response of the network in a motion discrimination task is in agreement with psychophysical data. Moreover, our implementation outperforms a previous implementation of the motion energy model by orders of magnitude in terms of computational speed and memory usage. The full network, which comprises 153,216 neurons and approximately 40 million synapses, processes 20 frames per second of a 40 × 40 input video in real-time using a single off-the-shelf GPU. To promote the use of this algorithm among neuroscientists and computer vision researchers, the source code for the simulator, the network, and analysis scripts are publicly available.

  14. Interval-valued intuitionistic fuzzy multi-criteria model for design concept selection

    Directory of Open Access Journals (Sweden)

    Daniel Osezua Aikhuele

    2017-09-01

    Full Text Available This paper presents a new approach for design concept selection by using an integrated Fuzzy Analytical Hierarchy Process (FAHP and an Interval-valued intuitionistic fuzzy modified TOP-SIS (IVIF-modified TOPSIS model. The integrated model which uses the improved score func-tion and a weighted normalized Euclidean distance method for the calculation of the separation measures of alternatives from the positive and negative intuitionistic ideal solutions provides a new approach for the computation of intuitionistic fuzzy ideal solutions. The results of the two approaches are integrated using a reflection defuzzification integration formula. To ensure the feasibility and the rationality of the integrated model, the method is successfully applied for eval-uating and selecting some design related problems including a real-life case study for the selec-tion of the best concept design for a new printed-circuit-board (PCB and for a hypothetical ex-ample. The model which provides a novel alternative, has been compared with similar computa-tional methods in the literature.

  15. Predictive modeling, simulation, and optimization of laser processing techniques: UV nanosecond-pulsed laser micromachining of polymers and selective laser melting of powder metals

    Science.gov (United States)

    Criales Escobar, Luis Ernesto

    One of the most frequently evolving areas of research is the utilization of lasers for micro-manufacturing and additive manufacturing purposes. The use of laser beam as a tool for manufacturing arises from the need for flexible and rapid manufacturing at a low-to-mid cost. Laser micro-machining provides an advantage over mechanical micro-machining due to the faster production times of large batch sizes and the high costs associated with specific tools. Laser based additive manufacturing enables processing of powder metals for direct and rapid fabrication of products. Therefore, laser processing can be viewed as a fast, flexible, and cost-effective approach compared to traditional manufacturing processes. Two types of laser processing techniques are studied: laser ablation of polymers for micro-channel fabrication and selective laser melting of metal powders. Initially, a feasibility study for laser-based micro-channel fabrication of poly(dimethylsiloxane) (PDMS) via experimentation is presented. In particular, the effectiveness of utilizing a nanosecond-pulsed laser as the energy source for laser ablation is studied. The results are analyzed statistically and a relationship between process parameters and micro-channel dimensions is established. Additionally, a process model is introduced for predicting channel depth. Model outputs are compared and analyzed to experimental results. The second part of this research focuses on a physics-based FEM approach for predicting the temperature profile and melt pool geometry in selective laser melting (SLM) of metal powders. Temperature profiles are calculated for a moving laser heat source to understand the temperature rise due to heating during SLM. Based on the predicted temperature distributions, melt pool geometry, i.e. the locations at which melting of the powder material occurs, is determined. Simulation results are compared against data obtained from experimental Inconel 625 test coupons fabricated at the National

  16. Radial Domany-Kinzel models with mutation and selection

    Science.gov (United States)

    Lavrentovich, Maxim O.; Korolev, Kirill S.; Nelson, David R.

    2013-01-01

    We study the effect of spatial structure, genetic drift, mutation, and selective pressure on the evolutionary dynamics in a simplified model of asexual organisms colonizing a new territory. Under an appropriate coarse-graining, the evolutionary dynamics is related to the directed percolation processes that arise in voter models, the Domany-Kinzel (DK) model, contact process, and so on. We explore the differences between linear (flat front) expansions and the much less familiar radial (curved front) range expansions. For the radial expansion, we develop a generalized, off-lattice DK model that minimizes otherwise persistent lattice artifacts. With both simulations and analytical techniques, we study the survival probability of advantageous mutants, the spatial correlations between domains of neutral strains, and the dynamics of populations with deleterious mutations. “Inflation” at the frontier leads to striking differences between radial and linear expansions. For a colony with initial radius R0 expanding at velocity v, significant genetic demixing, caused by local genetic drift, occurs only up to a finite time t*=R0/v, after which portions of the colony become causally disconnected due to the inflating perimeter of the expanding front. As a result, the effect of a selective advantage is amplified relative to genetic drift, increasing the survival probability of advantageous mutants. Inflation also modifies the underlying directed percolation transition, introducing novel scaling functions and modifications similar to a finite-size effect. Finally, we consider radial range expansions with deflating perimeters, as might arise from colonization initiated along the shores of an island.

  17. Selection of models to calculate the LLW source term

    International Nuclear Information System (INIS)

    Sullivan, T.M.

    1991-10-01

    Performance assessment of a LLW disposal facility begins with an estimation of the rate at which radionuclides migrate out of the facility (i.e., the source term). The focus of this work is to develop a methodology for calculating the source term. In general, the source term is influenced by the radionuclide inventory, the wasteforms and containers used to dispose of the inventory, and the physical processes that lead to release from the facility (fluid flow, container degradation, wasteform leaching, and radionuclide transport). In turn, many of these physical processes are influenced by the design of the disposal facility (e.g., infiltration of water). The complexity of the problem and the absence of appropriate data prevent development of an entirely mechanistic representation of radionuclide release from a disposal facility. Typically, a number of assumptions, based on knowledge of the disposal system, are used to simplify the problem. This document provides a brief overview of disposal practices and reviews existing source term models as background for selecting appropriate models for estimating the source term. The selection rationale and the mathematical details of the models are presented. Finally, guidance is presented for combining the inventory data with appropriate mechanisms describing release from the disposal facility. 44 refs., 6 figs., 1 tab

  18. Hencky's model for elastomer forming process

    Science.gov (United States)

    Oleinikov, A. A.; Oleinikov, A. I.

    2016-08-01

    In the numerical simulation of elastomer forming process, Henckys isotropic hyperelastic material model can guarantee relatively accurate prediction of strain range in terms of large deformations. It is shown, that this material model prolongate Hooke's law from the area of infinitesimal strains to the area of moderate ones. New representation of the fourth-order elasticity tensor for Hencky's hyperelastic isotropic material is obtained, it possesses both minor symmetries, and the major symmetry. Constitutive relations of considered model is implemented into MSC.Marc code. By calculating and fitting curves, the polyurethane elastomer material constants are selected. Simulation of equipment for elastomer sheet forming are considered.

  19. A Collective Case Study of Secondary Students' Model-Based Inquiry on Natural Selection through Programming in an Agent-Based Modeling Environment

    Science.gov (United States)

    Xiang, Lin

    This is a collective case study seeking to develop detailed descriptions of how programming an agent-based simulation influences a group of 8 th grade students' model-based inquiry (MBI) by examining students' agent-based programmable modeling (ABPM) processes and the learning outcomes. The context of the present study was a biology unit on natural selection implemented in a charter school of a major California city during spring semester of 2009. Eight 8th grade students, two boys and six girls, participated in this study. All of them were low socioeconomic status (SES). English was a second language for all of them, but they had been identified as fluent English speakers at least a year before the study. None of them had learned either natural selection or programming before the study. The study spanned over 7 weeks and was comprised of two study phases. In phase one the subject students learned natural selection in science classroom and how to do programming in NetLogo, an ABPM tool, in a computer lab; in phase two, the subject students were asked to program a simulation of adaptation based on the natural selection model in NetLogo. Both qualitative and quantitative data were collected in this study. The data resources included (1) pre and post test questionnaire, (2) student in-class worksheet, (3) programming planning sheet, (4) code-conception matching sheet, (5) student NetLogo projects, (6) videotaped programming processes, (7) final interview, and (8) investigator's field notes. Both qualitative and quantitative approaches were applied to analyze the gathered data. The findings suggested that students made progress on understanding adaptation phenomena and natural selection at the end of ABPM-supported MBI learning but the progress was limited. These students still held some misconceptions in their conceptual models, such as the idea that animals need to "learn" to adapt into the environment. Besides, their models of natural selection appeared to be

  20. Fast Bayesian Inference in Dirichlet Process Mixture Models.

    Science.gov (United States)

    Wang, Lianming; Dunson, David B

    2011-01-01

    There has been increasing interest in applying Bayesian nonparametric methods in large samples and high dimensions. As Markov chain Monte Carlo (MCMC) algorithms are often infeasible, there is a pressing need for much faster algorithms. This article proposes a fast approach for inference in Dirichlet process mixture (DPM) models. Viewing the partitioning of subjects into clusters as a model selection problem, we propose a sequential greedy search algorithm for selecting the partition. Then, when conjugate priors are chosen, the resulting posterior conditionally on the selected partition is available in closed form. This approach allows testing of parametric models versus nonparametric alternatives based on Bayes factors. We evaluate the approach using simulation studies and compare it with four other fast nonparametric methods in the literature. We apply the proposed approach to three datasets including one from a large epidemiologic study. Matlab codes for the simulation and data analyses using the proposed approach are available online in the supplemental materials.

  1. Processes in arithmetic strategy selection: A fMRI study.

    Directory of Open Access Journals (Sweden)

    Julien eTaillan

    2015-02-01

    Full Text Available This neuroimaging (fMRI study investigated neural correlates of strategy selection. Young adults performed an arithmetic task in two different conditions. In both conditions, participants had to provide estimates of two-digit multiplication problems like 54 x 78. In the choice condition, participants had to select the better of two available rounding strategies, rounding-up strategy (RU (i.e., doing 60x80 = 4,800 or rounding-down strategy (RD (i.e., doing 50x70=3,500 to estimate product of 54x78. In the no-choice condition, participants did not have to select strategy on each problem but were told which strategy to use; they executed RU and RD strategies each on a series of problems. Participants also had a control task (i.e., providing correct products of multiplication problems like 40x50. Brain activations and performance were analyzed as a function of these conditions. Participants were able to frequently choose the better strategy in the choice condition; they were also slower when they executed the difficult RU than the easier RD. Neuroimaging data showed greater brain activations in right anterior cingulate cortex (ACC, dorso-lateral prefrontal cortex (DLPFC, and angular gyrus (ANG, when selecting (relative to executing the better strategy on each problem. Moreover, RU was associated with more parietal cortex activation than RD. These results suggest an important role of fronto-parietal network in strategy selection and have important implications for our further understanding and modelling cognitive processes underlying strategy selection.

  2. Processes in arithmetic strategy selection: a fMRI study.

    Science.gov (United States)

    Taillan, Julien; Ardiale, Eléonore; Anton, Jean-Luc; Nazarian, Bruno; Félician, Olivier; Lemaire, Patrick

    2015-01-01

    This neuroimaging (functional magnetic resonance imaging) study investigated neural correlates of strategy selection. Young adults performed an arithmetic task in two different conditions. In both conditions, participants had to provide estimates of two-digit multiplication problems like 54 × 78. In the choice condition, participants had to select the better of two available rounding strategies, rounding-up (RU) strategy (i.e., doing 60 × 80 = 4,800) or rounding-down (RD) strategy (i.e., doing 50 × 70 = 3,500 to estimate product of 54 × 78). In the no-choice condition, participants did not have to select strategy on each problem but were told which strategy to use; they executed RU and RD strategies each on a series of problems. Participants also had a control task (i.e., providing correct products of multiplication problems like 40 × 50). Brain activations and performance were analyzed as a function of these conditions. Participants were able to frequently choose the better strategy in the choice condition; they were also slower when they executed the difficult RU than the easier RD. Neuroimaging data showed greater brain activations in right anterior cingulate cortex (ACC), dorso-lateral prefrontal cortex (DLPFC), and angular gyrus (ANG), when selecting (relative to executing) the better strategy on each problem. Moreover, RU was associated with more parietal cortex activation than RD. These results suggest an important role of fronto-parietal network in strategy selection and have important implications for our further understanding and modeling cognitive processes underlying strategy selection.

  3. Engineered Barrier System Degradation, Flow, and Transport Process Model Report

    Energy Technology Data Exchange (ETDEWEB)

    E.L. Hardin

    2000-07-17

    The Engineered Barrier System Degradation, Flow, and Transport Process Model Report (EBS PMR) is one of nine PMRs supporting the Total System Performance Assessment (TSPA) being developed by the Yucca Mountain Project for the Site Recommendation Report (SRR). The EBS PMR summarizes the development and abstraction of models for processes that govern the evolution of conditions within the emplacement drifts of a potential high-level nuclear waste repository at Yucca Mountain, Nye County, Nevada. Details of these individual models are documented in 23 supporting Analysis/Model Reports (AMRs). Nineteen of these AMRs are for process models, and the remaining 4 describe the abstraction of results for application in TSPA. The process models themselves cluster around four major topics: ''Water Distribution and Removal Model, Physical and Chemical Environment Model, Radionuclide Transport Model, and Multiscale Thermohydrologic Model''. One AMR (Engineered Barrier System-Features, Events, and Processes/Degradation Modes Analysis) summarizes the formal screening analysis used to select the Features, Events, and Processes (FEPs) included in TSPA and those excluded from further consideration. Performance of a potential Yucca Mountain high-level radioactive waste repository depends on both the natural barrier system (NBS) and the engineered barrier system (EBS) and on their interactions. Although the waste packages are generally considered as components of the EBS, the EBS as defined in the EBS PMR includes all engineered components outside the waste packages. The principal function of the EBS is to complement the geologic system in limiting the amount of water contacting nuclear waste. A number of alternatives were considered by the Project for different EBS designs that could provide better performance than the design analyzed for the Viability Assessment. The design concept selected was Enhanced Design Alternative II (EDA II).

  4. Engineered Barrier System Degradation, Flow, and Transport Process Model Report

    International Nuclear Information System (INIS)

    E.L. Hardin

    2000-01-01

    The Engineered Barrier System Degradation, Flow, and Transport Process Model Report (EBS PMR) is one of nine PMRs supporting the Total System Performance Assessment (TSPA) being developed by the Yucca Mountain Project for the Site Recommendation Report (SRR). The EBS PMR summarizes the development and abstraction of models for processes that govern the evolution of conditions within the emplacement drifts of a potential high-level nuclear waste repository at Yucca Mountain, Nye County, Nevada. Details of these individual models are documented in 23 supporting Analysis/Model Reports (AMRs). Nineteen of these AMRs are for process models, and the remaining 4 describe the abstraction of results for application in TSPA. The process models themselves cluster around four major topics: ''Water Distribution and Removal Model, Physical and Chemical Environment Model, Radionuclide Transport Model, and Multiscale Thermohydrologic Model''. One AMR (Engineered Barrier System-Features, Events, and Processes/Degradation Modes Analysis) summarizes the formal screening analysis used to select the Features, Events, and Processes (FEPs) included in TSPA and those excluded from further consideration. Performance of a potential Yucca Mountain high-level radioactive waste repository depends on both the natural barrier system (NBS) and the engineered barrier system (EBS) and on their interactions. Although the waste packages are generally considered as components of the EBS, the EBS as defined in the EBS PMR includes all engineered components outside the waste packages. The principal function of the EBS is to complement the geologic system in limiting the amount of water contacting nuclear waste. A number of alternatives were considered by the Project for different EBS designs that could provide better performance than the design analyzed for the Viability Assessment. The design concept selected was Enhanced Design Alternative II (EDA II)

  5. Analytic hierarchy process helps select site for limestone quarry expansion in Barbados.

    Science.gov (United States)

    Dey, Prasanta Kumar; Ramcharan, Eugene K

    2008-09-01

    Site selection is a key activity for quarry expansion to support cement production, and is governed by factors such as resource availability, logistics, costs, and socio-economic-environmental factors. Adequate consideration of all the factors facilitates both industrial productivity and sustainable economic growth. This study illustrates the site selection process that was undertaken for the expansion of limestone quarry operations to support cement production in Barbados. First, alternate sites with adequate resources to support a 25-year development horizon were identified. Second, technical and socio-economic-environmental factors were then identified. Third, a database was developed for each site with respect to each factor. Fourth, a hierarchical model in analytic hierarchy process (AHP) framework was then developed. Fifth, the relative ranking of the alternate sites was then derived through pair wise comparison in all the levels and through subsequent synthesizing of the results across the hierarchy through computer software (Expert Choice). The study reveals that an integrated framework using the AHP can help select a site for the quarry expansion project in Barbados.

  6. X-33 Telemetry Best Source Selection, Processing, Display, and Simulation Model Comparison

    Science.gov (United States)

    Burkes, Darryl A.

    1998-01-01

    The X-33 program requires the use of multiple telemetry ground stations to cover the launch, ascent, transition, descent, and approach phases for the flights from Edwards AFB to landings at Dugway Proving Grounds, UT and Malmstrom AFB, MT. This paper will discuss the X-33 telemetry requirements and design, including information on fixed and mobile telemetry systems, best source selection, and support for Range Safety Officers. A best source selection system will be utilized to automatically determine the best source based on the frame synchronization status of the incoming telemetry streams. These systems will be used to select the best source at the landing sites and at NASA Dryden Flight Research Center to determine the overall best source between the launch site, intermediate sites, and landing site sources. The best source at the landing sites will be decommutated to display critical flight safety parameters for the Range Safety Officers. The overall best source will be sent to the Lockheed Martin's Operational Control Center at Edwards AFB for performance monitoring by X-33 program personnel and for monitoring of critical flight safety parameters by the primary Range Safety Officer. The real-time telemetry data (received signal strength, etc.) from each of the primary ground stations will also be compared during each nu'ssion with simulation data generated using the Dynamic Ground Station Analysis software program. An overall assessment of the accuracy of the model will occur after each mission. Acknowledgment: The work described in this paper was NASA supported through cooperative agreement NCC8-115 with Lockheed Martin Skunk Works.

  7. Generation unit selection via capital asset pricing model for generation planning

    Energy Technology Data Exchange (ETDEWEB)

    Cahyadi, Romy; Jo Min, K. [College of Engineering, Ames, IA (United States); Chunghsiao Wang [LG and E Energy Corp., Louisville, KY (United States); Abi-Samra, Nick [Electric Power Research Inst., Palo Alto, CA (United States)

    2003-07-01

    The electric power industry in many parts of U.S.A. is undergoing substantial regulatory and organizational changes. Such changes introduce substantial financial risk in generation planning. In order to incorporate the financial risk into the capital investment decision process of generation planning, in this paper, we develop and analyse a generation unit selection process via the capital asset pricing model (CAPM). In particular, utilizing realistic data on gas-fired, coal-fired, and wind power generation units, we show which and how concrete steps can be taken for generation planning purposes. It is hoped that the generation unit selection process developed in this paper will help utilities in the area of effective and efficient generation planning when financial risks are considered. (Author)

  8. Development of modelling method selection tool for health services management: from problem structuring methods to modelling and simulation methods.

    Science.gov (United States)

    Jun, Gyuchan T; Morris, Zoe; Eldabi, Tillal; Harper, Paul; Naseer, Aisha; Patel, Brijesh; Clarkson, John P

    2011-05-19

    There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection.

  9. Variable Selection for Regression Models of Percentile Flows

    Science.gov (United States)

    Fouad, G.

    2017-12-01

    Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high

  10. Computer-aided tool for solvent selection in pharmaceutical processes: Solvent swap

    DEFF Research Database (Denmark)

    Papadakis, Emmanouil; K. Tula, Anjan; Gernaey, Krist V.

    -liquid equilibria). The application of the developed model-based framework is highlighted through several cases studies published in the literature. In the current state, the framework is suitable for problems where the original solvent is exchanged by distillation. A solvent selection guide for fast of suitable......-aided framework with the objective to assist the pharmaceutical industry in gaining better process understanding. A software interface to improve the usability of the tool has been created also....

  11. Understanding Managers Decision Making Process for Tools Selection in the Core Front End of Innovation

    DEFF Research Database (Denmark)

    Appio, Francesco P.; Achiche, Sofiane; McAloone, Tim C.

    2011-01-01

    New product development (NPD) describes the process of bringing a new product or service to the market. The Fuzzy Front End (FFE) of Innovation is the term describing the activities happening before the product development phase of NPD. In the FFE of innovation, several tools are used to facilita...... hypotheses are tested. A preliminary version of a theoretical model depicting the decision process of managers during tools selection in the FFE is proposed. The theoretical model is built from the constructed hypotheses....

  12. Managing the Public Sector Research and Development Portfolio Selection Process: A Case Study of Quantitative Selection and Optimization

    Science.gov (United States)

    2016-09-01

    PUBLIC SECTOR RESEARCH & DEVELOPMENT PORTFOLIO SELECTION PROCESS: A CASE STUDY OF QUANTITATIVE SELECTION AND OPTIMIZATION by Jason A. Schwartz...PUBLIC SECTOR RESEARCH & DEVELOPMENT PORTFOLIO SELECTION PROCESS: A CASE STUDY OF QUANTITATIVE SELECTION AND OPTIMIZATION 5. FUNDING NUMBERS 6...describing how public sector organizations can implement a research and development (R&D) portfolio optimization strategy to maximize the cost

  13. The site selection process for a spent fuel repository in Finland. Summary report

    Energy Technology Data Exchange (ETDEWEB)

    McEwen, T. [EnvirosQuantiSci (United Kingdom); Aeikaes, T. [Posiva Oy, Helsinki (Finland)

    2000-12-01

    This Summary Report describes the Finnish programme for the selection and characterisation of potential sites for the deep disposal of spent nuclear fuel and explains the process by which Olkiluoto has been selected as the single site proposed for the development of a spent fuel disposal facility. Its aim is to provide an overview of this process, initiated almost twenty years ago, which has entered its final phase. It provides information in three areas: a review of the early site selection criteria, a description of the site selection process, including all the associated site characterisation work, up to the point at which a single site was selected and an outline of the proposed work, in particular that proposed underground, to characterise further the Olkiluoto site. In 1983 the Finnish Government made a policy decision on the management of nuclear waste in which the main goals and milestones for the site selection programme for the deep disposal of spent fuel were presented. According to this decision several site candidates, whose selection was to be based on careful studies of the whole country, should be characterised and the site for the repository selected by the end of the year 2000. This report describes the process by which this policy decision has been achieved. The report begins with a discussion of the definition of the geological and environmental site selection criteria and how they were applied in order to select a small number of sites, five in all, that were to be the subject of the preliminary investigations. The methods used to investigate these sites and the results of these investigations are described, as is the evaluation of the results of these investigations and the process used to discard two of the sites and continue more detailed investigations at the remaining three. The detailed site investigations that commenced in 1993 are described with respect to the overall strategy followed and the investigation techniques applied. The

  14. Process-Improvement Cost Model for the Emergency Department.

    Science.gov (United States)

    Dyas, Sheila R; Greenfield, Eric; Messimer, Sherri; Thotakura, Swati; Gholston, Sampson; Doughty, Tracy; Hays, Mary; Ivey, Richard; Spalding, Joseph; Phillips, Robin

    2015-01-01

    The objective of this report is to present a simplified, activity-based costing approach for hospital emergency departments (EDs) to use with Lean Six Sigma cost-benefit analyses. The cost model complexity is reduced by removing diagnostic and condition-specific costs, thereby revealing the underlying process activities' cost inefficiencies. Examples are provided for evaluating the cost savings from reducing discharge delays and the cost impact of keeping patients in the ED (boarding) after the decision to admit has been made. The process-improvement cost model provides a needed tool in selecting, prioritizing, and validating Lean process-improvement projects in the ED and other areas of patient care that involve multiple dissimilar diagnoses.

  15. Decision making model design for antivirus software selection using Factor Analysis and Analytical Hierarchy Process

    OpenAIRE

    Nurhayati Ai; Gautama Aditya; Naseer Muchammad

    2018-01-01

    Virus spread increase significantly through the internet in 2017. One of the protection method is using antivirus software. The wide variety of antivirus software in the market tends to creating confusion among consumer. Selecting the right antivirus according to their needs has become difficult. This is the reason we conduct our research. We formulate a decision making model for antivirus software consumer. The model is constructed by using factor analysis and AHP method. First we spread que...

  16. Neuroscientific Model of Motivational Process

    Science.gov (United States)

    Kim, Sung-il

    2013-01-01

    Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment. PMID:23459598

  17. Neuroscientific model of motivational process.

    Science.gov (United States)

    Kim, Sung-Il

    2013-01-01

    Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three sub processes, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous sub processes, namely reward-driven approach, value-based decision-making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area) in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision-making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area) play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area) and the dorsolateral prefrontal cortex (cognitive control area) are the main neural circuits related to regulation of motivation. These three sub processes interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment.

  18. Towards the Significance of Decision Aid in Building Information Modeling (BIM Software Selection Process

    Directory of Open Access Journals (Sweden)

    Omar Mohd Faizal

    2014-01-01

    Full Text Available Building Information Modeling (BIM has been considered as a solution in construction industry to numerous problems such as delays, increased lead in times and increased costs. This is due to the concept and characteristic of BIM that will reshaped the way construction project teams work together to increase productivity and improve the final project outcomes (cost, time, quality, safety, functionality, maintainability, etc.. As a result, the construction industry has witnesses numerous of BIM software available in market. Each of this software has offers different function, features. Furthermore, the adoption of BIM required high investment on software, hardware and also training expenses. Thus, there is indentified that there is a need of decision aid for appropriated BIM software selection that fulfill the project needs. However, research indicates that there is limited study attempt to guide decision in BIM software selection problem. Thus, this paper highlight the importance of decision making and support for BIM software selection as it is vital to increase productivity, construction project throughout building lifecycle.

  19. Material and process selection using product examples

    DEFF Research Database (Denmark)

    Lenau, Torben Anker

    2001-01-01

    The objective of the paper is to suggest a different procedure for selecting materials and processes within the product development work. The procedure includes using product examples in order to increase the number of alternative materials and processes that is considered. Product examples can c...... a search engine, and through hyperlinks can relevant materials and processes be explored. Realising that designers are very sensitive to user interfaces do all descriptions of materials, processes and products include graphical descriptions, i.e. pictures or computer graphics....

  20. Material and process selection using product examples

    DEFF Research Database (Denmark)

    Lenau, Torben Anker

    2002-01-01

    The objective of the paper is to suggest a different procedure for selecting materials and processes within the product development work. The procedure includes using product examples in order to increase the number of alternative materials and processes that is considered. Product examples can c...... a search engine, and through hyperlinks can relevant materials and processes be explored. Realising that designers are very sensitive to user interfaces do all descriptions of materials, processes and products include graphical descriptions, i.e. pictures or computer graphics....

  1. Computational Process Modeling for Additive Manufacturing (OSU)

    Science.gov (United States)

    Bagg, Stacey; Zhang, Wei

    2015-01-01

    Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

  2. Model Selection with the Linear Mixed Model for Longitudinal Data

    Science.gov (United States)

    Ryoo, Ji Hoon

    2011-01-01

    Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…

  3. Stability of choice in the honey bee nest-site selection process.

    Science.gov (United States)

    Nevai, Andrew L; Passino, Kevin M; Srinivasan, Parthasarathy

    2010-03-07

    We introduce a pair of compartment models for the honey bee nest-site selection process that lend themselves to analytic methods. The first model represents a swarm of bees deciding whether a site is viable, and the second characterizes its ability to select between two viable sites. We find that the one-site assessment process has two equilibrium states: a disinterested equilibrium (DE) in which the bees show no interest in the site and an interested equilibrium (IE) in which bees show interest. In analogy with epidemic models, we define basic and absolute recruitment numbers (R(0) and B(0)) as measures of the swarm's sensitivity to dancing by a single bee. If R(0) is less than one then the DE is locally stable, and if B(0) is less than one then it is globally stable. If R(0) is greater than one then the DE is unstable and the IE is stable under realistic conditions. In addition, there exists a critical site quality threshold Q(*) above which the site can attract some interest (at equilibrium) and below which it cannot. We also find the existence of a second critical site quality threshold Q(**) above which the site can attract a quorum (at equilibrium) and below which it cannot. The two-site discrimination process, in which we examine a swarm's ability to simultaneously consider two sites differing in both site quality and discovery time, has a stable DE if and only if both sites' individual basic recruitment numbers are less than one. Numerical experiments are performed to study the influences of site quality on quorum time and the outcome of competition between a lower quality site discovered first and a higher quality site discovered second. 2009 Elsevier Ltd. All rights reserved.

  4. Dealing with selection bias in educational transition models

    DEFF Research Database (Denmark)

    Holm, Anders; Jæger, Mads Meier

    2011-01-01

    This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational tr...... account for selection on unobserved variables and high-quality data are both required in order to estimate credible educational transition models.......This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational...... transitions to be correlated across transitions. We use simulated and real data to illustrate how the BPSM improves on the traditional Mare model in terms of correcting for selection bias and providing credible estimates of the effect of family background on educational success. We conclude that models which...

  5. A review of channel selection algorithms for EEG signal processing

    Science.gov (United States)

    Alotaiby, Turky; El-Samie, Fathi E. Abd; Alshebeili, Saleh A.; Ahmad, Ishtiaq

    2015-12-01

    Digital processing of electroencephalography (EEG) signals has now been popularly used in a wide variety of applications such as seizure detection/prediction, motor imagery classification, mental task classification, emotion classification, sleep state classification, and drug effects diagnosis. With the large number of EEG channels acquired, it has become apparent that efficient channel selection algorithms are needed with varying importance from one application to another. The main purpose of the channel selection process is threefold: (i) to reduce the computational complexity of any processing task performed on EEG signals by selecting the relevant channels and hence extracting the features of major importance, (ii) to reduce the amount of overfitting that may arise due to the utilization of unnecessary channels, for the purpose of improving the performance, and (iii) to reduce the setup time in some applications. Signal processing tools such as time-domain analysis, power spectral estimation, and wavelet transform have been used for feature extraction and hence for channel selection in most of channel selection algorithms. In addition, different evaluation approaches such as filtering, wrapper, embedded, hybrid, and human-based techniques have been widely used for the evaluation of the selected subset of channels. In this paper, we survey the recent developments in the field of EEG channel selection methods along with their applications and classify these methods according to the evaluation approach.

  6. Simulation of the selective oxidation process of semiconductors

    International Nuclear Information System (INIS)

    Chahoud, M.

    2012-01-01

    A new approach to simulate the selective oxidation of semiconductors is presented. This approach is based on the so-called b lack box simulation method . This method is usually used to simulate complex processes. The chemical and physical details within the process are not considered. Only the input and output data of the process are relevant for the simulation. A virtual function linking the input and output data has to be found. In the case of selective oxidation the input data are the mask geometry and the oxidation duration whereas the output data are the oxidation thickness distribution. The virtual function is determined as four virtual diffusion processes between the masked und non-masked areas. Each process delivers one part of the oxidation profile. The method is applied successfully on the oxidation system silicon-silicon nitride (Si-Si 3 N 4 ). The fitting parameters are determined through comparison of experimental and simulation results two-dimensionally.(author)

  7. Process Design Aspects for Scandium-Selective Leaching of Bauxite Residue with Sulfuric Acid

    OpenAIRE

    Konstantinos Hatzilyberis; Theopisti Lymperopoulou; Lamprini-Areti Tsakanika; Klaus-Michael Ochsenkühn; Paraskevas Georgiou; Nikolaos Defteraios; Fotios Tsopelas; Maria Ochsenkühn-Petropoulou

    2018-01-01

    Aiming at the industrial scale development of a Scandium (Sc)-selective leaching process of Bauxite Residue (BR), a set of process design aspects has been investigated. The interpretation of experimental data for Sc leaching yield, with sulfuric acid as the leaching solvent, has shown significant impact from acid feed concentration, mixing time, liquid to solids ratio (L/S), and number of cycles of leachate re-usage onto fresh BR. The thin film diffusion model, as the fundamental theory for l...

  8. Natural Selection as an Emergent Process: Instructional Implications

    Science.gov (United States)

    Cooper, Robert A.

    2017-01-01

    Student reasoning about cases of natural selection is often plagued by errors that stem from miscategorising selection as a direct, causal process, misunderstanding the role of randomness, and from the intuitive ideas of intentionality, teleology and essentialism. The common thread throughout many of these reasoning errors is a failure to apply…

  9. Estimation of a multivariate mean under model selection uncertainty

    Directory of Open Access Journals (Sweden)

    Georges Nguefack-Tsague

    2014-05-01

    Full Text Available Model selection uncertainty would occur if we selected a model based on one data set and subsequently applied it for statistical inferences, because the "correct" model would not be selected with certainty.  When the selection and inference are based on the same dataset, some additional problems arise due to the correlation of the two stages (selection and inference. In this paper model selection uncertainty is considered and model averaging is proposed. The proposal is related to the theory of James and Stein of estimating more than three parameters from independent normal observations. We suggest that a model averaging scheme taking into account the selection procedure could be more appropriate than model selection alone. Some properties of this model averaging estimator are investigated; in particular we show using Stein's results that it is a minimax estimator and can outperform Stein-type estimators.

  10. Financial performance as a decision criterion of credit scoring models selection [doi: 10.21529/RECADM.2017004

    Directory of Open Access Journals (Sweden)

    Rodrigo Alves Silva

    2017-09-01

    Full Text Available This paper aims to show the importance of the use of financial metrics in decision-making of credit scoring models selection. In order to achieve such, we considered an automatic approval system approach and we carried out a performance analysis of the financial metrics on the theoretical portfolios generated by seven credit scoring models based on main statistical learning techniques. The models were estimated on German Credit dataset and the results were analyzed based on four metrics: total accuracy, error cost, risk adjusted return on capital and Sharpe index. The results show that total accuracy, widely used as a criterion for selecting credit scoring models, is unable to select the most profitable model for the company, indicating the need to incorporate financial metrics into the credit scoring model selection process. Keywords Credit risk; Model’s selection; Statistical learning.

  11. Selection Process of ERP Systems

    OpenAIRE

    Molnár, Bálint; Szabó, Gyula; Benczúr, András

    2013-01-01

    Background: The application and introduction of ERP systems have become a central issue for management and operation of enterprises. The competition on market enforces the improvement and optimization of business processes of enterprises to increase their efficiency, effectiveness, and to manage better the resources outside the company. The primary task of ERP systems is to achieve the before-mentioned objectives. Objective: The selection of a particular ERP system has a decisive effect on th...

  12. Review and selection of unsaturated flow models

    Energy Technology Data Exchange (ETDEWEB)

    Reeves, M.; Baker, N.A.; Duguid, J.O. [INTERA, Inc., Las Vegas, NV (United States)

    1994-04-04

    Since the 1960`s, ground-water flow models have been used for analysis of water resources problems. In the 1970`s, emphasis began to shift to analysis of waste management problems. This shift in emphasis was largely brought about by site selection activities for geologic repositories for disposal of high-level radioactive wastes. Model development during the 1970`s and well into the 1980`s focused primarily on saturated ground-water flow because geologic repositories in salt, basalt, granite, shale, and tuff were envisioned to be below the water table. Selection of the unsaturated zone at Yucca Mountain, Nevada, for potential disposal of waste began to shift model development toward unsaturated flow models. Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M&O) has the responsibility to review, evaluate, and document existing computer models; to conduct performance assessments; and to develop performance assessment models, where necessary. This document describes the CRWMS M&O approach to model review and evaluation (Chapter 2), and the requirements for unsaturated flow models which are the bases for selection from among the current models (Chapter 3). Chapter 4 identifies existing models, and their characteristics. Through a detailed examination of characteristics, Chapter 5 presents the selection of models for testing. Chapter 6 discusses the testing and verification of selected models. Chapters 7 and 8 give conclusions and make recommendations, respectively. Chapter 9 records the major references for each of the models reviewed. Appendix A, a collection of technical reviews for each model, contains a more complete list of references. Finally, Appendix B characterizes the problems used for model testing.

  13. Review and selection of unsaturated flow models

    International Nuclear Information System (INIS)

    Reeves, M.; Baker, N.A.; Duguid, J.O.

    1994-01-01

    Since the 1960's, ground-water flow models have been used for analysis of water resources problems. In the 1970's, emphasis began to shift to analysis of waste management problems. This shift in emphasis was largely brought about by site selection activities for geologic repositories for disposal of high-level radioactive wastes. Model development during the 1970's and well into the 1980's focused primarily on saturated ground-water flow because geologic repositories in salt, basalt, granite, shale, and tuff were envisioned to be below the water table. Selection of the unsaturated zone at Yucca Mountain, Nevada, for potential disposal of waste began to shift model development toward unsaturated flow models. Under the US Department of Energy (DOE), the Civilian Radioactive Waste Management System Management and Operating Contractor (CRWMS M ampersand O) has the responsibility to review, evaluate, and document existing computer models; to conduct performance assessments; and to develop performance assessment models, where necessary. This document describes the CRWMS M ampersand O approach to model review and evaluation (Chapter 2), and the requirements for unsaturated flow models which are the bases for selection from among the current models (Chapter 3). Chapter 4 identifies existing models, and their characteristics. Through a detailed examination of characteristics, Chapter 5 presents the selection of models for testing. Chapter 6 discusses the testing and verification of selected models. Chapters 7 and 8 give conclusions and make recommendations, respectively. Chapter 9 records the major references for each of the models reviewed. Appendix A, a collection of technical reviews for each model, contains a more complete list of references. Finally, Appendix B characterizes the problems used for model testing

  14. Method for Business Process Management System Selection

    OpenAIRE

    Westelaken, van de, Thijs; Terwee, Bas; Ravesteijn, Pascal

    2013-01-01

    In recent years business process management (BPM) and specifically information systems that support the analysis, design and execution of processes (also called business process management systems (BPMS)) are getting more attention. This has lead to an increase in research on BPM and BPMS. However the research on BPMS is mostly focused on the architecture of the system and how to implement such systems. How to select a BPM system that fits the strategy and goals of a specific organization is ...

  15. Model Selection in Continuous Test Norming With GAMLSS.

    Science.gov (United States)

    Voncken, Lieke; Albers, Casper J; Timmerman, Marieke E

    2017-06-01

    To compute norms from reference group test scores, continuous norming is preferred over traditional norming. A suitable continuous norming approach for continuous data is the use of the Box-Cox Power Exponential model, which is found in the generalized additive models for location, scale, and shape. Applying the Box-Cox Power Exponential model for test norming requires model selection, but it is unknown how well this can be done with an automatic selection procedure. In a simulation study, we compared the performance of two stepwise model selection procedures combined with four model-fit criteria (Akaike information criterion, Bayesian information criterion, generalized Akaike information criterion (3), cross-validation), varying data complexity, sampling design, and sample size in a fully crossed design. The new procedure combined with one of the generalized Akaike information criterion was the most efficient model selection procedure (i.e., required the smallest sample size). The advocated model selection procedure is illustrated with norming data of an intelligence test.

  16. Modeling of plant in vitro cultures: overview and estimation of biotechnological processes.

    Science.gov (United States)

    Maschke, Rüdiger W; Geipel, Katja; Bley, Thomas

    2015-01-01

    Plant cell and tissue cultivations are of growing interest for the production of structurally complex and expensive plant-derived products, especially in pharmaceutical production. Problems with up-scaling, low yields, and high-priced process conditions result in an increased demand for models to provide comprehension, simulation, and optimization of production processes. In the last 25 years, many models have evolved in plant biotechnology; the majority of them are specialized models for a few selected products or nutritional conditions. In this article we review, delineate, and discuss the concepts and characteristics of the most commonly used models. Therefore, the authors focus on models for plant suspension and submerged hairy root cultures. The article includes a short overview of modeling and mathematics and integrated parameters, as well as the application scope for each model. The review is meant to help researchers better understand and utilize the numerous models published for plant cultures, and to select the most suitable model for their purposes. © 2014 Wiley Periodicals, Inc.

  17. Neuroscientific Model of Motivational Process

    Directory of Open Access Journals (Sweden)

    Sung-Il eKim

    2013-03-01

    Full Text Available Considering the neuroscientific findings on reward, learning, value, decision-making, and cognitive control, motivation can be parsed into three subprocesses, a process of generating motivation, a process of maintaining motivation, and a process of regulating motivation. I propose a tentative neuroscientific model of motivational processes which consists of three distinct but continuous subprocesses, namely reward-driven approach, value-based decision making, and goal-directed control. Reward-driven approach is the process in which motivation is generated by reward anticipation and selective approach behaviors toward reward. This process recruits the ventral striatum (reward area in which basic stimulus-action association is formed, and is classified as an automatic motivation to which relatively less attention is assigned. By contrast, value-based decision making is the process of evaluating various outcomes of actions, learning through positive prediction error, and calculating the value continuously. The striatum and the orbitofrontal cortex (valuation area play crucial roles in sustaining motivation. Lastly, the goal-directed control is the process of regulating motivation through cognitive control to achieve goals. This consciously controlled motivation is associated with higher-level cognitive functions such as planning, retaining the goal, monitoring the performance, and regulating action. The anterior cingulate cortex (attention area and the dorsolateral prefrontal cortex (cognitive control area are the main neural circuits related to regulation of motivation. These three subprocesses interact with each other by sending reward prediction error signals through dopaminergic pathway from the striatum and to the prefrontal cortex. The neuroscientific model of motivational process suggests several educational implications with regard to the generation, maintenance, and regulation of motivation to learn in the learning environment.

  18. Manufacturing plant location selection in logistics network using Analytic Hierarchy Process

    Directory of Open Access Journals (Sweden)

    Ping-Yu Chang

    2015-11-01

    Full Text Available Purpose: In recent years, numerous companies have moved their manufacturing plants to China to capitalize on lower cost and tax. Plant location has such an impact on cost, stocks, and logistics network but location selection in the company is usually based on subjective preference of high ranking managers. Such a decision-making process might result in selecting a location with a lower fixed cost but a higher operational cost. Therefore, this research adapts real data from an electronics company to develop a framework that incorporates both quantitative and qualitative factors for selecting new plant locations. Design/methodology/approach: In-depth interviews were conducted with 12 high rank managers (7 of them are department manager, 2 of them are vice-president, 1 of them is senior engineer, and 2 of them are plant manager in the departments of construction, finance, planning, production, and warehouse to determine the important factors. A questionnaire survey is then conducted for comparing factors which are analyzed using the Analytic Hierarchy Process (AHP. Findings: Results show that the best location chosen by the developed framework coincides well with the company’s primal production base. The results have been presented to the company’s high ranking managers for realizing the accuracy of the framework. Positive responses of the managers indicate usefulness of implementing the proposed model into reality, which adds to the value of this research. Practical implications: The proposed framework can save numerous time-consuming meetings called to compromise opinions and conflictions from different departments in location selection. Originality/value: This paper adapts the Analytic Hierarchy Process (AHP to incorporate quantitative and qualitative factors which are obtained through in-depth interviews with high rank managers in a company into the location decision.

  19. A multidimensional analysis and modelling of flotation process for selected Polish lithological copper ore types

    Directory of Open Access Journals (Sweden)

    Niedoba Tomasz

    2017-01-01

    Full Text Available The flotation of copper ore is a complex technological process that depends on many parameters. Therefore, it is necessary to take into account the complexity of this phenomenon by choosing a multidimensional data analysis. The paper presents the results of modelling and analysis of beneficiation process of sandstone copper ore. Considering the implementation of multidimensional statistical methods it was necessary to carry out a multi-level experiment, which included 4 parameters (size fraction, collector type and dosage, flotation time. The main aim of the paper was the preparation of flotation process models for the recovery and the content of the metal in products. A MANOVA was implemented to explore the relationship between dependent (β, ϑ, ε, η and independent (d, t, cd, ct variables. The design of models was based on linear and nonlinear regression. The results of the variation analysis indicated the high significance of all parameters for the process. The average degree of matching of linear models to experimental data was set at 49% and 33% for copper content in the concentrate and tailings and 47% for the recovery of copper minerals in the both. The results confirms the complexity and stochasticity of the Polish copper ore flotation.

  20. Integration of Fast Predictive Model and SLM Process Development Chamber, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This STTR project seeks to develop a fast predictive model for selective laser melting (SLM) processes and then integrate that model with an SLM chamber that allows...

  1. Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

    Science.gov (United States)

    Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

    2016-01-01

    Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic

  2. Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

    Directory of Open Access Journals (Sweden)

    Shiori Yabe

    Full Text Available Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS, which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the

  3. Application of PROMETHEE-GAIA method for non-traditional machining processes selection

    Directory of Open Access Journals (Sweden)

    Prasad Karande

    2012-10-01

    Full Text Available With ever increasing demand for manufactured products of hard alloys and metals with high surface finish and complex shape geometry, more interest is now being paid to non-traditional machining (NTM processes, where energy in its direct form is used to remove material from workpiece surface. Compared to conventional machining processes, NTM processes possess almost unlimited capabilities and there is a strong believe that use of NTM processes would go on increasing in diverse range of applications. Presence of a large number of NTM processes along with complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Past researchers have already attempted to solve NTM process selection problems using various complex mathematical approaches which often require a profound knowledge in mathematics/artificial intelligence from the part of process engineers. In this paper, four NTM process selection problems are solved using an integrated PROMETHEE (preference ranking organization method for enrichment evaluation and GAIA (geometrical analysis for interactive aid method which would act as a visual decision aid to the process engineers. The observed results are quite satisfactory and exactly match with the expected solutions.

  4. A CONCEPTUAL MODEL FOR IMPROVED PROJECT SELECTION AND PRIORITISATION

    Directory of Open Access Journals (Sweden)

    P. J. Viljoen

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: Project portfolio management processes are often designed and operated as a series of stages (or project phases and gates. However, the flow of such a process is often slow, characterised by queues waiting for a gate decision and by repeated work from previous stages waiting for additional information or for re-processing. In this paper the authors propose a conceptual model that applies supply chain and constraint management principles to the project portfolio management process. An advantage of the proposed model is that it provides the ability to select and prioritise projects without undue changes to project schedules. This should result in faster flow through the system.

    AFRIKAANSE OPSOMMING: Prosesse om portefeuljes van projekte te bestuur word normaalweg ontwerp en bedryf as ’n reeks fases en hekke. Die vloei deur so ’n proses is dikwels stadig en word gekenmerk deur toue wat wag vir besluite by die hekke en ook deur herwerk van vorige fases wat wag vir verdere inligting of vir herprosessering. In hierdie artikel word ‘n konseptuele model voorgestel. Die model berus op die beginsels van voorsieningskettings sowel as van beperkingsbestuur, en bied die voordeel dat projekte geselekteer en geprioritiseer kan word sonder onnodige veranderinge aan projekskedules. Dit behoort te lei tot versnelde vloei deur die stelsel.

  5. The Ideal Criteria of Supplier Selection for SMEs Food Processing Industry

    OpenAIRE

    Ramlan Rohaizan; Engku Abu Bakar Engku Muhammad Nazri; Mahmud Fatimah; Ng Hooi Keng

    2016-01-01

    Selection of good supplier is important to determine the performance and profitability of SMEs food processing industry. The lack of managerial capability on supplier selection in SMEs food processing industry affects the competitiveness of SMEs food processing industry. This research aims to determine the ideal criteria of supplier for food processing industry using Analytical Hierarchy Process (AHP). The research was carried out in a quantitative method by distributing questionnaires to 50 ...

  6. Management Model for Evaluation and Selection of Engineering Equipment Suppliers for Construction Projects in Iraq

    Directory of Open Access Journals (Sweden)

    Kadhim Raheem Erzaij

    2016-06-01

    Full Text Available Engineering equipment is essential part in the construction project and usually manufactured with long lead times, large costs and special engineering requirements. Construction manager targets that equipment to be delivered in the site need date with the right quantity, appropriate cost and required quality, and this entails an efficient supplier can satisfy these targets. Selection of engineering equipment supplier is a crucial managerial process .it requires evaluation of multiple suppliers according to multiple criteria. This process is usually performed manually and based on just limited evaluation criteria, so better alternatives may be neglected. Three stages of survey comprised number of public and private companies in Iraqi construction sector were employed to identify main criteria and sub criteria for supplier selection and their priorities.The main criteria identified were quality of product, commercial aspect, delivery, reputation and position, and system quality . An effective technique in multiple criteria decision making (MCDM as analytical hierarchy process (AHP have been used to get importance weights of criteria based on experts judgment. Thereafter, a management software system for Evaluation and Selection of Engineering Equipment Suppliers (ESEES has been developed based on the results obtained from AHP. This model was validated in a case study at municipality of Baghdad involved actual cases of selection pumps suppliers for infrastructure projects .According to experts, this model can improve the current process followed in the supplier selection and aid decision makers to adopt better choices in the domain of selection engineering equipment suppliers.

  7. Modeling styles in business process modeling

    NARCIS (Netherlands)

    Pinggera, J.; Soffer, P.; Zugal, S.; Weber, B.; Weidlich, M.; Fahland, D.; Reijers, H.A.; Mendling, J.; Bider, I.; Halpin, T.; Krogstie, J.; Nurcan, S.; Proper, E.; Schmidt, R.; Soffer, P.; Wrycza, S.

    2012-01-01

    Research on quality issues of business process models has recently begun to explore the process of creating process models. As a consequence, the question arises whether different ways of creating process models exist. In this vein, we observed 115 students engaged in the act of modeling, recording

  8. Energy distribution in selected fragment vibrations in dissociation processes in polyatomic molecules

    International Nuclear Information System (INIS)

    Band, Y.B.; Freed, K.F.

    1977-01-01

    The full quantum theory of dissociation processes in polyatomic molecules is converted to a form enabling the isolation of a selected fragment vibration. This form enables the easy evaluation of the probability distribution for energy partitioning between this vibration and all other degrees of freedom that results from the sudden Franck--Condon rearrangement process. The resultant Franck--Condon factors involve the square of the one-dimensional overlap integral between effective oscillator wavefunctions and the wavefunctions for the selected fragment vibration, a form that resembles the simple golden rule model for polyatomic dissociation and reaction processes. The full quantum theory can, therefore, be viewed as providing both a rigorous justification for certain generic aspects of the simple golden rule model as well as providing a number of important generalizations thereof. Some of these involve dealing with initial bound state vibrational excitation, explicit molecule, fragment and energy dependence of the effective oscillator, and the incorporation of all isotopic dependence. In certain limiting situations the full quantum theory yields simple, readily usable analytic expressions for the frequency and equilibrium position of the effective oscillator. Specific applications are presented for the direct photodissociation of HCN, DCN, and CO 2 where comparisons between the full theory and the simple golden rule are presented. We also discuss the generalizations of the previous theory to enable the incorporation of effects of distortion in the normal modes as a function of the reaction coordinate on the repulsive potential energy surface

  9. Cloud decision model for selecting sustainable energy crop based on linguistic intuitionistic information

    Science.gov (United States)

    Peng, Hong-Gang; Wang, Jian-Qiang

    2017-11-01

    In recent years, sustainable energy crop has become an important energy development strategy topic in many countries. Selecting the most sustainable energy crop is a significant problem that must be addressed during any biofuel production process. The focus of this study is the development of an innovative multi-criteria decision-making (MCDM) method to handle sustainable energy crop selection problems. Given that various uncertain data are encountered in the evaluation of sustainable energy crops, linguistic intuitionistic fuzzy numbers (LIFNs) are introduced to present the information necessary to the evaluation process. Processing qualitative concepts requires the effective support of reliable tools; then, a cloud model can be used to deal with linguistic intuitionistic information. First, LIFNs are converted and a novel concept of linguistic intuitionistic cloud (LIC) is proposed. The operations, score function and similarity measurement of the LICs are defined. Subsequently, the linguistic intuitionistic cloud density-prioritised weighted Heronian mean operator is developed, which served as the basis for the construction of an applicable MCDM model for sustainable energy crop selection. Finally, an illustrative example is provided to demonstrate the proposed method, and its feasibility and validity are further verified by comparing it with other existing methods.

  10. Pavement maintenance optimization model using Markov Decision Processes

    Science.gov (United States)

    Mandiartha, P.; Duffield, C. F.; Razelan, I. S. b. M.; Ismail, A. b. H.

    2017-09-01

    This paper presents an optimization model for selection of pavement maintenance intervention using a theory of Markov Decision Processes (MDP). There are some particular characteristics of the MDP developed in this paper which distinguish it from other similar studies or optimization models intended for pavement maintenance policy development. These unique characteristics include a direct inclusion of constraints into the formulation of MDP, the use of an average cost method of MDP, and the policy development process based on the dual linear programming solution. The limited information or discussions that are available on these matters in terms of stochastic based optimization model in road network management motivates this study. This paper uses a data set acquired from road authorities of state of Victoria, Australia, to test the model and recommends steps in the computation of MDP based stochastic optimization model, leading to the development of optimum pavement maintenance policy.

  11. Application of mechanistic models to fermentation and biocatalysis for next-generation processes

    DEFF Research Database (Denmark)

    Gernaey, Krist; Eliasson Lantz, Anna; Tufvesson, Pär

    2010-01-01

    of variables required for measurement, control and process design. In the near future, mechanistic models with a higher degree of detail will play key roles in the development of efficient next-generation fermentation and biocatalytic processes. Moreover, mechanistic models will be used increasingly......Mechanistic models are based on deterministic principles, and recently, interest in them has grown substantially. Herein we present an overview of mechanistic models and their applications in biotechnology, including future perspectives. Model utility is highlighted with respect to selection...

  12. The role of interviewers in job effective recruitment and selection processes

    Directory of Open Access Journals (Sweden)

    Kola O. Odeku

    2015-04-01

    Full Text Available Interview processes are dynamic and sometimes very sensitive and as such, they need to be managed effectively and efficiently by evaluating applicants equally without showing favour or prejudice prior, during and until all processes have been completed. A lot of interview processes for purposes of appointment selections have been tainted with unethical practices where the panellists, who took part in the processes, displayed various forms of partisanship, prejudices and so on. Sometimes, a selector may have premeditated negative mind set towards an applicant which may be evidenced during the interview. This may impact on the reasoning and judgements of the selector and the panellists, thus influencing the decisions of the selector. A brilliant and well performed applicant may be found unqualified Ineffective selection and recruitment processes are increasingly affecting employers by denting their cooperate image and sometimes being subjected to vicious legal battles in courts. This article examines the problems associated with prejudices and unethical practices during selection processes particularly by the recruiters and selectors. It points out that panellists must be properly scrutinised before they are appointed to be part of any selection process and that they should disclose any interest, prejudices, bias and so on that could affect the outcome of the process. It is argued that any member of the panel who is found to have compromised his or her position in any selection processes should be punitively sanctioned.

  13. Development of Electrically Switched Ion Exchange Process for Selective Ion Separations

    International Nuclear Information System (INIS)

    Rassat, Scot D.; Sukamto, Johanes H.; Orth, Rick J.; Lilga, Michael A.; Hallen, Richard T.

    1999-01-01

    The electrically switched ion exchange (ESIX) process, being developed at Pacific Northwest National Laboratory, provides an alternative separation method to selectively remove ions from process and waste streams. In the ESIX process, in which an electroactive ion exchange film is deposited onto a high surface area electrode, uptake and elution are controlled directly by modulating the electrochemical potential of the film. This paper addresses engineering issues necessary to fully develop ESIX for specific industrial alkali cation separation challenges. The cycling and chemical stability and alkali cation selectivity of nickel hexacyanoferrate (NiHCF) electroactive films were investigated. The selectivity of NiHCF was determined using cyclic voltammetry and a quartz crystal microbalance to quantify ion uptake in the film. Separation factors indicated a high selectivity for cesium and a moderate selectivity for potassium in high sodium content solutions. A NiHCF film with improved redox cycling and chemical stability in a simulated pulp mill process stream, a targeted application for ESIX, was also prepared and tested

  14. Divided versus selective attention: evidence for common processing mechanisms.

    Science.gov (United States)

    Hahn, Britta; Wolkenberg, Frank A; Ross, Thomas J; Myers, Carol S; Heishman, Stephen J; Stein, Dan J; Kurup, Pradeep K; Stein, Elliot A

    2008-06-18

    The current study revisited the question of whether there are brain mechanisms specific to divided attention that differ from those used in selective attention. Increased neuronal activity required to simultaneously process two stimulus dimensions as compared with each separate dimension has often been observed, but rarely has activity induced by a divided attention condition exceeded the sum of activity induced by the component tasks. Healthy participants performed a selective-divided attention paradigm while undergoing functional Magnetic Resonance Imaging (fMRI). The task required participants to make a same-different judgment about either one of two simultaneously presented stimulus dimensions, or about both dimensions. Performance accuracy was equated between tasks by dynamically adjusting the stimulus display time. Blood Oxygenation Level Dependent (BOLD) signal differences between tasks were identified by whole-brain voxel-wise comparisons and by region-specific analyses of all areas modulated by the divided attention task (DIV). No region displayed greater activation or deactivation by DIV than the sum of signal change by the two selective attention tasks. Instead, regional activity followed the tasks' processing demands as reflected by reaction time. Only a left cerebellar region displayed a correlation between participants' BOLD signal intensity and reaction time that was selective for DIV. The correlation was positive, reflecting slower responding with greater activation. Overall, the findings do not support the existence of functional brain activity specific to DIV. Increased activity appears to reflect additional processing demands by introducing a secondary task, but those demands do not appear to qualitatively differ from processes of selective attention.

  15. Mathematical modeling of biological processes

    CERN Document Server

    Friedman, Avner

    2014-01-01

    This book on mathematical modeling of biological processes includes a wide selection of biological topics that demonstrate the power of mathematics and computational codes in setting up biological processes with a rigorous and predictive framework. Topics include: enzyme dynamics, spread of disease, harvesting bacteria, competition among live species, neuronal oscillations, transport of neurofilaments in axon, cancer and cancer therapy, and granulomas. Complete with a description of the biological background and biological question that requires the use of mathematics, this book is developed for graduate students and advanced undergraduate students with only basic knowledge of ordinary differential equations and partial differential equations; background in biology is not required. Students will gain knowledge on how to program with MATLAB without previous programming experience and how to use codes in order to test biological hypothesis.

  16. Country Selection Model for Sustainable Construction Businesses Using Hybrid of Objective and Subjective Information

    Directory of Open Access Journals (Sweden)

    Kang-Wook Lee

    2017-05-01

    Full Text Available An important issue for international businesses and academia is selecting countries in which to expand in order to achieve entrepreneurial sustainability. This study develops a country selection model for sustainable construction businesses using both objective and subjective information. The objective information consists of 14 variables related to country risk and project performance in 32 countries over 25 years. This hybrid model applies subjective weighting from industrial experts to objective information using a fuzzy LinPreRa-based Analytic Hierarchy Process. The hybrid model yields a more accurate country selection compared to a purely objective information-based model in experienced countries. Interestingly, the hybrid model provides some different predictions with only subjective opinions in unexperienced countries, which implies that expert opinion is not always reliable. In addition, feedback from five experts in top international companies is used to validate the model’s completeness, effectiveness, generality, and applicability. The model is expected to aid decision makers in selecting better candidate countries that lead to sustainable business success.

  17. Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

    Science.gov (United States)

    Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

    2017-09-01

    In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  18. Strategy for design NIR calibration sets based on process spectrum and model space: An innovative approach for process analytical technology.

    Science.gov (United States)

    Cárdenas, V; Cordobés, M; Blanco, M; Alcalà, M

    2015-10-10

    The pharmaceutical industry is under stringent regulations on quality control of their products because is critical for both, productive process and consumer safety. According to the framework of "process analytical technology" (PAT), a complete understanding of the process and a stepwise monitoring of manufacturing are required. Near infrared spectroscopy (NIRS) combined with chemometrics have lately performed efficient, useful and robust for pharmaceutical analysis. One crucial step in developing effective NIRS-based methodologies is selecting an appropriate calibration set to construct models affording accurate predictions. In this work, we developed calibration models for a pharmaceutical formulation during its three manufacturing stages: blending, compaction and coating. A novel methodology is proposed for selecting the calibration set -"process spectrum"-, into which physical changes in the samples at each stage are algebraically incorporated. Also, we established a "model space" defined by Hotelling's T(2) and Q-residuals statistics for outlier identification - inside/outside the defined space - in order to select objectively the factors to be used in calibration set construction. The results obtained confirm the efficacy of the proposed methodology for stepwise pharmaceutical quality control, and the relevance of the study as a guideline for the implementation of this easy and fast methodology in the pharma industry. Copyright © 2015 Elsevier B.V. All rights reserved.

  19. Application of Bayesian Model Selection for Metal Yield Models using ALEGRA and Dakota.

    Energy Technology Data Exchange (ETDEWEB)

    Portone, Teresa; Niederhaus, John Henry; Sanchez, Jason James; Swiler, Laura Painton

    2018-02-01

    This report introduces the concepts of Bayesian model selection, which provides a systematic means of calibrating and selecting an optimal model to represent a phenomenon. This has many potential applications, including for comparing constitutive models. The ideas described herein are applied to a model selection problem between different yield models for hardened steel under extreme loading conditions.

  20. Selecting public relations personnel of hospitals by analytic network process.

    Science.gov (United States)

    Liao, Sen-Kuei; Chang, Kuei-Lun

    2009-01-01

    This study describes the use of analytic network process (ANP) in the Taiwanese hospital public relations personnel selection process. Starting with interviewing 48 practitioners and executives in north Taiwan, we collected selection criteria. Then, we retained the 12 critical criteria that were mentioned above 40 times by theses respondents, including: interpersonal skill, experience, negotiation, language, ability to follow orders, cognitive ability, adaptation to environment, adaptation to company, emotion, loyalty, attitude, and Response. Finally, we discussed with the 20 executives to take these important criteria into three perspectives to structure the hierarchy for hospital public relations personnel selection. After discussing with practitioners and executives, we find that selecting criteria are interrelated. The ANP, which incorporates interdependence relationships, is a new approach for multi-criteria decision-making. Thus, we apply ANP to select the most optimal public relations personnel of hospitals. An empirical study of public relations personnel selection problems in Taiwan hospitals is conducted to illustrate how the selection procedure works.

  1. Process modeling style

    CERN Document Server

    Long, John

    2014-01-01

    Process Modeling Style focuses on other aspects of process modeling beyond notation that are very important to practitioners. Many people who model processes focus on the specific notation used to create their drawings. While that is important, there are many other aspects to modeling, such as naming, creating identifiers, descriptions, interfaces, patterns, and creating useful process documentation. Experience author John Long focuses on those non-notational aspects of modeling, which practitioners will find invaluable. Gives solid advice for creating roles, work produ

  2. Intermediate product selection and blending in the food processing industry

    DEFF Research Database (Denmark)

    Kilic, Onur A.; Akkerman, Renzo; van Donk, Dirk Pieter

    2013-01-01

    This study addresses a capacitated intermediate product selection and blending problem typical for two-stage production systems in the food processing industry. The problem involves the selection of a set of intermediates and end-product recipes characterising how those selected intermediates...

  3. Intermediate product selection and blending in the food processing industry

    NARCIS (Netherlands)

    Kilic, Onur A.; Akkerman, Renzo; van Donk, Dirk Pieter; Grunow, Martin

    2013-01-01

    This study addresses a capacitated intermediate product selection and blending problem typical for two-stage production systems in the food processing industry. The problem involves the selection of a set of intermediates and end-product recipes characterising how those selected intermediates are

  4. Integrated Site Model Process Model Report

    International Nuclear Information System (INIS)

    Booth, T.

    2000-01-01

    The Integrated Site Model (ISM) provides a framework for discussing the geologic features and properties of Yucca Mountain, which is being evaluated as a potential site for a geologic repository for the disposal of nuclear waste. The ISM is important to the evaluation of the site because it provides 3-D portrayals of site geologic, rock property, and mineralogic characteristics and their spatial variabilities. The ISM is not a single discrete model; rather, it is a set of static representations that provide three-dimensional (3-D), computer representations of site geology, selected hydrologic and rock properties, and mineralogic-characteristics data. These representations are manifested in three separate model components of the ISM: the Geologic Framework Model (GFM), the Rock Properties Model (RPM), and the Mineralogic Model (MM). The GFM provides a representation of the 3-D stratigraphy and geologic structure. Based on the framework provided by the GFM, the RPM and MM provide spatial simulations of the rock and hydrologic properties, and mineralogy, respectively. Functional summaries of the component models and their respective output are provided in Section 1.4. Each of the component models of the ISM considers different specific aspects of the site geologic setting. Each model was developed using unique methodologies and inputs, and the determination of the modeled units for each of the components is dependent on the requirements of that component. Therefore, while the ISM represents the integration of the rock properties and mineralogy into a geologic framework, the discussion of ISM construction and results is most appropriately presented in terms of the three separate components. This Process Model Report (PMR) summarizes the individual component models of the ISM (the GFM, RPM, and MM) and describes how the three components are constructed and combined to form the ISM

  5. The application of the analytic hierarchy process (AHP) in uranium mine mining method of the optimal selection

    International Nuclear Information System (INIS)

    Tan Zhongyin; Kuang Zhengping; Qiu Huiyuan

    2014-01-01

    Analytic hierarchy process, AHP, is a combination of qualitative and quantitative, systematic and hierarchical analysis method. Basic decision theory of analytic hierarchy process is applied in this article, with a project example in north Guangdong region as the research object, the in-situ mining method optimization choose hierarchical analysis model is established and the analysis method, The results show that, the AHP model for mining method selecting model was reliable, optimization results were conformity with the actual use of the in-situ mining method, and it has better practicability. (authors)

  6. Communication activities for NUMO's site selection process

    International Nuclear Information System (INIS)

    Takeuchi, Mitsuo; Okuyama, Shigeru; Kitayama, Kazumi; Kuba, Michiyoshi

    2004-01-01

    A siting program for geological disposal of high-level radioactive waste (HLW) in Japan has just started and is moving into a new stage of communication with the public. A final repository site will be selected via a stepwise process, as stipulated in the Specified Radioactive Waste Final Disposal Act promulgated in June 2000. Based on the Act, the site selection process of the Nuclear Waste Management Organization of Japan (NUMO, established in October 2000) will be carried out in the three steps: selection of Preliminary Investigation Areas (PIAs), selection of Detailed Investigation Areas (DIAs) and selection of the Repository Site. The Act also defines NUMO's responsibilities in terms of implementing the HLW disposal program in an open and transparent manner. NUMO fully understands the importance of public participation in its activities and is aiming to promote public involvement in the process of site selection based on a fundamental policy, which consists of 'adopting a stepwise approach', 'respecting the initiative of municipalities' and 'ensuring transparency in information disclosure'. This policy is clearly reflected in the adoption of an open solicitation approach for volunteer municipalities for Preliminary Investigation Areas (PIAs). NUMO made the official announcement of the start of its open solicitation program on 19 December 2002. This paper outlines how NUMO's activities are currently carried out with a view to encouraging municipalities to volunteer as PIAs and how public awareness of the safety of the HLW disposal is evaluated at this stage

  7. Modeling Natural Selection

    Science.gov (United States)

    Bogiages, Christopher A.; Lotter, Christine

    2011-01-01

    In their research, scientists generate, test, and modify scientific models. These models can be shared with others and demonstrate a scientist's understanding of how the natural world works. Similarly, students can generate and modify models to gain a better understanding of the content, process, and nature of science (Kenyon, Schwarz, and Hug…

  8. From scenarios to domain models: processes and representations

    Science.gov (United States)

    Haddock, Gail; Harbison, Karan

    1994-03-01

    The domain specific software architectures (DSSA) community has defined a philosophy for the development of complex systems. This philosophy improves productivity and efficiency by increasing the user's role in the definition of requirements, increasing the systems engineer's role in the reuse of components, and decreasing the software engineer's role to the development of new components and component modifications only. The scenario-based engineering process (SEP), the first instantiation of the DSSA philosophy, has been adopted by the next generation controller project. It is also the chosen methodology of the trauma care information management system project, and the surrogate semi-autonomous vehicle project. SEP uses scenarios from the user to create domain models and define the system's requirements. Domain knowledge is obtained from a variety of sources including experts, documents, and videos. This knowledge is analyzed using three techniques: scenario analysis, task analysis, and object-oriented analysis. Scenario analysis results in formal representations of selected scenarios. Task analysis of the scenario representations results in descriptions of tasks necessary for object-oriented analysis and also subtasks necessary for functional system analysis. Object-oriented analysis of task descriptions produces domain models and system requirements. This paper examines the representations that support the DSSA philosophy, including reference requirements, reference architectures, and domain models. The processes used to create and use the representations are explained through use of the scenario-based engineering process. Selected examples are taken from the next generation controller project.

  9. Aplication of AHP method in partner's selection process for supply chain development

    Directory of Open Access Journals (Sweden)

    Barac Nada

    2012-06-01

    Full Text Available The process of developing a supply chain is long and complex. with many restrictions and obstacles that accompany it. In this paper the authors focus on the first stage in developing the supply chain and the selection process and selection of partners. This phase of the development significantly affect the competitive position of the supply chain and create value for the consumer. Selected partners or 'links' of the supply chain influence the future performance of the chain which points to the necessity of full commitment to this process. The process of selection and choice of partner is conditioned by the key criteria that are used on that occasion. The use of inadequate criteria may endanger the whole process of building a supply chain partner selection through inadequate future supply chain needs. This paper is an analysis of partner selection based on key criteria used by managers in Serbia. For this purpose we used the AHP method. the results show that these are the top ranked criteria in terms of managers.

  10. Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

    Directory of Open Access Journals (Sweden)

    Hui-qiang Ma

    2014-01-01

    Full Text Available We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance efficient frontier analytically. The results show that the mean-variance efficient frontier is still a parabola in the mean-variance plane, and the optimal strategies depend not only on the total wealth but also on the stock price. Moreover, some numerical examples are given to analyze the sensitivity of the efficient frontier with respect to the elasticity parameter and to illustrate the results presented in this paper. The numerical results show that the price of risk decreases as the elasticity coefficient increases.

  11. Effects of the Ordering of Natural Selection and Population Regulation Mechanisms on Wright-Fisher Models.

    Science.gov (United States)

    He, Zhangyi; Beaumont, Mark; Yu, Feng

    2017-07-05

    We explore the effect of different mechanisms of natural selection on the evolution of populations for one- and two-locus systems. We compare the effect of viability and fecundity selection in the context of the Wright-Fisher model with selection under the assumption of multiplicative fitness. We show that these two modes of natural selection correspond to different orderings of the processes of population regulation and natural selection in the Wright-Fisher model. We find that under the Wright-Fisher model these two different orderings can affect the distribution of trajectories of haplotype frequencies evolving with genetic recombination. However, the difference in the distribution of trajectories is only appreciable when the population is in significant linkage disequilibrium. We find that as linkage disequilibrium decays the trajectories for the two different models rapidly become indistinguishable. We discuss the significance of these findings in terms of biological examples of viability and fecundity selection, and speculate that the effect may be significant when factors such as gene migration maintain a degree of linkage disequilibrium. Copyright © 2017 He et al.

  12. Continuing professional education and the selection of candidates: the case for a tripartite model.

    Science.gov (United States)

    Ellis, L B

    2000-02-01

    This paper argues the case for a tripartite model involving the manager educator and practitioner in the selection of candidates to programmes of continuing professional education (CPE). Nurse educators are said to play a key link in the education practice chain (Pendleton & Myles 1991), yet with the introduction of a market philosophy for education, the educator appears to have little, if any, influence over the selection of CPE candidates. Empirical studies on the value of an effective system for identifying the educational needs of the individual and the locality are unequivocal in specifying the benefits of a collaborative selection process (Larcombe & Maggs 1991). However, there are few studies that offer a model of collaboration and fewer still on how to operationalize such a model. This paper presents the policy and legislative context of CPE leading to the development of a market philosophy. The tension between educational reforms such as life-long learning and diminishing and finite resources are highlighted. These strategic issues provide the backdrop and rationale for considering the process for identifying CPE needs, and the characteristics of an effective system as suggested in the literature. Finally, this paper outlines recommendations for a partnership between the manager practitioner and educationalist in the selection of CPE candidates.

  13. A Heckman Selection- t Model

    KAUST Repository

    Marchenko, Yulia V.; Genton, Marc G.

    2012-01-01

    for sample selection bias based on the SLt model and compare it with the performances of several tests used with the SLN model. Our findings indicate that the latter tests can be misleading in the presence of heavy-tailed data. © 2012 American Statistical

  14. Parameters in selective laser melting for processing metallic powders

    Science.gov (United States)

    Kurzynowski, Tomasz; Chlebus, Edward; Kuźnicka, Bogumiła; Reiner, Jacek

    2012-03-01

    The paper presents results of studies on Selective Laser Melting. SLM is an additive manufacturing technology which may be used to process almost all metallic materials in the form of powder. Types of energy emission sources, mainly fiber lasers and/or Nd:YAG laser with similar characteristics and the wavelength of 1,06 - 1,08 microns, are provided primarily for processing metallic powder materials with high absorption of laser radiation. The paper presents results of selected variable parameters (laser power, scanning time, scanning strategy) and fixed parameters such as the protective atmosphere (argon, nitrogen, helium), temperature, type and shape of the powder material. The thematic scope is very broad, so the work was focused on optimizing the process of selective laser micrometallurgy for producing fully dense parts. The density is closely linked with other two conditions: discontinuity of the microstructure (microcracks) and stability (repeatability) of the process. Materials used for the research were stainless steel 316L (AISI), tool steel H13 (AISI), and titanium alloy Ti6Al7Nb (ISO 5832-11). Studies were performed with a scanning electron microscope, a light microscopes, a confocal microscope and a μCT scanner.

  15. Transforming Collaborative Process Models into Interface Process Models by Applying an MDA Approach

    Science.gov (United States)

    Lazarte, Ivanna M.; Chiotti, Omar; Villarreal, Pablo D.

    Collaborative business models among enterprises require defining collaborative business processes. Enterprises implement B2B collaborations to execute these processes. In B2B collaborations the integration and interoperability of processes and systems of the enterprises are required to support the execution of collaborative processes. From a collaborative process model, which describes the global view of the enterprise interactions, each enterprise must define the interface process that represents the role it performs in the collaborative process in order to implement the process in a Business Process Management System. Hence, in this work we propose a method for the automatic generation of the interface process model of each enterprise from a collaborative process model. This method is based on a Model-Driven Architecture to transform collaborative process models into interface process models. By applying this method, interface processes are guaranteed to be interoperable and defined according to a collaborative process.

  16. SELECTION OF NON-CONVENTIONAL MACHINING PROCESSES USING THE OCRA METHOD

    Directory of Open Access Journals (Sweden)

    Miloš Madić

    2015-04-01

    Full Text Available Selection of the most suitable nonconventional machining process (NCMP for a given machining application can be viewed as multi-criteria decision making (MCDM problem with many conflicting and diverse criteria. To aid these selection processes, different MCDM methods have been proposed. This paper introduces the use of an almost unexplored MCDM method, i.e. operational competitiveness ratings analysis (OCRA method for solving the NCMP selection problems. Applicability, suitability and computational procedure of OCRA method have been demonstrated while solving three case studies dealing with selection of the most suitable NCMP. In each case study the obtained rankings were compared with those derived by the past researchers using different MCDM methods. The results obtained using the OCRA method have good correlation with those derived by the past researchers which validate the usefulness of this method while solving complex NCMP selection problems.

  17. Mutation-selection models of codon substitution and their use to estimate selective strengths on codon usage

    DEFF Research Database (Denmark)

    Yang, Ziheng; Nielsen, Rasmus

    2008-01-01

    Current models of codon substitution are formulated at the levels of nucleotide substitution and do not explicitly consider the separate effects of mutation and selection. They are thus incapable of inferring whether mutation or selection is responsible for evolution at silent sites. Here we impl...... codon usage in mammals. Estimates of selection coefficients nevertheless suggest that selection on codon usage is weak and most mutations are nearly neutral. The sensitivity of the analysis on the assumed mutation model is discussed.......Current models of codon substitution are formulated at the levels of nucleotide substitution and do not explicitly consider the separate effects of mutation and selection. They are thus incapable of inferring whether mutation or selection is responsible for evolution at silent sites. Here we...... implement a few population genetics models of codon substitution that explicitly consider mutation bias and natural selection at the DNA level. Selection on codon usage is modeled by introducing codon-fitness parameters, which together with mutation-bias parameters, predict optimal codon frequencies...

  18. Optimization‐based framework for resin selection strategies in biopharmaceutical purification process development

    Science.gov (United States)

    Liu, Songsong; Gerontas, Spyridon; Gruber, David; Turner, Richard; Titchener‐Hooker, Nigel J.

    2017-01-01

    This work addresses rapid resin selection for integrated chromatographic separations when conducted as part of a high‐throughput screening exercise during the early stages of purification process development. An optimization‐based decision support framework is proposed to process the data generated from microscale experiments to identify the best resins to maximize key performance metrics for a biopharmaceutical manufacturing process, such as yield and purity. A multiobjective mixed integer nonlinear programming model is developed and solved using the ε‐constraint method. Dinkelbach's algorithm is used to solve the resulting mixed integer linear fractional programming model. The proposed framework is successfully applied to an industrial case study of a process to purify recombinant Fc Fusion protein from low molecular weight and high molecular weight product related impurities, involving two chromatographic steps with eight and three candidate resins for each step, respectively. The computational results show the advantage of the proposed framework in terms of computational efficiency and flexibility. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1116–1126, 2017 PMID:28393478

  19. A Computational Model of Selection by Consequences

    Science.gov (United States)

    McDowell, J. J.

    2004-01-01

    Darwinian selection by consequences was instantiated in a computational model that consisted of a repertoire of behaviors undergoing selection, reproduction, and mutation over many generations. The model in effect created a digital organism that emitted behavior continuously. The behavior of this digital organism was studied in three series of…

  20. Selection of Representative Models for Decision Analysis Under Uncertainty

    Science.gov (United States)

    Meira, Luis A. A.; Coelho, Guilherme P.; Santos, Antonio Alberto S.; Schiozer, Denis J.

    2016-03-01

    The decision-making process in oil fields includes a step of risk analysis associated with the uncertainties present in the variables of the problem. Such uncertainties lead to hundreds, even thousands, of possible scenarios that are supposed to be analyzed so an effective production strategy can be selected. Given this high number of scenarios, a technique to reduce this set to a smaller, feasible subset of representative scenarios is imperative. The selected scenarios must be representative of the original set and also free of optimistic and pessimistic bias. This paper is devoted to propose an assisted methodology to identify representative models in oil fields. To do so, first a mathematical function was developed to model the representativeness of a subset of models with respect to the full set that characterizes the problem. Then, an optimization tool was implemented to identify the representative models of any problem, considering not only the cross-plots of the main output variables, but also the risk curves and the probability distribution of the attribute-levels of the problem. The proposed technique was applied to two benchmark cases and the results, evaluated by experts in the field, indicate that the obtained solutions are richer than those identified by previously adopted manual approaches. The program bytecode is available under request.

  1. Conflict between public perceptions and technical processes in site selection

    International Nuclear Information System (INIS)

    Avant, R.V. Jr.; Jacobi, L.R.

    1985-01-01

    U.S. Nuclear Regulatory Commission regulations and guidance on site selection are based on sound technical reasoning. Geology, hydrology, flora and fauna, transportation, demographics, and sociopolitical concerns, to name a few, have been factored into the process. Regardless of the technical objectivity of a site selection process, local opposition groups will challenge technical decisions using technical, nontechnical, and emotional arguments. This paper explores the many conflicts between public perceptions, technical requirements designed to protect the general public, and common arguments against site selection. Ways to deal with opposition are also discussed with emphasis placed on developing effective community relations

  2. A model evaluation checklist for process-based environmental models

    Science.gov (United States)

    Jackson-Blake, Leah

    2015-04-01

    Mechanistic catchment-scale phosphorus models appear to perform poorly where diffuse sources dominate. The reasons for this were investigated for one commonly-applied model, the INtegrated model of CAtchment Phosphorus (INCA-P). Model output was compared to 18 months of daily water quality monitoring data in a small agricultural catchment in Scotland, and model structure, key model processes and internal model responses were examined. Although the model broadly reproduced dissolved phosphorus dynamics, it struggled with particulates. The reasons for poor performance were explored, together with ways in which improvements could be made. The process of critiquing and assessing model performance was then generalised to provide a broadly-applicable model evaluation checklist, incorporating: (1) Calibration challenges, relating to difficulties in thoroughly searching a high-dimensional parameter space and in selecting appropriate means of evaluating model performance. In this study, for example, model simplification was identified as a necessary improvement to reduce the number of parameters requiring calibration, whilst the traditionally-used Nash Sutcliffe model performance statistic was not able to discriminate between realistic and unrealistic model simulations, and alternative statistics were needed. (2) Data limitations, relating to a lack of (or uncertainty in) input data, data to constrain model parameters, data for model calibration and testing, and data to test internal model processes. In this study, model reliability could be improved by addressing all four kinds of data limitation. For example, there was insufficient surface water monitoring data for model testing against an independent dataset to that used in calibration, whilst additional monitoring of groundwater and effluent phosphorus inputs would help distinguish between alternative plausible model parameterisations. (3) Model structural inadequacies, whereby model structure may inadequately represent

  3. Attribute based selection of thermoplastic resin for vacuum infusion process

    DEFF Research Database (Denmark)

    Prabhakaran, R.T. Durai; Lystrup, Aage; Løgstrup Andersen, Tom

    2011-01-01

    The composite industry looks toward a new material system (resins) based on thermoplastic polymers for the vacuum infusion process, similar to the infusion process using thermosetting polymers. A large number of thermoplastics are available in the market with a variety of properties suitable...... for different engineering applications, and few of those are available in a not yet polymerised form suitable for resin infusion. The proper selection of a new resin system among these thermoplastic polymers is a concern for manufactures in the current scenario and a special mathematical tool would...... be beneficial. In this paper, the authors introduce a new decision making tool for resin selection based on significant attributes. This article provides a broad overview of suitable thermoplastic material systems for vacuum infusion process available in today’s market. An illustrative example—resin selection...

  4. An Evaluation Model To Select an Integrated Learning System in a Large, Suburban School District.

    Science.gov (United States)

    Curlette, William L.; And Others

    The systematic evaluation process used in Georgia's DeKalb County School System to purchase comprehensive instructional software--an integrated learning system (ILS)--is described, and the decision-making model for selection is presented. Selection and implementation of an ILS were part of an instructional technology plan for the DeKalb schools…

  5. Orientation selection process during the early stage of cubic dendrite growth: A phase-field crystal study

    International Nuclear Information System (INIS)

    Tang Sai; Wang Zhijun; Guo Yaolin; Wang Jincheng; Yu Yanmei; Zhou Yaohe

    2012-01-01

    Using the phase-field crystal model, we investigate the orientation selection of the cubic dendrite growth at the atomic scale. Our simulation results reproduce how a face-centered cubic (fcc) octahedral nucleus and a body-centered cubic (bcc) truncated-rhombic dodecahedral nucleus choose the preferred growth direction and then evolve into the dendrite pattern. The interface energy anisotropy inherent in the fcc crystal structure leads to the fastest growth velocity in the 〈1 0 0〉 directions. New { 1 1 1} atomic layers prefer to nucleate at positions near the tips of the fcc octahedron, which leads to the directed growth of the fcc dendrite tips in the 〈1 0 0〉 directions. A similar orientation selection process is also found during the early stage of bcc dendrite growth. The orientation selection regime obtained by phase-field crystal simulation is helpful for understanding the orientation selection processes of real dendrite growth.

  6. A computational model of selection by consequences.

    OpenAIRE

    McDowell, J J

    2004-01-01

    Darwinian selection by consequences was instantiated in a computational model that consisted of a repertoire of behaviors undergoing selection, reproduction, and mutation over many generations. The model in effect created a digital organism that emitted behavior continuously. The behavior of this digital organism was studied in three series of computational experiments that arranged reinforcement according to random-interval (RI) schedules. The quantitative features of the model were varied o...

  7. Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection.

    Directory of Open Access Journals (Sweden)

    Mark N Read

    2016-09-01

    Full Text Available The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks (CRWs against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto

  8. MATHEMATICAL МODELLING OF SELECTING INFORMATIVE FEATURES FOR ANALYZING THE LIFE CYCLE PROCESSES OF RADIO-ELECTRONIC MEANS

    Directory of Open Access Journals (Sweden)

    Николай Григорьевич Стародубцев

    2017-09-01

    Full Text Available The subject of the study are methods and models for extracting information about the processes of the life cycle of radio electronic means at the design, production and operation stages. The goal is to develop the fundamentals of the theory of holistic monitoring of the life cycle of radio electronic means at the stages of their design, production and operation, in particular the development of information models for monitoring life cycle indicators in the production of radio electronic means. The attainment of this goal is achieved by solving such problems: research and development of a methodology for solving the problems of selecting informative features characterizing the state of the life cycle of radio electronic means; choice of informative features characterizing the state of the life cycle processes of radio electronic means; identification of the state of the life cycle processes of radio electronic means. To solve these problems, general scientific methods were used: the main provisions of functional analysis, nonequilibrium thermodynamics, estimation and prediction of random processes, optimization methods, pattern recognition. The following results are obtained. Methods for solving the problems of selecting informative features for monitoring the life cycle of radioelectronic facilities are developed by classifying the states of radioelectronic means and the processes of LC in the space of characteristics, each of which has a certain significance, which allowed finding a complex criterion and formalizing the selection procedures. When the number of a priori data is insufficient for a correct classification, heuristic methods of selection according to the criteria for using basic prototypes and information priorities are proposed. Conclusions. The solution of the problem of mathematical modeling of the efficiency functions of the processes of the life cycle of radioelectronic facilities and the choice of informative features for

  9. Statistical model selection with “Big Data”

    Directory of Open Access Journals (Sweden)

    Jurgen A. Doornik

    2015-12-01

    Full Text Available Big Data offer potential benefits for statistical modelling, but confront problems including an excess of false positives, mistaking correlations for causes, ignoring sampling biases and selecting by inappropriate methods. We consider the many important requirements when searching for a data-based relationship using Big Data, and the possible role of Autometrics in that context. Paramount considerations include embedding relationships in general initial models, possibly restricting the number of variables to be selected over by non-statistical criteria (the formulation problem, using good quality data on all variables, analyzed with tight significance levels by a powerful selection procedure, retaining available theory insights (the selection problem while testing for relationships being well specified and invariant to shifts in explanatory variables (the evaluation problem, using a viable approach that resolves the computational problem of immense numbers of possible models.

  10. 3D physical modeling for patterning process development

    Science.gov (United States)

    Sarma, Chandra; Abdo, Amr; Bailey, Todd; Conley, Will; Dunn, Derren; Marokkey, Sajan; Talbi, Mohamed

    2010-03-01

    In this paper we will demonstrate how a 3D physical patterning model can act as a forensic tool for OPC and ground-rule development. We discuss examples where the 2D modeling shows no issues in printing gate lines but 3D modeling shows severe resist loss in the middle. In absence of corrective measure, there is a high likelihood of line discontinuity post etch. Such early insight into process limitations of prospective ground rules can be invaluable for early technology development. We will also demonstrate how the root cause of broken poly-line after etch could be traced to resist necking in the region of STI step with the help of 3D models. We discuss different cases of metal and contact layouts where 3D modeling gives an early insight in to technology limitations. In addition such a 3D physical model could be used for early resist evaluation and selection for required ground-rule challenges, which can substantially reduce the cycle time for process development.

  11. Handling equipment Selection in open pit mines by using an integrated model based on group decision making

    Directory of Open Access Journals (Sweden)

    Abdolreza Yazdani-Chamzini

    2012-10-01

    Full Text Available Process of handling equipment selection is one of the most important and basic parts in the project planning, particularly mining projects due to holding a high charge of the total project's cost. Different criteria impact on the handling equipment selection, while these criteria often are in conflicting with each other. Therefore, the process of handling equipment selection is a complex and multi criteria decision making problem. There are a variety of methods for selecting the most appropriate equipment among a set of alternatives. Likewise, according to the sophisticated structure of the problem, imprecise data, less of information, and inherent uncertainty, the usage of the fuzzy sets can be useful. In this study a new integrated model based on fuzzy analytic hierarchy process (FAHP and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS is proposed, which uses group decision making to reduce individual errors. In order to calculate the weights of the evaluation criteria, FAHP is utilized in the process of handling equipment selection, and then these weights are inserted to the FTOPSIS computations to select the most appropriate handling system among a pool of alternatives. The results of this study demonstrate the potential application and effectiveness of the proposed model, which can be applied to different types of sophisticated problems in real problems.

  12. Training Self-Regulated Learning Skills with Video Modeling Examples: Do Task-Selection Skills Transfer?

    Science.gov (United States)

    Raaijmakers, Steven F.; Baars, Martine; Schaap, Lydia; Paas, Fred; van Merriënboer, Jeroen; van Gog, Tamara

    2018-01-01

    Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and…

  13. Seeking inclusion in an exclusive process: discourses of medical school student selection.

    Science.gov (United States)

    Razack, Saleem; Hodges, Brian; Steinert, Yvonne; Maguire, Mary

    2015-01-01

    Calls to increase medical class representativeness to better reflect the diversity of society represent a growing international trend. There is an inherent tension between these calls and competitive student selection processes driven by academic achievement. How is this tension manifested? Our three-phase interdisciplinary research programme focused on the discourses of excellence, equity and diversity in the medical school selection process, as conveyed by key stakeholders: (i) institutions and regulatory bodies (the websites of 17 medical schools and 15 policy documents from national regulatory bodies); (ii) admissions committee members (ACMs) (according to semi-structured interviews [n = 9]), and (iii) successful applicants (according to semi-structured interviews [n = 14]). The work is theoretically situated within the works of Foucault, Bourdieu and Bakhtin. The conceptual framework is supplemented by critical hermeneutics and the performance theories of Goffman. Academic excellence discourses consistently predominate over discourses calling for greater representativeness in medical classes. Policy addressing demographic representativeness in medicine may unwittingly contribute to the reproduction of historical patterns of exclusion of under-represented groups. In ACM selection practices, another discursive tension is exposed as the inherent privilege in the process is marked, challenging the ideal of medicine as a meritocracy. Applicants' representations of self in the 'performance' of interviewing demonstrate implicit recognition of the power inherent in the act of selection and are manifested in the use of explicit strategies to 'fit in'. How can this critical discourse analysis inform improved inclusiveness in student selection? Policymakers addressing diversity and equity issues in medical school admissions should explicitly recognise the power dynamics at play between the profession and marginalised groups. For greater inclusion and to avoid one

  14. Advanced modeling of management processes in information technology

    CERN Document Server

    Kowalczuk, Zdzislaw

    2014-01-01

    This book deals with the issues of modelling management processes of information technology and IT projects while its core is the model of information technology management and its component models (contextual, local) describing initial processing and the maturity capsule as well as a decision-making system represented by a multi-level sequential model of IT technology selection, which acquires a fuzzy rule-based implementation in this work. In terms of applicability, this work may also be useful for diagnosing applicability of IT standards in evaluation of IT organizations. The results of this diagnosis might prove valid for those preparing new standards so that – apart from their own visions – they could, to an even greater extent, take into account the capabilities and needs of the leaders of project and manufacturing teams. The book is intended for IT professionals using the ITIL, COBIT and TOGAF standards in their work. Students of computer science and management who are interested in the issue of IT...

  15. A Dual-Stage Two-Phase Model of Selective Attention

    Science.gov (United States)

    Hubner, Ronald; Steinhauser, Marco; Lehle, Carola

    2010-01-01

    The dual-stage two-phase (DSTP) model is introduced as a formal and general model of selective attention that includes both an early and a late stage of stimulus selection. Whereas at the early stage information is selected by perceptual filters whose selectivity is relatively limited, at the late stage stimuli are selected more efficiently on a…

  16. River water quality model no. 1 (RWQM1): II. Biochemical process equations

    DEFF Research Database (Denmark)

    Reichert, P.; Borchardt, D.; Henze, Mogens

    2001-01-01

    In this paper, biochemical process equations are presented as a basis for water quality modelling in rivers under aerobic and anoxic conditions. These equations are not new, but they summarise parts of the development over the past 75 years. The primary goals of the presentation are to stimulate...... transformation processes. This paper is part of a series of three papers. In the first paper, the general modelling approach is described; in the present paper, the biochemical process equations of a complex model are presented; and in the third paper, recommendations are given for the selection of a reasonable...

  17. Comparison of climate envelope models developed using expert-selected variables versus statistical selection

    Science.gov (United States)

    Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

    2017-01-01

    Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

  18. Modelling of innovative SANEX process mal-operations

    International Nuclear Information System (INIS)

    McLachlan, F.; Taylor, R.; Whittaker, D.; Woodhead, D.; Geist, A.

    2016-01-01

    The innovative (i-) SANEX process for the separation of minor actinides from PUREX highly active raffinate is expected to employ a solvent phase comprising 0.2 M TODGA with 5 v/v% 1-octanol in an inert diluent. An initial extract / scrub section would be used to extract trivalent actinides and lanthanides from the feed whilst leaving other fission products in the aqueous phase, before the loaded solvent is contacted with a low acidity aqueous phase containing a sulphonated bis-triazinyl pyridine ligand (BTP) to effect a selective strip of the actinides, so yielding separate actinide (An) and lanthanide (Ln) product streams. This process has been demonstrated in lab scale trials at Juelich (FZJ). The SACSESS (Safety of Actinide Separation processes) project is focused on the evaluation and improvement of the safety of such future systems. A key element of this is the development of an understanding of the response of a process to upsets (mal-operations). It is only practical to study a small subset of possible mal-operations experimentally and consideration of the majority of mal-operations entails the use of a validated dynamic model of the process. Distribution algorithms for HNO_3, Am, Cm and the lanthanides have been developed and incorporated into a dynamic flowsheet model that has, so far, been configured to correspond to the extract-scrub section of the i-SANEX flowsheet trial undertaken at FZJ in 2013. Comparison is made between the steady state model results and experimental results. Results from modelling of low acidity and high temperature mal-operations are presented. (authors)

  19. Using Card Games to Simulate the Process of Natural Selection

    Science.gov (United States)

    Grilliot, Matthew E.; Harden, Siegfried

    2014-01-01

    In 1858, Darwin published "On the Origin of Species by Means of Natural Selection." His explanation of evolution by natural selection has become the unifying theme of biology. We have found that many students do not fully comprehend the process of evolution by natural selection. We discuss a few simple games that incorporate hands-on…

  20. Elementary Teachers' Selection and Use of Visual Models

    Science.gov (United States)

    Lee, Tammy D.; Gail Jones, M.

    2018-02-01

    As science grows in complexity, science teachers face an increasing challenge of helping students interpret models that represent complex science systems. Little is known about how teachers select and use models when planning lessons. This mixed methods study investigated the pedagogical approaches and visual models used by elementary in-service and preservice teachers in the development of a science lesson about a complex system (e.g., water cycle). Sixty-seven elementary in-service and 69 elementary preservice teachers completed a card sort task designed to document the types of visual models (e.g., images) that teachers choose when planning science instruction. Quantitative and qualitative analyses were conducted to analyze the card sort task. Semistructured interviews were conducted with a subsample of teachers to elicit the rationale for image selection. Results from this study showed that both experienced in-service teachers and novice preservice teachers tended to select similar models and use similar rationales for images to be used in lessons. Teachers tended to select models that were aesthetically pleasing and simple in design and illustrated specific elements of the water cycle. The results also showed that teachers were not likely to select images that represented the less obvious dimensions of the water cycle. Furthermore, teachers selected visual models more as a pedagogical tool to illustrate specific elements of the water cycle and less often as a tool to promote student learning related to complex systems.

  1. Genetic search feature selection for affective modeling

    DEFF Research Database (Denmark)

    Martínez, Héctor P.; Yannakakis, Georgios N.

    2010-01-01

    Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

  2. Procedure for the Selection and Validation of a Calibration Model I-Description and Application.

    Science.gov (United States)

    Desharnais, Brigitte; Camirand-Lemyre, Félix; Mireault, Pascal; Skinner, Cameron D

    2017-05-01

    Calibration model selection is required for all quantitative methods in toxicology and more broadly in bioanalysis. This typically involves selecting the equation order (quadratic or linear) and weighting factor correctly modelizing the data. A mis-selection of the calibration model will generate lower quality control (QC) accuracy, with an error up to 154%. Unfortunately, simple tools to perform this selection and tests to validate the resulting model are lacking. We present a stepwise, analyst-independent scheme for selection and validation of calibration models. The success rate of this scheme is on average 40% higher than a traditional "fit and check the QCs accuracy" method of selecting the calibration model. Moreover, the process was completely automated through a script (available in Supplemental Data 3) running in RStudio (free, open-source software). The need for weighting was assessed through an F-test using the variances of the upper limit of quantification and lower limit of quantification replicate measurements. When weighting was required, the choice between 1/x and 1/x2 was determined by calculating which option generated the smallest spread of weighted normalized variances. Finally, model order was selected through a partial F-test. The chosen calibration model was validated through Cramer-von Mises or Kolmogorov-Smirnov normality testing of the standardized residuals. Performance of the different tests was assessed using 50 simulated data sets per possible calibration model (e.g., linear-no weight, quadratic-no weight, linear-1/x, etc.). This first of two papers describes the tests, procedures and outcomes of the developed procedure using real LC-MS-MS results for the quantification of cocaine and naltrexone. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  3. Concepts of radiation processes selection for industrial realization. Chapter 6

    International Nuclear Information System (INIS)

    1997-01-01

    For selection of radiation processes in industry the processes usually are analyzing by technological and social effects, power-insensitivity, common efficiency. Technological effect is generally conditioned with uniqueness of radiation technologies which allow to obtain new material or certain one but with new properties. Social effect first of all concerns with influence of radiation technologies on consumer's psychology. Implementation of equipment for radiation technological process for both the new material production and natural materials radiation treatment is related with decision of three tasks: 1) Choice of radiation source; 2). Creation of special equipment for radiation and untraditional stages of the process; 3) Selection of radiation and other conditions ensuring of achievement of optimal technological and economical indexes

  4. PARAMETER ESTIMATION AND MODEL SELECTION FOR INDOOR ENVIRONMENTS BASED ON SPARSE OBSERVATIONS

    Directory of Open Access Journals (Sweden)

    Y. Dehbi

    2017-09-01

    Full Text Available This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

  5. Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations

    Science.gov (United States)

    Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.

    2017-09-01

    This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

  6. Modelling Technical and Economic Parameters in Selection of Manufacturing Devices

    Directory of Open Access Journals (Sweden)

    Naqib Daneshjo

    2017-11-01

    Full Text Available Sustainable science and technology development is also conditioned by continuous development of means of production which have a key role in structure of each production system. Mechanical nature of the means of production is complemented by controlling and electronic devices in context of intelligent industry. A selection of production machines for a technological process or technological project has so far been practically resolved, often only intuitively. With regard to increasing intelligence, the number of variable parameters that have to be considered when choosing a production device is also increasing. It is necessary to use computing techniques and decision making methods according to heuristic methods and more precise methodological procedures during the selection. The authors present an innovative model for optimization of technical and economic parameters in the selection of manufacturing devices for industry 4.0.

  7. Selecting an interprofessional education model for a tertiary health care setting.

    Science.gov (United States)

    Menard, Prudy; Varpio, Lara

    2014-07-01

    The World Health Organization describes interprofessional education (IPE) and collaboration as necessary components of all health professionals' education - in curriculum and in practice. However, no standard framework exists to guide healthcare settings in developing or selecting an IPE model that meets the learning needs of licensed practitioners in practice and that suits the unique needs of their setting. Initially, a broad review of the grey literature (organizational websites, government documents and published books) and healthcare databases was undertaken for existing IPE models. Subsequently, database searches of published papers using Scopus, Scholars Portal and Medline was undertaken. Through this search process five IPE models were identified in the literature. This paper attempts to: briefly outline the five different models of IPE that are presently offered in the literature; and illustrate how a healthcare setting can select the IPE model within their context using Reeves' seven key trends in developing IPE. In presenting these results, the paper contributes to the interprofessional literature by offering an overview of possible IPE models that can be used to inform the implementation or modification of interprofessional practices in a tertiary healthcare setting.

  8. Investigation of the site selection examples adopted local participation. The site selection processes in Belgium, UK and Switzerland

    International Nuclear Information System (INIS)

    Kageyama, Hitoshi; Suzuki, Shinji; Hirose, Ikuro; Yoshioka, Tatsuji

    2014-06-01

    In late years, local participation policies are being adopted in foreign countries at site selection for the disposal of the radioactive waste. We performed documents investigation about the examples of the site selection processes of Belgium, the U.K., and Switzerland to establish the site selection policy in Japan. In Belgium, after the failure of the site selection for the disposal of short-lived low and intermediate level radioactive waste (LILW) in an early stage, the idea of the local partnership (LP) was developed and three independent LPs were established between the implementing body and each municipality. About 7 years later, one site was decided as the disposal site in the cabinet meeting of the federal government. In the U.K., after the failure of the site selection for the rock characterization facility, the government policy was changed and the consultation process comprised of six phases was started. Though the process had been carried out for over 4 years since one combined partnership was established between the implementing body and the municipalities involved, they had to withdraw from the consulting process because a county council had not accepted that the process would step forward to the 4th phase. In Switzerland, the implementing body selected one site for LILW disposal at an early stage, but the project was denied by the referendum in the Canton having jurisdiction over the site area. After that the Federal Parliament established new Nuclear Energy Act and Nuclear Energy Ordinance precluding the veto of Canton. Now the site selection project is being carried out according to the process comprised of three phases with local participation policy. Reviewing the merits and demerits of each example through this investigation, we confirmed if we are to adopt local participation policy in our country in future, further prudent study would be necessary, considering current and future social conditions in Japan. (author)

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

    Science.gov (United States)

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

    2017-07-01

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

  10. STUDY CONCERNING THE ELABORATION OF CERTAIN ORIENTATION MODELS AND THE INITIAL SELECTION FOR SPEED SKATING

    Directory of Open Access Journals (Sweden)

    Vaida Marius

    2009-12-01

    Full Text Available In realizing this study I started from the premise that, by elaborating certain orientation models and initial selection for the speed skating and their application will appear superior results, necessary results, taking into account the actual evolution of the high performance sport in general and of the speed skating, in special.The target of this study has been the identification of an orientation model and a complete initial selection that should be based on the favorable aptitudes of the speed skating. On the basis of the made researched orientation models and initial selection has been made, things that have been demonstrated experimental that are not viable, the study starting from the data of the 120 copies, the complete experiment being made by 32 subjects separated in two groups, one using the proposed model and the other formed fromsubjects randomly selected.These models can serve as common working instruments both for the orientation process and for the initial selection one, being able to integrate in the proper practical activity, these being used easily both by coaches that are in charge with the proper selection of the athletes but also by the physical education teachers orschool teachers that are in contact with children of an early age.

  11. Using Deep Learning for Targeted Data Selection, Improving Satellite Observation Utilization for Model Initialization

    Science.gov (United States)

    Lee, Y. J.; Bonfanti, C. E.; Trailovic, L.; Etherton, B.; Govett, M.; Stewart, J.

    2017-12-01

    At present, a fraction of all satellite observations are ultimately used for model assimilation. The satellite data assimilation process is computationally expensive and data are often reduced in resolution to allow timely incorporation into the forecast. This problem is only exacerbated by the recent launch of Geostationary Operational Environmental Satellite (GOES)-16 satellite and future satellites providing several order of magnitude increase in data volume. At the NOAA Earth System Research Laboratory (ESRL) we are researching the use of machine learning the improve the initial selection of satellite data to be used in the model assimilation process. In particular, we are investigating the use of deep learning. Deep learning is being applied to many image processing and computer vision problems with great success. Through our research, we are using convolutional neural network to find and mark regions of interest (ROI) to lead to intelligent extraction of observations from satellite observation systems. These targeted observations will be used to improve the quality of data selected for model assimilation and ultimately improve the impact of satellite data on weather forecasts. Our preliminary efforts to identify the ROI's are focused in two areas: applying and comparing state-of-art convolutional neural network models using the analysis data from the National Center for Environmental Prediction (NCEP) Global Forecast System (GFS) weather model, and using these results as a starting point to optimize convolution neural network model for pattern recognition on the higher resolution water vapor data from GOES-WEST and other satellite. This presentation will provide an introduction to our convolutional neural network model to identify and process these ROI's, along with the challenges of data preparation, training the model, and parameter optimization.

  12. An automated process for building reliable and optimal in vitro/in vivo correlation models based on Monte Carlo simulations.

    Science.gov (United States)

    Sutton, Steven C; Hu, Mingxiu

    2006-05-05

    Many mathematical models have been proposed for establishing an in vitro/in vivo correlation (IVIVC). The traditional IVIVC model building process consists of 5 steps: deconvolution, model fitting, convolution, prediction error evaluation, and cross-validation. This is a time-consuming process and typically a few models at most are tested for any given data set. The objectives of this work were to (1) propose a statistical tool to screen models for further development of an IVIVC, (2) evaluate the performance of each model under different circumstances, and (3) investigate the effectiveness of common statistical model selection criteria for choosing IVIVC models. A computer program was developed to explore which model(s) would be most likely to work well with a random variation from the original formulation. The process used Monte Carlo simulation techniques to build IVIVC models. Data-based model selection criteria (Akaike Information Criteria [AIC], R2) and the probability of passing the Food and Drug Administration "prediction error" requirement was calculated. To illustrate this approach, several real data sets representing a broad range of release profiles are used to illustrate the process and to demonstrate the advantages of this automated process over the traditional approach. The Hixson-Crowell and Weibull models were often preferred over the linear. When evaluating whether a Level A IVIVC model was possible, the model selection criteria AIC generally selected the best model. We believe that the approach we proposed may be a rapid tool to determine which IVIVC model (if any) is the most applicable.

  13. Standard Model processes

    CERN Document Server

    Mangano, M.L.; Aguilar-Saavedra, Juan Antonio; Alekhin, S.; Badger, S.; Bauer, C.W.; Becher, T.; Bertone, V.; Bonvini, M.; Boselli, S.; Bothmann, E.; Boughezal, R.; Cacciari, M.; Carloni Calame, C.M.; Caola, F.; Campbell, J.M.; Carrazza, S.; Chiesa, M.; Cieri, L.; Cimaglia, F.; Febres Cordero, F.; Ferrarese, P.; D'Enterria, D.; Ferrera, G.; Garcia i Tormo, X.; Garzelli, M.V.; Germann, E.; Hirschi, V.; Han, T.; Ita, H.; Jäger, B.; Kallweit, S.; Karlberg, A.; Kuttimalai, S.; Krauss, F.; Larkoski, A.J.; Lindert, J.; Luisoni, G.; Maierhöfer, P.; Mattelaer, O.; Martinez, H.; Moch, S.; Montagna, G.; Moretti, M.; Nason, P.; Nicrosini, O.; Oleari, C.; Pagani, D.; Papaefstathiou, A.; Petriello, F.; Piccinini, F.; Pierini, M.; Pierog, T.; Pozzorini, S.; Re, E.; Robens, T.; Rojo, J.; Ruiz, R.; Sakurai, K.; Salam, G.P.; Salfelder, L.; Schönherr, M.; Schulze, M.; Schumann, S.; Selvaggi, M.; Shivaji, A.; Siodmok, A.; Skands, P.; Torrielli, P.; Tramontano, F.; Tsinikos, I.; Tweedie, B.; Vicini, A.; Westhoff, S.; Zaro, M.; Zeppenfeld, D.; CERN. Geneva. ATS Department

    2017-06-22

    This report summarises the properties of Standard Model processes at the 100 TeV pp collider. We document the production rates and typical distributions for a number of benchmark Standard Model processes, and discuss new dynamical phenomena arising at the highest energies available at this collider. We discuss the intrinsic physics interest in the measurement of these Standard Model processes, as well as their role as backgrounds for New Physics searches.

  14. Process Simulation for the Design and Scale Up of Heterogeneous Catalytic Process: Kinetic Modelling Issues

    Directory of Open Access Journals (Sweden)

    Antonio Tripodi

    2017-05-01

    Full Text Available Process simulation represents an important tool for plant design and optimization, either applied to well established or to newly developed processes. Suitable thermodynamic packages should be selected in order to properly describe the behavior of reactors and unit operations and to precisely define phase equilibria. Moreover, a detailed and representative kinetic scheme should be available to predict correctly the dependence of the process on its main variables. This review points out some models and methods for kinetic analysis specifically applied to the simulation of catalytic processes, as a basis for process design and optimization. Attention is paid also to microkinetic modelling and to the methods based on first principles, to elucidate mechanisms and independently calculate thermodynamic and kinetic parameters. Different case studies support the discussion. At first, we have selected two basic examples from the industrial chemistry practice, e.g., ammonia and methanol synthesis, which may be described through a relatively simple reaction pathway and the relative available kinetic scheme. Then, a more complex reaction network is deeply discussed to define the conversion of bioethanol into syngas/hydrogen or into building blocks, such as ethylene. In this case, lumped kinetic schemes completely fail the description of process behavior. Thus, in this case, more detailed—e.g., microkinetic—schemes should be available to implement into the simulator. However, the correct definition of all the kinetic data when complex microkinetic mechanisms are used, often leads to unreliable, highly correlated parameters. In such cases, greater effort to independently estimate some relevant kinetic/thermodynamic data through Density Functional Theory (DFT/ab initio methods may be helpful to improve process description.

  15. Modeling of sorption processes on solid-phase ion-exchangers

    Science.gov (United States)

    Dorofeeva, Ludmila; Kuan, Nguyen Anh

    2018-03-01

    Research of alkaline elements separation on solid-phase ion-exchangers is carried out to define the selectivity coefficients and height of an equivalent theoretical stage for both continuous and stepwise filling of column by ionite. On inorganic selective sorbents the increase in isotope enrichment factor up to 0.0127 is received. Also, parametrical models that are adequately describing dependence of the pressure difference and the magnitude expansion in the ion-exchange layer from the flow rate and temperature have been obtained. The concentration rate value under the optimum realization conditions of process and depending on type of a selective material changes in a range 1.021÷1.092. Calculated results show agreement with experimental data.

  16. A Dynamic Model for Limb Selection

    NARCIS (Netherlands)

    Cox, R.F.A; Smitsman, A.W.

    2008-01-01

    Two experiments and a model on limb selection are reported. In Experiment 1 left-handed and right-handed participants (N = 36) repeatedly used one hand for grasping a small cube. After a clear switch in the cube’s location, perseverative limb selection was revealed in both handedness groups. In

  17. A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data

    International Nuclear Information System (INIS)

    Louit, D.M.; Pascual, R.; Jardine, A.K.S.

    2009-01-01

    Many times, reliability studies rely on false premises such as independent and identically distributed time between failures assumption (renewal process). This can lead to erroneous model selection for the time to failure of a particular component or system, which can in turn lead to wrong conclusions and decisions. A strong statistical focus, a lack of a systematic approach and sometimes inadequate theoretical background seem to have made it difficult for maintenance analysts to adopt the necessary stage of data testing before the selection of a suitable model. In this paper, a framework for model selection to represent the failure process for a component or system is presented, based on a review of available trend tests. The paper focuses only on single-time-variable models and is primarily directed to analysts responsible for reliability analyses in an industrial maintenance environment. The model selection framework is directed towards the discrimination between the use of statistical distributions to represent the time to failure ('renewal approach'); and the use of stochastic point processes ('repairable systems approach'), when there may be the presence of system ageing or reliability growth. An illustrative example based on failure data from a fleet of backhoes is included.

  18. Visualizing the process of process modeling with PPMCharts

    NARCIS (Netherlands)

    Claes, J.; Vanderfeesten, I.T.P.; Pinggera, J.; Reijers, H.A.; Weber, B.; Poels, G.; La Rosa, M.; Soffer, P.

    2013-01-01

    In the quest for knowledge about how to make good process models, recent research focus is shifting from studying the quality of process models to studying the process of process modeling (often abbreviated as PPM) itself. This paper reports on our efforts to visualize this specific process in such

  19. Understanding tradeoffs in the supplier selection process : The role of flexibility, delivery, and value-added services/support

    NARCIS (Netherlands)

    Rhee, van der B.; Verma, R.; Plaschka, G.

    2009-01-01

    In this study, we present, based on econometric choice modeling framework, how manufacturing managers/executives trade-off between cost, delivery, flexibility, and service features in the supplier selection process for commodity raw materials, given acceptable quality. Empirical data for this study

  20. A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection

    Science.gov (United States)

    Sabourin, Jeremy A; Valdar, William; Nobel, Andrew B

    2015-01-01

    Summary We describe a simple, computationally effcient, permutation-based procedure for selecting the penalty parameter in LASSO penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study and an analysis of real biomedical data sets in which permutation selection is compared with selection based on the following: cross-validation (CV), the Bayesian information criterion (BIC), Scaled Sparse Linear Regression, and a selection method based on recently developed testing procedures for the LASSO. PMID:26243050

  1. Attentional selection of relative SF mediates global versus local processing: evidence from EEG.

    Science.gov (United States)

    Flevaris, Anastasia V; Bentin, Shlomo; Robertson, Lynn C

    2011-06-13

    Previous research on functional hemispheric differences in visual processing has associated global perception with low spatial frequency (LSF) processing biases of the right hemisphere (RH) and local perception with high spatial frequency (HSF) processing biases of the left hemisphere (LH). The Double Filtering by Frequency (DFF) theory expanded this hypothesis by proposing that visual attention selects and is directed to relatively LSFs by the RH and relatively HSFs by the LH, suggesting a direct causal relationship between SF selection and global versus local perception. We tested this idea in the current experiment by comparing activity in the EEG recorded at posterior right and posterior left hemisphere sites while participants' attention was directed to global or local levels of processing after selection of relatively LSFs versus HSFs in a previous stimulus. Hemispheric asymmetry in the alpha band (8-12 Hz) during preparation for global versus local processing was modulated by the selected SF. In contrast, preparatory activity associated with selection of SF was not modulated by the previously attended level (global/local). These results support the DFF theory that top-down attentional selection of SF mediates global and local processing.

  2. An integrated knowledge-based and optimization tool for the sustainable selection of wastewater treatment process concepts

    DEFF Research Database (Denmark)

    Castillo, A.; Cheali, Peam; Gómez, V.

    2016-01-01

    The increasing demand on wastewater treatment plants (WWTPs) has involved an interest in improving the alternative treatment selection process. In this study, an integrated framework including an intelligent knowledge-based system and superstructure-based optimization has been developed and applied...... to a real case study. Hence, a multi-criteria analysis together with mathematical models is applied to generate a ranked short-list of feasible treatments for three different scenarios. Finally, the uncertainty analysis performed allows for increasing the quality and robustness of the decisions considering...... benefit and synergy is achieved when both tools are integrated because expert knowledge and expertise are considered together with mathematical models to select the most appropriate treatment alternative...

  3. Application of Tecnomatix Plant Simulation for Modeling Production and Logistics Processes

    Directory of Open Access Journals (Sweden)

    Julia Siderska

    2016-06-01

    Full Text Available The main objective of the article was to present the possibilities and examples of using Tecnomatix Plant Simulation (by Siemens to simulate the production and logistics processes. This tool allows to simulate discrete events and create digital models of logistic systems (e.g. production, optimize the operation of production plants, production lines, as well as individual logistics processes. The review of implementations of Tecnomatix Plant Simulation for modeling processes in production engineering and logistics was conducted and a few selected examples of simulations were presented. The author’s future studies are going to focus on simulation of production and logistic processes and their optimization with the use of genetic algorithms and artificial neural networks.

  4. Statistical test data selection for reliability evalution of process computer software

    International Nuclear Information System (INIS)

    Volkmann, K.P.; Hoermann, H.; Ehrenberger, W.

    1976-01-01

    The paper presents a concept for converting knowledge about the characteristics of process states into practicable procedures for the statistical selection of test cases in testing process computer software. Process states are defined as vectors whose components consist of values of input variables lying in discrete positions or within given limits. Two approaches for test data selection, based on knowledge about cases of demand, are outlined referring to a purely probabilistic method and to the mathematics of stratified sampling. (orig.) [de

  5. HOSPITAL SITE SELECTION USING TWO-STAGE FUZZY MULTI-CRITERIA DECISION MAKING PROCESS

    Directory of Open Access Journals (Sweden)

    Ali Soltani

    2011-06-01

    Full Text Available Site selection for sitting of urban activities/facilities is one of the crucial policy-related decisions taken by urban planners and policy makers. The process of site selection is inherently complicated. A careless site imposes exorbitant costs on city budget and damages the environment inevitably. Nowadays, multi-attributes decision making approaches are suggested to use to improve precision of decision making and reduce surplus side effects. Two well-known techniques, analytical hierarchal process and analytical network process are among multi-criteria decision making systems which can easily be consistent with both quantitative and qualitative criteria. These are also developed to be fuzzy analytical hierarchal process and fuzzy analytical network process systems which are capable of accommodating inherent uncertainty and vagueness in multi-criteria decision-making. This paper reports the process and results of a hospital site selection within the Region 5 of Shiraz metropolitan area, Iran using integrated fuzzy analytical network process systems with Geographic Information System (GIS. The weights of the alternatives were calculated using fuzzy analytical network process. Then a sensitivity analysis was conducted to measure the elasticity of a decision in regards to different criteria. This study contributes to planning practice by suggesting a more comprehensive decision making tool for site selection.

  6. HOSPITAL SITE SELECTION USING TWO-STAGE FUZZY MULTI-CRITERIA DECISION MAKING PROCESS

    Directory of Open Access Journals (Sweden)

    Ali Soltani

    2011-01-01

    Full Text Available Site selection for sitting of urban activities/facilities is one of the crucial policy-related decisions taken by urban planners and policy makers. The process of site selection is inherently complicated. A careless site imposes exorbitant costs on city budget and damages the environment inevitably. Nowadays, multi-attributes decision making approaches are suggested to use to improve precision of decision making and reduce surplus side effects. Two well-known techniques, analytical hierarchal process and analytical network process are among multi-criteria decision making systems which can easily be consistent with both quantitative and qualitative criteria. These are also developed to be fuzzy analytical hierarchal process and fuzzy analytical network process systems which are capable of accommodating inherent uncertainty and vagueness in multi-criteria decision-making. This paper reports the process and results of a hospital site selection within the Region 5 of Shiraz metropolitan area, Iran using integrated fuzzy analytical network process systems with Geographic Information System (GIS. The weights of the alternatives were calculated using fuzzy analytical network process. Then a sensitivity analysis was conducted to measure the elasticity of a decision in regards to different criteria. This study contributes to planning practice by suggesting a more comprehensive decision making tool for site selection.

  7. Model selection for convolutive ICA with an application to spatiotemporal analysis of EEG

    DEFF Research Database (Denmark)

    Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

    2007-01-01

    We present a new algorithm for maximum likelihood convolutive independent component analysis (ICA) in which components are unmixed using stable autoregressive filters determined implicitly by estimating a convolutive model of the mixing process. By introducing a convolutive mixing model...... for the components, we show how the order of the filters in the model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving a subspace of independent components in electroencephalography (EEG). Initial results suggest that in some cases, convolutive mixing may...

  8. An International Perspective on Pharmacy Student Selection Policies and Processes.

    Science.gov (United States)

    Shaw, John; Kennedy, Julia; Jensen, Maree; Sheridan, Janie

    2015-10-25

    Objective. To reflect on selection policies and procedures for programs at pharmacy schools that are members of an international alliance of universities (Universitas 21). Methods. A questionnaire on selection policies and procedures was distributed to admissions directors at participating schools. Results. Completed questionnaires were received from 7 schools in 6 countries. Although marked differences were noted in the programs in different countries, there were commonalities in the selection processes. There was an emphasis on previous academic performance, especially in science subjects. With one exception, all schools had some form of interview, with several having moved to multiple mini-interviews in recent years. Conclusion. The majority of pharmacy schools in this survey relied on traditional selection processes. While there was increasing use of multiple mini-interviews, the authors suggest that additional new approaches may be required in light of the changing nature of the profession.

  9. Selected missense mutations impair frataxin processing in Friedreich ataxia.

    Science.gov (United States)

    Clark, Elisia; Butler, Jill S; Isaacs, Charles J; Napierala, Marek; Lynch, David R

    2017-08-01

    Frataxin (FXN) is a highly conserved mitochondrial protein. Reduced FXN levels cause Friedreich ataxia, a recessive neurodegenerative disease. Typical patients carry GAA repeat expansions on both alleles, while a subgroup of patients carry a missense mutation on one allele and a GAA repeat expansion on the other. Here, we report that selected disease-related FXN missense mutations impair FXN localization, interaction with mitochondria processing peptidase, and processing. Immunocytochemical studies and subcellular fractionation were performed to study FXN import into the mitochondria and examine the mechanism by which mutations impair FXN processing. Coimmunoprecipitation was performed to study the interaction between FXN and mitochondrial processing peptidase. A proteasome inhibitor was used to model traditional therapeutic strategies. In addition, clinical profiles of subjects with and without point mutations were compared in a large natural history study. FXN I 154F and FXN G 130V missense mutations decrease FXN 81-210 levels compared with FXN WT , FXN R 165C , and FXN W 155R , but do not block its association with mitochondria. FXN I 154F and FXN G 130V also impair FXN maturation and enhance the binding between FXN 42-210 and mitochondria processing peptidase. Furthermore, blocking proteosomal degradation does not increase FXN 81-210 levels. Additionally, impaired FXN processing also occurs in fibroblasts from patients with FXN G 130V . Finally, clinical data from patients with FXN G 130V and FXN I 154F mutations demonstrates a lower severity compared with other individuals with Friedreich ataxia. These data suggest that the effects on processing associated with FXN G 130V and FXN I 154F mutations lead to higher levels of partially processed FXN, which may contribute to the milder clinical phenotypes in these patients.

  10. Analysis of the resolution processes of three modeling tasks

    Directory of Open Access Journals (Sweden)

    Cèsar Gallart Palau

    2017-08-01

    Full Text Available In this paper we present a comparative analysis of the resolution process of three modeling tasks performed by secondary education students (13-14 years, designed from three different points of view: The Modelling-eliciting Activities, the LEMA project, and the Realistic Mathematical Problems. The purpose of this analysis is to obtain a methodological characterization of them in order to provide to secondary education teachers a proper selection and sequencing of tasks for their implementation in the classroom.

  11. The Process of Marketing Segmentation Strategy Selection

    OpenAIRE

    Ionel Dumitru

    2007-01-01

    The process of marketing segmentation strategy selection represents the essence of strategical marketing. We present hereinafter the main forms of the marketing statategy segmentation: undifferentiated marketing, differentiated marketing, concentrated marketing and personalized marketing. In practice, the companies use a mix of these marketing segmentation methods in order to maximize the proffit and to satisfy the consumers’ needs.

  12. Robust inference in sample selection models

    KAUST Repository

    Zhelonkin, Mikhail; Genton, Marc G.; Ronchetti, Elvezio

    2015-01-01

    The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman's two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

  13. Robust inference in sample selection models

    KAUST Repository

    Zhelonkin, Mikhail

    2015-11-20

    The problem of non-random sample selectivity often occurs in practice in many fields. The classical estimators introduced by Heckman are the backbone of the standard statistical analysis of these models. However, these estimators are very sensitive to small deviations from the distributional assumptions which are often not satisfied in practice. We develop a general framework to study the robustness properties of estimators and tests in sample selection models. We derive the influence function and the change-of-variance function of Heckman\\'s two-stage estimator, and we demonstrate the non-robustness of this estimator and its estimated variance to small deviations from the model assumed. We propose a procedure for robustifying the estimator, prove its asymptotic normality and give its asymptotic variance. Both cases with and without an exclusion restriction are covered. This allows us to construct a simple robust alternative to the sample selection bias test. We illustrate the use of our new methodology in an analysis of ambulatory expenditures and we compare the performance of the classical and robust methods in a Monte Carlo simulation study.

  14. 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...

  15. Adverse selection model regarding tobacco consumption

    Directory of Open Access Journals (Sweden)

    Dumitru MARIN

    2006-01-01

    Full Text Available The impact of introducing a tax on tobacco consumption can be studied trough an adverse selection model. The objective of the model presented in the following is to characterize the optimal contractual relationship between the governmental authorities and the two type employees: smokers and non-smokers, taking into account that the consumers’ decision to smoke or not represents an element of risk and uncertainty. Two scenarios are run using the General Algebraic Modeling Systems software: one without taxes set on tobacco consumption and another one with taxes set on tobacco consumption, based on an adverse selection model described previously. The results of the two scenarios are compared in the end of the paper: the wage earnings levels and the social welfare in case of a smoking agent and in case of a non-smoking agent.

  16. Two-step variable selection in quantile regression models

    Directory of Open Access Journals (Sweden)

    FAN Yali

    2015-06-01

    Full Text Available We propose a two-step variable selection procedure for high dimensional quantile regressions, in which the dimension of the covariates, pn is much larger than the sample size n. In the first step, we perform ℓ1 penalty, and we demonstrate that the first step penalized estimator with the LASSO penalty can reduce the model from an ultra-high dimensional to a model whose size has the same order as that of the true model, and the selected model can cover the true model. The second step excludes the remained irrelevant covariates by applying the adaptive LASSO penalty to the reduced model obtained from the first step. Under some regularity conditions, we show that our procedure enjoys the model selection consistency. We conduct a simulation study and a real data analysis to evaluate the finite sample performance of the proposed approach.

  17. Computationally efficient thermal-mechanical modelling of selective laser melting

    Science.gov (United States)

    Yang, Yabin; Ayas, Can

    2017-10-01

    The Selective laser melting (SLM) is a powder based additive manufacturing (AM) method to produce high density metal parts with complex topology. However, part distortions and accompanying residual stresses deteriorates the mechanical reliability of SLM products. Modelling of the SLM process is anticipated to be instrumental for understanding and predicting the development of residual stress field during the build process. However, SLM process modelling requires determination of the heat transients within the part being built which is coupled to a mechanical boundary value problem to calculate displacement and residual stress fields. Thermal models associated with SLM are typically complex and computationally demanding. In this paper, we present a simple semi-analytical thermal-mechanical model, developed for SLM that represents the effect of laser scanning vectors with line heat sources. The temperature field within the part being build is attained by superposition of temperature field associated with line heat sources in a semi-infinite medium and a complimentary temperature field which accounts for the actual boundary conditions. An analytical solution of a line heat source in a semi-infinite medium is first described followed by the numerical procedure used for finding the complimentary temperature field. This analytical description of the line heat sources is able to capture the steep temperature gradients in the vicinity of the laser spot which is typically tens of micrometers. In turn, semi-analytical thermal model allows for having a relatively coarse discretisation of the complimentary temperature field. The temperature history determined is used to calculate the thermal strain induced on the SLM part. Finally, a mechanical model governed by elastic-plastic constitutive rule having isotropic hardening is used to predict the residual stresses.

  18. Automated sample plan selection for OPC modeling

    Science.gov (United States)

    Casati, Nathalie; Gabrani, Maria; Viswanathan, Ramya; Bayraktar, Zikri; Jaiswal, Om; DeMaris, David; Abdo, Amr Y.; Oberschmidt, James; Krause, Andreas

    2014-03-01

    It is desired to reduce the time required to produce metrology data for calibration of Optical Proximity Correction (OPC) models and also maintain or improve the quality of the data collected with regard to how well that data represents the types of patterns that occur in real circuit designs. Previous work based on clustering in geometry and/or image parameter space has shown some benefit over strictly manual or intuitive selection, but leads to arbitrary pattern exclusion or selection which may not be the best representation of the product. Forming the pattern selection as an optimization problem, which co-optimizes a number of objective functions reflecting modelers' insight and expertise, has shown to produce models with equivalent quality to the traditional plan of record (POR) set but in a less time.

  19. A Network Analysis Model for Selecting Sustainable Technology

    Directory of Open Access Journals (Sweden)

    Sangsung Park

    2015-09-01

    Full Text Available Most companies develop technologies to improve their competitiveness in the marketplace. Typically, they then patent these technologies around the world in order to protect their intellectual property. Other companies may use patented technologies to develop new products, but must pay royalties to the patent holders or owners. Should they fail to do so, this can result in legal disputes in the form of patent infringement actions between companies. To avoid such situations, companies attempt to research and develop necessary technologies before their competitors do so. An important part of this process is analyzing existing patent documents in order to identify emerging technologies. In such analyses, extracting sustainable technology from patent data is important, because sustainable technology drives technological competition among companies and, thus, the development of new technologies. In addition, selecting sustainable technologies makes it possible to plan their R&D (research and development efficiently. In this study, we propose a network model that can be used to select the sustainable technology from patent documents, based on the centrality and degree of a social network analysis. To verify the performance of the proposed model, we carry out a case study using actual patent data from patent databases.

  20. Performance Measurement Model for the Supplier Selection Based on AHP

    Directory of Open Access Journals (Sweden)

    Fabio De Felice

    2015-10-01

    Full Text Available The performance of the supplier is a crucial factor for the success or failure of any company. Rational and effective decision making in terms of the supplier selection process can help the organization to optimize cost and quality functions. The nature of supplier selection processes is generally complex, especially when the company has a large variety of products and vendors. Over the years, several solutions and methods have emerged for addressing the supplier selection problem (SSP. Experience and studies have shown that there is no best way for evaluating and selecting a specific supplier process, but that it varies from one organization to another. The aim of this research is to demonstrate how a multiple attribute decision making approach can be effectively applied for the supplier selection process.

  1. Continuous process for selective metal extraction with an ionic liquid

    NARCIS (Netherlands)

    Parmentier, D.; Paradis, S.; Metz, S.J.; Wiedmer, S.K.; Kroon, M.C.

    2016-01-01

    This work describes for the first time a continuous process for selective metal extraction with an ionic liquid (IL) at room temperature. The hydrophobic fatty acid based IL tetraoctylphosphonium oleate ([P8888][oleate]) was specifically chosen for its low viscosity and high selectivity towards

  2. Goal selection versus process control while learning to use a brain-computer interface

    Science.gov (United States)

    Royer, Audrey S.; Rose, Minn L.; He, Bin

    2011-06-01

    A brain-computer interface (BCI) can be used to accomplish a task without requiring motor output. Two major control strategies used by BCIs during task completion are process control and goal selection. In process control, the user exerts continuous control and independently executes the given task. In goal selection, the user communicates their goal to the BCI and then receives assistance executing the task. A previous study has shown that goal selection is more accurate and faster in use. An unanswered question is, which control strategy is easier to learn? This study directly compares goal selection and process control while learning to use a sensorimotor rhythm-based BCI. Twenty young healthy human subjects were randomly assigned either to a goal selection or a process control-based paradigm for eight sessions. At the end of the study, the best user from each paradigm completed two additional sessions using all paradigms randomly mixed. The results of this study were that goal selection required a shorter training period for increased speed, accuracy, and information transfer over process control. These results held for the best subjects as well as in the general subject population. The demonstrated characteristics of goal selection make it a promising option to increase the utility of BCIs intended for both disabled and able-bodied users.

  3. Selected Topics on Systems Modeling and Natural Language Processing: Editorial Introduction to the Issue 7 of CSIMQ

    Directory of Open Access Journals (Sweden)

    Witold Andrzejewski

    2016-07-01

    Full Text Available The seventh issue of Complex Systems Informatics and Modeling Quarterly presents five papers devoted to two distinct research topics: systems modeling and natural language processing (NLP. Both of these subjects are very important in computer science. Through modeling we can simplify the studied problem by concentrating on only one aspect at a time. Moreover, a properly constructed model allows the modeler to work on higher levels of abstraction and not having to concentrate on details. Since the size and complexity of information systems grows rapidly, creating good models of such systems is crucial. The analysis of natural language is slowly becoming a widely used tool in commerce and day to day life. Opinion mining allows recommender systems to provide accurate recommendations based on user-generated reviews. Speech recognition and NLP are the basis for such widely used personal assistants as Apple’s Siri, Microsoft’s Cortana, and Google Now. While a lot of work has already been done on natural language processing, the research usually concerns widely used languages, such as English. Consequently, natural language processing in languages other than English is very relevant subject and is addressed in this issue.

  4. Understanding the selection processes of public research projects

    NARCIS (Netherlands)

    Materia, V.C.; Pascucci, S.; Kolympiris, C.

    2015-01-01

    This paper analyses factors that affect the funding of agricultural research projects by regional governments and other regional public authorities. We study the selection process of agricultural research projects funded by the emilia Romagna regional government in Italy, which follows funding

  5. Development of Solar Drying Model for Selected Cambodian Fish Species

    Science.gov (United States)

    Hubackova, Anna; Kucerova, Iva; Chrun, Rithy; Chaloupkova, Petra; Banout, Jan

    2014-01-01

    A solar drying was investigated as one of perspective techniques for fish processing in Cambodia. The solar drying was compared to conventional drying in electric oven. Five typical Cambodian fish species were selected for this study. Mean solar drying temperature and drying air relative humidity were 55.6°C and 19.9%, respectively. The overall solar dryer efficiency was 12.37%, which is typical for natural convection solar dryers. An average evaporative capacity of solar dryer was 0.049 kg·h−1. Based on coefficient of determination (R 2), chi-square (χ 2) test, and root-mean-square error (RMSE), the most suitable models describing natural convection solar drying kinetics were Logarithmic model, Diffusion approximate model, and Two-term model for climbing perch and Nile tilapia, swamp eel and walking catfish and Channa fish, respectively. In case of electric oven drying, the Modified Page 1 model shows the best results for all investigated fish species except Channa fish where the two-term model is the best one. Sensory evaluation shows that most preferable fish is climbing perch, followed by Nile tilapia and walking catfish. This study brings new knowledge about drying kinetics of fresh water fish species in Cambodia and confirms the solar drying as acceptable technology for fish processing. PMID:25250381

  6. Process for Selecting System Level Assessments for Human System Technologies

    Science.gov (United States)

    Watts, James; Park, John

    2006-01-01

    The integration of many life support systems necessary to construct a stable habitat is difficult. The correct identification of the appropriate technologies and corresponding interfaces is an exhaustive process. Once technologies are selected secondary issues such as mechanical and electrical interfaces must be addressed. The required analytical and testing work must be approached in a piecewise fashion to achieve timely results. A repeatable process has been developed to identify and prioritize system level assessments and testing needs. This Assessment Selection Process has been defined to assess cross cutting integration issues on topics at the system or component levels. Assessments are used to identify risks, encourage future actions to mitigate risks, or spur further studies.

  7. High-dimensional model estimation and model selection

    CERN Multimedia

    CERN. Geneva

    2015-01-01

    I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

  8. The influence of executive capacity on selective attention and subsequent processing

    Directory of Open Access Journals (Sweden)

    Kirk R. Daffner

    2012-06-01

    Full Text Available Recent investigations that suggest selective attention is dependent on top-down control mechanisms lead to the expectation that individuals with high executive capacity would exhibit more robust neural indices of selective attention. This prediction was tested by using event-related potentials (ERPs to examine differences in markers of information processing across 25 subjects divided into 2 groups based on high vs. average executive capacity, as defined by neuropsychological test scores. Subjects performed an experimental task requiring selective attention to a specified color. In contrast to expectation, individuals with high and average executive capacity did not differ in the size of ERP indices of selective attention: the anterior Selection Positivity (SP and posterior Selection Negativity (SN. However, there were substantial differences between groups in markers of subsequent processing, including the anterior N2 (a measure of attentional control and the P3a (an index of the orienting of attention. Executive capacity predicted speed of processing at both early and late attentional stages. Individuals with lower executive capacity exhibited prolonged SN, P3a, and P3b latencies. However, the delays in carrying out selective attention operations did not account for subsequent delays in decision making, or explain excessive orienting and reduced attentional control mechanisms in response to stimuli that should have been ignored. SN latency, P3 latency, and the size of the anterior N2 made independent contributions to the variance of executive capacity. In summary, our findings suggest that current views regarding the relationship between top-down control mechanisms and selective attention may need refinement.

  9. Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

    Science.gov (United States)

    Yan, Wei; Chang, Yuwen

    2016-12-01

    Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

  10. Business process model repositories : efficient process retrieval

    NARCIS (Netherlands)

    Yan, Z.

    2012-01-01

    As organizations increasingly work in process-oriented manner, the number of business process models that they develop and have to maintain increases. As a consequence, it has become common for organizations to have collections of hundreds or even thousands of business process models. When a

  11. BioModels Database: a repository of mathematical models of biological processes.

    Science.gov (United States)

    Chelliah, Vijayalakshmi; Laibe, Camille; Le Novère, Nicolas

    2013-01-01

    BioModels Database is a public online resource that allows storing and sharing of published, peer-reviewed quantitative, dynamic models of biological processes. The model components and behaviour are thoroughly checked to correspond the original publication and manually curated to ensure reliability. Furthermore, the model elements are annotated with terms from controlled vocabularies as well as linked to relevant external data resources. This greatly helps in model interpretation and reuse. Models are stored in SBML format, accepted in SBML and CellML formats, and are available for download in various other common formats such as BioPAX, Octave, SciLab, VCML, XPP and PDF, in addition to SBML. The reaction network diagram of the models is also available in several formats. BioModels Database features a search engine, which provides simple and more advanced searches. Features such as online simulation and creation of smaller models (submodels) from the selected model elements of a larger one are provided. BioModels Database can be accessed both via a web interface and programmatically via web services. New models are available in BioModels Database at regular releases, about every 4 months.

  12. Continuous Self-Selection Processes in Teacher Education: The Way for Survival.

    Science.gov (United States)

    Zak, Itai

    1981-01-01

    Three selection phases were found in a study investigating the selection process of students into the teaching profession: (1) self selection by the potential teacher; (2) admission to the teacher-training program; and (3) election to undergo the course of instruction. Results suggest that personality traits are more important than cognitive…

  13. Laser Process for Selective Emitter Silicon Solar Cells

    Directory of Open Access Journals (Sweden)

    G. Poulain

    2012-01-01

    Full Text Available Selective emitter solar cells can provide a significant increase in conversion efficiency. However current approaches need many technological steps and alignment procedures. This paper reports on a preliminary attempt to reduce the number of processing steps and therefore the cost of selective emitter cells. In the developed procedure, a phosphorous glass covered with silicon nitride acts as the doping source. A laser is used to open locally the antireflection coating and at the same time achieve local phosphorus diffusion. In this process the standard chemical etching of the phosphorous glass is avoided. Sheet resistance variation from 100 Ω/sq to 40 Ω/sq is demonstrated with a nanosecond UV laser. Numerical simulation of the laser-matter interaction is discussed to understand the dopant diffusion efficiency. Preliminary solar cells results show a 0.5% improvement compared with a homogeneous emitter structure.

  14. A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data

    Energy Technology Data Exchange (ETDEWEB)

    Louit, D.M. [Komatsu Chile, Av. Americo Vespucio 0631, Quilicura, Santiago (Chile)], E-mail: rpascual@ing.puc.cl; Pascual, R. [Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna Mackenna 4860, Santiago (Chile); Jardine, A.K.S. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King' s College Road, Toronto, Ont., M5S 3G8 (Canada)

    2009-10-15

    Many times, reliability studies rely on false premises such as independent and identically distributed time between failures assumption (renewal process). This can lead to erroneous model selection for the time to failure of a particular component or system, which can in turn lead to wrong conclusions and decisions. A strong statistical focus, a lack of a systematic approach and sometimes inadequate theoretical background seem to have made it difficult for maintenance analysts to adopt the necessary stage of data testing before the selection of a suitable model. In this paper, a framework for model selection to represent the failure process for a component or system is presented, based on a review of available trend tests. The paper focuses only on single-time-variable models and is primarily directed to analysts responsible for reliability analyses in an industrial maintenance environment. The model selection framework is directed towards the discrimination between the use of statistical distributions to represent the time to failure ('renewal approach'); and the use of stochastic point processes ('repairable systems approach'), when there may be the presence of system ageing or reliability growth. An illustrative example based on failure data from a fleet of backhoes is included.

  15. Temporally selective processing of communication signals by auditory midbrain neurons

    DEFF Research Database (Denmark)

    Elliott, Taffeta M; Christensen-Dalsgaard, Jakob; Kelley, Darcy B

    2011-01-01

    click rates ranged from 4 to 50 Hz, the rate at which the clicks begin to overlap. Frequency selectivity and temporal processing were characterized using response-intensity curves, temporal-discharge patterns, and autocorrelations of reduplicated responses to click trains. Characteristic frequencies...... of the rate of clicks in calls. The majority of neurons (85%) were selective for click rates, and this selectivity remained unchanged over sound levels 10 to 20 dB above threshold. Selective neurons give phasic, tonic, or adapting responses to tone bursts and click trains. Some algorithms that could compute...

  16. Point, surface and volumetric heat sources in the thermal modelling of selective laser melting

    Science.gov (United States)

    Yang, Yabin; Ayas, Can

    2017-10-01

    Selective laser melting (SLM) is a powder based additive manufacturing technique suitable for producing high precision metal parts. However, distortions and residual stresses within products arise during SLM because of the high temperature gradients created by the laser heating. Residual stresses limit the load resistance of the product and may even lead to fracture during the built process. It is therefore of paramount importance to predict the level of part distortion and residual stress as a function of SLM process parameters which requires a reliable thermal modelling of the SLM process. Consequently, a key question arises which is how to describe the laser source appropriately. Reasonable simplification of the laser representation is crucial for the computational efficiency of the thermal model of the SLM process. In this paper, first a semi-analytical thermal modelling approach is described. Subsequently, the laser heating is modelled using point, surface and volumetric sources, in order to compare the influence of different laser source geometries on the thermal history prediction of the thermal model. The present work provides guidelines on appropriate representation of the laser source in the thermal modelling of the SLM process.

  17. A decision modeling for phasor measurement unit location selection in smart grid systems

    Science.gov (United States)

    Lee, Seung Yup

    As a key technology for enhancing the smart grid system, Phasor Measurement Unit (PMU) provides synchronized phasor measurements of voltages and currents of wide-area electric power grid. With various benefits from its application, one of the critical issues in utilizing PMUs is the optimal site selection of units. The main aim of this research is to develop a decision support system, which can be used in resource allocation task for smart grid system analysis. As an effort to suggest a robust decision model and standardize the decision modeling process, a harmonized modeling framework, which considers operational circumstances of component, is proposed in connection with a deterministic approach utilizing integer programming. With the results obtained from the optimal PMU placement problem, the advantages and potential that the harmonized modeling process possesses are assessed and discussed.

  18. Multiple High-Fidelity Modeling Tools for Metal Additive Manufacturing Process Development, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Despite the rapid commercialization of additive manufacturing technology such as selective laser melting, SLM, there are gaps in process modeling and material...

  19. Multiple High-Fidelity Modeling Tools for Metal Additive Manufacturing Process Development, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Despite the rapid commercialization of additive manufacturing technology such as selective laser melting, SLM, there are gaps in process modeling and material...

  20. Modeling Aspects of Activated Sludge Processes Part l l: Mathematical Process Modeling and Biokinetics of Activated Sludge Processes

    Energy Technology Data Exchange (ETDEWEB)

    AbdElHaleem, H S [Cairo Univ.-CivlI Eng. Dept., Giza (Egypt); EI-Ahwany, A H [CairoUlmrsity- Faculty ofEngincering - Chemical Engineering Department, Giza (Egypt); Ibrahim, H I [Helwan University- Faculty of Engineering - Biomedical Engineering Department, Helwan (Egypt); Ibrahim, G [Menofia University- Faculty of Engineering Sbebin EI Kom- Basic Eng. Sc. Dept., Menofia (Egypt)

    2004-07-01

    Mathematical process modeling and biokinetics of activated sludge process were reviewed considering different types of models. It has been evaluated the task group models of ASMI. and 2, and 3 versioned by Henze et al considering the conditions of each model and the different processes of which every model consists. It is revealed that ASMI contains some defects avoided in ASM3. Relied on homogeneity, Models can be classified into homogenous models characterized by taking the activated sludge process as one phase. In this type of models, the internal mass transfer inside the floes was neglected.. Hence, the kinetic parameter produces can be considered inaccurate. The other type of models is the heterogeneous model This type considers the mass transfer operations in addition to the biochemical reaction processes; hence, the resulted kinetic parameters can be considered more accurate than that of homogenous type.

  1. Modeling Aspects of Activated Sludge Processes Part l l: Mathematical Process Modeling and Biokinetics of Activated Sludge Processes

    International Nuclear Information System (INIS)

    AbdElHaleem, H.S.; EI-Ahwany, A. H.; Ibrahim, H.I.; Ibrahim, G.

    2004-01-01

    Mathematical process modeling and biokinetics of activated sludge process were reviewed considering different types of models. It has been evaluated the task group models of ASMI. and 2, and 3 versioned by Henze et al considering the conditions of each model and the different processes of which every model consists. It is revealed that ASMI contains some defects avoided in ASM3. Relied on homogeneity, Models can be classified into homogenous models characterized by taking the activated sludge process as one phase. In this type of models, the internal mass transfer inside the floes was neglected.. Hence, the kinetic parameter produces can be considered inaccurate. The other type of models is the heterogeneous model This type considers the mass transfer operations in addition to the biochemical reaction processes; hence, the resulted kinetic parameters can be considered more accurate than that of homogenous type

  2. A Quality Function Deployment-Based Model for Cutting Fluid Selection

    Directory of Open Access Journals (Sweden)

    Kanika Prasad

    2016-01-01

    Full Text Available Cutting fluid is applied for numerous reasons while machining a workpiece, like increasing tool life, minimizing workpiece thermal deformation, enhancing surface finish, flushing away chips from cutting surface, and so on. Hence, choosing a proper cutting fluid for a specific machining application becomes important for enhanced efficiency and effectiveness of a manufacturing process. Cutting fluid selection is a complex procedure as the decision depends on many complicated interactions, including work material’s machinability, rigorousness of operation, cutting tool material, metallurgical, chemical, and human compatibility, reliability and stability of fluid, and cost. In this paper, a decision making model is developed based on quality function deployment technique with a view to respond to the complex character of cutting fluid selection problem and facilitate judicious selection of cutting fluid from a comprehensive list of available alternatives. In the first example, HD-CUTSOL is recognized as the most suitable cutting fluid for drilling holes in titanium alloy with tungsten carbide tool and in the second example, for performing honing operation on stainless steel alloy with cubic boron nitride tool, CF5 emerges out as the best honing fluid. Implementation of this model would result in cost reduction through decreased manpower requirement, enhanced workforce efficiency, and efficient information exploitation.

  3. Process correlation analysis model for process improvement identification.

    Science.gov (United States)

    Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

    2014-01-01

    Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

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

    DEFF Research Database (Denmark)

    Martini, Markus; Pinggera, Jakob; Neurauter, Manuel

    2016-01-01

    of reconciliation phases was positively related to PM quality in experienced modellers. Our research reveals central cognitive mechanisms in process modelling and has potential practical implications for the development of modelling software and teaching the craft of process modelling....... the role of cognitive processes as well as modelling processes in creating a PM in experienced and inexperienced modellers. Specifically, two working memory (WM) functions (holding and processing of information and relational integration) and three process of process modelling phases (comprehension...

  5. Product and Process Modelling

    DEFF Research Database (Denmark)

    Cameron, Ian T.; Gani, Rafiqul

    . These approaches are put into the context of life cycle modelling, where multiscale and multiform modelling is increasingly prevalent in the 21st century. The book commences with a discussion of modern product and process modelling theory and practice followed by a series of case studies drawn from a variety......This book covers the area of product and process modelling via a case study approach. It addresses a wide range of modelling applications with emphasis on modelling methodology and the subsequent in-depth analysis of mathematical models to gain insight via structural aspects of the models...... to biotechnology applications, food, polymer and human health application areas. The book highlights to important nature of modern product and process modelling in the decision making processes across the life cycle. As such it provides an important resource for students, researchers and industrial practitioners....

  6. Melody Track Selection Using Discriminative Language Model

    Science.gov (United States)

    Wu, Xiao; Li, Ming; Suo, Hongbin; Yan, Yonghong

    In this letter we focus on the task of selecting the melody track from a polyphonic MIDI file. Based on the intuition that music and language are similar in many aspects, we solve the selection problem by introducing an n-gram language model to learn the melody co-occurrence patterns in a statistical manner and determine the melodic degree of a given MIDI track. Furthermore, we propose the idea of using background model and posterior probability criteria to make modeling more discriminative. In the evaluation, the achieved 81.6% correct rate indicates the feasibility of our approach.

  7. Model selection for Gaussian kernel PCA denoising

    DEFF Research Database (Denmark)

    Jørgensen, Kasper Winther; Hansen, Lars Kai

    2012-01-01

    We propose kernel Parallel Analysis (kPA) for automatic kernel scale and model order selection in Gaussian kernel PCA. Parallel Analysis [1] is based on a permutation test for covariance and has previously been applied for model order selection in linear PCA, we here augment the procedure to also...... tune the Gaussian kernel scale of radial basis function based kernel PCA.We evaluate kPA for denoising of simulated data and the US Postal data set of handwritten digits. We find that kPA outperforms other heuristics to choose the model order and kernel scale in terms of signal-to-noise ratio (SNR...

  8. PRESEMO - a predictive model of codend selectivity - a tool for fishery managers

    DEFF Research Database (Denmark)

    O'Neill, F.G.; Herrmann, Bent

    2007-01-01

    parameters are expressed in terms of the gear design parameters and in terms of both catch size and gear design parameters. The potential use of these results in a management context and for the development of more selective gears is highlighted by plotting iso-/(50) and iso-sr curves used to identify gear...... design parameters that give equal estimates of the 50% retention length and the selection range, respectively. It is emphasized that this approach can be extended to consider the influence of other design parameters and, if sufficient relevant quantitative information exists, biological and behavioural...... parameters. As such, the model presented here will provide a better understanding of the selection process, permit a more targeted approach to codend selectivity experiments, and assist fishery managers to assess the impact of proposed technical measures that are introduced to reduce the catch of undersized...

  9. Selective laser melting of Ni-rich NiTi: selection of process parameters and the superelastic response

    Science.gov (United States)

    Shayesteh Moghaddam, Narges; Saedi, Soheil; Amerinatanzi, Amirhesam; Saghaian, Ehsan; Jahadakbar, Ahmadreza; Karaca, Haluk; Elahinia, Mohammad

    2018-03-01

    Material and mechanical properties of NiTi shape memory alloys strongly depend on the fabrication process parameters and the resulting microstructure. In selective laser melting, the combination of parameters such as laser power, scanning speed, and hatch spacing determine the microstructural defects, grain size and texture. Therefore, processing parameters can be adjusted to tailor the microstructure and mechanical response of the alloy. In this work, NiTi samples were fabricated using Ni50.8Ti (at.%) powder via SLM PXM by Phenix/3D Systems and the effects of processing parameters were systematically studied. The relationship between the processing parameters and superelastic properties were investigated thoroughly. It will be shown that energy density is not the only parameter that governs the material response. It will be shown that hatch spacing is the dominant factor to tailor the superelastic response. It will be revealed that with the selection of right process parameters, perfect superelasticity with recoverable strains of up to 5.6% can be observed in the as-fabricated condition.

  10. Explicit attention interferes with selective emotion processing in human extrastriate cortex

    Directory of Open Access Journals (Sweden)

    Junghöfer Markus

    2007-02-01

    Full Text Available Abstract Background Brain imaging and event-related potential studies provide strong evidence that emotional stimuli guide selective attention in visual processing. A reflection of the emotional attention capture is the increased Early Posterior Negativity (EPN for pleasant and unpleasant compared to neutral images (~150–300 ms poststimulus. The present study explored whether this early emotion discrimination reflects an automatic phenomenon or is subject to interference by competing processing demands. Thus, emotional processing was assessed while participants performed a concurrent feature-based attention task varying in processing demands. Results Participants successfully performed the primary visual attention task as revealed by behavioral performance and selected event-related potential components (Selection Negativity and P3b. Replicating previous results, emotional modulation of the EPN was observed in a task condition with low processing demands. In contrast, pleasant and unpleasant pictures failed to elicit increased EPN amplitudes compared to neutral images in more difficult explicit attention task conditions. Further analyses determined that even the processing of pleasant and unpleasant pictures high in emotional arousal is subject to interference in experimental conditions with high task demand. Taken together, performing demanding feature-based counting tasks interfered with differential emotion processing indexed by the EPN. Conclusion The present findings demonstrate that taxing processing resources by a competing primary visual attention task markedly attenuated the early discrimination of emotional from neutral picture contents. Thus, these results provide further empirical support for an interference account of the emotion-attention interaction under conditions of competition. Previous studies revealed the interference of selective emotion processing when attentional resources were directed to locations of explicitly task

  11. Explicit attention interferes with selective emotion processing in human extrastriate cortex.

    Science.gov (United States)

    Schupp, Harald T; Stockburger, Jessica; Bublatzky, Florian; Junghöfer, Markus; Weike, Almut I; Hamm, Alfons O

    2007-02-22

    Brain imaging and event-related potential studies provide strong evidence that emotional stimuli guide selective attention in visual processing. A reflection of the emotional attention capture is the increased Early Posterior Negativity (EPN) for pleasant and unpleasant compared to neutral images (approximately 150-300 ms poststimulus). The present study explored whether this early emotion discrimination reflects an automatic phenomenon or is subject to interference by competing processing demands. Thus, emotional processing was assessed while participants performed a concurrent feature-based attention task varying in processing demands. Participants successfully performed the primary visual attention task as revealed by behavioral performance and selected event-related potential components (Selection Negativity and P3b). Replicating previous results, emotional modulation of the EPN was observed in a task condition with low processing demands. In contrast, pleasant and unpleasant pictures failed to elicit increased EPN amplitudes compared to neutral images in more difficult explicit attention task conditions. Further analyses determined that even the processing of pleasant and unpleasant pictures high in emotional arousal is subject to interference in experimental conditions with high task demand. Taken together, performing demanding feature-based counting tasks interfered with differential emotion processing indexed by the EPN. The present findings demonstrate that taxing processing resources by a competing primary visual attention task markedly attenuated the early discrimination of emotional from neutral picture contents. Thus, these results provide further empirical support for an interference account of the emotion-attention interaction under conditions of competition. Previous studies revealed the interference of selective emotion processing when attentional resources were directed to locations of explicitly task-relevant stimuli. The present data suggest

  12. A novel adjuvant to the resident selection process: the hartman value profile.

    Science.gov (United States)

    Cone, Jeffrey D; Byrum, C Stephen; Payne, Wyatt G; Smith, David J

    2012-01-01

    The goal of resident selection is twofold: (1) select candidates who will be successful residents and eventually successful practitioners and (2) avoid selecting candidates who will be unsuccessful residents and/or eventually unsuccessful practitioners. Traditional tools used to select residents have well-known limitations. The Hartman Value Profile (HVP) is a proven adjuvant tool to predicting future performance in candidates for advanced positions in the corporate setting. No literature exists to indicate use of the HVP for resident selection. The HVP evaluates the structure and the dynamics of an individual value system. Given the potential impact, we implemented its use beginning in 2007 as an adjuvant tool to the traditional selection process. Experience gained from incorporating the HVP into the residency selection process suggests that it may add objectivity and refinement in predicting resident performance. Further evaluation is warranted with longer follow-up times.

  13. Description of processes for the immobilization of selected transuranic wastes

    International Nuclear Information System (INIS)

    Timmerman, C.L.

    1980-12-01

    Processed sludge and incinerator-ash wastes contaminated with transuranic (TRU) elements may require immobilization to prevent the release of these elements to the environment. As part of the TRU Waste Immobilization Program sponsored by the Department of Energy (DOE), the Pacific Northwest Laboratory is developing applicable waste-form and processing technology that may meet this need. This report defines and describes processes that are capable of immobilizing a selected TRU waste-stream consisting of a blend of three parts process sludge and one part incinerator ash. These selected waste streams are based on the compositions and generation rates of the waste processing and incineration facility at the Rocky Flats Plant. The specific waste forms that could be produced by the described processes include: in-can melted borosilicate-glass monolith; joule-heated melter borosilicate-glass monolith or marble; joule-heated melter aluminosilicate-glass monolith or marble; joule-heated melter basaltic-glass monolith or marble; joule-heated melter glass-ceramic monolith; cast-cement monolith; pressed-cement pellet; and cold-pressed sintered-ceramic pellet

  14. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

    Science.gov (United States)

    Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

    2017-07-01

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

  15. On selection of optimal stochastic model for accelerated life testing

    International Nuclear Information System (INIS)

    Volf, P.; Timková, J.

    2014-01-01

    This paper deals with the problem of proper lifetime model selection in the context of statistical reliability analysis. Namely, we consider regression models describing the dependence of failure intensities on a covariate, for instance, a stressor. Testing the model fit is standardly based on the so-called martingale residuals. Their analysis has already been studied by many authors. Nevertheless, the Bayes approach to the problem, in spite of its advantages, is just developing. We shall present the Bayes procedure of estimation in several semi-parametric regression models of failure intensity. Then, our main concern is the Bayes construction of residual processes and goodness-of-fit tests based on them. The method is illustrated with both artificial and real-data examples. - Highlights: • Statistical survival and reliability analysis and Bayes approach. • Bayes semi-parametric regression modeling in Cox's and AFT models. • Bayes version of martingale residuals and goodness-of-fit test

  16. EQUAL EMPLOYMENT OPPORTUNITIES IN THE RECRUITMENT AND SELECTION PROCESS OF HUMAN RESOURCES

    Directory of Open Access Journals (Sweden)

    Aleksandra Stoilkovska

    2015-12-01

    Full Text Available The aim of this article is to examine the problem of the concept of equal employment opportunities in the HR recruitment and selection process. Due to the fact that in these processes, both the HR managers and the applicants are involved, this research is conducted separately among them. Thus, it will be determined if both sides share the same opinion with respect to the existence of this concept in the mentioned processes. Providing equal employment opportunities is crucial for any company and represents a key for selecting the real employees. Therefore, the research includes the existence of prejudices in the recruitment and selection process such as discrimination based on national and social origin, gender and sexual orientation, age, political affiliation etc. As an essential part of this concept, the legislation in the Republic of Macedonia and its impact in the process of generating equal opportunities will be considered.

  17. Process-driven selection of information systems for healthcare

    Science.gov (United States)

    Mills, Stephen F.; Yeh, Raymond T.; Giroir, Brett P.; Tanik, Murat M.

    1995-05-01

    Integration of networking and data management technologies such as PACS, RIS and HIS into a healthcare enterprise in a clinically acceptable manner is a difficult problem. Data within such a facility are generally managed via a combination of manual hardcopy systems and proprietary, special-purpose data processing systems. Process modeling techniques have been successfully applied to engineering and manufacturing enterprises, but have not generally been applied to service-based enterprises such as healthcare facilities. The use of process modeling techniques can provide guidance for the placement, configuration and usage of PACS and other informatics technologies within the healthcare enterprise, and thus improve the quality of healthcare. Initial process modeling activities conducted within the Pediatric ICU at Children's Medical Center in Dallas, Texas are described. The ongoing development of a full enterprise- level model for the Pediatric ICU is also described.

  18. Automation of Endmember Pixel Selection in SEBAL/METRIC Model

    Science.gov (United States)

    Bhattarai, N.; Quackenbush, L. J.; Im, J.; Shaw, S. B.

    2015-12-01

    The commonly applied surface energy balance for land (SEBAL) and its variant, mapping evapotranspiration (ET) at high resolution with internalized calibration (METRIC) models require manual selection of endmember (i.e. hot and cold) pixels to calibrate sensible heat flux. Current approaches for automating this process are based on statistical methods and do not appear to be robust under varying climate conditions and seasons. In this paper, we introduce a new approach based on simple machine learning tools and search algorithms that provides an automatic and time efficient way of identifying endmember pixels for use in these models. The fully automated models were applied on over 100 cloud-free Landsat images with each image covering several eddy covariance flux sites in Florida and Oklahoma. Observed land surface temperatures at automatically identified hot and cold pixels were within 0.5% of those from pixels manually identified by an experienced operator (coefficient of determination, R2, ≥ 0.92, Nash-Sutcliffe efficiency, NSE, ≥ 0.92, and root mean squared error, RMSE, ≤ 1.67 K). Daily ET estimates derived from the automated SEBAL and METRIC models were in good agreement with their manual counterparts (e.g., NSE ≥ 0.91 and RMSE ≤ 0.35 mm day-1). Automated and manual pixel selection resulted in similar estimates of observed ET across all sites. The proposed approach should reduce time demands for applying SEBAL/METRIC models and allow for their more widespread and frequent use. This automation can also reduce potential bias that could be introduced by an inexperienced operator and extend the domain of the models to new users.

  19. Aplication of AHP method in partner's selection process for supply chain development

    OpenAIRE

    Barac Nada; Anđelković Aleksandra

    2012-01-01

    The process of developing a supply chain is long and complex. with many restrictions and obstacles that accompany it. In this paper the authors focus on the first stage in developing the supply chain and the selection process and selection of partners. This phase of the development significantly affect the competitive position of the supply chain and create value for the consumer. Selected partners or 'links' of the supply chain influence the future performance of the chain which points to th...

  20. The cost of ethanol production from lignocellulosic biomass -- A comparison of selected alternative processes. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Grethlein, H.E.; Dill, T.

    1993-04-30

    The purpose of this report is to compare the cost of selected alternative processes for the conversion of lignocellulosic biomass to ethanol. In turn, this information will be used by the ARS/USDA to guide the management of research and development programs in biomass conversion. The report will identify where the cost leverages are for the selected alternatives and what performance parameters need to be achieved to improve the economics. The process alternatives considered here are not exhaustive, but are selected on the basis of having a reasonable potential in improving the economics of producing ethanol from biomass. When other alternatives come under consideration, they should be evaluated by the same methodology used in this report to give fair comparisons of opportunities. A generic plant design is developed for an annual production of 25 million gallons of anhydrous ethanol using corn stover as the model substrate at $30/dry ton. Standard chemical engineering techniques are used to give first order estimates of the capital and operating costs. Following the format of the corn to ethanol plant, there are nine sections to the plant; feed preparation, pretreatment, hydrolysis, fermentation, distillation and dehydration, stillage evaporation, storage and denaturation, utilities, and enzyme production. There are three pretreatment alternatives considered: the AFEX process, the modified AFEX process (which is abbreviated as MAFEX), and the STAKETECH process. These all use enzymatic hydrolysis and so an enzyme production section is included in the plant. The STAKETECH is the only commercially available process among the alternative processes.

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

    Science.gov (United States)

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

    2016-05-09

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

  2. Applying the Business Process and Practice Alignment Meta-model: Daily Practices and Process Modelling

    Directory of Open Access Journals (Sweden)

    Ventura Martins Paula

    2017-03-01

    Full Text Available Background: Business Process Modelling (BPM is one of the most important phases of information system design. Business Process (BP meta-models allow capturing informational and behavioural aspects of business processes. Unfortunately, standard BP meta-modelling approaches focus just on process description, providing different BP models. It is not possible to compare and identify related daily practices in order to improve BP models. This lack of information implies that further research in BP meta-models is needed to reflect the evolution/change in BP. Considering this limitation, this paper introduces a new BP meta-model designed by Business Process and Practice Alignment Meta-model (BPPAMeta-model. Our intention is to present a meta-model that addresses features related to the alignment between daily work practices and BP descriptions. Objectives: This paper intends to present a metamodel which is going to integrate daily work information into coherent and sound process definitions. Methods/Approach: The methodology employed in the research follows a design-science approach. Results: The results of the case study are related to the application of the proposed meta-model to align the specification of a BP model with work practices models. Conclusions: This meta-model can be used within the BPPAM methodology to specify or improve business processes models based on work practice descriptions.

  3. Implementation of a thermomechanical model for the simulation of selective laser melting

    Energy Technology Data Exchange (ETDEWEB)

    Hodge, N. E. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ferencz, R. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Solberg, J. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-07-01

    Selective laser melting (SLM) is an additive manufacturing process in which multiple, successive layers of metal powders are heated via laser in order to build a part. Modeling of SLM requires consideration of both heat transfer and solid mechanics. The present work describes continuum modeling of SLM as envisioned for eventual support of part-scale modeling of this fabrication process to determine end-state information such as residual stresses and distortion. The determination of the evolving temperatures is dependent on the material, the state of the material (powder or solid), the specified heating, and the configuration. Similarly, the current configuration is dependent on the temperatures, the powder-solid state, and the constitutive models. A multi-physics numerical formulation is required to solve such problems. This article describes the problem formulation, numerical method, and constitutive parameters necessary to solve such a problem. Additionally, various verification and example problems are simulated in the parallel, multi-physics finite element code Diablo, and the results presented herein.

  4. Development of Solar Drying Model for Selected Cambodian Fish Species

    Directory of Open Access Journals (Sweden)

    Anna Hubackova

    2014-01-01

    Full Text Available A solar drying was investigated as one of perspective techniques for fish processing in Cambodia. The solar drying was compared to conventional drying in electric oven. Five typical Cambodian fish species were selected for this study. Mean solar drying temperature and drying air relative humidity were 55.6°C and 19.9%, respectively. The overall solar dryer efficiency was 12.37%, which is typical for natural convection solar dryers. An average evaporative capacity of solar dryer was 0.049 kg·h−1. Based on coefficient of determination (R2, chi-square (χ2 test, and root-mean-square error (RMSE, the most suitable models describing natural convection solar drying kinetics were Logarithmic model, Diffusion approximate model, and Two-term model for climbing perch and Nile tilapia, swamp eel and walking catfish and Channa fish, respectively. In case of electric oven drying, the Modified Page 1 model shows the best results for all investigated fish species except Channa fish where the two-term model is the best one. Sensory evaluation shows that most preferable fish is climbing perch, followed by Nile tilapia and walking catfish. This study brings new knowledge about drying kinetics of fresh water fish species in Cambodia and confirms the solar drying as acceptable technology for fish processing.

  5. Selecting locations for landing of various formations of helicopters using spatial modelling

    International Nuclear Information System (INIS)

    Kovarik, V; Rybansky, M

    2014-01-01

    During crisis situations such as floods, landslides, humanitarian crisis and even military clashes there are situations when it is necessary to send helicopters to the crisis areas. To facilitate the process of searching for the sites suitable for landing, it is possible to use the tools of spatial modelling. The paper describes a procedure of selecting areas potentially suitable for landing of particular formations of helicopters. It lists natural and man-made terrain features that represent the obstacles that can prevent helicopters from landing. It also states specific requirements of the NATO documents that have to be respected when selecting the areas for landing. These requirements relate to a slope of ground and an obstruction angle on approach and exit paths. Creating the knowledge base and graphical models in ERDAS IMAGINE is then described. In the first step of the procedure the areas generally suitable for landing are selected. Then the different configurations of landing points that form the landing sites are created and corresponding outputs are generated. Finally, several tactical requirements are incorporated

  6. Modelling and Development of a High Performance Milling Process with Monolithic Cutting Tools

    International Nuclear Information System (INIS)

    Ozturk, E.; Taylor, C. M.; Turner, S.; Devey, M.

    2011-01-01

    Critical aerospace components usually require difficult to machine workpiece materials like nickel based alloys. Moreover; there is a pressing need to maximize the productivity of machining operations. This need can be satisfied by selection of higher feed velocity, axial and radial depths. But there may be several problems during machining in this case. Due to high cutting speeds in high performance machining, the tool life may be unacceptably low. If magnitudes of cutting forces are high, out of tolerance static form errors may result; moreover in the extreme cases, the cutting tool may break apart. Forced vibrations may deteriorate the surface quality. Chatter vibrations may develop if the selected parameters result in instability. In this study, in order to deal with the tool life issue, several experimental cuts are made with different tool geometries, and the best combination in terms of tool life is selected. A force model is developed and the results of the force model are verified by experimental results. The force model is used in predicting the effect of process parameters on cutting forces. In order to account for the other concerns such as static form errors, forced and chatter vibrations, additional process models are currently under development.

  7. Modeling multiphase materials processes

    CERN Document Server

    Iguchi, Manabu

    2010-01-01

    ""Modeling Multiphase Materials Processes: Gas-Liquid Systems"" describes the methodology and application of physical and mathematical modeling to multi-phase flow phenomena in materials processing. The book focuses on systems involving gas-liquid interaction, the most prevalent in current metallurgical processes. The performance characteristics of these processes are largely dependent on transport phenomena. This volume covers the inherent characteristics that complicate the modeling of transport phenomena in such systems, including complex multiphase structure, intense turbulence, opacity of

  8. On selecting a prior for the precision parameter of Dirichlet process mixture models

    Science.gov (United States)

    Dorazio, R.M.

    2009-01-01

    In hierarchical mixture models the Dirichlet process is used to specify latent patterns of heterogeneity, particularly when the distribution of latent parameters is thought to be clustered (multimodal). The parameters of a Dirichlet process include a precision parameter ?? and a base probability measure G0. In problems where ?? is unknown and must be estimated, inferences about the level of clustering can be sensitive to the choice of prior assumed for ??. In this paper an approach is developed for computing a prior for the precision parameter ?? that can be used in the presence or absence of prior information about the level of clustering. This approach is illustrated in an analysis of counts of stream fishes. The results of this fully Bayesian analysis are compared with an empirical Bayes analysis of the same data and with a Bayesian analysis based on an alternative commonly used prior.

  9. Modelling a process for dimerisation of 2-methylpropene

    Energy Technology Data Exchange (ETDEWEB)

    Ouni, T.

    2005-07-01

    Isooctane can be used to replace methyl-tert-butyl ether (MTBE) as a fuel additive. Isooctane is hydrogenated from isooctene, which is produced by dimerizing 2-methylpropene. In dimerization, two 2-methylpropene molecules react on ionexchange resin catalyst to produce isooctene isomers (2,4,4-trimethyl-1-pentene, 2,4,4- trimethyl-2-pentene). Presence of 2-methyl-2-propanol (TBA) improves reaction selectivity. Trimers and tetramers are formed as side products. Water and alkenes have reaction equilibrium with corresponding alcohols. The process configuration for isooctene production is a side reactor concept, and consists of reactor part, separation part (distillation tower) and a recycle structure. Units of miniplant at Helsinki University of Technology imitates the actual units of the isooctene production line in smaller scale, providing valuable information about the process and about the behaviour of individual units, as well as about the dynamics and operability of the process. Ideology behind Miniplant is to separate thermodynamical models from hardware specific models, so that they could be used as such in other contexts, e.g. in industrial scale. In the specific case of 2-methylpropene dimerisation the key thermodynamical models are vapour-liquid and liquid-liquid equilibrium as well as reaction kinetics. Hardware specific models include distillation column with spring-shaped packings and tubular catalytic reactor with heating coil and a thermowell. Developing these models through experiments and simulations was the primary target of this work. (orig.)

  10. Selectivity of radiation-induced processes in hydrocarbons, related polymers and organized polymer systems

    International Nuclear Information System (INIS)

    Feldman, V.I.; Sukhov, F.F.; Zezin, A.A.; Orlov, A.Yu.

    1999-01-01

    Fundamental aspects of the selectivity of radiation-induced events in polymers and polymeric systems were considered: (1) The grounds of selectivity of the primary events were analyzed on the basis of the results of studies of model compounds (molecular aspect). Basic results were obtained for hydrocarbon molecules irradiated in low-temperature matrices. The effects of selective localization of the primary events on the radical formation were examined for several polymers irradiated at low and superlow temperatures (77 and 15 K). A remarkable correlation between the properties of prototype ionized molecules (radical cations) and selectivity of the primary bond rupture in the corresponding polymers were found for polyethylene, polystyrene and some other hydrocarbon polymers. The first direct indication of selective localization of primary events at conformational defects was obtained for oriented high-crystalline polyethylene irradiated at 15 K. The significance of dimeric ring association was proved for the radiation chemistry of polystyrene. Specific mechanisms of low-temperature radiation-induced degradation were also analyzed for polycarbonate and poly(alkylene terephthalates). (2) Specific features of the localization of primary radiation-induced events in microheterogeneous polymeric systems were investigated (microstructural aspect). It was found that the interphase processes played an important role in the radiation chemistry of such systems. The interphase electron migration may result in both positive and negative non-additive effects in the formation of radiolysis products. The effects of component diffusion and chemical reactions on the radiation-induced processes in microheterogeneous polymeric systems were studied with the example of polycarbonate - poly(alkylene terephthalate) blends. (3) The effects of restricted molecular motion on the development of the radiation-chemical processes in polymers were investigated (dynamic aspect). In particular, it

  11. Process and analytical studies of enhanced low severity co-processing using selective coal pretreatment

    Energy Technology Data Exchange (ETDEWEB)

    Baldwin, R.M.; Miller, R.L.

    1991-12-01

    The findings in the first phase were as follows: 1. Both reductive (non-selective) alkylation and selective oxygen alkylation brought about an increase in liquefaction reactivity for both coals. 2. Selective oxygen alkylation is more effective in enhancing the reactivity of low rank coals. In the second phase of studies, the major findings were as follows: 1. Liquefaction reactivity increases with increasing level of alkylation for both hydroliquefaction and co-processing reaction conditions. 2. the increase in reactivity found for O-alkylated Wyodak subbituminous coal is caused by chemical changes at phenolic and carboxylic functional sites. 3. O-methylation of Wyodak subbituminous coal reduced the apparent activation energy for liquefaction of this coal.

  12. Goal selection versus process control in a brain-computer interface based on sensorimotor rhythms.

    Science.gov (United States)

    Royer, Audrey S; He, Bin

    2009-02-01

    In a brain-computer interface (BCI) utilizing a process control strategy, the signal from the cortex is used to control the fine motor details normally handled by other parts of the brain. In a BCI utilizing a goal selection strategy, the signal from the cortex is used to determine the overall end goal of the user, and the BCI controls the fine motor details. A BCI based on goal selection may be an easier and more natural system than one based on process control. Although goal selection in theory may surpass process control, the two have never been directly compared, as we are reporting here. Eight young healthy human subjects participated in the present study, three trained and five naïve in BCI usage. Scalp-recorded electroencephalograms (EEG) were used to control a computer cursor during five different paradigms. The paradigms were similar in their underlying signal processing and used the same control signal. However, three were based on goal selection, and two on process control. For both the trained and naïve populations, goal selection had more hits per run, was faster, more accurate (for seven out of eight subjects) and had a higher information transfer rate than process control. Goal selection outperformed process control in every measure studied in the present investigation.

  13. DESIGNING THE PROCESS: SCALE MODELS IN THE WORK OF KAZUYO SEJIMAAND SOU FUJIMOTO.

    Directory of Open Access Journals (Sweden)

    Marta Alonso-Provencio

    2011-03-01

    Full Text Available This paper attempts to clarify a design process that is being used by Kazuyo Sejima and Sou Fujimoto based on the use of scale models. Two typical cases are studied and represented graphically in order to map the workflow. The results reveal that the mutual influence between team members, the continuous process of production and selection are closer to an "editing process" rather than the conventional linear design process. The architectural quality and character of the work produced by Sejima and Fujimoto can be seen as a consequence of the process itself. The process based on the use of scale models becomes an object of design, and its advantages and disadvantages are discussed in this article. This systematical study is expected to offer new ideas to practitioners on how to integrate scale models in the design process and how to enhance creativity and collaborative teamwork.

  14. Yakima tribal perspectives on high level selection process

    International Nuclear Information System (INIS)

    Jim, R.; Wittman, J.; Tousley, D.R.; Hovis, J.B.

    1987-01-01

    When Congress went through the arduous process of fashioning a comprehensive plan for resolution of the nation's long-standing nuclear waste problem, it explicitly recognized that past federal efforts in this area had been inadequate. Congress also recognized that the primary reasons for the failure of earlier federal efforts was failure on the part of the federal government to seriously deal with very real technical questions about the geologic adequacy of prospective repository sites, and failure to address the concerns of state, tribal, and local governments in the repository selection and development process

  15. Semantic Business Process Modeling

    OpenAIRE

    Markovic, Ivan

    2010-01-01

    This book presents a process-oriented business modeling framework based on semantic technologies. The framework consists of modeling languages, methods, and tools that allow for semantic modeling of business motivation, business policies and rules, and business processes. Quality of the proposed modeling framework is evaluated based on the modeling content of SAP Solution Composer and several real-world business scenarios.

  16. Site selection and characterization processes for deep geologic disposal of high level nuclear waste

    International Nuclear Information System (INIS)

    Costin, L.S.

    1997-10-01

    In this paper, the major elements of the site selection and characterization processes used in the US high level waste program are discussed. While much of the evolution of the site selection and characterization processes have been driven by the unique nature of the US program, these processes, which are well defined and documented, could be used as an initial basis for developing site screening, selection, and characterization programs in other countries. Thus, this paper focuses more on the process elements than the specific details of the US program

  17. Belief–logic conflict resolution in syllogistic reasoning: Inspection-time evidence for a parallel process model

    OpenAIRE

    Stupple, Edward J.N; Ball, Linden

    2008-01-01

    An experiment is reported examining dual-process models of belief bias in syllogistic reasoning using a problem complexity manipulation and an inspection-time method to monitor processing latencies for premises and conclusions. Endorsement rates indicated increased belief bias on complex problems, a finding that runs counter to the “belief-first” selective scrutiny model, but which is consistent with other theories, including “reasoning-first” and “parallel-process” models. Inspection-time da...

  18. Process for selected gas oxide removal by radiofrequency catalysts

    Science.gov (United States)

    Cha, Chang Y.

    1993-01-01

    This process to remove gas oxides from flue gas utilizes adsorption on a char bed subsequently followed by radiofrequency catalysis enhancing such removal through selected reactions. Common gas oxides include SO.sub.2 and NO.sub.x.

  19. Business Process Modeling: Perceived Benefits

    Science.gov (United States)

    Indulska, Marta; Green, Peter; Recker, Jan; Rosemann, Michael

    The process-centered design of organizations and information systems is globally seen as an appropriate response to the increased economic pressure on organizations. At the methodological core of process-centered management is process modeling. However, business process modeling in large initiatives can be a time-consuming and costly exercise, making it potentially difficult to convince executive management of its benefits. To date, and despite substantial interest and research in the area of process modeling, the understanding of the actual benefits of process modeling in academia and practice is limited. To address this gap, this paper explores the perception of benefits derived from process modeling initiatives, as reported through a global Delphi study. The study incorporates the views of three groups of stakeholders - academics, practitioners and vendors. Our findings lead to the first identification and ranking of 19 unique benefits associated with process modeling. The study in particular found that process modeling benefits vary significantly between practitioners and academics. We argue that the variations may point to a disconnect between research projects and practical demands.

  20. Materials Selection And Fabrication Practices For Food Processing Equipment Manufacturers In Uganda

    Directory of Open Access Journals (Sweden)

    John Baptist Kirabira

    2017-08-01

    Full Text Available The food processing industry is one of the fast-growing sub-sectors in Uganda. The industry which is majorly composed of medium and small scale firms depends on the locally developed food processing equipment. Due to lack of effective materials selection practices employed by the equipment manufacturers the materials normally selected for most designs are not the most appropriate ones hence compromising the quality of the equipment produced. This has not only led to poor quality food products due to contamination but could also turn out health hazardous to the consumers of the food products. This study involved the assessment of the current materials selection and fabrication procedures used by the food processing equipment manufacturers with a view of devising best practices that can be used to improve the quality of the food products processed by the locally fabricated equipment. Results of the study show that designers experience biasness and desire to minimize cost compromise the materials selection procedure. In addition to failing to choose the best material for a given application most equipment manufacturers are commonly fabricating equipment with inadequate surface finish and improper weldments. This hinders the equipments ability to meet food hygiene standards.

  1. On theoretical models of gene expression evolution with random genetic drift and natural selection.

    Directory of Open Access Journals (Sweden)

    Osamu Ogasawara

    2009-11-01

    Full Text Available The relative contributions of natural selection and random genetic drift are a major source of debate in the study of gene expression evolution, which is hypothesized to serve as a bridge from molecular to phenotypic evolution. It has been suggested that the conflict between views is caused by the lack of a definite model of the neutral hypothesis, which can describe the long-run behavior of evolutionary change in mRNA abundance. Therefore previous studies have used inadequate analogies with the neutral prediction of other phenomena, such as amino acid or nucleotide sequence evolution, as the null hypothesis of their statistical inference.In this study, we introduced two novel theoretical models, one based on neutral drift and the other assuming natural selection, by focusing on a common property of the distribution of mRNA abundance among a variety of eukaryotic cells, which reflects the result of long-term evolution. Our results demonstrated that (1 our models can reproduce two independently found phenomena simultaneously: the time development of gene expression divergence and Zipf's law of the transcriptome; (2 cytological constraints can be explicitly formulated to describe long-term evolution; (3 the model assuming that natural selection optimized relative mRNA abundance was more consistent with previously published observations than the model of optimized absolute mRNA abundances.The models introduced in this study give a formulation of evolutionary change in the mRNA abundance of each gene as a stochastic process, on the basis of previously published observations. This model provides a foundation for interpreting observed data in studies of gene expression evolution, including identifying an adequate time scale for discriminating the effect of natural selection from that of random genetic drift of selectively neutral variations.

  2. Applying a Hybrid MCDM Model for Six Sigma Project Selection

    Directory of Open Access Journals (Sweden)

    Fu-Kwun Wang

    2014-01-01

    Full Text Available Six Sigma is a project-driven methodology; the projects that provide the maximum financial benefits and other impacts to the organization must be prioritized. Project selection (PS is a type of multiple criteria decision making (MCDM problem. In this study, we present a hybrid MCDM model combining the decision-making trial and evaluation laboratory (DEMATEL technique, analytic network process (ANP, and the VIKOR method to evaluate and improve Six Sigma projects for reducing performance gaps in each criterion and dimension. We consider the film printing industry of Taiwan as an empirical case. The results show that our study not only can use the best project selection, but can also be used to analyze the gaps between existing performance values and aspiration levels for improving the gaps in each dimension and criterion based on the influential network relation map.

  3. Equifinality and process-based modelling

    Science.gov (United States)

    Khatami, S.; Peel, M. C.; Peterson, T. J.; Western, A. W.

    2017-12-01

    Equifinality is understood as one of the fundamental difficulties in the study of open complex systems, including catchment hydrology. A review of the hydrologic literature reveals that the term equifinality has been widely used, but in many cases inconsistently and without coherent recognition of the various facets of equifinality, which can lead to ambiguity but also methodological fallacies. Therefore, in this study we first characterise the term equifinality within the context of hydrological modelling by reviewing the genesis of the concept of equifinality and then presenting a theoretical framework. During past decades, equifinality has mainly been studied as a subset of aleatory (arising due to randomness) uncertainty and for the assessment of model parameter uncertainty. Although the connection between parameter uncertainty and equifinality is undeniable, we argue there is more to equifinality than just aleatory parameter uncertainty. That is, the importance of equifinality and epistemic uncertainty (arising due to lack of knowledge) and their implications is overlooked in our current practice of model evaluation. Equifinality and epistemic uncertainty in studying, modelling, and evaluating hydrologic processes are treated as if they can be simply discussed in (or often reduced to) probabilistic terms (as for aleatory uncertainty). The deficiencies of this approach to conceptual rainfall-runoff modelling are demonstrated for selected Australian catchments by examination of parameter and internal flux distributions and interactions within SIMHYD. On this basis, we present a new approach that expands equifinality concept beyond model parameters to inform epistemic uncertainty. The new approach potentially facilitates the identification and development of more physically plausible models and model evaluation schemes particularly within the multiple working hypotheses framework, and is generalisable to other fields of environmental modelling as well.

  4. Materials selection for process equipment in the Hanford waste vitrification plant

    Energy Technology Data Exchange (ETDEWEB)

    Elmore, M R; Jensen, G A

    1991-07-01

    The Hanford Waste Vitrification Plant (HWVP) is being designed to vitrify defense liquid high-level wastes and transuranic wastes stored at Hanford. The HWVP Functional Design Criteria (FDC) requires that materials used for fabrication of remote process equipment and piping in the facility be compatible with the expected waste stream compositions and process conditions. To satisfy FDC requirements, corrosion-resistant materials have been evaluated under simulated HWVP-specific conditions and recommendations have been made for HWVP applications. The materials recommendations provide to the project architect/engineer the best available corrosion rate information for the materials under the expected HWVP process conditions. Existing data and sound engineering judgement must be used and a solid technical basis must be developed to define an approach to selecting suitable construction materials for the HWVP. This report contains the strategy, approach, criteria, and technical basis developed for selecting materials of construction. Based on materials testing specific to HWVP and on related outside testing, this report recommends for constructing specific process equipment and identifies future testing needs to complete verification of the performance of the selected materials. 30 refs., 7 figs., 11 tabs.

  5. The Naïve Overfitting Index Selection (NOIS): A new method to optimize model complexity for hyperspectral data

    Science.gov (United States)

    Rocha, Alby D.; Groen, Thomas A.; Skidmore, Andrew K.; Darvishzadeh, Roshanak; Willemen, Louise

    2017-11-01

    The growing number of narrow spectral bands in hyperspectral remote sensing improves the capacity to describe and predict biological processes in ecosystems. But it also poses a challenge to fit empirical models based on such high dimensional data, which often contain correlated and noisy predictors. As sample sizes, to train and validate empirical models, seem not to be increasing at the same rate, overfitting has become a serious concern. Overly complex models lead to overfitting by capturing more than the underlying relationship, and also through fitting random noise in the data. Many regression techniques claim to overcome these problems by using different strategies to constrain complexity, such as limiting the number of terms in the model, by creating latent variables or by shrinking parameter coefficients. This paper is proposing a new method, named Naïve Overfitting Index Selection (NOIS), which makes use of artificially generated spectra, to quantify the relative model overfitting and to select an optimal model complexity supported by the data. The robustness of this new method is assessed by comparing it to a traditional model selection based on cross-validation. The optimal model complexity is determined for seven different regression techniques, such as partial least squares regression, support vector machine, artificial neural network and tree-based regressions using five hyperspectral datasets. The NOIS method selects less complex models, which present accuracies similar to the cross-validation method. The NOIS method reduces the chance of overfitting, thereby avoiding models that present accurate predictions that are only valid for the data used, and too complex to make inferences about the underlying process.

  6. Bioprocesses: Modelling needs for process evaluation and sustainability assessment

    DEFF Research Database (Denmark)

    Jiménez-Gonzaléz, Concepcion; Woodley, John

    2010-01-01

    development such that they can also be used to evaluate processes against sustainability metrics, as well as economics as an integral part of assessments. Finally, property models will also be required based on compounds not currently present in existing databases. It is clear that many new opportunities......The next generation of process engineers will face a new set of challenges, with the need to devise new bioprocesses, with high selectivity for pharmaceutical manufacture, and for lower value chemicals manufacture based on renewable feedstocks. In this paper the current and predicted future roles...... of process system engineering and life cycle inventory and assessment in the design, development and improvement of sustainable bioprocesses are explored. The existing process systems engineering software tools will prove essential to assist this work. However, the existing tools will also require further...

  7. Pareto-Optimal Model Selection via SPRINT-Race.

    Science.gov (United States)

    Zhang, Tiantian; Georgiopoulos, Michael; Anagnostopoulos, Georgios C

    2018-02-01

    In machine learning, the notion of multi-objective model selection (MOMS) refers to the problem of identifying the set of Pareto-optimal models that optimize by compromising more than one predefined objectives simultaneously. This paper introduces SPRINT-Race, the first multi-objective racing algorithm in a fixed-confidence setting, which is based on the sequential probability ratio with indifference zone test. SPRINT-Race addresses the problem of MOMS with multiple stochastic optimization objectives in the proper Pareto-optimality sense. In SPRINT-Race, a pairwise dominance or non-dominance relationship is statistically inferred via a non-parametric, ternary-decision, dual-sequential probability ratio test. The overall probability of falsely eliminating any Pareto-optimal models or mistakenly returning any clearly dominated models is strictly controlled by a sequential Holm's step-down family-wise error rate control method. As a fixed-confidence model selection algorithm, the objective of SPRINT-Race is to minimize the computational effort required to achieve a prescribed confidence level about the quality of the returned models. The performance of SPRINT-Race is first examined via an artificially constructed MOMS problem with known ground truth. Subsequently, SPRINT-Race is applied on two real-world applications: 1) hybrid recommender system design and 2) multi-criteria stock selection. The experimental results verify that SPRINT-Race is an effective and efficient tool for such MOMS problems. code of SPRINT-Race is available at https://github.com/watera427/SPRINT-Race.

  8. On the selection of significant variables in a model for the deteriorating process of facades

    Science.gov (United States)

    Serrat, C.; Gibert, V.; Casas, J. R.; Rapinski, J.

    2017-10-01

    In previous works the authors of this paper have introduced a predictive system that uses survival analysis techniques for the study of time-to-failure in the facades of a building stock. The approach is population based, in order to obtain information on the evolution of the stock across time, and to help the manager in the decision making process on global maintenance strategies. For the decision making it is crutial to determine those covariates -like materials, morphology and characteristics of the facade, orientation or environmental conditions- that play a significative role in the progression of different failures. The proposed platform also incorporates an open source GIS plugin that includes survival and test moduli that allow the investigator to model the time until a lesion taking into account the variables collected during the inspection process. The aim of this paper is double: a) to shortly introduce the predictive system, as well as the inspection and the analysis methodologies and b) to introduce and illustrate the modeling strategy for the deteriorating process of an urban front. The illustration will be focused on the city of L’Hospitalet de Llobregat (Barcelona, Spain) in which more than 14,000 facades have been inspected and analyzed.

  9. The application of the FMEA method in the selected production process of a company

    Directory of Open Access Journals (Sweden)

    Piotr Barosz

    2018-04-01

    Full Text Available The aim of this article is to show the use of the analysis of the failure causes and effects as a prevention tool in controlling the quality of a given production process in the company. The scope of the work covers an analysis of a selected process, definition of inconsistencies present in this process, and then the FMEA analysis. In the production company one should implement thinking and actions based on the so-called ‘quality loop’ – it is an interdependence model of the undertaken actions which affect the quality shaping. It is carried out from the possibility for identifying a customer’s requirements through a project, production process, up to the assessment of effective capability for meeting the defined requirements. The application of such an approach enables to take the actions improving the operation of quality management in a systemic way.

  10. Application of SELECT and SWAT models to simulate source load, fate, and transport of fecal bacteria in watersheds.

    Science.gov (United States)

    Ranatunga, T.

    2017-12-01

    Modeling of fate and transport of fecal bacteria in a watershed is a processed based approach that considers releases from manure, point sources, and septic systems. Overland transport with water and sediments, infiltration into soils, transport in the vadose zone and groundwater, die-off and growth processes, and in-stream transport are considered as the other major processes in bacteria simulation. This presentation will discuss a simulation of fecal indicator bacteria source loading and in-stream conditions of a non-tidal watershed (Cedar Bayou Watershed) in South Central Texas using two models; Spatially Explicit Load Enrichment Calculation Tool (SELECT) and Soil and Water Assessment Tool (SWAT). Furthermore, it will discuss a probable approach of bacteria source load reduction in order to meet the water quality standards in the streams. The selected watershed is listed as having levels of fecal indicator bacteria that posed a risk for contact recreation and wading by the Texas Commission of Environmental Quality (TCEQ). The SELECT modeling approach was used in estimating the bacteria source loading from land categories. Major bacteria sources considered were, failing septic systems, discharges from wastewater treatment facilities, excreta from livestock (Cattle, Horses, Sheep and Goat), excreta from Wildlife (Feral Hogs, and Deer), Pet waste (mainly from Dogs), and runoff from urban surfaces. The estimated source loads from SELECT model were input to the SWAT model, and simulate the bacteria transport through the land and in-stream. The calibrated SWAT model was then used to estimate the indicator bacteria in-stream concentrations for future years based on regional land use, population and household forecast (up to 2040). Based on the reductions required to meet the water quality standards in-stream, the corresponding required source load reductions were estimated.

  11. Compositional Changes in Selected Minimally Processed Vegetables

    OpenAIRE

    O'Reilly, Emer, (Thesis)

    2000-01-01

    Compositional, physiological and microbiological changes in selected minimally processed vegetables packaged under a modified atmosphere of 2% oxygen and 5% carbon dioxide were monitored over a ten day storage period at 40 C and 80 C. The analysis targeted specific changes in the nutritional, chemical and physiological make up of the vegetables as well as the changes in the microbial levels. In addition the changes in the gas atmospheres within the packs were monitored. It has been widely acc...

  12. On Optimal Input Design and Model Selection for Communication Channels

    Energy Technology Data Exchange (ETDEWEB)

    Li, Yanyan [ORNL; Djouadi, Seddik M [ORNL; Olama, Mohammed M [ORNL

    2013-01-01

    In this paper, the optimal model (structure) selection and input design which minimize the worst case identification error for communication systems are provided. The problem is formulated using metric complexity theory in a Hilbert space setting. It is pointed out that model selection and input design can be handled independently. Kolmogorov n-width is used to characterize the representation error introduced by model selection, while Gel fand and Time n-widths are used to represent the inherent error introduced by input design. After the model is selected, an optimal input which minimizes the worst case identification error is shown to exist. In particular, it is proven that the optimal model for reducing the representation error is a Finite Impulse Response (FIR) model, and the optimal input is an impulse at the start of the observation interval. FIR models are widely popular in communication systems, such as, in Orthogonal Frequency Division Multiplexing (OFDM) systems.

  13. Working covariance model selection for generalized estimating equations.

    Science.gov (United States)

    Carey, Vincent J; Wang, You-Gan

    2011-11-20

    We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice. Copyright © 2011 John Wiley & Sons, Ltd.

  14. Site selection and characterization processes for deep geologic disposal of high level nuclear waste

    International Nuclear Information System (INIS)

    Costin, L.S.

    1997-01-01

    In this paper, the major elements of the site selection and characterization processes used in the U. S. high level waste program are discussed. While much of the evolution of the site selection and characterization processes have been driven by the unique nature of the U. S. program, these processes, which are well-defined and documented, could be used as an initial basis for developing site screening, selection, and characterization programs in other countries. Thus, this paper focuses more on the process elements than the specific details of the U. S. program. (author). 3 refs., 2 tabs., 5 figs

  15. Site selection and characterization processes for deep geologic disposal of high level nuclear waste

    Energy Technology Data Exchange (ETDEWEB)

    Costin, L.S. [Sandia National Labs., Albuquerque, NM (United States)

    1997-12-31

    In this paper, the major elements of the site selection and characterization processes used in the U. S. high level waste program are discussed. While much of the evolution of the site selection and characterization processes have been driven by the unique nature of the U. S. program, these processes, which are well-defined and documented, could be used as an initial basis for developing site screening, selection, and characterization programs in other countries. Thus, this paper focuses more on the process elements than the specific details of the U. S. program. (author). 3 refs., 2 tabs., 5 figs.

  16. [On-line processing mechanisms in text comprehension: a theoretical review on constructing situation models].

    Science.gov (United States)

    Iseki, Ryuta

    2004-12-01

    This article reviewed research on construction of situation models during reading. To position variety of research in overall process appropriately, an unitary framework was devised in terms of three theories for on-line processing: resonance process, event-indexing model, and constructionist theory. Resonance process was treated as a basic activation mechanism in the framework. Event-indexing model was regarded as a screening system which selected and encoded activated information in situation models along with situational dimensions. Constructionist theory was considered to have a supervisory role based on coherence and explanation. From a view of the unitary framework, some problems concerning each theory were examined and possible interpretations were given. Finally, it was pointed out that there were little theoretical arguments on associative processing at global level and encoding text- and inference-information into long-term memory.

  17. Selective Interference on the Holistic Processing of Faces in Working Memory

    Science.gov (United States)

    Cheung, Olivia S.; Gauthier, Isabel

    2010-01-01

    Faces and objects of expertise compete for early perceptual processes and holistic processing resources (Gauthier, Curran, Curby, & Collins, 2003). Here, we examined the nature of interference on holistic face processing in working memory by comparing how various types of loads affect selective attention to parts of face composites. In dual…

  18. Detecting consistent patterns of directional adaptation using differential selection codon models.

    Science.gov (United States)

    Parto, Sahar; Lartillot, Nicolas

    2017-06-23

    Phylogenetic codon models are often used to characterize the selective regimes acting on protein-coding sequences. Recent methodological developments have led to models explicitly accounting for the interplay between mutation and selection, by modeling the amino acid fitness landscape along the sequence. However, thus far, most of these models have assumed that the fitness landscape is constant over time. Fluctuations of the fitness landscape may often be random or depend on complex and unknown factors. However, some organisms may be subject to systematic changes in selective pressure, resulting in reproducible molecular adaptations across independent lineages subject to similar conditions. Here, we introduce a codon-based differential selection model, which aims to detect and quantify the fine-grained consistent patterns of adaptation at the protein-coding level, as a function of external conditions experienced by the organism under investigation. The model parameterizes the global mutational pressure, as well as the site- and condition-specific amino acid selective preferences. This phylogenetic model is implemented in a Bayesian MCMC framework. After validation with simulations, we applied our method to a dataset of HIV sequences from patients with known HLA genetic background. Our differential selection model detects and characterizes differentially selected coding positions specifically associated with two different HLA alleles. Our differential selection model is able to identify consistent molecular adaptations as a function of repeated changes in the environment of the organism. These models can be applied to many other problems, ranging from viral adaptation to evolution of life-history strategies in plants or animals.

  19. On the selection of ordinary differential equation models with application to predator-prey dynamical models.

    Science.gov (United States)

    Zhang, Xinyu; Cao, Jiguo; Carroll, Raymond J

    2015-03-01

    We consider model selection and estimation in a context where there are competing ordinary differential equation (ODE) models, and all the models are special cases of a "full" model. We propose a computationally inexpensive approach that employs statistical estimation of the full model, followed by a combination of a least squares approximation (LSA) and the adaptive Lasso. We show the resulting method, here called the LSA method, to be an (asymptotically) oracle model selection method. The finite sample performance of the proposed LSA method is investigated with Monte Carlo simulations, in which we examine the percentage of selecting true ODE models, the efficiency of the parameter estimation compared to simply using the full and true models, and coverage probabilities of the estimated confidence intervals for ODE parameters, all of which have satisfactory performances. Our method is also demonstrated by selecting the best predator-prey ODE to model a lynx and hare population dynamical system among some well-known and biologically interpretable ODE models. © 2014, The International Biometric Society.

  20. Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

    Science.gov (United States)

    Konno, Hidetoshi; Tamura, Yoshiyasu

    2018-01-01

    In neural spike counting experiments, it is known that there are two main features: (i) the counting number has a fractional power-law growth with time and (ii) the waiting time (i.e., the inter-spike-interval) distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs) is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii) can be modeled by the method of SSPPs. Namely, the first one (i) associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP).

  1. Executive Selection in Government Agencies: An Analysis of the Department of the Navy and Immigration and Naturalization Services Senior Executive Service Selection Processes

    National Research Council Canada - National Science Library

    Jordan, Mark

    2001-01-01

    .... The Senior Executive Service (SES) selection process for the Department of the Navy (DON) is analyzed and compared to the SES selection process used by the Immigration and Naturalization Service...

  2. Optimization of A(2)O BNR processes using ASM and EAWAG Bio-P models: model performance.

    Science.gov (United States)

    El Shorbagy, Walid E; Radif, Nawras N; Droste, Ronald L

    2013-12-01

    This paper presents the performance of an optimization model for a biological nutrient removal (BNR) system using the anaerobic-anoxic-oxic (A(2)O) process. The formulated model simulates removal of organics, nitrogen, and phosphorus using a reduced International Water Association (IWA) Activated Sludge Model #3 (ASM3) model and a Swiss Federal Institute for Environmental Science and Technology (EAWAG) Bio-P module. Optimal sizing is attained considering capital and operational costs. Process performance is evaluated against the effect of influent conditions, effluent limits, and selected parameters of various optimal solutions with the following results: an increase of influent temperature from 10 degrees C to 25 degrees C decreases the annual cost by about 8.5%, an increase of influent flow from 500 to 2500 m(3)/h triples the annual cost, the A(2)O BNR system is more sensitive to variations in influent ammonia than phosphorus concentration and the maximum growth rate of autotrophic biomass was the most sensitive kinetic parameter in the optimization model.

  3. Gender Differences in Resistance to Schooling: The Role of Dynamic Peer-Influence and Selection Processes.

    Science.gov (United States)

    Geven, Sara; O Jonsson, Jan; van Tubergen, Frank

    2017-12-01

    Boys engage in notably higher levels of resistance to schooling than girls. While scholars argue that peer processes contribute to this gender gap, this claim has not been tested with longitudinal quantitative data. This study fills this lacuna by examining the role of dynamic peer-selection and influence processes in the gender gap in resistance to schooling (i.e., arguing with teachers, skipping class, not putting effort into school, receiving punishments at school, and coming late to class) with two-wave panel data. We expect that, compared to girls, boys are more exposed and more responsive to peers who exhibit resistant behavior. We estimate hybrid models on 5448 students from 251 school classes in Sweden (14-15 years, 49% boys), and stochastic actor-based models (SIENA) on a subsample of these data (2480 students in 98 classes; 49% boys). We find that boys are more exposed to resistant friends than girls, and that adolescents are influenced by the resistant behavior of friends. These peer processes do not contribute to a widening of the gender gap in resistance to schooling, yet they contribute somewhat to the persistence of the initial gender gap. Boys are not more responsive to the resistant behavior of friends than girls. Instead, girls are influenced more by the resistant behavior of lower status friends than boys. This explains to some extent why boys increase their resistance to schooling more over time. All in all, peer-influence and selection processes seem to play a minor role in gender differences in resistance to schooling. These findings nuance under investigated claims that have been made in the literature.

  4. Equilibrium and nonequilibrium attractors for a discrete, selection-migration model

    Science.gov (United States)

    James F. Selgrade; James H. Roberds

    2003-01-01

    This study presents a discrete-time model for the effects of selection and immigration on the demographic and genetic compositions of a population. Under biologically reasonable conditions, it is shown that the model always has an equilibrium. Although equilibria for similar models without migration must have real eigenvalues, for this selection-migration model we...

  5. Application of numerical modeling of selective NOx reduction by hydrocarbon under diesel transient conditions in consideration of hydrocarbon adsorption and desorption process

    International Nuclear Information System (INIS)

    Watanabe, Y.; Asano, A.; Banno, K.; Yokota, K.; Sugiura, M.

    2001-01-01

    A model of NO x selective reduction by hydrocarbon (HC) was developed, which takes into account the adsorption and desorption of HC. The model was applied for predicting the performance of a De-NO x catalytic reactor, working under transient conditions such as a legislative driving cycle. Diesel fuel was used as a supplemental reductant. The behavior of HC and NO x reactions and HC adsorption and desorption has been simulated successfully by our numerical approach under the transient conditions of the simulated Japanese 10-15 driving cycle. Our model is expected to optimize the design of selective diesel NO x reduction systems using a diesel fuel as a supplemental reductant

  6. WWTP Process Tank Modelling

    DEFF Research Database (Denmark)

    Laursen, Jesper

    The present thesis considers numerical modeling of activated sludge tanks on municipal wastewater treatment plants. Focus is aimed at integrated modeling where the detailed microbiological model the Activated Sludge Model 3 (ASM3) is combined with a detailed hydrodynamic model based on a numerical...... solution of the Navier-Stokes equations in a multiphase scheme. After a general introduction to the activated sludge tank as a system, the activated sludge tank model is gradually setup in separate stages. The individual sub-processes that are often occurring in activated sludge tanks are initially...... hydrofoil shaped propellers. These two sub-processes deliver the main part of the supplied energy to the activated sludge tank, and for this reason they are important for the mixing conditions in the tank. For other important processes occurring in the activated sludge tank, existing models and measurements...

  7. Dynamic flowgraph modeling of process and control systems of a nuclear-based hydrogen production plant

    Energy Technology Data Exchange (ETDEWEB)

    Al-Dabbagh, Ahmad W. [Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada); Lu, Lixuan [Faculty of Energy Systems and Nuclear Science, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada)

    2010-09-15

    Modeling and analysis of system reliability facilitate the identification of areas of potential improvement. The Dynamic Flowgraph Methodology (DFM) is an emerging discrete modeling framework that allows for capturing time dependent behaviour, switching logic and multi-state representation of system components. The objective of this research is to demonstrate the process of dynamic flowgraph modeling of a nuclear-based hydrogen production plant with the copper-chlorine (Cu-Cl) cycle. Modeling of the thermochemical process of the Cu-Cl cycle in conjunction with a networked control system proposed for monitoring and control of the process is provided. This forms the basis for future component selection. (author)

  8. Application of a collaborative modelling and strategic fuzzy decision support system for selecting appropriate resilience strategies for seaport operations

    Directory of Open Access Journals (Sweden)

    Andrew John

    2014-06-01

    Full Text Available The selection of an appropriate resilience investment strategy to optimize the operational efficiency of a seaport is a challenging task given that many criteria need to be considered and modelled under an uncertain environment. The design of such a complex decision system consists of many subjective and imprecise parameters contained in different quantitative and qualitative forms. This paper proposes a fuzzy multi-attribute decision making methodology for the selection of an appropriate resilience investment strategy in a succinct and straightforward manner. The decision support model allows for a collaborative modelling of the system by multiple analysts in a group decision making process. Fuzzy analytical hierarchy process (FAHP was utilized to analyse the complex structure of the system to obtain the weights of all the criteria while fuzzy technique for order of preference by similarity to ideal solution (TOPSIS was employed to facilitate the ranking process of the resilience strategies. Given that it is often financially difficult to invest in all the resilience strategies, it is envisaged that the proposed approach could provide decision makers with a flexible and transparent tool for selecting appropriate resilience strategies aimed at increasing the resilience of seaport operations.

  9. modeling grinding modeling grinding processes as micro processes

    African Journals Online (AJOL)

    eobe

    industrial precision grinding processes are cylindrical, center less and ... Several model shave been proposed and used to study grinding ..... grinding force for the two cases were 9.07237N/mm ..... International Journal of Machine Tools &.

  10. A model for strategic selection of feeder management systems: A case study

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Hsing Hung [Faculty of Management and Administration, Macau University of Science and Technology, Avenue Wei Long, Taipa, Macau (China); Lee, Amy H.I. [Department of Industrial Management, Chung Hua University, No. 707, Sec. 2, Wu Fu Rd., Hsinchu 300 (China); Kang, He-Yau [Department of Industrial Engineering and Management, National Chin-Yi University of Technology, 35, Lane 215, Sec. 1, Chung San Rd., Taiping, Taichung 411 (China)

    2010-06-15

    The move to integrating distribution management system (DMS) and feeder management system (FMS) in China is becoming the main trend in recent years, in addition to upgrading and rebuilding existing energy management system (EMS) and DMS. However, with increasing complexity in the social environments along with rapidly changing technologies, how to select a suitable contractor and a FMS project is becoming an important issue for electric power companies. This paper first briefly introduces FMS and then lists its critical success criteria. A model that applies a multi-criteria decision-making (MCDM) method, an analytic network process (ANP) associated with benefits, opportunities, costs and risks (BOCR), is constructed to help power companies to select the most suitable FMS project. (author)

  11. Biomechanical differences in the stem straightening process among Pinus pinaster provenances. A new approach for early selection of stem straightness.

    Science.gov (United States)

    Sierra-de-Grado, Rosario; Pando, Valentín; Martínez-Zurimendi, Pablo; Peñalvo, Alejandro; Báscones, Esther; Moulia, Bruno

    2008-06-01

    Stem straightness is an important selection trait in Pinus pinaster Ait. breeding programs. Despite the stability of stem straightness rankings in provenance trials, the efficiency of breeding programs based on a quantitative index of stem straightness remains low. An alternative approach is to analyze biomechanical processes that underlie stem form. The rationale for this selection method is that genetic differences in the biomechanical processes that maintain stem straightness in young plants will continue to control stem form throughout the life of the tree. We analyzed the components contributing most to genetic differences among provenances in stem straightening processes by kinetic analysis and with a biomechanical model defining the interactions between the variables involved (Fournier's model). This framework was tested on three P. pinaster provenances differing in adult stem straightness and growth. One-year-old plants were tilted at 45 degrees, and individual stem positions and sizes were recorded weekly for 5 months. We measured the radial extension of reaction wood and the anatomical features of wood cells in serial stem cross sections. The integral effect of reaction wood on stem leaning was computed with Fournier's model. Responses driven by both primary and secondary growth were involved in the stem straightening process, but secondary-growth-driven responses accounted for most differences among provenances. Plants from the straight-stemmed provenance showed a greater capacity for stem straightening than plants from the sinuous provenances mainly because of (1) more efficient reaction wood (higher maturation strains) and (2) more pronounced secondary-growth-driven autotropic decurving. These two process-based traits are thus good candidates for early selection of stem straightness, but additional tests on a greater number of genotypes over a longer period are required.

  12. A Cognitive Model of Document Use during a Research Project. Study I. Document Selection.

    Science.gov (United States)

    Wang, Peiling; Soergel, Dagobert

    1998-01-01

    Proposes a model of document selection by real users of a bibliographic retrieval system. Reports on Part I of a longitudinal study of decision making on document use by academics (25 faculty and graduate students in Agricultural Economics). Examines what components are relevant to the users' decisions and what cognitive process may have occurred…

  13. Stock Selection for Portfolios Using Expected Utility-Entropy Decision Model

    Directory of Open Access Journals (Sweden)

    Jiping Yang

    2017-09-01

    Full Text Available Yang and Qiu proposed and then recently improved an expected utility-entropy (EU-E measure of risk and decision model. When segregation holds, Luce et al. derived an expected utility term, plus a constant multiplies the Shannon entropy as the representation of risky choices, further demonstrating the reasonability of the EU-E decision model. In this paper, we apply the EU-E decision model to selecting the set of stocks to be included in the portfolios. We first select 7 and 10 stocks from the 30 component stocks of Dow Jones Industrial Average index, and then derive and compare the efficient portfolios in the mean-variance framework. The conclusions imply that efficient portfolios composed of 7(10 stocks selected using the EU-E model with intermediate intervals of the tradeoff coefficients are more efficient than that composed of the sets of stocks selected using the expected utility model. Furthermore, the efficient portfolio of 7(10 stocks selected by the EU-E decision model have almost the same efficient frontier as that of the sample of all stocks. This suggests the necessity of incorporating both the expected utility and Shannon entropy together when taking risky decisions, further demonstrating the importance of Shannon entropy as the measure of uncertainty, as well as the applicability of the EU-E model as a decision-making model.

  14. The iFlow modelling framework v2.4: a modular idealized process-based model for flow and transport in estuaries

    Science.gov (United States)

    Dijkstra, Yoeri M.; Brouwer, Ronald L.; Schuttelaars, Henk M.; Schramkowski, George P.

    2017-07-01

    The iFlow modelling framework is a width-averaged model for the systematic analysis of the water motion and sediment transport processes in estuaries and tidal rivers. The distinctive solution method, a mathematical perturbation method, used in the model allows for identification of the effect of individual physical processes on the water motion and sediment transport and study of the sensitivity of these processes to model parameters. This distinction between processes provides a unique tool for interpreting and explaining hydrodynamic interactions and sediment trapping. iFlow also includes a large number of options to configure the model geometry and multiple choices of turbulence and salinity models. Additionally, the model contains auxiliary components, including one that facilitates easy and fast sensitivity studies. iFlow has a modular structure, which makes it easy to include, exclude or change individual model components, called modules. Depending on the required functionality for the application at hand, modules can be selected to construct anything from very simple quasi-linear models to rather complex models involving multiple non-linear interactions. This way, the model complexity can be adjusted to the application. Once the modules containing the required functionality are selected, the underlying model structure automatically ensures modules are called in the correct order. The model inserts iteration loops over groups of modules that are mutually dependent. iFlow also ensures a smooth coupling of modules using analytical and numerical solution methods. This way the model combines the speed and accuracy of analytical solutions with the versatility of numerical solution methods. In this paper we present the modular structure, solution method and two examples of the use of iFlow. In the examples we present two case studies, of the Yangtze and Scheldt rivers, demonstrating how iFlow facilitates the analysis of model results, the understanding of the

  15. SELECTION OF PROJECT MANAGERS IN CONSTRUCTION FIRMS USING ANALYTIC HIERARCHY PROCESS (AHP AND FUZZY TOPSIS: A CASE STUDY

    Directory of Open Access Journals (Sweden)

    Fatemeh Torfi

    2011-10-01

    Full Text Available Selecting a project manager is a major decision for every construction company. Traditionally, a project manager is selected by interviewing applicants and evaluating their capabilities by considering the special requirements of the project. The interviews are usually conducted by senior managers, and the selection of the best candidate depends on their opinions. Thus, the results may not be completely reliable. Moreover, conducting interviews for a large group of candidates is time-consuming. Thus, there is a need for computational models that can be used to select the most suitable applicant, given the project specifications and the applicants’ details. In this paper, a case study is performed in which a Fuzzy Multiple Criteria Decision Making (FMCDM model is used to select the best candidate for the post of project manager in a large construction firm. First, with the opinions of the senior managers, all the criteria and sub-criteria required for the selection are gathered, and the criteria priorities are qualitatively specified. Then, the applicants are ranked using the Analytic Hierarchy Process (AHP, approximate weights of the criteria, and fuzzy technique for order performance by similarity to ideal solution (TOPSIS. The results of the case study are shown to be satisfactory.

  16. Informative gene selection using Adaptive Analytic Hierarchy Process (A2HP

    Directory of Open Access Journals (Sweden)

    Abhishek Bhola

    2017-12-01

    Full Text Available Gene expression dataset derived from microarray experiments are marked by large number of genes, which contains the gene expression values at different sample conditions/time-points. Selection of informative genes from these large datasets is an issue of major concern for various researchers and biologists. In this study, we propose a gene selection and dimensionality reduction method called Adaptive Analytic Hierarchy Process (A2HP. Traditional analytic hierarchy process is a multiple-criteria based decision analysis method whose result depends upon the expert knowledge or decision makers. It is mainly used to solve the decision problems in different fields. On the other hand, A2HP is a fused method that combines the outcomes of five individual gene selection ranking methods t-test, chi-square variance test, z-test, wilcoxon test and signal-to-noise ratio (SNR. At first, the preprocessing of gene expression dataset is done and then the reduced number of genes obtained, will be fed as input for A2HP. A2HP utilizes both quantitative and qualitative factors to select the informative genes. Results demonstrate that A2HP selects efficient number of genes as compared to the individual gene selection methods. The percentage of deduction in number of genes and time complexity are taken as the performance measure for the proposed method. And it is shown that A2HP outperforms individual gene selection methods.

  17. Temporally selective attention supports speech processing in 3- to 5-year-old children.

    Science.gov (United States)

    Astheimer, Lori B; Sanders, Lisa D

    2012-01-01

    Recent event-related potential (ERP) evidence demonstrates that adults employ temporally selective attention to preferentially process the initial portions of words in continuous speech. Doing so is an effective listening strategy since word-initial segments are highly informative. Although the development of this process remains unexplored, directing attention to word onsets may be important for speech processing in young children who would otherwise be overwhelmed by the rapidly changing acoustic signals that constitute speech. We examined the use of temporally selective attention in 3- to 5-year-old children listening to stories by comparing ERPs elicited by attention probes presented at four acoustically matched times relative to word onsets: concurrently with a word onset, 100 ms before, 100 ms after, and at random control times. By 80 ms, probes presented at and after word onsets elicited a larger negativity than probes presented before word onsets or at control times. The latency and distribution of this effect is similar to temporally and spatially selective attention effects measured in adults and, despite differences in polarity, spatially selective attention effects measured in children. These results indicate that, like adults, preschool aged children modulate temporally selective attention to preferentially process the initial portions of words in continuous speech. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. Discrimination against international medical graduates in the United States residency program selection process.

    Science.gov (United States)

    Desbiens, Norman A; Vidaillet, Humberto J

    2010-01-25

    Available evidence suggests that international medical graduates have improved the availability of U.S. health care while maintaining academic standards. We wondered whether studies had been conducted to address how international graduates were treated in the post-graduate selection process compared to U.S. graduates. We conducted a Medline search for research on the selection process. Two studies provide strong evidence that psychiatry and family practice programs respond to identical requests for applications at least 80% more often for U.S. medical graduates than for international graduates. In a third study, a survey of surgical program directors, over 70% perceived that there was discrimination against international graduates in the selection process. There is sufficient evidence to support action against discrimination in the selection process. Medical organizations should publish explicit proscriptions of discrimination against international medical graduates (as the American Psychiatric Association has done) and promote them in diversity statements. They should develop uniform and transparent policies for program directors to use to select applicants that minimize the possibility of non-academic discrimination, and the accreditation organization should monitor whether it is occurring. Whether there should be protectionism for U.S. graduates or whether post-graduate medical education should be an unfettered meritocracy needs to be openly discussed by medicine and society.

  19. Modeling of column apparatus processes

    CERN Document Server

    Boyadjiev, Christo; Boyadjiev, Boyan; Popova-Krumova, Petya

    2016-01-01

    This book presents a new approach for the modeling of chemical and interphase mass transfer processes in industrial column apparatuses, using convection-diffusion and average-concentration models. The convection-diffusion type models are used for a qualitative analysis of the processes and to assess the main, small and slight physical effects, and then reject the slight effects. As a result, the process mechanism can be identified. It also introduces average concentration models for quantitative analysis, which use the average values of the velocity and concentration over the cross-sectional area of the column. The new models are used to analyze different processes (simple and complex chemical reactions, absorption, adsorption and catalytic reactions), and make it possible to model the processes of gas purification with sulfur dioxide, which form the basis of several patents.

  20. Short-Run Asset Selection using a Logistic Model

    Directory of Open Access Journals (Sweden)

    Walter Gonçalves Junior

    2011-06-01

    Full Text Available Investors constantly look for significant predictors and accurate models to forecast future results, whose occasional efficacy end up being neutralized by market efficiency. Regardless, such predictors are widely used for seeking better (and more unique perceptions. This paper aims to investigate to what extent some of the most notorious indicators have discriminatory power to select stocks, and if it is feasible with such variables to build models that could anticipate those with good performance. In order to do that, logistical regressions were conducted with stocks traded at Bovespa using the selected indicators as explanatory variables. Investigated in this study were the outputs of Bovespa Index, liquidity, the Sharpe Ratio, ROE, MB, size and age evidenced to be significant predictors. Also examined were half-year, logistical models, which were adjusted in order to check the potential acceptable discriminatory power for the asset selection.

  1. Using AHP for Selecting the Best Wastewater Treatment Process

    Directory of Open Access Journals (Sweden)

    AbdolReza Karimi

    2011-01-01

    Full Text Available In this paper, Analytical Hierarchy Process (AHP method that is based on expert knowledge is used for the selection of the optimal anaerobic wastewater treatment process in industrial estates. This method can be applied for complicated multi-criteria decision making to obtain reasonable results. The different anaerobic processes employed in Iranian industrial estates consist of UASB, UAFB, ABR, Contact process, and Anaerobic Lagoons. Based on the general conditions in wastewater treatment plants in industrial estates and on expert judgments and using technical, economic, environmental, and administrative criteria, the processes are weighted and the results obtained are assessed using the Expert Choice Software. Finally, the five processes investigated are ranked as 1 to 5 in a descending order of UAFB, ABR, UASB, Anaerobic Lagoon, and Contact Process. Sensitivity analysis showing the effects of input parameters on changes in the results was applied for technical, economic, environmental, and administrative criteria.

  2. Integrated model for supplier selection and performance evaluation

    Directory of Open Access Journals (Sweden)

    Borges de Araújo, Maria Creuza

    2015-08-01

    Full Text Available This paper puts forward a model for selecting suppliers and evaluating the performance of those already working with a company. A simulation was conducted in a food industry. This sector has high significance in the economy of Brazil. The model enables the phases of selecting and evaluating suppliers to be integrated. This is important so that a company can have partnerships with suppliers who are able to meet their needs. Additionally, a group method is used to enable managers who will be affected by this decision to take part in the selection stage. Finally, the classes resulting from the performance evaluation are shown to support the contractor in choosing the most appropriate relationship with its suppliers.

  3. Investigating the Process of Process Modeling with Eye Movement Analysis

    OpenAIRE

    Pinggera, Jakob; Furtner, Marco; Martini, Markus; Sachse, Pierre; Reiter, Katharina; Zugal, Stefan; Weber, Barbara

    2015-01-01

    Research on quality issues of business process models has recently begun to explore the process of creating process models by analyzing the modeler's interactions with the modeling environment. In this paper we aim to complement previous insights on the modeler's modeling behavior with data gathered by tracking the modeler's eye movements when engaged in the act of modeling. We present preliminary results and outline directions for future research to triangulate toward a more comprehensive un...

  4. What makes process models understandable?

    NARCIS (Netherlands)

    Mendling, J.; Reijers, H.A.; Cardoso, J.; Alonso, G.; Dadam, P.; Rosemann, M.

    2007-01-01

    Despite that formal and informal quality aspects are of significant importance to business process modeling, there is only little empirical work reported on process model quality and its impact factors. In this paper we investigate understandability as a proxy for quality of process models and focus

  5. Employee Selection Process: Integrating Employee Needs and Employer Motivators.

    Science.gov (United States)

    Carroll, Brian J.

    1989-01-01

    Offers suggestions for managers relative to the employee selection process, focusing on the identification of a potential employee's needs and the employer's motivators that affect employee productivity. Discusses the use of a preemployment survey and offers a questionnaire that allows matching of the employee's needs with employment…

  6. Application of ion beam analysis to the selective sublimation processing of thin films for gas sensing

    International Nuclear Information System (INIS)

    Vomiero, A.; Scian, C.; Della Mea, G.; Guidi, V.; Martinelli, G.; Schiffrer, G.; Comini, E.; Ferroni, M.; Sberveglieri, G.

    2006-01-01

    Ion beam analysis was successfully applied to a novel technique, named selective sublimation process (SSP), for deposition of nanostructured gas-sensing films through reactive sputtering. The method consists of the co-deposition of a mixed oxide, one of which has a relatively low sublimation temperature. Annealing at suitable temperature causes the sublimation of the most volatile compound, leaving a layer with adjustable composition. The appropriate choice of thermal treatments and the consequent tailoring of the composition play a crucial role in the determination of the microstructural properties. We developed a model based on diffusion equations that provides a useful guide to control the deposition and processing parameters and we applied the model on the systems TiO 2 -WO 3 and TiO 2 -MoO 3 . Rutherford backscattering (RBS) was demonstrated to be effective for the characterization of the diffusion and sublimation processes during SSP. Experimental results fully agree with theoretical prediction, and allowed the calculation of all the parameters involved in SSP

  7. Toward a formalization of the process to select IMIA Yearbook best papers.

    Science.gov (United States)

    Lamy, J-B; Séroussi, B; Griffon, N; Kerdelhué, G; Jaulent, M-C; Bouaud, J

    2015-01-01

    Each year, the International Medical Informatics Association Yearbook recognizes significant scientific papers, labelled as "best papers", published the previous year in the subfields of biomedical informatics that correspond to the different section topics of the journal. For each section, about fifteen pre-selected "candidate" best papers are externally peer-reviewed to select the actual best papers. Although based on the available literature, little is known about the pre-selection process. To move toward an explicit formalization of the candidate best papers selection process to reduce variability in the literature search across sections and over years. A methodological framework is proposed to build for each section topic specific queries tailored to PubMed and Web of Science citation databases. The two sets of returned papers are merged and reviewed by two independent section editors and citations are tagged as "discarded", "pending", and "kept". A protocolized consolidation step is then jointly conducted to resolve conflicts. A bibliographic software tool, BibReview, was developed to support the whole process. The proposed search strategy was fully applied to the Decision Support section of the 2013 edition of the Yearbook. For this section, 1124 references were returned (689 PubMed-specific, 254 WoS-specific, 181 common to both databases) among which the 15 candidate best papers were selected. The search strategy for determining candidate best papers for an IMIA Yearbook's section is now explicitly specified and allows for reproducibility. However, some aspects of the whole process remain reviewer-dependent, mostly because there is no characterization of a "best paper".

  8. Modeling the Object-Oriented Software Process: OPEN and the Unified Process

    NARCIS (Netherlands)

    van den Berg, Klaas; Aksit, Mehmet; van den Broek, P.M.

    A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is

  9. Some fuzzy techniques for staff selection process: A survey

    Science.gov (United States)

    Md Saad, R.; Ahmad, M. Z.; Abu, M. S.; Jusoh, M. S.

    2013-04-01

    With high level of business competition, it is vital to have flexible staff that are able to adapt themselves with work circumstances. However, staff selection process is not an easy task to be solved, even when it is tackled in a simplified version containing only a single criterion and a homogeneous skill. When multiple criteria and various skills are involved, the problem becomes much more complicated. In adddition, there are some information that could not be measured precisely. This is patently obvious when dealing with opinions, thoughts, feelings, believes, etc. One possible tool to handle this issue is by using fuzzy set theory. Therefore, the objective of this paper is to review the existing fuzzy techniques for solving staff selection process. It classifies several existing research methods and identifies areas where there is a gap and need further research. Finally, this paper concludes by suggesting new ideas for future research based on the gaps identified.

  10. Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

    Directory of Open Access Journals (Sweden)

    Hidetoshi Konno

    2018-01-01

    Full Text Available In neural spike counting experiments, it is known that there are two main features: (i the counting number has a fractional power-law growth with time and (ii the waiting time (i.e., the inter-spike-interval distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii can be modeled by the method of SSPPs. Namely, the first one (i associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP.

  11. Model Selection in Historical Research Using Approximate Bayesian Computation

    Science.gov (United States)

    Rubio-Campillo, Xavier

    2016-01-01

    Formal Models and History Computational models are increasingly being used to study historical dynamics. This new trend, which could be named Model-Based History, makes use of recently published datasets and innovative quantitative methods to improve our understanding of past societies based on their written sources. The extensive use of formal models allows historians to re-evaluate hypotheses formulated decades ago and still subject to debate due to the lack of an adequate quantitative framework. The initiative has the potential to transform the discipline if it solves the challenges posed by the study of historical dynamics. These difficulties are based on the complexities of modelling social interaction, and the methodological issues raised by the evaluation of formal models against data with low sample size, high variance and strong fragmentation. Case Study This work examines an alternate approach to this evaluation based on a Bayesian-inspired model selection method. The validity of the classical Lanchester’s laws of combat is examined against a dataset comprising over a thousand battles spanning 300 years. Four variations of the basic equations are discussed, including the three most common formulations (linear, squared, and logarithmic) and a new variant introducing fatigue. Approximate Bayesian Computation is then used to infer both parameter values and model selection via Bayes Factors. Impact Results indicate decisive evidence favouring the new fatigue model. The interpretation of both parameter estimations and model selection provides new insights into the factors guiding the evolution of warfare. At a methodological level, the case study shows how model selection methods can be used to guide historical research through the comparison between existing hypotheses and empirical evidence. PMID:26730953

  12. Measures and limits of models of fixation selection.

    Directory of Open Access Journals (Sweden)

    Niklas Wilming

    Full Text Available Models of fixation selection are a central tool in the quest to understand how the human mind selects relevant information. Using this tool in the evaluation of competing claims often requires comparing different models' relative performance in predicting eye movements. However, studies use a wide variety of performance measures with markedly different properties, which makes a comparison difficult. We make three main contributions to this line of research: First we argue for a set of desirable properties, review commonly used measures, and conclude that no single measure unites all desirable properties. However the area under the ROC curve (a classification measure and the KL-divergence (a distance measure of probability distributions combine many desirable properties and allow a meaningful comparison of critical model performance. We give an analytical proof of the linearity of the ROC measure with respect to averaging over subjects and demonstrate an appropriate correction of entropy-based measures like KL-divergence for small sample sizes in the context of eye-tracking data. Second, we provide a lower bound and an upper bound of these measures, based on image-independent properties of fixation data and between subject consistency respectively. Based on these bounds it is possible to give a reference frame to judge the predictive power of a model of fixation selection. We provide open-source python code to compute the reference frame. Third, we show that the upper, between subject consistency bound holds only for models that predict averages of subject populations. Departing from this we show that incorporating subject-specific viewing behavior can generate predictions which surpass that upper bound. Taken together, these findings lay out the required information that allow a well-founded judgment of the quality of any model of fixation selection and should therefore be reported when a new model is introduced.

  13. Natural Selection Is a Sorting Process: What Does that Mean?

    Science.gov (United States)

    Price, Rebecca M.

    2013-01-01

    To learn why natural selection acts only on existing variation, students categorize processes as either creative or sorting. This activity helps students confront the misconception that adaptations evolve because species need them.

  14. Evaluation of End-Products in Architecture Design Process: A Fuzzy Decision-Making Model

    Directory of Open Access Journals (Sweden)

    Serkan PALABIYIK

    2012-06-01

    Full Text Available This paper presents a study on the development of a fuzzy multi-criteria decision-making model for the evaluation of end products of the architectural design process. Potentials of the developed model were investigated within the scope of architectural design education, specifically an international design studio titled “Design for Disassembly and Reuse: Design & Building Multipurpose Transformable Pavilions.” The studio work followed a design process that integrated systematic and heuristic thinking. The design objectives and assessment criteria were clearly set out at the beginning of the process by the studio coordinator with the aim of narrowing the design space and increasing awareness of the consequences of design decisions. At the end of the design process, designs produced in the studio were evaluated using the developed model to support decision making. The model facilitated the identification of positive and negative aspects of the designs and selection of the design alternative that best met the studio objectives set at the beginning.

  15. Modeling the Object-Oriented Software Process: OPEN and the Unified Process

    OpenAIRE

    van den Berg, Klaas; Aksit, Mehmet; van den Broek, P.M.

    1999-01-01

    A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is reviewed.

  16. IDENTIFYING AND SELECTING THE STRATEGIC PROCESS USING THE CROSS-EFFICIENCY APPROACH BASED ON SATISFACTION LEVEL AND EXTENDDED BALANCED SCORECARD

    Directory of Open Access Journals (Sweden)

    Ardeshir Bazrkar

    2018-03-01

    Full Text Available The strategy is a macro and strategic plan, and will only be implemented when it is defined in the form of various projects. In order to exploit the benefits of lean six sigma projects, these projects should be in line with the strategic goals of the organization. Organizations should select projects which are compatible with the organization overall goals and fulfill the strategic requirements of the organization. The purpose of this study is to identify the strategic process among the bank facility processes to use it in lean six sigma methodology in order to improve process performance and efficiency using a combination of cross-efficiency and extended balanced scorecard methods. In the first step, the criteria for selecting the strategic process were identified using the six measures of the balanced scorecard method. In the second step, after collecting information using the cross-efficiency model based on satisfaction level, the bank facility processes are ranked based on the efficiency score. The results show that the ranking of the processes under consideration is carried out without any interference, and one of the processes (process 3 is considered as the strategic process to use in the six sigma methodology.

  17. Mathematical Formulation Requirements and Specifications for the Process Models

    Energy Technology Data Exchange (ETDEWEB)

    Steefel, C.; Moulton, D.; Pau, G.; Lipnikov, K.; Meza, J.; Lichtner, P.; Wolery, T.; Bacon, D.; Spycher, N.; Bell, J.; Moridis, G.; Yabusaki, S.; Sonnenthal, E.; Zyvoloski, G.; Andre, B.; Zheng, L.; Davis, J.

    2010-11-01

    The Advanced Simulation Capability for Environmental Management (ASCEM) is intended to be a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The ASCEM program is aimed at addressing critical EM program needs to better understand and quantify flow and contaminant transport behavior in complex geological systems. It will also address the long-term performance of engineered components including cementitious materials in nuclear waste disposal facilities, in order to reduce uncertainties and risks associated with DOE EM's environmental cleanup and closure activities. Building upon national capabilities developed from decades of Research and Development in subsurface geosciences, computational and computer science, modeling and applied mathematics, and environmental remediation, the ASCEM initiative will develop an integrated, open-source, high-performance computer modeling system for multiphase, multicomponent, multiscale subsurface flow and contaminant transport. This integrated modeling system will incorporate capabilities for predicting releases from various waste forms, identifying exposure pathways and performing dose calculations, and conducting systematic uncertainty quantification. The ASCEM approach will be demonstrated on selected sites, and then applied to support the next generation of performance assessments of nuclear waste disposal and facility decommissioning across the EM complex. The Multi-Process High Performance Computing (HPC) Simulator is one of three thrust areas in ASCEM. The other two are the Platform and Integrated Toolsets (dubbed the Platform) and Site Applications. The primary objective of the HPC Simulator is to provide a flexible and extensible computational engine to simulate the coupled processes and flow scenarios described by the conceptual models developed using the ASCEM Platform. The graded and iterative approach to assessments

  18. Mathematical Formulation Requirements and Specifications for the Process Models

    International Nuclear Information System (INIS)

    Steefel, C.; Moulton, D.; Pau, G.; Lipnikov, K.; Meza, J.; Lichtner, P.; Wolery, T.; Bacon, D.; Spycher, N.; Bell, J.; Moridis, G.; Yabusaki, S.; Sonnenthal, E.; Zyvoloski, G.; Andre, B.; Zheng, L.; Davis, J.

    2010-01-01

    The Advanced Simulation Capability for Environmental Management (ASCEM) is intended to be a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The ASCEM program is aimed at addressing critical EM program needs to better understand and quantify flow and contaminant transport behavior in complex geological systems. It will also address the long-term performance of engineered components including cementitious materials in nuclear waste disposal facilities, in order to reduce uncertainties and risks associated with DOE EM's environmental cleanup and closure activities. Building upon national capabilities developed from decades of Research and Development in subsurface geosciences, computational and computer science, modeling and applied mathematics, and environmental remediation, the ASCEM initiative will develop an integrated, open-source, high-performance computer modeling system for multiphase, multicomponent, multiscale subsurface flow and contaminant transport. This integrated modeling system will incorporate capabilities for predicting releases from various waste forms, identifying exposure pathways and performing dose calculations, and conducting systematic uncertainty quantification. The ASCEM approach will be demonstrated on selected sites, and then applied to support the next generation of performance assessments of nuclear waste disposal and facility decommissioning across the EM complex. The Multi-Process High Performance Computing (HPC) Simulator is one of three thrust areas in ASCEM. The other two are the Platform and Integrated Toolsets (dubbed the Platform) and Site Applications. The primary objective of the HPC Simulator is to provide a flexible and extensible computational engine to simulate the coupled processes and flow scenarios described by the conceptual models developed using the ASCEM Platform. The graded and iterative approach to assessments naturally

  19. PROCESS MODELLING AND DEBOTTLENECKING STUDY OF A VACCINE PRODUCTION

    Directory of Open Access Journals (Sweden)

    Nurul Huda Mohamed Safri

    2012-04-01

    Full Text Available ABSTRACT: The main objective of this research work was to model and optimise the production of a locally-developed Infectious Coryza (IC vaccine. The simulation work was performed using a commercially available batch process simulator SuperPro Designer v5.5. Six debottlenecking schemes were analysed using throughput analysis and cost to benefit ratio (CBR when the annual production was set to increase by 100%. Based on the economic analysis, the selected debottlenecking scheme has an annual predicted revenue of USD 240 million, with a gross margin of 9.13% and a return on investment (ROI of 46.12%. In addition, the payback period of the selected scheme is estimated to be within three years. ABSTRAK: Objektif utama dalam penyelidikan ini adalah untuk memodelkan dan mengoptimumkan hasil pembuatan vaksin tempatan Coryza berjangkit. Kerja simulasi ini dijalankan menggunakan alat simulasi Super Pro Designer v5.5. Sebanyak enam (6 skema khusus diujikaji menggunakan analisis pemprosesan dan kos kepada nisbah faedah (CBR apabila pembuatan tahunan meningkat kepada 100%. Berdasarkan analisis ekonomi yang telah dilakukan, sesuatu skema khusus yang dipilih mempunyai keuntungan sebanyak USD 240 juta dengan margin kasar 9.13% dan pulangan atas pelaburan (ROI sebanyak 46.12%. Selain itu juga, tempoh pembayaran balik bagi skema yang dipilih dianggarkan dalam tempoh tiga(3 tahun.KEYWORDS: process simulation; modelling; debottlenecking; optimisation

  20. Carrier-lifetime-controlled selective etching process for semiconductors using photochemical etching

    International Nuclear Information System (INIS)

    Ashby, C.I.H.; Myers, D.R.

    1992-01-01

    This patent describes a process for selectively photochemically etching a semiconductor material. It comprises introducing at least one impurity into at least one selected region of a semiconductor material to be etched to increase a local impurity concentration in the at least one selected region relative to an impurity concentration in regions of the semiconductor material adjacent thereto, for reducing minority carrier lifetimes within the at least one selected region relative to the adjacent regions for thereby providing a photochemical etch-inhibiting mask at the at least one selected region; and etching the semiconductor material by subjecting the surface of the semiconductor material to a carrier-driven photochemical etching reaction for selectively etching the regions of the semiconductor material adjacent the at least one selected region having the increase impurity concentration; wherein the step of introducing at least one impurity is performed so as not to produce damage to the at least one selected region before any etching is performed

  1. Introduction to gas lasers with emphasis on selective excitation processes

    CERN Document Server

    Willett, Colin S

    1974-01-01

    Introduction to Gas Lasers: Population Inversion Mechanisms focuses on important processes in gas discharge lasers and basic atomic collision processes that operate in a gas laser. Organized into six chapters, this book first discusses the historical development and basic principles of gas lasers. Subsequent chapters describe the selective excitation processes in gas discharges and the specific neutral, ionized and molecular laser systems. This book will be a valuable reference on the behavior of gas-discharge lasers to anyone already in the field.

  2. Selected Tether Applications Cost Model

    Science.gov (United States)

    Keeley, Michael G.

    1988-01-01

    Diverse cost-estimating techniques and data combined into single program. Selected Tether Applications Cost Model (STACOM 1.0) is interactive accounting software tool providing means for combining several independent cost-estimating programs into fully-integrated mathematical model capable of assessing costs, analyzing benefits, providing file-handling utilities, and putting out information in text and graphical forms to screen, printer, or plotter. Program based on Lotus 1-2-3, version 2.0. Developed to provide clear, concise traceability and visibility into methodology and rationale for estimating costs and benefits of operations of Space Station tether deployer system.

  3. Modeling the effect of selection history on pop-out visual search.

    Directory of Open Access Journals (Sweden)

    Yuan-Chi Tseng

    Full Text Available While attentional effects in visual selection tasks have traditionally been assigned "top-down" or "bottom-up" origins, more recently it has been proposed that there are three major factors affecting visual selection: (1 physical salience, (2 current goals and (3 selection history. Here, we look further into selection history by investigating Priming of Pop-out (POP and the Distractor Preview Effect (DPE, two inter-trial effects that demonstrate the influence of recent history on visual search performance. Using the Ratcliff diffusion model, we model observed saccadic selections from an oddball search experiment that included a mix of both POP and DPE conditions. We find that the Ratcliff diffusion model can effectively model the manner in which selection history affects current attentional control in visual inter-trial effects. The model evidence shows that bias regarding the current trial's most likely target color is the most critical parameter underlying the effect of selection history. Our results are consistent with the view that the 3-item color-oddball task used for POP and DPE experiments is best understood as an attentional decision making task.

  4. Forecasting house prices in the 50 states using Dynamic Model Averaging and Dynamic Model Selection

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    2015-01-01

    We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves substantia......We examine house price forecastability across the 50 states using Dynamic Model Averaging and Dynamic Model Selection, which allow for model change and parameter shifts. By allowing the entire forecasting model to change over time and across locations, the forecasting accuracy improves...

  5. Effect of Thermo-extrusion Process Parameters on Selected Quality ...

    African Journals Online (AJOL)

    Effect of Thermo-extrusion Process Parameters on Selected Quality Attributes of Meat Analogue from Mucuna Bean Seed Flour. ... Nigerian Food Journal ... The product functional responses with coefficients of determination (R2) ranging between 0.658 and 0.894 were most affected by changes in barrel temperature and ...

  6. Process model repositories and PNML

    NARCIS (Netherlands)

    Hee, van K.M.; Post, R.D.J.; Somers, L.J.A.M.; Werf, van der J.M.E.M.; Kindler, E.

    2004-01-01

    Bringing system and process models together in repositories facilitates the interchange of model information between modelling tools, and allows the combination and interlinking of complementary models. Petriweb is a web application for managing such repositories. It supports hierarchical process

  7. Model-based software process improvement

    Science.gov (United States)

    Zettervall, Brenda T.

    1994-01-01

    The activities of a field test site for the Software Engineering Institute's software process definition project are discussed. Products tested included the improvement model itself, descriptive modeling techniques, the CMM level 2 framework document, and the use of process definition guidelines and templates. The software process improvement model represents a five stage cyclic approach for organizational process improvement. The cycles consist of the initiating, diagnosing, establishing, acting, and leveraging phases.

  8. Ensembling Variable Selectors by Stability Selection for the Cox Model

    Directory of Open Access Journals (Sweden)

    Qing-Yan Yin

    2017-01-01

    Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.

  9. Business process modeling of industrial maintenance at TRANSPETRO: integrating oil pipeline and marine terminals activities

    Energy Technology Data Exchange (ETDEWEB)

    Arruda, Daniela Mendonca; Oliveira, Italo Luiz [TRANSPETRO - PETROBRAS Transporte S.A., Rio de Janeiro, RJ (Brazil). Diretoria de Terminais e Oleodutos; Almeida, Maria Fatima Ludovico de [Pontificia Universidade Catolica do Rio de Janeiro (PUC-Rio), Rio de Janeiro, RJ (Brazil). Programa de Pos-Graduacao em Metrologia para Qualidade e Inovacao

    2009-07-01

    This paper describes the experience of TRANSPETRO in remodeling industrial maintenance activities focusing on: preparing for business process modeling (BPM); mapping and analyzing 'As-Is' process; designing 'To-Be' process; implementing remodeled process; improving process continuously. The conceptual model and results achieved will contribute to several areas within the company as: reliability engineering; human resources, including employees' selective processes, training and development, and certifications; standardization process encompassing standard and operational procedures adoption according to up-dating external normative references and legal requirements; health, safety and environment (HSE) performance improvement. These are some of potential benefits from BPM focusing on TRANSPETRO's industrial maintenance area in the search of operational excellence. (author)

  10. Skewed factor models using selection mechanisms

    KAUST Repository

    Kim, Hyoung-Moon

    2015-12-21

    Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

  11. Skewed factor models using selection mechanisms

    KAUST Repository

    Kim, Hyoung-Moon; Maadooliat, Mehdi; Arellano-Valle, Reinaldo B.; Genton, Marc G.

    2015-01-01

    Traditional factor models explicitly or implicitly assume that the factors follow a multivariate normal distribution; that is, only moments up to order two are involved. However, it may happen in real data problems that the first two moments cannot explain the factors. Based on this motivation, here we devise three new skewed factor models, the skew-normal, the skew-tt, and the generalized skew-normal factor models depending on a selection mechanism on the factors. The ECME algorithms are adopted to estimate related parameters for statistical inference. Monte Carlo simulations validate our new models and we demonstrate the need for skewed factor models using the classic open/closed book exam scores dataset.

  12. The selective processing of emotional visual stimuli while detecting auditory targets: an ERP analysis.

    Science.gov (United States)

    Schupp, Harald T; Stockburger, Jessica; Bublatzky, Florian; Junghöfer, Markus; Weike, Almut I; Hamm, Alfons O

    2008-09-16

    Event-related potential studies revealed an early posterior negativity (EPN) for emotional compared to neutral pictures. Exploring the emotion-attention relationship, a previous study observed that a primary visual discrimination task interfered with the emotional modulation of the EPN component. To specify the locus of interference, the present study assessed the fate of selective visual emotion processing while attention is directed towards the auditory modality. While simply viewing a rapid and continuous stream of pleasant, neutral, and unpleasant pictures in one experimental condition, processing demands of a concurrent auditory target discrimination task were systematically varied in three further experimental conditions. Participants successfully performed the auditory task as revealed by behavioral performance and selected event-related potential components. Replicating previous results, emotional pictures were associated with a larger posterior negativity compared to neutral pictures. Of main interest, increasing demands of the auditory task did not modulate the selective processing of emotional visual stimuli. With regard to the locus of interference, selective emotion processing as indexed by the EPN does not seem to reflect shared processing resources of visual and auditory modality.

  13. A Qualitative Exploration of First Generation College Students and the Use of Facebook in the College Choice Selection Process

    Science.gov (United States)

    Coker, Cindy E.

    2015-01-01

    The purpose of this exploratory phenomenological narrative qualitative study was to investigate the influence of Facebook on first-generation college students' selection of a college framed within Hossler and Gallagher's (1987) college process model. The three questions which guided this research explored the influence of the social media website…

  14. Experimental verification of the energetic model of the dry mechanical reclamation process

    Directory of Open Access Journals (Sweden)

    R. Dańko

    2008-04-01

    Full Text Available The experimental results of the dry mechanical reclamation process, which constituted the bases for the verification of the energetic model of this process, developed by the author on the grounds of the Rittinger’s deterministic hypothesis of the crushing process, are presented in the paper. Used foundry sands with bentonite, with water-glass from the floster technology and used sands with furan FL 105 resin were used in the reclamation tests. In the mechanical and mechanical-cryogenic reclamation a wide range of time variations and reclamation conditions influencing intensity of the reclamation process – covering all possible parameters used in industrial devices - were applied. The developed theoretical model constitutes a new tool allowing selecting optimal times for the reclamation treatment of the given spent foundry sand at the assumed process intensity realized in rotor reclaimers - with leaves or rods as grinding elements mounted horizontally on the rotor axis.

  15. Optimizing selective cutting strategies for maximum carbon stocks and yield of Moso bamboo forest using BIOME-BGC model.

    Science.gov (United States)

    Mao, Fangjie; Zhou, Guomo; Li, Pingheng; Du, Huaqiang; Xu, Xiaojun; Shi, Yongjun; Mo, Lufeng; Zhou, Yufeng; Tu, Guoqing

    2017-04-15

    The selective cutting method currently used in Moso bamboo forests has resulted in a reduction of stand productivity and carbon sequestration capacity. Given the time and labor expense involved in addressing this problem manually, simulation using an ecosystem model is the most suitable approach. The BIOME-BGC model was improved to suit managed Moso bamboo forests, which was adapted to include age structure, specific ecological processes and management measures of Moso bamboo forest. A field selective cutting experiment was done in nine plots with three cutting intensities (high-intensity, moderate-intensity and low-intensity) during 2010-2013, and biomass of these plots was measured for model validation. Then four selective cutting scenarios were simulated by the improved BIOME-BGC model to optimize the selective cutting timings, intervals, retained ages and intensities. The improved model matched the observed aboveground carbon density and yield of different plots, with a range of relative error from 9.83% to 15.74%. The results of different selective cutting scenarios suggested that the optimal selective cutting measure should be cutting 30% culms of age 6, 80% culms of age 7, and all culms thereafter (above age 8) in winter every other year. The vegetation carbon density and harvested carbon density of this selective cutting method can increase by 74.63% and 21.5%, respectively, compared with the current selective cutting measure. The optimized selective cutting measure developed in this study can significantly promote carbon density, yield, and carbon sink capacity in Moso bamboo forests. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models

    Science.gov (United States)

    Hogan, Daniel R; Salomon, Joshua A; Canning, David; Hammitt, James K; Zaslavsky, Alan M; Bärnighausen, Till

    2012-01-01

    Objectives Population-based HIV testing surveys have become central to deriving estimates of national HIV prevalence in sub-Saharan Africa. However, limited participation in these surveys can lead to selection bias. We control for selection bias in national HIV prevalence estimates using a novel approach, which unlike conventional imputation can account for selection on unobserved factors. Methods For 12 Demographic and Health Surveys conducted from 2001 to 2009 (N=138 300), we predict HIV status among those missing a valid HIV test with Heckman-type selection models, which allow for correlation between infection status and participation in survey HIV testing. We compare these estimates with conventional ones and introduce a simulation procedure that incorporates regression model parameter uncertainty into confidence intervals. Results Selection model point estimates of national HIV prevalence were greater than unadjusted estimates for 10 of 12 surveys for men and 11 of 12 surveys for women, and were also greater than the majority of estimates obtained from conventional imputation, with significantly higher HIV prevalence estimates for men in Cote d'Ivoire 2005, Mali 2006 and Zambia 2007. Accounting for selective non-participation yielded 95% confidence intervals around HIV prevalence estimates that are wider than those obtained with conventional imputation by an average factor of 4.5. Conclusions Our analysis indicates that national HIV prevalence estimates for many countries in sub-Saharan African are more uncertain than previously thought, and may be underestimated in several cases, underscoring the need for increasing participation in HIV surveys. Heckman-type selection models should be included in the set of tools used for routine estimation of HIV prevalence. PMID:23172342

  17. Selective Cooperation in Early Childhood - How to Choose Models and Partners.

    Directory of Open Access Journals (Sweden)

    Jonas Hermes

    Full Text Available Cooperation is essential for human society, and children engage in cooperation from early on. It is unclear, however, how children select their partners for cooperation. We know that children choose selectively whom to learn from (e.g. preferring reliable over unreliable models on a rational basis. The present study investigated whether children (and adults also choose their cooperative partners selectively and what model characteristics they regard as important for cooperative partners and for informants about novel words. Three- and four-year-old children (N = 64 and adults (N = 14 saw contrasting pairs of models differing either in physical strength or in accuracy (in labeling known objects. Participants then performed different tasks (cooperative problem solving and word learning requiring the choice of a partner or informant. Both children and adults chose their cooperative partners selectively. Moreover they showed the same pattern of selective model choice, regarding a wide range of model characteristics as important for cooperation (preferring both the strong and the accurate model for a strength-requiring cooperation tasks, but only prior knowledge as important for word learning (preferring the knowledgeable but not the strong model for word learning tasks. Young children's selective model choice thus reveals an early rational competence: They infer characteristics from past behavior and flexibly consider what characteristics are relevant for certain tasks.

  18. Switching and optimizing control for coal flotation process based on a hybrid model

    Science.gov (United States)

    Dong, Zhiyong; Wang, Ranfeng; Fan, Minqiang; Fu, Xiang

    2017-01-01

    Flotation is an important part of coal preparation, and the flotation column is widely applied as efficient flotation equipment. This process is complex and affected by many factors, with the froth depth and reagent dosage being two of the most important and frequently manipulated variables. This paper proposes a new method of switching and optimizing control for the coal flotation process. A hybrid model is built and evaluated using industrial data. First, wavelet analysis and principal component analysis (PCA) are applied for signal pre-processing. Second, a control model for optimizing the set point of the froth depth is constructed based on fuzzy control, and a control model is designed to optimize the reagent dosages based on expert system. Finally, the least squares-support vector machine (LS-SVM) is used to identify the operating conditions of the flotation process and to select one of the two models (froth depth or reagent dosage) for subsequent operation according to the condition parameters. The hybrid model is developed and evaluated on an industrial coal flotation column and exhibits satisfactory performance. PMID:29040305

  19. Using Unified Modelling Language (UML) as a process-modelling technique for clinical-research process improvement.

    Science.gov (United States)

    Kumarapeli, P; De Lusignan, S; Ellis, T; Jones, B

    2007-03-01

    The Primary Care Data Quality programme (PCDQ) is a quality-improvement programme which processes routinely collected general practice computer data. Patient data collected from a wide range of different brands of clinical computer systems are aggregated, processed, and fed back to practices in an educational context to improve the quality of care. Process modelling is a well-established approach used to gain understanding and systematic appraisal, and identify areas of improvement of a business process. Unified modelling language (UML) is a general purpose modelling technique used for this purpose. We used UML to appraise the PCDQ process to see if the efficiency and predictability of the process could be improved. Activity analysis and thinking-aloud sessions were used to collect data to generate UML diagrams. The UML model highlighted the sequential nature of the current process as a barrier for efficiency gains. It also identified the uneven distribution of process controls, lack of symmetric communication channels, critical dependencies among processing stages, and failure to implement all the lessons learned in the piloting phase. It also suggested that improved structured reporting at each stage - especially from the pilot phase, parallel processing of data and correctly positioned process controls - should improve the efficiency and predictability of research projects. Process modelling provided a rational basis for the critical appraisal of a clinical data processing system; its potential maybe underutilized within health care.

  20. SELECTION AND PRELIMINARY EVALUATION OF ALTERNATIVE REDUCTANTS FOR SRAT PROCESSING

    Energy Technology Data Exchange (ETDEWEB)

    Stone, M.; Pickenheim, B.; Peeler, D.

    2009-06-30

    Defense Waste Processing Facility - Engineering (DWPF-E) has requested the Savannah River National Laboratory (SRNL) to perform scoping evaluations of alternative flowsheets with the primary focus on alternatives to formic acid during Chemical Process Cell (CPC) processing. The reductants shown below were selected for testing during the evaluation of alternative reductants for Sludge Receipt and Adjustment Tank (SRAT) processing. The reductants fall into two general categories: reducing acids and non-acidic reducing agents. Reducing acids were selected as direct replacements for formic acid to reduce mercury in the SRAT, to acidify the sludge, and to balance the melter REDuction/OXidation potential (REDOX). Non-acidic reductants were selected as melter reductants and would not be able to reduce mercury in the SRAT. Sugar was not tested during this scoping evaluation as previous work has already been conducted on the use of sugar with DWPF feeds. Based on the testing performed, the only viable short-term path to mitigating hydrogen generation in the CPC is replacement of formic acid with a mixture of glycolic and formic acids. An experiment using glycolic acid blended with formic on an 80:20 molar basis was able to reduce mercury, while also targeting a predicted REDuction/OXidation (REDOX) of 0.2 expressed as Fe{sup 2+}/{Sigma}Fe. Based on this result, SRNL recommends performing a complete CPC demonstration of the glycolic/formic acid flowsheet followed by a design basis development and documentation. Of the options tested recently and in the past, nitric/glycolic/formic blended acids has the potential for near term implementation in the existing CPC equipment providing rapid throughput improvement. Use of a non-acidic reductant is recommended only if the processing constraints to remove mercury and acidify the sludge acidification are eliminated. The non-acidic reductants (e.g. sugar) will not reduce mercury during CPC processing and sludge acidification would

  1. The Choice Is Yours: The Role of Cognitive Processes for IT-Supported Idea Selection

    DEFF Research Database (Denmark)

    Seeber, Isabella; Weber, Barbara; Maier, Ronald

    2018-01-01

    of selection direction and selection type. A laboratory experiment using eye-tracking will investigate variations in selection type and selection direction. Moreover, the experiment will test the effects on the decision-making process and the number and quality of ideas in a filtered set. Findings will provide......The selection of good ideas out of hundreds or even thousands has proven to be the next big challenge for organizations that conduct open idea contests for innovation. Cognitive load and attention loss hinder crowds to effectively run their idea selection process. Facilitation techniques...... for the reduction and clarification of ideas could help with such problems, but have not yet been researched in crowd settings that are prevalent in idea contests. This research-in-progress paper aims to contribute to this research gap by investigating IT-supported selection techniques that differ in terms...

  2. Developing engineering processes through integrated modelling of product and process

    DEFF Research Database (Denmark)

    Nielsen, Jeppe Bjerrum; Hvam, Lars

    2012-01-01

    This article aims at developing an operational tool for integrated modelling of product assortments and engineering processes in companies making customer specific products. Integrating a product model in the design of engineering processes will provide a deeper understanding of the engineering...... activities as well as insight into how product features affect the engineering processes. The article suggests possible ways of integrating models of products with models of engineering processes. The models have been tested and further developed in an action research study carried out in collaboration...... with a major international engineering company....

  3. Manufacturing Process Selection of Composite Bicycle’s Crank Arm using Analytical Hierarchy Process (AHP)

    Science.gov (United States)

    Luqman, M.; Rosli, M. U.; Khor, C. Y.; Zambree, Shayfull; Jahidi, H.

    2018-03-01

    Crank arm is one of the important parts in a bicycle that is an expensive product due to the high cost of material and production process. This research is aimed to investigate the potential type of manufacturing process to fabricate composite bicycle crank arm and to describe an approach based on analytical hierarchy process (AHP) that assists decision makers or manufacturing engineers in determining the most suitable process to be employed in manufacturing of composite bicycle crank arm at the early stage of the product development process to reduce the production cost. There are four types of processes were considered, namely resin transfer molding (RTM), compression molding (CM), vacuum bag molding and filament winding (FW). The analysis ranks these four types of process for its suitability in the manufacturing of bicycle crank arm based on five main selection factors and 10 sub factors. Determining the right manufacturing process was performed based on AHP process steps. Consistency test was performed to make sure the judgements are consistent during the comparison. The results indicated that the compression molding was the most appropriate manufacturing process because it has the highest value (33.6%) among the other manufacturing processes.

  4. Process selection methodology for service management in SME

    Directory of Open Access Journals (Sweden)

    Juan Luis Rubio Sánchez

    2017-09-01

    Full Text Available It is a fact that more and more companies operations lay in information and communication technologies (ICT. Traditional management models need to be adapted to this new reality. That is why some initiatives are emerging (COBIT [control objectives for information and related technology], CMMI [capability maturity model integration], ITIL [information technology infrastructure library], etc. which pretend to guide about the processes, metrics and technology management indicators most suitable. This document focuses in ITIL, that is the best representation of what has been called IT Governance. ITIL is a reference in technology services companies and in ICT departments of any company. That is due to the high level of utility provided by the organization and coverage of the processes proposed. Implantation of a management model based in ITIL processes forces companies to a relevant decision: which processes should be implemented?, which one should be the first one?, etc. The answer to this and other questions is not easy because the adoption of these processes implies an economical investment. This article shows an approach to the implementation order so we can optimize the position of the company in front of the competence in its sector, in front of similar sized companies or any other parameter we could define.

  5. Selective attention supports working memory maintenance by modulating perceptual processing of distractors.

    Science.gov (United States)

    Sreenivasan, Kartik K; Jha, Amishi P

    2007-01-01

    Selective attention has been shown to bias sensory processing in favor of relevant stimuli and against irrelevant or distracting stimuli in perceptual tasks. Increasing evidence suggests that selective attention plays an important role during working memory maintenance, possibly by biasing sensory processing in favor of to-be-remembered items. In the current study, we investigated whether selective attention may also support working memory by biasing processing against irrelevant and potentially distracting information. Event-related potentials (ERPs) were recorded while subjects (n = 22) performed a delayed-recognition task for faces and shoes. The delay period was filled with face or shoe distractors. Behavioral performance was impaired when distractors were congruent with the working memory domain (e.g., face distractor during working memory for faces) relative to when distractors were incongruent with the working memory domain (e.g., face distractor during shoe working memory). If attentional biasing against distractor processing is indeed functionally relevant in supporting working memory maintenance, perceptual processing of distractors is predicted to be attenuated when distractors are more behaviorally intrusive relative to when they are nonintrusive. As such, we predicted that perceptual processing of distracting faces, as measured by the face-sensitive N170 ERP component, would be reduced in the context of congruent (face) working memory relative to incongruent (shoe) working memory. The N170 elicited by distracting faces demonstrated reduced amplitude during congruent versus incongruent working memory. These results suggest that perceptual processing of distracting faces may be attenuated due to attentional biasing against sensory processing of distractors that are most behaviorally intrusive during working memory maintenance.

  6. Automatic extraction of process categories from process model collections

    NARCIS (Netherlands)

    Malinova, M.; Dijkman, R.M.; Mendling, J.; Lohmann, N.; Song, M.; Wohed, P.

    2014-01-01

    Many organizations build up their business process management activities in an incremental way. As a result, there is no overarching structure defined at the beginning. However, as business process modeling initiatives often yield hundreds to thousands of process models, there is a growing need for

  7. Biosphere Process Model Report

    Energy Technology Data Exchange (ETDEWEB)

    J. Schmitt

    2000-05-25

    To evaluate the postclosure performance of a potential monitored geologic repository at Yucca Mountain, a Total System Performance Assessment (TSPA) will be conducted. Nine Process Model Reports (PMRs), including this document, are being developed to summarize the technical basis for each of the process models supporting the TSPA model. These reports cover the following areas: (1) Integrated Site Model; (2) Unsaturated Zone Flow and Transport; (3) Near Field Environment; (4) Engineered Barrier System Degradation, Flow, and Transport; (5) Waste Package Degradation; (6) Waste Form Degradation; (7) Saturated Zone Flow and Transport; (8) Biosphere; and (9) Disruptive Events. Analysis/Model Reports (AMRs) contain the more detailed technical information used to support TSPA and the PMRs. The AMRs consists of data, analyses, models, software, and supporting documentation that will be used to defend the applicability of each process model for evaluating the postclosure performance of the potential Yucca Mountain repository system. This documentation will ensure the traceability of information from its source through its ultimate use in the TSPA-Site Recommendation (SR) and in the National Environmental Policy Act (NEPA) analysis processes. The objective of the Biosphere PMR is to summarize (1) the development of the biosphere model, and (2) the Biosphere Dose Conversion Factors (BDCFs) developed for use in TSPA. The Biosphere PMR does not present or summarize estimates of potential radiation doses to human receptors. Dose calculations are performed as part of TSPA and will be presented in the TSPA documentation. The biosphere model is a component of the process to evaluate postclosure repository performance and regulatory compliance for a potential monitored geologic repository at Yucca Mountain, Nevada. The biosphere model describes those exposure pathways in the biosphere by which radionuclides released from a potential repository could reach a human receptor

  8. Biosphere Process Model Report

    International Nuclear Information System (INIS)

    Schmitt, J.

    2000-01-01

    To evaluate the postclosure performance of a potential monitored geologic repository at Yucca Mountain, a Total System Performance Assessment (TSPA) will be conducted. Nine Process Model Reports (PMRs), including this document, are being developed to summarize the technical basis for each of the process models supporting the TSPA model. These reports cover the following areas: (1) Integrated Site Model; (2) Unsaturated Zone Flow and Transport; (3) Near Field Environment; (4) Engineered Barrier System Degradation, Flow, and Transport; (5) Waste Package Degradation; (6) Waste Form Degradation; (7) Saturated Zone Flow and Transport; (8) Biosphere; and (9) Disruptive Events. Analysis/Model Reports (AMRs) contain the more detailed technical information used to support TSPA and the PMRs. The AMRs consists of data, analyses, models, software, and supporting documentation that will be used to defend the applicability of each process model for evaluating the postclosure performance of the potential Yucca Mountain repository system. This documentation will ensure the traceability of information from its source through its ultimate use in the TSPA-Site Recommendation (SR) and in the National Environmental Policy Act (NEPA) analysis processes. The objective of the Biosphere PMR is to summarize (1) the development of the biosphere model, and (2) the Biosphere Dose Conversion Factors (BDCFs) developed for use in TSPA. The Biosphere PMR does not present or summarize estimates of potential radiation doses to human receptors. Dose calculations are performed as part of TSPA and will be presented in the TSPA documentation. The biosphere model is a component of the process to evaluate postclosure repository performance and regulatory compliance for a potential monitored geologic repository at Yucca Mountain, Nevada. The biosphere model describes those exposure pathways in the biosphere by which radionuclides released from a potential repository could reach a human receptor

  9. Action video games and improved attentional control: Disentangling selection- and response-based processes.

    Science.gov (United States)

    Chisholm, Joseph D; Kingstone, Alan

    2015-10-01

    Research has demonstrated that experience with action video games is associated with improvements in a host of cognitive tasks. Evidence from paradigms that assess aspects of attention has suggested that action video game players (AVGPs) possess greater control over the allocation of attentional resources than do non-video-game players (NVGPs). Using a compound search task that teased apart selection- and response-based processes (Duncan, 1985), we required participants to perform an oculomotor capture task in which they made saccades to a uniquely colored target (selection-based process) and then produced a manual directional response based on information within the target (response-based process). We replicated the finding that AVGPs are less susceptible to attentional distraction and, critically, revealed that AVGPs outperform NVGPs on both selection-based and response-based processes. These results not only are consistent with the improved-attentional-control account of AVGP benefits, but they suggest that the benefit of action video game playing extends across the full breadth of attention-mediated stimulus-response processes that impact human performance.

  10. Conceptual models of information processing

    Science.gov (United States)

    Stewart, L. J.

    1983-01-01

    The conceptual information processing issues are examined. Human information processing is defined as an active cognitive process that is analogous to a system. It is the flow and transformation of information within a human. The human is viewed as an active information seeker who is constantly receiving, processing, and acting upon the surrounding environmental stimuli. Human information processing models are conceptual representations of cognitive behaviors. Models of information processing are useful in representing the different theoretical positions and in attempting to define the limits and capabilities of human memory. It is concluded that an understanding of conceptual human information processing models and their applications to systems design leads to a better human factors approach.

  11. Nursing documentation: experience of the use of the nursing process model in selected hospitals in Ibadan, Oyo State, Nigeria.

    Science.gov (United States)

    Ofi, Bola; Sowunmi, Olanrewaju

    2012-08-01

    The descriptive study was conducted to determine the extent of utilization of the nursing process for documentation of nursing care in three selected hospitals, Ibadan, Nigeria. One hundred fifty nurses and 115 discharged clients' records were selected from the hospitals. Questionnaires and checklists were used to collect data. Utilization of nursing process for care was 100%, 73.6% and 34.8% in the three hospitals. Nurses encountered difficulties in history taking, formulation of nursing diagnoses, objectives, nursing orders and evaluation. Most nurses disagreed or were undecided with the use of authorized abbreviations and symbols (34.3%, 40.3% and 69.5%), recording errors that occurred during care (37.1%, 56.1% and 52.2%) and inclusion of change in clients' condition (54.3%, 56.1% and 73.8%). Most nurses appreciated the significance of documentation. Lack of time, knowledge and need for extensive writing are the major barriers against documentation. Seventy-seven point four per cent of the 115 clients' records from one hospital showed evidence of documentation, no evidence from the other two. Study findings have implications for continuing professional education, practice and supervision. © 2012 Blackwell Publishing Asia Pty Ltd.

  12. The iFlow modelling framework v2.4: a modular idealized process-based model for flow and transport in estuaries

    Directory of Open Access Journals (Sweden)

    Y. M. Dijkstra

    2017-07-01

    Full Text Available The iFlow modelling framework is a width-averaged model for the systematic analysis of the water motion and sediment transport processes in estuaries and tidal rivers. The distinctive solution method, a mathematical perturbation method, used in the model allows for identification of the effect of individual physical processes on the water motion and sediment transport and study of the sensitivity of these processes to model parameters. This distinction between processes provides a unique tool for interpreting and explaining hydrodynamic interactions and sediment trapping. iFlow also includes a large number of options to configure the model geometry and multiple choices of turbulence and salinity models. Additionally, the model contains auxiliary components, including one that facilitates easy and fast sensitivity studies. iFlow has a modular structure, which makes it easy to include, exclude or change individual model components, called modules. Depending on the required functionality for the application at hand, modules can be selected to construct anything from very simple quasi-linear models to rather complex models involving multiple non-linear interactions. This way, the model complexity can be adjusted to the application. Once the modules containing the required functionality are selected, the underlying model structure automatically ensures modules are called in the correct order. The model inserts iteration loops over groups of modules that are mutually dependent. iFlow also ensures a smooth coupling of modules using analytical and numerical solution methods. This way the model combines the speed and accuracy of analytical solutions with the versatility of numerical solution methods. In this paper we present the modular structure, solution method and two examples of the use of iFlow. In the examples we present two case studies, of the Yangtze and Scheldt rivers, demonstrating how iFlow facilitates the analysis of model results, the

  13. Customer Order Decoupling Point Selection Model in Mass Customization Based on MAS

    Institute of Scientific and Technical Information of China (English)

    XU Xuanguo; LI Xiangyang

    2006-01-01

    Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration. Literatures on mass customization have been focused on mechanism of MC, but little on customer order decoupling point selection. The aim of this paper is to present a model for customer order decoupling point selection of domain knowledge interactions between enterprises and customers in mass customization. Based on the analysis of other researchers' achievements combining the demand problems of customer and enterprise, a model of group decision for customer order decoupling point selection is constructed based on quality function deployment and multi-agent system. Considering relatively the decision makers of independent functional departments as independent decision agents, a decision agent set is added as the third dimensionality to house of quality, the cubic quality function deployment is formed. The decision-making can be consisted of two procedures: the first one is to build each plane house of quality in various functional departments to express each opinions; the other is to evaluate and gather the foregoing sub-decisions by a new plane quality function deployment. Thus, department decision-making can well use its domain knowledge by ontology, and total decision-making can keep simple by avoiding too many customer requirements.

  14. Book Selection, Collection Development, and Bounded Rationality.

    Science.gov (United States)

    Schwartz, Charles A.

    1989-01-01

    Reviews previously proposed schemes of classical rationality in book selection, describes new approaches to rational choice behavior, and presents a model of book selection based on bounded rationality in a garbage can decision process. The role of tacit knowledge and symbolic content in the selection process are also discussed. (102 references)…

  15. An Empirical Study of Wrappers for Feature Subset Selection based on a Parallel Genetic Algorithm: The Multi-Wrapper Model

    KAUST Repository

    Soufan, Othman

    2012-09-01

    Feature selection is the first task of any learning approach that is applied in major fields of biomedical, bioinformatics, robotics, natural language processing and social networking. In feature subset selection problem, a search methodology with a proper criterion seeks to find the best subset of features describing data (relevance) and achieving better performance (optimality). Wrapper approaches are feature selection methods which are wrapped around a classification algorithm and use a performance measure to select the best subset of features. We analyze the proper design of the objective function for the wrapper approach and highlight an objective based on several classification algorithms. We compare the wrapper approaches to different feature selection methods based on distance and information based criteria. Significant improvement in performance, computational time, and selection of minimally sized feature subsets is achieved by combining different objectives for the wrapper model. In addition, considering various classification methods in the feature selection process could lead to a global solution of desirable characteristics.

  16. Variable selection for mixture and promotion time cure rate models.

    Science.gov (United States)

    Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng

    2016-11-16

    Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.

  17. Attribute Based Selection of Thermoplastic Resin for Vacuum Infusion Process: A Decision Making Methodology

    DEFF Research Database (Denmark)

    Raghavalu Thirumalai, Durai Prabhakaran; Lystrup, Aage; Løgstrup Andersen, Tom

    2012-01-01

    The composite industry looks toward a new material system (resins) based on thermoplastic polymers for the vacuum infusion process, similar to the infusion process using thermosetting polymers. A large number of thermoplastics are available in the market with a variety of properties suitable...... be beneficial. In this paper, the authors introduce a new decision making tool for resin selection based on significant attributes. This article provides a broad overview of suitable thermoplastic material systems for vacuum infusion process available in today’s market. An illustrative example—resin selection...... for vacuum infused of a wind turbine blade—is shown to demonstrate the intricacies involved in the proposed methodology for resin selection....

  18. Model structure selection in convolutive mixtures

    DEFF Research Database (Denmark)

    Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

    2006-01-01

    The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: ’Are we actually dealing with a convolutive mixture?’. We try to answer this question for EEG data....

  19. 48 CFR 636.602-5 - Short selection processes for contracts not to exceed the simplified acquisition threshold.

    Science.gov (United States)

    2010-10-01

    ... 48 Federal Acquisition Regulations System 4 2010-10-01 2010-10-01 false Short selection processes... ARCHITECT-ENGINEER CONTRACTS Architect-Engineer Services 636.602-5 Short selection processes for contracts not to exceed the simplified acquisition threshold. The short selection process described in FAR 36...

  20. Improved model management with aggregated business process models

    NARCIS (Netherlands)

    Reijers, H.A.; Mans, R.S.; Toorn, van der R.A.

    2009-01-01

    Contemporary organizations invest much efforts in creating models of their business processes. This raises the issue of how to deal with large sets of process models that become available over time. This paper proposes an extension of Event-driven Process Chains, called the aggregate EPC (aEPC),

  1. Friendship Selection and Influence Processes for Physical Aggression and Prosociality: Differences between Single-Sex and Mixed-Sex Contexts.

    Science.gov (United States)

    Dijkstra, Jan Kornelis; Berger, Christian

    2018-01-01

    The present study examined to what extent selection and influence processes for physical aggression and prosociality in friendship networks differed between sex-specific contexts (i.e., all-male, all-female, and mixed-sex classrooms), while controlling for perceived popularity. Whereas selection processes reflect how behaviors shape friendships, influence processes reveal the reversed pattern by indicating how friends affect individual behaviors. Data were derived from a longitudinal sample of early adolescents from Chile. Four all-male classrooms ( n  = 150 male adolescents), four all-female classrooms ( n  = 190 female adolescents), and eight mixed-sex classrooms ( n  = 272 students) were followed one year from grades 5 to 6 ( M age  = 13). Analyses were conducted by means of stochastic-actor-based modeling as implemented in RSIENA. Although it was expected that selection and influence effects for physical aggression and prosociality would vary by context, these effects showed remarkably similar trends across all-male, all-female, and mixed-sex classrooms, with physical aggression reducing and with prosociality increasing the number of nominations received as best friend in all-male and particularly all-female classrooms. Further, perceived popularity increased the number of friendship nominations received in all contexts. Influence processes were only found for perceived popularity, but not for physical aggression and prosociality in any of the three contexts. Together, these findings highlight the importance of both behaviors for friendship selection independent of sex-specific contexts, attenuating the implications of these gendered behaviors for peer relations.

  2. Determining Selection across Heterogeneous Landscapes: A Perturbation-Based Method and Its Application to Modeling Evolution in Space.

    Science.gov (United States)

    Wickman, Jonas; Diehl, Sebastian; Blasius, Bernd; Klausmeier, Christopher A; Ryabov, Alexey B; Brännström, Åke

    2017-04-01

    Spatial structure can decisively influence the way evolutionary processes unfold. To date, several methods have been used to study evolution in spatial systems, including population genetics, quantitative genetics, moment-closure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply both in continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very efficient and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

  3. Otolaryngology residency selection process. Medical student perspective.

    Science.gov (United States)

    Stringer, S P; Cassisi, N J; Slattery, W H

    1992-04-01

    In an effort to improve the otolaryngology matching process at the University of Florida, Gainesville, we sought to obtain the medical student's perspective of the current system. All students who interviewed here over a 3-year period were surveyed regarding the application, interview, and ranking process. In addition, suggestions for improving the system were sought from the students. The application and interviewing patterns of the students surveyed were found to be similar to those of the entire otolaryngology residency applicant pool. We were unable to identify any factors that influence a student's rank list that could be prospectively used to help select applicants for interview. A variety of suggestions for improvements in the match were received, several of which could easily be instituted. A uniform interview invitation date as requested by the students could be rapidly implemented and would provide benefits for both the students and the residency programs.

  4. The effect of addition of selected carrageenans on viscoelastic properties of model processed cheese spreads

    Directory of Open Access Journals (Sweden)

    Michaela Černíková

    2007-01-01

    Full Text Available The effect of 0.25% w/w κ-carrageenan and ι‑carrageenan on viscoelastic properties of processed cheese were studied using model samples containing 40% w/w dry matter and 45 and 50% w/w fat in dry matter. Experimental samples of processed cheese were evaluated after 14 days of storage at the temperature of 6 ± 2 °C. Basic parameters of processed cheese samples under study (i.e. their dry matter content and pH were not different (P ≥ 0.05. There were no statistically significant differences in values of storage modulus G´ [Pa], loss modulus G'' [Pa] and tangent of phase shift angle tan δ [-] for the reference frequency of 1 Hz between processed cheese with κ‑carrageenan applied in the form of powder and in the form of aqueous dispersion (P ≥ 0.05. The addition of 0.25% w/w κ‑carrageenan and ι‑carrageenan (in the powder form resulted in an increase in storage (G´ and loss (G'' moduli and a decrease in values of tan δ (P < 0.05. As compared with control (i.e. without added carrageenans, samples of processed cheese became firmer. Iota-carrageenan added in the powder form in concentration of 0.25% w/w showed a more intensive effect on the increase in firmness of processed cheese under study than κ‑carrageenan (P < 0.05.

  5. Business process modeling in healthcare.

    Science.gov (United States)

    Ruiz, Francisco; Garcia, Felix; Calahorra, Luis; Llorente, César; Gonçalves, Luis; Daniel, Christel; Blobel, Bernd

    2012-01-01

    The importance of the process point of view is not restricted to a specific enterprise sector. In the field of health, as a result of the nature of the service offered, health institutions' processes are also the basis for decision making which is focused on achieving their objective of providing quality medical assistance. In this chapter the application of business process modelling - using the Business Process Modelling Notation (BPMN) standard is described. Main challenges of business process modelling in healthcare are the definition of healthcare processes, the multi-disciplinary nature of healthcare, the flexibility and variability of the activities involved in health care processes, the need of interoperability between multiple information systems, and the continuous updating of scientific knowledge in healthcare.

  6. Diversified models for portfolio selection based on uncertain semivariance

    Science.gov (United States)

    Chen, Lin; Peng, Jin; Zhang, Bo; Rosyida, Isnaini

    2017-02-01

    Since the financial markets are complex, sometimes the future security returns are represented mainly based on experts' estimations due to lack of historical data. This paper proposes a semivariance method for diversified portfolio selection, in which the security returns are given subjective to experts' estimations and depicted as uncertain variables. In the paper, three properties of the semivariance of uncertain variables are verified. Based on the concept of semivariance of uncertain variables, two types of mean-semivariance diversified models for uncertain portfolio selection are proposed. Since the models are complex, a hybrid intelligent algorithm which is based on 99-method and genetic algorithm is designed to solve the models. In this hybrid intelligent algorithm, 99-method is applied to compute the expected value and semivariance of uncertain variables, and genetic algorithm is employed to seek the best allocation plan for portfolio selection. At last, several numerical examples are presented to illustrate the modelling idea and the effectiveness of the algorithm.

  7. 48 CFR 36.602-5 - Short selection process for contracts not to exceed the simplified acquisition threshold.

    Science.gov (United States)

    2010-10-01

    ... 48 Federal Acquisition Regulations System 1 2010-10-01 2010-10-01 false Short selection process... AND ARCHITECT-ENGINEER CONTRACTS Architect-Engineer Services 36.602-5 Short selection process for... of the short processes described in this subsection may be used to select firms for contracts not...

  8. Model-Based Integrated Process Design and Controller Design of Chemical Processes

    DEFF Research Database (Denmark)

    Abd Hamid, Mohd Kamaruddin Bin

    that is typically formulated as a mathematical programming (optimization with constraints) problem is solved by the so-called reverse approach by decomposing it into four sequential hierarchical sub-problems: (i) pre-analysis, (ii) design analysis, (iii) controller design analysis, and (iv) final selection......This thesis describes the development and application of a new systematic modelbased methodology for performing integrated process design and controller design (IPDC) of chemical processes. The new methodology is simple to apply, easy to visualize and efficient to solve. Here, the IPDC problem...... are ordered according to the defined performance criteria (objective function). The final selected design is then verified through rigorous simulation. In the pre-analysis sub-problem, the concepts of attainable region and driving force are used to locate the optimal process-controller design solution...

  9. Selecting university undergraduate student activities via compromised-analytical hierarchy process and 0-1 integer programming to maximize SETARA points

    Science.gov (United States)

    Nazri, Engku Muhammad; Yusof, Nur Ai'Syah; Ahmad, Norazura; Shariffuddin, Mohd Dino Khairri; Khan, Shazida Jan Mohd

    2017-11-01

    Prioritizing and making decisions on what student activities to be selected and conducted to fulfill the aspiration of a university as translated in its strategic plan must be executed with transparency and accountability. It is becoming even more crucial, particularly for universities in Malaysia with the recent budget cut imposed by the Malaysian government. In this paper, we illustrated how 0-1 integer programming (0-1 IP) model was implemented to select which activities among the forty activities proposed by the student body of Universiti Utara Malaysia (UUM) to be implemented for the 2017/2018 academic year. Two different models were constructed. The first model was developed to determine the minimum total budget that should be given to the student body by the UUM management to conduct all the activities that can fulfill the minimum targeted number of activities as stated in its strategic plan. On the other hand, the second model was developed to determine which activities to be selected based on the total budget already allocated beforehand by the UUM management towards fulfilling the requirements as set in its strategic plan. The selection of activities for the second model, was also based on the preference of the members of the student body whereby the preference value for each activity was determined using Compromised-Analytical Hierarchy Process. The outputs from both models were compared and discussed. The technique used in this study will be useful and suitable to be implemented by organizations with key performance indicator-oriented programs and having limited budget allocation issues.

  10. Enhanced Fuzzy-OWA model for municipal solid waste landfill site selection

    Science.gov (United States)

    Ahmad, Siti Zubaidah; Ahamad, Mohd Sanusi S.; Yusoff, Mohd Suffian; Abujayyab, Sohaib K. M.

    2017-10-01

    In Malaysia, the municipal solid waste landfill site is an essential facility that needs to be evaluated as its demand is infrequently getting higher. The increment of waste generation forces the government to cater the appropriate site for waste disposal. However, the selection process for new landfill sites is a difficult task with regard to land scarcity and time consumption. In addition, the complication will proliferate when there are various criteria to be considered. Therefore, this paper intends to show the significance of the fuzzy logic-ordered weighted average (Fuzzy-OWA) model for the landfill site suitability analysis. The model was developed to generalize the multi-criteria combination that was extended to the GIS applications as part of the decision support module. OWA has the capability to implement different combination operators through the selection of appropriate order weight that is possible in changing the form of aggregation such as minimum, intermediate and maximum types of combination. OWA give six forms of aggregation results that have their specific significance that indirectly evaluates the environmental, physical and socio-economic (EPSE) criteria respectively. Nevertheless, one of the aggregated results has shown similarity with the weighted linear combination (WLC) method.

  11. An Integrated Model for Supplier Selection for a High-Tech Manufacturer

    Science.gov (United States)

    Lee, Amy H. I.; Kang, He-Yau; Lin, Chun-Yu

    2011-11-01

    Global competitiveness has become the biggest concern of manufacturing companies, especially in high-tech industries. Improving competitive edges in an environment with rapidly changing technological innovations and dynamic customer needs is essential for a firm to survive and to acquire a decent profit. Thus, the introduction of successful new products is a source of new sales and profits and is a necessity in the intense competitive international market. After a product is developed, a firm needs the cooperation of upstream suppliers to provide satisfactory components and parts for manufacturing final products. Therefore, the selection of suitable suppliers has also become a very important decision. In this study, an analytical approach is proposed to select the most appropriate critical-part suppliers in order to maintain a high reliability of the supply chain. A fuzzy analytic network process (FANP) model, which incorporates the benefits, opportunities, costs and risks (BOCR) concept, is constructed to evaluate various aspects of suppliers. The proposed model is adopted in a TFT-LCD manufacturer in Taiwan in evaluating the expected performance of suppliers with respect to each important factor, and an overall ranking of the suppliers can be generated as a result.

  12. Engineering development of selective agglomeration: Task 5, Bench- scale process testing

    Energy Technology Data Exchange (ETDEWEB)

    1991-09-01

    Under the overall objectives of DOE Contract ``Engineering Development of Selective Agglomeration,`` there were a number of specific objectives in the Task 5 program. The prime objectives of Task 5 are highlighted below: (1) Maximize process performance in pyritic sulfur rejection and BTU recovery, (2) Produce a low ash product, (3) Compare the performance of the heavy agglomerant process based on diesel and the light agglomerant process using heptane, (4) Define optimum processing conditions for engineering design, (5) Provide first-level evaluation of product handleability, and (6) Explore and investigate process options/ideas which may enhance process performance and/or product handleability.

  13. Optimization of the selection process of the co-substrates for chicken manure fermentation using neural modeling

    Directory of Open Access Journals (Sweden)

    Lewicki Andrzej

    2016-01-01

    Full Text Available Intense development of research equipment leads directly to increasing cognitive abilities. However, along with the raising amount of data generated, the development of the techniques allowing the analysis is also essential. Currently, one of the most dynamically developing branch of computer science and mathematics are the Artificial Neural Networks (ANN. Their main advantage is very high ability to solve the regression and approximation issues. This paper presents the possibility of application of artificial intelligence methods to optimize the selection of co-substrates intended for methane fermentation of chicken manure. 4-layer MLP network has proven to be the optimal structure modeling the obtained empirical data.

  14. High-temperature experimental and thermodynamic modelling research on the pyrometallurgical processing of copper

    Science.gov (United States)

    Hidayat, Taufiq; Shishin, Denis; Decterov, Sergei A.; Hayes, Peter C.; Jak, Evgueni

    2017-01-01

    Uncertainty in the metal price and competition between producers mean that the daily operation of a smelter needs to target high recovery of valuable elements at low operating cost. Options for the improvement of the plant operation can be examined and decision making can be informed based on accurate information from laboratory experimentation coupled with predictions using advanced thermodynamic models. Integrated high-temperature experimental and thermodynamic modelling research on phase equilibria and thermodynamics of copper-containing systems have been undertaken at the Pyrometallurgy Innovation Centre (PYROSEARCH). The experimental phase equilibria studies involve high-temperature equilibration, rapid quenching and direct measurement of phase compositions using electron probe X-ray microanalysis (EPMA). The thermodynamic modelling deals with the development of accurate thermodynamic database built through critical evaluation of experimental data, selection of solution models, and optimization of models parameters. The database covers the Al-Ca-Cu-Fe-Mg-O-S-Si chemical system. The gas, slag, matte, liquid and solid metal phases, spinel solid solution as well as numerous solid oxide and sulphide phases are included. The database works within the FactSage software environment. Examples of phase equilibria data and thermodynamic models of selected systems, as well as possible implementation of the research outcomes to selected copper making processes are presented.

  15. Integrating textual and model-based process descriptions for comprehensive process search

    NARCIS (Netherlands)

    Leopold, Henrik; van der Aa, Han; Pittke, Fabian; Raffel, Manuel; Mendling, Jan; Reijers, Hajo A.

    2016-01-01

    Documenting business processes using process models is common practice in many organizations. However, not all process information is best captured in process models. Hence, many organizations complement these models with textual descriptions that specify additional details. The problem with this

  16. Selected papers on noise and stochastic processes

    CERN Document Server

    1954-01-01

    Six classic papers on stochastic process, selected to meet the needs of physicists, applied mathematicians, and engineers. Contents: 1.Chandrasekhar, S.: Stochastic Problems in Physics and Astronomy. 2. Uhlenbeck, G. E. and Ornstein, L. S.: On the Theory of the Browninan Motion. 3. Ming Chen Wang and Uhlenbeck, G. E.: On the Theory of the Browninan Motion II. 4. Rice, S. O.: Mathematical Analysis of Random Noise. 5. Kac, Mark: Random Walk and the Theory of Brownian Motion. 6. Doob, J. L.: The Brownian Movement and Stochastic Equations. Unabridged republication of the Dover reprint (1954). Pre

  17. Reduced auditory processing capacity during vocalization in children with Selective Mutism.

    Science.gov (United States)

    Arie, Miri; Henkin, Yael; Lamy, Dominique; Tetin-Schneider, Simona; Apter, Alan; Sadeh, Avi; Bar-Haim, Yair

    2007-02-01

    Because abnormal Auditory Efferent Activity (AEA) is associated with auditory distortions during vocalization, we tested whether auditory processing is impaired during vocalization in children with Selective Mutism (SM). Participants were children with SM and abnormal AEA, children with SM and normal AEA, and normally speaking controls, who had to detect aurally presented target words embedded within word lists under two conditions: silence (single task), and while vocalizing (dual task). To ascertain specificity of auditory-vocal deficit, effects of concurrent vocalizing were also examined during a visual task. Children with SM and abnormal AEA showed impaired auditory processing during vocalization relative to children with SM and normal AEA, and relative to control children. This impairment is specific to the auditory modality and does not reflect difficulties in dual task per se. The data extends previous findings suggesting that deficient auditory processing is involved in speech selectivity in SM.

  18. Fisher-Wright model with deterministic seed bank and selection.

    Science.gov (United States)

    Koopmann, Bendix; Müller, Johannes; Tellier, Aurélien; Živković, Daniel

    2017-04-01

    Seed banks are common characteristics to many plant species, which allow storage of genetic diversity in the soil as dormant seeds for various periods of time. We investigate an above-ground population following a Fisher-Wright model with selection coupled with a deterministic seed bank assuming the length of the seed bank is kept constant and the number of seeds is large. To assess the combined impact of seed banks and selection on genetic diversity, we derive a general diffusion model. The applied techniques outline a path of approximating a stochastic delay differential equation by an appropriately rescaled stochastic differential equation. We compute the equilibrium solution of the site-frequency spectrum and derive the times to fixation of an allele with and without selection. Finally, it is demonstrated that seed banks enhance the effect of selection onto the site-frequency spectrum while slowing down the time until the mutation-selection equilibrium is reached. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. The Selection of Materials for Roller Chains From The Perspective Of Manufacturing Process

    Directory of Open Access Journals (Sweden)

    Rahmat Saptono

    2010-10-01

    Full Text Available The selection of materials for an engineering component is not only requested by its design function and shape, but also the sequence through which it is manufactured. The manufacturing operation of roller chains involves drawing and trimming processes aimed at producing semi-finished chain drives component with a well-standardized dimension. In addition to final combination of properties required by design constraints, the ability of materials to be formed into a desired shape and geometry without failure is also critical. The objective of materials selection should therefore involve additional attributes that are not typically  accommodated by the standard procedure of materials selection. The present paper deals with the selection of materials for roller chains from the perspective of manufacturing process. Ears and un-uniform wall thickness have been identified as a key problem in the mass production of component. Provided all process parameters were established, the  anisotropy factor of materials is critical. Simulative test can be reasonably used to obtain material performance indices that can be added up to the standard procedure of material selection. Of three commercially available steel grades evaluated with regard to the criteria defined, one grade is more suitable for the present objective.

  20. An application of locally linear model tree algorithm with combination of feature selection in credit scoring

    Science.gov (United States)

    Siami, Mohammad; Gholamian, Mohammad Reza; Basiri, Javad

    2014-10-01

    Nowadays, credit scoring is one of the most important topics in the banking sector. Credit scoring models have been widely used to facilitate the process of credit assessing. In this paper, an application of the locally linear model tree algorithm (LOLIMOT) was experimented to evaluate the superiority of its performance to predict the customer's credit status. The algorithm is improved with an aim of adjustment by credit scoring domain by means of data fusion and feature selection techniques. Two real world credit data sets - Australian and German - from UCI machine learning database were selected to demonstrate the performance of our new classifier. The analytical results indicate that the improved LOLIMOT significantly increase the prediction accuracy.

  1. A BAYESIAN NONPARAMETRIC MIXTURE MODEL FOR SELECTING GENES AND GENE SUBNETWORKS.

    Science.gov (United States)

    Zhao, Yize; Kang, Jian; Yu, Tianwei

    2014-06-01

    It is very challenging to select informative features from tens of thousands of measured features in high-throughput data analysis. Recently, several parametric/regression models have been developed utilizing the gene network information to select genes or pathways strongly associated with a clinical/biological outcome. Alternatively, in this paper, we propose a nonparametric Bayesian model for gene selection incorporating network information. In addition to identifying genes that have a strong association with a clinical outcome, our model can select genes with particular expressional behavior, in which case the regression models are not directly applicable. We show that our proposed model is equivalent to an infinity mixture model for which we develop a posterior computation algorithm based on Markov chain Monte Carlo (MCMC) methods. We also propose two fast computing algorithms that approximate the posterior simulation with good accuracy but relatively low computational cost. We illustrate our methods on simulation studies and the analysis of Spellman yeast cell cycle microarray data.

  2. Multiscale Model Selection for High-Frequency Financial Data of a Large Tick Stock by Means of the Jensen–Shannon Metric

    Directory of Open Access Journals (Sweden)

    Gianbiagio Curato

    2014-01-01

    Full Text Available Modeling financial time series at different time scales is still an open challenge. The choice of a suitable indicator quantifying the distance between the model and the data is therefore of fundamental importance for selecting models. In this paper, we propose a multiscale model selection method based on the Jensen–Shannon distance in order to select the model that is able to better reproduce the distribution of price changes at different time scales. Specifically, we consider the problem of modeling the ultra high frequency dynamics of an asset with a large tick-to-price ratio. We study the price process at different time scales and compute the Jensen–Shannon distance between the original dataset and different models, showing that the coupling between spread and returns is important to model return distribution at different time scales of observation, ranging from the scale of single transactions to the daily time scale.

  3. Selection of climate change scenario data for impact modelling

    DEFF Research Database (Denmark)

    Sloth Madsen, M; Fox Maule, C; MacKellar, N

    2012-01-01

    Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study...... illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make...... the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented...

  4. THM-coupled modeling of selected processes in argillaceous rock relevant to rock mechanics

    International Nuclear Information System (INIS)

    Czaikowski, Oliver

    2012-01-01

    Scientific investigations in European countries other than Germany concentrate not only on granite formations (Switzerland, Sweden) but also on argillaceous rock formations (France, Switzerland, Belgium) to assess their suitability as host and barrier rock for the final storage of radioactive waste. In Germany, rock salt has been under thorough study as a host rock over the past few decades. According to a study by the German Federal Institute for Geosciences and Natural Resources, however, not only salt deposits but also argillaceous rock deposits are available at relevant depths and of extensions in space which make final storage of high-level radioactive waste basically possible in Germany. Equally qualified findings about the suitability/unsuitability of non-saline rock formations require fundamental studies to be conducted nationally because of the comparatively low level of knowledge. The article presents basic analyses of coupled mechanical and hydraulic properties of argillaceous rock formations as host rock for a repository. The interaction of various processes is explained on the basis of knowledge derived from laboratory studies, and open problems are deduced. For modeling coupled processes, a simplified analytical computation method is proposed and compared with the results of numerical simulations, and the limits to its application are outlined. (orig.)

  5. Experimental Analysis and Process Modeling of Carbon Dioxide Removal Using Tuff

    Directory of Open Access Journals (Sweden)

    Emanuele Bonamente

    2016-12-01

    Full Text Available Removal of carbon dioxide via selective adsorption is a key process to obtain consumer-grade natural gas from biogas and, more generally, CO2 capture and sequestration from gaseous mixtures. The aim of this work is the characterization and classification of a natural alternative to synthetic zeolites that could be used as a carbon dioxide adsorbent. Tuff particulate, easily available as a byproduct of the construction industry, was tested with different laboratory procedures to verify its suitability for CO2 removal applications. Relevant physical and adsorption properties were measured during an intensive experimental campaign. Porosity, pore size distribution, and specific surface area were obtained with mercury intrusion porosimetry. Adsorption isotherms and saturation curves were obtained using two custom experimental apparatuses. The selective adsorption was finally modeled using an original phenomenological parameterization, and a simplified simulation of the process was performed using a computational fluid dynamic approach, validated against observed data. Results show that natural zeolites represent a very promising and sustainable alternative to synthetic zeolites in pressure swing adsorption processes for CO2 removal.

  6. Neural pathways in processing of sexual arousal: a dynamic causal modeling study.

    Science.gov (United States)

    Seok, J-W; Park, M-S; Sohn, J-H

    2016-09-01

    Three decades of research have investigated brain processing of visual sexual stimuli with neuroimaging methods. These researchers have found that sexual arousal stimuli elicit activity in a broad neural network of cortical and subcortical brain areas that are known to be associated with cognitive, emotional, motivational and physiological components. However, it is not completely understood how these neural systems integrate and modulated incoming information. Therefore, we identify cerebral areas whose activations were correlated with sexual arousal using event-related functional magnetic resonance imaging and used the dynamic causal modeling method for searching the effective connectivity about the sexual arousal processing network. Thirteen heterosexual males were scanned while they passively viewed alternating short trials of erotic and neutral pictures on a monitor. We created a subset of seven models based on our results and previous studies and selected a dominant connectivity model. Consequently, we suggest a dynamic causal model of the brain processes mediating the cognitive, emotional, motivational and physiological factors of human male sexual arousal. These findings are significant implications for the neuropsychology of male sexuality.

  7. Research and Application of a Novel Hybrid Model Based on Data Selection and Artificial Intelligence Algorithm for Short Term Load Forecasting

    Directory of Open Access Journals (Sweden)

    Wendong Yang

    2017-01-01

    Full Text Available Machine learning plays a vital role in several modern economic and industrial fields, and selecting an optimized machine learning method to improve time series’ forecasting accuracy is challenging. Advanced machine learning methods, e.g., the support vector regression (SVR model, are widely employed in forecasting fields, but the individual SVR pays no attention to the significance of data selection, signal processing and optimization, which cannot always satisfy the requirements of time series forecasting. By preprocessing and analyzing the original time series, in this paper, a hybrid SVR model is developed, considering periodicity, trend and randomness, and combined with data selection, signal processing and an optimization algorithm for short-term load forecasting. Case studies of electricity power data from New South Wales and Singapore are regarded as exemplifications to estimate the performance of the developed novel model. The experimental results demonstrate that the proposed hybrid method is not only robust but also capable of achieving significant improvement compared with the traditional single models and can be an effective and efficient tool for power load forecasting.

  8. Selection of a reference process for treatment of the West Valley alkaline waste

    International Nuclear Information System (INIS)

    Holton, L.K.; Wise, B.M.; Bray, L.A.; Pope, J.M.; Carl, D.E.

    1984-08-01

    As part of the West Valley Demonstration Project (WVDP) the alkaline PUREX supernatant stored in Tank 8D2 will be partially decontaminated by the removal of radiocesium. Four processes for removal of radiocesium from the alkaline supernatant were studied through experimentation and engineering analysis to identify a reference approach for the WVDP. These processes included the use of a zeolite inorganic ion-exchanger (Linde Ionsiv IE-95), an organic ion exchange resin (Duolite CS-100), and two precipitation processes; one using sodium tetraphenylboron (NaTPB) and the other using phosphotungstic acid (PTA). Based upon process performance, safety and environmental considerations, process and equipment complexity and impacts to the waste vitrification system, the zeolite ion-exchange process has been selected by West Valley Nuclear Services, Inc., as the reference supernatant treatment process for the WVDP. This paper will summarize the technical basis for the selection of the zeolite ion-exchange process. 4 figures, 2 tables

  9. A model selection support system for numerical simulations of nuclear thermal-hydraulics

    International Nuclear Information System (INIS)

    Gofuku, Akio; Shimizu, Kenji; Sugano, Keiji; Yoshikawa, Hidekazu; Wakabayashi, Jiro

    1990-01-01

    In order to execute efficiently a dynamic simulation of a large-scaled engineering system such as a nuclear power plant, it is necessary to develop intelligent simulation support system for all phases of the simulation. This study is concerned with the intelligent support for the program development phase and is engaged in the adequate model selection support method by applying AI (Artificial Intelligence) techniques to execute a simulation consistent with its purpose and conditions. A proto-type expert system to support the model selection for numerical simulations of nuclear thermal-hydraulics in the case of cold leg small break loss-of-coolant accident of PWR plant is now under development on a personal computer. The steps to support the selection of both fluid model and constitutive equations for the drift flux model have been developed. Several cases of model selection were carried out and reasonable model selection results were obtained. (author)

  10. Effect of processing on iodine content of some selected plants food ...

    African Journals Online (AJOL)

    Effect of processing on iodine content of some selected plants food was investigated. Results show significant reduction (p < 0.05) in the iodine content of the processed food compared with the raw forms. The iodine value of 658.60 ± 17.2 ìg/100g observed in raw edible portion of Discorea rotundata was significantly higher ...

  11. Modeling Directional Selectivity Using Self-Organizing Delay-Aadaptation Maps

    OpenAIRE

    Tversky, Mr. Tal; Miikkulainen, Dr. Risto

    2002-01-01

    Using a delay adaptation learning rule, we model the activity-dependent development of directionally selective cells in the primary visual cortex. Based on input stimuli, a learning rule shifts delays to create synchronous arrival of spikes at cortical cells. As a result, delays become tuned creating a smooth cortical map of direction selectivity. This result demonstrates how delay adaption can serve as a powerful abstraction for modeling temporal learning in the brain.

  12. Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty.

    Science.gov (United States)

    Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning

    2018-03-05

    This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

  13. Process modeling for Humanities: tracing and analyzing scientific processes

    OpenAIRE

    Hug , Charlotte; Salinesi , Camille; Deneckere , Rebecca; Lamasse , Stéphane

    2011-01-01

    International audience; This paper concerns epistemology and the understanding of research processes in Humanities, such as Archaeology. We believe that to properly understand research processes, it is essential to trace them. The collected traces depend on the process model established, which has to be as accurate as possible to exhaustively record the traces. In this paper, we briefly explain why the existing process models for Humanities are not sufficient to represent traces. We then pres...

  14. Dream interpretation, affect, and the theory of neuronal group selection: Freud, Winnicott, Bion, and Modell.

    Science.gov (United States)

    Shields, Walker

    2006-12-01

    The author uses a dream specimen as interpreted during psychoanalysis to illustrate Modell's hypothesis that Edelman's theory of neuronal group selection (TNGS) may provide a valuable neurobiological model for Freud's dynamic unconscious, imaginative processes in the mind, the retranscription of memory in psychoanalysis, and intersubjective processes in the analytic relationship. He draws parallels between the interpretation of the dream material with keen attention to affect-laden meanings in the evolving analytic relationship in the domain of psychoanalysis and the principles of Edelman's TNGS in the domain of neurobiology. The author notes how this correlation may underscore the importance of dream interpretation in psychoanalysis. He also suggests areas for further investigation in both realms based on study of their interplay.

  15. Dendrites Enable a Robust Mechanism for Neuronal Stimulus Selectivity.

    Science.gov (United States)

    Cazé, Romain D; Jarvis, Sarah; Foust, Amanda J; Schultz, Simon R

    2017-09-01

    Hearing, vision, touch: underlying all of these senses is stimulus selectivity, a robust information processing operation in which cortical neurons respond more to some stimuli than to others. Previous models assume that these neurons receive the highest weighted input from an ensemble encoding the preferred stimulus, but dendrites enable other possibilities. Nonlinear dendritic processing can produce stimulus selectivity based on the spatial distribution of synapses, even if the total preferred stimulus weight does not exceed that of nonpreferred stimuli. Using a multi-subunit nonlinear model, we demonstrate that stimulus selectivity can arise from the spatial distribution of synapses. We propose this as a general mechanism for information processing by neurons possessing dendritic trees. Moreover, we show that this implementation of stimulus selectivity increases the neuron's robustness to synaptic and dendritic failure. Importantly, our model can maintain stimulus selectivity for a larger range of loss of synapses or dendrites than an equivalent linear model. We then use a layer 2/3 biophysical neuron model to show that our implementation is consistent with two recent experimental observations: (1) one can observe a mixture of selectivities in dendrites that can differ from the somatic selectivity, and (2) hyperpolarization can broaden somatic tuning without affecting dendritic tuning. Our model predicts that an initially nonselective neuron can become selective when depolarized. In addition to motivating new experiments, the model's increased robustness to synapses and dendrites loss provides a starting point for fault-resistant neuromorphic chip development.

  16. A two-temperature model for selective photothermolysis laser treatment of port wine stains

    International Nuclear Information System (INIS)

    Li, D.; Wang, G.X.; He, Y.L.; Kelly, K.M.; Wu, W.J.; Wang, Y.X.; Ying, Z.X.

    2013-01-01

    Selective photothermolysis is the basic principle for laser treatment of vascular malformations such as port wine stain birthmarks (PWS). During cutaneous laser surgery, blood inside blood vessels is heated due to selective absorption of laser energy, while the surrounding normal tissue is spared. As a result, the blood and the surrounding tissue experience a local thermodynamic non-equilibrium condition. Traditionally, the PWS laser treatment process was simulated by a discrete-blood-vessel model that simplifies blood vessels into parallel cylinders buried in a multi-layer skin model. In this paper, PWS skin is treated as a porous medium made of tissue matrix and blood in the dermis. A two-temperature model is constructed following the local thermal non-equilibrium theory of porous media. Both transient and steady heat conduction problems are solved in a unit cell for the interfacial heat transfer between blood vessels and the surrounding tissue to close the present two-temperature model. The present two-temperature model is validated by good agreement with those from the discrete-blood-vessel model. The characteristics of the present two-temperature model are further illustrated through a comparison with the previously-used homogenous model, in which a local thermodynamic equilibrium assumption between the blood and the surrounding tissue is employed. -- Highlights: • Local thermal non-equilibrium theory was adapted in field of laser dermatology. • Transient interfacial heat transfer coefficient between two phases is presented. • Less PWS blood vessel micro-structure information is required in present model. • Good agreement between present model and classical discrete-blood-vessel model

  17. Modeling nuclear processes by Simulink

    Energy Technology Data Exchange (ETDEWEB)

    Rashid, Nahrul Khair Alang Md, E-mail: nahrul@iium.edu.my [Faculty of Engineering, International Islamic University Malaysia, Jalan Gombak, Selangor (Malaysia)

    2015-04-29

    Modelling and simulation are essential parts in the study of dynamic systems behaviours. In nuclear engineering, modelling and simulation are important to assess the expected results of an experiment before the actual experiment is conducted or in the design of nuclear facilities. In education, modelling can give insight into the dynamic of systems and processes. Most nuclear processes can be described by ordinary or partial differential equations. Efforts expended to solve the equations using analytical or numerical solutions consume time and distract attention from the objectives of modelling itself. This paper presents the use of Simulink, a MATLAB toolbox software that is widely used in control engineering, as a modelling platform for the study of nuclear processes including nuclear reactor behaviours. Starting from the describing equations, Simulink models for heat transfer, radionuclide decay process, delayed neutrons effect, reactor point kinetic equations with delayed neutron groups, and the effect of temperature feedback are used as examples.

  18. Modeling nuclear processes by Simulink

    International Nuclear Information System (INIS)

    Rashid, Nahrul Khair Alang Md

    2015-01-01

    Modelling and simulation are essential parts in the study of dynamic systems behaviours. In nuclear engineering, modelling and simulation are important to assess the expected results of an experiment before the actual experiment is conducted or in the design of nuclear facilities. In education, modelling can give insight into the dynamic of systems and processes. Most nuclear processes can be described by ordinary or partial differential equations. Efforts expended to solve the equations using analytical or numerical solutions consume time and distract attention from the objectives of modelling itself. This paper presents the use of Simulink, a MATLAB toolbox software that is widely used in control engineering, as a modelling platform for the study of nuclear processes including nuclear reactor behaviours. Starting from the describing equations, Simulink models for heat transfer, radionuclide decay process, delayed neutrons effect, reactor point kinetic equations with delayed neutron groups, and the effect of temperature feedback are used as examples

  19. The Mixed Waste Management Facility: Technology selection and implementation plan, Part 2, Support processes

    International Nuclear Information System (INIS)

    Streit, R.D.; Couture, S.A.

    1995-03-01

    The purpose of this document is to establish the foundation for the selection and implementation of technologies to be demonstrated in the Mixed Waste Management Facility, and to select the technologies for initial pilot-scale demonstration. Criteria are defined for judging demonstration technologies, and the framework for future technology selection is established. On the basis of these criteria, an initial suite of technologies was chosen, and the demonstration implementation scheme was developed. Part 1, previously released, addresses the selection of the primary processes. Part II addresses process support systems that are considered ''demonstration technologies.'' Other support technologies, e.g., facility off-gas, receiving and shipping, and water treatment, while part of the integrated demonstration, use best available commercial equipment and are not selected against the demonstration technology criteria

  20. Geometry characteristics modeling and process optimization in coaxial laser inside wire cladding

    Science.gov (United States)

    Shi, Jianjun; Zhu, Ping; Fu, Geyan; Shi, Shihong

    2018-05-01

    Coaxial laser inside wire cladding method is very promising as it has a very high efficiency and a consistent interaction between the laser and wire. In this paper, the energy and mass conservation law, and the regression algorithm are used together for establishing the mathematical models to study the relationship between the layer geometry characteristics (width, height and cross section area) and process parameters (laser power, scanning velocity and wire feeding speed). At the selected parameter ranges, the predicted values from the models are compared with the experimental measured results, and there is minor error existing, but they reflect the same regularity. From the models, it is seen the width of the cladding layer is proportional to both the laser power and wire feeding speed, while it firstly increases and then decreases with the increasing of the scanning velocity. The height of the cladding layer is proportional to the scanning velocity and feeding speed and inversely proportional to the laser power. The cross section area increases with the increasing of feeding speed and decreasing of scanning velocity. By using the mathematical models, the geometry characteristics of the cladding layer can be predicted by the known process parameters. Conversely, the process parameters can be calculated by the targeted geometry characteristics. The models are also suitable for multi-layer forming process. By using the optimized process parameters calculated from the models, a 45 mm-high thin-wall part is formed with smooth side surfaces.